KULLIYYAH OF INFORMATION AND COMMUNICATION TECHNOLOGY

DEPARTMENT OF INFORMATION SYSTEMS





Draft Research Proposal





An Empirical Study of physicians behaviour Intention to accept and use of information technology in Malaysian Government Hospital


By

Mohd Daud bin Rajab



Chapter One

INTRODUCTION

1.1 Introduction

1.2 Definition of Terms

1.21 Information Technology Applications
1.22 Malaysian Government Hospital
1.23 Determinants
1.24 Behaviour Intention
1.25 Use Behaviour or actual use


1.3 Problem Statement
1.31 Research Questions
1.32 Research Objective

1.4 Research Proposal Model

1.5 Research Methodology

1.6 Significance of research

1.61 Contribution to Academic Research
1.62 Contribution to Practice

1.7 Chapter Summary





Chapter Two

2.0 Introduction

2.1 Major Theory That Use in User Technology Acceptance

2.1.1 Theory of Reasoned Action

2.1.2 Innovation Diffusion Theory
2.1.3 Theory of Planned behavior
2.1. 4 Technology Acceptance Model

2.1.5 Task Technology Fit

2.2 Chau and Hu Frame Work
2.3 Unified Theory of Acceptance and Use of Technology
2.4 Rationale for Choosing UTAUT and Chau Frame Work
2.5 Research on Organizational Context in Technology Acceptance
2.5.1 Health Care in IT
2.5.1.1 Organization Support
2.5.1.2Accessibility and Communication
2.5.1.3 Information Technology Application
2.5.1.4 IT and Policymaking
2.5.1.5 Regulation
2.5.1.6 Provision
2.5.1.7 Physician-patient

2.5.2 Health Care Technology Researches

2.5.2.1 Health Care Technology Acceptance Researches


2.6 Research Model

2.6.1 Organization Context
2.6.1.1 Perceive Task
2.6.1.2 Perceive Cost and Financial
2.6.1.3 Perceive Management Support
2.6.1.4 Perceive Accessibility
2.6.1.5 Perceive Technical competent

2.6.2 Implementation Context
2. 6.2.1 Social influence
2. 6.2.2 Organizational Facilitating conditions
2. 6.2.3 Compatibility

2.6.3 Individual Context
2.6.3.1 Computer anxiety
2.6.3.2 Computer self-efficacy
2.6.3.3 Computer attitude
2.6.3.3 Perceive Technology Control

2.6.4 Technological Context
2.6.4.1 Effort Expectancy
2.6.4.2 Performance Expectancy

2.6.5 Behaviour Intention


Chapter Three

Research framework and Hypotheses

3.0Introduction

3.1Research Framework

3.1.1 Research Framework Origin

3.2 Research Model

3.2.1Behavior Intention
3.2.2Implementation Context
3.2.3Technological Context
3.2.4Individual Context
3.2.5Organizational Context
3.2.6Conclusion
3.2.7Chapter Summary
Chapter Four

4.0 Research Methodology

4.1 Introduction

4.2 Research Design

4.3 Population and Sampling Frame

4.4 Data Collection Method

4.5 Questionnaire Layout and Structure

4.6 Operational Definition and Measured Operational Definition

4.6.1 Individual Factors
4.6.2 Technology Factors
4.6.3 Implementation Factors
4.6.4 Organizational Factors
4.6.5 Behaviour Intention
4.6.6 Pre-testing Instrument
4.6.7 Pre-testing Survey Instrument




Title: An empirical study of physicians’ behaviour intention to accept and use of information technology in Malaysian Government Hospital



1.1 Introduction

Information Technology has become a very important element and a success factor in most sectors of the business industries nowadays. This information technology application has brought a lot of benefits and advantages to the end-users and the organizations. Currently throughout the globe, governments have allocated and a huge amount of budget on healthcare programs to improve the hospital services in order to enhance their services to the public. The Malaysian Government Hospital contributions to the front line of health services to the public, the ICT development in hospital and the public Works Department were reported to have invested about RM588 millions to implement an integrated Total Hospital Information System (THIS) in 13 selected hospital in Malaysia, (New Straits Times, Thursday, March 14, 2002). Total Hospital Information System (THIS), is the first Hospital Information System to integrate clinical, imaging, financial and administration processes in selected hospital in Malaysia region, A conducted survey discovered that almost 90% of respondents had minimal IT knowledge and about 96% of respondents interested in IT innovation, (NCD Malaysia, 2003, Vol.3, No. 1). This indicates that there is a need to detail out the understanding on information technology acceptance by healthcare individual professional, (Chau,2002a)

Nowadays, there are a lot of information technology applications that has been used in the healthcare industries in order to enhance the workflow and reduce the workloads of the healthcare staff, for example is the physicians. Some of these information systems or applications that have been found to be used in the healthcare organizations include the Electronic Claims, Online Eligibility and Authorizations, Online or Internet Based scheduling, Online Results Reporting, Online Access to Clinical Information, Automated Clinical Information, Automated Clinical Decision Support, Access to Patient Satisfaction Data, E-mail, Voice Recognition, Automated Dictation, Disease Management, Electronic Medical Record, Wireless and hand Held Devices, Common Practice Management System and others. (HISS, 2000).

This research will focus on the physician’s behavior intention towards the use and acceptance of information technology applications. A study conducted by Chua and Hu (2001) on 400 physicians found that the physicians were lacking in their capabilities to accept the information technology applications. The research was based on the technology acceptance model and the most influencing antecedents such as perceived usefulness and ease of use (Davis, 1989). They found that the perceived usefulness were more significant compared to ease of use. The Information Technology applications was applied is to increase the effectiveness and the efficiency of not only in the health care quality of the end user of the hospital but also in other organizations. In health care for instances this information technology was special design to improve the quality care especially the patient medical management. Perhaps these Information technology applications will increase the physician’s capabilities to become a better pre and post health care management services. The information technology applications will also provide the most sufficient patient data management compared to the previous paper based data collection. Paper based patient data collection is inefficient when it comes to extracting information on an urgent or emergency procedure that had to be done to a patient. Paper base data collection may create the problem of unreadable writings of the physicians, when compared to the output of a word processor. In some cases, hand writings may reduce accuracy and completeness of patient medical record and will cause wrong perceptions or diagnosis by other physicians and pharmacologists.

Physicians may be described by their different groups, according to their job functions in the healthcare center. The groups are divided into Medical Groups, Management and Policies Groups, Support Groups and Facilities Support Groups.
The groups that will be the main target or focus in this research study are the medical group, they are directly involved with the patients under their supervision and treatment. The medical groups consist of the medical officer right up to the consultant that are directly involved in the treatment of the patient.
The focus of this research is to identify the factors that influence physicians’ behaviour intention towards the use and acceptance of Information Technology application such as the computer based system or hospital information system. In this study, the researcher intends to establish the understanding and analysis of the factors that influence in making decision-making towards the survival of their patient. A modified user technology acceptance model was proposed as a framework for implementing technological changes in the Information Technology applications. Perhaps, these findings may support and help to identify and provide some guidelines in as to understand the behaviour intention of physicians in the Malaysian context.


1.2 Definition of Terms
1.21 Information Technology applications
The purpose of the study, the term information technology applications will be included in the hospital information system (HIS), clinical information system (CIS), medical information system (MIS), electronic medical record (ERP), computer-based patient record (CPR) and internet application (IA). All the literature review done, might refer to any one of this term as it relates to the facility-wide effort to provide electronic or computer information system. As stated above, the focus of these studies is to understand the physicians’ behaviour intention towards information technology applications.

1.22 Malaysian Government Hospital
This is an empirical study to be conducted at Selayang Hospital(SH), Putra Jaya Hospital(PJH), Kuala Lumpur Hospital(KLH) and National University hospital (NUH). The studies only focus on Government Hospital because the facilities and support that are provided by the government.
1.23 Determinants
In this study the determinants are the factors or antecedents that influence to the behaviour intention which encompass organization context, implementation context, technology context and individual context.
1.24 Behaviour Intention
The intention-behaviour relationship is well documented in the technology acceptance literature and has been found to be conclusive when applied to industry and health-care contexts (Chau & Hu 2001; Chismar & Wiley- Patton 2003; Davis, Bagozzi & Warshaw 1989; Sheppard, Harwick & Warshaw 1988; Venkatesh et al. 2003).

1.25 Use Behaviour or actual use of technology
The link between intention to use a technology and actual usage is well-established (Ajzen 1991; Mathieson 1991; Sheppard, Harwick & Warshaw 1988; Taylor & Todd 1995; Venkatesh & Morris 2000) and both variables may be used to measure technology acceptance. Davis et al., (1989) and Davis, (1989) also found that the intention is related to behaviour or use behaviour or actual use. As we knew, TAM and TPB was based on TRA and found that the same intention-behavior link strong relationship.

1.30 Problem Statement

Technology acceptance research is a mature field in Information System Research, (Venkatesh et. al. 2003), more that 101 research articles, (Younghwa Lee,2003). But little research has been accomplished and studied in a health care perspective (Hu et al.,1999, Chau and Hu,2002a; Chau and Hu,2002b; Chismar and Patton, 2003; which bring a major significant gap in knowledge in the actual user technology acceptances. The knowledge and information in the healthcare industries professional especially the physician’s behavior intention on IT acceptance can contribute an extended information and knowledge to enhance the quality and performance of Information Technology application in health organization. Physicians are the main important subject that play extremely important role in the hospital daily operation and management. This means that physicians must be technical competent (Chau,2001) and well prepared in order to cater the challenging technological advancement. The purpose of the use of the Information Technology applications in the hospital environment and organizations are to improve the quality of patient care services. For this purpose it is important to understand the factors that influence the behaviour intention of physicians towards the use and acceptance of Information Technology applications. By understanding these influencing factors, it may help to develop a better understanding of physicians’ technology acceptance in the coming strategic information technology planning. Some research found that the failure to recognize the factors influencing the social context in IS life cycle may cause the unsuccessful of the IS project (Forsythe and Buchanan, 1992). Anderson and Aydin (1997) found the failure of implementation of new information system was because of user resistance and staff interference. Ernest (1997) suggested that a strategic management of information technology are needed to ensure the understanding of the environment of changes demanded in a competitive culture enable the organization to define more clearly and a detailed level, those problems that need to be resolved in order to archive the strategic objectivities successful.

The purpose of the research is to provide an empirical analysis for a model of physician’s behavior intention and acceptance of Information Technology applications and to identify the major factor that most influencing physician’s intention in acceptance information system in Malaysian government hospitals context. The research questions are based on technology acceptance literature as well as information technology or information system and medical research journal.

The framework for this study was based on UTAUT by Venkatesh and Chau and Hu, antecedence to understanding user behavior. In addition, we extended the frame work of incorporating an additional construct ( i.e., organization context) and examined its influence on the acceptance of information technology by physicians in selected information technology ready hospital in Malaysia.

1.31 Research Questions
What is the use behaviour of the information technology by physicians in the Malaysian Government Hospital?
What are the factors that influence physician intention to use information technology applications?
i. Does organization context influence the physicians’ behavior intention to use information technology applications?
ii. Does implementation context influence the physicians’ behavior intention to use information technology applications?
iii. Does technology context influence the physicians’ behavior intention to use information technology applications? ; and
iv. Does individual context influence the physicians’ behavior intention to use information technology applications?
3. Is there a joint effect among organizational context, technology context, individual context and the implementation context of technology acceptance on behavior intention to use information technology in Malaysian Government Hospitals?

1.32 Research Objective
To investigate the use of information technology by physicians in Malaysian Government Hospitals.
To determine factors that influence physicians’ behavior intention to use information technology applications in Malaysian Government Hospitals.
To examine the joint effect of organizational context, technology context, individual context and the implementation context of technology acceptance on behavior intention to use information technology in Malaysian Government Hospitals?




1.40 Research Proposed Model

Based on the work of Davis(1989), Venkatesh (1999), Hu et. al (1999), Chau ( 1996; 2001) , Oh et al.(2003), Yang (2005) and others, this study will investigate determinants of physicians’ behaviour intention about IT usage and acceptance by examining the direct and indirect affects of perceived usefulness, perceived ease of use, workload, age, gender, job function, organizations support , knowledge of IT on physicians attitudes toward the use and acceptance of Information Technology. Suggested relationships are shown as follow :



MODEL CONTENT
 

Organizational
Context
· Management Support
· Financial & Cost
· Accessibility
· Task Fit
· Technical Competence
· Social Influence

· Facilitating
Condition

· Compatibility
Implementation
Context
· Performance
Expectancy

· Effort
Expectancy

Technology
Context
· Anxiety
· Self Efficacy
· Attitude
· Personal
Innovativeness
· Perceived Technology Control
· Age
· Gender
· Experience
· Voluntariness



Individual
Context


Behaviour

Intention


Use

Behaviour


1.5 Research Methodology


In this study the research methodology was design and adopted form the previous research. The population of this study will be physicians of selected Malaysian government hospital. The concerned of government hospital because of the information technology facilities that provided by the government was sufficient enough in the study.
Self-administrative questionnaires were employed to collect the data from the user of the selected participating hospital. The questionnaires are developed based on the measures that had been verified and used by the pervious researchers. A pre-testing and pilot study will also be conducted prior to the actual data collection. This is to ensure that the respondents understood the contents of the research questionnaires. The study applied a stratified sampling technique to ensure the respondents were well represented.
As mention early, the organizations that will be participating in the study are Selayang Hospital, Kuala Lumpur Hospital, Putra Jaya Hospital and Serdang Hospital. A total of 400 questionnaires will be disseminated equally t o the four organizations.


1.6 Significance of research

1.61 Contribution to Academic Research

From the viewpoint of technology acceptance theories, this the study attempts to extend the technology acceptance model antecedent and additional context of belief ( i.e., organization context) as a determinant of an individual’s to acceptance of any specific information technology. Since this study will be carried out in Malaysia context, the study extended the exiting body of knowledge related to user technology acceptance model. This modified technology acceptance model will enhance the existing model. Indirectly, the study examines the applicable and robustness of the existing user technology acceptance theory in its ability to predict behaviour intention within different sampling frames. The finding of this study will strengthen or refute claims of others related studies. Enhance will valued added to theoretical and empirical contribution to the field of information technology acceptance by physicians.

1.62 Contribution to Practice

The study provide an important sample of study which antecedents how and what are this individual professional need or required to acceptance information technology compare to others user group. As stated by Hu et al, (1999), recommended that study on user technology acceptance should be done in broader point of view. This mean that, study on user acceptance must be study including the environment or conditions where the study takes place. This study exposure what are the most influence context that influence the physicians in order to adopt information technology as their additional tools to enhance their daily jobs. Better understanding of these factors will assist the policies maker such as Ministry of Health (MOH), in determining which ones is most important factor to improve the use to adopt information technologies. This will help the policies maker formulate strategies that could significantly affect information technologies adoption among their physicians. Finally, many physicians in other developing countries might share the same problems, experience and exposure or go through the same phase or processes in their information technology endeavors and activities as physicians in Malaysia.

1.7 Chapter Summary


This chapter point out of the importance and significant to extended the understanding of information technology among physician. The back ground of the research and the gaps that still wide open in the research of technology acceptance and motivated the investigation to be done.

Fundamentally, the research aims is to explore the antecedents of latest technology acceptance models and their relationship within information technology application dimensions as proposed research framework. Based on Hu et al.(1999) and Chau & Hu, finding on physician, this research also will provided broader understanding on physicians technology acceptance and use. Where additional context be explored and affect with respect to the fact that a physician indifferent behavior on information acceptance compare to others groups of end user. This study will explore additional knowledge that end user technology acceptance will defend of wider contexts base on the organizational, implementation, technological and individual factors.


Chapter 2
Literature Review

1.0 Introduction
The research on user technology acceptance has been a great business of interest for almost two decades. Researchers have developed and determine numerous factors that influence how user would adopt of information technology. Young Lee,( 2003) in his meta-analysis on technology acceptance model, found that almost 101 articles was written in well known journals and they still cannot find the most reliable or optimum factors that can deliver the most powerful predictive factors.
Several numbers of models were developed by researchers to achieve a well- established, predictive power and robust intention models. Over the years, a lot of models have been applied in the information system researches. After keeping on reading on theory in information system, we found several competing and well know models that have been widely used by information systems researchers to cause the most predictive power of intention to adopt information technology. The models are Theory of Reasoned Action ( TRA ) ( Fishbien & Ajzen, 1975 ), Innovation Diffusion Theory (IDT) ( Rogers, 1983 ), , Theory of Planned Behavior ( TPB ) ( Ajzen , 1991) ) , Technology Acceptance Model ( TAM ) ( Davis , 1989 ) , Task Technology Fit ( TTF) ( Goodhue and Thompson , 1995 ) and Unified Theory of Acceptance and Use of Technology ( Venkatesh et al., 2003 )


.2 Theories in User Technology Acceptance

2.2.1 Theory of Reasoned Action


Theory of Reasoned Action (Fishbien & Ajzen,1975) is known as TRA posits that individual behavior is driven by behavioral intentions where behavioural intentions are a function of an individual's attitude toward the behaviour and subjective norms surrounding the performance of the behavior.Attitude toward the behavior is defined as the individual's positive or negative feelings about performing behaviour. It is determined through an assessment of one's beliefs regarding the consequences arising from a behavior and an evaluation of the desirability of these consequences. Formally, overall attitude can be assessed as the sum of the individual consequence multiple by desirability assessments for all expected consequences of the behavior.Subjective norm is defined as an individual's perception of whether people important to the individual think the behavior should be performed. The contribution of the opinion of any given referent is weighted by the motivation that an individual has to comply with the wishes of that referent. Hence, overall subjective norm can be expressed as the sum of the individual perception multiple by motivation assessments for all relevant referents.
TRA also has widely applied in a multiplicity of researchers settings. TRA not only being tested to information system and information technology but also in psychological sciences such as food technology (Saba & Di Natale,2003) and medical science ( Codd & Cohen,2003). Base of the fundamental of the TRA factors such as attitude toward the behavior and subjective norm all of researches was dealing with how to predict behaviour intention. The number of the researches that have used TRA as their research model in information system and information technology are quiet large.

In their study regarding TRA comparison with TAM (Davis, Bagozzi and Warshaw, 1989), to predict the acceptance level between two model of a word processing program, Write One, found that TRA accounted 32% and at only 26% of the variance in behavior intention with in one hour and fourteen weeks of use. The accounted percents of behaviour intention decrease with in time. This show some critical understanding why the behaviour intention reduce as the use become more competence with the application e.g. the Write One word processing program. Results indicated that attitude has a strong significant influence on behaviour intention.

In their study on the user intention to use the VCR (Taylor and Todd, 1995a), the study was a comparison study between TRA and TPB. They found that TRA was well explained in predicting the intention to use the VCR technology. As the result show that attitude and subjective norm were positively significant factors to determinants of intention.

In their study to predict individual intention to use an expert system such as accountants system in U.S.A (Liker and Sindi, 1997 ), found that subjective norm was a significant factor of intention but they also found that attitude did not provide significant influence intention to use the expert system.

In their research to examine the differences in pre-adoption and post-adoption beliefs and attitude by using TRA as model base study (Karahanna et al.,1991),. A large financial institution was tested and they found that potential adopters intention to adopt Windows 3.1 was determined by subjective norm, on the other hand user intention was determined by attitude. The result showed that there was a relationship support of influencing factors between TRA factor in user adoption and continued usage behavior are determined by other factors.

In their paper, Gentry and Calantone (2002) on explaining Shop-Bot use on the web site, the study was a comparison study among well know model such as TRA, TPB and TAM. Shop-Bot is an intelligent agent that informs buyers which internet retailer provide the best pricing for any specific product. They show two different points of view, whereas TRA was found the best in predicting Shop-Bot use and TAM variance in behavioral intention and model fit, TAM was found to outperform other among the models.

In another study, Wu (2003) used TRA as the research model in order to understand the factors the can be used to encourage executives toward promoting the strategic role of IT in process reengineering. He discovered that changes in attitude and subjective norm would change the executives’ behaviour toward promoting the strategic role of IT in process reengineering.

Kolekofski and Heminger (2003) used the TRA as the framework in order to explore the beliefs and attitude that influence intentions to share information in an organization. They identified that a number of beliefs that influenced attitude. The worker intention was influence by three type of attitude such as: attitude toward the ownership versus stewardship pf organization information, the instrumentality of sharing and the interpersonal feeling of engaging in the potential information-sharing relationships.

2.1.2 Innovation Diffusion Theory

Diffusion of innovation theory sees innovations as being communicated through certain channels over time and within a particular social system (Rogers, 1995). Individuals are seen as possessing different degrees of willingness to adopt innovations and thus it is generally observed that the portion of the population adopting an innovation is approximately normally distributed over time (Rogers, 1995). Breaking this normal distribution into segments leads to the segregation of individuals into the following five categories of individual innovativeness (from earliest to latest adopters): innovators, early adopters, early majority, late majority, laggards (Rogers, 1995). The rate of adoption of innovations is impacted by five factors: relative advantage, compatibility, trialability, observability, and complexity (Rogers, 1995). The first four factors are generally positively correlated with rate of adoption while the last factor, complexity, is generally negatively correlated with rate of adoption (Rogers, 1995). The actual rate of adoption is governed by both the rate at which an innovation takes off and the rate of later growth. Low cost innovations may have a rapid take-off while innovations whose value increases with widespread adoption (network effects) may have faster late stage growth. Innovation adoption rates can, however, be impacted by other phenomena. For instance, the adaptation of technology to individual needs can change the nature of the innovation over time. In addition, a new innovation can impact the adoption rate of an existing innovation and path dependence may lock potentially inferior technologies in place.
The theory has been broadly used in IT acceptance researches ( Agarwal, 2000 ) , the theory has been tested in several research areas such as comprehensive instrument designed to examine the IT adopt decision ( Moore and Benbasat, 1991), operating system ( Karahanna, Straub & Chervany,1999), Internet banking ( Gerrard & Cunning,2003), and factors of attitude toward using a technology ( Taylor and Todd, 1995a and Tan & Teo , 2000 ).
Moore and Benbasat ( 1991 ) used the theory factors as instruments to measure the acceptance and perception of adopting any information technology. Four of Rogers factors was remain such as relative advantage, compatibility, ease of use, and trialability. Moore and Benbasat added two factors such as (voluntariness and image) and divide the Rogers’ observability factor into two to result demonstrability and visibility. The result from their study provides a valid and reliable 38 item instrument made up of eight unique scales.
Taylor and Todd(1995a) used there IDT factors such as relative advantage, ease of use and compatibility as part of their research to predict attitude toward using the computer resource center. In the research, 786 numbers of students of business school involved. The result showed that the factor of the IDT capable to explain about 76% of the variance in attitude and only perceived usefulness was significantly hypothesized affects the attitude.
Parthasarathy and Bhattacherjee ( 1998) used the IDT to understand which factor that can distinct discriminate between continuers and discontinuers of an innovation and examine the post behavior among users of online services. In their study, they examined few factors such as communication influence, utilization level, relative advantage, ease of use, compatibility, and network externalities. Only two factors was not significant discriminators, the factors was utilization and ease of use. They found that in IDT attributes, the results show that discontinuers perceived the service as less useful and less compatible with the users work habits.
Karahanna et. al. (1999) mixed the IDT and TRA to examine factors the influence Windows 3.1 user adoption across time. Several IDT attributes were tested such as relative advantage, image, compatibility, ease of use, visibility, result demonstrability and trialability. They found that among potential adopters all factors were significantly affect the adoption attitude and not impact by image. They also found that for the users only perceived usefulness and images were found significant.
Tan and Teo(2000) used four IDT attributes such as relative advantage, compatibility, complexity and trialability as additional factor in their research model to predict the intention to adopt the internet banking services. The result show that the relative advantage, compatibility and trialability has significantly affected the intention to adopt the internet banking services, on the other hand they found that complexity was non significant factor.
In another study, Plouffe, Hualland and Vandenbosch (2001) compared IDT with technology acceptance model (TAM) in understanding and predicting the intention to adopt smart card among retailers. They found that relative advantage, compatibility, image, visibility and trialability was significantly explained the intention to adopt the smart card technology among the retailers. What is interesting was the level of power in predicting between IDT and TAM was corresponding at 45% and 36.2%.
In their study about the online customer intention to use virtual stores (Chen, Gillenson & Sherrell, 2002). The study was conducted to 253 registered users of a non-profit organization and including additional new groups. An IDT attributes was added into the technology acceptance model (TAM). They found that there are compatibility between using a virtual store and a consumer’s belief, values and needs significantly affected attitude toward using the virtual stores.
Hardgrave, Davis and Riemenschneider (2003 ) conducted a study to identify factors that influence applications developers intention to follow a software development methodology. Three of IDT attributes was used in their study such as usefulness, complexity and compatibility. They found that usefulness and compatibility influenced the intention, but not the complexity.
Gerrard and Cunningham ( 2003 ) used IDT in their research on internet banking diffusion in Singapore. The result showed that the adopters of internet banking were perceived the service as more convenient, with a reduction of complex and extra compatible to them.
Venkatesh, Morris, Davis and Davis ( 2003 ) in a review of technology acceptance model found that relative advantage, ease of use, result demonstrability, trialability, visibility, image, compatibility, and voluntariness capable to explained respectively approximately 54% and 47% of the variance in intention in voluntary and mandatory setting. Two of IDT attributes such as relative advantage and ease of use were found significant in predicting intention both in voluntary and mandatory conditions. But, image was a significant predictor of the intention in mandatory setting.
In their research investigated what determine user mobile commerce (MC) acceptance
( J.H. Wu, S.C. Wang, 2005 ). The study involved TAM and IDT where innovation diffusion theory, perceived risk and cost was integrated into as an extended of the TAM. The proposed model was empirically tested using data collected from a survey of MC consumers. Data for this study were collected from the B2CMC context, where users invoked one of four general online transactions: online banking, shopping, investing, and online services. This left 310 sets of data out of 850 questionnaires for statistical analysis, a 36.7% valid return rate. The structural equation modeling technique was used to evaluate the causal model and confirmatory factor analysis was performed to examine the reliability and validity of the measurement model. Our findings indicated that all variables except perceived ease of use significantly affected users’ behavioral intent. The compatibility had the most significant influence and the positive influence of perceived risk on behavioral intention to use but was not clear.
In another research that aims to explore the factors influencing ICT adoption within construction organizations experienced with a high level of ICT use (V. Peansupap and D. Walker, 2005). Three large Australian construction organizations (a public client, a contractor, and an engineering consultant) participated in the survey. Research results indicated eleven factors influencing ICT use and adoption. These 11 factors and grouped into management (M) : Supervisor and organizational support, Professional development and technical support and Supporting tangible and intangible reward, individual (I) : Supporting individual=personal characteristics, Clear benefits of ICT use, Positive feelings towards ICT use and Negative emotions towards ICT use and technology (T) : Supporting technology characteristics and Frustration with ICT use and workplace environment (E).: Supporting open discussion environment and Supporting colleague help. These factors capable to impact upon ICT diffusion in the organization tested.

2.1.3 Theory of Planned behavior

TPB posits that individual behavior is driven by behavioral intentions where behavioural intentions are a function of an individual's attitude toward the behaviour, the subjective norms surrounding the performance of the behavior, and the individual's perception of the ease with which the behavior can be performed (behavioral control).Attitude toward the behavior is defined as the individual's positive or negative feelings about performing behaviour. It is determined through an assessment of one's beliefs regarding the consequences arising from a behavior and an evaluation of the desirability of these consequences. Subjective norm is defined as an individual's perception of whether people important to the individual think the behavior should be performed. The contribution of the opinion of any given referent is weighted by the motivation that an individual has to comply with the wishes of that referent.Behavioral control is defined as one's perception of the difficulty of performing a behavior. TPB views the control that people have over their behavior as lying on a continuum from behaviors that are easily performed to those requiring considerable effort, resources, etc.
Although Ajzen has suggested that the link between behavior and behavioral control outlined in the model should be between behavior and actual behavioural control rather than perceived behavioural control, the difficulty of assessing actual control has led to the use of perceived control as a proxy.

TPB also has been used widely in various setting including IT acceptance research.
Mathieson ( 1991 ) in a study on students intention to use a spreadsheet, he found that TPB capable to explain the intention to use the software well. This indicated the intention was predicted by attitude and perceived behavioral control. But, in this study, TRA failed to explain the subject norm influences on intention.

According to Taylor and Todd ( 1995a) computing behavior in computing resource center found that attitude, subjective norm and perceived behavioral control had clear significant effect on behavior and in their other study on consumer behavior ( Taylor and Todd, 1995b), they found that TPB was comparable to the TRA in terms of predictive power. The results show that attitude, subjective norm, and perceived control were significant factors on behavioral intention.

Accordingly to Harrison et al. (1997) technology acceptance can be explain and predict among small business executives decisions to adopt information technology. They found that attitude, subjective norm, and perceived behavioral control was significant on the executive decision to adopt information technology.

In a research on physicians adopt on telemedicine technology in Hong Kong (Hu and Chau, 1999 ).They found that attitude and perceived behavioral control was significant factors the influence physicians’ acceptance of the telemedicine technology. But, they also found that subjective norm was not significant influence the physician intention to acceptance the technology.

Limayem, Khalifa and Frini ( 2000 ) used TPB in they investigation on user acceptance of online shopping. They found that TPB was the most excellent to explained behavioral intention and applicability to other online shopping services. Three of the TPB attribute such as attitude, subjective norm, perceived behavioral control and others factors like perceived consequences and personal innovativeness were significant factors of intentions of user to engage in online shopping.

Venkatesh, Morris and Ackerman ( 2000 ) used TPB to explore the gender differences in software adoption decision making processes. They found that men were strongly influenced by their attitude toward using the new technology compare to women were more strongly influenced by subjective norm and perceived behavioral control.

In a study of adoption on the application of software development methodology within Fortune 1000 company (Riemenschnieder, Hardgrave and Davis, 2002),. They found that attitude and subjective norm were significant factors of adoption toward the intention to accept the software methodology. But, perceived behavioral control was not significant. They also found beside the subjective norm pressure, the perception of a formal mandate and the compatibility of the methodology with the currents workers style of performing work to adopt the methodology.

As explaining by Gentry and Calantone (2002) on Shop-Bot use on the web site, the study was a comparison study among well know model such as TRA, TPB and TAM. Shop-Bot is an intelligent agent that informs buyers which internet retailer provide the best pricing for any specific product. They show two different points of view, whereas TRA was found the best in predicting Shop-Bot use and TAM variance in behavioral intention and model fit, TAM was found to outperform among the models.

George ( 2002) used TPB as research model about privacy and internet trustworthiness on attitude. 1194 of samples were collected survey conducted by the Graphics, Visualization and Usability center of Georgia Institute of Technology. The result found that privacy and internet trustworthiness belief were significant factor on attitude. Furthermore, the study showed that attention had a significant influence on the intent on purchase.

2.1.4 Technology Acceptance Model


TAM is an adaptation of the Theory of Reasoned Action (TRA) to the field of IS. TAM posits that perceived usefulness and perceived ease of use determine an individual's intention to use a system with intention to use serving as a mediator of actual system use. Perceived usefulness is also seen as being directly impacted by perceived ease of use. Researchers have simplified TAM by removing the attitude construct found in TRA from the current specification (Venkatesh et. al., 2003). Attempts to extend TAM have generally taken one of three approaches: by introducing factors from related models, by introducing additional or alternative belief factors, and by examining factors and moderators of perceived usefulness and perceived ease of use (Wixom and Todd, 2005).TRA and TAM, both of which have strong behavioural elements, assume that when someone forms an intention to act, that they will be free to act without limitation. In practice constraints such as limited ability, time, environmental or organizational limits, and unconscious habits will limit the freedom to act.


TAM has established great interest and empirical support among IT researchers in many setting and technologies. TAM has been tested on different type of technologies in wide range of information communication technology such as voice mail, e-mail, software, groupware, and World Wide Web ( Adams, Nelson, & Todd,1992; Davis et al., 1989; Lederer, Maupin, Sena & Zhung, 2000 ; Mathieson, 1991 ; Taylor & Todd, 1995a ; Venkatesh et al., 2003). TAM was found by researchers as predictive power and few predict construction ( Agawal & Prasad, 1999) and quite robustness and capable to applied to wide range of technologies ( Venkatesh & Davis, 2000).

Davis (1989) developed and validated new measurement scales for perceived usefulness and perceived ease of use, to examine predictability of use on application acceptance. 152 participants was tested with four applications programs. The results show that perceived usefulness and perceived ease of use of use were significantly correlated with self-reported current usage and self-predicted future usage. The study also found that perceived usefulness are greater correlation with usage behaviour compare to perceived ease of use.

Davis et al. (1989) investigated on the technology acceptance of word processing program such as WriteOne. The study also found that perceived usefulness was a major determinant of intention to use the application, while perceived ease of use was considered a significant secondary determinant.

Adams et al. (1992) tested again Davis’s (1989) work. The study was to evaluate the psychometric perceived usefulness, perceived ease of use and system usage in two different studies. The first study was tested among 118 respondents from 10 different organizations for their attitude toward voice and electronic mail. The second study was conducted on 73 undergraduate and MBA students for their attitude toward three different applications such as WordPerfect, Lotus 1-2-3 and Harvard Graphics. They found that both studies showed that perceived usefulness was important determinant of system usage and perceive ease of use was less important.

Taylor and Todd (1995a) found that TAM worked well in predicting of user behavioral intention and accounted about 52% variances. As stated by Davis (1989) that perceive usefulness was significant influence to attitude and perceived ease of use was significant influence perceive usefulness and attitude. But they also found that attitude was not significant to behavioral intention.

In another by Morris and Dillion (1997) on students acceptance of Netscape browser, found that all factors were fully supported the hypothesized but only one was marginally supported. As predicted, perceived usefulness and perceived ease of use were significantly influenced attitude. Perceived usefulness and attitude had a significant influence on behavior intention. Behavioral intention has a significant influence on actual usage. Perceive ease of use was marginally influence perceived usefulness.





2.1.5 Task Technology Fit


Task-technology fit (TTF) theory holds that IT is more likely to have a positive impact on individual performance and be used if the capabilities of the IT match the tasks that the user must perform (Goodhue and Thompson, 1995). Goodhue and Thompson (1995) developed a measure of task-technology fit that consists of 8 factors: quality, locatability, authorization, compatibility, ease of use/training, production timeliness, systems reliability, and relationship with users. Goodhue and Thompson (1995) found the TTF measure, in conjunction with utilization, to be a significant predictor of user reports of improved job performance and effectiveness that was attributable to their use of the system under investigation.Although the Goodhue and Thompson (1995) model operates at the individual level of analysis, Zigurs and Buckland (1998) presented an analogous model operating at the group level. Since the initial work, TTF has been applied in the context of a diverse range of information systems including electronic commerce systems and combined with or used as an extension of other models related to IS outcomes such as the technology acceptance model (TAM). The TTF measure presented by Goodhue and Thompson (1995) has undergone numerous modifications to suit the purposes of the particular study

K. Mathieson, M. Keil(1998) examined the idea more formally of technology acceptance antecedent, by testing whether perceived EOU is affected by the fit between task and technology. In other words, will an information system that helps a user perform a task more effectively be perceived as easier to use than a system that does not help the user as much, even if they have comparable interfaces? The subjects were undergraduate business students enrolled in an information technology course at a large university in the western U.S. A total of 271 subjects participated in the experiment. This study show an empirical evidence that task technology fit affects perceived ease of use (EOU), independent of system interface.


D.L. Goodhue et al. (2000), examined on user evaluations of task-technology fit for mandatory use systems and develop theoretical arguments for the link to individual performance. The data was collected from 155 pairs of undergraduate business students participated in four 1-hr lab sessions learning and using a query language and a database to answer managerial questions about two different divisions of a fictitious company. The research was done under laboratory situation where its could manipulate TTF enough to cause changes in objective performance, and simultaneously capture measures of user evaluations of TTF. The result found that a strong link between user evaluation and performance may require when users receive feedback on their performance is proposed, in addition, awareness on the part of the user of the impact of different conditions of TTF on performance. This awareness could sharpen the user's assessment of TTF, and lower the error variance in the user evaluation of TTF.

A.I. Shirani et al. (1999), examined the interaction between task structure and technology to support synchronous and asynchronous group communication. In their research the technology that was tested were e-mail and group support system (GSS). 148 graduate students participated in the experiment and a total of 46 groups were formed. The subjects were all M.B.A. students enrolled in an information systems course at a US, accredited business school. This study compared two technologies GSS and email used by work groups for communication in synchronous and asynchronous settings. Controlled experiments were conducted and group outcomes were measured in terms of basic and inferential ideas. Results indicated that GSS-supported groups generated significantly more total and basic ideas than groups supported by e-mail; the latter groups, however, generated a higher proportion of inferential ideas.

Dennis et al.(2001), conducted a meta analysis to summarize and synthesize the results of the past 15 years of research. 61 articles about GGS from MIS, psychology, and management journals and conference proceedings, read previous literature reviews, and posted messages soliciting studies from the subscribers of the GSS-L listserv. The analysis found that fitting the GSS to the task had the most impact on outcome effectiveness (decision quality and ideas), while appropriation support had the most impact on the process and time required and process satisfaction.

In their study by Karimi, Somers, and Gupta ( 2004 ) on the impact of environmental uncertainty and task characteristics on user satisfaction with data, the study attempts (1) to provide common definitions and assumptions for studying the relationship between IS and the organizational environment, and (2) to investigate how environmental factors may influence the design, use, and consequences of IS use. The study was conducted with 77 CEOs and 166 senior managers, who were end users of IS. They found that managerial decision-making tasks are affected by rapid changes that occur in organizational task environments, and that when confronted with environmental uncertainty, users experience more non routine and interdependent tasks. The study provided a more comprehensive understanding of the relationship between the two, and showed their respective abilities to predict variation in users’ task characteristics. The findings suggest that task characteristics have both a direct and mediating impact on user satisfaction with data. User satisfaction may result user will use or not to use or to accept any technology or information technology.

2.2 Chau and Hu Frame Work

In their research on individual professional’s task performance in information technology acceptance were clearly significant (Chau and Hu, 2002). The study investigates technology acceptance by individual professionals by examining physicians’ decisions to accept telemedicine technology. Using data collected from more than 400 physicians practicing in public tertiary hospitals in Hong Kong. Results of the study suggest several areas where individual professionals” might subtly differ in their technology acceptance decision-making, as compared with end users and business managers in ordinary business settings. Base on the behavior of physician, physicians appeared to be fairly pragmatic, largely anchoring their acceptance decisions in the usefulness of the technology rather than in its ease of use the compatibility of the technology with their practices, less importance on controlling technology, and limited weight to peers’ opinions about using the technology. According to this revised framework, the main thrusts of an individual professional are decision to accept or not to accept a technology would be their attitudinal assessment of accepting the technology and the evaluation of their control over the technology use. These factors characterize the individual context and directly affect individual technology acceptance. At the same time, these factors, to a great extent, are directly influenced by other sets of factors that define the technological context and the implementation context. The characteristics of the technological context that may include perceived usefulness and perceived ease of use, which directly affect the individual context in terms of attitudinal assessment and perceived technology control. Meanwhile, perceived usefulness and perceived ease of use of the technology may be directly affected by such factors as compatibility and peer influence or general known in TRA as subjective norm, which together characterize the implementation context. The compatibility or technology-practice fit or technology task fit (Goodhue and Thompson,1995) may be conceived as a technology’s compliance and congruence with the underlying service rendering process or procedure and thus can be measured accordingly.
The research study that done by Chau and Hu provide us an interesting option to understand more clear about user technology acceptance as a resultant in context such as mention by Chau and Hu were implementation context, technology context and individual context.


2.3 Unified Theory of Acceptance and Use of Technology


The UTAUT aims to explain user intentions to use an IS and subsequent usage behavior. The theory holds that four key constructs (performance expectancy, effort expectancy, social influence, and facilitating conditions) are direct determinants of usage intention and behaviour (Venkatesh et. al., 2003). Gender, age, experience, and voluntariness of use are posited to mediate the impact of the four key constructs on usage intention and behavior (Venkatesh et. al., 2003). The theory was developed through a review and consolidation of the constructs of eight models that earlier research had employed to explain IS usage behaviour (theory of reasoned action, technology acceptance model, motivational model, theory of planned behavior, a combined theory of planned behavior/technology acceptance model, model of PC utilization, innovation diffusion theory, and social cognitive theory). Subsequent validation of UTAUT in a longitudinal study found it to account for 70% of the variance in usage intention (Venkatesh et. al., 2003).


2.3 Rationale for Choosing UTAUT and Chau Frame Work


The combination model, UTAUT,2003 and Chau and Hu antecedence,2002 was proposed as the guiding framework for this study.

I. UTAUT was use in this study due to several factors such as:

1. The model was developed through a review and consolidation of the constructs of eight models that earlier research had employed to explain IS usage behaviour (theory of reasoned action, technology acceptance model, and motivational model, theory of planned behavior, a combined theory of planned behavior/technology acceptance model, model of PC utilization, innovation diffusion theory, and social cognitive theory).
2. Researches using UTAUT was still limited, not yet valid and will be tested in hospital setting.
3. Considering of the R square on the output was quite high about 70 %,( Venkatesh, 2003)
4. Interesting result may produce regarding to individual professional such as physician in the research, Chau and Hu, (2002) found that individual professional behavior are different compare to others non-medical organizational.
II. The main idea of Chau and Hu was it is appeared that individual professional may be considered different in their acceptance on information technology. They concluded that there should be a resultant among contexts that may influenced the end user technology acceptance in any organization. The resultant that proposed in Chau and Hu frame was in hierarchical model, where implement context may impact technological context and as the resultant of all, these implementation and technology context may provided actual impact to end user to accept or not to accept any technology. Chau and Hu in their research suggested that there are clear significant of compatibility among individual professional, where in was believed that technology-practice fit or task technology fit (Goodhue, 1995) appeared to be considered as an important contribution of factors toward user to accept any information technology.

In this research and previous study, it is believe will that result in a clearer understanding of the relationship between factors and that additional specific impact these that can have on behavior.

2.5 Research on Organizational Context in Technology Acceptance

Hu et. al.,(1999) examined physician using telemedicine technology, they found that a lot of study have been done in implementation and management point of view. Additional efforts are needed to be done on other particular angle involving different technology, user population or organizational context and Venkatesh et al,2003 suggested the study in the organizational require a proliferation of competing explanatory models of individual acceptance of information technology. The technology, the user group and organization context are all new to IT acceptance / adoption research, Hu et. al.,1999, pp-92. They argue that Technology Acceptance Model (TAM), originated by Davis,1989, was the most promising model in explaining or predicting user acceptance of computer technology. TAM has been used extensively as the theoretical basis for many empirical user technology acceptance studies. They concluded that theory testing on different context such as different technology use, user group such as professional group and in the researcher on healthcare-context and organizational context. TAM provided the important preeminent intention-based model that different context from the previous study in health-care organization and extended testing on the parsimony of TAM which provided strong evident to improve the model. They also found that in managerial standpoint play an important point in order to foster individual intentions to use technology, which encourage and cultivated a positive attitude toward using the technology. The managerial can provide an important information sessions and trainings on new technology and in this research is the telemedicine on how technology can help improve the efficiency and effectiveness of physicians’ patient care and service delivery to a certain extent than on the steps or actions of actual use of the technology. Hu et. al.,1999 suggested that studies on user technology acceptance should not limit by only original TAM but extended model may be required on different condition and context.

Venkatesh et al, (2003) works on advances individual acceptance research by unifying the theoretical perspectives common in the literature and incorporating four moderators to account for dynamic influences including organizational context, user experience, and demographic characteristics. The study has explored additional factor such as organizational context beside the purpose to understand individualistic of technology acceptance. No doubt those organization or user groups provide a critical factors that influence direct or indirect to user acceptance.

Santiago Rementeria, (1997) informed that current software assessment models are frequently constrained to the software development and management process only. This will cause difficulty in obtaining adequate profits from growing software investments, and also in aligning software strategy with the parent organization s business strategy. There is an interest to include the broader organizational context in models for assessing and improving the strategic influence of software within manufacturing and service firms. The survey was based on an adapted version of the European Quality Award model. The logic of the model is that in any Software Producing Unit (SPU), leadership driving policy and strategy, SPU people management, customer-supplier partnership, resource management and processes lead to software excellence, which in turn enhances end-user satisfaction, SPU people satisfaction, brings a positive impact on the organization as well as effective business results. Enablers and results are respectable concerned with the way the software unit is managed and on the effectiveness of that management, which mean what has been achieved by the organization. How well the management in my study the top management support, can manage properly and as a motivation factors to the end user are very clear to influence the end user to utilize the technologies.

Juhani I,(2002) focuses on the success of individual information system applications and interpret an information system (IS) as a computer-based system that provides its users with information on specified topics in a certain organizational context. The DeLone-McLean model for IS success, assumes that system quality and information quality, individually and jointly, affect user satisfaction and use. It also posits use and user satisfaction to be reciprocally interdependent, and presumes them to be direct antecedents of individual impact, which should also have some organizational impact. This individual impact may be come from the technological acceptance by the individual after accept the technology. This mean that individual impact and organization impact have an close relationship in the end user acceptance of technology, but the issues are the impact of DeLone-McLean model is from user to organization where this issues can be bidirectional. This mean organization may impact both direction on only the user behavior but also other context such as implementation context , technological context which all of these context may provide the actual resultant ( Chau and Hu,2002a).

Chau (1995) attempted to understand how packaged software such as computer base information system was selected by the owners or manager of any organizations. Although in his study, he focus on the method of selecting the computer base information system, he reported that, the significant factors that influence the end users in the organization were consultant effectiveness, vendor support, IS experience, sufficiency of financial resources, CEO support, and user participation. Result show that owners or managers or more generalize the organization context, found that ease of use or user-friendliness of the software package was viewed as an important factor, not sophisticated software packaged and in-house technical support are required.

2.5 Health Care in Information Technology

(Wainwright and Waring, 2000) reported that the new focus on clinical information systems (CIS) is a response to attain a more balanced approach meeting the needs of patients, health-care professionals, managers and planners and the public; the prime focus now being the clinicians by route of the Electronic Patient Record (EPR) and the Electronic Health Record (EHR). The new emphasis focuses on integration of patient-based data for 24-hour access by multi-disciplinary stakeholders within the health-care system, stripping out the concept of professional boundaries and geographic location. They reported that last decade prior to the millennium has been unprecedented in terms of scale of change within the NHS due to government policies, political ideology, health-care reform and pace of technological progress. It was also argued that the pace of change has outstripped the ability of health-care organizations to respond effectively in order to implement the key goals set by strategic policymakers within the NHS.

Wainwright and Waring adopted the development of critiques of the approach using the Nolan stage model which was one of the first attempts at the Nolan maturity model, known as the stages of growth theory, was derived from work carried out in the USA which identified that similar problems of growth were encountered by many companies involved in adopting computer-based systems. They discovered that budgets for IT expenditure followed an S shaped curve with three distinct change points enabling them to identify four key stages of growth in the life of IT systems. Initially four stages were identified comprising: initiation, contagion, control and maturity.

Lebuox et al. ,( 2000) indicated the important factors that indicted which telehealth application do or do not contribute to the delivery of health care services. They showed that the information technology application such as telehealth was found to have 4 mechanisms that are capable of

Decreasing the patient transfer
Decreasing the trips made by providers and patients
Meeting the needs of underserved populations
Helping to building provider’s and patient’s knowledge
Reducing rural isolation

There are many possibilities offered by IT applications, but the levels of utilization remained low for most applications. In the 90’s, several project were launched with a renewed impetus in Europe, North America, Australia and Asia. Lebuox et. al. report that there are rapidly increasing in telehealth application due to two factors:

The effort on R&D in numerous technological improvements and more competitive prices among the providers.
The context of health care reforms initiated by industrialized countries, this improves clinical communication and access to expertise.

Lebuox et. al., (2000) highlighted that tele-health applications was not made available and its contribution to actual health population remains unclear. Furthermore, the development of several telehealth applications is still in its early stages, where potential users such as providers and patients can play a pivotal role in steering the evolution of telehealth. Besides these potential users, physicians are one of the most important characters that can cause huge impacts to improvements in the evolution of telehealth.

2.5.1.1 Organization Support of IT in Health Care
According to Dawn and Ann,(2004) in their study on adoption of information technology in the supply chain, shows that the organization culture and structure can either hasten or impede innovation adoption. Information technology application configurations and variables may also influence the technology adoption. The study included familiar system variables in their study such as centralization, interconnectedness and system openness. They made assumptions on the centralization whereby the degree to control and decision-making rests with the few powerful members of the organization. This applies to the health care organization or any other organizations. Interconnectedness is the strength of interpersonal networks within the firm or organization, both within a management unit and across departments. System openness refers to how cosmopolitan the firm or organization is, which means how transparent networked individuals in the firm are to outsiders.

Dawn and Anne,(200$) highlighted the relativity of centralization, interconnectedness and system openness function, which contributes to the shortage or lack in organizational adoption or acceptance of IT tools in logistics organizations. In their study of supply chain organizations marked by centralization, a low number of organizations are expected to innovate because even when the decision-makers are creative and innovation-oriented, problems occur due to the rapid change in information technology. The IT knowledge flows from numerous sources cannot be diffused effectively if it is required to flow through narrow channels.

2.5.1.2 Accessibility and Communication

Dawn and Anne,( 2004) reported in their study on the important factors that the supply chain must take into account, which is technology acceptance and communications. They assume the communication channel in two sections, which are the interpersonal and mediated. Both are used to communicate the new technology to targeted potential adopters. In interpersonal channels, they include factors such as word of mouth, face-to-face, training programs, sales and consultant presentations. These methods of communication were common amongst staff in any organizations, including in the health-care industry.

Dawn and Anne, (2004) added that communication through the mediated channels could be through mass e-mailings, brochures, websites, training videos and manuals, memos and videoconference presentations. These mediated channels can also include any type of computer base applications that are used by health care staff to communicate. Today, information technology application may be widely used throughout the healthcare organization, but we still need to understand the user’s doubt in IT utilization and the level of usage to ensure successful technology acceptance.

Dawn and Anne, (2004) found out that a study on communication channel done by researchers gets very little attention. Communication channels provide simple formal communication that can be face to face or in mediated form. This formal communication brings forward the formal training program, which includes face-to-face instructions and printed manuals, brochures, videotapes and the websites. They also believe that formal communication is positively related to the adoption of IT since it is the top managers who control the pro-adoption change agents. This means that formal communication is capable of pushing and driving the organization’s staff to adopt IT.

In their study of ICT adoption in SMEs, they found out that there are different factors that might influence ICT adoption in organizations (Helen el. at., 2003). Adoption drivers are more likely to emerge from customers or end users, suppliers, business partners and competitors. In the healthcare’s point of view, the ability to utilize information technology gives advantage as proposals or critical information can be highlighted to the management. Helen el. at. referred to some researchers like Poon and Swatman (1997), and Venkatraman’s model, that a stage-based transformation process occurs when SME uses ICT to improve the end user strategic position, which indirectly helps the use of information technology applications. On the other hand, the lack of adoption and implementation of ICTs by SMEs, prevent them from overcoming current performance deficits and exploiting new opportunities as mention by Zmud,1984.

Newman, K, (1997) reported a programme to change the health care organization’s structure, roles and responsibilities of non-medical staff. Kingston Hospital Trust was successfully embarked on a major organization change programme with the adoption of patient focus care in order to focus processes and activities on the patient, improve quality of care and efficiency through multi-tasking, new post and team working.

Kingston Trust Hospital is a small 414 bed hospital with an income of around 52 millions pound sterling, in 1996 to 1997 treating some 170,522 outpatient, 23,064 inpatients, 12,607 day surgery cases and 77,241 accident and emergencies and employing around 1,440 staff. The case study was adopted, combing analysis and interpretation of hospital documents, semi-structured interviews with the chief executive and training of development manager and staff in the medical unit, together with the observation of other units during the summer of 1996 to illustrate contemporary events.

Newman K. (1997) found that the requirements for the subsequent development of a pilot electronic patient record (EPR) based on exception reporting are mandatory. Besides the need for the study to be more efficient and effective in the patient’s health care, Newman came across the need to have a new supporting information technology system to support the current patient health care services.

Apart from issues related to the junior physician’s, the public commitment and visible leadership of the chief executive, an independent and full-time transitions team together with the external high-level support and funding are essential prerequisites for the successful introduction and embedding of change. In other words, organization support is compulsory. Newman also concluded that communication needs to be integrated with normal day-to-day staff meeting and briefing, and some of the communication of facts and use of information technology application such as videos, letters, email, fax-mail or any communication applications, are essential in order to increase efficiency and effectiveness of health care services.

N. Wickramasinghe, R. Lamb, (2002) suggested that knowledge workers are one of the most significant in health care organizations, and they are the key employees in today’s workforce. Due to their importance, about one out of seven dollars spent on final goods and services in the US economy go to the health sector. In their study, they focused on the relationship between the managed care organization and its primary care physician in terms of a principal-knowledge worker agent relationship, and identified the key role for information system or information technology.

Wickramasinghe, (2002) recognized that there are parties with different interests and objectives whom are heavily reliant on transferring information between the managed care organization (MCO) and primary care physician (PCP). Because of different interests and business objectives, both MCO and PCP must come out with a better goal-alignment, by which information systems or information technology is being used to perform monitoring of both activities.

Wickramasinghe, (2002) reported that information systems or information technology is capable of providing effective and efficient communication and decision making for parties involved in the health care management. In addition, information systems and information technology are capable of transferring huge volume of data effectively and efficiently in an organized fashion, regardless of their location and geographical condition. In such a way, potential decision-making is encouraged and the probability of agreement is increased.


Group Practice
Goal alignment
Pay attention to monitoring
IS/IT
Restructuring
Internal monitoring enable by IS/IT
Specialty Physicians
High since the implementation of the billing / practice management system
Do not pay attention to data from MCO
IDX up and running
Has formed an administrative arm within its PCS’s
Yes – IDX enables internal monitoring
Independent docs
Low
Do not pay attention to data from best MCO
Currently implementing billing / practice management system
Is to restructure and create an administrative arm
Will occur once IS/IT up and running
Faculty docs
Low
Do not pay attention from best MCO
Currently in the process of implementing IDX
Has created an MSO – essentially an administrative arm
Will occur once IS/IT (IDX) up and running.

Source from N. Wickramasinghe, R. Lamb, 2002 – The Key points of different goals and power of primary care physician and managed care organization.

Wickramasinghe & Lamb. (2002) found out that the health-care industry is a large and key industry in the USA, but it has been notably slow to embrace technologies that enable and facilitate effective and efficient management functions and enable better clinical practice. The research elaborates that the interactions between PCP’s and MCO’s, the key players in a managed care environment, is clearly vital and important. The important role of IS/IT in enhancing the capability of the communication amongst user or employees and increasing the collaboration within the organization is proven.



2.5.1.3 Information Technology Application in Health Care

Kusniruk (2002) studies the usability and effectiveness of physicians in acceptance to the clinical information system, and from there they develop a framework for designing that can evaluate the use of web-based information system by both patients and providers, including the assessment of the use of web-based clinical guidelines by physicians. Kusniruk (2002) also reported the effect of changes being brought about by emerging technology, including Internet-based information resources for patient, must be considered in relation to patient understanding and provider therapeutic goals.

Furthermore, to develop individualized, context-sensitive information systems that will end up being useful for physicians and patients, the information system must be understood, and also find out who is trying to understand the information. Most importantly, the issues and problems that occur in its comprehension and application must be identified.

Kusniruk (2002) identified some guidelines on evaluation of Internet-based technology that are typically undertaken in medical informatics:

Determining the extent to which the end user’s view of the system differs from that of the designers and how potential ‘mismatches’ influence system effectiveness, especially as the range of users becomes increasingly varied.
Going beyond assessment of user satisfaction to consideration of how the user’s interaction with the system changes over time and how use of such technology changes the interactions between patients and health-care professionals. Characterizing the impact of systems on reasoning and thought processes as a result of continued use. Identifying technical and methodological issues for performing evaluations remotely.

Kusniruk (2002) used the cognitive task analysis in the evaluation study process and found out that some of the effects associated with the use of health information systems on physician’s decision-making and interaction with patients. This includes a combination of methods used like video recordings of user-system interactions and follow-up interviews with end users. Kusniruk (2002) used a multi-methods approach in order to adequately address the multiple objectives; these including on-line questionnaires, Web-based Information System, Tracking of system Use, Video-based usability testing, on-line commenting and telephone interviews.

Major development efforts involving health-care information systems are not readily available at the actual site of system development yet. This shows that the financial organization and developer have to make proper and correct investments to create the optimal working environment for everyone in the healthcare organization.

Sung (2000) reported the capability of collaborative medicine system that allows the medical specialist to share patient records and communicate with each other over the Internet. CoMed is a web-based system, which consists of a multimedia medical database and a real-time teleconferencing system, a whiteboard, and a chatting system. This real-time collaboration of a medicine system supports the synchronous interaction among medical specialists and allows for real-time sharing of patient information and collaborative consultation.

Multiple computer-based medicine systems such as Telemed, Medfast, MedNet and Bermed, allow medical specialists to do the teleconsultation among themselves or with patients and also allows medical specialists to supply high-quality health-care services. In this study, Sung proposed a multimedia patient record and real-time collaboration system which is capable in cooperating with other multi-type of data from medicine systems such as physicians textual memo, numerical data from medical result, image data examination, sound data, audio and voice data, motion picture and video data. The usefulness of using information technology application such as telemedicine, teleconferencing or their propose system the CoMed, is that even the most remote locations can be accessed. CoMed provides the advantage and ability for effective and efficient collaborative consultations among medical specialists with the patients.

Heather (1999) reported in their study of a difficult issue, which arises through the interaction between information technology and multi-disciplinary people in a complex organization such as health care industries. However, the research was very useful in order to evaluate and understand the multi-disciplinary work and exploit the potential rich source of data of Electronic Patient Records (EPR).

Rick’s, (2004) commentary of the article on the importance and assessment of training and program was that healthcare professionals headed for healthcare organizations should attend such programs. Rick reported that the American Health Informatics Association (AMIA) is in the process of delineating competencies in health informatics and the International Medical Informatics Association (IMIA) has a set of competencies as well. These two organizations are the organizations that play an important role in healthcare industries.

Tam (2004) analyzes the e-health development in East Asian tigers: Japan, Hong Kong, Singapore, South Korea and Taiwan. They found out that there were few factors that mostly hamper and interfere in the growth of e-hearth in those countries. The factors are policymaking, regulation, provision, funding and physician-patient relationship. The implementation of IT application to the public sector sparked interest, as the e-government concept is said to cause an impact in the development of healthcare systems throughout the world.

On the other hand, the development of these countries was being limited by the abovementioned factors. Other factors are the institutional, culture and financials issues of these countries. They highlight that in some nations like the USA, factors like policymaking, regulation, provision, funding are the most sought upon factors when it comes to government ruling. There is clear involvement in structural features of the US government system, including fragmentation of government and the healthcare sector, which play a key role in the healthcare development. They added that regulation has caused the failure of internet-related development, which is closely related to the success of e-health practitioners, this including the issues and problems of global licensing when monitoring information quality in a virtual world with no boundaries. Usual regulation causes confusion of rules and codes to individuals or organizations, when either party tries to propose new ideas and approaches.
2.5.1.4 IT and Policymaking, Regulation, Provision

In Taiwan, the Department of Health (DoH) launched e-health project in 2002 with a timeline stretching to 2006, funded by the central government. Both public and private sectors are permitted to participate on a self-paying basis, and this project seeks to promote electronic medical records. This helps medical information to flow to all parts of the healthcare sector extensively.

For Japan, they launched an e-Japan strategy to promote IT in the healthcare sector; the aim was to computerize the entire sector by 2004 and to introduce an electronic medical records system covering 60% of clinics and 60% of hospital with 400 plus beds by 2006.

For Hong Kong, Health Welfare and Food Bureau (HWFB) contains standard bureaucratic information, current policy, speeches and public health information, where a major networking link is being created among hospitals which will likely to have policy consequences.

E-health itself creates a number of regulation problems; excessive regulation may impede e-health growth and the courts always interfere whenever administrative regulation fails. Like Singapore, the regulation issues defend the government’s policy, implying that online communication with the healthcare system is allowed only locally but not overseas. In Japan, physicians are not allowed to answer any questions about healthcare by e-mail or telephone.
In Japan provision of healthcare services is not allowed. Whereas in Hong Kong, only single provisioning is allowed, which is the online information sharing among healthcare professionals. In Singapore, only provision of online medical advice to patients by the ministry of health is allowed. For South Korea, provisioning is not allowed. And in Taiwan, certain patient provisioning is not allowed.

2.5.1.7 Physician-patient
East Asian societies retain many traditional features, which generate some resistance to change in established modes of physician-patient contact. But, there are also factors operating in the opposite direction, such as a long term impact of the SARS crisis may boost the use for e-health. This study was conducted in a series of fieldwork interviews and analysis of key healthcare websites. I. Holliday, W.k. Tam, found out that the development of e-health in the region is less advanced; with institutional, cultural and financial factors being the main issues of the study.

Cox and Dawe, (2002) investigated medical and ancillary staff, and the impact of workload on radiography usage of picture-archiving and communication system (PACS). The methodology of the researcher was done quantitatively and qualitatively, and through process analysis. Positive response was recorded from medical and ancillary staff on technology acceptance. A wide range of facilities was needed, such as the compatibility with the existing IT system, adequate IT support and utilization of the communication system throughout the hospital.

Hanmer (1999) reported the importance in evaluation of district health information systems (DHIS); this case study was done in nine provinces of South Africa. In the study, she highlighted the complexity of evaluation, networking and collaboration among the caregivers, managers, services provider and the policy maker throughout the health care organization at district level in South Africa.

From the study, she found out that the correct and proper way of evaluation of the effectiveness of DHIS’s is through information systems or information technology applications, which are essential components towards effective health care services, and also contributes a significant improvement in overall health status. Hanmer has developed a comprehensive, practical evaluation instrument for DHIS to facilitate DHIS evaluation program.

Some criteria are communication, which refers to the capacity to obtain required information, either electronically or by other means; district management information, Patient / client information, appropriateness and accessibility, acceptability to the community, user acceptance, and timeliness of the information. These criterions that she listed have prominent and direct impact that determine the success of District health information system as an IT application in health care organizations.




2.5.2 Health Care Technology Acceptance Researches

Chismar and Wiley-Patton (2002) tested the applicability of the TAM2 model in the healthcare setting, specifically within pediatrics. TAM2 model was proposed by Venkatesh and Davis in 2000, which are the extended model of TAM and added with additional factors to enhance the predictable capability of the model. As they reported that, while the use of IT in healthcare has increased tremendously, key players, particularly physicians still have not fully embraced the valuable resource of the Internet as one of information technology application. They utilized TAM2 to examine physicians’ intention toward the adoption of Internet based health applications. Both models, TAM and TAM2 posit that an individual’s intention to use a system is determined by two primary belief factors: perceived usefulness and perceived ease of use. TAM2 however, includes two other theoretical constructs: cognitive instrumental processes and social influence processes. Four cognitive factors influence perceived usefulness: job relevance, output quality, result demonstrability, and perceived ease of use. Three social forces influence perceived usefulness: subjective norm, image, and voluntariness. Theses additional factors will hope to improve the model (TAM2) predictive ability as Chismar and Wiley-Patton hope to understand the physicians often misunderstand the functions and full potential of the Internet and TAM2 has not been tested in the healthcare arena, with the exception of this research. They hope can address the needs of the pediatric and medical community as a whole in applying information technology.

The TAM2 questionnaire was adapted and tailored to be more specific to pediatricians. The modifications were based on the findings of a physician-centered focus group and pretest procedures. Although the TAM scales have been validated by much prior research, the modified instrument was examined for reliability within the context of pediatricians. Factor analysis was then conducted to examine convergent and discriminate validity. Convergent validity is considered to be satisfactory when items load high on their respective construct or factor.

Regression analyses were used to explain intention toward usage (ITU) also referred to as behavioral intention. Perceived usefulness (B = .660, p <. 000) was a strong determinant of intention to use. The effects of perceived usefulness and output quality explained 59% of the variance of usage intentions by pediatricians. While perceived usefulness had a significant effect on intention to use, perceived ease of use and the social processes of subjective norm and image did not. TAM2 explained up to 59% of variance in perceived usefulness and perceived ease of use and the social influence processes were not significant at the 0.05 level in this model. The results suggest that TAM2 was partially adequate and applicable in the professional context of physicians. The perceived usefulness was found to have a significant and strong influence on physicians’ usage intention. But, perceived ease of use, one of TAM’s core constructs was not significant. As study done by Hu et al. and Chau et al (1999), its found that perceived usefulness was the most significant factor affecting physicians’ or professionals acceptance of technology, while perceived ease of use had no significant effect on either perceived usefulness or attitude. Physicians are considerably different from the students, administrative staff, knowledge workers, and system developers typically examined in previous TAM studies. For these reasons the variables of perceived ease of use may not be sufficient or perceived as critical with this professional user group. Usefulness is operational as increasing the pediatricians’ productivity, improving their quality of care, enhancing their effectiveness and providing overall practical service. The study presents implications for health care information technology management. To encourage the individual physician to adopt and use of IHA, the organizational management needs to 1) emphasize the usefulness of the technology to the physician, and 2) deemphasize the ease of use of the particular information technology, while focusing on the importance and utility of the technology in performing daily tasks. Chismar and Wiley-Paton suggested changes for future studies such as: 
1. A modified version of TAM2 would be very useful in assessing physicians’ attitudes toward acceptance of Internet-based health applications. In developing this model, new constructs should be tested for the abstract notion of easy to use or “without effort”. Physician-centered variables with regards to ease of use should be defined. 2. Additional research is needed to examine the effects of physicians’ characteristics on information technology adoption, evaluation and comparison of physicians across specialties, disciplines, geographic boundaries, and cultures would be valuable. 3. In addition, future studies should look at the effects of “hands-on” educational interventions on basic TAM2 relationships in a professional context. Chau and Hu (2002), investigated of technology acceptance by individual professionals by examining physicians’ decisions to accept or reject telemedicine technology. The intention of the study was to develop a generic research framework to provide a necessary foundation upon which a research model for telemedicine technology acceptance by physicians. The purpose of using data collected from more than 400 physicians practicing in public tertiary hospitals in Hong Kong. Results of the study suggest several areas where individual “professionals” might subtly differ in their technology acceptance decision-making, as compared with end users and business managers in ordinary business settings. Results obtained from the structural equation modeling analysis suggested that the research model exhibited a satisfactory overall fit to the collected data and was capable of providing a reasonable explanation of individual physicians’ acceptance of telemedicine technology. As aspect, perceived usefulness is the most significant determinant of physicians’ acceptance of telemedicine technology. In addition to its strong direct effect on intention, perceived usefulness also exhibited a considerable indirect effect on intention, via attitude. The observed significant effect of perceived usefulness on technology acceptance impact and provide emphasize a physician’s utilized the usage of technology. Perceived ease of use, in the research, was found to have limitation impact on attitude. This result reported in several prior technologies acceptance and adoption studies that had focused on common user groups. The responsibility and dedicated group the support the physicians may cause why perceived ease of use was insignificant. Furthermore, perceived ease of use appeared to have no significant effects on perceived usefulness, suggesting that physicians are not likely to consider a technology to be useful simply because it is easy to use. Perceived ease of use, on the other hand, appeared to have a significant effect on perceived technology control. This finding suggests that a physician’s perceived control in the use of telemedicine technology may improve when the technology is considered to be easy to use. Understandably, the perceived level of technology control in operating a technology decreases when the technology is considered to not be difficult or complicated to use. In this research, Chau and Hu (2002) found that compatibility was found to be a significant determinant of perceived usefulness and not perceived ease of use. The indirect effect of compatibility on intention is comparable to the direct effect of perceived usefulness on intention and is greater than the direct effect of attitude on intention. The compatibility of a technology with an individual professional’s current work practice may be a critical antecedent to perceived usefulness, which may play an important, although indirect, role in developing a positive attitude toward using the technology. A physician’s use of a technology highly compatible to their current practice style/preference is not likely to introduce unfavorable changes in their perceived role in the provision of services and, at the same time, may contribute to increased usefulness of the technology as perceived by the physician. Compatibility appeared to have no significant direct influences on intention but it exhibited a significant indirect effect on intention via perceived usefulness, alone or in conjunction with attitude. This finding suggests that compatibility may represent a necessary but insufficient condition for technology acceptance by individual professionals. Chau and Hu (2002) found the attitude showed a significant direct effect on intention and, in effect, appeared to be the second most important determinant of intention, next to perceived usefulness. This finding is largely consistent with results from many previous studies that have examined the relationship between attitude and behavioral intention. Thus, forming a positive attitude toward accepting the technology under discussion is crucial for both professional and common users. Chau and Hu (2002) also discovered that peer influence appeared to have no significant effects on either attitude or intention. They also found that perceived technology control appeared to have a significant effect on intention, but to a lesser extent than attitude and perceived usefulness did. This may cause of the technology operations in general may not be particularly complicated, especially when considering physicians’ learning capability and staff support from nurses and technologists alike. the relatively uncomplicated technology operations, reasonable staff support, and relatively high intellectual/learning capacity may have decreased the effects of perceived technology control on technology acceptance by individual physicians. Findings of Chau and Hu, (2002) study shed light on several areas where professional and common users might subtly differ in their respective technology acceptance decision-making. Specifically, professionals appear to be fairly pragmatic, focusing on the usefulness of a technology rather than on its ease of use. Individual professionals appear to have strong concerns about technology-practice compatibility, tend to place less emphasis on their control of technology use, and appear to attach a limited weight to suggestions or opinions from peers. Chau and Hu, (2002) found in this study reveal the importance of attitude cultivation and solidification in managing technology acceptance by individual professionals. The dissemination and communication of positive perceptions of the technology’s usefulness are crucial. Management needs to devise strategies that establish and communicate assurance of the technology’s compatibility with the physicians’ current practices rather than requiring a major overhaul of existing service routines or styles. Chau and Hu, (2002) observed insignificance of peer influence might suggest that physicians are not easily susceptible to influence from others, an interesting manifestation of a characteristic natural to their underlying professionalism. Nevertheless, when promoting telemedicine technology, management may need to focus on highlighting and demonstrating the technology’s usefulness rather than heavily depend on persuasion by those with limited experiences with the technology. Chau and Hu(2002b), examined physicians’ acceptance of telemedicine technology, using a theory comparison approach, theories that used including the technology acceptance model (TAM), the theory of planned behavior (TPB) and an integrated model, may perhaps explain individual physicians’ technology acceptance decisions. The number of responded from more than 400 physicians in Hong Kong hospital. Chau and Hu, (2002b) found perceived usefulness appeared to be the most significant factor affecting physicians’ acceptance of telemedicine technology. The path coefficients from perceived usefulness to both attitude and behavioral intention were consistently the highest in all the models examined. perceived usefulness is likely to insert great influences on a physicians’ intention to use telemedicine technology. Physicians apparently tended to be pragmatic in their technology acceptance decisions, appearing to focus on usefulness in technology assessment. Perceived usefulness was a critical determinant of attitude, exhibiting tremendous influences on individual attitude formation. The observed significant role of perceived usefulness in individual attitude formulation might also have been partially rooted in physicians’ tool-oriented view of technology, acceptable only when demonstrating proven or desired utility in their practices. Chau and Hu(2002b) found perceived ease of use appeared to have no significant effects on either perceived usefulness or attitude. Perceived ease of use was found inconsistent with the results and others prior studies. The inconsistency may cause of signify fundamental differences between individual professionals and the typical technology users commonly examined in previous research. Physicians have relatively high general competence and mental/cognitive capacity and may comprehend the use of a technology quickly; that is, become familiar with its operations without going through the intense training that might be necessary among other user populations. Physicians in many cases have relatively strong staff support for operating medical equipment and related technologies. Chau and Hu(2002b) found that attitude appeared to be the second most important determinant of a physicians’ intention for accepting telemedicine technology. A critical role of attitude in technology acceptance decision making by individual professionals and therefore singles out the importance of attitude cultivation and management to successful technology implementation. Chau and Hu(2002b) establish that subjective norms appeared to have no significant effects on behavioral intention. Physicians are likely to develop independent evaluations and consequently may place less weight on others’ opinions. The finding that highlights the insignificance of perceived ease of use suggests another interesting dimension on which technology acceptance decisions might differ between individual professionals and other user populations. Chau and Hu (2002b) found that perceived behavioral control appeared to have significant influence on behavioral intention but not to an extent comparable to attitude the significant but modest effect is that the operations of telemedicine technology in general may not be particularly complicated, especially when considering physicians’ general competence, learning capability, and the staff support commonly available from nurses and technologists. The path from perceived behavioral control to behavioral intention was also less significant than that from perceived usefulness to behavioral intention. The weaker link between perceived behavioral control and behavioral intention might partially have resulted from physicians’ limited experience with telemedicine technology. The healthcare professionals appear to be fairly pragmatic, concentrating on the technology’s usefulness rather than on its ease of use. These professionals seem to be relatively independent in making technology acceptance decisions, e.g. not attaching much weight to suggestions or opinions from others. The study generates interesting empirical evidence that highlights plausible limitations of TAM and TPB in explaining or predicting technology acceptance by healthcare and possibly other professionals. Both models were able to account for an acceptable but not a dominant portion of the behavioral intention variances observed. The fact that none of the investigated models was able to explain half of the behavioral intention variance may signify the need for a broader exploration of factors beyond TAM and TPB. Chau and Hu, (2004) reported some important issues and common pitfalls in telemedicine technology implemented in Hong Kong. There were several important information’s was gathered form their observation such as the role of a motivated and determined clinical administrator was critical to telemedicine technology implementation. In the early implementation stages, the influence of a clinical administrator may be particularly prominent. The clinical administrator should be responsible for cultivating favorable attitudes, encouraging discussion and assessment of target services and technology requirements, facilitating technology experimentation and evaluation, and fostering technology acceptance and utilization. Secondly, from their study is that consensus is an inevitable ingredient for effective implementation, and must be closely monitored and managed in anticipation of a subsequent adoption decision where its maybe positive or otherwise. Informal communication that takes place on a peer-to-peer basis may be instrumental to consensus building. Managerial influences can catalyze and accelerate such communication, but its convergence cannot be driven administratively. Thirdly, user acceptance greatly depends on consensus building in the initiation phase and on member physicians’ participation in adoption decision making and subsequent adaptation activities. Favorable psychological attachments and cognitive/behavioral familiarity with system operations are both important to technology acceptance, and can be effectively achieved through user involvement and training in early implementation stages. Convenient access is also relevant, because of the virtual nature of telemedicine, system access may need to extend beyond geographical constraints or organizational boundaries, allowing. Fourth, connection choice is critical and when not adequately selected, may eventually become a bottleneck to technology utilization. Fifth, routinization requires adequate service financing and must be economically accountable for operations costs incurred in service provision and delivery. And in Hong Kong funding from various government agencies or private organizations is reasonably available. Lastly, integration of telemedicine services with the existing infrastructure is an essential prerequisite to its amalgamation into the adopting organization. Chau and Hu, (2004) recommended that telemedicine represents a promising and exciting technology-enabled solution for long-standing problems in health care, including service accessibility, quality, costs, and resource allocation. From their point of view, the ultimate success of telemedicine as a viable service delivery and collaboration alternative requires that health care organizations properly address technological and managerial challenges. 2.6 Research Model The literature review that has been done in previous, bring this research to formulate the research framework. This research frame will be use and analysis in Malaysian hospital environment for the purpose to test the theoretical and the actual practice. In formulating, the conceptual framework was driven from the previous researcher such as Chau and Hu(2002b) and Venkatesh,(2003) . This study makes an effort to grant a wide range framework integrating the enhancement of organizational, implementation, technological and individual factors on understanding the end user technology acceptance. In order to determine more easily to understand the technology acceptance by end user, reshaping the way of viewing the independent factors by generalization approach may contributing better perceptive. Implementation Context Technological Context Individual Context Behavioral Intention Goal Behavior Moderator Belief Altitudinal Behave Adopt from Chau and Hu Frame work(2002), Venkatesh (2003) and Schaper and Paven (2005) 2.6.1 Organization Context 2.6.1.1 Perceive Task Task-technology fit (TTF) theory holds that IT is more likely to have a positive impact on individual performance and be used if the capabilities of the IT match the tasks that the user must perform (Goodhue and Thompson, 1995). The main idea of this theory understand the task provide by any body or organization must be fit with the technology to been provide and will product positive impact on individual performance. D.L. Goodhue et al. (2000), in their research on user evaluations of task-technology fit for mandatory use systems and develop theoretical arguments for the link to individual performance. The result found that a strong link between user evaluation and performance may require when users receive feedback on their performance is proposed. A.I. Shirani et al. (1999) , in the study was to examine the interaction between task structure and technology to support synchronous and asynchronous group communication. Dennis et al.(2001), they conducted a meta analysis to summarize and synthesize the results of the past 15 years of research. The analysis found that fitting the GSS to the task had the most impact on outcome effectiveness (decision quality and ideas), while appropriation support had the most impact on the process and time required and process satisfaction. Karimi, Somers, and Gupta ( 2004 ) in their study on the impact of environmental uncertainty and task characteristics on user satisfaction with data. They found that managerial decision-making tasks are affected by rapid changes that occur in organizational task environments, and that when confronted with environmental uncertainty, users experience more non routine and interdependent tasks. The study believe that perceive task may be very important determinant factors to ensure that what happening of any adoption should be match with technology that must fit with user and in this study the physicians. As Chau and Hu, 2002b presented that physician may differ to other type of end user such as managerial, student and others. We perceive that any task must fit with technology in health care context. As found in Chau and Hu,2002a, Hu et. al, 1999, Chismar and Payton, 2003 and Rawstore , 1998 , perceive usefulness as determinate factors for physician in making decision. This conclude that task of job must fit with technology that be presented to physicians. 2.6.1.2 Perceive Cost and Financial Santiago Rementeria, (1997) informed that current software assessment models are frequently constrained to the software development and management process only. This will cause of difficulty in obtaining adequate profits from growing software investments, and also in aligning software strategy with the parent organization s business strategy. Chau,(2002a) indicated that persistent problems plaguing contemporary health care, including access, quality, resource distribution, and cost containment, have contributed to telemedicine’s economic, social, and political appeal. Chau and Lai, (2003) reported that organization or company provided different competitive strategies, which include cost containment, performance improvement, market penetration, and product transformation, banks and financial services companies are finding ways to utilize Internet technologies and to launch Internet banking services. Such as consumer-tracking technology allows the identification of individual buyers and information-rich products lend themselves to cost-effective personalization. They also found that the Internet is also believed to be a ubiquitous and low-cost platform for implementing inters organizational systems. More important developments will provide integrated services such as one-stop comprehensive financial services, which can lead to a huge cost reduction in customer services. Chau and Tam, (2000), reported that higher cost for an innovation is negatively associated with its adoption. In open systems, the cost of adoption may be associated with the technical or organizational uncertainties involved. Chau and Hui, (2001), studied with 200 organizations in various industry groups surveyed, the study concluded that relative advantage, technical compatibility, and cost are significant factors in making the EDI adoption decision. An important group of characteristics affecting the innovation process are those related to the cost–benefit trade-off of adopting a particular innovation. The potentially high cost, in terms of getting the EDI system in place and in function, may reduce the incentive to adopt. As indicated by many practitioners, the difference between traditional EDI and Web-based EDI lies mainly on cost and connectivity. This has profound implications to small businesses because one of our key findings is that cost is major impedance barring small businesses from adopting EDI. Therefore, one could expect the perceived cost dimension to be of much less significance in Web-based EDI adoption in small businesses but may be not to others organization. Chau and Hu, (2004) routinization requires adequated service financing and must be economically accountable for operations costs incurred in service provision and delivery. And in Hong Kong funding from various government agencies or private organizations is reasonably available. 2.6.1.3 Perceive Management Support Top management support was defined as the degree to which top management understands the importance of the Information system function and the extent to which it is involved in Information System activities. The study on top management support was been done in a non healthcare environment and in healthcare environment, some of the studies in a non health care environment such as the implementation of internet (King,2001), Information Technology and Information system integration (Bakar,2001), public management information system ( Ang et. al, 2001; Hussein et al.,2005b), Enterprise Resources Planning ( Ramayah & Eri, 2005) and others. Chau and Hu, (2004) in their research reported some important issues and common pitfalls in telemedicine technology implemented in Hong Kong. Several important information’s were gathered form their observation such as the role of a motivated and determined clinical administrator was critical to telemedicine technology implementation. In the early implementation stages, the influence of a clinical administrator may be particularly prominent. The clinical administrator should be responsible for cultivating favorable attitudes, encouraging discussion and assessment of target services and technology requirements, facilitating technology experimentation and evaluation, and fostering technology acceptance and utilization. From their study is that consensus is an inevitable ingredient for effective implementation, and must be closely monitored and managed in anticipation of a subsequent adoption decision where its maybe positive or otherwise. From their point of view, the ultimate success of telemedicine as a viable service delivery and collaboration alternative requires that health care organizations properly address technological and managerial challenges. Chau and Hu(2002b), from a technology management standpoint, findings of the study revealed the importance of attitude cultivation and management. To foster individual acceptance of a newly adopted or implemented technology, management in a professional organization needs to devise strategies for cultivating positive attitudes toward using the technology. Upon deciding to adopt telemedicine technology, management should strongly emphasize, demonstrate and communicate the technology’s usefulness to the routine tasks and services of individual physicians. Initial information sessions and training programs should focus on how the technology can improve the efficiency or effectiveness of individual physicians’ patient care and services rather than on familiarization with the detailed procedures for operating the technology. Continued education programs, clinical workshops and international conferences are adequate arrangements for increased awareness and knowledge about telemedicine technology and its applications. When introducing telemedicine technology and promoting it, the acceptance among physicians, management, nevertheless, needs to evaluate these facilitating conditions, e.g. access and training. Igbria et. al. (1997) used the results from a survey of 358 users in small firms in New Zealand to test a structural model examining the hypothesized relationships among the following constructs: intraorganizational factors, extraorganizational factors, perceived ease of use, perceived usefulness, and personal computing acceptance. Among the researches that has been done was to large and small organizations which the same purpose to identified several factors affecting IS success and in this research to study an identified the healthcare organization and investigate it acceptance technology by physicians. Management supports, external or internal technological supports or trainings are confirmed to have significant influence on user perceptions such as perceived usefulness or ease of use in small firms. Even though not directly comparing small firms and big firms, they still made some convincing arguments that users in small firms differ from those in big firms in terms of user technology acceptance, especially the influence of facilitating. Igbria et al, (1994) found that some has identified that the organizational commitment have also been identified as important attitudinal outcome of employee career motivation and management support will be identical to the organization commitment because in any organization there must be direct and indirect effect from top to bottom management. As Davis, 1989 identified that there numerous external factors that influence on perceived ease of use and perceived usefulness, so in this study the internal and external computing and management support will become the external factors as defined by Davis, 1989. 2.6.1.4 Perceive Accessibility Chau and Hu (2004) convenient access is also relevant, because of the virtual nature of telemedicine, system access may need to extend beyond geographical constraints or organizational boundaries. Another research done by Chau and Lai (2003) on the determinants of user acceptance of internet banking was done based on Davis’s technology acceptance model with 4 additional variables that are theoretically justified as having influence on perceived usefulness and perceived ease of use, a research model for the investigated technology acceptance was developed and empirically examined, using responses from more than 160 intended users of the technology. They found that, the results of the data analysis generally support the proposed hypotheses. One of this hypotheses relate to my study is that the accessibility factor, was found to have significant influence on perceived usefulness and perceived ease of use, which, in turn, was found to be an important factor in fostering a positive attitude toward accepting the services. As stated by Venkatesh et. al., (2003) performance expectancy represent perceived usefulness and effect expectancy represent perceived ease of use. This meant that accessibility ( Karahana and Straub,1999 ) as and important aspect the provided direct and indirect impact to user behavior intention. As accessibility factors an external factor that influenced the effect expectancy represent perceived ease of use, where this factors can influences the behavior intention directly and indirectly via performance expectancy represent perceived usefulness. This highlighted that there were some looping between accessibility factors and performance expectancy and effect expectancy. As suggested and empirically supported by Karahanna and Straub, 1999 accessibility is a multidimensional construct encompassing both physical terminal access and system usage ability. They found that the more accessible an information system is, the less effort is needed to use the system or applications. In the context of organization, accessibility refers to the physical and information accessibility of information system with the organizational context. Accessibility was measured by a scale adapted from Culnan, 1985 in assessing user perceptions of information accessibility when using computer-based IS. Two items were used to reflect the physical and informational of healthcare organizational. 2.6.1.5 Perceive Technical competent Kuan and Chau, 2001, informed that the benefits perceived by company organization can be achieved within the allotted resources. They belief that perceived benefits cannot be achieved due to lack of company resources, adoption is worthless to the company regardless of how huge the benefit are. They reported that technical knowledge and skill have been identified as important factor the hinder IT growth in small organizations. Some researcher named factors like costs and technical knowledge and skill as organizational readiness to be important factors affecting EDI or information technology adoption in small business. In physicians’ point of view are they competent enough to handle the information technology as their supporting tools in their daily working environment. This technical competent were identified as important factors for EDI or information technology use and their organization. Chau and Hui, 2001 found that prior EDI experience (Dishaw and Strong,1999; Jackson et al.,1997) was to be significant determinant of EDI adoption in small businesses. Regardless of the size of an organization, one critical factor in the adoption decision of an IT is the extent of experience and knowledge of that particular type of technology as perceived by that organization. 2.6.2 Implementation Context The implementation context refers to the particular professional setting or situations where the target technology is to be implemented. Chau and Hu (2002b) applied the idea of the implementation context. Shaper and Paven,2005 suggested that professional environment of the user as outlined in their research model includes the determinants of social influence, organizational facilitating conditions and compatibility, where they added organizational facilitating conditions as suggested by (Venkatesh et. al.,2003). Social influence in UTAUT was define as the degree to which an individual perceives that important others believe he or she should use a technology and Peer influence in Chau and Hu (2002b) there were closely related to subjective norms but focus to professional peers only. Venkatest et. al.,2003 found that in internalization and identification an individual’s belief structure is altered, whereas compliance causes an individual to alter his or her intention based on social influence, and has effect of social influence on behavioural intention has been shown in technology acceptance studies (Karahanna, Straub & Chervany 1999; Venkatesh & Davis, 2000). But different finding was acknowledge form the health care setting. Social influences were insignificant in the intention decisions of physicians to use Internet-based health applications (Chismar & Wiley-Patton 2003) and in the intention decisions of physicians to use telemedicine (Chau & Hu 2002b). Organisational facilitating conditions are defined as the degree to which an individual believes that an organisational and technical infrastructure exists to support use of the system (Venkatesh et al. 2003). (Venkatesh ,2000) found support for full mediation of the effect of facilitating conditions on behavior intention by effort expectancy. Chau, (1996) found that transitional support as organisational facilitating conditions indirect support in CASE acceptance study. Chau, 1997 also found that complexity of IT infrastructure has significant influence to IT innovation decision making, as define by UTAUT IT innovation able to influence effort expectancy, effort performance and usage behavior. UTAUT found evidence suggesting the insignificance of facilitating conditions in predicting behavioural intention when both performance expectancy constructs and effort expectancy constructs are present in the model (Venkatesh et al. 2003). Chau and Hu, (2002b) use compatibility as important factors and defines as to the degree to which the use of telemedicine technology is perceived by a physician to be consistent with their practice style or preference. Compatibility show its consistent finding in technology acceptance researches such as IT adopt decision ( Moore and Benbasat, 1991), operating system ( Karahanna, Straub & Chervany,1999), Internet banking ( Gerrard & Cunning,2003), and factors of attitude toward using a technology ( Taylor and Todd, 1995a and Tan & Teo , 2000 ). But in UTAUT, compatibility was included in facilitation conditions ( Venkatesh et. al, 2003). Because compatibility has clear reputation as determine, in this research compatibility as important antecedent. Compatibility may also influence behavioural intention indirectly through performance expectancy and effort expectancy. Chau & Hu (2002a) found support for compatibility of telemedicine technology exerting a significant effect on perceived usefulness. 2.6.3 Individual Context The individual context of the research model encompasses (Shaper and Paven,2005) and attitude and Perceived Technology Control ( Chau and Hu,2002a). Venkatesh, (2003) in the analysis of development UTAUT, found that computer anxiety, computer self-efficacy and computer attitude not insignificant to behavior intention because of the effect of effort expectancy ( Venkatesh, 2003 ) but form Chau and Hu,2002a found that attitude ad perceived technology control was significantly influence the behavioral intention. Compare to both study it was found that professional individual ( Chau and Hu, 2002a ) has different perception and characteristics business managers and students who have been the traditional subjects of technology acceptance research. Attitude towards computers was found to play a critical role in the technology acceptance decisions of physicians (Chau & Hu 2002b; Hu et al. 1999) and a direct predictor of behavioural intent in nursing staff (Hebert 1994). Perceived behavioral control appeared to have significant influence on behavioral intention but modest effect is that the operations of telemedicine technology in general may not be particularly complicated, especially when considering physicians’ general competence, learning capability, and the staff support commonly available from nurses and technologists (Chau and Hu, 2002b). Personal Innovativeness in the domain of Information Technology ( PIIT ) Personal Innovativeness was proposed by Agarwal and Karahanna, 2000. PIIT in defined as the willingness of an individual to try out any new information technology and in this study it can be posit as the individual wiliness to explore new application on the exiting information technology. PIIT was belief to be one of the main factors that being left out in the technology acceptance model. PIIT was found to be significant to explain behaviour intention. Venkatesh and Brown, (2001) suggested that future studies on personal computer adoption in household, that managers in organizational settings must consider the influence of non-utilitarian technology outcomes. They proposed that personal innovativeness (Agarwal and Prasad 1998) present starting points for work that aims to leverage hedonism in the workplace to create more favorable user perceptions about technology. They noted that having a PC at home associated with increased workplace adoption, greater understanding of utilitarian and hedonic outcomes, or perhaps ease of learning new applications. One is very likely to feed the other, and their mutual relationship and understanding can be examined. This mean PIIT can play a main role when the user has a mutual relationship with the information technology and to getting to acceptance it. Thatcher & Perrewe (2002), found that there are clear change on the pattern of relationships among dynamic, IT-specific individual differences (i.e., computer anxiety and computer self-efficacy) and stable individual differences (i.e., personal innovativeness, negative affectivity, and trait anxiety). A total of 280 surveys were distributed and a total of 211 responses (75%) were used in this analysis. The sample consisted of students at a large public university in the Southeastern United States. The findings provide insight into the nomological net among dynamic individual differences, situation-specific stable traits, and broad stable traits that relate to IT acceptance and use. The study found that PIIT has a positive correlate with computer self-efficacy and negative relationship with computer anxiety. Due to computer self-efficacy and computer anxiety are important antecedents to computing beliefs (Venkatesh and Davis 1996) and attitudes (Harris 1999). It is important to develop a more comprehensive model of how organizations encourage IT acceptance and use. Lewis et al., (2003), found that institutional forces, social forces, and individual characteristics exhibit significant and differential impacts on two key individual beliefs about the use of information technologies: beliefs related to usefulness and ease of use. A total of 161 complete survey was returned across a variety of academic disciplines return for the final sample used for data analysis. The result found that the individual factor of personal innovativeness and institutional factor of top management commitment had significant relationships with perceived usefulness, both about 50. Significant determinants of ease of use were top management commitment and support, and both the individual factors of computer self-efficacy and personal innovativeness, and accumulated about 40% of the variance in the dependent variable. Age Age has be present one of most important influence factor in many technology adoption researches ( Gefen & Straub, 1997; Venkatesh et al., 2003) and as control for demographic variables (Schultze & Carte, 2007; Klientop & Blau, 1994). Study by Lehane & Huf, (2005) indicates that age may effect of participant characteristic on responses to system acceptance criteria, and were considered in conjunction with the role of the participant in the corporate structure. Ho & Lui (2003) in their exploratory study on one’s acceptance of the Internet content filters in publicly accessed computers. They found that aging issue especial female, have impacts on one’s perceived needs to restrict the objectionable materials from the Internet. Gender Venkatesh et. al., (2003) found that gender was one of the most significant moderating. Gender has direct impact to behavioral intention via performance expectancy, effort expectancy and social influence. In others study gender was use as control for demographic variables (Schultze & Carte, 2007; Klientop & Blau, 1994). According to Lehane & Huf, (2005) that gender may effect of participant characteristic on responses to system acceptance criteria, and were considered in conjunction with the role of the participant in the corporate structure and perceived needs to restrict, ( Ho & Lui, 2003) of internet materials. 2.6.4 Technological Context The importance of perception in an individual’s evaluation of technology and their decision to accept it is attested to in literature from both the cognitive and behavioural sciences. Perceptions rather than objective technology attributes have been found to be more relevant to technology acceptance decision making (Moore & Benbasat 1991), and are the focus of the investigation into technological context in this study. The technological context is made up of two determinants – performance expectancy and effort expectancy. Performance Expectancy Performance expectancy (operationalised as ‘usefulness’) is defined as the degree to which an individual believes that using IT will help him or her to attain gains in job performance (Venkatesh et al. 2003). In previous acceptance studies, the performance expectancy construct is consistently a strong predictor of intention (Davis, Bagozzi & Warshaw 1992; Taylor & Todd 1995; Venkatesh & Davis 2000; Venkatesh et al. 2003). In a health care context, performance expectancy is important to technology acceptance decision making and may influence behavioural intention both directly and indirectly through the determinant of attitude (Chau & Hu 2002a). The significance of performance expectancy to health professionals has been consistently shown in those studies that have examined technology acceptance in health (Chau & Hu 2002b; Chismar & Wiley-Patton 2003; Hu et al. 1999; Jayasuriya 1998). 2.6.4.1 Effort Expectancy Effort expectancy is defined as the degree of ease associated with the use of the system (Venkatesh et al. 2003). In stark contrast to technology acceptance studies in other environments, studies completed in the health sector suggest that effort expectancy is not applicable in the health professional context (Chau & Hu 2002b; Chismar & Wiley-Patton 2003; Hu et al. 1999; Jayasuriya 1998). In all these studies, effort expectancy (operationalised as ‘ease of use’) was found to have no significant influence on intention behaviour. Despite these results, it was decided to include effort expectancy in the research model to limit deviation from UTAUT and due to the need for further empirical research to validate the significance of effort expectancy on acceptance decisions. Indeed, given the significant time demands placed on clinicians, it could be argued that technologies that are perceived to be uncomplicated or easy to use would have positive influences on behavioural intention, due to the limited time a therapist would need to invest in learning how to use the technology. 2.6.5 Behaviour Intention The intention-behaviour relationship is well documented in the technology acceptance literature and has been found to be conclusive when applied to industry and health-care contexts (Chau & Hu 2001; Chismar & Wiley- Patton 2003; Davis, Bagozzi & Warshaw 1989; Sheppard, Harwick & Warshaw 1988; Venkatesh et al. 2003). The link between intention to use a technology and actual usage is well-established (Ajzen 1991; Mathieson 1991; Sheppard, Harwick & Warshaw 1988; Taylor & Todd 1995; Venkatesh & Morris 2000) and both variables may be used to measure technology acceptance. Use Behavior (Davis, 1993; Davis et al., 1989; Mathieson, 1991) reported that behavioral intention usually explanation for variance in actual use behavior. (Venkatesh et al., 2003 ) empirically showed that behavioral intention and facilitating conditions determined actual use behavior. (Venkatesh et al., 2003 ), UTAUT believe behavior intention to be the most significant factor determining actual use behavior. UTAUT incorporates three key determinants for behavioral intention: performance expectancy, effort expectancy and social influence, and one factor, together with behavioral intentions, that influences actual use behavior directly: facilitating conditions. (Adams, Nelson, & Todd, 1992) in their two studies that replicated Davis’ work and test the validity of the ease-of-use and usefulness scales using independent sample for a variety of technologies. The results of study show that usefulness is an important determinant of system use. But the second results found it mixed, but indicate the importance of both ease of use and usefulness. It shows that in difference conditions of usage explain of both findings. This mean usefulness and ease of use are not only factors that will influence the usage of information technology. Its may influence by other factors depend on conditions of the end users. (Szajna, 1994) reported in his finding that perceive usefulness and perceive ease of use instrument has been shown to have predictive validity for intentions to use, self report usage, self-predicted usage, attitudes toward use, and choice. (Taylor & Todd, 1995) found that different variables within the model may have different influences on intention and usage depending on experience. Experience plays one of a prominent role in IT usage among users because others factor that related with experience should be consider to in order understanding the usage. Other factors like gender, year in the program and etc should be considered when dealing with experienced and inexperienced users. The user may have different perception on IT usage referent to the experience. (Igbaria, Zinatelli, Cragg, & Cavaye, 1997), found that factors affecting personal computing acceptance among users in small firms, they found that perceived ease of use is a dominant factor in explaining perceived usefulness and system usage, and that perceived usefulness has a strong effect on system usage. The focus of the study was on voluntary computer use rather than mandatory use, system usage was used as an indicator of personal computing acceptance. From the finding it also shows that system used was impacted by exogenous variables that influenced both perceived ease of use and perceived usefulness, particularly management support and external support. This mean, system use or usage was depending on various external factors in considering IT usage. Organizational Context · Management Support · Financial & Cost · Accessibility · Task Fit · Technical Competence · Social Influence · Facilitating Condition · Compatibility Implementation Context · Performance Expectancy · Effort Expectancy Technology Context · Anxiety · Self Efficacy · Attitude · Personal Innovativeness · Perceived Technology Control · Age · Gender · Experience · Voluntariness Individual Context Behaviour Intention Use Behaviour Research Model 

RESEARCH FRAMEWORK AND HYPOTHESES 3.0 Introduction The previous chapter provided a literature review of user technology acceptance model and the importance of information technology in health sector. This chapter presents a research framework to establish the interaction between independent and dependent variable. This research frame work will be use and analysis in Malaysian hospital environment for the purpose to empirically study the theoretical and the actual practice. 3.1 The Conceptual Framework The conceptual framework was formulated based from the previous study by Davis(1989), Hu et. al,(1999), Davis and Venkatesh,(2000), Dixon and Stewart(2000), Chua and Hu(2002a), Chau and Hu(2002b), Venkatesh,(2003), Schaper and Paven,2003. and Chismar and Patton,2003. This study attempts to provide a wide range framework by integrating the enhancement of organizational, implementation, technological and individual factors on understanding the end user technology acceptance. In order to determine more easily and to understand the technology acceptance by end user, reshaping the way of viewing the dependent and independent factors by generalization approach may contribute better perceptive. 3.2 Research Framework This thesis intends is to investigate the factors influencing information technology acceptance amongst physicians in government hospital. Based several previous researches, literature reviews and empirical evident done by well know researchers, the independent factors that will be focused in this studies are, individual, implementation, technological and organization factors. Following are the antecedent of these factors. Generalizing factors Individual Context Computer anxiety Venkatesh(2003) Computer self-efficacy Venkatesh(2003) Computer attitude Chau & Hu, 2002b; Hu et al.,1999; Hebert,1994. Perceived Technology Control Ajez,1995 Personal Innovativeness Agarwal and Prasad [1998]; Agarwal and Karahanna [2000] Technological Context Performance expectancy Davis et. al.,1992; Taylor and Todd,1995; Venkatesh & Davis, 2000; Venkatesh et. al.,2003 Effort expectancy ; Hu et al.,1999;Chau & Hu,2002b; Chismar & Wiley-Patton,2003; Venkatesh(2003) Implementation Context Social influence Venkatesh & Davis,2000; Venkatesh,2003; Karahana et al.,1999; Chismar & Wiley-Patton,2003; Chau & Hu,2002b Compatibility Chau & Hu,2002a; Moore & Benbasat, 1991; Taylor & Todd,1995 Facilitating conditions Venkatesh,2003 Perceived Behavioral Control Azjen, 1995 Organization Context Perceive Cost and Financial Chau, 2001 Perceived Technical Competence Chau, 2001 Management support Igbria et al.,1999; Liao and Landry,2000 Accessibility Karahanna and Straub,1999; Karahanna and Limeyem,2000 Perceived Task Goodhue, 1995 In this study, modified model by integrating UTUAT by Venkatesh, (2003) and Chau and Hu, (2002b), where Organization Context are included as one of major factors that influencing physicians behavioral intention in using information technology in there daily works operations. 3.3 The Research Model Based on the research framework in model below, the research hypotheses were formulated in this section. Organizational Context · Management Support · Financial & Cost · Accessibility · Task Fit · Social Influence · Facilitating Condition · Compatibility Implementation Context · Performance Expectancy · Effort Expectancy Technology Context Behaviour Intention Use Behaviour H1 H15, H16, H117, H18 H2, H3a, 3b, 3c & H4a, 4b H5a,5b & H6 H7, H8a,8b, H9a, 9b, & H10, H11, H12, H13 & H14 · Anxiety · Self Efficacy · Attitude · Personal Innovativeness · Perceived Technology Control · Age, Gender , experience & Voluntariness Individual Context 3.2.1 Behavioral Intention 3.2.1.1 Behavioral and Intention relationship is well know factor in industry and healthcare context ( Chau & Hu,2001; Chirmar & Wiley-Patton,2003; Davis et al.,1989; Venkatesh,2003). H1: Behavioral intention will have a significant positive influence on physicians’ use behavior. 3.2.1.2 Link between behavior intention to use and actual usage is well known and established ( Ajzen,1991; Mathieson,1991; Taylor & Todd,1995; Venkatesh & Morris, 2000) and both variables can used to measure technology acceptance. 3.2.2 Implementation Context 3.2.2.1 Social Influence - is the degree to which an individual perceives that import others believes him/her to use technology. There are significant (Venkatesh & Davis,2000; Venkatesh,2003; Karahana et al.,1999) and insignificant (Chismar & Wiley-Patton,2003; Chau & Hu,2002b) in their studies. This factor can be test in this research for better understanding. H2 – Social influence will positively affect the intensity of physicians’ behavior intention. 3.2.2.2 Compatibility – The degree to which an innovation is perceived as being consistent with the existing values, needs, and past experience of potential adopters in healthcare( Chau & Hu,2002a; Moore & Benbasat, 1991; Taylor & Todd,1995). H3a – Compatibility will positively affect the intensity of physicians’ behavior intention. Compatibility may also have indirect influence on behavioral intention through performance expectancy and effort expectancy. (Chau & Hu,2002a) H3b - Compatibility will have an indirect effect on the behavioral intention. H3c - Compatibility will have an indirect effect on the behavioral intention. 3.2.2.3 Facilitating conditions are defined as the degree to which an individual believes that an organizational and technical infrastructure exists to support use of the system.( Venkatesh et. al,2003 ) H4a - Facilitating conditions will not have a significant influence on behavioral intention H4b: The influence of facilitating conditions on usage 3.2.3 Technological Context 3.2.3.1 Performance Expectancy – is defined as the degree to which an individual believes that using ICT will help him/her to attain gains in job performance (Venkatesh et. al.,2003) and a strong predictor of intention ( Davis et. al.,1992; Taylor and Todd,1995; Venkatesh & Davis, 2000; Venkatesh et. al.,2003) H5a - Performance expectancy will positively affect physicians’ behavioral intention. H5b – Performance expectancy will indirect affect physicians’ behavioral intention via computer attitude. 3.2.3.2 Effort Expectancy – is defined as the degree of ease associated with the use of the system(Venkatesh,2003), is not applicable in the health professional context, (Chau & Hu,2002b; Chismar & Wiley-Patton,2003; Hu et al.,1999) but due to further empirical research to validated the significance of effort expectancy on acceptance decisions. Because of the limited time a physicians would need to invest in learning hoe to use the technology. H6 – Effort expectancy will positively affect the intensity of physicians’ behavioral intention. 3.2.4 Individual Context 3.2.4.1 Encompasses computer anxiety, computer self-efficacy and computer attitude. Attitude towards computers is a critical role in the technology acceptance decisions of physicians (Chau & Hu, 2002b; Hu et al.,1999), acting as the second most important determinant of acceptance, and a direct predictor of behavioral intent in nursing staff(Hebert,1994) H7 – Computer attitude will positively affect the intensity of physicians’ behavioral intention. UTAUT by Venkatesh(2003) reported computer anxiety and computer self-efficacy has indirect effect on effort expectancy. H8a – Computer self-efficacy will have a indirect affect the intensity of physicians’ behavioral intention via effort expectancy. H8b - Computer self-efficacy will not have a significant effect on physicians behavioral intention. H9a - Computer anxiety will have a indirect affect the intensity of physicians’ behavioral intention via effort expectancy. H9b - Computer anxiety will not have a significant effect on physicians behavioral intention. 3.2.4 2 Perceived behaviour control - TPB extends from TRA by incorporating an additional construct, namely perceived behavioral control, this factor support a situations which an individual lacks substantial control over the targeted behaviour (Ajzen, 1991). Perceived behavioral control also has a direct effect on behavioral intention. H10 – Perceived behaviour control will positively affect the intensity of physicians behavioral intention 3.2.5 Organizational context 3.2.5.1 Technical Competence - The technical competence is an important of sufficient technical factor of organization successful ( Chau, 2001) H15 – Technical competence will positively affect the intensity of physicians’ behavioral intention 3.2.5.2 Financial Cost – The financial cost is an important of resources allocation factor of organization successful ( Chau, 2001) H16 - The financial cost will positively affect the intensity of physicians’ behavioral intention 3.2.5.3 Management Support -The degree of support from the managers to ensure sufficient allocation of resources and act as a change agent to create a more conductive environment for IS success (Igbria et al.,1999; Liao and Landry,2000) H17 - management support is associated with behavioural intention 3.2.5.4 Accessibility - Physical accessibility : the extent to which someone has physical access to the hardware needed to use the system. Information accessibility : the ability to retrieve the desired information from the system( Karahanna and Straub,1999; Karahanna and Limeyem,2000) H18 – The physical and information accessibility is associated with behavioral intention 3.2.5.5 Perceive Task Technology Fit – The task-technology fit model suggests that individual not only consider beliefs about perceived usefulness – performance expectancy and perceived ease of use – effort expectancy, but also the extent to which in the this research is the information technology activities meet their task needs and individual abilities(Goodhue, 1995). H19- Task-technology fit is positively related to behavioral intention. 3.2.6 Conclusion In this research, all factors will be expected to be tested and verified. In this framework, additional context such as organization context will be introduced in the modified and adopted from Chau and Hu, 2002b and Venkatesh,2003 model. Additional factors also included in this study such as standard verbal communication, hedonic and communication establishment. 3.2.7 Chapter Summary This chapter discusses on the development of the research framework resulting from the empirical and conceptual relationships between the independent and dependent variables of the research. From this relationship, about 22 hypotheses will be examined and tested to modified-adopt model. The hypotheses were adopted from previous technology acceptance research where almost all of these hypotheses was never be tested and used in the health care environment. User technology acceptance model of information was found to be a mature model, Venkatesh noted that R square is 69 % but most of the result came from non-medical environments organization. 4.0 Research Methodology 4.1 Introduction This chapter will discuss the methods that will be used in the research that will be carried out within the government hospital in Malaysia. Based on the population of the study, the questionnaire will be given to the very important personnel, the physicians in the hospital that directly intact or dedicatedly responsibly to his / her patients. This study will try to understand in depth of the behavioral intention of physicians towards the information technology by dividing the questionnaire in individual context, technology context, implementation context and additional part is organizational context. 4.2 Research Design This study is to investigate the factors influencing the behavioral intention of technology acceptance among physicians towards the use of information technology in government hospitals. The study will use the quantitative survey and involves data collection from information technology based government hospitals. The instrument used for primary data collection measures the level of acceptance of information technology among physicians in a hospital setting. This study used the psychometric questioners as research instrument, and largely based on a similar questionnaires used by Davis(1989), Hu et. al.(1999), Venkatesh and Davis(2000), Chau and Hu (2002a), Venkatesh(2003), Chau and Hu,2002b; Chismar and Patton, 2003. Davis, (1989) conceived that TAM demonstrates the perceive usefulness and perceive ease of use has a great influence of intention to use of information technology. Chau and Hu, 2002a and Hu et. al.,1999 had tested the model in predicting the intention to use on physician in using information technology application, such as telemedicine. Schaper and Pervan, 2004 develop an conceptual model where the model was adaptation form Chau and hu, 2002b and Venkatesh,2003 where the antecedent of the Venkatesh model was rearrange in to different context such as implementation context, individual context and technology context. The current study tests the conceptual model and added with new context such as organizational context. The population and sampling frame for the current study relies on the physicians in Malaysian Government Hospital that has implemented the information technology application as their communication medium. 4.3 Population and Sampling Frame The population of the study will involve physician located in government hospital, the physicians, in Selayang Hospital, Serdang Hospital, Putra Jaya Hospital and Kuala Lumpur Hospital. In this study, the hospitals act as the government entities that have implemented information technology system application as their tools and facilities in their daily works. S. Rath et al (1999) had defined that the term hospital information system (HIS) that they include all systems of a hospital, both computer-based and manual, that deal with handling and storage of the data. 4.4 Data Collection Method The primary data will be collected using the self - administered procedure. As suggested that a lengthy questionnaire a drop-off method self-administered procedure. This means that the questionnaire would be dropped to the contact personnel and picked up within two weeks from the day they were sent. As physicians are constrained by time available and is a factor very crucial to the life of his or her patient. Perhaps that this time of filling the questionnaire will be more conducive to the physicians compared to their working hours. Folwer,1988 argued that self-administered procedures are considered to be the most excellent since the respondent does not have to admit directly to the interviews a socially undesirable or negatively valued characteristic or behavior. As we know physicians need to be precise and accurate in their jobs, so any interruptions could cause potential loss of their patient life. 4.5 Measurement 4.5.1 Questionnaire Layout and Structure The purpose of the section is to define all variable in the framework for better understanding. As stated by Sekaran (2000) all concepts need to operationally defined for the purpose of measurement. He suggested that, the use of a well-developed instrument, operationally defined, accepted, tested for reliability and validity. As noted, exiting scales of this study was adopted form the previous studies in management information system researches. The questionnaire was structured with seven section, section A to section G and each of the section compassing a different subject. Section Subjects A Demographic Variable B Organizational Context C Implementation Context D Technological Context E Individual Context F Behavioral Intention G Use Behavior In this study, the variables to be measured contain demographic variable, individual context, technological context, implementation context, organizational context, and behavioral intention and use behavior. . The measurement will adapted from the previous study that operational defined, accepted and proven. All most of the questions will be based on a seven-point Likert-scale to represent the responses of the subjects In this research, the variable that will be tested in Malaysian environment that had be tested by Schaper and Pervan,2004 model adapting from Chau and Hu,2002b and Venkatesh,2003 by using UTAUT antecedents. In the current study, the organization context was introduce in the Schaper and Pervan model, and some additional antecedents such as hedonic , workload and communication, standard technology languages use. 4.6 Operational Definition and Measured Operational Definition 4.6.1 Measures of Organizational Factors The study take up four organizational factors, which included of management support, financial and cost, accessibility and technology fit. The definitions were achieved from previous studies on management support (Igbaria et al.,1997) , financial and cost (Kuan & Chau, 2001), accessibility (Karahanna and Limayem, 2000) and task technology fit (Goodhue,1995). Table below, illustrates the four items and their scales of measurement. The items such as management support (Igbaria et al.,1997) and accessibility (Karahanna and Limayem, 2000) were usually used in user technology acceptance previous study compare to financial and cost (Kuan & Chau, 2001 and task technology fit (Goodhue,1995). A seven-point Likert scale was used to measure the responses ranging from 1 = strongly disagree to 7 = strongly agree. Variable Construct Definition Management Support Igbaria et al.,( 1997) The degree of support from managers to ensure sufficient allocation of resources and act as a change agent to create a more conductive environment for IS success. Financial & Cost Kuan & Chau, 2001 Perceived cost and financial referred to the financial resources to pay for “system” installation costs, for implementation of any subsequence enhancements, and for ongoing expenses during usage. Accessibility Karahanna and Limayem, 2000 Physical accessibility : the extent to which someone has physical access to the hardware needed to use the system. Information accessibility : the ability to retrieve the desired information from the system. Technology Fit Goodhue, 1995 The task technology fit model suggest that individual not only considers beliefs about perceived usefulness – performance expectancy and perceived ease of use – effort expectancy, but also the extent to which in this research is the information technology activities meet their task needs and individual abilities. 4.6.2 Measurement of Organizational Factors using Likert-scales Items Scales ` Strongly Disagree Strongly Agree I Management Support 1 Management is aware of the benefits that can be achieved with the use of computers. 1 2 3 4 5 6 7 2 Management always supports and encourages the use o f computer for job-related work. 1 2 3 4 5 6 7 3 Management provides most of the necessary help and resources to enable people to use computers 1 2 3 4 5 6 7 4 Management is really keen to see that people are happy with using computers 1 2 3 4 5 6 7 5 Management provides good access to hardware resources when people need them. 1 2 3 4 5 6 7 6 Management provides good access to various types of software when people need them. 1 2 3 4 5 6 7 II Accessibility (please indicate the degree) 1 Computer base system in my office is physically accessible to me. 1 2 3 4 5 6 7 2 It is easy to me to access the information of my computer system. 1 2 3 4 5 6 7 3 It is easy to me to access the information in my organization/department (locally) when I need it. 1 2 3 4 5 6 7 4 It is easy to access the information in my organization/department (remotely) when I need it. 1 2 3 4 5 6 7 4 If I use the system, I will increase my chances of getting a raise. 1 2 3 4 5 6 7 III Perceived Technical Competence 1 I believe the performance providing IT support by my hospital / organization is good. 1 2 3 4 5 6 7 2 In my experience the supporting IT/Computer base system on software application by my hospital / organization is good 1 2 3 4 5 6 7 3 The expertise in supporting IT / Computer base system by my hospital / organization is good 1 2 3 4 5 6 7 4 The senior management of the hospital has been helpful in the use of the system. 1 2 3 4 5 6 7 5 In general, the hospital/organization has supported the use of the system. 1 2 3 4 5 6 7 IV Perceived Financial Cost 1 High set-up cost ( The computer base system have very high set-up cost) 1 2 3 4 5 6 7 2 High running cost ( The computer base system have very high operation cost ) 1 2 3 4 5 6 7 3 High training cost ( The computer system have very high training cost 1 2 3 4 5 6 7 e Task Fit 1 Sufficiently detailed application information about the IT / computer base systems is maintained 1 2 3 4 5 6 7 2 On the IT / computer base system I use, the application information is either obvious or easy to find out 1 2 3 4 5 6 7 3 I can get the application information quickly and easily from a website when I need it 1 2 3 4 5 6 7 4 The application information that I use or would like to use is accurate enough for my purposes. 1 2 3 4 5 6 7 5 The application information is up to date enough for my purposes. 1 2 3 4 5 6 7 6 The application information that I need is displayed in a readable and understandable form. 1 2 3 4 5 6 7 7 The application information maintained at websites is pretty much what I need to carry out my tasks. 1 2 3 4 5 6 7 8 The application information is stored in so many forms it is hard to know how to use it effectively. 1 2 3 4 5 6 7 4.6.3 Implementation Factors Implementation factors had been acknowledged as benefactor of user technology acceptance. The study identified three implementation factors that weighted user technology acceptance. The factors are social influence, facilitating condition and compatibility. A lot of studies in previous researcher show that this operationalizes the technological variables. The study adapted measures by Venkatesh et al. (2003) and Chau and Hu, (2001) that had been empirically demonstrated to be consistent and convincing. A seven-point Likert scale was used to measure the responses ranging from 1 = strongly disagree to 7 = strongly agree. Variable Construct Definition Social Influence Subjective Norm (Ajzen 1991; Davis et al. 1989; Fishbein and Azjen 1975; Mathieson 1991; Taylor and Todd 1995a, 1995b) The person’s perception that most people who are important to him think he should or should not perform the behavior in question. Social Factors (Thompson et al. 1991) The individual’s internalization of the reference group’s subjective culture, and specific interpersonal agreements that the individual has made with others, in specific social situations. Image (Moore and Benbasat 1991) The degree to which use of an innovation is perceived to enhance one’s image or status in one’s social system. Facilitating Conditions Perceived Behavioral Control (Ajzen 1991; Taylor and Todd 1995a, 1995b) Reflects perceptions of internal and external constraints on behavior and encompasses self-efficacy, resource facilitating conditions, and technology facilitating conditions. FacilitatingConditions (Thompson et al. 1991) Objective factors in the environment that observers agree make an act easy to do, including the provision of computer support. Compatibility (Moore and Benbasat, 1991) The degree to which an innovation is perceived as being consistent with existing values, needs, and experiences of potential adopters. Compatibility Rogers [1983] The degree to which an innovation is perceived as being difficult to use 4.6.4 Measurement of Implementation Factors using Likert-scales Items Scale Strongly Disagree Strongly Agree I Social Influence 1 People who influence my behavior think that I should use the IT / computer base system. 1 2 3 4 5 6 7 2 People who are important to me think that I should use the IT / computer base system. 1 2 3 4 5 6 7 3 The senior management of the hospital has been helpful in the use of the IT / computer base system. 1 2 3 4 5 6 7 4 In general, the hospital/organization has supported the use of the IT / computer base system. 1 2 3 4 5 6 7 II Facilitating Conditions 1 I have the resources necessary to use the IT / computer base system. 1 2 3 4 5 6 7 2 I have the knowledge necessary to use the IT / computer base system. 1 2 3 4 5 6 7 3 The IT / computer base system is not compatible with other IT / computer base systems I use. 1 2 3 4 5 6 7 4 A specific person (or group) is available for assistance with IT / computer base system difficulties. 1 2 3 4 5 6 7 III Compatibility 1 Using computers is compatible with aspects of tasks of my job. 1 2 3 4 5 6 7 2 I think that using computers fits well with the way I like to work. 1 2 3 4 5 6 7 3 Using computers fits into my work style. 1 2 3 4 5 6 7 4 Using IT/computer base system fits with the way I work 1 2 3 4 5 6 7 5 Using IT/computer base system does not fit with my practice preferences 1 2 3 4 5 6 7 6 Using IT/computer base system fits with my service needs 1 2 3 4 5 6 7 1 I feel apprehensive about using the IT / computer base system. 1 2 3 4 5 6 7 2 It scares me to think that I could lose a lot of information using the IT / computer base system by hitting the wrong key. 1 2 3 4 5 6 7 3 I hesitate to use the IT / computer base system for fear of making mistakes I cannot correct. 1 2 3 4 5 6 7 4 The IT / computer base system is somewhat intimidating to me. 1 2 3 4 5 6 7 4.6.5 Technological Factors Technological factors measures the focus on a particular system ( Davis, 1989; Davis et al., 1989), to be instrumental ( Davis et al. 1992), capabilities of a system ( Thompson, et al, 1991) and using an innovation (Moore and Benbasat 1991) would improve or enhance the end user job performance. This mean that technological factors will be directly involved with the system or information system or others devices related with information technology. Performance expectancy and effort expectancy was selected in this study due most accepted by previous studies. A seven-point Likert scale was used to measure the responses ranging from 1 = strongly disagree to 7 = strongly agree. Variable Construct Definition Performance Expectancy Perceived Usefulness (Davis,1989; Davis et al. 1989) The degree to which that using a particular system would enhance his or her job performance. Extrinsic Motivation (Davis et al. 1992) The perception that users will want to perform an activity because it is perceived to be instrumental in achieving valued outcomes that are distinct from the activity itself, such as improved job performance, pay, or promotions Job-fit (Thompson et al. 1991) How the capabilities of a system enhance an individual’s job performance. Relative Advantage (Moore and Benbasat 1991) The degree to which using an innovation is perceived as being better than using its precursor. Outcome Expectations (Compeau and Higgins 1995b; Compeau et al. 1999) Outcome expectations relate to the consequences of the behavior. Based on empirical evidence, they were separated into performance expectations (job-related) and personal expectations (individual goals). For pragmatic reasons, four of the highest loading items from the performance expectations and three of the highest loading items from the personal expectations were chosen from Compeau and Higgins (1995b) and Compeau et al. (1999) for inclusion in the current research. However, our factor analysis showed the two dimensions to load on a single factor. Effort Expectancy Perceived Ease of Use (Davis 1989; Davis et al. 1989) The degree to which a person believes that using a system would be free of effort. Complexity (Thompson et al. 1991) The degree to which a system is perceived as relatively difficult to understand and use. Ease of Use (Moore and Benbasat 1991) The degree to which using an innovation is perceived as being difficult to use. 4.6.6 Measurement of Technological Factors using Likert-scales Items Scale Strongly Disagree Strongly Agree I Performance Expectancy 1 I would find the IT / computer base system useful in my job. 1 2 3 4 5 6 7 2 Using the IT / computer base system enables me to accomplish tasks more quickly 1 2 3 4 5 6 7 3 Using the IT / computer base system increases my productivity. 1 2 3 4 5 6 7 4 If I use the IT / computer base system, I will increase my chances of getting a raise. 1 2 3 4 5 6 7 II Effort Expectancy 1 My interaction with the IT / computer base system would be clear and understandable. 1 2 3 4 5 6 7 2 It would be easy for me to become skillful at using the IT / computer base system. 1 2 3 4 5 6 7 3 I would find the IT / computer base system easy to use. 1 2 3 4 5 6 7 4 Learning to operate the IT / computer base system is easy for me 1 2 3 4 5 6 7 4.6.1 Individual Factors Individual factors measure the characteristics of the end user behaviour and attitude. These including an individual apprehension, or even fear, belief that one has the capability, accepted or rejected in using computer or information technology. Variable Construct Definition Computer anxiety Simonson et al. [1987] An individual’s apprehension, or even fear, when she/he is faced with the possibility of using computers Computer self-efficacy Bandura[1977] The belief that one has the capability to perform a particular behavior Computer attitude Ajzen and Fishbein[1980] The degree to which a person likes or dislikes the object Personal Innovativeness Agarwal and Prasad [1998]; Agarwal and Karahanna [2000] An individual trait reflecting a willingness to try out any new technology Perceived Technology Control Ajzen and Fishbein[1988] Perceived behavioral control (PBC) is the perceived ease or difficulty of performing a behavior and a personal sense of control over performing it Voluntariness Moore and Benbasat [1991] The degree to which use of the innovation is perceived as being voluntary, or of free will Age Venkatesh et al., 2003 Physiological phenomena Gender Venkatesh et al., 2003 Physiological phenomena Experience Venkatesh et al., 2003 Experience gained 4.6.7 Measurement of Individual Factors using Likert-scales D Items Scale Strongly Disagree Strongly Agree I Anxiety 1 I feel apprehensive about using the IT / computer base system. 1 2 3 4 5 6 7 2 It scares me to think that I could lose a lot of information using the IT / computer base system by hitting the wrong key. 1 2 3 4 5 6 7 3 I hesitate to use the IT / computer base system for fear of making mistakes I cannot correct. 1 2 3 4 5 6 7 4 The IT / computer base system is somewhat intimidating to me. 1 2 3 4 5 6 7 II Attitude toward using technology 1 2 3 4 5 6 7 1 Using the IT / computer base system is a bad/good idea 1 2 3 4 5 6 7 2 The IT / computer base system makes work more instating 1 2 3 4 5 6 7 3 Working with the IT / computer base system is fun 1 2 3 4 5 6 7 4 I like working with the IT / computer base system 1 2 3 4 5 6 7 III Computer Affect 1 I like working with computers 1 2 3 4 5 6 7 2 I look forward to those aspects of my job that require me to use a computer 1 2 3 4 5 6 7 3 Once I start working on the computer , I find it hard to stop 1 2 3 4 5 6 7 4 Using a computer is frustrating for me. 1 2 3 4 5 6 7 5 I get bored quickly when working on a computer. 1 2 3 4 5 6 7 IV Computer Self-Efficacy I COULD COMPLETE THE JOB USING THE SOFTWARE......... 1 if there was no one around to tell me what to do as I go 1 2 3 4 5 6 7 2 if I had never used a package like it before 1 2 3 4 5 6 7 3 if I had only the software manuals for reference 1 2 3 4 5 6 7 4 if I had seen someone else using it before trying it myself 1 2 3 4 5 6 7 5 if I could call someone for help if I got stuck 1 2 3 4 5 6 7 6 if someone else had help me to get 1 2 3 4 5 6 7 7 if I had a lot of time to complete the job for which the software was provided 1 2 3 4 5 6 7 8 if I had just the built-in help (manual) facility for assistance 1 2 3 4 5 6 7 9 if someone showed me how to do it first 1 2 3 4 5 6 7 10 if I had used similar package before this one to do the same job 1 2 3 4 5 6 7 V Perceived technology control (PTC) 6 7 1 I would have the ability to use computer base system in my patient care and management 1 2 3 4 5 6 7 2 Using computer base system would be entirely within my control. 1 2 3 4 5 6 7 3 I would not have the knowledge to make use of computer base system in my patient care and management. 1 2 3 4 5 6 7 4 I would have the resources (including training) to make use of computer base system in my patient care and management. 1 2 3 4 5 6 7 VI Voluntariness 1 My use of computers is voluntary (as opposed to being required by my superiors or job description). 1 2 3 4 5 6 7 2 My boss does NOT require me to use computers. 1 2 3 4 5 6 7 3 Using computers or other alternatives is completely up to me 1 2 3 4 5 6 7 VII Personal Innovativeness 1 If I heard abut a new information technology, I would look for ways to experiment with it. 1 2 3 4 5 6 7 2 Among my peers, I am usually the first to try out new information technologies. 1 2 3 4 5 6 7 3 In general, I am hesitant to try out new information technologies. 1 2 3 4 5 6 7 4 I like to experiment with new information technologies 1 2 3 4 5 6 7 4.6.8 Behavior Intention Behavior intention was proposed by Fishbien and Ajzen in 1980. Behavior intention was firstly beliefs are product of attitude and subjective norm in their early model. This factor was being tested and retested almost two decades. Form the previous studies, show that attitude (Taylor and Todd, 1995a and 1995b; Karahanna et al., 1991; Kolelofski & Heminger, 2003; Mathison, 1991; Harrison et. al., 1997; Hu & Chau, 1999; Limayem et al., Riemenscheider et al.,2002) will be the main cause of user behaviour intention to performance an action. A seven-point Likert scale was used to measure the responses ranging from 1 = strongly disagree to 7 = strongly agree. Variable Construct Definition Attitude Toward Using Technology (Behavior Intention) Attitude Toward Behavior (Davis et al. 1989; Fishbein and Ajzen 1975; Taylor and Todd 1995a, 1995b) An individual’s positive or negative feelings about performing the target behavior. Intrinsic Motivation (Davis et al. 1992) The perception that users will want to perform an activity for no apparent reinforcement other than the process of performing the activity per se. Affect Toward Use (Thompson et al. 1991) Feelings of joy, elation, or pleasure; or depression, disgust, displeasure, or hate associated by an individual with a particular act. Affect (Compeau and Higgins ,1995b; Compeau et al. (1999) An individual’s liking of the behavior. 4.6.9 Measurement of Behaviour Intention Factors using Likert-scales Item Scale Strongly Disagree Strongly Agree 1 I intend to use the IT / computer base system (information technology) daily in my work 1 2 3 4 5 6 7 2 I predict I would use the IT / computer base system (information technology) daily in my work 1 2 3 4 5 6 7 3 I plan to use the IT / computer base system (information technology) daily in my work 1 2 3 4 5 6 7 Use behaviour The link between intention to use a technology and actual usage is well-established (Ajzen 1991; Mathieson 1991; Sheppard, Harwick & Warshaw 1988; Taylor & Todd 1995; Venkatesh & Morris 2000) and both variables may be used to measure technology acceptance. Davis et al., (1989) and Davis, (1989) also found that the intention is related to behaviour or use behaviour or actual use. As we knew, TAM and TPB was based on TRA and found that the same intention-behavior link strong relationship. For the finding it’s strongly proposed that use behaviour become the predict result of behaviour intention. Pre-testing Instrument Variable Factors Major Minor Independents Implementation Technological Individual Organizational Yes Yes Yes No Dependents Behavioral Intention Use Behavior Yes Yes Demographic Age Gender, Experience Voluntaries of Use, Yes Yes Yes Yes 4.6.6 Pre-testing Survey Instrument “An empirical study of physician’s behavior intention towards the acceptance and usage of Information Technology / Computer Base System in Malaysian Government Hospital” Dear Doctor / Physician This survey is being sent to you as part of my thesis on the use and acceptance of information technology by doctor / physician. The purpose of this study is to identify factors that influencing physician’s in explaining behavior intention towards the acceptance and usage of Information Technology / Computer Base System and how well prepared they are to adapt to the imminent changes in Malaysia’s health sector brought about by information technologies. By returning this survey you will providing valuable information which will be used to describe the experiences and uses of IT by doctor / physican and to develop an action plan to extend and enhance the capacity if doctors / physician to utilize the potential exiting and developing technologies. Your responses are very important in helping us understand physician’s in acceptance of information technology in Malaysia health context. Please indicate yours responses about your acceptance and usage toward the use of Information Technology / Computer Base System in your department/section. Your participation in this study is completely voluntary. However, your input will be a great deal of help to enhance user acceptance model. Information Technology / Computer Base System/System applications may cover: “Electronic Claims, Online Eligibility and Authorizations, Online or Internet Based scheduling, Online Results Reporting, Online Access to clinical Information’s, Automated Clinical Information’s, Telemedicine, Automated Clinical Decision Support, Access to Patient Satisfaction Data, E-mail, Voice Recognition, Automated Dictation, Disease Management, Electronic Medical Record, Wireless and hand Held Devices, Common Practice Management system and others”. “All responses regarding this questionnaire are confidential” (Please feel free to response to the entire question, page 2 to 6) For any inquiries regarding this questionnaire, please contact: Mohd Daud bin Rajab Phone : 017 - 8781700 Email : md.daud.rajab@time.net.my Kulliyyah Information Communication and Technology International Islamic University Malaysia A. Demographic Variables 1. Age (Please fill in the blank) …………… years 2. Gender : i. Male □ ii. Female □ 3. What is your racial identity? A. Malay □ B. Chinese □ C. Indian □ D. Others □ 4. Your department/section (Please specify ) …………………../……………………….. 5. Please indicate your location / hospital ? ………………………………/…………………………… 6. How long have you being working as a physician? ……………….. 7. Your job level in your department (Please tick ONLY ONE) i. HO □ ii. MO □ iii. Specialist □ iv. Consultant □ 8. Education level i. Bachelor □ ii. Master □ iii. Doctorate □ iv. Others: ………………….. 9. Nationality Malaysian □ ii. Non- Malaysian □ 10. For how many years have you been using information technology/computers related to your patient data and information? ……………. years B. IT / computer base system Usage Daily use: How much time do you spend with the IT / computer base system during an ordinary day when you use computers? Scarcely at all 1 Less than 1/2 hours 2 1/2- 1 hours 3 1-2 hours 4 2-3 hours 5 More than 3 hours 6 Frequency of use: How often on average do you use the IT / computer base system? Less than once a month 1 Once a month 2 A few times a month 3 A few times a week 4 Once a day 5 Several times a day 6 11. How many packaged application software (word processing, spreadsheets, databases, graphics, CAD/CAE …etc.) you have used? One … Two … 3 – 5 … 6 - 10 … More than 10 … 12. Do you use a computer at home? ( ) Yes ( ) No 13. How would you rate your knowledge about computer? Novice Expert 1 2 3 4 5 6 7 Please indicate if you agree or disagree with the following statements. Please circle the number that best fits your response. Strongly Disagree Agree Strongly Agree Measurement A Organizational Context a Management Support 1 2 3 4 5 6 7 1 Management is aware of the benefits that can be achieved with the use of computers. 1 2 3 4 5 6 7 2 Management always supports and encourages the use o f computer for job-related work. 1 2 3 4 5 6 7 3 Management provides most of the necessary help and resources to enable people to use computers 1 2 3 4 5 6 7 4 Management is really keen to see that people are happy with using computers 1 2 3 4 5 6 7 5 Management provides good access to hardware resources when people need them. 1 2 3 4 5 6 7 6 Management provides good access to various types of software when people need them. 1 2 3 4 5 6 7 b Accessibility (please indicate the degree) 1 2 3 4 5 6 7 1 Computer base system in my office is physically accessible to me. 1 2 3 4 5 6 7 2 It is easy to me to access the information of my computer system. 1 2 3 4 5 6 7 3 It is easy to me to access the information in my organization/department (locally) when I need it. 1 2 3 4 5 6 7 4 It is easy to access the information in my organization/department (remotely) when I need it. 4 If I use the IT / computer base system, I will increase my chances of getting a raise. 1 2 3 4 5 6 7 c Perceived Technical Competence 1 2 3 4 5 6 7 1 I believe the performance providing IT support by my hospital / organization is good. 1 2 3 4 5 6 7 2 In my experience the supporting IT/Computer base system on software application by my hospital / organization is good 1 2 3 4 5 6 7 3 The expertise in supporting IT / Computer base system by my hospital / organization is good 1 2 3 4 5 6 7 3 The senior management of the hospital has been helpful in the use of the IT / computer base system. 4 In general, the hospital/organization has supported the use of the system. 1 2 3 4 5 6 7 d Perceived Financial Cost 1 2 3 4 5 6 7 1 High set-up cost ( The computer base system have very high set-up cost) 1 2 3 4 5 6 7 2 High running cost ( The computer base system have very high operation cost ) 1 2 3 4 5 6 7 3 High training cost ( The computer system have very high training cost 1 2 3 4 5 6 7 e Task Fit 1 2 3 4 5 6 7 1 Sufficiently detailed application information about the IT / computer base systems is maintained 1 2 3 4 5 6 7 2 On the IT / computer base system I use, the application information is either obvious or easy to find out 1 2 3 4 5 6 7 3 I can get the application information quickly and easily from a website when I need it 4 The application information that I use or would like to use is accurate enough for my purposes. 5 The application information is up to date enough for my purposes. 1 2 3 4 5 6 7 6 The application information that I need is displayed in a readable and understandable form. 1 2 3 4 5 6 7 7 The application information maintained at websites is pretty much what I need to carry out my tasks. 1 2 3 4 5 6 7 8 The application information is stored in so many forms it is hard to know how to use it effectively. 1 2 3 4 5 6 7 B Implementation Context a Facilitating Conditions 1 I have the resources necessary to use the IT / computer base system. 1 2 3 4 5 6 7 2 I have the knowledge necessary to use the IT / computer base system. 1 2 3 4 5 6 7 3 The IT / computer base system is not compatible with other IT / computer base systems I use. 1 2 3 4 5 6 7 4 A specific person (or group) is available for assistance with IT / computer base system difficulties. 1 2 3 4 5 6 7 b Compatibility 1 2 3 4 5 6 7 1 Using computers is compatible with aspects of tasks of my job. 1 2 3 4 5 6 7 2 I think that using computers fits well with the way I like to work. 1 2 3 4 5 6 7 3 Using computers fits into my work style. 1 2 3 4 5 6 7 4 Using IT/computer base system fits with the way I work 1 2 3 4 5 6 7 5 Using IT/computer base system does not fit with my practice preferences 1 2 3 4 5 6 7 6 Using IT/computer base system fits with my service needs 1 2 3 4 5 6 7 c Social Influence 1 People who influence my behavior think that I should use the IT / computer base system. 1 2 3 4 5 6 7 2 People who are important to me think that I should use the IT / computer base system. 1 2 3 4 5 6 7 3 The senior management of the hospital has been helpful in the use of the IT / computer base system. 1 2 3 4 5 6 7 4 In general, the hospital/organization has supported the use of the IT / computer base system. 1 2 3 4 5 6 7 C Technology Context a Performance Expectancy 1 2 3 4 5 6 7 1 I would find the IT / computer base system useful in my job. 1 2 3 4 5 6 7 2 Using the IT / computer base system enables me to accomplish tasks more quickly 1 2 3 4 5 6 7 3 Using the IT / computer base system increases my productivity. 1 2 3 4 5 6 7 4 If I use the IT / computer base system, I will increase my chances of getting a raise. 1 2 3 4 5 6 7 b Effort Expectancy 1 My interaction with the IT / computer base system would be clear and understandable. 1 2 3 4 5 6 7 2 It would be easy for me to become skillful at using the IT / computer base system. 1 2 3 4 5 6 7 3 I would find the IT / computer base system easy to use. 1 2 3 4 5 6 7 4 Learning to operate the IT / computer base system is easy for me 1 2 3 4 5 6 7 D Individual Context a Anxiety 1 2 3 4 5 6 7 1 I feel apprehensive about using the IT / computer base system. 1 2 3 4 5 6 7 2 It scares me to think that I could lose a lot of information using the IT / computer base system by hitting the wrong key. 1 2 3 4 5 6 7 3 I hesitate to use the IT / computer base system for fear of making mistakes I cannot correct. 1 2 3 4 5 6 7 4 The IT / computer base system is somewhat intimidating to me. 1 2 3 4 5 6 7 1 2 3 4 5 6 7

b Attitude toward using technology 1 2 3 4 5 6 7 
1 Using the IT / computer base system is a bad/good idea 1 2 3 4 5 6 7
 2 The IT / computer base system makes work more instating 1 2 3 4 5 6 7 
3 Working with the IT / computer base system is fun 1 2 3 4 5 6 7
 4 I like working with the IT / computer base system 1 2 3 4 5 6 7 

c Computer Affect 
1 I like working with computers 1 2 3 4 5 6 7
 2 I look forward to those aspects of my job that require me to use a computer 1 2 3 4 5 6 7 
3 Once I start working on the computer , I find it hard to stop 1 2 3 4 5 6 7
 4 Using a computer is frustrating for me. 1 2 3 4 5 6 7 
5 I get bored quickly when working on a computer. 1 2 3 4 5 6 7


 d Computer Self-Efficacy 1 2 3 4 5 6 7 I COULD COMPLETE THE JOB USING THE SOFTWARE.........
1 if there was no one around to tell me what to do as I go 1 2 3 4 5 6 7
2 if I had never used a package like it before 1 2 3 4 5 6 7 
3 if I had only the software manuals for reference 1 2 3 4 5 6 7 
4 if I had seen someone else using it before trying it myself 1 2 3 4 5 6 7
5 if I could call someone for help if I got stuck 1 2 3 4 5 6 7
6 if someone else had help me to get 1 2 3 4 5 6 7 
7 if I had a lot of time to complete the job for which the software was provided 1 2 3 4 5 6 7 
8 if I had just the built-in help (manual) facility for assistance 1 2 3 4 5 6 7 
9 if someone showed me how to do it first 1 2 3 4 5 6 7 
10 if I had used similar package before this one to do the same job 1 2 3 4 5 6 7 

e Perceived technology control (PTC) 1 2 3 4 5 6 7 
1 I would have the ability to use computer base IT / computer base system in my patient care and management 1 2 3 4 5 6 7 
2 Using computer base system would be entirely within my control. 1 2 3 4 5 6 7 
3 I would not have the knowledge to make use of computer base system in my patient care and management. 1 2 3 4 5 6 7 
4 I would have the resources (including training) to make use of computer base system in my patient care and management. 1 2 3 4 5 6 7 

f Voluntariness 1 2 3 4 5 6 7 
1. My use of computers is voluntary (as opposed to being required by my superiors or job description). 1 2 3 4 5 6 7
 2. My boss does NOT require me to use computers. 1 2 3 4 5 6 7 
3 Using computers or other alternatives is completely up to me 1 2 3 4 5 6 7 

h. Personal Innovativeness

 If I heard abut a new information technology, I would look for ways to experiment with it. 1 2 3 4 5 6 7
 2. Among my peers, I am usually the first to try out new information technologies. 1 2 3 4 5 6 7 3. In general, I am hesitant to try out new information technologies. 1 2 3 4 5 6 7 4 
I like to experiment with new information technologies 1 2 3 4 5 6 7 






Thanks for your great help.
 Please return the questionnaire at the main entrance. For any inquiries regarding this questionnaire, please contact: Mohd Daud bin Rajab Phone : 017 - 8781700 Email : md.daud.rajab@time.net.my

 Refferences: 

 Ajzen, I. 1991, 'The theory of planned behavior', Organizational Behavior and Human Decision Processes, vol. 50, no. 2, pp. 179-211. 
Al-Gahtani, S. S. & King, M. 1999, 'Attitudes, satisfaction and usage: factors contributing to each in the acceptance of information technology', Behaviour and Information Technology, vol. 18, no. 4, pp. 277-297. Anderson, J. G. 1997, 'Clearing the way for physicians' use of clinical information systems', Association for Computing Machinery. Communications of the ACM, vol. 40, no. 8, pp. 83-90. Bergeron, F., Rivard, S. & DeSerre, L. 1990, 'Investigating the support role of the information center', MIS Quarterly, vol. 14, no. 3, pp. 247-260. 
Chau, P. Y. K. & Hu, P. J. 2001, 'Information technology acceptance by individual professionals: a model comparison approach', Decision Sciences, vol. 32, no. 4, pp. 699-719. 
Chau, P. Y. K. & Hu, P. J. 2002a, 'Examining a model of information technology acceptance by individual professionals: an exploratory study', Journal of Management Information Systems, vol. 18, no. 4, pp. 191- 229. Chau, P. Y. K. & Hu, P. J.-H. 2002b, 'Investigating healthcare professionals' decisions to accept telemedicine technology: an empirical test of competing theories', Information and Management, vol. 39, pp. 297-311. 
Chismar, W. G. & Wiley-Patton, S. 2003, 'Does the extended technology acceptance model apply to physicians', in 36th Hawaii International Congress on System Sciences (HICSS'03), IEEE Computer Society, Big Island, Hawaii. Compeau, D. R. & Higgins, C. A. 1995a, 'Application of social cognitive theory to training for computer skills', Information Systems Research, vol. 6, no. 2, pp. 118-143. 
Compeau, D. R. & Higgins, C. A. 1995b, 'Computer self-efficacy: development of a measure and initial test', MIS Quarterly, vol. 19, no. 2, pp. 189-211. 
Compeau, D. R., Higgins, C. A. & Huff, S. 1999, 'Social cognitive theory and individual reactions to computing technology: a longitudinal study', MIS Quarterly, vol. 23, no. 2, pp. 145-158. 
Davis, F. D. 1989, 'Perceived usefulness, perceived ease of use, and user acceptance of information technology', MIS Quarterly, vol. September, pp. 319-340. 
Davis, F. D., Bagozzi, R. P. & Warshaw, P. R. 1989, 'User acceptance of computer technology: a comparison of two theoretical models', Management Science, vol. 35, no. 8, pp. 982-1003. 
Davis, F. D., Bagozzi, R. P. & Warshaw, P. R. 1992, 'Extrinsic and intrinsic motivation to use computers in the workplace', Journal of Applied Social Psychology, vol. 22, no. 14, pp. 1111-1132. 
Dixon, D. R. & Stewart, M. 2000, 'Exploring information technology adoption by family physicians: survey instrument validation', in AMIA 2000 Annual Symposium, Session S69 - Current issues in medical informatics edn, ed. American Medical Informatics Association, Online, Los Angeles, CA. 
Fishbein, M. & Ajzen, I. 1975, Belief, attitude, intention and behavior: an introudction to theory and research, Addison-Wesley, Reading, MA. Hebert, M. 1994, 'Adopting information technology in hospitals: the relationship between attitudes/expectations and behavior', Hospital & Health Services Administration, vol. 39, no. 3, pp. 369-383. 
Hu, P. J., Chau, P. Y. K., Liu Sheng, O. R. & Tam, K. Y. 1999, 'Examining the technology acceptance model using physician acceptance of telemedicine technology', Journal of Management Information Systems, vol. 16, no. 2, pp. 91-112. 
Igbaria, M., Zinatelli, N., Cragg, P. & Cavaye, A. 1997, 'Personal computing acceptance factors in small firms: a structural equation model', MIS Quarterly, vol. 21, no. 3, pp. 279-302.
 Jayasuriya, R. 1998, 'Determinants of microcomputer technology use: implications for education and training of health staff', International Journal of Medical Informatics, vol. 50, pp. 187-194. 
Kaplan, B. 1997, 'Addressing organizational issues into the evaluation of medical systems', Journal of the American Medical Informatics Association, vol. 4, no. 2, pp. 94-101. 
Kaplan, B. 2001, 'Evaluating informatics applications - some alternative approaches: theory, social interactionism, and call for methodological pluralism', International Journal of Medical Informatics, vol. 64, pp. 39-56.
 Kaplan, B. & Duchon, D. 1988, 'Combining qualitative and quantitative methods in information systems research: a case study', MIS Quarterly, vol. 12, no. 4, pp. 570-586. 
Karahanna, E., Straub, D. & Chervany, N. L. 1999, 'Information technology adoption across time: a cross sectional comparison of pre-adoption and post-adoption beliefs', MIS Quarterly, vol. 23, no. 2, pp. 183-204.
 Mathieson, K. 1991, 'Predicting user intention: comparing the technology acceptance model with theory of planned behavior', Information Systems Research, vol. 2, no. 3, pp. 179-191.
 May, C., Gask, L., Atkinson, T., Ellis, N., Mair, F. & Esmail, A. 2001, 'Resisting and promoting new technologies in clinical practice: the case of telepsychiatry', Social Science and Medicine, vol. 52, no. 12, pp. 1889-1901. 
Moore, G. C. & Benbasat, I. 1991, 'Development of an instrument to measure the perception of adopting an information technology innovation', Information Systems Research, vol. 2, no. 3, pp. 192-223.
 Sheppard, B. H., Harwick, J. & Warshaw, P. R. 1988, 'The theory of reasoned action: a meta-analysis of past research with recommendation for modifications and future research', Journal of Consumer Research, vol. 15, no. 3, pp. 325-343. 
Taylor, S. & Todd, P. A. 1995, 'Understanding information technology usage: a test of competing models', Information Systems Research, vol. 6, no. 4, pp. 144-176. 
Thompson, R. L., Higgins, C. A. & Howell, J. M. 1991, 'Personal computing: toward a conceptual model of utilization', MIS Quarterly, vol. 15, no. 1, pp. 124-143. 
Venkatesh, V. 2000, 'Determinants of perceived ease of use: integrating control, intrinsic motivation, and emotion into the technology acceptance model', Information Systems Research, vol. 11, no. 4, pp. 342-365. 
Venkatesh, V. & Davis, F. D. 2000, 'A theoretical extension of the Technology Acceptance Model: four longitudinal field studies', Management Science, vol. 46, no. 2, pp. 186-204. 
Venkatesh, V. & Morris, M. G. 2000, 'Why don't men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior', MIS Quarterly, vol. 24, no. 1, p. 115. 
Venkatesh, V., Morris, M. G. & Ackerman, P. L. 2000, 'A longitudinal field investigation of gender differences in individual technology adoption decision-making processes', Organizational Behavior and Human Decision Processes, vol. 83, no. 1, pp. 33-60. 
Venkatesh, V., Morris, M. G., Davis, G. B. & Davis, F. D. 2003, 'User acceptance of information technology: toward a unified view', MIS Quarterly, vol. 27, no. 3, pp. 425-478.