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Technological change and impact on employee behavior

Dissertation
Author: Chi Leung Lai
Abstract:
Technological changes in organizations are challenging. While there are success stories, the failure rate is alarmingly high. This thesis presents the development and testing of three models on the impact of technological change on employees' behavior. The first model examines the current understanding of technology acceptance, as well as the notion of mandated use. An integrated model is proposed. The results indicate that there are differences in the underlying relationships of the technology acceptance process when use is mandated. The second study, as an extension of study one, looks at the earlier deep usage effect on employees' job outcome changes in an 18 months period. The mediating effect of job autonomy on long-term job outcomes is evidenced. By applying the job demand-control model, study three examines the job demand increase effect in job performance changes in the transformation process. Latent growth modeling was used. These three studies are validated by a longitudinal field study conducted in the Hong Kong Police Department. This research project makes important contributions by deepening our understanding of the employee behavioral changes instigated by technological change. [PUBLICATION ABSTRACT]

Table of Contents

Title Page i

Authorization Page ii

Signature Page iii

Acknowledgements iv

Abstract xi

Chapter 1 Introduction 1

1.1 Motivation for this Research Project 1

1.2 Study One: Understanding Employees’ Attitude Change toward Information Technology Mandated Use: A Theoretical Model and Longitudinal Test 2

1.3 Study Two: Explaining Employees’ Job Outcomes Following Organizational Technological Change. 3

1.4 Study Three: Changes in Job Performance: The Norm or the Exception in the Technological Change? A Latent Growth Modeling Approach

4

Chapter 2 Understanding Employees’ Attitude Change toward Information Technology Mandated Use: A Theoretical Model and Longitudinal Test 5

2.1 Introduction 5

2.2 Literature Review 6

2.3 The Research Model 10

2.4 Model Development and Hypotheses 12

2.4.1

Technology Perceptions in Pre-use-stage 12

2.4.2

Effect of Perceived Usefulness and Perceived Ease of Use on Pre-use-Stage Attitude 13

2.4.3

Diminishing Role of Behavioral Intention in Mandated Use 14

2.4.4

Relationship between Pre-Use-Stage Attitude and Use-Stage Attitude 15

2.4.5 The Disconfirmation Experience 16

vi

2.4.6 Feedback 17

2.4.7 Effect of Use-stage Attitude on Usage 19

2.5 The Study 20

2.5.1 Contextual Consideration 20

2.5.2 Use of Information Technology in the HKP 20

2.5.3

Maintenance Problems and Operational Deficiencies 21

2.5.4 The Review and Expectations 22

2.5.5

3rd Generation Command and Control System (CC III) 23

2.5.6 Project Communication & Training 24

2.5.7 The Sample 26

2.6 Measures Development 27

2.6.1 Perceived Usefulness and Ease of Use 28

2.6.2 Attitude 28

2.6.3 The Disconfirmation Experience 29

2.6.4 Feedback 30

2.6.5 Deep Usage 30

2.7. Results 32

2.7.1 Internal Reliability Test 32

2.7.2 Scale Validation 32

2.7.3 Empirical Results 34

2.7.4 Hypotheses Testing 34

2.8 Discussion of Results 37

2.9 Limitations and Future Studies 38

Chapter 3 Explaining Employees’ Job Outcomes Following Organizational Technological Change. 40

3.1 Introduction 40

3.2 Theoretical Background and Model Development 44

3.2.1 Effect of Deep Usage on Job Outcome 44

3.2.2 Capability to Increase Job Autonomy in the Long Run 46

3.2.3 Effect of Job Autonomy on Job Outcomes 48

3.3 The Study 50

vii

3.3.1 The Sample 50

3.4 Measures Development 51

3.4.1 Deep Usage 51

3.4.2 Job Performance 51

3.4.3 Job Satisfaction 52

3.4.4 Job Autonomy 52

3.5 Results 53

3.5.1 Internal Reliability Test 53

3.5.2 Scale Validation 53

3.5.3

Empirical Results 55

3.5.4 Hypotheses Testing Result 56

3.6 Discussion of Results 59

3.7 Limitation and Future Work 60

Chapter 4 Changes in Job Performance: The Norm or the Exception in the Technological Change? A Latent Growth Modeling Approach 62

4.1 Introduction 62

4.2 Literature Review 64

4.3 The Research Model 65

4.4 Model Development and Hypotheses 68

4.4.1

IT Implementation and Job Performance Changes 68

4.4.2

Job Demand Increase and Changes in Job Performance 69

4.4.3 Feedback 71

4.4.4 System Control Improvement and Changes in Job Performance 72

4.4.5

The Effect of Feedback on System Control Improvement 73

4.4.6

Job Satisfaction and Job Performance before IT Implementation 74

4.5 The Study 75

4.5.1 Data Collection 75

4.6 Measures Development 76

4.6.1 Job Performance 76

4.6.2 Job Satisfaction 78

4.6.3 Job Demand Increase 79

viii 4.6.4 Feedback 79

4.6.5

System Control Improvement 80

4.7 Data Analysis Approach 81

4.7.1

Analysis of Job Performance Change – Modeling Growth Trajectories Change 81

4.7.2 Predictors on Job Performances 84

4.7.3 Empirical Results 84

4.7.4 Hypotheses Testing Results 88

4.8 Theoretical and Managerial Contributions 88

4.9 Limitation and Future Research 90

Chapter 5 Conclusion 92

ix

List of Figures Figure 2.1

The Research Model of Study One 11

Figure 2.2

The Research Model Result of Study One 36

Figure 3.1

The Research Model of Study Two 43

Figure 3.2

The Research Model Result of Study Two 58

Figure 4.1

The Research Model of Study Three 67

Figure 4.2

The Research Model Result of Study Three 87

List of Tables Table 2.1

Fit Indices for the Measurement Model of Study One 33

Table 2.2

Fit Indices for the Structural Model of Study One 34

Table 2.3

Hypotheses Testing Result of Study One 35

Table 3.1

Fit Indices for the Measurement Model of Study Two 54

Table 3.2

Fit Indices for the Structural Model of Study Two 55

Table 3.3

Hypotheses Testing Results of Study Two 57

Table 4.1

Tests of Univariate LGM Analysis of Study Three 83

Table 4.2

Growth Parameter Estimates of Study Three

83

Table 4.3

Fit Indices for the Full LGM Model of Study Three 85

Table 4.4

Hypotheses Testing Results of Study Three 86

Bibliography and References 95

Appendix A Item Means, Standard Deviation & Internal Reliability of Study One 117

Appendix B Standardized Item Loading, Measurement Error, t-value of Study One 118

Appendix C Factor Scores of Scale Items of Study One 119

Appendix D Correlation Matrix of Measurement Constructs with AVE and ICR of Study One 120

Appendix E Covariance Matrix for All Constructs of Study One 121

Appendix F Survey Items of Study One (English) 122

x

Survey Items of Study One (Chinese Translation) 125

Appendix G Item Means, Standard Deviation & Internal Reliability of Study Two 127

Appendix H Standardized Item Loading, Measurement Error, t-value of Study Two 128

Appendix I Factor Scores of Scale Items of Study Two 129

Appendix J Correlation Matrix of Measurement Constructs with AVE and ICR of Study Two

130

Appendix K Survey Items of Study Two (English) 131

Survey Items of Study Two (Chinese Translation) 133

Appendix L Representation of a three-factor polynomial LGM for Impact of Technological Change on Job Performance over time 135

Appendix M Item Means, Standard Deviation & Internal Reliability of Study Three 136

Appendix N Standardized Item Loading, t-value of Study Three 137

Appendix O Factor Scores of Scale Items of Study Three

138

Appendix P Correlation Matrix of Measurement Constructs with AVE and ICR of Study Three

139

Appendix Q Covariance Matrix for all Constructs of Study Three 140

Appendix R Survey Items for Study Three 141

Survey Items for Study Three (Chinese Translation) 142

xi

Technological Change and Impact on Employee Behavior

by

LAI, Chi Leung

Department of Information Systems, Business Statistics and Operations Management, School of Business and Management Hong Kong University of Science and Technology

Abstract

Technological changes in organizations are challenging. While there are success stories, the failure rate is alarmingly high. This thesis presents the development and testing of three models on the impact of technological change on employees’ behavior. The first model examines the current understanding of technology acceptance, as well as the notion of mandated use. An integrated model is proposed. The results indicate that there are differences in the underlying relationships of the technology acceptance process when use is mandated. The second study, as an extension of study one, looks at the earlier deep usage effect on employees’ job outcome changes in an 18 months period. The mediating effect of job autonomy on long-term job outcomes is evidenced. By applying the job demand-control model, study three examines the job demand increase effect in job performance changes in the transformation process. Latent growth modeling was used. These three studies are validated by a longitudinal field study conducted in the Hong Kong Police Department. This research project makes important contributions by deepening our understanding of the employee behavioral changes instigated by technological change.

CHAPTER ONE Introduction 1.1 Motivation for this Research Project Organizations have undergone a revolution in the adoption and application of complex information technology. In the hope of extracting the greatest value from innovations, organizations have adjusted their management structures, work processes, dyads relationships and culture (Orlikowski 2000). Yet, swift technology enhancement unintentionally reduces the presumed lifespan of many IT systems. Organizations build and rebuild their existing IT systems in response to needs and market changes. The results of these initiatives are often rather disappointing. Half of these technological change projects experience failure (Adam and O’Doherty 2003). The difficulties associated with achieving the intended benefits of IS are still a crucial issue facing organizational management (Kwon and Zmud 1987; Lucas et al. 2007). Thus, this research project is developed with the aim of deepening our understanding of this critical transformation issue.

2 1.2 Study One: Understanding Employees’ Attitude Change toward Information Technology Mandated Use: A Theoretical Model and Longitudinal Test Because of the research design limitations, many prior IT implementation studies did not elaborate on the actual behavior beyond simple continuance intention. The voluntary setting of IS used in these studies also did not provide an opportunity to understand the institutional effects on IT acceptance in an organizational context (Legris et al. 2003). When technology use is mandated, as it is in many organizations, it is expected that the underlying relationships of traditional technology acceptance models will be different. The motivation of study one is to integrate the Technology Acceptance Model and Expectation Confirmation Theory into a two-stage model to address this knowledge gap. This study empirically validates the causative drivers and emergent mechanisms steering employees’ attitude change and its impact on use-stage behavior. The results show that there are dissimilarities in the underlying relationships of technology acceptance models in this compulsory use circumstances. The study concludes that use-stage attitude is a key determinant for IT acceptance in a mandate context (Brown et al. 2002; Fazio and Zanna 1981; Eagly and Chaiken 1993).

3 1.3 Study Two: Explaining Employees’ Job Outcomes Following Organizational Technological Change Other than directly influencing job performance, IT has the power to change the nature of employees’ working conditions including workload, working environment, and interpersonal relationships and, in the process, have a considerable impact on employees’ job satisfaction, a salient predictor of work behaviors (e.g. Mumford and Weird 1979; Mumford 1983; George and Jones 1997). The negative change is not negligible. For instance, a dissatisfied employee may stay in the job but with less enthusiasm and lowered job commitment (Ferguson and Cheyne 1995). Despite a great deal of research suggesting the importance of these issues, relatively little is known about the structural relationships between each factor. A model of the relationships was developed with the objective of examining the impact of earlier deep usage on job performance and job satisfaction; whether deep usage will enhance job autonomy; and whether job autonomy will be positively associated with job performance and job satisfaction. The study concludes with practical insights for IT practitioners.

4 1.4 Study Three: Changes in Job Performance: The Norm or the Exception in the Technological Change? A Latent Growth Modeling Approach In the context of IT implementation, work stress associated with technological change is perceptible. Far from having a calming effect on overworked employees, change of technology has itself become a source of increasing psychological demand and stress on employees (Karasek 1979; Spector and Jex 1991; Beer and Spector 1990; Bemels and Reshef 1991; Mullarkey et al. 1997). In the organizational behavior literature, the job demands-control (D-C) model is an important tool for predicting job-related stress. The last study employs the D-C model with the objective of examining the impact of job demand increase associated with the technological transformation on employees’ job performance changes. The latent growth modeling approach is adopted to empirically validate the proposed research model. An interesting result emerged from this study, a result that holds clear implications for practising managers and IS scholars.

5 CHAPTER TWO Understanding Employees’ Attitude Change toward Information Technology Mandated Use: A Theoretical Model and Longitudinal Test

2.1 Introduction The world has more technology than ever before with technological changes increasing at an accelerating pace. The amalgamation of data processing, communications and the advances of software allows firms to gain a competitive advantage, improve performance and develop new businesses from various areas. Use of information technology is now shifting from a supportive role to a more strategically oriented role in organizations (Lucas and Turner 1982). The 1980s were marked by major breakthroughs in computing in organizations as organizations had undergone a revolution in the adoption and application of complex information technology. In the hope of extracting the greatest value from innovations, organizations have adjusted their management structures, work processes, dyads relationships and culture (Orlikowski 2000). Nevertheless, swift technology enhancement unintentionally reduces the presumed lifespan of many IT systems. Organizations build and rebuild their existing IT systems in response to needs and market changes. The outcomes of these initiatives are often rather unsatisfactory. Half of these technological change projects experience failure (Adam and O’Doherty 2003). This is consistent

6 with past research, which shows that it is common for complex IT to be successfully implemented but unsuccessfully appropriated. For example, organizational employees often refuse to go along with changes brought about by technology (Kling and Iacono 1989; Joshi 1991; Martinko 1996; Lapointe and Rivard 2005). They might also operate technology in manners that are not expected a priori (Kraut et al. 1989). Given this complexity, organizational technological change is not easy to accomplish (e.g., Robey 1979; Markus 1983; Goodhue and Thompson 1995; Clark 1988; Clemons 1986; Joshi 1990; McLoughlin and Clark 1997). The difficulties associated with achieving the intended benefits of information systems are still a crucial issue facing organizational management (Kwon and Zmud 1987; Lucas et al. 2007). 2.2 Literature Review During the past two decades, the technology acceptance model (TAM) has emerged in the literature for studies of IT utilization behavior (e.g., Davis 1989; Davis et al. 1989; Igbaria et al. 1995; Venkatesh and Davis 2000). The TAM, adapted from the Theory of Reasoned Action to the study of IT usage (Ajzen and Fishbein 1980; Davis 1989), posits that two constructs, perceived usefulness and perceived ease of use, are likely to influence an individual’s decision to use an IS. Usefulness is defined as the degree to which the person believes that using the IS will be of advantage in an organizational context. Ease of use is defined as subjective probability to which the

7 person thinks that using the IS will be free of effort. Ease of use influences usefulness as well as attitude towards system use. Usefulness also influences attitude as well as behavioral intention. The TAM posits that behavioral intention completely mediates actual behavior. Although the TAM is a useful tool in predicting an earlier decision before actual usage, it emphasizes causation that flows in a single direction from beliefs to attitudes to intentions to behavior. First, it might oversimplify the links between attitudes and behaviors (Eagly and Chaiken 1993). Second, when users gain experience with the system, the prior general belief before actual use might be displaced by a more instrumental consideration such as the impact of the innovation on job performance (Szajna 1996; Karahanna et al 1999; Bhattacherjee and Premkumar 2004). Belief and attitude change from pre-use-stage to use-stage are not represented in the model. Another area of concern is in relation to the context of adoption. With few exceptions (e.g., Venkatesh and Davis, 2000), TAM research has been conducted in environments in which adoption was voluntary and focused entirely on volitional choices and behavior (Legris et al. 2003). It is unclear if the same relationships will hold when the adoption is mandatory where many of the behaviors in organizations are not volitional (Brown et al. 2002). A review of the information systems implementation literature revealed several

8 studies in relation to the outcome chain on actual use. For instance, Ginzberg (1981) examined the effect of unrealistic expectations via an empirical study in a US bank. He classified the pre-implementation expectations of system developers as the standard level of expectation and examined the realism of user expectation by measuring deviations from this standard. Ginzberg’s results showed that users who held realistic expectations of a system at the pre-implementation stage had higher levels of satisfaction and were more likely to use the system than users who held unrealistic expectations. A recent study conducted by Bhattacherjee (2001) uses expectation confirmation theory taken from consumer satisfaction literature to articulate user satisfaction and continuance intention of IS use. His model posits that expectation of the IS and confirmation of expectation following actual use will determine user satisfaction. User satisfaction in addition to perceived usefulness belief will influence individuals’ IS continuance decisions. Along the same line, Bhattacherjee and Premkumar (2004) employed cognitive dissonance theory in the social psychology literature to elaborate why users’ beliefs and attitudes change as they gain first-hand experience in IT usage, and expectation confirmation theory to articulate the role of disconfirmation driving this change. These studies explain that the effect of disconfirmation of expectation is an emergent factor that drives system beliefs and attitude change among IT users. Both the TAM and the Expectation Confirmation Model (ECM) were developed in IS research to

9 understand users’ attitude towards, and evaluation of, IT adoption. The motivation of this study is to develop and evaluate an integrated TAM/ECM model. Application of the TAM is used to focus early in the outcome chain on pre-use attitude formation. The ECM on the other hand provides application focus on attitude after actual use and its effect on usage behavior. It is believed that an integration of the two will be useful in understanding how pre-deployment attitude affects use-stage attitude and actual use. Another research focus of this study is on the effect of an emergent management intervention on employees’ attitude changes at the use-stage. While highlighting the management intervention effect, it may be more beneficial for organizations to formulate a more effective strategy to ensure the success of the technological change. The hypothesized model is validated empirically using data from a field survey of a non-profit organization where use of IS are mandatory. The remainder of this study is organized as follows: the second section integrates the TAM with the ECM, followed by model development. The third section describes the research methodology used to empirically test the model. The fourth section describes instrument construction and validation. The fifth section presents the data analysis results. The final section discusses research implications and limitations. 2.3 The Research Model The constructs and hypothesized links in the model are shown in Figure 2.1.

10 The integrated model has seven paths, labeled H1-H7, connecting the TAM model to the ECM model. Deep usage is the dependent construct. As theorized in the TAM, perceived usefulness is influenced by perceived ease of use (Davis et al. 1989). Attitude represents the affect felt by the user towards using the system and is developed from beliefs, which in the case of the TAM are perceived usefulness and ease of use (H2 and H3) (Ajzen and Fishein 1980; Davis 1989). The attitude formed in the pre-use-stage is hypothesized to have a direct positive effect on use-stage attitude (H4). In the IT literature, the ECM posits confirmation of expectations after gaining experience will influence individuals’ cognitive beliefs and affect their continued IT usage decisions (Bhattacherjee 2001; Bhattacherjee and Premkumar 2004). Thus, confirmation of expectation would have a positive effect on use-stage attitude. Feedback, as a major management intervention in use-stage, is hypothesized to have a positive influence on use-stage attitude (H6). Last, a key expectation of the model is that favorable attitudes can be used to predict system use (H7). The use-stage attitude and deep usage link implies that people engage in behaviors for which they have positive beliefs (Fishbein and Ajzen 1975).

11

H1 One Month before Implementation (Pre-use-stage) Perceived Usefulness Disconfirmation

Pre-use-stage Attitude

Use-stage Attitude Deep One Month after Implementation (Use-stage) Perceived Ease of Use Feedback Figure 2.1 H2 H3 H4 H5 H6 H7

12 2.4 Model Development and Hypotheses 2.4.1 Technology Perceptions in Pre-use-stage As organization systems (e.g, ERP) are increasingly complex, individuals find it difficult to anticipate what a new system will look like and how it will impact on their daily activities before hands-on-use. They might only be able to generate an intuitive perception of the future system through early user participation (Wagner and Newell 2007). Research in psychology has suggested that people without direct experience in a given domain base their perceptions on more abstract criteria (Eagly and Chaiken 1993). In an IT usage context, perceived usefulness and perceived ease of use have recurred as highly fundamental beliefs of key acceptance outcomes with considerable support in the literature (e.g., Davis 1989; Venkatesh and Davis 2000; Venkatesh and Morris 2000). Given the recurrence of these beliefs and sound theoretical explanation, this study will focus on usefulness and ease of use as the two primary independent variables as the key determinants of initial attitude formed at pre-use stage. Consistent with the theoretical arguments underlying the TAM, it is anticipated that beliefs about the ease of use will have a direct impact on perceived usefulness (Davis et al. 1989). H1: Perceived ease of use of the new system has a significant influence on beliefs about the usefulness of the new system.

13 2.4.2 Effect of Perceived Usefulness and Perceived Ease of Use on Pre-use-stage Attitude Within the context of implementing an information system, attitudes are influenced by the beliefs and expectations of the employees who must use it. In the TAM, attitude represents the affect felt by the user towards using the system (Davis 1989). It mediates evaluative beliefs (perceived usefulness and perceived ease of use) that the individual may have formed about using the system. It is derived by the strength of the person’s belief that adopting the IT will lead to specific consequences (Davis 1989; Davis et al. 1989; Ajzen and Fishbein 1980). This contention originates from cognitive research in psychology in which attitude is defined as a psychological tendency that is articulated by evaluating a particular entity with some degree of favor or disfavor (Eagly and Chaiken 1993). If this tendency to respond is established, the person is said to be forming an attitude toward the object. In the TAM, there is considerable support for positive relationships between perceived ease of use, perceived usefulness and the pre-use stage attitude in the literature. Based on the discussion, we test the following hypotheses. H2: Perceived usefulness of the new IT system is positively related to the attitude towards using the system at pre-use stage. H3: Perceived ease of use of the new IT system is positively related to the

14 attitude towards using the system at pre-use stage. 2.4.3 Diminishing Role of Behavioral Intention in Mandated Use Adopting the theoretical underpinning from Theory of Reasoned Action, the TAM includes the very important assumption that the behavior is volitional, which is to say voluntary or at the discretion of the user and under the control of his/her intention (Fishbein and Ajzen 1975). When adoption is voluntary, attitudes have been shown to correlate with behavioral intention and subsequently with use (Davis et al. 1989). However, considering the prevalent nature of IS use in organizations, it often takes the form of mandatory systems that they must use in order to meet organizations’ and management’s requirements. In carrying out a mandatory task, the role of behavioral intention is diminished. Bagozzi and Yi (1989) show that only when intention is well formed does behavioral intention capture the effect of attitude on behavior. In other words, attitudes would elicit behavior with little or no intervening thought. That is, attitudes would not be associated with behavioral intention, as employees would use the system regardless of whether they have positive or negative attitudes toward it, unless they intend to quit. Hence, attitudes will likely take on a heightened weight in determining the employees’ level of acceptance for instance, the delay or obstruction of the implementation, and the users may resent, underutilize or sabotage the new system (Markus 1983; Leonard-Barton 1988; Marakas and Hornik

15 1996; Zuboff 1988). With these reasons, this study leaves out behavioral intention in the model. 2.4.4 Relationship between Pre-use-stage Attitude and Use-stage Attitude A long history of research on cognitive consistency and attitude change has found that people act in ways that preserve their established knowledge structures, perceptions, schemata, and memories (Greenwald 1980; Eagly and Chaiken 1993). People perceive new stimuli as deviations and adjust appropriately for any new positive or negative stimuli. Based on the assumption that stimuli are judged with respect to internal norms, adaptation level theory contends that new cognitions stand for the mingled effects of present and past experience. It represents a region on a continuum, and there is a changing adaptation level at all times (Helson 1964). Grounded on adaptation level theory, Bhattacherjee and Premkumar (2004) examine the relationship between pre-use-stage and use-stage attitudes. Their study found that prior pre-usage attitudes are an important determinant of use-stage attitudes. As Yi (1990) points out, people are subjected to two sets of forces from an object about which they have developed an attitude. On the one hand, new experiences produce forces towards change. An attitude may change with experience. On the other hand, the existing attitude creates forces towards stability (e.g., resistance to change). Hence, a prior attitude could influence cognitive evaluations of actual experience. This is

16 consistent with the findings by Lord et al. (1979) and Oliver (1980) that a prior attitude steers the judgment of relevant evidence or information processing. Based on the research findings, we hypothesize that: H4: Pre-use-stage attitude has a significant positive influence on use-stage attitude. 2.4.5 The Disconfirmation Experience Research in psychology suggests that attitudes and beliefs are relatively temporary and changeable. Salient beliefs may endure over time. They may be weakened, strengthened, or replaced by novel beliefs (Yi 1990). Fishbein and Ajzen (1975) suggest that these associations are crafted through various sources or inference processes such as direct experience and active information acquisition. Change in belief is considered to be the result of a cognitive process described by the expectation disconfirmation theory. Disconfirmation is conceptualized as the cognitive comparison between a set of beliefs about desired attributes of a product or service and what a person actually receives (Oliver 1980). When there is a discrepancy between the expectation and the actual experience, a disconfirmation occurs. There are three possible levels of confirmation of expectations: expectations match perceived performance; expectation worse than perceived performance and expectation better than perceived performance. Whenever experiences are below expectations, such

17 experiences reduce satisfaction. When experiences surpass expectations, expectations exert a positive surprise effect on satisfaction. Recently, the expectation confirmation model (ECM) has been widely employed in IS research. For instance, Bhattacherjee and Premkumar (2004) used the ECM to understand changes in beliefs and attitudes toward IT usage. They report that disconfirmation is critical to changes in IT users’ beliefs and attitudes; depending on the user’s reaction to the new system, that experience may either be positive (negatively disconfirmed), neutral (confirmed), or negative (positively disconfirmed). When the actual experience is not as good as expected, the user probably feels more dissonance and may tend to have a more unfavorable attitude or vice versa (Oliver 1997). H5: Confirmation of expectation has a positive effect on use-stage attitude. 2.4.6 Feedback As systems are increasingly complex, employees are likely to feel uncomfortable with the technological change (Yoon et al. 1995). Due to limited technical knowledge and the different focuses of end users in the pre-implementation phase, early IS participation could hardly be fully effective to help employees to forestall changes (Wagner and Newell 2007). Unmet expectations of employees are likely and they might generate negative attitudes towards the new system (Goodhue and Thompson 1995). Prior IT adoption literature suggests that if this feeling is not

18 properly addressed, it could lead to severe resistance to IT innovation (e.g., Markus et al. 2003; Ahuja and Thatcher 2005; Jasperson et al. 2005). Studies of service recovery have pointed out that customer responses to service failure depend on what is done to patch up the problems (outcomes), as well as how they are resolved (processes) (e.g., Mattila and Cranage 2005; Sparks and McColl-Kennedy 2001). Marketing literature suggests that feedback is the amount of voice a customer is able to provide regarding the procedures and practices of a business. The ability for customers to put across their views or sentiments about an issue has been found to alter perceptions concerning the quality of a service provider’s actions even when the customers’ input was not connected to the decision making. Thus it is regarded as an important determinant of satisfaction (Goodwin and Ross 1990; Lind et al. 1990; Sparks and McColl-Kennedy 2001). Practically speaking, a feedback mechanism at an earlier use-stage allows the system developer to answer queries from users, collect their enhancement requests and make any necessary adjustments to the system to improve overall system technology-fit perception (Goodhue and Thompson 1995). It provides an opportunity between employees and employer to resolve problems following the technological change. In theory, feedback at the use-stage is similar to service guarantees in marketing, which would influence users by giving assurances about the quality of the product and ultimately leading the users to attribute positive perceptions to the new

Full document contains 154 pages
Abstract: Technological changes in organizations are challenging. While there are success stories, the failure rate is alarmingly high. This thesis presents the development and testing of three models on the impact of technological change on employees' behavior. The first model examines the current understanding of technology acceptance, as well as the notion of mandated use. An integrated model is proposed. The results indicate that there are differences in the underlying relationships of the technology acceptance process when use is mandated. The second study, as an extension of study one, looks at the earlier deep usage effect on employees' job outcome changes in an 18 months period. The mediating effect of job autonomy on long-term job outcomes is evidenced. By applying the job demand-control model, study three examines the job demand increase effect in job performance changes in the transformation process. Latent growth modeling was used. These three studies are validated by a longitudinal field study conducted in the Hong Kong Police Department. This research project makes important contributions by deepening our understanding of the employee behavioral changes instigated by technological change. [PUBLICATION ABSTRACT]