Continued usage of technology versus situational factors: An empirical analysis

Mainstream technology management literature suggests that research on continued usage of technology is largely based on two perspectives, namely (i) a forward-looking perspective that underpins the technology acceptance model (TAM), and (ii) a retrospective perspective that is based on the expectation disconfirmation theory (EDT). We propose an extended framework to re-examine continued usage of technology by combining these two perspectives and incorporating individual, social and environmental factors as additional variables. Our study, in the context of users’ continued usage of e-learning tools, reveals that in addition to user satisfaction and perceived usefulness, self-efficacy, system service support and social pressure are significant factors that affect continued usage of technology. Our findings enrich the theoretical framework of continued usage of technology, and provide e-learning developers with managerial insights on how to entice learners to continue using their e-learning tools.     

Are Individual Differences Germane to the Acceptance of New Information Technologies?

Persuading users to adopt new information technologies persists as an important problem confronting those responsible for implementing new information systems. In order to better understand and manage the process of new technology adoption, several theoretical models have been proposed, of which the technology acceptance model (TAM) has gained considerable support. Beliefs and attitudes represent significant constructs in TAM. A parallel research stream suggests that individual difference factors are important in information technology acceptance but does not explicate the process by which acceptance is influenced. The objective of this paper is to clarify this process by proposing a theoretical model wherein the relationship between individual differences and IT acceptance is hypothesized to be mediated by the constructs of the technology acceptance model. In essence then, these factors are viewed as influencing an individual's beliefs about an information technology innovation; this relationship is further supported by drawing upon extensive research in learning. The theoretical model was tested in an empirical study of 230 users of an information technology innovation. Results confirm the basic structure of the model, including the mediating role of beliefs. Results also identify several individual difference variables that have significant effects on TAM's beliefs. Theoretical contributions and practical implications that follow are discussed.     

Acceptance of automation manufacturing technology in China: an examination of perceived norm and organizational efficacy

Abstract

With a shift to more automation technology, social acceptance of technology plays an important role in the manufacturing sector. To what extent this occurs, and affects the adoption of technology, has been less researched, but is important in deciding how such technology is introduced, and the nature of the shift from labour-intensive manufacturing to automation. This research applies the revised technology acceptance model (TAM) to examine the impact of social and individual antecedents on the acceptance of automation manufacturing technology. Survey data are collected from 258 Chinese manufacturers. Results suggest that perceived norms significantly affect organizational intention to use automation manufacturing technology both directly and via perceived usefulness; organizational efficacy explains the intention to use via mediating effect of perceived usefulness and perceived ease of use. This research is one of the first extending and applying TAM from individuals to organizations.     

Information Technology Acceptance by Individual Professionals: A Model Comparison Approach*

The proliferation of innovative and exciting information technology applications that target individual “professionals” has made the examination or re‐examination of existing technology acceptance theories and models in a “professional” setting increasingly important. The current research represents a conceptual replication of several previous model comparison studies. The particular models under investigation are the Technology Acceptance Model (TAM), the Theory of Planned Behavior (TPB), and a decomposed TPB model, potentially adequate in the targeted healthcare professional setting. These models are empirically examined and compared, using the responses to a survey on telemedicine technology acceptance collected from more than 400 physicians practicing in public tertiary hospitals in Hong Kong. Results of the study highlight several plausible limitations of TAM and TPB in explaining or predicting technology acceptance by individual professionals. In addition, findings from the study also suggest that instruments that have been developed and repeatedly tested in previous studies involving end users and business managers in ordinary business settings may not be equally valid in a professional setting. Several implications for technology acceptance/adoption research and technology management practices are discussed.     

行为控制对威客持续参与意愿的影响:被调节的中介模型

威客的持续参与意愿是维持众包平台可持续性发展的关键因素。在众包参与过程中,平台实施的控制机制是否会影响持续参与意愿还缺乏系统的理论分析和实证研究。基于感知组织支持理论,本文构建了被调节的中介模型和相关假设,探讨行为控制如何通过归属感的中介作用影响持续参与意愿,以及在不同的程序公平水平下,行为控制通过归属感提升持续参与意愿的机制会有怎样的变化。基于“猪八戒网”搜集的290份样本数据,对模型进行实证检验。结果表明,归属感在行为控制影响持续参与意愿的关系中起部分中介作用;同时,程序公平正向调节上述中介作用,即程序公平越高,归属感在行为控制与持续参与意愿关系间的中介作用越容易实现。研究结果丰富、扩展了已有的众包理论研究,并为众包实践提供了管理启示与指导。     

Technology Acceptance Model 3 and a Research Agenda on Interventions

Prior research has provided valuable insights into how and why employees make a decision about the adoption and use of information technologies (ITs) in the workplace. From an organizational point of view, however, the more important issue is how managers make informed decisions about interventions that can lead to greater acceptance and effective utilization of IT. There is limited research in the IT implementation literature that deals with the role of interventions to aid such managerial decision making. Particularly, there is a need to understand how various interventions can influence the known determinants of IT adoption and use. To address this gap in the literature, we draw from the vast body of research on the technology acceptance model (TAM), particularly the work on the determinants of perceived usefulness and perceived ease of use, and: (i) develop a comprehensive nomological network (integrated model) of the determinants of individual level (IT) adoption and use; (ii) empirically test the proposed integrated model; and (iii) present a research agenda focused on potential pre‐ and postimplementation interventions that can enhance employees' adoption and use of IT. Our findings and research agenda have important implications for managerial decision making on IT implementation in organizations.     

Building a Model of Technology Preference: The Case of Channel Choices

Intention theories, such as the Theory of Reasoned Action, the Theory of Planned Behavior, and the Technology Acceptance Model (TAM), have been widely adopted to explain information system usage. These theories, however, do not explicitly consider the availability of alternative systems that users may have access to and may have a preference for. Recent calls for advancing knowledge in technology acceptance have included the examination of selection among competing channels and extending the investigation beyond adoption of a single technology. In this study, we provide a theoretical extension to the TAM by integrating preferential decision knowledge to its constructs. The concept of Attitude‐Based Preference and Attribute‐Based Preference are introduced to produce a new intention model, namely the Model of Technology Preference (MTP). MTP was validated in the context of alternative behaviors in adopting two service channels: one a technology‐based online store and the other a traditional brick‐and‐mortar store. A sample of 320 responses was used to run a structural equation model. Empirical results show that MTP is a powerful predictor of alternative behaviors. Furthermore, in the context of service channel selection, incorporating preferential decision knowledge into intention models can be used to develop successful business strategies.     

Toward an Understanding of the Behavioral Intention to Use an Information System

Organizational investment in information systems is often large and risky given the variety of information requirements placed on systems today. To make more informed decisions and to meet the challenge of developing systems that satisfy these demands, system developers need to achieve a better understanding of factors that ultimately lead to system usage. To enhance this understanding, we posit a holistic framework to examine several constructs suggested in the literature that lead to the behavioral intention to use an information system. Our framework includes situational involvement, intrinsic involvement, argument for change, perceived usefulness, ease of use, prior usage, and attitude constructs. We extend the Davis, Bagozzi, and Warshaw Technology Acceptance Model (TAM), which is founded on the Theory of Reasoned Action. A diverse sample from industry is used to test our model. Structural equation modeling is used to examine the entire pattern of intercorrelations among the constructs and to test related propositions. A hierarchical structure is used to compare the explanatory ability of TAM with our extension. Our model explains a large portion of the covariance among the constructs that lead to a user's behavioral intention to use an information system and compares favorably with TAM. The results indicate that (1) the direct effect of situational involvement on behavioral intention as well as attitude is significant in the negative direction, (2) attitude seems to play a mediating role, and (3) intrinsic involvement plays a significant role in shaping perceptions. Finally, we conclude that the user involvement construct needs to be separated into its psychological as well as its participative components for developers to understand its impact on the systems development process.     

A conceptual model for the process of IT innovation adoption in organizations

In this paper, we develop a conceptual model for IT innovation adoption process in organizations. The model utilizes Diffusion of Innovation (DOI) theory, Theory of Reasoned Action (TRA), Technology Acceptance Model (TAM), Theory of Planned Behaviour (TPB) and a framework that contains characteristics of innovation, organization, environment, chief executive officer (CEO) and user acceptance. The model presents IT adoption as a sequence of stages, progressing from initiation to adoption-decision to implementation. The study presents a model with an interactive process perspective which considers organizational level analysis until acquisition of technology and individual level analysis for the user acceptance of IT.     

Managerial Influences on Intraorganizational Information Technology Use: A Principal-Agent Model

Our current understanding of information technology (IT) usage does not explain why and how managers can influence organizational members to use a new IT. Drawing on principal-agent research, this paper develops and tests a model of intraorganizational IT usage that addresses this important issue. Managerial incentives and control are examined as important components of managerial influences, which are linked to IT usage via a principal-agent model (PAM). Seven research hypotheses are generated from this model and empirically tested using a laboratory experiment. Results of the study indicate that managers can promote IT usage within organizations by designing appropriate incentives and control structures such as monitoring and multiple-period contracts. However, the effectiveness of these structures will depend on potential users' ability to distinguish between various forms of incentives and control.     

Paper Versus Electronic Medical Records: The Effects of Access on Physicians' Decisions to Use Complex Information Technologies*

This study examines physicians' responses to complex information technologies (IT) in the health care supply chain. We extend individual‐level IT adoption models by incorporating a new construct: system accessibility. The main premise of the study is, when faced with a decision between alternate IT systems, individual users tend to select and make use of the technology or system that is most readily accessible. We discuss both physical and logical dimensions of accessibility as they relate to adoption of electronic medical records (EMR). Physical accessibility refers to the availability of computers that can be used to access EMR, while logical accessibility refers to the ease or difficulty of logging into the system. Using data from a survey of 199 physicians practicing in a large U.S. hospital, we show that, when deciding between the paper chart and EMR, accessibility is an important consideration in a physician's decision to use the system. Both dimensions of accessibility act as barriers to EMR use intentions through their indirect effect on physicians' perceptions of EMR usefulness and ease of use. Logical access also has a direct effect on EMR use intentions. We conclude that accessibility is an important factor that limits acceptance of complex IT such as EMR.     

The effects of self-efficacy on computer usage

This paper examines the effect of self-efficacy, belief in one's capabilities of using a computer in the accomplishment of specific tasks, on computer usage. It introduces an extended technology acceptance model (TAM) that explicitly incorporates self-efficacy and its determinants (experience and organizational support) as factors affecting computer anxiety, perceived ease of use, perceived usefulness and the use of computer technology. A survey of 450 microcomputer users in Finland found strong support for the conceptual model. In accordance with TAM, perceived usefulness had a strong direct effect on usage, while perceived ease of use had indirect effect on usage through perceived usefulness. Self-efficacy had both direct and indirect effects on usage, demonstrating its importance in the decision to use computer technology. It also had a strong direct effect on perceived ease of use, but only an indirect effect on perceived usefulness through perceived ease of use. Computer experience was found to have a strong positive direct effect on self-efficacy, perceived ease of use, perceived usefulness and usage. Organizational support and computer anxiety had only indirect effects on usage, mainly through perceived usefulness. Implications of these findings are discussed for researchers and practitioners.     

The Effect of Board of Directors’ IT Awareness on CIO Compensation and Firm Performance

Chief information officers (CIOs) play increasingly strategic roles in firms in this competitive global economy, which is now largely powered by information technology (IT). However, research has shown a lack of board of directors’ oversight on CIO‐ and IT‐related issues. Drawing on agency, resource dependence, and alignment theories, we investigate the effect of board of directors’ IT awareness on CIO compensation structure and firm performance. We conduct cross‐sectional time series analyses of data collected from various sources. Our study underlines three important findings. First, we show that some commonly known executive compensation determinants, such as individual characteristics and governance structure, do not have significant effects on CIO compensation structure. Second, with regard to CIO compensation structure, firms respond to increasing information asymmetry differently according to the level of IT awareness of their boards. Finally, firms perform better when their boards have higher levels of IT awareness, and this positive effect of IT awareness is considerably larger in IT intensive industries. Overall, our study provides empirical support for the important role of boards’ IT awareness in shaping CIO compensation and improving firm performance. Our results suggest that boards with functional area knowledge—or higher IT awareness in this case—can more effectively monitor and better incentivize executives, and consequently lead to better firm performance.     

Understanding the Role of Individual Innovativeness in the Acceptance of IT‐Based Innovations: Comparative Analyses of Models and Measures*

As new technological innovations are rapidly introduced and changed, identifying an individual characteristic that has a persistent effect on the acceptance decisions across multiple technologies is of substantial value for the successful implementation of information systems. Augmenting prior work on individual innovativeness within the context of information technology, we developed a new measure of adopter category innovativeness (ACI) and compared its effectiveness with the existing measure of personal innovativeness in IT (PIIT). Further, we examined two alternative models in which the role of individual innovativeness was theorized differently—either as a moderator of the effects the perceived innovation characteristics of usefulness, ease of use, and compatibility have on future use intention (moderator model) or as a direct determinant of the innovation characteristics (direct determinant model). To ensure the generalizability of the study findings, two field studies (N= 634) were conducted, each of which examined the two models (moderator and direct determinant) and measured individual innovativeness using the two measures (ACI and PIIT). Study 1 surveyed the online buying practices of 412 individuals, and Study 2 surveyed personal digital assistant adoption of 222 healthcare professionals. Across the markedly different adoption contexts, the study results consistently show that individual innovativeness is a direct determinant of the innovation characteristics, and the two measures share many commonalities. The new measure offers some additional utilities not found in the PIIT measure by allowing individuals to be directly classified and mapped into adopter categories. Implications are drawn for future research and practice.     

Employee Misuse of Information Technology Resources: Testing a Contemporary Deterrence Model

Recent research in information systems and operations management has considered the positive impacts of information technology (IT). However, an undesirable side effect of firms’ increasing reliance on IT to support the distribution and delivery of goods and services to customers is a greater exposure to a diverse set of IT security risks. One such risk is intentional employee misuse of technology resources. In this article, we draw upon modern deterrence frameworks to develop a predictive model of technology misuse intention that incorporates formal and informal sanctions as well as employment context factors. The model specifies previously untested relationships between formal and informal sanctions, thereby providing fresh insight into the role of sanctions in deterring technology misuse in organizations. Our results suggest that a predisposition toward the need for social approval and moral beliefs regarding the behavior are key determinants of technology misuse. Contrary to criminological research that has questioned the relative importance of formal sanctions in the deterrence process, we also found that the threat of formal sanctions has both direct and indirect influences on technology misuse intention. Further, from an employment context standpoint, employees who spend more working days away from the office (i.e., “virtual” mode) appear more inclined to misuse their organization's technology resources. The findings have implications for the research and practice of technology management.     

Public Acceptance of Fully Automated Driving: Effects of Social Trust and Risk/Benefit Perceptions

Automated driving (AD) is one of the most significant technical advances in the transportation industry. Its safety, economic, and environmental benefits cannot be realized if it is not used. To explain, predict, and increase its acceptance, we need to understand how people perceive and why they accept or reject AD technology. Drawing upon the trust heuristic, we tested a psychological model to explain three acceptance measures of fully AD (FAD): general acceptance, willingness to pay (WTP), and behavioral intention (BI). This heuristic suggests that social trust can directly affect acceptance or indirectly affect acceptance through perceived benefits and risks. Using a survey (N = 441), we found that social trust retained a direct effect as well as an indirect effect on all FAD acceptance measures. The indirect effect of social trust was more prominent in forming general acceptance; the direct effect of social trust was more prominent in explaining WTP and BI. Compared to perceived risk, perceived benefit was a stronger predictor of all FAD acceptance measures and also a stronger mediator of the trust–acceptance relationship. Predictive ability of the proposed model for the three acceptance measures was confirmed. We discuss the implications of our results for theory and practice.     

Using Davis's Perceived Usefulness and Ease-of-use Instruments for Decision Making: A Confirmatory and Multigroup Invariance Analysis

As key components of Davis's technology acceptance model (TAM), the perceived usefulness and perceived ease-of-use instruments are widely accepted among the MIS research community as tools for evaluating information system applications and predicting usage. Despite this wide acceptance, a series of incremental cross-validation studies have produced conflicting and equivocal results that do not provide guidance for researchers or practitioners who might use the TAM for decision making. Using a sample of 902 “initial exposure” responses, this research conducts: (1) a confirmatory factor analysis to assess the validity and reliability of the original instruments proposed by Davis, and (2) a multigroup invariance analysis to assess the equivalence of these instruments across subgroups based on type of application, experience with computing, and gender. In contrast to the mixed results of prior cross-validation efforts, the results of this confirmatory study provide strong support for the validity and reliability of Davis's sixitem perceived usefulness and six-item ease-of-use instruments. The multigroup invariance analysis suggests the usefulness and ease-of-use instruments have invariant true scores across most, but not all, subgroups. With notable exemptions for word processing applications and users with no prior computing experience, this research provides evidence that the item-factor loadings (true scores) are invariant across spread sheet, database, and graphic applications. The implications of the results for managerial decision making are discussed.     

Job Strain,Effort-Reward Imbalance and Mental Distress: A study of occupations in general medical practice

There is increasing evidence to support the predictive power of social epidemiological models such as Effort-Reward Imbalance (Siegrist, 1996) and the Job-Strain Model (Karasek, and Theorell, 1990) for explaining occupational stress, although it has been suggested that the models may have distinctive contributions towards explaining work stress in specific work settings. Alternatively, it has been suggested that the explanatory power of the different models might be enhanced if they were combined. The aim of this paper is to explore these questions by examining the power of the two different models both separately and in combination for explaining job satisfaction and mental distress in general medical practice. This analysis was based on data collected from a postal survey of the members of staff (N=1089, response rate = 70%) of 81 practices, which were randomly selected from all general practices in the National Health Service Executive South East region. The results show that while both models were predictors of mental distress and job satisfaction the models that combined different dimensions were the strongest predictors.     

Predicting System Usage from Intention and Past Use: Scale Issues in the Predictors

The objective of this study is to provide insights into how the predictive power for computer‐recorded system usage can be improved. Based on 386 responses from actual users of an information system, we examine the predictive power for system usage according to the scales of the predictors used, namely, intention and past use. First, we show that the predictive power of intention can be significantly improved with the choice of an appropriate measure. However, even the desirable intention measure failed to explain two‐thirds of the variance in system usage. Second, the results show that past use as measured by computer‐recorded log data can significantly enhance our ability to predict system usage. Finally, when both intention and past use are controlled for, the explained variance in system usage is shown to vary widely from 20% to 73%, depending on the predictors' scales. Overall, our findings suggest that an accurate prediction of system usage requires a more rigorous approach than that often applied in information systems research.