A Model of the Antecedents of Perceived Ease of Use: Development and Test*

The Technology Acceptance Model (TAM) has been widely used to predict user acceptance and use based on perceived ease of use and usefulness. However, in order to design effective training interventions to improve user acceptance, it is necessary to better understand the antecedents and determinants of key acceptance constructs. In this research, we focus on understanding the determinants of perceived ease of use. Data from three experiments spanning 108 subjects and six different systems supported our hypothesis that an individual's perception of a particular system's ease of use is anchored to her or his general computer self-efficacy at all times, and objective usability has an impact on ease of use perceptions about a specific system only after direct experience with the system. In addition to being an important research issue in user acceptance research, understanding antecedents of perceived ease of use is also important from a practical standpoint since several systems in which millions of dollars are invested are rejected because of poor user interfaces. Moreover, the actual underlying problem might be low computer self-efficacy of the target user group. In such cases, training interventions aimed at improving computer self-efficacy of users may be more effective than improved interface design for increasing user acceptance.     

User Acceptance Enablers in Individual Decision Making About Technology: Toward an Integrated Model

Building on recent unique, yet potentially complementary, approaches to understanding the formation of user perceptions about technology (Venkatesh, 1999; Venkatesh & Speier, 1999), the present work reanalyzes the data from both studies to develop an integrated model of technology acceptance. The integrated model specifically examines the influence of pre‐training and training environment interventions (termed user acceptance enablers) to understand how user perceptions are formed prior to system implementation. The model is then further extended and tested using longitudinal data in a field setting. The results indicate that the integrated model emerged as a better predictor of user behavior when compared to the existing models.     

The Effect of Perceived Novelty on the Adoption of Information Technology Innovations: A Risk/Reward Perspective

A fundamental characteristic of any innovation is its novelty, the newness or freshness of the innovation in the eyes of the adopter. Past research has often considered novelty to be inherent to an information technology (IT) innovation, yet it is also likely that perceptions of novelty differ widely across individuals. Nevertheless, the role that the novelty of an IT innovation plays in adoption is not well understood. The primary goal of this research effort is to frame the perceived novelty of an IT innovation as a salient affective belief in the nomological network related to adoption. Further, we examine how perceived novelty influences the way individuals reconcile their perceptions of risk versus reward when considering the adoption of an IT innovation. Two empirical studies with 424 and 138 participants, respectively, examine the effect of perceived novelty on IT innovations from a risk/reward perspective. Results indicate that perceived novelty is a salient affective belief that plays a significant role in the adoption of IT innovations. Implications for both theory and organizational decision making are examined.     

Examining the Impact of Pre‐Implementation Expectations on Post‐Implementation Use of Enterprise Systems: A Longitudinal Study

This article builds upon the technology acceptance model and theories of technology sensemaking to explore pre‐enterprise system adoption expectations and post‐enterprise system adoption outcomes in a longitudinal setting. Building on the exploitation and exploration paradigm, we propose that task productivity and task innovation expectations are the key drivers of users’ pre‐adoption enterprise system usage intention. Further, we argue that the enterprise system facilitates generation of a common knowledge base that may encourage a more integrated organizational culture and promote shared understanding among employees. Considering the distinction between mandatory and voluntary contexts, we propose that user acceptance of the enterprise system at the pre‐ and post‐adoption stages will mediate these relationships in a mandatory context. The results show that the influence of pre‐adoption expectations regarding task productivity and task innovation on intention to use an enterprise system is mediated by user acceptance of the enterprise system. Intention to use an enterprise system is positively related to actual use. At the post‐adoption stage, the influence of actual use on shared understanding is mediated by user acceptance of an enterprise system and enterprise system use has a direct negative impact on task efficiency in the initial period after implementation. Overall, the results highlight that user acceptance at both pre‐ and post‐adoption stages are critical factors when usage is mandatory. These findings suggest a number of important implications for research and for managerial action.     

Organizational Computing as a Facilitator of Operational and Managerial Decision Making: An Exploratory Study of Managers' Perceptions*

Much of the current knowledge pertaining to information technology (IT) and decision making is based on decades old technologies that revolved around a central computing function and application-specific systems. The purpose of this research is to examine the IT decision-making relationship within the emerging organizational computing (OC) environment permeated by spontaneous utilization of both application-and nonapplication-specific computing and communication technologies. Specifically, this study seeks to explore managers' perceptions of the emerging OC environment as a facilitator of their decision-making activities. To achieve a higher level of clarity than previous works, a two-dimensional research framework is developed with the IT dimension consisting of computing and communication, and the decision-making dimension differentiated between operational and managerial decisions. A survey instrument was constructed that measured the computing and communication dimensions of information technology use and their perceived effects upon operational and managerial decisions. The major findings of the study confirmed that managers recognize the value of general, nonapplication-specific information technologies in decision making, and that this recognition is highly associated with how intensively these information technologies are used. Additionally, it was found that the two dimensions of IT differ in their relationships to decision making, and that IT usage relates to managerial decisions differently than operational decisions. These study findings have significant implication for practice and research, especially in the context of information resource management in which the primary purpose of the IS function is the delivery of general information service to users rather than the development of specific IS applications.     

The Determinants of DSS Success: An Integrated Model*

The results of a field study investigating the determinants of decision support systems (DSS) success are presented. A multivariate model was developed and tested using multiple regression hierarchical analysis on responses from 118 DSS users. Several specific hypotheses are also proposed and tested. Data analyses indicate that DSS success, as measured by DSS satisfaction and perceived benefits, depends on several factors: previous user experience with DSS, user involvement, user training, top management support, information sources, the level of managerial activity, and task structure, difficulty and interdependence. Based on the research results, several suggestions are made to improve the likelihood of successful DSS implementation.     

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.     

Explaining information technology usage: A test of competing models

While much of the prior information technology (IT) research has attempted to explain users’ acceptance of new IT, recent research has focused on IT continuance or continued usage. The technology acceptance model (TAM) and the expectation–disconfirmation theory (EDT) are currently the dominant referent theoretical frameworks explaining user acceptance and continuance of IT, respectively. However, no study to date has yet empirically compared the relative ability of the two competing theories in explaining IT continuance intention. This paper fills this gap in the literature by comparing the explanatory ability of the two models via a longitudinal study of computer-based tutorial usage. Our findings confirm that both models have good explanatory power with the TAM providing a better prediction of intention. An integrated model, combining TAM and EDT, provided a marginally better explanatory power.     

How a Nuclear Power Plant Accident Influences Acceptance of Nuclear Power: Results of a Longitudinal Study Before and After the Fukushima Disaster

Major nuclear accidents, such as the recent accident in Fukushima, Japan, have been shown to decrease the public's acceptance of nuclear power. However, little is known about how a serious accident affects people's acceptance of nuclear power and the determinants of acceptance. We conducted a longitudinal study (N= 790) in Switzerland: one survey was done five months before and one directly after the accident in Fukushima. We assessed acceptance, perceived risks, perceived benefits, and trust related to nuclear power stations. In our model, we assumed that both benefit and risk perceptions determine acceptance of nuclear power. We further hypothesized that trust influences benefit and risk perceptions and that trust before a disaster relates to trust after a disaster. Results showed that the acceptance and perceptions of nuclear power as well as its trust were more negative after the accident. In our model, perceived benefits and risks determined the acceptance of nuclear power stations both before and after Fukushima. Trust had strong effects on perceived benefits and risks, at both times. People's trust before Fukushima strongly influenced their trust after the accident. In addition, perceived benefits before Fukushima correlated with perceived benefits after the accident. Thus, the nuclear accident did not seem to have changed the relations between the determinants of acceptance. Even after a severe accident, the public may still consider the benefits as relevant, and trust remains important for determining their risk and benefit perceptions. A discussion of the benefits of nuclear power seems most likely to affect the public's acceptance of nuclear power, even after a nuclear accident.     

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.     

顾客采用网络银行的影响因素研究

网络银行已经成为银行业保留老顾客和获取新顾客的一种新兴的服务渠道,而有关顾客采用网络银行影响因素的研究也越来越激发兴趣,引起关注。感知风险和信任是网络银行顾客最为担心的因素,但这似乎并没有引起学者们的足够重视。大多数研究都将顾客方面的建构作为认知建构的前置因素,而将银行方面的建构作为认知建构的前置因素的研究还几乎无人问津。本研究的重要意义在于:在具体的网络银行环境下,以科技接受模型为基础,在认知建构中增加感知风险和信任等变量,同时将顾客方面的自我效能和银行方面的便利条件两个建构分别作为认知构建的前置因素,从而对网络银行的采用意图进行理论探讨和实证检验。     

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.     

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.     

Examining the Antecedents and Consequences of CIO Strategic Decision‐Making Authority: An Empirical Study*

Despite the strategic importance of information technology (IT) to contemporary firms, chief information officers (CIO) often still have varying degrees of strategic decision‐making authority. In this study, we apply the theory of managerial discretion to define CIO strategic decision‐making authority and argue that the CIO's level of strategic decision‐making authority directly influences IT's contribution to organization performance. We also draw on the power and politics perspective in the strategic decision‐making literature to identify the direct antecedents to the CIO's strategic decision‐making authority. A theoretical model is presented and empirically tested using survey data collected from a cross‐industry sample of 174 matched pairs of CIOs and top business executives through structural equation modeling. The results suggest that organizational climate, organizational support for IT, the CIO's structural power, the CIO's level of strategic effectiveness, and a strong partnership between the CIO and top management team directly influence the CIO's level of strategic decision‐making authority within the organization. The results also suggest that the CIO's strategic decision‐making authority in the organization directly influences the contribution of IT to firm performance and that effective CIOs have a greater influence on IT's contribution when provided with strategic decision‐making authority.     

Data Envelopment Analysis for Managerial Control and Diagnosis*

Data envelopment analysis (DEA) is a linear programming-based technique that converts multiple input and output measures into a single comprehensive measure of productive efficiency. This is accomplished via the construction of an empirically based production frontier and by the identification of peer groups. Each unit is evaluated by comparison against a composite unit that is constructed as a convex combination of other units in its peer group. DEA has now been applied in a variety of managerial contexts. In this paper we draw on theories of decision making, measurement and control, the mathematical properties of DEA, prior reported applications, and our own experience, to assess the potential of DEA as a general management tool. We first make the distinction between managerial diagnosis and control. We show how measurement requirements differ for these two managerial decision contexts, and argue that DEA has the potential to provide support in each context. Measurement and decision support criteria for each activity are then developed by reference to the literature on diagnosis and control. Based on its mathematical definition and properties, the relevant attributes of DEA are then derived. The technique is evaluated in each capacity by comparison to the appropriate set of criteria. This evaluation is supported with evidence from our experience with DEA in a large public-sector organization. We argue that the structural properties of DEA, critical managerial choices in its application, and situationally specific factors, interact to determine the strengths and limitations of DEA in each decision context. Implications for research and practice are discussed.     

An Empirical Agent‐Based Model to Simulate the Adoption of Water Reuse Using the Social Amplification of Risk Framework

Water reuse can serve as a sustainable alternative water source for urban areas. However, the successful implementation of large‐scale water reuse projects depends on community acceptance. Because of the negative perceptions that are traditionally associated with reclaimed water, water reuse is often not considered in the development of urban water management plans. This study develops a simulation model for understanding community opinion dynamics surrounding the issue of water reuse, and how individual perceptions evolve within that context, which can help in the planning and decision‐making process. Based on the social amplification of risk framework, our agent‐based model simulates consumer perceptions, discussion patterns, and their adoption or rejection of water reuse. The model is based on the “risk publics” model, an empirical approach that uses the concept of belief clusters to explain the adoption of new technology. Each household is represented as an agent, and parameters that define their behavior and attributes are defined from survey data. Community‐level parameters—including social groups, relationships, and communication variables, also from survey data—are encoded to simulate the social processes that influence community opinion. The model demonstrates its capabilities to simulate opinion dynamics and consumer adoption of water reuse. In addition, based on empirical data, the model is applied to investigate water reuse behavior in different regions of the United States. Importantly, our results reveal that public opinion dynamics emerge differently based on membership in opinion clusters, frequency of discussion, and the structure of social networks.     

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.     

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.     

The Emergence of Artificial Intelligence as a Reference Discipline for Decision Support Systems Research

It is timely and appropriate to examine both philosophical and pragmatical issues associated with formalizing the adoption of artificial intelligence as a reference discipline for decision support systems research. This paper reflects on where we were when the first special issue of Decision Sciences on expert systems and decision support systems was published, addresses the dynamics of what has taken place subsequent to the publication of that first special issue, sets forth a proposition to stimulate ongoing dialog with respect to synergies between the decision support system research agenda and the research agenda of the artificial intelligence discipline, and demonstrates how the papers appearing in this follow-up special issue of Decision Sciences are representative of an emerging, challenging, and exciting new decision support systems era.