Georgia State University

A large number of studies have been conducted during the last decade and a half attempting to identify those factors that contribute to information systems success. However, the dependent variable in these studies—I/S success—has been an elusive one to define. Different researchers have addressed different aspects of success, making comparisons difficult and the prospect of building a cumulative tradition for I/S research similarly elusive. To organize this diverse research, as well as to present a more integrated view of the concept of I/S success, a comprehensive taxonomy is introduced. This taxonomy posits six major dimensions or categories of I/S success—SYSTEM QUALITY, INFORMATION QUALITY, USE, USER SATISFACTION, INDIVIDUAL IMPACT, and ORGANIZATIONAL IMPACT. Using these dimensions, both conceptual and empirical studies are then reviewed (a total of 180 articles are cited) and organized according to the dimensions of the taxonomy. Finally, the many aspects of I/S success are drawn together into a descriptive model and its implications for future I/S research are discussed.

A separate and distinct interaction with both the actual e-vendor and with its IT Web site interface is at the heart of online shopping. Previous research has established, accordingly, that online purchase intentions are the product of both consumer assessments of the IT itself—specifically its perceived usefulness and ease-of-use (TAM)—and trust in the e-vendor. But these perspectives have been examined independently by IS researchers. Integrating these two perspectives and examining the factors that build online trust in an environment that lacks the typical human interaction that often leads to trust in other circumstances advances our understanding of these constructs and their linkages to behavior. Our research on experienced repeat online shoppers shows that consumer trust is as important to online commerce as the widely accepted TAM use-antecedents, perceived usefulness and perceived ease of use. Together these variable sets explain a considerable proportion of variance in intended behavior. The study also provides evidence that online trust is built through (1) a belief that the vendor has nothing to gain by cheating, (2) a belief that there are safety mechanisms built into the Web site, and (3) by having a typical interface, (4) one that is, moreover, easy to use.

Researchers have used the absorptive capacity construct to explain various organizational phenomena. In this article we review the literature to identify key dimensions of absorptive capacity and offer a reconceptualization of this construct. Building upon the dynamic capabilities view of the firm, we distinguish between a firm's potential and realized capacity. We then advance a model outlining the conditions when the firm's potential and realized capacities can differentially influence the creation and sustenance of its competitive advantage.

The growing interest in Structured Equation Modeling (SEM) techniques and recognition of their importance in IS research raises the need to compare and contrast the different types of SEM techniques so that research designs can be selected appropriately. After assessing the extent to which these techniques are currently being used in IS research, the article presents a running example which analyzes the same dataset via three very different statistical techniques. It then compares two classes of SEM: covariance-based SEM and partial-least-squares-based SEM. Finally, the article discusses linear regression models and suggests guidelines as to when SEM techniques and when regression techniques should be used. The article concludes with heuristics and rule of thumb thresholds to guide practice, and a discussion of the extent to which practice is in accord with these guidelines.

Business intelligence and analytics (BI&A) has emerged as an important area of study for both practitioners and researchers, reflecting the magnitude and impact of data-related problems to be solved in contemporary business organizations. This introduction to the MIS Quarterly Special Issue on Business Intelligence Research first provides a framework that identifies the evolution, applications, and emerging research areas of BI&A. BI&A 1.0, BI&A 2.0, and BI&A 3.0 are defined and described in terms of their key characteristics and capabilities. Current research in BI&A is analyzed and challenges and opportunities associated with BI&A research and education are identified. We also report a bibliometric study of critical BI&A publications, researchers, and research topics based on more than a decade of related academic and industry publications. Finally, the six articles that comprise this special issue are introduced and characterized in terms of the proposed BI&A research framework.

Studies that combine moderation and mediation are prevalent in basic and applied psychology research. Typically, these studies are framed in terms of moderated mediation or mediated moderation, both of which involve similar analytical approaches. Unfortunately, these approaches have important shortcomings that conceal the nature of the moderated and the mediated effects under investigation. This article presents a general analytical framework for combining moderation and mediation that integrates moderated regression analysis and path analysis. This framework clarifies how moderator variables influence the paths that constitute the direct, indirect, and total effects of mediated models. The authors empirically illustrate this framework and give step-by-step instructions for estimation and interpretation. They summarize the advantages of their framework over current approaches, explain how it subsumes moderated mediation and mediated moderation, and describe how it can accommodate additional moderator and mediator variables, curvilinear relationships, and structural equation models with latent variables.

This article reports the results of a comprehensive meta-analysis of turnover antecedents, extending an earlier one by Hom and Griffeth (1995). As such, this updated meta-analysis represents the most wide-ranging quantitative review to date of the predictive strength of numerous turnover antecedents. Importantly, the present investigation identifies various moderators of antecedent-turnover correlations. The implications of these findings for both theory and practice are discussed.

The process of information technology adoption and use is critical to deriving the benefits of information technology. Yet from a conceptual standpoint, few empirical studies have made a distinction between individuals' pre-adoption and postadoption (continued use) beliefs and attitudes. This distinction is crucial in understanding and managing this process over time. The current study combines innovation diffusion and attitude theories in a theoretical framework to examine differences in pre-adoption and post-adoption beliefs and attitudes. The examination of Windows technology in a single organization indicates that users and potential adopters of information technology differ on their determinants of behavioral intention, attitude, and subjective norm. Potential adopter intention to adopt is solely determined by normative pressures, whereas user intention is solely determined by attitude. In addition, potential adopters base their attitude on a richer set of innovation characteristics than users. Whereas pre-adoption attitude is based on perceptions of usefulness, ease-of-use, result demonstrability, visibility, and trialability, post-adoption attitude is only based on instrumentality beliefs of usefulness and perceptions of image enhancements.

Transformative artificially intelligent tools, such as ChatGPT, designed to generate sophisticated text indistinguishable from that produced by a human, are applicable across a wide range of contexts. The technology presents opportunities as well as, often ethical and legal, challenges, and has the potential for both positive and negative impacts for organisations, society, and individuals. Offering multi-disciplinary insight into some of these, this article brings together 43 contributions from experts in fields such as computer science, marketing, information systems, education, policy, hospitality and tourism, management, publishing, and nursing. The contributors acknowledge ChatGPT’s capabilities to enhance productivity and suggest that it is likely to offer significant gains in the banking, hospitality and tourism, and information technology industries, and enhance business activities, such as management and marketing. Nevertheless, they also consider its limitations, disruptions to practices, threats to privacy and security, and consequences of biases, misuse, and misinformation. However, opinion is split on whether ChatGPT’s use should be restricted or legislated. Drawing on these contributions, the article identifies questions requiring further research across three thematic areas: knowledge, transparency, and ethics; digital transformation of organisations and societies; and teaching, learning, and scholarly research. The avenues for further research include: identifying skills, resources, and capabilities needed to handle generative AI; examining biases of generative AI attributable to training datasets and processes; exploring business and societal contexts best suited for generative AI implementation; determining optimal combinations of human and generative AI for various tasks; identifying ways to assess accuracy of text produced by generative AI; and uncovering the ethical and legal issues in using generative AI across different contexts.

Employees develop exchange relationships both with organizations and immediate superiors, as evidenced by research on perceived organizational support (POS) and leader-member exchange (LMX), respectively. Despite conceptual similarities between these two constructs, theoretical development and research has proceeded independently. In an attempt to integrate these literatures, we developed and tested a model of the antecedents and consequences of POS and LMX, based on social exchange theory. Results indicated that POS and LMX have unique antecedents and are differentially related to outcome variables, providing support for the importance of both types of exchanges.

This article addresses Rönkkö and Evermann’s criticisms of the partial least squares (PLS) approach to structural equation modeling. We contend that the alleged shortcomings of PLS are not due to problems with the technique, but instead to three problems with Rönkkö and Evermann’s study: (a) the adherence to the common factor model, (b) a very limited simulation designs, and (c) overstretched generalizations of their findings. Whereas Rönkkö and Evermann claim to be dispelling myths about PLS, they have in reality created new myths that we, in turn, debunk. By examining their claims, our article contributes to reestablishing a constructive discussion of the PLS method and its properties. We show that PLS does offer advantages for exploratory research and that it is a viable estimator for composite factor models. This can pose an interesting alternative if the common factor model does not hold. Therefore, we can conclude that PLS should continue to be used as an important statistical tool for management and organizational research, as well as other social science disciplines.

Results for 160 samples of disaster victims were coded as to sample type, disaster type, disaster location, outcomes and risk factors observed, and overall severity of impairment. In order of frequency, outcomes included specific psychological problems, nonspecific distress, health problems, chronic problems in living, resource loss, and problems specific to youth. Regression analyses showed that samples were more likely to be impaired if they were composed of youth rather than adults, were from developing rather than developed countries, or experienced mass violence (e.g., terrorism, shooting sprees) rather than natural or technological disasters. Most samples of rescue and recovery workers showed remarkable resilience. Within adult samples, more severe exposure, female gender, middle age, ethnic minority status, secondary stressors, prior psychiatric problems, and weak or deteriorating psychosocial resources most consistently increased the likelihood of adverse outcomes. Among youth, family factors were primary. Implications of the research for clinical practice and community intervention are discussed in a companion article (Norris, Friedman, and Watson, this volume).

While researchers go to great lengths to justify and prove theoretical links between constructs, the relationship between measurement items and constructs is often ignored. By default, the relationship between construct and item is assumed to be reflective, meaning that the measurement items are a reflection of the construct. Many times, though, the nature of the construct is not reflective, but rather formative. Formative constructs occur when the items describe and define the construct rather than vice versa. In this research, we examine whether formative constructs are indeed being mistaken for reflective constructs by information systems researchers. By examining complete volumes of MIS Quarterly and Information Systems Research over the last 3 years, we discovered that a significant number of articles have indeed misspecified formative constructs. For scientific results to be valid, we argue that researchers must properly specify formative constructs. This paper discusses the implications of different patterns of common misspecifications of formative constructs on both Type I and Type II errors. To avoid these errors, the paper provides a roadmap to researchers to properly specify formative constructs. We also discuss how to address formative constructs within a research model after they are specified.

The issue of whether IS positivist researchers were sufficiently validating their instruments was initially raised fifteen years ago and rigor in IS research is still one of the most critical scientific issues facing the field. Without solid validation of the instruments that are used to gather data on which findings and interpretations are based, the very scientific basis of the profession is threatened. This study builds on four prior retrospectives of IS research that conclude that IS positivist researchers continue to face major barriers in instrument, statistical, and other forms of validation. It goes beyond these studies by offering analyses of the state-of-the-art of research validities and deriving specific heuristics for research practice in the validities. Some of these heuristics will, no doubt, be controversial. But we believe that it is time for the IS academic profession to bring such issues into the open for community debate. This article is a first step in that direction. Based on our interpretation of the importance of a long list of validities, this paper suggests heuristics for reinvigorating the quest for validation in IS research via content/construct validity, reliability, manipulation validity, and statistical conclusion validity. New guidelines for validation and new research directions are offered.

autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

On 5 February 2020, in Yokohama, Japan, a cruise ship hosting 3,711 people underwent a 2-week quarantine after a former passenger was found with COVID-19 post-disembarking. As at 20 February, 634 persons on board tested positive for the causative virus. We conducted statistical modelling to derive the delay-adjusted asymptomatic proportion of infections, along with the infections' timeline. The estimated asymptomatic proportion was 17.9% (95% credible interval (CrI): 15.5-20.2%). Most infections occurred before the quarantine start.

odological concerns. This review is decidedly mixed. The book begins with a discussion of social interaction and observation and quickly moves into a classic study of interaction, Parten's (1932) study of social interaction in children. The issue of sequence versus marginal summation is brought in with argument favoring retention of sequence at all times until independence from sequence is established. Some discussion of the observation-theory issue in the philosophy of science is brought in (see Willson, 1987, for some commentary on this). The second chapter is devoted to developing a coding scheme for observation. It is here that the lack of attention to the reading literature is apparent. Frick and Semmel's (1978) paper is widely cited for development of coding schemes in reading. Researchers in this field have had to grapple with extremely complex issues. Flanders' (1960) work is often cited in education as an early effort, but does not appear in Bakeman and Gottman's book at all. Frick and Semmel pointed researchers to important considerations such as inference level in observation and its development in the coding scheme. This issue is not given nearly the space it requires, especially with the research showing the problems of reliability with highinference observation. The chapter ends with some examples of coding schemes but little practical advice on how to set up the coding schemes and the definitional menus that are absolutely required when several observers other than the developer are to use the system. Chapter 3 discusses recording methods but is notable for its lack of detail

This study extends the TAM model (Davis 1989) and the SPIR addendum (Straub 1994) by adding gender to an IT diffusion model. The technology acceptance model (TAM) has been widely studied in IS research as an explanation of the use of information systems across IS types and nationalities. While this line of research has found significant cross-cultural differences, it has ignored the effects of gender, even though in socio-linguistic research, gender is a fundamental aspect of culture. Indeed, socio-linguistic research has shown that men tend to focus discourse on hierarchy and independence, while women focus on intimacy and solidarity. This literature provides a solid grounding for conceptual extensions to the IT diffusion research and the technology acceptance model. Testing gender differences that might relate to beliefs and use of computer-based media, this study sampled 392 female and male responses via a cross-sectional survey instrument. The sample drew from comparable groups of knowledge workers using e-mail systems in the airline industry in North America, Asia, and Europe. Study findings indicate that women and men differ in their perceptions but not use of e-mail. These findings suggest that researchers should include gender in IT diffusion models along with other cultural effects. Managers and co-workers, moreover, need to realize that the same mode of communication may be perceived differently by the sexes, suggesting that more favorable communications environments might be created, environments that take into account not only organizational contextual factors, but also the gender of users. The creation of these environments involves not only the actual deployment of communication media, but also organizational training on communications media.

Research in social psychology has extensively referenced and used Fishbein and Ajzen's theory of reasoned action to predict and understand motivational influences on behavior Recently Ajzen has proposed an extension of the theory by including perceptions of behavioral control as an additional predictor of intentions and behavior. The present research compared Ajzen's theory of planned behavior with the theory of reasoned action for 10 behaviors chosen to represent a range with respect to control over performing the behavior. he results indicate that inclusion of perceived behavioral control enhances the prediction of behavioral intention and behavior Consistent with the theory of planned behavior, the effects of perceived behavioral control on a target behavior are most vivid when the behavior presents some problem with respect to control.

Companies are facing increasing pressure to both maintain profitability and behave in socially responsible ways, yet researchers have provided little information on how corporate social responsibility impacts profitability. This paper reports the findings from in‐depth interviews of consumers to determine their views concerning the social responsibilities of companies. A typology of consumers whose purchasing behavior ranges from unresponsive to highly responsive to corporate social responsibility was developed from the analysis.