Venkatesh, V., Thong, J.Y.L., Spohrer, K., Chan, F.K.Y., Hoehle, H., Arora, A., and Raman, S. “Examining the Post-adoptive Use of Agile Systems Development Methods in Software Development Teams: A Social Exchange Perspective,” MIS Quarterly, forthcoming.
Venkatesh, V., Cheung, C.M.K., Davis, F.D., and Lee, Z.W.Y. “Cyberslacking in the Workplace: Antecedents and Effects on Job Performance,” MIS Quarterly, forthcoming. https://doi.org/10.25300/misq/2022/14985
Employees' nonwork use of information technology (IT), or cyberslacking, is of growing concern due to its erosion of job performance and other negative organizational consequences. Research on cyberslacking antecedents has drawn on diverse theoretical perspectives, resulting in a lack of cohesive explanation of cyberslacking. Further, prior studies generally overlooked IT-specific variables. To address the cyberslacking problems in organizations and research gaps in the literature, we used a combination of a literature-based approach and a qualitative inquiry to develop a model of cyberslacking that includes a 2x2 typology of antecedents. The proposed model was tested and supported in a three-wave field study of 395 employees in a Fortune-100 US organization. For research, this work organizes antecedents from diverse research streams and validates their relative impact on cyberslacking, thus providing a cohesive theoretical explanation of cyberslacking. This work also incorporates contextualization (i.e., IT-specific factors) into theory development and enriches IS literature by examining the nonwork aspects of IT use and their negative consequences to organizations. For practice, the results provide practitioners with insights into nonwork use of IT in organizations, particularly on how they can take organizational action to mitigate cyberslacking and maintain employee productivity.
Goyal, S., Venkatesh, V., and Shi, X. “Role of Users’ Status Quo on Continuance Intentions,” Information & Management, 2022, 103686. https://doi.org/10.1016/j.im.2022.103686
Accelerated technological innovations have led to shorter product life cycles. Yet, consumers often decide not to discard the incumbent technology in favor of a new technology. To explain this decision-making process, a rich research stream has investigated subconscious motivations. However, there is little understanding of the role of conscious motivations and, more importantly, their interplay with subconscious motivations in their decisions. Using the value appreciation perspective, we controlled for the predictors of the second version of the unified theory of acceptance and use of technology (UTAUT2) and leverage prospect theory to enrich our understanding of users’ continuance intentions. We conceptualize status quo preference with two new constructs—namely, the value of status quo and users’ commitment to status quo—and integrate them with other known predictors of continuance intentions (related to an incumbent system)—i.e., trust and habit. We empirically test our model in two studies. Study 1 was conducted among 2,096 users of smartphones in Hong Kong. Study 2 reports longitudinal data, across three waves of data collection over a period of six months, from 240 analysts introduced to a new technology to support their work in a large financial services organization. The findings support our model and suggest that (1) users’ status quo preferences significantly determine continuance intentions; and (2) trust and habit have an effect on users’ status quo preferences. These findings advance knowledge on continuance intentions by integrating the effects of users’ conscious and subconscious intentions to continue using the incumbent technology.
Venkatesh, V., Weng, Q., Maruping, L.M., and Rai, A. “Guidelines for the Development of Three-level Models: Bridging Levels of Analysis and Integrating Contextual Influences in IS Research” Journal for the Association of Information Systems, forthcoming.
The use of multilevel analysis has steadily increased in information systems (IS) research. Many studies are doing an admirable job of integrating two-level models into their examination of IS phenomena. However, two-level models are limited in how well they enable researchers to (1) more explicitly incorporate context into theory development and testing and (2) bridge the existing gap between micro- and macro-level research by focusing on intervening mechanisms that link hierarchically distal levels of analysis. Three-level models have emerged as a potential way to address these limitations. While literature has clearly outlined the mechanics of how to estimate three-level models, there is very little, if any, guidance on when and how to integrate the use of such models with theory development. Consequently, IS researchers have little guidance to inform their decisions about integrating the use of three-level models with their theory development and testing. In this article, we identify the circumstances under which IS researchers should consider the use of three-level models, develop guidelines about how to map the use of three-level model estimation to the theoretical objectives, and provide an illustration of how to implement the guidelines.
Windeler, J., Maruping, L.M., Venkatesh, V., and Weng, Q. “Bridge the Gap or Mind the Gap? The Role of Leaders and Technology in Configurationally Dispersed Teams,” Information & Management, forthcoming.
Haag, S., Eckhardt, A., and Venkatesh, V. “Deviant Affordances: When Tensions, Deadlocks and Noncompliance Generate Performance,” MIS Quarterly (46:4), 2023, 2111-2162. https://doi.org/10.25300/misq/2022/14340
Novel information technologies (ITs), such as mobile devices or third-party cloud services, offer users an increasing variety of action possibilities, i.e., affordances. Organizational IT policies, however, often specify their actualization, i.e., turning those affordances into action, as undesired. Organizations face the challenge that their employees, to reach their goals, still frequently take advantage of those affordances by using those very ITs and thereby deviate from the IT policies. Although prior work has extensively studied how goal-oriented users actualize affordances that are associated with outcomes that support organizational goals, little attention has been paid to the structures, mechanisms, and conditions underlying affordances that deviate from organizational IT policies. We conceptualize those affordances as deviant affordances. Leveraging the orders of change framework and using a multimethod research design integrating interview and experimental studies, we identify three key mechanisms underlying deviant affordances—i.e., tension, deadlock, and actualization mechanisms—that can link together to produce a deviant outcome supporting the individual goal and an organizational goal. Our work explains the importance of users’ perceived deadlock in stimulating the generation of deviant outcomes that support the organizational goals through improving task, contextual, and innovative job performance.
Venkatesh, Speier-Pero, C., Aljafari, R., and Bala, H. “IT Use and Job Outcomes: A Longitudinal Field Study of Technology Contingencies,” Journal of the AIS, (23:5), 2022, 1184-1210. https://doi.org/10.17705/1jais.00760
As information technology (IT) continues to be an integral yet evolving component in work settings, organizations need to ensure that they realize value from IT. Prior studies examining the postadoption consequences of IT use in terms of employee job outcomes have been inconclusive with respect to the magnitude and direction of these impacts—i.e., the positive, negative, and nonsignificant impacts of IT use on job outcomes. The question of under what conditions IT use leads to favorable job outcomes over time thus remains largely unanswered. We develop a model of IT-related contingencies that integrates core constructs from the IT adoption research with two key job outcomes: job satisfaction and job performance. We hypothesize that in the post-adoption phase, technology-job fit is a key moderator of the relationships between IT use for supporting sales operations and job outcomes. Further, we suggest a theoretical extension of the classical predictors of IT adoption—perceived usefulness and perceived ease of use—as we expect them to moderate the effect of IT use on job performance over time. We tested our model in a longitudinal field study among 295 field sales personnel over a 24-month period. We found that although IT use had a negative effect on job satisfaction during the post-adoption phase, this effect was moderated by technology-job fit such that the negative effect was significantly attenuated by technology-job fit. We also found that perceived usefulness, perceived ease of use, and technology-job fit enhanced the positive effect of IT use on job performance. Our findings offer insights into the mechanisms and conditions related to the post-adoption impacts of IT use on key job outcomes.
Venkatesh, V., Speier-Pero, C., and Schuetz, S.W. “Why Do People Shop Online? A Comprehensive Framework of Consumers’ Online Shopping Intentions and Behaviors,” Information Technology & People (35:5), 2022, 1590-1620. https://doi.org/10.1108/itp-12-2020-0867
Purpose – Consumer adoption of online shopping continues to increase each year. At the same time, online retailers face intense competition and few are profitable. This suggests that businesses and researchers still have much to learn regarding key antecedents of online shopping adoption and success. Based on extensive past research that has focused on the importance of various online shopping antecedents, this work seeks to provide an integrative, comprehensive nomological network. Design/methodology/approach – The authors employ a mixed-methods approach to develop a comprehensive model of consumers online shopping behavior. To that end, in addition to a literature review, qualitative data are collected to identify a broad array of possible antecedents. Then, using a longitudinal survey, the model of consumer shopping intentions and behaviors is validated among 9,992<br/>consumers. Findings – The authors identified antecedents to online shopping related to culture, demographics, economics, technology and personal psychology. Our quantitative analysis showed that the main drivers of online shopping were congruence, impulse buying behavior, value consciousness, risk, local shopping, shopping enjoyment, and browsing enjoyment. Originality/value – The validated model provides a rich explanation of the phenomenon of online shopping that integrates and extends prior work by incorporating new antecedents.
Venkatesh, V. and Goyal, S. “Impact of an Enterprise System Implementation on Job Outcomes: Challenging the Linearity Assumption,” Journal of Management Information Systems (39:1), 2022, 6-40. https://doi.org/10.1080/07421222.2021.2023405
Organizations usually have difficulty adjusting to technology-enabled changes. Recent research has examined the interaction between technology and the key job outcomes of employees. But this research stream has done so using a linear lens even though this interplay has been recognized to be dynamic and complex. We challenge here this linearity assumption. We theorized that enterprise system (ES) use influences post-implementation job scope, and the change from pre- to post-implementation job scope perceptions will have a complex effect on job outcomes that are best captured by a polynomial model. Drawing on the anchoring-and-adjustment perspective in decision-making research, our polynomial model highlights the dynamic nature of employee reactions to changes in job scope brought about by an ES implementation that cannot be captured by traditional linear models. We found support for our model using data collected in a longitudinal field study from 2,794 employees at a telecommunications firm over a period of 12 months. Our findings highlight the key role an ES implementation can have in changing the nature of jobs and how those changes can, in turn, drive job performance and job satisfaction. This research also extends classical job characteristics research by arguing for a more complex relationship between the scope and outcomes of technology-supported jobs.
Raman, R., Aljafari, R., Venkatesh, V., and Richardson, V. “Mixed-Methods Research in the Age of Analytics, an Exemplar Leveraging Sentiments from News Articles to Predict Firm Performance,” International Journal of Information Management (64), 2022, 102451. https://doi.org/10.1016/j.ijinfomgt.2021.102451
Investors and companies have always aspired to make informed investment decisions by using diverse information sources. With the explosion of information sources on the web and emergence of predictive analytics, many investors moved beyond traditional financial measures, as key predictors of firm performance, to textual content from analysts’ reports. Empirical research suggests that these information sources complement each other by providing a clear picture of firm performance, but remains silent on the role of additional textual content that continues to emerge and reach more potential investors on the web. We build on this line of research to examine the effect of textual content from business journals in conjunction with summary measures on cumulative abnormal returns. We use sentiment analysis with machine learning and econometrics methods to examine content extracted from textual articles about S&P 500 index companies that are published in the Wall Street Journal (years 2013–2016). Textual analysis of business journals in conjunction with quantitative measures revealed direct and interaction effects on abnormal returns over time. We also tested for robustness by replicating the analysis with different variable operationalization and observe consistent patterns. Relative to positive sentiments, negative sentiments have more profound effects on cumulative abnormal returns. The effect of positive sentiments becomes weaker when past quantitative measures are high. As information sources continue to emerge on the web, this work makes key contributions to the practice of sentiment analysis in financial markets.