Understanding Crowdsourcing Contest Fitness Strategic Decision Factors and Performance: An Expectation-Confirmation Theory Perspective

Contest-based intermediary crowdsourcing represents a powerful new business model for generating ideas or solutions by engaging the crowd through an online competition. Prior research has examined motivating factors such as increased monetary reward or demotivating factors such as project requirement ambiguity. However, problematic issues related to crowd contest fitness have received little attention, particularly with regard to crowd strategic decision-making and contest outcomes that are critical for success of crowdsourcing platforms as well as implementation of crowdsourcing models in organizations. Using Expectation-Confirmation Theory (ECT), we take a different approach that focuses on contest level outcomes by developing a model to explain contest duration and performance. We postulate these contest outcomes are a function of managing crowdsourcing participant contest-fitness expectations and disconfirmation, particularly during the bidding process. Our empirical results show that contest fitness expectations and disconfirmation have an overall positive effect on contest performance. This study contributes to theory by demonstrating the adaptability of ECT literature to the online crowdsourcing domain at the level of the project contest. For practice, important insights regarding strategic decision making and understanding how crowd contest-fitness are observed for enhancing outcomes related to platform viability and successful organizational implementation

Siri, Alexa, and Other Digital Assistants: A Study of Customer Satisfaction With Artificial Intelligence Applications

Siri, Alexa, and other digital assistants are rapidly becoming embraced by consumers and the adoption is projected to grow from 390 million to 1.8 billion for the period of 2015 to 2021. Digital assistants are offering benefits to consumers while also proving to be a disruptive technology for businesses. Coupling digital assistants with other artificial intelligence technologies offers the potential to transform companies by creating more efficient business processes, automating complex tasks, and improving the customer service experience. Businesses have begun integrating this technology into their operations with the expectation of achieving significant productivity gains. Customer satisfaction has been discussed extensively throughout marketing literature. Yet, there is little empirical evidence of customer satisfaction with digital assistants. This study used PLS-SEM to analyze 244 survey responses obtained from a cross-section of consumers. Using the Expectations Confirmation Theory as its foundation, the study identified that expectations and confirmation of expectations substantially explained customer satisfaction with digital assistants. For practice, the study provides guidance which allows firms to prioritize marketing and managerial activities. Firms should focus priorities on assisting digital assistant users to become aware of new skill capabilities while also providing relevant examples of how these skills can be used to meet user needs. In addition, priorities should be focused on assisting users with understanding how the average person can use digital assistants to perform more than just mundane tasks with relative ease. These priorities were identified as areas of high importance for customer satisfaction and require performance improvements

Post-Acceptance of Electronic Medical Records: Evidence from a Longitudinal Field Study

Many studies investigating post-acceptance of electronic medical records (EMR) assume that healthcare professionals exclusively base their continuance behavior on reasoned actions. While rational considerations certainly affect the intention to use an EMR, it does not fully explain the definitive user continuance behavior. Evidence exists that also subliminal effects such as habits and emotions play an important role. Consequently, we propose to investigate post-acceptance of EMR applying three different, but complementary views: (i) continuance behavior as result of reasoned actions, (ii) continuance behavior as result of emotional responses, and (iii) continuance behavior as result of habitual responses. The results from a longitudinal field study showed that automatic behavior, enabled by sufficient facilitating conditions and a good task-technology-fit, as well as positive emotions considerably affected healthcare professionals EMR continuance behavior. It also showed that a user’s computer literacy level didn’t play a significant role regarding the post-acceptance behavior

An Integrated Temporal Model of Belief and Attitude Change: An Empirical Test With the iPad

Bhattacherjee and Premkumar (2004) propose a temporal model of belief and attitude change to understand fluctuating patterns of information technology (IT) usage. However, they overlook the role of perceived enjoyment in the process of temporal IT usage. Perceived enjoyment has become an increasingly important part of how consumers assess technology. Thus, we build on Bhattacherjee and Premkumar’s model (BP model) and propose a new model by investigating the comparative role of perceived usefulness (PU) and perceived enjoyment (PE) for explaining temporal changes in users’ beliefs and attitudes toward IT usage. We name our proposed model the integrated temporal model (ITM). Through an empirical study of iPad usage in a classroom setting at three different stages, we found that 1) the effect of PE on PU was stronger at the pre-usage (vs. post-usage) stage and that its effect was stronger at the initial-usage (vs. later-usage) stage; 2) while PE has a stronger effect than PU on attitude at both pre-usage and initial-usage stages, that was not the case at the later-usage stage; instead, the effect of PU on attitude was stronger at the later-usage (vs. initial-usage) stage; 3) the effect of disconfirmation on modified PU and PE was stronger at the initial (vs. later) stage, while the effect of PU and PE expectation on modified PU and PE was weaker at the initial (vs. later) stage. Our study extends the BP model to IT with hedonic elements (i.e., the iPad) and is the first of its kind to empirically examine the combined and relative impact of PU and PE on the temporal usage of IT with hedonic elements in the classroom setting

User Satisfaction Research in Information Systems: Historical Roots and Approaches

User satisfaction with information systems (IS) is considered an important indicator of information systems success and has been the subject of numerous research studies since the field’s inception. In this paper, we review the user satisfaction research in the IS field. We discuss the roots of user satisfaction research as it pertains to satisfaction studies in marketing research and how these studies have been used to inform the IS context. We also discuss how the study of user satisfaction and use of the construct in IS research has evolved and matured over time. Finally, we discuss antecedents and outcomes of user satisfaction identified in IS research and provide suggestions for future research

Measuring the impact of enjoyment on the usage continuance intention

Dissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Marketing Research e CRMThis study examines the behavioural intentions of video-on-demand (VoD) consumers to continue using the service and further examines the influence of enjoyment over the intention to continue to use. To explore the usage continuance, we adopt the expectation confirmation model (ECM) for information technology and integrate it with the hedonic system adoption model. Specifically, we measure the influence of enjoyment over the behavioural intention to continue to use. The results suggest that satisfaction is the greatest predictor of the usage continuance intention and enjoyment strongly impacts satisfaction. In fact, our model explains 48.1% of the variance of the usage continuance and 53.8% of the satisfaction

Information Systems Research Themes: A Seventeen-year Data-driven Temporal Analysis

Extending the research on our discipline’s identity, we examine how the major research themes have evolved in four top IS journals: Management Information Systems Quarterly (MISQ), Information Systems Research (ISR), Journal of the Association for Information Systems (JAIS), and Journal of Management Information Systems (JMIS). By doing so, we answer Palvia, Daneshvar Kakhki, Ghoshal, Uppala, and Wang’s (2015) call to provide continuous updates to the research trends in IS due to the discipline’s dynamism. Second, building on Sidorov, Evangelopoulos, Valacich, and Ramakrishnan (2008) we examine temporal trends in prominent research streams over the last 17 years. We show that, as IS research evolves over time, certain themes appear to endure the test of time, while others peak and trough. More importantly, our analysis identifies new emergent themes that have begun to gain prominence in IS research community. Further, we break down our findings by journal and show the type of content that they may desire most. Our findings also allow the IS research community to discern the specific contributions and roles of our premier journals in the evolution of research themes over time

How Team Cohesion Leads to Attitude Change in the Context of ERP Learning

Universities and corporate training programs have realized the importance of enterprise resource planning (ERP) systems in the business world and have incorporated such systems into their curricula and training. Although there is a rich body of literature on ERP, extant research remains relatively scant in examining team-based ERP learning. Drawing upon attitude change literature and expectation-confirmation theory, this study presents an Attitude Change Model of Team-Based ERP Learning. In particular, this study focuses on how team cohesion influences satisfaction and attitude change in ERP learning. The results of structural equation modeling support all but one hypothesis. The study concludes with discussions and implications for researchers, educators, and practitioners

User Compensation as a Data Breach Recovery Action: An Investigation of the Sony PlayStation Network Breach

Drawing on expectation confirmation research, we develop hypotheses regarding the effect of compensation on key customer outcomes following a major data breach and consequent service recovery effort. Data were collected in a longitudinal field study of Sony customers during their data breach in 2011. A total of 144 customers participated in the two-phase data collection that began when the breach was announced and concluded after reparations were made. Using polynomial modeling and response surface analysis, we demonstrate that a modified assimilation–contrast model explained perceptions of service quality and continuance intention and a generalized negativity model explained repurchase intention. The results of our work contribute to research on data breaches and service failure by demonstrating the impacts of compensation on customer outcomes. We discuss theoretical and practical implication

User Satisfaction with Wearables

This study investigates user satisfaction with wearable technologies. It proposes that the integration of expectation confirmation theory with affordance theory sheds light on the sources of user’s (dis)confirmation when evaluating technology performance experiences and explains the origins of satisfaction ratings. A qualitative and quantitative analysis of online user reviews of a popular fitness wristband supports the research model. Since the band lacks buttons and numeric displays, users need to interact with the companion software to obtain the information they need. Findings indicate that satisfaction depends on the interaction’s quality, the value of digitalizing physical activity, and the extent to which the informational feedback meets users’ needs. Moreover, the results suggest that digitalizing physical activity has different effects for different users. While some appreciate data availability in general regardless of their accuracy, those who look for precision do not find such quantification useful. Thus, their evaluative judgments depend on the wearable system’s actual performance and the influence that the feedback has on their pursuit of their fitness goals. These results provide theoretical and practical contributions to advance our understanding of wearable technologies