Omnichannel Business

The widespread diffusion of digital technologies along with evolving consumer behaviors and requirements have fostered the emergence of omnichannel businesses, i.e., firms that can exploit integrated processes and information systems to realize a seamless and consistent consumer experience across a plenitude of digital and physical channels. To date, omnichannel research has been cluttered and characterized by significant terminological ambiguity that creates unnecessary challenges for researchers and markeeters trying to navigate and advance research and practice in this area. This fundamentals article seeks to address this problem by presenting a definition of omnichannel business that is grounded in its unique characteristics involving technology, organizational, and market perspectives and clearly distinguishes omnichannel from other terms, such as multi-channel or cross-channel. We leverage this conceptual clarity to analyze and structure the previous research on omnichannel business and conclude with an integrated framework that signifies fields of interest for future omnichannel business research.

Designing business model taxonomies – synthesis and guidance from information systems research

Classification is an essential approach in business model research. Empirical classifications, termed taxonomies, are widespread in and beyond Information Systems (IS) and enjoy high popularity as both stand-alone artifacts and the foundation for further application. In this article, we focus on the study of empirical business model taxonomies for two reasons. Firstly, as these taxonomies serve as a tool to store empirical data about business models, we investigate their coverage of different industries and technologies. Secondly, as they are emerging artifacts in IS research, we aim to strengthen rigor in their design by illustrating essential design dimensions and characteristics. In doing this, we contribute to research and practice by synthesizing the diffusion of business model taxonomies that helps to draw on the available body of empirical knowledge and providing artifact-specific guidance for building taxonomies in the context of business models.

Immunizing with information – Inoculation messages against conversational agents’ response failures

Conversational agents (CAs) are often unable to provide meaningful responses to user requests, thereby triggering user resistance and impairing the successful diffusion of CAs. Literature mostly focuses on improving CA responses but fails to address user resistance in the event of further response failures. Drawing on inoculation theory and the elaboration likelihood model, we examine how inoculation messages, as communication that seeks to prepare users for a possible response failure, can be used as an alleviation mechanism. We conducted a randomized experiment with 558 users, investigating how the performance level (high or low) and the linguistic form of the performance information (qualitative or quantitative) affected users’ decision to discontinue CA usage after a response failure. We found that inoculation messages indicating a low performance level alleviate the negative effects of CA response failures on discontinuance. However, quantitative performance level information exhibits this moderating effect on users’ central processing, while qualitative performance level information affected users’ peripheral processing. Extending studies that primarily discuss ex-post strategies, our results provide meaningful insights for practitioners.

More than a snapshot: dynamic value-in-use emergence in e-services

Supporting consumers’ value-in-use (ViU) emergence throughout a usage process has become increasingly challenging as, in today’s environment, usage has shifted from discrete events to continuous e-service interactions. Although researchers acknowledge that ViU is dynamic and evolves over time, most studies treat it as a static concept. Using the empirical context of language learning applications, the authors adopt a dynamic perspective on e-service ViU and extend it with regulatory mode theory using a qualitative approach. By applying the underlying functions of self-regulation: locomotion and assessment, the authors investigate how ViU emerges throughout a usage process and establish an eight-stage ViU emergence process, ranging from initial trigger to termination. By examining a consumer’s usage, assessments, and movements, practitioners can pinpoint a consumer’s location in the ViU emergence process and take appropriate measures to further promote ViU emergence in e-services.

On the stress potential of videoconferencing: definition and root causes of Zoom fatigue

As a consequence of lockdowns due to the coronavirus disease (COVID-19) and the resulting restricted social mobility, several billion people worldwide have recently had to replace physical face-to-face communication with computer-mediated interaction. Notably, the adoption rates of videoconferencing increased significantly in 2020, predominantly because videoconferencing resembles face-to-face interaction. Tools such as Zoom, Microsoft Teams, and Cisco Webex are used by hundreds of millions of people today. Videoconferencing may bring benefits (e.g., saving of travel costs, preservation of environment). However, prolonged and inappropriate use of videoconferencing may also have an enormous stress potential. A new phenomenon and term emerged, Zoom fatigue, a synonym for videoconference fatigue. This paper develops a definition for Zoom fatigue and presents a conceptual framework that explores the major root causes of videoconferencing fatigue and stress. The development of the framework draws upon media naturalness theory and its underlying theorizing is based on research published across various scientific fields, including the disciplines of both behavioral science and neuroscience. Based on this theoretical foundation, hypotheses are outlined. Moreover, implications for research and practice are discussed.

Iterative uncertainty reduction in multi-actor smart service innovation

Smart service innovation is the process of reconfiguring resources, structures, and value co-creation processes in service systems that result in novel data-driven service offerings. The nature of such offerings requires the involvement of multiple actors, which has been investigated by a few studies only. In particular, little is known about the multiple actors’ efforts to manage uncertainty in the process of establishing smart service systems. Empirically grounded in data from 25 interviews with industry experts, we explore how organizations act and interact in smart service innovation processes. For our data analysis, we adopt a microfoundational view to derive a theoretical model that conceptualizes actor engagement as a microfoundation for iterative uncertainty reduction in the actor-to-actor network of the smart service system. Our study contributes to information systems research on service systems engineering and digital transformation by explaining smart service innovation from both a multi-actor and a multi-level perspective, drawing on service-dominant (S-D) logic and microfoundations as well-established theoretical lenses.