AI-Based Information Systems Buxmann, Peter; Hess, Thomas; Thatcher, Jason Bennett
Business & information systems engineering,
02/2021, Letnik:
63, Številka:
1
Journal Article
Business Models Veit, Daniel; Clemons, Eric; Benlian, Alexander ...
Business & information systems engineering,
02/2014, Letnik:
6, Številka:
1
Journal Article
Recenzirano
The business model concept, although a relatively new topic for research, has garnered growing attention over the past decade. Whilst it has been robustly defined, the concept has so far attracted ...very little substantive research. In the context of the wide-spread digitization of businesses and society at large, the logic inherent in a business model has become critical for business success and, hence, a focus for academic inquiry. The business model concept is identified as the missing link between business strategy, processes, and Information Technology (IT). The authors argue that the BISE community offers distinct and unique competencies (e.g., translating business strategies into IT systems, managing business and IT processes, etc.) that can be harnessed for significant research contributions to this field. Within this research gap three distinct streams are delineated, namely, business models in IT industries, IT enabled or digital business models, and IT support for developing and managing business models. For these streams, the current state of the art, suggest critical research questions, and suitable research methodologies are outlined.
With the rise of machine learning (ML), humans are no longer the only ones capable of learning and contributing to an organization's stock of knowledge. We study how organizations can coordinate ...human learning and ML in order to learn effectively as a whole. Based on a series of agent-based simulations, we find that, first, ML can reduce an organization's demand for human explorative learning that is aimed at uncovering new ideas; second, adjustments to ML systems made by humans are largely beneficial, but this effect can diminish or even become harmful under certain conditions; and third, reliance on knowledge created by ML systems can facilitate organizational learning in turbulent environments, but this requires significant investments in the initial setup of these systems as well as adequately coordinating them with humans. These insights contribute to rethinking organizational learning in the presence of ML and can aid organizations in reallocating scarce resources to facilitate organizational learning in practice.
•Communication Visibility Theory shows enterprise social networks’ (ESNs) benefits.•We lend credence to Communication Visibility Theory’s validity across contexts.•Meta-knowledge in ESNs not only ...develops in the long but also in the short-run.•Managers can develop more meta-knowledge in ESNs than non-managers do.
Employees’ knowledge about their coworkers’ knowledge (i.e., meta-knowledge) is central for organizations to create competitive advantages. According to Communication Visibility Theory, enterprise social networks (ESNs) have the potential to foster long-term formation of meta-knowledge. However, research about this potential is still limited. Using a quantitative study, we improve the understanding of how ESNs facilitate the development of meta-knowledge in three ways: we (1) show that the creation of meta-knowledge through ESNs works across contexts, (2) find that ESNs can lead to rather immediate increases in meta-knowledge, and (3) reveal that managers can gain more meta-knowledge using ESNs than can non-managers.
We propose a conceptual model of acceptance of contact tracing apps based on the privacy calculus perspective. Moving beyond the duality of personal benefits and privacy risks, we theorize that users ...hold social considerations (i.e., social benefits and risks) that underlie their acceptance decisions. To test our propositions, we chose the context of COVID-19 contact tracing apps and conducted a qualitative pre-study and longitudinal quantitative main study with 589 participants from Germany and Switzerland. Our findings confirm the prominence of individual privacy calculus in explaining intention to use and actual behavior. While privacy risks are a significant determinant of intention to use, social risks (operationalized as fear of mass surveillance) have a notably stronger impact. Our mediation analysis suggests that social risks represent the underlying mechanism behind the observed negative link between individual privacy risks and contact tracing apps' acceptance. Furthermore, we find a substantial intention–behavior gap.
•We model CTA acceptance by integrating social considerations into privacy calculus.•A longitudinal study with 589 participants from Germany and Switzerland.•Social risks (fear of mass surveillance) have a stronger impact than privacy risks.•Social risks fully mediate the “privacy risks-CTA use” link.•A substantial intention-behavior gap is revealed, with a nearly 40% dropout rate.
•Validation of a new distributive equity scale for free data-driven services.•Reconceptualization of individual’s perception of these services.•User’s and provider’s net value is related to ...distributive equity perceptions.•The higher distributive equity perceptions the higher user’s satisfaction.•Satisfaction mediates the link between distributive equity and continued use.
Individuals are supposed to perform a privacy risk-benefit analysis when deciding to transact with a free data-driven service provider. Building on equity theory, this article suggests that users incorporate the net value for providers in their trade-off. Based on two pre-studies and an experimental survey study among 200 free data-driven service users, we provide evidence that users’ balance their own net value (benefits minus risks) as well as providers’ net value from monetizing users’ data. This leads to distributive equity perceptions which, in turn, affect users’ satisfaction with the service and thus long-term success of the user-provider-relationship. In this vein, a distributive equity scale for the context of data-driven services is developed. Implications for research, providers and users are discussed.
This papers shows that the management of contractual relationships in IS/IT outsourcing is not only receiving greater attention in academic research, but that it has also moved into focus of ...companies with high outsourcing degrees. This shift of management attention is accompanied by observable changes in IT organizations’ design, revealing an underrepresented but promising research topic. While prior research has predominantly explored single aspects, for example, supplier selection or relationship building, this article takes a more holistic approach on IT supplier relationship management (SRM) with a focus on organizational design. A conceptual framework, covering three core elements of organizational design, strategy, structure and process, guided the multiple case study on IT SRM in five client IT organizations. One key finding from sourcing strategy is that IT organizations have in parts significantly and abruptly reduced their number of suppliers in the last years, a phenomenon typically well known in the automobile industry. With regard to structure, different organizational models are presented, varying upon their degree of centralization and mode of sourcing. The concept of a hybrid (centralized-decentralized) structure, where a central unit fulfills SRM activities, was shown to be the predominant model within our case organizations. Design and potential benefits of this barely examined model are discussed in detail and empirical examples are provided respectively. As a third organizational design component, formal processes and lateral connections are presented as a means to bridge barriers between organizational entities central to IT SRM. Finally, various opportunities for future research are illustrated.
In today's challenging economic climate it is more important than ever for companies to acquire comparable competitive advantage in their market. While previous research has investigated the ...performance measurement of R&D as a whole organization, very little research has been done into the performance management for just the research function itself. This, however, is of particular interest to larger organizations. This paper (1) introduces a framework for performance measurement for industrial research, and (2) presents a set of clusters, representing the content dimension for measuring research organizations. Based on the clusters, we were able to evaluate the extent to which performance measurement in practice in different companies can be compared. We discovered that the clusters follow a particular consistent distribution across organizations when the clusters are ranked by importance. For this empirical analysis, data was collected through in-depth case studies including more than 60 interviews and thorough document analyses.
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