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One for all, all for one
(2022)
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.
Algorithmic management
(2022)
This study seeks to explain the major drivers of trading activity in commodity futures markets and gage the effect of trading activity on commodity prices. Rather than concentrating on a specific commodity subgroup or a particular type of commodity traders, we provide an extensive overview of the behavior across all market participants and their influence on commodity prices by using a broad set of commodity futures contracts. Although commodity futures returns show co-movement with financial fundamentals (U.S. dollar index, equity, and bond markets), based on the Disaggregated Commitment of Traders Report (DCOT), this relationship cannot be attributed to trading activity. Pricing in commodity markets can be predominantly attributed to hedgers and influential speculators (money managers), whereas small speculators (nonreportable traders) are crucial to some soft commodity futures similar to dealers in metals commodity futures. Furthermore, we find limited cases where inventory changes exert a sizable influence on position changes of DCOT traders.
We examine the determinants of the disclosure of value-based (VB) performance measures in Germany. We argue that firms are more likely to disclose VB performance measures when information asymmetry is greater, as greater information asymmetry means firms have a greater need to credibly signal a shareholder value orientation. Using a hand-collected dataset of German listed firms covering 1,528 firm-years from 2004 to 2011, we demonstrate that firms are more likely to disclose a VB performance measure if the free float is larger than the blocking minority and also, when firms are large, if they have high foreign sales to total sales ratios and are not cross-listed internationally. Our results indicate that German firms use VB performance measures to improve investor communication and to substantiate their shareholder value orientation. Our results should be interpreted against a background of increased shareholder value orientation and sophisticated cost accounting in German firms.
In this study, we contribute to the scholarly conversation on firm-level business model changes following a neoconfigurational approach. By exploring configurations of business model changes over time, we add the direction of business model changes-namely business model convergence or divergence-as a vital avenue to the business model innovation literature. We identify necessary business model convergence and divergence recipes in a sample of N = 217 strategic dyadic alliances. Firstly, technological proximity emerges as a single precondition to both converging and diverging business models. Secondly, business models between competitors either converge through complementarities or tend not to change relative to each other. Thirdly, equity participation enables business model divergence through co-specialization. We conclude with a discussion of business model trajectories and future research directions.
Aim Hospitals noticeably struggle with maintaining hundreds of IT systems and applications in compliance with the latest IT standards and regulations. Thus, hospitals search for efficient opportunities to discover and integrate useful digital health innovations into their existing IT landscapes. In addition, although a multitude of digital innovations from digital health startups enter the market, numerous barriers impede their successful implementation and adoption. Against this background, the aim of this study was to explore typical digital innovation barriers in hospitals, and to assess how a hospital data management platform (HDMP) architecture might help hospitals to extract such innovative capabilities. Subject and methods Based on the concept of organizational ambidexterity (OA), we pursued a qualitative mixed-methods approach. First, we explored and consolidated innovation barriers through a systematic literature review, interviews with 20 startup representatives, and a focus group interview with a hospital IT team and the CEO of an HDMP provider. Finally, we conducted a case-study analysis of 36 digital health startups to explore and conceptualize the potential impact of DI and apply the morphological method to synthesize our findings from a multi-level perspective. Results We first provide a systematic and conceptual overview of typical barriers for digital innovation in hospitals. Hereupon, we explain how an HDMP might enable hospitals to mitigate such barriers and extract value from digital innovations at both individual and organizational level. Conclusion Our results imply that an HDMP can help hospitals to approach organizational ambidexterity through integrating and maintaining hundreds of systems and applications, which allows for a structured and controlled integration of external digital innovations.
Creative thinking is an indispensable cognitive skill that is becoming increasingly important. In the present research, we tested the impact of games on creativity and emotions in a between-subject online experiment with four conditions (N = 658). (1) participants played a simple puzzle game that allowed many solutions (priming divergent thinking); (2) participants played a short game that required one fitting solution (priming convergent thinking); (3) participants performed mental arithmetic; (4) passive control condition. Results show that divergent and convergent creativity were higher after playing games and lower after mental arithmetic. Positive emotions did not function as a mediator, even though they were also heightened after playing the games and lower after mental arithmetic. However, contrary to previous research, we found no direct effect of emotions, creative self-efficacy, and growth- vs. fixed on creative performance. We discuss practical implications for digital learning and application settings.
Time for change?
(2022)
Purpose:
This study aims to provide probable future developments in the form of holistic scenarios for business negotiations. In recent years, negotiation research did not put a lot of emphasis on external changes. Consequently, current challenges and trends are scarcely integrated, making it difficult to support negotiation practice perspectively.
Design/methodology/approach:
This paper applies the structured, multi-method approach of scenario analysis. To examine the future space of negotiations, this combines qualitative and quantitative measures to base our analysis on negotiation experts’ assessments, estimations and visions of the negotiation future.
Findings:
The results comprise an overview of five negotiation scenarios in the year 2030 and of their individual drivers. The five revealed scenarios are: digital intelligence, business as usual, powerful network – the route to collaboration, powerful network – the route to predominance and system crash.
Originality/value:
The scenario analysis is a suitable approach that enables to relate various factors of the negotiation environment to negotiations themselves and allows an examination of future changes in buyer–seller negotiations and the creation of possible future scenarios. The identified scenarios provide an orientation for business decisions in the field of negotiation.
The number of alternative suppliers is widely considered to be the most important source of power in supply chains. It is common knowledge that a buying company benefits from an increasing number of suppliers until a marginalization effect occurs. Consequently, a cost-benefit optimum must exist but has not been analyzed in a sufficiently differentiated manner in the literature. Particularly, research has not taken the variety of product groups, which is reflected by the degree of innovation, into account. Using a two-way analysis of variance, this study identifies the cost-benefit optimum for the number of suppliers and analyzes the moderating role of the degree of innovation. The analysis is based on real automotive business-to-business negotiation data. The results reveal that a cost-benefit optimum is reached at a number of three suppliers at the most. Furthermore, the impact of the number of suppliers is higher for innovative products than for more functional products. Purchasing managers can use the findings to determine the optimal size of their supplier choice set.