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Although scholars argue that artificial intelligence (AI) represents a tool to potentially smoothen the bullwhip effect in the supply chain, only little research has examined this phenomenon. In this article, the authors conceptualize a framework that allows for a more structured management approach to examine the bullwhip effect using AI. In addition, the authors conduct a systematic literature review of this current status of how management can use AI to reduce the bullwhip effect and locate opportunities for future research.

Guided by the systematic literature review approach from Durach et al. (2017), the authors review and analyze key attributes and characteristics of both AI and the bullwhip effect from a management perspective.

The authors' findings reveal that literature examining how management can use AI to smoothen the bullwhip effect is a rather under-researched area that provides an abundance of research avenues. Based on identified AI capabilities, the authors propose three key management pillars that form the basis of the authors' Bullwhip-Smoothing-Framework (BSF): (1) digital skills, (2) leadership and (3) collaboration. The authors also critically assess current research efforts and offer suggestions for future research.

By providing a structured management approach to examine the link between AI and the bullwhip phenomena, this study offers scholars and managers a foundation for the advancement of theorizing how to smoothen the bullwhip effect along the supply chain.

In response, the purpose of this paper is to provide theoretical frameworks about the organizational uncertainty behind what and when to adopt blockchain technology and their implications on transaction costs. The immature nature and the absence of standards in blockchain technology lead to uncertainty in government organizations concerning the adoption (“what to adopt”) and the identification of the right time (“when to start”).

Using transaction cost theory and path dependency theory, this paper proposes two frameworks: to assess transaction cost risks and opportunities costs; and to depict four different types of transaction costs outcomes regarding blockchain adoption.

This paper identifies various theoretical concepts that influence blockchain adoption and combine the two critical constructs of “bounded rationality” and the “lock-in effect” to categorize the multiple transaction costs outcomes for blockchain adoption.

Although existing research in blockchain highlights mainly the potential benefits of blockchain applications, only a little attention has been given to frameworks that categorize potential transaction costs outcomes under uncertainty, in particular from organizational theorists.

Both frameworks advance the understanding of the decision-making behind blockchain adoption and synthesize the current literature to offer conceptual clarity regarding the varied implications and outcomes linked to the uncertainty regarding transactions costs stemming from blockchain technology.

The purpose of this paper is to provide new insights into the reactions and lessons learned with regard to the COVID-19 pandemic in terms of how logistics service providers (LSPs) managed to maintain supply chains resilience and what focus areas have been changed to keep operations functional and uphold financial stability.

Based on data-gathering techniques in interpretive research this study collected primary data via semi-structured interviews, interviewing informants from selected LSPs that operate on a global scale.

The results show that LSPs have built their reactions and actions to the COVID-19 outbreak around five main themes: “create revenue streams,” “enhance operational transport flexibility,” “enforce digitalization and data management,” “optimize logistics infrastructure” and “optimize personnel capacity.” These pillars build the foundation to LSP resilience that enables supply chains to stay resilient during an external shock of high impact and low probability.

The results of this study provide insights into how LSPs have managed the downsides and found innovative ways to overcome operational and financial challenges during the COVID-19 outbreak. As one of the first studies that specially focuses on the role of LSPs during the COVID-19 pandemic, this study categorizes the LSPs’ reactions and provides a “lessons learned” framework from a managerial perspective. From a theoretical perspective, this paper discusses the strategic role of LSPs in supply chain management and thereby extends current supply chain literature with a focus on LSP resilience.

Despite increasing interest in digital services and products, the emergence of digitalization in the logistics and supply chain (L&SC) industry has received little attention, in particular from organizational theorists. In response, taking an institutionalist view, the authors argue that the emergence and adoption of digitalization is a socially constructed phenomenon.

This paper shows how actor-level frameshifts contribute to an emergence of an overarching “digitalization logic” in the L&SC industry at the field level. Building on a longitudinal analysis of field actors' frames and logics, the authors track the development of digitalization over the last 60 years in the L&SC sector.

The authors classify specific time periods by key field-configuring events, describe the relevant frameshifts in each time period and present a process that explains how and why digitalization has emerged, been adopted and manifested itself in the L&SC industry.

The findings of the study provide insights about the evolution of a digitalization logic and thus advance the institutional view on digitalization in the L&SC industry.

A perceived misalignment between socially responsible fans and football club management has recently led to a major crisis during the annual meeting in 2021 of Bayern Munich, one of the largest professional football teams in Europe. In an unprecedented scenario, Bayern Munich fans demanded that management drop one of its largest sponsors due to alleged violation of human rights. The goal of this paper is to examine this particular phenomenon, as it not only demonstrates a discrepancy between the social organizational identity and its image, but more importantly, how it impacts legitimation strategies and the fans' loyalty attitudes towards the club.

Using the underlying concepts of legitimacy and loyalty, this conceptual model paper proposes two frameworks for social responsibility in professional football clubs: (1) analyzing how the (mis-)alignment between organizational identity and image impacts fan loyalty and (2) depicting four different types of social responsibility strategies to align organizational identity and image.

The authors identify various theoretical concepts that influence organizational identity and image in and for social responsibility and combine the two critical concepts of legitimacy and loyalty to categorize the social responsibility strategies for professional football clubs.

Both frameworks advance the understanding of the decision-making behind social responsibility strategies and also synthesize the current literature to offer conceptual clarity regarding the varied implications and outcomes linked to the misalignment between organizational identity and image.

Digital freight forwarder (DFF) start-ups and their associated business models have gained increasing attention within both academia and industry. However, there is a lack of empirical research investigating the differences between DFFs and traditional freight forwarders (TFF) and the impact of digital start-ups on incumbents' companies. In response, this study aims to examine the key business model characteristics that determine DFFs and TFFs and propose a framework illustrating the extent to which digital logistics start-ups influence incumbent logistics companies.

Based on the primary data gathered from eight interviews with experts from start-ups' and incumbents' logistics companies, as well as secondary data, the authors identify the main factors of DFFs start-ups that have an impact on TFFs and analyze the similarities and differences in regard to the business model components' value proposition, value creation, value delivery and value capture.

The results show that differences between DFFs and TFFs appear in all four business models' components: value proposition, value creation, value delivery and value capture. In particular, the authors identify three main factors that need to be considered when assessing the impact of DFFs on TFFs: (1) the company size, (2) the market cultivation strategy and (3) the transport mode.

This is one of the first studies to specifically examine the key business model differences between DFFs and TFFs and to propose a conceptual framework for understanding the impact of digital logistics start-ups on incumbent companies.

Disruptive technologies in the global logistics industry are often regarded as a threat to the existing business models of incumbents’ companies. Existing research, however, focuses mainly on whether technologies have disruptive potential, thereby neglecting when such disruptive transitions occur. To understand the timing of potential disruptive technological change, this paper aims to investigate the elements of the underlying ecosystem shaping these transitions.

Building on the established ecosystem framework from Adner and Kapoor (2016a), this paper constructs four categories of technology substitution to assess how quickly disruptive change may occur in the global logistics industry and defines key technology substitution determinants in logistics to emphasize the role of ecosystems for further consideration into disruptive innovation theory.

Based on the key determinants, this paper proposes first definitions of distinctive ecosystems elements linked to the three types of innovations, namely, sustaining innovations, low-end disruptions and new-market disruptions, thereby integrating ecosystems into Christensen’s (1997) disruptive innovation theory.

By developing a framework that conceptualizes the pace of technology substitution, this paper contributes to a more nuanced understanding of how logistics managers and academics can better predict disruptive transitions and develop strategies to allocate resources.