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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.

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.

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.

The study aimed to analyze the association between dynamic capabilities and sustainable business model innovation of startups in the Brazilian logistics sector.

A qualitative approach was used through a multiple case study that was operated from semi-structured interviews and secondary data analysis.

The evidence found pointed to different types of innovations in sustainable business models and distinct activities inherent to the three dynamic capabilities surveyed. In addition, the results confirmed that dynamic capabilities can be considered internal drivers that stimulate sustainable business model innovation, since the conception until the change or dissemination.

The diffusion of a model that jointly addresses the theory of dynamic capabilities and sustainable business model innovation.

For managers, the study provides insights into the archetypes of sustainable business model innovation and guidance on how to incorporate into the organization's strategic activities aimed at the different dynamic capabilities to achieve sustainable innovation.

Sustainable business model innovation is seen as a key factor for competitive advantage and corporate sustainability. However, a more comprehensive understanding is necessary for those that promote the design and innovation of sustainable business models. Therefore, the paper addresses this gap by (1) systematizing sustainable logistics initiatives, (2) detailing the processes that support the development of startups' sustainable dynamic capabilities and (3) proposing a framework that establishes connections between capabilities, business model innovation processes, business model archetypes and the environmental, social and economic impacts.

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.

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.

The paper offers a comprehensive understanding of how digital transformation affects business models and how firms operate and compete effectively and successfully in a digital economy.

The research adopted an abductive approach (Dubois and Gadde, 2002) through constant movement between theory and empirical evidence. A systematic literature review led the first conceptual development and examples of practices from cultural heritage sectors were used in the theorizing process.

This paper depicts a digital model framework through a set of assumptions about how an organization creates and delivers value in an interconnected way by orchestrating new interactive processes, and providing experience propositions to customers, and about how value is framed in terms of economic, social and cultural outcomes.

The study contributes to the scientific debate by discussing the role of digital business models as enhancements more rather than replacements of traditional business models; it frames a digital business model as consisting of three main pillars: value orchestration, experience propositions and value sharing.

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.

Innovation output around the world is concentrated in very few economies possessing the requisite skills, knowledge and market acumen to capitalize on emerging technologies. Within the broader European Union, Central and Eastern Europe countries persistently lag in innovation rankings compared to their Western Europe counterparts. The existence of cultural barriers to innovation has been offered as an explanation for the lag, in the sense that perceptions about innovation affect innovation performance. The purpose of this paper is to provide evidence-based analysis on whether there are divergent perceptions at the firm level between East and West.

The focus is on four countries with distinct socioeconomic profiles (Germany, Poland, Portugal and North Macedonia) for which innovation data of sufficient granularity exist. Using Probit analysis across the regressors of firm size, sector and innovativeness, a detailed picture of perceptions of innovation emerges naturally.

The analysis demonstrates that there is no discernible East-West cultural divide but rather a palette of shades regarding perceptions of innovation, entrenched in firm-level characteristics. Specifically, firm size colors perceptions of innovation and such perceptions in turn are moderated by whether a firm is involved or not in innovation activities.

A better understanding of innovation culture at the firm level is essential to drive policy interventions aiming to remove barriers to innovation. The results of this study provide sufficient clues for more refined interventions, both internal (“procedures”) and external (“policies”) to the firm, targeting well-defined size segments as well as addressing differently innovative and non-innovative companies.

Blockchain technology enhances information management in healthcare supply chains by securing healthcare information and providing medical resource traceability. However, there is no decision framework to support blockchain implementation for managing information, especially in emerging economies’ healthcare supply chains. This paper develops a hierarchical decision model for implementing blockchain technology for information management in emerging economies’ healthcare supply chains.

This study uses 20 health supply chain experts in Ghana to rank 17 decision criteria for implementing blockchain for healthcare information management using the best-worst method (BWM) multi-criteria decision technique.

The results show that “security” and “privacy,” “infrastructural facility” and “presence of training facilities” are the top three critical factors impacting blockchain adoption in the health supply chain for healthcare information management. Other sub-factors are prioritized.

To implement blockchain effectively to enhance information management in the healthcare supply chain, health institutions, blockchain technology providers and state authorities should concentrate on the highly critical factors extracted from the study.

This is the first study that develops a hierarchical decision model for implementing blockchain technology in emerging economies' health supply chains.