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This study aims to explore the gaps concerning the organizational operant resources (OORs) of logistics service providers (LSPs) expected in outsourcing relationships. The study considers the views of both manufacturing firms (M-firms) and LSPs in India and DACH region (Germany, Austria and Switzerland) seeking gaps within and across regions.

This research employed a survey targeting executives from large M-firms and LSPs in both India and DACH. The perceptions about the importance and improvement expectations of 17 OORs are analyzed. A modified version of importance-improvement analysis (A-B), a novel comparative A-B analysis (CABA) method, has been proposed to identify the importance and improvement gaps in OORs between M-firms and LSPs within and across India and the DACH region.

There are more gaps between M-firms and LSPs in India compared to DACH. Cross-country comparisons reveal that LSPs in India and DACH have similar perceptions concerning the OORs, but M-firms in India have significantly higher improvement expectations than those in DACH.

This study proposes an analytical approach that enables managers to identify improvement areas and better align with their outsourcing relationship partners. It also highlights aspects that need to be considered while entering emerging markets such as India.

The analysis approach using CABA is novel. Also, among the cross-country studies, this is the first to compare outsourcing relationships in India with the DACH region while involving both users' and service providers' perspectives.

According to the logistics performance index, emerging countries such as India are lagging behind developed countries such as Germany, Austria and Switzerland (DACH region). The purpose of this study is to compare and understand the differences in logistics outsourcing outlook in the two regions by considering both manufacturing firms (M-firms) and logistics service providers’ (LSPs) perspectives.

A survey targeting both LSPs and M-firms in DACH and India is conducted. A total of 96 responses were analyzed by using the chi-square test to investigate the differences and alignments in outsourcing motivation, relationship and governance between firms within and across regions.

M-firms in India bear strategic motivations behind outsourcing and those in DACH incline towards costs. LSPs in both regions align with the motivations of M-firms. M-firms in India rely more on LSPs by transferring the ownership of outsourced tasks, as compared to DACH. Both M-firms and LSPs in DACH claim a high level of ownership. However, firms in DACH and India do not differ significantly in terms of outsourcing engagements they seek.

The findings may only be generalized to large firms in India and DACH.

The findings of this study help managers enhance their understanding of the differences between M-firms and LSPs, and also across countries. LSPs in DACH, if they wish to operate successfully in India, will have to adapt to the M-firms strategic motivations and offer higher dependency.

This study is novel, as it investigates differences between India and DACH countries while also including both manufacturers’ and logistics service providers’ perspectives.

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.

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.

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.

This study aims to compare the humanitarian supply chains and logistics of two countries in earthquake preparedness by modifying and using a previously established preparedness evaluation framework.

A European flood emergency management system (FEMS) is a seven-dimensional framework to assess a country’s preparedness for flood emergencies. The FEMS framework was modified to apply to earthquakes. Leveraging a multiple explanatory case study approach with data analysis, the authors reconstructed the events of the earthquakes in Pakistan (2005) and Japan (2011) with an applied grading (1–5). Findings were evaluated within the adopted FEMS framework. From a practitioner’s perspective, the framework is applicable and can accelerate support in the field.

Pakistan lacked emergency plans before the 2005 earthquake. In contrast, Japan possessed emergency plans before the disaster, helping minimise casualties. Overall, Japan demonstrated considerably better emergency management effectiveness. However, both countries significantly lacked the distribution of responsibilities among actors.

Practical factors in the humanitarian supply chain are well understood. However, synthesising individual factors into a comprehensive framework is difficult, which the study solves by applying and adopting the FEMS framework to earthquakes. The developed framework allows practitioners a structured baseline for prioritising measures in the field. Furthermore, this study exemplifies the usefulness of cross-hazard research within emergency management and preparedness in a real-world scenario.

Although logistics management is a crucial part of local and global sports events, there is no research-driven characterization of “sports logistics management”. The purpose of this paper is to conceptualize a framework that allows for a more structured recognition of logistics in sports, in general, and sport event management, in particular. In addition, we conduct a systematic literature review of sports logistics management and locate opportunities for future research both for sports management and logistics management scholars.

Guided by Durach et al.’s (2017) systematic literature review approach, we identify key attributes and characteristics of sports logistics management. These are based on studies featuring at least partial aspects of logistics management in sports and sport events, and that were published between 2000 and mid-2019.

The study reveals that sports logistics management – meaning logistics activities in sports and sport event management – is a heavily under-researched area that provides an abundance of scientific opportunities. Based on the three sport event types of local/regional sport events, major sport events and mega sport events, the authors propose four sports logistics management pillars that are central to the proposed Sport Logistics Framework: venue logistics management, sports equipment logistics management, athletes logistics management, and fan and spectators logistics management.

By providing a conceptual framework for sports logistics, the authors progress towards informing the sport sector on relevant strategic and operational levels of logistics management and set the stage for empirical studies that are likely to advance sport logistics planning and management.

This is the first study that builds on a systematic review of literature specifically focused on the logistics aspect in sports and sport event management. It provides a conceptual framework of sports logistics management and offers an agenda of future research opportunities.

The purpose of this paper is to further advance an existing supplier evaluation model for the purpose of identifying those supplier relations which predominantly threaten or worsen a company's performance. A defined basic set of parameters to determine complexity facilitates the identification of critical locations within a supply network (SN) under certain business conditions.

This paper is based on a structured literature review in scientific periodicals in logistics/supply chain management between 2000 and 2009. Articles are analysed based on a structured framework and the identified complexity parameters are operationalised using quantitative and summable measures. The conceptual model is applied within a multiple case study in the Austrian agricultural industry.

This paper illustrates how complexity in SNs can be operationalised in a company‐specific configuration in order to achieve concrete managerial recommendations. Hence, the model allows evaluating SN‐partners based on selected parameters to determine the contribution of a single partner to the overall complexity.

Due to the literature review executed and the case study approach chosen, the research may lack generalisability. Therefore, continued validation by means of implementing a greater amount of use cases in other companies and industries is advisable.

Applying the model, a company is able to determine tier‐1 to tier‐n suppliers which are predominantly affecting its business from a complexity perspective.

Unlike typical current complexity evaluation approaches, the proposed model respects rapid and continuous applicability, profound conceptualisation and practical feasibility.