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This work analyzes a pharmaceutical supply chain (PSC) in terms of supply chain visibility (SCV). The current good distribution practice (GDP) guideline demands increased visibility from firms. The purpose of this paper is to propose a solution for SCV enhancements based on automatic identification (Auto-ID) technologies.

The authors qualitatively analyze data from ten case studies of actors in a PSC. A review of Auto-ID technologies supports the derivation of solutions to enhance SCV.

This work shows that the functionalities of Auto-ID technologies offered by current practical monitoring solutions and challenges created by the GDP guideline necessitate further SCV enhancements. To enhance SCV, the authors propose three solutions: securPharm with passive radio frequency identification tags, transport containers with sensor nodes, and an SCV dashboard.

This study is limited to a PSC in Germany and is therefore not intended to be exhaustive. Thus, the results serve as a foundation for further analyses.

This study provides an overview of the functionality of Auto-ID technologies. In juxtaposition with the influence of the GDP guideline, the use of our Auto-ID-based solutions can help to enhance SCV.

This work analyzes a PSC in Germany, with consideration given to the influence of current legislation. Based on a multiple-case-study design, the authors derive three Auto-ID-based solutions for enhancing SCV.

Information-sharing and flexibility are considered to be major tools for risk mitigation and supply chain resiliency. However, less light has been shed on the role of information-sharing as an enabler to utilize flexibility capabilities before and after supply chain disruptions. The aim of this paper is to provide indications on how digitalized information-sharing (DIS) enhances flexibility capability utilization.

The methodology follows a qualitative approach, including 31 transcribed semi-structured interviews with supply chain experts in Germany and Japan.

The findings indicate that DIS supports flexibility capability utilization in pre- and post-disruptive supply chain management. First, the enhancement of estimated transport time accuracy supports rapid supplier and transport mode adjustment. Second, while the effects of DIS in manufacturing are limited without pre-existing flexibility capabilities, steady internal and external DIS utilizes exciting manufacturing flexibility to cope with disruptions beyond production. Third, track and trace technologies enhance the value of shared data and allow flexibility in the form of demand-oriented distribution, but companies unable to adopt technologies can still enhance flexibility capabilities with DIS using the existing infrastructure.

This paper highlights the essential role of digital information-sharing for flexibility utilization in supply chain risk management. While existing studies engaged with flexibility and information-sharing in supply chain risk management, this study contributes by emphasizing digital information-sharing as a key triggering enabler for flexibility in pre- and post-disruptive phases.

The purpose of this paper is to identify and systematically discuss generic forms of contract logistics services and their distinct underlying approaches for fulfilling their respective value propositions. A general frame of reference is developed that addresses the value proposition, as well as the value creation architecture that leads to generic business model configurations for contract logistics services. The framework is built upon the basic notions of service theory, competence research and the resource based view.

The paper combines service theory with work of organizational theory and develops an analytical framework based on conceptual considerations. First empirical results are additionally used to support and illustrate the key outcomes.

Combining the dimensions of integration power and intangible knowledge creation, the authors are able to specify generic types of contract logistics services. Thereby the authors deducted for every type the distinct requirements for service fulfilment and present this in a specific frame of reference.

The illustrated empirical results are still limited due to a limited sample size for the interviews. Additional empirical work on the whole third party logistics (3PL) market is suggested.

The paper provides generic types of 3PL services and a characterization of properties and architectures of respective business models. Combined with first empirical results, the paper's results offer insights for practitioners to rethink their value propositions and potentially redesign their service architectures.

The paper delivers a set of distinct business models for 3PL services reflecting the customer's, as well as the service provider's point of view. It addresses specific aspects of the generation/production of required services that are so far mostly neglected.

The study analyses how Industry 4.0 and underlying digital technologies influence the design of ecosystems in global value chains (GVCs).

A qualitative-exploratory research design is used. It deploys a multiple case study based on semi-structured interviews with 73 German managers of multinational enterprises. Applying a qualitative content analysis, the expert interviews are inductively analyzed and triangulated with secondary data to develop a synthesized data structure.

The analysis reveals a general tendency towards decentralization of value chain activities. Depending on the nature of each activity and several contextual factors, however, hybrids between centralization and decentralization of processes can be observed in Industry 4.0 environments. Consequences for global ecosystems are altered cooperation with business partners, new organizational forms and novel market environments.

Given inherent limitations in scope and methodology, the study calls for cross-industry and cross-country analyses. Further studies should research implications of Industry 4.0 changes in ecosystems and GVCs, and the role digital platforms can play in this context.

The results help companies to analyze and adapt their role in ecosystems and associated GVC activities to Industry 4.0 environments, thus staying competitive in changing market conditions.

This study is among the first to empirically investigate the influence of Industry 4.0 on ecosystems embedded in GVCs. Reflecting existing company environments, it adds an international and company-external perspective to Industry 4.0 research.

This article celebrates the 50th anniversary of IJPDLM, reflects on the contribution of IJPDLM to the field of logistics and supply chain management (LSCM) and discusses future directions for the journal.

Descriptive analysis of manuscripts received and accepted by IJPDLM during 2015–2019 is used to provide an overview of the journal. Content analysis of selected articles is used to highlight important contributions of the journal. Changes made since 2020 are highlighted to inform future directions of IJPDLM. Invited articles are discussed and used to clarify future directions.

IJPDLM has made tremendous progress in informing and shaping the field of LSCM. Key issues addressed include sustainability and reverse logistics, omni-channel, e-commerce, retail logistics, risk, resilience, volatility, and complexity and digital technology innovation. The journal has expanded the use of methods beyond the typical qualitative and quantitative methods to explore the use of design science, experiment, conjoint analysis, qualitative comparative analysis, narrative analysis. The invited articles provide (1) a historical reflection of the purpose of the journal when it was launched, (2) new guidance on how to develop theories using literature review and grounded theories and (3) understanding of startups and supply chain ecosystems.

Some exemplar articles are highlighted to explain how IJPDLM informs LSCM managers, companies and policy makers.

This article explains the recent development and sets future directions for the LSCM field.

The purpose of this paper is to explore the social process of Big Data and predictive analytics (BDPA) use for logistics and supply chain management (LSCM), focusing on interactions among technology, human behavior and organizational context that occur at the technology’s post-adoption phases in retail supply chain (RSC) organizations.

The authors follow a grounded theory approach for theory building based on interviews with senior managers of 15 organizations positioned across multiple echelons in the RSC.

Findings reveal how user involvement shapes BDPA to fit organizational structures and how changes made to the technology retroactively affect its design and institutional properties. Findings also reveal previously unreported aspects of BDPA use for LSCM. These include the presence of temporal and spatial discontinuities in the technology use across RSC organizations.

This study unveils that it is impossible to design a BDPA technology ready for immediate use. The emergent process framework shows that institutional and social factors require BDPA use specific to the organization, as the technology comes to reflect the properties of the organization and the wider social environment for which its designers originally intended. BDPA is, thus, not easily transferrable among collaborating RSC organizations and requires managerial attention to the institutional context within which its usage takes place.

The literature describes why organizations will use BDPA but fails to provide adequate insight into how BDPA use occurs. The authors address the “how” and bring a social perspective into a technology-centric area.

The purpose of the study is to shed light on how to implement Industry 4.0 effectively across companies in buyer–supplier relationships.

The study follows an exploratory research design and analyzes qualitative empirical data of eight case companies from the German automotive industry. The data are inductively categorized to uncover patterns and structures in a qualitative content analysis, whereupon a deeper data structure is developed.

The research reveals that a comprehensive implementation approach is required to pave the way for digitalized and interconnected supply chains. Several challenges occur during the implementation, such as system heterogeneity and resource scarcity. Prerequisites and fundamentals for a successful implementation include a vision and strategy, management involvement, and sufficient resources. Lastly, indications on how to conduct the implementations were found.

The study is based on an exploratory methodology, analyzing data from the German automotive industry. The methodology entails some limitations, and caution must be given when transferring the results to different industries and national contexts. Future studies could complement the findings by studying different contexts and including further supply chain levels.

Managers and practitioners can study the recurring themes in the implementation approaches and the best practices and subsequently learn from the experiences. This knowledge could aid to shape the strategy of companies accordingly.

The study empirically sheds light on the Industry 4.0 implementation approach across companies in buyer–supplier relationships and helps to understand the success factors and underlying mechanisms.