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The focus of this paper is to understand the initial formation of inter-firm relationship with the ultimate aim to form a long-term relationship in offshore-wind sector. The research question is “How and why new inter-firm relationships are built in nascent industries with highly uncertain business environments?”

Longitudinal case studies of three pairs of new inter-firm relationships based on interviews and other archival data are analysed.

Not all new inter-firm relationships progressed to expansion stage, largely owing to incompatibility and uncertainty. In some cases incompatibility could be rectified by trust and sharing of information. High trust is required to move the relationship from awareness to exploration stage. Investment in R&D is required to move the relationship from exploration to expansion. Innovation complementarity is the key in OSW sector.

Provide insights into how new inter-firm relationships in OSW sector could fail or be built up. High trust at the beginning helps to lower risk and encourages further investment.

Inform inter-firm relationship theories under high market risk and political uncertainty, especially for OSW sector.

Following counterarguments from previous studies, overwhelming evidence from meta-analyses shows that supply-chain integration (SCI) is not universally associated with improved performance. This study aims to clarify all the mechanisms purported to reach the combined effects of SCI dimensions.

In this study, the authors first conducted a literature review and identified the effects of different individual SCI dimensions and their interactions and mediation, or arcs of integration, as reported by past studies. Data from a survey of 348 firms were analyzed using multiple regressions, structural equation modeling and latent class analysis.

The results showed that the positive independent associations between SCI dimensions and operational performance change as they interact. Larger combinational effects were found in a second-order SCI construct and a mediation model. Smaller effects and fewer significant paths (and even negative signs) were also found. This shows that more SCI is not always better. Finally, configurational effects varied: the latent class analysis showed that a more inward (internal integration) gestalt performed better for some firms.

Some variables that could affect operations performance were missing from the models, and this paper did not specify the directions of relationships among the five performance dimensions. The authors are aware of cumulative models, but they are not within the scope of this paper. In addition, this study did not consider other sociocultural factors that may influence different dimensions of SCI.

This study shows SCI dimensions play different roles. Therefore, it is needed to theorize the distinct roles of internal and external integration and how they somehow compensate or substitute for each other. The results suggest that future studies need to reexamine the universal predictions especially from resource-based, resource-advantage and relational views. SCIs are not inimitable and rare resources for all firms. Furthermore, implementing SCI does not guarantee resource and relational advantages for all firms.

It remains unclear how environmental scanning (ES) can generate firm performance through supply chain management (SCM) practices. The purpose of this paper is to investigate the effects of ES on operational performance through supply chain integration (SCI) and supply chain responsiveness (SCR).

The scanning–interpretation–action–performance (SIAP) model and organization information processing theory (OIPT) are used to explain the ES–SCI–SCR–performance (S–I–A–P) relationships, which were tested by structural equation modeling of survey data of 329 manufacturing firms in China.

The results indicate that ES has a significant positive effect on SCI and SCR. SCI is significantly and positively related to SCR. SCR partially mediates the relationship between ES and operational performance, and fully mediates the relationship between SCI and operational performance.

Supply chain managers should collaborate with senior executives to obtain signals from ES activities, as input for building SCI and SCR and use SCI as a joint interpretation mechanism of ES signals for developing SCR to reap operational advantages in the rapidly changing business environment.

Strategic management academics and practitioners have explicitly emphasized the importance of ES in developing strategic plans but are unsure about the role of SCM in creating operational advantages through ES. Using the SIAP model, this study theorizes and demonstrates how SCI and SCR transform signals from ES into operational performance. In doing so, a more precise application of OIPT is explicated in the supply chain context.

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 examine whether the fit between innovativeness and lean practices (LPs) can affect triple bottom line (TBL) performance. Two types of fit are tested: fit-as-mediation in which innovativeness creates TBL performance through the mediation of LPs and fit-as-moderation whereby the effects of innovativeness on TBL performance are moderated by LPs.

Structural equation modelling and moderated regression are used to test the fit-as-mediation and fit-as-moderation models using survey data collected from 241 manufacturers in China.

The results show that innovativeness is positively associated with LPs that emphasize operational excellence. Innovativeness indirectly affects all three TBL dimensions through the mediation of LPs, and LPs do not moderate the effects of innovativeness. The applicability of fit-as-mediation model suggests directing attention towards integrating innovation and LPs within same organizational units to achieve improved TBL performance.

The findings suggest manufacturers should involve employees within the same organizational unit embrace an integrated culture of innovativeness and LPs and avoid separate attention to innovativeness and LPs.

This is the first study of which the authors are aware developing and empirically testing both fit-as-mediation and fit-as-moderation models within the same study to understand how innovativeness and LPs work together to influence TBL performance. This study extends the boundaries of current understanding by examining how, when and why the innovativeness – LPs–TBL relationship arises between constructs central to our theories.

This study aims to evaluate the usage of partial least squares structural equation modeling (PLS-SEM) in journals related to logistics and supply chain management (LSCM).

Based on a structured literature review approach, the authors reviewed 401 articles in the field of LSCM applying PLS-SEM published in 15 major journals between 2014 and 2022. The analysis focused on reasons for using PLS-SEM, measurement model and structural model evaluation criteria, advanced analysis techniques and reporting practices.

LSCM researchers sometimes did not clarify the reasons for using PLS-SEM, such as sample size, complex models and non-normal distributions. Additionally, most articles exhibit limited use of measurement models and structural model evaluation techniques, leading to inappropriate use of assessment criteria. Furthermore, progress in the practical implementation of advanced analysis techniques is slow, and there is a need for improved transparency in reporting analysis algorithms.

This study contributes to the field of LSCM by providing clear criteria and steps for using PLS-SEM, enriching the understanding and advancement of research methodologies in this field.