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Endeavoring to expand their global market presence, firms often launch products into emerging markets where managers face the daunting task of deploying products by managing available, and often limited, supply chain resources. Yet, literature has not empirically examined managerial resource orchestration in this context. Accordingly, by embedding resource orchestration theory (ROT) into the emerging market context, the authors offer middle-range theorizing on supply chain resource orchestration (SCRO) and empirically test how acquiring, bundling and leveraging activities impact new product launch performance.

The authors test the model by analyzing empirical data from 175 individual product launches into emerging markets using a survey methodology.

The authors’ results suggest that SCRO holds the promise of being a viable middle-range theory in the supply chain field, especially where managers face limited resources and must “work with what they have to do what they can.”

The authors’ study also has some limitations. First, because a panel data service company was used to collect the data, the authors were not provided with any information regarding the respondents' company names or other identifying data. Second, because the authors did not directly interact with the respondents nor were the authors able to contact multiple individuals from their respective organizations, the study was limited to a single-respondent design. However, to counter issues associated with single-response bias, the central constructs in the study referenced phenomena related to a specific product launch project as opposed to constructs at the firm or inter-firm relational level.

The authors’ results reveal that SCRO activities can enhance the performance of new product launches, even in resource-starved emerging market contexts.

The results validate measures for several of the SCRO processes (i.e. supply chain resource acquisition, supply chain resource bundling and supply chain leveraging) and provide evidence that supply chain resource bundling and supply chain leveraging mediate the relationship between supply chain resource acquisition and product launch performance. Further, soft logistics infrastructure is found to be an important boundary condition for these relationships.

This study aims to explain the value of using critical realist case research in supply chain management (SCM). While positivist case research focuses on generalizable law-like rules, and interpretivist research explores social meaning, critical realist case research seeks to make objective explanations that are bound by the case context. This study demonstrates how a critical realist synthesis of causal reasoning and contextual complexity allows for stronger theorizing in SCM.

This study highlights the possibilities of conducting critical realist case research in SCM by investigating philosophical perspectives in existing literature.

Based on existing literature, this study identifies which parts of contemporary SCM research will benefit from the critical realist perspective. This study also contends that supply chain scholars can use critical realist case research to develop new types of contextualized middle-range theories.

This study proposes to complement the qualitative SCM toolbox with critical realist case research to further refine the development of novel theories. This will benefit not only researchers but also managers, as it opens the doors to new and inspiring research.

This study takes an important step toward establishing critical realist case studies as a key methodology in SCM. While other scholars have introduced critical realism as a paradigmatic approach in SCM, to the best of the authors’ knowledge, this is the first article that develops a qualitative critical realist case research approach.

The authors explore the entanglement of smartphone technology and power in this paper. This paper explores the following question: In what ways does the actualization of smartphone affordances result in empowering outcomes (i.e. increase or reduce oppression) in the daily lives of refugees? Leveraging both affordance and feminist theories, the authors develop a hybrid lens bringing attention to the contextualized relationship between social process goals and affordances for sociality, upon which the authors introduce the notion of “goal-affordance interrelations”. The authors then trace how the actualization of these interrelations increases or reduces oppression.

Using an abductive approach, the authors analyze 32 semi-structured interview transcriptions conducted with Syrian refugees in Lebanon.

The analysis in this study reveals four categories of social process goals (meet financial needs, satisfy security needs, communicate and learn and maintain pre-existing social ties) that are intimate components of contextually meaningful affordances. When actualized, the goal–affordance interrelations fundamentally shape refugee experiences of power outcomes. The findings suggest forms of empowerment where powerlessness, marginalization, violence and exploitation are perceived to be reduced. Actualization outcomes are also found to increase perceived oppression. Additionally, the findings reveal that not all interrelations are actualized, such that the anticipation of an oppressive power outcome may limit the actualization of affordances for sociality.

This research raises considerations concerning technology and oppression, and that efforts to empower refugees through technology should critically question whether the lived experiences of oppression will be reduced. The findings of this study reveal various forms of less empowering (i.e. oppressive) outcomes for the refugees sampled, they also point to the potential politicization of the actualization of goal–affordance interrelations.

Experiencing more frequent, system-wide disruptions, such as pandemics and geopolitical conflicts, supply chains can be largely destabilized by a lack of materials, services or components. Supply chain resilience (SCRES) constitutes the network ability to recover after and survive during such unexpected events. To enhance the understanding of SCRES as a system-wide quality, this study tests a comprehensive SCRES model with data from multiple industries.

The study proposes a theoretical framework conceptualizing SCRES as system quality, extending the classical proactive/reactive taxonomy by multiple system states consisting of the supply system properties, behaviors and responses to disruptions. Underlying hypotheses were tested using an online survey. The sample consists of 219 responses from German industries. Maximum likelihood structural equation modeling (ML-SEM) and moderation analysis were used for analyzing the survey data. The study was particularly designed to elaborate on supply chain theory.

Two pathways of parallel SCRES building were identified: proactive preparedness via anticipation and reactive responsiveness via agility. Both system responses are primarily built simultaneously rather than successively. The present study further provides empirical evidence on the central role of visibility and velocity in achieving comprehensive SCRES, while flexibility only exerts short-term support after a disruption. The study additionally points to potential “spillover effects” such as the vital role of proactive SCRES in achieving reactive responsiveness.

The present study confirms and expands existing theories on SCRES. While stressing the multidimensionality of SCRES, it theorizes the (inter-)temporal evolution of a system and offers practical guidelines for SCRES building in various industrial contexts. It thus supports the transformation toward more resilient and viable supply chains, contributing to the increasing efforts of middle-range theory building to achieve an overarching theory. The study also points to potential future research avenues.

This study proposes a systematic and comprehensive circular economy (CE) performance measure as an instrument to operationalize and quantify circularity. It seeks to evaluate the relative contribution of blockchain technology to evaluate various measures in this study. A general research agenda for investigating blockchain capabilities to performance assessment in CE is presented.

Empirical survey data from 32 CE and blockchain experts are collected to inform this study. Inductive reasoning, heatmaps, and a middle-range theory building approach are utilized to generalize theoretical patterns for blockchain support of CE performance assessment and measurement. A series of propositions are then developed as a middle-range theory for the true, false, perceptible, and hidden affordances of blockchain technology capabilities for CE performance measurement.

Overall, sixteen performance measures and metrics are identified and examined. The authors find most of these measures and metrics – based on literature and expert opinion – can be supported using blockchain technology capabilities. Four major blockchain capabilities, transparency and traceability, reliability and security, smart contracts, and incentivization and tokenization are shown to have varying potential support for CE performance assessment. There needs to be an evaluation of true, false, perceptible, and hidden affordances of blockchain technology capabilities for CE performance measurement in future studies.

Blockchain application for CE, and specifically performance measurements, is a new area. Research and practice evaluation on this issue is important but needs substantially additional investigation to help CE progress. This study provides a framework for evaluation and a foundation for future research at the nexus of CE, blockchain technology, and performance measurement.

Digital transformation using Industry 4.0 technologies can address various challenges in food supply chains (FSCs). However, the integration of emerging technologies to achieve digital transformation in FSCs is unclear. This study aims to establish how the digital transformation of FSCs can be achieved by adopting key technologies such as the Internet of Things (IoTs), cloud computing (CC) and big data analytics (BDA).

A systematic literature review (SLR) resulted in 57 articles from 2008 to 2022. Following descriptive and thematic analysis, a conceptual framework based on the diffusion of innovation (DOI) theory and the context-intervention-mechanism-outcome (CIMO) logic is established, along with avenues for future research.

The combination of DOI theory and CIMO logic provides the theoretical foundation for linking the general innovation process to the digital transformation process. A novel conceptual framework for achieving digital transformation in FSCs is developed from the initiation to implementation phases. Objectives and principles for digitally transforming FSCs are identified for the initiation phase. A four-layer technology implementation architecture is developed for the implementation phase, facilitating multiple applications for FSC digital transformation.

The study contributes to the development of theory on digital transformation in FSCs and offers managerial guidelines for accelerating the growth of the food industry using key Industry 4.0 emerging technologies. The proposed framework brings clarity into the “neglected” intermediate stage of data management between data collection and analysis. The study highlights the need for a balanced integration of IoT, CC and BDA as key Industry 4.0 technologies to achieve digital transformation successfully.

The research on supply chain resilience (SCRES) has gained momentum after organizations have experienced more frequent and severe disruptions, especially with COVID-19 and the Russia/Ukraine conflict. Due to its potential for new practices and capability building, SCRES requires dynamic capabilities (DC) to enable an organization to prepare for, counter, and recuperate from disruptions leading to performance improvements and competitive advantage.

The present literature study seeks to enrich the theoretical debate on DC in SCRES, contributing to an advanced understanding of SCRES. Therefore, a meta-review of 83 peer-reviewed literature reviews has been conducted. Based on qualitative content analysis and abductive reasoning, relevant constructs are synthesized to facilitate theory-building for SCRES DC into a comprehensive framework.

The analysis reveals that SCRES has developed into an independent research area. Thus, resilience capabilities must be considered bundles of practices, evolving from different areas beyond supply chain risk management (SCRM). Most recent literature reviews on SCRES address more than one practice bundle applying SCRES DC as antecedents of new DC when organizational structures become more mature, leading to path dependencies when building business capabilities.

Aggregating extant literature on SCRES into a theoretical framework, the study contributes to a better understanding of the relationships between DC and SCRES practices while offering potential avenues for future research. It enriches DC theory by extending its microfoundations towards a holding/buffering dimension, which particularly accounts for the stability-based view of SCRES.

This research proposes and illustrates a conditional view of lean supply chain management (LSCM) based upon the contextual contingent alignment between lean performance objectives (i.e. a contextual factor) and supply chain management challenges (i.e. a contingent condition) in the selection of lean approaches (i.e. a contingent event).

Drawing on the notions of contingency-based practices and strategic fit, the authors’ LSCM reconceptualization jointly considers contextual and contingency factors in specifying what lean approaches to adopt. The authors illustrate the practical relevance of LSCM reconceptualization for the Canadian agri-food industry using the Delphi method.

The authors highlight that LSCM is founded upon alignment associations between specific lean performance objectives and supply chain challenges as well as their influence on the selection of suitable lean approaches. The empirical illustration shows that those alignment associations do not occur at random, which supports the conditional view of LSCM.

The contextual contingent view of LSCM can inform future scholarly inquiry and can reframe practically relevant middle-range theorization on LSCM.

The Delphi method-derived descriptive model of LSCM provides guidance to managers in the Canadian agri-food sector in identifying suitable lean approaches to adopt given the specific performance objective(s) pursued and supply chain management challenge(s) encountered.

The authors advance scholarly theorization and managerial understanding of LSCM by providing a conditional conceptualization that jointly considers relevant contextual and contingency factors that hitherto have not been examined. In ascribing what lean approach(es) to adopt to the alignment associations influence between lean performance objective(s) pursued and supply chain management challenge(s) encountered, the authors provide compelling conceptual and empirical support for the joint conditional view of LSCM.