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The emergence of distributed manufacturing (DM) is examined as a new form of localised production, distinct from previous manifestations of multi-domestic and indigenous production.

Supply network (SN) configuration and infrastructural provisioning perspectives were used to examine the literature on established localised production models as well as DM. A multiple case study was then undertaken to describe and explore the DM model further. A maximum variation sampling procedure was used to select five exemplar cases.

Three main contributions emerge from this study. First, the research uniquely brings together two bodies of literature, namely SN configuration and infrastructure provisioning to explore the DM context. Second, the research applies these theoretical lenses to establish the distinctive nature of DM across seven dimensions of analysis. Third, emerging DM design rules are identified and compared with the more established models of localised production, drawing on both literature and DM case evidence.

This study provides a rich SN configuration and infrastructural provisioning view on DM leading to a set of design rules for DM adoption, thus supporting practitioners in their efforts to develop viable DM implementation plans.

The authors contribute to the intra- and inter-organisational requirements for the emerging DM context by providing new perspectives through the combined lenses of SN configuration and infrastructural provisioning approaches.

International Journal of Operations and Production Management (IJOPM)'s Impact Pathway (IP) section has been launched in 2020 to host short contributions grounded in current managerial practices and/or policy development, challenging established operations and supply chain management (OSCM) knowledge and highlighting innovative and relevant research directions. This commentary reflects on the achievements of the section, delineates the key features of IP papers and stimulates further development.

This commentary provides a brief overview of the IJOPM's IP section, taking stock of the contributions that have been published so far, analysing their topics, methodologies, insights and impact.

The 19 contributions published over the last three years have dealt with a variety of emerging topics, ranging from the COVID-19 response to additive manufacturing, leveraging on key evidence from managerial practice that challenges consolidated knowledge and theory, providing clear research directions as well as managerial and/or policy guidelines.

The commentary reflects on the importance of phenomenon-driven research that seeks to bridge the gap between theory and practice, thus increasing the impact and reach of OSCM research. This is a call for contributions from scholars, business leaders and policymakers to develop further impact-oriented research.

This paper aims to propose an integration of the analytic hierarchy process (AHP) and data envelopment analysis (DEA) methods in a multiattribute grey relational analysis (GRA) methodology in which the attribute weights are completely unknown and the attribute values take the form of fuzzy numbers.

This research has been organized to proceed along the following steps: computing the grey relational coefficients for alternatives with respect to each attribute using a fuzzy GRA methodology. Grey relational coefficients provide the required (output) data for additive DEA models; computing the priority weights of attributes using the AHP method to impose weight bounds on attribute weights in additive DEA models; computing grey relational grades using a pair of additive DEA models to assess the performance of each alternative from the optimistic and pessimistic perspectives; and combining the optimistic and pessimistic grey relational grades using a compromise grade to assess the overall performance of each alternative.

The proposed approach provides a more reasonable and encompassing measure of performance, based on which the overall ranking position of alternatives is obtained. An illustrated example of a nuclear waste dump site selection is used to highlight the usefulness of the proposed approach.

This research is a step forward to overcome the current shortcomings in the weighting schemes of attributes in a fuzzy multiattribute GRA methodology.

Policy makers, professional associations and scholars continue to advocate for the integration of enhanced clinical experiences for future teachers’ preparation. These recommendations reflect the growing recognition that few events in preservice teachers’ education are more significant than their experiences in the classrooms of veteran peers. Aware of the fact that the field of teacher education needs examples of effective clinical experiences, the authors examined the “critical, project-based” (CPB) model, employing Photovoice activities in a dropout prevention course in a secondary education partner school at the beginning of the COVID-19 pandemic. This paper aims to discuss the aforementioned objective.

Aware that the field of teacher education needs examples of effective clinical experiences, the authors examined the CPB model, employing Photovoice activities in a dropout prevention course in a secondary education partner school at the beginning of the COVID-19 pandemic. In this article they detail a practitioner research examination that explores the experiences of 12 preservice middle/high school teachers, reporting on these individuals’ considerations of general pedagogies, writing instruction strategies and teaching personas.

Results suggest that preservice teachers might best identify pedagogical practices that are consistent with their nascent teaching identities via experiences that occur in school-university partnerships in which future teachers are positioned as pedagogues.

This manuscript explores the use of the “CPB” clinical experience model, identifying the impacts of this approach for preparing future teachers.