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The importance of supply network flexibility (SNF) in the development of mass customization capability (MCC) has been implied in the literature but seldom subjected to empirical investigation. To fill the gap and contribute to MC literature, this paper aims to examine the role of SNF in facilitating the development of MCC of organizations. Furthermore, it has been investigated whether the use of information and communication technologies (ICTs) strengthens the above relationship.

Drawing on the supply chain literature and dynamic capability theory, the study proposes a research framework depicting the interconnectedness among the variables of interest. The proposed framework has been tested using structural equation modelling based on partial least squares by using the data collected from a questionnaire-based survey of a sample of Indian manufacturing organizations.

The findings indicate that the dimensions of SNF, namely, sourcing flexibility and supplier flexibility, positively affect the MCC of the organizations and the strength of these relationships is further amplified by the implementation of ICTs.

The study shows the managerial opportunities for the development of a flexible and competent supply network to facilitate the development or enhancement of MCC.

This study contributes to scant literature by providing empirical evidence for the relationship between SNF and MCC. Further, this study enriches the understanding of the crucial role of ICT by exploring its moderating effect on the relationship between the variables of interest.

The purpose of this research is to identify the crucial barriers to the implementation of mass customization (MC) in Indian SMEs and to investigate the interactions among them so that important managerial implications could be formulated to facilitate the implementation of MC in SMEs.

The contextual relationships and hierarchies of the barriers are established through the interpretive structural modelling (ISM) approach, and MICMAC analysis has been used to classify the barriers into different groups. Further, structural equation modelling based on partial least squares (PLS-SEM) has been applied to statistically validate the ISM model using the data collected through a questionnaire-based survey of Indian organizations.

A portfolio of barriers, containing 16 items, has been identified from the literature review and a series of semi-structured interviews of practitioners. The study develops a structural model by establishing relationships and imposing directions among the barriers and classifies the barriers according to their driving and dependence power to serve as a roadmap for SMEs willing to implement MC into practice.

The study highlights the critical barriers which have a significant impact on other barriers and need to be handled at priority. Also, the present research renders insights to SMEs to better prioritize their efforts and resources to overcome these barriers.

This research happens to be first in the MC literature that investigates the key barriers responsible for hindering the implementation of MC in SMEs and develops a statistically validated contextual model showing hierarchies and relationships of the barriers.

Owing to the paucity of literature, in the specific context of mass customization (MC), that explains what factors need to be considered while selecting suppliers and what strategies need to be implemented for effective management of suppliers, this paper aims to explore the effective supplier selection and management strategies and also investigate their impact on the development of mass customization capability (MCC).

Through an extensive review of literature, a total of 18 factors for supplier selection and management have been identified. Further, using multiple regression analysis, the linkages between these factors and MCCs have been examined based on the data set from the survey of Indian manufacturing organizations.

The results indicate that while concentrating on the responsive and reconfiguration capability, all the five measures of supplier selection and the four measures of supplier management have shown a significant influence. However, in the case of relational capability, only two of the supplier selection strategies and three of the supplier management strategies have shown a notable impact.

The study provides help to the firms in deciding whom to select and how to manage the suppliers in the course of improving their MCCs. The study has shown the possibility that different types of MCCs might require different approaches to both the supplier selection and management.

To the best of the authors’ knowledge, this study happens to be the first of its kind that investigates the interconnectedness among the supplier selection and management strategies and MCCs.

Over the years, technology development has rationalized supply chain processes. The demand economy is disrupting every sector causing the supply chain to be more innovative than ever before. The digitalization of the supply chain fulfils this demand. Several technologies such as blockchain, big data analytics, 3D printing, Internet of things (IoT), artificial intelligence (AI), augmented reality (AR), etc. have been innovated in recent years, which expedite the digitalization of the supply chain. The paper aims to analyse the applicability of these technological enablers in the digital transformation of the supply chain and to present an interpretive structural modelling (ISM) model, which presents a sequence in which enablers can be implemented in a sequential manner.

This paper employed the ISM approach to propose a various levelled model for the enablers of the digital supply chain. The enablers are also classified graphically based on their driving and dependence powers using matrix multiplication cross-impact applied to classification (MICMAC) analysis.

The study indicates that the enablers “big data analytics”, “IoT”, “blockchain” and “AI” are the most powerful enablers for the digitalization of the supply chain and actualizing these enablers should be a topmost concern for organizations, which want to exploit new opportunities created by these technologies.

This study presents a systematic approach to adopt new technologies for performing various supply chain activities and assists the policymakers better organize their assets and execution endeavours towards digitalization of the supply chain.

This is one of the initial research studies, which has analysed the enablers for the digitalization supply chain using the ISM approach.

The purpose of this study is to investigate the effects of flexible manufacturing competence (FMC) and workforce management practices (WMP) in facilitating the development of mass customization capability (MCC). More specifically, this research analyzes not only the direct effects of FMC and WMP on MCC but also the moderating effect of WMP on the relationship between FMC and MCC.

Building on the resource-based view, a research framework depicting the linkages among the variables of interest has been proposed. The examination of the proposed research model and hypotheses are conducted by applying partial least squares-structural equation modelling (PLS-SEM) on a dataset of Indian manufacturing organizations.

The findings suggest that both FMC and WMP significantly and positively affect the development of MCC. Also, the results show that the relationship between FMC and MCC is strengthened by the implementation of WMP.

The study identifies several crucial practices for enhancement of flexible manufacturing competence and effective management of the workforce and also highlights the complementarities among them to develop superior MCC.

While the research on the antecedent of MCC has increased substantially, the understanding of the interactions among FMC, WMP, and MCC is still limited. This is the first study that sheds light on the interconnectedness among the variables of interest.

Digital supply chain (DSC) is an agile, customer-driven and productive way to develop different forms of returns for companies and to leverage efficient approaches with emerging techniques and data analytics. Though the advantages of digital supply chain management (DSCM) are many, its implementation is quite slow for several reasons. The purpose of this paper is to identify the major barriers which hinder the adoption of DSC and to analyse the interrelationship among them. The barriers of DSC are explored on the basis of existing literature and experts’ opinion.

This paper uses the interpretive structural modelling (ISM) approach to develop a hierarchical structural model which shows the mutual dependence among the barriers of DSC. Cross-impact matrix multiplication applied to classification analysis was performed to represent these barriers graphically on the basis of their driving power and dependence.

The research demonstrates that the barriers “no sense of urgency”, “lack of industry specific guidelines”, “lack of digital skills and talent” and “high implementation and running cost” are the most significant barriers to digital transformation of supply chain. This paper also suggests some managerial implications to overcome the barriers which hinder the implementation of digital transformation of supply chain.

This paper assists managers and policymakers to understand the order in which these barriers must be tackled and adopts a roadmap for successful implementation of DSCM and reap its benefits.

This is one of the initial research studies which has analysed the barriers of DSC using ISM approach.

Knowledge management (KM) is the process of leveraging organizational knowledge to deliver long‐term advantage to a business and is based on a business strategy that involves engineering various knowledge‐centric business processes and developing organization structures to support these. These, in turn, require technology to capture, codify, store, disseminate and reuse the knowledge. Successful deployment of KM is not a simple process. This paper suggests that a major reason for the failure of many KM projects is the absence of a well‐defined strategic plan to guide implementation. This paper discusses the strategic planning needs of the KM deployment process, and develops a framework that could be used specifically by engineering firms to guide the KM implementation process.

Current dynamic and turbulent business environment calls for adopting newer strategies so that organizations can create a niche for itself in the market, mass customization (MC) being one of them. The purpose of this paper is to identify the critical enablers necessary to realize the objectives of MC, study the relationship among them and prioritize them in order of their importance so that a clear roadmap can be easily prepared for successful implementation of MC.

A portfolio of enablers of MC has been elicited from a thorough review of literature and experts’ opinion. Then, contextually relevant relations are chosen for each pair. In addition, a hierarchy-based structural model is developed by using Interpretive Structural Modelling (ISM) technique.

The findings classify the enablers into different groups according to their driving and dependence power. The findings show the enablers of strategic importance that need focused attention. This paper develops a structural model including hierarchy of enablers that forms a basis for the firms considering transition to MC.

This paper allows the firms to differentiate the dependent and independent variables and their mutual relationships, also by identifying and establishing the connection and relationships among the enabling practices; firms can better prioritize the resources and implementation effort to successfully provide each customer exactly they want.

This paper happens to be one of the first of its kind in the area of mass customization research that presents a contextual model having a hierarchy of enablers.

Over the past two decades, interest in the use of flexible manufacturing as a competitive weapon has increased significantly. Globalization and liberalization have forced Indian organizations to aim for globally competitiveness through the use of advanced technology, technical manpower, and innovative research and development. This paper reports the findings of case studies carried out in two large Indian manufacturing organization, and highlights the status of adoption of FMS. These organizations deal in the manufacture of shoes and railway coaches. The studies pay particular attention to the methods used to justify the investment involved. The experience of these firms’ can provide useful insight to other firms interested in implementing FMS.

In this age of globalization, to survive, organizations need a good capacity to retain, develop, organize and utilize their knowledge assets. The knowledge of an organization comprises of professional intellect, such as know‐how, know‐why, and self‐motivated creativity; as also the experience, concepts, values, beliefs and ways of working that can be shared and communicated. Knowledge Management (KM) is described as the management of an organization’s knowledge through the processes of creating, sustaining, applying, sharing and renewing knowledge to enhance organizational performance and create value. Interpretive Structual Modeling (ISM) is a methodology for identifying and summarizing relationships among specific elements, which define an issue or problem. It provides a means by which order can be imposed on the complexity of such elements. In the present paper the important elements (also referred to as variables) for the implementation of KM in engineering industries have been analyzed to obtain an ISM, which shows the inter‐relationships of the variables and their levels. These variables have also been categorized depending on their driving power and dependence.