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The purpose of this paper is to analyze preferred supplier enablers (PSEs) and measure the interdependencies among themselves for enhancing preferred supplier relationship.

In the current study, an approach has been developed in which the significance of various PSEs was determined by applying Fuzzy Analytic Hierarchy Process (FAHP) and the prominent PSEs were screened out through Pareto analysis. Also, the interdependence among the prominent PSEs was measured by applying the Fuzzy Decision Making Trial and Evaluation Laboratory method in order to select the right PSEs in ascribing the Preferred Supplier Status. Finally, the weakest relationships among the PSEs were confirmed by applying the student’s t-test and then an impact relationship map of PSEs was developed.

The strength of relationships among the PSEs, grouping of PSEs into causes and effects on a causal diagram and a concise impact relationship map of PSEs were determined. Further, the PSEs that a manufacturer must primarily focus and monitor were also obtained.

The study was conducted in an Indian electronic manufacturing environment. Therefore, the results obtained would be more relevant to the high end technology product manufacturers operating in the developing countries.

From the current study, a manufacturer can alleviate, favorably associate and integrate with the good suppliers and then eventually establish a strong supply base.

Manufacturers are looking for the closer and favored relationships by bringing in the concept of preferred supplier while dealing with their key suppliers. Thus, the results obtained from the current study would be of great assistance to a manufacturer in gaining an extra cutting-edge and, in turn, tackling the increased competitive pressures and reduced availability of resources.

The purpose of this paper is to assist a manufacturer with a process to measure the level of preferred supplier status (PSS) of its key suppliers along the timeline.

In measuring the PSS, the prominent preferred supplier enablers (PSEs) were identified and were broadly categorized under manufacturer’s interest component, common interest component and supplier’s characteristic component. These PSEs were further analyzed by using fuzzy analytic hierarchy process, Euclidean distance measurement and grey relation analysis methods. In order to demonstrate the application and utility of the proposed approach, a case study conducted in an Indian automotive component manufacturing company has been presented.

By applying the proposed methodology in a case company, the PSSs of five of its key suppliers were measured and then the suppliers’ characteristic scores were determined. Based on these scores, a preferential status plot of the suppliers was developed. Through the status plot, the manufacturer was suggested with whom the proposed initiatives can be productive and with whom the manufacturer has to appeal for improvement strategies.

Since the methodology was tried in the Indian manufacturing environment, the emphasis laid on the PSEs and in turn the measurement of PSS may not address the concern at large.

Measuring PSS would not only earn competitive advantages for the manufacturers but also facilitate the evolution of competitive suppliers.

Measuring PSS along the time would assist a manufacturer to effectively manage the preferences given to its suppliers and thereby enhance the supply base contribution in the value addition process.

Buying firms involve suppliers early in New Product Development (NPD) projects to benefit from their capabilities. The authors investigate the joint impact on project performance improvement, of the social capital established throughout the project, and the strategic preferred buyer/supplier statuses awarded prior to the project, from the buyer's perspective.

The authors propose a conceptual model underlining the complementary contribution to project performance of social capital dimensions and of preferred partners' statuses resulting from social exchange expectations. The model is analyzed with Partial Least Squares using 80 responses of purchasers and R&D managers involved in collaborative NPD projects with suppliers.

The relational capital built during the project has a positive central role, with a direct impact on NPD project performance and mediating effects through cognitive and structural capitals. The preferred partners' statuses have strong direct impacts on performance, and mediating effects that do not completely supplant the social capital's contribution.

The implications for the efficient management of supplier involvement are twofold. First, the authors encourage strategic investments of buying firms to acquire preferred buyer's status and to support preferred supplier programs. Second, the authors alert them on the importance of establishing trust and shared cognition during the project.

This study captures NPD project performance from the social angle of buyer–supplier relationship management. It demonstrates the complementarity of relationship management at the strategic and operational levels, before and during the project unfolding.

The purpose of this study is to determine the extent to which institutional pressures affect supplier and customer collaboration and how collaboration explains green supply chain performance using institutional and stakeholder theories.

The paper builds on empirical evidence gathered from responses of Iranian industrial managers based on a self-administered survey. The hypotheses in the conceptual model are tested using Smart-PLS (partial least square).

The results provide evidence that regulatory requirements and internal motivators, as institutional pressure, enable customer and supplier collaboration. Furthermore, customer collaboration has a positive effect on supplier collaboration and, consequently, positively affects environmental and economic performance. But supplier collaboration is just positively affecting environmental performances and is not effective on economic performance.

The subject is that the study is a questionnaire-based survey, and the validity and reliability of the results are influenced by the respondents' idiosyncrasies. This study provides a comprehensive model of drivers, supply chain collaboration and performance in the context of the industry sector. The study contributes by providing empirical data with a focus on customer and supplier collaboration and their interrelationship in GSCM modelling.

The current paper is one of the new field of research which demonstrate the significance of customer and supplier collaboration with each other to attain green performance. It also contributes to show the effect of institutional pressure on the customer-supplier collaboration that fosters green performance in the supply chain.

Due to the current volatile environment and fierce competition, manufacturing firms (MFs) must improve their performance to survive. In this regard, checking and monitoring the suppliers' risk should significantly improve the performance of MFs. In addition, a relation based on not being an opportunist, confidence and reliance are influential factors in reducing the supplier defaults on his/her supply obligations and improving supply chain performance (SCP). Besides, the moderator function of supplier involvement (SI) in the relationship between quality of the relationship (QoR) and supply risk mitigation (SRM) is undeniable.

Based on the survey of 148 samples from small to large-sized MFs in Jordan, Turkey and Egypt, empirical evidence has been conducted to support a majority of the authors’ hypotheses. This paper provides a theoretical review of buyer–supplier relationships and supply risk. Hypotheses were tested by using structural equation modeling (SEM)/Smart PLS-4.

According to the results, confidence and reliance have statistically significant and positive impacts on SRM, resulting in better SCP. Moreover, the findings show that SI positively affects and moderates the relationship between confidence (C) and SRM, while it has no statistically significant influence on the relationship between reliance (R) and SRM.

This study provides necessary material for managers and decision-makers in MFs to confirm the importance and understanding of the QoR in building relationships and business dealings with partners in the SC, in addition to limiting and mitigating the risks of an interruption in supply in particular. Therefore, building a high-quality relationship as a practice based on trust and reliability with suppliers positively affects the performance of the SCs of MFs.

This research paper offers empirical evidence for using QoR within SRM resources of MFs' context for enhancing their supply chain performance. This study is one of few studies that examine the QoR and SRM that contribute to enhancing SCP in MFs in developing countries, which also can serve as a reference for many SC managers and practitioners.

The study aims to assess and prioritise the enablers of manufacturing flexibility by evaluating the degree of environmental uncertainty and manufacturing flexibility in an uncertain environment.

The study proposes a methodological approach based on fuzzy quality function deployment (FQFD), fuzzy analytical hierarchical process (FAHP) and fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS) to assess and prioritise enablers of manufacturing flexibility in an uncertain environment.

The study proposes a methodological approach that can facilitate firms to concentrate on preferred enablers and assist them in formulating a strategy to develop manufacturing flexibility. The empirical case study analysis of an Indian auto-air conditioning manufacturing firm was done to illustrate the effectiveness, flexibility and feasibility of the proposed approach.

The proposed approach is limited to manufacturing flexibility. This study does not consider inter-dependencies among environmental uncertainties.

The proposed methodological approach can assist practitioners in the identification and development of the preferred enablers to improve manufacturing flexibility. Thus, practitioners can invest strategically in the right resources to improve manufacturing flexibility.

The study proposes and validates a methodological approach that simultaneously addresses drivers and enablers of manufacturing flexibility; therefore, it aims to fill the gaps of earlier studies that have majorly studied flexibility concept in an isolated way.

The purpose of this paper is to identify, rank, classify and establish the structural relationships between the preferred customer enablers (PCEs). This analysis would assist a manufacturer in selectively exercising the PCEs and effectively run-through the concept of reverse marketing in the buyer-supplier relationships.

In the current study, the interpretive structure modelling and Fuzzy Matriced’ Impacts Croisés Appliquée á un Classement methods are used to analyze and structurally relate the PCEs for Indian automotive component manufacturing industry. Furthermore, the structural relationships among the PCEs were confirmed by applying a Student’s t-test.

The classification of PCEs through driver dependence diagrams, structural digraphs of PCEs and statistical significance of the relationships between the PCEs are the main outcomes of this study. Further, certain PCEs (under supplier interest and common interest domains) were recommended in the Indian manufacturing environment to broadly control and monitor for achieving the preferred customer status (PCS).

The current study provides certain basis for a manufacturer to selectively emphasize and monitor the right PCEs and in turn effectively achieve the PCS from its key suppliers. The findings from the current analysis are more applicable in the context of Indian automotive component manufacturing industry.

The outcomes from the methodology would provide a basis for a manufacturer to develop the right strategies to become a preferred supply chain partner.

Even though the concept of PCS or reverse marketing can make remarkable impact on the business practices, it has been an ignored topic of research and its practice has been passively prophesied. In this regard, the current study could be a worthy addition toward the practice of preferred customer concept.

Suppliers and marketers have started planning toward postpandemic scenarios where logistics and retail will happen in a new way with the help of technological advances. This shift means new challenges for manufacturers, suppliers and retailers, and there is a need for strategic sourcing decisions for a robust supply chain system, logistics and on-time delivery system, as consumers have shown a positive change in online buying behavior. Furthermore, with digital transformation, customers are expected to not return to traditional buying. Hence, it becomes essential to identify the factors acting as enablers of online purchase behavior for sustainable digital business. This study aims to analyze the positive shifts in online purchasing by consumers, identify and model the enablers of positive transformations in online purchasing by consumers.

The interpretative structural modeling (ISM) technique is used to draw the interrelationships among the variables and their impact on online buying. A context-oriented relationship among the factors has been set up through the expert opinion technique. A total of 40 specialists have been approached for this. ISM with Matrice d’impacts croisés multiplication appliquée á un classment (MICMAC) analysis was used to prioritize these drivers, identify the most critical factors and establish a driver-dependence relationship among these drivers.

Several significant categories of enablers like health, trust, convenience, work from home, referral buying, panic purchase and overstocking possess a strong influence on the shift to online due to the pandemic. The results will help the policymakers, suppliers, retailers, managers and practitioners with insights to plan, prepare for challenges and make decisions toward preparation and shifting to the emergent digital world. In addition, the study provides academicians scope for further research in the related area.

Consumer behavior significantly impacts retail and supply chain business, as it is an interface with the customer and links between a manufacturer and a customer. This study provides an insight into the shift in purchase behavior which can help suppliers in this transition phase to be better prepared for tomorrow to achieve sustainable competitive advantage.

This study assists practitioners and researchers in understanding the interrelationships among the factors using ISM-MICMAC analysis in a realistic way rather than daydreaming with overambitious goals.

The purpose of this paper is to report a study on the application of interpretative structural modelling (ISM) integrated with multi-criteria decision-making (MCDM) techniques for enabling the sustainability supplier selection.

In this paper, two approaches of hybrid MCDM methods are followed and the selection of sustainable supplier was based on the comparative results obtained from both the methods. The first hybrid approach is ISM – analytic network process (ANP) – ELimination and Et Choice Translating REality (ELECTRE II) and the second hybrid approach is ISM – ANP – Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR). ISM was used to identify the inter relationship between the criteria. Inter-relationship of criteria obtained from ISM will serve as an input for ANP. The weights obtained from ANP will be used in ELECTRE II and VIKOR. ELECTRE II is an outranking method, whereas VIKOR is a compromise ranking method; comparison of both the methods was carried out in this study.

In this study, two modules ISM–ANP – ELECTRE and ISM–ANP – VIKOR were compared for the problem of sustainable supplier selection. ELECTRE results with a single solution showed that Supplier 2 can be selected as the best supplier; VIKOR result shows that Supplier 1 and Supplier 2 can be selected as the best suppliers.

The selection of sustainable supplier considering the interrelationship of criteria using ISM and ranking the alternatives using compromise and outranking techniques was found to be original and novel contribution of the author.

Amidst offshoring and reshoring trends, the purpose of this paper is to explore why business practitioners, especially from the labour-intensive clothing industry, choose to manufacture some products in proximity to the high-cost European market. Moreover, the rise of sustainability concerns led us to further explore whether these reasons relate to triple bottom line (TBL): business, environment and society.

The content analysis was adopted for within-case and cross-case analysis of data from semi-structured interviews of managers from 12 clothing companies.

Within-case analysis showed enablers and barriers (factors) of proximity manufacturing within each company’s characteristics under TBL. Cross-case analysis showed the most-mentioned enablers (high-quality suppliers, short lead-time and fast replenishment) and barriers (expensive production cost and lack of industrial set-up and seamstresses). The findings revealed both common and different factors from existing studies.

Besides being motives for companies to bring manufacturing back to Europe, the results can be used by researchers and companies to develop criteria and performance measures of manufacturing locations for enhancing the TBL sustainability. Future research may explore different locations and industries for possibilities of proximity–manufacturing generalisation.

Findings show that governments could focus on eliminating barriers of proximity manufacturing and creating favourable institutional infrastructure for the European clothing industry and sustainability.

This paper highlights updated proximity–manufacturing factors from practices in relation to TBL sustainability, including support for proximity manufacturing as a practice for TBL enhancement.