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Outsourcing logistical activities have become a widely used approach for firms to avoid high fixed costs and heavy investment requirements and to achieve competitive advantages. Lean six sigma (LSS) has been accepted globally across sectors as a management strategy for achieving process excellence. The purpose of this paper is to feature the application of LSS for improving the supplier selection process (SSP) of outsourced logistics services in a multinational health-care company.

This study is based on an action research case study conducted on the SSP of the freight and distribution department in a multinational health-care company. This paper reports on the application of the LSS define-measure-analyze-improve-control (DMAIC) approach for reducing supplier selection lead time.

The study features a real-world case study of the LSS DMAIC application to improve the supplier selection process of a large health-care company. The key issues that were identified are lack of information visibility, top-down changes and unclear communication lines. To counteract these three root causes, the lean six sigma techniques that are implemented are the 5S, stakeholder analysis and standard operating procedure.

This research provided empirical evidence of how practical challenges in SSP can be managed with the use of LSS. It further proposed plausible solutions for reducing and sustaining improved outcomes. As the study is limited to one case, the validity of the results can be improved by including more organisations and more case studies from other similar organisations.

Research in supplier selection processes rarely links continuous improvement ideology such as LSS to support strategic selection and procurement of logistics services. This paper could serve as a resource for both practitioners to derive useful implications and to academicians as it contributes to the LSS body of knowledge for further theory testing.

In a developing economy like India, the contribution of small- and medium-sized enterprises (SMEs) to the national gross domestic product is significant. This sector creates immense employment opportunities and produces economic products and services. To survive in the globalized marked condition, it is essential for SMEs to be competitive on several fronts such as quality, cost, delivery, lead time, flexibility, etc. Hence, it is imperative for them to have a sound supplier base. Therefore, supplier selection problem (SSP) has a vital role to play in supply chain management of SMEs. The paper aims to discuss these issues.

However, SSP has now become a significant challenge to address due to the complexity, vagueness and various criteria involved in it. Recently, fuzzy Technique for Order Performance by Similarity to Ideal Solution method has been widely used to tackle such problems.

The present paper aims at developing an intelligent system for SSP, which can consider the multiple criteria and the uncertainty aspects in the decision process. A case study of a small-scale manufacturing company has been presented.

This study provides a guideline for SME sector to implement intelligent systems for supplier selection decision-making problems. Case application concludes that this model improves firm’s decision making and suppliers’ performance.

The proposed intelligent model can provide the guidelines and directions for the decision makers to effectively choose suppliers in the current competitive environment. And it also provides an opportunity for supplier improvement.

The purpose of this paper is to present an approach to successful supplier selection process (SSP) by understanding the dynamics between SSP enablers (SSPEs), using interpretive structure modelling (ISM) methodology and find out driving and the dependence power of enablers, using fuzzy MICMAC (Matriced’ Impacts Croisés Appliquée á un Classement) analysis.

The group of experts from industries and the academics were consulted and ISM is used to develop the contextual relationship among various SSPEs for each dimension of supplier selection. The results of the ISM are used as an input to the fuzzy MICMAC analysis to identify the driving and the dependence power of SSPEs.

The research presents a hierarchy-based model and mutual relationships among SSPEs. The research shows that there is a group of SSPEs having a high driving power and low dependence, which requires maximum attention and is of strategic importance, while another group consists of those SSPEs that have high dependence and low driving power, which requires the resultant actions.

The weightage obtained for the ISM model development and fuzzy MICMAC are obtained through the judgment of academician and few industry experts. It is the only subjective judgment and any biasing by the person who is judging the SSPEs might influence the final result. A questionnaire survey can be conducted to catch the insight on these SSPEs from more organizations.

This category provides a useful tool for top management to differentiate between independent and dependent SSPEs and their mutual relationships which would help them to focus on those key SSPEs that are most significant for effective supplier selection.

Arrangement of SSPEs in a hierarchy, the categorization into the driver and dependent categories, and fuzzy MICMAC are an exclusive effort in the area of supplier selection.

This article investigates the importance of the supplier management process in the quality of the final product. A methodology is developed to analyze the variables involved in the supplier management process and it is illustrated with a case study of the chair manufacturing industry. Research results indicate that the supplier selection process appears to be the most significant variable as it helps in achieving high quality products and customer satisfaction. This paper shows the different analytical steps that arise naturally in the systematic categorization of variables for supplier management. Nine variables related to the supplier selection process were analyzed. Each of these variables was then evaluated through an experimental design using statistical information based on three factors, namely, quality, cost and productivity.

In developing countries such as India, start-ups play an essential role in “industrial output,” “Gross Domestic Product ” and “employment creation.” Evidence suggests that pandemics have risen over the last century due to rising global travel and assimilation, urbanization, alterations in land use, and significantly larger exploitation of the natural environment. These trends are likely to continue and intensify. These pandemic episodes affect businesses, especially start-ups. Supplier selection is among the vital critical elements that start-ups must include in start-ups' strategy procedures during the pandemic episodes. This study's focus is to “identify,” “analyze,” and “categorize” the factors affecting supplier selection in start-ups during frequent pandemic episodes like coronavirus disease 2019 (COVID-19).

Through “literature review” and “experts' opinion” from various start-ups in India, ten affecting factors were identified. Total Interpretative Structural Modeling (TISM) and Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) were employed to analyze the interrelationship among the factors affecting the supplier selection on start-ups during frequent pandemic episodes, and these factors were ranked as “autonomous,” “independent,” “linkage,” and “dependent” factors.

The findings show that “performance history,” “service levels,” “technical capability,” and “financial stability” are the most critical factors affecting the supplier selection on start-ups during frequent pandemic episodes. The next importance should be safety and environmental concern” and “quality.”

The factors affecting supplier selection on start-ups during frequent pandemic episodes are the current focus of this study. This study is mainly performed on Indian start-ups and can be extended to other countries.

The start-ups can rely on this study to clearly understand the factors affecting the supplier selection on start-ups during frequent pandemic episodes.

There is no research regarding factors affecting supplier selection on start-ups during the COVID-19 emergencies. This research gap is filled by analyzing aspects linked to supplier selection in start-ups. This gap inspired the present study, which employs the “Total Interpretive Structural Modeling (TISM)” technique to uncover supplier selection determinants and investigate hierarchical interconnections among factors influencing/affecting supplier selection in start-ups during frequent pandemic episodes.

Different entities in a supply chain network operate in a highly interdependent environment when it comes to improving performance of the network in terms of objectives such as delivery performance, quality assurance and cost minimization, etc. In this research, an attempt has been made to evaluate the supplier performance by adopting evolutionary fuzzy system owing to the linguistic nature of the attributes associated with the suppliers and manufacturing units. The proposed methodology offers consistently good performance when applied to a variety of standard problems related to evaluation of supplier's performance available in the literatures.

This paper aims to examines the moderating effect of small vs large supply base size on the relationship between strategic sustainable purchasing (SSP) and organizational sustainability performance (OSP). SSP is conceptualized as a dynamic capability consisting of strategic purchasing and environmental purchasing. Environmental collaboration is conceptualized as a mediator between SSP and OSP. Extant research has not examined the effect of the size of the supply base on the relationship between SSP and OSP.

The hypothesized relationships are tested using a two-step multi-group analysis in partial least squares-structural equation modeling (PLS-SEM).

A small supply base size positively moderates the relationship between SSP and environmental collaboration, thus achieving OSP. In contrast, when the supply base is large, strategic purchasing is positively associated with environmental collaboration, while environmental purchasing is negatively related to environmental collaboration. A large supply base has a positive relationship to environmental collaboration and economic sustainability, while the relationship between environmental collaboration and environmental and social performance is not significant.

This research argues that despite the nuances in the moderating effects of small versus large supply base size, managers need to invest in both dynamic and relational capabilities to achieve organizational sustainability.

Scant research is available in supply chain management research that has examined the important effect of the supply base size on the relationship between SSP and OSP. This research aims to fill this gap. The study helps practitioners understand the effects of supply base sizes for their organizations, increase interrelationships among suppliers, reduce the level of differentiation among them, and, thereby, reduce costs and increase revenues.

This paper draws on the experiences of project marketing and solution selling to improve the understanding of how to create superior value for customers. Project marketing and solution selling have both developed approaches to deal with complex marketing situations for a number of years now. The upstream mobilization of customer network actors and the downstream enlargement of the content and scope of the offering are the key features of these approaches.

This paper presents two case studies to focus attention on elements that are crucial to this twin-track approach. The downstream extension of the offering relies on services supporting the customer's action (SSC), which supplement traditional services that support the supplier's product (SSP). The upstream extension leads to an introduction to other types of services or elements of the offering – the services supporting the customer's network actors (SSCN).

Furthermore, the paper proposes a marketing process that takes the supplier's viewpoint, for whom the entire approach is a network mobilization, into account. This approach to the offering, which included SSP, SSC, and SSCN, is typical of a network strategy in which the supplier recruits and enrolls new actors to (re)model the buying center.

This marketing process is in tune with the latest developments of the service-dominant (S-D) logic, as it proposes a move from the value chain toward a value-creation network/constellation. Consequently, creating superior value for customer means mobilizing and servicing actors far beyond the boundaries of the buying center, supply chain, and customer solution net.

The purpose of this paper is to demonstrate a newly developed integrated multi‐criteria decision method (MCDM) with two‐sided preferences or selection scenario in build‐to‐order supply chains so as to explore the future applications like supplier parks.

The current state of the consolidation scenario of original equipment manufacturers (OEMs) and suppliers is presented and build‐to‐order imperativeness in the case of a supplier park is highlighted. These motivations guided the need for development of a new technique in two‐sided selection scenario. The MCDM technique, like analytical network process (ANP), is integrated with a mutual compatibility index. A hypothetical example is presented to demonstrate the proposed methodology.

The newly developed integrated methodology helps the decision maker to incorporate both sided preferences in the final supplier‐manufacturer selection.

This paper allows the reader to understand the build‐to‐order supply chain and supplier park situation. The emerging trends in the automobile sector in India are also highlighted. This new integrated technique certainly adds value to the decision maker in today's competitive world.