Supplier selection in agile supply chains: An information-processing model and an illustration

An integrated multi-criteria decision-making approach to optimize the number of leagile-sustainable suppliers in supply chains

Global supply chains are increasingly becoming complex by having numerous suppliers around the world. To manage this complexity, organizations must identify the optimum number of suppliers. There have been many examples in the literature that used different approaches to solve this problem. Despite the importance of this issue, less attention has been paid to it and managers of the companies do not know how, and based on which approach and criteria, they should determine the optimal number of suppliers which leads to lower cost and higher reliability of the production line. Therefore, in this study, a hybrid methodology is proposed to expose the process of this problem which helps managers to learn how they can determine the optimal number of suppliers. We address this gap by developing an integrated approach based on multi-criteria decision-making (MCDM) comprising best-worst method (BWM), simple additive weighting (SAW), and technique for order preference by similarity to ideal solution (TOPSIS), and simulation to determine the optimal number of suppliers. This study utilizes a comprehensive approach based on leagile and environmentally sustainable criteria to determine the optimal number of suppliers. To examine the efficiency of the proposed approach, an empirical case study is conducted in an Iranian oil company. The final results represent that the scenario with a 1-1-1 arrangement (one supplier for each type of equipment) is the best possible scenario to determine the optimal number of leagile-sustainable suppliers. To examine the reliability and robustness of the obtained results, a sensitivity analysis based on the three most important criteria is conducted. Finally, discussions on the findings as well as theoretical and managerial implications are presented.

A Self-Assessment Framework for Global Supply Chain Operations

This research developed an effective supply chain management (SCM) operation model and a corresponding diagnostic methodology in the global competitive environment by combining three phases and methodologies. In Phases 1, a list of impact factors was collected from relevant studies, and a hierarchy for the current complex research issue was established. In Phase 2, an expert survey was conducted for enhancing the content effectiveness of the model. Subsequently, an analytic hierarchy process (AHP) was applied to determine the weights of those factors. In Phase 3, a self-assessment framework was developed to examine the effectiveness of the global SCM. Finally, a case was analyzed to verify the effectiveness of the self-assessment scales. The results show that the concept of global SCM tends to be broader and more comprehensive than traditional one. Especially in the coordination and cooperation between market, organization itself and suppliers, while using information technology as a communication tool.

The green-agile supplier selection problem for the medical devices: a hybrid fuzzy decision-making approach

The supplier selection problem (SSP) is known as one of the major issues in the supply chain management area. In this field, the literature shows that the combination of green and agile indicators has been ignored by researchers. Hence, this research attempts to study the SSP considering green and agile aspects, simultaneously. To do this, an efficient hybrid fuzzy decision-making approach is developed based on the Fuzzy Decision-Making Trial and Evaluation Laboratory (FDEMATEL), Fuzzy Best-Worst Method (FBWM), Fuzzy Analytic Network Process (FANP), and Fuzzy Vlse Kriterijumsk Optimizacija Kompromisno Resenje (FVIKOR) methods. Then, to show the efficiency and application of the proposed approach, a case study in the medical devices industry is investigated. After determining the main indicators and alternatives, the interrelationships between indicators are identified employing FDEMATEL. Then, the weights of indicators are calculated using integrated FBWM-FANP. Finally, the potential suppliers are ranked applying FVIKOR. Based on the obtained results, price and greenness are the more important aspects and also material costs, environmental performance evaluation, manufacture flexibility, service level, and system reliability are the most important criteria for the green-agile supplier selection problem in the medical devices industry. Since all of the consistency ratios are less than 0.1, the reliability of the results is proved. On the other side, the results of conducting sensitivity analysis show that by changing the defuzzification methods, there is no significant change in the obtained results that demonstrates the validity of the proposed approach. Eventually, based on the obtained results, suppliers #1 and #5 are the best suppliers for the considered company.

Risk Management: Rethinking Fashion Supply Chain Management for Multinational Corporations in Light of the COVID-19 Outbreak

Through an international business risk management lens, the widespread and catalytic implications of the 2020 COVID-19 pandemic on the supply chains (SCs) of fashion multinational corporations (MNC) are analyzed to contribute to existing research on supply chain management (SCM). While a movement towards agile, networked supply chain models had been in consideration for many firms prior to the outbreak, the pandemic highlights issues inherent in supply chains that employ concentrated production. We examined the current state of fashion supply chains, risks that have arisen historically and recently, and existing risk mitigation methods. We found that while lean supply chain management is primarily favored for its cost and waste reduction advantages, the structure is limited by the lack of supply chain transparency that results as well as the increasing demand volatility observed even before the COVID-19 outbreak. Although this problem might exist in the agile supply chain, agile supply chains combat this by focusing on enhancing communication and buyer-supplier relationships to improve information exchange. However, this structure also entails an associated increase in inventory and inventory costs. The COVID-19 pandemic has caused supply and demand disruptions which have resonating effects on supply chain activities and management, indicating a need to build flexibility to mitigate epidemic and demand risks. To address this, several strategies that firms can adopt to control for such risks are outlined and key areas for further research are identified which consider parties both upstream and downstream of the fashion supply chain.

Green Supplier Selection Criteria: From a Literature Review to a Comprehensive Knowledge Base

The supplier selection problem is one of the most important competitive challenges used by modern enterprises. Due to the fact that companies have to improve their practices in the management of a green supply chain that aims to respect green practices and technologies to increase sustainability, selecting the optimal green supplier is a challenging multi-dimensional problem. While most of the research has focused on the development and improvement of new methods, relatively limited attention has been paid to the identifying sets of criteria and capturing the domain knowledge. This issue is significant because a correctly identified set of criteria plays a vital role in supporting the decision-making process. The approach presented creates a gap between classical assumption of decision making and knowledge-based problem structuring. The current paper presents a methodological and practical background for capturing and handling knowledge about green supplier selection criteria, supported by a formal guideline for their appropriate acquisition. In addressing this research challenge, the aims of this paper are twofold: providing meta-analysis to reveal a collection of key data supported by a formal and trustworthy bibliometric analysis, and capturing knowledge in one place in the form of ontology for enabling selection and evaluation criteria of green suppliers is proposed. The proposed ontology is available for public use.

Strategic partner evaluation criteria for logistics service provider networks

Purpose

The purpose of this paper is to establish criteria for evaluating strategic partners in a network of logistics service providers (LSPs) to show how analytical network process (ANP) can be used to identify the weights of these criteria on a case-specific basis, and to investigate whether the ANP model can be used as a starting point to evaluate strategic partners for other LSP networks.

Design/methodology/approach

Based on a literature review of vertical cooperation, the authors develop an overview of criteria for the evaluation of partners in a network of LSPs. The authors then apply ANP at LSP1 to validate the criteria, identify weights for these criteria and to validate model outcomes. Furthermore, the authors investigate whether the ANP model developed for LSP1 can be applied to another LSP with similar characteristics (LSP2). In-depth interviews are used to draw conclusions on the modeling approach and the model outcomes.

Findings

The research shows that evaluation criteria for partners in vertical partnerships between shippers and LSPs are applicable to LSP partners in horizontal partnership networks. The ANP model with criteria weights provides a good starting point for LSPs to customize the evaluation framework according to their specific needs or operating environments.

Originality/value

Limited research is available on evaluating LSP partners in horizontal partnerships. To the best of the authors’ knowledge, this paper is the first to bring forward horizontal LSP partner evaluation criteria to develop an ANP model for LSP partner evaluation and to apply this to two cases, and to provide a starting point for evaluating partners in similar horizontal LSP networks.

Agile manufacturing: a systematic review of literature and implications for future research

Purpose

Agile manufacturing (AM) has evolved as a revolutionary way of manufacturing the products while managing the uncertainties, product introduction time, responsiveness, innovation, superior quality, etc. along the supply chain to satisfy the ever increasing customer demand and to maximize the profit. The purpose of this paper is to critically analyze the literature related to various dimensions of AM and to report the findings.

Design/methodology/approach

This paper presents the reviews of 300 scholarly articles from 1993 to 2016 by various researchers and practitioners on AM collected from different sources, i.e. Google Scholar and ResearchGate. The information related to AM is also captured during industrial visits to different Indian manufacturing plants.

Findings

AM definitions are reported along divergent scopes and objectives in the literature. The researchers have given importance on performance measurement and process analysis through empirical and descriptive analysis whereas its implementation issues are neglected. It is also observed that the effort made on AM is significant for manufacturing industries which is overlooked in service industries.

Practical implications

This literature review has identified many research gaps in AM which were not paid attention before. Researchers can address these research gaps for strengthening the AM implementation.

Originality/value

In total, 300 research papers are reviewed and analyzed to capture the various aspects of AM and its related issues but not restricted to research methodologies, author profiles, types of industries, tools/techniques/methodology used, etc.

Supplier selection in agile supply chain

Purpose

The recent global market trend is seemed enforcing existing manufacturing organizations (as well as service sectors) to improve existing supply chain systems or to take up/adapt advanced manufacturing strategies for being competitive. The concept of the agile supply chain (ASC) has become increasingly important as a means of achieving a competitive edge in highly turbulent business environments. An ASC is a dynamic alliance of member enterprises, the formation of which is likely to introduce velocity, responsiveness, and flexibility into the manufacturing system. In ASC management, supplier/partner selection is a key strategic concern. Apart from traditional supplier/partner selection criteria; different agility-related criteria/attributes need to be taken under consideration while selecting an appropriate supplier in an ASC. The paper aims to discuss these issues.

Design/methodology/approach

Therefore, evaluation and selection of potential supplier in an ASC have become an important multi-criteria decision making problem. Most of the evaluation criteria being subjective in nature; traditional decision-making approaches (mostly dealing with objective data) fail to solve this problem. However, fuzzy set theory appears an important mean to tackle with vague and imprecise data given by the experts. In this work, application potential of the fuzzy multi-level multi-criteria decision making (FMLMCDM) approach proposed by Chu and Velásquez (2009) and Chu and Varma (2012) has been examined and compared to that of Fuzzy-techniques for order preference by similarity to ideal solution (TOPSIS) and Fuzzy-MOORA in the context of supplier selection in ASC.

Findings

It has been observed that similar ranking order appears in FMLMCDM as well as Fuzzy-TOPSIS. In Fuzzy-MOORA, the best alternative appears same as in case of FMLMCDM as well as Fuzzy-TOPSIS; but for other alternatives ranking order differs. A comparative analysis has also been made in view of working principles of FMLMCDM, Fuzzy-TOPSIS as well as Fuzzy-MOORA.

Originality/value

Application feasibility of FMLMCDM approach has been verified in comparison with Fuzzy-TOPSIS and Fuzzy-MOORA in the context of agile supplier selection.

Supply chain strategy and the role of suppliers: evidence from the Indian sub-continent

Purpose

Supply chain strategy is widely recognized as being a crucial component of a broader corporate strategy. However, the relationships between a firm’s strategic supply chain focus, the tactical orientation of its suppliers, and the firm’s performance, are less well understood. Much of what is known is also based on developed country contexts. The purpose of this paper is to empirically examine relationships between a buying firm’s supply chain strategy and operational dimensions of its suppliers in a developing country context.

Design/methodology/approach

A structural equation model is developed and tested using empirical data drawn from 296 organizations in India and Pakistan.

Findings

The results demonstrate a positive relationship between a firm’s strategic supply chain focus (lean and responsiveness) and key supplier practices (quality, cost effectiveness, delivery, and flexibility), which in turn have a positive impact on firm performance (operational, quality and market, and financial).

Practical implications

The study paper offers supply chain managers in developing markets with insights that can shape effective supplier selection and management and lead to positive performance outcomes.

Originality/value

The results provide insights into supply chain strategy, and empirically validate the importance of the alignment between strategy and the ability of suppliers to execute in a corresponding manner. It also offers evidence of the impact of the buyer-supplier interface in a developing market context.

Supplier/partner selection in agile supply chain

Purpose

– The concept of agile supply chain (ASC) has become increasingly important as means of achieving a competitive edge in turbulent business environments. An ASC is a dynamic alliance of member enterprises, the adaptation of which is likely to introduce velocity, responsiveness and flexibility into the manufacturing system. In ASC management, supplier/partner selection is a key strategic concern; influenced by various agility-related criteria/attributes. Therefore, evaluation and selection of potential supplier in an ASC has become an important multi-criteria decision-making problem. The purpose of this paper is to report, a supplier selection procedure (module) in the context of ASC.

Design/methodology/approach

– During supplier selection, subjectivity of evaluation information (human judgment) often creates conflict and bears some kind of uncertainty. To overcome this, the present work attempts to explore vague set theory to deal with uncertainties in the supplier selection decision-making process. Since, vague sets can provide more accurate information as compared to fuzzy sets. It considers true membership function as well as false membership function which give more superior results for uncertain information. In this procedure, first, linguistic variables have been used to assess appropriateness rating (performance extent) as well as priority weights for individual quantitative or qualitative criterions. Second, the concept of degree of similarity and probability of vague sets has been used to determine appropriate ranking order of the potential supplier alternatives.

Findings

– A case empirical example has been provided. It has been proved that the methodology would be fruitful in considering different evaluation criterion (indices); may be contradicting in nature like beneficial and cost criterions. The application of vague set theory has also been proved as a better option to work under uncertain (fuzzy) decision-making environment in comparison to fuzzy set theory.

Originality/value

– The application of vague set theory in multi-criteria group decision making has been reported in literature to a limited extent. Application of vague set as a decision-making tool in agile supplier selection appears relative new and unexplored work area. The work has got remarkable managerial implications.

Multi-period demand allocation among supplier in a supply chain

Purpose

– This paper aims to address the problem of optimal allocation of demand of items among candidate suppliers to maximize the purchase value of items. The purchase value of the items directly relates to cost and quality of raw materials purchased from the supplier. In an increasingly competitive environment, firms are paying more attention to selecting the right suppliers for procurement of raw materials and component parts for their products. The present research work focuses on this issue of supply chain management.

Design/methodology/approach

– This present research work devises a hybrid algorithm for multi-period demand allocation among the suppliers. The customer demand is allocated by using a hybrid algorithm based on the technique for order preference by similarity to ideal solution (TOPSIS), fuzzy set theory and the mixed linear integer programming (MILP) approaches.

Findings

– The supply chain network is witnessing a changing business environment due to government policies aimed at promoting new small manufacturing enterprises (small and medium-sized enterprises) for intermediate parts and components. Hence, the managers have an option to select a new group of suppliers and allocate the optimal multi-period demand among the new group of suppliers to maximize their purchase value. In this context, the proposed hybrid model would be beneficial for the managers to operate their supply chain effectively and efficiently. The present research work will be helpful for the managers who are interested to reconfigure their supply chain under the failure of any supply chain partner or in a changing business environment. The model provides flexibility to the managers for evaluation of the different available alternatives to take a decision of optimal demand allocation among the suppliers. The proposed hybrid (fuzzy, TOPSIS and MILP) model provides more objective information for supplier evaluation and demand allocation among suppliers in a supply chain. The managers can use the proposed model to the analysis of other management decision-making problems.

Originality/value

– This present research work devises a hybrid algorithm for multi-period demand allocation among the suppliers. This hybrid algorithm prioritizes the suppliers and then allocates the multi-period demand among the suppliers. The customer demand is allocated by using a hybrid algorithm based on the technique for order preference by similarity to ideal solution (TOPSIS), fuzzy set theory and the mixed linear integer programming (MILP) approaches.

How Australian manufacturing firms perceive and understand the concepts of agility and flexibility in the supply chain

Purpose

– The purpose of this paper is to address an important question which centres on investigating how do manufacturing businesses perceive and understand the concepts of agility and flexibility in their supply chains (SCs).

Design/methodology/approach

– A case study approach was utilised and data were gathered from semi-structured interviews with ten organisations in the Australian manufacturing sector. Data analysis was conducted using analytic techniques based on, for example, pattern matching and cross-case synthesis.

Findings

– Findings confirmed that there is some ambiguity concerning the understanding of the terms agile and flexible, both within and between organisations. The implications are that there is often little consistency in the way the terms are operationalised and then applied. In this regard, and to inform future research, the paper offers empirically grounded definitions for SC agility and flexibility. Moreover, four propositions are developed and discussed which shed light on the dynamics of agility and flexibility in the SC.

Originality/value

– This is one of the first empirical studies to address some of the apparent inconsistencies between organisational applications of agility and flexibility, and their impact on SC operations.

Benchmarking suppliers’ performance when some factors play the role of both inputs and outputs

Purpose

– The purpose of this paper is to develop a slack-based measure (SBM) model in the presence of dual-role factor. Then it is applied in supplier selection problem.

Design/methodology/approach

– The developed model in this paper is based on data envelopment analysis (DEA) technique.

Findings

– The proposed evaluation platform is capable of identifying ill-performing suppliers which seek to future improvement. The findings provide valuable insights for practitioners, as well as academicians, policy makers and also integrate selection criteria under the supply chain.

Originality/value

– This is the first time that a non-radial DEA model considers dual-role factors. The proposed model does not deal with dual-role factor as a non-discretionary factor. The proposed model considers dual-role factors on both the input and output sides in a similar manner. The proposed model can fully measure the inefficiency of suppliers. The proposed model can give a complete ranking of suppliers.