Strategic collaboration and sustainable supply chain management

A novel stochastic fuzzy decision model for agile and sustainable global manufacturing outsourcing partner selection in footwear industry

Purpose

The decision-making to outsource and select the most suitable global manufacturing outsourcing partner (MOP) is complex and uncertain due to multiple conflicting qualitative and quantitative criteria as well as multiple alternatives. Vagueness and variability exist in ratings of criteria and alternatives by group of decision-makers (DMs). The paper provides a novel Stochastic Fuzzy (SF) method for evaluation and selection of agile and sustainable global MOP in uncertain and volatile business environment.

Design/methodology/approach

Four main selection criteria for global MOP selection were identified such as economic, agile, environmental and social criteria. Total 16 sub-criteria were selected. To consider the vagueness and variability in ratings by group of DMs, SF method using t-distribution or z-distribution was adopted. The criteria weights were determined using the Stochastic Fuzzy-CRiteria Importance Through Intercriteria Correlation (SF-CRITIC), while MOP selection was carried out using Stochastic Fuzzy-VIseKriterijumskaOptimizacija I KompromisnoResenje (SF-VIKOR) in the case study of footwear industry. Sensitivity analysis was performed to test the robustness of the proposed model. A comparative analysis of SF-VIKOR and VIKOR was made.

Findings

The worker’s wages and welfare, product price, product quality, green manufacturing process and collaboration with partners are the most important criteria for MOP selection. The MOP3 was found to be the best agile and sustainable global MOP for the footwear company. In sensitivity analysis, significance level is found to have important role in MOP ranking. Hence, the study concluded that integrated SF-CRITIC and SF-VIKOR is an improved method for MOP selection problem.

Research limitations/implications

In a group decision-making, ambiguity, impreciseness and variability are found in relative ratings. Fuzzy variant Multi-Criteria Decision-Making methods cover impreciseness in ratings but not the variability. On the other hand, deterministic models do not cover either. Hence, the stochastic method based on the probability theory combining fuzzy theory is proposed to deal with decision-making problems in imprecise and uncertain environments. Most notably, the proposed model has novelty as it captures and reveals both the stochastic perspective and the fuzziness perspective in rating by group of DMs.

Practical implications

The proposed multi-criteria group decision-making model contributes to the sustainable and agile footwear supply chain management and will help the policymakers in selecting the best global MOP.

Originality/value

To the best of the authors’ knowledge, SF method has not been used to select MOP in the existing literature. For the first time, integrated SF-CRITIC and SF-VIKOR method were applied to select the best agile and sustainable MOP under uncertainty. Unlike other studies, this study considered agile criteria along with triple bottom line sustainable criteria for MOP selection. The novel method of SF assessment contributes to the literature and put forward the managerial implication for improving agility and sustainability of global manufacturing outsourcing in footwear industry.

Adapt or die: a competitive digital supply chain quality management strategy

Purpose

The evolution of modern digitalization technologies necessitates the development of a competitive digital supply chain quality management (SCQM) strategy by manufacturers. Using the new institutions and institutional theory (IIT), the study research first aims to identify the most important SCQM practices that can influence competitive performance (CP). Second, the authors intend to investigate the role of digital strategy alignment (DSA) in moderating the relationship between the multidimensionality of SCQM practices and CP among manufacturers.

Design/methodology/approach

The authors employ the Partial Least Squares-Structural Equation Modeling (PLS-SEM) technique to examine 225 valid samples from Malaysian manufacturers who use SCQM practices.

Findings

The study findings indicate that five of the twelve hypotheses developed were accepted. This suggests that supplier focus, strategic collaboration, information sharing and customer focus are positively and significantly correlated with CP. Unexpectedly, DSA moderates the relationship between leadership and CP.

Originality/value

This study extended the new IIT by empirically testing the six SCQM practices for CP in a DSA context, which can serve as a model for future research in the SCQM, CP and DS fields.

A modified range directional measure for assessing the sustainability of suppliers by DEA/UTASTAR

Sustainability in the supply chain means considering environmental, social, and economic practices. Conventional data envelopment analysis (DEA) models deal with desirable, discretionary, and nonnegative data. However, there might be undesirable outputs, nondiscretionary factors, and negative data. On the other hand, some criteria can be considered as outputs and inputs. These factors are named as the dual-role criteria. The objective of this paper is to develop a non-radial DEA model for dealing with negative data in the presence of undesirable, non-discretionary, and dual-role factors in weight restrictions context. The ordinal regression method, UTASTAR, is performed to define priorities in terms of criteria. The capabilities of the proposed method are compared with other methods. A case study is presented in which the best sustainable suppliers of SAPCO are selected. To check the importance of dual-role variables, two extra cases are considered.

The Effect of Relational Capital on Organizational Performance in Supply Chain: The Mediating Role of Explicit and Tacit Knowledge Sharing

Relational capital and organizational performance were important factors for achieving sustainable development of the supply chain, and knowledge sharing could create and maintain sustainable competitive advantages of the supply chain. This study examined the comprehensive relationship among relational capital, explicit and tacit knowledge sharing, and organizational performance and the mediating roles of explicit and tacit knowledge sharing between relational capital and organizational performance in the supply chain by using data collected from a questionnaire survey. SPSS, AMOS, and a structural equation model were used to analysis these data and the aforementioned relationships. The results confirmed that relational capital had a positive impact on explicit and tacit knowledge sharing, there was no relation to organizational performance, and explicit and tacit knowledge sharing played mediating roles between relational capital and organizational performance in the supply chain. The research results could provide theoretical guidance for managers to formulate sustainable development strategies that maintain good relationships and economic benefits of enterprises in the supply chain.

Identification of the Critical Factors for Global Supply Chain Management under the COVID-19 Outbreak via a Fusion Intelligent Decision Support System

Under the ravages of COVID-19, global supply chains have encountered unprecedented disruptions. Past experiences cannot fully explain the situations nor provide any suitable responses to these fatal shocks on supply chain management (SCM), especially in todays’ highly intertwined/globalized business environment. This research thus revisits and rechecks the crucial components for global SCM during such special periods, and the basic essence of such management covers numerous perspectives that can be categorized into a multiple criteria decision making (MCDM) approach. To handle this complex issue appropriately, one can introduce a fusion intelligent system that involves data envelopment analysis (DEA), rough set theory (RST), and MCDM to understand the reality of the analyzed problem in a faster and better manner. Based on the empirical results, we rank the priorities in order as cash management and information (D), raw material supply (B), global management strategy (C), and productivity and logistics (A) for improvement in SCM. This finding is confirmed by companies now undergoing a downsizing strategy in order to survive in this harsh business environment.

Environmentally responsible freight transport service providers' assessment under data-driven information uncertainty

Purpose

Freight transportation practices accounted for a significant share of environmental degradation and climate change over the years. Therefore, environmentally responsible transport practices (ERTPs) become a serious concern of freight shippers and transport service providers. Past studies generally ignored the assessment of ERTPs of freight transport companies during a transport service contract. To bridge the above literature gap, this paper proposed a hierarchical framework for evaluating freight transport companies based on ERTPs.

Design/methodology/approach

In a data-driven decision-making environment, transport firm selection is affected by multiple expert inputs, lack of information availability, decision-making ambiguity and background of experts. The evaluation of such decisions requires a multi-criteria decision-making method under a group decision-making approach. This paper used a data-driven method based on the intuitionistic fuzzy-set-based analytic hierarchy process (IF-AHP) and VIseKriterijumska Kompromisno Rangiranje (IF-VIKOR) method. The applicability of the proposed framework is validated with the Indian freight transport industry.

Findings

The result analysis shows that environmental knowledge sharing among freight transport actors, quality of organizations human resource, collaborative green awareness training programs, promoting environmental awareness program for employees and compliance of government transport emission law and practice have been ranked top five ERTPs which significantly contribute to the environmental sustainability of freight transport industry. The proposed framework also ranked freight transport companies based on ERTPs.

Research limitations/implications

This research is expected to provide a reference to develop ERTPs in the emerging economies freight transport industry and contribute to the development of a sustainable freight transport system.

Originality/value

This study assesses the environmental responsibility of the freight transportation industry. The emerging economies logistics planners can use proposed framework for assessing the performance of freight transportation companies based on ERTPs.

Open-Mindedness Culture, Knowledge-Sharing, Financial Performance, and Industry 4.0 in SMEs

Due to limited resources, the implementation of Industry 4.0 solutions is a big challenge in small- and medium-sized enterprises (SMEs). Therefore, it is important to identify the factors that facilitate such implementation. However, empirical research in this area is insufficient. The purpose of this article is to investigate whether open-mindedness culture, knowledge-sharing, and financial performance have a significant impact on willingness to implement Industry 4.0 in SMEs. To achieve the purpose of the article, quantitative research was conducted. Data from 562 Polish manufacturing SMEs were collected and analyses were performed using partial least squares path modeling (PLS-PM). The study results reveal that open-mindedness culture has both a direct and indirect (through knowledge sharing) impact on willingness to implement Industry 4.0 in SMEs. Results suggest that in terms of micro-enterprises, open-mindedness is more important and knowledge-sharing is less important for willingness to implement Industry 4.0 than in larger enterprises. Moreover, regardless of the company size, financial performance is positively related to willingness to implement Industry 4.0. The research results provide SME managers with guidelines on what activities within the company should be strengthened if the goal of the company is to implement Industry 4.0 solutions.

Influence of Social Media Usage on the Green Product Innovation of Manufacturing Firms through Environmental Collaboration

Firms are finding it increasingly important to leverage social media to facilitate knowledge access, get valuable feedback, and improve innovations to cater for emerging markets. However, using social media without integrating other key factors does not seem to add value to innovation efforts. Therefore, this study investigates the potential of social media usage (SMU) in enhancing green product innovation (GPI) and how two types of environmental collaboration may affect that relationship, which is a subject that has been under-explored. First, the literature on the expansion of the use of social media in enhancing GPI was reviewed to develop the theoretical framework and hypotheses. Then, data collected from 211 manufacturing firms were analysed using structural equation modelling to examine the proposed relationship. The results revealed that SMU does not directly influence GPI. Rather, internal environmental collaboration (IEC) and environmental collaboration with suppliers (ECS) fully mediate the relationship between SMU and GPI. The results further disclosed a positive relationship between IEC and ECS, where both types of environmental collaboration seem to be key factors in improving GPI. Hence, this study highlights the importance of knowledge sharing through environmental collaborations for the generation of ideas to improve products in order to remain competitive in the market.

Mediating effect of big data analytics on project performance of small and medium enterprises

Purpose

This study aims to investigate the mediating role of “Big Data Analytics” played between “Project Performance” and nine factors including top management, project knowledge management focus on sustainability, green purchasing, environmental technologies, social responsibility, project operational capabilities, project complexity, collaboration and explorative learning, and project success.

Design/methodology/approach

A sample of 321 responses from 106 Indian manufacturing small and medium-scaled enterprises (SMEs) was collected. Data were analyzed using empirical analysis through structural equation modeling.

Findings

The result shows that project knowledge management, green purchasing and project operational capabilities require the mediating support of big data analytics. The adoption of big data analytics has a positive influence on project performance in the manufacturing sector.

Practical implications

This study is useful to SMEs managers, practitioners and government policymakers to develop an understanding of big data analytics, eliminate challenges in the adoption of big data, and formulate strategies to handle projects efficiently in SMEs in the context of Indian manufacturing.

Originality/value

For the first time, big data for manufacturing firms handing innovative projects was discussed in the Indian SME context.

Arbitrage in gray markets and its impact on supply chain decisions

Purpose

The purpose of this paper is to investigate the impacts of different gray markets’ structures on both supply chain decisions and associated profits.

Design/methodology/approach

Within the context of gray markets, using game theory approach in this paper, supply chains have been considered as assets of manufacturers, distributors and speculators, within which manufacturers sell products to distinctive markets either directly or through authorized distributors, while speculators buy products from a lower price market and then sell them in a higher price market. Our study has examined different decision variables within such a framework.

Findings

Considering a situation where one manufacturer sells its products either directly in one market (Market 1) or through its authorized distributor (Market 2), due to different products prices in both markets, results have shown that, when market elasticity is less than its critical value, a speculator can sell a gray market product arbitrage in market 2, whereas when the market elasticity is greater than its critical value, a speculator can sell a gray market product arbitrage in market 1. In addition, manufacturers—as leaders of Stackelberg game—are always the most profitable stakeholders within a gray market supply chain.

Practical implications

In this study, equilibrium results for each market have been obtained, optimal results have been compared, and accordingly, valuable insights have been developed. Such results would help managers to take better managerial decisions, as well as strategizing policies in gray markets.

Originality/value

In this paper, we have considered a gray market where both distributors and speculators exist and act as parallel channels. To the best of our knowledge, the extant literature focuses either on distributors or speculators, but never concurrently on both. In fact, the coexistence of one distributor and one speculator in a gray market will impact their own decisions, as well as both decisions and profits of other stakeholders, and hence, will exert an impact on the manufacturer side.

How to use fuzzy screening system and data envelopment analysis for clustering sustainable suppliers? A case study in Iran

Purpose

The aim of this paper is to classify suppliers into some clusters based on sustainability factors. However, there might be some unqualified suppliers and we should identify and remove those suppliers before clustering.

Design/methodology/approach

First, using fuzzy screening system, the authors identify and remove the unqualified suppliers. Then, the authors run their proposed clustering method. This paper proposes a data envelopment analysis (DEA) algorithm to cluster suppliers.

Findings

This paper presents a two-aspect DEA-based algorithm for clustering suppliers into clusters. The first aspect applied DEA to consider efficient frontiers and the second aspect applied DEA to consider inefficient frontiers. The authors examine their proposed clustering approach by a numerical example. The results confirmed that their method can cluster DMUs into clusters.

Originality/value

The main contributions of this paper are as follows: This paper develops a new clustering algorithm based on DEA models. This paper presents a new DEA model in inefficiency aspect. For the first time, the authors’ proposed algorithm uses fuzzy screening system and DEA to select suppliers. Our proposed method clusters suppliers of MPASR based on sustainability factors.