PurposeThis study investigates how dynamic capability (DC) relationships and deployment patterns enable firms to transition from sustainable supply chain management to circular supply chains (CSC).Design/methodology/approachA mixed-methods, exploratory sequential design combined a multiple case analysis of four multinational manufacturing firms with quantitative validation. The qualitative phase analyzed semi-structured interviews and corporate documents to identify DCs and their deployment patterns. The quantitative phase employed Ward's hierarchical clustering on academic expert evaluations to examine relationships among capabilities, refining case-derived patterns into generalizable configurations that enable CSC transitions.FindingsThis research identifies Circular DCs into three groups, with their relationships facilitating the adoption of circularity. Foundational Innovation DCs (Technology Management, Product Design Management, Process Innovation) establish an internal infrastructure to enable circularity. Transitional Collaboration DCs (Supply Chain Collaboration, Supply Market Orientation) facilitate integration across the supply chain partners. Scaling Enablement capabilities (Human Resource Management, Marketing) support ongoing transformation. These groups enable firms to progress through three practice types supporting circularity strategies. Foundational practices emerge from complementary relationships among Foundational Innovation DCs deployed at balanced levels of reconfiguring and seizing. Transitional practices emerge when Transitional Collaboration DCs form integrative relationships with established Foundational Innovation DCs. Scaling practices require reconfiguring the dominant deployment of both Foundational Innovation and Transitional Collaboration DCs, with support from Scaling Enablement capabilities.Research limitations/implicationsThe limited longitudinal analysis and sample size suggest caution in generalization. Future research should examine DCs across diverse contexts and timeframes.Practical implicationsThe framework directs the sequencing of capability development, starting with establishing Foundational Innovation DCs through balanced deployment, then adding Transitional Collaboration DCs once the foundations are in place, and finally developing Scaling Enablement capabilities for ongoing transformation.Social implicationsThe research highlights ways to improve societal well-being by emphasizing collaboration among supply chain partners. These findings support sustainable employment and shape public attitudes toward circular practices.Originality/valueThis study advances DC theory by showing that adopting circularity depends on specific relational configurations and deployment patterns rather than individual capability strength. It reveals how complementary, integrative, and enabling relationships across deployment levels facilitate collaborative transitions to CSC practices.

PurposeRecently, interest in sustainability has grown globally in the heavy vehicle and equipment industry (HVEI). However, this industry's complexity poses a challenge to the implementation of generic sustainable supply chain management (SSCM) practices. This study aims to identify SSCM's barriers, practices and performance (BPP) indicators in the HVEI context.Design/methodology/approachThe results are derived from case studies of four multinational manufacturers. Within-case and cross-case analyses were conducted to categorise the SSCM BPP indicators that are unique to HVEI supply chains.FindingsThis study's analysis revealed that supply chain cost implications and a deficient information flow between focal firms and supply chain partners are the key barriers to SSCM in the HVEI. This analysis also revealed a set of policies, programmes and procedures that manufacturers have adopted to address SSCM barriers. The most common SSCM performance indicators included eco-portfolio sales to assess economic performance, health and safety indicators for social sustainability and carbon- and energy-related measures for environmental sustainability.Practical implicationsThe insights can help HVEI firms understand and overcome the typical SSCM barriers in their industry and develop, deploy and optimise their SSCM strategies and practices. Managers can use this knowledge to identify appropriate mechanisms with which to accelerate their transition into a sustainable business and effectively measure performance outcomes.Originality/valueThe extant SSCM literature has focused on the light vehicle industry, and it has lacked a concrete examination of HVEI supply chains' sustainability BPP. This study develops a framework that simultaneously analyses SSCM BPP in the HVEI.

Sustainable business practices are those that allow companies to increase their profit while still considering the triple bottom line of sustainability, which involves economic, environmental, and social aspects. There are a lot of studies exploring various aspects of supply chain practices. However, there remains a gap for the proposal of a complete framework concerning various industries. This research fills this gap by studying existing empirical and review studies. Based on a content analysis of 86 studies, 789 practices are derived and categorized, leading to a comprehensive classification of sustainable practices in supply chains. Moreover, the employed methods to analyze the data are investigated. The practices are cross-checked versus the studied industries showing the current sustainable industries. The details of the studied papers are presented in a comprehensive table. The sustainable framework showing the industrial solutions toward sustainable supply chains is divided into 38 minor practices classified into 11 main categories. This paper provides a novel interpretation of the sustainable solutions addressed by different industries and presents a new and updated classification of the literature identifying future directions. This offers many advantages for practitioners and researchers to transform a supply chain into an improved version in the bigger picture.

The integration of the concept of the circular economy (CE) within the supply chain is known as the circular supply chain (CSC). Although various articles have identified barriers to implementing CE, no comprehensive study has investigated the impacts of barriers focusing on CSC. This study includes a systematic literature review to contextualize the impact of barriers from the perspective of 3R (i.e., reusing, remanufacturing, and recycling) recovery approaches. It classifies barriers into seven main groups in the context of CSC. The most often observed barriers hindering 3R recovery approaches are identified, and their impacts are discussed. The results demonstrate that barriers related to "economics and finance," "governments and regulations," and "society and culture" substantially impact the ability of organizations in the initial phase of adopting recovery approaches. In particular, key findings outline that consumer willingness to purchase recovered products impacts reuse, deficient supportive regulations impact 3R approaches (especially recycling), and a lack of support in the market impacts the ability of organizations to execute remanufacturing effectively. In addition, conducting empirical research is still desirable and creates a meaningful link between theory and practice. It helps to understand the barriers to remanufacturing, reusing, and recycling.

Closed-loop supply chains (CLSCs) are seen as one of the circular economy’s leading approaches for reducing our natural environment load. Many CLSC models require collaboration among different parties. Game theory (GT) offers a way to consider the profits of all parties in a CLSC, providing insight into the costs and benefits to the involved parties in an objective and quantitative way. Presently, available reviews on the use of GT, in the context of CLSC, are quite limited and consider only a few relevant elements. Here, we present a new and more extensive framework, focusing on the collaboration structure of CLSCs. It contains a content-based analysis of 230 papers based on a four-step systematic literature review process. The characteristics studied are channels for collection, reprocessing and selling, the planning horizon, and the types of games. The structures found are graphically reviewed, leading to 196 different structures. The results show that, so far, most attention has been paid to the dual-channel collection, where collection by two retailers (dual-retailer) is the most studied case. With respect to selling, most attention has been paid to situations with two selling channels (dual-selling), i.e., one channel managed by a manufacturer and one channel managed by a remanufacturer. Studies have prioritized the role of manufacturers as that of the leader and collector. Finally, a number of directions for further research are pointed out.

Due to economic and environmental advantages, transferring from linear systems into circular economies has been accelerated, especially in developed countries, which affects companies’ relations. Among different tools and methodologies, the closed-loop supply chain (CLSC) model as an established approach has shown its efficiency in reflecting these relations regarding the consumers’ behavior. Because of the complexity, limited studies have considered the effects of different factors simultaneously on different CLSC network designs. This is the first attempt to study the effects of carbon emission and remanufacturing simultaneously on a dual-channel in both forward and reverse logistics, while there is competition on collection. Accordingly, a novel format for the demand function is suggested and employed. The decisions regarding the optimal pricing and collection strategies of CLSCs were investigated, within which the manufacturer is responsible for the remanufacturing process and selling the remanufactured products directly to the customer through the online channel. In contrast, new products are sold via the traditional retailer channel, imposing relevant costs. We explore the effect of different dual-collection settings when there is competition between collector parties under three possible options (i.e., Manufacturer-Retailer, Manufacturer-Third-party, and Retailer-Third-party). The considered demand for both new and remanufactured products addresses consumers who have different willingness to choose the remanufactured items and are sensitive to the produced products’ carbon footprint. The behavior of the formulated CLSC models is studied by game theory regarding decision variables, and each player's profit is discussed through systematic comparison. We analytically show that considering all the effects, third-party entry is not in the manufacturer's interest. The findings show that consumers’ willingness to choose remanufactured products is generally more influential on prices and profits than their sensitivity to the carbon footprint.

This paper provides a risk assessment framework to select shipping lanes for pharmaceutical products. The main categories of risks are determined through an algorithm based on yes/no decisions. Then, according to the risk categories, a Failure Mode and Effects Analysis (FMEA) table is proposed for risk assessment of pharmaceutical product shipments and logistics. The evaluations are based on Intuitionistic Fuzzy Numbers (IFNs) to be able to account for the uncertainty in the experts’ judgments. By using an intuitionistic fuzzy hybrid TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) approach, the evaluated risks of each shipment lane can be scored and prioritized. The proposed TOPSIS-based FMEA approach in the intuitionistic fuzzy environment provides an opportunity to aggregate the risk assessments of different experts in a practically efficient way. Different from the earlier literature, we address risk identification and risk assessment under uncertainty as the two key challenges in group decision making. Our method further provides a framework that integrates the categorization and evaluation of risks with subsequent decision making. A case study of shipping lane selection in the context of air cargo distribution of pharmaceutical products demonstrates a potential implementation of the proposed approach.

Closed-loop supply chain (CLSC) as one of the important configurations of the circular economy (CE) has received considerable attention in sustainability matters. It is composed of characteristics that, when identified, studied, and categorized, help not only to a better understanding of the current contributions in the literature but also lead to formulating new models. This research presents one of the first in-depth studies to investigate factors influencing CLSCs. It concerns the investigation of the models which are designed based on the game theory (GT). Therefore, the reviewed works focused on cooperation and competition among the game participants. A systematic literature review is implemented as a four-step process consisting of material collection, a descriptive analysis, category selection, and evaluation stage to review and discuss the works that focus on CLSC and use GT simultaneously. A content-based analysis is carried for the final works, which include 215 papers. The identified characteristics of these papers are classified into 12 main categories. Moreover, they are divided into subcategories to highlight the contribution of each paper. Accordingly, results are derived, and gaps are explained.

Closed-loop supply chain (CLSC) as one of the important configurations of the circular economy (CE) has received considerable attention in sustainability matters. It is composed of characteristics that, when identified, studied, and categorized, help not only to a better understanding of the current contributions in the literature but also lead to formulating new models. This research presents one of the first in-depth studies to investigate factors influencing CLSCs. It concerns the investigation of the models which are designed based on the game theory (GT). Therefore, the reviewed works focused on cooperation and competition among the game participants. A systematic literature review is implemented as a four-step process consisting of material collection, a descriptive analysis, category selection, and evaluation stage to review and discuss the works that focus on CLSC and use GT simultaneously. A content-based analysis is carried for the final works, which include 215 papers. The identified characteristics of these papers are classified into 12 main categories. Moreover, they are divided into subcategories to highlight the contribution of each paper. Accordingly, results are derived, and gaps are explained.

ABSTRACTThis study aims to improve wettability and thermal resistance of lithium‐ion batteries separators. For this purpose, a commercial polypropylene (PP) separator was coated by 4A zeolite using poly(vinylidene fluoride) as binder and effects of the separators' zeolite content was investigated. All the coated separators showed lower contact angles, higher electrolyte uptakes, and less thermal shrinkages compared to the neat commercial separator. The coated PPA8 separator (zeolite to binder ratio of 8) showed the lowest wettability (contact angle of 0°) and electrolyte uptake (270%) due to its surface porosity resulting from the zeolite particles interstitial cavities as well as their internal cavities. Also, the PPA8 separator ion conductivity was found as 2.25 mS cm−1 and C‐rate and cycling performance of its assembled battery were higher compared to those of the commercial PP separator assembled battery. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019, 136, 47841.

In this research, inorganic material type and content influence on coating of commercially available polypropylene (PP) separator were studied for improving its performance and safety as lithium ion battery separator. Heat-resistant nanopowders of Al2O3, SiO2 and ZrO2 were coated using polyvinylidene fluoride (PVDF) binder. Coating effects on the separators morphology, wettability, high temperatures dimensional stability and electrochemical properties were investigated via their scanning electron microscopy images, electrolyte contact angles, electrolyte uptakes, thermal shrinkages analysis and ion conductivities. Furthermore, their performances were studied as the lithium ion batteries separator. All the coated separators have lower thermal shrinkages compared to the commercial neat PP separator. In addition, almost all of the coated separators have shown higher porosities and electrolyte uptakes than those of the commercial neat PP separators. The coated separator with Al2O3 / binder ratio of 8 (MOA8) revealed highest improvement in electrolyte contact angle of 0 °, electrolyte uptake of 218 % (2.04 times increment), ion conductivity of 1.685 mS/cm (1.89 times increment), 52 % porosity compared with the neat PP separator due to proper coating surface morphology, interstitial cavities and a higher Al2O3 dielectric constant than SiO2. In terms of assembled battery discharge capacity reduction after 100 cycles, MOA8 separator showed better cyclic performance as 8.89 % compared with that of the neat PP separator as 16.6 %.

This paper presents an original integrated procedure to evaluate and select suppliers for purchasing decisions. The procedure exploits the quality function deployment approach to define the suppliers' characteristics, coupled with the analytic network process to capture the interrelations among the selection criteria and integrated with a benefits, opportunities, costs and risks (BOCR) analysis. As such, the proposed approach is more structured than the existing methods for supplier selection; in particular, it allows simultaneously to take into account the relevant criteria for supplier selection, to capture the situation in which the decision criteria are somehow dependent on one another and to evaluate the positive and negative aspects of the selection process. By using the proposed approach, companies can derive useful information to guide their partner selection process. An extensive case study is reported to show the application of the model to a selection process of a real Italian company. The application shows that the model is effective in identifying the most suitable supplier; moreover, a detailed sensitivity analysis highlights that the results of the ranking are very robust against possible changes in the relative importance of the BOCR perspectives.

Kindi and Sarker (Prod Plan Control 22(3):325–333, 2011) develop an inventory model with backlogging to determine the optimal ordering policies in response to a discount offer. In the paper, there are some technical errors in developing of the optimal ordering policies. This paper presents the correct mathematical expressions and the solution to the numerical examples. Furthermore, this study also provides the closed forms for the optimal total gain costs that were not given by Kindi and Sarker (Prod Plan Control 22(3):325–333, 2011).

Poor quality control has become a major threat to medical laboratory services, especially in the developing countries. It has become necessary to assess and rank the quality of diagnostic services in medical laboratories using systematic approaches. The main aim of this research is to develop and apply a quantitative method in ranking medical laboratory services. This method is based on a combination of Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) with fuzzy set theory. VIKOR is a multiple criteria decision making technique which focuses on ranking and selection from a set of alternatives, and determines the compromise solution for a problem with different criteria. This approach aids decision makers to achieve the most acceptable decision amidst numerous alternatives. In the present evaluation method, international standard ISO 15189 (Medical Laboratories Particular Requirements for Quality and Competence) proposed by International Organization for Standardization (ISO) is used as a fundamental source of selected attributes of a medical laboratory. The study compares three medical laboratories to each other and ranks them. This study will be a valuable and effective contribution in enhancing both qualitative and quantitative criteria in the field of medical laboratory services. Finally, some directions for further studies are proposed.

Over the years since the advancement of inventory management and fuzzy set theories, a vast number of studies have been published to integrate these concepts. Nonetheless, no comprehensive and systematic literature review can be found that analyzed the studies in this research stream. It motivated us to conduct this survey as a systematic and comprehensive review in the field of fuzzy inventory management to identify major achievements attained so far and shed light on future directions. First, the earlier review papers are presented to reveal the necessity of this study, and then methodology applied in collecting sample papers is described, followed by an in-depth analysis of the papers. Totally, a sample of 210 papers is identified and classified according to the common characteristics of the models. Several aspects of the models are assessed that led to identification of some areas overlooked by researchers so far. (C) 2017 Elsevier B.V. All rights reserved.

In this paper, a mixed integer linear programming model for the multi-item uncapacitated lot-sizing problem is presented. The considered factors for formulating the proposed model are the monthly demand of the selected product from the case study company, type of parts used in the product and their consumption coefficients based on the bill of materials, lead time to receive parts from outsourcing suppliers, the costs of ordering, purchasing, and holding, and the amount of safety stock for each part. Accordingly, several forecasting techniques are tried to determine future demands. The prices of the selected parts are estimated using linear regression method. The optimal safety stock for each part is calculated based on variance in demand, lead time and the target service level. Material requirements planning are also performed to obtain the economic purchasing schedule of parts. LINGO and GAMS software are used to solve and validate the suggested model respectively. The results show that the proposed model can find the optimum order quantity for each part per period, which minimises the total cost.

The paper analyzes two different procurement strategies, i.e. single sourcing and double sourcing, for a buyer that adopts the economic order interval (EOI) reorder policy. The analysis consists of two steps. We start by developing a simulation model, which reproduces the two procurement strategies. In the single sourcing scenario, the buyer exploits only one supplier for purchasing. This supplier owns a defined level of reliability, i.e. a given capacity of providing the product when requested. In the case of double sourcing, besides the first supplier, the buyer can exploit a second vendor, which is always able to deliver the product required (reliability = 100%); however, it sells its product at a higher price, generating higher cost. The simulation model, built on Microsoft Excel (TM), allows deriving the total cost of the system under the two scenarios, thus helping the buyer select the most suitable (i.e. minimum cost) purchasing strategy. As a second step, for the double sourcing scenario, the analytic formulae of the total cost as a function of the supplier's reliability are derived and a sensitivity analysis is carried out to investigate how the total cost changes as a function of the input parameters.This paper expressively links the strategic decision of single sourcing vs. double sourcing to a specific reorder policy, such as EOI, which is very often implemented in real cases but not so widely investigated in literature. The proposed approach is thus expected to be of interest under both a practical perspective and a scientific one. (C) 2016 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved.

Despite the advantages of shell and tube heat exchangers, one of their major problems is low thermal efficiency. This problem can be improved by using heat transfer enhancement techniques such as adding nanoparticles to the hot or cold fluids, and/or using tube inserts as turbulators on tube side as well as changing baffles to a helical or twisted profile on the shell side. Although all of these techniques increase the thermal efficiency; however, engineers still need a quantitative approach to assess the impact of these technologies on the shell and tube heat exchangers. This study attempts to provide a combination of such techniques to increase the impact of these improvements quantitatively. For this purpose, at first stage the thermal and hydraulic characteristics of pure fluid, Al2O3/water nanofluid in a plain tube equipped with and without twisted tape turbulator is evaluated based on a developed rapid design algorithm. Therefore, the impact of using enhanced techniques either in form of individual or in hybrid format and the increase of nanoparticle concentration in base fluid have been studied. The results show that using turbulators individually and in hybrid format with nanofluid can be effected on design parameters of a typical heat exchanger by reducing the required heat transfer area up to 10 %.

Due to the repetitive nature of inventory planning over the planning horizon, the operator in charge has to perform planning tasks repetitively, and consequently s/he becomes more familiar with the tasks over time. Familiarity with the tasks suggests that learning takes place in inventory planning. Even though the operator's learning over time might improve his/her efficiency, prior research on fuzzy lot-sizing problems mostly overlooked the effect of human learning in their models and its impact on the operator's performance. To close the research gap in this area, this paper models the operator's learning in a fuzzy economic order quantity model with backorders. The paper models a situation where the operator applies the acquired knowledge over the cycles in setting the fuzzy parameters at the beginning of every planning cycle, where his/her learning ability includes the cognitive and motor capabilities of a human being. Subsequently, a mathematical model which takes account of a two-stage human learning over the planning cycles is developed, which is then analytically investigated using sample data-sets. The results indicate that both operator's capabilities, cognitive and motor, affect the efficiency of the fuzzy lot-sizing inventory model, but the influence of the cognitive capability is more profound, which in turn suggests the importance of training programmes for the workforces. The results of the sensitivity analysis also draw some managerial insights for the case that some model parameters vary over the planning horizon.