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The purpose of this study is to examine the impact of activation energy with binary chemical reaction for unsteady flow on permeable stretching surface.

The simultaneous effects of multiple slip and magneto-hydrodynamic effects at the boundary are taken into account. The thermal buoyancy parameter and thermal radiation are included in both energy and momentum equations, while expression of activation energy is considered in concentration equation. Three-stage Lobatto IIIa finite difference collocation technique with bvp4c MATLAB package is used to obtained numerical results.

The influence of key elements (Schmidt number, buoyancy force ratio factor, factor of radiation, magnetic element, unsteadiness factor, suction/injection parameter, Prandtl number, activation energy, chemical reaction rate parameter, heat source and sink parameters, velocity, thermal and concentration slips, porosity parameter and temperature difference parameter) on velocity, temperature and concentration profiles are illustrated pictorially. A detailed discussion is presented to see how the graphical aspects justify the physical prospect.

In the best of author’s knowledge, this work is yet not available in existing literature.

This paper aims to evaluate different logistics configuration to deliver batteries from the supplier to the production lines of a European carmaker who is implementing new propulsions for its models.

Several scenarios about the supply chain for traction batteries have been identified based on the company’s requirements and constraints. Then, the variables used for the assessment of each scenario have been selected to calculate the unit battery supply chain cost.

The results underline that a direct transport without intermediate nodes is the cheapest one. On the contrary, an additional warehouse makes the organization of the network more complex. However, with this configuration, it is possible to cover the risk of supply since that a certain level of inventory is always guaranteed.

This study is limited to the analysis of only one model car, and just manual operations have been taken into account for computing the human resource time and cost. The present study is one of the first works exploring the organization of the supply chain for the batteries integrated in electric and hybrid vehicles together with the choice of the location of the related warehouses.

This paper is one of the first work on the assessment of batteries’ supply chain that are going to be integrated in low impact vehicles, focusing on location of the associated warehouse. The evaluation is carried out by taking into account all the sources of cost.

Supplier evaluation and selection is an essential (multi-criteria decision-making) MCDM process that considers qualitative and quantitative factors. This research work attempts to use a MCDM technique based on merging fuzzy Technique for Order Preference by Similarity to Ideal Solution (F-TOPSIS) and Quality Function Deployment (QFD) ideas. The study attempts to find the supplier's attributes (HOWs) to accomplish its goals after determining the product's characteristics to suit the company's needs (WHATs).

The proposed research methodology comprises the following four steps: Step 1: Determine the product purchase requirements (“WHATs”) and those pertinent to supplier evaluation (“HOWs”). In Step 2, the relative importance of the “WHAT-HOW” correlation scores is determined and also the resulting weights of “HOWs”. In Step 3, linguistic evaluations of possible suppliers in comparison to subjective criteria are given to the decision-makers. Step 4 combines the QFD and F-TOPSIS techniques to select suppliers.

A fuzzy MCDM method based on fusing and integrating fuzzy information and QFD is presented to solve the drawbacks of conventional decision-making strategies used in supplier selection. Using the F-TOPSIS method, fuzzy positive ideal solution (FPIS) and fuzzy negative ideal solution (FNIS), the relative closeness coefficient values for all alternatives are computed. The suppliers are ranked by relating the closeness of coefficient values. This method permits the combination of ambiguous and subjective data expressed as fuzzy-defined integers or linguistic variables.

QFD and TOPSIS, two widely used approaches, are combined in this article to rank and evaluate suppliers based on the traits that the suppliers choose to prioritize. This study demonstrates that the method employed could address multiple-criteria decision-making scenarios in a computationally efficient manner. The effectiveness and applicability of the method are illustrated using an example.

This study research contributes in fulfilling the gap by carrying out a systematic literature review (SLR) of contemporary research studies in closed-loop supply chain (CLSC). To the best of the author’s knowledge, an SLR rooted in bibliometric analysis has not been carried focusing on advent developments in CLSC. SLR employs scientific methodologies to select papers from standard databases. The SLR using advanced bibliometric and network analysis enables unveiling the key features of the contemporary literature.

The author has analyzed over 333 documents published from 2008 and onward. Using the contemporary tools from bibliometric analysis tools, the author presented an exploratory analysis. A network analysis is utilized to visualize literature and create clusters for the cocited research studies, keywords and publication sources. A detailed multivariate analysis of most influential works published based top 100 articles via a cocitation matrix is done. The multivariate analysis used k-means clustering in which optimal number of clusters are estimated. The analysis is further extended by using a factor analysis, which enables determining the most influential clusters in the k-means clustering analysis.

The SLR using a bibliometric and network analysis enables unveiling the key features of the contemporary literature in CLSC. The author examined published research for influential authors, sources, region, among other key aspects. Network analysis enabled visualizing the clusters of cocited research studies, cowords and publication sources. Cluster analysis of cocited research studies is further explored using k-means clustering. Factor analysis extends findings by identifying most contributing grouping of research areas within CLSC research. Each clustering technique disclosed a unique grouping structure.

CLSC has received considerable attention, and its core areas start with focusing on reverse logistics concepts relating reuse, recycling, remanufacturing, among others. Contemporarily, the studies have enhanced reverse logistics core functionalities interfaced with the other interesting avenues related to CO₂ emission reduction, greening and environmental protection, sustainability, product design and governmental policies. Earlier studies have presented a literature review of CLSC; however, these reviews are commonly conducted in the traditional manner where the authors select papers based on their area of expertise, interest and experience. As such these reviews fall short in utilizing the advanced tools from bibliometric analysis.

Although manufacturers have traditionally viewed reverse supply chain (RSC) activities as a costly nuisance, more recent research has found that the RSC can contribute to the firm’s financial performance. The purpose of this paper is to identify how the RSC can contribute to the firm’s financial performance and examine the exogenous contingency factors decisive for the contribution’s size. Because the exogenous factors are outside the control of the firm’s operations and supply chain management, the factors influence the RSC’s financial contribution irrespective of managerial policies and design decisions.

The paper applies a systematic literature review using the sequence of planning the review, searching and screening literature, extracting information from the selected literature, and synthesizing and analyzing findings. In total, 112 papers were included.

The study has identified 15 distinct opportunities for RSC-contribution to the firm’s financial performance. The study has identified 56 contingency factors. These are related to market segmentation, customer behavior, product design, and the firm’s distributor network. The study includes an interrelationship network between factors and the RSC’s contribution.

For managers, the paper shows how the RSC can increase the firm’s financial performance and which contingency factors determine whether operating a RSC will be financially viable if implemented.

While extant literature includes several reviews about RSC-related managerial policies and design decisions, this paper contains the very first collection of RSC-contribution opportunities available to manufacturers as well as the first review of exogenous contingency factors.

The construction industry contributes to economic development by providing physical equipment and infrastructures. However, it also generates some undesirable outputs such as waste and environmental pollution, especially in developing countries. Due to the importance of the green supply chain management (GSCM) philosophy, for solving these problems, the current study aims to evaluate the drivers of GSCM adoption in the construction industry of Iran.

This research uses a descriptive and practical methodology. The participated experts in the study include senior managers of the construction department in Rasht municipality who had relevant academic education and suitable experiences in urban and industrial construction. The experts took part in both qualitative and quantitative phases of the research, namely verification of the drivers extracted from literature and ranking them in ascending order. In the quantitative phase, Step-Wise Weight Assessment Ratio Analysis (SWARA) as a new multi-criterion decision-making (MCDM) method is used to evaluate the drivers of GSCM adoption using MATLAB software.

The results show that environmental management systems, green product design and innovational capability with weights of 0.347, 0.218 and 0.143 are the most significant sub-drivers, respectively. The less important factor is an investment in environmental technology.

This study evaluated the motivational factors of GSCM in the construction industry. The findings help governments, companies and green supply chain (GSC) managers to improve their knowledge about GSCM and make the best decisions to decrease environmental pollution.