This study investigates the role played by service quality at manufacturer-distributor junction in small-medium manufacturing units, and presents a model that proposes and validates that contribution towards service quality on behalf of both the distributor and manufacturer leading to satisfaction as well as loyalty. The research design for this study includes a combination of literature review, exploratory interviews and a questionnaire survey conducted through interview schedule from 101 respondents working in different small-medium manufacturing units (SMEs) of North India. The study uses Structural Equation Modeling (SEM) to develop dual directional scales to measure service quality at manufacturer-distributor junction besides testing a set of propositions related to service quality. A model showing linkages of manufacturing organization’s service quality with distributor service quality leading to mutual satisfaction and loyalty is developed. The model is empirically tested and is found to be fit. This study would be of interest to SME practitioners interested in improving service quality w.r.t. distributors. This study finds support for strengthening relationships with distributors to achieve a win-win situation. Future researchers may validate this scale, and empirically test the proposed model in similar settings. Insights derived from this study may be transferred to other junctions of a manufacturing supply chain such as suppliers, retailers, employees and end customers.

Today, urban areas have been considerably expanded, which has caused numerous problems due to the large population in metropolitan areas. City logistics models can be effective in solving complicated problems such as traffic congestion, air pollution, accidents, and high energy consumption rate. The present paper proposes a bi-objective mathematical model for designing a city logistics distribution network in order to minimize the economic and environmental costs as well as the response time. The proposed model would make decisions on the location and allocation problems in the city logistics distribution network. In fact, the objective of the problem is to select some fixed sites in order to construct the city distribution centers. The demand for commodities is considered probabilistic and the network is modeled based on the queuing theory. Furthermore, in the proposed model, the policy of putting tax on carbon and applying the low-carbon emission resources are used for establishment at the city distribution centers. Afterwards, in order to validate the proposed model, a numerical example is generated and, then, the results obtained from solving the model via epsilon constraint method are presented. Analysis of the results in the present study indicates that the proposed model was highly efficient in achieving its objectives. Finally, there are some suggestions for future studies that can be taken into account.

The rise in the worldwide demand of forest products of the last decades predicts an expansion of the forest harvesting industry. In this context, the Argentinian Northeastern Region (NEA) is considered a promising land since the local forest harvesting industry has one of the largest growing rates in the world. Despite its potential, this region faces some challenging obstacles: budget shortage, trade barriers and poor logistic infrastructure. For instance, traditionally the forest products are delivered by truck, which is from three to five times more expensive than other means of transport, like maritime or river transport. This is why in this paper, after a revision of the most recent advances in the worldwide supply chain management practices in the forest industry, recommendations for Argentina in order to overcome its main drawbacks in the forest sector are presented.

This paper examines the spoke and hub location decisions in a routing problem. To minimize the total cost, the study analyzes on how to locate the spokes, hubs and the allocation of spoke nodes to hub nodes, the routing among the nodes and the number of vehicles assigned to each hub thoroughly. As there might be no facility assigned to some points, unsatisfied demands must be distributed to other nodes with available facilities. Furthermore, the realized demand is determined by considering the perceived utility of each path, using The Gravity rule. For this purpose, the proposed nonlinear model is transformed into a linear programming model, where some tightening rules and preprocessing procedures are applied, and also the sequential and integrated approaches are developed to solve the problem. In the sequential method, spokes are allocated, and hubs are selected based on the location of the spokes, after which the routing in the local tour is determined. Meanwhile, in the integrated approach, the aggregated model is solved. A heuristic is presented to address the integrated model. Numerical experiments are run on both approaches, to compare both, and obtain insights from the model.

Research Project Supply Chain is one of the most complex supply networks. The management of this complex system has created new challenges for industry managers and engineers. The optimization of supply chain networks is, therefore, essential within the context of the research projects. The aims of this paper is to design the network of Supply Chain Management for research projects in an Iranian project-based organization. This model integrates strategic decisions in the whole life cycle for research projects using a mathematical approach. This model is a guideline for managers in research projects that will enable them to identify the strategic decisions of PSCM in their own organizations in order to resolve and improve them. It also serves as a useful base for researchers to further expand research concerning PSCM in research projects.

The purpose of this paper is to propose an integrated multiple criteria decision making (MCDM) approach to analyze interrelationships among sustainability criteria, weight them, and then evaluate suppliers according to these criteria. Data were collected through interviewing with seven experts who are involved in the procurement department of the case. Interpretive structural modelling (ISM), and pairwise comparison questionnaire are used to elicit the existence, strength of relationships among criteria and then weight them by using Fuzzy (Decision Making Trial and Evaluation Laboratory (FDEMATEL), Fuzzy Preference Programming (FPP), and Analytical Network Process (ANP). Then, Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS) is employed to evaluate suppliers based on identified and analyzed sustainability criteria. This study provides several implications for practitioners and scholars. First, the results show the efficiency of the proposed approach in practice. Second, respondents state that the proposed approach was very useful in decision making based on interrelationships among criteria, alternatives and policies. Third, findings validate the significant difference in rankings with or without considering interdependencies among criteria.

Increasing in attentions to the environment, city legislative and social problems make companies change their prospects towards supply chain management and design sustainable transportation networks. In this paper, two-stage problem have been investigated in which the transportation stage is considered before Location-Routing Problem, so we call it Transportation-Location-Routing Problem (TLRP). It is an extension of the two-echelon Location-Routing Problem. In the first stage, there is a transportation problem with truck capacity limitation. Furthermore, customers’ time windows should be met in the second stage to make the mode more realistic. Minimization of distribution cost, fuel consumption, and carbon dioxide emission along with balancing the workloads for city drivers are considered as the objective functions of the mathematical model to design a sustainable distribution network. To tackle these conflicting objectives, Non-dominated Sorting Genetic Algorithm (NSGA-II) and Multi-Objective Particle Swarm Optimization (MOPSO) are applied to solve the problem. A new customized chromosome based on a priority based technique is presented for the problem. Due to the three comparison metrics for multi-objective problems, with tolerating a little more computational time, MOPSO has the better performance in this problem than NSGA-II.

Manufacturing organizations are under the pressure to give quality products at least cost within the possible minimum delivery time, even during unpredictable economic conditions. Due to competition like improved customer service and cost reduction, organizations are looking for innovative ways for creating competitive advantage. One such way is the effective information sharing among all the members of supply chain. To understand information sharing, we have to know the benefits of information sharing within the supply chain. In this study, on the basis of the relevant available literature and the suggestions of an expert team composed of managerial and technical experts of the manufacturing organization and academicians, eleven information sharing benefits have been diagnosed. An ISM-based model has been formed to study the understanding of the information sharing benefits in adopting the right information sharing within a manufacturing industry. We propose the ISM model, and a MICMAC investigation is applied. Its practical significance is to make use of the decision makers’ knowledge to give a fundamental understanding of a complicated situation, followed by a course of actions for problem-solving.

The present paper develops a sustainable framework under a supply chain environment by considering a vendor and a buyer. The vendor governs the manufacturing process to serve the demand of the buyer. The manufacturing system is imperfect which ends up producing some fraction of defectives. For the sake of maintaining the goodwill of the organization, it is imperative to maintain the quality standards. Thus, the buyer employs the screening process to bifurcate the perfect items from the imperfect ones. The imperfect items secluded after screening are reverted back to the vendor, for which a warranty cost is incurred. Further, in an attempt to achieve sustainability the model considers the carbon-emissions costs during the transportation process. A one-time discrete investment is also considered for minimizing the setup cost of the vendor for subsequent cycles. The models are developed for the case of the individual decision and for the joint verdict of the players under consideration. Moreover, it has been proved that the integrated model performs proficiently over the individual model. The objective is to jointly optimize the costs sustained by the two players. Numerical analysis and sensitivity analysis is done for imparting the validity and robustness of the model.

Most of the supply chain models have been developed under symmetric information structure i.e. players have complete knowledge of each other’s policies. But in most of the cases, players do not have complete information about the other players i.e. some information regarding their businesses is hidden. This paper studies supply chain model of imperfect quality items under asymmetric information in which unit price taken by the buyer and unit marketing expenditure are influencing product’s demand. This information is hidden to seller. The seller delivers the supply to the buyer. Each delivered lot goes through an inspection process at the buyer’s side. In the inspection process, the items are divided into two categories. The first category is perfect quality items while the second category is of imperfect quality items. After the inspecting the lots, the perfect quality commodities are to be sold at selling price and the imperfect items are supposed to get sold at a discounted price. The interaction between two constituents of the supply chain is modeled by non-cooperative Seller Stackelberg game approach in which the role of leader is played by the seller while the role of follower is played by the buyer. In our proposed model, the seller does not have information related to market demand but the buyer does. Numerical examples and sensitivity analysis explain the significance of the theory.