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.