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In recent years, manufacturers have started selling their products online. This study examines pricing in a supply chain involving manufacturing, retailers, logistics service providers, and integrators. There are three products in this chain: two physical products from manufacturers and a service product from logistics providers. Physical products are sold online and in retail stores, with online purchases including two products. The problem is examined in four scenarios, including decentralized, manufacturer integration with retailer, functional logistics service provider integration with logistics service integrator, and a combined approach of manufacturer integration with retailer and functional logistics service provider integration with logistics service integrator. This paper introduces a novel approach by analyzing the impact of logistics supply chain members, focusing on logistics service levels and pricing. The study aims to explore how the integration of supply chain members influences the profits and service levels of other stakeholders. The results indicate that integrating two supply chain members typically lowers profits for other members. Integrating a logistics service provider and integrator can increase manufacturer profit and decrease retailer profit in certain cases, while in other cases profits remain unchanged. Similarly, integrating manufacturer and retailer usually results in decreased profits for logistics service providers and integrators. The integration of functional logistics service provider and logistics service integrator has an impact on the relationship of parameters with service level. In the decentralized scenario, if service price and service coefficients increase, service levels increase. It also increases service levels as the cost of service increases.

Governments today are increasingly focused on managing environmental and economic challenges to safeguard the environment. Consequently, companies are striving to remain competitive in society. This paper introduces a revenue-sharing agreement between the retailer and the manufacturer. The contract is designed to alleviate the research and development costs incurred by the manufacturer in greening their products. Additionally, the paper incorporates consumer surplus as a consideration for the social dimension, which is a key pillar of sustainability.

Government interventions in this paper are modeled as subsidies that influence the final price of the product. Notably, this study, for the first time, integrates all three dimensions of sustainability—social, economic, and environmental—within a game-theoretic framework that includes government intervention and a revenue-sharing agreement between the retailer and the manufacturer.

The modeling results demonstrated that incorporating consumer surplus enhances the profitability of both the government and the manufacturer. Although consumer surplus reduces wholesale prices and revenue-sharing proportions, it leads to increased product sales. This boosts the benefits for consumers and members of the supply chain, contributing to improved greenness and higher levels of product sustainability. Consumers show a preference for purchasing products with greater environmental benefits; however, higher levels of greenness require increased production costs. Manufacturers can boost their sales through research and development efforts and by raising public awareness about green products. As a result, manufacturers, retailers, and the government adjust prices and subsidies to maximize their respective profits, altering the overall profitability of the supply chain. The findings highlight that social welfare is a crucial consideration in supply chains, as it significantly enhances the profitability of chain members and promotes higher levels of green production.

Originality/Value: 

This paper is the first to examine all dimensions of sustainability—social, economic, and environmental—within a theoretical framework that incorporates government intervention and the impact of consumer surplus on pricing policies and the greening of products. The scientific contribution of this research lies in providing new insights to managers and policymakers to enhance strategic decision-making aimed at improving sustainability and social welfare within green supply chains.

The global increase in the volume of foreign direct investment in recent decades has been the focus countries on it. The effects of foreign direct investment in sustainability indices has led many researchers to assess various aspects of this type investments. In the Foreign direct investment have two agents that are decision makers. They are the investor and the host country. So had to use the multi-agents decision makers’ methods for this kind of investment. This study for the first time examines foreign direct investment using game theory as an efficient tool in multi-agents decision-making. For this purpose has been paid to mathematical modeling and then using stackelberg game to solve the model in the different strategy. In Continue provide a numerical example and analyzed and finally, extracted Managements tips. The results of this study can be used as a decision support tool in the field of foreign direct investment.

In this paper, greening, pricing, and advertising policies in a supply chain will be examined with government intervention. The supply chain has two members. First, a manufacturer seeking to determine the wholesale price and the greening level and second, a retailer that has to determine the advertising cost and the retail price. The government is trying to encourage the manufacturer to green the production using subsidies. Using the game theory, at first, the demand function and the profit functions of both members are introduced, then in a dynamic game, their Stackelberg equilibrium is calculated. Sensitivity and parameter analysis are made to more illustration of the problem. We found the supply chain profit function behavior and results show that if the sensitivity of demand-price is less than a specific value, the manufacturer will not participate in greening policies.

This study deals with the effects of a supply chain (SC) with single product, multiple retailers and a manufacturer, where the manufacturer(he) produces lotsize of the product that contains a random portion of imperfect quality item. The imperfect quality products are sold in a secondary shop. The new contribution of this paper is a new non-linear demand function. Demand of the end customers varies with pricing and promotional effort of the rivalry amongst the retailers which can be used for the electronic goods, new lunched products, etc. We investigate the behavior of the supply chain under Manufacturer-Stackelberg(MS), and Retailer-Stackelberg(RS) model structures. The nature of the mentioned models provides great insights to a firm’s manager for achieving optimal strategy in a competitive marketing system. Within the framework of any bilevel decision problem, a leader's decision is influenced by the reaction of his followers. In MS model structure, following the method of replacing the lower level problem with its Kuhn-Tucker optimality condition, we transform the nonlinear bilevel programming problem into a nonlinear programming problem with the complementary slackness constraint condition. The objective of this paper is to determine the optimal selling price and promotional effort of each retailer, while the optimal wholesale price of the perfect quality products are determined by the manufacturer so that the above strategies are maximized. Finally, numerical examples with sensitivity analysis of the key parameters are illustrated to investigate the proposed model.

In this paper, integrated production and batch delivery scheduling problem for make to order production system and one customer in supply chain has been addressed. One manufacture received n orders from one customer. Orders must be processed by single machine and sent in batches to customer. Sending several jobs as a batch leads to less transportation cost but may increase the cost of tardiness jobs. The objective is determining the production and delivery scheduling so that the related costs is minimized. The problem is strongly NP-hard. In this paper, one new math programming model including Mixed Integer Programming (MIP) model, Ant Colony System (ACS) and Elastic Ant System (EAS) are presented for solving it. In order to evaluate the efficiency of these two methods computational tests based on full factorial experimental design has been conducted. Computational test is performed for evaluation of these methods. The obtained results show that the heuristic algorithm is efficient which has been verified by using. Analysis of variance (ANOVA) technique. The results showed that the ACS is the most efficient method.

Project portfolio selection is very important subject of decision-makers in project-based organizations. The best assignment of resources to the most appropriate projects is necessary as financing projects with low benefit is just waste of organization's resources. However, existing project selection models pay not much attention the structure and special features of projects as a selection criterion, while their hardness may prolong the project duration and even result in stopping the project. Furthermore, the models cannot consider correlations between projects which may affect the results of projects. In this paper, a model is proposed to measure the structural hardness of projects. Then, a project portfolio selection model is proposed considering hardness and correlations between projects. A case study is presented to test the performance of the model in real world problems. At the end, some large-sized numerical example has been solved. The results show the capability of the model to solve large-sized problems in a suitable time. The important role of structural hardness in project selection was discussed and sensitivity analysis has been done.

This paper considers the advertising, pricing, and service decisions simultaneously to coordinate the supply chain with a manufacturer and a retailer. The amount of market demand is influenced by advertising, pricing and service decisions. In this paper, three well-known approaches to the game theory, including the Nash, the Stackelberg-retailer, and the cooperative game are exploited to study the effects of these policies on the supply chain. Using these approaches, we identify optimal strategies in each case for the manufacturer and the retailer. Then, we will compare the outcomes of each strategy thus developed. The results show that, compared with the Nash game, the Stackelberg-retailer game yields higher profits for the retailer, the manufacturer, and the whole system. The cooperative game yields the highest profits. Finally, the Nash bargaining model will be presented and explored to investigate the possibilities for profit sharing.

In the current study, a dual-channel supply chain is considered containing one manufacturer and two retailers. It is assumed that the manufacturer and retailers have the same decision powers. A game-theoretic approach is developed to analyze pricing decisions under the centralized and decentralized scenarios. First, the Nash model is established to obtain the equilibrium decisions in the decentralized case. Then, the centralized model is developed to maximize the total profit of the whole system. Finally, the equilibrium decisions are discussed and some managerial insights are revealed.

In this paper, we study a supply chain scheduling problem that simultaneously considers production scheduling and product delivery. jobs have to be scheduled on a single machine and delivered to customers for further processing in batches. The objective is to minimize the sum of the total weighted number of tardy jobs and the delivery costs. In this paper, we present a heuristic algorithm (HA) and a branch and bound (B&B) method for the restricted case, where the tardy jobs are delivered separately, and compare these procedures with an existing dynamic programming (DP) algorithm by computational tests. The results of computational tests show significant improvement of the B&B over the dynamic programming algorithm.

Flow Shop Scheduling Problem (FSSP) with the objective of minimizing total amount of tardiness is an NP-hard problem and many articles has been written about it. In this context, great attention has been paide to metahuristic techniques such as genetic algorithm. Additionally determination of the paraemeters of the algorithms is an important subject in the research area that many researches have been allocated to it. The purpose of this paper is to investigate the effect of crossover and mutation operators of the genetic algorithm on the objective of minimizing total amount of tardiness in permutation FSSP in order to determine more suitable ones to be applied in the problem. The obtained numerical results indicate that in most cases among common crossover operators,using the one point and two point (first version) operators and among mutation operators,applying the adjacent exchange gives the best value for the mentioned problem.

The purpose of this study is to provide new methods for the problem with criteria interactivity in MCDM problem. Considering that the assessment criteria in MCDM may have effects on each other, so there are the necessary methods that take into account these interactions. This research In addition to identification, study, and Classify the different interaction that may the criteria have, introduces two new ways in this context. The new method presented in this paper is to solve the problems with the interactions between the criteria. The interaction between the criteria to be considered as a set of interactive effects between the criteria. The paper also offered two new ways to solve such problems. The proposed method approach is the effect of the interactions on the decision matrix.

Every year many people incur huge and often unavoidable damages because of accidents in roads of the country. This issue causes that, those involved in transportation focus on road safety subject. But the important issue in this area is that in order to increase the safety of roads it must be invested on which cases? So, in this paper, the effective factors in road transportation of the country have been studied using multivariate statistical analysis approach. Therefore, at first, effective variables on road transportation of the country have been specified and then principal factors have been extracted by factor analysis method. Moreover, the provinces of the country have been ranked according to a general index by concidering the obtained factor scores. Finally, trend of changing the general index were drawn and analyzied for some provinces from 1387 to 1392.

In this study an integrated production/distribution problem in flow shop scheduling with tardiness costs¡ inventory costs and distribution and resource allocation costs is modeled. Imagine a supply chain in which several jobs are to be processed on several machines. Each job has a contracted due date. This paper aims at proposing an efficient model for minimizing total production and distribution costs which include tardiness costs¡ inventory costs and distribution and resource allocation costs. The mixed integer non-linear programming of the problem is then presented. Considering that these problems fall into the group of NP-hard we utilize a NSGAII algorithm to solve the proposed problem. This problem has been solved with small dimensions and restrictions on the Pareto frontier obtained Epsilon limitation and large-scale NSGAII meta-heuristic algorithm as well as small-scale solved the problem solving methods (Epsilon restrictions and NSGAII) are compared with each other.

Knowledge management is one of the appropriate solutions to earn utility and efficiency in organizations. Procedure of increasing the role of knowledge in the management of organizations has caused the concept of knowledge management to become the heart of the organization's strategic policies. Accordingly, paying special attention to knowledge management and understanding the most important effective factors in its successful implementation is necessary to achieve the organization goals. Having studied various articles, in this article, 30 sub-factors in the forms of 7 main factors including leadership, organizational culture, resources and human resources, information technology, evaluation and performance measurement, strategies, processes and activities have been recognized. These factors are the effective ones in successful implementation of knowledge management in knowledge based organizations. The factors have been ranked by managers of knowledge based companies located in Isfahan Science and Technology town. According to this the priorities of main factors in the successful implementation of knowledge management have been determined in the form of resources and manpower, leadership, strategies, organizational culture, processes and activities, information technology and evaluation and performance measurement, among the effective sub-factors in successful implementation of knowledge management. Hiring qualified personnel, having the same prospect, creating appropriate space and time for brain storming and having a clear long- and short-term goals for knowledge management have the highest importance for the successful implementation of knowledge management in knowledge based organization, respectively.