نشریه پژوهش های نوین در تصمیم گیری
سال چهارم شماره 4 (زمستان 1398)

The petrochemical industry is one of the most important industries in the world where optimal management and decision-making in its activities will bring about great economic benefits as well as prosperity and development of related industries. This paper deals with the issue of petrochemical product supply chain management. A multi-objective optimization model is developed in which the strategic, long-term economic, social and environmental goals of the petrochemical industry are achieved. For this purpose, first using the Epsilon constrained evolution method, economic objective is considered as objective function and social and environmental goals are constrained as Epsilon. Then, the Pareto front is obtained from efficient solutions and in this front, the solution with the least deviation from the ideal is selected as the most efficient solution and recommended to industry managers. The data uncertainty in the proposed model is controlled using a robust feasibility planning approach. The numerical results show that not only the optimal fluctuation in the proposed robust approach is much less than the nominal value approach but it also significantly reduces the constraint flaw which reduces risk in decision making. In order to solve the proposed large-scale problem, the Banders decomposition method is applied based on the Epsilon multiple-constraint evolution method. Numerical results show that the proposed approach significantly improves the mean, standard deviation, and runtime in three quantitative measures and enables large-scale problem solving.

Today, the ERP system has become an essential and important tool for improving the competitive advantage of organizations and if this system implements successfully, companies can attain a competitive advantage in the global marketplace quickly. One of the success factors in the implementation of ERP systems is the proper identification of risks and appropriate responses to them throughout the lifecycle. Therefore, this research with an innovative point of view seeks to examine the risks and obstacles to the success of ERP implementation using the Critical System Heuristics (CSH) approach. The present research is both fundamental and applied in terms of purpose. The statistical population of this study is ERP elites, interviews with 12 of these elites were conducted using purposeful sampling method. The findings of this research indicate that the risks of implementing the ERP system are divided into three categories of risk before implementation, implementation time risks and post-implementation risks. In addition, the results of the study provide suggestions from the discovery and understanding of the boundary judgment of the stakeholders (initial judgments about the system and a general overview of it) in order to identify and ultimately control the risks of the implementation of the ERP system.

Due to the entry of companies into the competition among the networks the ultimate success of companies depends on the ability of management to integrate the interconnected network of interfirm relationships. Hence, this has required the identification of the structural characteristics of the networks for their better management. Traditional modeling and analysis approaches focus on individual firms or use a dyadic lens. This approach, however, fails to account for the systemic effects resulting from the complex topological and behavioral aspects inherent in supply networks (SNs). In spite of economic importance, little is known about diversification in the structural shape or topology of SNs. Therefore, many researchers have emphasized the use of social network analysis as a tool for morphological analysis of SNs. In this regard, this study examines the structural characteristics of the supply network in the Iran automotive industry for understanding the structural difference between the high-performing companies and the others in their network. The results showed that high-performing companies are not properly configured to respond to market requirnments and have little agility in this regard. Also, they exhibit significant relational power, more timely access to resources, greater levels of knowledge sharing and learning among SN members. In other words, they manage their relationships in a way that facilitates sharing of knowledge and learning.

Logistics strategy is an important advantage for supply chain management operations, which requires centralized planning of operations to reduce time and timely delivery of the product to increase the level of customer satisfaction. Cross-dock is an efficient method to control inventory flow that is essential in supply chain management. The other objectives of the cross dock are inventory reduction, increased levels of customer responsiveness and better control of the distribution operation. This paper focuses on the optimization of the transportation scheduling and the planning of the movement inbound and outbound trucks with a soft window, where time parameters are considered uncertain. Therefore, a mathematical model is presented with the goal of minimizing the total time of operation in the supply chain and using the possibility Linear programming model converts the mathematical model into a definite mathematical model. Since the article model is zero and one linear programming type of the integer and belongs to NP-hard issues, the time to solve them increases with increasing problem dimensions. Therefore, genetic algorithm and Simulated Annealing algorithm are used to find optimal solution problems. The parameters used in meta_ heuristic algorithms were determined by Taguchi method with mini-tab software and their optimal values were extracted. Then, according to constant parameters including the number of suppliers, customers, cross-dock, inbound and outbound trucks, and product types, sample problems were generated at three small, meddle and large production levels, and at each level, seven problem samples were generated and total of twenty one issues were solved.

In this study, a single-item obsolescence inventory model with one retailer and with all-unit quantity discounts has been investigated. The retailer purchases items with a possibility of future obsolescence based on the purchase price which is dependent into the order quantity. It is assumed in this paper that there are dependencies between different decisions on the amount of order quantity, considering the probability of obsolescence at any given moment and the purchase price of items by taking into account the use of discount. The aim of the model is to minimize the retailer’s inventory cost through the finding optimal purchase price and order replenishment. Although discount models have been developed for deteriorating items with a constant or varying rate of deterioration, but the use of these models, for obsolete items, in which the demand of item falls suddenly in the future based on a probability distribution, has not been so far investigated. While, these are the real conditions that many retailers are facing and in such situations the retailers need to encourage the customers to buy more. In this model, the length of obsolescence time is considered as exponential function and the obsolescence is occurred suddenly. The model has been developed mathematically and then the optimal solution and convexity are resulted from the first and second derivatives of objective function respectively. Finally, for the sake of clarity of the proposed model, a numerical example is presented and sensitivity analyses are performed on critical parameters of the model.

The purpose of this paper is to present a dynamic model of business and information technology alignment in agile organizations. Dynamic Capability Framework, an influential theoretical and managerial framework in modern information systems and agility research, has been used in order to develop the dynamic model of alignment. Based on alignment approaches, IT alignment is defined as the extent to which the IT mission, objectives, and plans support, and are supported by the organization’s mission, objectives, and plans. Therefore, this study uses fuzzy DEMATEL technique to find the relationship between information technology capabilities and higher-order dynamic capabilities, business capabilities, to identify dynamics of alignment and provide agility. To investigate the most important agility and alignment factors, data were collected through questionnaires completed by 100 experts and analyzed by SPSS and PLS software. In the simulation, a combination of fuzzy Dematel and system dynamics methods was used to design the dynamic modeling structure. The causal relationships and efficiency coefficients were calculated by using fuzzy Dematel method in MATLAB and Excel software. Finally, the dynamic model was designed by Vensim software. According to the results, “IT learning capability” is the most important factor that has the most impact on other factors and “Business responding capability” takes the highest effect from the system.

The prediction of the results of introducing a new product into the market is one of the vital issues the organization executives face before investing in marketing activities. The impact of various factors on the market as well as the specific characteristics of the market, depending on the region and its product type, has made it difficult to predict market behavior. In Iran, retailers are effective players, especially in the FMCG market. The objective of this paper was to suggest a model to the marketing managers to predict the result of launching their new product to market considering their special market attributes. Agent-based modeling, as a tool for modeling complicated systems, can be helpful for simulating real-world conditions. In the present paper, agent-based modeling was used to model the market for agents including brand owners, retailers and consumers with particular profit functions. The introduction over a three-year period of a new soft drink in the Iranian market is considered as a case study. The results showed that taking into account the needs of retailers and consumers simultaneously and changing policies based on long-term profitability make the new product diffusion process successful.