فصلنامه چشم انداز مدیریت صنعتی
سال دوازدهم شماره 3 (پیاپی 47، پاییز 1401)

The emergency department is one of the crowded wards of a hospital, so improving the performance of this ward has a significant impact on improving the quality of hospital services. Recently, researchers have paid more attention to resilience engineering (RE) and lean management approaches, because of their focus on performance improvement. The aim of this study is to present an integrated performance evaluation model for evaluation performance of the emergency wards of a private hospital, based on simultaneous applying resilience engineering and lean management. For this purpose, first by identifying the effective factors, a conceptual model of the problem was designed. Then the required data were collected using a standard questionnaire. In the next step, using the algorithm based on data envelopment analysis (DEA) and with the presence of all indicators, performance values were calculated. Also, the performance values were recalculated after removing each of the factors. The results show that the indicators of engineering commitment in the group of RE and operational improvement in the group of lean management; have the most impact; Therefore, by focusing on these factors, significant improvements can be made in the level of staff satisfaction and as a result, the performance of the organization.

Family businesses and their internationalization have attracted increasing attention. Over the years, scholars have attempted to shed light on different characteristics of family firms that support their successful internationalization. In this research, we focus on familiness and investigate how familiness plays a role in the process of internationalization. Familiness refers to competencies and capabilities that are created in family firms because of the interaction between family and business. To answer this question, we have employed a qualitative research method and semi-structured interviews to collect data from seven family businesses from an emerging economy that were operating internationally. Built upon the social capital theory, our findings shed light on how the nature of family relationships in terms of different aspects of cognitive, relational, and structural dimensions facilitate the internationalization of family firms.

Closed loop supply chain network design has attracted the attentions of many researchers due to the social and environmental requirements as well as the economic benefits. Most of the researchers have studied the design problem separated from the supplier assessment. Some other criteria except for price, regarding supplier features, the supplied part and the production process can have considerable effects on supply chain performance. In this paper, a closed loop supply chain network including production centres, disassembly, refurbishing, and disposal sites is considered. An integrated three-phase model is given so that in the first phase, integrated SWARA-WASPAS method is employed for suppliers’ evaluation; in the second phase, a new method is proposed in order to determine environmental-social scores of remanufacturing sites and in the third phase, a three-objective mixed integer linear programming model is developed. Determination of the eligible suppliers and sustainability of the supply chain considering economic, social and environmental objectives, are of most outputs of this model. Unsatisfied demand of customers are assumed to be lost. The numerical results show the validity of the model and the role of stockout option in reaching better solutions considering the sustainability metrics.

This article is the result of a research project in dynamic pricing and advertising to determine the number of sale tickets for a sporting or an entertainment event. For this purpose, a dynamic optimal control model was used to maximize the organizer's profit. To provide the best estimate, all potential variables and costs in ticket sales were considered. These included free ticket transfers, food and beverage sales, promotional goods, insurance, and other services (e.g., customer service) to ticket buyers. Using a piecewise continuous function (arrival intensity) we applied variables that are not controlled by organizers (e.g., impacts of seasonal change on demand) to determine the number of tickets for sale (capacity planning) and their dynamic and optimal price, considering the dynamic optimal advertising costs. Among the strengths of this study is the application of two piecewise continuous functions to analyze the effect of unsold tickets numbers on customers’ purchasing behavior. The impacts of such factors have not been studied in previous studies.

In the last few years, as the complexity increases, so does the level of uncertainty; Therefore, supply chain risk management is one of the topics that has been considered by organizations. One of the risks existing in the supply chain is the risk of suppliers. This research provides a model for evaluating supply chain risk management, with a focus on a real-world case: SHIFOO food industry. The model used is a combination of Fuzzy Linguistic Computing (FLC) to calculate the risk of factors in accordance with the verbal semantic spectrum, and the VIKOR method to measure the level of importance of these factors. By reviewing the studies and also using the opinions of experts, 5 factors of available capacity, lack of trust to the company, lack of skilled staff and distance between the supplier and organization were identified as factors affecting risk creation in the supply chain. Then, by using the modified two-tuple FLC (Fuzzy Linguistic Computing) model, the food supply chain risk of SHIFOO was obtained between "low" and "medium" options. Finally, by using the supply chain risk gap analysis technique, it was found that inability of supplier for provide a certain number of raw materials has importance risk among other criteria.

The first step in analyzing and evaluating supply chain risks is to identify these risks. Conventional analysis methods are based on manual filters or data-driven automated methods. Manual filtering methods suffer from validation problems due to sampling limitations, and automated data analysis methods, on the other hand, perform poorly in analyzing risk data that is complex and ambiguous. To fill the research gap, in this study, an interactive framework between the analyst and the machine is presented to analyze a large volume of risk data in the field of food supply chain using topic modeling techniques, word embedding, term correlation analysis, and knowledge map. The purpose of the supply chain risk monitoring system is to assist managers in food companies to monitor and identify crisis risks and provide a decision support information system to create a sustainable food supply chain. The results of the topic analysis of metadata showed a knowledge map in five areas of "harvest", "agriculture", "food retail", "food services", "distribution" and "consumption", which was approved by the expert panel. The results show that the risk analysis model is useful in extracting knowledge units related to the field of food supply chain crisis management.

The main purpose of this study is to provide a framework for evaluating the performance of Mashhad City Train Operating Company based on a balanced scorecard and multi-criteria decision technique (fuzzy best-worst). The current research is applied in terms of purpose and quantitative-documentary in terms of method. Qualitative data collection was done based on the opinion of 15 experts during the period between 2017 and 2019 in Mashhad Train Operation Company. Nine financial criteria, sixteen in terms of customers, eight in terms of internal process and fourteen in terms of growth and development and learning to evaluate performance through company documents and previous research are identified and weighted; Therefore, in this study, an attempt was made to calculate the weight of perspectives and criteria using the best-worst fuzzy technique, respectively, in which the perspective of customers had the most weight and the perspective of growth and development and learning had the least weight; Finally, the performance of Mashhad City Train Operating Company was evaluated. The overall performance of the company has decreased in 2018 compared to 2017, and has increased in 2019 compared to 2017 and 2018.

This paper studies the flexible job shop scheduling problem with parallel machines by considering cleaner production criteria, dual human-machine resources, job release date, and machine speed-dependent processing time. The objective functions of this problem include minimizing the sum of earliness and tardiness and the speed increasing. Here it is assumed that the speed of the machines can be increased to reduce the completion time while the increasing the speed leads to increasing the noise pollution in the production environment, and due to the cleaner production approach which is a preventive approach, an attempt has been made to reduce the amount of noise pollution by minimizing the speed increasing. In this regard, first, a mixed integer-programming model was developed, and since the model is bi-objective and NP-hard, a NRGA is proposed and the obtained results are compared with the NSGAII considering some multi-objectives criteria. The results show that the proposed algorithm considering the MID criterion in instances with 10 and 25 jobs and considering the RAS criterion in instances with 25 and 100 jobs have better performance compare to the NSGAII. Furthermore, the TOPSIS method is also used for analysis and the results show the efficiency of the proposed algorithm.

When it comes to providing aid to the victims of natural and unnatural disasters, the main goal of a relief chain is to provide the items needed by the victims such as water and food, medicine, shelter and other necessities to reduce the number of deaths caused by reduce the occurrence of disasters as much as possible; therefore, designing, developing and implementing a relief chain can play an important role in finding a suitable answer. The most obvious differences in dealing with the relief supply chain are the unpredictability of demand in terms of time, place, type, scale and volume. Other reasons such chains are the sudden occurrence of a large amount of demand and a very short opportunity to provide a large amount of goods, lack of resources including goods, relief forces, appropriate technology, transportation capacity, the need to provide timely and sufficient supplies after the accident, and the risks in the relief environment. In the present research, a mathematical model for the location-inventory problem for planning response to casualties is presented; also, due to the NP-hard nature of the problem considered, meta-heuristic algorithms were used to solve it.

Today, supply chain management must adopt solutions to meet the changing needs of customers. Using business intelligence, along with integraiton and agility, creates a competitive advantage in the supply chain, and as a result, the supply chain can achive a better position in the business. This paper aims to explore how business intelligence influences integration, agility, and supply chain performance. Meanwhile, the effect of supply chain integration and agility on supply chain performance will be examined. In this research, literature review was performed and a conceptual model was presented. Then the survey method was done. Data were collected through a survey of 369 companies from different industries and different cities in Iran during December 2020 and January 2021. The research analysis unit was manufacturing companies. Structural equation modeling was used to test hypotheses. The results show that business intelligence, integration, and agility play an important role in achieving better supply chain performance. In the meantime, BI has the greatest impact on supply chain performance. Additionally, business intelligence has a positive and significant effect on the integration and agility of the supply chain. It was also found that integration has a direct effect on supply chain agility.