فصلنامه مطالعات مدیریت صنعتی
پیاپی 59 (زمستان 1399)

In this study, we examined the effect of the interaction between demand uncertainty and supply chain integration on firm performance using a survey method with questionnaires. The sample consists of the firms that were in steel and auto parts industries. Previous studies had not examined the interaction effect between these three types of integration and uncertainty in supply chains as was done in this study. In total, 84 firms participated in the study. We used hierarchical regression model to test our hypotheses with industry type added as a control variable. Research findings showed that integration in internal and process dimensions can have a positive effect on both operational and financial performance. However, product integration had no effect on operational performance while it had a negative effect on financial performance. There was a significant interaction between demand uncertainty and integration dimensions as well. Under conditions of demand uncertainty, process integration improved financial performance. Considering these results, it is recommended that companies focus on internal and process integration as more effective types of integration, which improve both types of performance and give higher priority to process integration under high demand uncertainty conditions. Furthemore, type of industry did not influence study results.

Due to the awareness of the environmental protection, how to reduce the utilization of the materials by reusing and remanufacturing the used products has been a critical issue for an enterprise. This induces the concept of the reverse and closed-loop supply chain management. Different from a conventional supply chain, planning a closed-loop supply chain requires an additional function of recycling and thus, a closed-loop chain is a necessary infrastructure for a material flow. In this paper a mixed-integer linear programming is considered to mathematically model the essentially five stages along our supply chain network: suppliers, manufacturers, DCs, customers, and Dismantlers. NP-hardness of this problem is proved in many papers, so a novel metaheuristic solution method aiming minimization of total costs comprised fixed opening cost of plants, distribution centers and collection/inspection and distribution centers and transportation cost of products between open centers using spanning tree based encoding which has been rarely applied in this area. Comparison of outputs from proposed Clouded Based Simulated Annealing Algorithm (applied for the first time in SCND) shows the excellence of this new solution method in quality of answers with comparison to those of applied in the literature.

Credit risk assessment is one of the key issues for banks and financial institutions and various models have been developed for this. This study uses Case Based reasoning (CBR) Model and considers a database of bank credit customers to assess the credit risk of bank applicants. For this, 9 criteria were selected based on the experts' opinion and were weighted using the Fuzzy Analytical Hierarchy Process (FAHP). Return check, housing situation and income level are the most important criteria for credit risk assessment of the bank applicants. Then, using the TOPSIS Technique, we could evaluates the similarity of the new item with actual past cases or evaluate the new applicant with the ideal option, and uses a case-based reasoning model to predict the likelihood of default or non-default applicants. Survey research was applied for this study and the research community was the records of previous bank applicants between 1390-94 years.

The present research named” The Effect of open innovation on competitive advantage Considering the Mediation Role of knowledge management” in Sadad informatics corps of Tehran city in the year of 2016. The main goal of this research is to study The Effect of open innovation on competitive advantage(With dimensions of quality, efficiency, responsiveness and innovation) Considering the Mediation Role of knowledge management. This research is an applied one and the research method is descriptive and survey. Literature review and field study method have been used to collect information. The statistical population of this study included 200 employees of Sadad informatics corps in Tehran city. A group of 131 employees was selected as the sample for research through Cochran’s formula. Data analysis was performed by using descriptive and inferential statistics. At the level of descriptive statistics, indicators such as abundance and percentage of abundance were used; at inferential level, methods such as correlation, confirmatory factor analysis and structural equation modeling were used. To analyze the data was used of Lisrel and Spss software. Finally, the results have shown that open innovation plays an important role in effective management of organizations. Through open innovation, companies can turn knowledge management into an asset that promotes sustainable innovation that affects organizational sustainability.

In the present study, the redundancy allocation problem (RAP) of series-parallel system has been investigated to maximize the system's availability. To achieve the research objective, budget, weight and volume constraints, and the maximum and minimum number of elements assigned to each subsystem have been considered. The main innovation of this research is to consider the failure and repair rates of components with non-exponential distribution function in the process of optimization. The parameters affecting the under-study system in this paper make it impossible to calculate the availability using mathematical relations. Therefore, the present study has used simulation method to calculate system availability. Since the simulation has no optimization capability, this research tries to represent the results of the simulation as a mathematical function, which explains the way decision variables affect the system's availability. Further, due to the high degree of difficulty of developed mathematical function, the genetic metaheuristic algorithm was used to solve it. Finally, the efficiency of the genetic algorithm was measured against particle swarm algorithm and simulated annealing algorithm. To compare fairly, the parameters affecting the algorithms are adjusted using the Taguchi method and the algorithms are in their best practice. The computational results prove the high ability of the genetic algorithm in optimizing the concerned problem.

Appropriate scheduling of shifts of nurses for a hospital is a critical issue in hospital management. Researcher in this study improves the scheduling of shifts of nurses in health services organizations to provide lower cost and also reduce the computational complexity and finally realize the outcome of these actions in the form of job satisfaction and quality of received services. For problem discussed offered a linear mathematical model and after point to NP-hard this problem, Provided Genetic Algorithm for Solving the size was in fact and finally Implemented in Imam Khomeini Noor city as a real sample and proposed computational results and performance of the proposed algorithm in terms of solution quality and computational time, were analyzed. In the proposed model of accreditation standards for hospitals as well as the Productivity laws in the modeling is used. Production timetables by the proposed model, resulting in improved satisfaction levels of nurses and improve their job performance.

Research conducted has shown different results from the relationship between aspects of quality management and innovation performance. Most researches confirm the direct relationship between quality management and organizational innovation performance, but the effective aspects of quality management have not been thoroughly investigated, so the present study Was considered clarifies the aspects of quality management and their impact on organizational innovation performance. The purpose of this study was to investigate the impact of soft and hard aspects of quality management on innovation performance by mediating the role of employees' proactive behavior and technological innovation capability. The data of this study were collected from Iranian knowledge-based companies active in the field of laboratory equipment and materials. We tested the assumptions using structural equation modeling methodology and SmartPLS software.The results of this study showed that soft quality management mediated by innovation capability and proactive behavior of employees had significant effect on innovation performance and hard quality management had significant effect on innovation capability.Also innovation capability has a significant impact on the innovation performance of the organization.

Constant changes in today's business environment have made institutions recognize knowledge as their key asset. This study, while considering the importance of knowledge in the range of current organizational activities, seeks to identify the factors that influence knowledge sharing among project managers.  The present study is the result of Phase I of developmental research and Phase II of applied research. In terms of purpose, the first phase is an exploratory research and the second phase is an exploratory research. Also in the first phase is the qualitative type and method of data base theory research and in the second phase is a quantitative research using structural equations. The statistical population of the study is the group of system partners. In the first phase sampling was done by snowball method (targeted sampling) and in the second phase randomly. The sample size is 17 persons in the first phase and 253 in the second phase. The results have been reviewed and reviewed by two professors and some cases have been modified or modified.The research results in the data base of the Foundation lead to the identification of 22 key factors (such as knowledge dispersal as central phenomenon, organizational context order, synergistic configuration, knowledge retesting, maturity-driven and secure knowledge dispersion margins, organizational domain order, configuration time). Increased knowledge re-testing, maturity-driven development and secure margins). Their relationship to and influence on each other was accomplished through theoretical comparison and structural equations and path analysis.

Material requirements planning systems are used in discrete manufacturing systems. In this article, mixed-integer programming is used to minimize the total cost that contains work in process inventory cost, setup cost, backorder costs, lost sales, additional product cost, and changes in the lead-time cost. Furthermore, it is considered that some part of the delayed demand is backorders and the other part is lost sales. Moreover, defective items and their impact on the demand of customers are discussed in this paper. The suggested deterministic model is single-objective and applied to a ready-mixed concrete production company. According to the optimal results, by decreasing the number of defective items, the manufacturing costs in the studied company can be reduced by %30. Also, the material ordering plan can be implemented according to planned lead times. Furthermore, in this article, a lower bound is suggested for the problem and the computational efficiency of the lower bound is evaluated.

The purpose of this research is to develop a conceptual model and categorize the prerequisites and consequences of green supply chain in the parts manufacturing industry. A comprehensive and indigenous model is not provided. The method of studying qualitative content analysis and the main tools of data collection are semi-structured interviews. Data analysis was performed with combined and concise combined content analysis technique. The identified factors include 29 open codes, which are inserted in the form of seven main categories, and at the end, using Maxqda software; classification and conceptual model were drawn. In order to measure the reliability of the present coefficient, the calculated Kappa coefficient by SPSS software was equal to 0.960, which is at the level of excellent agreement. The results show that 7 components identified in the prerequisites and consequences of the green supply chain in the parts manufacturing industry include; Supplier and purchase of green, green design and packaging, green production, green distribution and marketing, environmental management, education and research, reverse logistics. The components of education and research and reverse logistics have emerged as new components in this research. Today, global organizations have found in a competitive environment that improving environmental performance can differentiate them from other competitors. The Green Supply Chain combines environmental concerns with the concept of supply chain through improved collaboration and coordination of supply chain members.