نشریه مدیریت صنعتی
سال سیزدهم شماره 42 (پاییز 1400)

Organizational excellence is not an unknown concept in management and organization; in addition, developing novel models, differences between the 2020 model and the old model of EFQM, and different firms’ efforts to develop customized OEM methodology all indicate the dynamics and importance of focusing on this fundamental concept. Therefore, in the present study, an attempt was made to configure and test organizational excellence methodology in Iran’s oil industry.

This research was conducted by using Multi-Grounded Theory (MGT), a complementary and extended method of Grounded Theory (GT), that provides a comprehensive framework to develop distinctive theories. To validate the results, expert surveys were used in a separate stage. The result verified the validity of the acquired results and appropriateness of the final model from the perspective of understandability, comprehensiveness, applicability, and innovation.

Analyzing the gathered data by reviewing more than 70 models developed over the last 40 years and conducting interviews with 22 experts selected through a combination of purposive and snowball sampling methods led to the development of a model with seven criteria, 32 subcriteria, and 102 concepts which improve the excellence of Iran’s oil industry in terms of "Strategic leadership and management development", "Management of organizational capital", "Organizational diplomacy", "Operation and customers", "Results of managerial and supportive processes", "Stakeholders results", and "Value chain results".

The obtained results of the present study can be applied in developing a roadmap for organizational excellence, evaluating and determining plans to improve Iran’s oil industry.

The present study seeks to identify the future of project-oriented organizations active in the financial services industry via the Scenario Planning Approach.

The present study is pragmatic in terms of philosophical foundations, applied in terms of orientation, and a survey in terms of data collection. Regarding the use of qualitative and quantitative methods, it has a mixed methodology. In this study, the Binomial statistical test was used to screen key drivers, modified fuzzy VIKOR method was applied for Key driver analysis, CATWOE was used to map research scenarios, and SECA technique was applied to determine probable Scenarios.

In this study, 25 drivers were obtained through reviewing the literature and conducting interviews with experts. These factors were screened using the Binominal test. In this step, 17 drivers had a significance coefficient, i.e. above five percent, and were removed from the analysis. The remaining eight drivers were examined using modified fuzzy VIKOR. The two drivers i.e. the legal environment of the financial services industry and the type of interaction of traditional financial institutions with fintech had the highest priority. Based on these two drivers, the four scenarios of Dreamland, Paranoia Age, Baseless World, and Ice Age were developed for the future of project-based organizations in the financial services industry. Each driver had two opposite modes. Four scenarios were constructed from a combination of different situations of research drivers. Finally, using the SECA technique, the Baseless World scenario was selected as the most probable one. Also in this study, the scenarios of the Dreamland and the Ice Age were optimistic and pessimistic scenarios, respectively. The probable scenario was an interstitial one between two optimistic and pessimistic scenarios.

Finally, the research proposals were developed based on the most probable and worst scenario with a negative dialectical approach. The common denominator between the two scenarios (probable and pessimistic) was the dispersion of rules and standards in the financial services industry. Therefore, research proposals were developed around legislation and regulation in Fintech and the financial services industry.

Considering that in most specialized fields, decisions are made in groups, in this study, a method to select the desired option in conditions of uncertainty is presented, which also considers the group decisions to increase the effectiveness.

In this study, the ZlCWAA method and data envelopment analysis, which are responsible for the averaging of Z numbers and assigning weight to specialists, were used to create the Z number extension of the best-worst method. This method is innovative in decision-making and, in this study, we used the Z number extension of the best-worst group method.

For better decision-making, the information should be more valid, accurate, and reliable. So we compared the FBWM, ZBWM, and DEA-GZBWM methods with each other, based on the case study and data collection from the perspective of each expert on the most important indicators of optimal stock portfolio selection. This comparison showed that the proposed method of DEA-GZBWM has a lower rate of incompatibility than the others. Therefore, the information obtained in this method can be more reliable for us.

To prove the effectiveness of the DEA-GZBWM method, a case study was conducted to show how to use this method in optimal stock portfolio selection; In which the investor, with the help of financial experts (experts in financial markets), invests and selects the optimal stock portfolio from the companies in the stock exchange and securities organization. Then, based on weight, rank, and incompatibility rate, the results of the proposed method, FBWM, and ZBWM methods were compared. This comparison showed that the proposed method is more functional than the others due to its lower incompatibility rate (0.108).

Cellular production is one of the important applications of group technology in production. With the development of modern industrial technology, many manufacturers use it as a solution to implement complex and realistic scenarios that increase the productivity and flexibility of a production system. Cellular production includes cell formation, cellular and intracellular arrangement, operation scheduling, and resource allocation. The process of formation and grouping of machines to produce families of parts to minimize the cost of moving materials among cells is called cell formation. In other words, cell formation in cell production systems and assignment of machine groups and family of parts to these cells is done to minimize the total cost and increase flexibility and productivity in production. The layout design is also related to the position of the cells relative to each other and the position of the machines in each cell relative to each other. In some production units, the placement of cells in relation to each other and even the placement of devices in each cell is not done properly, which increases the movement of materials, semi-finished parts, and consequently, production costs. On the other hand, with changes in customer needs and demand and competitive market conditions, the combination of existing cells and their arrangement in one period may not be appropriate for another period, and it is necessary to make changes to reply to customer needs and remain competitive. The possibility of making changes in cells combination, placement inside and between cells is called dynamic cell formation. In other words, dynamic cell formation involves changing the position of the cells relative to each other and the proper placement of the machines in one cell so that it is possible to move the machines to a new position or another cell and increase or decrease them.

Operation scheduling and assigning human resources incurring a notable proportion of expenses in the cell formation. These issues seem more important when financial resources are limited. In this research, dynamic cell formation problems based on scheduling, allocation of workers, and constraints of financial resources on machines and workers are simultaneously investigated, Accordingly, the present study seeks to minimize the total costs, including the costs of machines, workers, and transportation of parts. At first, a mathematical model was presented. The model was then linearized and validated. After that, a genetic algorithm was proposed to solve the problem where the parameters were adjusted and selected by using the Taguchi method. Sensitivity analysis was also performed based on the related parameters in constraints of financial resources of machines and workers.

The results showed the accuracy of the model and its validation. It was also shown that the proposed algorithm is highly efficient and can be used for medium and large-sized problems where it is not impossible to find the optimal solution.

Sensitivity analysis showed that the constraints of financial resources for purchasing machines have a greater impact on the objective function than workers' financial constraints, which is of high importance.

This study aimed to simulate a humanitarian supply chain coordination model to reconstruct houses of flood victims under inflationary and non-inflationary conditions.

A village in the Northern Iranian Province of Mazandaran with 160 households was studied. 60% of the village was ruined due to the floods that inundated the region in 2019. An agent-based simulation was used in this applied research. To achieve the research goal, the factors (actors) of the humanitarian supply chain for housing reconstruction in the flood disaster were identified. The housing reconstruction factors in the flood humanitarian supply chain were then determined. The relationship between the actors of the humanitarian supply chain to coordinate the reconstruction of housing in the flood disaster was identified. Finally, a model of factor behaviors for coordinating housing reconstruction in the flood humanitarian supply chain was presented. Considering the use of the factor-based simulation method to answer research questions, this was an analytical-descriptive study. It was causal in terms of the purpose of applied research. In terms of the data collection method, since it sought to identify factors and the relationship between them, it was a comparison. Also, according to Walker's classification, this research was an analytical-mathematical one.

Three agents of the government, celebrity donors, and flood victims (with damaged houses) were identified. Then, two scenarios of receiving government aid or only aid from celebrity donors under inflationary and non-inflationary conditions were considered. The agents' internal relationships, characteristics, behaviors, and decisions were also simulated using agent-based modeling. Finally, through interviews, the indicators of coordination in the reconstruction of flood-affected housing were identified, and coordination in each of the scenarios was evaluated.

As proved, in the receiving donor's financial aids scenario, the humanitarian supply chain coordination score was higher among the agents. Also, the houses reconstructed under non-inflationary conditions were higher in both scenarios.

In many production processes, the efficiency of decision-making units should be investigated in the presence of undesirable inputs and outputs and non-discretionary factors. It is also important for managers to examine the impact of changes on one index on another. Therefore, the purpose of this paper is to develop an approach to estimate the efficiency of systems with undesirable inputs and outputs and non-discretionary measures and also to analyze changes.

First, a novel approach based on data envelopment analysis was presented in order to analyze efficiency in the presence of undesirable input-output indices and non-discretionary factors. In fact, the new weak disposability axiom was used and the efficiency of the systems was investigated in the presence of undesirable input-output index and non-discretionary factors. Then the impact of changes of one non-discretionary index on another index was measured by maintaining efficiency, and the marginal rates of these changes were calculated.

In order to explain the proposed method in practice, an applied example provided based on 31 branches of Islamic Azad University (department of education) was presented and the results were discussed and analyzed. By using the suggested method, the efficiency scores and the impact of modifications were obtained.

Performance scores related to branches indicated that most of them behaved well. Also, it was observed that always increasing (decreasing) one index, while maintaining efficiency, does not end in an increase (decrease) in another index but it may remain unchanged or decreased (increased). Due to the inclusion of undesirable input and output measures and non-discretionary factors, the results of the proposed method were more acceptable than the classical DEA models.

The purpose of this study is to provide a model to identify the factors and components of sustainable development of the iron and steel industry using grounded data and fuzzy DEMATEL techniques.

The present study is descriptive in terms of purpose (qualitative and quantitative), exploratory in terms of identifying components, and cross-sectional in terms of time. The study population in the qualitative section included senior managers and academics with a history of sustainable development and in the quantitative section, the statistical population included senior industry managers and university professors. To determine the priority of components, two groups were formed. Statistical sample, in the qualitative stage, was formed using purposive judgmental sampling of 15 university and industry experts to extract a conceptual model to localize the model and check the content validity of the model and factors by grounded data technique. In the quantitative stage, due to the use of research techniques in operations and the fuzzy DEMATEL method to prioritize and identify the most effective and influential model factors, seven experts were selected from seniors of the community. Industry and university professors were selected. These people had master's and Ph.D. degrees and more than 15 years of work experience. In order to collect information by reviewing the research literature and consulting experts, the factors were identified by the grounded data technique. It was also used to collect the necessary data during the research through interviews and a pairwise comparison questionnaire. The validity of the assessment tool in the qualitative part, which is the use of semi-structured interviews, was done through face validity and observing the interview protocols, and in the quantitative part, Cronbach's alpha was used to assess the validity of the questionnaire. According to this method, the reliability of all research variables was more than 0.7. The number of statistical samples of the research included 15 interviewees in the first qualitative part (using grounded data) and seven in the quantitative part (Fuzzy DEMATEL).

In the first stage of the qualitative section, the categories were summarized with Maxqda software and 6 main factors, 13 sub-factors, and 46 concepts were identified. Then, using the fuzzy DEMATEL technique, the 13 factors of importance, effectiveness, and susceptibility were extracted, respectively. The most influential included "macro-management of iron and steel industry, economic and political conditions, market management, financial management, integrated resource management, environment", respectively and the most influential of all was "society and production".

Based on the results obtained to achieve organizational productivity, the organization should pay attention to the factor of steel production in the sustainable development of the steel and iron industry. "Steel industry macro-management factor" is also the most influential factor in the sustainable development of the steel and iron industry.