مجله مدیریت تولید و عملیات
سال سیزدهم شماره 2 (پیاپی 29، تابستان 1401)

Human resources are considered a competitive advantage in organizations, and according to the executive position of staff, the relative importance of the competitive advantage is enhanced so that the executive managers, and the senior staffs particularly in the production line, are of particular importance to company owners. Selecting competent and committed senior staff as well as maintaining them based on their satisfaction is one of the key factors in the success of organizations. Therefore, this paper aims to study the selection and assignment of senior staff problems so that they are selected based on their competency to manage the production workshops, and then they are assigned to the workshops based on their preferences. For this purpose, an integrated model of mathematical programming and Multi-Attribute Decision-Making (MCDM) is developed to select competent senior staff and assign them to the workshops based on their preferences.

In this paper, some of the staff as potential options have been determined, and then, their preferences to manage all workshops have been calculated using the TOPSIS technique. Also, a multi-objective integer programming model has been developed to select competent senior staff among all potential options and to assign them to the workshops based on their preferences. In this paper, a multi-objective global criteria method has been proposed as an approach to solving the selection and assignment problem.

The required data were collected through questionnaires and interviews with potential options. Consequently, the results indicated that the proposed method (weighted global criteria) outperforms the simple global criteria approach as well as the traditional method based on the decision of the managers and experts.

Research limitations/implications:

 The results were limited to the case of production workshops in an appliances plant, and all data were deterministic. Respectively, some directions as opportunities for future research were suggested. The first suggestion is to apply the current model in other production systems, and the second suggestion is to use fuzzy logic for developing both the fuzzy TOPSIS and fuzzy mathematical programming model based on the expert’s knowledge.

Practical implications: 

Since the non-optimal assignment of the staff to the workplaces increases the costs, and assigning them disregarding their preferences leads to staff dissatisfaction, the production system would be affected. Therefore, the lifecycle of the organization can be threatened. Therefore, the optimal staff assignment problem can be one of the most critical management challenges in industries.

Originality/value: 

To the best of our knowledge, there is no research in the literature on the staff assignment problem that considers preferences and competencies simultaneously as studied in this paper. Therefore, the following contributions to the literature are underlined: - - Selecting and assigning senior staff to production workshops, considering a multi-objective problem - - Collecting the evaluation criteria of preferences for the problem from the literature to determine final preferences for selecting the workshop - Integrating the integer programming (IP) model and TOPSIS to extend the new model of staff assignment problem

This study aims to model the impact of Covid-19’s stress and resilience on job burnout in knowledge-based companies.

Design/methodology/approach:

 This study is typically quantitative and cross-sectional and in terms of purpose it is applied research. The statistical population included the managers of the first and second-tier and the employees of the knowledge-based companies. Based on the equation of the statistical sample size of the unlimited population, 384 were examined.  The standard questionnaires of Maslach and Brief Resilient Coping Scale (BRCS) and Covid-19 researcher-made questionnaires were used for data collection. Radial Basis Functions - Artificial Neural Network (RBF-ANN) was used for data analysis.

65% of the managers and employees of knowledge-based companies were at moderate and lower resilience levels and 61% of the statistical sample had job burnout. Also, the amount of stress caused by Covid-19 was higher among married women compared to others. The RBF method was used to design the ANN. Accordingly, the number of neurons in the input layer was equal to 10, the number of neurons in the single hidden layer was equal to 35, the number of neurons in the output layer was equal to 1, and  was equal to 10. 70% and 30% of the data were used for training and testing, respectively. In the designed ANN, all but one of the test data, and all but two of the experimental data were correctly predicted and the Root Mean Square Error (RMSE) error was less than 0.3. Finally, based on the obtained results, the proposed model was confirmed.

Research limitations/implications:

 The difficulty of accessing statistical samples in Covid-19 conditions and the resulting limitations along with the lack of relevant research background were among the limitations of the present study. For future research, similar comparative studies are suggested to be conducted in the manufacturing knowledge-based companies for modeling and adapting the results and conducting a study using other methods of ANN design, including multilayer perceptron (MLP). Also, separating the areas of activity of knowledge-based companies and comparing the results are suggested as the subjects of study on the variables of this research.

Practical implications:

 Since in the research related to social sciences and humanities, less use is made of engineering methods such as neural network design, the present study seems innovative in terms of subject and methodology and the researchers and experts who are interested in the subject of this study can benefit from the findings. Business and entrepreneurship and organizational behavior, engineering sciences and sustainability issues, students and managers, and employees of technology and knowledge-based companies are the other beneficiaries of this study.

Social implications: 

Since there is no immediate and definitive solution to reduce the stress and burnout of managers and employees of the startups, constant pressure has created a long-term detrimental situation for startup companies. Addressing this issue is necessary because the performance and productivity of a company require the physical and mental health of its managers and employees; stress and resilience are also the two factors affecting job burnout which have been exacerbated by the Covid-19 crisis over the past two years.

Originality/value:

 Because dealing with complex relationships between research variables requires the use of precise and in-depth analytical methods, in this study, an ANN was used to predict their behavior and the impact of variables on each other. Therefore, the attempt made to reduce the theoretical gap and the contribution made in theory based on innovation in the subject and research variables and the analysis method has led this paper to have an interdisciplinary approach.

Today, the digital gaming industry has a significant impact on the economic, cultural, and social spheres around the world. The advent of real and virtual reality games, particularly in medical science, has taken this industry out of the realm of mere entertainment and has become one of the applied industries. This study aims to optimize the combination of indigenous digital game development strategies, using a goal mathematical programming model. Compared to other common methods, the proposed approach can be a good alternative to studying and using mathematical planning in strategic management, when strategies are evaluated and selected.

Design/methodology/approach:

 The research method of this study is typically mixed qualitative and quantitative for which, the main data were collected using library studies and theoretical framework review, in-depth and structured interviews with 12 experts and specialists in the digital games industry. A filled questionnaire was collected after coding variables. Thematic analysis (reasoning and rational analysis) was used to extract and classify the components. Also, an integration of House of Quality (HOQ), Analytical Hierarchy Process (AHP), and Simple Additive Weighting (SAW) techniques were used to determine the variables and parameters required in the mathematical model of the research. Finally, a goal programming model was used to determine the optimal combination of the strategies.

A portfolio of optimal strategies was proposed that were effective in removing barriers and challenges in the game industry, which facilitated the achievement of game development goals with desirable capabilities in implementation. The mentioned strategies were capabilities empowerment and development of game-making experts, targeting and enriching the content of homemade games, financing and facilitating investment, and increasing the level of competitiveness of game-making groups.

Research limitations/implications: 

The limited number of expert group members and the researcher's low access to them, in addition to creating problems related to the distribution and collection of questionnaires, review and increase the computational accuracy of validity and reliability, and also calculating the compatibility rate in the pairwise comparison questionnaires were the challenges and limitations of this study.

Practical implications:

 The digital games industry has a great potential for growth and development, and its favorable economic, cultural and social effects are undeniable. Some of the practical findings of this study are the creation of an elite network and a strong relationship between gaming enthusiasts and the university, empowerment of game developers' knowledge and game studios in the gaming ecosystem, and monitoring and support of governmental and non-governmental policy-making institutions.

Originality/value: 

In this paper, a new approach was proposed for evaluating and optimizing strategies for developing indigenous digital games to overcome their challenges and meet the relevant objectives in compliance with their feasibility (ease) of implementation. Also, the use of mathematical modeling in evaluating and selecting optimal strategies in this industry distinguishes this study from the literature.

This study aims to locate the Customer Order Decoupling Point (CODP) based on supply chain typology using Make to Stock (MTS) and Make to Order (MTO) approaches for standard and innovative products in the Bushehr Polymer industry.

Two mathematical models have been proposed that seek to minimize the costs of mass production, customized production, and transportation costs. To solve and simulate the models, MATLAB R2019a software has been used. Then, the indicators and requirements of pulling and pushing production management strategies have been extracted and calculated.

The results indicated that the polymerization stages of the products include six stages: casting, molding, extrusion, bonding, cutting, and forming. Also, findings indicated that the optimal locating of (CODP) for polymer products is in the pushing production area and the cutting and molding stage. The determined optimal location indicated that the producer will have the lowest cost at this location for future production. It was inferred that the (CODP) point is based on the supply chain typology approach in the cutting and mass production area. Considering the nature of the linear model minimization of this research, the total cost index (C) indicated the lowest value in this area. Research

Due to the unique characteristics of the case study, the results of this research cannot be generalized to other industries. The covid-19 pandemic resulted in difficult access to data. The lack of research-related studies was another limitation. It was recommended to examine the position (CODP) in the LARG, sustainable and robust supply chain. Also, it was suggested to perform similar research in other industries and compare the results. Practical implications: Most of the company's products were located in the mass production area or standard products, hence, the company must maintain its profit margin by focusing and relying on this area. On the other hand, it should be noted that in the current economic situation, accepting separate orders outside the normal production conditions, not only does not benefit the company but also leads to the loss of the available resources spent on production lines. The supply chain typology of polymer products outlined that the values of the variables of the studied model in a period of 12 months can be calculated based on the point of separation of the customer order.

This study removes additional and ineffective patterns in the literature and enumerates the necessary indicators to determine the point of CODP. The innovation aspect of this study is the typological approach of the polymer supply chain and identifying its six steps for determining the CODP point to manage cost and time.

This paper aims to introduce necessity and possibility equality constraints in a real case, developing and improving fuzzy network DEA models by using proposed relations and creating a suitable and applicable framework for situations with uncertain and ambiguous data with multi-stage and network structure.

First, the defuzzification relations of necessity equality constraints have been introduced. Then a new fuzzy network DEA model using proposed relations has been developed. After presenting the appropriate mathematical model and due to the infrastructural role of the electricity industry in the country's economy, electricity industry network structure, and uncertainty in some data of the electricity industry, the proposed fuzzy network DEA (FNDEA) has been used based on the possibility theory to evaluate all efficiency and sub-efficiency scores of Iran regional power companies.

For evaluating the efficiency of the proposed FNDEA, the designed fuzzy network DEA has been used to calculate all efficiency and sub-efficiency scores of Iran's regional power companies. According to the results, the proposed research approach can be used as an efficient tool for performance evaluation in processes similar to network-fuzzy nature.

For future studies, FNDEA-SBM could be reformulated using a credibility measure which is considered as an average of the Pos/Nec measure, and a general fuzzy measure that is equal to the convex combination of Pos and Nec measures. Also, the adjustable fuzzy DEA model (AFDEA), which was proposed by Peykani could be adopted to equality constraints using Theorem 1. The novel fuzzy concepts such as Z-number, fuzzy type-2, and random fuzzy variables model (for more details see Azadeh & Kokabi (2016), Qin, Liu, Liu and Wang (2009), and Tavana, Shiraz, Hatami-Marbini, Agrell and Paryab (Tavana et al., 2013). In addition, further investigation into the evaluation and ranking of DMUs in different contexts and real-life case studies with fuzzy data can be carried out by applying the proposed model.

The results of the proposed fuzzy network DEA model based on the possibility and necessity measures provided useful managerial implications for the efficiency and sub-efficiency evaluation of regional power companies. The study proved the usefulness of fuzzy network DEA as a decision-making tool in processes similar to network-fuzzy nature. Social implications: Due to the infrastructural role of the electricity industry in the country's economy, it is significant to evaluate the overall efficiency and sub-efficiencies of generation, transmission, and distribution centers of regional power companies. Allocating the optimal resources in the generation, transmission, and distribution centers of regional power companies based on the proper criteria increases the efficiency of the electricity industry and the quality of the level of welfare of the community.

Concerning the necessity (Nec) measure, there is a lack of any procedure or formula to deal with equality chance constraints and this is one of the main challenges in possibility theory; therefore, in this paper and for the first time a solution has been provided to deal with such a challenge.

 Scheduling of batch production and machine disruption are the two main challenges in manufacturing organizations. Due to the complexity of production processes, many industries try to group jobs according to family criteria and use a common setup time to process every family. Also, machine breakdown is an influential factor in the planning of production systems. In this paper, the problem of scheduling a single machine with family setup times and breakdowns is studied. It is assumed that there is a breakdown with an uncertain start time and duration based on the specified probability distribution functions during the planning horizon. The objective function of this problem is the sum of the expected maximum earliness and maximum tardiness.

Design/methodology/approach:

 For the problem under study, a new mixed integer linear programming model has been developed. Due to the NP-hardness of the problem, a new branch and bound algorithm with the dominance rules and an efficient lower bound is presented for its optimal solving, which uses a new heuristic approach to achieve the upper bound.

 To evaluate the performance of the introduced algorithms, 2520 instances were designed and solved with the presented algorithms. The computational results indicated that 98% of the instances were optimally solved in the specified time limitation by the branch and bound algorithm, and the average percentage of deviation from the optimal solution in the proposed heuristic approach was less than 30%. The results demonstrated the efficiency of the proposed algorithms.

Research limitations/implications:

 Considering the newness of the problem investigated in this paper, the proposed instances and algorithms can be used as a basis for evaluating other solution methodologies in future research studies. Also, considering other modes of machine failures such as scenario-based failures or re-scheduling the jobs to minimize the deviations of the actual schedule from the planned program, situations with more than one machine such as parallel machines, flow shops, and job shops, other objective functions related to scheduling such as maximum completion time or total completion time, as well as the development of other exact, heuristic or meta-heuristic algorithms are suggested as subjects for future study.

Practical implications:

 The problem studied in this paper can be attractive and practical for manufacturing organizations. Industries such as automotive, ship and aircraft manufacturing, steel, telecommunication power supply manufacturing, electronic, computer processors, and all industries and systems that somehow deal with the batch production process and unexpected machine breakdowns, can benefit from the results of this research.

Social implications:

 Because in this study, the starting and finishing times of machine breakdowns were predicted, by applying the results of this research, the production of defective products will be prevented when the machine breaks down, and this leads to the reduction of waste in the environment. Also, according to the objective function defined in the problem investigated in this article, the implication of the results of this research in production environments leads to the reduction of earliness and tardiness costs, which in turn increases the work efficiency of human resources and as a result, increases the job satisfaction.

Originality/value: 

It seems no study has been conducted on the single machine scheduling problem with batch production, random breakdown, and the objective function of minimizing the sum of the expected maximum earliness and maximum tardiness of the jobs. Particularly, innovations of this paper are threefold: i) a new mixed integer linear programming model was developed for the problem; ii) a novel heuristic approach was proposed to solve the problem, based on hill climbing (PHC); and iii) a new branch and bound algorithm with the dominance rules and an efficient lower bound was presented to solve the problem optimally, which used the PHC heuristic approach to achieve the upper bound.