مجله مدیریت تولید و عملیات
سال چهاردهم شماره 3 (پیاپی 34، پاییز 1402)

In this paper, a new comprehensive model has been developed to guide organizations regarding the establishment of a productivity management system with all essential elements and relations. Using the knowledge available in the literature and expert views, this research has tried to propose an evaluation scheme to measure the maturity of the system in Iranian organizations.

Design/Methodology/Approach: 

This study is typically an applied-developmental research as it introduces a framework for the assessment of productivity management systems in Iranian companies (developmental) and also attempts to offer a method for solving or simplification the complex, chronic problem of productivity in Iranian businesses (applied). From another perspective, the current research should be regarded as a qualitative research approach that seeks to describe and explain the phenomenon of productivity management system maturity based on an analysis of both quantitative and qualitative data. The main strategy adopted in identifying conceptual elements concerning the productivity management system has been encoding. The primary signs of conceptual elements have been identified with a systematic search of databases containing scientific documents and reports on one hand and during interviews with experts on the other. The main concepts and categories about the topic have been extracted through a combination of homogeneous signs.

Four categories were identified in the encoding process (labelled as four modules of the productivity management system) and 18 concepts underlying such categories were included within the four modules. Then, 76 signs were extracted from the analysis of documents and interviews as peripheral aspects or features expected from the corresponding elements. Accordingly, the first step in the establishment of a productivity management system in an organization was to provide the infrastructures required for the managerial subsystem. Next, the main processes of productivity needed to be activated based on the available or generated infrastructures. In the third step, the appropriate measures had to be taken to guarantee the sustainability of the subsystem and ensure its constant growth and development. Finally, the impacts of the establishment of the productivity management system were expected to be evaluated to indicate the extent to which the attempts made have helped to meet the various needs of different groups of extra-organizational beneficiaries (including environmental activists and local community members).

Social implications:

 Constant enhancement of productivity as one of the most significant aims of any organization, requires the establishment of a series of factors and elements that make up an organization’s productivity biome, all the aspects and layers of which need to be shaped correctly. Such a requirement can be operationalized in an organization only through the establishment of a comprehensive productivity management system, a managerial system that has not been considered accurately and practically so far in the rich literature review concerning the subject of productivity. This study was conducted to eliminate this research and administrative gap and plotted the conceptual map of such a structure through the extraction of signs of the conceptual elements concerning the managerial system using scientific documents and interviews with experts. By developing organizations that perform their activities more productively, they are more successful in achieving their goals. Therefore, people will also benefit from the performance of this productive organization and will be more satisfied.

Originality/value: 

This study has proposed a conceptual map for productivity management systems through the extraction of signs of the conceptual elements concerning the managerial system using scientific resources and interviews with experts. It has also proposed a comprehensive model showing how the productivity management system could be established in an Iranian organization using procedural documents such as the administrative guidance developed by the National Productivity Organization. The validity of the model (referred to as i-MAPS) was confirmed through the formulation and administration of the evaluation logic for the measurement of the maturity of the system and its pilot implementation in some private and public organizations in Yazd Province. The maturity of an organization in the establishment and utilization of the productivity management system can be analyzed using the developed model. Besides, the measures can be taken based on instructions extracted from the model contents to increase the organization’s success in the roadmap and to overcome probable challenges and obstacles.

This paper aims to analyze comprehensively and structurally the different methods proposed in the literature by researchers, and identify the new fields for future studies.

Design/methodology/approach: 

In this research, the methods proposed in the literature have been explained comprehensively and structurally focusing on mathematical functions, assumptions, functional objectives, results, weaknesses, and strengths. Different types of dependencies between system components have been also considered in this study.

In this paper, the methods in the literature were clustered by a new approach based on the system type, dependency, the method of considering the dependency and the objective. The different challenges of this field of study in the future were also investigated in this paper.

Research limitations/implications:

 Few practical studies in the field of multi-component systems have been performed in the literature. 

Practical implications: 

Since the analysis of multi-component systems is considered an important and applied issue in the reliability field for different complex products, the discussion of this paper and the results can be used by technical experts in different industries.

Social implications:

 This paper can be used as a reference for increasing people’s quality of life.

Originality/value: 

To the best of the authors’ knowledge, this is the first time that a comprehensive analysis of multi-component systems is reported in considering its structure and applied approach

This paper aims to evaluate the response of different countries against Covid-19 for three consecutive periods from January 2020 to October 2022. 16 countries have been chosen based on their differences in various demographic, cultural, and geographical characteristics.

Design/methodology/approach:

 Window Data Envelopment Analysis (DEA) model, Malmquist Productivity Index and DEA with non-controllable input variables have been used over three periods of 345 days to evaluate the efficiency of health systems of the countries. By the Window DEA and DEA with non-controllable input variables, the efficiency of the countries in several different periods has been compared. Also, the scores for the progress of countries' performance during successive periods have been computed by the Malmquist Productivity Index.

The performance scores calculated with the window DEA indicated that there is a difference in the countries' responses. Based on the obtained results, China had the most efficiency and Italy had the worst efficiency during the three periods. Based on the model of uncontrollable variables, Egypt had the best performance, although the model did not distinguish among most countries. The results of the Malmquist Productivity Index method also indicated that countries had different efficiencies and progress. Based on its results, Malaysia had the most progress, while Singapore had the least progress during the three periods. China despite its high-performance score from the window DEA, had not received a good score from the Malmquist Productivity Index and non-controllable input variables model, which implies the low growth and even retrogression of this country during the three periods. According to the results of the window DEA, Italy had progressed, but this growth has not been enough to make this country's performance efficient.

Research limitations/implications:

 The selection of different and more precise time intervals based on COVID-19 variants (alpha, delta and micron) and a wider selection of countries can be considered in future studies. Considering the amount of vaccination or the type of vaccine and observing its effects dynamically on the DEA model can be also a potential direction for future research. The development of window DEA and the Malmquist Productivity Index for uncontrollable variables and their application to the data of this paper are also suggested. Besides, the selection of input and output indicators based on other goals can be investigated in future studies.

Practical implications: 

To increase countries’ efficiency in dealing with epidemics such as COVID-19, different countries need to know as much as possible about their current situation. One of the ways to get this recognition is to compare them with other countries with the best performance. In such conditions, finding relative efficiency and trying to make the inefficient ones efficient is a solution to increase efficiency. It is possible to identify and extract coping strategies from successful countries with good performance in dealing with COVID-19, and suitable strategies can be implemented in Iran according to the required facilities and infrastructure.

Social implication:

 Appropriate reactions and successful strategies of health systems of countries in dealing with epidemic diseases such as COVID-19 can be very effective in controlling such diseases and reducing their negative social and economic impacts. The results of evaluating the efficiency of different countries along with the review of their strategies can be helpful in this direction.

Originality/value: 

An attempt has been made to present a new picture of countries' response to the COVID-19 pandemic by selecting a diverse range of countries, indicators, and relatively long periods using DEA. Windowed DEA, Malmquist productivity index and DEA with uncontrollable input variables in a period of almost three years were used for the first time to evaluate the efficiency of countries' health systems and their progress in dealing with COVID-19.

This study aims to propose a novel supplier-managed inventory model called Block-SMI, which is based on blockchain technology. Block-SMI is a customer-supplier collaboration architecture that utilizes blockchain technology to divide the main service integration problem into smaller sub-problems, each dealing with a smaller portion of the service/demand pool. Block-SMI aims to utilize the capabilities of blockchain technology to address the limitations of centralized approaches. Centralized approaches often struggle with large-scale problems and struggle to derive near-optimal solutions efficiently. By leveraging blockchain technology, Block-SMI seeks to overcome such challenges and achieve more efficient and effective solutions. Block-SMI operates under the same hypothesis as the supply chain collaboration model and seeks to address the challenges of scaling by utilizing the decentralized and distributed nature of blockchain technology. In this paper, the application of Blockchain technology and its potential for successful SMI implementation are investigated. The framework includes a mathematical model for multiple supplier-customer order fulfillment which is embedded in the blockchain framework. Some cases are studied to evaluate the performance of the proposed model compared to the literature, discussing the details of its blockchain framework.

Design/methodology/approach:

 First, a mathematical model has been formulated and developed. Then, the mathematical optimization of NLP with an objective model has been developed. The proposed model has been solved by GAMS software and a genetic algorithm. The problem has been solved in a centralized network using a genetic algorithm to provide the total cost value of supply chain management.

The objective function of Block-SMI aims to minimize the overall inventory cost within the entire supply chain management. This cost includes the expenses borne by both the supplier and the customer. This objective function is evaluated by all solvers and customers, and it is used to guide the matching process of customer demand with suitable suppliers. The aim is to find an optimal solution that minimizes the overall inventory cost while meeting the customer's requirements and ensuring that the supplier's capabilities are utilized effectively. By minimizing the total inventory cost, Block-SMI aims to reduce the overall cost of supply chain management and improve efficiency. To evaluate the effectiveness of Block-SMI, several scenarios were conducted. These scenarios involved comparing the proposed method with a centralized mechanism that was commonly employed to handle similar types of problems. By comparing the performance and outcomes of Block-SMI with the centralized approach, this study aimed to assess the advantages and benefits of utilizing the decentralized blockchain-based solution. The characteristics of Block-SMI were further described and analyzed, and the results demonstrated that Block-SMI is an effective solution for supplier-managed inventory problems, especially for large-scale scenarios.

Research limitations/implications:

 The most important limitation of the model, which can be seen as a development, is that the potential of the smart contract has not been used in the field of optimization.

Practical implications:

 Applying the proposed approach from the point of view of managerial insights, highlights the fact that the application of Blockchain technology enables the platform for managing the solvers’ contribution to the assignment of supplies to customers as new service provider business models. From the point of view of business model competency, solvers as assignment service providers must increase their competencies for better performance in solving their sub-problems. As a solver uses more time to proceed with its algorithm and get a better answer to increase its reward, other solvers may announce their solutions with overlap sooner. This causes persuades the solvers to restart the sub-problem formation.

Social implications: 

The framework applies a reward policy mechanism to both promote the near to optimum assignment for solvers and also benefit them from the yielded optimality with the blockchain token model. Finally, the proposed frameworks enable the detection of possible conflicts among the solvers for overlapping sub-problems and avoid the announcement of in-feasible assignments regarding supplier capabilities and customers. The findings imply that the yielded optimality of consolidated sub-problems is better from the point of view of solving time and resulting from optimality.

Originality/value: 

The proposed new mathematical model innovatively has investigated the supplier-managed inventory platform based on blockchain technology and uses the results to optimize time and cost reduction between stakeholders.

The design of facility layout and production planning accordingly is significantly important in the manufacturing industries. This type of design in traditional units is mainly based on the lowest cost of moving materials and effective environmental indicators, and social factors are ignored in the planning and design of facility layout; Therefore, usually, the arrangement does not match the human capacity, the intensity of the employees' work is not scientific and it causes a lot of damage to the physical and mental health of the employees for a long time. Considering the importance of the mentioned items, paying attention to biological issues such as energy, which is one of the main concerns of the country, and social issues, such as the safety of the operator's work environment, which is followed by governmental and non-governmental associations, can be considered a positive and new step in the layout design.

Design/methodology/approach: 

In this paper, a multi-objective mathematical programming model has been developed in a dynamic cellular manufacturing system, taking into account the minimization of the costs of moving and rearranging the facilities, the minimization of the risks of the work environment (the potential risk of placing machinery in a certain place), and the consumption of electrical energy in product production operations. To make the model closer to reality, other issues related to the production environment such as hiring and firing operators in each period, training, wages and their allocation are also included in the model. The proposed model is solved by designing samples in different dimensions, applying the epsilon constraint method and meta-heuristic algorithm NSGA-II and MOPSO, using performance indicators, and associated comparison and analysis by T-test.

Performance indices (spacing metric, diversification metric, mean ideal distance, CPU time) in solution methods were calculated and compared based on information inspired by the subject literature and the design of 15 problems with different dimensions. The results indicated that the quality of the solutions obtained from the NSGA-II algorithm was better than other methods and in terms of the solution time, the solution was reached at least two times earlier than the epsilon constraint method.

Research limitations/implications: 

For future studies, it is suggested to investigate the performance of other meta-heuristic algorithms to solve the proposed model; Also, the combination of other real-world industrial factors such as financial and energy resource limitations, facility idle time, and unequal facility dimensions can be considerably valuable for future research. In addition, the uncertainty of the parameters, which is one of the main and practical issues in the real world, can be added to the model in terms of demand or processing time.

Practical implications:

 The dynamic cellular manufacturing system is one of the well-known manufacturing systems that provides the possibility of increasing the level of reactivity, flexibility and agility in production to compete in the market, but with the growth of industrial development and the increasing attention of societies to the amount of energy consumption and the conditions of employees in production with a new challenge. It has been faced in such a way that it should include sustainability issues from the very beginning and in the design of the facility layout. The proposed model has provided a stable, dynamic and optimal layout by creating a balance between the dimensions of sustainability (cost, energy and layout safety) in manufacturing industries.

Social implications:

 Ignoring social issues and mismanagement of human resources has resulted in unforeseen costs for manufacturing companies. This study attempts to propose a model that is closer to reality and provides a more accurate and safe arrangement by considering various dimensions of human resource management in production, such as hiring, firing, training, wages, and allocation, which are effective tools for decision-making in organizations, alongside workplace safety.

Originality/value:

 In this paper, a nonlinear mixed integer programming model is proposed for the facility layout problem in a dynamic and sustainable cellular space. In this model, the amount of energy consumption, which is one of the main issues that manufacturing industries deal with, has been addressed and has helped industries in improving their performance. Two approaches have been proposed for this issue. The amount of energy used to move the machines and the amount of energy used in processing each part/product based on the selection of the best route. In this model, the best production route is selected in such a way that, in addition to reducing production costs, energy consumption in moving parts and processing each operation should be reduced.