نشریه مدیریت بهره وری
پیاپی 68 (بهار 1403)

Choosing a suitable opportunity in conditions of uncertainty is a common problem for entrepreneurs. The software startup procedure is particularly vulnerable to extreme uncertainty and competition; therefore, analyzing opportunities and threats is critical for software entrepreneurs. Hence, the present study aims to identify the criteria of uncertainty in evaluating entrepreneurial opportunities in technology-driven businesses of the software industry with a fuzzy approach using a mixture of qualitative and quantitative methods. The statistical population of the research includes experts in the software industry. In this regard, first, a theoretical basis was obtained by examining the background. Second, we performed semi-structured interviews and extracted and coded 115 phrases. Third, after combining the general and subsidiary phrases, we reached 84 phrases, and by combining similar phrases, we selected 29 phrases. Forth, after categorizing those phrases, we determined the six axes of uncertainty and used the fuzzy Ahp technique and Geometric Buckley averaging in Microsoft Excel to rank those six axes as follows: 1-uncertainty in resources, 2-uncertainty in competition, 3-technological uncertainty, 4-political uncertainty, 5-uncertainty in agents, and 6-customer uncertainty. Finally, the model of evaluating entrepreneurial opportunities in conditions of uncertainty was designed using a fuzzy approach in the software industry.

Global competition, dynamic markets, and rapidly shrinking innovation and technology cycles, all have imposed significant challenges on the financial, banking, and insurance industries and the need to data analysis for improving decision-making processes in these organizations has become increasingly important. In this regard, the data stored in the databases of these organizations are considered as valuable sources of information and knowledge needed for organizational decisions. In the present research, the researchers focus on the common customers of the bank and insurance industry. The purpose is to provide a methodology to predict the performance of new customers based on the behavior of previous customers. To this end, a hybrid model based on support vector machine and genetic algorithm is used. The support vector machine is responsible for modeling the relationship between customer performance and their identity information and the genetic algorithm is responsible for tuning and optimizing the parameters of the support vector machine. The results obtained from customer classification using the proposed model in this research led to customer classification with a high accuracy of 99%.

In health care provider organizations (HCPOs), there are several sub-units, simultaneously providing health and preventive services to the population covered, in which measuring productivity is one of the most important challenges for the managers of these organizations. Hence, the purpose of this study is to provide an integrative approach of data envelopment analysis (DEA) and Malmquist productivity index (MPI) to monitor the productivity in Iranian Petroleum Industry Health Organization (PIHO) as an HCPO. In this study, using the indicators related to efficiency and defining the specialized indicators affecting the performance of the sub-units of this organization, the growth rate of the performance of the sub-units was determined through calculating four distance functions and Malmquist productivity Index. According to the results of this study, 27 specialized indicators in the fields of direct and indirect health and preventive services for monitoring the effectiveness of proposed HCPO have been presented. Also, the growth rate of productivity of the fifteen areas of the organization under study has been evaluated from 2019 to 2021. The innovative aspect of this article lies in the definition of effectiveness measurement indicators and presentation of a theoretical framework for monitoring the rate of productivity in HCPOs. The findings of this applied research in health service organizations can be used to enhance capacity in different areas of health care and save resources.

This study aims to investigate the unique features of the food supply chain, examining the impact of food supply chain integration, consisting of internal integration, supplier and customer, the quality of food products and product innovation capability. Managers need to understand the importance of supplier and customer integration when responding to supply chain risk and company uncertainty. The data were collected from 168 managers active in the food industry in Tehran province. The partial least squares tool (SmartPLS 3.0) was used to analyze the data using Structural Equation Modeling (SEM) technique. The results show that there is a strong relationship between uncertainty and supply chain integration including customer, supplier and internal integration. The findings indicate that customer integration and supplier integration are critical factors in improving product quality in the food supply chain. The results can be related to the prominent role of customer relations and contact in the development of innovation capabilities in manufactured products, which has also been approved by some previous studies. Additionally, analyzing the various dimensions of supply chain integration separately revealed that internal integration is a capability factor for external integration. This study can help businesses in the food industry understand the value-creating roles of food supply chain integration and provide valuable guidance for them to decide how to meet the various challenges and manage food supply chain integration in order to improve product quality and product innovation capability.

The purpose of this research was to develop practical knowledge in a specific field. This research was conducted with the intention of using the findings to solve specific problems within the organization and measure the impact of coaching management on sustainable performance in the Red Crescent Organization of Sistan and Baluchistan province. This study was descriptive-survey and cross-sectional in terms of data collection method. The statistical population included all the employees of the Red Crescent Organization of Sistan and Baluchistan Province, who were 1850 people based on the obtained information. The sampling method was stratified random sampling and the sample size of 318 was determined using Cochran's sampling formula with 95% confidence level and 5% error. The data collection tools included standard questionnaires. In order to measure the intensity of coaching through a two-item scale related to the effectiveness of the supervisor's coaching behavior and the extent of this behavior, it was operationalized by matching the items with the feedback of Ilgen et al (1979). Moreover, to measure the sustainable performance, a standard questionnaire (Steniski & Erbakiuskas, 2009) including 16 items was used. The results of the analysis using the structural equation method showed that coaching management, the effectiveness of the supervisor's coaching behavior and the extent of this behavior have a positive significant effect on sustainable performance.

To achieve their goals, organizations need to consider several factors, one of the most important of which is organizational participation. Isfahan Governorate, in line with its organizational mission, tries to provide quality services with a central program through encouraging increased participation of employees and taking advantage of their opinions and suggestions. Hence, the current research is aimed to present a model for increasing employee participation in Isfahan Governorate. To this end, 54 influencing factors regarding employee participation were extracted through the review of research literature. The intended research community consisted of all the employees and managers of Isfahan Governorate, and 21 senior managers of the organization who were recruited through convenience samling and their opinions were analyzed using the fuzzy Delphi method. The final factors were codyfied in 7 dimensions of leadership, job satisfaction, performance evaluation, clear goal setting and policy making, organizational culture, human resource measures and organizational structure. The conceptual model and the relationship of the factors were presented using the DEMATEL method. The conceptual model with the addition of employee participation as a dependent variable was quantitatively investigated using the structural equation modeling method. The results revealed that there is a positive significant relationship between leadership and human resources measures; leadership and organizational structure; organizational structure, goal-setting and policy-making; human resources measures and organizational culture; organizational culture and performance evaluation; goal-setting and policy-making component and performance evaluation; performance evaluation component and job satisfaction; and job satisfaction and employee participation.

One of the most powerful tools to improve the performance of human capital is performance appraisal, which is very important for university faculty members because of the impact of this group on various economic, social, political and cultural aspects of the country. Hence, the present study aimed to identify and prioritize the factors affecting the evaluation of faculty members using the fuzzy Delphi method. This study has a mixed methods research design with quantitative and qualitative sections, in an inductive paradigm, which is applied in terms of purpose and exploratory in terms of nature and method. The statistical population of the study consisted of faculty members of Lorestan University, 60 of whom were selected based on the principle of theoretical adequacy using purposive sampling. In the qualitative section, semi-structured interviews were carried out to collect the qualitative data, the validity and reliability of which were confirmed using the CVR coefficient and the Kappa-Cohen test. The data obtained from the interviews were analyzed using Atlas.ti software and coding method in which the factors affecting the evaluation of the faculty members' performance were identified. In the quantitative part, a fuzzy Delphi questionnaire was employed to collect the data, the validity and reliability of which were confirmed by content validity and retest. Additionally, using the fuzzy Delphi method, the identified factors were prioritized and the most important factors were identified. The results show that among the factors affecting the evaluation of faculty members, having original and well-cited research in their fields, observing scientific and professional ethics, being known nationally and internationally, having prominent contribution to the field, having a work in which the applicant proposes an idea and has a high share of its credit, and having scientific credibility and authority.

Knowledge transfer between university and industry is an important driver in innovation and economic growth. The purpose of this study was to design a model for improving productivity in wood industry focusing on the commercialization of university knowledge and ideas. This research was developmental-applicative, a mixed method (qualitative-quantitative) study with a combined exploratory-sequential design. The target community of the research was experts who were aware of the research topic. In order to conduct in-depth interviews and collect qualitative data, from the targeted snowball technique to the theoretical saturation stage, 17 people were selected as a sample and in order to complete the researcher-made questionnaires in the quantitative section, a sample of five people was suggested. The validity of the qualitative data of the research was confirmed through continuous observation and review by a colleague and the reliability of these data was estimated to be 89% using the two-coder index method. The validity of the quantitative data was found to be 80% by using the Lawshe content validity ratio and their reliability was 86% using the Cronbach’s alpha coefficient. Conducting the thematic analysis method based on the model of Braun and Clark (2006), the effective indicators of improving productivity with a commercialization approach toward university knowledge and ideas were identified and then modeling was done using structural-interpretive analysis (ISM). Based on the results of the research, 114 primary concepts were identified including 20 sub-themes and 13 main themes. These indicators were at six levels of the structural-interpretive model consisting of the index of strategic plans at the sixth level, the structure and support management at the fifth level, the development of interaction at the fourth level, the improvement of the educational system, the development of infrastructure and the personal characteristics at the third level, the indicators of modeling, industrialization, motivation, human resources, and attracting the private sector at the second level, and the marketing index was at the first level. Therefore, managers and policy makers need to understand the nature and relationships among the identified indicators in wood industry and apply the necessary measures in this field in order to improve productivity in industries with a commercializing approach toward university knowledge and ideas.