Iranian Journal of Management Studies
Volume:13 Issue: 4, Autumn 2020

The main purpose of this research project was to investigate the impact of Strategic Human Resource Management practices on knowledge sharing behavior among university faculty members. This research also studied the mediating role of trust and organizational commitment in the relationship between SHRM practices and knowledge sharing behavior. Following the positivist paradigm, this research adopted the quantitative research strategy and collected the data from 700 faculty members of leading universities (top ranked by Higher Education Commission) of Pakistan through a self-administered questionnaire. Bi-variate and multi-variate quantitative analyses were used to test the hypothesis and achieve the research objectives. Structural Equation Modeling through Smart Partial Least Square was used to test the entire key hypothesis. The findings revealed that SHRM practices are vital in creating knowledge sharing behavior among faculty members, organizational commitment partially mediates the relationship among the aforementioned variables, while trust completely mediates the relationship between HR practices and knowledge sharing behavior. Thus, this study provides sufficient guidelines for HR policymakers and administration of public universities on how to make faculty members more committed to their institution and to develop the culture of knowledge sharing by adopting SHRM practices, while helping employees to have socio-emotional relationships so that trust can be developed among them.

The implementation of modern ERP solutions has introduced tremendous opportunities as well as challenges into the realm of intensely competent businesses. The ERP implementation phase is a very costly and time-consuming process. The failure of the implementation may result in the entire business to fail or to become incompetent. This fact along with the complexity of data streams has led the researchers to develop a hierarchical multi-level predictive solution to automatically predict the implementation success of ERP solution. This study exploits the strength and precision of the Adaptive Neuro-Fuzzy Inference System (ANFIS) for predicting the implementation success of ERP solutions before the initiation of the implementation phase. This capability is obtained by training the ANFIS system with a data set containing a large number of ERP implementation efforts that have led to success, failure, or a mid-range implementation. In the initial section of the paper, a brief review of the recent ERP solutions as well as ANFIS architecture and validation procedure is provided. After that, the major factors of ERP implementation success are deeply studied and extracted from the previous literature. The major influential implementation factors in the businesses are titled as Change Orchestration (CO), Implementation Guide (IG), and Requirements Coverage (RC). The factors represent the major elements that guide the implementation project to a final success or to a possible failure if mismanaged. Accordingly, three initial ANFIS models are designed, trained, and validated for the factors. The models are developed by gathering data from 414 SMEs located in the Islamic Republic of Iran during a three-year period. Each model is capable of identifying the weaknesses and predicting the successful implementation of major factors. After this step, a final ANFIS model is developed that integrates the outputs of three initial ANFIS models into a final fuzzy inference system, which predicts the overall success of the ERP implementation project before the initiation phase. This model provides the opportunity of embedding the previous precious experiences into a unified system that can reduce the heavy burden of implementation failure.

The aim of this study was to examine a psychosocial model of predicting perceived social status among faculty members. To this end, 135 faculty members in one of the state universities in Tehran, Iran, were recruited through convenient sampling. We used Perceived Organizational Support Scale (POSS), Perceptions of Organizational Politics Scale (POPS), Participation in Organizational Decisions Making Scale (PODMS), and Dominance and Prestige Scale (DPS) to collect data. Findings showed that 40% of participants believed that social status of academic careers has decreased in Iran since they have entered into their jobs. Perceived organizational support, perceived organizational politics, and participation in decision-making were associated with perceived social status directly and indirectly by the mediating role of prestige-based status-seeking style. The link between perceived organizational politics and perceived social status were negative, but there were positive associations between other factors in model and perceived social status. Then, we might conclude that perceived social status is determined by the quality of organizational support, political atmosphere in organization, participation in organizational decision-making, and prestige-based status-seeking styles. Faculty members with prestige-based status-seeking style had better feelings toward their job as a high social status job, which may facilitate their self- actualization

A correct social media strategy is essential for travel agencies working in today's global market to reach customers. The travel industry is a service-oriented industry, and travel agencies can easily reach their customers on social media by transforming their marketing strategies at no extra costs. There are so many options that a travel agency can use to make itself more visible on social media. However, it is very difficult to choose the most suitable option. From this viewpoint, an analytical framework including BWM and fuzzy VIKOR is presented to find the best social media platforms in this study. First, the weights of nine criteria that were identified by the literature survey and expert interviews were obtained using BWM. Then, these weights were incorporated with fuzzy VIKOR for the ranking of social media platforms. During the implementation phase, the managers of a travel agency in Turkey were supported by the proposed framework for the organization. Results indicated that the cost criterion was the most important criterion (0.189), followed by the audience as the second rank (0.158). The results of the framework show that the proposed methodology is valid and can contribute to improving the decision-making process of enterprises and organizations.

One of the emerging research areas in the strategic orientation is how to transfer different orientations from the commercial sector to the non-profit sector. Therefore, the objective of this study is to determine the mediating effect of Learning Orientation on the Market Orientation, Social Entrepreneurial Orientation, and Organizational Performance in the non-profit sector. The data from more than 300 employees of the non-profit organizations was collected through snowball sampling method from different parts of Pakistan and was analyzed using Smart PLS software to perform Structural Equation Modeling. The findings indicate that acquiring strategic resources is also relevant for non-profit sector, but these resources are useless if they can be easily imitated. Therefore, an organization should develop such capabilities to make resources imperfectly imitable. Research also shows that Market Orientation and Social Entrepreneurial Orientation are key strategic resources, but in the presence of Learning Orientation, an organization can exploit these resources more effectively. The study also discusses practical implications, limitations, and future directions.

One of the key issues in mining is the hauling system. Truck and shovels are the most widely used transportation equipment in mines. In this paper, a two-phase simulation-based optimization is presented to maximize utilization of hauling system in the largest Iranian open-pit copper mine. In the first phase, The OptQuest for Arena software package was used to solve the optimization problem to provide an optimal production quantity. In the second phase, the haulage system problem in the open-pit was modeled by bi-objective optimization programing by means of meta-modeling approach. Meta-modeling approach could estimate the exact total production quantities, and solved the problem by determining the optimal value of shovels using the design of experiments. The efficient solution of the bi-objective problem was obtained using -constraint method. The results of the proposed approach were compared with the current situation, where the total production had increased by 21% (equivalent to 10K tons) through the proposed approach. Therefore, calculations in this mine show that how the proposed framework can improve the production and productivity of haulage system.

This study, grounded on the Conservation of Resource (COR) theory, examines the role of perceived social support sources and the moderating impact of work-life policy on work-life balance (WLB) among female employees in the context of the Bangladeshi banking industry. Data were collected from 559 female employees from 39 commercial banks located in Dhaka and Chattogram through a questionnaire survey utilizing a multi-stage stratified sampling technique and analyzed applying multiple regression and hierarchical regression techniques. Findings highlight the importance of perceived workplace support, perceived supervisory emotional support, perceived supervisory instrumental support, perceived co-worker emotional support, and perceived family support on WLB of Bangladeshi female bankers. Further, work-life policy moderated the relationship between PFS and WLB. Findings may help the management practitioners, regulators, banking professionals, and researchers to develop a deeper insight of the sources of social support driving WLB and the indirect effect of WLB policies on the relationships between PSS sources and WLB. This research extends the existing literature of WLB by examining the indirect effect of WLB policies on the relationships between PSS sources and WLB applying the COR theory emerging from the W estern perspective, especially within the South-Asian developing country context.

Nowadays, fundraising is one of the most important issues for both Fintech investors and startups. The pattern of fundraising in terms of “number and type of rounds and stages needed” are important. The diverse features and factors that could stem from Fintech business models which can influence success are of the key issues in shaping these patterns. This study applied the top 100 KPMG Fintech startups’ data to extract clusters and fundraising pattern using sequential pattern discovery for each cluster. This led to the extraction of seven distinct clusters using 3 different clustering algorithms from 3 to 7 different rounds of investment for each cluster. The proposed frequent patterns can assist both investors and Fintech startups to show the future fundraising pattern based on their new or current startup cluster type and the ongoing stages of development.