Journal of System Management(JSM)

This research seeks to investigate the influence of human resource practices on organizational effectiveness by considering the mediating role of internal customer satisfaction. It draws on data from a human resource department and its employees; a total of 294 valid questionnaires are obtained. Structural equation modeling is employed to examine the proposed model. The results of this research hypotheses test indicate that human resource practices have direct and significant effects on internal customer satisfaction and organizational effectiveness. What’s more, internal customer satisfaction has a mediating role in the relationship between human resource practices and organizational effectiveness.

The purpose of this research is to provide a service compensation system with the approach of improving the employer brand in Refah Bank. The current research is applied in terms of purpose, exploratory in terms of data collection method, and qualitative and quantitative (mixed) in terms of data nature. The method of data collection and analysis was used in the qualitative part, interview type, and theme analysis method were used for analysis, and in the quantitative part, it was a questionnaire and structural equation modeling with the partial least squares (PLS) approach. The current research community was formed by experts and experts related to the research topic in Refah Bank branches as well as marketing professors in the university. In this research and the qualitative section, the opinions of 16 experts were used using the snowball sampling method. Also, in the statistical part of the research, based on the available sampling method and Cochran's formula, the opinions of 225 experts related to the research topic were used. The process of data analysis was done in two stages, which includes identifying the dimensions and components of the system through interviews and theme analysis; Validation of the research model is through questionnaire and structural equation modeling method with partial least squares (PLS) approach. The results showed that the service compensation system with the approach of improving the employer brand in Refah Bank has three main dimensions including system input indicators, system processes and system output indicators.

With the aim of comprehensively investigating the most important consequences of website quality in e-commerce, this research has collected and analyzed data about the relationship between website quality and customer trust, satisfaction, and loyalty. In this regard, various studies were collected and coded. After that, the eligible studies to enter the meta-analysis based on the determined criteria were identified to be 49, 68, and 29 studies for the relationship between website quality and trust, satisfaction, and loyalty, respectively. The findings of data analysis using CMA2 software showed that website quality has the strongest relationship with satisfaction with an effect size of 0.591 and the weakest relationship with loyalty with an effect size of 0.516. The effect size of trust was also positive and equal to 0.555. In addition, the findings from the analysis of moderator variables also showed that an increase in the year of publication led to a decrease in the effect size of website quality-trust studies but an increase in the effect size of website quality-satisfaction and website quality-loyalty studies. Additionally, with an increase in the sample size, the effect sizes of website quality-trust studies increased, but the effect sizes of website quality-satisfaction and website quality-loyalty decreased.

Since organizations work in complex and uncertain settings, their supply chains should be managed. The first step of supply chain management is to identify factors such as risks that disrupt this process. Risk and disruption can lead to failure of the supply chain of companies. Therefore, to reduce the effect of such disruption, the supply chain should be designed in such a way that they can recover to their initial state or even create better conditions by providing an efficient and effective response in the face of events. i.e., resilience in the structure of the supply network. Given the importance of risk management and resilience in the supply chain on the one hand, and few qualitative studies conducted in this field on the other hand, this study was conducted to propose a paradigmatic model of risk management based on resilience in the National Iranian Oil Products Distributing Company (NIOPDC) and the gasoline supply chain. This study has been conducted using a qualitative approach and multi-grounded theory (MGT) in such a way that with a deep review of the relevant literature and the use of 64 articles and 17 semi-structured interviews, data were collected and analyzed and a Conceptual Model of supply chain risk management (SCRM) was proposed by the resilience approach for gasoline products in the NIOPDC.Based on research findings, A total of 58 concepts and 14 dimensions were extracted under 5 categories of SCRM, a Conceptual Model was proposed, and accordingly two hypotheses were presented. Given the proposed paradigm model, risks cause disruption in the supply chain. If there is a governing platform for active supply risk management, by identifying risks and applying resilience capabilities to face the risks appropriately leads to management risks and achievement of the goal of "guaranteeing smooth and uninterrupted flow of fuel supply".

One of the factors that should be considered in important management decisions is corporate life cycle; Accordingly, the purpose of this paper is to examine the effects of corporate life cycle on real activities management by considering the role of family ownership. For statistical analysis, data from 106 firms listed on Tehran Stock Exchange from 2013 to 2022 was used. The results of regression analysis of the study showed that firms in the growth stages engage in a higher levels of real activities management via sales management and production cost management than mature firms. However, in the growth stages, they are engage in a lower levels of real earnings management via discretionary expense management than mature firms. Also, the findings suggest that firms in the decline stages engage in a higher levels of real activities management than mature firms. In addition, family firms can be more aggressive in real activities management than non-family firms. The findings of this paper can be used and interest to investors, auditors, regulators, and academics concerning financial reporting quality and financial statement analysis. They can consider the corporate life cycle in their decisions about evaluating real activities management.

This research aimed to rank the components of smart network governance in the Iranian banking system. This article discusses the prioritization of the governing elements of smart grids identified from the research conducted by the researcher is discussed. This research was carried out quantitatively and with a simple survey method. The participants of this research were managers and experts of the country's banking system. Participants were selected via purposive sampling with the criterion of at least 10 years of experience in banking management, at least a master's degree, and with the study field of preferably management. The data analysis was done using the method of network analysis process. Super Decision software was used for data analysis. The research results show that the components of the smart network governance model compiled in order of priority include behavioral factors, stability and economic prosperity, mechanism factors, legal considerations, structural factors, comprehensive development, and information and communication technology.

In this paper, we present a comprehensive approach for evaluating efficiency in complex networks by integrating network data envelopment analysis (NDEA) with the Malmquist productivity index. The proposed method addresses the inherent challenge of accommodating negative data within the network efficiency evaluation framework, which is a common occurrence in real-world network operations. Through the introduction of a two-stage structure, the model not only effectively manages the presence of negative values, but also provides a robust and insightful assessment of network efficiency. A case study from banking sector is employed to demonstrate the efficacy of the proposed approach, showcasing its capacity to offer valuable and actionable insights for decision-making in complex network environments. The results highlight the practical applicability and importance of the extended approach in addressing the complexities associated with evaluating efficiency in diverse network settings.

After assessing the efficiency of the units under evaluation, determining their ranking becomes a critical concern for decision-making. Ranking methodologies rely on specific unit inputs and outputs, but some variables affecting unit performance are not directly observable and are termed contextual variables. Thus, the primary objective of this research is to introduce a ranking methodology that incorporates these variables. To achieve this, a two-step approach is employed. Firstly, the Data Envelopment Analysis (DEA) technique calculates efficiency scores for each Decision-Making Unit (DMU), considering its unique inputs and outputs. Subsequently, the linear regression method is applied to assess the impact of contextual variables on efficiency. Finally, efficiency scores are modified by removing the impact of contextual variables, enabling unit ranking. To illustrate this proposed methodology, we conducted a performance evaluation of provincial gas companies in Iran. The evaluation covered four periods, from 2013 to 2016.

Sound waves are one of the essential factors of daily life and work activities that can cause environmental pollution in the necessary contact between humans and the surrounding world. Noise pollution is reported to be amongst the leading causes of occupational diseases and the second leading cause of occupational injuries in the workplace. A variety of equipment, machines, and work processes are used in industry that are considered sources of disturbing noise. The aim of this study is to assess the noise exposure of workers in industrial environments using the Bowtie approach and Data Envelope Analysis (DEA). The motivation of the research is the multidimensional nature of the concept of noise exposure from the perspective of the exposure situation and the capability of DEA models to evaluate the efficiency of stations based on multiple inputs and outputs. This study uses a quantitative approach. The research method is descriptive cross-sectional. In this research, a case study was conducted to evaluate 10 stations of a company in the industrial area in the first half of 2023. The Bowtie approach was used to determine the correlation between noise exposure and its consequences. The collection of noise exposure measurement data enables the mathematical modeling of the BCC input based on the DEA approach using the EMS software, where the input of the model is the "equivalent sound level" and the output of the model is the "noise pollution situation". The results show the different efficiencies of the 10 stations investigated and the superiority of station 7 compared to the other stations. In the industrial area studied, 30% of the total measuring stations were located in the risk range. The average sound pressure level was estimated at 101.70 dB. It seems that companies can effectively improve the health of their employees in the workplace by directing their activities within the permissible range of noise exposure. The efficiency of measuring stations plays a constructive role in reducing exposure and improving the health of employees in the workplace.

The present study aimed to identify the factors influencing the implementation of sustainable development policies, with a specific focus on small wins in Iran. This applied and descriptive-survey study utilized a qualitative approach and employed the grounded theory method. Data collection involved interviews and the codification was conducted using the emerging (Glaserian) grounded-theory classical approach. the interview questions were meticulously developed based on a comprehensive review of the literature, and the collected data were coded using Strauss and Corbin’s (1998) paradigm model. The research population comprised specialists and experts who held influential roles in policy implementation, and they were selected using purposive and theoretical sampling. The sampling process continued until the data were theoretically saturated, ensuring a comprehensive understanding of the subject matter. the results of the study revealed the significant impact of various factors on the implementation of sustainable development policies. Notably, in line with the new concept of small wins and the principles of sustainable development, the study identified 36 indicators, which were categorized into drivers and inhibitors. Each main indicator encompassed six economic, social, cultural, strategic, environmental, and organizational factors, along with 18 sub-indicators. These findings underscore the importance of considering these indicators for formulating sustainable development policies and goals, particularly for developing countries like Iran, in order to achieve sustainable development on a global scale.

The main goal of this article is to identify the optimal patterns of financial wealth and the mathematical requirements of reserves based on risks in Iran. The method of this article is descriptive-inferential in terms of practical purpose and library data collection method. The statistical population of the research is all the experts in the country's insurance industry. The results of this article showed that the country's insurance industry experts, including university professors and senior managers of Iran Insurance Company, agree with these four main risks in the financial prosperity model (П); But these four main risks are not enough for the model of financial prosperity (П). In the final model, the optimal pattern of financial wealth and the mathematical requirements of risk-based reserves in the Iranian insurance company includes four main pillars, which include 6 basic and general contain asset/liability mismatch risk, reinvestment risk, exchange rate risk, international market risk, life insurance account separation risk from non-life insurance account, life insurance account investment risk risks in the insurance industry Each of the basic and general risks of the insurance industry also has several risks and sub-categories

As the digital landscape continues to reshape the banking industry, understanding the factors influencing customer loyalty in online banking becomes paramount. This study investigates the intricate relationships between e-satisfaction, e-loyalty, and the moderating effects of consumer perceived risk and skill. Drawing on a sample of 168 customers from selected branches of Bank Mellat in Mashhad, statistical analyses were conducted using SPSS and Smart-PLS. The results reveal a direct and positive impact of e-satisfaction on e-loyalty, elucidating the fundamental role of customer contentment in fostering loyalty in the online banking domain. Moreover, the study uncovers a nuanced interplay, demonstrating that the relationship between e-satisfaction and e-loyalty is contingent on the levels of consumer perceived risk and skill. High perceived risk and low skill levels diminish the impact of e-satisfaction on e-loyalty, highlighting the need for tailored strategies for these customer segments. This research contributes to the evolving understanding of e-loyalty dynamics, emphasizing the significance of customization, security, convenience, delivery, communication, and website aesthetics in shaping customers' e-loyalty. The findings provide actionable insights for banking institutions to refine their online platforms, fostering a more personalized, secure, and engaging digital banking experience to enhance customer loyalty.