Research Paper
Management approaches in the field of smart
Mojtaba Ahmadi; Alireza pourebrahimi; Ladan Riazi; Seyed Abdollah Amin Mousavi
Abstract
In this paper, the challenges to the implementation of the IT audit process in Iran's banking network have been identified through a number of case studies in four large Iranian banks. The data has been collected through conducting 20 interviews with experts in both IT management and IT audit fields ...
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In this paper, the challenges to the implementation of the IT audit process in Iran's banking network have been identified through a number of case studies in four large Iranian banks. The data has been collected through conducting 20 interviews with experts in both IT management and IT audit fields of the mentioned credit institutions, and reviewing some of their internal documents. In this research, 20 cases of the main challenges and problems in the implementation of the IT audit process were identified. The findings of the research showed the existance of "Lack of independence and existence of common financial interests", "Inability to establishing communication between IT audit unit and IT unit", "Inappropriate organization and administrative structure of the entity under audit", "Lack of specialized information technology knowledge and necessary capabilities" information technology audit", "insufficient experience and inappropriate records of information technology auditors", "lack of valid training courses and lack of auditors having valid international certificates and documents of information technology audit" and "insufficient self-confidence of auditors", are among the main challenges to the implementation of the audit process that is considered information technology.
Introduction
In this paper, the challenges to the implementation of the IT audit process in Iran's banking network have been identified through a number of case studies in four large Iranian banks. The data has been collected through conducting 20 interviews with experts in both IT management and IT audit fields of the mentioned credit institutions, and reviewing some of their internal documents. In this research, 20 cases of the main challenges and problems in the implementation of the IT audit process were identified. The findings of the research showed the existance of "Lack of independence and existence of common financial interests", "Inability to establishing communication between IT audit unit and IT unit", "Inappropriate organization and administrative structure of the entity under audit", "Lack of specialized information technology knowledge and necessary capabilities" information technology audit", "insufficient experience and inappropriate records of information technology auditors", "lack of valid training courses and lack of auditors having valid international certificates and documents of information technology audit" and "insufficient self-confidence of auditors", are among the main challenges to the implementation of the audit process that is considered information technology.
Among the most effective ways of evaluating and crediting the financial and management reports calculated with the help of information technology tools is information technology audit. Today, information technology control and audit have become an important mechanism to ensure integrated information systems and financial reports of organizations to prevent heavy financial failures in the future.
According to the Central Bank regulations, Iranian banks have been required to perform the information technology audit process and provide related reports in accordance with the ISACA ITAF. The evaluation shows unfavorable results. According to the issues raised, this research tries to use Stoll and Havelka's model (Stoll and Havelka, 2021), which lead to the successful implementation and improvement of information technology audit quality, including "organizational factors", "control factors" and "Individual factors of the auditor" has been devoted to the detailed analysis of problems, challenges and enabling and inhibiting factors in the field of challenges of implementing the IT audit process in the banking network of Iran.
Literature Review
"Information technology audit" is the inspection of the organization's IT systems and infrastructure to ensure that standards and guidelines are followed, documented, have the necessary efficiency, and operate effectively in line with business goals (ISACA, 2015a). The need for optimal implementation of the IT audit process has been recognized by many researchers as the main concern of many organizations today. Studies have mainly focused on IT audit concepts, dimensions, patterns and frameworks that can be used to properly implement the IT audit process. In this paper, considering that our focus is on reviewing IT audit challenges, articles have been reviewed and evaluated that mostly deal with the main challenges that most organizations face in this field. Information technology audit in banks is different from other organizations due to the sensitivity of business, complexity of operations, unique regulations, different characteristics and security needs, high-risk environment, the importance of maintaining customers' financial information and data confidentiality, and auditors should pay attention to General frameworks should be used to review and evaluate the information technology field of banks using the specific security standards and regulations of this industry.
Methodology
In the first stage, it has been helped to review the theoretical foundations and extract categories, concepts and key codes of the challenges of implementing the information technology audit process, and then in the second stage, each of the mentioned categories, concepts and key codes, according to the information obtained from the face-to-face interviews It has been analyzed with the participants and experts' opinions of both information technology and information technology audit. In order to accurately assess the problems, challenges and enabling and inhibiting factors in the optimal implementation of information technology audit, the information technology area of 4 Iranian banks (as a representative of four types of banks in the country including: government commercial, specialized government, semi-private and fully private), to conduct a case study has been selected. The current research is fundamental-applied in terms of research directions and a case study in terms of research strategy. The main tool for collecting information and data is through interview, observation and review of collected documents and documents, and therefore its approach is qualitative.
Results
The categories, concepts and the number of 20 key codes regarding the challenges of implementing the IT audit process were extracted based on the research literature and Stoll and Havalka's model (2021) and according to the information obtained from the interviews with the participants and the opinions of experts in both IT fields and Information technology audits were analyzed. The results indicate that "Lack of independence and existence of common financial interests", "Inability to establish communication between the information technology audit unit and the information technology unit", "Inappropriate organization and administrative structure of the entity under audit", "Lack of specialized information technology knowledge and capabilities" The necessity of information technology audit", "Insufficient experience and inappropriate records of information technology auditors", "Lack of valid training courses and lack of auditors having international valid information technology audit certificates and documents" and "Insufficient self-confidence of auditors", are among the main challenges of implementing the process. It is an information technology audit.
Discussion and Conclusion
Information technology audit is the main way to measure the effectiveness of information technology services, guarantee its efficiency and avoid threats and risks. In this paper, the challenges of implementing the IT audit process in Iran's banking network were identified through a case study in four large Iranian banks. The data has been collected by conducting twenty 45-minute interviews with experts in both IT management and IT audit fields of the mentioned credit institutions and reviewing some of their internal documents. In this research, 20 cases of the main challenges and problems of implementing the IT audit process were identified. Recognizing these challenges, while providing the background for future studies regarding the formulation of IT audit implementation frameworks and models for researchers, helps credit institutions to identify these challenges and take effective measures to implement the IT audit process. The study of this research included only four Iranian banks, which of course are among the large and complex organizations; However, it limits the generalizability of the results to other organizations and businesses, which is one of the limitations of this research.
Keywords: Information Technology Audit, Information Technology Inspection, Iranian Banking Industry, Audit Implementation Challenges, Internal Audit.
Research Paper
Data science, intelligence and future analysis
Melika Armandi; Mina Ranjbarfard; Zahra Taheri
Abstract
In this research, an expert system was designed and implemented based on the ISO/ICE27001 standard. In order to create the knowledge base of this expert system, control goals and criteria for evaluating these goals were extracted based on the ISO/ICE27001 standard, and the necessary information was collected ...
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In this research, an expert system was designed and implemented based on the ISO/ICE27001 standard. In order to create the knowledge base of this expert system, control goals and criteria for evaluating these goals were extracted based on the ISO/ICE27001 standard, and the necessary information was collected to define the rules. Then, the approach of creating rules as well as the rules were confirmed through interviews with experts. The control objectives and evaluation criteria of the control objectives were using the Dematel technique along with the Dalala formula and WASPA method. In the next stage, the five main security objectives were chosen to continue the work due to their emphasis in the research literature. The specified goals were reviewed and confirmed during face-to-face interviews with experts. After designing the expert system, Visual Basic was used to implement the user interface and Excel 2016 was used for inference. The designed system is able to calculate the information security score according to the standard and also is able to calculate the information security score by applying the weight of the control objectives, the evaluation criteria of the control objectives and the percentage of realization of the main objectives of the information security. The resulted score is shown in three levels of critical status, average status and very good status to the user. Results of the system implementation in two Iranian organizations showed that the system with an average accuracy of 95% has the necessary accuracy and efficiency to evaluate information security.
Introduction
Information is a vital element for the survival of the organization and information security plays a decisive role in modern information organizations. Many organizations use successful global standards such as ISO/ICE27001 to ensure success in implementing and evaluating their information security management system. Organizations can become aware of the state of information security with the lowest cost and highest efficiency by using the intelligent information security audit system. In this research, an expert system with hierarchical coefficients to calculate the organization's information security score based on the ISO/ICE27001 standard was designed and implemented: considering the importance of control goals and evaluation criteria for these goals, as well as calculating the degree of achievement of the main security goals. In the design of this system, unlike other audit expert systems, the importance of information security evaluation criteria has not been considered equal. This system can be used in various organizations and industries for intra-organizational evaluations of information security status and determining corrective measures. Organization with ISO/ICE27001 certification can also use this system as an alternative to traditional audits to increase efficiency and reduce time and cost.
Literature review
ISO 27001 information security management standard
Information security management standards provide a security framework along with specialized techniques for implementing security in the information exchange space. The ISO 27001 international standard was prepared to provide requirements for the establishment, implementation, maintenance and continuous improvement of an information security management system (Chang and Lee 2013).
The ISO 27001 standard has been able to provide a complete form of security processes and controls for the organization (Wallhoff 2004). Referring to the capabilities of various information security standards shows that ISO 27001 is a leader compared to other standards, especially in the field of information security management systems; (Susanto, Almunawar, and Tuan 2011).
Intelligent information security audit systems
An expert system uses human knowledge to solve problems that normally require human intelligence. Expert systems are designed in such a way that they acquire the intelligence and information available in the minds of experts and provide this knowledge to other members of the organization with the aim of solving problems. The main components of an expert system are its knowledge base and inference engine. The knowledge base contains the necessary knowledge to understand, explain and solve the problem, and it is the inference engine of the brain of the expert system that determines its reasoning method (Tripathi 2011).
Research Question(s)
What are the control goals and evaluation criteria of the information security evaluation expert system?
What is the appropriate architecture of the expert system with coefficients to evaluate the organization's information security?
How are the goals and control security evaluation criteria determined?
How is the main security goal determined for each control?
What is the method of inference in the expert system of evaluating the organization's information security?
Does the designed system have the necessary credibility to measure the organization's information security?
Methodology
This research is applied-developmental in terms of purpose, because by using the ISO 27001 international standard and in order to improve and perfect the strategies, behaviors, methods, tools, devices, structures and patterns used by the organization. has designed the audit expert system. Also, the research is descriptive in terms of data and its strategy is design.
In order to create the knowledge base of this expert system, control goals, criteria for evaluating these goals and recommendations were extracted based on the ISO/ICE27001 standard, and the necessary information was collected to define the rules. Then, the approach of creating rules as well as the rules were confirmed through interviews with experts. The necessary information for ranking the control objectives and evaluation criteria of the control objectives was collected through a questionnaire and the weight of the control objectives and criteria was calculated using the Dematel technique along with the Dalala formula and WASPA method. In the next stage, the five main security objectives: authenticity, confidentiality, availability, accountability and auditability were chosen to continue the work due to their emphasis in the research literature. After determining which of the main security goals each control is aimed at, the specified goals were reviewed and confirmed during face-to-face interviews with experts. Then, using the information of these four stages, an expert system was designed to evaluate information security based on the ISO/ICE27001 standard. Visual Basic was used to implement the user interface and Excel 2016 was used for inference.
Discussion
In this research, the control objectives and information security evaluation criteria are extracted from the ISO 27001 standard, and the checklist used is completely in accordance with the standard, and the system has calculated the organization's information security score based on the standard. In addition, compared to previous researches, the presented system has special innovative aspects. The ranking of standard control goals and criteria has been done according to the opinion of experts, and the information security score has also been calculated by taking into account the weight of control goals and evaluation criteria. In addition, the main objectives of information security for each recommendation (control) have been determined according to the opinion of experts, and the designed system has also evaluated the degree of realization of the main security objective in the organization.
It is worth mentioning that the method of assigning points to each control is based on interviews with security auditors in Iran, and the structure of the ISO 27001 standard does not specify a specific method for scoring, which has an impact on the creation of rules and the efficiency of the expert system.
Results
The designed system is able to calculate the information security score according to the standard and also is able to calculate the information security score by applying the weight of the control objectives, the evaluation criteria of the control objectives and the percentage of realization of the main objectives of the information security. The resulted score is shown in three levels of critical status, average status and very good status to the user. Results of the system implementation in two Iranian organizations showed that the system with an average accuracy of 95% has the necessary accuracy and efficiency to evaluate information security.
Keywords:Information Security Management System, Expert System, ISO27001 International Standard, Dematel Technique, Dalala Formula, WASPAS Method
Research Paper
Data science, intelligence and future analysis
Abbas Bagherian Kasgari; Iman Raeesi Vanani; Maghsoud Amiri; Saeid Homayoun
Abstract
Most traditional fraud detection systems primarily focus on financial criteria to identify financial fraud, often overlooking the potential for fraudulent companies to engage in various types of non-financial misconduct. Recent studies have predominantly highlighted the significance of financial data ...
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Most traditional fraud detection systems primarily focus on financial criteria to identify financial fraud, often overlooking the potential for fraudulent companies to engage in various types of non-financial misconduct. Recent studies have predominantly highlighted the significance of financial data as the sole indicator of fraud, neglecting the exploration of non-financial or Environmental, Social, and Governance (ESG) metrics as supplementary predictors. This research aims to enhance fraud prediction by integrating financial and ESG data through sophisticated machine learning and deep learning models. It examines the effectiveness of supervised machine learning and deep learning algorithms in detecting financial fraud over a 10-year period ending in 1401. This study innovatively demonstrates that a hybrid model, which combines financial and non-financial criteria, yields superior predictive accuracy for financial fraud than models based solely on financial data. The results of this study, addressing the first research question, indicate that among various machine learning and deep learning algorithms, the classification or bagging algorithm demonstrated superior efficiency. Furthermore, in response to the second research question, it was found that the dataset encompassing all features—integrating both financial and non-financial data—outperformed those datasets limited to either financial or non-financial data alone. The research results indicated that the bagging machine learning algorithms act the best with combined feature set including financial and ESG metrics combined. The adoption of the proposed model significantly improves the accuracy and effectiveness of fraud detection systems.
Introduction
In an era marked by rapid advancements in data analytics and increasing corporate accountability, the detection of financial fraud has become a priority for stakeholders across the global business landscape. Traditional fraud detection systems have primarily focused on analyzing financial data, often at the expense of overlooking non-financial metrics that may equally signal fraudulent activities. This oversight is significant considering the growing evidence suggesting that non-financial indicators, particularly Environmental, Social, and Governance (ESG) metrics, can provide critical insights into the operational integrity of organizations.
Literature Review
Recent scholarly works and industry reports have highlighted a significant shift towards integrating ESG metrics with financial data to enhance the predictive accuracy of fraud detection systems. This integration reflects an expanded understanding of what constitutes corporate transparency and accountability, extending beyond mere financial disclosures to include broader sustainability and governance factors. Indeed, the integration of these diverse data sources promises a more holistic approach to fraud detection, aligning with contemporary demands for corporate responsibility and ethical business practices. The research presented in this paper builds on this foundation by employing advanced machine learning (ML) and deep learning (DL) algorithms to analyze a combination of financial and non-financial metrics. The study's innovative approach leverages a decade's worth of data from over 6000 public companies, utilizing a variety of ML and DL models to explore the efficacy of integrated datasets in predicting fraudulent activities more effectively than traditional methods. The findings aim to contribute not only to academic discourse but also to practical applications in corporate governance, offering valuable insights for regulators, investors, and policymakers committed to upholding the highest standards of corporate ethics and governance. By synthesizing complex data sets and applying sophisticated analytical techniques, this research underscores the potential of ML and DL models to revolutionize fraud detection, setting a new standard for both the scope and depth of fraud analysis.
Objective
The primary goal of this research is to improve financial fraud detection in public enterprises by integrating Environmental, Social, and Governance (ESG) metrics with traditional financial data, using machine learning (ML) and deep learning (DL) techniques. This approach addresses the limitations of traditional systems that focus mainly on financial indicators, often missing non-financial signs of fraud. This study rigorously tests various ML and DL models trained on ESG-enriched datasets against those using only financial data, exploring whether a holistic approach can enhance fraud predictiveness. The research aims to offer a broader view of company operations, in line with sustainable practices, potentially shifting how data science is applied in fraud detection. Ultimately, this study seeks to enrich discussions on integrating financial and non-financial data in fraud detection, influencing future corporate risk and governance strategies, and improving fraud prediction accuracy in line with emerging standards of corporate accountability and transparency.
Method
This study employs a sophisticated analytical approach using machine learning (ML) and deep learning (DL) to enhance financial fraud detection, leveraging a robust dataset that includes both traditional financial indicators and Environmental, Social, and Governance (ESG) metrics from over 6000 public companies worldwide. These metrics, sourced from reputable databases such as Thomson Reuters ASSET4, are crucial for advanced analyses. The methodology involves thorough data preprocessing, including handling missing values, normalizing data, and encoding categorical variables, with a focus on balancing the dataset using oversampling techniques to counter class imbalance and improve model generalization for detecting rare fraudulent cases.
The research rigorously evaluates various ML and DL models like Decision Trees, Naive Bayes, SVM, CNN, LSTM, and ensemble methods such as Bagging, Extra Trees, and Random Forests. The models are trained and tested on divided datasets to assess their effectiveness using metrics like accuracy, precision, recall, F1-score, and the Matthews Correlation Coefficient (MCC), with extensive validation techniques including cross-validation to ensure stability and prevent overfitting. The models' performance is compared with baseline models that use only financial data, highlighting the benefits of integrating ESG metrics for deeper insights and enhanced predictiveness in fraud detection.
Results
This study evaluates the integration of Environmental, Social, and Governance (ESG) metrics with traditional financial data in detecting financial fraud using various machine learning (ML) and deep learning (DL) algorithms. Results highlight the enhanced performance of fraud detection models when using combinations of financial and ESG metrics. Notably, the Extra Tree classifier and bagging algorithms excelled, particularly when analyzing balanced datasets that included both types of metrics. The use of oversampling techniques proved crucial in improving detection rates for rare fraudulent cases, thus balancing the dataset and reducing bias.
Models integrating both financial and ESG data consistently outperformed those using only one data type, enhancing accuracy, precision, recall, and F1 score. This underscores the value of a multidimensional approach in fraud detection. Advanced metrics like the Matthews Correlation Coefficient (MCC) and the Area Under the ROC Curve (AUC) provided a nuanced assessment of model performance, with higher MCC and AUC values indicating greater effectiveness in identifying fraudulent activities. The integration of ESG metrics was particularly effective in identifying potential fraud in companies that might appear financially sound but engage in unethical practices.
The findings recommend that companies, regulatory bodies, and technology developers adopt integrated approaches that encompass both financial and ESG data to improve fraud detection. Future research could focus on real-time data integration and more complex models like hybrid deep learning frameworks to further boost detection capabilities. The study demonstrates that using ESG metrics alongside financial data with advanced ML techniques significantly improves the accuracy and reliability of fraud detection systems, aligning with sustainable business practices and setting the stage for future innovations in fraud detection. This comprehensive approach not only yields superior performance but also enhances the model's capabilities, emphasizing the effectiveness of combining financial and non-financial data.
Conclusion
This research significantly advances the use of machine learning (ML) and deep learning (DL) in detecting financial fraud, highlighting the integration of Environmental, Social, and Governance (ESG) metrics with traditional financial data to enrich datasets and enhance model predictive power. Models trained on datasets combining financial and ESG metrics show superior performance in accuracy, precision, recall, and F1 score, improving anomaly detection and fraud prediction. The use of oversampling techniques addresses class imbalance issues, enhancing sensitivity to rare fraudulent cases and boosting the performance of ensemble methods like the Extra Tree classifier.
The findings highlight the critical role of ESG metrics in enhancing corporate governance and risk management, providing deeper insights into non-financial behaviors that indicate potential risks, which supports more informed decision-making and boosts transparency. Future research should investigate real-time fraud detection systems and the use of unsupervised and semi-supervised models to adapt to evolving fraud tactics. Practitioners are encouraged to adopt advanced machine learning (ML) and deep learning (DL) techniques, incorporating ESG metrics to improve fraud detection systems' accuracy and reliability, aligning with sustainable business practices and setting new standards in fraud detection technology.
Keywords: Fraud Detection Intelligent Systems, Deep Learning, Machine Learning, Financial Metrics, Non-Financial Metrics (ESG).
Research Paper
Data, information and knowledge management in the field of smart business
Ehsan allah Khoshkhoy Nilash; Mansour Esmaeilpour; Behrooz Bayat; Alireza Isfandyari Moghaddam; Erfan Hassannayebi
Abstract
Banks have complex and long-term processes for facilities, including many stages, control points and approvals. Continuous analysis of such processes is increasingly important for continuous improvement and gaining knowledge from them. The main goal of the present research is to provide a comprehensive ...
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Banks have complex and long-term processes for facilities, including many stages, control points and approvals. Continuous analysis of such processes is increasingly important for continuous improvement and gaining knowledge from them. The main goal of the present research is to provide a comprehensive methodological framework based on process mining and data mining regarding the analysis of fixed capital facility processes. The method used in the present research is derived from the techniques of process mining and data mining based on the event log of the facility system, an active bank in Iran. This method includes nine phases of initiation, preparation, inspection, exploration and analysis, evaluation, multi-dimensional analysis, prediction, review of results and improvement. Among the results of the present research is the extraction of the real process model, identification of bottlenecks, frequent activities in a case and all cases and process variant. In addition to this identification of branches and people with the most important roles and based on data features in reducing the time of payment of facilities, the analysis of the process from dimensions such as the province was one of the other findings. One of the initiatives of the present research was the use of data mining to predict the payment time of facilities. In the comparison of various methods, the decision tree algorithm had the best performance with 72% accuracy. In addition to identifying deviations, based on the creation of event log and its analysis, the improved process of extracting which showed a 67% improvement.
Introduction
Today's businesses benefit from a number of processes in order to earn more income and better services (Dakich et al., 2018). They are looking for processes that have better and more successful performance in order to achieve organizational goals and optimal use of resources in the operational environment (Van Der Aalst, 2016). Therefore, continuous analysis of processes for continuous improvement in organizations is very important.
Considering that the processes of providing facilities, especially fixed capital, are very effective in the creation and development of industrial, mineral and tourism units, having knowledge of them is of increasing importance. One of the efficient and effective methods for analyzing and improving business processes is process mining. With the help of its various concepts and techniques this method provides useful knowledge for the detailed examination of processes and how they are realized.
On the other hand, the efficient method of data mining, which provides the possibility of extracting knowledge from historical and predictive data (Basha, 2017), can be combined with the process mining method. With the investigations carried out, the methodological framework in order to provide process-centric and data-centric analysis, including the discovery of the real process model of facility payment, performance analysis of such processes, analysis of process varints, multi-dimensional process-centric analysis, payment time prediction, recommendations for improvement and process improvement based on event log simulation is not presented. Also, due to the novelty of the process mining method, the purpose of this research is to provide a comprehensive methodological framework using these techniques, concepts and tools of process mining in combination with data mining methods regarding the analysis of business processes with the study of fixed capital facilities processes.
Research Question(s)
How to provide a methodological framework for the analysis of fixed capital processes by using the techniques and concepts of process analysis and data mining methods?
Literature Review
In Table No. 1, a number of related studies are compared with each other.
Table 1. Summary of the research conducted
Research
Business
Components used
Event log
Miners
(Urrea-Contreras et al., 2017)
SME organizations
Event Log extraction, discovery, conformance checking, extend model, and return integrated model
software development system (JIRA)
inductive
(EL KODSSI & Sbai, 2024)
Smart environments
Data selection, data transformation, generation of event log, discovery, enhancement
Unstructured sensor generated data
MDA and machine learning
(Rashed et al., 2023)
hospital
Preprocessing, model discovery and analysis
Heart surgery unit in a hospital in Egypt
heuristic, inductive, ILP and ETM
(Erdogan & Tarhan, 2022)
Emergency
Determining goals, extracting event log, pre-processing, applying multi-perspective process mining, analysis, recommendation for improvement and evaluation of results.
Emergency system log
fuzzy
(Pan & Zhang, 2021)
Construction project
Event log generation and preparation, discovery and validation
Example of a construction project
Fuzzy and inductive
(Lorenz et al., 2021)
Production business
Mapping, analysis and improvement
Production business event log
fuzzy
(Augusto et al., 202)
Healthcare trends
Planning, data extraction, data processing and evaluation
Patients in Victoria, Australia
fuzzy
(Pang et al., 2021)
Acute care and treatment processes
Coding and categorizing activities, extracting and filtering event log, discovering and improving the process model and performance analysis
Stroke care process
IDHM miner, alpha, fuzzy and heuristic
(Ramos et al., 2021)
ERP configuration, intelligent agriculture and computer configuration
Extract configuration event log, control and clean data based on feature model, build data clusters and discover related workflow.
Greed, hierarchy and genetics
A number of studies are not comprehensive in using the concepts of data mining and process mining. Some of them lack features such as multidimensional process centric analysis, event log simulation for improvement, evaluation of results with field specialists and so on. Comparing the studies, each of these cases can be expressed as a research gap. It is also necessary to consider all the components and phases as a methodological framework as another research gap.
Methodology
The method used in the present research is based on the techniques, concepts and methods of the process mining in its manifest (Will van der Alast et al., 2011). In this research, the event log of the fixed capital facility system of one of the active banks in Iran has been used. The proposed framework includes nine phases of initialization, preparation, inspection, analysis, evaluation, process centric analysis, prediction, transfer results and finally improvement. Figure 1 depicts the mentioned methodological framework.
Figure 1. The mentioned methodological framework
Results
Process models were discovered based on alpha, alpha++, heuristic, genetic, fuzzy and inductive techniques. By comparing inductive and fuzzy model, fuzzy model is very effective due to less edge filter and coverage of all activities. Process bottlenecks, people and branches with the most important roles were identified.
The heuristic algorithm with a value of 0.833 had the best performance in the average values of the quality indicators of the process model. In Figure 2, the mentioned methods are compared.
Figure 2. Comparison of miners
Analyzing the impact of data features with a target throughput time of 271 days, according to the dimensions of the Civil Partnership Bases contract, Riyal Civil Partnership Contracts and SME customers had the greatest impact in reducing the process throughput time.
The J48 decision tree algorithm had the best performance with 72% accuracy compared to all the data mining methods used.
Figure 3. Results of data mining analysis with J48 algorithm
203 records were used to simulate new event data. The results of the analysis showed a 67% improvement.
Keywords: Fixed capital processes, methodological framework, event log, process mining, data mining.
Research Paper
Management approaches in the field of smart
maryam ahmadi; Mehran Ziaeian; Hajar Soleymanizadeh
Abstract
Nowadays, intelligence and industry 4.0 has been the focus of many industries due to its various benefits such as tracking raw materials and manufactured products, reducing costs, etc. One of the most important factors in facilitating the implementation of Industry 4.0 is human resources. The purpose ...
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Nowadays, intelligence and industry 4.0 has been the focus of many industries due to its various benefits such as tracking raw materials and manufactured products, reducing costs, etc. One of the most important factors in facilitating the implementation of Industry 4.0 is human resources. The purpose of this research is to investigate the role of human resources on the implementation of Industry 4.0 in the steel industry of Yazd. Using research literature, 13 factors related to human resources affecting the implementation of Industry 4.0 have been identified. In the following, by using the fuzzy Delphi approach and selecting 17 university professors and managers of Yazd steel industry by snowball sampling and asking for their opinions, three factors of continuous learning ability, data analysis and business intelligence, and security and privacy protection weren’t confirmed. Also, based on the request of the authors of the research from the related experts, by adding factors related to the implementation of Industry 4.0, three factors of freedom of action in doing work, sufficient time to do work, and innovation and creativity were introduced. Finally, the cause-and-effect relationships between the factors were investigated using the fuzzy DEMATEL approach. The results showed that cooperation and interaction are the most important factors for the implementation of Industry 4.0 in Yazd steel industry. Perceived usefulness and recruitment of skilled labor are known as the most effective factors, and innovation, creativity, learning, and empowerment are known as the most effective factors on the implementation of Industry 4.0.
Introduction
The steel industry is known as one of the vital and very important industries in the world and especially in Iran. Despite the importance of the steel industry in the country, this industry faces many challenges and problems such as the supply of resources and raw materials (Soltanzadeh, Rahmani, & Majidpour, 2024), high production costs and the increase in the price of raw materials (Morshedi, Nezafati, & Shokouhyar, 2023), lack of global standards in the quality of manufactured products (Pourmehdi, Paydar, Ghadimi, & Azadnia, 2022) and...
To answer these challenges, the country's steel industries, including the Yazd steel industry, seek to provide effective solutions for survival, entering global markets and surpassing competitors. One of the most accepted approaches among manufacturing companies in recent years to face the mentioned challenges is Industry 4.0. The use of Industry 4.0 technologies brings various advantages such as predicting errors, minimizing environmentally destructive activities, tracking raw materials and manufactured products, etc. Despite the benefits of Industry 4.0 and the increasing interest in it from researchers and managers of various industries, there are vague perceptions regarding the adoption and deployment of Industry 4.0 (Morovati Sharifabadi, Ziaeian, Mirfakhradini, & Zanjirchi, 2024). Many authors state that the implementation of Industry 4.0 is a difficult task and faces various problems and challenges, including scientific, technical, economic, social, human resources, and even political issues (Wankhede & Vinodh, 2021). Among the mentioned factors, one of the most important factors for establishing Industry 4.0 is human power (Ziaei Nafchi & Mohelská, 2021). The purpose of the current research is to investigate the role of human resources in the establishment of Industry 4.0 technologies and the intelligentization of Yazd steel industry.
Literature Review
The term Industry 4.0 was first introduced in November 2011 by the German government at the Hanover Trade Fair (Frank, Dalenogare, & Ayala, 2019). Industry 4.0 aims to connect the physical and digital worlds, decentralize business processes, intelligentize product production processes and provide services using advanced technologies such as the Internet of Things, blockchain, cyber-physical systems (Entezirian)., & Mehraeen, 2024) and ... in order to simplify production processes, monitor production at any place and time, increase productivity, efficiency and profitability (Javaid, Haleem, Singh, Suman, & Gonzalez, 2022) ). Saniuk et al. (2023) investigated the knowledge and skills of industrial and managerial employees for the implementation of Industry 4.0. The results of this research showed that employees' knowledge and skills, creativity and innovation, employees' resistance to changes are among the most important factors affecting the establishment of Industry 4.0 (Saniuk, Caganova, & Saniuk, 2023). In a study, Verma and Venkatsan (2022) investigated human resource factors for the successful implementation of Industry 4.0. The results of this research showed that training, recruitment, job design, performance evaluation and health and safety of employees are among the most important factors in the establishment of Industry 4.0.
Methodology
The present research is practical in terms of its purpose, because its results can be used in various industries and organizations to demand the establishment of Industry 4.0. Also, this research is descriptive-causal in terms of nature and method, and survey in terms of data collection. In this research, in order to identify the final influencing factors related to human resources on the establishment of Industry 4.0 technologies and the intelligentization of industries, the fuzzy Delphi approach has been used. In the following, in order to present the cause-and-effect relationship between the identified factors, the fuzzy DEMATEL approach has been used.
Results
In this research, by studying the literature, work motivation factors, work commitment, technical and engineering knowledge, cooperation and interaction, learning and empowerment, system thinking, continuous learning ability, data analysis and business intelligence, security and privacy protection, receiving salaries according to Activity, perceived usefulness and perceived ease were identified as factors related to human resources affecting the establishment of Industry 4.0. In order to verify the identified factors, university experts and Yazd steel industry managers were consulted using the fuzzy Delphi approach. Based on the results obtained from the fuzzy Delphi approach, three factors of continuous learning ability, data analysis and business intelligence, and security and privacy preservation were not confirmed due to the de-fuzzified value lower than the threshold (0.6). In addition, the three variables of freedom of action in the work, sufficient time to do the work and innovation and creativity were introduced by the experts and confirmed in the second stage of asking their opinions. Based on the results of the fuzzy DEMATEL approach and considering the highest value of R+J for cooperation and interaction, this factor was recognized as the most important factor related to human resources in the establishment of Industry 4.0 in Yazd steel industry.
Keywords: Fourth Industrial Revolution, Industry 4.0, Human Resource Management, Fuzzy Delphi, Fuzzy DEMATEL.
Research Paper
Management approaches in the field of smart
Pegah Ghasemi Ghonchehnazi; Ali Atashsooz
Abstract
Technology-based reforms with an emphasis on digital society (especially in the public sector) have been placed on the agenda of most countries and have become a major challenge for governments. One of the most important strategic tools of organizations in this field is "digital leadership". The main ...
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Technology-based reforms with an emphasis on digital society (especially in the public sector) have been placed on the agenda of most countries and have become a major challenge for governments. One of the most important strategic tools of organizations in this field is "digital leadership". The main purpose of the current research is to explain the role of digital leadership and its impact in creating digital transformation in Telecomunication Infrastracture Company. The statistical population of this research includes experts and senior experts of the studied organization, who were selected by a judgmental method. First, the dimensions and elements of digital transformation leadership were examined, and in order to examine the components of digital transformation leadership, as well as to set research questions and create a review protocol. The guiding principles of Xiao and Watson (2017) were used. Data collection was done through a questionnaire. Cronbach's test was used to measure the reliability of the questionnaire and Kendall's coefficient was used as an index of coordination and agreement. The results showed that the constructive dimensions of the concept of digital transformation leadership have a significant impact on creating digital transformation, and among them, Leader's digital expertise and giving importance to customer experience have the most impact.
Introduction
In the digital age, due to the emergence of new technologies and technologies, the traditional beliefs of business have fundamentally changed. Chaotic conditions caused by fundamental changes in the organization, uncertainty, lack of transparency of investment consequences and high cost of investment have prevented many organizations from entering this field (Osterrider et al., 2020). Organizations have undergone changes as one of the economic and social ecosystem elements. Therefore, in order to respond to these expectations, organizations must put fundamental changes in their agenda, which is the strategic tool of organizations in this field, "digital leadership" (Enak & Dharma, 2020). This research aims to identify the dimensions of digital transformation leadership and in order to better understand this iss Anak ue from a managerial point of view, to show the components of each factor in the form of the organization's digital transformation leadership framework.
Literature Review
Digital transformation is the application of new technologies in the three internal, external and overall dimensions of an organization. Three stages for digital transformation, which include the transition to digitalization, the digitization stage, and the digital transformation stage, are proposed, and each stage shapes specific requirements for digital resources, organizational structure, growth strategies, and performance standards (Verhoef et al., 2021).
Digital leadership includes two important dimensions of digital maturity, including what technology is (as digital capabilities) and how to lead change (as leadership capabilities). Digital capabilities include creating a pleasant digital experience for customers, improving internal processes and reinventing the business model, and leadership capabilities that include the ability to create a digital vision, engage all employees enthusiastically, focus on digital governance, and technology leadership capabilities (Westerman et al., 2014). Combining the three factors of vision, engagement and management creates a strong prescription for digital leadership. These three factors create synergy with each other and each reinforces the other over time. The fourth powerful leadership factor is technology. Four dimensions of digital transformation achievements and indicators that are evaluated in these dimensions in order to explain the role of digital leadership in the organization can be evaluated in the cases of business model (ecosystem), processes, customer experience and employee experience (Nadeem et al., 2018).
Muller et al. (2024) described the competencies that business leaders need to facilitate digital transformation. Based on a literature review, they identified four distinct sets of competencies that leaders need under different circumstances in a portfolio model labeled challenger, executive, organizer, and challenger. Yao et al. (2024) in research entitled the influence of digital leadership on digital transformation showed that digital leadership has a positive effect on digital transformation and digital strategic consensus plays a mediating role in this relationship. In research conducted by Tigre et al. (2023) based on bibliometrics and network analysis, they stated that few retrospective studies have been conducted in this field and this topic continues to attract more research because it has not yet entered its maturity stage. is in another study, Bonnet and Nandan (2021) believe that today's leaders are constantly facing new challenges so that they must adapt their organization and leadership style to the new environment. In addition, the key role of leaders in shaping the identity of the organization in the digital age and the need for forward-looking design and its active movement are felt today more than ever.
Methodology
A literature review and Delphi method were used in a mixed design. In order to identify the components of digital transformation leadership, as well as to set research questions and create a review protocol, Xiao and Watson (2017) guiding principles have been used. The eight-step systematic review process was implemented, leading to the execution phase. Ninety-two studies related to the research were selected, and conceptual elements were identified. Using Shannon’s entropy, the support from previous studies for the conceptual elements of digital transformation leadership and their importance were calculated. The synthesized findings were used in the initial framework, which informed the Delphi study. Quality assessment, as a screening factor for refining articles, employed the Okoli and Pawlowski method in the current research. Fourteen experts in digital transformation-related domains were selected for participation in the Delphi panel. The initial research framework was developed based on panel opinions, and Kendall’s coefficient was used to assess consensus. Questionnaires were prepared, and three rounds of question distribution were conducted, incorporating feedback to apply new indicators and remove redundant ones. Kendall’s coefficient determined the level of agreement among opinions.
Results
To analyze the data, the Delphi method was implemented in three rounds. The first round of Delphi questionnaire, which includes one section, was given to 14 panel members. Adopting digital technologies, focusing on the impact of digital technologies on customer behavior, strategic use of the organization's digital resources, new capabilities and competencies for leadership, the ability to establish governance in the digital age, analysis and having experience in management layers. Organization, technology leadership ability, etc. are among the results of the first round of the Delphi method.
In the second round, the final indicators of the research, which were designed in the form of a questionnaire, were sent to the experts for evaluation and a summary of the experts' opinions was reported. Kendall's coefficient in the second round is equal to 0.765, which shows the agreement of the experts on the indicators. At this stage, the questionnaire was sent again to the experts for preliminary approval. The third-round questionnaire also included two sections, the survey section and the effective factors section on digital leadership, and its results are shown in below table.
factors
Mean
Standard Err.
Kendall
Acceptance of digital technologies
4.79
0.58
31.32
Changing business models
4.43
0.51
22.39
….
…
…
…
Changing leadership paradigms in the digital arena
4.43
0.65
23.07
…
…
…
…
Focus on digital governance
4.71
0.61
30.40
Technology leadership
4.43
0.51
21.89
Kendall Coeff.
0.599
Discussion
The results showed that the constructive dimensions of the concept of digital transformation leadership include the adoption of digital technologies, changing business models, focusing on the impact of digital technologies on customer behavior, digital attitude and behavior, using digital technology to facilitate transformation and changes. Alignment between technology, process and employees, strategic use of the organization's digital resources, changing leadership paradigms in the digital arena, alignment of the organization with digital transformations, deep understanding of customers, ability to understand technology and business, new capabilities and competencies for leadership, management and supervision Digital transformation is the ability to establish governance dimensions in the digital age. Although the expansion of communication and technology can be a threat to some businesses.
Conclusion
It is clear that leading and keeping up with the digital age depends on the capacity and potential capabilities of organizations. Therefore, each of the indicators identified in this research can play an important role in creating digital transformation in the organization. According to the results of the research it is suggested to the organizations that in order to achieve the goals of digital transformation programs, they employ leaders and managers who have digital leadership abilities like what was identified in this research.
Keywords: digital leadership, digital transformation, digital maturity, digital governance
Research Paper
Management approaches in the field of smart
Mehrdad Mehrkam; zakieh nasimi
Abstract
Taxation is one of the vital aspects of development in countries and plays an essential role in advancing the economic progress of countries. For this reason, different countries of the world implement comprehensive plans to improve and transform their tax systems. This study was conducted ...
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Taxation is one of the vital aspects of development in countries and plays an essential role in advancing the economic progress of countries. For this reason, different countries of the world implement comprehensive plans to improve and transform their tax systems. This study was conducted with the aim of evaluating the leadership style of managers on digital transformation among senior and middle managers of the country's tax affairs organization.A random sample of 44 expert managers was selected. This study used Smart-PLS software for data analysis and was conducted in the summer of 1402. The findings of the study showed that the leadership style of the managers and the digital transformation strategy have an impact on the digital transformation of the tax organization. In other words, it was found that the digital transformation strategy significantly mediates the relationship between managers' leadership style and digital transformation, not a moderating role. In addition, the results showed that managers' leadership style and digital transformation strategy have the greatest impact on digital transformation. have The obtained findings have shown that the proposed hypotheses are acceptable.
Introduction
In today's global landscape, digital transformation is paramount for organizational success. Even government bodies are revamping their tax systems to adapt to evolving environments. However, challenges like skill shortages and resource constraints impede progress. Nonetheless, integrating digital transformation technologies offers numerous benefits, such as enhanced transparency and innovation. Failing to keep up with technological advancements can lead to organizational obsolescence. Thus, thriving in competitive markets requires adeptness in digital transformation, innovation, and emerging technologies, supported by robust implementation strategies.
Literature Review
Digital transformation, as a managerial strategy, revolutionizes organizational operations and processes through the integration of digital technologies. These changes encompass the overhaul of products, business procedures, sales avenues, value chains, and business models. Beyond internal and external organizational shifts, digital transformation extends to establishing a distinct market presence both presently and in the future. Embracing this transformation necessitates the organization's agility in adopting new technologies and implementing comprehensive measures. However, digital transformation initiatives must transcend mere technological integration and instead prioritize process re-engineering and alignment among technology, processes, and personnel. Effective leadership and adept change management capabilities are also crucial components in this transformative journey.
2-1- The relationship between digital transformation and the leadership style of managers:
Digital transformation, as an organizational shift towards digital institutional frameworks, hinges on the legitimacy of the organization's belief system. Managers are pivotal in driving the success of this transformation; through strategic programs and effective leadership, they steer organizations toward digital evolution. The leadership style adopted by managers holds significant sway in this process, with studies indicating that a transformational leadership approach yields positive impacts on both organizational innovation and performance. Consequently, the text proposes a hypothesis asserting that managers' leadership style exerts a positive and noteworthy influence on digital transformation.
2-2- The relationship between digital transformation and digital transformation strategy:
Amidst the era of digital transformation, the significance of a well-crafted strategy for managing institutional change is underscored. Digital transformation is characterized as a dynamic and ongoing process necessitating a thorough reassessment of operations, strategy, leadership capabilities, innovation, and business models. In this context, the formulation of a digital strategy, encompassing both corporate and business strategies, emerges as a primary driver of success in digital transformation endeavors. Consequently, a hypothesis is posited, asserting that the digital transformation strategy exerts a positive and substantial impact on digital transformation outcomes.
2-3- The relationship between managers' leadership style and digital transformation strategy:
This text emphasizes the crucial role of the Chief Digital Officer (CDO) in operationalizing digital strategy and ensuring its alignment with the company's mission and goals. Ineffective implementation of digital strategy by senior managers and employees hinders reaping benefits from digital transformation. Successful utilization of digital transformation requires organizations to develop robust digital strategies and drive digital transformation efforts under senior executives' leadership. The text presents a hypothesis asserting that managers' leadership style significantly and positively affects digital transformation strategy.
2-4- Digital transformation strategy mediation:
The text highlights the significance of a well-designed and efficiently executed digital transformation strategy in guiding organizational digital transformations. Additionally, it proposes a hypothesis suggesting that the digital transformation strategy serves as a mediator in the relationship between managers' leadership style and the organization's digital transformation.
2-5- Moderation of digital transformation strategy:
The text defines digital strategy as a series of strategic IT and information systems actions directed by managerial decisions regarding the utilization of current infrastructure. It suggests that even if managers excel in handling risk and uncertainty, if their actions don't align with existing strategies, digital transformation might not yield desired outcomes. Consequently, the text hypothesizes that the digital transformation strategy moderates the relationship between managers' leadership style and the organization's digital transformation.
Methodology
Type of Research: This research is applied and descriptive-survey in nature, aimed at examining the relationship between managers' leadership style and digital transformation.
Population and Sample: The statistical population includes 50 middle and senior managers of the country's tax affairs organization. Based on Morgan's table, 44 managers with sufficient knowledge of digital transformation processes were selected as the sample. Simple random sampling was used to select the managers.
Data Collection Tools: Data were collected through semi-structured interviews and questionnaires. The interviews aimed to identify the managers' level of knowledge about digital transformation and the existing challenges. The questionnaires included both closed and open-ended questions and assessed various aspects of leadership style and digital transformation strategy.
Findings: The results indicated that the level of familiarity of managers with digital transformation concepts varies, and this difference depends on factors such as work experience and managerial role.
Data Analysis Method: For data analysis, structural equation modeling using Partial Least Squares (PLS) was employed. This method includes two models: the measurement model (examining the relationship between observable and latent variables) and the structural model (investigating the relationships among latent variables).
Results
This study emphasizes the dual nature of digital transformation, presenting both challenges and opportunities for organizations, including government bodies like tax authorities. The implementation of the taxpayer system serves as a successful example of digitalizing tax processes, demonstrating how technology can improve efficiency and transparency while minimizing redundancy. The role of managers in driving digitalization is crucial, requiring adept leadership and strategic approaches. Furthermore, the study highlights the digital transformation strategy's pivotal role as a mediator between managers' leadership style and organizational digital transformation. However, the finding that the strategy does not moderate this relationship suggests a nuanced perspective influenced by research context and environmental factors. Overall, the text underscores the importance of digital transformation for organizational success, advocating for strategic planning, effective leadership, and prudent technological adoption.
Figure 1. Conceptual model
H3
H4
H1
H2
Leadership style of managers
Digital transformation
Digital transformation strategy
5.conclsion
According to the statistical results, one of the factors that influence the digital transformation is the leadership style of managers. Organizational managers directly influence digital transformation; Therefore, managers should provide the necessary platform for moving towards digitalization for the employees and the organization so that the organization can move in this direction.
As the statistical results showed, digital transformation strategy has an impact on digital transformation. When organizations are going to move towards digitalization, they must abandon their traditional processes and change them to modern ones; Therefore, in order to do this correctly, the strategy of the organization needs to be changed and designed according to the new goals of the organization, which is digitization, so that the organization can move in the right direction. In the absence of a suitable strategy, the organization will deviate from its path and digitization will not happen.
Finally, we used a cross-sectional research design while the discussion of digital transformation and digitalization happens over time; Therefore, it is suggested to use a time study to examine the growth of digital transformation implementation and capture the lessons learned over time.
Keywords: Managers' Leadership Style, Digital Transformation, Digital Transformation Strategy, Tax Affairs Organization.
