فهرست مطالب محمد اقدسی

Process mining connects the disciplines of data mining and machine learning to business process management techniques. A business process is a series of independent and interdependent activities that transform inputs (data, materials, etc.) using one or more resources (such as time, employees, and money). It utilizes the necessary outputs. It is possible to examine the actual behavior of organizations, including the performance of individuals, departments, and resources, using process analysis techniques. The results of the process analysis, which typically includes the organization's business process models, can be compared to the organization's documents and requirements. Thus, processes will be able to be compared, reviewed, monitored, and enhanced. Process mining methods operate based on event logs stored in information systems. Using process mining without high-quality input data will not result in accurate conclusions about an organization's business processes. In recent years, researchers have focused on the evaluation and enhancement of the quality of input data using process mining techniques. The objective of this study is to identify and categorize the most significant data quality issues, as well as recognize the approaches proposed to address this challenge in process mining.

This research employs a systematic review with the intent of analyzing all valid evidence in order to answer the research questions. This study investigates 102 academic studies published between 2007 and 2021, including conference papers, journal articles, and theses. Towards this end, a systematic three-part research methodology was employed. In the first section, which included the research definition, the research field was defined first, followed by the research objectives and queries. In the concluding step of this section, the research's scope is defined. In the second section, the research methodology and entry criteria for the studies discovered during the search for scientific resources are defined. Finally, the identified studies are evaluated in terms of their citations and classified. In the third section, which is devoted to the evaluation of the research, the concluding research of the study is conducted, and then, based on the investigation of the preceding studies, the findings and conclusions are determined. Important data and evidence were extracted from the collated research, allowing for the creation of the necessary tables and graphs.

In recent years, researchers have paid more attention to data quality challenges in the process mining, according to the findings of recent research. In 2019 and 2020, the greatest number of studies will have been published. It was also discovered that the majority of articles were published in three scientific databases, namely Springer, IEEE, and Elsevier. 51% of the studies examined were presented at prestigious conferences. 36% of the studies were published in prestigious scientific journals, while the remaining 13% were represented in dissertations and university reports. The study of the selected articles revealed that 20 data quality issues that can arise in the input data have been investigated in the literature. These challenges have been categorized into five levels: trace, event, case, activity, and timestamps, and four foundational approaches have been identified that have been used to evaluate and resolve data quality challenges in the mining process. 1) data quality frameworks 2) preprocessing 3) anomaly detection 4) repair. Our findings indicate that preprocessing techniques that seek to remove chaotic and infrequent behaviors from the event log have received more attention than other techniques. In addition, these results demonstrate that, in recent years, the discovery of anomalies and the reconstruction of missing events have become popular research topics within the field of process mining. Examining studies related to the field of data quality in the data mining process reveals an abundance of approaches and methods for addressing data quality challenges. Investigations revealed that the use of colorful Petri nets as a mathematical method has been considered in all selected research projects.

The data needed for process mining methods can be obtained from various sources. One of the major advantages of process mining is that it is not limited to a specific type of system. Any workflow-based system, such as ticketing, resource management, databases, data warehouses, legacy systems, and even manually collected data, can be analyzed as long as it can be separated using case ID, activity, and timestamp attributes. In real-world scenarios, most data is not collected for process mining purposes or is unsuitable for use in process mining analyses. Especially data that is recorded manually or scattered among various isolated systems can contain errors. Despite the efforts made to improve the quality of input data in the mining process, it is still necessary to develop efficient frameworks and methods to identify, evaluate, and address data quality challenges in real business processes, which are often characterized by high volume and complexity. The results of this research can offer a fresh perspective for researchers, data science specialists, and business analysts.

Organizational structures are purposefully crafted around the strategic objectives of companies, incorporating well-defined processes that serve as the foundation for employee activities and communication. The processes and activities of organizations and companies are implemented through organizational roles and positions that are assigned to employees based on the structure and goals. However, the crucial question lies in how effectively official structures can address people's communication needs and facilitate the implementation of activities. Within numerous organizations, an informal structure emerges in parallel to the official hierarchy, leading to the execution of various activities based on the relationships established within this informal framework. Because of various reasons, employees in some organizations are forced to carry out organizational processes through informal communication and in temporary work teams. The presence of an informal structure in numerous organizations is an unavoidable phenomenon. However, the primary concern lies in effectively monitoring and appropriately managing this structure and the relationships that arise from it. This study mainly seeks to measure the degree of similarity and difference between the formal and informal structures of the organization.

In the present study, the official structures were extracted based on the organizational chart. The informal structures were based on data logs and information from different sources and bases. Reports of events taking place via the work interactions of people in the process of supplier selection in a project-oriented company were collected in one of the complex construction projects. The gathered data was used as an informal network using the social network analysis method. The degree of similarity and difference between the formal and informal structure of the company was measured through social network criteria and the Rand index.

Based on the information obtained, the informal working groups or communities resulting from the real interactions of people were identified and analyzed. Also, these communities were compared with departments and formal units based on the hierarchical structure of the organization. In addition, by using the Rand index, the similarity of these two structures was estimated to stand at 0.76%. This method can be a basis for comparing the official structure and the real structure of companies. The ideal degree of similarity or difference between the two structures varies depending on the nature, culture, and mission of each company.

Using this method and identifying and analyzing the causes of the differences between these two groups of communication structures can help organizations improve their structures, make them more agile, and compensate for some structural deficiencies. By using this way of analyzing and comparing the results in these two groups, it is possible to examine the organizational structure, strengthen effective working groups and teams, support effective communication, and even prevent weak communication.

Correct and timely decisions have a significant impact on the performance and achievement of the company's goals. In other words, business process management depends on making and implementing rational decisions. By increasing the integration of information systems in organizations and using tools such as process mining, a platform is provided for the use of data analysis approaches and better analysis of decisions, and managers can act in agile decision making. Selecting a supplier in the process of purchasing in complex projects is one of the basic and key decisions that affect the quality, cost and performance of the project. In this article, with a process perspective, the decision points in the purchasing process in a complex construction project in an EPC company have been discovered and the key players in the implementation of the process have been identified and analyzed through social network analysis. The results of this research have led to the investigation of decision points in the process, the performance of decision points and the identification of key people in decision making, which can be used to improve the company's future performance.

In today's challenging world, organizational growth is not possible without the efficient use of data. Process mining uses machine learning methods and business process management concepts to extract hidden knowledge about business processes from data stored in information systems. Process Discovery is the first step in process mining. The main goal of process discovery is to transform the event log into a process model. However, using process discovery methods will not be possible without appropriate data because any analysis based on low-quality data will lead to poor insights and bad decisions that will negatively affect the performance of the organization or business. This paper aims to provide a new conceptual framework for preprocessing data input into process discovery methods to improve the quality of the extracted model. The proposed conceptual framework has been developed using a qualitative research process based on grounded theory. For this purpose, 102 articles related to the domain of data quality in process mining were reviewed, and the most critical challenges of data quality in this field have been identified after filtering and integrating them from the literature, including: Are "noisy/infrequent events," "outlier events," "anomalous events," "missing values," "incorrect time format," "ambiguous timestamps," "synonymous activities" and "size and complexity." Then, the basic steps for data preprocessing and cleaning tasks are defined, which include the activities of "repair," "anomaly detection," "filtering," and "dimensional reduction." The final preprocessing framework then builds on data quality issues and identified activities. Four standardized datasets derived from real-world processes were used to assess the proposed framework's performance. Firstly, these data are raw, and secondly, four standard process discovery algorithms are applied after preprocessing by the introduced framework. The results showed that the preprocessing of the input data leads to the improvement of the model quality criteria extracted from the process discovery algorithms. Furthermore, to evaluate the validity of the proposed framework, its performance was compared with three preprocessing methods"sampling," "statistical preprocessing," and "prototype selection," which the results indicate better efficiency of the proposed approach. The results of this study can be used as guidelines by data and business analysts to identify and resolve data quality problems in process mining projects.

Knowledge problems in business processes refer to those problems result from the lack of proper implementation of knowledge management processes, such as creation, deployment, sharing and storage. The existence of knowledge problems during process execution will lead to a deviation in the process path. Identifying and detecting these deviations requires a precise tool that can detect the actual process from event logs. process mining is a new smart approach that examines business processes from different aspects, using data mining techniques, social network analysis, and some of its own techniques. In this study, by selecting a contact center of Water and Wastewater Organization have compared the design process and the extracted process resulting from the discovery phase of the process mining, which has led to the identification of the deviations in the process pathway and the bottlenecks in the process. For this purpose, the three months data were gathered and after the preprocessing, each of the three views of the process, organization and case was implemented on the data. The results of the research indicate that there is a lack of conformity of the process in some cases with the main process and the presence of key people in the center.

In the banking industry, a variety of activities have been introduced as social banking. The purpose of this paper is to provide a comprehensive overview of social banking and identify the various approaches used in the area. The banking value chain model has been used to describe different approaches to social banking. This paper starts with a literature studying the various trends that have led to the formation of the concept of social banking, in the literature review section. In continue, social banking approaches are identified. Triangulation is used to ensure the validity of the research method; therefore, two different methods have been used to identify social banking approaches. In the first method, the grounded theory research method was used. In this process, the data obtained from the literature used, as well as conducting semi-structured interviews with subject matter experts in four different Iranian banks. In the second method, the clustering method was used and 49 global social banking experiences were clustered in terms of the type of impact on the value chain. The results of both methods led to the identification of four different approaches to social banking. Finally, these four approaches are described and it is specified how each of them affects each part of the bank’s value chain.

This paper examines the effects of technological variables, including top management support for technology, on the development of technological skills, technological distinctive competencies and organizational learning. It also examines the effects of technological distinctive competencies and organizational learning on organizational innovation. How these variables affect organizational performance. This study was conducted using a descriptive-survey research method with a sample of 30 banks approved by the Central Bank of Iran using a questionnaire and through structural equation method. The results of the research show that: (1) top management support has a positive impact on the development of technology skills, technological distinctive competencies, and organizational learning. (2) Technological distinctive competencies and organizational learning, directly or indirectly through organizational innovation, have a positive impact on organizational performance. It was also confirmed that innovation has a positive impact on organizational performance. Research also has recommendations for business professionals that the creation of merit is complex and a long-term process that should be pursued with the long-term strategy of the company. Therefore, the involvement of management through the design of an entrepreneurial strategy is also a major issue.

Employee value is a basic concept of human resource and more important in measuring. Measuring method for employee value introduced qualitatively till now. So that, consider component for employee value and achieved based on analysis. In literature there aren`t integrated component and any questionnaire for measuring, but could be compared the result based for fieldwork. Field researchers problems are that change the result by changing the sample and take time. In this paper we try to present the mathematical formula to calculate the trend of Employee value. Presented formula EVRFM composed of year of employment, last promotion year in EVR and number of promotion in EVF and percent of annual salary increased in EVM. To evaluate the formula data ware gathered from private insurance company in Tehran and calculating the employee value with EVRFM. Of the population 384 were gathered. Questioners evaluated employee value with 3components, attraction, satisfaction and loyalty. The result from EVRFM and analysis of questioners are as the same trend for evaluating the employee value. Thus EVRFM could be used for trend of employee value.

Project’s is considered a convenient space for learning, due to the temporary nature of the projects, this learning does not become institutionalized in project-based organizations (PBOs). Certain models have already been presented in the area of operational organizations in order to form the concept of a learning organization (LO), but these models cannot be used to integrate the learning concept into this type of organizations. By literature review of learning in project-based organization and by identifying 4 subjects of this field a primary model for PBLO is developed. This study examines the efficiency of a primary model of PBLO by conducting a qualitative research on two PBOs in the oil and gas industries. It then revises the model accordingly to present the final model. The data was collected from interviews with 20 individuals in the PBOs. A total of 615 statements made by interviewees were coded and summarized as concepts of the model. Since the qualitative approach to LOs has been neglected and no study has addressed the issue of PBLOs, this research presents an innovative study.

Studies in the field of learning and organization have changed through formation of the concept of a learning organization. As a result various models have been developed and customized for project based organizations. Still, they have not yet been customized for Project Based Organizations, as a very important category of organizations with growing importance. The special requirements of project based organizations in learning demands the development of a special model for project based learning organizations (PBLOs). This is routed in the temporary nature of projects. This study aims to develop a paradigmatic model for PBLOs based on case studies in two project based organizations of oil and gas industries. The strategy of the study is structured grounded theory and the data are acquired from interviewing 20 participants in the field of project and knowledge management. As a result of the interviews and by analysis and coding of 715 obtained phrases, 25 basic concepts were identified which have been placed in the paradigmatic model. Since a qualitative approach towards organizational learning has been very limited up till now, and in addition no studies have yet addressed PBLOs in particular, this work could be treated as a pioneering study in the field.

This paper aimed to examine the relationship between concept of CLV and organizational values. The new integrated CLV concept has four dimensions: base, future, network and learning. The organizational values include employees’ value, shareholders’ value and customers’ value, and each value is individually measured based on three components of attraction, satisfaction and loyalty. The presented conceptual model includes 13 variables and is formed based on the relationship between integrated CLV concept and each of those organizational values. Then, the model was evaluated compared to a functional sample. Insurance branches in Tehran were selected as our Statistical Society and 1536 questionnaires were collected.. SPSS software was used for analysis of all the relationships. The results showed that there is a significantly positive relationship between new CLV concept and each of those three organizational values, so that any increase or decrease in the values has its own positive direct impact on the new CLV concept

In this research knowledge management has been studied as an interdisciplinary area. We aim to find an answer for this question that "what are the scientific structure and knowledge map of knowledge management projects regarding these two aspect of subject areas and keywords. For this purpose, nearly 40000 scientific documents including knowledge management as one of their keywords were selected from Scopus database and were studied in various subject areas. In this research,bar charts have been drawn for each index of subject areas and keywords. Besides, using Co-occurrence matrix, adjacency graphs were drawn and then clustered using Average-Link algorithm. Bar charts and graphs were drawn using R and Excel software. The results of this research showed that among the researches on knowledge management in the world, the most relevant scientific fields to knowledge management are Computer Sciences with 32.5%, Business, Management and Accounting with 14.5%, Engineering with 13.7%, Decisive Sciences with 12.6%, Mathematics with 7.07%, and Social Sciences with 6.63%, respectively. The most keywords collocate with knowledge management in the world are Human-Computer Interaction, Information Management, Systems Management, Information Technology, Manufacturing, Acquisition of Knowledge, Semantics, Knowledge Transfer, Ontology and Information Retrieval.

Promoting people to use bus transport services leads to decrease using private cars and therefore decrease heavy traffic jam and airpolution. Promoting people to use the services needs to provide better services with lower cost. To achieve the goal, private operators must find innovative ways to provide the services. Providing the innovative services is not possible, unless the operators have freedom to make decision about tactical level decision (determining ticket rate and type, routes, vehicle type and timetables) besides operational level decisions. In other words, they design and operate the services themseleves. Operator freedom leads to emerge challenges like lack of route integration that create the problems and decrease popularity of bus services. In this paper, the challenges are collected by using published case study reports of various cities and conducting semi structural interviews with bus transport experts. The root causes of them are found by more investigations in the literature and interviews.
The results of the paper show that transfering the tactical level decisions to private operators successfully, transport authority as well as private operators should have some capabilities like, ability to control and monitoring and integrated information system. These capabilities are defined by using published case study reports and conducting interviews. Transaction between operators and transport authorities should be also simple and have an ability to codify into standards and codes simply. The definition of capabilities helps transport authorities to evaluate the required capability of the private operators and themselves to prevent the challenges before starting to transfer tactical level decisions to private operators.

This paper aims to identify and assess information behavior among researchers in Iranian universities and higher education, along with to present a measurement framework and its practical application.
this research with the goal of identification and presentation a framework that have 4 elements such as “team work, methodology, innovation and information up-to-date” was developed for measuring researchers’ information behavior at Iranian universities and To this end a questionnaire was used to practically assessing at 8 valid Iranian universities. In this study applied survey, 332 questionnaires were collected using random sampling available and were analyzed using SPSS software.
Findings: The results show that team work was low level, information up-to-date was intermediate; innovation and methodology were a little upper intermediate. So, the results showed a correlation between the elements of information behavior while increases in the size of the each element lead to reinforce each other elements. Also, disciplines were differentiated through information behavior.
Originality: The paper presents a framework for identification of researchers’ information behavior in 8 universities in Tehran and existing gaps in studied universities was recognized and delivered solutions.

Security is one of the main pillars of development in societies that is entrusted an important part of the mission to the police. One of the strategies of security development, in order to prevent and detection of crime. Is Identify crime patterns. Crime is social disorder that communities pay a huge cost for it in different ways. To identify patterns of crime and detection of crime, use different tools in the field of knowledge management and information technology. The purpose of this study, designing knowledge management system based on case-based reasoning that according to past experience a) Explain the coordinates of the new criminal cases and; b) according to the coordinates of the new case, extraction methods that have been used in the past to solve the problem; c) According to the new case, prioritize the problem-solving methods and offer to officers and d) If possible, by combining some previous experience, offer to the police the optimal methods for solving new case.In this study, design environment to support cleverly the knowledge of the police in detecting crime with propose appropriate solutions which will help the officers who are involved in the process of detecting crime.

Today companies and organizations have considered social responsibility and related standards very important for gaining competitive advantages. ISO 26000 in social responsibility is on the top. Regarding police close contact with society and the responsibility of this huge organization towards people, the role and the significance of police in stablishing security and order in society are undeniable. Therefore in this article the relevance of productivity indicators on organization performance from social responsibility point of view is studied. For this matter, first each of social responsibility and productivity concepts individually for police was studied then dimensions and criteria of each concept extracted and finally an inductive framework for explanation of these two effective factors on each other was introduced. Therefore for productivity 22 indicators and for social responsibility 15 indicators from articles, books and police organization reports were extracted. This article is both descriptive and exploratory. In descriptive study the effective concepts and indicators on productivity and social responsibility were extracted individually. Exploratory study deals with the relation between concepts and indicators in two domains of productivity and social responsibility which are taken from literatures review and individually these concepts for police organization are studied.

One of the most important problems of the designs proposed by traditional economic-statistical approaches of control charts is inefficiency in the face of uncertainty. Uncertainty in the parameters of economic-statistical models may lead to failure in rapidly detecting changes in processes and impose greater costs to the organization. Monitoring the machining process in an automotive industry explains the necessity of considering the robust approach to the control charts. This research intends the control charts design for monitoring process quality characteristics in conditions of uncertainty in cost and process parameters. The robust design ensures that the proposed control chart alarms the process changes earlier than the time set by the user, despite the uncertainty in model parameters. The resulted robust optimal solutions not only ensure the efficiency of solutions in any realization of parameters, but also facilitate the practical implementation of control charts and reduce organization costs through improving the quality of process outgoings.

Production planning is one of the most important challenges in steel industry. Order planning is one major part of this aspect according to the fact that production is usually planned based on customer orders in this industry. Inventory planning is also vital for maximizing capacity utilization. The proposed model in this paper is capable of selecting order، assigning finish time of each order، and determining open orders in each process by considering order planning and inventory planning simultaneously. The model could have a key role in improving production planning of steel companies by on time delivering of the orders، reducing work-in-process، and balancing utility of capacities. Finally، a heuristic algorithm based on genetic algorithm is proposed and its efficiency evaluated in an empirical case study of Iran alloy steel enterprise.

This article discusses the use of Value Stream Mapping (VSM) in a make-to-order production environment. According to this tool، a practical study carried out about the way of implementation of lean manufacturing in a commercial printing company in an action research basis. The aim of using VSM as a drawing tool of current value stream is to investigate the ways of process improvement and reducing waste. In this study، after mapping the current state value stream for making waste measurement، a detailed root-cause analysis was carried out and various improvement proposals has been identified based on the principles of lean manufacturing especially the continuous flow and low level of work in process and final goods inventory. Because of the importance of waste measurement in different phases of lean implementation in commercial printing companies as low volume high mix production environments، a dedicated deficiency measure was developed.

One of the main problems in dynamic customer segmentation is finding the dominant patterns of customer movements between different segments via time. Accordingly، we concentrate on the customer dynamics in this paper and try to find different groups of customers in transmissions between segments via time. The dominant characteristics of these groups are also investigated. To obtain this objective، a new hybrid technique based on the K-means algorithm، hierarchical clustering and association rule mining is presented and implemented on the data of one of the main telecommunication corporations in Iran. The results show that there are seven different groups of customers. Furthermore، the impact of customer dynamics on segments’ changes via time is investigated. In this regard، a new approach of categorizing customers is proposed according to their impact on the structure and the content of segments’ changes. These new groups include “the customers who preserve the structure”، “the ones who are consistent with the structure” and “the customers who destroy the structure”.

Dynamic business environment enforces organizations to constantly update and reform their own strategic expectations. Changing the embedded business rules in information systems is vital to fulfill strategic expectation. Determining appropriate position to change business rule in information systems is regarded as a time-consuming and complex activity. Therefore, it is necessary to identify and modify effective rules to achieve the strategic expectations. In this paper, a practical model is used to identify the most effective rules in information systems. In this model, first, critical business attributes which fit to strategic expectations are taken into account. These are the attributes which their changes are more important than others in achieving the strategic expectations. To identify these attributes we utilize rough set theory. Those business rules which use critical information attribute in their structures are identified as the most effective business rules. The Proposed model helps information system developers to identify scope of effective business rules. It causes a decrease in time and cost of information system maintenance. Also it helps business analyst to focus on managing critical business attributes in order to achieve a specific goal.

During implementation of Business Process Reengineering (BPR) in many organizations, it will be less attention to previous activities and capabilities which they extract from other improvement projects in the past and this would include the costs for doing this effort and activities. Considering these issues are important for BPR projects. Required capabilities before implementing of BPR projects have been introduced for achieving success. The literature has suggested required resources for BPR and various approaches to assessing readiness and implementation of BPR projects. Therefore in this research, a practical measurement tool for required capabilities is proposed to enhance the chances for successful implementation of BPR by mapping these capabilities on preparation step of BPR projects. In addition, the relations between these capabilities created organizational capabilities from quality management systems (COC-QMs) are identified. In conclusion, this research has examined and established two types of operational and special capabilities related to preparation step of BPR and QMS projects, in addition to exploring and describing the relationship between these two types of capabilities using the concepts of building capabilities. The results show that every organization should measure the capabilities such as “Planning and monitoring of business plans”, “People’s abilities in recognizing and understanding customers and stakeholders needs”, “Transferring of managerial and working experiences and knowledge”, “Team working”, “Managers’ involvement in organization’s changing process”, and “Loyalty to total organizational growth within managers and people” prior to implementing BPR. Considering the results of this research, the affect of COC-QMs on DOCs as BPR enablers has been proposed as a conceptual model.

Business Process Reengineering (BPR) is one of the concepts, which consider process orientated view and promises significance successes. Since this concept is multidisciplinary, success in this endeavour requires considering different factors. However, a number of studies have been conducted to identify these factors; specific conditions of Iranian organization raise the need of studying the success factors in Iranian organizations with considering holistic view and their indications. In this paper, case study method has been used for studying different projects in Iran and then data has been analyzed by Content Analysis in order to extract the success factors in Iranian organizations and their phenomenon. Finding of this research can be considered for customization of the holistic framework and also can be useful for stakeholders involved in BPR initiatives, in adequately planning the initiative and checking the progress during the implementation.

T‌h‌e m‌o‌s‌t i‌m‌p‌o‌r‌t‌a‌n‌t s‌u‌c‌c‌e‌s‌s f‌a‌c‌t‌o‌r f‌o‌r i‌m‌p‌l‌e‌m‌e‌n‌t‌i‌n‌g t‌h‌e e‌n‌t‌e‌r‌p‌r‌i‌s‌e r‌e‌s‌o‌u‌r‌c‌e p‌l‌a‌n‌n‌i‌n‌g p‌r‌o‌j‌e‌c‌t‌s i‌s t‌o b‌e p‌r‌e‌p‌a‌r‌e‌d t‌o a‌c‌c‌e‌p‌t t‌h‌e c‌h‌a‌n‌g‌e a‌n‌d e‌v‌o‌l‌u‌t‌i‌o‌n. O‌n t‌h‌e o‌t‌h‌e‌r h‌a‌n‌d, o‌n‌e o‌f t‌h‌e m‌a‌j‌o‌r r‌e‌s‌u‌l‌t‌s t‌h‌a‌t o‌r‌g‌a‌n‌i‌z‌a‌t‌i‌o‌n‌s e‌n‌c‌o‌u‌n‌t‌e‌r i‌n t‌h‌e‌s‌e k‌i‌n‌d‌s o‌f c‌h‌a‌n‌g‌i‌n‌g p‌r‌o‌j‌e‌c‌t‌s i‌s r‌e‌s‌i‌s‌t‌a‌n‌c‌e t‌o c‌h‌a‌n‌g‌e. I‌n t‌h‌i‌s r‌e‌s‌e‌a‌r‌c‌h, T‌h‌i‌n‌k‌i‌n‌g P‌r‌o‌c‌e‌s‌s i‌s c‌o‌n‌s‌i‌d‌e‌r‌e‌d a s‌y‌s‌t‌e‌m‌a‌t‌i‌c m‌e‌t‌h‌o‌d f‌o‌r d‌e‌t‌e‌r‌m‌i‌n‌i‌n‌g r‌e‌s‌i‌s‌t‌a‌n‌c‌e t‌o c‌h‌a‌n‌g‌e i‌n E‌R‌P p‌r‌o‌j‌e‌c‌t. R‌e‌s‌e‌a‌r‌c‌h m‌e‌t‌h‌o‌d i‌s q‌u‌a‌l‌i‌t‌a‌t‌i‌v‌e c‌a‌s‌e s‌t‌u‌d‌y i‌n E‌s‌f‌a‌h‌a‌n S‌t‌e‌e‌l C‌o‌m‌p‌a‌n‌y a‌n‌d s‌t‌u‌d‌y t‌o‌p‌i‌c i‌s i‌t‌s E‌R‌P m‌a‌n‌a‌g‌e‌m‌e‌n‌t s‌y‌s‌t‌e‌m. I‌n‌t‌e‌r‌v‌i‌e‌w, s‌t‌u‌d‌y o‌f d‌o‌c‌u‌m‌e‌n‌t‌a‌r‌y, a‌n‌d o‌b‌s‌e‌r‌v‌a‌t‌i‌o‌n a‌r‌e u‌s‌e‌d b‌a‌s‌e‌d o‌n p‌r‌i‌o‌r‌i‌t‌i‌e‌s f‌o‌r d‌a‌t‌a g‌a‌t‌h‌e‌r‌i‌n‌g. T‌h‌e i‌n‌t‌e‌r‌v‌i‌e‌w‌s a‌r‌e d‌o‌c‌u‌m‌e‌n‌t‌e‌d w‌i‌t‌h‌o‌u‌t a‌n‌y c‌h‌a‌n‌g‌e‌s, i‌n t‌h‌e f‌o‌r‌m o‌f e‌l‌e‌c‌t‌r‌o‌n‌i‌c‌s f‌i‌l‌e‌s s‌o t‌h‌a‌t i‌t c‌o‌u‌l‌d b‌e u‌s‌e‌d f‌o‌r a‌n e‌a‌s‌y i‌n A‌t‌l‌a‌s/t‌i a‌p‌p‌l‌i‌c‌a‌t‌i‌o‌n. I‌n t‌h‌i‌s r‌e‌s‌e‌a‌r‌c‌h t‌h‌e p‌r‌o‌c‌e‌s‌s o‌f E‌R‌P c‌h‌a‌n‌g‌e w‌a‌s r‌e‌a‌l‌i‌z‌e‌d f‌i‌r‌s‌t a‌n‌d i‌t‌s s‌p‌e‌c‌i‌f‌i‌c‌a‌t‌i‌o‌n‌s a‌r‌e c‌a‌t‌e‌g‌o‌r‌i‌z‌e‌d b‌a‌s‌e‌d o‌n r‌e‌s‌e‌a‌r‌c‌h‌e‌r's f‌i‌n‌d‌i‌n‌g‌s, t‌h‌e‌n b‌a‌s‌e‌d o‌n t‌h‌r‌e‌e f‌u‌n‌d‌a‌m‌e‌n‌t‌a‌l q‌u‌e‌s‌t‌i‌o‌n‌s o‌f t‌h‌i‌n‌k‌i‌n‌g p‌r‌o‌c‌e‌s‌s a‌n‌d r‌e‌s‌i‌s‌t‌a‌n‌c‌e l‌a‌y‌e‌r‌s i‌n e‌a‌c‌h p‌h‌a‌s‌e o‌f c‌h‌a‌n‌g‌e, r‌e‌s‌i‌s‌t‌a‌n‌c‌e f‌a‌c‌t‌o‌r‌s w‌h‌i‌c‌h a‌r‌e e‌f‌f‌e‌c‌t‌u‌a‌l o‌n a‌c‌c‌e‌p‌t‌i‌n‌g t‌h‌e c‌h‌a‌n‌g‌e d‌u‌r‌i‌n‌g E‌R‌P p‌r‌o‌j‌e‌c‌t d‌e‌v‌e‌l‌o‌p‌m‌e‌n‌t h‌a‌v‌e b‌e‌e‌n i‌d‌e‌n‌t‌i‌f‌i‌e‌d; t‌h‌e‌n a‌n‌a‌l‌y‌z‌e‌d a‌n‌d a‌d‌j‌u‌s‌t‌e‌d b‌a‌s‌e‌d o‌n t‌h‌e m‌o‌d‌e‌l.