fuzzy cognitive map

This study investigates the impact of competitive assurance elements on agile management in small and medium enterprises (SMEs).  

The research is descriptive-survey in nature, involving a sample of 41 managers and employees from Fidar Steel Company. Data were collected using the standardized agile management questionnaire by Zhang and Sharifi (2000). The data analysis was conducted using path analysis with SmartPLS software, version 4. 

The results indicate that all examined variables, including digital transformation, system alignment, agile methods, Scrum, and customer focus, have a positive and significant effect on agile management. Customer focus showed the strongest impact, with a path coefficient of 0.708 and a t-statistic of 8.997. Additionally, digital transformation and system alignment significantly contributed to enhancing organizational agility. These findings highlight the importance of leveraging modern technologies and agile practices to improve organizational performance.  

The study demonstrates that various factors, such as digital transformation, system alignment, and customer focus, can enhance agile management in SMEs. Implementing these elements can help organizations increase their flexibility and responsiveness to market changes. It is recommended that SMEs invest more in developing digital technologies and agile practices.

In general, consumer perception about the price of a store is known as "price image". Due to the significant expansion of online shopping in the retail industry and changing consumer behavior, one of the concerns of E-retailers is creating a good price image. This research aims to provide a cognitive map of the E-retailers' price image. in designing a fuzzy cognitive map, first by reviewing the literature, factors that affect the price image were identified. Then through interviews with academic and industry experts, as well as E-retailers customers, the impact of the identified factors was investigated and new factors were discovered. The results of this research indicate that factors such as price perception, website perceived quality, product perceived quality, and competition in the industry have the greatest impact on the price image. Also among all the variables website perceived quality, perception of the price level, and price image of E-retailers have the highest impact capacity and centrality index, respectively.

By combining interactive elements and immersive narratives, interactive storytelling offers a powerful tool for engaging target audiences and creating an unforgettable experience that allows brands to break free from the limitations of traditional marketing and connect with their audiences on a deeper level. This approach transforms passive observers into active participants, creating a more memorable and impactful experience. This research aimed to identify and analyze the antecedents and consequences of interactive storytelling in digital marketing. This research is exploratory in terms of its applied purpose and in terms of its data collection method, in which digital business managers and marketing and e-commerce professors were selected as samples. The present study is mixed research with an exploratory approach, in which in the qualitative part, qualitative data collected using the opinions of 19 experts were analyzed using MaxQDA software and content analysis and coding methods. Then, in the quantitative part, the data was provided to the same sample in the form of a paired comparison questionnaire and analyzed using the fuzzy cognitive map method. The results showed that among the antecedents of interactive storytelling in digital marketing, immersion has the highest capacity for impact and persuasive story has the highest capacity for impact. Also, among the consequences of interactive storytelling in digital marketing, awareness of customer interests has the highest capacity for impact and personalization has the highest capacity for impact.

Intelligent voice assistants with the ability to understand natural language provide multifunctional services, ease of use, increase speed and efficiency of equipment. The purpose of this research is to identify the antecedents and consequences of the use of intelligent audio assistants in defense equipment. The current research is of mixed type (qualitative and then quantitative) study. The general approach is forward-looking research and exploratory in terms of the gathering information method. In a qualitative study, interviews with experts were conducted until theoretical saturation and content analysis was used to extract antecedents and consequences. In a quantitative study, the fuzzy cognitive mapping method was used to determine the key antecedent and consequential factors. From the perspective of research experts, 18 antecedent and 19 subsequent factors were identified. The most important antecedent factors include the development IOT, security and maintaining confidentiality, multilingual support, digitalization of equipment. The most important subsequent factors include breach of security and confidentiality, effective communication, greater environmental awareness in the battlefield and increased operational efficiency. The use of smart equipment and their operational efficiency points out the need for evolution in defense production. The application of intelligent voice assistants in military equipment has made these smart tools an important part of future defense equipment by facilitating user interaction, increasing environmental awareness of the battle scene, and increasing efficiency. The requirements in the use of these tools are digitization, localization of sensitive devices, voice interfaces with multilingual support and strengthening of encryption methods.

The current research is practical in terms of its purpose, and in terms of gathering information, it is among exploratory research. Also, this research is a mixed qualitative and quantitative research based on comparative and inductive philosophy. The statistical population of the research is the experts who were selected by the purposeful sampling method and based on the principle of theoretical adequacy. The data collection tool is in the qualitative part of the interview, whose validity and reliability were confirmed using content validity and theoretical validity and intra-coder and inter-coder reliability methods. Also, the data collection tool is in the quantitative part of the questionnaire, whose validity and reliability were confirmed using the content validity and retest reliability of the test. Qualitative data was analyzed by content analysis method and quantitative data was analyzed by fuzzy cognitive mapping method. The findings of this research indicate that the ability to tolerate high ambiguity, systemic and multidimensional thinking, and flexibility are the most important antecedents of applying visionary leadership. Also, empowering employees, aligning employees through creating a vision, forming an active organizational voice were identified as the most important consequences of visionary leadership in knowledge-based organizations.

The current research was conducted with the aim of identifying factors affecting political brand using fuzzy cognitive map with FCM method. Brands are strategic and key assets to achieve competitive advantage. Brands can be considered as a heuristic device that includes a set of values that enable the consumer to make quick and efficient choices. Recently, the concept of political branding and branding slogans have been widely adopted by many political parties as they seek to differentiate themselves, leading to an emerging interest in the idea of political branding.

This research is descriptive and exploratory in terms of practical purpose and in terms of data collection method, which has an inductive comparative research philosophy. The statistical population of the current research is the employees of the Political Vice-Chancellor of Lorestan Governorate and the governors of Lorestan, in addition to the professors of political science and marketing fields of Lorestan universities. that the sample members were selected using the purposeful sampling method and based on the principle of theoretical saturation. The data collection tool in the qualitative part is a semi-structured interview and in the quantitative part is a questionnaire whose validity and reliability are respectively through CVR and Cohen's kappa test and in the questionnaire part using content validity and intra-coder and inter-coder reliability of the interview and validity and content validity and retest reliability for the questionnaire. has been analyzed. I. C

Throughout the history of human life, diseases have been considered one of the most important threats to humans; which have destructive and irreparable effects on people's lives if they are not diagnosed or diagnosed correctly and on time. The existence of multiple parameters in some problems causes the complexity of the investigated subject; For this reason, in the last few decades, computer diagnosis and decision-making tools with the aim of helping the doctor in making decisions have been considered as a decision support system. Because the initial symptoms of diabetes insipidus are very similar to diabetes mellitus and the differential diagnosis of different types of diabetes insipidus is important, this disease was investigated in the current research.

In this research, based on library studies and using the experiences and opinions of experts, the factors of central and renal diabetes insipidus were examined and determined; then, using Spss, FCMapper, and Pajek software, fuzzy cognitive maps were analyzed in order to investigate factors and relationships between them.

The results of the analysis of fuzzy cognitive maps in central diabetes insipidus, the factors that improve urine concentration after taking vasopressin and urine volume > 40 ml/kg and osmolarity of 300 mosom/l, and in renal diabetes insipidus, the factors of kidney failure Synthetic vasopressin use (no change in urine concentration) and hyperuria were identified as the most influential and important variables that should be given special attention.

Originality/Value: 

So far, no definitive treatment has been discovered for this disease, and if a person is infected with it, it will affect him for the rest of his life. But with a faster and timely diagnosis, it can be prevented from progressing and the damage of lack of treatment, which can be irreparable. For the first time, the identification, ranking and impact of central and renal diabetes insipidus disease symptoms have been investigated using fuzzy cognitive maps and Spss, FCMapper and Pajek software.

An Empirical Case Study of E-Commerce Development of Leading Countries in The Era of Digital Economy
The emergence of new technologies of the digital economy era has increased the speed of e-commerce development globally and has become a factor for competitiveness in this sector. Hence, examining the upstream documents in order to identify the key factors driving the growth of e-commerce in the leading countries in the digital economy era, would support to find more effective policy solutions for Iran. In the present study, the theoretical background of the research was first investigated, and then a systematic review of the sixteen documents in the field of e-commerce from four selected pioneering countries was conducted. After reviewing the documents, the qualitative content analysis of the documents was done and led to the identification of four fundamental drivers for the development of digital infrastructures and five drivers for the development of e-commerce. The key drivers for the development of digital infrastructures are: development and strengthening of digital data connection, data storage and processing infrastructure, data terminal and device, digital service infrastructure and applications. The five key drivers identified also include strengthening digital adaptation by emerging technologies, digital business context, rules and regulations, export, international cooperation and development of sustainable e-commerce for social responsibilities and environment protection. Then, based on these findings and applying the Pazhek and Gefi fuzzy cognitive mind map software, the documents of the selected countries were analyzed and it was found that the driver of development and strengthening of digital data connection infrastructure shows the most effectiveness and efficiency. Finally, suggestions for Iran were presented.

Customer brand co-creation behavior plays a crucial role in effective branding. However, previous research has not thoroughly explored the challenges associated with fostering this behavior or the strategies for overcoming them. This study aimed to identify these challenges, analyze their interrelationships, and propose actionable strategies. Conducted in 3 phases, the research involved a population of academic experts and professionals in the e-commerce industry, utilizing judgmental and snowball sampling methods. In the first and third phases, qualitative approaches—including semi-structured interviews and thematic analysis—were employed to identify challenges and strategies. The second phase utilized a quantitative approach, incorporating a researcher-designed questionnaire and fuzzy cognitive mapping to analyze the relationships among the identified challenges and create scenarios. The findings revealed 15 challenges categorized into 3 general levels: "internal organizational challenges", "environmental obstacles", and "customer-related issues". Notably, challenges, such as ineffective communication between brands and customers, a weak employer brand, and a lack of strategic alignment, were prominent across all backward scenarios, underscoring their significance. Conversely, cultural issues within society emerged as the most independent challenges in forward scenarios. Additionally, weak corporate branding and a closed organizational culture were present in all forward scenarios, highlighting their critical importance. The analysis of both scenarios emphasized the significant impact of the weak employer brand challenge. To address these potential obstacles, the study proposed 16 strategies organized into 3 key levels: "preparing the organization for co-creation", "mitigating the effects of external environmental obstacles", and "encouraging customer engagement in brand co-creation".

The Internet of Things (IoT) is considered a modern concept in the production industry, based on which the physical and digital worlds are connected using the potential of the Internet. Since this technology is new, its acceptance and implementation in the oil and gas industry are associated with barriers. Therefore, this study aims to identify and analyze such barriers.

This study has been performed with a mixed approach in two phases. The qualitative phase was conducted to identify the barriers to using the Internet of Things in the oil and gas industry, and the quantitative phase was conducted to model and analyze the scenario. To identify and extract the barriers to using IoT in the oil and gas industry, it is identified through a literature review and content analysis method. In this research, 58 articles were analyzed and 10 industrial and academic experts analysed extracted barriers by using the Fuzzy cognitive mapping method. To analyze the scenarios, two categories of backward and forward scenarios have been designed. FCMapper software has been used for scenario design.

The results of the content analysis showed 10 barriers, which are subcategories of four aspects. The barriers identified are "limited coordination and collaboration" "lack of automation in organizations", "insufficient leadership support", "weak staff knowledge and abilities", "limited scalability", "opposition to change", "lack of Certain rules and standards for the adoption of the IoT", "the cost of data storage and analysis", "the high cost of implementation and maintenance", "security and confidentiality issues". Finally, these barriers were categorized into four main subcategories: "Organizational", "Integration", "Economic" and "Technical". The results of the fuzzy cognitive mapping method indicate that the barrier "security and confidentiality issues" with a factor of 4.34 has the highest level of influence, and the barrier "high implementation and maintenance cost" with a factor of 4.95 has the highest level of influence, and the barrier "security and confidentiality issues" has the highest centrality with a coefficient of 6.45.

Like any other research, this research has been faced with limitations. Considering that the research was limited to a specific industry, its findings may be affected by the opinions and biases of experts involved in the process, and we cannot generalize the results to another industry. Another limitation of this research is the complexity and time-consuming methods used in it. The methods of content analysis and fuzzy cognitive map may be complex and require sufficient time and a high level of expertise to use them, which can limit their application in some fields.

Considering that the IOT is an emerging and new technology, the adoption of this concept in the oil and gas industry can have several operational advantages, such as reducing testing and calibration time, minimizing production downtime, improving performance, and predicting maintenance performance. One of the important barriers to the use of IoT in the oil and gas industry is "security and data confidentiality" issues in different parts, and this issue causes the unwillingness of stakeholders and decision-makers to use this technology. Conducting research in the field of raising and increasing the security of these systems and ways to increase the security of privacy will greatly help in solving this barrier.

The study offers valuable insights for researchers, managers, and policymakers in the oil and gas industry concerning the adoption of Internet of Things (IoT) technologies. To facilitate the adoption of IoT in the oil and gas industry, companies should invest in comprehensive training programs for managers and stakeholders to improve awareness and understanding of IoT technologies and their benefits.

Since several barriers have prevented the widespread adoption of the IOT in the oil and gas industry, in this research, the identification and extraction of these factors have been done comprehensively for the first time. Modelling and scenario analysis of these barriers with fuzzy cognitive mapping were also performed for the first time.

One of the challenges in human resource management is the impact of risks associated with Industry 4.0 on reducing workforce productivity. Therefore, the present study aims to identify and determine the cause-effect relationships of human resource risks in the fourth-generation automotive industry. 

This study conducted through a mixed-method (qualitative-quantitative) approach. The study population comprises 16 experts and managers from an automotive company, selected through purposive non-probability sampling. 

Risks were identified and extracted in the qualitative section using interviews and a combined (directed-conventional) content analysis approach, then evaluated through the fuzzy Delphi method. The findings from the qualitative section indicated that the most significant risks include “psychological risk,” “technical risk,” “operational risk,” “social risk,” “legal risk,” “organizational risk,” “managerial risk,” and “economic risk.” Subsequently, data collected through pairwise comparison questionnaires were analyzed using the fuzzy cognitive map method. The findings from this section revealed that “Human Resource Planning 4.0 risk,” “Employee Investment 4.0 risk,” “Employee Payment 4.0 risk,” “Employee Regulations 4.0 risk,” “Industry Standards 4.0 risk,” and “Employee Leadership 4.0 risk” are driving risks, in such a way that the connections propagate through “Human Resource Planning 4.0 risk” and “Employee Job Security 4.0 risk” across the entire system. 

Based on these findings, it is concluded that a lack of effective Human Resource Planning 4.0 exacerbates risks, thereby endangering employees' job security and resulting in psychological issues for employees within Industry 4.0. It is recommended that automotive decision-makers focus on digital human resource strategy.

The potentials and capabilities of export enterprises in the carpet industry are so great that export enterprises operating in this field have a high ability to create brand signatures in the carpet industry in international markets. Therefore, the current research was conducted with the aim of identifying the antecedent and consequent elements of brand signatures for carpet export enterprises and analyzing these elements using the fuzzy cognitive mapping (FCM) method. It is an applied study, and as for the method of collecting the descriptive information, it is a survey. Methodologically, this study is an investigation that combines qualitative and quantitative approaches within an analogous inductive paradigm. The statistical population of the study is the experts, 30 of whom were selected according to the principle of theoretical adequacy and using the purposive sampling method. The instrument used to collect information is a semi-structured interview in the qualitative part of the study and a questionnaire in the quantitative part, whose validity and reliability were determined by the CVR coefficient and the Kappa-Cohen test, respectively. For the questionnaire part, content validity and retest reliability were confirmed. In the qualitative part, the data obtained from the interview were analyzed using MAXQDA software and the coding method, and the antecedents and suffixes of the brand signature were identified. In the quantitative part of the research, the fuzzy cognitive map of the brand signature was constructed using the FCM method, and the most important antecedents and consequent factors of the brand signature were identified.

The aim of this study is to analyze the factors influencing the financing of renewable energy projects to achieve sustainable development goals using a fuzzy cognitive map approach.

This applied research was conducted in both qualitative and quantitative sections. In the qualitative section, content analysis with a conventional and directed approach was employed, and in the quantitative section, a causal method was used. Data were collected through semi-structured interviews in the qualitative phase and pairwise comparison questionnaires in the quantitative phase. The participants were senior managers and experts from the Renewable Energy and Energy Efficiency Organization (SATBA), selected using purposive and theoretical sampling (a total of 21 participants).

The qualitative findings revealed key influencing factors, including "social responsibility," "direct and indirect government support," "sustainable economic development," "environmental sustainability," "support from financial funds," "commercial creditworthiness of financial suppliers," "foresight and capital planning," "financial capacities," "investment return policies," "empowerment of financial institutions," "renewable energy development policies," "investment culture in renewable energy," and "optimal management of investment risks." The fuzzy cognitive map results showed that "direct and indirect government support for the energy industry" had the highest output and influence, while "commercial creditworthiness of financial suppliers" had the highest input power and susceptibility to influence.

This study provides a comprehensive analysis of the factors affecting the financing of renewable energy projects. It highlights the critical roles of government support policies and the commercial creditworthiness of financial suppliers in the success of these projects, suggesting that improvements in these areas can contribute to achieving sustainable development goals.

 the present research was conducted with the aim of identifying the effective factors and consequences of using strategic management dashboards with the FCM method.

The current research has been done quantitatively and qualitatively. This research is practical in terms of purpose and survey and exploratory in terms of data collection method. The statistical population of the research is the managers of government organizations and university professors, whose sample members were selected by the purposeful sampling method and based on the principle of theoretical saturation.  In this research, content analysis and coding method was used in qualitative part and fuzzy cognitive map method in quantitative part for data analysis.

The research results show that improving organizational efficiency and effectiveness is the most important factor affecting in using strategic management dashboards. Also, increasing decision speed and reducing the cost of decision mistakes is its most important consequence. 

This research has studied one of the newest organizational phenomena under the title of strategic management dashboards. Other researches in this field have either focused on the design of management dashboards or have measured strategic management dashboards with other factors. However, by identifying the effective factors and the consequences of using strategic management dashboards, the current research provides solutions that make managers aware of how to use it.

Consumers' attitude towards advertising plays a key role in influencing the dimensions of brand equity. Considering the ever-increasing competition between companies and the challenge of attracting new customers and keeping current customers, companies should seek to improve customers' attitudes and reduce their doubts about advertisements. In this regard, persuasive knowledge management has a significant role in achieving this goal. Therefore, the present research was carried out with the aim of identifying the programs and consequences of persuasive knowledge management with the method of fuzzy cognitive mapping.

The present research is an exploratory research in terms of practical purpose in terms of gathering information. Also, this research is a mixed type of research based on qualitative and quantitative research. The statistical population of the research in the qualitative part is the experts and customers of the cosmetics industry, 30 of whom were selected using purposeful sampling and based on the principle of theoretical saturation. Also, the statistical population of the research in the quantitative part is the customers of the cosmetic and health industry, and due to the unlimited population, 384 of them were selected using Cochran's formula and available sampling method. The data collection tool in the qualitative part is an interview and in the quantitative part is a questionnaire. The validity and reliability of the interview was confirmed using content validity and theoretical validity and intra-coder inter-coder reliability. Also, the validity and reliability of the questionnaire was measured by content and retest validity.

Nowadays, due to the population’s growth and the expansion of science and new technologies, various businesses have been created in society. These businesses need to pay special attention to human resources in order to have good productivity and not be weak in front of their competitors. This research aims to design a model to determine the factors affecting the emergance of human resource black holes using a fuzzy cognitive map (FCM). The statistical population of this research includes experts familiar with the subject at Lorestan University and Azad University, Lorestan branch whose sample members were selected using the snowball sampling method based on the principle of theoretical saturation. The data collection instrument consisted of the interviews in the qualitative part, whose validity was confirwmed using content validity, and their reliability was calculated using intra-coder inter-coder reliability with a coefficient of 78. The data collection instrument is the quantitative part included a questionnaire, whose validity and reliability were confirmed by content validity and test- retest reliability, whose coefficient was found to be 84. In this research, the content analysis and coding methods were used in the qualitative part and the FCM was used in the quantitative part to analyze the data. The findings in the qualitative part included identifying factors affecting the emergeance of human resource black holes, and the findings of the quantitative part included the ranking of these factors based on the degree of importance. The results of the research showed that a preference for engagement over expertise with the highest capacity for influence and consequently the highest degree of centrality was identified as the most important factor influencing the emergence of human resource black holes. Following this, the supervisors' inattention to the organization's problems and events, lack of proper performance evaluation system, individualism, and managers' inefficiency were identified as other important factors affecting the emergence of human resources black holes.

The objective of this study is to design scenarios that can examine brand switching behavior in customers within the sports equipment industry and identify and analyze the influencing factors. 

In this research, first, a literature review was conducted to identify the factors influencing brand switching behavior in customers. Then, a questionnaire was designed and distributed to examine the current status of these factors in the sports equipment industry in the country. Seventy experts from the sports equipment industry responded to this questionnaire. Subsequently, using the fuzzy cognitive map technique, the systemic relationship between the factors was identified, and forward and backward scenarios were developed to improve the structure. 

The results of the study indicate that among the 10 identified factors, the quality of products and services offered in sports equipment is the most important factor in implementing a systemic structure to prevent brand switching. The identified factors are: trust, competitive pricing, customer attitudes, customer satisfaction, reliability, quality, customer relationship management, word-of-mouth advertising, knowledge management systems, and government regulations. 

Focusing on the quality of products and services offered in the sports equipment industry can serve as an effective strategy to reduce brand switching among customers and provide a distinct competitive advantage for brands.

Industry 4.0 has brought significant changes to industries and businesses. This transformation, involving the interconnection of devices, processes, and systems through smart networks and the use of data-driven technologies and artificial intelligence, has created a comprehensive approach in businesses. This development is crucial and has substantial impacts on various areas, including production, services, supply chain, and marketing. Given the increasing stability and future competitiveness of the production sector, the new technologies of the fourth industrial revolution (Industry 4.0) have gained considerable attention from the academic and industrial communities in recent years. However, manufacturers face numerous factors in implementing Industry 4.0, which need to be identified and analyzed. The purpose of this research is to identify the organizational factors influencing the adoption of Industry 4.0 and to present a fuzzy cognitive model.

This research is considered applied-developmental in terms of its purpose and hybrid (exploratory mixed) in terms of the research type. The statistical population of this research comprised small and medium-sized manufacturing companies, with 12 experts from small and medium-sized manufacturing companies active in the industrial town of Yazd province selected purposefully. Initially, to identify the organizational determinants of Industry 4.0, the meta-combination method was used, and then the relationships of these factors were determined using the fuzzy cognitive mapping method and the Fcmappear and Mental Modeler software.

The findings of the meta-combination method indicate 36 primary codes and 11 determining factors affecting the acceptance of Industry 4.0 technologies in small and medium-sized manufacturing companies operating in Yazd Industrial Town. These factors include absorption capacity, commercial assets, technical competence in digitization, digitalization knowledge and expertise, participation in the implementation process, strategic management competence for Industry 4.0, organizational culture, organizational structure, availability of resources, social capital, and top management characteristics. Among these factors, participation in the implementation process, absorption capacity, and social capital have the highest influencing capacity, while top management characteristics, digitalization knowledge and expertise, technical competence in digitization, and strategic management competence have the highest impact. Ultimately, the factors of technical competence in digitization, digitalization knowledge and expertise, top management characteristics, and participation in the implementation process obtained the most central indicators.

Industry 4.0 is a vital strategic option for small and medium-sized manufacturing companies, enabling them to keep pace with the digitization race. Small and medium-sized manufacturing companies are significantly behind large organizations in leveraging Industry 4.0 technologies. Additionally, these companies are still grappling with early adoption decisions regarding digital transformation under Industry 4.0, which is a concerning issue. The results identified various organizational determinants that may explain these conditions and provide efficient solutions for small and medium manufacturing companies. This study created an organizational digitalization roadmap that describes the necessary conditions to facilitate the digitalization of small and medium-sized manufacturing companies under Industry 4.0.

The supply chain of the food industry is crucial for countries, yet it is vulnerable to disruptions caused by natural disasters like floods, frost, and heatwaves, as well as operational shutdowns. These disruptions can trigger a ripple effect throughout the food supply chain, posing significant challenges for the country. Therefore, it is imperative to identify and analyze strategies to mitigate the ripple effect. This research has been conducted in two stages: qualitative and quantitative. The qualitative stage aimed to identify coping strategies, employing thematic analysis. The quantitative stage involved scenario modeling and analysis using fuzzy cognitive maps. The findings revealed 84 primary codes grouped into 21 sub-categories and 4 main categories: "Strategic Management," "Operations Management," "Compilation and Correct Implementation of Laws," and "Supply Chain Management." Analysis of backward scenarios underscored the importance of "supplier relationship management," "cooperation and coordination in the supply chain," and "contingency plans." Conversely, analysis of forward scenarios highlighted the significance of "monitoring environmental changes" and "strategic planning." Focusing on short-term plans, enhancing managers' decision-making and problem-solving skills, refining supplier selection criteria, optimizing supply network design with backup locations, and maintaining safety stock for critical goods are recommended actions for industry stakeholders.

Nowadays, the advancement of Science and technology and the rapid changes in the course of life are closing the way to repetitive methods and requiring new and creative solutions. In the meantime, cyber entrepreneurship uses innovation and initiative to harness the potential of technology to solve problems, thus creating the basis for the formation of new jobs. Therefore, the present study was conducted with the aim of identifying and analyzing the key success factors and consequences of implementing cyber entrepreneurship. The present study is a mixed study that has been done qualitatively and quantitatively. This research is a survey and exploratory method in terms of practical purpose and data collection method, which has an inductive comparative research approach. The statistical research community, experts consist of managers of start-ups, startups and online businesses of the province of larestan, whose sample members were selected using the targeted sampling method and based on the principle of theoretical saturation. The data collection tool is in the qualitative part of the interview and in the quantitative part of the questionnaire, where the validity and reliability of the tools were analyzed using the Guba and Lincoln partial strength indicators for the interview and the content valid