فصلنامه مطالعات مدیریت کسب و کار هوشمند
پیاپی 45 (پاییز 1402)

The evolution of information technology, artificial intelligence, and large volumes of data in web2, led to the formation of a new approach from the convergence of two scientific fields of business intelligence (BI) and social media analysis (SMA), which is called social business intelligence (SBI) with some researchers. Growing the number of studies in BI and SMA and the explosion of information, required coherence, integration and summary to knowledge extraction. The purpose of this paper is to recognize the capabilities that are the result of the two scientific field convergence. The bibliometric methods have been used to analyze publications tile 2022 and map the topics trend, historical graph, co-occurrence network and knowledge map of social business intelligence capabilities. The results indicate that the nature of business intelligence studies changes toward the analysis of big social media data and integration of analytical and managerial capabilities in BI with the power of marketing, communication and networking in SM. Also, five clusters of social marketing capability, data analytic capability, knowledge capability, communication capability, and transformational capability have been identified for SBI. About the role of SBI in empowering organizations in the digital era, especially in business related to marketing and innovation goals, it is recommended to equip organizations with this technology and its capabilities.

The touch of the product plays an important role in the final decision of the customer when purchasing from physical and online retail, and the sensations that come to be enjoyed through touch enable them to experience the product from all angles. Therefore, considering the importance of touch, this research has investigated the lived experience of touching the product from the point of view of customers of physical and online stores. The following article is done with qualitative method and phenomenological paradigm. The research community is made up of electronic and clothing buyers from online and physical stores: Technolife, Adak, Havadar and Happyland in Tehran, and through semi-structured interviews, evidence was collected based on the purposeful sampling method. The interviews continued until reaching the theoretical saturation, and in this research, the interviews reached saturation with 15 people. Based on the extracted results, the main themes include; Product perception is physical touch, virtual touch, touch experiences, need for touch and touch perceptions. According to the results, managers of physical and online stores should provide conditions (such as the use of modern technologies) that touch and contact with the product happen to both groups of online and physical buyers so that they can buy products based on their needs and wants, and also this research can pave the way for the development of touch literature for researchers.

The concept of progress has long been a central focus of scholarly discourse, with science and technology serving as key drivers for societal advancement and the continual improvement of quality of life. In this context, the integration of AI into scientific discoveries has resulted in notable ontological and epistemological developments within the realm of science, lending itself to an understanding informed by post normal science approaches. This article aims to elucidate how artificial intelligence can augment the power of scientific discoveries and human knowledge in the ongoing progression of science. The research methodology employed for this study entails documentary studies and trend analysis is conducted to explore the influence of artificial intelligence on the advancement of science and technology.The principal findings of this investigation reveal that artificial intelligence has fundamentally transformed the structure, function, methodology, and human agency associated with scientific progress. Consequently, a new paradigm of dominance and subjugation within the scientific domain has emerged, perpetuating an increasing divide between AI beneficiaries and those deprived of such technological resources. This growing disparity underscores the significance of unequal access to emerging technologies and its implications for scientific research.

The maturity of business intelligence, which is the main goal of this research, plays an important role in intelligent decision-making, planning, control and monitoring in the field of health care. In order to identify the effective factors, the Delphi method was used and experts' opinions were, and in order to determine the effectiveness and effectiveness of the indicators and finally to prioritize them, used the DANP method. The statistical sample includes 20 targeted academic experts and health care experts. According to the results of the Delphi section, 26 main indicators finalized in the research were identified, which are divided into three main categories including organizational, process and judgment criteria. According to the results of the DANP process, flexible and expandable technical infrastructure criteria, data and system quality and the correct definition of business intelligence problems and processes were prioritized as the three criteria with the highest ranking in the maturity of business intelligence. The business intelligence maturity model proposed by the research can be a road map for the successful implementation of business intelligence in the field of health care.

The current digital revolution has given rise to a new organizational form, the Platform company. Today, the most valuable companies in the world and the first ones with a market value of more than a trillion dollars are platform companies. The Platform Economy is developing at an exponential rate and has become a top priority for governments across the world.The present study aims to provide a framework for evaluating the Digital Platform Economy at the international level. Utilizing a systematic review and meta-synthesis approach, the Platform Economy dimensions are identified as Digital Users, Digital Entrepreneurs, Digital Platforms, Digital Infrastructure, Innovation Capacity, and Institutional Environment and by extracting relevant indicators from international reports, the Platform Economy Composite Index is developed.Using the Partial Least Squares-Path Modelling (PLS-PM) method and specifically the Higher-Order Construct model, the measurement model is validated, and by employing a non-compensatory aggregation method, the Platform Economy Composite Index ranks 128 countries. The study is concluded by scrutinizing Iran’s current status regarding the enabling factors of the platform economy and identifying its strengths and weaknesses and providing recommendations for improvement. The results indicate that although Iran’s current status in terms of demand-side enablers is relatively good, it faces serious issues in terms of supply-side enablers.

The fifth-generation networks of smart manufacturing and smart factory is rapidly evolving as a technology that integrates industrial production and smart Internet, bringing new support for the digital transformation of the industry and the development of a high-quality economy. Therefore, this article, with emphasis on the fifth generation of the Internet and with the aim of identifying 5G-based intelligent manufacturing projects, seeks to prioritize these projects using the hierarchical analysis method. Therefore, after reviewing the literature and interviewing with 17 experts, 5 main criteria for project prioritization were selected and weighted by AHP method using an expert questionnaire. Then, using the opinions of experts, 22 identified smart factory projects were prioritized according to the criteria weight. The criteria were calculated according to the income, cost and risk level of the project. Also Intelligent production line, intelligent logistics, intelligent resource allocation and process automation were identified as the most important intelligent production projects.

The aim of the current research was to provide a world-class information systems development model using the balanced scorecard approach in sports organizations. The current research is practical in terms of purpose; In terms of how to collect information, it was a survey. The statistical population of the research was made up of the employees of all 31 general sports and youth departments of the country's provinces (5882 people) and the statistical sample was selected using the Karjesi and Morgan table of 361 people. To collect data, a researcher-made questionnaire was used according to the balanced scorecard approach (4 components and 48 items). The validity of the questionnaire was confirmed by 10 sports management professors and the reliability was 0.86, which indicated its good reliability. Data analysis was done using confirmatory factor analysis and structural equation modeling with PLS software. The findings from the analysis of the conceptual model of the research show that the development model of world-class information systems in sports organizations, in the financial perspective using 5 indicators, in the customer perspective with 12 indicators, in the business processes perspective with 14 indicators and in the growth perspective and learning was confirmed with 17 indicators. Therefore, it is concluded that the development of world-class information systems in sports organizations by increasing efficiency and effectiveness will improve organizational productivity and be considered as a sustainable competitive advantage.

Traditional banking needs new fintech innovations and technologies to improve its processes and services. Various factors affect the cooperation of banks and fintechs, some of which are related to banks and others to the banking environment.The purpose of this study is to identify and analyze the strategic factors affecting the cooperation of banks and fintechs in Bank. The present study is applied in terms of orientation and has a quantitative nature in terms of methodology. Two methods of fuzzy Delphi and fuzzy dematel were used to analyze the data. The fuzzy Delphi method was used to screen the strategic factors of the research and the fuzzy dematel technique was used to identify the most effective factors. Two tools of interview and questionnaire were used to collect data. The research questionnaires were:Fuzzy Screening Questionnaire and effect analysis Questionnaire. Initially, through literature review and interviews with experts, 28 strategic factors were identified.These factors were screened by fuzzy Delphi technique.10 internal factors and eight external factors had a defuzzy number greater than 0.7 and were selected for analysis with fuzzy dematel.Analysis of internal factors with fuzzy dematel showed that the factors of the nature of the needs of the bank's customers,the future thinking of the bank's senior managers, the culture of risk-taking between managers and senior experts and the agility of the bank's structure and processes have the most net effect In relation to external factors, the factors of intensity of competition between banks, effective factors on the cooperation between banks and fintechs.

Fraud cases have increased in recent years, especially in important and sensitive financial and insurance fields. Therefore, to deal with such frauds, there is a need for different measures than traditional inspection methods. Agricultural insurance is also not exempted from this threat due to its nature and wide extent and every year a lot of money is spent on paying fake damages. This research was presented with the aim of providing a model to discover unrealistic damage claims in agricultural insurance by using data mining and machine learning techniques. It was used to build a deep learning model. The data used was obtained from the Agricultural Insurance Fund and related to wet and rainfed wheat insurance policies of Khuzestan province, for which compensation was paid in the 2018-2019 crop year. After preparing and preprocessing the data, using deep learning to discover unusual cases, the action and results were evaluated by the experts of the Agricultural Insurance Fund. After analyzing the results, it was found that 1% of the damages paid were related to unrealistic requests and more care should be taken in paying the damages. The accuracy of the model in detecting unusual cases for wet and dry wheat was 53.53 and 63.37 percent, respectively. In the review of the results, it was found that 5 categories of unusual behavior have led to the payment of unrealistic damages, and the behavior of not providing damage documentation was more frequent than the others.

The aims of this study is to provide a conceptual model of hospital accreditation in Iran through qualitative research. The grounded theory model was compiled using the results of the analysis of the interviews. Then, with the help of the grounded theory model and the results of qualitative analysis, a state diagram was obtained. Using the state diagram, initial sampling, systematic review of sources and results of interviews, 9 conceptual agents "governance organizations, management and leadership, clinical personnel, support personnel, hospital infrastructure, assessor, standards, assessment method and service recipient" were identified. Finally, the conceptual model of agent-based, environment, behavioral rules of agents and their input and output interactions was presented. In future researches, reinforcement learning models can be designed according to the conceptual model of this study, so that by using it, software developers can develop a suitable framework for solving complex problems in the field of hospital accreditation. Because the field of hospital management systems is one of the desirable types of socio-technical systems that have high capacities.