فصلنامه مطالعات مدیریت کسب و کار هوشمند
پیاپی 46 (زمستان 1402)

The maturity of business intelligence is a result of the evolution and advancement of technology and management approaches that help to provide accurate information, predictive analyzes and improve decisions in organizations using advanced technologies such as artificial intelligence and data analysis. Despite technological maturity that improves the efficiency and performance of organizations over time, business intelligence is far from becoming a mainstream trend in organizations. According to numerous researches in the field of business intelligence, the aim of this research was to present the framework of factors affecting the maturity of business intelligence using a meta-composite approach. In order to reach a comprehensive framework that includes all the maturity factors of business intelligence, 221 scientific studies were reviewed. Relevant codes were extracted using content analysis in metacomposite method. The categories were leveled using the comprehensive interpretive structural modeling method and the most influential ones were determined. The findings show that a total of 93 codes were extracted and divided into 6 categories. These categories include organization and management factors, environment, technology infrastructure, human resources - knowledge, data management and data analysis. The categories of technology infrastructure, data management and data analysis were placed at level three and have the greatest impact on the maturity of business intelligence.

The business model is an important factor in the competitive advantage of companies, and companies need to recreate their business model by changing the business environment due to changes in technology and communication. The current research aims to design a dynamic model based on text mining and soft methods to determine the most important key factors of electronic business models. This research is based on the text mining method and using the system dynamics modeling approach. In order to extract the key factors, the text mining of 779 articles of the last ten years from the world's authoritative databases has been examined. After examining the experts and selecting 17 key factors from among the extracted factors, in order to investigate the causal relationships between the key factors, the DEMATEL technique was used and the DEMATEL matrix was completed by the experts, and finally, the dynamic model of the research was drawn using Vensim software. The most influential causal factor is "Internet of Things" followed by "blockchain and cloud processing", and the most impressionable disabling factor is "provided value in the business". Also, the most influential factor on all factors was "nature of the media" and the most impressionable factor among the set of factors was "type of used technology ".

In recent years, studies on the paradigm of social Manufacturing and its applications have been developed as a new production paradigm and have led to the production of diverse and scattered knowledge in this field. Knowing the sub-fields, new topics and the research process of the social production paradigm can be of great help to researchers in this field. The current research has been carried out with the aim of identifying and categorizing research in the field of social Manufacturing, recognizing sub-fields and achieving a coherent view of its research process.This research has investigated the research field of social Manufacturing using bibliometric analysis. The data of this research was collected from 200 articles of the Scopus database and an analysis of the co-occurrence analysis of key words and bibliographic pairs was performed on them, and in this way the sub-fields and the research process of this field were identified.Based on the findings of this study, the research in the field of social Manufacturing has been categorized into 5 clusters and it has also been determined that in recent years, topics such as cloud computing, smart production, blockchain, Internet of Things, social physical cyber systems, innovation systems, society 5.0 and Digital twins have received more attention in research in this field. This research provides a framework of concepts and main topics of interest in the research field of social production, which provides a comprehensive perspective for researchers in this field that can help in choosing their research path.

Although digitization brings important possibilities, implementing its technologies in practice can be challenging. One of the current major developments in this field is to discover the potential of gamification for the empowerment of knowledge-based companies. Based on this, the current research was conducted with the aim of identifying the qualitative components of gamification implementation in the working environment of knowledge-based companies. This research has a qualitative approach, through in-depth semi-structured interviews, it has compiled and validated the conceptual framework with thematic analysis method. The statistical population includes experts and experts of knowledge-based companies, among whom 12 people were selected by purposeful sampling and participated in this study. The number of samples follows the rule of saturation. The findings of the research show that concepts were identified in the form of 4 main themes, including the acceptance process with 2 organizing themes, promotion strategies with 4 organizing themes, development and design strategies with 4 organizing themes, evaluation and implementation platforms with 3 organizing themes Gamification actually provides various possibilities to increase the motivation of employees for knowledge-based activities. But to reveal its potential, it needs a suitable environment.

The implementation of Industry 4.0 in the healthcare sector to improve community health is of great importance. Therefore, it is crucial to identify the critical success factors for implementing Industry 4.0 in the healthcare sector, model them, and analyze scenarios for targeted interventions. This issue has not been investigated in previous studies, and this research aims to fill this research gap. This research was conducted in two qualitative and quantitative stages. The statistical population was experts in both stages, and the judgmental and snowball sampling methods were used. The first stage had a population size of 17, determined based on theoretical saturation, while the second stage had a population size of 10. Thematic analysis was used as the data analysis method in the first stage, and fuzzy cognitive mapping was used in the second stage. The results showed that "competent managers," "support and cooperation," and "competent human resources" have the most significant impact, while "project management," "appropriate planning," and "support and cooperation" are the most susceptible. Furthermore, "support and cooperation," "appropriate planning," and "project management" are the most central. Three forward and three backward scenarios were designed for more effective interventions. It is recommended to improve the organization's educational system, strengthen the succession system, implement transparent contracts, and improve the quality of human resource management to achieve independent variables.

Among the growth and development of businesses, managing financial flows and increasing its effectiveness is an important achievement that causes value stability, efficiency of systems and procedures throughout the chains of Business. Therefore, paying attention to uncontrollable and controllable variables that lead to value creation is inevitable. The purpose of this study is to study the impact of social and biological factors (production and recycling of polymer parts) of environment on the value creation of the company along the supply chain. Also the key role of financial ratios has also been considered in this regard.The present research is of quantitative and applied types and is based on mathematical modeling. It is the result of a combination of genetic algorithms and Simulated Annealing. The financial analysis parameters of the model include current ratios, debt to equity, Instantaneous ratio, net profit margin, cash ratio and rate of return.The analysis of the results shows that considering financial goals and indicators leads to improved profitability and by removing financial indicators from the model, profitability is reduced. Therefore,this is means that the environmental and social performance of the supply chain is improved.Companies can pay special attention to social issues and environmental factors along with their profitability Increase their economic value. Profitability can also be improved by exposing social responsibilities and the mission of environmental protection.

Blockchain technology is one of the most promising technologies of this ‎century that has the potential to bring about fundamental changes in business ‎models in a wide range of industries. The current research seeks to identify ‎the antecedents of the development of digital marketing based on blockchain ‎technology from the point of view of marketing experts in the aviation ‎industry.This research is practical in terms of orientation and positivist from a ‎philosophical point of view, which was carried out using a mixed method.,In ‎this study, the antecedents of the development of digital marketing based on ‎blockchain technology were first extracted by literature review and semi-‎structured interviews, and with the help of experts, the final factors were ‎identified;Then, these factors in the form of Q cards were provided to ‎‏22‏‎ ‎marketing experts in the aviation industry who were selected purposefully ‎and finally their views were analyzed using exploratory factor analysis.The ‎participants in this research have ‎‏6‏‎ different views and their mental patterns ‎are categorized based on market variables, internal, content, technological, ‎human and environmental factors.The results of this research have given ‎useful insight to managers and decision makers in the aviation industry, so ‎that by knowing these factors, they can strengthen and develop digital ‎marketing in airline companies.‎

Accelerating the agility of production control systems in today's dynamic production environment is one of the challenges that many types of research have been conducted using multi-agent systems to improve it. The current models of these systems have shortcomings such as limited predictability, low reliability in the decision-making process, poor ability to understand and interpret the current state of the system, control with many limitations, and generally the existence of error-prone systems. In order to solve these problems, the current research presents a new methodology for multi-agent production control based on integration with ERP, which improves the capabilities of the system in the face of the above deficiencies. The research method employed in this study is qualitative, and developmental-applicative, aiming to enhance the integration of multi-agent production control systems with ERP. The objective is to improve the flow of material, production, and the quality of semi-finished products on the production line by considering the parameters that influence them. The key accomplishment of this research is the development of a reliable production control methodology that encompasses three components: a data exchange framework, tools, and implementation. These components are derived from existing ERP information systems that are functionally mature and designed based on best practices with a focus on maintenance, modification, and performance, aiming to minimize errors. The developed methodology offers a practical and agile solution for enhancing production control using an ERP system, with a lower implementation cost than the implementation of a commercial ERP system with a separate multi-agent system.

Gamification is a relatively new concept that has seen a significant increase in its use in recent years. Gamification involves the application of game elements in a non-gaming environment to create a gaming experience related to a product or service. The aim of this research is to investigate the impact of different aspects of gamification (immersion, achievement, social) on customer engagement (emotional, cognitive, social) in the online store of Digikala. The research population consists of consumers and users of the Digikala website who have made at least one purchase on this site. In this regard, 222 questionnaires obtained from Digikala website users' data were analyzed. The research model was designed by reviewing the literature related to the research topic and previous studies, and it was analyzed using structural equation modeling. Finally, it was determined that the aspects of gamification have a positive and significant effect on customer engagement. The immersion aspects of gamification have a positive impact on emotional aspects of customer engagement, the achievement aspects affect the cognitive aspects of customer engagement, and the social aspects of gamification also have a stronger positive impact on the social aspects of customer engagement.

Recently, the Internet has played a significant and substantial role in people's lives. However, the content available in the global web environment should align with users' daily needs, providing them with useful and up-to-date information tailored to their tastes. In this context, recommender systems assist users by suggesting items that closely match their preferences in less time. Today, with the exponential growth of data, the utilization of recommender systems has surged. Conversely, these systems encounter challenges such as evolving user preferences over time, cold start problem, sparsity within the user-item matrix, the infiltration of fake users in the systems, and their adverse impact on the recommendation lists.The objective of this paper is to propose a recommender system grounded in time and trust factors to enhance the efficiency and precision of system recommendations. Initially, the proposed system addresses the data sparsity dilemma by incorporating reliable implicit ratings into the user-item matrix. Subsequently, it constructs a weighted user-user network based on user rating timestamps and trust relationships among users, thereby mitigating the cold start problem and accounting for changing user preferences over time. The proposed recommender system employs a novel community detection algorithm introduced in this paper to identify the nearest neighbors of active users and recommends the top @k items based on the collaborative filtering approach. Evaluation results of the proposed system, tested on a film recommender system using the Epinions dataset, demonstrate its superior efficiency compared to basic systems.