فصلنامه مطالعات مدیریت کسب و کار هوشمند
پیاپی 39 (بهار 1401)

The purpose of this research was investigating the effect of work- family conflict on life satisfaction and the mediation roles of job stress and job satisfaction. This research was descriptive correlation. The statistical population included university professors and 384 persons were selected by available sampling data collection was performed using electronic questionnaires and statistical analysis was performed with SPSS and SMARTPLS 3. The results showed that with the increase in WFC, life satisfaction decreased only in the situation of virtual teaching; The effect of job stress on life satisfaction was not significant in both face-to-face and virtual situations; The effect of WFC on life satisfaction with partial mediation of job satisfaction was significant only in situation of virtual teaching; and the role of job stress in the relationship between WFC and job satisfaction was confirmed as a partial mediator. The results of comparing the mean differences showed that the interaction of work with family based on strain in the virtual teaching situation was more than the face-to-face teaching situation and the professors were in much worse situation.

Technology progress, during the recent decades, has influenced the banking industry. Banks have moved from traditional banking to online banking. Users expect to view systems on different browsers or different devices without disrupting the overall/page due to the small size of the display on some devices such. This expectation is responsiveness which is one of the factors influencing the user experience. Responsiveness means that the contents of a web-based system are displayed correctly and clearly on all devices and browsers, regardless of screen size. The purpose of this article is also to design a responsive Internet Banking system based on design science. It has been designed, based on the study of the scientific background and considering the concepts of Internet Banking, its adoption factors, responsiveness and user experience and the system requirements, from a business and technical point of view.The present study provides a system design that can be used by all financial institutions. It can also be applicable for universities and higher education institutions, as it describes, step by step, how to practically use the research method in a real system.Considering the results of this study, user experience, including issues such as responsiveness, ease of use and learnability, is much interesting for users, and the Internet banks that provide these factors along with security and performance are very attractive and are highly appreciated.

Customer churning is one of the most important issues facing Internet Service Providers in a competitive and rapidly saturating market. Due to the high costs associated with attracting new customers, ISPs have turned to a customer retention approach that explicitly seeks to reduce churn. This study has been surveyed the churning of internet service customers in one of the largest telecommunication companies in Iran. In order to predict the churn, customer data has been collected during six months, and their churning behavior has been investigated over a period of one year after. In addition to churn prediction, the most important factors affecting churn have been identified. In the preprocessing step, the "Random Under-Sampling" method is used to balance the data set and the "minimum-Redundancy, Maximum-Relevance" method is used to feature selection. Then, the "Random Forest", "Support Vector Machine" and "K-Nearest Neighbors" algorithms were applied to classify churning and non-churning customers, and the evaluation criteria showed the superiority of the random forest algorithm. The final model, which was obtained from a combination of balancing, feature selection and classification methods, called the RUS-mRMR-RF model, is considered as an efficient model in customer churn prediction and identifying the most important factors affecting churn. The results of this study provide valuable insights for the company to develop customer retention strategies.

Global Developments in the fields of science and technology as well as; Consecutive challenges of economic and financial systems have led to deeper attention of policymakers and thinkers to the development of market intelligence in organizations. In this regard, market intelligence activities, which include the production and dissemination of market intelligence in the development of new products, can increase the chances of success and effectiveness of innovation. The purpose of this study is to investigate the relationship between innovation and market intelligence features on the company's performance with emphasis on the mediating role of business acquisition and application of market intelligence in the specialized departments of Bank Mellat in Tehran. The statistical population of the present study includes: Managers, deputies and experts of the General Departments of Bank Mellat in Tehran. The sample size of the research is 253 people based on Cochran's formula and simple random sampling method . In this study, The statistical population of the study was surveyed using a questionnaire and to determine the validity of the questionnaires, the content validity method was used and also its reliability was estimated 0.931using Cronbach's alpha coefficient .The results of this study indicate that between company innovation and Acquire & employing market intelligence, between intelligence acquisition and market intelligence application, between market intelligence acquisition and company performance, between market intelligence application and innovation performance, between innovation performance and market performance and between Market performance and company performance; There is a positive and significant relationship.

Due to the widespread use of information systems, a large amount of data has been stored in organizations, and the analysis of this data is a valuable resource to help organizations making better decisions. This concept is known as business intelligence (BI) and is one of the most important factors for the success of organizations in the contemporary world. Given the importance of BI, it is necessary to systematically review the research conducted in Iran on it. The purpose of this research is to identify the topics researched in selected journals, analyze the dispersion and frequency of studies, identify research methods, the purpose of articles, the level of analysis of BI research and finally identify research gaps and provide the future research suggestions. The research was conducted by analyzing secondary data and systematically mapping the existing knowledge of BI in 6 selected databases. For this purpose, 2108 articles were reviewed and in the initial review, 1274 articles were selected and 91 articles were approved by studying the abstracts. Finally, considering the exclusion criteria, 81 final articles were selected and analyzed. The results show that the most thematic coverage of BI in these journals was the specific topic of knowledge management and general topic was BI tools with 44.45%. The most used research method was descriptive-survey with 34.57%, the most purpose was practical with 82.71% and the highest level of analysis used was community analysis with 66.66%. Finally, research gaps were presented in the form of future research suggestions.

Over the last years, extensive research has been done in the field of blockchain technology and there are a growing number of areas to which blockchain is being applied, creating broad knowledge in this field. Classifying the subfields and identifying new topics and research trends in the area of blockchain would be of significant help to researchers. The present study aims to review and categorize studies on blockchain technology, identify subfields, and achieve a coherent view of its research process. using bibliometric analyses. The data used in this research has been collected from 423 articles in the Scopus database. Then, the bibliographic coupling analysis and keyword co-occurrence have been performed.According to the findings of this study, researches on blockchain technology are divided into 5 clusters: 1. Computer systems, 2. Financial sciences, 3. Smart contracts, 4. Data management and authentication, and 5. Electronic cash. In recent years, topics such as machine learning, trust, deep learning, risk assessment, edge computing, Ethereum, and consensus have drawn the attention of the research community. This research provides a comprehensive classification of the main concepts and topics discussed in blockchain-related research, designated to help researchers in this field choose a line of research.

IoT technology offers many benefits in health care and epidemic control and will greatly facilitate the process of continuous remote patient diagnosis and monitoring with wireless sensors and smart devices. This article aims to identify and analyze the applications of the Internet of Things to combat and control epidemics such as covid 19 disease. This research was applied in terms of purpose, which was conducted in two stages. First, by reviewing the theoretical foundations and previous studies through the method of reviewing texts, IoT applications in combating and controlling epidemic diseases such as covid 19 disease were identified; then, to confirm and prioritize the identified applications, these applications were provided to 23 experts from academic experts and experts in the medical field. IoT applications in the fight against and control of epidemic diseases such as covid 19, It has the dimensions of therapeutic applications (5 components and 9 indicators), Monitoring applications (4 components and 14 indicators), Information applications (2 components and 5 indicators), management applications (2 components and 8 indicators), prevention applications (7 components and 14 indicators). In the case of epidemics such as covid19 disease, The Internet of Things improves the quality of treatment and diagnosis, supports decision-making and monitoring patients 'vital signs, reduces hospital visits, and increases the ability to monitor and monitor patients' condition.

The growing evolution of social networks with intensified role in the business world and consequently in the advertising in one hand, and the ease of deception in such emerging media on the other hand, have increased the prevalence of deceptive advertising and false claims in the communication and commercial media. In this way, it is difficult for the audiences of social media ads to distinguish between the truthful and deceptive advertising and this can lead to distrust to social media advertising and reduced sales. In this regard, the present research aimed at providing a model for the perceived deception of social media advertising using grounded theory. For the purpose, in-depth and semi-structured interviews were performed among 15 people who had past deception related experiences in their purchase from social networks. Data analysis was undertaken using open coding method and MAXQDA 2020 software. Finally, the research conceptual model was designed based on 8 main categories, 15 sub-categories, and 71 concepts, and it was revealed that social media perceived usefulness and social media ads characteristics as “causes”, and media characteristics as “covariance” were effective on perceived deception. In this regard, customer knowledge and perceived trust were considered as “contingencies”. Consumer attitude was recognized as “condition”, and consumer characteristics was presented as contextual factor for such a process resulting in the occurrence of consumer psychological damage known as individual consequence of social media ads perceived deception.

Customer retention is an important issue for any organization, so finding a way to retain the customer is one of the critical needs of any organization. In this regard, the goal in the field of machine learning is focusing on the problem of accurate customer needs with a method based on extracting opinion and sentiment analysis and quantifying customers' emotional orientation.In the other words, the issue is designing a recommender system to provide appropriate services to customers, using their opinions and experiences. The proposed solution, by receiving and reviewing customers' opinions and experiences in the form of extracting variables such as user sentiment score for tweets, relation score, cosine similarity, and confidence factor, and considering groups of relevant features and registration ideas in the process of training and testing, the result is presented in the form of a banking service suitable offer. In order to provide a recommending solution, appropriate classification methods are used along with opinion mining methods and an appropriate validation approach, and the final designed system with a small error, in order to provide personalized services, will step in to help bank managers.Since currently there is no complete provision of banking services tailored to the situation of customers, so in this regard, this mentioned system will be very helpful.

Dashboards are an important tool for monitoring the performance of the organization and the decisions of managers, so their proper design in an integrated and orderly manner, taking into account the needs of customers and users and in accordance with organizational goals, is essential. The purpose of this study is to provide a framework for designing management dashboards with QFD approach. For this purpose, after in-depth study in literature review, a conceptual research model was proposed, then using a mixed exploratory research Approach, management dashboard design framework, was presented. The statistical population of the qualitative section included 40 articles out of 452 articles related to the period 2005 to 2020 and related to dashboard topics and its design, which was done by Meta-Synthesizing method. Also, in quantitative part of the research, in order to validate the proposed framework and screen the indicators, fuzzy Delphi technique was used. The statistical population at this stage was 18 managers in different fields and 12 IT specialists and thus the framework. The design of management dashboards consisted of 4 dimensions, 11 components and 102 final indicators.

Technological innovation in the financial industry created the financial technology ecosystem. With the advent of artificial intelligence, the technology and financial worlds are intertwined to allow smarter financial processes to enable managers to make smarter decisions. It is not a fixed method of using the machine and accurate prediction of the test results using the machine algorithms is challenging. Much research has been done on the specific management of the customer experience, but research on financial technology in the artificial intelligence and machine industry in the sense of constructing a theory that can create a customer experience is a subject that pays less attention to. . This article, by reviewing 75 articles and summarizing it in 41 research articles, has examined the subject of the present study. In order to predict the presentation of theory, research method is a fundamental theory. The purpose of this article is to cover the gap of studies through which a research path is studied and the field of financial technology and artificial intelligence is examined. Findings show that what is done in extraordinary networks can be divided into five main parts of innovation. The findings provide a good way to address some of the issues in financial and artificial technology research for knowledge management experience through the possibility of providing a customer performance model.