فصلنامه مطالعات مدیریت کسب و کار هوشمند
پیاپی 48 (تابستان 1403)

Crowdfunding is an effective way to achieve the non-profit goals of the charities which can be expanded using information and communication technology. In this regard, this study was conducted with the aim of providing an online donation intention model for collective financing of charitable institutions in Iran. The current research is an applied-developmental research in terms of its purpose, and it is considered a cross-sectional survey research from the data collection point of view. The statistical population in the qualitative section includes managers of charity institutions and university professors. Sampling was done using a purposeful method and theoretical saturation with 10 interviews. In the quantitative section, the views of 357 benefactors were used. The data collection tool is a semi-structured interview and a researcher-made questionnaire. To analyze the collected data, qualitative thematic analysis and partial least squares were used. The research findings showed that the technical infrastructure facilitating conditions, the quality and transparency of the website information, the security of the site and the application, and the preservation of privacy affect the perceived risk. Perceived risk affects the expectation of effort and the pleasure of helping others and leads to the expectation of performance and social influence. Finally, online donation intention is strengthened through trust.

Today, digitization is considered as a requirement for all financial and monetary institutions and markets, and the banking industry is no exception. However, moving to digital banking is not an easy task for banks, and the digital revolution has become a major challenge for this industry. In order to keep their business stable, banks need to launch digital platforms and create robust ecosystems around them that have the ability to evolve and adapt to the challenges caused by the chaotic and unpredictable environment in which organizations operate and the increase in internal inefficiencies. Therefore, this research was conducted with the purpose of modeling the generative mechanisms of the evolution of Iran's digital banking ecosystem. For this purpose, the qualitative content analysis method has been used. A semi-structured interview has been used to collect information using the opinions of experts in the field of digital banking. The analysis of the conducted interviews led to the identification of 674 themes, 181 codes, 59 subcategories, and 20 categories. The results of the research show that there are external factors, including cyber-attacks, political and governance obstacles, the increasing progress of communication and information technology, changes in the competitive environment, and conflicting investment relationships in the financial and banking fields, and internal factors, including the absence of strong security infrastructure in the network and weak security, weakness in digital human capital, changing needs and demands of actors, weakness in the traditional business model, and the lack of a management perspective regarding the growth of digital banking and regulatory and legal requirements, are the stimuli for the co-evolution of the elements of the digital banking ecosystem, which occurs with the activation of reinforcing and transformative generative mechanisms. The consequences of the evolution of the digital banking ecosystem can be classified into three levels: users, owner, and society.

This study aimed to investigate the effect of brand interaction through social media on brand loyalty through brand equity. The research is a descriptive research of the correlational type in terms of practical purpose and based on the method. The statistical population of this research includes the customers of three Iranian brands, My, Cinere and Callista. The size of the population is considered unlimited and the G-POWER tool was used to determine the sample size and the statistical sample size was calculated to be 199 people. A simple random sampling method was chosen for data collection and the data collection required in this research was done using a localized standard questionnaire. In order to confirm content validity, CVI and CVR and expert panel were used. In order to determine the reliability of the questionnaire, Cronbach's alpha coefficient, combined reliability and homogeneous reliability were used. Because the data do not follow normal modeling; Therefore, structural equation model and partial least squares method and PLS software were used for hypothesis testing and path analysis. The results of this study showed that customer interaction with the brand through social media can have a positive effect on brand loyalty. Also, brand equity was a positive mediating factor in the relationship between brand interaction and brand loyalty. Among the three cognitive, emotional and behavioral paths, the behavioral path with a path coefficient of 0.630 is the best path in influencing customer interaction with the brand on brand loyalty.

New technologies in the field of Industry 4.0 enable companies to enhance their business processes and customize products and services through the generation of new knowledge. The creation and sharing of this new knowledge depends on both the optimal use of Industry 4.0 technologies and interactions along the value chain. However, achieving business benefits is highly dependent on human resources and their digital skills and competencies. Therefore, companies approaching the Industry 4.0 paradigm should consider these new technologies as tools that facilitate the creation and sharing of new knowledge. They should pay attention to the digital skills and competencies required to manage this technological transformation and enhance internal competencies. The purpose of this research is to combine the results and findings obtained from qualitative studies, providing new insights from previous research. In this study, a meta-composite approach was used to investigate qualitative case studies, examining the relationship between knowledge management and Industry 4.0 capabilities in organizations. The results show that knowledge management capabilities in the field of Industry 4.0 are examined in two dimensions: business models and organizational innovation. This research also emphasizes that in order to address organizational challenges, knowledge management strategies and the maturity level of Industry 4.0 technologies within organizations must be understood.

The purpose of this research is to identify the main components and dimensions of digital content marketing according to the conditions of Iran and to present a model using a qualitative method based on the Grounded Theory approach. Data were collected through semi-structured in-depth interviews with experts. These experts included university professors in the field of digital content marketing and managers and activists of advertising and digital marketing agencies. Using targeted sampling and after conducting 15 in-depth interviews, theoretical saturation was achieved after the implementation and analysis of interviews and open, axial, and selective coding. The results showed that digital content marketing is realized by these conditions. Causal conditions (Internet development, ease of use, popularity of cyberspace, ease of communication with customers, virtual network features, The appeal of Digital Content Marketing, changing customer behavior, changing current structures), contextual conditions (personal characteristics, social characteristics), intervening factors (technical limitations, increasing competitors, lack of access, unawareness, severity of the spread of Covid-19), central category (Digital Content Marketing), strategies (make it enjoyable, increasing participation, providing various services to users, using various methods to increasing audience, exchange of information, infrastructure improvement, audience-friendly style, customer orientation), and consequences (market expansion, increasing profitability, groundwork for brand creation). The results indicate that the research model is acceptable level.

The effort of this article is to solve one of the main problems in the field of banking, which is closely related to the field of information technology. The combination of the management discussion of this topic with the field of information technology will be one of the important topics in the field of information technology management. The main goal of this article is the clustering of bank customers.At first, all customer characteristics were extracted from the bank's database, which was randomly extracted for 900,000 customers, which will be provided as input to the proposed method of this article. All the characteristics of these customers were extracted and 10 characteristics (except four characteristics of the LRFM method) were listed using the opinions of experts. The proposed method should be able to choose among these 10 features for clustering customers, which results in more resolution in clustering. Due to the high number of cases of this problem, it is not possible to do it manually, and the proposed method tries to provide a separate model for clustering for the customers of each bank by examining different cases. Also, the problem of choosing the right value for the number of clusters in the K-means method is solved by the method proposed in this article. The results show that it is better than the basic RFM and LRFM methods.Keywords: relationship management with bank customers, clustering, RFM model, LRFM model, particle swarm algorithm, K-means method.

The digital world provides many opportunities for marketers to reach customers. However, in the fast-paced world, finding new and innovative ways to advertise and sell products and services is very important. Due to the advancement of artificial intelligence and its development in the field of advertising and sales, professionals now have the tools to completely redefine the current understanding of branding, marketing, advertising and sales. The growing popularity of the Internet and the increased use of mobile devices are generating massive amounts of consumer data that feed artificial intelligence-based systems. This research is a type of mixed research with a qualitative and quantitative approach, which is a survey descriptive study in terms of its purpose, application, and in terms of data collection. The statistical population of the research was managers and experts in the field of digital marketing and IT in the field of advertising and sales, who were selected using the snowball sampling method. In the qualitative part, the tools for collecting information were library and articles review, interviews, and in the quantitative part, questionnaires. In the qualitative part of the data analysis method, using the theme analysis that was compiled with MAXQDA software and using the coding method, and in the quantitative part, the analysis method was based on Kendall's correlation test. According to the results of the research, 7 main themes, 22 sub-themes and 44 codes were discovered, which included the consequences of using artificial intelligence and machine learning in advertising and sales

Fintech and its entrepreneurial opportunities have the ability to play an effective role in the development of the financial industry. Therefore, it is necessary to make a correct and effective policy in this area to identify its probable future. This study is exploratory in terms of purpose and practical in terms of orientation. Interviews and questionnaires were used to collect data. 28 drivers were extracted by reviewing the background and interviewing experts. In order to screen the propellants, expert questionnaire and fuzzy Delphi method were used. Then the propellants screened were ranked through the priority assessment questionnaire and the developed COPRAS technique. The two drivers of the development of smart contracts in the financial industry and the tendency of financial institutions towards open innovation had the highest priority and were used to write research scenarios. Based on these two drivers, 4 scenarios of the era of pristine opportunities, the era of conservative managers, the era of dilapidated infrastructure and the ice age were developed. Then, using the MABAC technique, the scenario of the age of dilapidated infrastructures was selected as the possible scenario of the research. Research proposals were proposed based on priority drivers and possible scenarios. Government support, providing sufficient funds in order to create the necessary infrastructure for the development of smart contracts by banks or establishing a cooperative relationship between banks and financial institutions, fair legislation, development of regtechs, creating compatibility between current systems with new technologies were the most important practical proposals of the study.