فصلنامه مطالعات مدیریت کسب و کار هوشمند
پیاپی 42 (زمستان 1401)

Many organizations employ knowledge engineers to acquire tacit knowledge from experts using the principles and techniques of knowledge acquisition. The main purpose of this study is to provide a comprehensive pattern of knowledge acquisition in institutional organizations. For this purpose, Semantic mapping (one of the research methods in Soft Operation Research) has been used; and using a graphical arrangement that shows the main ideas and relationships between the meanings of words, a kind of visual classification of knowledge acquisition is proposed. In this regard, first, the central concept was examined and related micro-concepts including 15 micro-concepts were identified and recorded in the pattern. These included “agreement and relationship of knowledge acquisition system with other organizational systems”, “connection of knowledge acquisition system to knowledge management cycle”, “officials and trustees of knowledge acquisition”, “special characteristics of institutional organizations” and “basic layers of the organization”. Each of these concepts was then considered a central idea, and the development of branches to extract the micro-words associated with each concept continued, sometimes up to four layers. The total number of concepts drawn in this pattern were 183.Keywords: Knowledge Acquisition, Tacit Knowledge, Institutional Organizations, Semantic Map, Cognitive Mapping.

For today's businesses, the move to digital transformation and the use of disruptive technologies for survival and growth is inevitable and can create many innovative opportunities for them. In order for organizations to move in this direction and design a roadmap for their digital transformation, they must first have a comprehensive and holistic understanding of the current digital situation of themselves. Assessing digital maturity can be the first step in developing the roadmap of digital transformation. Since digital transformation is not a one-dimensional issue and involves many dimensions in the organization, so identifying and paying attention to these dimensions can make it easier to plan for the digital transformation of the organization. This is possible with the help of digital maturity models. This study was conducted to provide a framework for assessing digital maturity. The research method used here was a systematic literature review. Dimensions of digital maturity in this framework include "strategy", "governance and leadership", "business model and ecosystem", "culture and skills", "process", "employee experience", "customer experience", "technology", "data" "Innovation" were identified and then 69 indicators related to each dimension were introduced.

Social networks have facilitated the online customer engagement of the marketing industry. This research aims to investigate customer engagement in Iranian cosmetics brand pages on Instagram which has been done by quantitative content analysis. The statistical population was all available cosmetic brands, from which five popular brands (May, Calista, Inley, Cinere and Amoutia) were selected and 60 posts analyzed from each brand page. The results indicate that there is a positive and significant relationship between the type of content (Incentive, Promotional, information and entertainment) at the significant level of p <0.001 and customer engagement. Also, there is no significant relationship between content and Interactivity and negative valence with more engagement. Between the Vividness of the posts and the positive valence, the hypothesis was partially supported and indicated its partly impact on customer engagement. The results of multiple regression analysis for the number of likes and comments in the posts show that the total variance of the model and R-squared for these two are 0.668% with F = 15.372 and p <0.001 and 0.410% with F = 7.590 p <0.001, respectively and shows its significance. The adjusted R-squared also shows that 66.5% of the changes of the dependent variable (likes) and 40.6% of the changes of comments are only the result of the effect of the independent variables of the research.

The industrial revolution has affected the economy and various industries. Technology is the main factor of the fourth industrial revolution, which has a significant impact on tourism. The development of information technology and intelligence has led to the transformation of the tourism industry and creates a lot of competition and makes many developers of the tourism sector to engage in real innovations to attract tourists. Therefore, to investigate the smart economy in tourism, this study tries to evaluate the indicators of the smart tourism economy in Iran by using a model based on the best-worst multi-criteria decision-making method. For this purpose, first, by studying the research literature and the opinions of experts in the field of tourism, the effective dimensions and indicators of the smart economy in the tourism industry have been determined. According to experts, the best-worst method, increasing attractions and activities is the most important criterion in the economy of smart tourism. In addition, creating new markets for selling domestic products and using information technology are placed in the second and third priorities, respectively. The results of this research show that managers of the tourism industry should focus on increasing attractions, introducing services related to tourism information through smart tools, using online markets or e-commerce and making more use of the information technology platform.

Hundreds of thousands of new businesses are created every year around the world, and it is estimated that about half a billion people worldwide are actively trying to start new businesses. Therefore, creating a new business is very important; because it creates new job opportunities, produces new technology and creates wealth and value in society. However, a large percentage of small businesses fail in the early years of their existence. Meanwhile, in the field of superior technologies, due to the high dependence on changing technology and also the need for high initial capital, firms are facing a more difficult situation. The purpose of this study is to provide a rule based database to determine the success and failure of IT startups in Iran. For this purpose, using research conducted in this field and also receiving the opinions of experts through a semi-open questionnaire, we identified 36 factors affecting the success and failure of startups and classified them into 5 categories. In this research, the method of fuzzy inference system by Mamdani method has been used to analyze the factors. The statistical community is the founders of Iranian startups as well as professors and business professionals;30 founders of successful Iranian startups have been randomly selected as a sample. The results show that team-related factors and team characteristics have the greatest impact on the success and failure of startups.

The current research was conducted with the aim of identifying the effective drivers for the development of virtual social networks in identifying entrepreneurial opportunities. Virtual social networks, as a network of human communication, include WhatsApp, Instagram, Google Plus, LinkedIn, Facebook, Twitter and other platforms that include many opportunities in the field of entrepreneurship. The research was applied in terms of its purpose, and in terms of the nature and method of data collection, it was analytical-exploratory and of a mixed approach, in which Content analysis method was used in the qualitative part, and the MicMac method was used in the quantitative part. The intended sample in the qualitative section includes 9 experts, and in the quantitative section, it includes 20 experts who are proficient in the subject, who were selected by snowball sampling. The method of data collection in the qualitative part included library studies and interviews, and in the quantitative part it included the MicMac questionnaire. At the stage of library studies and interviews, 18 primary variables were identified, and 16 variables were used for quantitative analysis by adjusting the opinions of experts. After analyzing the data obtained from the MicMac questionnaire, 10 variables were determined as effective drivers. The results show that the most effective factor include; The size of virtual social networks and the presence of business contacts in virtual social networks and the least effective variable include; Transfer of information and existence of information resources in virtual social network.

Due to the advancement of technology and communication, traditional educational management methods aren't answer to our educational needs, in order to improve the educational system by using new technologies. The purpose of this research is to design a model that adapts the content of skills training courses based on the needs of the labor market and the ability of the learner using smart contracts. The general method of this research is the Design science, which uses a Meta-synthesis method to design the model and a questionnaire is designed to evaluate the model. This questionnaire was completed by a statistical sample of 30 people, from the statistical population that includes teachers of technical courses, managers of the vocational education department of education organization and persons for compilation of skill courses. This statistical sample was selected by purposive sampling method.Questionnaire information was processed by Descriptive statistics and Statistical inference using the one sample T-Test method. The introduced model that is designed using smart contracts technology may be very useful for the effectiveness of skill training and the results of statistical analysis shows that the proposed model has a very high degree of validity.

With the importance of lending in the banking industry, it is very important to use the indicators affecting credit to decide on lending. The purpose of the present study is to identify and prioritize the effective features in customer accreditation using the viewpoints of bank experts in Kerman and to compare them with existing indicators in models extracted from Meta-Heuristic and Artificial Intelligence methods. The aim is to find out whether there is a match between the human views that arise from knowledge and experience and the views of artificial intelligence that look at the problem as black-box modeling. Required data were collected by questionnaire method and Quantum Binary particle swarm optimization algorithm and analyzed by Delphi. The results show that the selected indices have 80% overlap between the two methods. Due to the results of research and high accuracy of artificial intelligence techniques, it is suggested that in order to give credit to customers in banks and financial and credit institutions, to consider a higher weight for these indicators.

The emergence of a wide range of digital technologies has fundamentally changed the nature, process and outcomes of innovation. Researchers emphasize the distinction between digital innovation and traditional innovation and consider it necessary to theorize in this field due to the novelty of the concept of digital innovation. In this research, in an inductive way with the aim of conceptualizing and identifying the main dimensions of digital innovation in industrial organizations, first, using the systematic literature review approach, related articles were examined in the period from 2014 to 2022, and 48 articles were selected for analysis. Then, using the grounded theory approach, open, axial, and selective coding procedures were performed. According to this, the main dimensions of digital innovation were categorized in the form of a paradigm model include causal factors (13 categories under the 4 main dimensions of digital industrial platform and technology management, digital innovation ecosystem management, intelligent processes, digital structure and organization), contextual factors, intervening factors, strategies, and consequences. Also, by reviewing the definitions and identified dimensions, a novel definition for digital innovation in industrial organizations was presented. The resulting theoretical framework, in addition helping further conceptualization of this phenomenon, can be used in the design of organizations' digital innovation maturity models.