نشریه ارزش آفرینی در مدیریت کسب و کار
سال سوم شماره 2 (پیاپی 8، تابستان 1402)

The aim of this research is to identify the dimensions and components of acceptance of social systems of customer relationship management by professional users using Web 2.0 technology. The current research is applicable in terms of nature, qualitative in terms of implementation method, and of descriptive and thematic kind. The statistical population of this research was made up of 15 university professors in the fields of management, business and IT along with managers of digital business companies, selected by non-random sampling method. The criteria for selecting people are having a doctorate degree with more than 10 years of experience in digital businesses, having time, interest and ability to take part in interviews (a semi-structured) and fill the questionnaires. Also, MAXQDA 2020 software was used in data analysis. The identified factors were extracted in the form of 40 indicators, 8 components and 3 dimensions. Components and indicators of dimensions and components of acceptance of customer relationship management social systems included three dimensions; organizational, customer, and technological; which organizational dimension has three components (manpower, organizational culture, organizational structure), customer dimension includes three components (value creation, customer satisfaction, expectation of performance), and technologically has two components (social networks, content production).

The purpose of this research is to design a model of artificial intelligence competencies on organizational performance, taking into account business-to-business marketing capabilities. The research method is exploratory (qualitative-quantitative). In the qualitative part, it is considered with the Shannon entropy approach, and in the quantitative part, it is descriptive-survey. The participants of the present research in the qualitative part are faculty members and elites of artificial intelligence and marketing and management, which was conducted with 14 people based on the theoretical saturation rule, and in the quantitative part, the 540number of executive directors of industrial towns in northern Iran, of which 190 were selected as statistics sample. The data collection tool was semi-structured interview in the qualitative part, and researcher made questionnaire in the quantitative part. The method of data analysis was selected in the quantitative part of confirmatory factor analysis tests using SmartPLS software. The results showed that the mechanisms of artificial intelligence competencies have an effect on business-to-business marketing capabilities and organizational performance, and also the model of artificial intelligence competencies on organizational performance is confirmed considering the aspect of business-to-business marketing capabilities.

The purpose of this study is to examine how electronic customer relationship management affects marketing performance, with a particular focus on the mediating influence of product innovation and the significance of customer knowledge. The research method is a descriptive survey and applicable in terms of purpose. The statistical population of the study includes managers and supervisors of Dana Insurance's central office, branches, and representatives in Mashhad. Based on Morgan's table, 165 samples were simple-randomly selected. Data were collected through a standard questionnaire and then analyzed using structural equation modeling (SEM) through Smart PLS 3 software. The findings demonstrate that electronic customer relationship management significantly and positively influences product innovation development. Furthermore, product innovation development has a positive and significant effect on marketing performance. Additionally, customer knowledge positively and significantly affects both marketing performance and product innovation development. In conclusion, both electronic customer relationship management and customer knowledge play a vital role in positively and significantly influencing marketing performance through the development of product innovation.

This article aims to compare RW and PW models in profit forecasting for small and medium-sized companies. The research method is applicable in terms of its purpose, and it is an inductive and quantitative research in terms of the implementation logic and the nature of the data. Financial statements in the period of 2011 to 2021 have been used to collect data. In order to select the appropriate statistical sample, the systematic elimination sampling method was used. In this method, firstly, the small and medium-sized companies are identified, according to the number of employees and the nominal value of the capital, and conditions are defined for the selection of the sample, and those that do not have the mentioned conditions are removed from the sample. These conditions are determined according to the hypothesis test model and research variables. Also, in this article, the panel model and Eviuse software have been used to extract the proposed model from the principal component analysis approach and to fit the model to the observations. According to the results obtained from the analysis presented in this research, it can be seen that the new model provided for profit forecasting is more effective than the profit forecasting of RW and PW models, and this issue confirms the ability of regression models to forecast profit in the field of financial and profitability strategies for small and medium-sized companies.

The purpose of this research was to investigate the role of Flow theory in viral promotional advergames with an emphasis on sharing personal data and forwarding the games. Using a viral marketing campaign, 393 out of 765 participants clicked on the game link sent via email, But 288 people participated in the game, 141 people answered the questions, invited their friends to the game, or shared their personal data. Poisson regression was used to investigate the role of Flow theory on game forwarding, and logistic regression was used on sharing personal data through Eviews software. Players with intrinsic enjoyment and psychological Flow (dimensions of Flow) tend to invite more people to the game and share more personal data about themselves. Perceived reward value is also positively related to game forwarding behaviors, although not related to sharing personal data. That is, players seem to communicate more about the game when they have extrinsic motivation (rewards), but are less likely to share personal data with the brand. On the other hand, extrinsically motivated players still have significant privacy concerns. In contrast, Flow is positively related to sharing personal data, suggesting that fully immersed players tend to "lose themselves" and forget about their more conscious concerns and thus appear more likely to share personal data with the brand. Companies that want to capture customers' personal data should focus more on designing game elements than rewards in such a way as to stimulate the psychological Flow of the players.

The aim of this research is to present a model for the development of the tourism industry with an emphasis on the role of media management using a mixed approach. A mixed (qualitative-quantitative) approach has been used in this research. The statistical sample in the qualitative part included 15 professors and specialists and experts in communication, media and tourism: and in the quantitative part of the research, it included 200 managers and senior tourism experts in Mazandaran. In the first step of the research, the coding of the specialized research interviews was done using the qualitative analysis of the theme with MAXQDA v10.R150410 software. In the next step, the results of confirmatory factor analysis with Smart PLS software are presented. Then, the existing categories were leveled with the structural-interpretive method with MicMac software and the initial research model was designed. Based on the results obtained in this research, advertising, service quality, policy making, participation of local people, tourism culture, proper use of the environment, income generation in tourism destination and infrastructure facilities were identified as the main components that have an impact on the tourism industry. The results of the quantitative part of the research showed that the proposed model has a good fit and credibility for the impact of mass media on the development of the tourism industry.