فصلنامه مطالعات مدیریت کسب و کار هوشمند
پیاپی 21 (پاییز 1396)

In recent years, we have observed the rapid development of social media, which has drastically transformed the way in which people communicate and obtain information. Nowadays, customers on e-commerce sites mostly rely on comments posted by customers, producers, and service providers. In this research, in the first part the application of network mining is extracted using content analysis method in different dimensions of Political, Social, Economic and Technical (PEST). Then, in the second part, the applications used in two technical and economic sections are selected and using surveying expert opinion and statistical tests the more important applications have been identified among these applications. In the next step, to prioritize the applications using Analytic Hierarchy Process (AHP), paired comparisons were performed and by distributing pairwise comparison questionnaire data was collected and then the applications were ranked in order of priority. The results showed that in the economic dimension, the discovery of fraud, the discovery of the needs and interests of customers, and in the technical dimention improving e-commerce and identifying network traffic have the highest rank

Virtual communities are very impressive in the activities associated with the business and broad access to consumers. In this regard, providing the antecedents and consequences of consumers' participation in virtual communities can be effective in the competitive environment from the cognitive aspects of consumer behavior. The purpose of this study is considering the antecedents and consequences of consumers’ participation in virtual communities. The research method was mixed one in a way that in the qualitative section semi-structured interviews with 14 experts was performed and after analyzing the results using the content analysis technique, the designed model in the sample size of 384 persons was tested quantitatively. The results of this study showed that individual and social backgrounds, services provided by the web site, our willingness, attitude and intentions have a significant impact on participation. Considering the implications of participation, we-intentions to participate in virtual communities have a negative impact on communication with family and friends, as well as less use of other media, but increases consumer information.v

In recent years, the growth of social networks and, consequently, the increasing content of these networks have led people to use others’ opinions to make decisions for the purchase and use of products, services or even political choices. Given the fact that users' comments are textual and their reading and summarizing is timely and difficult, the automation of the extraction of opinions and sentiments of users' comments is one of the suggested solutions for online sales sites to provide more efficient services to customers for better decision making. Sentiment analysis or opinion mining is a process where people's opinions, feelings and attitudes are extracted in relation to a particular subject and are recognized as a branch of the text mining. The results of sentiment analysis can be used in recommender systems to provide more effective shopping suggestions. Information derived from the opinion mining can be used in a variety of fields such as libraries for better choices and purchases based on the users' real opinions. In this research, a system for automatically categorizing the sentiments expressed in the opinions of the buyers of the Amazon book website is presented. The system is designed using ensemble voting models to analyze the sentiment of Amazon users' comments. For all analyses, Python text mining packages are used. In ensemble method two methods are used: majority voting and weight-based voting. In the weighting method, a greater weight is assigned to a classifier by higher accuracy. By comparing the performance of the results, the weighting model is chosen as the final model for making the sentiment analysis. Results show that the proposed system can automatically classify positive and negative comments with an accuracy of over 80%.

Organizational Dashboard is a tool full of rich indicators, reports, and graphs that dynamically acts to help managers to control the performance of their organization at any time. For data productivity, using Business Intelligence(BI) logic is inevitable. BI is a system in which different, dispersed and heterogeneous data of an organization is integrated and through the establishment of analytical database for managers to make decisions. This study is a developmental and practical research. After reviewing literature and interviewing with 38 experts in universities and organizations, organizational dashboard developmental factors with the business intelligence logic were presented that were 357 codes. Using content analysis and focus group methods, these codes were grouped into 24 based content and 7 organizer contents. In the next step, in two distinct stages, using interpretative structural modeling method, the modeling of the basic themes and the organizing content separately and considering the consistency of the two models, their integration and creation of the final model of evaluation of the development of organizational dashboard with the logic of business intelligence has been made. This can be a precise roadmap for organizations to design and implement this system

For about two decades, the different organizations have begun offering various types of electronic services in the world and many researchers have spoken about governments using multiple approaches to become smarter. However, there is no consensus and no precise definition of the smart government, its components and dimensions. On the other hand, the high cost of implementing macro-scale e-service projects encourages governments to initially model e-government and control costs. Hence, over a decade, various models for the development, delivery, evaluation, and other dimensions of e-government have been presented and discussed, but because of the novelty of the smart government as the new generation of e-government, no specific framework and model are provided. The purpose of this research is to identify the components and dimensions of smart government and their classification. Therefore, it tries to use the meta-synthesis method to systematically study scientific documents related to the discussion and to express the dimensions of the smart government. Finally, by using the Shannon entropy method, the indices of each dimension are ranked according to previous studies. The result of the research shows that the smart government has six dimensions: 1. Smart management and leadership; 2. Infrastructure and smart technology; 3. Smart interaction; 4. Smart service; 5. Smart environment; and 6. Smart security. The results of the research show that the proposed model is more complete than other studies, and it has a specific category. This research is the first research to rank the indicators and dimensions of smart government.

In this study, focusing on the subject of the study, the site of Tebyan Institute of Cultural and Information Science has been carefully analyzed using subject clustering. Using clustering and text mining, while identifying outstanding and insignificant clusters, the importance of this issue among the users of Tebyan network has been discussed. The results indicate that due to the cultural and information nature of Tebyan social network, searching the reading and study keywords will provide most relevant results in thematic category of culture with 26% and 18%, respectively. Due to the virtual and electronic nature of Tobayan network, it is necessary that the electronic education section of this site cover the shortage by generating more educational contents. Despite the high number of results in the thematic category of society, the results in the whole network seems to be very low for reading (only 952 and 1199, respectively, in the search for key terms of reading and study), and this requires more planning for promoting the importance and value of reading issues in the society by Tebyan. The international community brings modern technology to the society in the light of new developments and in the meanwhile, if anyone is left behind in the knowledge of the day, he has no opportunity to compensate for the lost resources; therefore, (s)he should be deeply thought-out and broadly planned for the importance and value of people to read, study and promote, even on social networks.