فصلنامه مطالعات مدیریت کسب و کار هوشمند
پیاپی 28 (تابستان 1398)

The business ecosystem represents the collaborative and co-existence role of an organization in a larger network, whose recognition requires understanding the relationships among the members of the ecosystem. The aim of this study is to investigate the ecosystem of mobile communication in Iran using social network analysis technique. After a survey of mobile communications experts in Iran the boundaries of the mobile ecosystem is defined. Then, using snowball method, key actors of Iran's mobile communications ecosystem have been identified. After conducting interviews with the managers of the organizations, the data on the relationships among these actors were collected and using social network analysis (SNA) technique the network of actors was drawn up. Presentation of visual model of mobile ecosystem of Iran is one of the results of this research. The findings show that two mobile network operators in Iran have the highest centrality in the network and are considered as mobile ecosystem leaders in Iran. Analysis of the betweenness indicator shows that Communications Regulatory Authority after two network operators mentioned above has a more prominent role of betweenness in the network. Besides, among the main parts of the ecosystem, controlling and monitoring institutions have the strongest connections across the entire network and hence they are considered as the most powerful part.

Knowledge management (KM) makes noticeable changes in different levels of new organizations. Human components related to knowledge sharing and workers motivation are two important components in successful implementation of knowledge management systems. The aim of this study is to determine the situation of knowledge sharing and workers motivation, before and after of implementing knowledge management system and to present a framework for companies active in chilling industry. In this study, we extracted and examined 9 components consist of social interactions, culture, subjective norms, social media, efficient knowledge, helping enjoyment, trust, feedback, and perceiving the usefulness of social media. Also, a framework was presented for knowledge sharing and workers motivation and according to this framework the situation of these two components was indicated before and after implementation of knowledge management system in 2 companies active in chilling industry. As a result, this framework can indicate the situation of knowledge sharing and employees’ motivation before and after implementation of knowledge management in an organization and can help private organizations to improve their current situation. The results showed that employee motivation and knowledge sharing after implementation of KM in comparison with the previous one has a significant difference and improved. With the help of this framework, the chilling industry can examine the impacts of KM implementation on employees’ motivation and knowledge sharing.

Banks are endeavoring to gain more funds in a highly competitive environment. Given the higher costs of attracting new customers than retaining existing ones, most banks focus on maintaining their existing customers. Therefore, it is quite important for the banks to predict the customer churn in advance. In almost all related research works in banking, customers are divided into two types of static categories: “churners” and “loyal” customers. However, due to the nature of banking particularly in Iran, it is necessary to define churn in a dynamic manner in a variety of circumstances. In this study, the concept of state chain is introduced, which identifies changes in customers’ partial churn status over time. Using the sequence of chains and a combination of hierarchical clustering techniques as well as support vector machine, a model was developed to predict partial churn of bank customers. To construct a practical sample and to evaluate the prediction accuracy, 5 years of real European bank customers’ data as well as 3 years of customers’ data from three different Iranian banks were used. The results indicate a high level of prediction accuracy for the model in all 4 banks, particularly when longer sequences of states are used.

Nowadays, with the development of organizations and complexity of business processes, the management and control of such organizations are much more important than before. Business process models (BPM) typically capture some of the graphical notations, tasks, events, states, and logic of a business process control flow. Business process models are key artifacts in the development of information systems. While one of their main purposes is to facilitate communication among stakeholders, little is known about the factors that influence their comprehension by human agents. Among the various factors that affect the understandability and comprehension of business process modeling, this paper deals with two factors: a reader’s cognitive style and theoretical knowledge on business process modeling. The research examines the cognitive style index (CSI) differences and how styles relate to their scores in process model understandability. This study is a descriptive-survey research and was carried out in Mellat Bank’s Information Technology and Plan and Program Management by selecting 183 samples using a questionnaire. The results showed that a high percentage of respondents had an adaptive cognitive style (60 people, 33%), 85 respondents (46%) were at level 2 of theoretical knowledge about BPM and BPMN2.0, and only 6% were in level 4. The results also indicate a significant difference between intuitive and analytic samples with respect to the level of BPM understandability. There was also a significant relationship between theoretical knowledge of business process modeling and their understanding of the model.

Nowadays, some customers tend to buy clothes through social networks, and several factors affect this willingness. One of the important factors influencing people's willingness to buy clothing through social networks is social and cultural factors. Hence, this research seeks to examine the role of social and cultural factors in the purchase of clothing through social networks. In this research, a mixed method has been used. In the qualitative section, texts were transcribed and coded through literature reviews and interviews with active vendors in social networks. The components were categorized into 4 final categories and then presented in the original model. In the quantitative part, based on the original model, a questionnaire was prepared and distributed among 385 apparel buyers in the networks. For data analysis, structural equation method and to examine the mediating role, Sobel test were used. The results showed that friends' recommendations, affirmation of others, and social conditions have a significant effect on the trust of individuals in social networks, and the trust of individuals has a significant effect on the consumer's willingness to buy clothing through social networks.

Uncertainty is inherent and inevitable component of projects. Research literature suggests that Information Technology (IT)projects and, in particular, outsourcing of these projects are at high risk. Therefore, according to the importance of this field, this study aimed to identify and prioritize the risks of outsourcing IT projects. Initially, by reviewing the research, a list of identified criteria was provided to the company's experts. Then, the criteria were selected after the scrutiny case study and according to the experts' opinion with the fuzzy Delphi method. In the next step, based on SWARA method, the final weights of the criteria were obtained. Also, after reviewing the literature, a list of important risks for outsourcing IT projects was identified. Then, for the prioritization of the identified risks, ARAS gray method was used. The results showed that the criterion of sharing knowledge and experience as the most important criterion and loss of resources of competitive advantage was identified as the most important risk.