فصلنامه مطالعات مدیریت کسب و کار هوشمند
پیاپی 33 (پاییز 1399)

Educational performance measurement through the identification and analysis of data extracted from learners’ activities can effectively result in the improvement of educational performance. In this Article, data of international learners was analyzed based on design science methodology and using data mining methods. In this regard, domestic and international research has been reviewed over the past decade and the academic and non-academic data of students were clustered into three categories: family, supportive, and academic behavior. After the validation of algorithms outputs and determining the number of optimal clusters in each category, clusters were labeled and analyzed. Analysis of labels presents the experience of success or failure of students and roots of effective performance in each cluster, and the labeling method proposed is a new and applicable method in most of the learning centers for segmenting and formulating the educational performance.

Today, on the one hand, the growth of web-based businesses and, on the other hand tense market competition, encouraged business owners to identify effective approaches to achieve customer loyalty and attachment. In the meantime, gamification has been vastly appreciated as a solution to engage customers more to the businesses. In this paper, a model of gamification is developed to shed some light on this area. Through qualitative approach and grounded theory as method of analyzing, some strategies are suggested to solve problems such as carelessness and lack of loyalty of audiences (customers). The model with all its component shape a strategic structure that can help web-based businesses to implement gamifications to gain a maximum results such as customer (audience) loyalty.

Multi-channel banking have attracted a lot of attention in recent years. So, the design of multi-channel banking services and the identification of the costs of each of these levels, it is an important issue for both banking professionals and researchers in this field. The main concern that this article deals with is how to design a hybrid channels services so that users can afford to use them. This study, by relying on the affordance theory and with the epistemological assumptions in designing the research method, qualitative data has been gathered. In order to collect qualitative data, we have used an in depth-interview with the experts of the banking industry. The results indicate that to improve the users ‘affordance of multi-channel banking, it is possible to consider 15 issues. Topics that can be considered by the user as well as the possible perceptual and lead to higher levels of use. The findings of this research can help experts and senior managers of the banking industry in the design of multi- channels services.

Shopping is an intrinsic part of people's daily lives. Due to the rapid growth of Internet technology, customer buying behavior has changed; And the Internet has created a public space where people interact with others, do their banking activities And shopping that have affecting multiple factors people's shopping intentions. The main purpose of this study is to identify the factors affecting online shopping intentions and to review and synthesis the results of research conducted in this area with a meta-analysis approach. The statistical population of the study is online shopping studies published in international journals between 2000 and 2018. To conduct this research, after reviewing and screening more than 635 articles related to online shopping, 89 articles were selected for meta-analysis. After reviewing the selected articles, a total of 24 variables with a frequency greater than 5 were identified that were selected as influencing variables on online shopping intentions. The results related to the effect size of the variables showed that the satisfaction variable with the effect size of 0.614 had the most impact and then perceived value and shopping experience had the most impact on online shopping.

in today's competitive world, pricing, as one of the 4 elements of marketing mix, plays a key role in the success or failure of companies. Based on theoretical principles, in value-based pricing, companies calculate the distinct value of their products from customer insights. The purpose of this research, which is based on design science, is to design and implement a system to help competitive pricing based on customer value by categorizing and analyzing customer emotions with the aim of maximizing profits. choice of this research is The hoteling industry , in which customer opinions and values play key rule. In this research, first, it has been tried to identify and classify important and valuable items in the minds of the customers of these 5-star hotels in Tehran by the method of topic modeling with LDA algorithm. Then, in each category, each customer's comments are tagged, and these comments processed with different text mining algorithms. Then the accuracy of the algorithms calculated. the deep learning algorithm with 0.9 accuracy had the highest accuracy of calculations. Finally, the analysis of sentiments with the available data was performed by the system designed in the previous step and acceptable results were obtained. The application of the proposed system is to identify the value of hotels in the minds of target customers over competitors and to help value-based pricing.

In today's fast-paced and highly uncertain environment where customer needs, technology, employee needs, community status, monetary systems, geographic location and everything are changing, companies cannot always rely on the production and supply of their existing products. A new product development strategy is an important activity that helps companies stay alive and make continuous improvements. However, most organizations consider these factors static and disregard these dynamics. Since the relationship between the factors contributing to the success of new product development has many dynamics and feedbacks, the systems dynamics tool is a useful tool to analyze in this area. In this research, in order to identify and analyze the dynamics of the factors affecting the success of a new product development, based on the theoretical background and opinions of industry experts, key variables in the field of new product development have been identified and the causal relationships between these variables are outlined. Accordingly, the system simulated in Tejarat Bank from 1392 to 1404. The results of the simulation and review show that considering the considered policies optimizes the new product development of regulatory financial products in the aforementioned organization.

Process discovery is a branch of process mining that by using event logs extracts the process model that describes the events’ behavior properly. Since, Heuristic process discovery algorithms are among the most significant and popular process discovery methods and due to the fact that the quality of outputs of these algorithms is heavily dependent on the quality of extracted dependency graph, in this paper for the first time, an approach to transform the problem of dependency graph discovery to a binary programming problem has been proposed and also, an objective function is introduced that simultaneously considers fitness and precision measures of output models. The weights dedicated to each of the measures are determined by means of a user-defined threshold. The mentioned measures are the most important metrics in assessing quality of output models of process discovery algorithms. Hence, in fact this approach focuses on improving quality metrics of output models. Moreover, by means of defining suitable constrains, the proposed approach is capable of involving domain knowledge in mining procedure, as well as guiding the result through whether the models that are more likely to be sound. This is depicted in a case study of a real company that is described in this paper. In the case study, the proposed approach has been applied to marketing event log of the mentioned company by utilizing the constrains defined according to domain knowledge and structural rules of dependency graph and at the end, the results were presented.

Changing caused by blockchain requires preparation, and this preparation can facilitate the conditions for acceptance and implementation of blockchain. Without examining the readiness of the industry to embrace blockchain, cannot expect the various areas of activity in the energy industry to receive a good or appropriate response from the implementation of blockchain schemes. Therefore, the main question of this study was to determine what framework could be devised for preparing different domains for acceptance of blockchain in order to evaluate the activity of oil and gas companies? This study investigates the concept of blockchain and derives a framework for measuring readiness for blockchain acceptance. Then the field of activity of the companies in the oil and gas sector was identified and these areas were evaluated on the basis of blockchain readiness indicators. The research method is descriptive and applied and the opinions of 15 experts were used for pairwise comparisons and assessing the readiness of companies in the oil and gas sector. Based on the results, the energy trading area at the level of sales to other partner companies is most likely to accept blockchain. After that, the energy trade comes second in sales to the customer. In third place is the development and design of applications in the field of blockchain-based energy services.

Strategic alignment of marketing and information technology is one of the managers’ priorities in recent years, that should be considered in order to achieve optimal performance in the field of digital marketing. Applying information technology in a proper way, in line with marketing strategies, to meet marketing needs is the main emphasis of strategic alignment between marketing and information technology. Despite the growth of investment in marketing technologies and the necessity of strategic alignment in this field, the literature on identifying the effective factors for strategic alignment of marketing and information technology has not been addressed yet. Therefore, the main purpose of the current research is to identify the effectiveness in strategic alignment of marketing and information technology in organizations hoping to improve the efficiency of IT investments in marketing. The research is conducted in two stages applying a mixed approach. In the first stage, qualitative approach and semi-structured interview tools are used to identify and extract the factors from the experts’ perspectives. In the second step, quantitative approach and BWM technique are used to weight and prioritize the identified factors. The statistical population of this study includes all academic experts in the field of research and senior executives with experience in marketing and information technology in organizations with digital marketing who were selected by purposeful sampling. The findings of the study include 7 factors of support and support of senior marketing manager, IT capabilities, partnerships / communications, governance, marketing competencies, skills / manpower and competitive factors, of which partnership / communication has the most weight and importance and competitive / environmental factors with the least weight were the least important.