Data science, intelligence and future analysis
Mohammad Amin Yalpanian; Iman Raeesi Vanani; Mohammad Taghi Taghavifard
Abstract
The ever-increasing development of digital technologies has brought about significant changes in business performance. The increase in the number of published articles on this topic also shows the special attention of researchers in information systems, business management, and innovation. While digital ...
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The ever-increasing development of digital technologies has brought about significant changes in business performance. The increase in the number of published articles on this topic also shows the special attention of researchers in information systems, business management, and innovation. While digital changes are inevitable in the digital age, previous research has been limited to a specific domain. This research aims to identify key themes and macro topics through a systematic review of 201 articles from 2018 to 2023 through two high-quality databases (Scopus and Web of Science). First, using thematic analysis, the main themes are identified, and their relationships are investigated from the perspective of digital technology development. In the next step, by using topic modeling (Latent Dirichlet Allocation), the major domains of the impact of these technologies will be investigated, and future research trends will be identified using the scientometric approach. The innovation of this research is designing a thematic network through in-depth text review and text mining analysis, which leads to a better understanding of the relationships between critical components. In the last step, recommendations are given to researchers and managers to conduct future research.
Mohammadreza Taghva; Iman Raeesi Vanani; Zohreh Dehdashti Shahrokh; Mana Shakerin
Abstract
IntroductionToday, the strategic importance of information is obvious to all businesses. In addition, the competitive environment of each company is constantly changing. The Spring 2020 event was a testament to this fact. Due to the health and economic crisis caused by the emergence and spread of an ...
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IntroductionToday, the strategic importance of information is obvious to all businesses. In addition, the competitive environment of each company is constantly changing. The Spring 2020 event was a testament to this fact. Due to the health and economic crisis caused by the emergence and spread of an unknown virus, various teams found it difficult to convey their advertising messages, campaigns and services. They could no longer rely on their assumptions about what customers buy and why and how they buy it (Johnson, 2020). Access to rich information for businesses that operate both in the field of e-commerce and in the retail sector of perishables is crucial. These products have a short life cycle and should be consumed faster. If the market intelligence model is properly designed for such businesses based on the supply chain of perishables, then managers will be able to correctly identify their customers, competitors and the business environment and run their business more successfully and grow as a result. In Iran, not much research has been conducted to provide a model that simultaneously addresses the aspects related to supply chain, market intelligence and online retail of fast-moving (perishable) products. and each of the models or patterns in the literature address one aspect of the issue. If market intelligence is at the service of the supply chain, it can create opportunities to reduce costs and increase customer satisfaction through collaborative decisions. Based on what was presented in the introduction, the main question of the research is extracted as follows.Research QuestionRQ1: what are dimensions and components of Market Intelligence model in the supply chain of FMCG (perishables) products in online retailing.Literature ReviewThe concept of market intelligence has attracted a lot of attention in recent years. Various experts have defined market intelligence in some way: market intelligence is formed through detailed and accurate information about business environment in general, consumer needs and preferences, technology and changes in the business environment that can affect buyers. (Hedin,2014). Market intelligence enables small businesses to identify market attractiveness and create value and drive innovation (Del Vecchio, 2018). 2.1. Supply Market IntelligenceThe relationship between market intelligence and supply chain can be found under concept of supply market intelligence. (SMI). Market intelligence is a process for gaining competitive advantage and reducing risk by increasing knowledge about market dynamics and includes market intelligence, process and price benchmarking to evaluate sourcing performance, competitive sourcing identifying strategic opportunities in markets that lead to lower prices ,emerging supply channels and markets (Hanfield,,2010). 2.2. Organization Information Processing Theory (OIPT)One of the theories which is the basis for market intelligence and business intelligence is organization information processing theory (OIPT), which was introduced by Galbraith in late 1973. According to Galbraith, when uncertainty is low, organizations can be managed by relying on rules and programs and hierarchical referrals but in situations where the organization is facing high uncertainty, the need for information processing increases and there are two general solutions in this regard: organizations must either reduce the need for information processing or increase information processing capabilities by investing in information systems (Galbraith, 1974).2.3. Market OrientationThe root of market intelligence can also be traced to a concept called market orientation. The concept of market orientation has been developed from two perspectives: behavioral perspective and market intelligence perspective. According to Kohli and Jaworski, market orientation is a set of behaviors or activities related to market intelligence, dissemination of market intelligence among different units of the organization and responsiveness based on it (Kohli & Jaworski, 1990). According to Narver and Slater, Market Intelligence has three main components: customer orientation, competitiveness, and cross-sectoral coordination. In short, market orientation states that customer orientation helps companies to understand the needs and wants of their customers and take basic steps to meet them. Competitiveness will enable companies to create more value for customers than competitors and thus achieve a sustainable competitive advantage. The role of market intelligence is in collecting, analyzing and disseminating this information (Narver & Slater, 1990). MethodologyIn this study mixed method approach has been adopted. First, in order to achieve the research objectives and identify the indicators of market intelligence in the supply chain of perishable products (fruits and vegetables), the seven-step approach of Sandelowski and Barroso’s (2003) meta-synthesis method was used. The statistical population covers the research published in 3 databases of ProQuest, Science Direct and Google Scholar during the period time of 2010-2021 for keywords of market intelligence and supply market intelligence. For other keywords, different period time was applied. In the second part, to obtain additional indicators, semi-structured interviews were conducted by an exploratory approach. In this regard, interviews were conducted with experts in the field of retail of fast-moving and perishable products, service providers of fruits in Iran’s e-commerce environment. ResultsIn order to achieve the most relevant research to enter the meta-synthesis process, criteria for inclusion and exclusion of research were considered.. A total of 1654 studies were reviewed, of which 276 studies had related topics, and with elimination of duplicated studies, There were 202 researches available, of which 113 had abstracts, 48 had content and 31 had appropriate quality and analysis method. In order to combine the findings of the research, the approach of Sandelowski and Barroso has been followed, in the sense that after careful study of studies and articles, codes have been identified from their texts and the researcher has formed a classification based on it and Similar classifications were placed on the topic that best described it. The sample of Codes, concepts and category identified in meta-synthesis phase is illustrated in table 1.Table 1. An example of coding in meta-synthesis processCodesConceptCategoryCustomer Demographic InformationCustomer InsightCustomer & Market Insight Customer personalizationCustomer interests and NeedsFocus group sessions with customersCustomer EngagementCall Center interaction with customerCustomers surveysThe coding process at the meta-synthesis stage led to the identification of 5 categories (supply chain intelligence, market and customer insight, business intelligence, social business intelligence and competitive intelligence), 23 concepts and 5 categories.In the second phase of the research, the new items identified in the theme analysis of semi-structured interviews with experts which included Order, Co-Branding, Customer Club, and Financial Issues. By comparing and combining the dimensions and components obtained in the two qualitative stages of the research, the market intelligence model for perishable products in the field of online retail was presented in the form of the model presented in Figure 1. Figure 1. Supply market intelligence (research model) In order to validate the model, the conditions for establishing reliability and validity (convergent and divergent validity) and fit indices must be met according to Table 2. Table 2. Conditions for establishing Reliability & ValidityindicatorsAllowable ValidityReliabilityComposite Reliability > 0.7 and Cronbach's alpha>0.6Convergent validityLoading Factor >0.5CR>AVEAVE>0/5Rho_A>0/6Discriminate validityAVE>MSVFit IndicesGOF>0/36SRMR<0/1NFI>0/9Descriptive statistics and central indicators such as mean, standard deviation, skewness and kurtosis for each of the components and dimensions and indicators are reported in the above table 3.Table 3. Sample of Descriptive indicators and first-order confirmatory factor analysis The reliability index was evaluated by measuring the factor loads and the reliability of the latent variables was evaluated by the compositional reliability . Cronbach's alpha results, compositional reliability and are shown in Table 4.Table 4. Sample of Cronbach's alpha results, composite reliability and convergent validityDimensionComponentsCronbach’s AlphaCA>0/6rho_A>06Composite ReliabilityCR>0/7Average variance extractedAVE>0/5Supply chain intelligenceSuppliers club & insight0/6920/7150/8650/762Service Provider Portal0/9250/9260/9380/656Competitive intelligenceResponse to Competition0/8440/8480/8950/682Tactical competition0/8910/8940/9330/822Customer & Market InsightCustomer Engagement0/9000/9000/9380/834Social Business IntelligenceCompetitive insight in social network0/7160/7160/8760/779Social Customer Interaction0/8450/8450/9280/866According to Table4, the Cronbach's alpha value for all variables is greater than the appropriate limit of 0.6 . Also the value of the compositional reliability coefficient for each variable is more than the desired limit of 0.7. In this model, the convergent validity of the model variables is all higher than 0.5, all of which are at an appropriate level. ConclusionIn this study, the aim was to develop a market intelligence model in the supply chain of perishable products in the field of online retailing. Handfield (Handfield, 2006), introduced the supply market intelligence concept and considered business intelligence and market intelligence as the information drivers of supply chain processes. According to the meta-synthesis of literature and analysis of semi-structured interviews with 14 experts, the components of each of the proposed dimensions were identified and social business intelligence and supply chain intelligence were identified as new dimensions of supply market intelligence model. In fact, a complete and optimal supply chain should include those activities that the customers value and are willing to pay for the resulting services or products. Therefore, understanding customer behavior is very important. What is very important in the supply chain is that supply is aligned with demand across the supply chain, so a better understanding of suppliers and end customers is the best way to reduce costs in the supply chain., As a summary, the identified dimensions and the importance and role of each in the supply market intelligence model is discussed. - Supply chain intelligence. In this dimension, the components related to the to the links that make up the chain (logistics, sourcing, service provider gateway ...) should be considered to ensure that these links work efficiently. In e-commerce, logistics and service provider portals (such as website or mobile App) are very important because they are the connection point with customers and if the delivery is not done properly, especially for perishable products, in addition to customer dissatisfaction will cause product waste. Also, the service provider portals should have appropriate features such as speed, graphics, user friendliness, user experience, security, providing complementary services, ease of payment and other important features to make users and customers will revisit the website.- Market and customer insights. In this dimension, 4p components and customers are defined. It is crucial to identify market trends as well as the position that the business has with its customers. In fact, depending on the type of product and service that customers are willing to pay for, supply chain processes can be restructured. - Competitive intelligence. The way competitors market their products and services and the scanning of the external business environment are crucial in shaping the business supply chain. According to the resource-based view theory, a service should be defined in the supply chain that cannot be easily copied or provided by competitors and brings a competitive advantage to the firm, and this requires knowledge of the technologies adopted by competitors and the type of service and price offered by them.- Business intelligence. One of the important dimensions of the supply market intelligence model is business intelligence. In fact, the revenue model, sales volume, statistics and financial information and value that the retailer has created for itself, and the and the evaluation of incentives provided in the form of discount plans, provide insight to managers to focus on those products and services in the supply chain that they bring better and more to the business, and according to these factors, the company's revenue model can be defined.- Social business intelligence. Social networks have had a significant impact in the last decade. Social customers are able to share information with countless members of these networks, so analyzing social customer relationships and current trends in these networks and analyzing the performance of competitors in these networks is very important. In fact, these networks have created a new potential market for businesses and require their own sourcing and marketing.Based on what was covered in this study, it can be concluded that those businesses that operate in the field of online retailing, always need to find themselves in the path of information flow, which is an attempt to reduce uncertainty.
Mohammad Saleh Torkestani; Zohreh Dehdashti Shahrokh; Iman Raeesi Vanan; Fatemeh Golshan
Abstract
Providing valuable information in the form of attractive content and interaction with customers is one of the most important elements of content marketing. The most important factor in the success of content marketing is answering to the question of what causes the audience to engage in content. Despite ...
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Providing valuable information in the form of attractive content and interaction with customers is one of the most important elements of content marketing. The most important factor in the success of content marketing is answering to the question of what causes the audience to engage in content. Despite numerous researches in the field of identifying the dimensions of engagement and motivators of audiences to engage with content, the audience engagement is still one of the most important concerns of actors in the field of content marketing and they are looking for effective ways to identify factors affecting the promotion of audiences' engagement. The present study, using Meta - synthesis method based on the Sandelowski and Barros (2007) model, identifies influential indicators of content marketing on promoting the audience engagement. For this purpose, studies according to years 2003 – 2019 were collected and the papers that did not obtain the intended criteria were excluded from the study. Finally, the findings of 45 papers were selected. By classification of identified codes, 23 categories were identified in 4 dimensions including engagement, categories related to content features, categories related to content writer and other user's reactions. Among all identified categories, the possibility of content personalization for each audience, the sentiment embedded in content and the history of content, the membership level of writer and his/her identity in the online community made the highest priority.
Sina Raeesi Vanani; Iman Raeesi Vanani; Mohammad Taghi Taghavifard
Abstract
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 ...
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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.
Hadi Khan Mohammadi; Iman Raeesi Vanani; Sahar Malek Mohammadi
Abstract
The focus on the establishment and development of electronic government in Iran is one of the serious plans of all governments in the Islamic Republic. Indeed, all government programs in the field of reforming the administrative system have dealt with the importance and urgency of developing executive ...
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The focus on the establishment and development of electronic government in Iran is one of the serious plans of all governments in the Islamic Republic. Indeed, all government programs in the field of reforming the administrative system have dealt with the importance and urgency of developing executive programs for its development. Currently, the establishment of electronic government has experienced ups and downs which making it difficult to be actualized and generalized. However, according to UN statistics, Iran has fallen in the ranking. Thus, the paper tries to identify the pattern of the effect - and being affected - of the challenges and strategic issues of e-government development using DEMATEL. Data collection tool was a questionnaire. Out of 15 questionnaires distributed among e-government experts, 12 questionnaires were returned. The results showed that from among the 9 challenges, the lack of effective competition in information technology (IT) infrastructure and the relative monopoly in the government were the major problems. Furthermore, the existence of an appropriate view and firm belief in IT between managers and experts of government agencies and private sectors of the country greatly contributes to the development of electronic government. Ultimately, online access to the databases of the country is of great significance
Imani Raeesi Vanan; Mohammad Reza Taghva; Delnia Amir Ashayeri
Abstract
In this research, for the purpose of evaluating the performance of knowledge management systems as an improving infrastructure for organizational learning and performance in software development industry, a fuzzy inference system is designed and evaluated. At first, input variables were extracted ...
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In this research, for the purpose of evaluating the performance of knowledge management systems as an improving infrastructure for organizational learning and performance in software development industry, a fuzzy inference system is designed and evaluated. At first, input variables were extracted as the performance evaluators of knowledge management system. Then, if-then rules were identified through the utilization of experts’ opinions and inserted to the fuzzy rule-base. The output of inference system was also designed for performance evaluation of knowledge management system. The designed system, through a comprehensive assessment of knowledge management systems, can enable organizations to identify the strengths, weaknesses, current condition, and future decisions making for the purpose of performance improvement. For the validation of fuzzy inference system, a comparison was made between system outputs and experts viewpoints. Considering the very small difference between the average of experts’ opinions and system output, it can be stated that the system has an appropriate precision and validity for future assessment.
Babak Sohrabi; Iman Raeesi Vanani; Babak Bootorabi
Abstract
With the emergence of new businesses leading to the complicated and changing business environments, industrial managers and investors need tools and mechanisms to acquire a more clarified view of their business in different financial aspects in the future. The financial status of industrial firms ...
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With the emergence of new businesses leading to the complicated and changing business environments, industrial managers and investors need tools and mechanisms to acquire a more clarified view of their business in different financial aspects in the future. The financial status of industrial firms has always had a significant analytical role and the evaluation of profitability has been conducted through the analysis of financial indicators that appear as key performance measures. In this regard, financial statements provides the stakeholders with accurate organizational status in a specific period of time. In the current research, the researchers have attempted to utilize the financial ratios as well as data mining algorithms so as to design a system that accurately predicts the net profit based on the previous performance of firms and accordingly, providing an appropriate performance analysis. The designed neural network model predicts the profit through the detection of relationships among financial ratios and previous profitability of the industrial firm.
