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.
Manochehr Zamani Farizhandi; Payam Hanafizadeh; Zohreh Dehdashti Shahrokh; Mohammadtaghi Taghavifard
Abstract
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 ...
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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.
Zohreh Dehdashti Shahrokh; Mohammad Taghi Taghavifard; Mohammad Reza Karimi Alavijeh; Mohammad Mehdi Poursaeed
Volume 3, Issue 9 , December 2014, , Pages 1-24
Abstract
Fundamental changes occurred in the society and economy since the nineteenth century has clearly reflected in the development of our communities. Consumption communities which had not been previously existed came to the existence by the development of mass media especially Web 2.0 and modern marketing. ...
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Fundamental changes occurred in the society and economy since the nineteenth century has clearly reflected in the development of our communities. Consumption communities which had not been previously existed came to the existence by the development of mass media especially Web 2.0 and modern marketing. As a result; people are increasingly taking their identity tied to their brands. On the other hand, the market in the twenty-first century is dominated by advanced communication technology and e-commerce and hence, virtual brand communities are rapidly expanding. With regards to the above, in this study factors affecting participation in such communities are identified. The research method used is survey and the population consisted of those customers who are the members of virtual communities. Data were collected from 408 members of these communities. In order to test the hypotheses related to the components of the model, confirmatory factor analysis and structural equation modeling were used. The study findings suggest that four factors that is: factors related to the brand, social factors, factors related to the product, and functional factors are affecting participation in virtual brand communities.
