• Asia Marketing Journal
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• v.19 no.3
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• pp.75-98
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• 2017

Our study is trying to investigate the perceived training effectiveness by applying the theory of planned behavior (TPB) and Technological Acceptance Model (TAM) and intend to examine the effects of individual differences on perceived training effectiveness and performance of individuals. The main purpose is to evaluate the perceived training effectiveness, and role of individual differences in terms of learning. The results of this study supported all the hypothesis that participants with higher level of creative self-efficacy, intrinsic motivation, creativity and emotional intelligence (EI) will have greater inclinations to learn. Results showed that perceive training effectiveness is positively related to training transfer and training transfer increase the performance of individuals. Study results significantly agree with the theory of planned behavior (TPB) which was applied to measure the perceived training effectiveness and suggest trainee's perception of usefulness, ease and benefits enhance learning dimensions of participants that make any program effective. The study has highlighted a number of issues that influence the perceived training effectiveness.

• Journal of the Korean Society of Clothing and Textiles
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• v.32 no.3
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• pp.408-417
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• 2008

The purposes of this study were to investigate the degree of market orientation of textile firms and to explore the effect of market orientation on business performance and job satisfaction. The data were collected from 167 subjects who work at textile firms located in the Daegu and Kyungbuk province through survey. The collected data were analyzed by descriptive statistics, t-tests, correlation, regression, and structural equation modeling using AMOS 6.0. Market orientation has a significant and positive impact on the business performance as well as job satisfaction of employees in textile firms. In other words, the greater the market intelligence creation, the market intelligence dissemination and responsiveness of the organization, the greater the business performance. The greater these three factors of textile firms, the greater job satisfaction of employees. In addition, the relationships between company characteristics and market orientation were investigated.

• Knowledge Management Research
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• v.20 no.3
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• pp.17-38
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• 2019

Rrecently, companies have made great efforts to satisfy various needs and heightened expectations of customers, and the importance of customer center as customer contact department for customer relationship management is increasing. In the knowledge ecosystem, corporate customer centers are emerging as a new alternative to acquiring corporate competitiveness by increasing sales and increasing market share by improving marketing support activities and customer relationship management at customer contact points. As a result, the interest in the customer center has increased rapidly because it provides the opportunity to contact with the customer. In addition, in the era of the fourth industrial revolution, the customer center, which is a collection of information and communication technologies, has a big databased voice recognition technology to elaborate customer service, thereby enhancing customer satisfaction and contributing to marketing through continuous interaction with customers. Of course, we have the opportunity to transform into the frontline business intelligence front for customer knowledge. This study is a comparative case study on how the customer center of K Life Insurance that takes the lead in the customer center industry has successfully renewed and established their key information systems to improve customer services and reinforce marketing support competencies. Based on the above, this study will present factors affecting successful implementation and settlement of the customer service information systems of customer centers by independently analyzing two individual cases.

• Korean Journal of Artificial Intelligence
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• v.8 no.2
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• pp.23-28
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• 2020

Purpose: Today, we often hear complaints from customers: poor quality, poor service, expensive prices, etc. Customer complaints are an indication that the company's products and services do not meet customer requirements, which in turn causes customer complaints. An important content of corporate marketing practice is how to use the opportunity of handling customer complaints to win the trust of customers and gain a competitive advantage. According to the concept of marketing, the way for an enterprise to obtain profits is to continuously meet the needs of customers. However, with increasingly fierce market competition and the overall formation of a buyer's market, providing high-quality products and high-efficiency and high-level services have become the eternal theme of enterprises. Therefore, meeting the actual needs of customers and effectively handling customer complaints are issues that we must take seriously. Research design, data, and methodology: This article mainly analyzes the causes of customer complaints, proposes relevant solutions for different types of complaints, builds a customer complaint management system, improves the efficiency and ability of handling complaints, and provides more references and basis for enterprises to solve customer complaints. Conclusions: To further improve the quality of enterprise products and service standards, to help enterprises increase customer loyalty and satisfaction, and to enable enterprises to gain advantages in the increasingly competitive global market.

• Journal of Digital Convergence
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• v.18 no.10
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• pp.175-180
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• 2020

Through case studies for insurance service marketing using artificial intelligence(AI) in the insurtech industry, it investigated how innovative technologies(artificial intelligence, machine learning etc.) are being used in the insurance ecosystems. In particular, through domestic and international case studies, it was examined by Lemonade's service of insurance contracts and getting the indemnity and AI company's service of calculating the compensation through a medical certificate image based on OCR, which brought disruptive innovations using artificial intelligence. As a result of the case analysis, these services have drastically shortened the lead time of insurance contracts and payment through machine learning using numerous customer data based on artificial intelligence. And accurate and reasonable compensation was calculated in the estimation of indemnity, which has a lot of disputes between customers and insurance companies. It was able to increase customer satisfaction and customer value.

• Journal of Intelligence and Information Systems
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• v.12 no.1
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• pp.163-175
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• 2006

This paper provides a corporation's marketing strategy under a ubiquitous computing environment: a WOM(word-of-mouth) marketing using RFID(Radio Frequency Identification) technology and a business model which facilitates the word-of-mouth marketing. To this end, we examine the word-of-mouth communication effects on consumers' life, changes in corporations' attitude toward word-of-mouth marketing, and the difficulties that corporations have in conducting word-of-mouth marketing. The business model this paper suggests makes seamless business-to-consumer and consumer-to-consumer networking possible using the RFID technology and facilitates the word-of-mouth marketing through incentive system of each economic player.

• Korean Management Science Review
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• v.17 no.3
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• pp.19-30
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• 2000

Customization and personalization services are considered as a critical success factor to be a successful Internet store or web service provider. As a representative personalization technique, personalized recommendation techniques are studied and commercialized to suggest products or services to a customer of Internet storefronts based on demographics of the customer or based on an analysis of the past purchasing behavior of the customer. The underlining theories of recommendation techniques are statistics, data mining, artificial intelligence, and/or rule-based matching. In the rule-based approach for personalized recommendation, marketing rules for personalization are usually collected from marketing experts and are used to inference with customers data. however, it is difficult to extract marketing rules from marketing experts, and also difficult to validate and to maintain the constructed knowledge base. In this paper, we proposed a marketing rule extraction technique for personalized recommendation on Internet storefronts using market basket analysis technique, a well-known data mining technique. Using marketing basket analysis technique, marketing rules for cross sales are extracted, and are used to provide personalized advertisement selection when a customer visits in an Internet store. An experiment has been performed to evaluate the effectiveness of proposed approach comparing with preference scoring approach and random selection.

• Journal of Intelligence and Information Systems
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• v.9 no.1
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• pp.195-209
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• 2003

Making traditional plan of target marketing based on association rule has brought restriction to obtain the target of marketing. This paper is to present inverse association rule as a new association rule for target marketing. Inverse association rule does not use information about relation between items that customers purchase, but use information about relation between items that customers do not purchase. By adding inverse association rule to target marketing, we generate new marketing strategy to look for new target of marketing. There are three steps to apply the marketing strategy proposed by this Paper to target marketing. Firstly, a database is converted to an inverse database. Although inverse association rules can be generated from a database, it is easier to explain inverse association rule in an inverse database than in a database. Secondly, association rules and inverse association rules are generated from inverse database. Finally, two types of rules which are created in the previous steps are applied to target marketing. From new marketing rule, this paper is to show direct marketing about target item and indirect marketing about another item associated with target item to sell target item. The reason is that sales of the item associated with target item have an influence on sales of target item.

• The Journal of Asian Finance, Economics and Business
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• v.10 no.2
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• pp.15-27
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• 2023

The purpose of this research is to investigate the impact of Business Intelligence (BI) on the relation between Big Data Analytics (BDA) and Financial Performance (FP), at the beginning we reviewed the academic accounting and finance literature to develop the theoretical framework of business intelligence, big data and financial performance in terms of definition, motivations and theories, then we conduct an empirical analysis based on questionnaire-base survey data collected. The researchers identified the study population in the joint-stock companies listed on the Egyptian Stock Exchange and operating in the sectors and activities related to modern technologies in information systems, big data analytics, and business intelligence, in addition to the auditing offices that review the financial reports of these companies, and The sector closest to the research objective is the communications, media, and information technology sector, where the survey list was distributed among the sample companies with (15) lists for each company, and (15) lists for each audit office, so that the total sample becomes (120) individuals (with a response rate 83.3%), The results show, First, Big data analytics significantly affect organizations' financial performance, second, Business intelligence mediates (partial) the relationship between big data analytics and financial performance.

• Korean Journal of Artificial Intelligence
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• v.10 no.2
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• pp.7-11
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• 2022

OLED displays cannot be used permanently due to burn-in or generation of dark spots due to degradation. Therefore, the time when the display can operate normally is very important. It is close to impossible to physically measure the time when the display operates normally. Therefore, the time that works normally should be predicted in a way other than a physical way. Therefore, if you do computer simulations based on artificial intelligence, you can increase the accuracy of prediction by saving time and continuous learning. Therefore, if we do computer simulations based on artificial intelligence, we can increase the accuracy of prediction by saving time and continuous learning. In this paper, a dataset in the form of development from generation to diffusion of dark spots, which is one of the causes related to the life of OLED, was generated by applying the finite element method. The dark spots were generated in nine conditions, such as 0.1 to 2.0 ㎛ with the size of pinholes, the number was 10 to 100, and 50% with water content. The learning data created in this way may be a criterion for generating an artificial intelligence-based dataset.