• Title/Summary/Keyword: Customers

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Comparing Corporate and Public ESG Perceptions Using Text Mining and ChatGPT Analysis: Based on Sustainability Reports and Social Media (텍스트마이닝과 ChatGPT 분석을 활용한 기업과 대중의 ESG 인식 비교: 지속가능경영보고서와 소셜미디어를 기반으로)

  • Jae-Hoon Choi;Sung-Byung Yang;Sang-Hyeak Yoon
    • Journal of Intelligence and Information Systems
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    • v.29 no.4
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    • pp.347-373
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    • 2023
  • As the significance of ESG (Environmental, Social, and Governance) management amplifies in driving sustainable growth, this study delves into and compares ESG trends and interrelationships from both corporate and societal viewpoints. Employing a combination of Latent Dirichlet Allocation Topic Modeling (LDA) and Semantic Network Analysis, we analyzed sustainability reports alongside corresponding social media datasets. Additionally, an in-depth examination of social media content was conducted using Joint Sentiment Topic Modeling (JST), further enriched by Semantic Network Analysis (SNA). Complementing text mining analysis with the assistance of ChatGPT, this study identified 25 different ESG topics. It highlighted differences between companies aiming to avoid risks and build trust, and the general public's diverse concerns like investment options and working conditions. Key terms like 'greenwashing,' 'serious accidents,' and 'boycotts' show that many people doubt how companies handle ESG issues. The findings from this study set the foundation for a plan that serves key ESG groups, including businesses, government agencies, customers, and investors. This study also provide to guide the creation of more trustworthy and effective ESG strategies, helping to direct the discussion on ESG effectiveness.

Prediction of Customer Satisfaction Using RFE-SHAP Feature Selection Method (RFE-SHAP을 활용한 온라인 리뷰를 통한 고객 만족도 예측)

  • Olga Chernyaeva;Taeho Hong
    • Journal of Intelligence and Information Systems
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    • v.29 no.4
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    • pp.325-345
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    • 2023
  • In the rapidly evolving domain of e-commerce, our study presents a cohesive approach to enhance customer satisfaction prediction from online reviews, aligning methodological innovation with practical insights. We integrate the RFE-SHAP feature selection with LDA topic modeling to streamline predictive analytics in e-commerce. This integration facilitates the identification of key features-specifically, narrowing down from an initial set of 28 to an optimal subset of 14 features for the Random Forest algorithm. Our approach strategically mitigates the common issue of overfitting in models with an excess of features, leading to an improved accuracy rate of 84% in our Random Forest model. Central to our analysis is the understanding that certain aspects in review content, such as quality, fit, and durability, play a pivotal role in influencing customer satisfaction, especially in the clothing sector. We delve into explaining how each of these selected features impacts customer satisfaction, providing a comprehensive view of the elements most appreciated by customers. Our research makes significant contributions in two key areas. First, it enhances predictive modeling within the realm of e-commerce analytics by introducing a streamlined, feature-centric approach. This refinement in methodology not only bolsters the accuracy of customer satisfaction predictions but also sets a new standard for handling feature selection in predictive models. Second, the study provides actionable insights for e-commerce platforms, especially those in the clothing sector. By highlighting which aspects of customer reviews-like quality, fit, and durability-most influence satisfaction, we offer a strategic direction for businesses to tailor their products and services.

An Empirical Study on the Effects of Venture Company's Website Properties on Bounce Rate (벤처기업 웹사이트의 속성이 웹사이트 이탈률에 미치는 영향에 관한 실증연구)

  • Yun Do Hwang;Tae Kwan Ha
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.18 no.2
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    • pp.67-79
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    • 2023
  • The bounce rate is the rate at which a user leaves immediately after visiting, and this study aimed to find out what attributes of a website affect the bounce rate. Web site evaluation items were defined as a total of 4 items and 27 evaluation attributes, including usability, information, service interaction, and technology, so that they can be commonly applied to venture companies in various industries through prior research. As a result of the study, 6 website attributes that affect the bounce rate were verified to be significant by discriminant analysis and decision tree analysis. Suggestions to reduce the bounce rate of venture business websites through this study are as follows. First, the path name of the website is displayed as mandatory and a pull-down menu function is added to facilitate movement to other pages. Second, it is good to expose core content that can attract users' attention in the form of a banner, and place internal link banners in the right place on sub-pages. Third, external links should be linked to a new window so that they do not leave the current page immediately so that they can be re-entered. Lastly, it is recommended to expose the contact information of the person in charge and consultation function as direct information for communication with customers, but if individual response is difficult, at least the consultation function must be added. These suggestions are expected to be of practical help in various fields such as website development, operation, and marketing. However, in special cases, a high bounce rate may be normal, so it should be considered according to the situation.

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Research on the Effect of Korean Wave(Hallyu) Experience in Southeast Asian Countries on Purchase of Korean Cosmetics: Focused on Malaysia and the Philippines (동남아국가 한류체험이 한국 화장품 구매의도에 미치는 영향연구: 말레이시아와 필리핀을 중심으로)

  • Chung, Moon Suk;An, Eun Jae
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.18 no.3
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    • pp.173-189
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    • 2023
  • Although many researches have been conducted that the contents consumption, called Hallyu, has a positive effect on the national image of Korea, which leads to product purchases, there have been few empirical studies based on the experience economy theory that connects to value relationships with customers. Therefore, based on the experiential economy theory, this research conducted an empirical analysis of the effect on Korean image and cosmetics purchase intention targeting women living in Malaysia and the Philippines who have experienced the Korean Wave(Hallyu). As a result of the research, entertainment experience, educational experience, and escape experience had a significant effect on the image of Korea, but aesthetic experience did not. Entertainment experience, educational experience and escape experience also had significant relationships in the indirect effect of Korean image on cosmetics purchase intention. In the moderating effect analysis comparing the two countries, in Malaysia, escape experience had a significant effect on the image of Korea, but in the Philippines, entertainment experience and educational experience had a significant effect on the image of Korea, so there was a difference between the two countries. The effect of Korean image on cosmetics purchase intention was confirmed significantly in both countries, but it was greater in the Philippines than in Malaysia. This research is meaningful in that it is an empirical study based on the systematic framework of experiential economy theory. In order to maintain the effectiveness of the Korean Wave(Hallyu), various improvements in the contents that make up the Korean Wave are required and policy consideration by the relevant authorities is needed. It is also necessary to consider each country's different acceptance of the Korean Wave(Hallyu).

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A Study on the Mediating Effect of Perceived Customer Value onthe Relationship Between Relationship Marketing Factors and Loyalty on Rural Tourism (농촌관광의 관계마케팅 활동요인과 충성도 간의 관계에서 고객지각가치의 매개효과에 관한 연구)

  • Lee, Joo-Heon;Hwang, Tae Hee
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.17 no.2
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    • pp.179-193
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    • 2022
  • This study aims to identify the relationship marketing factors and examine the mediating factors of perceived customer value on the relationship between relationship marketing factors and loyal on rural tourism. We collected and analyzed the survey data from the customers who had experienced rural tourism before. The results from the empirical analysis are as follows. First, through the exploratory factor analysis, four factors such as customer orientation, responsive attraction, professionalism, and ties were derived. Second, it was found all four factors have significant positive effects on loyalty. Third, both responsive attraction and professionalism have significant positive effects on perceived customer value. However, customer orientation and ties do not have significant effects. Fourth, the perceived customer value showed a full mediating effect between responsive attraction and loyalty, whereas it showed a partial mediating effect between professionalism and loyalty. Additionally, it was found that gender did not affect loyalty but significantly affected perceived customer value. This means that women had lower perceived value for rural tourism than men. To improve the loyalty of rural tourism, it is necessary to improve customer orientation, professionalism, ties, and perceived customer value.

The Effects of Independent Business Owners' Emotional Labor on Emotional Exhaustion and Depression: Moderating Role of Regulatory Focus (독립사업자의 감정노동전략이 감정소진과 우울감에 미치는 영향: 조절초점의 조절효과)

  • Lee, Hoon;Jeon, Joo-Eon
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.17 no.5
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    • pp.251-264
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    • 2022
  • Previous researches related to emotional labor have been cross-sectional studies focusing on static differences in emotional exhaustion. Previous studies on these relationships have not highlighted the dynamic properties of these relationships. This purpose of this study is to investigate the effect of emotional labor strategy on perceived emotional exhaustion and depression. This study was conducted by paying attention to the fact that service industry workers who have to respond kindly to customers often have to show emotions which is necessary for their business to the outside world rather than showing their true emotions. The results of this study are summarized as follows. First, it was confirmed that surface acting had a positive influence on emotional exhaustion, but deep acting had a negative influence to emotional exhaustion. Second, it was found that surface acting had a positive influence on depression, but deep acting had a negative influence on depression. Third, it was confirmed that the effect of deep acting on emotional exhaustion decreased when emotional labor was performed through deep acting on Mondays, Tuesdays, and Wednesdays, while emotional exhaustion was not significant on Thursdays and Fridays. Fourth, it was confirmed that the difference in the effect of emotional labor strategy on depression was greater in the case of performing emotional labor through surface acting than in the case of performing emotional labor through deep acting.

The Meditating Role of Customer Satisfaction on Relationship between Brand Embeddedness and Cross-Buying Intention (브랜드배태성과 교차구매의도의 관계에 대한 고객만족의 매개역할)

  • Hansung Yun;Deok Hyun Seong
    • Journal of Industrial Convergence
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    • v.22 no.2
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    • pp.33-43
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    • 2024
  • This study aims to test the relationship between brand embeddedness and cross-selling intention, as well as how customer satisfaction affects as mediator its relationship. The data set includes 258 consumers using a specific smartphone brand and we gather the data by conducting a survey. We use structural equation modeling to verify hypotheses and do nonparametric bootstrap approach for additional analysis of the mediating role of customer satisfaction. The results of analysis are as follows. First, it has been shown that barnd embeddedness positively affects customer satisfaction and cross-buying intention. Second, customer satisfaction is found to have a positive effect on cross-buying. By combining these results and additional analysis, we confirm that the direct effect of brand embeddedness is more effective for cross-buying intention than the indirect effect of customer satisfaction. The results of this empirical analysis show the academic value that brand embeddedness as social capital can be a antecedent for cross-buying intention. In addition, this study suggests the need for brand practitioners to increase the embeddedness of customers related to the brand and consider the mediating role of customer satisfaction together in order to increase cross-buying.

The Differential Impacts of Temporary Aberration on Online Review Consumption and Generation (온라인 리뷰 소비 및 생성에 대한 일시적 이상 현상의 차등 효과)

  • Junyeong Lee;Hyungjin Lukas Kim
    • Information Systems Review
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    • v.23 no.3
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    • pp.127-158
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    • 2021
  • Many online travel agencies (OTAs) provide average ratings and time-relevant information or the most recently posted reviews regarding hotels to satisfy customers. To identify these two factors' relative influence on behavioral decision-making processes, we conducted two studies: (1) an experimental research design to explore the relative influence of the two on online review consumption and (2) an empirical approach to examine their relative impact on online review generation. The results show that when review posters observe an inconsistency between average ratings and recent reviews, they tend to deviate from the recent reviews regardless of the overall direction (reactance behavior). Meanwhile, review consumers tend to conform to the opinions presented in recent reviews (herding behavior). Additionally, in both cases, the effects are amplified in case of a negative aberration. Based on the findings, this study provides theoretical and practical implications regarding the relative influences of average rating and recently posted reviews and their different impacts on online review consumption and generation.

Domain Knowledge Incorporated Local Rule-based Explanation for ML-based Bankruptcy Prediction Model (머신러닝 기반 부도예측모형에서 로컬영역의 도메인 지식 통합 규칙 기반 설명 방법)

  • Soo Hyun Cho;Kyung-shik Shin
    • Information Systems Review
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    • v.24 no.1
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    • pp.105-123
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    • 2022
  • Thanks to the remarkable success of Artificial Intelligence (A.I.) techniques, a new possibility for its application on the real-world problem has begun. One of the prominent applications is the bankruptcy prediction model as it is often used as a basic knowledge base for credit scoring models in the financial industry. As a result, there has been extensive research on how to improve the prediction accuracy of the model. However, despite its impressive performance, it is difficult to implement machine learning (ML)-based models due to its intrinsic trait of obscurity, especially when the field requires or values an explanation about the result obtained by the model. The financial domain is one of the areas where explanation matters to stakeholders such as domain experts and customers. In this paper, we propose a novel approach to incorporate financial domain knowledge into local rule generation to provide explanations for the bankruptcy prediction model at instance level. The result shows the proposed method successfully selects and classifies the extracted rules based on the feasibility and information they convey to the users.