顧客行動を促進するシステム開発のための要素分析

早大学位記番号:新7901早稲田大

A Cross-cultural Analysis of Brand Personality: Comparisons of China’s and the US Energy Companies’ English Websites

With the rapid development of economic globalization, projecting a positive image overseas and creating world famous brands have become vital to enhance industrial and national core competencies and execute the "Going out" strategy. To achieve the goals, corporates attach significance to establish and maintain corporate websites in view of its convenience, autonomy and interactivity while encountering cross-cultural challenges. This study employs corpus analytical tools to conduct content analysis on the existing cross-cultural differences and the linguistic and cultural features, between Chinese and US energy companies’ websites based on Aaker’s brand personality framework and Hofstede’s cultural dimension theory. Findings reveal that there is a significant difference between occurrence frequencies of brand personality dimensions between China and US, and their websites linguistic discrepancies are relevant to their cultural differences. The study may provide meaningful implications on employing linguistic theories and methods to conduct multidisciplinary studies on corporate communication online

Assessment of Shopping Mall Customers’ Experience through Criteria of Attractiveness in Tier-II and Tier-III Cities of India: An Exploratory Study

The present research attempts to develop a theoretical framework for the assessment of shopping mall customer experience dimensions. It further classifies the variables associated with retail experiences that may attract customers in Tier-II and Tier- III cities towards the malls. Exhaustive literature review and expert opinion approaches have been used to explore the evaluation criteria for the assessment of the mall experience. ISM is used to develop a structural model that represents relationships among variables at different levels along with driving and dependence relationships in the structural model. The result highlights that factors like customer value orientation, tenant mix, employees, facilities management are the most significant benchmarking criteria for customers’ assessment of their mall experience in the present study. To achieve profitable operations in these cities, retailer’s need to acquaint themselves with the expectations of customers in order to attract their attention. This indicates that it is imperative for mall managers to identify how consumers benchmark different parameters while evaluating a mall experience. Understanding the importance of such parameters will allow malls to be built according to some standard specifications that can meet a consumer’s threshold for appeal and attractiveness. The study adds to the existing literature of assessing shopping experience in Tier-II and Tier-III cities’ malls through a structural model. The most and the least dominant factors found in this study will help mall managers to develop strategies to enhance the customer shopping experience in malls

Language Management in a Japanese Multinational Company: A Data-Driven Approach

Globalization poses a challenge for businesses with linguistically diverse staff, prompting the choice of English as the default corporate language. In Japan, research on the use of English in business contexts from both corporate and employees' perspectives is very limited, let alone studies adopting a data-driven approach. This study focuses on Rakuten, a Japanese multinational corporation (MNC), with the aim of illustrating the key challenges the company faces when it adopts English as its official language. The research is interdisciplinary and is positioned at the intersection of business communication, computational sociolinguistics, and language management. The first article, "Content analysis of language-sensitive recruitment influenced by corporate language policy using topic modeling", explores the match (or mismatch) between language-sensitive recruitment (English, Japanese, or bilingual) and corporate language policy. The second article, "It is all about TOEIC: discovering topics and trends m employee perceptions of corporate language policy", examines the barriers m multinational companies that have adopted a foreign language and analyzes employees' attitudes. The third and final article, "Analyzing cultural expatriates' attitude toward 'Englishnization' using dynamic topic modeling", investigates changes in employee' perceptions of Japanese work practices and values over time. The results of my study have implications for the implementation of language-sensitive recruitment in a multilingual corporate context. Furthermore, the thesis also highlights the evolutionary nature of corporate language policy topics by exploring and categorizing large amounts of text. Overall, the results presented in the three articles expand the understanding of the challenges associated with the use of English in a Japanese busines

A User-POI-Guide Cost Optimization Method for Tourism Planning Considering Social Distance and User Preferences

MaaS (Mobility as a Service) itself has come into common use, and these developments have attracted keen interest from the industry in recent years. MaaS can be applied as a solution to deal with the current situation by considering the social distance. However, due to the time-share mechanism, personal assets are monopolized by specific users for a long time that cannot be shared with other users at the same time. Thus, the sharing economy companies in the tourism industry (e.g., Airbnb Experience and Huber) are in a dilemma of low productivity and high cost. In this research, we propose a new travel guide sharing service that considers the concept of social distance and user preferences. The user side only needs to select simple conditions such as travel time and the number of POIs (Point of Interest) that she/he plans to visit, meanwhile, the guide side simply inputs the POIs that she/he can guide. Furthermore, by analyzing these basic information, our proposed system can recommend the tour guides, scenic spots, and route planning to provide a real-time tour guide plan, which addressed the user's preferences and reduced the face-to-face communication to users in advance. To verify the effectiveness of our proposed method, we also ask 68 users to evaluate our system and analyze the results of questionnaires

BERT, SHAP, Kano 모델을 기반한 소비자 만족 요소 다이나믹스

학위논문(석사) -- 서울대학교대학원 : 경영대학 경영학과, 2022.2. 오정석 교수.최근 10년 간 온라인 쇼핑 산업의 성장으로 온라인 쇼핑몰 플랫폼에 온라인 리뷰 등 무한한 소비자 반응, 만족도 관련 정보가 생성되고 있다. 이에 많은 기업들과 학계에서 이를 활용하여 VoC (Voice of Customer)를 반영한 소비자 만족도 모델링을 시도하고 있다. 본 논문은 BERT, GBM, SHAP 등을 활용하여 카노 모델 (Kano Model)에 기반한 소비자 만족도 특성 (Customer Satisfaction Dimension)을 분류하고 각 특성의 소비자 요구 충족 여부가 소비자 만족도에 미치는 영향도를 측정한다. 본 논문의 방법론에 활용된 각 빅데이터 모델 성능과 선행 연구들에서 사용된 모델 성능을 직접 구현 및 비교하여, 본 논문에서 활용된 모델들의 정확성과 안정성을 보였다. 또한 해석적 머신러닝 기법인 SHAP를 도입하여, 카노 카테고리를 분류하는 통일된 분류 방식을 제안한다. 본 연구는 제시된 방법론을 통해 스마트폰 및 스마트워치 제품군을 대상으로 실증 연구를 진행하며, 산업계에 제품 개발 및 개선, 고객 세분화 전략 등 기업 의사결정 방향성에 유의미한 제언을 제시함으로써 본 방법론의 실용적 가치를 입증하였다.As a large number of online reviews are loaded on e-commerce platforms in recent days, companies are being able to measure customer satisfaction reflecting VoC (Voice of Customer) with big data analytics. This paper proposes the improved framework for identifying characteristics of customer satisfaction dimensions (CSD) based on Kano model using BERT (Bidirectional Encoder Representations from Transformers), GBM (Gradient Boosting Machine), and SHAP (Shapley Additive eXplanation). We proved each model outperformance by comparing other models which previous studies have used. And this paper suggests the unified rule of Kano model classification using SHAP. Furthermore, we conducted empirical studies regarding smartphone and smartwatch products which suggest the direction of product enhancement/development strategy and multi-product level customer segmentation strategy to product manufacturers. This shows proposed methodology’s effectiveness and usefulness on industrial analysis.1. Introduction 1 2. A framework for modelling customer satisfaction from online review 5 3. Research Method 8 3.1 Mining customer’s sentiments toward CSDs from online reviews 8 3.2 Measuring the effects of customer sentiments toward each CSD on customer satisfaction 11 3.3 Identifying the feature of each CSD from the customer’s perspective 11 3.4 Classifying each CSD into Kano categories 14 4. Empirical Study 17 4.1 Study 1 17 4.2 Study 2 24 5. Conclusion 27 6. Reference 29석

Effectiveness of Social Media Analytics on Detecting Service Quality Metrics in the U.S. Airline Industry

During the past few decades, social media has provided a number of online tools that allow people to discuss anything freely, with an increase in mobile connectivity. More and more consumers are sharing their opinions online with others. Electronic Word of Mouth (eWOM) is the virtual communication in use; it plays an important role in customers’ buying decisions. Customers can choose to complain or to compliment services or products on their social media platforms, rather than to complete the survey offered by the providers of those services. Compared with the traditional survey, or with the air travel customer report published by U.S. Department of Transportation (DOT) each month, social media offers features that can spread information quickly and broadly. This dissertation offers a novel methodology that, by utilizing emotional sentiment analysis, can help the airline industry to improve its service quality. Longitudinal data, retrieved from Twitter, are collected from twelve U.S.-based airline companies, in order to represent airline companies in different levels and categories. The data covers three consecutive months in Quarter 2 of 2017. Applied alongside the service quality metrics of the airline industry, the benchmark datasets for each metric are created. The purpose of this dissertation is to bridge the gap in traditional methodology for a service quality measurement in the airline industry and to demonstrate the way in which socialized textual data can measure the quality of the service offered by airline service providers. In addition, sentiment analysis is applied, in order to get the sentiment score of each tweet. Emotional lexicons are used to detect the emotion expressed by the tweet in two emotional dimensions: each tweet’s Valence and Arousal are calculated. Once the SERVQUAL model is applied and the keywords to find the corresponding social media data are created for each dimension, the results show that responsiveness, assurance, and reliability are positively correlated to the AQR score that measures the service quality of airline industry. This study also finds that a large amount of negative social media data will negatively affect the AQR score. Finally, this study finds that the interaction of the sentiment score and the arousal score of textual social media data play the important role in predicting the service quality of the airline industry. Finally, an opinion-oriented information system is proposed. In the last, this study provides theory verification of SERVQUAL