Basic Search / Detailed Display

Author: 張聖彥
Sheng-Yen Chang
Thesis Title: 社會輿論與行動意圖: 挖掘客戶需求混合模式之研究
What People Talk and What They Intend to Do: A Hybrid Method to Dig out Customer Desires
Advisor: 盧希鵬
Hsi-Peng Lu
Committee: 盧希鵬
Hsi-Peng Lu
羅天一
Tain-Yi Luor
黃世禎
Sun-Jen Huang
王孔政
Kung-Jeng Wang
徐慧霞
Kung-Jeng Wang
Degree: 博士
Doctor
Department: 管理學院 - 管理研究所
Graduate Institute of Management
Thesis Publication Year: 2022
Graduation Academic Year: 110
Language: 英文
Pages: 76
Keywords (in Chinese): 線上消費者行為網路口碑大數據文本挖掘消費價值理論理性行動理論可穿戴設備客戶共創
Keywords (in other languages): online consumer behavior, electronic word-of-mouth, big data, text mining, consumption value theory, theory of reasoned action, wearable devices, customer cocreation
Reference times: Clicks: 345Downloads: 0
Share:
School Collection Retrieve National Library Collection Retrieve Error Report
  • 產品能自我銷售嗎?企業能否透過網路聲量挖掘消費者需求,以開發適當的產品來滿足客戶?如果能做到,產品理應可以自己銷售自己。然而,目前尚不清楚網路聲量的積累是否能準確地預測到客戶偏好和購買意願。我們研究了人們在網上的談論議題以及他們在採用階段行為意圖的兩個相關觀點,以便為投注心力在產品開發和網路行銷工作中表現企圖心的公司提供建議。借鑒消費價值理論,我們以台灣消費者為樣本,考察了消費者對使用可穿戴設備的討論和意圖。採用文本挖掘技術(即人們談論什麼)和基於調查的研究使用結構方程模型(即人們打算做什麼)來探索上述問題。
    大數據分析的結果,功能、情感和條件價值是可穿戴設備前三高的網路聲量。相對的,情感、認知和功能價值是客戶採用意願最有影響力的主要驅動因素。我們的研究結果表明,不同的價值維度與消費者購買決策過程中的不同時點有相對應的關聯。一些價值觀激發了消費者在購買前資訊搜索階段相關的線上討論,而另一些價值觀則在人們購買意願的形成過程中顯得很重要。我們的結論是企業可以通過大數據發現消費者的需求來開發產品,然而,在不同的客戶旅程階段,消費者感知價值會外界干擾產生變化,企業應提前部署不同的銷售和行銷策略以因應變化。我們討論了我們研究的理論和實踐意義,並為未來的研究提供了建議。


    Can a product sell itself? How to develop your products as a result of consumer desires via Internet buzz? If it can be done, the product should be able to sell itself. However, it remains unclear whether the accumulation of Internet buzz can accurately predict customer preferences and buying intentions. We study two related perspectives with regard to what people talk about online and what they intend to do in the adoption phase to offer advice to companies aiming to excel in products development and online marketing efforts. Drawing on the consumption value theory, we examine buyers’ discussions about and intention to use wearable devices for a sample of consumers in Taiwan. A framework is advanced to explore the results of big data analysis employing text-mining techniques (i.e., what people talk about) and survey-based research using structural equation modelling (i.e., what people intend to do).
    Functional, emotional and conditional values surfaced as the highest Internet buzzes of wearable devices. Conversely, emotional, epistemic and functional values emerged as the most influential drivers of customers’ adoption intention. Our findings suggest that different value dimensions are relevant at different points of the purchase-related decision-making process. Some values animate Internet discussions that pertain to the pre-purchase information search stage, and others appear significant during the formation of people’s purchase intentions. The firms can discover consumer desires via big data to develop products, additionally, in different customer journey stages that consumer perceived values are also different, firms should deploy troops ahead of different business and marketing strategies to adopt the change to form as corporate innovation process. We discuss the theoretical and practical implications of our study and provide suggestions for future research.

    推薦書 I 審定書 II Table of Contents III Table V Figure VI 中文摘要 VII Abstract VIII Acknowledgements IX 1、 Introduction 1 1.1 Research motivation 1 1.2 Research background 2 1.3 Research purpose 5 2、 Literature review 8 2.1 Innovation 8 2.2 Theory of reasoned action (TRA) 12 2.3 Big data and Internet buzz 14 2.4 Consumption value theory 16 3、 Methodology 24 3.1 Study I – Big data research 27 3.1.1 Study I methods 27 3.1.2 Study I findings 29 3.2 Study II - Quantitative research 31 3.2.1 Study II methods 31 3.1.2 Study II findings 32 3.3 Related perspectives from the two studies 36 4、 Discussion 38 5、 Results 42 6、 Conclusion, Limitation and Suggestions for Further Research 45 6.1 Conclusion 45 6.2 Limitation 45 6.3 Suggestions for Further Research 46 Reference 47 Appendix 63 Table 1:Innovation Type and Definition (Moore, 2004, summarize by this study) 9 Table 2:Examples of the 4-step process to extract terms from the dataset 29 Table 3:Cronbach’s alphas, composite reliability, and average variance extracted 33 Table 4:Discriminant validity 34 Table 5:Variance inflation factors (VIF) 35 Table 6:Summary results of this study 36 Figure 1. Theory of reasoned action model 14 Figure 2. Sheth’s Consumption value theory model 17 Figure 3. Research model this study proposed 18 Figure 4. Innovation process system thinking diagram 24 Figure 5. General research framework 26 Figure 6. 4-step process to extract consumption value terms 29 Figure 7. Internet buzz of each consumption value of wearable devices 30 Figure 8. Results of path analysis using structural equation modeling 36

    Agnihotri, R., Dingus, R., Hu, M. Y., & Krush, M. T. (2016). Social media: Influencing customer satisfaction in B2B sales. Industrial Marketing Management, 53, 172-180.
    Alamäki, A., & Korpela, P. (2021). Digital transformation and value-based selling activities: seller and buyer perspectives. Baltic Journal of Management. 16(2), 298-317
    Alghizzawi, M. (2019). A survey of the role of social media platforms in viral marketing: The influence of e-WOM. International Journal of Information Technology, 3(2), 54-60.
    Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological bulletin, 103(3), 411.
    Anthony, S. D., Eyring, M., & Gibson, L. (2006). Mapping your innovation strategy. Harvard business review, 84(5), 104-13.
    Baddeley, M. (2010). Herding, social influence and economic decision-making: Socio-psychological and neuroscientific analyses. Philosophical Transactions of the Royal Society B: Biological Sciences, 365(1538), 281-290.
    Bai, X. (2011). Predicting consumer sentiments from online text. Decision Support Systems, 50(4), 732-742.
    Banfield, R., Eriksson, M., & Walkingshaw, N. (2017). Product Leadership: How Top Product Managers Launch Awesome Products and Build Successful Teams. O’Reilly Media, Inc.
    Barlow, J., & Maul, D. (2000). Emotional Value: Creating Strong Bonds with Your Customers. Berrett-Koehler Publishers.
    Belk, R. W. (1988). Possessions and the extended self. Journal of consumer research, 15(2), 139-168.
    Betz, F. (1993). Strategic technology management. McGraw-Hill.
    Bhat, S., & Reddy, S. K. (1998). Symbolic and functional positioning of brands. Journal of consumer marketing, 15(1), 32-43.
    Brodie, R. J., Hollebeek, L. D., Jurić, B., & Ilić, A. (2011). Customer engagement: Conceptual domain, fundamental propositions, and implications for research. Journal of service research, 14(3), 252-271.
    Bronner, F., & De Hoog, R. (2011). Vacationers and eWOM: who posts, and why, where, and what?. Journal of travel research, 50(1), 15-26.
    Bronner, F., & De Hoog, R. (2019). Comparing conspicuous consumption across different experiential products: Culture and leisure. International Journal of Market Research, 61(4), 430-446.
    Cao, Q., Duan, W., & Gan, Q. (2011). Exploring determinants of voting for the “helpfulness” of online user reviews: A text-mining approach. Decision Support Systems, 20(2), 511-521.
    Carlson, J., Rahman, M., Voola, R., & De Vries, N. (2018). Customer engagement behaviours in social media: capturing innovation opportunities. Journal of Services Marketing. 32(1),83-94.
    Chang, H.S., Lee, S.C., & Ji, Y.G. (2016). Wearable device adoption model with TAM and TTF. International Journal of Mobile Communications, 14(5), 518-537.
    Chang, S. Y., Lu, H. P., & Liang, C. J. (2013). A teaching case study: Innovation, product development, and organizational transformation at the Sunnic Group. International Journal of Innovation Science. 5(1), 45-67.
    Chell, E., Nicolopoulou, K., & Karataş-Özkan, M. (2010). Social entrepreneurship and enterprise: International and innovation perspectives. Entrepreneurship & Regional Development, 22(6), 485-493.
    Chen, K.J., & You, J.M. (2002). A study on word similarity using context vector models. International Journal of Computational Linguistics & Chinese Language Processing, 7(2), 37-58.
    Chen, Y.C., Shang, R.A., & Lin, A.K. (2008). The intention to download music files in a P2P environment: Consumption value, fashion, and ethical decision perspectives. Electronic Commerce Research and Applications, 7(4), 411-422.
    Cheng, J.M.S., Wang, E.S.T., Lin, J.Y.C., & Vivek, S.D. (2009). Why do customers utilize the internet as a retailing platform? A view from consumer perceived value. Asia Pacific Journal of Marketing and Logistics, 21(1), 144-160.
    Cheung, C.M., & Thadani, D.R. (2012). The impact of electronic word-of-mouth communication: A literature analysis and integrative model. Decision Support Systems, 54(1), 461-470.
    Clark, J., & Guy, K. (1998). Innovation and competitiveness: a review: Practitioners' forum. Technology Analysis & Strategic Management, 10(3), 363-395.
    Cova, B., Dalli, D., & Zwick, D. (2011). Critical perspectives on consumers’ role as ‘producers’: Broadening the debate on value co-creation in marketing processes. Marketing Theory, 11(3), 231-241.
    Cui, W., Liu, S., Tan, L., Shi, C., Song, Y., Gao, Z., ... & Tong, X. (2011). Textflow: Towards better understanding of evolving topics in text. IEEE transactions on visualization and computer graphics, 17(12), 2412-2421.
    Daugherty, T., & Hoffman, E. (2014). e-WOM and the importance of capturing consumer attention within social media. Journal of Marketing Communications, 20(1-2), 82-102.
    Desouza, K. C., Awazu, Y., Jha, S., Dombrowski, C., Papagari, S., Baloh, P., & Kim, J. Y. (2008). Customer-driven innovation. Research-Technology Management, 51(3), 35-44.
    Dewan, S., & Ramaprasad, J. (2014). Social media, traditional media, and music sales. MIS Quarterly, 38(1), 101-122.
    Divakaran, P.K.P., Palmer, A., Søndergaard, H.A., & Matkovskyy, R. (2017). Pre-launch prediction of market performance for short lifecycle products using online community data. Journal of Interactive Marketing, 38, 12-28.
    Dodds, W.B., Monroe, K.B., & Grewal, D. (1991). Effects of price, brand, and store information on buyers’ product evaluations. Journal of Marketing Research, 28(3), 307-319.
    Drucker, P. F. (2002). The discipline of innovation. Harvard business review, 80(8), 95-102.
    Drucker, P.F. (2006). Innovation and Entrepreneurship: Practices and Principles. Harper & Row.
    Erevelles, S., Fukawa, N., & Swayne, L. (2016). Big Data consumer analytics and the transformation of marketing. Journal of business research, 69(2), 897-904.
    Erkan, I., & Evans, C. (2016). The influence of e-WOM in social media on consumers’ purchase intentions: An extended approach to information adoption. Computers in Human Behavior, 61, 47-55.
    Fishbein, M., & Ajzen, I. (1974). Attitudes towards objects as predictors of single and multiple behavioral criteria. Psychological Review, 81(1), 59-74.
    Flaxman, S., Goel, S., & Rao, J.M. (2016). Filter bubbles, echo chambers, and online news consumption. Public Opinion Quarterly, 80(S1), 298-320.
    Fornell, C., & Larcker, D.F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
    Gandomi, A., & Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics. International Journal of Information Management, 35(2), 137-144.
    Geng, R., Wang, S., Chen, X., Song, D., & Yu, J. (2020). Content marketing in e-commerce platforms in the internet celebrity economy. Industrial Management & Data Systems, 120(3), 464-485.
    Gonçalves, H.M., Lourenço, T.F., & Silva, G.M. (2016). Green buying behavior and the theory of consumption values: A fuzzy-set approach. Journal of Business Research, 69(4), 1484-1491.
    Hair, J.F., Hult, G.T.M., Ringle, C., & Sarstedt, M. (2016). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Sage Publications.
    Hair, J.F., Ringle, C.M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139-152.
    Harrison, D. A., Mykytyn Jr, P. P., & Riemenschneider, C. K. (1997). Executive Decisions About Adoption of Information Technology in Small Business: Theory and Empirical Tests. Information Systems Research, 8(2), 171-195.
    Hearst, M. (2003). What is text mining. SIMS. UC Berkeley, 5.
    Henderson, R., Rickwood, D., & Roberts, P. (1998). The beta test of an electronic supermarket. Interacting with Computers, 10(4), 385–399.
    Hennig-Thurau, T., Gwinner, K.P., Walsh, G., & Gremler, D.D. (2004). Electronic word-of-mouth via consumer-opinion platforms: What motivates consumers to articulate themselves on the internet? Journal of Interactive Marketing, 18(1), 38-52.
    Hernandez-Ortega, B. (2020). What about “U”? The influence of positive online consumer reviews on the individual’s perception of consumption benefits. Online Information Review, 44(4), 863-885.
    Herr, P.M., Kardes, F.R., & Kim, J. (1991). Effects of word-of-mouth and product-attribute information on persuasion: An accessibility-diagnosticity perspective. Journal of Consumer Research, 17(4), 454-462.
    Hidayanti, I., Herman, L. E., & Farida, N. (2018). Engaging customers through social media to improve industrial product development: the role of customer co-creation value. Journal of Relationship Marketing, 17(1), 17-28.
    Hippel, E. V. (2007). The sources of innovation. In: Das Summa Summarum des Management, 111-120. Gabler.
    Holbrook, M. B. (1994). The nature of customer value: An axiology of services in the consumption experience. Service Quality: New Directions in Theory and Practice, 21, 21-71.
    Holbrook, M.B., & Hirschman, E.C. (1982). The experiential aspects of consumption: Consumer fantasies, feelings, and fun. Journal of Consumer Research, 9(2), 132-140.
    Hong, J. C., Lin, P. H., & Hsieh, P. C. (2017). The effect of consumer innovativeness on perceived value and continuance intention to use smartwatch. Computers in Human Behavior, 67, 264-272.
    Huang, A.H., Yen, D.C., & Zhang, X. (2008). Exploring the potential effects of emoticons. Information & Management, 45(7), 466-473.
    Huarng, K.-H., Yu, T.H.-K., & Lee, C.F. (2022). Adoption model of healthcare wearable devices. Technological Forecasting and Social Change, 174, 121286.
    Hubbard, D.W. (2011). Pulse: The New Science of Harnessing Internet Buzz to Track Threats and
    Opportunities. John Wiley & Sons.
    IDC (2021). Wearable Devices Market Share. Accessed January 28, 2022. Available at: https://www.idc.com/promo/wearablevendor
    Iriobe, O., & Abiola-Oke, E. (2019). Moderating effect of the use of eWOM on subjective norms, behavioural control and religious tourist revisit intention. International Journal of Religious Tourism and Pilgrimage, 7(3), 38-47.
    James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An Introduction to Statistical Learning. New York: Springer.
    Jeong, J.S., Kim, D.S., & Kim, J.W. (2015). Influence analysis of Internet buzz to corporate performance: Individual stock price prediction using sentiment analysis of online news. Journal of Intelligence and Information Systems, 21(4), 37-51.
    Jung Choo, H., Moon, H., Kim, H., & Yoon, N. (2012). Luxury customer value. Journal of Fashion Marketing and Management: An International Journal, 16(1), 81-101.
    Jussila, J. J., Kärkkäinen, H., & Leino, M. (2012). Learning from and with customers with social media: A model for social customer learning. International Journal of Management, Knowledge and Learning, 1(1), 5-25.
    Kaur, P., Dhir, A., Rajala, R., & Dwivedi, Y. (2018). Why people use online social media brand communities: A consumption value theory perspective. Online Information Review, 42(2), 205-221.
    Kim, D., Park, K., & Bang, Y. (2022). The Effect of TV Drama Piracy: An Analysis of Digital Piracy Users, Internet Buzz, and TV Drama Viewership. Information & Management, 103599.
    Kim, H.W., Gupta, S., & Koh, J. (2011). Investigating the intention to purchase digital items in social networking communities: A customer value perspective. Information & Management, 48(6), 228-234.
    Krey, N., Chuah, S.H.-W., Ramayah, T., & Rauschnabel, P.A. (2019). How functional and emotional ads drive smartwatch adoption: The moderating role of consumer innovativeness and extraversion. Internet Research, 29(3), 578-602.
    Kumar, M., & Noble, C. H. (2016). Beyond form and function: Why do consumers value product design? Journal of Business Research, 69(2), 613-620.
    Laney, D. (2001). 3D data management: Controlling data volume, velocity and variety. META Group Research Notes, 6(70), 1-12.
    Langley, D.J., Hoeve, M.C., Ortt, J.R., Pals, N., & van der Vecht, B. (2014). Patterns of herding and their occurrence in an online setting. Journal of Interactive Marketing, 28(1), 16-25.

    Ledden, L., Kalafatis, S.P., & Samouel, P. (2007). The relationship between personal values and perceived value of education. Journal of Business Research, 60(9), 965-974.
    Lee, M., Ko, E., Lee, S., & Kim, K. (2015). Understanding luxury disposition. Psychology & Marketing, 32(4), 467-480.
    Lemon, K.N., & Verhoef, P.C. (2016). Understanding customer experience throughout the customer journey. Journal of Marketing, 80(6), 69-96.
    Li, L., Chi, T., Hao, T., & Yu, T. (2018). Customer demand analysis of the electronic commerce supply chain using Big Data. Annals of Operations Research, 268(1), 113-128.
    Lin, P.C., & Huang, Y.H. (2012). The influence factors on choice behavior regarding green products based on the theory of consumption values. Journal of Cleaner Production, 22(1), 11-18.
    Lin, K. Y., & Lu, H. P. (2015). Predicting mobile social network acceptance based on mobile value and social influence. Internet Research.25(1), 107-130.
    Liu, Y. (2006). Word of mouth for movies: Its dynamics and impact on box office revenue. Journal of Marketing, 70(3), 74-89.
    Lindič, J., & Da Silva, C. M. (2011). Value proposition as a catalyst for a customer focused innovation. Management Decision. 49(10), 694-1708.
    Luo, X., & Zhang, J. (2013). How do consumer buzz and traffic in social media marketing predict the value of the firm? Journal of Management Information Systems, 30(2), 213-238.
    Magidson, J., & Brandyberry, G. (2001). Putting Customers in the ‘Wish Mode’. Harvard Business Review, 79(8), 26-28.
    Mariani, M., Di Fatta, G., & Di Felice, M. (2018). Understanding customer satisfaction with services by leveraging big data: the role of services attributes and consumers’ cultural background. IEEE Access, 7, 8195-8208.
    Markin, R.J. (1979). The role of rationalization in consumer decision processes: A revisionist approach to consumer behavior. Journal of the Academy of Marketing Science, 7(3), 316-334.
    Mayer‐Schönberger, V., & Ingelsson, E. (2018). Big data and medicine: A big deal? Journal of Internal Medicine, 283(5), 418-429.
    Mayzlin, D. (2006). Promotional chat on the Internet. Marketing Science, 25(2), 155-163.
    McCracken, G. (1986). Culture and consumption: A theoretical account of the structure and movement of the cultural meaning of consumer goods. Journal of Consumer Research, 13(1), 71-84.
    McGregor, S.L. (2000). Using social and consumer values to predict market‐place behavior: Questions of congruency. Journal of Consumer Studies & Home Economics, 24(2), 94-103.
    MIC (2014). Online Community e-WOM Demand. https://mic.iii.org.tw/news.aspx?id=366
    Midi, H., Sarkar, S.K., & Rana, S. (2010). Collinearity diagnostics of binary logistic regression model. Journal of Interdisciplinary Mathematics, 13(3), 253-267.
    Moore, G. A. (2004). Darwin and the demon: Innovating within established enterprises. Harvard business review, 82(7-8), 86-92.
    Moore, K., Berger, P.D., & Weinberg, B.D. (2013). Issues for exploration of differing values among sub-groups of young-adult consumers. International Journal of Business and Social Science, 4(5), 35-39.
    Narver, J. C., Slater, S. F., & MacLachlan, D. L. (2004). Responsive and proactive market orientation and new‐product success. Journal of product innovation management, 21(5), 334-347.
    Nassirtoussi, A.K., Aghabozorgi, S., Wah, T.Y., & Ngo, D.C.L. (2014). Text mining for market prediction: A systematic review. Expert Systems with Applications, 41(16), 7653-7670.
    Negahban, A., & Chung, C.H. (2014). Discovering determinants of users’ perception of mobile device functionality fit. Computers in Human Behavior, 35, 75-84.
    Noy, C. (2008). Sampling knowledge: The hermeneutics of snowball sampling in qualitative research. International Journal of Social Research Methodology, 11(4), 327-344.
    Nunnally, J. (1978). Psychometric Methods. McGraw-Hill.
    Overby, J.W., & Lee, E.J. (2006). The effects of utilitarian and hedonic online shopping value on consumer preference and intentions. Journal of Business Research, 59(10-11), 1160-1166.
    Park, C.W., Jaworski, B.J., & Maclnnis, D.J. (1986). Strategic brand concept-image management. Journal of Marketing, 50(4), 135-145.
    Park, G.W., Kim, Y., Park, K., & Agarwal, A. (2016). Patient-centric quality assessment framework for healthcare services. Technological Forecasting and Social Change, 113, 468-474.
    Park, H.J., & Rabolt, N.J. (2009). Cultural value, consumption value, and global brand image: A cross‐national study. Psychology & Marketing, 26(8), 714-735.
    Pavlou, P.A., & Fygenson, M. (2006). Understanding and predicting electronic commerce adoption: An extension of the theory of planned behavior. MIS Quarterly, 13(1), 115-143.
    Payne, A., Frow, P., & Eggert, A. (2017). The customer value proposition: evolution, development, and application in marketing. Journal of the Academy of Marketing Science, 45(4), 467-489.
    Pérez-Luño, A., Wiklund, J., & Cabrera, R. V. (2011). The dual nature of innovative activity: How entrepreneurial orientation influences innovation generation and adoption. Journal of business Venturing, 26(5), 555-571.
    Piller, F. T., Vossen, A., & Ihl, C. (2012). From social media to social product development: the impact of social media on co-creation of innovation. Die Unternehmung, 65(1).
    Pol, E., & Carroll, P. G. H. (2006). An introduction to economics with emphasis on innovation.
    Rintamäki, T., Kanto, A., Kuusela, H., & Spence, M.T. (2006). Decomposing the value of department store shopping into utilitarian, hedonic and social dimensions: Evidence from Finland. International Journal of Retail & Distribution Management, 34(1), 6-24.
    Sashi, C. M. (2012). Customer engagement, buyer‐seller relationships, and social media. Management decision, 50(2), 253-272.
    Sawhney, M., Verona, G., & Prandelli, E. (2005). Collaborating to create: The Internet as a platform for customer engagement in product innovation. Journal of interactive marketing, 19(4), 4-17.
    Schumpeter, J. A. (1982). The theory of economic development: An inquiry into profits, capital, credit, interest, and the business cycle (1912/1934). Transaction Publishers.–1982.–January, 1, 244.
    Shan, Y., & King, K. W. (2015). The effects of interpersonal tie strength and subjective norms on consumers' brand-related eWOM referral intentions. Journal of Interactive Advertising, 15(1), 16-27.
    Sharma, S. (2015, December). Rise of Big Data and related issues. In 2015 annual ieee india conference (indicon), (pp. 1-6). IEEE.
    Shen, X.L., Sun, Y., & Wang, N. (2013). Recommendations from friends anytime and anywhere: Toward a model of contextual offer and consumption values. Cyberpsychology, Behavior, and Social Networking, 16(5), 349-356.
    Sheth, J.N., Newman, B.I., & Gross, B.L. (1991). Why we buy what we buy: A theory of consumption values. Journal of Business Research, 22(2), 159-170.
    Simsek, Z., Vaara, E., Paruchuri, S., Nadkarni, S., & Shaw, J.D. (2019). New ways of seeing big data. Academy of Management Journal, 62(4), 971-978.
    Singh, P., Dwivedi, Y.K., Kahlon, K.S., Pathania, A., & Sawhney, R.S. (2020). Can twitter analytics predict election outcome? An insight from 2017 Punjab assembly elections. Government Information Quarterly, 37(2), 101444.
    Smith, J.B., & Colgate, M. (2007). Customer value creation: A practical framework. Journal of Marketing Theory and Practice, 15(1), 7-23.
    Snyder, H., Witell, L., Gustafsson, A., Fombelle, P., & Kristensson, P. (2016). Identifying categories of service innovation: A review and synthesis of the literature. Journal of Business Research, 69(7), 2401-2408.
    Spann, M., Ernst, H., Skiera, B., & Soll, J. H. (2009). Identification of lead users for consumer products via virtual stock markets. Journal of Product Innovation Management, 26(3), 322-335.
    Stokburger-Sauer, N., Ratneshwar, S., & Sen, S. (2012). Drivers of consumer–brand identification. International Journal of Research in Marketing, 29(4), 406-418.
    Sunder, S., Kim, K.H., & Yorkston, E.A. (2019). What drives herding behavior in online ratings? The role of rater experience, product portfolio, and diverging opinions. Journal of Marketing, 83(6), 93-112.
    Sweeney, J.C., & Soutar, G.N. (2001). Consumer perceived value: The development of a multiple item scale. Journal of Retailing, 77(2), 203-220.
    Tan, W., Blake, M.B., Saleh, I., & Dustdar, S. (2013). Social-network-sourced big data analytics. IEEE Internet Computing, 17(5), 62-69.
    Terho, H., Haas, A., Eggert, A., & Ulaga, W. (2012). ‘It's almost like taking the sales out of selling’—Towards a conceptualization of value-based selling in business markets. Industrial Marketing Management, 41(1), 174-185.
    Thomas, G.M. (2004). Building the buzz in the hive mind. Journal of Consumer Behavior: An International Research Review, 4(1), 64-72.
    Thompke, S., & von Hippel, E. (2002). Customers as innovators. Harvard Business Review, 80(4), 74-81.
    Thomson, M., MacInnis, D.J., & Whan Park, C. (2005). The ties that bind: Measuring the strength of consumers’ emotional attachments to brands. Journal of Consumer Psychology, 15(1), 77-91.
    Töytäri, P., & Rajala, R. (2015). Value-based selling: An organizational capability perspective. Industrial Marketing Management, 45, 101-112.
    Turel, O., Serenko, A., & Bontis, N. (2010). User acceptance of hedonic digital artifacts: A theory of consumption values perspective. Information & Management, 47(1), 53-59.
    Tzeng, J.Y. (2011). Perceived values and prospective users’ acceptance of prospective technology: The case of a career eportfolio system. Computers & Education, 56(1), 157-165.
    Verhoef, P. C., Reinartz, W. J., & Krafft, M. (2010). Customer engagement as a new perspective in customer management. Journal of service research, 13(3), 247-252.
    Verma, S., & Bhattacharyya, S. S. (2017). Perceived strategic value-based adoption of Big Data Analytics in emerging economy: A qualitative approach for Indian firms. Journal of Enterprise Information Management.
    Veryzer Jr, R. W. (1998). Discontinuous innovation and the new product development process. Journal of Product Innovation Management: an international publication of the product development & management association, 15(4), 304-321.
    Vida, I., Koklic, M.K., Kukar-Kinney, M., & Penz, E. (2012). Predicting consumer digital piracy behavior: The role of rationalization and perceived consequences. Journal of Research in Interactive Marketing, 6(4), 298-313.
    Walsh, S.P., & White, K.M. (2007). Me, my mobile, and I: The role of self- and prototypical identity influences in the prediction of mobile phone behavior. Journal of Applied Social Psychology, 37(10), 2405-2434.
    Wang, H.Y., Liao, C., & Yang, L.H. (2013). What affects mobile application use? The roles of consumption values. International Journal of Marketing Studies, 5(2), 11-22.
    Weiss, S. M., Indurkhya, N., Zhang, T., & Damerau, F. (2010). Text Mining: Predictive Methods for Analyzing Unstructured Information. Springer Science & Business Media.
    Wold, H. (1982). Models for knowledge. The making of statisticians, 189-212.
    Wolny, J., & Mueller, C. (2013). Analysis of fashion consumers’ motives to engage in electronic word-of-mouth communication through social media platforms. Journal of Marketing Management, 29(5-6), 562-583.
    Xiao, G., & Kim, J.O. (2009). The investigation of Chinese consumer values, consumption values, life satisfaction, and consumption behaviors. Psychology & Marketing, 26(7), 610-624.
    Yeh, C.H., Wang, Y.S., & Yieh, K. (2016). Predicting smartphone brand loyalty: Consumer value and consumer-brand identification perspectives. International Journal of Information Management, 36(3), 245-257.
    Yeo, B.L., Mohamed, R.H.N., & Muda, M. (2016). A study of Malaysian customers purchases motivation of halal cosmetics retail products: Examining theory of consumption value and customer satisfaction. Procedia Economics and Finance, 37, 176-182.
    Yıldız, T. (2019). Examining the concept of industry 4.0 studies using text mining and scientific mapping method. Procedia Computer Science, 158, 498-507.
    Zhang, K.Z., Cheung, C.M., & Lee, M.K. (2014). Examining the moderating effect of inconsistent reviews and its gender differences on consumers’ online shopping decision. International Journal of Information Management, 34(2), 89-98.

    無法下載圖示
    Full text public date 2024/07/26 (Internet public)
    Full text public date 2024/07/26 (National library)
    QR CODE