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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 任立中(Lichung Jen) | |
dc.contributor.author | Kuan-Wei Lu | en |
dc.contributor.author | 呂冠緯 | zh_TW |
dc.date.accessioned | 2021-06-16T08:06:07Z | - |
dc.date.available | 2019-07-16 | |
dc.date.copyright | 2014-07-16 | |
dc.date.issued | 2014 | |
dc.date.submitted | 2014-06-23 | |
dc.identifier.citation | Agarwal, Ritu, and Viswanath Venkatesh. 'Assessing a firm's web presence: a heuristic evaluation procedure for the measurement of usability.' Information Systems Research 13.2 (2002): 168-186.
Anderson, Eugene W., Claes Fornell, and Sanal K. Mazvancheryl. 'Customer Satisfaction and Shareholder Value.' Journal of Marketing, 68 (4), (2004): 172-85. Ayanso, Anteneh, and Reena Yoogalingam. 'Profiling retail Web site functionalities and conversion rates: A cluster analysis.' International Journal of Electronic Commerce 14.1 (2009): 79-114. Coffey, Steven. 'Media metrix methodology.' Media Metrix (1999). Hallowell, Roger. 'The relationships of customer satisfaction, customer loyalty, and profitability: an empirical study.' International journal of service industry management 7.4 (1996): 27-42. Hoffman, D.L. and Novak, T.P. “How to acquire customers on the Web”. Harvard Business Review 78, 3, (2000): 179–185. Ittner, Christopher D., and David F. Larcker. 'Are nonfinancial measures leading indicators of financial performance? An analysis of customer satisfaction.' Journal of accounting research 36 (1998): 1-1. Jen, Lichung and Pim Soonsawad. “The Impact of Customer Concentration on Financial Performance: Firm Characteristics as Moderator.” Seminar Paper, The 10th International Conference on Multinational Enterprises (2014). Jiang, Zhenhui, et al. 'Effects of Interactivity on Website Involvement and Purchase Intention.' Journal of the Association for Information Systems 11.1 (2010). Jones, Marshall. 'Home advantage in the NBA as a game-long process.' Journal of Quantitative Analysis in Sports 3.4 (2007): 1-14. Kotha, Suresh, Shivaram Rajgopal, and Mohan Venkatachalam. 'The Role of Online Buying Experience as a Competitive Advantage: Evidence from Third‐Party Ratings for E‐Commerce Firms.' The Journal of Business 77.S2 (2004): S109-S133. Kumar, V., Denish Shah, and Rajkumar Venkatesan. 'Managing retailer profitability—one customer at a time!' Journal of Retailing 82.4 (2006): 277-294. Lewellen, Wilbur G., and S. G. Badrinath. 'On the measurement of Tobin's q' Journal of Financial Economics 44.1 (1997): 77-122. Liang, Ting-Peng and Jin-Shiang Huang. 'An empirical study on consumer acceptance of products in electronic markets: a transaction cost model.' Decision Support Systems, 24 (1), (1998): 29-43. Lin, Judy Chuan-Chuan. 'Online stickiness: its antecedents and effect on purchasing intention.' Behaviour & Information Technology 26.6 (2007): 507-516. Lin, Lin, et al. 'Is stickiness profitable for electronic retailers?.' Communications of the ACM 53.3 (2010): 132-136. Lynch, John G., and Dan Ariely. 'Interactive home shopping: effects of search cost for price and quality information on consumer price sensitivity, satisfaction with merchandise, and retention.' Marketing Science and the Internet, INFORM College on Marketing Mini-Conference. Cambridge, MA. 1998. Moe, Wendy W., and Peter S. Fader. 'Dynamic conversion behavior at e-commerce sites.' Management Science 50.3 (2004): 326-335. Montgomery, Alan L., et al. 'Predicting online purchase conversion using web path analysis.' Marketing Science 23.4 (2004): 579-595. Palepu, Krishna G., Paul M. Healy, and Victor L. Bernard. Business Analysis and Valuation: Using Financial Statement. Mason, OH.: Thomson South-Western, 2004. Pitta, Dennis, Frank Franzak, and Danielle Fowler. 'A strategic approach to building online customer loyalty: integrating customer profitability tiers.' Journal of Consumer Marketing 23.7 (2006): 421-429. Poon, Simpson and Paula M.C. Swatman. 'An exploratory study of small business Internet commerce issues.' Information & Management, 35 (1), (1999): 9-18. Reichheld, Frederick P., and W. Earl Sasser. 'Zero Defections: Quality Comes to Services.' Harvard Business Review (September/October 1990): 105-11. Reichheld, Frederick F., Robert G. Markey Jr, and Christopher Hopton. 'The loyalty effect–the relationship between loyalty and profits.' European Business Journal 12.3 (2000a): 134-139. Reichheld, Frederick F., Robert G. Markey Jr, and Christopher Hopton. 'E-customer loyalty–applying the traditional rules of business for online success.' European Business Journal12.4 (2000b): 173-79. Reinartz, Werner J., and Vijay Kumar. 'On the profitability of long-life customers in a noncontractual setting: An empirical investigation and implications for marketing.' Journal of marketing 64.4 (2000): 17-35. Saleh, Khalid, and Ayat Shukairy. Conversion Optimization: The Art and Science of Converting Prospects to Customers. O'Reilly Media, Inc., 2010. Schwartz, Barry, and Stephen F. Barsky. 'The home advantage.' Social forces 55.3 (1977): 641-661. Simon, Carol J. and Mary W. Sullivan. 'The Measurement and Determinants of Brand Equity: A Financial Approach.' Marketing Science, 12 (1), (1993): 28-52. Stefan Ingves. 'Keynote address to the 10th Asia-Pacific High-Level Meeting on Banking Supervision.' Basel Committee on Banking Supervision, Bank for International Settlements, (2014). Tobin, James. 'A General Equilibrium Approach To Monetary Theory.' Journal of Money, Credit and Banking, 1 (1), (1969):15-29. Zauberman, Gal. 'The intertemporal dynamics of consumer lock-in. ' Journal of Consumer Research 30, 3, (2003): 405-419. Gold, K. ' Web site conversion metrics.' . N.p., 2004. Web. 28 May 2014. <http:// content.websitegear.com/article/conversion_metrics.htm/>. Henneberry, Russ. 'The Daily Egg - The Best Website KPI’s For Three Different Website Types. '. N.p., 22 Jan. 2013. Web. 28 May 2014. < blog.crazyegg.com/2013/01/22/best-website-kpi />. LePine, Peter. 'Big Data (Adv. Analytics) in 15 Mins.' . Emtec Inc., 2013. Web. 28 May 2014. <http://www.emtecinc.com/assets/files/Medinah2013_Big_Data_in_15Mins_PeterLePine.pdf>. Niu David, Liu Andrew I., and Chang Edward. 'System and method for generating real-time promotions on an electronic commerce world wide website to increase the likelihood of purchase', United States Patent Application 20020062245 (2002). 'Accenture 2013 Global Consumer Pulse Research .' . Accenture , 2013. Web. 28 May 2014. <http://www.accenture.com/microsites/global-consumer-pulse-research/Pages/home.aspx>. 'Big Data & Analytics.' IBM, n.d. Web. 28 May 2014. <http://www.ibm.com/big-data/us/en/big-data-and-analytics/>. 'Company Information.' Hoover’s Inc., n.d. Web. 28 May 2014. <http://www.hoovers.com/>. 'Company Annual Report (Form 10-K).' SEC EDGAR Archives. Various public companies, 2012. Web. 28 May 2014. <http://www.sec.gov/cgi-bin/srch-edgar>. 'Ecommerce Sales Topped $1 Trillion for First Time in 2012.' - eMarketer. 5 Feb. 2013. Web. 28 May 2014. <http://www.emarketer.com/Article/Ecommerce-Sales-Topped-1-Trillion-First-Time-2012/1009649>. 'IBM SPSS Decision Trees 21.' . IBM, 2012. Web. 30 Apr. 2014. < ftp://public.dhe.ibm.com/software/analytics/spss/documentation/statistics/21.0/en/client/Manuals/IBM_SPSS_Decision_Trees.pdf >. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/58109 | - |
dc.description.abstract | 網路與數位化時代的來臨,使得資訊搜尋與交易成本大幅下降,消費者得以同時接觸並比較同一產業中之眾多廠商。根據埃森哲顧問公司所進行的全球消費者調查,消費者近年來更傾向於更換供應商及降低了顧客忠誠計劃的接受度。因此,以現今資料重新評估顧客忠誠度對財務績效影響的實證研究,將為數位時代之企業提供是否仍應投資於顧客忠誠計劃之方向指引。
我們認為過去的文獻有二處缺憾需要進行實證補足。首先,前人所做過的顧客忠誠度實證研究,因資料與研究方法之限制,無法將同一消費者與產業中所有競爭廠商之關係納入考量。一個在他們的研究中所定義的忠誠客戶,其實可能在該公司的競爭對手那裡購買更多的產品或服務。其次,很多電子商務從業人員認為轉換率(Conversion Rate)是評估網站成功與否的最重要指標之一,有許多研究專家也視轉換率為電子商務網站的獲利能力。然而,在實證研究證實轉換率和財務績效間存在明確的關係前,企業以提升轉換率為營運目標可能只是非理性的集體迷思。 本研究運用comScore高品質的網路消費者資料庫,納入競爭對手的資訊,克服前人研究的不足之處。定義產業界線是確定競爭對手的前提,我們採用了四個標準,篩選出8個合適的產業作為研究樣本,並運用統計迴歸模型和決策樹模型來探討顧客忠誠度、瀏覽行為、及網站的行銷策略對財務績效的影響。 即使在消費者能同時比較多個競爭廠商的數位時代,我們的研究結果仍支持企業應將資源配置於顧客忠誠計劃的論點。在迴歸模型中,我們發現顧客忠誠度對財務績效的影響比轉換率更具有統計顯著性,因此我們建議企業應將培育客戶忠誠度視為其營運之首要任務。 與顧客間建立更深入黏著的關係,與運用適當的行銷策略,對提升財務績效也有很大的影響。更深入黏著的顧客關係對財務績效有正面的影響,我們認為顧客黏著性可能和網站的「主場優勢」有關。本研究最重要的發現是轉換率不應被直接視為網站營運績效的指標,而應作為行銷策略的考慮變數。 網站如將轉換率做為營運指標,並試圖將每位造訪者轉換為實際消費之顧客,對其財務績效不盡然有正面之影響。因為有些造訪者或顧客,並不屬於對該企業的財務績效有正面貢獻的群體,這些造訪者或顧客與網站間未建立深入黏著的關係,如果他們沒有得到具吸引力的價格,便不會在下次造訪時消費。一味的以提升轉換率作為營運指標,實際上可能會徒勞無功。我們認為轉換率應和顧客的瀏覽行為連結,並對個別顧客採用合適的轉換率策略,才能提升企業的營運績效,這也間接證實了互動式行銷能影響企業的財務績效。 企業應當投資於互動式行銷與即時運算之系統和資料庫,以更深入地了解每個造訪者後,對個別顧客採用合適的行銷策略。我們的研究發現相對於以黏著度淺的游離顧客為主的公司,藉由培育顧客忠誠度與深化關係黏著度,並採用合適行銷策略的企業,平均能提升其股東價值達31%。 本研究不僅為企業的行銷人員、財務長與最高決策者提供寶貴的指引,同時資本市場的投資人與分析師也應參考之。總而言之,本研究支持傳統的顧客忠誠理論適用於今日的電子商務環境,但企業應有策略的、以更明智的方式運用行銷資訊系統配合之。 | zh_TW |
dc.description.abstract | Search and transaction costs have been substantially reduced in the digital world, enabling consumers to reach multiple providers of similar products or services at the same time. As the Accenture Global Consumer Survey (2013) indicates that consumers are more inclined to switch providers and the adoption of loyalty programs has declined slightly in recent years, an empirical study evaluating the impact of customer loyalty on financial performance would provide guidance for whether firms should still invest in customer loyalty program in the digital world today.
Research gaps exist in prior research. First, most prior empirical studies in the field of customer loyalty are not able to consider the same customer’s relationship with the company’s competitors, and a loyal customer defined in their studies might purchase more at the company’s competitors. Second, many eCommerce practitioners view conversion rate as one of the most important performance indicators and many researchers associate conversion rate with profitability of Web sites. However, no empirical research measures the relationship between conversion rate and financial performance before. Therefore, the goal toward higher conversion rate might be irrational groupthink. This research overcomes the insufficiency in prior research by incorporating competitors’ information and utilizing high-quality online consumer data collected by comScore. Defining industry boundaries is the premise for identifying competitors; we use four criteria to select the appropriate sample firms across 8 industries. Two statistical models- regression and decision tree model are employed to investigate the impact of customer loyalty, browsing behavior, and websites’ marketing strategy on financial performance. Our research result justifies the allocation of resources to customer loyalty programs, even when consumers are able to compare multiple items easily online today. In the multiple regression model, we find that the impact of customer loyalty on financial performance is much stronger than conversion rate, and we suggest companies should prioritize their efforts on cultivating customer loyalty. Building stickier relationships and utilization of the appropriate interaction strategies play the import roles as well. Stickiness is positive related to financial performance, and we think stickiness might generate “home advantage” for Websites. The most important finding from our research is the conversion rate, which should be considered as a variable for marketing strategy, not a performance indicator. A website’s conversion rate, as trying to convert every visitor to customer, is not the best performance indicator; some customers or visitors may within the segmentation that would not benefit a firm financially, because they are not sticky and will not make repeated purchase if they do not get attractive pricing. It is meaningless to convert those visitors to customers. We find that customer conversion rate should be associated with browsing behavior, and the appropriate conversion strategy should be applied for individual customer, implying the utilization of interactive marketing is an important factor for financial performance. Companies should invest in interactive database marketing and real-time computing systems, know each visitor better, and then apply the appropriate marketing strategy. Companies selling products or services to stickier loyal customers with right marketing strategies, can create 31% more value to shareholders, compared to companies selling products or services to less sticky disloyal customers. Our research provides valuable insight not only for marketers, CFOs and CEOs in the business, but also for investors and analysts in the capital market. In conclusion, to improve financial performance, we propose the traditional customer loyal model should be used for eCommerce, and applied with the “smarter way”. | en |
dc.description.provenance | Made available in DSpace on 2021-06-16T08:06:07Z (GMT). No. of bitstreams: 1 ntu-103-R00724018-1.pdf: 953364 bytes, checksum: 583a03e4cf07d99d4eb344fd91477e4b (MD5) Previous issue date: 2014 | en |
dc.description.tableofcontents | CHAPTER 1: INTRODUCTION………………………………………………………………………1
1.1) Research Objectives…………………………………………………………………3 1.2) Research Gap and Expected Contribution………………………………………4 CHAPTER 2: LITERATURE REVIEW………………………………………………………………8 2.1) Marketing Literature…………………………………………………………………8 2.1.1) Customer Loyalty……………………………………………………………………8 2.1.2) Stickiness and Browsing Behavior………………………………………………9 2.1.3) Conversion Rate………………………………………………………………………10 2.1.4) Websites’ Marketing Strategy – Interaction with Customers……………11 2.2) Finance Literature……………………………………………………………………12 2.2.1) Financial Performance Measure…………………………………………………12 2.2.2) Application of Tobin’s q to Financial Performance……………………15 CHAPTER 3: RELATIONSHIP BETWEEN CUSTOMER LOYALTY, BROWSING BEHAVIOR, WEBSITES’ MARKETING STRATEGY AND FINANCIAL PERFORMANCE……………………………17 3.1) Hypothesis Development………………………………………………………………17 3.1.1) Customer Loyalty and Firm Performance………………………………………17 3.1.2) Stickiness and Firm Performance………………………………………………17 3.1.3) Conversion Rate and Firm Performance………………………………………18 3.2) Research Methodology………………………………………………………………18 3.2.1) Sampling Method……………………………………………………………………19 3.2.1a) Selection Criteria for Sample Firms………………………………………19 3.2.1b) Definition of Industries………………………………………………………22 3.2.1c) Analysis of Sample Selection…………………………………………………24 3.2.1d) Removal of Inadequate Sample Firms…………………………………………28 3.2.2) Data: Sources and Processing…………………………………………………31 3.2.2a) Data Collection…………………………………………………………………31 3.2.2b) Data Processing…………………………………………………………………32 3.2.3) Measurement…………………………………………………………………………33 3.2.4) Statistical Model…………………………………………………………………36 CHAPTER 4: EMPIRICAL STUDY RESULTS………………………………………………………39 4.1) Descriptive Statistics………………………………………………………………39 4.1.1) Statistics at Aggregate Level……………………………………………………41 4.1.2) Statistics at Individual Level………………………………………………46 4.2) Empirical Results: Regression Models……………………………………………50 4.2.1) Empirical Results from Multiple Regression………………………………50 4.2.2) Empirical Results from Simple Regression…………………………………51 4.3) Decision Tree Model……………………………………………………………………54 CHAPTER 5: DISCUSSION AND CONCLUSION……………………………………………………66 5.1) Discussion and Managerial Implications…………………………………………66 5.2) Conclusion, Limitations and Future Research Directions……………………69 REFERENCES………………………………………………………………………………………73 APPENDIX…………………………………………………………………………………………76 | |
dc.language.iso | en | |
dc.title | 融合競爭者訊息探討顧客忠誠度、瀏覽行為與網站行銷策略對財務績效之影響 | zh_TW |
dc.title | Incorporating Competitors’ Information to Investigate the Impact of Customer Loyalty, Browsing Behavior, and Websites’ Marketing Strategy on Financial Performance | en |
dc.type | Thesis | |
dc.date.schoolyear | 102-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 周建亨(Chien-Heng Chou),陳靜怡(Ching-I Chen) | |
dc.subject.keyword | 顧客忠誠度,瀏覽行為,黏著度,轉換率,網站行銷策略,財務績效,網路電子商務, | zh_TW |
dc.subject.keyword | customer loyalty,browsing behavior,stickiness,conversion rate,financial performance,online eCommerce, | en |
dc.relation.page | 80 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2014-06-23 | |
dc.contributor.author-college | 管理學院 | zh_TW |
dc.contributor.author-dept | 國際企業學研究所 | zh_TW |
顯示於系所單位: | 國際企業學系 |
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