品牌合作活動為基礎的顧客參與服務平台:以搜尋引擎優化之觀點 - 政大學術集成

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(1)國立政治大學資訊管理學系. 碩士學位論文. 政治大. 立品牌合作活動為基礎的顧客參與服務平台:以. ‧ 國. 學. 搜尋引擎優化之觀點. ‧. Brand Alliance-Based Campaign in Customer Engagement. Nat. n. al. er. io. sit. y. Site: A Search Engine Optimizing Perspective. Ch. engchi. i Un. v. 指導教授：苑守慈博士研究生：楊維正撰中華民國一○四年七月.

(2) Optimizing Stakeholder-Based Customer Engagement Site: A Search Engine’s Acquisition Perspective 運用錨定理論於創新服務特色之心理偏好分析. by Wei-Cheng Yang. A Dissertation Submitted in Total Fulfillment of. 治政 the Requirement for the 大 Degree of 立. ‧ 國. 學. Master of Science. ‧. in. Nat. er. io. sit. y. Management information Systems. al. n. iv n C Supervisor: Soe-Tysr Professor, MIS, NCCU h e n gYuan, chi U. Department of Management Information Systems NATIONAL CHENGCHI UNIVERSITY July 2015 © Wei-Cheng Yang 2015.

(3) 謝辭在政大這兩年，讓我的生命有著很多的沈澱，思考著許多之前不曾想過的問題。有著許多良師益友的指教及討論，讓這些生命中的問題昇華，並指引著我生命的方向。論文的完成最先要感謝苑守慈老師，在學習的每一步老師都是很有耐心地指引著我，付出了很多時間與心力，讓作為學生的我，能夠學習如何從過去前人的研究中汲取養分，如何去驗證自己的想法並付諸實現，老師總是很有耐心地把服務科學設計的核心理念，一點一滴的交付給我。不僅僅只是完成這一篇的論文，也教我學習怎麼以正確的態度來處理生活中的每一件事情。論文口試期間，感謝林宛瑩老師、宋同正老師、莊皓鈞老師、劉惠美老師給予許多論文上的建議，讓我在過程中更確立方向，並在論文的撰寫中更為完善。. 政治大也很感謝兩年的過程中，郁方老師、陳恭老師、溫肇東老師、吳豐祥老師、周彥立君老師等在專業領域上的教導，使我受益良多，並讓我更能夠具備獨自思考問. ‧ 國. 學. 題的能力。. ‧. 碩士求學的過程中，需要感謝很多的是研究所一起成長的夥伴們。哲偉和永樂，你們認真學習的態度，陪伴支持我完成論文，彼此的討論，更刺激了許多. al. er. io. sit. y. Nat. idea 的發想。一起打拼的 LAB 夥伴小巫和小志，感謝你們容忍我不成熟的領導風格，儘管過程艱辛，我們仍一起完成了這項挑戰的任務。. v. n. 感謝我親愛的家人，父親、母親、姐姐、爺爺、奶奶、外公、外婆，謝謝您們無微不至的關心與照顧，無論何時都給我陪伴與鼓勵以及無條件的支持。因為您們，我才可以無憂顧慮的學習不需要害怕挫折；也因為有您們，才給予了我成長的機會；也因為有您們，我永遠想要成為並追尋一個更好的我！很感謝您們，默默的付出以及為我所做的一切，希望我可以真實地報答您們教養以及所有一切的恩情。. Ch. engchi. I. i Un.

(4) 中文摘要. 在這個新媒體服務竄起的時代，許多中小型商家卻難以充分利用新媒體在顧客生命週期(customer life cycle)管理的過程中提升顧客參與行為。而在所有新媒體當中，搜尋引擎又被認為是獲取和發展新顧客最有效的方式之一。因此本研究在搜尋引擎的基礎上提出了一個藉由合作營銷活動最大化顧客參與的新架構。我們利用在顧客參與平台上建構反向鏈結以及長尾關鍵字服務來實現我們的架構。通過針對中小型商家和顧客的控制實驗，我們驗證了該架構的可用性和. 政治大而高網路能見度及高搜尋精準度可以幫助中小型商家提升顧客參與行為，不論是立. 效果。我們發現兩種服務對於增進網路能見度以及搜尋精準度都有明顯的提升。. ‧ 國. 學. 在顧客參與平台或是其官方網站。因此本研究認為中小型商家可以利用顧客參與平台上的服務來建立合作營銷活動，以促進顧客參與行為。在這個過程中，不僅. ‧. 有利於顧客對於品牌態度的建立也有助於其轉變為中小型商家忠實顧客的可能. n. al. er. io. sit. y. Nat. 性。. i Un. v. 關鍵字: 顧客參與行為, 品牌合作, 價值共創, 搜尋引擎優化. Ch. engchi. II.

(5) Abstract. Facing the fast-changing trend of service economy upon new media, most small and medium enterprises (SMEs) don’t have the capability to utilize new media to stimulate customer engagement behavior (CEB) through customer life cycle (acquisition, development, and retention). In all the new media, search engine is the most helpful way on acquiring and developing new customers, thus we propose a new framework based on search engine to maximizing the CEB through brand. 政治大. alliance-based campaign (which is a popular marketing strategy for SMEs to acquire. 立. new customers).. ‧ 國. 學. According to our framework, the study implements two search engine services including inlink building service and long tail keyword service on engagement site.. ‧. With conducting controlled experiments toward SMEs and customers, we testify our. Nat. sit. y. system by SMEs and the effects of services toward the customers. We find that inlink. n. al. er. io. building service and long tail keyword service increase both on high search. i Un. v. targetability and web visibility for customers. With high web visibility and search. Ch. engchi. targeatbiliy, CEB can be stimulated on engagement site and also target sites of SMEs. Thus we conclude that SMEs can use brand alliance-based campaign with our services as a trigger to stimulate CEB. With increment on engagement behavior, customer’s brand attitudes then increase and in the end become loyal customers to the SMEs.. Keywords: Customer engagement behavior, brand partnership, value co-creation, search engine optimization.. III.

(6) Table of Contents 謝辭 .......................................................................................................................................................... I 中文摘要 ................................................................................................................................................. II ABSTRACT ......................................................................................................................................... III TABLE OF CONTENTS .................................................................................................................... IV LIST OF TABLES ............................................................................................................................... VI LIST OF FIGURES .......................................................................................................................... VIII CHAPTER 1 INTRODUCTION ........................................................................................................... 1 1.1 BACKGROUND AND MOTIVATION ............................................................................................... 1. 治政大 .................................................................................................................. 5 立 .................................................................................................... 6. 1.2 RESEARCH PROBLEM ................................................................................................................. 3 1.3 RESEARCH METHOD. 1.4 PURPOSE AND CONTRIBUTION. ‧ 國. 學. 1.5 CONTENT ORGANIZATION .......................................................................................................... 7 CHAPTER 2 LITERATURE REVIEW ............................................................................................... 8. ‧. 2.1 CUSTOMER ENGAGEMENT BEHAVIOR ..................................................................................... 8 2.1.1 CEB in New media ............................................................................................................... 10. y. Nat. sit. 2.1.2 Engagement Site................................................................................................................... 12. io. er. 2.2 CEB CO-CREATION THROUGH BRAND PARTNERSHIP ........................................................... 13 2.2.2 BRAND PARTNERSHIP AS DRIVER ......................................................................................... 13. n. al. i Un. v. 2.3 SEARCH ENGINE OPTIMIZATION ........................................................................................... 14. Ch. engchi. CHAPTER 3 IENGAGEMENT PROJECT ...................................................................................... 18 3.1 THE CONCEPTUAL FRAMEWORK OF IENGAGEMENT ................................................................. 18 3.1.1 Situation – Organization and Eco-stakeholders................................................................... 19 3.1.2 Organism – E-empowerment ................................................................................................ 19 3.1.3 Behavior – CEB ................................................................................................................... 21 3.1.4 Consequence - Value conversion .......................................................................................... 21 3.2 THE SYSTEM ARCHITECTURE OF IENGAGEMENT...................................................................... 22 3.3 SYSTEM SCENARIO .................................................................................................................. 24 CHAPTER 4 THE BRAND ALLIANCED-BASED CUSTOMER ENGAGEMENT INCREMENT MECHANISM ON SEARCH EGNEINE ................................................................. 27 4.1 CONCEPTUAL FRAMEWORK................................................................................................... 27 4.2 DESIGN LOGIC AND RESEARCH APPROACH ............................................................................ 30 4.3 BRAND ALLIANCE MANAGEMENT MODULE ......................................................................... 32 IV.

(7) 4.4 BRAND ALLIANCE-BASED SEARCH ENGINE OPTIMIZATION FOR CAMPAIGN MODULE....... 33 4.4.1 Brand Alliance-based Campaign ......................................................................................... 34 4.4.2 Brand Alliance-based Campaign Keyword Suggestion ........................................................ 34 4.4.3 Brand Alliance-based Campaign Inlink Building ................................................................ 38 4.5 MEASUREMENT MODULE....................................................................................................... 40 CHAPTER 5 APPLICATION SCENARIO ....................................................................................... 42 5.1. WHY & HOW: THREE BELIEFS THAT WE HOLD AND HOW WE ACHIEVE IT ................ 43. 5.2 AN APPLICATION SCENARIO ................................................................................................... 48 CHAPTER 6 EVALUATION .............................................................................................................. 55 6.1 PROPOSITIONS ........................................................................................................................ 55 6.1.1 Assumptions ......................................................................................................................... 57. 政治大 6.2.3 Results of Controlled Experiment A ..................................................................................... 62 立 6.2 CONTROLLED EXPERIMENT A AND INTERVIEW FOR SME ................................................... 57 6.2.2 Subjects of Controlled experiment A with SME .................................................................... 61. 6.3 CONTROLLED EXPERIMENT B WITH CUSTOMERS ................................................................. 69. ‧ 國. 學. 6.3.1 Design and Objective of Experiment B ................................................................................ 70 6.3.2 Subjects of Controlled experiment 2 with customer ............................................................. 75. ‧. 6.3.3 Result of Controlled experiment 2 with customer ................................................................ 77 6.4 DISCUSSION OF FINDINGS....................................................................................................... 97. Nat. sit. y. 6.4.1 Propositions ......................................................................................................................... 97. n. al. er. io. CHAPTER 7 CONCLUSION............................................................................................................ 106. v. 7.1 CONTRIBUTIONS ................................................................................................................... 106. Ch. i Un. 7.2 MANAGERIAL IMPLICATIONS ............................................................................................... 107. engchi. 7.3 LIMITATIONS AND FUTURE WORKS ..................................................................................... 110 REFERENCES ................................................................................................................................... 111 APPENDIX A. CAMPAIGN ID 2-4 FOR WEB VISIBILITY INCREASE ON KEYWORDS CHANGING........................................................................................................................................ 116 APPENDIX B. 14 IMAGES WORDS LIST ..................................................................................... 120 APPENDIX C. SEARCH QUERIES CLICKS FROM ENGAGEMENT SITE (HTTP://TAIPEING.NET) ................................................................................................................ 121 APPENDIX D. EXPERIMENT 2 ON SUBJECT’S BACKGROUND .......................................... 123. V.

(8) List of Tables TABLE 2.1 THE BRAND PARTNER RELATIONSHIP TABLE .................................................... 14 TABLE 2.2 THE BRAND PARTNER RELATIONSHIP TABLE .................................................... 16 TABLE 4.1 EXAMPLE OF GOGOA COMPANY’S BRAND PARTNER INFORMATION........ 33 TABLE 4.2 EXAMPLE OF RECOMMENDED INLINK ................................................................ 40 TABLE 4.3 MEASUREMENT METRICS......................................................................................... 41 TABLE 6.2.1 ROLE PLAYING COMPANY SETTING ................................................................... 58 TABLE 6.2.2 CAMPAIGN SCENARIOS ........................................................................................... 58 TABLE 6.2.3 BACKGROUND OF SME SUBJECTS ....................................................................... 61. 政治大 CHANGING.......................................................................................................................................... 63 立 TABLE 6.2.4 CAMPAIGN ID 1 FOR WEB VISIBILITY INCREASE ON KEYWORDS. ‧ 國. 學. TABLE 6.2.5 CAMPAIGN ID 1 FOR WEB VISIBILITY INCREASE ON KEYWORDS CHANGING (FITNESS IS THE SCORE FROM 4.4.2, 1 IS BEST FIT FOR THE KEYWORDS AND 0 IS THE WORST) ..................................................................................................................... 66. ‧. TABLE 6.2.6 CAMPAIGN WITH IMAGE-RELATED INLINK SITE .......................................... 68. sit. y. Nat. TABLE 6.3.1 ONE-SAMPLE T TEST FOR INCREMENT OF SEARCH TARGETABILITY. io. er. FOR KEYWORDS ............................................................................................................................... 79 TABLE 6.3.2 ONE-SAMPLE T TEST FOR SUBTRACTION OF RELATED-IMAGE LINK. n. al. i Un. v. OVER IMAGE-UNRELATED CONSISTENCY .............................................................................. 81. Ch. engchi. TABLE 6.3.3 TOP 10 QUERIES FOR ENGAGEMENT SITE (TAIPEING) ................................. 82 TABLE 6.3.4 PAIRED-SAMPLE T TEST FOR AVERAGE ENGAGEMENT LEVEL DIFFERENCE IN LOW AND HIGH SEARCH TARGETABILITY KEYWORDS ..................... 84 TABLE 6.3.5 PAIRED-SAMPLE T TEST FOR AVERAGE ENGAGEMENT LEVEL DIFFERENCE IN LOW AND HIGH SEARCH TARGETABILITY INLINK SITE .................... 86 TABLE 6.3.6 PAIRED-SAMPLE T TEST FOR AVERAGE ENGAGEMENT LEVEL DIFFERENCE IN SME-REVISED AND SME-ORIGINAL-CHOOSE KEYWORDS ................ 90 TABLE 6.3.7 PAIRED-SAMPLE T TEST FOR AVERAGE ENGAGEMENT LEVEL DIFFERENCE IN SME-REVISED AND SME-ORIGIANL-CHOOSE KEYWORDS ................ 92 TABLE 6.3.8 PAIRED-SAMPLE T TEST FOR AVERAGE ENGAGEMENT LEVEL ON IMAGE-RELATED LINK AND IMAGE-UNRELATED LINK TO TARGET SITE ................... 94. VI.

(9) TABLE 6.3.9 PAIRED-SAMPLE T TEST FOR AVERAGE ENGAGEMENT LEVEL DIFFERENCE IN SME-REVISED AND SME-ORIGINAL-CHOOSE KEYWORDS ................ 96 TABLE 7.1 A COMPARISON OF MODERN PRACTICE AND IN-HOUSE ENGAGEMENT SITE (SEARCH ENGINE MODULE) ............................................................................................. 109. 立. 政治大. ‧. ‧ 國. 學. n. er. io. sit. y. Nat. al. Ch. engchi. VII. i Un. v.

(10) List of Figures FIGURE 2.1 DIMENSION OF CEB..................................................................................................... 9 FIGURE 2.2 CEB’S NEW MEDIA FRAMEWORK (ADAPTED FROM HENNIG-THURAU ET AL., 2010) .............................................................................................................................................. 10 FIGURE 2.3 ENGAGEMENT SITE FRAMEWORK (ADAPTED FROM JUDD ET AL., 2012) ................................................................................................................................................................ 12 FIGURE 3.1 IENGAGEMENT CONCEPTUAL FRAMEWORK .................................................. 19 FIGURE 3.2 IENGAGEMENT SYSTEM ARCHITECTURE ........................................................ 22 FIGURE 4.1 CREATE THE VIRTUOUS POSITIVE CYCLE IN NEW MEDIA ......................... 27. 政治大. FIGURE 4.1.1 CONCEPTUAL FRAMEWORK DIAGRAM.......................................................... 28. 立. FIGURE 4.1.2 LONG TAIL KEYWORDS SEARCH DEMAND CURVE ..................................... 28. ‧ 國. 學. FIGURE 4.2 SYSTEM ARCHITECTURE ........................................................................................ 31 FIGURE 4.3 BRAND ALLIANCE MANAGEMENT MODULE .................................................... 32. ‧. FIGURE 4.4 BRAND ALLIANCE-BASED CAMPAIGN KEYWORD STEPS............................. 35. sit. y. Nat. FIGURE 4.5 BRAND ALLIANCE-BASED CAMPAIGN KEYWORD SUGGESTION. io. er. SERVICES ............................................................................................................................................ 37 FIGURE 4.6 EXAMPLE OF BRAND ALLIANCE-BASED CAMPAIGN KEYWORD SERVICE. n. al. i Un. v. ................................................................................................................................................................ 38. Ch. engchi. FIGURE 4.7 BRAND ALLIANCE-BASED CAMPAIGN INLINK BUILDING SERVICE ......... 39 FIGURE 5.1 THE GOLDEN CIRCLE THEORY (SIMON SINEK, 2011)..................................... 43 FIGURE 5.1.3 PLAN+VALUE CO-CREATEDO+VALUE CO-CREATEACT+VALUE CO-CREATE ........................................................................................................................................ 45 FIGURE 5.1.2 GOLDEN CIRCLE OF ENGAGEMENT SITE ...................................................... 46 FIGURE 5.1.4 ENGAGEMENT SITE’S SERVICE JOURNEY ..................................................... 47 FIGURE 5.2.5 REGISTRATION PAGE ON IENGAGEMENT PLATFORM .............................. 48 FIGURE 5.2.6 THE BIG WHY OF ENGAGEMENT SITE SERVICE .......................................... 49 FIGURE 5.2.7 THE HOW OF ENGAGEMENT SITE SERVICE THROUGH DIFFERENT MEDIA .................................................................................................................................................. 50. VIII.

(11) FIGURE 5.2.8 THE BRAND ALLIANCE PARTNER MATCHING SERVICE THROUGH IMAGE .................................................................................................................................................. 51 FIGURE 5.2.9 THREE MAIN COMPONENT OF ENGAGEMENT SITE SERVICE................. 52 FIGURE 5.2.10 DATA OBSERVATION COMPONENT ................................................................. 52 FIGURE 5.2.11 START OF THE CAMPAIGN LABORATORY .................................................... 53 FIGURE 5.2.12 CAMPAIGN THERMOMETER REAL-TIME DECISION SUPPORT FOR MULTI-MEDIA .................................................................................................................................... 54 FIGURE 6.2.1 THE PROCEDURE OF CONTROLLED EXPERIMENT FOR SME .................. 57 FIGURE 6.2.2 BRAND ALLIANCE CAMPAIGN INFORMATION ............................................. 59 FIGURE 6.2.3 FOUR CAMPAIGNS THAT PROPAGATED WITH SME .................................... 61. 政治大. FIGURE 6.3.4 NUMBER OF KEYWORDS THAT LET THE CAMPAIGN APPEAR IN TOP 10 PAGES OF GOOGLE SEARCH RESULT ........................................................................................ 67. 立. FIGURE 6.3.1 THE PROCEDURE OF CONTROLLED EXPERIMENT FOR SME .................. 70. ‧ 國. 學. FIGURE 6.3.2 BRAND ALLIANCE CAMPAIGN INFORMATION ............................................. 71 FIGURE 6.3.3 MEASURE THE TARGETABILITY OF KEYWORDS AND LINKS .................. 71. ‧. FIGURE 6.3.4 BETWEEN BRAND CONSISTENCY SCORE ....................................................... 72. Nat. sit. y. FIGURE 6.3.5 BRAND AND CAMPAIGN CONSISTENCY SCORE ............................................ 72. er. io. FIGURE 6.3.6 IMAGE DISTINGUISH ABILITY SCORE FOR SUBJECT 1 .............................. 73. al. n. iv n C FIGURE 6.3.8 FOUR SCENARIOS TOh TEST THE ENGAGEMENT LEVEL OF CUSTOMERS engchi U ................................................................................................................................................................ 74 FIGURE 6.3.7 IMAGES SELECTION FOR CAMPAIGN, BRANDS, SITE AND FAVORITE .. 73. FIGURE 6.3.9 IMAGE-RELATED INLINK SITE ENGAGEMENT LEVEL .............................. 74 FIGURE 6.3.10 SME-REVISED INLINK LONG TAIL KEYWORD ............................................ 75 FIGURE 6.3.11 DEMOGRAPHICS OF GENDER ........................................................................... 76 FIGURE 6.3.12 DEMOGRAPHICS OF MAJOR ............................................................................. 76 FIGURE 6.3.13 DEMOGRAPHICS OF EDUCATIONAL BACKGROUND ................................ 76 FIGURE 6.3.14 HOURS OF SPENDING ON SURFING INTERNET PER DAY ......................... 77 FIGURE 6.3.15 SME-ORIGINAL-CHOOSE KEYWORDS VS SME-REVISED LONG TAIL KEYWORDS SEARCH TARGETABILITY ..................................................................................... 78. IX.

(12) FIGURE 6.3.16 HYPOTHESIS OF THE TESTING FOR LINKING SERVICE INCREASE IN SEARCH TARGETABILITY ............................................................................................................. 78 FIGURE 6.3.17 IMAGE-RELATED VS IMAGE-UNRELATED INLINK SITE SEARCH TARGETABILITY ............................................................................................................................... 79 FIGURE 6.3.18 SUBTRACTION OF IMAGE- RELATED INLINK OVER IMAGE-UNRELATED INLINK CONSISTENCY WITH CAMPAIGN AND BRANDS ............. 80 FIGURE 6.3.19 SUBTRACTION OF RELATED-IMAGE LINK OVER IMAGE-UNRELATED CONSISTENCY ................................................................................................................................... 81 FIGURE 6.3.20 HIGH SEARCH TARGETABILITY KEYWORDS ENGAGEMENT LEVEL . 83 FIGURE 6.3.21 LOW SEARCH TARGETABILITY KEYWORDS ENGAGEMENT LEVEL... 83 FIGURE 6.3.22 HYPOTHESIS OF THE TESTING FOR AVERAGE ENGAGEMENT LEVEL. 政治大 FIGURE 6.3.23 HIGH SEARCH TARGETABILITY INLINK SITE ENGAGEMENT LEVEL 85 立 DIFFERENCE IN LOW AND HIGH SEARCH TARGETABILITY KEYWORDS ..................... 84. ‧ 國. 學. FIGURE 6.3.24 LOW SEARCH TARGETABILITY INLINK SITE ENGAGEMENT LEVEL . 85 FIGURE 6.3.25 HYPOTHESIS OF THE TESTING FOR AVERAGE ENGAGEMENT LEVEL. ‧. DIFFERENCE IN LOW AND HIGH SEARCH TARGETABILITY INLINK SITE .................... 85 FIGURE 6.3.26 CAMPAIGN AND PARTNER IMAGE CONSISTENCY VS AVERAGE. Nat. sit. y. ENGAGEMENT LEVEL .................................................................................................................... 86. al. er. io. FIGURE 6.3.27 ENGAGEMENT SITE AVERAGE ENGAGEMENT SCORE VS TARGET SITE. n. AVERAGE ENGAGEMENT SCORE ................................................................................................ 87. Ch. i Un. v. FIGURE 6.3.28 PEARSON CORRELATION BETWEEN ENGAGEMENT SITE AVERAGE. engchi. ENGAGEMENT SCORE AND TARGET SITE AVERAGE ENGAGEMENT SCORE............... 87 FIGURE 6.3.29 ENGAGEMENT BEHAVIOR SCORE DIFFERENCE BETWEEN BRANDS IN ONE CAMPAIGN ................................................................................................................................ 88 FIGURE 6.3.30 SME-ORIGINAL-CHOOSE KEYWORDS ENGAGEMENT LEVEL ON ENGAGEMENT SITE ......................................................................................................................... 89 FIGURE 6.3.31 SME-REVISED LONG TAIL KEYWORDS ENGAGEMENT LEVEL ON ENGAGEMENT SITE ......................................................................................................................... 89 FIGURE 6.3.32 HYPOTHESIS OF THE TESTING FOR AVERAGE ENGAGEMENT LEVEL ON ENGAGEMENT SITES DIFFERENCE SME-REVISED AND SME-ORIGINAL-CHOOSE KEYWORDS ........................................................................................................................................ 90 FIGURE 6.3.33 SME-ORIGINAL-CHOOSE LONG TAIL KEYWORDS TO TARGET SITE FROM ENGAGEMENT SITE ON ENGAGEMENT LEVEL ........................................................ 91 X.

(13) FIGURE 6.3.34 SME-REVISED LONG TAIL KEYWORDS TO TARGET SITE FROM ENGAGEMENT SITE ON ENGAGEMENT LEVEL ..................................................................... 91 FIGURE 6.3.35 HYPOTHESIS OF THE TESTING FOR AVERAGE ENGAGEMENT LEVEL ON ENGAGEMENT SITES DIFFERENCE SME-REVISED AND SME-ORIGIANL-CHOOSE KEYWORDS ........................................................................................................................................ 92 FIGURE 6.3.36 IMAGE-RELATED LINK ENGAGEMENT LEVEL (FOR THE CAMPAIGN) ................................................................................................................................................................ 93 FIGURE 6.3.37 IMAGE-UNRELATED LINK ENGAGEMENT LEVEL (FOR THE CAMPAIGN)......................................................................................................................................... 94 FIGURE 6.3.38 HYPOTHESIS OF THE TESTING FOR AVERAGE ENGAGEMENT LEVEL ON IMAGE-RELATED LINK AND IMAGE-UNRELATED LINK TO TARGET SITE ............ 94. 政治大. FIGURE 6.3.39 IMAGE-RELATED LINK TO TARGET SITE ENGAGEMENT LEVEL (FOR THE CAMPAIGN) ............................................................................................................................... 95. 立. FIGURE 6.3.40 IMAGE-UNRELATED LINK TO TARGET SITE ENGAGEMENT LEVEL. ‧ 國. 學. (FOR THE CAMPAIGN)..................................................................................................................... 95 FIGURE 6.3.41 HYPOTHESIS OF THE TESTING FOR AVERAGE ENGAGEMENT LEVEL. ‧. ON IMAGE-RELATED LINK AND IMAGE-UNRELATED LINK .............................................. 96 FIGURE 6.4.1 PROPOSITIONS ........................................................................................................ 97. y. Nat. io. sit. FIGURE 6.4.2 MAX FITNESS KEYWORDS SEARCH TARGETABILITY COMPARISON ... 99. n. al. er. FIGURE 6.4.3 IMAGE-UNRELATED INLINK SITE (LEFT) VS IMAGE-RELATED INLINK. i Un. v. SITE (RIGHT) .................................................................................................................................... 100. Ch. engchi. FIGURE 6.4.4 HIGH IMAGE DISTINGUISH ABILITY CUSTOMERS JUDGEMENT OVER IMAGE-RELATED AND IMAGE-UNRELATED LINK CONSISTENCY ................................. 101 FIGURE 6.4.5 LOW IMAGE DISTINGUISH ABILITY CUSTOMERS JUDGEMENT OVER IMAGE-RELATED AND IMAGE-UNRELATED LINK CONSISTENCY ................................. 101 FIGURE 6.4.6 HIGH CAMPAIGN AND PARTNER IMAGE CONSISTENCY INLINK SITE ENGAGEMENT LEVEL .................................................................................................................. 103 FIGURE 6.4.7 LOW CAMPAIGN AND PARTNER IMAGE CONSISTENCY INLINK SITE ENGAGEMENT LEVEL .................................................................................................................. 103. XI.

(14) CHAPTER 1 INTRODUCTION 1.1 Background and Motivation In the current era of service economy, there are three important trends (Omar & Francis, 2013) that the new media have changed how CEOs and CMOs’ marketing strategy from traditional media in the dynamic digital marketing as follows: (a) Primacy of the Customer Experience: As in a world of experiential goods and digital services, customer experience becomes primate as value is primarily created through the process of consumption and the experience. 政治大. through digital platform. (b) Distributed Co-Creation of Value: The way that. 立. value is created in the digital marketing become more complex. Vargo and Lusch. ‧ 國. 學. (2004, 2008) brought up a new concept in the marketing field called service-dominant logic (SDL) and claimed that value now is co-created by not. ‧. only firms but also customers and other stakeholders. (c) Continuous. y. Nat. io. sit. Sense-and-Respond Experimentation: The key changes in digital platforms with. er. the proliferation of ubiquitous access, ease of capturing data, and digital services,. al. n. iv n Ctoh engage in continuous engchi U experimentation in ways they could not before. will. enable. enterprises. sense-and-respond. First, for the trend on primacy of customer experience, there are more and more executives focusing beyond product quality and value as a driver of firm performance, and marketing scholars have begun to focus on customer-based metrics for measuring organizational performance (Forrester Consulting, 2008). Researchers have proposed to measure the customer engagement behavior (CEB) (van Doorn et al., 2010), going beyond transactions, and may be specifically defined as a customer’s behavioral manifestations that have a brand or firm focus, resulting from motivational drivers. In today’s digital economy, actions of 1.

(15) the focal firm and its customers are highly transparent and visible to customers of other firms. Over time, such cross-brand and cross-customer utilization of information in the public domain can affect the entire industry (van Doorn et al., 2010). Thus, engaged customers may play a very important role of monitoring firm performance and disseminating information to multiple stakeholders. Customer engagement thus has consequences for many different stakeholders including the focal customer, the focal brand/firm, as well as other constituents. Second, for the trend on distributed co-creation of value, Ramaswamy and Gouillart (2010) mentioned that new media could help accelerate the process of. 治政 value co-creation, a valuable activity completed 大 by two or more stakeholders 立 (Sander & Stappers, 2008). The process of value co-creation can be categorized ‧ 國. 學. into four periods: design, analysis, development, and full launch (Hao et al.,. ‧. 2014). This study will focus on improving the design, analysis and development. sit. y. Nat. phases of value co-creation on the new media environment. New media are. io. er. defined as websites and other digital communication and information channels in. al. n. which active consumers engage in behaviors that can be consumed by others both in real time and. iv n C long h afterwards regardless e n g c h i U of. their spatial location. (Hennig-Thurau al., 2010). Among all the media, the one this study will focus on will be search engine. A 2011 Pew Internet study (Purcell et al., 2012) found that about 59% of Internet users use search engines on a typical day. Thus we believe effort should be made on search engine to achieve the goal of value co-creation. Third, for the trend on Continuous Sense-and-Respond Experimentation, there is a need of continuous and fast response service system to collect and react in the dynamic digital environment. The service system that this study will propose to catch the dynamical CEB change in new media reference to an engagement site mentioned in a US patent (Judd et al., 2012). The engagement 2.

(16) site creates and sends electronic communications to customers and prospective customers, and publishes and store electronic communications. Through collecting CEB in multi-media constantly, marketers can then conduct the correct strategy to act on their targeted customer and thus bring deeper engagement level and help adjust the process of value co-creation. 1.2 Research Problem In the new media era, the CEOs and the marketers will have to react to these three important trends, but the reality can’t match the trend exactly. A Yesmail. 治政 and Gleanster's study (2013) found that 80 大 percent of consumer-facing 立 companies don't understand their customers beyond basic demographics and ‧ 國. 學. purchase history. It reveals that though marketers think they know their. sit. y. Nat. develop personalized, relevant service in new media era.. ‧. customers well, they still lack the deep data insights that would enable them to. io. er. We argue that focusing on problem of CEB that will close the gap in pursuit. al. of the future trends as enlisted below. (1) CEB shortens the gap of Primacy of. n. iv n C the Customer Experience: it focuses on customer’s behavioral manifestations heng chi U which go beyond the transactional data and thus give more insight about customer’s experience. (2) CEB shortens the gap of Distributed Co-Creation of Value: Through CEB, customer and brand partners can contribute their resources within their networks (Nambisan & Baron, 2009) to co-create value with the focal firm. (3) CEB shortens the gap of Continuous Sense-and-Respond Experimentation: Through new media, constant collection of the CEB data can get the insight of the target customers so that firms can choose different strategy to react to the market. 3.

(17) As our study will focus on the search engine of new media, the most relevant existing research about search engine marketing approaches are search engine optimization (SEO) techniques. Search Engine Optimization (Solihin, 2013) is the process of increasing the number of visitors to a website by achieving high ranking of the search results returned by a search engine. Common SEO techniques can be categorized into four categories (Solihin, 2013): Keyword research, Indexing, On-page, and Off-page optimization. Keyword research helps sites to maximize the click through rate by identifying the popular keyword trend and similarity of keyword with the products. Indexing makes sure. 治政 the accessibility of a website to search engine 大 spider. On-page optimization 立 refers to the alteration of numerous on-page elements to help search engine ‧ 國. 學. spiders determine what the page is about and how it may be useful for users.. ‧. Off-page optimization refers to the link building process that influences how. sit. y. Nat. search engines rank a web page. As we review search engine optimizing. io. er. approaches, we find that instead of focusing on CEB, marketers put their effort on maximization of page visit which is a minimum level of CEB since it’s the. al. n. iv n C easiest way to measure and improve. example by pursue the goal of CEB, h e n For gchi U. the company can focus on the target audience’s interaction compared to putting lots of effort on high exposure advertisement or events. Also through the interpretation of CEB, company can get a deeper understanding of customers and thus choose the right strategy to constantly react. Thus we concluded our research problem as following: (1) What are the factors to maximize customer engagement behavior through the search engine of new media and how does it influence engagement behavior? (2) What service shall we provide to maximize the customer engagement level in search engine? 4.

(18) 1.3 Research Method As we can see the gap under the search engine, there is lack of real application to react on CEB quickly and responsively with the brand partners. To design the innovated application, we choose to develop an engagement site to collect, analyze and stimulate the CEB of customers of which the idea comes from the US patent (Judd et al., 2012). In the origin patent, the engagement site includes only data from social media, forum and other customer-related data with email module and web content builder to engage with target customer. In this study, we. 政治大. restructure Engagement site to extend the brand partnership and realize it in. 立. three ways:. ‧ 國. 學. (1) Extending the value co-creation through brand partnership: Firms might benefit from building brand relationships with their brand partners,. ‧. especially service-dominant firm (Merz & Vargo, 2009). Through identifying. Nat. sit. y. and involving the brand partners, our engagement site works not only for the. n. al. er. io. customers but also design for brand partners. The engagement site through. i Un. v. search engine perspective helps identify and disclose information about. Ch. engchi. possible brand partners under the new media.. (2) Creating Engagement site services beyond email and web content builder: Through extending the engagement site services, it helps marketers to further stimulate their customers’ CEB. The increment of Engagement site services have one big objective that is to help better engage with the brand partners to value co-create and be able to deliver the value to the targeted customers. (3) Adjusting the engagement site services through CEB to achieve brand partners based optimization: Through collecting CEB not only from the firm’s website but also the engagement site, we can evaluate whether or not 5.

(19) our co-creation value have been delivered and constantly react the CEB with close interaction with brand partners. All in all, through development of engagement site we believe we can shorten the gap between future new media trend of primacy of customer experience, distributed co-creation value and continuous sense-and-response experimentation by cultivating and monitoring of CEB with brand partners. 1.4 Purpose and Contribution The aim of this study is to develop a way to maximize the engagement level. 治政 under search engine perspectives within the context 大 of different related brand 立 partners. In addition, our system will develop for each focal business to let them ‧ 國. 學. optimize CEB. There are two general purposes: one is to help the focal firm. ‧. identify and involve their brand partners to value co-create and develop customer. sit. y. Nat. primacy services. The other one is to optimize the engagement level under the. io. er. scope of brand partners.. al. Through developing the above purposes, our study will give two major. n. iv n C contributions to management implications. h e n g c hFirst, i Uthrough co-creation business could provide a more customer-centric service and bring more value to customers which in terms create the competitive advantage over its competitors. Second, optimizing CEB in a stakeholders’ point of view help the brand create the impact not only responsive but also sustainable. For example, there is a small business in service industry; it is pretty new and quite unknown to most of their customers. They decide to establish a marketing strategy which puts focus on identifying suitable brand partners to co-create their services and how to decrease the threshold of potential customers’ finding time to find their co-created service. And they may pay attention to keep 6.

(20) the brand image consistent under the new media environment. Through co-creating with their service with brand partners and stimulating CEB in new media under our system, the firm can reduce their cost and time on identifying brand partners, delivering their co-create services, and measuring the consequence of the co-create services in terms of CEB.. 1.5 Content Organization In Chapter 1, we elaborate the current new media environment to provide an. 政治大. overall view of our research background, motivations and define the research problem and purposes.. 立. ‧ 國. 學. In Chapter 2, which is the literature review section, we will discuss and try to find the theoretical support (e.g. CEB, CEB co-creation, engagement site,. ‧. search engine optimization) that can help us define the specific objectives that. Nat. sit. y. are extended from Chapter 1 and build the knowledge base.. n. al. er. io. In Chapter 3, we get a bigger picture of iEngagement project through. i Un. v. building the conceptual framework and its architecture. At the end of Chapter 3,. Ch. engchi. we develop a scenario to give reader an idea of our system’s value. In Chapter 4, we build a conceptual framework from the review and finding in the Chapter 2 and try to use information technology to develop a possible solution that can be realized. An engagement site of maximization CEB of brand partners-based will be introduced in detail. In Chapter 5, we sum up the contribution of the study from the academic and the industrial point of view and the future work that will be developed.. 7.

(21) CHAPTER 2 LITERATURE REVIEW In this chapter, we discuss the foundations and methodologies as the background knowledge of our research. The review of the CEB, CEB in new media, CEB co-creation through brand partnership, engagement site and search engine optimization are elaborated in order to build the fundamental as the required to sustain the research. 2.1 Customer Engagement Behavior. 政治大 specific firm or brand driven motivation that has beyond purchase of behavioral 立 The definition of CEB, as described in Chapter 1, is customer engagement with. ‧ 國. 學. focus (van Doorn et al., 2010). CEB is extended from customer engagement which is a concept focus on the business and customer relationship in terms of. ‧. the emphasis on the customer primacy experience. As Brodie et.al (2011). Nat. sit. y. reviews those different dimensions of customer engagement, including. n. al. er. io. emotional, cognitive, and behavioral. However, it’s easier to collect and analyze. i Un. v. the customer engagement behavior especially from the new media because the. Ch. engchi. customer behavior data can now be recorded through different new media platform according to different business practices (Forrester, 2008; Levy, 2013). On the other hand we can not only get an understanding of customer’s cognitive and emotional level through collecting CEB but also stimulate customer’s cognitive and emotional level of engagement through stimulating the CEB (van Doorn et al., 2010).. 8.

(22) Valence. modality. scope. CEB nature of impact. customer goals. 政治大立Figure 2.1 Dimension of CEB. ‧ 國. 學. CEB can be divided into five dimensions (See Figure 2.1), including valence, modality, scope, nature of impact, customer goals (van Doorn et al.,. ‧. 2010). With these five dimensions, the CEB could be determined into being. Nat. sit. y. positive to negative (i.e., valence), through different ways of engagement. n. al. er. io. practices such as WOM and blogging (i.e., modality), variety of temporal or. i Un. v. geographic scope (i.e., scope), different breadth or longevity of impacts (i.e.,. Ch. engchi. nature of impact), and diversity of customer’s goal (i.e., customer goals). For example, the KitKat have conducted a series of activities that ask customer feedback on their favorite favor which caused positive feedback, though Facebook and online forum to engage their opinions, focusing more on region of UK, being continued ever since 2012, and understand different user’s goal through the feedback and thus create a success in increasing 8% of teenager’s market. As we reviewed the definition and five dimensions of CEB, we will develop a mechanism to achieve CEB for a firm or a brand using 9.

(23) non-transactional customer behavior data on search engine. In addition, the mechanism will also include the development of the measurements of CEB on the five dimensions. 2.1.1 CEB in New media The new media era has given opportunity for marketers to analyze CEB, because nowadays new media could record most of the CEB that customer conduct on the website and execute different strategies through new media. A conceptual framework of CEB in new media has been developed (Hennig-Thurau et al.,. 治政 2010) to identify the relationship between customer, 大 firm and new media. The 立 main contribution of the study is dividing new media into 4 kinds of information ‧ 國. 學. & services and 6 main technologies (e.g., search engine) to stimulate a virtual. ‧. circle of realizing CEB through new media (See Figure 2.2). Our study will. sit. y. Nat. focus on helping the firm conduct the arrow (1) by building up the information. io. n. al. Company/Brand (1). er. & services through monitoring CEB data that generated from arrow (2) & (3) . Marketing actions & outcomes. Ch. engchi U (2). v Customer i n- Brand Attitudes - New Media Attitudes. New Media Information & service s Technologies. (3). Other Consumers - Affect and behavior. Figure 2.2 CEB’s New Media Framework (adapted from Hennig-Thurau et al., 2010). 10.

(24) In the framework, Hennig-Thurau et al. (2012) deduced two main reasons to affect CEB, including brand attitude (e.g.,satisfaction, liking) and new media attitudes (e.g., utilitarian, social-psychological). For new media attitudes, there’s little firm can do except communicate through multi-channel among new media and simplify the UI to stimulate the CEB. For brand attitudes, a firm thus intends to build positive image and satisfy its customers. According to van Doorn et.al (2010), customer’s brand attitude could also be affected by brand’s equity or reward provision, and also by establishing the processes and platforms to support specific customer actions (e.g., suggestions, ideas). For brand equity, Firm with. 治政 high reputation and equity are likely to induce higher 大 levels of positive CEB 立 (Walsh, 2009). For providing rewards, firms give incentives to customers that ‧ 國. 學. have referral actions and thus increase the CEB. For developing the processes. ‧. and support for specific customer actions, firms now use IT to build processes. sit. y. Nat. for customer to conduct C2C and also C2B conversation through platforms such. io. er. as online chat forums, event pages, and engagement site which will discuss in. al. 2.1.2 section. Through the improvement on the brand attitudes by increasing. n. iv n C brand equity, providing rewardhprovision, and giving e n g c h i U platforms for customer to co-create, firm can form the positive virtual circle from the virtual to real cycle.. As we review the CEB and CEB in new media, we build fundamental background and idea of how to stimulate CEB and form the virtual to real positive cycle. However, in chapter one, we can see there is still gap for development of the positive circle. Thus, we intend to provide a practical implementation in search engine perspective to help firm to rebuild the positive cycle of CEB.. 11.

(25) 2.1.2 Engagement Site As previous section 2.1.1 mentioned that there are several platforms to conduct the engagement of customer including the engagement site. An engagement site intends to cultivate the CEB through web page building and email module (Judd et al., 2012). It has the following characteristics. The engagement site collects support data from social media, image/creative assets, user content, etc. Based on the analysis of supporting data, marketers can build the web pages on the engagement site and email content to further engage the customers. Also, the. 政治大 visibility of main website through increasing of PageRank and showing up twice 立. engagement site has different domain name so that it can increase the business’. ‧ 國. 學. time in the search engine. Our study will build up our engagement site which is inspired from the patent but in the enabling the positive CEB cycle’s point of. Nat. User Module. New Market. Media. Manager. Services. sit media Brand aSocial v Brand Partners i l C Partnership hengchi Un. n. Board. Delivery. er. io. CEB. Support Data. y. ‧. view (See Figure 2.3).. Recommend er. New. System. Media. Consumers. Platform. And Customers. Search Engine. Figure 2.3 Engagement Site Framework (adapted from Judd et al., 2012). 12.

(26) 2.2 CEB Co-creation through Brand partnership Nowadays, the concept of value co-creation is more and more important as the industry now are more focusing on customer centric experience and service. In addition, service industries take rise to 75 percent of the gross domestic product of developed nations (Larson, 2008). Value co-creation could be divided as three parts: First is “Value”, what kind of value being delivered and deliver to whom? Second is “Co”, by what kind of resources integration (e.g., B2C, B2C, B2B). Third is “Creation”, through what kind of mechanism? (e.g., social media, online. 政治大 part we focus on C2B and B2C behavior actions; for the creation part, we create 立. forum). In this study, for value part we take CEB as the value proposition; for Co. ‧ 國. 學. CEB on the new media of search engine and driven by brand partnership as our mechanism. Thus, we build the CEB co-creation for the value co-creation.. ‧. 2.2.2 Brand partnership as driver. sit. y. Nat. n. al. er. io. Nowadays, brand partnership has been raised as an attractive management option. i Un. v. for past three decades to extend the brand equities (Besharat & Langan,. Ch. engchi. 2014).As mention in section 2.1.1, Firms with higher brand equity have higher possibility to stimulate higher CEB. Thus, there are strong driver for brand to get partnership for further attracting new customers in the new media platform. We reviewed different brand partnership papers and categorize the following three level of categories (from low to high), including co-advertising, Cause-related marketing, co-branding (See Table 2.1).. 13.

(27) Table 2.1 the brand partner relationship table Partner relationship. Definition Co-advertising is defined as the partnership that firms jointly promote their products together through advertising. Co-advertising. for achieving brand awareness and knowledge. The duration of the relationship normally last 3-4 months.(d’Astous et al., 2007) Cause-related marketing is defined as the partnership that. 政治大. improves a company’s corporate social reputation with a. 學. marketing. 立. cause through partnering to introduce a new (or existing). ‧ 國. Cause-related. product (Dickinson & Barker, 2007). For example, Apple accompanies with Motorola hit a success with Product Red. ‧. through funding hundreds of millions to AIDs globally.. y. Nat. sit. Long term alliances between two or more brands to create. n. al. er. io. new product or service for entering an existing or new Co-branding. i Un. v. market. The identity of the co-branded brands is. Ch. engchi. communicated through the inclusion of the brand names on the product or service (Walchli, 2007).. 2.3 Search Engine Optimization To help the firm start the brand partnership and engage customers with search engine, we reviewed the existed search engine optimization methods. As we described in section 2.3, search engine optimization have these four methods, including keyword research, indexing, on-page optimization, and off-page optimization (Solihin, 2013). In this study, we will focus on keyword research 14.

(28) and off-page optimization (link optimization), because these two are the core elements for optimization that have many discussed papers of methods. In our study, Link optimization is an optimization problem on PageRank. PageRank (Page et al., 1999) is one of the most popular search engine ranking algorithms through link structure which is originally used by Google. PageRank can be divided into two parts to simulate a random web surfer, including personalization part and surfing through link part. Personalization part determined from individual, mimicking the behavior that user enter an url directly. For surfing through link part, determined from the behavior that user. relevant content and forming a better link structure.. 學. ‧ 國. 治政 surfs the web by clicking through link in the site. 大For optimization purpose, 立 these two parts should both manipulate and optimize through building links to ‧. Keyword research in our study is also an optimization problem that we. sit. y. Nat. want to provide service to give keyword suggestion for focal firm and its brand. io. al. er. partners so that target customers can easily find the brand alliance-based. n. campaign content on engagement site and co-create CEB value. We review different techniques of. iv n C keyword including h e n gresearch, chi U. meta-tag spiders,. proximity-based technique, query-log mining, advertiser-log mining, TermsNet, and using GA method to optimize query (See Table 2.2). We found that except GA method the keyword generation methods need a seed term to do the generations of keywords. However, most of the time marketers may not sure which keyword seed term to use. On the other hand, GA method can accept user-defined description as input and suggest the keywords based on the search results which will change through time. Additionally, GA method provides the optimization of the query so that through the method can generate ranked query which fits our optimization in search engine perspective. There is one setback of 15.

(29) the GA method which generates query that only a few people using these kind of query, since the GA method is originally developed to generate diverse and long query to search for topical documents. For example yahoo site wants to add the documents of different categories, they can use this method. To solve this setback, we will limit the query length. Table 2.2 the brand partner relationship table Keyword generation Definition techniques. 治政大highly ranked webpages. extracts meta-tag words from these 立. A meta-tag spider queries search engine for seed keyword and. Proximity-based tools issue queries to a search engine to get. 學. Proximity-based technique. highly ranked webpages for the seed keyword and expand the. ‧. ‧ 國. meta-tag spider. seed with words found in its proximity.. Nat. sit. y. The Google Adwords Tool (https://www.google.com/adwords/). n. al. er. io. relies on query log mining for keyword generation. Pick up the. query log mining. i Un. v. query that has the seed term and generate the query that include. Ch. the seed term.. engchi. To avoid only generating the query that includes the seed term. Google Adwords (https://www.google.com/adwords/) also advertiser-log mining consider mining through the advertiser search logs to add more variety. Including the relationship between words through top search TermsNet. result snippets’ word connection and then output the ranked keywords (Joshi & Motwani, 2006).. 16.

(30) A technique through user defined description to select good query terms through web search result by genetic algorithm. By crossover and mutation to generate query diversity and GA method optimization through iterations of matching similarity between user-defined description and search result documents (Cecchini et al., 2007).. As reviewed through the CEB (section 2.1), we know that the five dimensions of CEB which will further being used in development of the CEB measurement. 治政 CEB cycle in the New media framework which will大 be further developed in our 立 matrix (section 4.4), how the CEB could be stimulated and form the virtual positive. conceptual framework.. ‧ 國. 學. After that we further extended the virtual cycle through CEB co-creation in the. ‧. ways of brand partnership (inspired from the notion in new media framework’s. sit. y. Nat. brand attitude). Reviewing the different levels of brand partnership and derive. io. er. insight from a patent’s framework to heat up the bigger cycle with brand partners.. al. At the search engine optimization section, we dig down with existing method. n. iv n C of search engine optimization. With of the keyword research and h the e nunderstanding gchi U link optimization, we can then develop the practical implementation on the engagement site to build the CEB positive cycle in the perspectives of search engine.. 17.

(31) CHAPTER 3 iEngagement PROJECT The purpose of this chapter is to describe an overview of our whole research project – “iEngagement”. iEngagement means integrated engagement in multi-media. The objective of the iEngagement research project aims at helping firm achieve the maximization of CEB (i.e., Vising rate, WOM, Shares, and Referral) in the new media’s ecosystem. The new media can be divided into 10 categories, including technologies and service & information (Hennig-Thurau et al., 2010), and we found that we can combine three new media including. 政治大 the 6 technologies (e.g., search bot, shopping bot, mobile technologies) and 4 立. recommender system, search engine, and social media to cover the capacity of. ‧ 國. 學. new media services (e.g., online communities, Customer as retailers). Through development of these three new media platforms, we can then cover the major. ‧. new media as our embodiment. This project will develop an interactive. Nat. sit. y. framework that study how value creation are actually applied in customer. al. n. ecosystems.. er. io. engagement behaviors (CEBs) through new media channels in service. Ch. engchi. i Un. v. The first section describes the conceptual framework of iEngagement research project (Chou & Yuan, 2014). Next, an introduction of the system architecture is provided. In the third section, we use an example to illustrate how the system works. 3.1 The Conceptual Framework of iEngagement In this study, we categorize the CEB stimulation process (See Figure 3.1) as four components, including situation organism, behavior and consequence which. 18.

(32) derived from Chou & Yuan (2014) and will further discuss in the following four subsections.. 3.1.1 Situation – Organization and Eco-stakeholders. 學. ‧ 國. 政治大 Figure 3.1 立iEngagement Conceptual Framework ‧. Nowadays in digital service ecosystems, there are not only fast-paced, but also. Nat. sit. y. turbulent (El Sawy & Francis, 2013). Turbulence is a causal texture of the. n. al. er. io. environment that stems from complex interconnectedness between players. i Un. v. (Selsky et al. 2007). All players are interconnected with the ecosystem,. Ch. engchi. competitors must often work together in “coopetition”, for example to establish technical standards or common platforms. This means the individual must compete as a value-adder and that the number of competitors may be quite different in a value network to those in a value chain. This combination of cooperative and competitive processes has been termed “co-opetition” (Bengtsson & Kock, 1999). 3.1.2 Organism – E-empowerment. 19.

(33) As the rise of new media channels such as, Google, YouTube and Facebook, which enable customers to take a more active role as market players and reach almost everyone at anywhere and anytime. Different from the traditional role of Internet channel, new media allows consumers to reach other consumers and companies almost anywhere at any time through their mobile devices. That is, new media also empowered consumers to promote and distribute their own offers (Hennig-Thurau et al., 2010). In this study, we refer e-empowerment as to the empowerment perceived by customers on the new media toward the firm. From resource exchange theory and affect theory of social exchange,. 治政 Verleye et al. (2013) argued that managerial processes 大 that generate positive 立 customer affect toward the firm result in CEBs that benefit the firm and its ‧ 國. 學. stakeholders. Resource exchange theory (Foa 1971) holds that people exchange. ‧. resources that are similar in terms of concreteness and particularism. In line with. sit. y. Nat. social exchange theory (Blau 2004), Verleye et al. (2013) labeled exchanges. io. er. beyond mere economic obligations as “social exchanges”. The affect theory of. al. social exchange (Lawler 2006) holds that social exchanges are driven by. n. iv n C customer affect. Based on thishtheory, Verleye et e n g c h i Ual. (2013) hypothesized that. higher levels of customer affect toward the firm (i.e., positive feelings toward the firm) increase customers’ likelihood to show CEBs that benefit the firm and its stakeholders. From role theory (Kahn et al. 1964), Verleye et al. (2013) assumed that customers’ willingness to show CEBs that benefit the firm and its stakeholders depends not only on customers’ affect toward the firm but also on their role readiness. In line with Verleye et al. (2013), we define customer role readiness as the degree to which customers feel prepared for encounters with the organization in terms of feeling confident and having the appropriate knowledge and skills. 20.

(34) Verleye et al. (2013) proposed that not only customer compliance but also other CEBs depend on customer role readiness. Customers who do not have the appropriate knowledge or skills for encounters with the organization might be less willing to feedback to service system, or give suggestions for service improvement. Thus, we propose that e-empowerment perceived by customer increases customer role readiness, resulting in higher levels of CEBs. 3.1.3 Behavior – CEB Customers now have opportunities to show their engagement to the firm and its. 治政 eco-stakeholders, since they increasingly participate 大in the creation, production, 立 and delivery of service (Zeithaml et al., 2009). In an increasingly networked ‧ 國. 學. society, customers cannot only show CEBs in interactions with firms and their. ‧. employees. Customers can also show CEBs in C2C interactions by helping other. sit. y. Nat. customers and spreading positive WOM behaviors. Therefore, we identify CEBs. io. er. into two types of engaged objects: C2B&C2S and C2C CEBs. Customers. al. usually exhibit three types of C2B&C2S CEBs in interactions with firms and. n. iv n C their stakeholders: cooperation,h feedback, and compliance (Verleye et al., 2013). engchi U 3.1.4 Consequence - Value conversion. The value of a customer’s contribution to initiating new product and service innovation ideas needs to be included as a component of CE value. With such customer participation, manufacturers have the potential to enhance product innovation and to speed up the development process, both of which are key objectives of managers to lower costs and improve market acceptance of new offerings. As a result, the extent to which customers are willing to engage in conversations can significantly influence a firm’s value, especially as it affects 21.

(35) what customers are prepared to tell others, and what insights they are willing to provide firms regarding product development and enhancement. In a digital service ecosystem, value is co-created, co-converted, and co-captured together with the different players in the ecosystem: customers, competitors, complementors, and community Thus, organization in keystone positions in the ecosystem may choose to leave many activities of value creation to others in the ecosystem, while choosing to focus on creating value that is critical to the ecosystem’s prosperity. Therefore, we argue that CEBs toward the organization increase the extent of value co-creation by customers, continuously. 治政 resulting higher levels service offerings of organization 大 and eco-stakeholders. 立 CEB Cocreation. Stakeholder. Social media. Brand Partnership Module. Recommender System. io. y. n. Social Media Module. Ch. Recommender System Module Search Engine Module. sit. Identification Module. al. ‧. Support Data. Nat. User Module. er. ‧ 國. 學. 3.2 The System Architecture of iEngagement. engchi. i v CEB n U Collection Module. Search Engine. Feedback. Figure 3.2 iEngagement System Architecture Our system intends to provide services to help the firm to do the customer empowerment of customer’s CEB. We use stakeholder identification module to identify the current situation coopetition, three new media module to e-empower the customers, through CEB data from CEB collection module to co-create by brand partnership module (See Figure 3.2). 22.

(36) Stakeholder identification module: The main objective of this module is to give recommendation of brand partners that they can cooperate with to the firm using data from the support database. Firm nowadays may confused and have little idea of what brand partners can they approach and partner with, since most of the firm on the new media they might have never heard of them. (1) Social Media Module: The main objective of this module is to help the firm to maximize the possibility of consumers to do the content like, share and feedback. By spreading through social relationship, it can give both increasing the customers affect according to social exchange theory and the. 治政 degree of their acceptance as customer role readiness. 大 At the end, give rise 立 to the C2C and B2C CEB. ‧ 國. 學. (2) Search Engine Module: Search engine is one of the most popular way for. ‧. customer to search for the information. During the process of searching, the. sit. y. Nat. user has a higher willingness to learn the information, because they launch. io. er. the search themselves. Thus, it is important to let the target customers get firm’s information when target customers use the term that is related to the. al. n. iv n C firm. The main objective of is to help the firm to increase the h ethisnmodule gchi U. acquisition of search engine. Through correct acquisition, the firm can then build up the customer’s awareness of the brand and the basic knowledge for making the degree of customers feel prepared for encounters with the organization (customer role readiness) higher. (3) Recommender system module: The main objective of this module is to help the firm to maximize the possibility of consumers to find the right maven (expert in the domain) to curate the content knowledge to further develop the customer’s role readiness. Through the development of the customer’s role readiness, firm can have an arousal on CEB. 23.

(37) (4) CEB collection module: CEB collection module is to intend to collect the CEB to provide not only the feedback of the present state, but also the feedback to the three new media module so that the three new media module can give an adapted service to the specific firms. (5) Brand Partnership module: Brand partnership module’s objective is to help the firm to communicate with the multi-stakeholder. In this module, we use the most common way in business, email communication channel, to help the firm manage the brand partnership with their cooperators. 3.3 System Scenario. 立. 政治大. CTaipei website (http://www.taipeing.net/), established in 2012, is objective for. ‧ 國. 學. redesigning the Taipei city through store image (e.g., romantic, natural). ‧. co-creation with store owners, customers, government. Firm can create an. sit. y. Nat. account on CTaipei, write store information, and the customer can then vote for. io. er. what the store image might be. In addition to receiving the customers’ perceived. al. image, businesses are also very concerned about how to engage customer with. n. iv n C new media. Based on the need, CTaipei website to an engagement h we e nextend gchi U site.. In the previous situation, there’s a science bookstore called R8 wants to find some brand partners to cooperate with. He first identify brand partners with the same district and similar images through CTaipei that has around 20000 stores in Taipei for color images which contains 14 categories of images such as amusing, classic, nature. etc. (Yuan et al., 2012). He found a potentially suitable school image’s bookstore called Elite bookstore in the same street district to deliver a co-created brand alliance-based campaign and develop the positive CEB through our engagement site. 24.

(38) . Optimization of keywords and links of brand alliance-based campaign pages: R8 and their partners, Elite bookstore, can submit a description of a brand alliance-based campaign pages to SEO service: In NCCU, Elite bookstore now is providing students free space to read books. There are new science books being imported from R8 with a discount of 20%.... And optimization service will provide R8 with some keywords – Wenshan, young, freedom – for them to restructure their brand alliance-based campaign pages’ content. Besides, SEO services also suggest R8 with some partners’ website links, such as NCCU. We hope that the use of these two features allows. their. 學. ‧ 國. . 治政 the page rank upgrade, and more target user may大 find the information. 立 Giving maven summarized content: After ensuring business and. stakeholders, iEngagement will collect the related articles on internet and find. ‧. out business’s maven on the recommender system. iEngagement site will process. sit. y. Nat. articles for summarization and influence mavens attitude through these. io. al. Maximizing introvert leaders WOM likelihood: R8 can provide us with the link. iv n C of their Facebook fan page, and will analysis their fans’ behavior h eiEngagement ngchi U n. . er. summarization. We can then arouse more CEB from maven’s engagement.. data and find out the introvert leaders – user A, B, C – on their fan page. System will give A, B, and C the articles about R8 and the brand alliance-based marketing is mentioned about. Using some articles that introvert leaders are interested in to maximize WOM likelihood and engage fans. Each of the service module can share their database with other to regulate their module if need. And R8 can manage their new media marketing and customer engagement on iEngagement site. In R8 case, business has a single site for managing WOM on new media, matching cooperation stakeholders, 25.

(39) operating brand alliance-based marketing, and enhancing customer engagement. This would then be our iEngagement project’s ultimate purpose.. 立. 政治大. ‧. ‧ 國. 學. n. er. io. sit. y. Nat. al. Ch. engchi. 26. i Un. v.

(40) CHAPTER 4 THE BRAND ALLIANCED-BASED CUSTOMER ENGAGEMENT INCREMENT MECHANISM ON SEARCH EGNEINE. This chapter illustrates how to develop CEB through modules which can help SMEs to acquire and develop the customers (See Figure 4.1).. Create virtuous circle in New media. Development Acquisition. Retention. 政治大. Using high search targetability and consistent inlink and high search targetability keywords to arouse the engagement of customers.. through inlink and keyword to acquire the target customers. 立. With integration with multimedia feed we achieve the ability of retain the customers. ‧. ‧ 國. 學. Figure 4.1 create the virtuous positive cycle in new media. io. sit. y. Nat. 4.1 Conceptual Framework. n. al. er. This section provides the conceptual framework of our study. The main idea is. Ch. i Un. v. that in the engagement site our ultimate purpose is to maximize the engagement. engchi. level for our target customers under search engine. Through utilizing our conceptual framework we need to design engagement site service to implement the concept. There are following important concepts in our conceptual framework, long tail keyword service, inlink building service, web visbiliity, search targetability, campaign and partner image consistency, engagement level and its arrow relationship (See Figure 4.1).. 27.

(41) Customer. SME. 1-1. Web Visibility 4-1. Long Tail Keyword Service. 1-2 4-2 2-1. Search Targetability. 5-1 4-3. 2-2 Inlink Building Service 3. Engagement Site Engagement Level. 5-2. Campaign and Partner Image Consistency. Long Tail Page in target site Engagement Level. 政治大 Figure 立4.1.1 Conceptual Framework Diagram. ‧ 國. 學. Long Tail Keyword Service: Long tail keyword service outputs the high fitness. ‧. keywords for the campaign. The SMEs can then pick up the appropriate. sit. y. Nat. keywords to form their long-tail keyword-focused campaign page (Long tail page). Long tail keywords is defined as longer and more specific keyword. io. er. . phrases that visitors are more likely to use when they’re closer to a. n. al. ni C h4.1.2) point-of-purchase. (See Figure U engchi. v. Figure 4.1.2 Long tail keywords search demand curve (Moz Foundation, 2009). 28.

(42) . Inlink Building Service: Inlink building service output the image-related links and recommender system links for SMEs to promote their own campaign.. . Web visibility: In the study, web visibility refers to how likely a user is to encounter a reference to a website in his or her web (or online) environment (Wolk and Theysohn, 2007).. . Campaign and Partner Image Consistency: The fit between campaign and the images of participating brands.. . Search Targetability: Search targetabtility is defined as the ability to decrease the search cost of customers.. 學. ‧ 國. . 治政 Engagement Level: According to Forrester 大 research (2008), customer 立 engagement can be divided into four categories, including involvement, interaction, intimacy, and influence.. Arrow (1-1, 1-2): We argue that long tail keyword service and link building. y. sit. Arrow (2-1, 2-2): We believe that long tail keyword service and link building. io. er. . Nat. service can both increase the web visibility for customers.. ‧. . al. service can help increase targetability and reduce the customers search cost.. n. iv n C Arrow (3): We argue that through image-related links, SMEs h e nlink-building’s gchi U. . can increase the campaign and partner image consistency. Due to the fact that if SMEs promote their events on the image-related site, there will be an additional image inside the campaign and thus will increase the campaign and partner image consistency. . Arrow (4-1): Web Visibility on Engagement site’s Engagement level: We argue that web visibility will positively influence the engagement level. For example, if a customer can hardly search or get link with the company related information, then it will be hard for company to engage their customer online. 29.