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Group 4 Hung Wing Shan (13007017) Kwan Nok Him, Jeffrey (12021148) Tang Mei Ling (13007025) Tsang Wing Shan (13007386) Wong Sze Ching (13006274)

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Agenda 2 1.Introduction 1.1 Keywords definition 1.2 Research paper concept 1.3 Research rationale 1.4 Research objectives 3-10 2.Research method 2.1 Model 2.2 Questionnaire 2.3 Data analysis and results 11-35 3.Findings 3.1 Continuance intention 3.2 Associations between antecedent constructs 36-44 4.Conclusion 4.1 Limitations 4.2 Further discussion 45-48

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1.1 Keywords definition 1.2 Research paper concept 1.3 Research rationale 1.4 Research objectives 3

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1.1 Keywords definition IS Use Information Systems Use The internet redefines rules of doing business by: Increasing transaction efficiencies Reducing costs Lowering barriers to entry Causing online firms turning to customers relationship management (CRM) to survive in internet economy Continuance Consumers continuance intention Determined by: Consumers satisfaction with initial service use Perceived usefulness of service use Interaction between perceived usefulness & loyalty incentives for service use 4

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Customer satisfaction A measure of: how products and services supplied by a company meet or surpass customer expectation Predicted by consumers confirmation of expectations from initial service use Customer Relationship Management (CRM) A new customer-centric business model Reorients firm operations around customer needs opposed to products, resources, or processes Improve customer satisfaction, loyalty, and retention 5 1.1 Keywords definition

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Expectationconfirmation Theory (ECT) Theory in consumer behavior literature Points satisfaction with a product or service is the primary motivation for its continuance Technology Acceptance Model An application of attitude theories to IS use contexts Presents usefulness of an IS Perceived by potential users as an important determinant of their intentions regarding IS use 6 1.1 Keywords definition

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1.2 Researcher paper concept The paper examines key drivers of consumers intention to continue using business-to-consumer e-commerce services. 7

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1.3 Research rationale 8

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1.4 Research objectives 10

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2.1 Model 2.2 Questionnaire 2.3 Data analysis and results 11

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2.1 Model 12 Fig. 1. A theoretical model of customer satisfaction/continuance.

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2.1 Model B2C firms typically have 3 customer touch points: 13 Marketing Pre- transaction Sales Transaction Service Post- transaction

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2.1.1 Determinants of continuance intention (expectations) 3 key factors - influencing consumers decision to continue using e-commerce services Satisfaction Perceived usefulness Loyalty incentives 14

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2.1.2 Relationships among the determinants of intention H1 H1: Positive effect from satisfaction to continuance intention H2 H2: Positive effect from perceived usefulness to continuance intention 15 Satisfaction +ve Continuance intention Perceived usefulness +ve Continuance intention

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2.1.2 Relationships among the determinants of intention H3 H3: Positive effect from loyalty incentives to Continuance intention 16 Loyalty incentives +ve Continuance intention

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2.1.2 Relationships among the determinants of intention H4 H4: Positive effect from confirmation to satisfaction H5 H5: Positive effect from confirmation to perceived usefulness 17 Confirmation +ve Perceived usefulness Confirmation +ve Satisfaction

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2.2 Questionnaire Continuance intention: IN1. I want to continue using my OLB rather than discontinue its use. IN2. My intentions are to continue using my OLB rather than any alternative means. IN3. If I could, I would like to discontinue use of my OLB. Satisfaction: ST1. I am satisfied with my decision my OLB use. ST2. My choice to use this OLB was a wise one. *ST3. I am not happy with my earlier decision to use my OLB. *ST4. My experience with using this OLB was very unsatisfactory. ST5. I think I did the right thing by deciding to use my OLB. )ST6. If I were to do it again, I would feel differently about using my OLB. 18 *Reverse coded items. Items dropped from final analysis due to poor factor loadings.

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2.2 Questionnaire Perceived usefulness: US1. Using my OLB helps me improve my performance in managing personal investments. US2. I think that my OLB use improves my productivity in managing personal investments. US3. In my opinion, using my OLB increases my effectiveness in managing personal investments. US4. I find my OLB useful in managing personal investments. Loyalty incentives: LI1. My OLB offers incentives for its continued use, such as frequent flier miles or bonus points. LI2. I get rewarded for my continued patronage of my OLB. *LI3. My OLB generally does not give me any loyalty incentives for my continued use of its service. 19 *Reverse coded items. Items dropped from final analysis due to poor factor loadings.

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2.2 Questionnaire Confirmation: CN1. My OLBs execution of online trades meets my expectations. CN2. My OLB gives me all the information and tools needed to place and execute trades. *CN3. My online trading experience via my OLB falls short of my expectations. CN4. My OLB is generally good at handling questions or complaints before or after a trade. CN5. After-sales service provided by my OLB meets my expectations. CN6. I generally get the level of service I expect from my OLB. CN7. My OLB provides me with customized one-on-one marketing as I would expect. CN8. Products and services recommended to me by my OLB meet my expectations. CN9. My OLBs direct marketing activities meet my expectations. 20 *Reverse coded items. Items dropped from final analysis due to poor factor loadings.

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2.2.1 Study background Online survey of Online brokerage (OLB) use On 4 popular investment-related websites Opportunity to register in a drawing for small cash prizes as incentive 172 usable responses from OLB users Data collection 21 Yahoo Finance, Silicon Investor, Motley Fool & Raging Bull

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2.2.1 Study background Respondents 22 4% 24% Silicon Investor 73% Yahoo boards Motley Fool and Raging Bull

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2.2.1 Study background Subjects represented a wide range of OLBs, as listed in Table 1. 23

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2.2.1 Study background Respondents 24 Age19 to 54 Gender69% male & 31% female Annual incomeBetween US$24,000 and 200,000 ProfessionsWide range (IS professionals, salesrmarketing, bank- ingrfinance, law, and education) Educational levelsDiverse (from college freshmen to doctoral degrees) Experience in OLBsMany: relatively new to online trading; Some: had used as early as 1994 34%: transitioned from a traditional full-service brokerage to an OLB 11%: switched from a different OLB to their current one (primary reasons: service dissatisfaction & higher commissions)

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2.3 Data analysis and results Examine the measurement model Validating Refining the research instrument Stage 1 Analyze the structural equation model Testing the associations Stage 2 25

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Stage 1: Measurement model Using confirmatory factor analysis (CFA) 26 Construct validity Assessed by examining the standardized CFA factor loadings Minimum factor loadings: 0.60 Scale reliability Using Cronbach alpha Standard acceptance norm: 0.80

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1 st Construct: Continuance intention Questionnaire: Alpha > 0.80 Factor loadings > 0.60 remaining 27

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2 nd Construct: Satisfaction Questionnaire: ST5, ST6 fail to meet criterion dropped 28

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3 rd Construct: Perceived Usefulness Questionnaire: Alpha > 0.80 Factor loadings > 0.60 remaining 29

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4 th Construct: Loyalty incentives Questionnaire: 30

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5 th Construct: Confirmation Questionnaire: 31

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Stage 2: Structural equation model 32

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Stage 2: Structural equation model Hypothesis 1 33 SatisfactionContinuance intention

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Stage 2: Structural equation model Hypothesis 2 34 Perceived usefulnessContinuance intention

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Stage 2: Structural equation model Hypothesis 3 35 Loyalty incentivesContinuance intention

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3.1 Continuance intention 3.2 Associations between antecedent constructs 36

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3. Findings 37 Goal 1. Identify the antecedents of consumers continuance intentions from a CRM standpoint 2. Identify interrelationships among these antecedents

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3.1 Continuance intention (Satisfaction) Satisfaction and perceived usefulness Strong predictors of consumers intention Satisfaction most important predictor! Minimizing the effects of customer churn & Establishing a loyal customer base Seek to identify dissatisfied consumers and redress their dissatisfaction concern 38

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3.1 Continuance intention (Satisfaction) Key metric = Satisfaction Change from customer aware customer centered 39 Reasons to minimize churn (discontinuance) 1. Churn reduces firms customer base and revenue 2. Negative WOM initiated by discontinuers is more persuasive 3. Firms incur substantial costs in order to get back prior consumers

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3.1 Continuance intention (Perceived usefulness) Perceived usefulness = Secondary determinant What we can do? 'educate them 40 Whats the limitation? 1. Continue subscribing service only if its useful. 2. Do not recognize all of service's benefit due to limited prior experience.

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3.1 Continuance intention (Perceived usefulness) Loyalty incentive e.g. frequent filter miles, loyalty points and cash back --> X Significant Interaction effect with perceived usefulness Significant Mix consumer training/education and loyalty program Maximize the effect of loyalty incentives 41

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3.2 Association between antecedent constructs Confirmation significant predictor of satisfaction and perceived usefulness Influence consumer's decision process(confirmation) Expectation vary greatly Solution: Segmentation 42 Expectation is a complex and challenging task High expect disconfirmation Low expect reduce motivation continue to use service

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43 3.2 Associations between antecedent constructs Confirmation Marketing expectations Sales Services Marketing confirmationSales and service confirmat ion Personalized One to one Direct marketing Sales Service Unclear what extent individual consumers are aware of such expectation problematic in confirming expectations Well-defined by virtue of their prior experience Readily assess those firm is meeting at least expectations Confirmation Dissociation From CRM perspective During empirical analysis

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44 3.2 Associations between antecedent constructs Firms: Evaluate whether such costs are justified in lieu of retaining a dissatisfied consumers business Implementing satisfaction guaranteed policy e.g. Additional service & manpower cost Uncertainty about whether dissatisfied consumers will return after dissatisfaction is resolved Cost

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4.1 Limitations 4.2 Further discussion 45

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4.1 Limitations 1.Methodological limitation - Novelty effect Problem: empirical data may be biased Test for biases: 99% comfortable with online surveys 2.Non-response bias Problem: respondents recruited via online message board differ from general population Test for biases: Compare variable [1] Not a serious concern Demographic Age Income level Contextual Portfolio size Weakly significant Non-significant Target population fairly represented, response not substantively different [1] Silicon Investor, Silicon Investor User Profile, http://www.go2net.com/corporate/advertising/siliconinvestor/demo.html, 1999. 46

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4.1 Limitations 3. Bias on continuance intentions option 40 % of respondents: complicated and expensive process NOT view OLB discontinuance as a viable option Test for biases: Separate discontinuance-aware & unware respondents rerun the result separately Result: Overall pattern of path significance and relative influence of determinants were unchanged Bias in perceptions of continuance behaviors not affect response 47

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Application of theoretical model may cause bias in interpreting the causative relationships Constraints: variables, relationships, assumptions, boundary conditions biased interpretation of problem domain and solution space Problem: Additional determinants relevant to continuance intention examined 48 4.2 Further discussion Using diverse theoretical perspectives Validate the model/propose a more comprehensive explanation

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Q&A 49