臺灣博碩士論文加值系統

服務產業在資源有限的情況下，各個企業試圖將資源配置在具有獲利性的顧客上，因而形成企業對於顧客關係管理(CRM)相關研究議題日益重視。準此，本研究以關係資訊程序(Relational Information Processes)與顧客為基礎之績效衡量(Customer-based performance)之影響關係。其中關係資訊程序包括資訊互惠、資訊擷取、資訊整合、資訊檢索、資訊使用；而以顧客為基礎之績效衡量包括顧客滿意度、正向口碑、區隔顧客、取得和保留顧客、發掘潛在顧客。又，以互動傾向(Interaction Orientation)與顧客關係管理系統準備度(CRM System Readiness)作為關係資訊程序與以顧客為基礎之績效衡量關係之干擾效果。本研究以服務產業為對象，研究方法採質性與量化研究，首先針對三家服務業進行個案分析，將訪談結果作為問卷設計的基礎；並且採用兩階段結構方程模式及階層式廻歸作為資料分析。分析結果發現互動傾向對關係資訊程序與顧客為基礎之關係績效有干擾效果，在互動傾向對關係資訊程序與以顧客為基礎的關係績效有直接影響；且顧客關係管理系統準備度對關係資訊程序與以顧客基礎的利益績效亦有直接影響。

Due to resource scarcity in the service industry, firms should adequately align resources spent on customers in proportion to the revenues or profits derived from them. Customer relationship management (CRM) plays a very important role in contemporary enterprises. This research adopted CRM relational information processes and customer-based performance as main constructs. The study was designed to determine the effect of CRM relational information processes toward customer-based performance. The CRM relational information processes embraced information reciprocity, information capture, information integration, information access, and information use. Customer-based performance consisted of customer satisfaction, positive word-of-mouth, identification of profitable customers, acquisition and retention of profitable customers, and conversion of unprofitable customers to profitable ones. Interaction Orientation and CRM system readiness are moderators between the relationships of CRM relational information processes toward customer-based performance. The population of the study was taken from service industries in Taiwan. This study adopted a qualitative approach and a quantitative approach. Three companies participated in the case study. In accordance with interviewed content, this study modified constructs and designed a questionnaire. This study applied a two-step structural equation model (SEM) and hierarchical regression for data analysis. The results showed that interaction orientation enhanced the effect of CRM relational information processes toward customer-based relational performance. In additional, the research found that interaction orientation has a positive effect on CRM relational information processes and customer-based relational performance and that a CRM system readiness has a positive effect on CRM relational information processes and customer-based profit performance.

ABSTRACT Ⅰ
中文摘要 Ⅱ
誌謝 Ⅲ
TABEL OF CONTENT Ⅳ
LIST OF FIGURE Ⅶ
LIST OF TABLE Ⅷ

CHAPTER 1 INTRODUCTION
1.1 Research Background and Motivation 1
1.2 Importance of the study 3
1.3 Research Objectives 5
1.4 Research Procedure 6

CHAPTER 2 LITERATURE REVIEW
2.1 CRM Relational Information Processes 8
2.2 Customer-based Performance 11
2.2.1 Customer-based Relational Performance 12
2.2.2 Customer-based Relational Performance 14
2.3 The Moderating Variables 18
2.3.1 Interaction Orientation 18
2.3.2 CRM System Readiness 20
2.3.2.1 Organization Readiness 21
2.3.2.2 Technology Readiness 22

CHAPTER 3 RESEARCH FRAMEWORK AND METHODOLOGY
3.1 Conceptual Framework 26
3.2 Research Methodology 30
3.3 Measure Development 31
3.4 Sample Characteristics 35
3.5 Data Analysis Method 35

CHAPTER 4 CASE STUDY
4.1 Case Study 39
4.2 Case Study Summary 43
4.3 Revised Model: Based on Organizational Case 49
4.4 Questionnaire Design 51

CHAPTER 5 DATA ANALYSIS
5.1 Pilot Test 54
5.2 Sample Characteristics 57
5.3 Measurement Model Analysis 58
5.3.1 Confirmatory Factor Analysis 58
5.3.2 Reliability 62
5.3.3 Convergent Validity 63
5.3.4 Discriminant Validity 64
5.4 Structural Equation Model Analysis 65
5.5 Moderating Effects: Hierarchical Regression Analysis 67
5.6 Additional Research 70
5.7 ANOVA Analysis 75
5.7.1 Age 75
5.7.2 Education 76
5.7.3 Work Seniority 77
5.7.4 Industry 78
5.7.5 Position 79
5.7.6 Department 80

CHAPTER 6 CONCLUSIONS AND SUGGESTIONS
6.1 Discussion 81
6.1.1 CRM Relational Information Processes VS. Customer-based Profit Performance 82
6.1.2 CRM System Readiness VS. Customer-based Relational Performance 82
6.1.3 Interaction Orientation VS. Customer-based Profit Performance 83
6.1.4 CRM System Readiness VS. Customer-based Profit Performance 84
6.1.5 Demographic Variable VS. Research Variable 84
6.1.6 Additional Research 86
6.2 Theoretical Implication 88
6.3 Managerial Implication 89
6.4 Limitation and Suggestion for Future Research 90

REFERENCES 91
APPENDIX 103


LIST OF FIGURE
Figure 3-1 Conceptual Framework 29
Figure 4-1 Modified Framework (Based on Organizational Case Studies finding) 50
Figure 5-1 Full Constructs of CFA Measurement Model 61
Figure 5-2 Results of Structural Equation Modeling (Main Effects) 66
Figure 5-3 Results of Structural Equation Modeling (Additional Research) 74


LIST OF TABLE
Table 3-1 All Construct of Descriptions Summaries 33
Table 3-1 Continued All Construct of Descriptions Summaries 34
Table 4-1 Organizational Case Summary 47
Table 4-1 Continued Organizational Case Summary 48
Table 4-2 Constructs of Measurement Items 52
Table 4-2 Continued Constructs of Measurement Items 53
Table 5-1 Results of Pilot Test 55
Table 5-1 Continued Results of Pilot Test 56
Table 5-2 Demographic Statistics of Respondents 57
Table 5-3 CFA and Item-to-total Analysis 59
Table 5-4 Continued CFA and Item-to-total Analysis 60
Table 5-5 A summary of Fit Indices for Measurement Model 62
Table 5-6 Reliability and Validity Index 63
Table 5-7 Results of Chi-square Difference Tests 64
Table 5-8 Path Analysis and Hypotheses Tests 65
Table 5-9 A summary of Fit Indices for the SEM 65
Table 5-10 Results of Hierarchical Regression: H4a and H5b 69
Table 5-11 Results of Hierarchical Regression: H4b and H5a 70
Table 5-12 A summary of Fit Indices for the SEM (Additional Research) 71
Table 5-13 Path Analysis and Hypotheses Test 71
Table 5-14 ANOVA Analysis of Different Age Groups on Each Variable 75
Table 5-15 ANOVA Analysis of Different Education Level on Each Variable 76
Table 5-16 ANOVA Analysis of Different Work Seniority on Each Variable 77
Table 5-17 ANOVA Analysis of Different Industry on Each Variable 78
Table 5-18 ANOVA Analysis of Different Position on Each Variable 79
Table 5-19 ANOVA Analysis of Different Department on Each Variable 80

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