臺灣博碩士論文加值系統

In recent years location-based services (LBS) have played as an important role in the global mobile-commerce (M-Commerce) market and the service providers have also detected business opportunities and so are exploring more and more wireless applications to attract and retain their customers. In addition, most private firms in Taiwan now operate a five-day workweek. In such case, it allows Taiwanese people to travel individually in their leisure time. An LBS application can provide location-based information to users for visiting and staying at a new location. The information should be useful and valuable for users. Nevertheless, the adoption rates of the LBS are still far from satisfactory in Taiwan according to statistics conducted by ACI-FIND.
Thus, this research attempts to dig out what factors will affect Taiwan’s user’s willingness to adopt the LBS by employing the ZMET (Zaltman Metaphor Elicitation Technique) method and questionnaire survey, combining both qualitative and quantitative research methods.
The result can fill the gap in the case of the low LBS adoption rate, which prior researches have not discussed much. And these findings will become crucial references for the service providers when they attempt to enhance the quality and practicability of LBS to satisfy users’ requirements.

CHAPTER1　INTRODUCTION 1
1.1 MOTIVATION 1
1.2 OBJECTIVE 2
1.3 SCOPES AND CONFINES 3
1.4 RESEARCH STRUCTURE 4
CHAPTER2　LITERATURE REVIEW 6
2.1 MOBILE COMMERCE (M-COMMERCE) 6
2.1.1 Current Applications Status of M-Commerce in Taiwan 7
2.2 LOCATION-BASED SERVICE (LBS) 9
2.2.1 Current Development Status of LBS Worldwide 12
2.2.2 Current Development Status of LBS in Taiwan 13
2.3 ZALTMAN METAPHOR ELICITATION TECHNIQUE (ZMET) 16
2.4 TECHNOLOGY ACCEPTANCE MODEL (TAM) 19
2.5 SECURITY AND PRIVACY 21
2.6 COST 22
CHAPTER3　THESIS METHODOLOGY 24
3.1 ORIGINAL MODEL DEVELOPMENT 24
3.2 QUALITATIVE RESEARCH METHOD—ZMET APPROACH 26
3.2.1 Processes of ZMET Application 27
3.3 RESEARCH MODEL 43
3.4 HYPOTHESES 44
3.5 QUESTIONNAIRE DESIGN 46
3.6 DATE ANALYSIS 50
CHAPTER4　DATA ANALYSIS 53
4.1 DATA COLLECTION 53
4.2 DEMOGRAPHIC ANALYSIS 53
4.3 VALIDITY ANALYSIS 58
4.4 RELIABILITY ANALYSIS 60
4.5 CORRELATION ANALYSIS 60
4.6 REGRESSION ANALYSIS 63
4.7 DISCUSSION 69
CHAPTER 5　CONCLUSION AND SUGGESTIONS 76
5.1 CONCLUSION 76
5.2 CONTRIBUTION 78
5.3 SUGGESTIONS FOR FUTURE RESEARCH 79
5.4 LIMITATION 80
REFERENCE 82

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