臺灣博碩士論文加值系統

Online To Offline(O2O)消費模式是台灣近年崛起的電子商務模式，在講求快速與便利的時代，消費者更可透過智慧型行動裝置進行O2O的消費，此亦已漸漸成為一種的消費型態。因此，對線上商店而言，如何在線上與離線提供公平的服務，以建立與行動商務消費者的良好關係品質，是一項重要的議題。故本研究聚焦於從行動裝置消費者觀點探討O2O消費模式下服務公平性對關係品質之影響，並以行動裝置消費者的科技準備度為干擾變項。並探討消費者之人口統計變數、地理變數、行為變數對科技準備度、服務公平性、關係品質之關係。
本研究以「透過行動裝置於團購網進行O2O消費」為研究對象，本研究正式調查受訪者為朝陽科技大學學生，問卷採便利抽樣方式。正式問卷共發放311份，回收問卷303份，扣除填答不完整問卷47份，有效問卷256份，有效回收率為82.3%。資料分析方法包括:樣本結構分析、敘述性統計分析、信度與效度分析、探索性因素分析、t檢定、變異數分析、相關分析與階層多元迴歸分析。
主要研究結論包括：行動裝置消費者對於O2O消費模式的「互動公平性」、「人際公平性」與「分配公平性」的認知，會正向影響對線上店家的「信賴」。而消費者對於O2O消費模式的「人際公平性」、「分配公平性」與「價格認知公平性」的認知，會正向影響對線上店家的「滿意與認同」。此外，消費者對「科技創新的接受程度」會干擾O2O消費模式的「作業程序公平性」與「信賴」的關係。消費者對「科技的信任程度」會干擾O2O消費模式的「分配公平性」與「滿意與認同」的關係，以及O2O消費模式的「人際公平性」與「滿意與認同」的關係。至於，消費者對「科技的樂觀程度」與對「科技的適應程度」均會干擾O2O消費模式的「互動公平性」與「滿意與認同」的關係。而不同性別、學院別、零用金別、消費頻率別對科技準備度認知有顯著差異；不同學院別對服務公平性認知有顯著差異；不同性別、消費頻率別對關係品質有顯著差異。

Online To Offline(O2O) Consumption Model is an e-commerce model that has risen in recent years in Taiwan. In this fast-paced and convenient era, consumers can even make O2O purchases through smart mobile devices, and it has gradually become a type of consumption pattern. Hence, it is an important topic for online stores to provide fair service in Online To Offline(O2O) Consumption Model to establish a good relationship quality with mobile commerce consumers . Focusing on the mobile device consumer’s perspective, this research explores the impacts that service fairness has on relationship quality in Online to Offline Business Model, with the technology readiness index of the mobile device consumer as the moderating effect. It also probes into the relationship between the consumer’s demographic, geographic and behavioral variables, and the technology readiness index, service fairness and relationship quality.
This research takes “ Online Shopping and Offline Consumption via Mobile Devices on a Group Buying Website” as the study object. The correspondents were the students of Chaoyuang University of Technology, in convenience sampling. In total, 311 official questionnaires were distributed, 303 of which were returned; if 47 uncompleted questionnaires are deducted, 256 are valid ones, and the valid return rate is 82.3%. Data analytic methods include Sample Structural Analysis, Descriptive Statistical Analysis, Reliability and Validity Analysis, Exploratory Factor Analysis, t-test, Analysis of Variance, Correlation Analysis, and Multiple Hierarchical Regression Analysis.
The conclusions in the research are as follows. Mobile device consumers’ perceptions of “interactional fairness,” “interpersonal fairness,” and “distributive fairness” will positively influence the “trust” toward online stores. Consumers’ perceptions of “interpersonal fairness,” “distributive fairness” and “perception of price fairness” in O2O Consumption Model will affect “satisfaction and identity” toward online stores in a positive way. Besides, “levels of acceptance towards technological innovation” of consumers will impact the relationship between “operating procedural fairness” and “trust.” “Levels of trust towards technology” of consumers will affect the relationship between “distributive fairness” and “satisfaction and identity” as well as the relationship between “interpersonal fairness” and “satisfaction and identity” in O2O Consumption Model. Therefore, both “levels of technological optimism” and “levels of technological comfort” of consumers will have a moderating effect on the relationship between “interactional fairness” and “satisfaction and identity” in O2O Consumption Model. Moreover, based on different genders, colleges, allowances, consumption frequencies of consumers, there are distinct differences to the technology readiness index; different colleges have obvious differences to the perception of service fairness; different colleges have clear distinctions to the perception of service fairness; different genders and consumption frequencies of consumers have obvious differences to relationship quality.

摘要 I
Abstract II
目錄 V
表目錄 VI
圖目錄 VIII
第一章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的 5
第三節 研究流程 6
第二章 文獻探討 7
第一節 Online to Offline（O2O） 7
第二節 科技準備度 12
第三節 服務公平性 16
第四節 關係品質 24
第三章 研究方法 38
第一節 研究架構 38
第二節 研究假說 39
第三節 研究變項之操作性定義與衡量題項設計 42
第四節 問卷設計 48
第五節 資料分析方法 50
第六節 預試問卷分析 53
第四章 資料分析與討論 59
第一節 樣本結構分析 60
第二節 信度與效度分析 64
第三節 探索性因素分析 68
第四節 敘述性統計分析 77
第五節 相關分析 83
第六節 階層多元迴歸分析 86
第七節 t檢定與變異數分析 102
第五章 結論與建議 124
第一節 研究結論 124
第二節 管理與實務意涵 138
第三節 研究限制與未來研究建議 143
參考文獻 144
附錄 正式問卷 159

表目錄
表2-1-1線上團購網模式 10
表2-2-1科技準備度構面與定義（Parasuraman, 2000） 13
表2-2-2科技準備度構面與定義（Kuo, 2013） 13
表2-3-1各學者對於服務公平性提出的構面 19
表2-4-1關係品質的定義 25
表2-4-2各學者對於關係品質提出的構面 29
表2-4-3信任的定義 31
表2-4-4滿意的定義 34
表2-4-5承諾的定義 36
表3-3-1科技準備度量表 43
表3-3-2 O2O服務公平性量表 44
表3-3-3關係品質量表 46
表3-4-1學生族群問卷基本資料設計 49
表3-6-1預試問卷發放與回收概況 53
表3-6-2科技準備度之預試信度分析 54
表3-6-3 O2O服務公平性預試信度分析 55
表3-6-4關係品質之預試信度分析 58
表4-0-1問卷發放與回收概況 59
表4-1-1受訪者使用行動裝置的購物體驗題項資料分析 61
表4-1-2基本資料題項資料分析 62
表4-2-1科技準備度變項之正式調查信度分析 65
表4-2-2 O2O服務公平性變項之正式調查信度分析 66
表4-2-3關係品質變項之正式調查信度分析 67
表4-3-1科技準備度變項之KMP值與Bartlett’s球形檢定表 69
表4-3-2科技準備度變項之因素分析 69
表4-3-3 O2O服務公平性變項之KMP值與Bartlett’s球形檢定表 72
表4-3-4 O2O服務公平性變項之因素分析 72
表4-3-5關係品質變項之KMP值與Bartlett’s球形檢定表 75
表4-3-6關係品質變項之因素分析 75
表4-4-1科技準備度變項之敘述性統計分析 78
表4-4-2 O2O服務公平性變項之敘述性統計分析 80
表4-4-3關係品質變項之敘述性統計分析 82
表4-5-1相關係數強度判斷表 83
表4-5-2各構面Pearson相關分析 85
表4-6-1科技準備度干擾下O2O服務公平性對關係品質的影響效果之階層迴歸分析-以信賴構面為依變項 93
表4-6-2科技準備度干擾下O2O服務公平性對關係品質的影響效果之階層迴歸分析-以滿意與認同構面為依變項 100
表4-7-1受訪者性別特徵之t檢定 104
表4-7-2受訪者居住地特徵之變異數分析 106
表4-7-3受訪者年齡特徵之變異數分析 108
表4-7-4受訪者年級特徵之變異數分析 110
表4-7-5受訪者學院別特徵之變異數分析 113
表4-7-6受訪者系所別特徵之變異數分析 117
表4-7-7受訪者系所別特徵之變異數分析-事後比較表 118
表4-7-8受訪者零用金別特徵之變異數分析 120
表4-7-9受訪者消費頻率特徵之變異數分析 123
表5-1-1研究假說驗證結果 124
表5-1-2研究假說H1驗證結果 126
表5-1-3研究假說H2驗證結果 129
表5-1-4研究假說H3驗證結果 133
表5-1-5研究假說H4驗證結果 135
表5-1-6研究假說H5驗證結果 137

圖目錄
圖1-1-1 2010-2018(f)臺灣智慧型手機普及率發展趨勢及預測 1
圖1-1-2 2010-2018(f)臺灣平板電腦普及率發展趨勢及預測 2
圖1-3-1研究流程 6
圖2-1-1 O2O的合作模式 7
圖2-2-1科技準備度之架構 14
圖3-1-1概念性研究架構 38
圖4-6-1修正後概念性研究架構 86

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