臺灣博碩士論文加值系統

在體驗經濟的時代，服務業的重要性在這幾十年內變得越來越重要。消費者現在在意的不僅是服務本身，還在意在服務過程中所得到的感受.然而，有關於對服務體驗價值計算的相關研究卻有限，因此，本研究致力於建構一個架構模型，能以消費者的角度來衡量從服務體驗中所感受到的服務體驗值。本研究有以下兩個研究問題要探討：(1)服務體驗有哪些衡量構面及其重要性? (2)不同消費者所算出的服務體驗值有什麼不同? 同時，本研究有兩個研究目的：(1)建構出一個模式可以量化消費者在服務體驗中感受得的價值。(2) 而透過此計算模式可以消費者的角度給與服務廠商如何調整或改變營運模式。
本研究根據"服務證明"的概念，以消費者的角度將在服務體驗中所可能感受到的正負向構面綜合而得到"服務體驗值(Service Experience Value). 研究架構由三個正向構面與兩個負向構面所組成，分別為服務氣氛、服務流程、服務人員、擁擠度、與等候時間.本研究以多屬性效用分析來做為計算服務體驗值的計算基礎。在實際個案的測試部分，本研究以去過洋蔥與西堤牛排館的消費者分別做為前測與正式問卷分析。最後，洋蔥的有效樣本為68，西堤的有效樣本為345. 從結果可以得到消費者對主構面與子構面的重視排序而去了解消費者對餐廳服務的偏好是什麼。另一方面，本研究觀察消費者在不同情境下效用值的變動關係，而得到負向構面是影響消費者滿意度的重要因素，尤其是在等候時間的部分。
本研究將服務體驗值的結果依照小至大分為5組。研究結果顯示，從小樣本的洋蔥到大樣本的西堤可看出相同脈絡，兩者在體驗值偏中間值的消費者對加入擁擠度因子的反差較大。而在加入等候時間因子的結果又更加明顯，若等候時間的影響效果越大, 服務體驗值則會越小。無論是洋蔥或西堤，若是負向構面的影響使消費者無法容忍，縱使前面正向構面的總效用值高，最後的服務體驗值還是相當低，由此再次可證明負向構面的影響效果。而以樣本的分布來說，兩者都是呈常態分配，但由於樣本的來源不同，所以結果也會有所不同，以洋蔥來說，女性顧客有較高的服務體驗值，而以西堤來說則是男性顧客有較高的服務體驗值，由此可看出不同餐廳在不同性別的顧客上會有所差異。
本研究的貢獻為以餐廳將顧客的服務感知量化為服務體驗值，因此彌補了過去文獻缺少針對以消費者角度衡量服務體驗的計算模式。透過具體的數字，可以使服務提供者了解在服務體驗的共程中有哪些元素需要再調整。換句話說，本研究透過量化的分析來給服務提供者一個改變服務體驗品質的藍圖與方向。

In the era of experience economy, the importance of service has increased dramatically over the past decade. Customers not only focus on how the service is presented, but also pay attention to service perceptions. However, it lacks of researches regarding value measurement for service experience among literature. This research aims to construct a model to evaluate the customer perceived value for service experience. There are two research questions: (1) what are the dimensions and their importance of service experience? (2) What is service experience value and what are the differences among customers? Meanwhile, there are two goals of this research: (1) proposing a novel model to quantify the value of service experience and (2) help firms adjust service operations based on customer’s perception and experience.
This research utilizes the concept of “the evidence of service” and proposes a novel notion from customers’ viewpoint of “service experience value (SEV)” by combining positive and negative dimensions. The conceptual model is composed by three positive dimensions and two negative dimensions, which contains service atmosphere, service process, service employee, crowdedness, and waiting time. This research uses multi-attribute utility theory (MAUT) to calculate the utility that customers had felt during the service experience. We selected Onion steakhouse as the pilot study and TASTY steakhouse as the formal examination. The data was obtained from the customers who have been dined in these two restaurants in Taiwan. The valid number of samples for Onion is 68 and 345 for TASTY.
According to the results, we obtain the sequence of perceived weight for major dimension and sub-dimension to understand the preferences of customers at the situation of restaurant service. Besides, we also discovered that negative dimensions are the key reason affecting customer satisfaction; especially waiting time.
This research also separates the results into 5 groups by sorting SEV. First, average utility of each group and SEV have the positive increasing relationship, which means greater average utility results in greater SEV. Second, the result shows that customer of group 3 (middle range of all SEV) has the greater contrast between positive and negative dimensions than the other groups. After adding waiting time, the outcome of Onion and TASTY all have the descending trend of SEV, which indicates that the effect of waiting time is significant.
Third, both Onion and TASTY have the same phenomenon that the positive dimension of total utility of minimum SEV’s is greater than the maximum SEV’s at the beginning. However, the final results of minimum SEV and maximum SEV have the converse outcomes. We can use the two-factor theory to explain the result. Negative dimensions are similar to the hygiene factor and positive dimensions are similar to the motivator factor. Thus, negative dimensions play an important role in our research. Finally, the distribution of results for Onion and TASTY is different. In general, females have the better SEV for Onion and males have the better SEV for TASTY based on our results.
SEV provides an actual value of perception for service experience, which is also the major contribution of this research. It fits the gap by proposing the mathematical model for service experience with examination from real world cases. By quantifying utility value, service providers can obtain customer perception from service experience for further analysis and assist companies adjust or revise the service components during experience. In other words, this research provides a roadmap for companies to measure service experience and obtain the influence of positive and negative dimensions by deeper analysis.

Table of Contents I
List of Tables II
List of Figures III
Chapter1 Introduction 1
1.1 Background 1
1.2 Problem Statement 4
1.3 Research Question and goal 6
1.4 Structure of the Study 8
Chapter2 Review of Literature 10
2.1 Service Experience 10
2.2 Service Atmosphere 12
2.3 Service process and service employee 16
Chapter3 Research Method 25
3.1 Conceptual Model 25
3.2 Research Method 27
3.2.1 Multi Attribute Utility Theory (MAUT) 27
3.2.2 Modeling Service Experience Value 29
Chapter 4 Analysis 36
4.1 Questionnaire Design 36
4.2 Data Collection 37
4.3 Pilot study : Onion Steakhouse 38
4.3.1 Analysis of Reliability, and Descriptive Statistics 38
4.3.2 Data Analysis 43
4.4 Case study :TASTY Steakhouse 56
4.4.1 Analysis of Reliability, and Descriptive Statistics 56
4.4.2 Data Analysis 60
Chapter 5 Conclusion 72
5.1 Cross Analysis 72
5.3 Research Contribution and Managerial Implications 80
5.4 Limitations and Future Research 82
Reference 83
Appendix 96

List of Tables
Table 2-1 Summary of researches of service experience 12
Table 2-2 Summary of the five senses among literature 15
Table 2-3 Related literature of service blueprint 18
Table 2-4 Related literature of service employee 19
Table 2-5 Literature about positive or negative effect of crowding 22
Table 3-1 Positive dimension sub-dimensions 27
Table 3-2 Conceptual definitions and assessment approaches of each sub-dimension 31
Table 3-3 Variables included in the SEV model 32
Table 4-1 Reliability of the number of observations 38
Table 4-2 Cronbach’s Alpha values for all variables 38
Table 4-4 Service atmosphere statistics for Onion 47
Table 4-5 Service process statistics for Onion 48
Table 4-6 Service employee statistics for Onion 49
Table 4-10 Cronbach’s Alpha values for the variables 56
Table 4-12 Service process statistics for TASTY 63
Table 4-13 Service process statistics for TASTY 65
Table 4-14 Service employee statistics for TASTY 66
Table 5-1 Cross Analysis of TASTY and Onion dimensions 72
Table 5-2 Cross Analysis of the service atmosphere dimension for TASTY and Onion 73
Table 5-3 Cross Analysis of service process for TASTY and Onion 74
List of Figures
Figure 1-1 Global GDP compositions by sector 2
Figure 1-2 Contribution of the service industry to global GDP 3
Figure 1-3 Evidence of service from a consumer perspective 6
Figure 1-4 Structure of the study 9
Figure 3-1 SEV conceptual model 25
Figure 3-2 The crowding function 34
Figure 3-3 The waiting period function 35
Figure 4-1 Gender of Onion patrons 39
Figure 4-2 Age of Onion patrons 39
Figure 4-3 Occupation of Onion patrons 40
Figure 4-4 Education level of Onion patrons 40
Figure 4-5 Reasons for visiting the Onion 41
Figure 4-6 Medium through which customers heard of Onion 41
Figure 4-7 Assessment of Onion features 42
Figure 4-8 Percentage of customers who would recommend Onion 42
Figure 4-9 Average utility of the dimensions of each group 51
Figure 4-10 Average utility of each dimension with the weight and total utility of each group 51
Figure 4-11 Crowding statistics for Onion 52
Figure 4-12 Average negative dimension values for each group 54
Figure 4-13 Variation among different groups 55
Figure 4-14 Gender of TASTY patrons 57
Figure 4-15 Age of TASTY patrons 57
Figure 4-16 Occupation of TASTY patrons 58
Figure 4-17 Education level of TASTY customers 58
Figure 4-18 Reasons for visiting TASTY 59
Figure 4-19 Medium through which customers heard of TASTY 59
Figure 4-20 Assessment of TASTY features 60
Figure 4-21 Percentages of customers who would recommend TASTY 60
Figure 4-22 Average utility of the dimensions of each group 67
Figure 4-23 Average utility of each dimension with the weight and total utility for each group 68
Figure 4-24 Statistics of crowding for TASTY 69
Figure 4-25 Average negative dimension values for each group 70
Figure 4-26 Variation among different groups 71
Figure 5-1 Sample distribution of each group by restaurant 77
Figure 5-2 Sample distribution of each group by gender and restaurant 78

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