A Utility Based Model for Service Experience Value Estimation

碩士 === 淡江大學 === 企業管理學系碩士班 === 101 === 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...

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Bibliographic Details
Main Authors: Ling-Yao Huang, 黃齡瑤
Other Authors: 張瑋倫
Format: Others
Language:en_US
Published: 2013
Online Access:http://ndltd.ncl.edu.tw/handle/34364910802952051196
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Summary:碩士 === 淡江大學 === 企業管理學系碩士班 === 101 === 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.