中 華 大 學 博 士 論 文
整合消費情緒於國際觀光旅館顧客滿意度模式 建置研究
Integrating Consumption Emotions into
International Tourist Hotel Customer Satisfaction model
系 所 別 ： 科技管理博士學位學程 學 號 姓 名 ： D 0 9 7 0 3 0 2 3 宋 明 律 指 導 教 授 ： 葉 鳴 朗 博 士
鄧 維 兆 博 士
中華民國 103 年 07 月
摘 要
觀光產業在許多國家之國民生產毛額(GDP)已占有相當比例，而旅館業更是扮演 著關鍵的地位。國內旅館業伴隨著國人日漸重視生活品質、旅遊活動頻繁所帶來的商 機，觀光旅館業市場不斷擴張，近年不論國際型或國內型知名品牌紛紛設立如雨後春 筍般，競爭更為激烈。旅館業者一直將增進顧客滿意度視為維持競爭力之經營策略，
業者莫不費盡心思設計客製化服務，創造產品的價值，以期讓顧客知覺愉悅的氛圍，
去建立顧客正向的消費情緒，以提升顧客滿意度，最終建立顧客忠誠度，以期維持競 爭優勢，獲取更高之利益，進而達到永續經營的目的。
本 研 究 目 的 在 建 置 旅 館 顧 客 滿 意 度 模 式 (Hotel Customer Satisfaction Index, H-CSI)，以美國國家顧客滿意度模式(American Customer Satisfaction Index, ACSI)為基 礎，將消費情緒構面整合於其中，應用於衡量國際觀光旅館顧客滿意度。問卷題項係 經文獻探討後，並彚整焦點團體訪談之專家建議編製而成，總計回收 412 份有效問 卷，運用部分最小平方法(Partial Least Squares, PLS)進行信、效度檢測、路徑分析及 計算顧客滿意度指標等資料分析。研究結果指出旅館顧客滿意度模式(H-CSI)有良好 的信、效度表現，另外在路徑分析部份皆達顯著水準。
依據研究結果，建議旅館管理者可應用旅館顧客滿意度模式(H-CSI)進行調查，
以獲取較多的資訊，實際了解顧客在消費過程中的感受，包含情緒、價值、滿意度及 購後行為或未來的回遊意願，做為經營策略規劃參考，以期建立競爭優勢。
關鍵字：顧客滿意度模式、國際觀光旅館、消費情緒
i
ABSTRACT
The tourism industry is important in terms of gross domestic product (GDP) and provides numerous employment opportunities in many nations. The hotel industry is a key sector within the tourism industry and faces more intense global competition than other supply industries. With the proliferation of domestic and international brands, the Taiwanese hotel industry has become highly competitive. For International Tourist Hotels (ITHs) sharing a common market position, hardware differentiation is less important than software differentiation, which is crucial to competitiveness. An important motivation to enhance customer satisfaction involves reducing customer switching to others that as a defensive strategy to a firm lead to a stronger competitive position. Delivering superior customer value and satisfaction is crucial to firm competitiveness. Positive emotions are created though experiences with hotel products and services, which imply customer real needs, and the role that emotions play in the selection of hotel. Further, developing customer loyalty is one of the main operational strategies used by hotels facing increasing competition and that increasing customer satisfaction is crucial factor for ensuring customer loyalty.
This study integrates consumption emotions into the American Customer Satisfaction Index (ACSI) model to propose a hotel customer satisfaction index (H-CSI) model that can be applied to estimate customer satisfaction towards ITHs. The H-CSI scale items were designed based on reference to the relevant literature and the suggestions of a focus group.
Four-hundred and twelve customers of ITHs were surveyed. The Partial Least Squares (PLS) method was employed to validate the measurement instruments in the H-CSI model and estimate item weights for the customer satisfaction scales. The H-CSI model is a comprehensive model for the measurement of customer satisfaction that includes most possible antecedents and outcomes. The research results show that the H-CSI model
ii
displayed strong explanatory power based on its reliability and validity.
Accordingly, if hotel managers apply the H-SCI model instead of a general customer satisfaction survey, they can obtain a robust estimation of customer satisfaction, as well as extra information of post-purchase customer behavior to better manage customer satisfaction and achieve a competitive advantage.
Keywords: Customer satisfaction model, International tourist hotel, Consumption emotion
iii
誌 謝 辭
由衷的感謝指導教授鄧維兆博士在論文寫作上給予細心的指導，每次找老師討論 時，您嚴謹的態度是學生學習的榜樣，當遇及寫作瓶頸時，您精闢的建議總是可以迎 刃而解，經由您的導引讓我對服務品質及顧客滿意度模式等相關的領域有更進一步的 認識，並得以成功發表於社會科學索引(Social Science Citation Index, SSCI)收錄期刊 之中順利取得畢業資格。另一位指導教授葉鳴朗博士，感謝您給予學生最大的支持，
您的建議總是充滿著創新及創造力，縈繞在我的腦海裡。
修課期間，深受蔡明春博士及徐聖訓博士等教師無私的傳授專業知識及引領學生 們的討論，在學習的道路上更加充實、茁壯，感謝研究所師長們的用心教學，您的教 導讓學生得以學習充實的知識，更是學術研究的基腳石。此外，非常慶幸在修業有琮 階學長、國樑學弟在博士班課程的相互討論、學習，彼此間相互的打氣、鼓勵，更是 我前進的動力。研究室學妹莉臻及音帆，非常幸運有機會能與你們一同討論研究議題 相互砥礪。
在蒐集資料時，感謝協助我進行國際觀光旅館問卷調查的相關工作人員，讓我得 以更順利的完成資料蒐集並加以分析，因為您的協助才得以有今日豐碩的研究果實。
同時感謝論文口試委員蔡志弘教授、王秀媛博士、巫哲緯博士、蕭登元博士及鍾譽偉 博士，在百忙之中抽空閱讀論文，並對論文提出改善之建議，使此篇論文更具完整、
周延。
最後，感謝家人的支持與鼓勵，在這段期間分攤了許家務事，讓我沒有後顧之憂 的完成論文，另外，就讀期間家中多了一位生力軍-女兒牧恩，因為有你，我的人生 更加圓滿，讓我深刻體會付出、努力，所帶來的幸福。最後，敬謹將此份成就獻給我 所摯愛的親友。
宋明律 謹誌於中華大學 民國103年07月
iv
Contents
摘要...i
ABSTRACT...ii
誌謝辭...iv
Contents ...v
List of Tables...vii
List of Figures...viii
Chapter 1 Introduction...1
Section 1 Research background and motivation...1
Section 2 Research objectives...3
Chapter 2 Literature Review...4
Section 1 Customer satisfaction index...4
Section 2 Service quality...9
Section 3 Consumption emotions...11
Section 4 Perceived value... ...13
Section 5 Customer complaints...14
Section 6 Customer loyalty...16
Chapter 3 Research methodology...18
Section 1 Research framework...18
Section 2 Research hypotheses...19
Section 3 Scale design...21
Section 4 Data collection...23
Section 5 Data analysis... ...25
Chapter 4 Results...29
Section 1 Descriptive analysis...29
v
Section 2 Reliability analysis...31
Section 3 Validity analysis………...33
Section 4 Path estimates………...34
Section 5 H-CSI score calculate……….……..……...38
Section 6 Preliminary test of H-CSI………...……...39
Chapter 5 Conclusions...41
Section 1 Theoretical implication...41
Section 2 Managerial implication...43
Section 3 Suggestions for future research...45
Reference ...46
附錄 A ...55
附錄 B ...56
vi
List of Tables
Table 1 Review of CSI studies...5
Table 2 The instrument of service quality in hotel industry...10
Table 3 Definitions of consumption emotions...12
Table 4 The latent variables and manifest items of H-CSI model...21
Table 5 Demographic of samples...25
Table 6 Means and standard deviations for items…...30
Table 7 H-CSI reliability... ...32
Table 8 H-CSI discriminant validity...34
Table 9 H-CSI path estimates...36
vii
List of Figures
Figure 1 The SCSB Model...5
Figure 2 The ACSI Model...6
Figure 3 The ECSI model...7
Figure 4 The H-CSI Model...18
Figure 5 Path estimates of the H-CSI Model...35
Figure 6 Preliminary test of H-CSI...40
viii
Chapter 1 Introduction
This chapter describes the research background related to hotel industry, research motivation and research objectives.
Section 1 Research background and motivation
The tourism industry is important in terms of gross domestic product (GDP) and provides numerous employment opportunities in many nations. The hotel industry is a key sector within the tourism industry and faces more intense global competition than other supply industries. With the proliferation of domestic and international brands, the Taiwanese hotel industry has become highly competitive. For international tourist hotels (ITHs) sharing a common market position, hardware differentiation is less important than software differentiation, which is crucial to competitiveness. Hotels currently achieve growth by increasing their market share relative to same market competitors. Delivering superior customer value and satisfaction is crucial to firm competitiveness (Kotler &
Armstrong, 1997; Weitz & Jap, 1995).
Fornell (1992) indicated that is an important motivation to enhance customer satisfaction involves reducing customer switching to others that as a defensive strategy to a firm lead to a stronger competitive position. The American Customer Satisfaction Index (ACSI) model is extensively used to measure satisfaction and loyalty at the national, industry, and corporate level (Anderson & Fornell, 2000; Hsu, 2008; Terblanche, 2006).
Anderson and Fornell (2000) have identified a strong positive relationship between ACSI model and national economic returns. Terblanche (2006) applied ACSI model to the South African motor vehicle industry to explain and forecast customer retention by particular companies or brands. Furthermore, numerous researchers have indicated that Customer Satisfaction Index (CSI) can predict firm profitability and market value (Anderson, Fornell
1
& Lehmann, 1994; Anderson, Fornell & Rust, 1997; Eklof, Hackl & Westlund, 1999).
Therefore, the ACSI model provides a direct and meaningful measure of customer consumption utility, subsequent behavior, and economic performance. Therefore, using a suitable CSI model to understand the state of customer satisfaction and post-purchase behaviors is a crucial management issue for hotels.
For the ACSI model, numerous researchers found that the construct of customer expectations does not significantly influence the level of customer satisfaction (Johnson, Gustafsson, Andreassen, Lervik, & Cha, 2001; Martensen, Gronholdt, & Kristensen, 2000).
These two studies have suggested that customer expectations should be removed from the CSI model. Barsky and Nash (2002) indicated that the emotions experienced by hotel guests during their stay are integral to satisfaction and loyalty. Han and Back (2006) and Han and Back (2007) both showed that consumption emotions significantly influenced customer satisfaction in the lodging industry. Brunner-Sperdin, Peters, and Strobl (2012) found customer emotional state to be closely related to customer satisfaction during service consumption in hotel settings. There are two kinds of consumption emotions, these being (1) positive emotions, and (2) negative emotions (Mittal, Ross, & Baldasare, 1998; Han &
Back, 2006). Many recent studies of the relationships between customer satisfaction and consumption emotions indicated that both positive and negative emotions have a significant positive/negative influence on customer satisfaction (Han & Back, 2006; Han, Back & Barrett, 2009; Han, Back & Barrett, 2010; Han & Jeong, 2012; Jung & Yoon, 2011). Bagozzi, Gopinath, and Nyer (1999) considered customer emotions the main determinant of customer behavior. Furthermore, Ryu and Jang (2007) and Jang and Namkung (2009) both view positive customer emotions as being directly related to customer satisfaction, and thus significantly affecting future customer behavior. Positive consumption emotions can create satisfactory service experiences and thus deliver
2
customer value and increase customer loyalty (Dube & Menon, 2000; Dube & Renaghan, 1999). Other, Parasuraman, Zeithaml, and Berry (1988) argued service quality that could be defined as the differences between expectations (E) and perceptions (P) judged by consumers are aggregated into a single score representing overall SQ of a given service performance (SQ=P-E). This study will consider replacing customer expectations with consumption emotions (including both positive and negative emotions) in the ACSI model since customer expectations does not significantly influence the level of customer satisfaction. After excluding customer expectations from ACSI model, the service quality is the perceptions of delivering service that also call perceived quality. Therefore, this study renames “perceived quality” as “service quality”. Further, the present study provides theoretical and practical contributions. On the theoretical side, we propose and empirically test Hotel Customer Satisfaction Index (H-CSI) model, which is a modified version of the ACSI model. On the practical side, this model can serve as ITHs diagnostic tool to represent customers are satisfied or dissatisfied. In addition the study also showed the complaints-handling system is effective; how to improve customer satisfaction; and how effective efforts in improving customer satisfaction have been met.
Section 2 Research objectives
For now, a CSI for ITHs has never been created, validated, and tested. Hence, this study is to propose a H-CSI model for ITHs by adapting the ACSI model and integrating the consumption emotion element.
3
Chapter 2 Literature Review
This study is to propose a H-CSI model by adapting the ACSI model and integrating consumption emotions construct. The chapter is focus on literature review about the construct of H-CSI that includes CSI, service quality, consumption emotions, perceived value, customer complaints and customer loyalty.
Section 1 Customer satisfaction index
The issue of customer satisfaction has attracted in consumer behavior studies more than 30 years. An important motivation to enhance customer satisfaction involves reducing customer switching to others that as a defensive strategy to a firm lead to a stronger competitive position. Customer satisfaction could be defined as the outcome of service quality or product (Cronin & Taylor, 1992). Fornell (1992) indicated the higher customer satisfaction can reduce price elasticity, lower business cost, reduce failure cost and obtain in higher market share and profit.
CSI is the measurement of customer satisfaction on a macroeconomic level of a sector or whole industry. Swedish Customer Satisfaction Barometer (SCSB) was the first CSI (Fornell, 1992). Further, the successful experiences was inspired both ACSI (Fornell, et al., 1996) and European Customer Satisfaction Index (ECSI) (Kristensen, Martensen, &
Gronholdt, 2000). Moreover, the CSI models not only applied to national level but also have designed the CSI for the specific industry (in Table 1). For instance, Table 1 shows the mobile phone sector in Turkish (Türkyilmaz & Özkan, 2007) and the Online-CSI was established in 2008 (Hsu, 2008). The CSI shows a uniform, cross company, cross-industry national measurement instrument of customer satisfaction and evaluations of quality of products and services.
4
+ Perceived Performance
Customer Expectations
Customer Satisfaction
Customer Complaints
Customer Loyalty +
+
+ -
- Table 1
Review of CSI studies
Name of CSI Authors Level of study
SCSB Fornell (1992) National level
ACSI Fornell, et al., (1996) National level
ECSI Kristensen, et al., (2000) National level TMPS Türkyilmaz & Özkan (2007) Industrial level
e-CSI Hsu (2008) Industrial level
SCSB model was the first national CSI reported in 1989. It was conducted 130 companies from 32 industries (Fornell, 1992). Figure 1 illustrated the structural model is caused by two antecedent factors (customer expectations and perceived performance) and the two consequences factors (customer complaints and customer loyalty). Both antecedents are expected to have positive effect on satisfaction. The consequences of satisfaction that is expected to increase in satisfaction should decrease complaints and increase customer loyalty.
Figure 1 The SCSB Model
Note. From “A national customer satisfaction barometer: The Swedish experience,” by Fornell, C., Journal of Marketing, 56(1), 6-21.
5
+
+ Perceived
Quality
Customer Expectations
Perceived Value
Overall Customer Satisfaction
Customer Complaints
Customer Loyalty +
+
+
+
-
+
The ACSI model was adapted SCSB model in the distinct characteristics of the US economy. The survey of ACSI was conducted for 7 main economic sectors, 35 industries, and more than 200 companies with revenues totaling nearly 40 percent of the GNP. Figure 2 shows the ACSI model, there is a little difference between SCSB. In ACSI, new added perceived quality (PQ) component such as distinct from perceived performance, and renamed the perceived performance to perceived value (PV). In addition, ACSI stay the customer expectations (CE) element. The causal relationship of ACSI model were PQ, CE, and PV has positive effect customer satisfaction. For the consequences, as in the SCSB, customer satisfaction increase then customer loyalty (CL) increase and complaints decrease (Fornell, et al., 1996).
Figure 2 The ACSI Model
Note. From “The American Customer Satisfaction Index: Nature, Purpose, and Findings,”
by Fornell, C., et al., Journal of Marketing, 60(4), 7-18.
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Image
Expectations
Perceived Value
Customer
Satisfaction Customer Loyalty Perceived Quality
of Hard Ware
Perceived Quality of Human Ware
The successful experiences of the SCSB and ACSI have further inspired ECSI. The ECSI model was introduced in 1999, across 12 European countries (Kristensen, et al., 2000) which was modified adaption the ACSI model, considers the whole European economy.
Figure 3 shows the determinants of customer satisfaction were perceived brand Image, CE, PQ, and PV. Customer loyalty was the consequence in ECSI model, but does not include the complaint behavior construct as the consequence of satisfaction. Brand image is expected to have direct effect on perceived value and loyalty. Perceived quality was divided into two dimensions such as hard ware and human ware. Hard ware represents the quality of the product/service attributes and human ware which consists the associated customer interactive elements in consumption process.
Figure 3 The ECSI model
Note. From “Customer satisfaction measurement at Post Denmark: Results of application of the European Customer Satisfaction Index Methodology,” by Kristensen, K., et al., Total Quality Management, 11(7), 1007-1015.
7
Then the Turkish mobile phone sector (TMPS) was applied ECSI framework which comprise the antecedents (image, customer expectations, perceived quality, and perceived value) and consequence of satisfaction (loyalty) (Türkyilmaz & Özkan, 2007). In addition, Hsu (2008) modified adaption of the ACSI to propose an online customer satisfaction index (e-CSI) for online retailer. The e-CSI model is removed customer expectation by trust and perceived quality is replaced by e-Service quality.
However, CSI model could be designed for the specific industry and which structural model is based on the assumptions the customer satisfaction is caused by some factors such as perceived quality, perceived value, customer expectation, image of a firm and etc. These factors are the antecedents of overall customer satisfaction. The model also estimates the results when a customer is satisfied or not. These results of customer satisfaction are consequences factors such as complaints handling or loyalty of customer (Johnson, et al., 2001). Each factor in the CSI model is a latent construct which is operationalized by multiple indicators (Chien, et al., 2002; Fornell, 1992). Overview the CSI model is defines customer’s consumption experience to date with product or service provider and predicts customer intention. This approach to satisfaction provides a more direct and comprehensive measure of a customer’s consumption utility, subsequent behaviors and economic performance (Fornell, et al., 1996). CSIs were built upon a cumulative view of satisfaction.
Despite the great contribution of SCSB and ECSI model to the literature. It is undeniable customer complaint behavior has possible exist in consumption process, but ECSI does not include measure of the complaint behavior. Within SCSB without quality construct but that is crucial factor in service setting. Consider the real situation to better understand customer behavior in hotel. Therefore, the H-CSI model is adapting the ACSI model and integrating the consumption emotions element. The CSI has more direct and
8
comprehensive measure of customer consumption utility, subsequent behaviors and economic performance (Fornell, et al, 1996).
Section 2 Service quality
Superior service quality enables a firm to differentiate itself from its competition, gain a sustainable competitive advantage, and enhance efficiency (Kandampully & Suhartanto, 2000). Service quality has been extensively researched in service marketing. Parasuraman, et al., (1988) have developed a standardized instrument called SERVQUAL to measure service quality which has five dimensions: tangibles, reliability, responsiveness, assurance, and empathy. SERVQUAL is applied to measure customers’ expectations and perceptions of service performance. Perceived service quality can be determined by comparing customers’ expectations and perceptions of actual service performance. On the other hand, Cronin and Taylor (1992) demonstrated the performance-based (SERVPERF) measurement of service perceptions that can explain the most variance in the measurement of overall service quality.
Service quality is identified as crucial in differentiating service products, and creating competitive advantage in the service sector. SERVQUAL has been successfully applied to the hotel sector. Table 2 indicated the importance of service quality studies in hotel industry. Knutson, Stevens, Wullaert, Patton and Yokoyama (1990) adapted the SERVQUAL dimensions and developed an instrument called LODGSERV to assess service quality in the lodging industry. Reliability is the most important element in LODGSERV. Further, HOLSERV was extended the dimensions of SERVQUAL in the Australian hotel industry and developed the three dimensions (employees, tangibles and reliability) (Mei, Dean, & White, 1999). Moreover, Getty and Getty (2003) argued the Lodging Quality Index (LQI) with five service quality dimensions (tangibles, reliability,
9
responsiveness, confidence and communication). Above shows the SERVQUAL has been extensive discuss and attempted to identify the elements in hotel industry. Several studies have emphasized the reliability is the most important element of service quality in hotel.
Table 2
The instrument of service quality in hotel industry
Instrument Authors Elements
SERVQUAL Parasuraman, et al., (1988) tangibles, reliability, responsiveness, assurance, and empathy
LODGSERV Knutson, et al., (1996) tangibles, reliability, responsiveness, assurance, and empathy
HOLSERV Kristensen, et al., (2000) employees, tangibles and reliability Lodging Quality
Index (LQI)
Getty & Getty (2003) tangibles, reliability, responsiveness, confidence and communication
On the other hand, Kandampully and Suhartanto (2000) stated that customer satisfaction of housekeeping was found to be the only significant factor that affected customer loyalty. Reception, food and beverages, and prices were regarded as supporting factors of customer retention. This result is consistent with Min and Min (1997; 2005) who indicated the cleanliness of guest rooms is an impressed service attributes of service quality. Since hotel service is primarily a people-delivered service, ensuring service reliability is an important factor for service delivery in the hotel industry. The reliability service represented the degree to which hotel offering is reliable and standardized.
Hotel managers should continually provide and improve customization services to meet customer requirements and achieve competitive advantage. These customization services include more amenities, comfortable rooms, fast check-in/check-out, courtesy, and high-speed Internet service. Within hotel, the interaction between customer and service provider can have a substantial impact on the evaluation of hotel services. Customization service describes the efforts of a hotel to provide services that match changing customer
10
requirements and lifestyles.
Thus, regardless of whether for general or customized service, service quality clearly influences customer satisfaction and consumption values. Customer satisfaction can be ensured by providing high quality services (Getty & Getty, 2003; Tsang & Qu, 2000).
Service quality thus is an antecedent of customer satisfaction.
Section 3 Consumption emotions
Another important argument proposed by this study is that customer experiences with hotels will lead to certain consequences that are reflected in customer’s consumption emotions. Each emotional experience is influenced by the environment and represents actual customer perceptions and feelings regarding a service product. The role of affective processes is an important subject in consumer behavior. Hotels generally ask customers for feedback on the process involving their hotel stay, for instance the speed of guest check-in, for example without recording those reports of customers’ emotions and feelings. Hotel service delivery is characterized by strong interaction between employees and consumers (Lewis & McCann, 2004). Front-line employee actions and services frequently influence customer emotions (Mattila & Enz, 2002). Barsky and Nash (2002) have shown that consumption emotions significantly influence customer hotel selection decisions. Lodging best practices mentioned that customers desired and benefits were having a worry-free and comfortable stay in hotel (Dube & Renaghan, 1999). Consequently, numerous hotel providers have begun designing services to positively influence guest emotions (Jang &
Namkung, 2009). Attributes of the service delivery process (impressive architecture, tangible environment, front-line services etc.) influence the customer emotions generated in response to positive or negative experiences (Havlena & Holbrock, 1986). The concept of consumption emotion refers to the set of such emotional responses elicited specifically during consumption experiences (Westbrook & Oliver, 1991).
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Number of articles has been conceptualized on consumption emotions such as Table 3 shows that Izzard (1977) raised the Differential Emotional Scale (DES-II), Consumption Emotion Set (CES) established by Richins (1997) and hierarchical consumer emotions (Laros & Steenkamp, 2005). Examples of the DES, Izard (1977) postulates ten primary emotions: interest, joy, surprise, sadness, anger, disgust, contempt, fear, shame and guilt.
Westbrook and Oliver (1991) typology that patterns of emotional response, found five different emotional profiles: happy/content, pleasant surprise, unemotional, unpleasant surprise and angry/upset. A study of CES revealed sixteen emotion clusters including among others anger, worry, contentment and joy. Hence, with proliferation of brands, the hotel industry operates in a very competitive environment. The purpose of Hotel offering customize service is to create customer have positive emotions with accommodation experience. Barsky and Nash (2002) argued different customer emotions as components of satisfaction and loyalty during a hotel stay.
Table 3
Definitions of consumption emotions
Authors Emotions
Izard (1977) interest, joy, surprise, sadness, anger, disgust, contempt, fear, shame, and guilt
Westbrook and Oliver (1991)
happy/content, pleasant surprise, unemotional, unpleasant surprise, and angry/upset
Richins (1997) romantic love, love, peacefulness, contentment, optimism, joy, excitement, surprise, guilt, pride, eagerness, relief, anger, discontent, worry, sadness, fear, shame, envy, and loneliness
Barsky and Nash (2002)
comfortable, content, elegant, entertained, excited, extravagant, important, inspired, pampered, practical, relaxed, respected, secure, sophisticated, and welcome
On the other hand, numerous studies have both shown that there are two kinds of consumption emotions, which are (1) positive emotion, and (2) negative emotion (Han &
Back, 2006; Laros & Steenkamp, 2005; Mittal, et al., 1998). Hence, consumption emotions
12
have been conceptualized as discrete emotions or general dimensions such as positive emotions negative emotions. The role of emotions display mediator of consumer response (Bagozzi, et al., 1999).
Consumption emotions are created though experiences with hotel products and services, which imply customer real needs, and the role that emotions play in the selection of hotel (Barsky & Nash, 2002). Base on the literature review, consumption emotion is antecedent of customer satisfaction (Jang & Namkung, 2009). In addition, consumption emotion has positive associated between perceived value (Laverie, et al., 1993; Walls, 2013) and loyalty (Barsky & Nash, 2002).
Section 4 Perceived value
While progress had been made in the areas of perceived quality and prices, there
remains a great deal of uncertainty as how these concepts combine to for perceived value (Rust & Oliver, 1994). Holbrook (1996) defined customer value as an
interactive relativistic preference experience. The experimental value scale (EVS) measures consumer return on investment, service excellence, escapism and aesthetic appeal (Mathwick, Malhotra, & Rigdon, 2001). Further, Keng, Huang and Zhang (2007) interpreted value elements including efficiency value, aesthetics value, excellence value and playfulness value. Overall customer assessments of product utility are based on perceptions of what is received and given (Zeithaml, 1988).
Michael porter (1985) described that competitive advantage grows fundamentally out of the value a firm is able to create for customers. Customer choice is a function of consumption value that has various influences in different consumption situations (Sheth, Newman & Gross, 1991). Meanwhile, perceived excellence value reflects product performance and the generalized consumer appreciation of a service provider who demonstrates expertise and maintains reliable service (Wu & Liang, 2009). Within
13
consumption process, the customer perceived quality of the core product that offer quality is defined as a customer’s judgment about the relative superiority of a provider’s product compared to competitive alternatives (Lapierre, 2000).
In simple terms, perceived value is based on a trade-off between perceived cost and perceived quality (Zeithaml, 1988). Consumption value is based on the personal feeling of empowerment obtained from comparing and selecting goods or services. Thus, perceived value provides an opportunity for comparison of the firms according to their price-value ratio (Anderson, et al., 1994). Anderson and Fornell (2000) indicated that including perceived value in the CSI model increased the comparability of results across firms, industries, and sectors. Cronin, Brady, and Hult (2000) identified a positive relationship between perceived value and customer satisfaction. Perceived value thus is an antecedent of customer satisfaction and a consequence of perceived service quality.
Section 5 Customer complaints
Customer oriented driven the issue of customer complaining has drawn considerable interest from both researchers and marketers in the past 30 years. The information of Customer dissatisfaction provides firms with opportunities to improve their marketing programs so as to enhance consumer satisfaction and profitability (Fornell & Westbrook, 1984). On the contrary, complaints may give a hotel an unfavorable reputation, which might eventually undermine the hotel. From theoretical and practical perspective, that is critically important to understand customer complaining behavior.
Customer complaints are generally considered to comprise a set of responses to purchase dissatisfaction. Cheng and Lam (2008) indicated customer complaining behavior is affected by many factors, such as situational factors, product attributes, and personal variables. The complaining behavior can be found as voice responses, private responses, and third-party responses (Singh, 1988). Hence, customer complaint behavior is an action
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by an individual that involves communicating something negative regarding a product or service. Huang, Huang, and Wu (1996) indentified customer complaint behavior alternative as follows:
(1) Do nothing: internalize or ignore the dissatisfaction
(2) Change future behavior: do not buy the item or patronize the seller in the future (3) Private complaint: warm family and friends about the product or seller
(4) Voice complaint: complain to manufacture or retailer
(5) Third party: e.g. complain to customer group, take legal action
However, customer complaining behavior is the potential impact such behavior has on customer future repurchase intentions, their brand loyalty, the recovery strategies of organizations, as well as the spread of word-of-mouth information through such complaints.
When customer makes private complaints such as spreading negative word-of-mouth criticisms, hoteliers should pay more attention to those guests who choose not to complain.
Appropriate handling of customer complaints can increase satisfaction with recovery and thus increase positive word-of-mouth advertising (Maxham & Netemeyer, 2002). Hotel operators should be treating customer complaints as an important opportunity to improve.
In recognition of this, effective complaint handling becomes inevitable for hospitality organizations (Karatepe, 2006).
The relationship between customer satisfaction and customer complaints depends on unsatisfied customer behavior. Efficient handling of a customer complaint can increase customer satisfaction and transform a complaining customer into a loyal one (Fornell, 1992). The exit voice theory of Hirschman (1970) indicates that increasing customer satisfaction significantly reduces customer complaints.
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Section 6 Customer loyalty
In competition environment, service industries focus on service quality and excellence to acquire and retain a pool of loyal and profitable customer. Customer satisfaction is one of the objectives of marketing activity, linking the processes of purchasing and consumption with post-purchase phenomena. The basic argument for satisfying a customer is to improve profitability by expanding the business, gaining higher market share, and gaining repeat and referral business (Barsky, 1992). However, customer loyalty has become a topical issue in research and practice due to its proven dominance in a hotel organization’s success.
Loyalty implies repeat purchasing based on cognitive, evaluative and dispositional factors that are the classic primary components of attitude (Jacoby, 1971). The increase interest in loyalty is due to several benefits resulting from it, to both the hotel and the customer. For a hotel, loyal customers are the most profitable customer type since they tend to repeatedly purchase hotel services. For a customer, loyalty of the specific organization reduces the risk of service variability, allows customer to develop a social rapport with the provider. Furthermore, loyal customers represent a source of positive word-of-mouth advertising (Knutson, 1988). Many studies of customer satisfaction have identified customer retention and recommendations as crucial influences on hotel business success (Hallowell, 1996; Kandampully & Suhartanto, 2000). Thus, Fornell (1992) indicated attracting new customers is more costly and less profitable than retaining the existing ones. Furthermore, Edvardsson, Johnson, Gustafsson and Strandvik (2000) demonstrated customer loyalty has a positive effect on the profitability and revenues of the firm.
Numerous studies have identified increasing customer satisfaction as a crucial factor for ensuring customer loyalty (Barsky, 1992; Hallowell, 1996; Smith & Bolton, 1998).
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Studies show that loyal customers will make repeat purchases and provide favorable word-of-mouth (Fornell, 1992; Zeithaml, Berry & Parasuraman, 1996). Therefore, customer satisfaction is widely recognized as a key influence on the formation of purchase intentions (Castaneda, 2011). Developing customer loyalty is one of the main operational strategies used by hotels facing increasing competition. Consequently, as relationships show in the ACSI, customer loyalty increases and customer complaints decrease when customer satisfaction is good (Fornell, et al., 1996).
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+
+
+
+ +
+
+ -
- Service
Quality
Consumption Emotions
Perceived Value
Overall Customer Satisfaction
Customer Complaints
Customer Loyalty +
Chapter 3 Research methodology
This chapter describes the methods used to conduct the examination of the structure equation model. The first section overviews the research framework of this study. This is followed by a discussion of the development of the questionnaire used in the survey, as well as the data collection procedures. This chapter ends with a description of the statistical techniques used for data analysis.
Section 1 Research framework
Above literature review, it is undeniable customer complaint behavior has real exist in accommodation process and cannot without quality construct in service setting. Hence, the H-CSI is adapted from the ACSI model, where customer expectation is replaced by consumptions emotion. In addition, consider the hotel industry is belong to service setting, to increase the precision of the perceived quality construct for the hotel industry, this study renames “perceived quality” as “service quality”. The H-CSI model consists of the aforementioned constructs which are based on well established theories and approaches in customer behavior. The CSI model can be defined as an overall evaluation of a firm’s post-purchase performance or utilization of a service (Fornell, 1992).
Figure 4 The H-CSI Model
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As illustrated in Figure 4, the H-CSI model is embedded in a set of casual equations, it focus on three antecedents of customer satisfaction (service quality, consumption emotions and perceived value) and the two consequence of customer satisfaction (customer complaints and customer loyalty). The H-CSI is designed to represent the of hotel firm’s market value and profit.
Section 2 Research hypotheses
As show in Figure 4, the left side factors (i.e. service quality, consumption emotions, and perceived value) are the ancients of the customer satisfaction while the right side factors (i.e. customer complaints and customer loyalty) are the consequences. The hypothesized relationships between the latent construct are depicted with lines.
In the proposed H-CSI model, the first determinant of customer satisfaction is service quality, which was expected to directly and positively influence customer satisfaction (Cronin & Taylor, 1992; Terblanche & Boshoff, 2010). This prediction is intuitive and fundamental to all service encounters. Furthermore, service quality should be positively related to consumption emotions (Han & Back, 2006; Jang & Namkung, 2009; Ladhari, 2009; Mattila & Enz, 2002) and perceived value (Fornell, et al., 1996; Whittaker, et al., 2007; Wu & Liang, 2009). Based on the above, this study hypothesizes the following:
H1. Service quality is positively related to customer satisfaction.
H2. Service quality is positively related to perceived value.
H3. Service quality is positively related to consumption emotions.
Literature review identifies consumption emotions as an antecedent of customer satisfaction (Brunner-Sperdin, et al., 2012; Jung & Yoon, 2011; Han & Back, 2006; Han &
Back, 2007; Han, et al., 2009; Han & Jeong, 2012; Jang & Namkung, 2009; Ladhari, 2007;
Liljander & Strandvik, 1997; Mano & Oliver, 1993; Oliver, 1993; Westbrook & Oliver,
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1991), and as being significantly related to perceived value (Laverie, et al., 1993; Walls, 2013) and loyalty (Allen, et al., 1992; Barsky & Nash, 2002; Dube & Menon, 2000; Dube
& Renaghn, 1999; Han & Back, 2006; Han & Back, 2008; Jang & Namkung, 2009;
Ladhari, 2009). Based on the above, this study hypothesizes the following:
H4. Consumption emotions are significantly related to perceived value.
H5. Consumption emotions are significantly related to customer satisfaction.
H6. Consumption emotions are significantly related to customer loyalty.
The second determinant of customer satisfaction is perceived value. Adding perceived value incorporates price information into the model so consumer can compare brands and sectors from a monetary perspective (Johnson & Fornell, 1991). Studies show the positive relationship between the perceived value and customer satisfaction (Cronin, et al., 2000).
Above, this study hypothesizes the following:
H7. Perceived value is positively related to customer satisfaction.
The consequences of customer satisfaction are customer complaints and customer loyalty. The immediate results of an increase customer satisfaction are decreased customer complaints (Fornell, et al., 1996; Hirschman, 1970). Thus, suggest the relationship between customer satisfaction and customer complaint should be negative. Further, the relationship between the customer complaint and customer loyalty is negative (Fornell, 1992). Besides, customer satisfaction is widely recognized as a typical factor to influence customer loyalty.
Therefore, this study hypothesizes the following:
H8. Customer satisfaction is negatively related to customer complaint.
H9. Customer satisfaction is positively related to customer loyalty.
H10. Customer complaints are negatively related to customer loyalty.
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Section 3 Scale design
The H-CSI model consists of the aforementioned constructs based on well-established theories. The constructs of the H-CSI are latent variables indirectly described by a block of observables which are called manifest variables. The constructs and their observable items are given in Table 4. Use of the multiple questions for each construct increase the precision of the estimate, compared to an approach of using a single question.
Table 4
The latent variables and manifest items of H-CSI model Latent variables Manifest (observable) variables
Service quality SQ1: Hotel’s offering is customized to meet customer needs SQ2: Hotel’s offering is the same as it’s promise
SQ3: My overall perception of service quality is satisfactory Consumption emotions CE1: I feel amazed with the consumption process
CE2: I feel comfortable with the consumption process CE3: I feel disappointed with the consumption process Perceived value PE1: Hotel has good price under given quality
PE2: Hotel has good quality under given price Overall Customer
Satisfaction (CSI)
CS1: I feel satisfactory of hotel’s overall performance CS2: The hotel performance has met my expectation
CS3: The satisfaction level of hotel is quite close to my ideal hotel
Customer loyalty LY1: I will revisit the hotel in the future LY2: I will recommend this hotel to others
LY3: Even hotel price is increased, I will still revisit this hotel
Customer complaints CC1: I had complained about hotel’s product/service by either formal or informal way
The measurement scale items of the proposed H-CSI were designed primarily using the questionnaire of the ACSI study. In designing the questionnaire, a 10-point Likert scale, anchored by “1” meaning strongly disagree and “10” meaning strongly agree, was used to
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reduce the statistical problems of extreme skewness (Fornell, et al., 1996). For the measurement scale items of the service quality construct, this study utilized three scales of perceived quality in the ACSI questionnaire, these being: (1) the hotel offering is customized to meet customer needs, (2) the hotel offering is the same as its promise to be, and (3) overall perceived service quality (Fornell, et al., 1996). Regarding perceived value, this study utilized two components of perceived value in the ACSI questionnaire: (1) price relative to given quality, and (2) quality relative to given price (Fornell, et al., 1996).
This study used the Differential Emotions Scale (DES) (Izard, 1977) to develop the initial attributes of consumption emotions. Han, et al. (2010) and Han and Jeong (2012) have both indicated that “comfort” and “annoyance” are two factors that have higher influence on customer satisfaction than other factors. The attributes in the “comfort” factor are positive emotions and the attributes in the “annoyance” factor are negative emotions.
Therefore, the initial attributes of consumption emotions contained the two factors of
“comfort” and “annoyance”, with each having four positive or negative emotion attributes, respectively. For generating simple, clear and understandable items of consumption emotions, this study convened a focus group to decide final attributes of consumption emotions. The focus group was composed of two managers of ITHs, one professor in Hospitality Management, and two customers with ample experience of ITHs. A list of eight emotion attributes (comfortable, relaxed, pleased, amazed, frustrated, disappointed, angry, and skeptical) was presented to the focus group for the purpose of removing unusable attributes that were ambiguous or redundant. A pool of three consumption emotion attributes was retained (amazed, comfortable and disappointed). The first two attributes belong to the category of “comfort” factors and are positive emotion attributes.
The third attribute belongs to the category of “annoyance” factors and is a negative emotion attribute. Consequently, the finally generated scale items of consumption
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emotions were (1) I feel amazed with the consumption process, (2) I feel comfortable with the consumption process, and (3) I feel disappointed with the consumption process.
Customer satisfaction level represents a cumulative and post-purchase evaluation of services offered by an ITH. An assessment of customer satisfaction comprises a fundamental indicator of a firm’s past, current, and future performance, and significantly influences a firm’s operations and profitability. Customer satisfaction comprises the core of the proposed H-CSI model and the ACSI model. Customer satisfaction was assessed using three scale items in the ACSI questionnaire, namely (1) an overall satisfaction rating, (2) a rating of whether hotel performance falls short of or exceeds expectations, and (3) a rating of satisfaction in comparison to customer ideals regarding a product/service (Fornell, et al., 1996).
Customers may feel dissatisfied with a specific transaction and complain. By referring to the ACSI questionnaire, this study used “Did customers complain either formally or informally when they were dissatisfied with the product/service” as scale item to estimate customer complaint. In addition, the scale items for measuring customer loyalty were: (1) customer intention to revisit, (2) customer intention to recommend the hotel to others, and (3) customer tolerance of hotel pricing (Fornell, et al., 1996).
Two versions of the questionnaire were prepared: English and Chinese. The primary questionnaire was pre-tested on 30 customers who had stayed in an ITH in Hsinchu city, Taiwan. From the pilot run of the questionnaire survey, this study confirmed the questionnaire reliability and changed some ambiguous or misleading wording.
Section 4 Data collection
The questionnaire survey sites selected for this study were the lobby of the departure area at Taiwan Taoyuan International Airport and public parking lots of ITHs. Overseas tourists were a major source of respondents when the questionnaire was administered at
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Taiwan Taoyuan International Airport. Domestic group package tourists were a major source of respondents when the questionnaire was administered at parking lots of ITHs.
The survey conducted from July to September 2011. Before starting the formal survey, our investigators confirmed that all invited respondents had experience of staying at an ITH in Taiwan during the past month. The sampling method applied was convenience sampling.
The respondents were surveyed through on-site intercept with the offer of a free gift.
Tourists who were willing to participate in the survey and who had experience of staying at an ITH in Taiwan completed the questionnaires themselves based on their perceptions of their ITH stay.
Ultimately, 650 tourists were invited to complete the questionnaire, and 412 effective samples were obtained (usable response rate is 63.38%). The characteristics of the respondents are summarized in Table 5. The gender breakdown of the respondents was 52.6% male and 47.4% female. The mean age of the respondents was 35.28 years old. The main age group was 30-39, which represented 43.7% of the respondents. Most of the respondents (66.7%) had a college or university level education. The main respondents were domestic tourists, who represented 73.1% of the respondents.
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Table 5
Demographic of samples
Variables Frequency Percentage of total
Gender
Male 217 52.6
Female 195 47.4
Age
20-29 117 28.3
30-39 180 43.7
40-49 74 18.0
Above 50 41 10.0
Education
High school 46 11.2
College or university 275 66.7
Graduate 91 22.1
Nationality
Domestic 301 73.1
Overseas 111 26.9
Note: n=412
Section 5 Data analysis
Advances in causal modeling techniques have made it possible to simultaneously examine theory and measures (Hulland, 1999). Structure equation model (SEM) is comprehensive statistical approach for testing hypotheses about relations between observed and latent variables. Such techniques can be thought of as superior to more traditional techniques. The SEM combines features of factor analysis and multiple regressions for studying both the measurement and the structural properties of theoretical models.
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A CSI model consists of a set of latent variables (LVs) that depict the cause-and-effect relations between the antecedents and consequences of customer satisfaction. There are two statistical approaches for structure equation model. Maximum likelihood (ML) based approach is widely known technique to estimate SEM. That involves parameter estimation procedures which seek to reproduce as closely as possible the observed covariance matrix. The objective of ML based estimation is minimizing the difference between observed and predicted variance-covariance matrices (Hsu, Chen &
Hsieh, 2006). An alternative casual modeling approach known as Partial Least Squares (PLS) based variance analysis method (Wold, 1982). In contrast, Hulland (1999) argued the PLS has as its primary objective the minimization of error (or, equivalently, the maximization of variance explained) in all endogenous constructs. In addition, PLS has feature to handle both reflective and formative measurement models. Within H-CSI model manifest variables are related to their latent variables in reflective way in which manifest variables are viewed as being affected by the underlying construct. Reflective indicators are typical for classical factor analysis models (Chin, 1998).
While techniques such as ML based and PLS based can enrich existing methodological approaches to conducting analysis must be used appropriately. Hsu, et al.
(2006) reveal ML based SEM suffer from the factor indeterminacy problem and that evidenced the PLS based SEM has more suitable performance to estimate parameters in real-life CSI scenario. Hence, PLS approach is superior to the ML based structure analysis in specific situations and that is suggested as useful estimation method for CSI study.
The PLS method is particularly well-known due to having been successfully applied to CSI studies (Fornell, 1992; Fornell, et al., 1996; Hsu,2008; Kristensen, et al., 2000;
Türkyilmaz & Özkan, 2007). Hence, this study used PLS to estimate path modeling as that of ACSI and ECSI. Barclay, et al. (1995) suggested that PLS optimization is more suited
26
for predictive applications and theory development related to model research. Using the PLS analysis results of the CSI model and path coefficients, researchers can answer questions regarding the reasons for customer satisfaction or dissatisfaction, and how to improve customer satisfaction (Hsu, et al., 2006). Moreover, PLS is a useful tool for model research intended to obtain indicator weights and predict latent variables.
Three general sets of data analysis considerations are relevant to the application of PLS in present study: (1) assessing the reliability and validity of multiple construct; (2) determining the appropriate nature of the relationships between measures and constructs;
and (3) interpreting path coefficients, determining model adequacy. This sequence ensures the H-CSI has reliable and valid measures of constructs attempting to draw conclusions.
To verify the reliability and validity of the formal questionnaire, the composite reliability (ρс) for each construct was calculated to verify reliability, and confirmatory factor analysis (CFA) was performed to verify the validity of the measures by using PLS.
The reliability represents the internal consistency of all indicators in relation to the construct, and can be determined using the measure of composite construct reliability (ρс).
The composite construct reliability score is superior to the Cronbach’s alpha measure of internal consistency within a construct since it uses the item loadings obtained within the causal model (Fornell & Larcker, 1981). Hullad (1999) argued that low internal consistency can result from a variety of underlying causes, including poor construct definition and/or construct multidimensionality. The acceptable threshold of composite construct reliability is greater than 0.60 (Fornell & Larcker, 1981).
CFA can obtain the confirmatory factor loadings of the manifest variables with their respective constructs. If all confirmatory factor loadings exceeded 0.7, then the measurement model has convergent validity (Anderson & Gerbing, 1988). In this situation, more shared variance than error variance exists between the latent variables and their
27
associated measurements (Carmines & Zeller, 1979). A rule of thumb employed by many researchers is to accept items with loadings more than 0.70 which implies that there is more shared variance between the construct and its measure than error variance (Carmines
& Zeller, 1979; Hulland, 1999).
When the measurement model has multiple constructs, researchers should also concern themselves with the discriminant validity. The confirmation of construct discriminant validity can be examined using its Average Variance Extracted (AVE), which should yield the following results: (1) the AVE must exceed 0.5 (Fornell, 1992), and (2) the AVE should exceed all inter-construct correlations for each construct (Fornell & Larker, 1981). Other, PLS is not proper overall goodness-of-fit measures exist for model estimate and the degree to which any particular PLS model accomplishes this objective can be determined by examining the R2 values for the dependent constructs (Hulland, 1999).
Furthermore, PLS that typically used in CSI model will be applied to double test the validity of the proposed H-SCI model and to generate the estimated weights of customer satisfaction scale items. After having the estimated weights of customer satisfaction scale items, the H-CSI score can be predicted for specific ITH or Taiwanese ITH industry.
Additionally, the present study has a little work before the statistic analysis. As the framework of H-CSI, there is only one factor of consumption emotions. There were two positive emotion items and one negative emotion item in the consumption emotions section.
Thus, the negative emotion item scale was reversed before data analysis. In this way we could integrate negative emotion with positive emotion to examine the relationships of consumption emotions to service quality, perceived value, customer satisfaction, and customer loyalty.
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Chapter 4 Results
This study intends to investigate hotel related experience dimensions and their impact.
The chapter is comprised of five sections. Descriptive analysis of scale items are given in section 1. Section 2 and section 3 provide reliability and validity of H-CSI. Path estimates were showed in section 4. The Index score was calculated in section 5. Finally, the present study gives a preliminary test of H-CSI.
Section 1 Descriptive analysis
Using sample of 412 valid survey responses, this study analyzed the proposed H-CSI model using the PLS estimation approach and SmartPLS 2.0 software (PhpBB, 2005).
After confirming model reliability and validity, the estimated weights of customer satisfaction scales were obtained to calculate the final H-SCI score.
Means and standard deviation for all measures are reported in Table 6. All scales ranged from one to ten. Three service quality items received means greater than eight. The means value of customized and reliability service both were 8.57 and that have higher than other items in scale. Means of the three consumption emotions items were 7.01, 8.17, and 8.26. Two perceived value items received means around eight. The results showed that respondents reported great number of satisfaction experiences. Means for customer satisfaction items were 7.83, 8.02, and 7.95. Mean for customer complaints item was 2.37.
Finally, means for customer loyalty were 8.24, 8.28, and 7.29.
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Table 6
Means and standard deviations for items
Item Mean* SD
Service quality
Hotel’s offering is customized to meet customer needs 8.57 1.37 Hotel’s offering is the same as it’s promise 8.57 1.38 My overall perception of service quality is satisfactory 8.39 1.56 Consumption emotions
I feel amazed with the consumption process 7.01 1.42 I feel comfortable with the consumption process 8.17 1.42 I feel disappointed with the consumption process 8.26** 1.64**
Perceived value
Hotel has good price under given quality 7.97 1.44 Hotel has good quality under given price 8.08 1.45 Overall Customer Satisfaction (CSI)
I feel satisfactory of hotel’s overall performance 7.83 1.40 The hotel performance has met my expectation 8.02 1.28 The satisfaction level of hotel is quite close to my ideal hotel 7.95 1.56 Customer loyalty
I will revisit the hotel in the future 8.24 1.42
I will recommend this hotel to others 8.28 1.45
Even hotel price is increased, I will still revisit this hotel 7.29 1.71 Customer complaints
I had complained about hotel’s product/service by either formal or
informal way 2.37 1.65
*Ten-point Likert scale: 1= Strongly disagree; 10= Strongly agree.
**The numbers are obtained by negatively adjusted the values of negative emotion item scale
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Section 2 Reliability analysis
CFA can obtain the confirmatory factor loadings of the manifest variables with their respective constructs. To ensure that the measures used for the various constructs are reliable, the present study calculated loadings and composite reliability. Reliability checks were conducted on the multiple items measures used in this study. The reliability coefficients for the scales utilized in the present study are reported in Table 7.
Fornell and Larcker (1981) suggested that coefficients of 0.60 or higher were acceptable. Table 7 lists the composite construct reliability value of each construct and scale. The reliability coefficient of service quality was 0.93. Consumption emotion with three items used yielded a coefficient of 0.93. Perceived value yielded coefficient was 0.96 by two items. The reliability coefficient of customer satisfaction was 0.90. Coefficient for customer complaints was 1 and the customer loyalty was 0.91. Above shows the composite construct reliability values ranged from 0.93 to 1 (in Table 7). Therefore, the results showed the measurement model has acceptable reliability.
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Table 7
H-CSI reliability
Construct Loadings Composite construct reliability (ρс)
Service quality (SQ) a 0.93
SQ1 b 0.91
SQ2 0.84
SQ3 0.93
Consumption emotions (CE) 0.93
CE1 0.91
CE2 0.91
CE3 0.88
Perceived value (PV) 0.96
PV1 0.95
PV2 0.96
Overall Customer Satisfaction (CSI)
0.90
CS1 0.79
CS2 0.90
CS3 0.89
Customer complaints (CC) 1
CC1 1
Customer loyalty (LYT) 0.91
LYT1 0.92
LYT2 0.93
LYT3 0.80
a SQ (service quality), CE (consumption emotions), PV (perceived value),
CSI (overall customer satisfaction), CC (customer complaints), LYT (customer loyalty).
b SQ1 (first scale item of service quality), SQ2 (second scale item of service quality), SQ3 (third scale item of service quality).
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Section 3 Validity analysis
According Carmines and Zeller (1979) indicated the items with loadings should greater than 0.70. Table 7 lists the loadings value of each item. Three service quality items received loadings were 0.91, 0.84, and 0.93. Loadings of the three consumption emotions items were 0.97, 0.91, and 0.88. Two perceived value items received loadings greater than nine. The loadings of the three customer satisfaction were 0.79, 0.90, and 0.89. Loading for customer complaints item was 1. Loadings for customer loyalty were 0.92, 0.93, and 0.80.
All confirmatory factor loadings of each scale ranged from 0.79 to 1 (Table 7). These results demonstrate the convergent validity of the measurement model. The results showed all of the manifest variables have good measure of their latent variable.
Further, to assess discriminant validity measure should be greater than the variance shared between the construct and other constructs in the model (Fornell & Lacker, 1981;
Hulland, 1999). This can be demonstrated in a correlation matrix which includes the correlations between different constructs in the lower left off-diagonal elements of the matrix, and the average variance extracted values calculated for each of the constructs along the diagonal. For adequate discriminant validity, the diagonal elements should be significantly greater than the off-diagonal elements in the corresponding rows and columns.
As show in Table 8, the inter-construct correlations and AVE value (in the diagonal) for six constructs. The AVE values of SQ, CE, PV, CSI, CC, and LYT were 0.81, 0.81, 0.92, 0.74, 1.0, and 0.78, respectively. The inter-construct correlations of service quality ranged from 0.66 to 0.76, and were all below the AVE value of 0.81. Identical results exist for the other five constructs. Therefore, the measurement model has acceptable discriminant validity. This study first conducted confirmatory factor analysis (CFA) with PLS to confirm the reliability and validity of the constructs and all scales in the H-CSI model.
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Meanwhile, all scales used to examine the model demonstrated reasonable validity (i.e., convergent and discriminant validity) and reliability (i.e., composite reliability). However, the H-CSI model is a SEM which consists of well-established theories and approaches in customer behavior. The constructs of the H-CSI model are latent variables indirectly described by manifest variables.
Table 8
H-CSI discriminant validity
Constructs SQ CE PV CSI CC LYT
SQ 0.81
CE 0.73 0.81
PV 0.66 0.59 0.92
CSI 0.72 0.67 0.67 0.74
CC 0.76 0.68 0.62 0.67 1
LYT 0.73 0.64 0.71 0.73 0.70 0.78
Section 4 Path estimates
As the mentioned earlier, the proposed H-CSI model has adequate reliability and validity. This further implies that the measurement scales used for each latent variable are accurate, and all six constructs are both conceptually and empirically distinct. Furthermore, confirmatory measurement of the model demonstrates the soundness of its measurement system.
Next, the section is focus on empirically test an H-CSI model, which is a modified version of the ACSI model. This study assessed the path estimates of the H-CSI model.
Figure 5 shows ten path estimates corresponding to the ten research hypotheses. Each path coefficient was obtained by bootstrapping computation of R2 and t-value hypothesis testing for each hypothesis. In the PLS structural equation model (SEM), the estimated structural model of the interrelationships between the independent latent variables and dependent variables must be validated before researchers can conclude that model predicted values
34
accurately predict responses. Maximization of the explained variance for each dependent variable is the main objective of PLS and can be measured using R2 values. Fornell, et al., (1996) have demonstrated that the ability to explain important latent variables in a model is an indicator of model performance, particularly the overall customer satisfaction and customer loyalty variables. From the results shown in Figure 5, the R2 value of overall customer satisfaction is 0.61 and the R2 value of LYT is 0.62. In other words, the H-CSI model explained 61% of the variance in overall customer satisfaction and 62% of that in customer loyalty. These results mean that the H-CSI model closely fits the data, has satisfactory predictive capability, and can help hotel managers improve customer satisfaction.
Figure 5 Path estimates of the H-CSI Model
*t > 1.96, **t > 2.58, ***t > 3.29
0.73*** -0.32***
0.33***
PV
Overall
CS
R2 = 0.61
LYT
SQ CC
0.50***
0.22*
0.24**
0.14*
0.31***
0.42***
-0.67***
R2 = 0.62
CE
H1 H2
H3
H4
H5
H6 H7
H8
H10
H9
35
