influence of customer perceived value on tourist satisfaction … · 2017. 5. 3. · brine, leh...

International Journal of Accounting & Business Management

www.ftms.edu.my/journals/index.php/journals/ijabm

Vol. 4 (No.1), April , 2016

ISSN: 2289-4519 DOI: 10.24924/ijabm/2016.04/v4.iss1/98.119

This work is licensed under a Creative Commons Attribution 4.0 International License.

Research Paper

Influence of Customer Perceived Value on Tourist Satisfaction and Revisit Intention: A study on Guesthouses in Maldives

Abstract This study attempts to examine the customer perceived value associated with guesthouse services in tourism in local islands of Maldives. Also this study attempts to examine the relationship associated between CPV, tourist satisfaction and revisit intention. The study has been conducted on the Island of Maafushi, Maldives. Based on literature, a questionnaire was developed based on Seth, Newman and Gross (1991) Consumption Value Framework and sub variables are selected using past literature. Questionnaire was distributed among the tourist stayed in the guesthouses. The questionnaire consisted of 2 dependent variables (Satisfaction and Revisit Intention) measured the direct impact from the 5 variables and satisfaction to revisit intention. The 5 independent variables (functional value, emotional value, epistemic value, social value and conditional value) measured the direct influence and mediating effect on customer satisfaction and revisit intention. The Likert Scale (Disagree -1 and 5 for Agree) was used to answer the questionnaire consisting of 35 questions. 263 questionnaires were being distributed using convenient sampling method and a sample of 203 tourists was used in this study. Confirmatory factor analysis and followed by Structural Equation Modelling was conducted using AMOS 22 to analyse the impact of CPV on satisfaction and revisit intentions. The findings shows that only functional and emotional values have a positive and significant impact on tourist satisfaction. Social Value is the only CPV that has a positive and significant impact on Tourist intention to revisit. We found tourist satisfaction has direct positive and significant influence on their intention to revisit. The effect on revisit intention is directly mediated by satisfaction and social value while social value and satisfaction indirectly mediate revisit intention. Therefore it is important that the island council and the managements of guesthouses work together and resolve the issues that affect customer satisfaction and also to educate the locals of the importance of tourism in the island which supports the island economy. Future research may be focused on some other islands providing guest house tourism to confirm and generalise the findings throughout the country. Key Terms: Customer Perceived Value (CPV), Tourist Satisfaction, Revisit, Guesthouses, Maldives

Nishan Waheed School of Accounting and Business Management

FTMS College, Malaysia [email protected]

Zubair Hassan School of Accounting and Business Management

FTMS College, Malaysia [email protected]

http://creativecommons.org/licenses/by/4.0/

http://creativecommons.org/licenses/by-nc/4.0/

http://creativecommons.org/licenses/by-nc/4.0/

mailto:[email protected]

1. Introduction The research is conducted to identify the tourist perceived value of tourism in the local island of Maafushi and the impact on tourist satisfaction and revisit. Contextual Background The research has been carried out in the island of Maafushi which has the highest occupancy rates amongst local islands and has the highest number of local island guest houses and has the most number of beds. Tourism industries contribution to GDP in 2014 has been 41.5% and a rise of 2.7% has been forecasted to directly contribute in 2015 (World Travel and Tourism Council, 2015). The tourism in Maldives is saturated geographically in 26 natural atolls while it is administered in 20 atolls with 1190 islands. The statistics of 2014 shows that there are 111 resorts, 19 hotels, 220 guest houses and 161 safari’s (Ministry of Tourism, 2015), are directly contributing to the economy and also the supporting industries has developed together. Tourism is known to generate most employment to the country as well as earns more foreign currency than any other industry in the Maldives (Maldives Monetary Authority, 2015). An island heavily damaged in 2004 tsunami, now a thriving local economy after the government’s amendment of tourism law which approved guest houses for tourists in local islands (Ministry of Tourism, 2010). Maldives has been sustaining its tourism for decades in one island resort concept before 2010. The enclave tourism provided the sun, sand, sea, transportation, excursions, diving, snorkelling, other water sports and relaxation in quality and quiet environments (Jamal & Lagiewski, 2006) for the guests. The amendment in law which paved the path for local islands an economic opportunity has proven to be a model of success in Maafushi Island as the number of guesthouses increase and related business are also being developed. The focus on Maafushi Island for the research has been due to characteristics of these types of small islands natural environment, accessibility options and has the most demand among all islands. With the intensified demand, the carrying capacity (O’Reilly, 1986; Briguglio & Briguglio, 1996; Lime, 2001; Ribeiro, Ferreira & Silva, 2011) and the infrastructure (Ashley, Brine, leh & Wilde, 2007; Shardy Abdullah, Arman Abdul Razak & Mastura Jaafar, 2014; Panasiuk, 2007; Ardahaey, 2011) has been a question that raises doubts about customers satisfaction from the services that is been provided to the tourists. If the leading island can be assessed, the future of the other islands can be understood (Dwyer, et al., 2008) on factors that affects guests perceived value and the operational and environmental issues that arises with the establishment of guesthouses. The intensive competition in the island among investors who are all local, has developed the service quality of the guest houses gradually (Slater & Narver, 2000). Research background Several researches done on customer perceived value around the world has been shedding more clarity of research measurement scales for the researches that have been conducted. It helps organizations understand what the customer expects from what they have purchased (Raza, et al., 2012). In the past in many researchers attempted to identify the CPV associated with tourism and its related services in various countries such as Spa Industry of Thailand (Setiowati & Putri, 2012), Tourism industry of Malaysia (Haque & Khan, 2013), Medical tourism of Tunisia(Hallema & Bartha, 2011), Hotel and Tourism industry of China(Chiang & Lee ,2013; Xia, Jie, Chaolin & Feng, 2009), Tourism in Indonesia (Nasution & Mavondo, 2005)and in CPV associated with tourism in Pakistan were examined by Raza, Siddiquei, Ahmed, Awan & Hayat (2012) . In more developed countries such as USA, Williams & Soutar (2005) conducted a research on tourism in general and later Williams & Soutar (2009) conducted a research on adventure tourism of America. However , it is important to note that the researchers found no solid or formal research carried out to examine the impact of CPV on tourist satisfaction in Maldives, especially in Guesthouse

sector of the country. Therefore this study will examine the impact of CPV on tourist satisfaction and intention to revisit. To achieve this following objectives are formulated

Identify the CPV associated with Guesthouses Examine the impact of CPV on tourist satisfaction and revisit intention Examine the impact of tourist satisfaction on revisit intention

The two stages of structural equation (SEM) modelling outputs were interpreted and literature review is used for “face validity” to establish the theoretical model which was proposed. Conclusion will be drawn based on the analysis. 2. Literature Review The most commonly cited definition of CPV is proposed by Ziethmal (1988) is overall economic benefits of a product effectiveness. Alternatively CPV is overall assessment of the utility of a product in terms of what is obtained and what is paid (Ulaga and Chacour, 2001). Sheth et al (1991) argued that CPV is about computation values where it needs to explain why consumer chooses to buy or not to buy a particular product. Various theoretical models and frameworks were developed and empirically tested to assess the relationship between CPV and customer satisfaction. Some research were purely based on tourism sector. One of the pioneering model is Monroe (1985) Price Quality Model. This framework emphasis on quality and price. Trade off model introduced by Zeithaml (1988), is a unidimensional model to measure perceived value by using quality and price as key variables to measure the customer perception toward the products and services. These uni-dimensional frameworks fails to understand customer perceived value broadly in terms of tourism sector as uni-dimensional frameworks emphasis on determining satisfaction or dissatisfaction of consumer’s assessments from service quality and price (Zeithaml 1988; Bolton 1991; Eggert & Ulaga 2002). Alternatively, the multi-dimensional approaches of assessing CPV associated with services or tangible products are proposed with the emergence of service sector. Typology for Consumer Value introduced by Holbrook (1999) incorporated variables such as efficiency, excellence, play, aesthetics, ethics, status, esteem and spirituality as part of CPV. However again, the issue of measuring a CPV for a service is not considered but mainly focus on tangible products and limited focus on evaluating service sector and argued that there is a confusion on the ay define the extrinsic and extrinsic values(Richins, 1999) in relation with satisfaction. Similarly Value Hierarchy Model by Woodruff (1997), a widely adopted multi-dimensional model to assess Customer Perceived Value related with services. The model identifies about the value perception that keeps on changing and the need to understand the buyer behavior of decision making (Flint, et al., 1997). The model has been used on products and organizations to understand measures of value in these areas (Moosa & Hassan, 2015; Lexhagen, 2015). Alternatively Consumption Value framework developed by Seth, Norman & Newman (1991) is a multi-dimensional theory with five consumption values that influences consumer choice behaviour. This framework is suitable to consumer durables and non-durables, industrial products and services while, most of the research indicated are that customer’s purchase intentions are based on benefits as explored by Delafrooz, Paim & Khatibi (2010). The table below shows the key summary of the variable identified

Table 1: Theories and variables

Authors proposal Definition of Value Values

Monroe (1985) Conceptual “an assessment of what they give and what they receive”

1) Price 2) Quality

Zeithaml (1988)

Empirical ‘‘Perceived value is the consumer overall assessment of the utility of a product based on the perceptions of what is received and what is given’’

1) Value is low price 2) Value is whatever I want in a product or service

3) Value is the quality I get for the price I paid 4) Value is what I get for all that I give

Woodruff (1997)

Conceptual “The trade-off between desirable attributes compared with sacrifice attributes”.

1) Desired approach. 2) Received value.

Holbrook (1999)

Conceptual ”An evaluation of an object (product) by some subject (consumer)”.

1) Extrinsic versus intrinsic 2) Self oriented Versus other oriented. 3) Active versus reactive.

Sheth et al. (1991)

Conceptual “Consumer choice is a function of multiple consumption values. These are functional, social, emotional, epistemic and conditional. The consumption values make differential contributions in any given choice situation. The consumption values are independent.”

1) Functional value 2) Social value 3) Emotional value 4) Epistemic value 5) Conditional value

Recent empirical researches attempted to establish the link between CPV dimensions with customer satisfaction and loyalty or revisit or retention. Value for money (economic value) is being cited by most researchers as part of CPV (Setowati & Putri, 2012; Chiang & Lee, 2013) in association with customer satisfaction. Similarly Functional Value was also found to have influence on customer satisfaction (Khan & Kadir, 2011; Chiang & Lee, 2013; Moosa & Hassan, 2015 ). Many other researchers found other dimensions such as Social value (Moosa & Hassan, 2015; Chiang & Lee,2013), Epistemic and Novelty (Hallema & Bartha, 2011; Williams & Soutar 2009), Emotional value (Moosa & Hassan, 2015), Conditional value (Raza, Siddiquei, Ahmed, Awan & Hayat 2012), and Destination image (Haque & Khan ,2013) in association with customer satisfaction and retention or intention to repurchase. The conceptual Framework is illustrated below.

Independent Variables

Figure 1- Conceptual Framework of Customer Perceived Value and its influences on satisfaction and revisit

EMOTIONAL VALUE

TOURIST SATISFACTION

TOU

RIS

TS IN

TEN

TIO

N

TO R

EVIS

IT

DEPENDANT VARIABLE

FUNCTIONAL VALUE

SOCIAL VALUE

CONDITIONAL VALUE

EPISTEMIC VALUE

DEPENDANT VARIABLE

CPV

Source: Adopted from Seth et al, 1991 Functional value is defined as “the perceived utility acquired from an alternatives capacity for functional, utilitarian or physical performance” (Sheth, Newman & Gross, 1991). Quality, variety, reliability, comfort, safety, prices, accessibility, durability and many more are considered as functional value, though the principal attributes has been known as price, reliability and durability (Sheth, Newman & Gross, 1991). Price plays a major functional role in tourism for middle markets (Ogonowska, 2011; Song, et al., 2010) while overall convenience in services (food, accommodation, recreations and relaxation) also play a major role in the main functions of a hotel (Chou, 2013; Aziz, et al,. 2011). Accessibility to destination and services creates a positive impact on purchase decision making behavior (Hussain, 2014; Sukiman, et al., 2013). As the tourists satisfaction also depends on the service quality provided to the tourist (Beqiri, et al., 2014; Al-Abaneh, 2013; Mosahab, et al., 2010; Khan, et al., 2013), which also helps the hotels to positively affect their Hotel Image by which tourists perception increases for revisit intention (Rajesh, 2013; Artuger, et al., 2013). The following hypotheses are formulated H1: There is significant and positive impact of FV on tourist satisfaction H2: There is significant and positive impact of FV on tourist revisit intention Emotional Value is the ability to evoke feelings and reorient to emotional stage while consumption (Sheth et al., 1991). Relaxation is one of the main motives the tourist wish to achieve during a travel to another destination for holidays (Ngoc & Trinh, 2015; Hassan & Shahnewaz, 2014; Al-Abaneh, 2013). The feeling of belongingness or feeling of being in the right place increases the satisfaction and also revisit intention (Yuksel, et al., 2010). Exciting experiences (Banki, et al., 2014) can please the tourists (Ragavan, et al., 2014; Toyama & Yamada, 2012), as it can create memories and can positively affect (Huang, et al., 2015; Asgari & Borzooei, 2013; Ballantyne, et al., 2011) tourist satisfaction and revisit intention. The following hypotheses are formulated H3: There is significant and positive impact of EV on tourist satisfaction H4: There is significant and positive impact of EV on tourist revisit intention Epistemic value is known as the perceived benefit and obtained from curiosity and natural need for the knowledge and innovation (Sheth et al., 1991). Epistemic value gives expected benefits during the consumption experience (Williams & Soutar, 2000) Experiences in new social environments, meeting new people, new food experience, new knowledge, learning culture and new discoveries good tourist motivators (Paggiaro, 2012) while adventure seeking such as taking risks and exploring out of safer boundaries gives personal satisfaction (Dolnicar & Kemp, 2008) for travellers who enjoy in different cultures learning and experiencing the world and finds pleasure from it (Getz, 2008). Different countries have different belief systems from which the travellers experience a different belief system and it changes from destination to destination (Peleckis, 2013; Caliskan, 2013; Cohen, et al., 2013), which gives the travellers a knowledge seeking experience (Park & Yoon, 2009). The following hypotheses are formulated H5: There is significant and positive impact of EPV on tourist satisfaction H6: There is significant and positive impact of EPV on tourist revisit intention Conditional value occurs when product’s utility depends on a particular situation or circumstances under which the product is purchased (Sheth et al., 1991). With a bundle of cost and functionality factors, honeymoon choice is made with cost effective and secluded exotic destinations (Lee, et al., 2010; Naidoo, et al., 2012). Often School holidays chosen to travel on sunny climatic regions due to geographic exploration with colder weather conditions at home (Schanzel & Yeoman, 2015). Sun sand and sea destinations are usually chosen for vacations due to wellness, exploration and relaxation where cultural and historical importance is less (Cameron & Gatewood, 2008; Dodds, 2007). The following hypotheses are formulated

H7: There is significant and positive impact of CV on tourist satisfaction H8: There is significant and positive impact of CV on tourist revisit intention Social value is known to be the perceived utility associated with consumer’s geographic, demographic, socioeconomic, political and cultural dimensions in recognition with product attributes in social groups where the consumer belongs (Sheth et al., 1991). Visiting socially recommended destinations through media or friends are a usual practice in assuming to obtain satisfaction through assurance of satisfaction (Miguens, et al., 2008)Famous locations and destinations create a higher image and respected among people (Mahika, 2011) Social Relationships being a motivating factor for travelers, it creates satisfaction and revisit intention (Vuuren & Slabbert, 2011). The following hypotheses are formulated H9: There is significant and positive impact of SV on tourist satisfaction H10: There is significant and positive impact of SV on tourist revisit intention Tourist satisfaction is most important factor for competitive business in the tourism due to influence of the destination choice and consumption of products and services (Naidoo, 2010), and has been widely researched and conceptualized (Weiler & Black, 2014). Satisfaction through destination, place or Island is an outcome of many characteristics where they evaluate the overall pleasure in being there (Salleh, et al., 2013). People who live in a community and the way they interact would positively or negatively influence tourist satisfaction ( Rajesh, 2013). Revisit intention in tourism industry has been regarded as an essential factor for growth and business survival (Pratminingsih, Rudatin & Rimenta, 2014; Ngoc & Trinh, 2015), most of the studies had shown that destination Image and satisfaction are Influential variables (Beerli & Martin, 2004; Trauer & Ryan, 2005; Chen & Tsai, 2007) that affect behavioral intention (George & George, 2004). The following hypotheses are formulated H11: There is significant and positive impact of tourist satisfaction on revisit intention 3. Research Design and Methods To examine the hypotheses, tourists from 10 most popular guest houses in Maafushi, Maldives were being selected. The popularity is based on the number of tourist visited the guest houses from September 2015 to March 2016. The other factors that were used to select the guesthouses includes the following criteria: (1) Number of years in the market, (2) Occupancy rate over the years, (3) provide the consent letter to access to tourists and finally (3) capacity of the guesthouse The sample The population of interest for this study is all adult tourist. The tourists are selected within the target population who met the following criteria.

(1) Ages above 20 to 40 years or above 40 years (2) Earns a minimum income of USD 1000 per month (3) Willing to participate the survey without any pressure (4) Willing to sign the consent form that the data can be used for publication

A convenient sampling technique is used to select the participants since it is difficult and time consuming to select the participant using other methods such as random probability sampling as it is difficult to determine the actual background of the tourist who stays in the guesthouses. Also the records are not kept up-to-date.

The sample of 203 tourists, where 48.28% were Male and 51.72% were Female. The percentage of the age of male and female tourists are 3.94% who are 20 years, 40.39% who are between the ages 21-30 years, 32.02% who are between the ages 31-40 years, 23.65% who are above 41 years. Almost 90% of the tourists participated in the survey are aged between 21 to 30 years who tend to travel more often than people who are above 30 years of age. Most of these tourists are from Asian countries comprises of 39.9% while tourists from Europe composite with 32.51%, North American tourists is 11.82%, tourists from Africa is 9.36% , South American background tourists is 4.43% and tourists from Oceania is 1.97%. The 5 categories of income range analysed in the survey showed that European and Asian tourist travelled most that has a monthly income in between 1000 - 2000 USD and the overall percentage was 31.03%. The second most travelled category is whose monthly income range is between 2000 – 4000 USD where 29.56% of these tourists are from European and Asian countries. The income range of 4000 – 6000 USD per month among all categories is 12.32% and the income range of 6000 above USD is 9.85%. The lowest income range category shows a much interest in travelling to Maafushi/Maldives compared to the highest earners who are above 6000 USD. The percentage stands at 17.24% among all the income categories. Tourists who are married contributed 52.71% on individual basis. 27.59% participated tourists are married men, 25.12% are married women, 21.67% attributed to single women, 18.23% of single men, 2.46% of divorced women, 2.46% of female who identified as other and 2.46% of male who identified as other. Measures Table 2 lists all of the construct definitions of the instruments and the related literature. The items are modified where necessary to make it more suitable to the research context. Initial Items were presented to various relevant groups and minor modifications were made to ensure reliability and validity. Several items were removed during the process based on the factor loading where the values are lower than 0.5 (Hair et al, 2009) and based on the feedback from the pretesting subjects. These items are accessibility (functional value-item3), excitement (emotional value-item 3), celebrity status and recommendation (social values-items 2 and 3) and honeymoon(conditional values-item 1). All these items has a score of loading which are less than 0.5. All scales utilizes a five –point Likert scale where 1 was “strongly disagree” and 5 was “strongly agree”.. The higher score indicated the that the value is more likely associated with the tourism and les score means a particular value is not much associated with the guesthouse from tourists perspectives.

Table 2: Measures of Construct VALUE

DIMENSIONS

MEASURES SOURCE

FUNCTIONAL

VALUE

PRICE Ogonowska,( 2011)

CONVENIENCE Chou (2013)

ACCESSIBILITY Hussain (2014)

SERVICE QUALITY Beqiri, et al. (2014)

HOTEL IMAGE Rajesh (2013)

EMOTIONAL

VALUE

RELAXATION Ngoc & Trinh, (2015)

BELONGINGNESS Yuksel, et al. (2010)

EXCITEMENT Banki, et al., (2014)

MEMORIES Huang, et al., (2015);

PLEASED Ragavan, et al., (2014)

SOCIAL VALUE

SELF IMAGE Chon (1992)

CELEBRITY STATUS Lee, et al., (2008).

RECOMMENDED Miguens, et al., (2008)

RESPECTED Mahika, (2011)

RELATIONSHIPS Vuuren & Slabbert, (2011)

CONDITIONAL

HONEYMOON Naidoo, et al.,( 2012)

SCHOOL HOLIDAYS Schanzel & Yeoman, (2015)

CLIMATE Cameron & Gatewood,

VALUE (2008)

LOCAL EXPERIENCE Li, (2014)

SUN, SAND & SEA Prayag, 2009)

EPISTEMIC

VALUE

NEW EXPERIENCE Mansion & Paggiaro(2012)

ADVENTURE Dolnicar & Kemp,( 2008)

LEARN CUTURE Getz, (2008)

DIFFERENT BELIEF

SYSTEM

Cohen, et al., (2013)

NEW KNOWLEDGE Park & Yoon,( 2009)

SATISFACTION

ISLAND (destination) Ramkissiin & Mavondo,

(2015)

LOCALS Sunmali, (2014)

GUEST HOUSE

SERVICES

Angelova & Zekiri, (2011)

EMPLOYEES

PERFORMANCE

Salleh, et al., (2013)

NATURE Denys & Mendes, (2014)

REVISIT

INTENTION Ngoc & Trinh, (2015)

PLAN

(schedule/booking)

Som & Badarneh, (2011)

RECOMMEND Luo & Hsieh, (2013)

GROUPING (Alliance) Lee,( 2014)

ATTACHMENT George & George, (2004)

Statistical Analysis The conceptual framework shown in Figure 1 was analysed primarily using SEM, supported by AMOS22 software. Many researchers have proposed a hypothesis or causal research via two stage model-building processes for applying SEM (Hoyle, 1995; Hair et al., 1998). In stage 1 Confirmatory factor analysis (CFA) was used to examine the reliability and validity of the measurement model, and the SME model was analysed to test causal relation between independent variables and dependent variables as shown in Figure 1 4. Results and Analysis Measurement Model To assess the measurement model, two analyses were carried out. The main reason for conducting this analysis is to confirm the latent variables really reflect the intended measures in the instrument. Second the squared correlation was examined to measure each indicator and to examine whether each item measures a construct (Holmes-Smith, 2001; Hair et al., 2009). The first analysis shows that most of the items in the construct loaded more than 0.5 which shows a good reliability of the model (Holmes-Smith, 2001). Those factors which loaded less than 0.50 (EV3, SV2, SV3, CV1 and FV3) has been removed as per the rule of thumb of CFA construct validity (Hair et al., 2009).

Figure 2: First run measurement model of latent variables (Modified)

The measurement model was first assessed by CFA. Previous research has noted that the normed (the ratio between and the degree of freedom) provides direct statistical evidence for the test of comparative fit index (CFI) and root mean-square error of approximation (RMSEA) are commonly analysed to evaluate the model fitness (Jackson & Gillaspy, 2009). The observed normed for this model was 1.926 ( =739.44, df=384) smaller than the three(3) recommended by Bagozzi and Yi (1988). Other fit indexes also show good fit for the measurement model. The CFI is 0.841, less than the 0.9 recommended (Joreskog and Sorbom, 1996) and which is acceptable as its very close to 0.9 (Bagozzi and Yi, 1988). Finally, the root mean square error of approximation (RMSEA) is 0.068 is below the recommended threshold of 0.08 meaning it’s a good fit (Hooper, et al., 2008). In sum, the measurement model exhibited a fairly good fit with the data collected. The measurement model was further assessed for construct reliability and divergent validity. The table 3 below shows that each element under each constructs satisfy the model. Also in terms of reliability of construct. The reliability of CPV and its influence on customer satisfaction and revisit construct’s, the reliability (Cronbach Alpha) of the models loading (below tables) shows that all loadings are above 0.50 with SAT (satisfaction), REVISIT (revisit), FV (Functional Value), EV (Emotional Value) and EPV (Epistemic Value) are above 0.70 while SV (Social Value) and CV (Conditional Value) loadings show above 0.68, which is closer to 0.70 (recommended threshold) showing the dependability within the construct is strong (Hair et al., 2009; Ugulu, 2013) justifying the model acceptance.

Table 3: Summary of the measurement scale

SAT REVISIT SV FV EV EPV CV

SAT1 .682

SAT2 .761

SAT3 .591

SAT4 .656

7

SAT5 .530

REVISIT1 .748

REVISIT2 .516

REVISIT3 .609

REVISIT4 .722

REVISIT5 .708

SV5 .735

SV4 .679

SV1 .519

FV1 .847

FV2 .598

FV4 .620

FV5 .554

EV5 .719

EV4 .589

EV2 .731

EV1 .608

EPV5 .558

EPV4 .529

EPV3 .653

EPV2 .536

EPV1 .618

CV4 .683

CV3 .589

CV2 .562

CV5 .518

Reliability (α) 0.78 0.79 0.68 0.75 0.75 0.72 0.68

Average

variance (%)

53.48 40.59 43.14 56.14 65.22 54.54 51.37

Additionally, from Table 4, correlation between constructs ranged from 0.359 to 0.815, with the correlations of no pair of measures exceeding the criterion of 0.9 and above (Hair et al., 1998). Empirical support thus exists for the discriminant validity of the measures.

Table 4: Constructs Correlation SAT REVISIT SV FV EV EPV CV

SAT 1

REVISIT 0.756 1

SV 0.557 0.739 1

FV 0.803 0.469 0.359 1

EV 0.813 0.559 0.506 0.681 1

EPV 0.738 0.694 0.779 0.588 0.781 1

CV 0.729 0.717 0.732 0.596 0.610 0.815 1

Structural Modelling The hypothesized research model was tested using the structural model. The overall fit statistics suggest that the model has adequate model fit ( =739.44, df=384; normed =1.926, CFI=0.841, RMSEA=0.068). All the model fitness indexes exceed the recommended acceptance level indicating that the displayed fitted the data well.

Figure 3: Structural Model: CPV influence on Satisfaction and Revisit intention

Another way to confirm the model fitness is to compare the loading of the Measurement Model and Structural Model along with model fitness indexes (Hair, et al., 2010). The statistical significance of all the structural parameter estimates was examined to determine the validity of the hypothesized paths. According to the standard rule, the parameter estimates should show a very similar resemblance in the both models (Hair, et al., 2010). The above Table 5 suggest that both model are quite well fitted to the data. Alternatively assuring the validity of the structural model is to compare the measurement models factor loadings with the measurement models factor loadings to assess the close relationship by similarity of both models factor loadings (Hair, et al., 2010). The below Table 6 shows the factor loadings of measurement model and structural model are all above 0.50 and shows that the resemblance is 100% between both models. This indicates that the model is valid and a good fit model.

Table 5: Comparison of model fitness indexes

Df Normed CFI RMSEA P- value

Measurement

Model

739.440 384 1,926 0.841 0.068 0.000

Structural

Model

739.44 384 1.926 0.841 0.068 0.000

Table 6: Comparison of factor loadings

Construct Measurement Model Structural Model

SAT1 SAT .682 .682

SAT2 SAT .761 .761

SAT3 SAT .591 .591

SAT4 SAT .656 .656

SAT5 SAT .530 .530

REVISIT1 REVISIT .748 .748





SV5 SV .735 .735

SV4 SV .679 .679

SV1 SV .519 .519

FV1 FV .847 .847

FV2 FV .598 .598

FV4 FV .620 .620

FV5 FV .554 .554

EV5 EV .719 .719

EV4 EV .589 .589

EV2 EV .731 .731

EV1 EV .608 .608

EPV5 EPV .558 .558

EPV4 EPV .529 .529

EPV3 EPV .653 .653

EPV2 EPV .536 .536

EPV1 EPV .618 .618

CV4 CV .683 .683

CV3 CV .589 .589

CV2 CV .562 .562

CV5 CV .518 .518

The statistical significance of all the structural parameter estimates was examined to determine the validity of the hypothesized paths. Table 7 lists the structural parameter estimates and the hypothesis testing results. This study examines the relationships between the dimensions of CPV associated with Guesthouses (tourism) and tourist satisfaction and revisit intention mediated by overall tourist satisfaction in the tourism sector in Guesthouse context.

Table 7: Results of estimation structural model

The analytical results showed that Functional value (FV) and Emotional value (EV)of CPV positively affects tourist satisfaction respectively (β=0.389, p<0.000; β=0.429, p<0.018) providing support for H2 and H3. Moreover, Social value (SV) and Tourist satisfaction (SAT) is significant and positively affects Tourist revisit intention (REVISIT) respectively (β=0.400, p<0.046; β=0.860, p<0.003) supporting H6 and H11. All other hypotheses were rejected since the P-value is greater than 0.005 for all β-coefficients. Mediating Effects on Revisit Intention

Table 8- Mediating effect for Revisit intention

Structural Β-

Coefficient S.E. C.R. P

Direct Effect REVISIT <--- SV 0.500 0.210 2.398 0.016

REVISIT <--- SAT 0.565 0.099 6.218 ***

Indirect Effect REVISIT <--- SV 0.400 0.225 1.999 0.046

REVISIT <--- SAT 0.860 0.368 2.938 0.003

Dependent Variable

Hypotheses Structural β- Coefficients

S.E. C.R. P Decision

SAT H1 SV 0.102 0.145 .631 0.528 Rejected

SAT H2 FV 0.389 0.105 3.303 *** Accepted

SAT H3 EV 0.429 0.200 2.373 0.018 Accepted

SAT H4 EPV -0.107 0.374 -0.367 0.713 Rejected

SAT H5 CV 0.248 0.182 1.308 0.191 Rejected

REVISIT H6 SV 0.400 0.225 1.999 0.046 Accepted

REVISIT H7 FV -0.274 0.190 -1.621 0.105 Rejected

REVISIT H8 EV -0.211 0.349 -0.838 0.402 Rejected

REVISIT H9 EPV 0.000 0.542 0.001 0.999 Rejected

REVISIT H10 CV 0.090 0.283 0.383 0.702 Rejected

REVISIT H11 SAT 0.860 0.368 2.938 0.003 Accepted

Since the mediator is Tourist Satisfaction (SAT) on REVISIT, the β-Coefficient has changed along with the Significant P-values in comparison with direct influence and indirect influences of SAT on REVISIT respectively (β=0.565, p<0.000; β=0.860, P<0.003) indicating that SAT is a mediator and supports the path diagram shows in Figure 1. Also Social value which is only CPV that is significant and has a positive impact on REVISIT can be considered as mediator since the β-Coefficient and P-value has change under direct and indirect conditions. 5. Discussion and Conclusion This study adds to the recognition of consumption values on the influence of CPV of tourist satisfaction and revisit intention. The main purpose of this research is to examine the CPV associated with Guest Houses and its effects on satisfaction and revisit intention. First the this study found that Social Value does not have an impact on Satisfaction. However, Social values such as ‘’Relationships’’ (Vuuren & Slabbert, 2011) is the most important factor, “Respected” (Mahika, 2011) is the second most important and “Self-image” (Chon, 1992) is the least important factor of the social value dimension. As suggested by Vuuren and Slabbert (2011) relationship increases the perceived value associated with tourism as it improves self-image among the colleagues (Chon, 1992) resulting respect from friends for travelling unique or highly valued places. Also Social Value has a strong association with epistemic value. The finding indicated that Social value influences tourists Revisit Intention. This finding is similar to many previous studies (Vuuren & Slabbert, 2011). However our finding indicated that Social value do not have a significant influence on Tourist satisfaction. This is contrary to many past findings such as (Mahika, 2011; Chon, 1992). As discussed in the literature review, the revisit intention mostly arises when there is satisfaction. However Social value is proven to be mediator which is directly and indirectly affects revisit intention. Second, “Price” is the most important Functional value which is highly important for tourists who participated in this study. “Convenience” and “Service Quality” and “Hotel Image” are most important Functional values for the tourists” respectively (Chou, 2013; Beqiri, et al., 2014; Rajesh, 2013). The mentioned factors have a strong relation with Emotional value. Also Functional values was found to have strong and significantly positive influence on Tourist satisfaction. This is similar to many previous research on the similar field such as Beqiri, et al., (2014), Al-Abaneh (2013), and Khan, et al. (2013). However the findings suggested that Functional value do not have any significant impact on Tourist REVISIT intention. This is again contradicts with previous studies (Jamal, et al., 2011; Denys & Mendes, 2014; Phau, et al., 2014). Third, “Belongingness” and “Pleasure” of Emotional values has the most influence on tourists while “Relaxation” is moderately important (Yuksel, et al., 2010; Toyama & Yamada, 2012; Ngoc & Trinh, 2015). “Memories” are least important Emotional value for those tourists participated in this study. Emotional values are highly correlated with Epistemic values suggesting overall journey ‘’ah-ha’’ moments may not have existed alone but combination of Emotional and Epistemic values. Emotional values were found to have a positive and significant influence on Tourist satisfaction. This is similar to the previous studies (Toyama & Yamada, 2012; Ngoc & Trinh, 2015). Also The feeling of belongingness or feeling of being in the right place increases the satisfaction and also revisit intention (Pizam, et al., 1979; Selin& Myers, 1998; Yuksel, et al., 2010). However we found that there is no significant influence of Emotional value on REVISIT intentions. Fourth “New Experience”, “Adventure”, “Learn Culture”, “Different belief System” and “New Knowledge” of Epistemic values are found to be less important to tourists. Food is one more tourist motivator according to recent studies (Jang & Cai, 2002), although in this study it was found that “Food” do not play a critical role to increased the CPV associated with tourism. We found Epistemic values has no significant influence on both Tourist satisfaction and intention to REVISIT. However as discussed in literature, Epistemic values are very important to satisfy and

encourages to revisit. In past literature it was found that adventure seeking behaviour such as risk taking and exploring out of safer boundaries gives personal satisfaction (Sibthorp, et al., 2007; Dolnicar & Kemp, 2008) and for travelers who enjoy in different cultures learning and experiencing the world and finds pleasure from it (Litvin, et al., 2004; Getz, 2008). The difference in finding could be that the past research are carried out among luxury hotels and Yachts and tourists who stay in Guesthouses could be different. This requires further investigation. Also we found no significant influence of Conditional values on both tourist satisfaction and REVIST intention. Last , satisfaction is was found to have profoundly significant and positive influence on REVISIT intention. Luo & Hsieh (2013), constructed and researched the tourist revisit intention behavior which had four dimensions which were “features”, “impression”, “services” and “Scenery and culture”. While Revisit intention in tourism industry has been regarded as an essential factor for growth and business survival (Pratminingsih, Rudatin & Rimenta, 2014; Ngoc & Trinh, 2015), most of the studies had shown that destination Image and satisfaction are Influential variables (Beerli & Martin, 2004; Trauer & Ryan, 2005; Chen & Tsai, 2007) that affect REVISIT intention. Conclusion: Out of 11 hypotheses, 4 were accepted, and 7 were rejected. However we concluded that improving functional and emotional values will causes to increases customer satisfaction. Also we concluded by improving Tourist satisfaction will causes to increase tourists retention or revisit intension. Social values will increase the Tourist intention to return or revisit. Therefore it Guesthouses , particularly in Maafushi Maldives, should emphasis on improving Functional values such as price, convenience, quality and image of the Guesthouse to increase the tourist satisfaction. These functional values are also important as it has a direct correlation with emotional values such as belongingness, relaxation, and memory. Therefore Guesthouses and firms in tourism sector should try to create more emotional values through functional values as it increase satisfaction in turn it increases intention to revisit. Further Research Direction: Since the study is focused to just one island and it cannot judge the customer perceived value of tourism in different areas or the whole sub-sector, it is necessary to research in different islands in different atolls with more samples to explore the tourist perceived value of guesthouse tourism in local islands of Maldives associated with satisfaction and revisit intention. This study should be repeated in other sector of tourism such as resorts and Yachts to confirm the model reliability and validity as a whole and to generalise the findings. Reference Artuğer, S., Çetinsöz, B. C., & Kiliç, I. (2013). The effect of destination image on destination loyalty: An application in Alanya. European Journal of Business and Management, 5(13), 124-136. Hooper, D., Coughlan, J., & Mullen, M. (2008). Structural equation modelling: Guidelines for determining model fit. Articles, 2. World Travel and Tourism Council, 2015. Travel and Tourism: Economic Impact 2015 Maldives,

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