Keywords

Service Innovativeness, Commitment, Trust, Behavioral Intention, Affective Intention, Popularity of A Tourist Destination.

Introduction

Tourism is considered as a lucrative sector which contributes around 9.2% to the Indian GDP (WTTC). Tourism has attracted researchers to contribute research in various fields (Cibinskiene, 2012; McKercher, 2016; Panfiluk, 2015; Santos et al., 2016; Jurdana & Frleta, 2017; Montenegro, 2017; Tanford & Jung, 2017; Tiew et al., 2015; Yu¨ru¨k et al., 2017). There is stiff competition among the tourist destinations to attract tourists and hence is a strategic sector of the economy (Abreu et al., 2018; Island & Higgins, 2018; Kelly & Fairley, 2018; Teixeira & Ferreira, 2018). Highlighting a locations distinct features and service distinctions help create a competitive edge and needs more relevant scientific research (Cibinskiene, 2012). The success of a destination is dependent on the overall experience a tourist experiences during the visit to the location. The thrill, excitement, the supporting infrastructure, supporting services all add to the overall experience encountered. Maintaining, innovating and upgrading the services as per the customer requirement is crucial for sustaining the competition (Anderson & Zeithamal, 1984; Babakus & Boller, 1992; Garvin, 1983).

Service innovation and quality improvement helps in increasing the customer satisfaction (Kumar et al., 2008) which helps in building trust and influences the purchase decision (Oliver, 1980; Gremler et al., 2001). Tourists are attracted to a location due to the popularity of a location. The popularity of a location builds up with the experiences the tourists gets visiting the location. The ecosystem surrounding the location viz., quality of services of the enterprises, support systems, infrastructure, efficient supply chain and the natural environment available all adds to making a location famous.

Studies on customer motivation, satisfaction and competitiveness of a tourist destination has been limited to the tourist’s perception about the destination (Enright & Newton, 2004; Chen et al., 2016; Cracolici et al., 2008). There are a few studies conducted on the tourist satisfaction with regional competition (Chen et al., 2016). Some studies are found on organizational quality and satisfaction (Gong & Tung, 2016; Jurdana & Frleta, 2017; Lee et al., 2017; Montenegro, 2017; Oom et al., 2012; Okayasu et al., 2016; Santos et al., 2016; Yu¨ru¨k et al., 2017). There is still a gap in understanding customer satisfaction, its attributes and competition related to tourism (Pansiri, 2014). There is a need to study the relationship between of trust and affective and behavioral intention of consumers. Moreover, understanding the affective intention and behavioral intention of customer will tell us about the customer intention in choosing a destination.

The researcher in this paper tries to find out the factors which has an influence on increasing the popularity of a tourist destination. Service innovation and commitment increases the trust of the customer and trust in fact influences the affective and behavioral intention of the customer. Positive behavioral intention and affective intention will increase the popularity of a tourist location.

Literature Review

Tourism business usually depends on the flow of tourists to a location. People usually wish to travel to locations which are very popular. A tourist destination is an aggregation of products and services and public goods made available to tourists providing an overall integrated experience of the location (Buhalis, 2000; Harris & Leiper, 1995). Tourists travelling to destination experiences the services available in the location and holds positive or negative opinions. A destination is a place interpreted by the consumer’s purpose of the journey and past experience (Davison & Maitland, 1997; Hall, 2000). The consumer interprets the experience based on the travel purpose, schedule and past exposure (Fuchs & Weiermair, 2003). A good experience helps increase the popularity of the destination. A tourist location comprises of several stakeholders like the customers, firms, entities, public sector, the local population and NGOs (Buhalis, 2000). There is lot of conflict amongst the stakeholders in a tourist location (Sheehan et al., 2007) and a tourist destination are considered the most difficult entities to manage and operate (Sautter & Leisen, 1999). The choice of a tourist destination and decision to visit the destination again is dependent on the tourist satisfaction (Yoon & Uysal, 2005). Enhancing the level of customer satisfaction should be one of the priorities of the stakeholders (Morgan & Pritchard, 1998; Pearce, 1997; Seaton, 1997). Proper strategies increasing that locations attractiveness and competitive positioning (Álvarez et al., 2009) will help increase the traffic to the location.

Understanding the factors influencing satisfaction and increasing popularity is of utmost importance (Fuchs & Weiermair, 2003). There is a necessity for benchmarking customer satisfaction (Gomezelj & Mihalic, 2008) at a destination. Popularity of a location is dependent on several factors several factors such as service innovativeness, commitment, trust, behavioral intention and affective intention.

Service Innovativeness

Introducing something new to customers is service innovativeness (Barcet, 2010). The new innovation in services produce high service and value perceptions in customers (Hollebeek et al., 2018; Ordanini & Parasuraman, 2011). Service innovativeness helps firms in introducing innovation in the services provided thus developing competitive edge and superior customer services (Chen et al., 2018). Service innovations in terms of internet-based services from Trip Advisor, Airbnb, MakeMy Trip are enhancing the experiences provided to the customers (Snyder et al., 2016). Innovation drives economic growth both at the micro and macro levels (Gomezelj, 2016). Innovativeness drives growth through increased operational efficiency and value enhancement thereby increasing customer experience and loyalty leading to acquisition of new customers (Walls et al., 2011).

Studies were conducted on service innovativeness in the destination level (Stamboulis & Skayannis, 2003; Gomezelj, 2016), hotel and transportation area (Tsai, 2017), effects on consumer behaviour, satisfaction and loyalty (Hollebeek & Rather, 2019). There is a need to understand the role of customer co-creation, satisfaction, behavioral and affective intention and loyalty in tourism (Buonincontri et al., 2017, Divisekera & Nguyen, 2018; Kim et al., 2018).

There is a difference between service innovation and service innovativeness (Kim et al., 2018). Service innovation is new offering to the firm’s customers (Ordanini & Parasuraman, 2011). Service innovation denotes innovative organizations (Deshpandé et al., 1993) which has a favorable impact on its performance (Hwang et al., 2019). Service innovativeness is the firm’s capability to develop new services or ideas for its customers (Kim et al., 2018; Tajeddini et al., 2018). Service innovativeness is a relative advantage through newness in services (Leckie et al., 2018). Changes in the organization competences levels bring innovation (Menor & Roth, 2007).

Service innovativeness can be viewed form the angles of assimilation approach, demarcation approach and synthesis approaches (Coombs & Miles, 2000). Assimilation approach is a product innovation approach which focus on introduction of new technology (Hollebeek & Rather, 2019). Innovativeness in assimilation approach is seen from the perspective of goods dominant logic (Gallouj & Savona, 2009). There are inherent similarities in goods based and service based contexts (Nijssen et al., 2006). The demarcation approach holds good in services due to its distinctive characteristics of intangibility, variability, inseparability and perishability (Sundbo et al., 2007). This necessitates innovativeness in service integration (Hollebeek & Rather, 2019). The synthesis approach states that innovation posits novel aspects (Gallouj & Savona, 2009; Hsieh et al., 2013). Innovation proliferates by interlinking of the important aspects throwing light to gauge new opportunities (Gallouj & Weinstein, 1997). Innovation is the novel configuration of resources resulting in new service offerings benefiting stakeholders (Chen et al., 2018).

Service innovativeness brings in new services and builds trust in customers. Existing research also shows the impact of service innovativeness on customer involvement, trust, knowledge sharing, collaboration and motivation (Sarmah et al., 2017; Roberts et al., 2013). Base on the discussion the following hypothesis is proposed.

H1: Service Innovativeness has a positive influence on Trust

Commitment

Consumer usually compare their preconceived expectations with the experiences post-delivery. They are delighted if they get more than their expectations, mere satisfaction if the expectations are fulfilled and dissatisfaction if the expectations are not met (Hollebeek & Rather, 2019). There are several researches conducted in the area of commitment in relationship development (Morgan & Hunt, 1994; Gruen et al., 2000) and influence on consumer behavior (Sharma & Patterson, 2000; Verhoef et al., 2002; Bansal et al., 2004). Commitment is a firm inclination towards behavior of resisting any change (Fullerton, 2005; Gilliland & Bello, 2002). Commitment is the affective outcome of understanding the goals, objectives and values of parties in the exchange of relationship (Allen & Meyer, 1990). A firm’s commitment with the other firm indicates the expected relationship in future (Morgan & Hunt, 1994). The firm develops confidence in the stability of future relationship and stays committed to the relationship (Kumar et al., 1995). Commitment is a future status to conform to development and maintenance of a stable relationship (Wilson, 1995). Commitment strengthens the relationship (Liljander & Roos, 2002; Selnes, 1998). Trust and commitment are the foundation to relationship marketing (Bove & Robertson, 2005; Liljander & Roos, 2002; Spekman et al., 2000). Commitment is also an indication for long term stability of the relationship (Anderson & Weitz, 1992).

Commitment increases with the level of trust among partners (Bansal et al., 2004; Crotts & Turner, 1999; Garbarino & Johnson, 1999; Kwon & Suh, 2005; Morgan & Hunt, 1994; Sharma & Patterson, 2000). Consumers commitment is limited to the services they receive (Kandampully, 1997). Organizational commitment refers to the level of interest in its consumers and the effort taken in maintaining brand loyalty in terms of catering to the needs, communication, and services it provides (Álvarez et al., 2009). The consumer will trust the service provider more if she perceives that the firm is more committed towards the service delivery (Bansal et al., 2004; Sharma & Patterson, 2000). Based on the discussion the following hypothesis is proposed.

H2: Commitment has a positive influence on trust

Trust

Customer acquisition costs more (Blattberg & Deighton, 1991; Filiatrault & Lapierre, 1997). Trust helps in increasing profits between 20 to 85 percent (Álvarez et al., 2009) as it helps in developing relationship between the firm and the customer. Trust is the foundation of human interaction or exchange activity (Moorman et al., 1992). Trust is the integrity and reliability between partners (Morgan & Hunt, 1994). This is the reason firms should concentrate on the whole lifecycle rather than onetime transaction (Reichheld, 1996). Increasing successful transactions help the development of relationship over a period of time (Ravald & Grönroos, 1996).

Trust is a combination of cognition and behavior in terms of intentions, motivations, honesty and benevolence (Álvarez et al., 2009). Trust is measured empirically in terms of credibility and benevolence (Bove & Robertson, 2005; Morgan & Hunt, 1994; White, 2005).

Trust builds confidence in customers which leads to advocacy and customer recommendation or positive word-of-mouth and leads to repurchase (Reinartz et al., 2005; Sivadas & Baker-Prewitt, 2000). Positive word-of-mouth is a strong influencer in the buying process (Money, 2000) which is based on the past experience of the customer. Trust leads to building of customer loyalty and leads to a favorable attitude and repeat purchase towards a brand (Dick & Basu’s, 1994; East et al., 2005).

Trust is an important factor in developing positive relationship in tourism (Bejou & Palmer, 1998; Crotts et al., 1999; Kang et al., 2005; Ross, 2004). Trust helps in developing positive affective intention and also positive behavioral intention. Based on the discussion the following hypotheses are proposed.

H3: Trust has a positive influence on Behavioral Intention

H4: Trust has a positive influence on Affective Intention

Behavioral Intent

Behavioral measures are generally used for measurement of customer loyalty (Dekimpe et al., 1997; Kau & Loh, 2006). Consumers are more prone to switching brands if loyalty doesn’t convert to a favorable attitude (Bloemer & Kasper, 1995; Maicas et al., 2006).

Trust helps build positive behavioral intention. Several studies present the positive relationship between customer satisfaction and behavioral intentions (Oliver, 1980, 1997; Reichheld & Sasser, 1990). There are positive relationships between perceived quality, satisfaction and behavioral intentions (Getty & Thompson, 1994). Customer satisfaction has a positive influence on customers’ behavioral intentions (Park et al., 2019) of revisiting or recommending the services (Heung & Gu, 2012). Behavioral loyalty intent refers to the customers desire to revisit the company and recommend it to others (Grissemann & Stokburger Sauer, 2012). Behavioral loyalty intent is the probability of the consumer to repurchase and inclination to further recommend the offering (Oliver, 1997; Hollebeek & Rather, 2019). Behavioral intentions are indications of a person’s future behavior (Fishbein & Ajzen, 1980). Behavioral intent provides an in-depth insight to the consumer behavior (Hollebeek et al., 2014).

Behavioral intent is essential for positive consumer purchase intent in tourism (Hollebeek and Rather, 2019). Thus positive behavioral intent helps in building loyalty thereby increasing the popularity of a location. Based on the discussion the following hypothesis is proposed.

H5: Behavioral Intention has a positive influence on Popularity

Affective Intention

Emotions are a central to the consumption experience and consumer reactions (Babin et al., 1998) which influence customer satisfaction (Oliver, 1993; Oliver & Westbrook, 1993). Favorable consumption experience leads to customer satisfaction (Babin & Griffin, 1998). Several research studies were conducted to understand the relationship of positive emotions and customer satisfaction (Lyubomirsky et al., 2005). Positive affect is directly related to customer satisfaction (Babin & Darden, 1996). The positive emotions while consuming a product or service help consumers decide on the satisfaction (Rust & Oliver, 1994). Positive emotions or affect influences satisfaction (Park et al., 2019) and increases satisfaction level (Clark & Isen, 1982). Positive affective intention thereby has a tendency to increase popularity of a location. Based on the discussion the following hypothesis is proposed.

H6: Affective Intention has a positive influence on Popularity

Based on the premises developed a conceptual framework is developed as depicted in Figure 1.

A primary survey was carried out to measure the responses of the customers. A questionnaire was developed to collect the responses of the respondents. The variables for measurement used were Service innovation, Commitment, Trust, Behavioral intention, Affective intention and popularity of a tourist destination.

A total of 1200 questionnaire were distributed, out of which only 1050 questionnaires contained fully filled data. There are 20 items in the measurement scale. If we consider 10 samples per variable the total sample required will be 200 (Hair et al., 2008). Also, we see that several researchers mentioned that the minimum sample size for testing a SEM is 100 to 200 (Hoogland & Boomsma, 1998; Boomsma & Hoogland, 2001; Kline, 2005). So, a sample size of 1050 will suffice for testing the proposed model.

The research design used is descriptive in nature. A primary survey was carried out to collect data from customers who liked to travel. The research was carried out using a structured questionnaire. The responses were measured on a 5 point scale. 1 being highly disagree to 5 being highly agree.

The survey was done in Guwahati in the State of Assam and Shillong in the State of Meghalaya in India. The sample size of the survey was 1050. Random sampling method adopted was used. The respondents were customers who loved to travel. They were asked to rate on their views about their favorite tourist destination.

Data Analysis and Interpretation

Data was analyzed using SPSS 22 and LISREL 9.2.

Gender

Out of 1050 respondents surveyed 56.2% were male respondents and 43.8% were female respondents.

Income

27.3% of the respondents have an annual household income of less than INR 5 LPA, 39.6% of the respondents have an annual household income INR 5 LPA to less than 10 LPA, 21.2% of the respondents have an annual household income of INR 10 LPA to less than 15 LPA, 8.4% of the respondents have an annual household income of INR 15 LPA to less than 20 LPA and 3.4% of the respondents have an annual household income of INR 20 LPA and above.

Confirmatory Factor analysis

A confirmatory factor analysis was done on the 20 items under the six identified constructs. The KMO test value is 0.868 whish shows sample is adequate. Bartlett’s test of Sphericity shows high significance which indicates that there is correlation among the variables and data is adequate for the analysis. 86.69% of the variance is explained by the 6 factors. The pattern matrix of the 20 items are shown in Table 1.

Table1: Pattern MatrixA
	Component
	1	2	3	4	5	6
SI1					0.754
SI2					0.995
SI3					0.904
COM1						0.779
COM2						0.687
COM3						0.774
TRUST1		0.888
TRUST2		0.902
TRUST3		0.815
TRUST4		0.939
BI1				0.828
BI2				0.763
BI3				0.950
AI1			0.859
AI2			0.901
AI3			0.968
POP1	0.914
POP2	0.773
POP3	0.978
POP4	0.856

Test of Validity and Reliability

The factor loadings from Table 1 were used to calculate the Average Variance Explained (AVE) and Composite Reliability (CR) as shown in Table 2. Cronbach’s alpha value is also determined as shown in Table 2. Table 3 shows the discriminant validity of the constructs.

Table 2: Test of Validity and Reliability
Construct	Codes	Statements	Factor Loading	AVE	Cronbach's alpha	CR
Service Innovation (Leckie et al., 2018)	SI1	This tourist location services are new	0.754	0.884	0.946	0.806
	SI2	This tourist location services are unique	0.995
	SI3	This tourist location services are different	0.904
Commitment (Álvarez et al., 2009)	COM1	This tourist location carries out the necessary changes in the performance of its duties to deal with me suitably	0.779	0.747	0.921	0.747
	COM2	I observe that the tourist location considers consumers to be the basic target to be satisfied in the performance of its activities	0.687
	COM3	I believe this tourist location makes an effort for me to feel like an important consumer	0.774
Trust (Doney & Cannon,1997; Morgan & Hunt, 1994; Price & Arnould, 1999; Sharma & Patterson, 2000)	TRUST1	The tourist location is prepared to consider all my requests and suggestions	0.888	0.886	0.942	0.847
	TRUST2	The tourist location has detailed knowledge about the tourism products and services available in the market	0.902
	TRUST3	This tourist location guides me suitably when I ask for its opinion about the best tourism service	0.815
	TRUST4	Overall, I consider the location a good provider of tourism services	0.939
Behavioral Intention (Grissemann & Stokburger Sauer, 2012)	BI1	I program my trips with this tourist location because it is the best alternative available	0.828	0.847	0.834	0.792
	BI2	I consider myself very loyal to this tourist location	0.763
	BI3	The next time I travel, I will go to this tourist location	0.950
Affective Intention (Garbarino & Johnson, 1999; Price & Arnould, 1999)	AI1	Overall, I am happy with the relationship I go from the tourist location	0.859	0.909	0.921	0.814
	AI2	Overall, I think the tourist location has done a good job	0.901
	AI3	Overall, I have obtained value from the relationship from the tourist location	0.968
Popularity of a tourist destination (Yoo et al., 2018)	POP1	I would prefer to use the services of a tourist location who meets my expectations	0.914	0.880	0.945	0.846
	POP2	I would prefer to use the services of a location which I was satisfied even if the prices rise due to peak demand	0.773
	POP3	I would prefer to use additional products and services of my preferred location	0.978
	POP4	I would recommend my preferred location to others	0.856

Table 3: Discriminant Validity of the Constructs (Fornell & Larcker Criterion)
	SI	COM	TRUST	BI	AI	POP
SI	0.940
COM	0.610	0.864
TRUST	0.660	0.562	0.941
BI	0.657	0.402	0.694	0.920
AI	0.600	0.566	0.564	0.479	0.954
POP	0.575	0.812	0.490	0.383	0.565	0.938

Table 2 provides factor loadings, Cronbach’s alpha measures, AVE and Composite Reliability values.

Reliability is measured using Cronbach’s alpha (Cronbach, 1951) and Composite reliability gives the internal consistency (Fornell & Larcker, 1981). AVE gives the measure of content validity (Fornell & Larcker, 1981)

Factor loadings of 0.5 and higher is good. CR above 0.7 is good. AVE of above 0.5 is good. From Table 2, Cronbach’s Alpha value of the overall reliability is 0.955, which shows that the data is highly reliable. Cronbach’s Alpha of all the individual constructs are 0.834 and above, which indicates that the data of the individual parameters are reliable. Composite reliability (CR) of the constructs are 0.747 and above which is shows internal consistency.

AVE scores are 0.747 and above for all the constructs which shows convergent validity. In Table 3, the diagonals are the square root of the AVE. Off-diagonals are the correlations of the latent constructs. The diagonals indicate the highest of any column or row. Also in the cross loading in Factor analysis, the items under each construct fall under the same factors. This complies with the discriminant validity requirements.

The measurement model thus meets the reliability requirements. There is also compliance for convergent and discriminant validity.

Path Analysis

The results of the structural equation model analysis of the proposed conceptual model is depicted in Figure 2.

Results of the structural model analysis from Figure 2 is shown in Table 4.

Table 4: Goodness of Fit Indices for Structural Model
Fit Indices	Accepted Value	Model Value
Absolute Fit Measures
χ2 (Chi-square)		4.14
Df		8
χ2 (Chi-square)/df	3	0.517
GFI (Goodness of Fit Index)	> 0.9	0.944
RMSEA (Root Mean Square Error of Approximation)	< 0.10	0.0001
Incremental Fit Measures
AGFI (Adjusted Goodness of Fit Index)	> 0.80	0.984
NFI (Normed Fit Index)	> 0.90	0.960
CFI (Comparative Fit Index)	> 0.90	1.000
IFI (Incremental Fit Index)	> 0.90	1.035
RFI (Relative Fit Index)	> 0.90	0.925
Parsimony Fit Measures
PGFI (Parsimony Goodness of Fit Index)	> 0.50	0.379
PNFI (Parsimony Normed Fit Index)	> 0.50	0.512

The test of the structural model was performed using SEM in order to examine the hypothesized conceptual framework Figure 1 by performing a simultaneous test. Table 4 depicts that the goodness-of-fit for the model was met: χ2 (Chi-square)/df=0.571, CFI=1.000, GFI = 0.944, AGFI=0.984 and NFI=0.960. The overall values provided evidence of a good model fit. All of the model-fit indices exceed the respective common acceptance levels, following the suggested cut-off value, demonstrating that the model exhibited a good fit with the data collected. Thus, it is possible to proceed to examine the path coefficients.

Properties of the causal paths for the structural model (standardized path coefficients (β), standard error, and hypotheses result) are signified in Table 5.

Results of Path Analysis

Table 5: Summary of Hypotheses Testing Results
Path	Estimate (β)	S.E.	p	Results
SI à TRUST	-0.058	0.122	0.634	Reject H1
COM à TRUST	1.156	0.186	0.00001	Accept H2
TRUST à BI	1.150	0.213	0.00001	Accept H3
TRUST à AI	1.067	0.253	0.00001	Accept H4
BI à POP	-1.501	0.618	0.015	Accept H5
AI à POP	2.426	0.377	0.0001	Accept H6

Discussion and Conclusion

The data analysis shows that service innovation does not have an influence on trust. There is saturation in most of the tourist segments (Avci et al., 2011; Grissemann & Stokburger-Sauer, 2012; FitzPatrick et al., 2013). New and innovated services need to be introduced to sustain the competition. Though several researches show that introduction of new services increases the satisfaction level (Hollebeek & Rather, 2019) of the tourists yet it seems consumers are not confident of new service innovations introduced to increase the efficiency of the services delivery. Service innovativeness influences customer advocacy (Hollebeek & Rather, 2019). It is necessary that the service providers of the locations focus on service innovation and make the visitors aware of such services to increase their trust and confidence.

Commitment has a positive influence on trust. Due to information available the tourists are well aware of facilities available in a location and hence becoming more demanding (Sanchez et al., 2006). Tourists are dependent on the service providers of a destination. The commitment from the service providers builds confidence on the tourists and hence builds up the trust.

Trust has a positive influence on the behavioral intention. Building trust is difficult but if the tourist trusts the service provider it helps in positive purchase intentions and building loyalty.

Trust has a positive influence on affective intention. When trust builds up the customer starts developing positive opinions and positive attitude towards the service providers and the location.

Behavioral intention has a positive influence on popularity of a tourist destination. Research shows that overall satisfaction is a better predictor of behavioral intentions as it is closely related to related specific attitudes which is likely to help in prediction of future behavior (Anderson et al., 1994). Overall satisfaction influences repurchase intentions (Anderson et al., 1994; Bitner, 1990; Oliver, 1997; Parasuraman et al., 1994) and brand loyalty. Positive behavioral intention increases customer loyalty by choosing to visit a location again and recommending it to others thereby increasing the popularity of a location.

Affective intention has a positive influence on popularity of a location. The digital media has increased the importance of brand advocacy (Roy, 2013) through more customer engagement and referrals. Consumer trusts more in brand advocacy through family and friends than advertising (Sasser et al., 2014). Customer advocacy drives customer choice knowledge and involvement (Lawer & Knox, 2006). Advocacy affect brand perceptions (Groeger et al., 2016), customer satisfaction and commitment over a period of interactions (Roy, 2013). Positive affect develops an inclination towards the location by spreading positive vibes and feelings towards the location making the location popular.

The conclusion is that commitment influences trust, trust influences behavioral intention and affective intention, behavioral intention and affective intention influences popularity of a tourist destination. From this we can infer that synchronizing and improving the services helps in building trust in tourists which helps in increasing the popularity of a tourist destination.

Limitations

The survey was limited to the cities of Guwahati and Shillong. The study can be extended to other parts of the county.

Bussiness Implications

Business thrives on the number of customers for the sale of products or services. Increasing popularity will increase the traffic flow to a tourist destination. This will not only help business to flourish but also upgrade the local economy. The stakeholders of a tourist destination need to devise proper strategies to build trust through innovation and synchronized service delivery to develop positive relationship with the visitors. This will go a long way to develop a liking for the location and enhance popularity of the location.

References

1. Abreu, N.M., Ruhanen, L. & Arcodia, C. (2018). Destination competitiveness: a phenomenographic study. Tourism Management, 64, 324-334.
2. Allen, N.J., & Meyer, J.P. (1990). The measurement of antecedents of affective, continuance and normative commitment on the organization. Journal of Occupational Psychology, 63 (1), 1-18.
3. Álvarez, L.S., Casielles, R.V. & Martín, A.M.D. (2009). The role of commitment perceived by the consumer in service industries. Management research, 7(2), 141.
4. Anderson, C.R., & Zeithaml, C.P. (1994). Stage of the product life cycle, business strategy, and business performance. Academy of Management journal, 27(1), 5-24.
5. Anderson, E., & Weitz, B. (1992). The use of pledges to build and sustain commitment in distribution channels. Journal of Marketing Research, 29(2), 18-34.
6. Avci, U., Madanoglu, M., & Okumus, F. (2011). Strategic orientation and performance of tourism firms: evidence from a developing country. Tourism Management, 32(1), 147-157.
7. Babakus, E., & Boller, G.W. (1992). An empirical assessment of the Servqual scale. Journal of Business Research, 24 (3), 253-268.
8. Babin, B.J. & Darden, W.R. (1996). Good and bad shopping vibes: spending and patronage satisfaction. Journal of Business Research, 35(3), 201-206.
9. Babin, B.J. & Griffin, M., (1998). The nature of satisfaction: an updated examination and analysis. Journal of Business Research, 41(2), 127-136.
10. Bansal, H.S., Irving, P.G., & Taylor, S.F. (2004). A three component model of customer commitment to service providers. Journal of the Academy of Marketing Science, 32(3), 234-250.
11. Bitner, M.J. (1990). Evaluating service encounters: the effects of physical surroundings and employee responses. Journal of Marketing, 54(2), 69-82.
12. Blattberg, R.C., & Deighton, J. (1991). Interactive marketing: Exploiting the age of addressability. Sloan Management Review, 3(1), 5-14.
13. Bloemer, J.M., & Kasper, H. (1995). The complex relationship between consumer satisfaction and brand loyalty. Journal of Economic Psychology, 16(2), 311-329.
14. Boomsma, A., & Hoogland, J.J. (2001). The robustness of LISREL modeling revisited. Structural equation models: Present and future. A Festschrift in honor of Karl Jöreskog, 2(3),139-168.
15. Bove, L.L., & Robertson, N.L. (2005). Exploring the role of relationship variables in predicting customer voice to a service worker. Journal of Retailing and Consumer Services, 12(2), 83-97.
16. Buhalis, D. (2000). eTourism: Information technology for strategic tourism management, Pearson education.
17. Buonincontri, P., Morvillo, A., Okumus, F., & Van Niekerk, M. (2018). Managing the experience co-creation process in tourism destinations: empirical findings from Naples. Tourism Management, 62, 264-277.
18. Chen, C.M., Chen, S.H., Lee, H.T. & Tsai, T.H. (2016). Exploring destination resources and competitiveness: a comparative analysis of tourists’ perceptions and satisfaction toward an island of Taiwan. Ocean & Coastal Management, 119, 58-67.
19. Cibinskiene, A. (2012). Impact evaluation of events as factors of city tourism competitiveness. Economics and Management, 17(4), 1333-1339.
20. Coombs, R. & Miles, I. (2000). Innovation, measurement and services: the new problematique, in Metcalfe, J.S. and Miles, I. (Eds), Innovation System in the Service Economy, Springer, 85-103.
21. Cracolici, M.F., Nijkamp, P., & Rietveld, P. (2008). Assessment of tourism competitiveness by analyzing destination efficiency. Tourism Economics, 14(2), 325-342.
22. Crotts, J.C., & Turner, G.B. (1999). Determinants of intra-firm trust in buyer–seller relationships in the international travel trade. International Journal of Contemporary Hospitality Management, 11(2/3), 116-123.
23. Dekimpe, M., Steenkamp, J.B., Mellen, M., & Abeele, P. (1997). Decline and variability in brand loyalty. International Journal of Research in Marketing, 14(5), 405-420.
24. Deshpandé, R., Farley, J., & Webster, F. (1993). Corporate culture, customer orientation, and innovativeness in Japanese firms: a quadrant analysis. Journal of Marketing, 57(1), 23-37.
25. Dick, A.S., & Basu, K. (1994). Customer loyalty: Toward an integrated conceptual framework. Journal of Academy of Marketing Science, 22(2), 99-109.
26. Divisekera, S., & Nguyen, V.K. (2018). Determinants of innovation in tourism evidence from Australia. Tourism Management, 67, 157-167.
27. East, R., Gendall, P., Hammond, K., & Lomax, W. (2005). Consumer loyalty: Singular, additive or interactive. Australasian Marketing Journal, 13(2), 10-26
28. Enright, M.J., & Newton, J. (2004). Tourism destination competitiveness: a quantitative approach. Tourism Management, 25(6), 777-788.
29. Filiatrault, P., & Lapierre, J. (1997). Managing business to business marketing relationships in consulting engineering firms. Industrial Marketing Management, 26(2), 213-222.
30. Fishbein, M., & Ajzen, I. (1980). Understanding attitudes and predicting social behavior.
31. Fitz Patrick, M., Davey, J., Muller, L., & Davey, H. (2013). Value-creating assets in tourism management: applying marketing's service-dominant logic in the hotel industry. Tourism Management, 36, 86-98.
32. Fornell, C. & Larcker, D.F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
33. Fuchs, M., & Weiermair, K. (2003). New perspectives of satisfaction research in tourism destinations. Tourism Review, 58(3), 6-14.
34. Gallouj, F., & Savona, M. (2009). Innovation in services: a review of the debate and a research agenda. Journal of Evolutionary Economics, 19(2), 149-172.
35. Garbarino, E., & Johnson, M.S. (1999). The different roles of satisfaction, trust and commitment in consumer relationships. Journal of Marketing, 63(April), 70-87.
36. Garvin, D. (1983). Quality on the Line-Reply. Harvard Business Review, 61(6), 240-240.
37. Getty, J.M., & Thompson, K.N. (1994). A procedure for scaling perceptions of lodging quality. Hospitality Research Journal, 18(2), 75-96.
38. Gilliland, D.I., & Bello, D.C. (2002). Two sides to attitudinal commitment: The effect of calculative and loyalty commitment on enforcement mechanisms in distribution channels. Journal of the Academy of Marketing Science, 30(1), 24-43.
39. Gomezelj, D.O., & Mihalič, T. (2008). Destination competitiveness - Applying different models, the case of Slovenia. Tourism Management, 29(2), 294-307.
40. Gomezelj, D. (2016). A systematic review of research on innovation in hospitality and tourism. International Journal of Contemporary Hospitality Management, 28(3), 516-558.
41. Gong, T., & Tung, V.W.S. (2016). The impact of tourism mini-movies on destination image: the influence of travel motivation and advertising disclosure. Journal of Travel and Tourism Marketing, 8408, 1-13.
42. Gremler, D.D., Gwinner, K.P., & Brown, S.W., (2001). Generating positive word-of-mouth communication through consumer-employee relationships. International Journal of Service Industry Management, 12(1), 44-59.
43. Grissemann, U., & Stokburger-Sauer, N. (2012). Customer co-creation of travel services: the role of company support and customer satisfaction with the co-creation performance. Tourism Management, 33(6), 1483-1492.
44. Groeger, L., Moroko, L. & Hollebeek, L. (2016). Capturing value from non-paying consumers’ engagement behaviours: field evidence and development of a theoretical model. Journal of Strategic Marketing, 24, Nos 3/4, 190-209.
45. Gruen, T.W., Summers, J.O., & Acito, F. (2000). Relationship marketing activities, commitment, and membership behaviors in professional associations. Journal of Marketing, 59(1), 34-49.
46. Hair, J.F., Celsi, M., Ortinau, D.J., 7 Bush, R.P. (2008). Essentials of marketing research. New York, NY: McGraw-Hill/Higher Education.
47. Harris, R., & Leiper, N. eds. (1995). Sustainable tourism: an Australian perspective. Routledge.
48. Heung, V.C., & Gu, T. (2012). Influence of restaurant atmospherics on patron satisfaction and behavioral intentions. International Journal of Hospitality Management, 31(4), 1167-1177.
49. Hollebeek, L., Glynn, M., & Brodie, R. (2014). Consumer brand engagement in social media: conceptualization, scale development and validation. Journal of Interactive Marketing, 28(2), 149-165.
50. Hollebeek, L., Jaakkola, E., & Alexander, M. (2018). Beyond the dyadic: customer engagement in increasingly networked environments. Journal of Service Management, 29(3), 330-332.
51. Hollebeek, L., & Rather, R.A. (2019). Service innovativeness and tourism customer outcomes. International Journal of Contemporary Hospitality Management.
52. Hoogland, J.J., & Boomsma, A. (1998). Robustness studies in covariance structure modeling: An overview and a meta-analysis. Sociological Methods & Research, 26(3), 329-367.
53. Hwang, J., Lee, J., & Kim, H. (2019). Perceived innovativeness of drone food delivery services and its impacts on attitude and behavioral intentions: the moderating role of gender and age. International Journal of Hospitality Management, 81, 94-103.
54. Island, K. & Higgins, D.F. (2018). Event tourism and event imposition: a critical case study from. Tourism Management, 64, 73-86.
55. Kandampully, J. (1997). Firms should give loyalty before they can expect it from customers. Managing Service Quality, 7(2), 92-94.
56. Kang, I., Jeon, S., Lee, S., & Lee, C.K. (2005). Investigating structural relations affecting the effectiveness of service management. Tourism Management, 26(3), 301-310.
57. Kau, A.K., & Loh, E.W.Y. (2006). The effects of service recovery on consumer satisfaction: A comparison between complainants and non-complainants. Journal of Services Marketing, 20(2), 101-111.
58. Kelly, D.M. & Fairley, S. (2018). What about the event? How do tourism leveraging strategies affect small-scale events? Tourism Management, 64, 335-345.
59. Kim, E., Tang, L. & Bosselman, R. (2018). Measuring customer perceptions of restaurant innovativeness: developing and validating a scale. International Journal of Hospitality Management, 74, 85-98.
60. Kline, T. (2005). Psychological testing: A practical approach to design and evaluation. Sage.
61. Kumar, N., Scheer, L.K., & Steenkamp, J.E.M. (1995). The effects of perceived interdependence on dealer attitudes. Journal of Marketing Research, 32(August), 348-356.
62. Kumar, V., Smart, P.A., Maddern, H., & Maull, R.S. (2008). Alternative perspective on service quality and Customer satisfaction: the role of BPM. International Journal of Service Industry Management, 19(2), 25-35.
63. Kwon, I.W.G., & Suh, T. (2005). Trust, commitment and relationships in supply chain management: A path analysis. Supply Chain Management: An International Journal, 10(1), 26-33.
64. Lawer, C., & Knox, S. (2006). Customer advocacy and brand development. Journal of Product and Brand Management, 15(2), 121-129.
65. Lee, J.S., Choi, Y. & Chiang, C.H. (2017). Exploring the dynamic effect of multi-quality attributes on overall satisfaction: the case of incentive events. International Journal of Hospitality Management, 64, 51-61.
66. Liljander, V., & Roos, I. (2002). Customer-relationship levels from spurious to true relationships. Journal of Services Marketing, 16(7), 593-614.
67. Lyubomirsky, S., & Layous, K. (2013). How do simple positive activities increase well-being?. Current directions in psychological science, 22(1), 57-62.
68. Maicas, J.P., Polo, Y., & Sesé, F.J. (2006). The impact of customer relationship characteristics on customer switching behavior. Managing Service Quality, 16(6), 556-574.
69. McKercher, B. (2016). Towards a taxonomy of tourism products. Tourism Management, 54, 196-208.
70. Menor, L., & Roth, A. (2007). New service development competence in retail banking: construct development and measurement validation. Journal of Operations Management, 25(4), 825-846.
71. Money, R.B. (2000). Word-of-mouth referral sources for buyers of international corporate financial services. Journal of World Business, 35(3), 314-329.
72. Montenegro, A.F. (2017). Motivation, satisfaction and loyalty in the case of a film festival: differences between local and non-local participants. Journal of Cultural Economics, 41(2), 173-195.
73. Moorman, C., Zaltman, G., & Deshpande, R. (1992). Relationships between providers and users of market research: The dynamic of trust within and between organizations. Journal of Marketing Research, 29(1), 314-328.
74. Morgan, R., & Hunt, S. (1994). The commitment-trust theory of relationship marketing. Journal of Marketing, 5 (July), 20-38.
75. Morgan, N., & Pritchard, A. (1998). Tourism promotion and power: Creating images, creating identities. John Wiley & Sons Ltd.
76. Okayasu, I., Nogawa, H., Casper, J., & Morais, D. (2016). Leveraging sport heritage to promote tourism destinations: the case of the tour of Flanders cyclo event. Journal of Sport and Tourism, 20(3/4), 263-283.
77. Oliver, R.L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research, 17(4), 460-469.
78. Oliver, R. (1997). Satisfaction: A Behavioral Perspective on the Consumer, McGraw-Hill, New York, NY.
79. Oom, V.P., Mendes, J., & Guerreiro, M. (2012). Residents’ participation in events, events image, and destination image: a correspondence analysis. Journal of Travel & Tourism Marketing, 29(7), 647-664.
80. Ordanini, A., & Parasuraman, A. (2011). Service innovation viewed through a service-dominant logic lens: a conceptual framework and empirical analysis. Journal of Service Research, 14(1), 3-23.
81. Panfiluk, E. (2015). Impact of a tourist event of a regional range on the development of tourism. Procedia-Social and Behavioral Sciences, 213, 1020-1027.
82. Pansiri, J. (2014). Tourist motives and destination competitiveness: a gap analysis perspective. International Journal of Hospitality & Tourism Administration, 15(3), 217-247.
83. Parasuraman, A., Zeithamal, V., & Berry, L. (1985). A conceptual model of service quality and its implications for future research. Journal of Marketing, 49(4), 41-50.
84. Parasuraman, A., Zeithamal, V., & Berry, L. (1988). SERVQUAL - a multiple item scale for measuring consumer perceptions of service quality. Journal of Retailing, 64(1), 12-40.
85. Parasuraman, A., Zeithaml, V.A., & Berry, L.L. (1994). Reassessment of expectations as a comparison standard in measuring service quality: implications for further research. Journal of marketing, 58(1), 111-124.
86. Park, J.Y., Back, R.M., Bufquin, D., & Shapoval, V. (2019). Servicescape, positive affect, satisfaction and behavioral intentions: The moderating role of familiarity. International Journal of Hospitality Management, 78, 102-111.
87. Pearce, D. (1997). Tourism and the autonomous communities in Spain. Annals of Tourism Research, 24(1), 156-177.
88. Price, L., & Arnould, E.J. (1999). Commercial friendships: Service provider–client relationships in context. Journal of Marketing, 63(4), 38-56.
89. Ravald, A., & Grönroos, C. (1996). The value concept of relationship marketing. European Journal of Marketing, 30 (2), 19-30.
90. Reicheld, F.F., & Sasser, W.E. (1990). Zero defections: Quality comes to services. Harvard Business Review, 68(5), 105-111.
91. Reinartz, W., Thomas, J., & Kumar, V. (2005). Balancing acquisition and retention resources to maximize customer profitability. Journal of Marketing, 69(January), 63-79.
92. Roberts, D., Hughes, M., & Kertbo, K. (2013). Exploring consumers’ motivations to engage in innovation through co-creation activities. European Journal of Marketing, 48(1/2), 147-169.
93. Ross, G.F. (2004). Ethics, trust and expectations regarding the treatment of disabled staff within a tourism hospitality industry context. International Journal of Hospitality Management, 25(5), 523-544.
94. Roy, S. (2013). Consequences of customer advocacy. Journal of Strategic Marketing, 21(3), 260-276.
95. Rust, R.T., & Verhoef, P.C., 81. L. Oliver. (1994). Service Quality Insights and Managerial Implications from the Frontier. Service Quality: New Dimensions in Theory and Practice, 1-9.
96. Sanchez, J., Callarisa, L., Rodriguez, R.M., & Moliner, M.A. (2006). Perceived value of the purchase of a tourism product. Tourism Management, 27(3), 394-409.
97. Santos, J., Vareiro, L., Remoaldo, P., & Ribeiro, J. (2016). Cultural mega-events and the enhancement of a city’s image: differences between engaged participants and attendees. Journal of Policy Research in Tourism, Leisure and Events, 9(2), 1-23.
98. Sarmah, B., Rahman, Z., & Kamboj, S. (2017). Customer co-creation and adoption intention towards newly developed services: an empirical study. International Journal of Culture, Tourism and Hospitality Research, 11(3), 372-391.
99. Sasser, S., Kilgour, M., & Hollebeek, L.D. (2014). Marketing in an interactive world: the evolving nature of communication processes using social media. In Harnessing the Power of Social Media and Web Analytics, 29-52. IGI Global.
100. Sautter, E.T., & Leisen, B. (1999). Managing stakeholders a tourism planning model. Annals of Tourism Research, 26(2), 312-328.
101. Selnes, F. (1998). Antecedents and consequences of trust and satisfaction in buyer–seller relationships. European Journal of Marketing, 32(3/4), 305-322.
102. Sharma, N., & Patterson, P.G. (2000). Switching costs, alternative attractiveness and experience as moderators of relationship commitment in professional, consumer services. International Journal of Service Industry Management, 11(5), 470-490.
103. Sharpley, Richard and Telfer, David J. (2002). Tourism and development, 221. Channel View Publications.
104. Sivadas, E., & Baker-Prewitt, J.L. (2000). An examination of the relationship between service quality, customer satisfaction and store loyalty. International Journal of Retail & Distribution Management, 28(2), 73-82.
105. Smolčić Jurdana, D., & Soldić Frleta, D. (2017). Satisfaction as a determinant of tourist expenditure. Current Issues in Tourism, 20(7), 691-704.
106. Snyder, H., Witell, L., Gustafsson, A., Fombelle, P., & Kristensson, P. (2016). Identifying categories of service innovation: a review and synthesis of the literature. Journal of Business Research, 69(7), 2401-2408.
107. Spekman, R.E., Isabella, L.A., & MacAvoy, T.C. (2000). Alliance competence: Maximizing the value of your partnership. New York: John Wiley & Sons.
108. Stamboulis, Y., & Skayannis, P. (2003). Innovation strategies and technology for experience-based tourism. Tourism Management, 24(1), 35-43.
109. Tanford, S., & Jung, S. (2017). Festival attributes and perceptions: a meta-analysis of relationships with satisfaction and loyalty. Tourism Management, 61, 209-220.
110. Tajeddini, K., Altinay, L., & Ratten, V. (2018). Service innovativeness and the structuring of organizations: the moderating roles of learning orientation and inter-functional coordination. International Journal of Hospitality Management, 65, 100-114.
111. Teixeira, S.J., & Ferreira, J.J.M. (2018). Entrepreneurial artisan products as regional tourism competitiveness. International Journal of Entrepreneurial Behavior & Research Entrepreneurial, available at: https://doi.org/10.1108/IJEBR-01-2018-0023.
112. Tiew, F., Holmes, K., & Bussy, N. (2015). Tourism events and the nature of stakeholder power. Event Management, 19(4), 525-541.
113. Tsai, S. (2017). Driving holistic innovation to heighten hotel customer loyalty. Current Issues in Tourism, 20(15), 1604-1619.
114. Verhoef, P.C., Franses, P.H., & Hoekstra, J.C. (2002). The effect of relational constructs on customer referrals and number of services purchased from a multiservice provider: Does age of relationship matter? Journal of the Academy of Marketing Science, 30(3), 202-216.
115. Walls, A., Okumus, F., Wang, Y., & Kwun, D. (2011). An epistemological view of consumer experiences. International Journal of Hospitality Management, 30(1), 10-21.
116. White, T.B. (2005). Consumer trust and advice acceptance: The moderating roles of benevolence, expertise and negative emotions. Journal of Consumer Psychology, 15(2) ,141-148.
117. Wilson, D.T. (1995). An integrated model of buyer-seller relationships. Journal of the Academy of Marketing Science, 23(4), 335-345.
118. Wu, C.H.J., (2007). The impact of customer-to-customer interaction and customer homogeneity on customer satisfaction in tourism service-the service encounter prospective. Tourism Management, 28, 1518-1528.
119. Yoo, C.K., Yoon, D., & Park, E. (2018). Tourist motivation: an integral approach to destination choices. Tourism Review.
120. Yoon, Y., & Uysal, M., (2005). An examination of the effects of motivation and satisfaction on destination loyalty: a structural model. Tourism Management, 26(1), 45-56.
121. Yürük, P., Akyol, A., & Şimşek, G.G., (2017). Analyzing the effects of social impacts of events on satisfaction and loyalty. Tourism Management, 60, 367-378.