Editorial Board

A Refereed Monthly International Journal of Management

Empirical Study on Tourist’s Satisfaction towards Silk Route Tourism Sites at Jammu & Kashmir with special reference to Dal Lake

Author

Arun Kaushal Assistant Professor Institute of Business Management GLA University, Mathura Contact No.:- 9760546367 E-mail:- arun.kaushal@gla.ac.in

Dr. Suvijna Awastthi Professor Department of Management Studies Jiwaji University, Gwalior Contact No:- 8989022829 E-mail:- suvijna@gmail.com

Abstract

Advancement of latest technology and awareness level of people creates an environment in Indian Tourism industry results into up gradation of tourism scenario in India. “Incredible India” as name suggest that starting from the Indus valley civilization unique image of India Portrays an image in the mind of visitors all over the world to have at least one look in their whole life which indirectly facilitates the Indian Tourist industry to explore its wings in the new era of enriched India in terms of health, wealth and prosperity.

Tourism is the activity of travelling to a place for pleasure. Tourism Industry facilitates to the state Government as well as Country’s government by creating employment opportunities and sustainable development in the form of GDP Growth and Foreign exchange respectively. The Mughal emperor Jhangir said that if there is paradise on earth, it is here. J&K is also known as “Paradise on Earth”. J&K is well known for its scenic beauty, natural waterfall, apple valleys, deep gorges, poplar trees, deodar trees, chinars, wonderful panorama, pollution free air, snow clad mountains, fascinating gardens, enchanting lakes etc. J&K sate has enormous prospects for tourism. Large numbers of visitors are approaching J&K State every year. Present Study attempts to identify the contributing factors adopted for their perception towards Silk Route tourist sites with special reference to Dal Lake which is the heart of J&k State by Domestic Tourists .Further assessment of these factors will be studied on the overall satisfaction level of visitors with the help of Multiple Regression through SPSS 20.

Keywords: Indian Tourism, Tourism Industry, satisfaction.

1 Introduction

1.1: Current Scenario of Indian Tourism Industry:

Advancement of latest technology and awareness level of people creates a health environment in Indian Tourism industry results into up gradation of tourism scenario in India. Tourism industry has become the main driving pillar of economic Development of any country resulting in to destination Development. Apart from being as major contributor in foreign exchange, tourism industry also creates its landmark for employment generation of India. e- Tourist visa for (FTA) Foreign tourist’s arrival has touched its growth (56%) year on year till December 2016 as per the information of Ministry of Tourism. Massive expansion of foreign tourist arrivals from 45,300 in 2015 to 10, 79,696 in 2016 is only because of e- visas facility extended from 113 countries to 161 countries. India is well known for its rich culture, historical heritage, terrains, diversity in environment (ecology), and places of natural beauty which spread the fragrance of colorful India all over the world. Government of India has announced to start number of schemes to enhance the growth of Tourism Industry and hospitality via setting up 5 STZ (Special Tourism Zones), special pilgrimage or tourism trains and a great Campaign (Incredible India) in its Union Budget 2017-18 Source: https://www.ibef.org/industry/tourism-hospitality-india.aspx

“Incredible India” as name suggests that starting from the Indus valley civilization, unique image of India Portrays an impressive landmark in the mind of domestic as well as visitors all over the world. Tourists from India as well as from foreign countries have a dream to visit once in their whole lives (especially Taj Mahal and Kashmir) which indirectly facilitates the Indian Tourist industry to explore its wings in the new era of enriched India in terms of health, wealth and prosperity (Campbell 2004). All developed as well as developing countries strives to accelerate their economic performance indictor results into excellent sustainable growth of their economies. India as emerging economy also gear up their various industries for same. Tourism is one of the industries where people feel enjoyment, entertainment and happiness etc as their hobby as well as leisure. In the Dynamic Scenario, every industry stretch its landmarks so grow further in their respective area , Indian Tourism Industry continuously trying to find the new ways with the help of which Indian Tourism attain an competitive advantage in Indian economy .

1.2 Role of Silk Route Tourism Sites for Jammu and Kashmir Development

Tourism Industry facilitates to the state Government as well as Country’s government by creating employment opportunities and sustainable development in the form of GDP Growth and Foreign exchange respectively. Local employment and State Income is influenced by effective Tourism System (Wilson &John, 2001)

The Mughal emperor Jhangir said that if there is paradise on earth, it is here. J&K is also known as “Paradise on Earth”. J&K is well known for its scenic beauty, natural waterfall, apple valleys, deep gorges, poplar trees, deodar trees, chinars, wonderful panorama, pollution free air, snow clad mountains, fascinating gardens, enchanting lakes etc. J&K sate has massive prospects for tourism. Large numbers of visitors are approaching J&K State every year.

J&K is to the Himalayas what Switzerland is to the Alps. It is also called as the,“Switzerland of East”. J&K consists of three regions viz. Jammu, Kashmir and Ladakh. All these regions are well known for tourism potential all around the world. Jammu, also known as, “City Of Temples” is an important destination for pilgrimage tourism. Some of the famous pilgrimage Sites locate here are Vaishno Devi Temple, Pahalgam, Gurmarg , Sonmarg ,Dallake,Amarnath Cake etc which very much famous among national and international Visitors are considers as Silk Routes sites results into prospects for up gradation of Kashmir or Silk routes Sites Tourism for International trade between India and East .

1.3 Silk Route: As bridge for International Connectivity

The Silk Road or Silk Route was a very old network of do business that for centuries were central point for cultural communication and economic cooperation among various regions of the Asian continent connecting the East and West from China to the Mediterranean Sea. Strategic conception of “The Silk Road Economic Belt and the 21st-Century Maritime Silk Road” (in short, the Belt and Road Initiative) projected by the Chinese President Xi Jinping when he visited the Middle and Southeast Asian countries in 2013. With the recent initiatives taken by the countries along the Silk Road (including China, Kazakhstan, Iran, Kyrgyzstan, Uzbekistan, Turkey, India and Russia), the Silk Road promises to offer trade and cultural exchange opportunities with the potential to shape the modern world subsequently formulated as a formal national policy in 2015, aims at building an open-minded, comprehensive, balanced and inclusive regional economic cooperation framework. Under the pressing trends of multi–polarization, economic globalization, cultural diversity and rapid development of information technology, the Silk Road offers tremendous opportunities for the Service Industries (financial services, tourism and hospitality, IT services, logistics, healthcare, retailing, education.

Source: http://explore.tandfonline.com/cfp/bes/fsij-silk-road

1.4 Satisfaction of Tourists: Indicator of Massive Growth.

Tourism satisfaction is one of the main ingredients of successful tourism performance as it is fundamental point of consideration by tourism stakeholders as results of better combination of facilities and services offered (Fuchs and Weiermair, 2003). Satisfaction level of tourists for various destination sites is the outcome of alignment of tourist’s expectations regarding destination sites as per their pre visit information & indication of the destination (Before visit expectations ) with their assessment of the outcomes of their experience after visit experience.

( Pizam. et.al 1978 ; Gursov& Neal.2008) Tourist Satisfaction is the combined mixture of emotional and cognitive aspects of tourist’s feelings regarding Destination (Neal & Gursoy, 2008 ; Pizam, Neumann, & Reichel, 1978)

2. Theoretical Background

Bulai et. al. (2016) examined that tourists are more frequent with nearest destination, which allow tourists to control their expenses. the cost of get to has a solid impact over goal flow and advancement through lengths of stay, periodicity of travel, measure of cash spent at the goal, stay association level, climate which may impact choice of travel. Marcello Risitano(2016) concluded that typically visited the destination’s environment influence visitors. This typically visit creates an image and self concept in visitor minds. The main focus to the destination, creating a brand image in visitor’s mind and find out relevant associations. These associations improve the place brand value.

Bagri et. al. (2015) identified that Traveler satisfaction is perceived as a limited amongst the most vital wellsprings of the goal upper hand since the central objective of tourism partners is to survey both the sufficiency and adequacy of tourism items as far as the offices and administrations that all together give essential goal encounters to sightseers. Du Cros et. al. (2015) concluded that advertisement of tourism place’s image influence visitors. Effectual developing destination image generate competitive advantage. This type destination image make easier to change people’s mind. The positive picture created over a past visit can improve the probability of repeat visits.

Kozioł et. al. (2015) concluded that hygienic factors motivate tourist. The key customer indicator was achieved such level. Safety, Quality of tourist service and cleanness may result in reluctance to tourism activity, more precisely in decreased inbound tourism in Cracow.Singh Manhas et. al (2014) identified that tourism is one of the declared area of growth of economy. Tourism satisfaction creates impact with greater flexibility and a meaningful experience. There is evident of interdependence of attractions service, transportation, information and promotion which highlights the need for collaboration among identified attributes to provide a lot gain those located companies located in a tourist destination.

Šimkova et. al. (2014) examined that to fulfillment basic need people are motivated before moving others. Every tourist expected that Physiological and safety needs must meet on tourism place. Personality in rural tourism must included diligence for a businessman which influences tourists.Wong et. Al. (2013) concluded that tourism place must according to tourist or tourist must according to tourism place. These were two different conditions which affected to take decision to selecting a tourism place and these conditions also influence tourist or tourist groups. Tourist expectations and motivation must correlate with each others.

Gudlaugsson et. Al. (2012) identified that level of satisfaction of tourists changed according to tourism place and on the basis of experience. The tourism place hold which brand image also affected tourists decisions to chose any tourism place. Siri et. al. (2012) identified that tourists’ perception about tourist destination quality were not homogeneous. Therefore tourist service designed according to tourist. Special interest, cultural attraction in tourist place motivated tourist.Elena-Cristina Mahika (2011) examined that motivation is a big reason for particular tourism place, which based on different developed form of tourism. Tourist behavior and expenses evaluation was necessary to motivate tourism for a particular tourism place. Group travelling was one factor which influenced decisions for a tourism destination.

Haojie Sun.et.al(2011) explained the importance of Silk Road for national boundaries by highlighting the relevancy of trade road, culture gallery and traffic road .Silk road is empowered with beautiful natural scenes, long history and health culture. Although after understanding its emergence importance of Silk road special attempt has made to understand the various challenges faced in this regards like weak awareness, inconvenient traffic , inadequate investment etc. Susanne Becken (2010) founded that climate conditions dominion choice of destination. Temperature, chill wind, humidity and radiation and wind speed or snow depth are those factors which affected to tourism. Climate conditions in tourists’ home countries are very important for favorable tourism. These factors also increase traveling. Sunshine and cloudiness these components influence tourism feeling with particular place.

Lemieux et. al. (2010) concluded that climate works as a silent feature on tourist decision making and experience of travelling. Atmosphere is a key element considered by traveler, intentionally or certainly amid travel arranging, and speaks to both a push and force consider for visitors. Climate and atmosphere is a natural segment of the get-away understanding and have been observed to be a focal inspiration for travel. The impact of past seasons is justifiable, for a person that has encountered a pessimistic effect on occasion fulfillment or saw loss of occasion in the past because of climate, is probably going to be careful about this potential while considering current occasion alternatives.

(Dmitrovic et al., (2009) explained that for the expansion of strategies by travelling agencies an important component needs to consider to be considered by them is Tourist Satisfaction so that aggressive positioning of their agencies can be carried out for customer or tourist delights. Glenn Kreag (2001) examined that different groups are regularly worried about various tourism impacts. These impacts are economic impact, social impact and cultural impact which affected tourism attraction. There is no evidence that every community have experience about every impact. Tourism regularly prompts enhancements out in the open utilities.

3. Research Gap and Objectives of Study:

As visitor satisfaction influences tourists’ behavioral intentions and plays a imperative role in destination competitive advantage, it has engrossed researcher’s attention and vast number of articles, researcher papers as well as studies have focused on this facet with regard to various tourist destinations all over the world (Osti, Disegna, & Brida, 2012; Marcussen, 2011; Garau, & Alegre 2010; Cracoli & Nijkamp, 2008; Wang & Qu, 2006; Yoon & Uysal, 2005; Kozak, 2001; Baker & Crompton, 2000; Pizam et al., 1978).But Silk routes tourism and silk routes sites J& K region have limited literature in research or it is at infancy stage .Present research attempts to identify the contributing constructs or factors affecting the satisfaction level of the Indian domestic tourists in context of Silk Route site especially Dallake . The current study contributes in the area of tourist satisfaction by providing an empirical relationship between performances of sites attributes and generally tourist satisfaction by Using Multiple Regression. The results of this paper are also advantageous for tourism policymakers and stakeholders in design and rising sustainability of this Natural tourism destination.

4. Research Methodology

v Type of research - Descriptive research

v Sampling technique - Purposive sampling: Researchers have used purposive sampling because main focus is to collect the information domestic Tourists who have visited Dallake and nearby areas of Silk route Sites in Kashmir

v Sample Locale : Domestic Tourists who normally used to visit Jammu and Kashmir from Agra , NCR and New Delhi

v Sample size - 140 Respondents composed for Marketing Professionals and Marketing Academicians

v Data collection tools -

Ø For primary data – It was collected through the questionnaire.

Ø For secondary data – It was taken from the research which are already been published in past.

v Scaling technique – Likert scale ranges (1 to 5) of depicting strongly disagree to strongly agree.

v Data analysis tool – Descriptive Statistics and Exploratory Factor and Multiple Regression with the help Of SPSS. 22

5. Data Analysis

5.1 Demographic Descriptive Statistics of Respondents:

In here, all the data has been classified on the basis of demographic questions asked in the questionnaire. This section put a light on the demographic aspect that has been covered for this research.

Table 1 - Demographic Profile of respondents

TOTAL NUMBER OF RESPONDENTS				382
VARIABLES	VALUES	RESPONSES		PERCENTAGE
Gender	Male		280		73.30%
	Female		102		26.70%
Education	High School		15		3.93%
	Intermediate		15		3.93%
	Graduate		109		28.53%
	Post graduate		32		60.73%
	Doctorate		9		2.36%
Income (Monthly in Rs.)	Less than 20000		265		69.37%
	20000 to 34000		60		15.71%
	35000 to 50000		30		7.85%
	More than 50000		26		6.81%
Age Group	Less than 25 year		283		74.08%
	25-34 years		88		23.04%
	35-44 years		6		1.57%
	Above 45 years		5		1.31%
Occupation	Businessman		12		3.14%
	Service men		72		18.85%
	Professional		44		11.52%
	Student		253		66.23%

5.2 Normality Test for Data: For applying any kind of statistical test on the collected data in case of primary data, normality test is essential as it is the main assumption for parametric testing. Normality can be assessed by two ways: Graphically as well as understanding numerical values. Table below shows the results from two recognized tests of normality, namely the Kolmogorov-Smirnov Test and the Shapiro-Wilk Test. The Shapiro-Wilk Test is more appropriate for small sample sizes (< 50 samples), but can also handle sample sizes as large as 2000. Due to this consideration, Shapiro-Wilk test is used to assessment of normality as numerical means of assessing normality is done in this study.

Table 2:	Kolmogorov-Smirnova			Shapiro-Wilk
Visitor's Perception	Statistic	df	Sig.	Statistic	df	Sig.
	0.084	500	0.281	0.975	500	0.255
	a. Lilliefors Significance Correction

Table shows that data is normally distributed with significant level of .255. As standard rule, if the significance value of the Shapiro-Wilk Test is greater than 0.05, the data is normal. If it is below 0.05, the data significantly deviate from a normal distribution.

Reliability test

The reliability test is used to check whether the developed scales (questionnaire) are reliable or not for collecting the reliable responses. The reliability test tells the relationship between individual items in the scale. It simply meant how one variable is related to each other. It tells the inter-consistency of all the variables in the questionnaire. Reliability of the datasheet is done using SPSS (Version 23). In here all the scaled items from datasheet are selected for performing the reliability test.

Table 3: Reliability Statistics
Cronbach's Alpha	No. of Items
.939	32

From the table 3, it can be seen that the value for Cronbach’s Alpha is 0.939 which in turn can be considered as 93.9%. It simply concludes that questionnaire is 93.9% reliable for proceeding to further analysis. This 93.9% of reliability is of 32 scaled variables taken from the questionnaire. Hence, we can say that these 32 variables are 93.9% correlated to each other.

Now since, the reliability for our data is an appropriate (acceptable) value; so study had proceed for further analysis i.e. in order to complete main objective , researchers had performed an Exploratory Factor Analysis. Continuing same, analysis and interpretation will continue as per the objectives.

5.3 Exploratory Factor Analysis

Exploratory Factor Analysis is a statistical instrument that performs a multivariate analysis and helps researchers to explore the variable and form the constructs. Exploratory factor analysis is a dimension reduction method through which variables are reduced to a limited number of factors/constructs. Constructs is formed by identifying underlying variables that explain a correlation pattern among observed variables. According to factor analysis, these construct then explains the variances that occurs in dependent variable. In conclusion we can say that exploratory factor analysis identifies construct on the basis of total variances in dependent variable they explain. Basically these constructs are nothing but a combination of variables from the questionnaire. Further, the naming of these constructs are fully subjected to researcher’s perspective.

KMO and Bartlett’s test of Sphericity

To perform Exploratory Factor Analysis, it is necessary to determine sample size adequacy which can be calculated using Kaiser-Meyer-Olkin Measures of sampling adequacy. According to Rule of Thumb, the value above 0.577 of the Kaiser-Meyer-Olkin, abbreviated as KMO value, is acceptable for appropriateness of factor analysis. From table no. 4 KMO value is 0.929. It means that the sample size of our datasheet is 92.9% % adequate for conducting the factor analysis.

Table 4 :Kaiser-Meyer-Olkin Measure of Sampling Adequacy.		.929
Bartlett's Test of Sphericity	Approx. Chi-Square	9281.517
	Df	496
	Sig.	0.000

Bartlett’s test of Sphericity is applied to find intra-correlation of variables in a population matrix. Bartlett’s test of Sphericity verifies the correlation between the variables. It actually checks the correlation through identity matrix, note that having an identity matrix meant no correlation at all in between the variables of the population. The null hypothesis for Bartlett’s test of Sphericity can be defined as follows for the datasheet.

HO: There is no significant correlation in between the variables of the population.

H1: There is a significant correlation in between the variables of the population.

From Table, the significant value for the datasheet is .000 which is less than 0.05; therefore, we are rejecting the null hypothesis (HO). This implies that alternative hypothesis is accepted i.e. the variables in the study are significantly correlated with each other.

Now that the variables in study have passed the KMO and Bartlett’s test of Sphericity, it means that the factor analysis for the datasheet is appropriate. In here the constructs have been extracted through factor analysis based on Eigen Value (i.e. greater than 1). Various constructs that have been extracted with their factor loading, total variance and cumulative variance are shown in Table 5. There are a total of 8 constructs extracted.

Table 5 : Summary of Extracted Factors affecting Satisfaction Level of Tourists towards Silk Route Site Dallake

Extracted Factor	Statements	Factor Loading	PVE	CPTVE
WEATHER AND ACCESSIBILITY (F1)	Pleasant weather and climate	.681	36.763	36.763
	The destination is free from air and noise pollution	.842
	Availability and adequateness of transportation facilities	.774
	Completeness of roads and road signage to destination	.718
	Easy accessibility of hotels and lodges	.812
	Telecommunication facilities near tourist destination	.832
UNIQUENESS OF DESTINATION (F2)	Tranquility and panoramic view of natural environment	.815	11.579	48.342
	The wilderness and undisturbed nature	.799
	A rich spiritual and cultural heritage	.829
	Spiritual attractions are well kept and restored	.845
	Variety of tourist attractions	.837
	Protected cultural and natural resources	.774
	The destination is unique and authentic	.721
QUALITY OF TOURIST FACILITIES (F3)	Quality & hygiene at tourist place, accommodation & eateries	.669	7.609	55.951
	Proper interpretation facilities	.802
	Availability of competent tourist guide	.846
	Maintenance of tourist attractions	.786
	Cleanliness & maintenance of public convenience facilities	.780
	Availability of leisure and recreational activities	.571
	Availability of quality souvenirs	.704
	Uncrowded and unspoiled destination	.600
TOURIST MOTIVATION FACTOR (F4)	Low traffic and adequate parking facilities	.693	7.492	63.443
	Well-maintained pedestrian pathways, parks and green areas	.818
	Hospitality and friendliness of local people	.784
	Safety and security	.812
	Availability of information center	.806
	Value for money	.789
	Activity oriented tourism place for a whole year	.841
TOURIST OVERALL EXPIERENCE (F5)	Visit provide mental relaxation	.795	5.821	69.264
	Visit enhance my connectivity with nature	.791
	Visit provide physical relaxation	.770
	Visit provide happiness and enjoy	.753

*PVE (Percentage of Variance Explained), * CPTVE (Cumulative Percentage of Total Variance Explained)

To do the regression analysis, it is necessary to club the underlying variables into constructs via Compute Variable function in SPSS (version 23). Compute variables is a tool that help researchers to club a number of variables into one constructs by aggregating their responses.

5.4 Regression analysis

In current case, the association of independent variables with the dependent variable is computed using Regression analysis in SPSS.

5.4.1 R-Square test

In Regression analysis, only R-square value has an importance for study as it can tell us the association properties for the independent constructs with respect to online purchase Intention. R-square is also known as “Coefficient of multiple determinations”.

Table 6: R Square Test
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	.608a	.369	.361	.58530
Predictors: (Constant): WA, UD, QTF, TMF Dependent Variable: TOS

Table 6, the R-square value is 0.369. The independent constructs show 36.9% of association with Tourists Satisfaction towards DalLake . The value of R-square lies between 0 and 1. The degree up to which R-square value is closely approximated to 1, regression model is considered as highly fit. In current study, it only reaches to 36% which is not that good, still appropriate enough.

5.4.2 Global test

Global test facilitates only to test a combine impact of independent variables onto the behavior of dependent variable Analysis of variance (ANOVA) table from regression analysis output helps in global test to check the overall fitness of model using null hypothesis ,

H0: There is no significant difference between independent variables and Tourist’s Satisfaction

i .e. H0: β1= β2 = β3 = β4 = 0

H1: There is a significant difference between independent variables and Tourist’s Satisfaction

i.e. H1: β1 ≠β2 ≠ β3 ≠ β4 ≠ 0

where β1, β2, β3, β4, and β5 are coefficient of independent variables ( WA, UD, QTF, TMF ).

The ANOVA table of the study is as shown below.

Table 12: ANOVAa
Model		Sum of Squares	Df	Mean Square	F	Sig.
1	Regression	75.371	5	15.074	44.002	.000b
	Residual	128.808	376	.343
	Total	204.179	381
a. Dependent Variable: TOS
b. Predictors: (Constant): WA, UD, QTF, TMF

In Table , the significant value is .000, which is less than 0.05, therefore, we are rejecting the null hypothesis (HO). This implies that alternative hypothesis (H1) is accepted i.e. not all βs are zero i.e.

β1 ≠β2 ≠ β3 ≠ β4 ≠ β5 ≠ 0

This implies that there is a significant difference of independent variables (( WA, UD, QTF, TMF ).with tourist’s Satisfaction

In order to verify the impact of each independent variable over Tourists Satisfaction , there is need to study coefficient statistic .

5.4.3 Coefficient statistic :

Coefficient statistic facilitates a researcher to know or determine an individual independent variable’s influence on dependent variable. The coefficient statistic of our study is shown below.

Table shows the significance value for each and every independent variable. In order the test their significance we need to formulate hypothesis for every individual.

a. WEATHER AND ACCESSIBILITY (WA)

H0: There is no significant relation between Weather and Accessibility and tourist’s satisfaction

i.e. H0: β1 = 0

H1: There is a significant relation between Weather and Accessibility and tourist’s satisfaction

i.e. H1: β1 ≠ 0

From the above table, the significant value for WA is .000, which is less than 0.05. Hence, the null hypothesis (H0) has been rejected and the alternative hypothesis (H1) has been accepted. It concludes that there is a significant relation) Weather and Accessibility and tourist’s satisfaction . Hence,

TOS = 0.222 WA ………………. eq. 1

b. UNIQUENESS OF DESTINATION(UD)

H0: There is no significant relation between Uniqueness of destination and tourist’s satisfaction

i.e. H0: β2 = 0

H1: There is a significant relation between Uniqueness of destination and tourist’s satisfaction i.e. H1: β2 ≠ 0

From table above the significant value for UD is .003, which is less than 0.05. Hence, the null hypothesis (H0) has been rejected and the alternative hypothesis (H1) has been accepted. It concludes that there is a significant relation between Uniqueness of destination and tourist’s satisfaction Hence,

TOS = 0.127 UD ………………. eq. 2

c. QUALITY OF TOURIST FACILITIES (QTF)

H0: There is no significant relation between qualities of tourist facilities and tourist’s satisfaction i.e. H0: β3 = 0

H1: There is a significant relation between qualities of tourist facilities and tourist’s satisfaction

i.e. H1: β3≠ 0

From the TABLE significant value for QTF is 0.000., which is greater than 0.05. Hence, the null hypothesis (H0) has been accepted and the alternative hypothesis (H1) has been rejected. It concludes that there is no significant relation between qualities of tourist facilities and tourist’s satisfaction Hence,

TOS =0.32 QTF ………………………….eq. 3

d. TOURIST MOTIVATION FACTOR (TMF)

H0: There is no significant relation between Tourist motivation factor and tourist’s Satisfaction i.e. H0: β4 = 0

H1: There is a significant relation between Tourist motivation factor and tourist’s Satisfaction

i.e. H1: β4 ≠ 0

From the Table significant value for TMF is .040, which is less than 0.05. Hence, the null hypothesis (H0) has been rejected and the alternative hypothesis (H1) has been accepted. It concludes that there is a significant relation between Tourist motivation factor and tourist’s Satisfaction . Hence,

TOS =0.13 ………………. eq. 4

Now, if we combine all the equations (eq1, eq2, eq3 and eq4 then we get an overall Regression equation that explains the Satisfaction level of tourist due to all independent variables. The Regression equation is

TOS= 0.224 + 0.222WA +0.127UD + 0.324QTF + 0.134 TMF

6. Practical Implications of Study:

For the betterment of Tourism Industry and for vacationers’ effective appraisal, Jammu and Kashmir Tourism authority have to pay a whole lot concentration to prominent pleasure attributes and make investment in improvement of crucial tourism conveniences, preserve service fine, preserve the picturesque and religious first-rate of destination and create a melodious ambiance as these may be the source of competitive benefit for this emerging religious visitor destination. Pleasure is considered to realize how nicely tourism stakeholders perceive and react to the dreams of site visitors. Therefore, tourism stakeholders have to make a prerequisite to file the tourists’ annotations, court cases and recommendations as they're critical assets for Betterment of Silk course Tourism websites. authorities organizations and neighborhood tourism entrepreneurs ought to put in force sustainable improvement by implementing system for ecological safety, enlightening protection, escalating assignment and growth of tourism infrastructures, and nurturing human aid development for the tourism region in silk direction Tourism websites.

7. Conclusion and Scope for Future:

As the complete discussion of present paper r focus only on understanding the factors related to comprising satisfaction of Domestic Visitors for Silk Route sites and nearby areas along with assessing the dependence of satisfaction from independent constructs .But as like other research work , present work has its limitation in limited sample size , so generalization of identified relationship is limited . Although value of R Square is Approx. 36.9%, this is somewhere lacking in understanding the full information about satisfaction of Tourists. In order to enlightening the unclear aspects of low satisfaction special in-depth conversations with local people can be carried in future in the form of content analysis. Further work can be processed in form of comparison of satisfaction of Domestic Visitors versus Foreign Visitors.

References:

Ø United Nations World Tourism Organization (UNWTO), NWTO technical manual: Collection of Tourism Expenditure Statistics, 1995http://pub.unwto.org/WebRoot/Store/Shops/Infoshop/Products/1034/1034-1.pdf.(Retrieved on 2009-07-11).

Ø United Nations World Tourism Organization (UNWTO), World Tourism Barometer – June 2009. http://www.unwto.org/facts/eng/pdf/ barometer/UNWTO_Barom09_2_en_excerpt.pdf (Accessed 15 July 2009).

Ø United Nations World Tourism Organization (UNWTO), Tourism 2020 Vision, Madrid, UNWTO, 2001.

Ø World Travel and Tourism Council, Tourism impact data and forecasts, 2009. http://www.wttc.org/eng/Tourism_Research/Tourism_Economic_Research (Accessed 1 July 2009).

Ø United Nations World Tourism Organization (UNWTO), Workshop on Tourism Statistics, 2008. http://www.sesrtcic.org/imgs/news/Image/

Ø United Nations Conferences on Trade and Development (UNCTAD), UNCTAD Handbook of Statistics 2008, New York and Geneva, United Nations, 2008.

Ø United Nations World Tourism Organization (UNWTO), Compendium of tourism statistics (2007 edition), Madrid, UNWTO, 2007.

Ø Wall, G. and C. Badke, Tourism and climate change: an international perspective. Journal of Sustainable Tourism. 2 (1994)

Ø Boniface, B. and C. Cooper, The Geography of Travel and Tourism, London. Butterworth-Heinemann. 1994.

Ø S. Pike, Destination image analysis – A review of 142 papers from 1973 to 2000. Tourism Management. 23 (2002) 541.

Ø P. Anderssen and R. Colberg, Multivariate analysis in travel research: A tool for travel package design and market segmentations. Proc. Fourth Annual Travel Conference of the Travel Research Association, Travel Research Association, Sydney, Australia, 1973.

Ø Hu, Y.and J. Ritchie, Measuring destination attractiveness: A contextual approach. Journal of Travel Research. 32 (1993) 25.

Ø Butler, R., Seasonality in tourism: Issues and implications, in: Seasonality in Tourism (T. Baum and S. Lundtorp, eds), London. Pergamon, 2001.

Ø Aksu, A., Icigen, E. T., & Ehtiyar, R. (2010). A comparison of tourist expectations and satisfaction: A case study from Antalya region of Turkey. Turizam, 14 (2), 66-77.

Ø Aktas, A., Cevirgen, A., & Toker, B. (2009). Assessing holiday satisfaction of German and Russian tourists visiting Alanya. Tourism and Hospitality Management, 15 (1), 1-12.

Ø Alegre, J., & Garau, J. (2010). Tourist satisfaction and dissatisfaction. Annals of Tourism Research, 37 (1), 52-73.

Ø Baker, D. A., & Crompton, J. (2000). Quality, satisfaction and behavioral intentions. Annals of Tourism Research, 27 (3), 785-804.

Ø Bigne, J. E., Sanchez, I., & Andreu, L. (2009). The role of variety seeking in short and long run revisit intentions in holiday destinations. International Journal of Culture, Tourism and Hospitality Research, 3 (2), 103-115.

Ø Bigne, J. E., Sanchez, M. I., & Sanchez, J. (2001). Tourism image, evaluation variables and after purchase behaviour: Inter-relationship. Tourism Management, 22 (6), 607-616.

Ø Chen, C., & Chen, F. (2010). Experience quality, perceived value, satisfaction and behavioral intentions for heritage tourists. Tourism Management, 31 (1), 29-35.

Ø Chen, X. (2013). The modified importance-performance analysis method and its application in tourist satisfaction research. Tourism Tribune, 28 (11), 59-66.