Examining tourist holiday satisfaction using Holsat model: evidences from incredible India Campaign

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The present study is carried out in Delhi NCR (n=284) to examine the holiday satisfaction of inbound tourists to India on different tour related attributes and to explore role of Incredible India Campaign in holiday satisfaction.

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Nội dung Text: Examining tourist holiday satisfaction using Holsat model: evidences from incredible India Campaign

International Journal of Management (IJM) Volume 11, Issue 2, February 2020, pp. 48–61, Article ID: IJM_11_02_006 Available online at http://www.iaeme.com/ijm/issues.asp?JType=IJM&VType=11&IType=2 Journal Impact Factor (2020): 10.1471 (Calculated by GISI) www.jifactor.com ISSN Print: 0976-6502 and ISSN Online: 0976-6510 © IAEME Publication Scopus Indexed EXAMINING TOURIST HOLIDAY SATISFACTION USING HOLSAT MODEL: EVIDENCES FROM INCREDIBLE INDIA CAMPAIGN Dr. Swati Sharma* Amity Institute of Travel & Tourism, Amity University, Noida, India Manjula Chaudary Professor, Kurukshetra University, Kurukshetra, India. * Correspondence Author Email: ssharma3@amity.edu ABSTRACT The emergence of tourism as an important socio- cultural and economic activity for a large number of countries has shifted the focus to realization of its potential. Destinations now are managed and marketed in a planned manner that requires measuring and evaluating tourism performance on a number of quantitative and qualitative indicators. Tourism and destination images are closely interlinked. At the same time holiday satisfaction is equally significance and many researchers have coined that it holds a key parameter when discussing about the destination image among the potential tourists. A little dent on destination images even by extraneous reasons immediately affects perception of risks by tourists and their subsequent tour plans. Country and destination branding developed as a marketing tool to accomplish a number of national goals across the world though it has been adopted relatively late by the developing countries. The present study is carried out in Delhi NCR (n=284) to examine the holiday satisfaction of inbound tourists to India on different tour related attributes and to explore role of Incredible India Campaign in holiday satisfaction. HOLSAT model developed by John Tribe has been used to capture the tourist satisfaction. The collected data has been analyzed and significant outcomes of the research are shown after testing the hypothesis developed for the study. Keywords: Tourist Attributes, HOLSAT, Incredible India, Destination Image. Cite this Article: Dr. Swati Sharma and Manjula Chaudhary, Examining Tourist Holiday Satisfaction using HOLSAT Model: Evidences from Incredible India Campaign, International Journal of Management (IJM), 11 (2), 2020, pp. 48–61. http://www.iaeme.com/IJM/issues.asp?JType=IJM&VType=11&IType=2 http://www.iaeme.com/IJM/index.asp 48 editor@iaeme.com
Dr. Swati Sharma and Manjula Chaudhary 1. INTRODUCTION India launched its „Incredible India‟ campaign in 2002 aimed at building its tourism image and brand at global level. The primary objective of Incredible India branding was to create a distinctive identity for the Incredible India and the logo used exclamation mark in place of „I‟ in India. The same logo is being used till date without any alteration. Kaur (2012) stated that the mid-1990s was a period in which state initiatives resulted in the creation of a viable and global competitive corporate brand for the India seeking to develop favorable image. Furthermore, „„Brand India had a decade later gained world-wide recognition among multinational corporations as well as the rich industrialized nations as an attractive destination for investments stated by several practitioners. Thus, it can be summarized that the „Incredible India‟ campaign did have a positive impact on the perception people hold about India. The concept of „nation branding‟ was introduced by Simon Anholt in 1996. Since then various definitions of nation branding have been proposed by academia and (marketing) practitioners. Anholt (2003) proposed that „„Country branding occurs when public speaks to public; when a substantial proportion of the population of the country – not just civil servants and paid figureheads – gets behind the strategy and lives it out in their everyday dealings with the outside world‟‟. Furthermore, the perception gap between the brand identity (projected by the country) and brand image (perceived by the rest of the world) will be reduced through nation branding. Kotler et al, (1999) suggested four critical reasons explaining why cities should brand themselves. These four reasons are also applicable to a nation branding because every nation go through the same process just as a city would but in a wider context. These adapted reasons are: (1) Countries has to adjust and adapt to stay highly relevant and current due to changes in the global environment. (2) As time changes, country evolves due to urbanization. A strong brand would withstand difficult times to deal with urban decay and negative publicity. (3) Countries are more competitive these days for affluent residents and tourists. To sustain competitive advantage, countries are now more attentive to become a more attractive destination for tourists. (4) Self-governance and local funding is the final reason. The „Incredible India‟ campaign can be understood better by reading the following quote by Kant (2009) „„While it is easy to position and brand single-product destinations like the Maldives and Mauritius or a wildlife destination like South Africa, it is extremely difficult and complex to establish a clear, precise identity for a multiproduct like India. India is a land of contrasts, a combination of tradition and modernity – a land that is at once mystical and mysterious. India is bigger than the twenty-three countries of Europe put together and every single state of India has its own unique attractions. „Incredible India‟, therefore, necessarily had to be the mother brand with the states establishing their own brand entity and emerging as sub-brands‟‟ (Kant, 2009). The above said lines present before the challenge that the „Incredible India‟ team faced in order to create a brand that represents this multifaceted country. „Incredible India‟ campaign is a national-international variant. The former Union Tourism Minister , in relation to this variant said: „„The „Go Beyond‟ campaign focuses on promoting lesser known destinations to domestic as well as international tourists‟‟ (Press Information Bureau, Government of India, 2012). The separate international variant was launched in December 2012 at the „World Travel Market-2012‟, which was held at London (Press Information Bureau, Government of India, 2012). The name of the separate international variant is called „Find What You Seek‟. “Tourists from the world over can find the destination or product of their desire in India, be it heritage sites, forts, beaches, backwaters, lakes, mountains, adventure, wildlife, culture, festivals, medical, wellness, MICE, religion or shopping. India offers something for everyone and that is why we proudly say that India is an incredible destination with a range of products http://www.iaeme.com/IJM/index.asp 49 editor@iaeme.com
Examining Tourist Holiday Satisfaction using HOLSAT Model: Evidences from Incredible India Campaign as found nowhere else. It is truly in India, you will find what you are seeking” (Press Information Bureau, Government of India, 2012). While studying the structure of the „Incredible India‟ campaign, it can be said that entire promotional campaign is divided in to two stages. Stage one was launched in 2002 and was completed in 2009. According to the former Union Tourism Minister, “Till now, we had been promoting India internationally from the point of view of the destinations. The Incredible India campaigns which we launched in 2002 have been extremely successful‟‟ (Press Information Bureau, Government of India, 2012). Concerning the second stage of the campaign, a paradigm shift can be detected. He further added by saying „„In our „Take II‟ of the Incredible India campaign, we are going to focus on the consumer” (Press Information Bureau, The emergence of tourism as an important socio- cultural and economic activity for a large number of countries has shifted the focus to realization of its potential. Destinations now are managed and marketed in a planned manner that requires measuring and evaluating tourism performance on a number of quantitative and qualitative indicators. Tourism and destination images are closely interlinked. A little dent on destination images even by extraneous reasons immediately affects perception of risks by tourists and their subsequent tour plans. (Government of India, 2012). 2. OBJECTIVE OF THE STUDY The current study has been carried out keeping the following objective in mind:  To study the holiday satisfaction of inbound tourists to India on different tour related attributes The hypothesis developed for the study is: H1: Inbound tourists to India do not experience holiday satisfaction on different tour related attributes. 3. LITERATURE REVIEW Competitiveness and attractiveness of tourist destinations are a unique combination of a large number of tangible and intangible features and tend to be relative. The following studies have explored the features that make a destination attractive and competitive. Var, Beck & Loftus (1977) emphasized role of natural, social & historical factors, recreation & shopping opportunities, accessibility & accommodation of minimum touristic quality standards in determining touristic attractiveness of tourist areas. Mayo & Jarvis (1981) linked the tourist motivations to destination choices in their work on “The Psychology of Leisure Travel”. Kale & Weir (1986) -work in the context of India found that the major factors in destination competitiveness and attractiveness were the availability of things to do & see, cost, climate & accommodation. It found that culture, scenery, history & food affected choice of a specific destination. Mill & Morrison (1992) focused on the concept of tourism system composed of attractions, facilities, infrastructure, transport & hospitality. They concluded that several external factors such as culture, availability of time, socio-economic criteria, stage of life cycle, and individual life style too affect the destination decision. Uysal & Hagan (1993) in their research on “Destination Attractiveness Based on Supply and Demand Evaluation” highlighted the role of pull factors; tangible characteristics such as accommodation, recreation & facilities and cultural & historical resources in the attractiveness of a destination. This experimental study identified tourism-attraction dimensions and proposed a tourist destination attractiveness model. http://www.iaeme.com/IJM/index.asp 50 editor@iaeme.com
Dr. Swati Sharma and Manjula Chaudhary Laws (1995) work on „Tourist Destination Management‟ placed the features of attractiveness of destination under two categories of primary and secondary. Primary features include climate, ecology, culture & traditional architecture and secondary features contain hotels, catering, transport & entertainment. The primary purpose of tourists is to enjoy the primary features and the secondary features are necessary to reinforce the attractiveness of the destination. Author assessed the differing importance of tourism for residents, employees, investors and tourists with several cases including Tibet, Hawaii, South Africa, Wales, Tonga and Antarctica. Sirakaya, Mclellan & Uysal (1996) in their research “Modeling Vacation Destination Decisions: A behavioral approach” used behavioral decision theory to explain destination decisions. It highlighted the factors affecting tourist destination choices that included physical (infrastructure, superstructure, scenery, beaches, climate, historical sites), socio- psychological attractions (attitude of the local people, cultural events, nightlife & entertainment, novelty of the destination, accessibility, food, quietness & so forth), political & social environment, cost of trip and availability of time. Davidson & Maitland (1997) in the work “ Tourism Destinations” suggested that an area should be considered a tourist destination if it has certain criteria such as variety of natural, social & cultural resources & services, other economic activities, host community, a local council & an active private or public sector. This also discussed the emerging issues of green tourism and regeneration of tourism destinations. Nicolau & Mas (2006) in their research „The Influence of Distance and Prices on the Choice of Tourist Destinations‟ found that the pull motivators indicate to its potential customers the extent of attractiveness of destination. It concluded that the dissuasive influence of distance and prices on the selection of destinations is moderated by motivations that can be direct (increasing the dissuasive effect) or inverse (reducing the dissuasive effect). This empirical study used random coefficient logit models to control the possible correlations between different destinations and consider tourist heterogeneity. Metin, Kozak & Seyhmus, Baloglu (2011) in their work “Managing and Marketing tourism destinations” emphasized the motivations behind the destination choices and the factors influencing destination choices. They highlighted the need for managing brand equity, tourist experience, and information systems by involving internal and external stakeholders in strategic planning and implementation. 4. RESEARCH METHODOLOGY The present study was conducted in National Capital region (NCR) India. The National Capital Region (NCR) is the metropolitan area surrounding National Capital Delhi and includes urban areas in neighboring states of Haryana, Uttar Pradesh and Rajasthan. The selection of the sites frequented by tourists for data collection was done through convenient sampling method. The large sample size justifies the use of convenient sampling as results are not biased by the use of sample. Places covered were Monuments, gardens, religious places, museums, amusement parks etc. Convenient sampling method was used for selection of inbound tourists. for analysis of country wise data only those were considered where the number of inbound tourists was more than 10. The normality test indicated data to be not normal as per Kolmogorov-Smirnov and Shapiro-Wilk values. 4.1. HOLSAT Model HOLSAT model for the first time was used to evaluate tourist satisfaction in a resort in Cuba by John Tribe. HOLSAT model has conceptual differences with other popular satisfaction measurement models such as SERVQUAL and SERVPERF. HOLSAT measures satisfaction http://www.iaeme.com/IJM/index.asp 51 editor@iaeme.com
Examining Tourist Holiday Satisfaction using HOLSAT Model: Evidences from Incredible India Campaign in two phases, expectation and experience, thus comparing the satisfaction with experience. Another key feature of HOLSAT model is addressing the multidimensional characteristics and variables of tourists‟ satisfaction in a specific destination by comparing a broad range of destination attributes against customers‟ expectation of the same. Based on HOLSAT model, travelers are asked to score their expectation of each destination attribute before travel and are asked to rate their experience once more after visiting the site. In this research also the pre visit and post visit expectations and experiences respectively were sought. 5. DATA ANALYSIS The satisfaction of tourists was measured through the gap between experiences post visit and expectations with the help of HOLSAT model. The difference in mean values of pre tour expectations and post tour experiences, expectation experience gap and corresponding significance value calculated through Wilcoxon signed rank test is shown in table 3. For measuring pre tour expectations and during tour experiences five point Likert scale has been used with commonly used label scores; 5 (Strongly Agree), 4 (Agree), 3 (Cannot Say), 2 (Disagree), 1 (Strongly Disagree) in place of scale used in original HOLSAT model from +4 to -4 with scale labels of very satisfied to very dissatisfied. Both expectation and experiences were measured at the same time. Tourists have responded to expectations about tour attractions and amenities based on their memory and experiences were measured during different stages of tour for different tourists depending upon the time of contact with tourists. The pre and post tour responses on tour attractions and amenities were analyzed using mean, standard deviation, mean difference and Wilcoxon signed rank test. Table II provides the summary of mean, mean differences and standard deviation of pre tour and post tour responses on tour attractions and amenities. The data in the above table I indicates that mean values of expectations pre visit for most of the factors were higher compared to post visit mean values of experiences indicating low level of satisfaction. The experiences exceeded expectations only for three attributes namely; water transportation cost, tourist information centers and hygiene at tourist sites. The expectation experience gap was found to be statistically significant on most attributes except for domestic connectivity, water connectivity, water travel cost, visa facilitation and hygiene & cleanliness at tourism sites (Table 3). Table 1 Satisfaction level of foreign tourists Variables Mean Mean Mean Sig. ( Pre visit) (Post visit) difference (Wilcoxon) Festivals & Concerts 1.9873 1.7241 -0.2632 .000 Museums, Monuments,& Historic 1.9442 1.6497 .000 Buildings -0.2945 Handicraft 2.0380 1.8911 -0.1469 .000 Gastronomy 2.1899 1.9367 -0.2532 .000 Folklore 2.1772 1.9797 -0.1975 .000 Religion 1.9747 1.8329 -0.1418 .000 Customs& Traditions 1.8962 1.5949 -0.3013 .000 Climate/ Weather 2.6354 2.3241 -0.3113 .000 Beaches 2.5165 2.3139 -0.2026 .000 Flora 2.4203 2.2329 -0.1874 .000 Fauna 2.3873 2.3063 -0.0810 .002 Mountains 2.1320 1.8909 -0.2411 .000 Deserts 2.2076 2.0354 -0.1722 .000 http://www.iaeme.com/IJM/index.asp 52 editor@iaeme.com
Dr. Swati Sharma and Manjula Chaudhary Religious attractiveness 1.9392 1.7747 -0.1645 .000 Hospitality & Friendliness 2.1013 1.7266 -0.3747 .000 Quality of Life 2.6557 2.5038 -0.1519 .000 Yoga 2.1190 2.0000 -0.119 .010 Wellness & spa 2.3747 2.2296 -0.1451 .000 Cost effectiveness 2.3190 2.1556 -0.1634 .001 Modern Medical facilities 2.5975 2.4107 -0.1868 .000 Conference Centers 2.4025 2.2842 -0.1183 .001 Domestic connectivity 2.5316 2.4773 -0.0543 .085 Professional organizers 2.4709 2.3556 -0.1153 .008 Air connectivity 2.2481 1.9747 -0.2734 .000 Air travel cost 2.2152 2.0329 -0.1823 .000 Surface Connectivity 2.4329 2.1468 -0.2861 .000 Surface travel cost 2.3772 2.0861 -0.2911 .000 Water connectivity 2.7008 2.6113 -0.0895 .147 Water travel cost 2.4808 2.5115 0.03069 .553 Visa facilitation 2.1696 2.1494 -0.0202 .477 Hotels 2.2861 1.9165 -0.3696 .000 Guest houses 2.4481 2.2886 -0.1595 .001 Bars & discotheques 2.7570 2.5443 -0.2127 .003 safety and security at tourist 2.4000 2.2152 .000 destinations -0.1848 Safety & security during travel 2.4911 2.3342 -0.1569 .001 Safety & security within cities 2.7873 2.6051 -0.1822 .000 Safety & security for women 3.1468 2.9570 -0.1898 .000 Reliability in travel services 2.3975 2.2456 -0.1519 .001 Quality in travel services 2.4051 2.2481 -0.157 .000 Promptness in travel services 2.4405 2.2557 -0.1848 .000 Tourist information centers 2.4911 2.5190 0.0279 .000 Shopping 2.3291 2.0861 -0.243 .000 Receptiveness of host community 2.1797 1.8557 -0.324 .000 Hygiene & cleanliness at airport 2.1620 1.7570 -0.405 .000 Hygiene & cleanliness at Hotel 2.2506 2.0759 -0.1747 .000 Hygiene & Cleanliness at tourist sites 2.6886 2.7797 0.0911 .212 Overall value for money 2.1671 2.0430 -0.1241 .002 Table 2: Pre tour Expectations and Post tour Experiences of tourists on different image components of India Pre tour expectations Post tour experiences Tour attractions and amenities Mean Std. Mean Std. Expectation Deviation Deviation experience gap Festivals & Concerts 1.9873 .81380 1.7241 .74881 -0.2632 Museums, Monuments,& 1.9442 .77619 1.6497 .77108 Historic Buildings -0.2945 Handicraft 2.0380 .80675 1.8911 1.25070 -0.1469 Gastronomy 2.1899 .77190 1.9367 .84213 -0.2532 Folklore 2.1772 .76003 1.9797 .76044 -0.1975 R eligion 1.9747 .82127 1.8329 .75564 -0.1418 Customs& Traditions 1.8962 .84413 1.5949 .71813 -0.3013 Climate/ Weather 2.6354 .95522 2.3241 .90195 -0.3113 Beaches 2.5165 .96466 2.3139 .88855 -0.2026 Flora 2.4203 .83732 2.2329 .83783 -0.1874 Fauna 2.3873 .79615 2.3063 1.71581 -0.0810 Mountains 2.1320 .75351 1.8909 .78845 -0.2411 http://www.iaeme.com/IJM/index.asp 53 editor@iaeme.com
Examining Tourist Holiday Satisfaction using HOLSAT Model: Evidences from Incredible India Campaign Deserts 2.2076 .75228 2.0354 .82398 -0.1722 Religious attractiveness 1.9392 .76494 1.7747 .82003 -0.1645 Hospitality & Friendliness 2.1013 .90114 1.7266 .79413 -0.3747 Quality of Life 2.6557 1.02404 2.5038 1.18444 -0.1519 Yoga 2.1190 .86882 2.0000 .81127 -0.119 Wellness & spa 2.3747 .81320 2.2296 .81441 -0.1451 Cost effectiveness 2.3190 .80577 2.1556 .81153 -0.1634 Modern Medical facilities 2.5975 .82934 2.4107 .81369 -0.1868 Conference Centers 2.4025 .75568 2.2842 .77577 -0.1183 Domestic connectivity 2.5316 .77452 2.4773 .78685 -0.0543 Professional organizers 2.4709 .80672 2.3556 .78815 -0.1153 Air connectivity 2.2481 .86042 1.9747 .91760 -0.2734 Air travel cost 2.2152 .88517 2.0329 .83783 -0.1823 Surface Connectivity 2.4329 .93027 2.1468 .96049 -0.2861 Surface travel cost 2.3772 1.72676 2.0861 .89425 -0.2911 Water connectivity 2.7008 2.04061 2.6113 1.75332 -0.0895 Water travel cost 2.4808 .83452 2.5115 .88245 0.03069 Visa facilitation 2.1696 .84546 2.1494 1.00530 -0.0202 Hotels 2.2861 .77504 1.9165 .77434 -0.3696 Guest houses 2.4481 .78321 2.2886 .84766 -0.1595 Bars & discotheques 2.7570 1.34492 2.5443 .96378 -0.2127 Safety and security at tourist 2.4000 .87955 2.2152 1.86247 destinations -0.1848 Safety & security during travel 2.4911 .91062 2.3342 .92331 -0.1569 Safety & security within cities 2.7873 1.01027 2.6051 .99795 -0.1822 Safety & security for women 3.1468 1.00693 2.9570 1.15133 -0.1898 Reliability in travel services 2.3975 .86763 2.2456 .88010 -0.1519 Quality in travel services 2.4051 .82657 2.2481 .84253 -0.157 Promptness in travel services 2.4405 .90311 2.2557 .88870 -0.1848 tourist information centers 2.4911 .86194 2.5190 1.16048 0.0279 Shopping 2.3291 .81111 2.0861 .89140 -0.243 Receptiveness of host 2.1797 .76443 1.8557 .84116 community -0.324 Hygiene & cleanliness at airport 2.1620 .89504 1.7570 .84701 -0.405 Hygiene & cleanliness at Hotel 2.2506 .94276 2.0759 .92583 -0.1747 Hygiene & Cleanliness at tourist 2.6886 1.00342 2.7797 1.22146 sites 0.0911 Overall value for money 2.1671 .74889 2.0430 .78091 -0.1241 Table 3 Pre tour expectations and post tour experiences (Wilcoxon signed ranks test) Tour attractions and Types of Ranks Z Asymp Sig. amenities N Mean Rank Sum of Ranks Festivals & Concerts Negative Ranks 141 100.07 14110.50 -6.049 .000 Positive Ranks 55 94.46 5195.50 Ties 199 Museums, Negative Ranks 159 115.95 18436.50 -5.387 .000 Monuments & historic Positive Ranks 71 114.49 8128.50 Buildings Ties 164 Handicraft Negative Ranks 145 103.79 15050.00 -3.530 .000 Positive Ranks 73 120.84 8821.00 Ties 177 Gastronomy Negative Ranks 146 102.72 14996.50 -5.233 .000 Positive Ranks 61 107.07 6531.50 Ties 188 http://www.iaeme.com/IJM/index.asp 54 editor@iaeme.com
Dr. Swati Sharma and Manjula Chaudhary Folklore Negative Ranks 13 97.31 12942.50 -3.898 .000 Positive Ranks 66 105.42 6957.50 Ties 196 Religion Negative Ranks 12 108.49 13453.00 -3.035 .002 Positive Ranks 85 99.91 8492.00 Ties 186 Customs & Traditions Negative Ranks 144 108.67 15648.00 -5.833 .000 Positive Ranks 64 95.12 6088.00 Ties 187 Climate/ weather Negative Ranks 162 122.67 19872.00 -6.009 .000 Positive Ranks 74 109.38 8094.00 Ties 159 Beaches Negative Ranks 12 111.17 14118.00 -4.131 .000 Positive Ranks 80 92.62 7410.00 Ties 188 Flora Negative Ranks 132 100.64 13285.00 -3.880 .000 Positive Ranks 70 103.11 7218.00 Ties 193 Fauna Negative Ranks 129 107.32 13844.00 -3.073 .002 Positive Ranks 83 105.23 8734.00 Ties 183 Mountains Negative Ranks 140 103.03 14424.00 -5.042 .000 Positive Ranks 64 101.34 6486.00 Ties 190 Deserts Negative Ranks 134 107.22 14367.00 -3.878 .000 Positive Ranks 77 103.88 7999.00 Ties 184 Religious Negative Ranks 121 87.01 10528.00 -4.064 .000 attractiveness Positive Ranks 57 94.79 5403.00 Ties 217 Hospitality & Negative Ranks 167 130.36 21770.00 -6.635 .000 friendliness Positive Ranks 76 103.63 7876.00 Ties 152 Quality of life Negative Ranks 144 129.04 18582.00 -3.660 .000 Positive Ranks 99 111.76 11064.00 Ties 152 Yoga Negative Ranks 113 88.02 9946.50 -2.580 .010 Positive Ranks 68 95.95 6524.50 Ties 212 Wellness & spa Negative Ranks 108 93.69 10118.00 -3.530 .000 Positive Ranks 69 81.67 5635.00 Ties 215 Cost effectiveness Negative Ranks 128 98.67 12630.00 -3.360 .001 Positive Ranks 72 103.75 7470.00 Ties 192 Modern medical Negative Ranks 127 97.05 12325.50 -4.091 .000 hospitals and facilities Positive Ranks 66 96.90 6395.50 Ties 199 Conference centers Negative Ranks 95 75.20 7144.00 -3.354 .001 Positive Ranks 53 73.25 3882.00 Ties 225 Domestic connectivity Negative Ranks 97 88.51 8585.50 -1.723 .085 Positive Ranks 76 85.07 6465.50 Ties 202 Professional Negative Ranks 99 90.78 8987.00 -2.658 .008 organizers Positive Ranks 72 79.43 5719.00 Ties 203 Air Connectivity Negative Ranks 136 116.75 15878.50 -5.269 .000 http://www.iaeme.com/IJM/index.asp 55 editor@iaeme.com
Examining Tourist Holiday Satisfaction using HOLSAT Model: Evidences from Incredible India Campaign Positive Ranks 77 89.77 6912.50 Ties 182 Air Travel cost Negative Ranks 122 103.12 12581.00 -3.962 .000 Positive Ranks 74 90.88 6725.00 Ties 199 Surface connectivity Negative Ranks 156 111.76 17435.00 -5.624 .000 Positive Ranks 66 110.88 7318.00 Ties 173 Surface Travel cost Negative Ranks 144 106.79 15377.50 -4.712 .000 Positive Ranks 69 107.44 7413.50 Ties 182 water connectivity Negative Ranks 111 91.09 10110.50 -1.449 .147 Positive Ranks 79 101.70 8034.50 Ties 201 water travel cost Negative Ranks 98 90.22 8842.00 -.594 .553 Positive Ranks 94 103.04 9686.00 Ties 199 Visa facilitation Negative Ranks 96 95.75 9192.00 -.710 .477 Positive Ranks 90 91.10 8199.00 Ties 209 Hotels Negative Ranks 175 117.73 20602.00 -7.240 .000 Positive Ranks 58 114.81 6659.00 Ties 162 Guest houses Negative Ranks 140 104.30 14602.50 -3.205 .001 Positive Ranks 77 117.54 9050.50 Ties 178 Bars & discotheques Negative Ranks 151 118.79 17937.00 -2.982 .003 Positive Ranks 92 127.27 11709.00 Ties 152 Safety & security at Negative Ranks 149 102.13 15218.00 -4.597 .000 tourist destinations Positive Ranks 63 116.83 7360.00 Ties 183 safety & security Negative Ranks 127 92.20 11710.00 -3.220 .001 during travel Positive Ranks 66 106.23 7011.00 Ties 202 safety & security Negative Ranks 140 114.29 16000.00 -3.545 .000 within cities Positive Ranks 85 110.88 9425.00 Ties 170 Safety & security for Negative Ranks 136 120.76 16424.00 -3.677 .000 women Positive Ranks 91 103.89 9454.00 Ties 168 Reliability in travel Negative Ranks 139 117.06 16272.00 -3.181 .001 services Positive Ranks 91 113.11 10293.00 Ties 165 Quality of travel Negative Ranks 121 93.61 11326.50 -3.708 .000 services Positive Ranks 66 94.72 6251.50 Ties 208 Promptness in Travel Negative Ranks 126 110.35 13903.50 -3.555 .000 services Positive Ranks 83 96.89 8041.50 Ties 186 Tourist Information Negative Ranks 110 96.69 10636.00 -.281 .000 centers Positive Ranks 98 113.27 11100.00 Ties 187 Shopping Negative Ranks 143 106.73 15262.50 -5.125 .000 Positive Ranks 67 102.87 6892.50 Ties 185 Receptiveness of Host Negative Ranks 152 107.10 16279.00 -6.188 .000 community Positive Ranks 58 101.31 5876.00 http://www.iaeme.com/IJM/index.asp 56 editor@iaeme.com
Dr. Swati Sharma and Manjula Chaudhary Ties 185 Hygiene & Negative Ranks 168 118.44 19898.00 -7.521 .000 Cleanliness at airport Positive Ranks 58 99.19 5753.00 Ties 169 Hygiene & Negative Ranks 126 117.35 14786.00 -3.653 .000 Cleanliness at Hotel Positive Ranks 89 94.76 8434.00 Ties 180 Hygiene & Negative Ranks 126 110.80 13960.50 -1.248 .212 Cleanliness at Tourist Positive Ranks 121 137.75 16667.50 sites Ties 148 Overall value for Negative Ranks 117 93.08 10890.50 -3.086 .002 money Positive Ranks 70 95.54 6687.50 Ties 208 The ranks data in table 3 indicates that Beaches, Religion and folklore have got more ranks more than the negatives. The ties are in Mountains, Yoga, and Visa facilitation, Overall value for money, Quality of Travel services, safety and security during travel. Wilcoxon signed rank showed that domestic connectivity Z=-1.723 and p =.085 is not statistically significant pre and post visit, Hygiene and cleanliness at tourist sites with Z= -1.248 and p =.212 is not statistically significant, Visa facilitation Z = -.710 and p =.477 is not statistically significant; water transportation connectivity and cost are also not statistically significant. Tour related attributes and satisfaction of inbound tourists to India The pre tour expectations and post tour experiences responses of inbound tourists on 47 tour related attributes were analyzed with the help of factor analysis to identify the important variables and to reduce their number. At the pre tour expectation stage 47 variables were grouped into 12 major components using Principal component analysis (Table 4) and post tour experiences were grouped into 14 components (table 5). The 12 components of pre tour stage were Accessibility, Service Quality, Attractions, Hygiene & Quality, Natural attractions, Business, Medical, Safety & Security, Quality of life, Religious attractiveness, Water Connectivity & Accommodation. The additional two at the post tour stage were Gastronomy and Hospitality & Friendliness. This can be inferred that tourists had positive experiences for gastronomy and hospitality/friendliness in India that was not a high expectation prior to tour. Tourism product of India can be strengthened on all the 12 components common at pre and tour stage and the additional components of gastronomy and hospitality & friendliness can be used as core attractions. Atithi devo bhava campaign and its spirit can be continued for hospitality & friendliness experience in India and gastronomy tours can be started with greater focus. The objective was to find the important factors responsible for the satisfaction of inbound tourists to India. The responses of tourists on pre tour expectations and post tour experiences on 47 variables were analyzed with the help of factor analysis to reduce number of variables and to find the salient variables. Firstly, correlation matrix of items with other items was seen and each item was correlated with other items at least by.3 suggesting reasonable factorability. Secondly, Kaiser- Meyer- Olkin (KMO) was calculated as shown in table IV Table 4 KMO of pre visit expectations and post visit experiences of attributes Kaiser-Meyer-Olkin Measure of Sampling Adequacy. Pre - Visit Post – Visit .874 .803 Bartlett's Test of Spherecity Approx. Chi-Square 8811.874 6128.541 Df 1081 1081 Sig. .000 .000 http://www.iaeme.com/IJM/index.asp 57 editor@iaeme.com
Examining Tourist Holiday Satisfaction using HOLSAT Model: Evidences from Incredible India Campaign The KMO was 0.874 & 0.803 for pre and post visit respectively, which was above the recommended value of 0.6 and as per the Bartlett‟s Test of Spherecity the significance value was .000 for both pre and post visit, as the value of p >.05 so the test was found to be significant. Finally communalities were calculated and are presented in table 5 Table 5 Communalities for pre visit and post visit Communalities Pre- Visit Post- Visit Initial Extraction Extraction Festivals & Concerts 1.000 .576 .564 Museums, Monuments,& Historic Buildings 1.000 .641 .660 Handicraft 1.000 .549 .570 Gastronomy 1.000 .670 .676 Folklore 1.000 .629 .569 Religion 1.000 .707 .758 Customs& Traditions 1.000 .718 .720 Climate/ Weather 1.000 .669 .554 Beaches 1.000 .572 .626 Flora 1.000 .760 .599 Fauna 1.000 .784 .572 Mountains 1.000 .659 .585 Deserts 1.000 .613 .622 religious attractiveness 1.000 .619 .566 Hospitality & Friendliness 1.000 .553 .505 Quality of Life 1.000 .647 .565 Yoga 1.000 .718 .643 Wellness & spa 1.000 .700 .687 Cost effectiveness 1.000 .706 .687 Modern Medical facilities 1.000 .687 .592 Conference Centers 1.000 .675 .661 Domestic connectivity 1.000 .753 .631 Professional organizers 1.000 .721 .569 Air connectivity 1.000 .594 .658 Air travel cost 1.000 .571 .704 Surface Connectivity 1.000 .608 .708 Surface travel cost 1.000 .475 .654 Water connectivity 1.000 .622 .484 Water travel cost 1.000 .629 .629 Visa facilitation 1.000 .546 .604 Hotels 1.000 .587 .565 Guest houses 1.000 .553 .719 Bars & discotheques 1.000 .591 .590 safety and security at tourist destinations 1.000 .662 .444 Safety & security during travel 1.000 .741 .731 Safety & security within cities 1.000 .794 .783 Safety & security for women 1.000 .692 .684 Reliability in travel services 1.000 .808 .703 Quality in travel services 1.000 .841 .742 Promptness in travel services 1.000 .805 .714 tourist information centers 1.000 .554 .561 Shopping 1.000 .548 .672 Receptiveness of host community 1.000 .536 .587 Hygiene & cleanliness at airport 1.000 .593 .711 Hygiene & cleanliness at Hotel 1.000 .696 .709 Hygiene & Cleanliness at tourist sites 1.000 .683 .811 Overall value for money 1.000 .482 .588 http://www.iaeme.com/IJM/index.asp 58 editor@iaeme.com
Dr. Swati Sharma and Manjula Chaudhary 6. FINDINGS The data on pre tour expectations of tourists on different tour related attributes and during tour/post tour experiences on same attributes was analyzed through HOLSAT (Holiday Satisfaction) model, Wilcoxon signed rank test and significance test of rank values. The HOLSAT model was applied to measure the holiday satisfaction of inbound tourists through the expectation and experience gap that showed positive values only for 3 variables out of 47 variables namely. These 3 variables are Water travel cost, Tourist information centers and hygiene at tourism sites (Table 3). Analysis of same data on Wilcoxon signed rank showed positive ranks for Beaches, Religion and folklore and all other variables got ties or were negatively ranked (Table 3). The test of significance Wilcoxon signed rank test values suggested significant relationship between the pre and post visit ranks of attributes except for five attributes namely domestic connectivity, hygiene & cleanliness at tourism sites, visa facilitation, water transport connectivity and cost. The only common factor rated positive and significant between Wilcoxon signed rank test and HOLSAT test was tourist information centers. This positive attribute can be further strengthened to be converted into strength and other attributes found important and significant can be improvised to provide more satisfactory experience to tourists. The composite value of gap on HOLSAT model was found to be negative. The analysis of holiday satisfaction of inbound tourists on different tour attributes indicates tourist information centers as positive, high ranked and significant attribute; Wilcoxon signed rank test mentioned folklore, religion and beaches as high ranked attributes and all the tour related attributes significant except domestic connectivity, hygiene & cleanliness at tourism sites, visa facilitation, water transport connectivity and cost on the other hand HOLSAT presented water travel cost, tourist information centers and hygiene & cleanliness at tourism sites as positive attributes. The overall satisfaction was found to be negative thus nullifying the positive effect of few attributes. This requires a serious rethink and effort on almost all the attributes for the satisfying experience of tourists and to build a positive tourist destination image of India. The Hypothesis H1 (inbound tourists to India do not experience holiday satisfaction) is accepted for all tour related attributes except for five attributes; domestic connectivity, hygiene & cleanliness at tourism sites, visa facilitation, water transport connectivity and cost. REFERENCES [1] Aksoy, R., & Kiyci, S, A Destination Image As a Type of Image and Measuring Destination Image in Tourism (Amasra Case).European Journal of Social Sciences, 20 (3), 2011, pp 478. [2] Assael, H, Consumer behavior and marketing action. Boston: Kent Publishing, 1984 [3] Balgobind, S.V, An incredible investigation. Media & Business. Retrieved from http://hdl.handle.net/2105/15590, 2013 [4] Baloglu, D., & McCleary, K, A model of destination image formation, Annals of Tourism Research, 26:868-897, 1999 [5] Baloglu, S., & Brinberg, D, Affective images of tourism destinations. Journal of Travel Research, 35(4), 1997 pp 11–15. [6] Chon, K.-S, The role of destination image in tourism: A review and discussion. Revue de Tourisme, 45(2), 1990, pp 2-9. [7] Churchill, G. A., Jr, A paradigm for developing better measures of marketing constructs. Journal of Marketing Research, 16(February), 1979, pp 64-73. http://www.iaeme.com/IJM/index.asp 59 editor@iaeme.com
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