Destination Attributes and Destination Image Relationship in Volatile

ISSN (Print) : 0972-6225 ISSN (Online) : 2348-9324

Metamorphosis, Vol 14(2), 1–19, July–December 2015

Destination Attributes and Destination Image Relationship in Volatile Tourist Destination: Role of Perceived Risk Hardeep Chahal* and Asha Devi

Abstract The primary purpose of the study is to examine the role of perceived risk in the tourism destination attributes and destination image relationship and to find what type of risks are mostly associated with domestic tourists who visited volatile destinations. The data were gathered from domestic tourists (with atleast 7 days of stay in J&K) about Kashmir destination and were contacted at various places such as bus stand, airport, tourists’ guest houses and hotels etc. in Jammu and Katra cities using judgmental sampling technique. For analysing the data, EFA, CFA and SEM statistical techniques were used. The study finds that perceived risk significantly moderates the relationship between tourism destination attributes and destination image. Further, human induced risk, financial risk, service quality/facility risks etc. have negative impact on destination image. By understanding the quality of destination attributes and various risk perceptions among tourists associated with Kashmir destination and their impact on destination image, tourism marketers can design specific marketing strategies to cope with the risk perceptions. The study concludes with limitations and future research.

Keywords: Affective and Unique Image, Destination Image-Cognitive, Human Induced Risk, Perceived Risk-Financial Risk, Physical Risk and Other Risk, Service Facility Risks, Tourism Destination Attributes

1. Introduction

Tourism is a popular leisure activity, which has vast impact on the state or nation’s economy in terms of growth and development. Various strategic plans time to time are made by destination marketers and government authorities to enhance the flow of tourists. For instance, Government of India has sanctioned 14 mega tourism projects worth Rs. 73.50 crore with the aim of creating tourist-related infrastructure and conserving heritage sites in J&K. Among these, nine tourism projects relating to conservation of heritage corridor of Jamia Masjid at Srinagar and construction of Kashmir Haat at Chinar Bagh, construction of TRC at Yousmarg, accommodation at Aharbal, and development of picnic spot at Pahalgam, and Sarbal Lake at Verinag worth Rs. 38.35

crore in Kashmir Valley. Four tourism projects including mega heritage conservation project of Rs. 16.92 crore for conservation of the Mubarak Mandi heritage palace and about 13.78 crore for development of tourist infrastructure at Mansar, Sanasar and Natha top, development of Darhal as Base Camp and Shikar Marg as gate way of tourist destination of Pir Panjal in Jammu Division. A project of Rs. 4.45 crore is set for development of tourist infrastructure in Kargil (The Hindu, 2012). While state government has projected to spend about Rs 90 crore for conservation of Mubarak Mandi Heritage Complex, Raja Amar Singh Palace, Dogra Art Museum, Badi Deori, Royal Court & Gadvai Khana during 2011-1552(Interim Report of J&K). However the role of such strategic plans become insignificant in the presence of disasters particularly human-caused disasters such as terrorism, theft

Department of Commerce, University of Jammu, Jammu-180006, India; [email protected], [email protected] *Author for correspondence

Destination Attributes and Destination Image Relationship in Volatile Tourist Destination: Role of Perceived Risk

etc., which affect tourism industry to prosper, make money and contribute to state and national economy. Besides, number of times, natural calamities and disasters like flood, cloud burst etc. also disturb and damage the tourism destinations. Most recently the nature’s fury and calamity have resulted in huge losses in the tourist destinations of J&K, particularly Kashmir region. To add, rich poor divide across the states also give rise to crime, health, and physical hazards, and which are consistently on rise. The situation further gets aggravated in presence of political instability, strikes etc. All these factors pave way for the development of tourists’ negative image towards such destinations as they feel their personal safety will be at risk whilst visiting them. Such, disturbed destinations are considered as volatile destination. Fuchs and Reichel28 defined volatile destination as a destination having more terrorism, strikes, political unrest, crime and theft, which lead to negative or bad destination image. Visitors’ risk perceptions towards volatile destination are growing continuously and tourists (both domestic and foreign) perceive such destinations as a risky place to live and travel44. All these risk perceptions have serious implications for tourism industry. For instance, destination’s negative image that develops in the minds of tourists result in decreased flow of tourists and which may harm overall development of tourism industry. Thus, it is important to understand to what extent tourists’ perceive risk influences their decisions in the selection of volatile destinations, which enjoy high image in the tourist map. Further, the extant literature reviewed also highlighted the direct and negative impact of tourists’ risk perception on their travelling decision-making process and revisiting intentions41,46,48. However, majority of such studies are conducted in context of developed countries. A very few studies are done in developing context especially in China, Thailand and Iran and that too, are based on limited destinations and constructs. For instance, majority studies have studied perceived risk and its relationship with travelling decisions and destination image. Furthermore, many of the studies conducted on perceived risk have used varied aspects of risks namely terrorism19,38,41,42,70,75,77; crime19,32,46; psychological risk16,28,38,84; cultural differences46,64,69 and other risks such as physical, financial, time and safety risks etc16,84. To add, body of scholars such as Lai & Vinh43, Upadhyaya81, Aksay & Kiyci2, Battour, Ismail & Battor8, Prayag & Ryan62, Martin & Bosque52 and Ahmed1, have investigated destination personality factors and their impact on destination places including natural,

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Vol 14 (2) | July–December 2015 | www.metamorphosisjournal.com

religious and man-made attractions that influence destination image. While studies such as Lo et al49, Zouni & Kauremenos, (2008) and Enright & Newton25 have taken somewhat comprehensive aspect and covered cultural/ heritage, social, economic and environment attributes aspects as well. Further, very few studies namely Troung & King, (2009); Tourism Western Australia (TWA)79 and Buhalis (2000: pp-98) cited in Cakici & Harman12, have studied 5As (attractions, access, accommodation, amenities and awareness) and their influence on destination image. Despite considerable research on tourism attributes, perceived risk and travelling decisions, very limited studies have examined the direct relationship between perceived risk, destination attributes and destination image and its dimensions in the tourism literature. Hence our study on destination attributes, destination image and perceived risk, will contribute to the existing literature with respect to two important aspects: first, the study will identify the impact of comprehensive destination attributes – attraction, accommodation, accessibility, ancillaries’ services, awareness and their impact on destination image. Comprehensive destination refers to positive or negative characteristics of a particular destination, while destination image refers to the impressions that a person holds about a region in which he/she does not reside81. Second, the study will explore the role of perceived risk and its dimensions in the image formation process as tourists tend to hold a single, undifferentiated and risky image for the entire risky tourist destinations.

1.1 Research Context Kashmir is known as Switzerland of India. It is a beautiful valley with high-clad showy mountainous, landscape, rivers, and lakes, meadows of flowers, garden and orchards, and religious palaces etc. which enhance its grandeur. Kashmir is a source of great attraction to both domestic as well as international tourists (India Today, 2012). It is well known for multitude of tourist products such as pleasure (Mugal Garden, Manasbal Lake, Shalimar and Nishant Gardens and Dal lake), adventure (Golf, Trekking, Skiing and Fishing), pilgrimage (Sankaracharya Temple, Kheer Bhawani, and Amar Nath Temple) etc. However, its image has come down and is now considered as one of volatile destinations or distrusted region73. Before 1989, tourism was considered as an important industry of the J&K state and Kashmir region was one of the most popular regions of the India. From 1989 to 2005 the flow of tourists in

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Hardeep Chahal and Asha Devi

the valley came down drastically because of the ongoing disturbance in the region73. However after 2005, Kashmir valley has rebounded and again became one of the famous tourist destinations of India. For instance, Gulmarg has become one of the most popular ski resort destinations and a home to the world’s highest green golf course (JKTDC Annual Report, 2013). The decrease in violence in the state has boosted the state’s economy and tourism industry55. JKTDC Annual Report also highlighted that Kashmir valley has witnessed a huge tourists flow in 2013. But, at the same time increase in the flow of tourists does not depict that disturbance because of terrorism, is completely over and controlled in the valley or is free from any risk. Protests still continue to happen time to time at various places and against the government36. Hence in the present scenario, two prominent research questions arise are-first, what destination attributes motivate tourists to visit volatile destinations and second, what types of risks are perceived by domestic tourists when they visit Kashmir destinations. It is in this backdrop, the study is conducted to identify important destination attributes (attraction, accessibility, accommodation, ancillaries services and awareness) that motivate tourists to visit Kashmir, their impact on destination image (i.e. cognitive, affective and unique image) and to find how strongly perceived risk influence the destination attributes and destination image relationship.

2. Review of Literature 2.1 Destination Attributes Tourist destination refers to a place visited by a tourist and may be interpreted as a city, region and country1,22 (Dadgostar & Isotato, 1995). According to Jani, Jang & Hwang39 tourist destination comprises of multi-destination trip attributes that include both environmental atmospheric and service attributes which encourage tourists to visit and to stay longer within the destination. Similarly, Crouch21 also highlighted in his study that core attractors (special events, climate, and culture and heritage attraction), mix activities (sport and recreation activities and music and fun activities etc.), infrastructure, accessibility and market ties are the main factors that significantly influence the competitive positioning of a tourist destination. Most recently, Lo et al.49 categorised the destination attributes under four broader heads- cultural/heritage, social, economic and


environment attributes and suggested that all the four attributes are important indicators of the destination image. Alike, Enright & Newton25 also pointed that competitive success of a tourist destination largely depends upon the strengths and weaknesses of such attributes. Truong & King78 and Tourism Western Australia (TWA)79 have identified the most significant destination attributes which include attractions, accessibility, accommodation, ancillary services and awareness that influence tourist perception. This report also linked attraction of a destination to two types of attractions that include natural attractions – which involve mountains, valley, landscapes, forests, lakes and rivers etc. and man-made attractions that comprise palaces, heritage, museums, ancient monuments, theme parks and entertainment (casino, trade hall and theaters). Further, Chiu & Ananzeh18, and Battour, Ismail & Battor8, inferred in their study that pull, push and religious attributes motivate tourists to visit in a particular destination. Further, Upadhyaya81 recommended in his study that accessibility and accommodation facilities are the imperative attributes of the tourism industry. The literature reviewed have considered destination attributes as cultural/heritage, social, economic and environment attributes49 and primary and secondary features. The primary features include climate, ecology, culture and traditional architecture while secondary features of tourism destination including hotels, catering, transport and entertainment58; destination attraction, accommodation service, food services and tourism trade etc. (Zouni & Kouremenos, 2008); natural and man-made attraction40. And very limited studies have used 5As i.e. attraction, accessibility, accommodation ancillaries services, awareness attributes. Accessibility of the destination is referred to the infrastructure facilities such as roads, airports and railways, while accommodation encompasses hotels, bungalows and tented camps where tourists/visitors can stay eat, sleep, and feel easy and comfortable to travel around. Cakici & Harman12 advocated that ancillary services and awareness attributes are the foremost destination attributes that significantly sway destination image and revisit intentions of tourists, whereas other attributes such as attraction, infrastructure and cultural attributes have least influence. Ancillary services and awareness attributes include all those services provided to the visitors or the suppliers of tourist service and awareness implies the recalling ability of tourists about the image of a destination that exists in their mind. Besides, Enright & Newton25 and Aksoy & Kiyci2, also put forth that common touristic

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factors, special events shopping, food, restful atmosphere and climate, attraction, sport and recreation activities, music and fun activities, infrastructure and accessibility factors also significantly influence the competitive positioning of a tourist destination.

2.2 Destination Image Destination image plays critical role in positioning tourism products, brands, and place58. Although researchers have tried to conceptualise destination image but its exact meaning and dimensions are yet difficult to state. Date back to late seventies, Crompton20 defined destination image as an attitudinal construct consisting of an individual’s mental representation of knowledge (beliefs), feelings, and global impression about an object or destination. Akin to this, Gallarza, Saura & Garcia30 have defined it as a mental representation developed by tourists on the basis of impressions such as attraction, facilities provided by the service marketers. Pike61 demonstrated that destination image is comprised of two components functional (price, climate and special event that form a part of destination image) and psychological (friendliness of the locals, notoriety or beauty of the landscapes, and feelings associated with religious place or historic events) characteristics of a destination. On the other hand, Enright & Newton25 remarked that the core aspect of destination image can be conceptualised as a composite of tangible and intangible components; and cognitive, affective and conative components of the destination. Similarly, Beerli & Martin9, stated that overall tourist perception toward a destination largely depends upon the cognitive, affective and unique aspects of the destination. In similar line, Qu, Kim & Im65, Beerli & Martın9 remarked that cognitive, affective and unique image aspects of a destination represent key elements for measuring the overall destination image and behavioural intentions. Cognitive image refers to perceived beliefs and knowledge about a destination. It is developed through the construction of thought process, including remembering, problem solving and decision making about a destination. Whereas affective image refers to feelings and emotions raised by tourist destinations and can be developed by outcomes of factors such as relaxing, enjoying good weather, have fun, emotional attraction of a destination23. On the other hand unique image refers to the image derived from the way to communicate the expectations of a satisfactory travel experience that is uniquely associated with the particular

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destination61. Recently Upadhyaya81 put forth destination image as an impression that a person holds about a region in which he/she does not reside. Prebezac & Mikulic63 highlighted in their study, linkage of individual awareness about a destination on the basis of consumers’ cognitive evaluation and experience, learning, emotions and perceptions toward cognitive, affective and unique image of the destination, which influence the overall image of the destination. Hakak36 and Aksoy & Kiyci2, also put forth in their studies that destination factors such as quality and types of food served in hotels, shopping, information services, and experience and cleanness in and around hotels etc. significantly influence the tourist travelling decisions and image of the tourist destination.

2.3 Perceived Risk The term perceived risk (PR) was first introduced in the marketing literature by Bauer7, cited in Quintal & Polczynski66. He highlighted that consumer behaviour involves risk in the sense that any action of a consumer will produce consequences which he cannot anticipate. PR is vital component to understand how destination attributes influence destination image29. In tourism literature, perceived risk is defined as a cognitive evaluation that influences the tourist behaviour. In other words, risk perception of a tourist immense relies on what he perceives and what he experiences about the tourism product while they make purchasing and consuming traveling decisions. Tourists are assumed to be rational, risk averse consumers who prefer to avoid unsafe destinations38. Similarly, Chew & Jahari16, also highlighted that perception of a tourist is significantly influenced by the risks associated with varied destination attributes Researchers such as Tavitiyaman & Qu77; Jalilvand & Samiei38 and Fuchs & Reichel28 mentioned in their studies about varied risks such as financial, time, performance, social, psychological and physical risks that tourists face while visiting a destination. Akin, Roehl & Fesenmaier71 cited in Chew & Jahari16, and Fuchs & Reichel29 have identified various types of risks such as time risk, human-induced, financial, service facility/quality, socio-psychological, natural disasters etc., associated with traveling decision. Perceived human induced risk refers to tourists’ risk perception related to crime, terror, political instability and crowded sightseeing factors associated with a particular destination. Financial risk refers to monetary loss incurred when the product needs to be repaired, replaced or if the purchase price is refunded

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it includes expenses like assumed costs of touring to a particular destination as compared to touring other destinations, extra expenses at home and the influence of the trip. Service quality risks include risk related to the friendliness of the hosts, courteousness of hospitality employees, quality of facilities in the destination visited and level of satisfaction with the hotels etc. Lastly other risks may include possibility of other occurrences such as risk of unhygienic food, safety and weather etc. while staying in particular tourist destination. Further, studies such as Chiu & Lin19, Lepp, Gibson & Lane46, Law42 and Reisinger & Mavondo69 recognised that socio-cultural, terrorism, health, financial risk, natural disaster risk, cultural differences and barriers, violence, war and crime against human rights etc. are other risk factors associated with a volatile tourist destination.

3. Hypotheses Formulation 3.1 Destination Attributes and Destination Image Destination attributes refer to positive or negative characteristics of a particular destination on the basis of which tourists select, evaluate and identify the level of their satisfaction. Positive characteristics of a destination significantly and positively influence tourists’ destination image and their revisit intentions50. Several studies namely Gnoth, Andreu & Kozak33, Jani, Jang & Hwang39, Ekinci & Hosany24 and Beerli & Martin9 suggested that the travel experience within a destination is explained by attractiveness of the destination such as natural attraction, heritage attraction, shopping and accommodation and food facilities etc. All these tourism resources make significant contribution to build the image of a tourist destination. Upadhyaya81 highlighted in his study that accessibility, touristic attractions, physical atmosphere, friendly and relaxing environment have significant impact on destination image. Specifically, Qu Kim & Im65 and Pike & Ryan60 have measured cognitive, affective and unique images of the destination using different destination attributes related with attraction, accessibility and accommodation awareness. They recommended that attraction and accommodation attributes significantly contribute to cognitive image, whereas natural attraction and pleasant environment contribute to affective image and unique accommodation facilities, unique infrastructure of the destination contribute to unique image.


However from different prospective, Chiu & Ananzeh18, remarked that MICE (meetings, incentive travels, conferences, and exhibitions) tourism also play significant role in contributing to the economy. Furthermore, destination attributes like atmosphere attraction, political, social, tourist facilities natural resources etc. also play significant role in the formation of touristic image56. Tourism Western Australia, (2009) has categorised the various attributes under five heads namely attraction, accessibility, accommodation, awareness and ancillaries services and established positive relationship between destination attributes and destination image. Hence, based on the aforesaid discussion, following hypothesis is proposed: H1: Destination attributes (5As – attraction, accommodation, accessibility, awareness and ancillaries services) significantly contribute to the cognitive, affective and unique images of the destination.

3.2 Perceived Risk, Destination Attributes and Destination Image Perceived risk is derived from traits of tourism products, which comprises of various attributes of destination such as bad weather, terrorism, unfriendly locals, airport personnel on strike, inedibility of local food, terror, crime, political unrest, disease, and natural disasters. These factors increase the level of tourist perceived risk28. Further, Lin &Hsu47 established that tourism risks associated with destination attributes that include man-made risks, event related risk, damage events risk and destination level factors have consequence on risk and significantly affect cognitive behaviour of visitors which further lead to bad image to the destination. Even, Rittichainuwat and Chakraborty70 also stated in their study that traveler’s perception is much directly influenced by disaster but by the negative attitude of the travel agencies, which again have significant impact on the destination image. Chew & Jahari16, highlighted that a positive destination image could be generated through decreasing the risk perception of tourists related to specific risk factor such as human induced risk, service quality factors terrorism risk and other destination risk. Further Qi, Gibson and Zhang64 stated that destination attributes related to violence risk and the socio-psychological risk factors negatively affect tourists’ perception about the visiting destination. Hence the following hypotheses are formulated:

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H2: Perceived risk has negative influence on cognitive, affective and unique destination image H3: Perceived risk has negative influence on overall destination image. H4: Perceived risk moderates the relationship between tourism destination attributes and destination image.

4. Methodology 4.1 Generation of Scale Items The items of destination attributes were generated from studies namely Merrilees et al53, Boo et al10, Chi & Qu17, Prebazac & Mikulić63, Enright & Newton25. Among 43 tourism destination attribute items, 13 pertained to attraction, 8 pertained to accessibility, 13 pertained to ancillaries’ service, 5 pertained to accommodation and 4 pertained to awareness. The second construct, destination image included 28 items adopted from Gacria et al., (2012); Qu et al65, Pike61 and Avgoustis & Achana6, relating to cognitive image ( 19 items), affective image ( 4 items), and unique image ( 5 items). Lastly four types of tourists’ perceived risk namely financial risk, human induced risk, service quality and other risks associated with tourist destination were used and were measured by 12 items extracted from Fuchs & Reichel28, and Quintial & Polczynski, (2010) studies as all these items can measure the major risks associated with a tourist destination28,29. All the items were measured on five point Likert scale with 5 as strongly agree and 1 as strongly disagree anchors. In addition to the scale items, few items on demographic profile of the respondents and reasons for visiting the destinations were also included.

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Due to time limitation and non-availability of sample frame, the respondents were selected using judgmental sampling approach. The tourists were contacted at various places such as bus stand, airport, katra, tourists’ guest house and hotels etc. in Jammu and Katra cities (i.e. Jammu considered as Connectivity hub while Katra as a key pilgrimage place) of Jammu region to know about their actual and potential experience about Kashmir region. Accordingly a total 214 questionnaires were distributed, out of which 166 questionnaires, including 88 responses from actual domestic tourists and 78 responses from potential domestic tourists, were returned which gave response rate of 77.5%.

4.3 Descriptive Statistics Before applying the parametric statistical tests to analyse the data, negatively worded items were reversed and 27 outliers were identified and removed because of extreme responses. Subsequent to outlier removal, the skewness and kurtosis measures of the data were checked to access the normality of data35. The skewness values were in the range 0.036 to -.045 while kurtosis values were to in the range .053 to -.385, which established data to be normal.

4.4 Socio-Demographic Profile of Sample The dominant respondents are young tourists aged between 20 years to 35 years (52.73%), from services sector and visiting Kashmir for rest and relaxation. Most of the tourists who visited Kashmir regions were actual tourists (60.43%), and visited Kashmir at the most thrice.

5. Data Analysis

4.2 Sample Design and Data Collection

5.1 Exploratory Factor Analysis

In order to finalise the scale items, at the outset, before conducting final survey, pretesting was conducted on a sample of conveniently selected respondents (n = 30) from three tourist stay places namely Vasihno Devi Dham, Sarswati Dham and Airport of Jammu City in October 2012. After discussion with the respondents and the experts, few items were revised and refined and three items were excluded from the scale for final survey. This whole process resulted in 83 items covering various aspects of destination attributes (43), destination image (28) and perceived risk (12). The sample population consisted of domestic tourists with at least 7 days of stay in J&K and who visited Jammu and Kashmir destinations during January to March, 2013.

In order to purify the data, EFA was employed construct wise by using a principal axis factor analysis with varimax rotation technique. Under the perceived risk construct, whole process of EFA was completed in two rounds. In the first round one item having communality below .50 was deleted. Finally, five factors which are named as financial risk, human induced risk, service facility risk, physical health risk and food related risk were extracted with 67.22 % of variance explained and .575 of KMO. The scale reliability of each factor was tested by assessing the cronbach alpha coefficient value which ranged from 0.5 to 0.783, above the generally agreed upon lower limit of 0.50 for research at exploratory stage, suggesting internal consis-


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tency of items in the factors51. The communalities varied from 0.60 to 0.79, suggesting that the variance in each original variable reasonably explained the constructs. The factor loadings of the 11 variables ranged from 0.7 to 0.86, above the suggested threshold value of 0.30 for practical and statistical significance34. Similarly under tourism destination attributes, 11 items were recorded with low anti-image, communalities (less than .50), and low factor loadings (less than .50) and hence deleted in 11 subsequent rounds. Finally nine factors namely accessibility, man-made attraction, accommodation facilities, reasonable accommodation, public services, government initiatives, unique destination attributes, destination awareness attributes, and tourists’ awareness about destination attributes, were emerged with 68.24% of the explained variance and .628 as KMO. The scale reliability of each factor was tested by assessing item-to-total correlation for each item separately. The cronbach alpha coefficient value of all the factors were near and above the threshold value 0.50 for research at exploratory stage, suggested internal consistency of items in the factors51. The communalities and anti-image matrix values varied from 0.60 to 0.78, suggesting that the variance in each original variable reasonably explained the constructs. The factor loadings of the 25 variables ranged from 0.45 to 0.83, above the suggested threshold value of 0.30 for practical and statistical significance59. Five- factor solution was obtained under destination image. In the first and the subsequent eight rounds, total 8 items with communality and anti-image values below .5, and negative and cross factor loadings were deleted. Finally 20 items were retained, clubbed into five factors namely cognitive image (tourist attraction), cognitive image (infrastructure), cognitive image (experience quality), unique image, affective image, with explaining 65.156% of the shared variance and obtained .545 KMO value. The communalities and anti-image matrix varied between 0.60 to 0.72 and the factor loadings ranged from 0.53 to 0.90. The cronbach alpha for the five factors ranged from 0.5 to 0.700 (Table 2).

5.2 Confirmatory Factor Analysis To assess the measurement model quality and to provide a test of validity for the various indicators4, confirmatory factor analysis (CFA) technique was employed. The measures like normed fit index (NFI), goodness-of-fit index (GFI), adjusted goodness-of-fit index (AGFI), root mean


square error of approximation (RMSEA), and the normed chi-square statistic (χ2/df) were used to evaluate the measurement quality of different destination constructs. Threshold value of 0.9 for NFI, GFI, and AGFI, RMSEA value less than 0.08, and χ2/df values less than 5 suggested acceptable fit of measurement model34. While average variance extracted (AVE), standardised regression weight (SRW), critical ratio (CR) and cronbach alpha, with threshold criteria of ≥.5, ≥.5, ≥1.96 and ≥.7 respectively suggested validity and reliability of the indicators. Initial analysis suggested that of the 11 perceived risk items, only 9 (Table 1) met standardized beta coefficient, and critical ratio criteria to represent a construct11, and hence were found statistically significant. The goodness of fit of the perceived risk scale (Table 3) is adequate, and the items represented financial, service, physical health, food related and human induced risks associated with tourist destinations of Kashmir region. Further, of the 25 destination image items, only 15 recorded standardized beta coefficients greater than 0.5 (Table 2). The items represented accessibility, man-made attraction, public service, reasonable accommodation, accommodation facilities, awareness attributes, unique destination attributes, government initiatives and tourist awareness about destination attributes. Similarly, of the 13 destination image items, only 10 had standardised beta coefficients in excess of 0.5 and represented dimensions of cognitive image, unique and affective image of the Kashmir destinations. Lastly, AVE values of the three constructs (destination attributes, destination image and perceived risk) are above .05 with critical ratio above 1.96 and respective cronbach alpha values as .52, .48 and .56 respectively. The NFI, GFI, AGFI, and RMSEA in all three scales were within the recommended threshold, indicating acceptable model fit (Table 2).

5.3 Reliability and Validity Construct - wise reliability of the measurements was assessed through testing cronbach alpha co-efficient, which is the most commonly applied estimate. All alpha values were found to be near to and above .60, hence reliability of the scales were established35 (Table 2). Besides alpha measure, reliability and validity of the measurements were also supported by results of confirmatory factor analyses. The regression weights of all respective constructs (i.e., perceived risk, destination attributes and destination image) were positive, high in magnitude and statistically significant, indicating unidimensionality

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8

Perceived Risk

Health, time, functional and psychological risks.

Perceived risk associated with food hygienic.

Crime in the destination.

Functional, financial, psychological, Physical, social and time risk.

Property crime; violent crime; crime against human rights and terrorism.

Yeung and and Yee84

Yiamjanya and Wongleedee85

George and Swart32

Jalilvand and Samiei38

Chiu and Lin19

Turkey

Japan

Context


Awareness; travel information and visiting decision.

Tourism management and destination image

Sport tourism image.

Food safety; traveler perception and personal factors.

There is a strong relationship between perceived risk and tourist personal characteristics.

Perceived risk has significant influence on destination choice.

Perceived risk strongly moderates the relationship between destination image and revisit intentions relationship.

Perceived risk has significant influence on cognitive image and affective image.

Relationships

India

Iran

Risk perception has significant influence on international traveler traveling intentions.

Moderate influence of perceived risk on tourist travelling decisions related to Islamic destination.

South Africa Tourist perceptions has significant influence on sport destination image.

Thailand

Risk reduction strategies; China destination marketing and travelling decision.

Terrorism, political, Destination image; religious and crime tourist satisfaction and risks. revisit intentions.

Cognitive and affective destination image and intention to revisit.

Other Constructs

Tavitiyaman and Qu77

Chew and Jahari16 Physical, sociopsychological and financial Risks of destination.

Author’s & year

Table 1. Literature Reviewed on Perceived risk

Journal of Islamic Marketing

Journal of Sport & Tourism

World Academy of Science, Engineering and Technology

British Food Journal

Journal of Travel & Tourism Marketing

Tourism management

Journal

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Man-made risks, damage events risk African Journal (cable car accident, bus accident and of Business food poisoning), event-related risk Management (i.e. dread factor) and destination level factor (i.e. ripple effects) should be investigated in future.

To analyse the impact of perceived risk on destination image and Intentions to travel.

Mega-events and international tourist attractions and use several individual and behavioural criteria such as group composition and income and their affect on tourists’ crime–risk perceptions.

Research should be conducted to examine the level of risk perceptions & their types such as risk food safety by using different tourist sittings.

Impact of risk characteristics, risk reduction strategies, and risk perception on destination choice, will be need investigation.

Impact of travel risk and tourist demographic characteristics on destination image and tourist satisfaction should be investigated.

Overall and unique image, perceived risk including other types of risk associated with tourism should be investigated.

Research gap


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Religious destination attributes such as places of worship, availability of halal food, sexual permissiveness, banning of alcohol consumption, gambling and dress code

Overall risk perception

Personal safety, Destination image and cultural risk, socio– revisit intentions. psychological risk, violence risk.

Terrorism and disease.

Battour, Ismail and Battor8

Quintal and Polczynski66


Qi, Gibson and Zhang,(2009)

Rittichainuwat and Chakraborty70

First-time travelers and repeat travelers decision.

Tourist satisfaction; destination image and revisit intentions

Destination image and Tourist choice decisions

Thailand

China

Western Australia

Saudi Arabia, Palestine, Mauritania, Oman, Jordan, Yemen, Egypt and Sudan

Western Australia

Travelling experience; awareness; safe and secure attributes.

Overall risk perception.

Context

Aschamer, (2010)

Other Constructs USA

Perceived Risk

Lepp, Gibson and Risk associated with Destination image and Lane46 modern countries, revisiting intentions. primitive Africa, cultural differences and barriers, violence, war and crime.

Author’s & year

Examined the influence of perceived risks on tourists travelling decisions during crises.

Socio–psychological risk, violence risk have strong influence on destination image and revisit intentions than personal safety and cultural risks.

Perceived risk has strong and significant impact on tourist satisfaction and visitors travelling decision.

Religious destination attributes such as places of worship, halal food, sexual permissiveness, banning of alcohol have significant impact on destination marketing

Perceived risk significantly influence tourist satisfaction and traveling decision.

violence, war and crime have strong, whereas cultural differences and barriers have moderate influence on destination image and visitors risk perception.

Relationships

Asia Pacific Journal of Marketing and Logistics

Tourism Management

Journal

Asia Pacific Journal of Marketing and Logistics

Negative impact of perceived terrorism and disease risk is needed to be further investigated in other tourism setting.

Continue...

Tourism Management

Perceived risk impact on destination Journal of Sport image in other tourism setting. & Tourism

Perceived risk has impact on destination image and antecedents of revisiting a destination; crossculture issues and their impact on revisit intentions should be investigated in future

More religious attributes of tourist International destination incorporate in the future Journal of research Tourism Research

Multi-attitude effect of tourist perception on risk and behavioral intentions need to be examined.

To identifying common dimension of risks such as political stability, political tendencies, economic development and prices, by exploring safety related attributes.

Research gap


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10


Destination marketing, culture and image.

Destination marketing and tourism.

Kozak, Crotts and Terrorism; natural Law41 disaster and health disease.

Physical, social, financial, psychological, performance, time, overall risk perception.

Infectious disease, terrorist attack and natural disaster.

Socio-cultural, terrorism, health and financial risk.

Travel destination international/ domestic risk, safety concern and social.

Terrorism and political risk associated with tourist destination

Fuchs and Reichel28

Law42

Reisinger and Mavondo69

Floyd et al.27

Sonmez and Graefe74

China

Israel

China

USA

Context

Tourists travelling decisions and Destination attraction factors

Marketing and travel services.

Conceptual Paper

USA

Travel safety; anxiety Australia and revisiting intentions.

Tourists (present as well as future) travelling intentions.

Novelty and Familiarity of tourism.

Country based risk associated.

Lepp and Gibson45

Other Constructs

Perceived Risk

Author’s & year

Terrorism and political risk have direct impact on tourists’ destination choice decision.

Perceived risks related to safety and social risk have direct significant influence travelling decision.

Cultural and psychographic factors perceptions of travel risk have strong impact than financial, anxiety risk on travel intentions.

Physical disease, terrorist attack and natural disaster have significant impact on tourists’ risk perception and their travelling decisions.

Tourist visiting Israel experience more physical as well as psychological risks then time and performance risks perception.

Perceived risks have significant direct impact on the tendency to travel internationally

Risk perceptions of traveler to particular regions of the world significantly influence the novelty and familiarity of the country.

Relationships

Impacts of situational factors on touristic decisions need to be examined.

To assess whether risks are perceived by both domestic and international tourist about the volatile destination or not.

Empirical future study is needed to assess the changes in the travel risk and safety perceptions using destination attributes such as cultural, environmental, adventurous, or packaged versus individually purchased tourism products.

To investigate the relationship between perceived risk and demographic, psychographic and trip profile variable and the impact of perceived risk on travelling decision.

A empirical research is needed to explore the various risk associated with destination image of a particular city, region etc

Understanding the role of independent variables such as natural disaster, crime etc. on variances in respect of risk perceptions.

Psychology risk of the tourist needed to be explored in the future.

Research gap

Annals of Tourism Research

Journal of Travel & Tourism Marketing

Journal of Travel Research

International Journal Of Tourism Research

Journal of Hospitality and Leisure Marketing

International Journal of Tourism Research

Tourism Management

Journal


Metamorphosis


Table 2. EFA & CFA Results for Destination Constructs Destination Attributes S.no

Factor

Items

F.L

SRW

Alpha Value

T.Value

1

Accessibility

Adequate road Networks.

.482

.580

.715

4.70

Good internal transportation facilities.

.613

.610

4.84

Local parking facilities are adequate.

.727

.755

5.23

Road maintenance.

.748

.545

Interesting museums and galleries.

.752

.81

Good musical and performance

.659

.621

Place of interesting architecture

.695

.99

Public health care service.

.578

.562

Educational facilities.

.797

.689

Meals provided in the restaurants/ hotels at reasonable price.

.729

.99

Hotel booking and staying at reasonable price.

.853

.484

Suitable accommodation.

.851

.598

Place with quality infrastructure.

.699

.618

It is a place with good café and restaurants.

.576

.647

Comfortable place.

.527

.807

Government residential services.

.834

.498

Place with different culture.

.770

.554

Place with interesting festivals.

.802

.618

2

3 4

5

6 7

8 9

Man-made Attraction

Public Services Reasonable Accommodation

Accommodation Facilities

Government initiatives Unique destination attributes

Good Hospitality cultural centre

.613

.37

Destination awareness attributes

Good name & reputation.

.649

.352

Famous destination.

.524

.349

Tourist awareness about destination attributes

Good eating and drinking establishment.

.717

.88

Pilgrimage/leisure/adventure, this destination comes to my mind immediately.

.753

.264

Destination characteristics come to my mind quickly.

.499

.666

Model fit indices

4.76 3.47

.717

7.97 11.1

.815 3.52 .567

3.69

CMIN/df= 1.460 GFI=.82 AGFI=.783 NFI=.80 CFI=.572 RMR=.058 RMSEA=.069

2.85 .685 .582

3.41 3.48

.509

1.95

.625 1.81

2.27

Average variance explained = .52 and Composite Reliability = .942 Destination Image 1

2

Cognitive image (Tourist attraction)

Unique image

Positive attitude to multicultural society.

.688

.592

Fascinating architecture.

.837

.668

Good infrastructure.

.679

.518

Destination has unique cultural events.

.903

.793

Destination has unique communities’ centuries.

.621

.691


.289 .708

CMIN/df= 1.22 GFI=.92 AGFI=.884 NFI=.936 CFI=.747 RMR=.041 RMSEA=.0067

Continue...

Metamorphosis

11


Destination Attributes S.no Factor

Items

F.L

SRW

Alpha Value

T.Value

3

Destination as quite pleasant.

.857

.425

.581

.072

You feel quite excited about this destination.

.854

.969

Adequate travel information and transport.

.779

.627

.580

.365

Easy access to provide various places.

.575

.552

.443

Excellent and suitable accommodation.

.626

.490

.268

Safe and secure society.

.536

.412

Lots of state parks.

.723

.542

Number of historical places.

.677

.510

High pricing

.739

.88

High transport, accommodation and food cost.

.854

.593

You are paying extra for the use of facilities.

.796

.461

This destination provides unsatisfactory facilities.

.833

.963

This destination provides unfriendly hosts.

.724

.832

Food and drink consumed.

.830

.69

Unfavorable environment.

.867

.277

Strikes

.799

.982

Road accidents

.769

.270

Crime cases.

.833

.989

Political unrest.

.724

4

5

Affective image

Cognitive image (Infrastructure)

Cognitive image (experience quality)

.609

.316

.730

4.948

Model fit indices

Average variance explained = .48 and Composite Reliability = .887 Perceived risk 1

2

3 4 5

Financial risk

Service facility risk

Food related risk Physical health risk Human induced risk

5.817 .596 2.769

CMIN/df= 1.21 GFI=.936 AGFI=.901 NFI=.956 CFI=.806 RMR=.004 RMSEA.077

.717 3.317 .584 .519

3.255

Average variance explained = .56 and Composite Reliability = .933

and establishing convergent validity51. In addition, average variance extracted for each dimension exceeded .50, which indicated good convergent validity. Also, all constructs exhibited composite reliabilities well above the recommended threshold of .7035 (Table 2).

6. Hypotheses Testing and Results 6.1 Impact of 5DA’s on Destination Image In order to assess the hypotheses of the study, we used structural equation modelling (SEM) technique using average summated score of respective factor items of latent dimensions. The relationship is assessed both individually as well as integeratively between the components of

12


destination attributes and destination image. The overall fit measures suggest that the data provide a good fit for the hypothesised causal models. All the fit indices such as CMIN/df, GFI, AGFI, NFI, CFI, RMR and RMSEA of the different models met the threshold criteria (that is, CMIN/df < 5, GFI, AGFI, NFI and CFI should be > .9, RMR < .5and RMSEA