Title page with author details
Integrating country and brand images: Using the Product— Country Image framework to understand travelers’ loyalty towards responsible tourism operators Makarand Modya,*, Jonathon Dayb, Sandra Sydnorb, Xinran Lehtob, William Jafféb a
School of Hospitality Administration, Boston University, 928 Commonwealth Avenue, Boston 02215 b School of Hospitality and Tourism Management, Purdue University, 900 W. State Street, West Lafayette, IN 47907, USA *
Corresponding Author. Tel.: +1 617-358-1620 E-mail Addresses:
[email protected] (M. Mody),
[email protected] (J. Day),
[email protected] (S. Sydnor),
[email protected] (X. Lehto),
[email protected] (W. Jaffe).
*Highlights
HIGHLIGHTS Limited research on understanding loyalty beyond the level of the destination. A model of travel operator loyalty was developed based product-country image and tourism literatures. Push motivations to be responsible travelers interact with destination and travel operator images to impact attitudinal loyalty. Cognitive brand image is a critical antecedent to tour operator loyalty. Study advances PCI framework in the context of tourism, and extends place image theory.
*Manuscript (remove anything that identifies authors) Click here to view linked References
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Integrating country and brand images: Using the Product—Country Image framework to
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understand travelers’ loyalty towards responsible tourism operators
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Abstract
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While much research into loyalty has been conducted at the destination level, tourists’ loyalty
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towards their intermediary has not been considered. To address this gap, the present study
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develops a model of tourists’ loyalty towards responsible tourism operators by integrating two
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streams of literature. The first stream pertains to branding, consumer behavior, and international
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business, specifically Product-Country Image (PCI), while the second stream pertains to the
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extensive work concerning the concepts of destination image and destination loyalty in tourism.
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Data were collected using an Internet survey of domestic and international travelers to five
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responsible tourism operators in India. Results indicate that tourists’ motivations to participate in
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responsible tourism and their perceptions of the destination and the operator’s brand constitute
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the determinants of their attitudinal and behavioral loyalty towards their operator. The study
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advances the PCI framework in the context of tourism, thus contributing to the literature on
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image measurement and also extending place image theory. The findings have important product
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development and positioning implications for operators and destination marketers in India.
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Key Words: Product-Country Image, loyalty, tour operator, responsible tourism, India
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1. Introduction Although consumer loyalty has been studied extensively in hospitality and tourism,
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complete understanding of the topic remains elusive in both practice and theory. Much research
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into loyalty has been conducted at the level of the destination. McKercher, Denizci-Guillet, and
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Ng (2012) suggested the need to rethink loyalty at different tiers in the tourism system.
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Specifically, while “it is apparent that intermediaries exert significant influence on travel
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behavior, the role of intermediaries and other decision-makers has also not been considered in
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loyalty research” (p. 729).
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The present study responds to this gap by developing a model of tourists’ loyalty towards
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responsible tourism operators in India. It examines the concept of loyalty at a different tier in the
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tourism system—at the level of the brand—by integrating two streams of literature. The first
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stream originates in the literature on branding, consumer behavior, and international business:
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product—country image (PCI). The second stream stems from extensive work concerning the
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concepts of destination image and destination loyalty in tourism. The context of responsible
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tourism is particularly appropriate for such an examination. While there are no official statistics
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indicating the size of the responsible tourism industry, trends indicate that growth in responsible
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tourism continues to outpace the growth of the tourism industry as a whole (The Case for
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Responsible Travel: Trends & Statistics 2016, 2016). Moreover, there is a strong business case
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for responsible tourism: “tourists are increasingly showing a preference for products and
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suppliers that demonstrate good social and environmental performance. By improving its
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performance in these areas, a tour operator can enhance its reputation and recognition in the
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marketplace as a responsible operator” (p. 4). Thus, an understanding of the factors that
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determine loyalty towards responsible tourism operators has theoretical and practical
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significance. In addition to advancing the PCI literature in the context of tourism, the present
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study contributes to the literature on image measurement and to place image research, an area
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that has been challenged by lack of breadth (Elliot & Papadopoulos, 2016; Elliot, Papadopoulos,
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& Szamosi, 2013). Moreover, the findings provide responsible tourism operators with the type of
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information that is critical to the development and marketing of their products by answering a
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critical research question in the Indian context: What factors impact travelers’ loyalty towards
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their responsible tourism operator?
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2. Literature review 2.1. Responsible tourism The idea of responsible tourism can be charted back to the Manila Conference on
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World Tourism organized by the United Nations World Tourism Organization (UNWTO) in
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1980 (Goodwin, 2011). Following nearly three decades of intermittent progress in our
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understanding of responsible tourism, there has been a resurgence of research interest in the idea
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that “tourism-related actors can develop a sense of ethical and moral responsibility that has
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resonance beyond self-interest, and that there is at least a possibility that this could change
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behaviours and contribute to more sustainable development” (Bramwell, Lane, McCabe,
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Mosedale, & Scarles, 2008, p. 253). While the nomenclature surrounding responsibility and
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sustainability is often used interchangeably, it is not the purpose of the present study to delve
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into definitional and conceptual issues surrounding the phenomenon of responsible tourism. Thus,
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the authors adopt a broad conceptualization of responsible tourism as the practice-oriented
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manifestation of the concept of sustainable development (Mihalic, 2016), and examine tourism-
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related actors that self-identify as adhering to the principles of responsible tourism development.
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For suppliers, responsible tourism management is a strategic business decision: it has
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been shown to result in increased brand and company reputation, improved staff morale and
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retention, and a higher return on investment (Leslie, 2012). Moreover, the business case for
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responsible tourism is anchored in demand-side trends in international tourism which indicate
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that “consumers are increasingly looking for products and services that reflect their own values
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and provide a ‘feel good’ emotion by indirect support of the environment and society” (Frey &
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George, 2008, p. 111). Thus, there remains the need to understand the phenomenon of
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responsible tourism at the level of the business (Bramwell et al., 2008; Goodwin, 2011;
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Pomering, Noble, & Johnson, 2012). One particular type of business that occupies a unique
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position in the supply side of responsible tourism is the tour operator. According to Wearing &
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Mcdonald (2002) the tour operator plays a critical role as an intermediary in the responsible
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development of tourism, particularly in less developed countries, by harmonizing inequitable
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power relations in the tourism system and thus more effectively using tourism as a tool for
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poverty reduction (Erskine & Meyer, 2012). Thus, the practice of responsible tourism has
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manifested primarily in the context of less developed countries (Brown & Hall, 2008). Given this
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push for more responsible forms of tourism development in the developing world, India provides
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the canvas for our examination of the factors that contribute to the formation of loyalty at the
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level of the tour operator. The problems inherent in India’s political ecology and the limitations
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of governmental and non-governmental organization solutions to the country’s development
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challenges highlight the critical role of businesses in the supply side in effecting responsible
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tourism (Allen, Bhatt, Ganesh, & Kulkarni, 2012). The authors use a highly relevant framework
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from the literature on branding, consumer behavior, and international business to facilitate this
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examination: Product-Country Image (PCI).
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2.2. Product-country image (PCI)
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The literature concerning PCI provides the underlying model of consumer behavior used
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to understand the notion of brand loyalty in responsible tourism. The first empirical study in the
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domain of PCI was conducted by Schooler (1965), who found that the national origin of a
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product might have an influence on customer evaluations of that product: this proposition was
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subsequently referred to as the country of origin (COO) effect (Samiee, Leonidou, Aykol,
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Stöttinger, & Christodoulides, 2016). Following this study, research on topic proliferated and
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took various directions. For example, early research on the topic perceived COO as an
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information cue that consumers consider in the information search, evaluation of alternatives,
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and purchase decision stages of the purchase funnel (e.g. Ahmed & d′Astous, 1993; Steenkamp,
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1990), while later scholars examined the direct and moderating effects of demographic and/ or
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psychographic characteristics of consumers on the COO effect (e.g. Balabanis &
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Diamantopoulos, 2004; Leonidou, Hadjimarcou, Kaleka, & Stamenova, 1999). Another stream
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of research drew a distinction between COO and country of manufacture, country of assembly,
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and country of design (e.g. Chao, 1993; Verlegh & Steenkamp, 1999), while a fourth stream of
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research dissected the concept of country image into various components such as cognitive,
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affective, and conative (e.g. Laroche, Papadopoulos, Heslop, & Mourali, 2005), or macro and
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micro country images (e.g. Pappu, Quester, & Cooksey, 2007). While these streams of research
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collectively form the foundational platform for PCI studies, more recent empirical evidence has
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identified that the COO effect on consumer evaluations is moderated by product category (e.g.
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Ahmed et al., 2004; Andéhn, Nordin, & Nilsson, 2016; Mützel & Kilian, 2016). With this
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recognition, the present study uses the PCI framework to examine the factors that contribute to
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the formation of loyalty in the category of responsible tourism.
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While the concept of Tourism Destination Image (TDI) has been extensively examined in
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the field of tourism, the use of PCI in tourism has been a more recent phenomenon, following a
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recognition that developments in PCI can contribute significantly to place image theory (Nadeau,
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Heslop, & Luk, 2008). In one of the earliest attempts to bring these two streams together,
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Mossberg and Kleppe (2005) draw a parallel between country and product image constructs and
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destination images at different geographical units. In more recent studies, Stepchenkova (2015)
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and Zhang, Wu, Morrison, Tseng, and Chen (2016) found that country image affects destination
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image, which subsequently affects tourists’ visitor intentions or evaluations of their destination
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experience. In this regard, the work of Elliott, Papadopoulos, and colleagues (Elliot &
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Papadopoulos, 2016; Elliot, Papadopoulos, & Kim, 2011; Elliot et al., 2013) is notable in its
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efforts to create more integrative models that advance place image theory by combining PCI and
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TDI . The present study adds to this limited body of knowledge in the context of responsible
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tourism.
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2.3. PCI and responsible tourism loyalty
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The central proposition of the PCI framework is that the image of a brand/product is
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impacted by the image of the country from which the brand/product originates. German cars
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provide an example. Since Germany is a country well known for its automotive technology, one
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can hypothesize on the basis of the PCI literature that the image of a car made by a German
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manufacturer, like Audi, is positively impacted by the country’s favorable image pertaining to its
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automotive technology. Then such favorable brand/product image would result in a favorable
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consumer attitude and/or behavioral outcome for the brand. The underlying rationale for the
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model is captured in Figure 1.
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Fig.1. Product-Country Image (PCI) Framework
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While Figure 1 reflects the theoretical framework of the present study, the relationships
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between the constructs of country image, brand/product image, and consumer attitude/behavior
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are more nuanced. These must be developed in the present context of responsible tourism, based
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on the relationships that have been previously established in the literatures on PCI and tourism.
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Before expanding on these relationships, one should note that the authors will not differentiate
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between the constructs of brand and product image and will use the two terms interchangeably to
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refer to the image of the responsible tourism operator. While differentiating between the
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constructs of brand and product image may be useful in the examination of conventional
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products (for example, Toyota is the brand with several products such as the Camry, Corolla,
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Yaris, Land Cruiser, etc.), the responsible tourism operators examined in the present study are
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relatively small in size and product variation exists only at the level of the different itineraries
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that they offer. The brand is a more realistic level at which their image can be meaningfully
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captured. Moreover, such usage is consistent with research in the domain of PCI and more
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relevant to the present context of responsible tourism operators. As highlighted by Elliott (2004) ,
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one of the challenges towards more sustainable consumption lies in consumers’ inability to
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verify a company’s ethical claims, due to which their confidence in the brand has “far more 7
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impact in the long term than promoting individual products” (p. 21). Thus the brand represents
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the most meaningful level at which to examine the dynamics of loyalty in the context of
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responsible tourism. The relationships identified in the PCI literature pertaining to the construct
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of product image, and those pertaining to destination image and destination loyalty in the tourism
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literature, will be extrapolated to the level of the brand.
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2.3.1. Relationship between country image and cognitive brand image
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The country image-brand image dyad has been explained using two theoretical
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perspectives in the PCI literature: the halo effect view (Bilkey & Nes, 1982) and the summary
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effect view (Johansson, 1989). According to Bilked and Nes (1982), people generally use
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country image as a halo to infer the quality of the attributes of unfamiliar foreign products.
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Consequently, country-of-origin affects product beliefs: perceptions of the attributes of products
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from a country, such as reliability, workmanship, product quality etc. The summary effect view
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also establishes the impact of country image on product beliefs in conditions of low and high
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familiarity. Both views have conclusively established that country image impacts consumers’
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cognitive image of a brand/product. This relationship is fundamental to the PCI research
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endeavor and thus forms the basis for the first hypothesis of the present study. However, given
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Martínez and Alvarez's (2010) suggestion to account for the distinction between the generic
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image of a country and that of the country as a tourism destination, the present study
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conceptualizes country image as a global measure of India’s image as a tourism destination.
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Moreover, since the objective of the study is to understand consumer loyalty towards the
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operator and not the country, a breakdown of the construct of country image into its various
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components, such as cognitive, affective, and conative (Laroche et al., 2005), was considered
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unnecessary. A global measure of country image (as a tourism destination) keeps the resulting
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model parsimonious, interpretable, and practically useful.
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Based on the PCI literature, the authors propose the following relationship between the
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constructs of country image and cognitive brand image in the context of responsible tourism
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operators:
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H1: A favorable image of the country as a tourism destination has a positive impact on the cognitive brand image of the responsible tourism operator.
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2.3.2. Relationship between cognitive brand image and affective brand image To the present authors’ knowledge, the affective component of brand/product image has
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not been explicitly discussed or measured in the domain of PCI; however, the cognitive—
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affective sequence is implied by the PCI literature and must be examined separately. Thus, for
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the present study, the construct representing the responsible tourism operator’s brand image is
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separated into its cognitive and affective components. This deconstruction delivers two
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advantages. First, since the objective of the study is to understand consumer loyalty towards
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responsible tourism operators based on the PCI model presented in Figure 1, isolating the distinct
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impact of these components on the construct of loyalty is critical to providing specific, action-
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oriented information to these operators. Second, the research that has been conducted at the level
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of the destination, and which the present study draws on for the development of hypotheses, has
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most often separated these two components. According to San Martın and Rodrı´guez del
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Bosque (2008), the cognitive-affective sequencing of destination image is consistent with
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Russell's (1980) original circumplex model of affect in which he stated: “the way in which
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something is responded to emotionally depends on how it is perceived and cognized” (p. 314). In
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the context of foreign tourists visiting the Angkor temple area of Cambodia, Chen and Phou
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(2013) established the cognitive-affective sequence, which has also been suggested by Bagozzi's
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(1992) reformulation of attitude theory. Back (2005) and Back and Parks (2003) established the
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cognitive-affective sequence in the context of the brand loyalty in the lodging industry.
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Moreover, research in the domains of branding (e.g. Silva & Alwi, 2006) and consumer behavior
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(e.g. Anand, Holbrook, & Stephens, 1988) supports the cognitive-affective sequencing of brand
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image. Thus, the authors hypothesize:
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H2: A favorable cognitive brand image of the responsible tourism operator has a positive impact on the affective brand image of the operator.
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2.3.3. Relationship between brand image and attitudinal loyalty
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The relationship between the constructs of brand image and loyalty is derived from the
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literature concerning destination and product loyalty in the field of tourism. The concept of
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loyalty has been conceptualized and measured in three ways: based on the attitudinal approach,
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the behavioral approach, and the composite approach (Li, Cai, Lehto, & Huang, 2010). The
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present study employs the composite approach to loyalty, which suggests an integration of both
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attitude and behavior in the conceptualization and measurement of loyalty (Zhang, Fu, Cai, & Lu,
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2014).
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In their study of Malaysian travelers, Chew & Jahari (2014) found that both the cognitive
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and affective destination images of Japan impacted travelers’ attitudinal loyalty i.e. their revisit
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intentions to post-disaster Japan. Similarly, in a meta-analysis of destination image and tourist
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loyalty, Zhang et al. (2014) established that both cognitive and affective dimensions of image
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impacted the concept of attitudinal loyalty. While such studies have confirmed the impact of
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both cognitive and affective image on attitudinal loyalty, other research has established the
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impact of one (e.g. cognitive – Bigne Alcaniz, Sanchez Garcia, & Sanz Blas, 2009; Um, Chon, &
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Ro, 2006) or the other (e.g. affective – Huang & Hsu, 2009; Li et al., 2010) dimension on tourists’
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attitudinal loyalty to the destination. These relationships between the cognitive and affective
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dimensions of image and attitudinal loyalty have also been established in the branding and
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consumer behavior literatures (Alwi & Kitchen, 2014; Chaudhuri & Holbrook, 2001; Martinez,
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Montaner, & Pina, 2009; Park, Stoel, & Lennon, 2008). Thus, the authors propose the following
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relationships between the two constructs of brand image and attitudinal brand loyalty:
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H3: A favorable cognitive brand image of the responsible tourism operator has a positive impact on tourists’ attitudinal loyalty towards the operator. H4: A favorable affective brand image of the responsible tourism operator has a positive impact on tourists’ attitudinal loyalty towards the operator.
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2.3.4. Relationship between attitudinal loyalty and behavioral loyalty Baloglu (2002) emphasized the importance of using both attitudinal and behavioral
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measures i.e. the composite approach to loyalty: “marketers who are interested in determining
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whether their frequent guests are truly loyal must assess both their guests’ attitudes and their
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actions” (p.47). Based on the two dimensions of attitude and behavior, he categorized slot club
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members of a gaming corporation into four loyalty archetypes, namely those who exhibited true,
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spurious, latent, or low loyalty. The truly loyal were more likely to recommend the casino to
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others. They also spent more time in the casino and used more ancillary services than the other
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groups, thereby generating more total revenue for the company. Han, Kim, and Kim (2011)
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found that the construct of attitudinal loyalty, measured by customers’ commitment and intention
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to revisit three specific upper-midscale hotels, positively impacted their behavioral loyalty,
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measured as customers’ frequency of visiting these hotels as compared to any other hotel in the
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previous 12 months. Similarly, Tanford (2013) found that hotel loyalty program members who
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exhibited higher levels of attitudinal loyalty also demonstrated higher levels of behavioral loyalty.
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These and other studies have suggested the need to use a composite approach to measuring
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loyalty, which is even intuitively more comprehensive and logical. Yet, most research in tourism
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has been restricted to the attitudinal approach (Prayag & Ryan, 2012). Moreover, that attitudinal
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loyalty influences behavioral loyalty has also been established in the branding and consumer
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behavior literatures (Baldinger & Rubinson, 1996; Bandyopadhyay & Martell, 2007; Dick &
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Basu, 1994). Thus, the authors hypothesized the following relationship between the two
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dimensions of composite loyalty:
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H5: Tourists’ attitudinal loyalty towards the responsible tourism operator has a positive impact on their behavioral loyalty towards the operator.
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2.4. Role of travel motivation in a model of brand loyalty In addition to the relationships derived from the PCI and tourism literatures, one must
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acknowledge the impact of the construct of motivation on the country image, brand image, and
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consumer attitude/behavior triad represented in Figure 1. While researchers identify two types of
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motivation—push and pull—the literature has clearly established relationships between push
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motivations and the cognitive and affective dimensions of image. For example, Baloglu (2000)
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found that the cognitive image of Turkey was impacted by visitors’ socio-psychological push
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motivations of escape/relaxation, knowledge-seeking, and prestige. Similarly, Beerli and Martin
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(2004) found that the push motivations of relaxation and knowledge seeking had a significant
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impact on the affective dimension of image for both first-time and repeat visitors to Lanzarote,
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Spain. Li et al. (2010) found that the push motivations of intellectual gratification, belonging,
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and escape had varying impacts on both the cognitive and affective images of Harrison County
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in Indiana. While this relationship between motivation and image is fairly unique to the tourism
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domain, the literature on branding recognizes that “the associations that make up brand image….
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can be the result of both external and internal stimuli to each individual” (Martinez & Pina, 2003,
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p. 433). These stimuli can include the benefits provided to the customer, and thus motivations for
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purchase, which can subsequently elicit favorable brand image associations (Ataman & Ulengin,
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2003). Thus, the motivation-image relationship holds conceptual and empirical validity in the
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branding literature, whereby connecting customer motivations to the core benefits provided by
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the brand results in favorable brand image perceptions (Bauer, Stokburger-Sauer, & Exler, 2008;
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Nandan, 2005). This motivation-image relationship is based on Lazarus’ motivational-relational
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theory, which suggests that external and internal cues, such as those pertaining to the cognitive
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and affective dimensions of behavior formation, must be appraised in terms of an individual’s
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experience and goals, such as one’s motivations (Bigne, Andreu, & Gnoth, 2005). Thus, based
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on existing evidence (Beerli & Martin, 2004; Li et al., 2010; Suárez, 2011), the authors
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hypothesize the following relationships between push motivation and the two constructs of brand
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image in the context of responsible tourism operators:
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H6: The more the traveler is pushed towards responsible tourism, the more favorable the cognitive brand image of the operator with whom they travel. H7: The more the traveler is pushed towards responsible tourism, the more favorable the affective brand image of the operator with whom they travel.
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Based on the seven hypotheses proposed in present study, the authors derived the
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structural model of brand loyalty in responsible tourism presented in Figure 2. The model
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accommodates the deconstruction of brand image and loyalty from Figure 1 (as suggested by H1
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to H5) and the two additional hypotheses pertaining to travel motivation (H6 and H7). These
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hypotheses are grounded in the literature pertaining to branding, consumer behavior, and
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international business, and the extensive work concerning the concepts of destination image and
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destination loyalty in tourism.
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Fig.2. Hypothesized Model of Loyalty towards Responsible Tourism Operators
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3. Methodology
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3.1. Data collection
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An online survey was used to collect responses from travelers who had used one of five
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companies in India that identify themselves as responsible tourism operators: The Blue Yonder
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(TBY), Grassroutes, Help Tourism, Grass Routes (Orissa), and Kipepeo. These operators were
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selected based on a purposive sampling approach, given the challenges in specifying, identifying,
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1
and accessing the population of responsible tourism operators in India. However, collectively,
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the operators represent the breadth of responsible tourism operators in the country, both in
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geographical scope and product offerings, as evidenced in their profiles presented in Appendix A.
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It is important to highlight that many of the experiences offered by these responsible tourism
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operators are ostensibly similar to those offered by a “regular” tour operator. However, these
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operators function within a paradigm—a way of conducting business—in which responsibility
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towards the destination’s ecology, culture, and its communities take precedence. The lead
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authors’ personal experiences of on-site fieldwork with two of these operators as part of a larger
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research into responsible tourism attest to their self-identification as responsible tourism
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operators. A total of 1693 survey invitations were sent to travelers in the operators’ databases. 262
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people completed the survey, representing a response rate of 15.48%, which is consistent with
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the response rates for Internet-based surveys in tourism and hospitality (Hung & Law, 2011). For
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a model with 5 latent variables and 18 observed variables [anticipated effect size = .3; statistical
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power level = .8; α = .05], a minimum sample size of 150 is required to detect the specified
16
effect, while a minimum sample size of 128 is required given the structural complexity of the
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model (Soper, 2017). In this regard, the present study’s sample size is 175 percent of the
18
minimum sample size needed for hypothesis testing (262/150), indicating its sampling adequacy.
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3.2. Measurement of constructs The constructs examined in the present study (Figure 2) were operationalized using a
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combination of scales found in the existing literature. These items are presented in Table 2. All
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constructs were measured using multiple items, except behavioral loyalty, which was measured
15
1
as the number of times respondents had traveled with a particular operator. In addition to the
2
items used to measure the various constructs in the model, respondents were also provided an
3
opportunity to share open-ended comments about their experience with their responsible tourism
4
operator.
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3.3. Data analysis Given the main objective of the present study—to develop a model of tourists’ loyalty
8
towards responsible tourism operators—the Structural Equation Modeling (SEM) procedure was
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considered appropriate. The authors employed the two-step approach to SEM using AMOS 21.
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Confirmatory Factor Analysis (CFA) was conducted to estimate a measurement model, and was
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followed by the estimation of the structural model that combines these constructs.
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4. Results Table 1 presents the profile of the final sample.
Table 1 Respondent profile. Frequency Percentagea n = 262 Gender Male Female Education High School Graduate/University Degree Postgraduate Degree PhD/Doctoral Other Nationality Domestic (Indian)
124 132
47.3 50.4
7 97 130 15 6
2.7 37.0 49.6 5.7 2.3
156
59.5 16
International Income (Domestic Travelers) Less than INR 100,000 INR 100,000 - 199,999 INR 200,000 - 499,999 INR 500,000 - 999,999 INR 1,000,000 - 1,499,999 INR 1,500,000 - 1,999,999 INR 2,000,000 or above Income (International Travelers) US$15,000 - US$29,999 US$30,000 - US$44,999 US$45,000 - US$59,999 US$60,000 - US$74,999 US$75,000 - US$89,999 US$90,000 or above Information Source Word of Mouth Internet Know Founder Facebook
97
37.1
8 7 22 47 16 8 36
3.1 2.7 8.4 17.9 6.1 3.1 13.7
6 13 15 14 8 38
2.3 5.0 5.7 5.3 3.1 14.5
94 68 12 18
35.8 25.9 4.6
30
6.9 11.5
Length of Stayb Under 5 days 6 to 10 days 11 to 15 days 16 to 20 days More than 20 days
126 68 30 5 16
48.1 25.2 11.5 1.9 6.1
Travel withb Travel with friends Spouse Alone Other Family with children under 12 Family with children of several ages
122 69 46 43 25 5
Other
Age in years (Mean) Number of Domestic Holidays in past 5 years (Mean)
46.6 26.3 17.6 16.4 9.5 1.9 37.23 (SD = 12.52) 12.40 (SD = 16.57) 17
Number of International Holidays in past 5 years (Mean)
4.14 (SD = 5.42)
a
1 2 3 4 5
Calculated based on a sample size of 262. Percentages in a category may not add to 100 due to rounding, missing values, and/or multiple choice questions where respondents could select more than one option. b Multiple choice question to account for the same and multiple trips.
6
The sample was split evenly by gender and comprised of respondents who were highly
7
educated; 97.3% of them had at least an undergraduate degree. The majority of the sample was
8
domestic i.e. Indian respondents (59.5%) and mainly earned an annual household income of
9
between INR 500,000 (approx. US$7460) and INR 999,999 (approx. US$14,920) or more than
10
INR 2,000,000 per year (approx. US$29,840). Two-thirds of international tourists were from the
11
United States, the United Kingdom, and Germany and had a higher relative income; 14.5%
12
indicated they earned at least US$90,000. Most visitors (61.7%) had heard about their operator
13
through Word-of-Mouth (WOM) from a friend, relative, or someone else, or through the Internet.
14
Nearly half of the respondents traveled with their friends (46.6%), while more than a quarter
15
(26.3%) traveled with their spouses. Respondents to the present survey were fairly well traveled,
16
having taken an average of around 12 domestic and 4 international holidays in the past 5 years.
17
While nearly half of the respondents traveled with their responsible tourism operator for less than
18
5 days (48.1%), a significant proportion also had traveled for between 6 to 10 days (25.2%).
19
Table 2 presents the summary statistics for the items used to measure the various
20
constructs of the model. It also indicates the literature sources from which these measures were
21
adapted.
18
1 2
Table 2 Summary statistics and literature sources. Constructs and Measurement Items
Sample Size (n = 262) Mean SD
Adapted from
Push Motivation (Responsibility)a I want to make a positive economic contribution to the community through my trip I want to give something back to the community through my trip I believe that my trip would have a positive impact on the social, economic and natural environment of the destination and the community Country Imageb In general, your opinion of India as a travel destination is (1 - Very Negative to 5 – Very Positive) In general, your opinion of India as a travel destination is (1 - Highly Unfavorable to 5 – Highly Favorable) India has a good overall image as a travel destination (1 – Strongly Disagree to 5 – Strongly Agree) Cognitive Brand Imagea [Name of operator] provides good customer service [Name of operator] provides a reliable travel product [Name of operator] provides a good quality travel product [Name of operator] provides good value for money Affective Brand Imagec Gloomy(1)—Exciting(5) Unpleasant(1)—Pleasant(5) Sleepy(1)—Arousing(5) Distressing(1)—Relaxing(5) Attitudinal Loyaltyd Would you recommend [Name of Operator] to your friends/relatives? Would you say positive things about [Name of Operator] to other people? How likely is it that you will make another trip with [Name of Operator]?
4.07
.88
(Mody, Day, Sydnor, Jaffe, & Lehto, 2014)
4.06
.90
3.98
.99
4.44
.72
4.34
.69
3.81
.90
4.32
.78
4.26
.78
4.22
.68
4.21
.78
4.48 4.51 4.24 4.24
.64 .70 .71 .78
(Chew & Jahari, 2014; Russell & Pratt, 1980; Suárez, 2011)
4.65
.64
4.62
.71
(Seddighi & Theocharous, 2002; Yoon & Uysal, 2005)
4.05
.94
(Baloglu & Mccleary, 1999; Beerli & Martin, 2004; Bigne et al., 2005; Martínez & Alvarez, 2010)
(Coulter, 2002; Heung & Zhu, 2005; Hui & Wan, 2005)
19
1 2 3 4 5 6
Behavioral Loyalty How many times have you traveled with 1.10 1.32 (Lee, Kyle, & Scott, [Name of Operator] before? (Open-ended 2012;Lee & Shen, question) 2013) a Measured on a 5 point Likert scale, where 1 = Strongly Disagree and 5 = Strongly Agree b Measured on a 5 point Likert scale c Measured on a 5 point semantic differential scale d Measured on a 5 point Likert scale, where 1 = Very Unlikely and 5 = Very Likely
The results of the CFA are presented in Table 3. The chi-square test for the measurement
7
model was significant (χ2 = 193.39; p < .001), indicating a poor fit. However, chi-square
8
statistical results tend to be significant in large sample sizes and complex models. The other
9
widely used fit indices indicated an acceptable fit of the model to the data (χ2/DF = 1.598; IFI
10
= .958; CFI = .957; SRMR = .06; RMSEA = .059). The scales indicated high reliability—
11
Cronbach’s α ranged from .74 to .92, above Nunnally and Bernstein's (1994) recommended
12
threshold of .70. The authors also checked for the validity of the CFA model. All items loaded on
13
to their respective constructs with high and significant (p < .001) standardized factor loadings
14
that ranged from .679 to .940 (Table 3), indicating convergent validity. The AVE for each
15
construct was higher than .50, further demonstrating convergent validity, while the square root of
16
the AVE for each construct was greater than inter-construct correlations (Table 4), demonstrating
17
discriminant validity.
18 19 20
Table 3 CFA results. Constructs and Measurement Items Push Motivation (Responsibility) I want to make a positive economic contribution to the community through my trip I want to give something back to the community through my trip
Standardized Factor Loadings
Cronbach’s α
AVE
.85
.634
.867
.743
20
I believe that my trip would have a positive impact on the social, economic and natural environment of the destination and the community Country Image In general, your opinion of India as a travel destination is (1 – Very Negative to 5 – Very Positive) In general, your opinion of India as a travel destination is (1 – Highly Unfavorable to 5 – Highly Favorable) India has a good overall image as a travel destination (1 – Strongly Disagree to 5 – Strongly Agree) Cognitive Brand Image [Name of operator] provides good customer service [Name of operator] provides a reliable travel product [Name of operator] provides a good quality travel product [Name of operator] provides good value for money Affective Brand Image Gloomy(1)—Exciting(5) Unpleasant(1)—Pleasant(5) Sleepy(1)—Arousing(5) Distressing(1)—Relaxing(5) Attitudinal Loyalty Would you recommend [Name of Operator] to your friends/relatives? Would you say positive things about [Name of Operator] to other people? How likely is it that you will make another trip with [Name of Operator]? Behavioral Loyalty How many times have you traveled with [Name of Operator] before? (Open-ended question)
.774
.74
.550
.92
.759
.79
.537
.82
.703
.878
.803
.679
.910 .908 .890 .771
.836 .803 .737 .731 .914 .940 .723
1.000
1 2 Table 4 3 Comparison of square root of AVE and inter-construct correlations. Cognitive Brand Image Cognitive Brand Image
Push Motivation (Responsibility)
Country Image
Affective Brand Image
Attitudinal Loyalty
0.871 21
Push Motivation (Responsibility) Country Image Affective Brand Image Attitudinal Loyalty 1
0.215 0.208
0.796 0.213
0.742
0.660 0.559
0.310 0.200
0.160 0.077
0.733 0.520
0.838
Note: Square root of AVE is on the diagonal (in bold). Inter-construct correlations are on the off-diagonal.
2 3
Univariate skewness values for the variables ranged from -2.660 to 2.125, and kurtosis
4
values ranged from -.426 to 9.580. From a multivariate perspective, Mardia’s normalized
5
estimate of multivariate kurtosis was found to be 131.877, indicating significant positive kurtosis
6
and that the data are multivariate nonnormal. Thus, the authors used the bootstrapping procedure
7
with maximum likelihood estimation to address the issue of nonnormality (Bryne, 2010).
8 9
The hypothesized structural model resulted in the following measures of fit: χ2/DF = 1.648; IFI = .952; CFI = .951; SRMR = .069; RMSEA = .061. Given the use of the bootstrapping
10
procedure to address nonnormality in the data, the authors used the bias-corrected percentile
11
bootstrap intervals to test the significance of the estimates for the various structural relationships
12
in the model; this procedure is considered to yield the most accurate confidence intervals to test
13
for parameter significance (Bryne, 2010). All the relationships hypothesized in the structural
14
model—H1 to H7—were significant and are presented in Table 5. Moreover, not only does
15
cognitive image have a significant direct impact on attitudinal loyalty, but also it indirectly
16
facilitates attitudinal loyalty through positive affective outcomes [β (Cognitive Brand Image
17
Attitudinal Loyalty through Affective Brand Image) = .152; p = 049]. These findings point to the
18
criticality of the cognitive dimension of brand image in facilitating brand loyalty (Dick & Basu,
19
1994; Silva & Alwi, 2006).
20 21
Table 5 22
1
SEM results. Estimate
p-valuea
Country Image Cognitive Brand Image (H1)
.170
.063b
Cognitive Brand Image Affective Brand Image (H2)
.488
.007
Cognitive Brand Image Attitudinal Loyalty (H3)
.341
.010
Affective Brand Image Attitudinal Loyalty (H4)
.311
< .001
Attitudinal Loyalty Behavioral Loyalty (H5)
397
.009
.150
.012
.116
.036
Structural Path
Push Motivation (Responsibility) Cognitive Brand Image (H6) Push Motivation (Responsibility) Affective Brand Image (H7) 2 3 4
a
p-value based on bias-corrected percentile bootstrap intervals significant at p = .10
b
5
5. Discussion and Conclusion
6
5.1. Theoretical implications
7
The present study makes significant theoretical contributions to the modeling of brand
8
loyalty in the tourism literature, to the specific context of responsible tourism, and to the
9
literature on PCI. In view of McKercher et al.’s (2012) suggestion to rethink loyalty at different
10
tiers in the tourism system, the present authors sought to create a model of brand loyalty by
11
examining the antecedents of tourists’ loyalty towards responsible tourism operators in India.
12
The significant growth of responsible tourism necessitates a more comprehensive examination of
13
the demand side engagement with the phenomenon. Responsible tourist behavior is multifaceted
14
and complex, and businesses catering to these visitors must understand the various dimensions
15
and the degrees of these dimensions that underlie their behavior (Stanford, 2008). The present
16
study contributes to this endeavor. Moreover, the notion of loyalty is highly relevant in the
17
context of responsible tourism. The additional threat of greenwashing makes it more likely that
18
consumers’ reuse of the operator’s services will depend heavily upon their confidence in the 23
1
operator’s brand (Font & Epler Wood, 2007). The present study provides evidence to support
2
such an assertion, since it was found that travelers who have favorable perceptions of their
3
operator’s brand, in both cognitive and affective terms, were more likely to recommend and
4
reuse the operator. Moreover, this attitudinal support translated into repeat purchases for the
5
operator. These findings are consistent with the modeling of brand loyalty in the business
6
literature. For example, Dick and Basu’s (1994) framework for customer loyalty identifies
7
cognitive and affective antecedents of attitudinal loyalty, which subsequently fosters patronage
8
behavior. Similarly, our findings pertaining to the cognitive-affective sequence and the indirect
9
effect of cognitive image on attitudinal loyalty are consistent with Silva and Alwi’s (2006)
10
framework for customer loyalty in retail corporate branding, which in turn is grounded in De
11
Chernatony's (2002) brand triangle framework. Our findings thus “address a deeper
12
understanding of how consumers feel, think and act, which in effect will provide valuable
13
guidance to address brand management challenges” (Silva & Alwi, 2006, p. 297) by
14
understanding the nature of brand development in the context of responsible tourism operators.
15
Relatedly, in successfully developing and testing this model of brand loyalty in
16
responsible tourism, the authors successfully integrated two streams of literature pertaining to
17
branding, consumer behavior, and international business, and the extensive work concerning the
18
concepts of destination image and destination loyalty in tourism. As noted by Papadopoulos
19
(1993), traditional product and tourism image research are closely related and researchers could
20
profitably learn from advances in each other’s fields. For tourism operators, widely held country
21
images affect attitudes towards their products and services, thus impacting the pathways of
22
travelers’ engagement with them (Kotler & Gertner, 2002). Despite this recognition, empirical
23
research that adopts a more integrative approach to place-based marketing has been limited. By
24
1
incorporating the PCI framework in the present examination of brand loyalty in responsible
2
tourism, the authors demonstrate that “the broader conceptualization of country image can lead
3
to a greater understanding of touristic intentions” (Nadeau et al., 2008, p. 84), and “provide
4
empirical evidence of the need for place marketers to move toward greater integration between
5
product- and tourism-oriented place image campaigns” (Elliot, Papadopoulos, & Kim, 2011, p.
6
520). Moreover, while the PCI literature has traditionally included only cognitive brand/product
7
evaluation, the present context of tourism, and responsible tourism, necessitated the inclusion of
8
the affective component of brand image. In this regard, the present study extends the PCI
9
literature through its specific application in the tourism context. Future research using PCI in
10
different product categories would be well served not only by differentiating the construct of
11
country image into its cognitive, affective, and conative components (Laroche et al., 2005) but
12
also by examining the nuances of brand/product image evaluation as in the present study.
13 14 15
5.2. Practical implications The study’s findings have important implications for responsible tourism operators and
16
marketers in India. Operators wanting to build a loyal customer base must first attract those who
17
are predisposed towards more responsible forms of travel since their motivations have a
18
significant impact on their cognitive (β = .150; p = .012) and affective (β = .116; p = .036)
19
perceptions of the operator’s brand. More specifically, operators’ marketing messages must
20
target travelers’ responsibility-oriented push motivations. These messages must emphasize the
21
ability of the operators’ itineraries to provide travelers with the opportunity to have a positive
22
impact on the social, economic, and natural environment of the destinations and communities
23
they visit. Travelers must perceive that they are “giving something back” through their trip. For
25
1
example, The Blue Yonder provides its travelers with the opportunity to volunteer their skills
2
towards the rehabilitation of people with paraplegia, chronic psychiatric illness, prolonged
3
kidney diseases, and long term irreversible elements through an initiative called Footprints at
4
IIPM (the Institute of Palliative Medicine) (“Partnering palliative care movement,” 2010). Help
5
Tourism allows its visitors to experience the Sunderbans Jungle Camp, an initiative that supports
6
mangrove conservation and various social development programs and was a finalist of the World
7
Travel & Tourism Council’s 2007 Tourism for Tomorrow award (“Sunderbans Jungle Camp,”
8
n.d.). The development and communication of such initiatives will appeal to travelers’
9
responsibility-oriented push motivations, which will subsequently elicit favorable cognitive and
10
affective perceptions of the operator’s brand.
11
That consumers often “buy into” the concept of sustainability means that much of what
12
we need to know about their motivations for responsible travel is rooted in how that knowledge
13
and understanding of sustainability issues is created (Elliott, 2004). In this regard, Krantz and
14
Chong (2009) recommend that the effective marketing of responsible tourism products requires
15
operators to “generate word of mouth advertising by providing high value for money travel
16
experiences and delivering on promises” (p. 108). This recommendation was confirmed in the
17
present study by the positive impact of the cognitive image of the operator on its affective image
18
(β = .488; p = .007), on travelers’ attitudinal loyalty (β = .341; p = .010), and indirectly on
19
attitudinal loyalty through affective brand image (β = .152; p = .049). These findings highlight
20
that, while being inclined towards responsibility, travelers expect high levels of customer service
21
(mean = 4.32), reliability (mean = 4.26), high quality (mean = 4.22) and value for money (mean
22
= 4.21). Their inclinations to make a difference do not mean that they will accept inadequate care
23
as customers. Moreover, the criticality of the cognitive dimension of brand image in facilitating
26
1
brand loyalty (Dick & Basu, 1994; Silva & Alwi, 2006) means that operators of responsible
2
tourism must actively facilitate e-WOM by encouraging customers to talk about their positive
3
experiences on social media, particularly those pertaining to the high levels of customer service,
4
reliability, quality, and value for money provided by the operator. Operators must be proactive in
5
managing the conversation pertaining to their brands on social media, particularly on platforms
6
such as TripAdvisor that play a critical role in the customer’s travel decision making process
7
(Ayeh, Au, & Law, 2013). As a corollary, operators must follow best practice for addressing
8
both positive and negative conversation on social media platforms (Barsky & Frame, 2009), such
9
that they can maintain a favorable and coherent online brand image. That most visitors (61.7%)
10
had heard about their operator through WOM from a friend, relative, or someone else, or through
11
the Internet provides support to our suggestions.
12
The relationship between affective brand image and attitudinal loyalty (β = .311; p < .001)
13
emphasizes the need for responsible tourism operators to deliver experiences that are pleasant,
14
arousing, exciting, and relaxing. Also, only when operators have established high levels of
15
attitudinal loyalty among their travelers can they expect these individuals to travel with them
16
again, as revealed by the significant relationship between attitudinal and behavioral loyalty (β
17
= .397; p = .009). Two additional findings support the validity of this relationship. First, the
18
authors found a significant positive correlation between behavioral loyalty (previous travel) and
19
confirmed future trips (ρ= .373; p < .001). Second, nearly 36% of the travelers found out about
20
their operator through a friend, relative, or someone else. Also, nearly half of the sample traveled
21
with friends (46.6%), which was likely a result of the WOM effect. These findings indicate that
22
words (attitudes) do translate into action (behavior) in the context of responsible tourism
23
operators.
27
1
Finally, the positive relationship between the constructs of country image and cognitive
2
brand image (β = .170; p = .063) suggests the need for a better integration between the domestic
3
and international promotion of India as a tourism destination and that of its responsible tourism
4
product (Elliot et al., 2011). One of the Indian Ministry of Tourism’s key tourism product
5
development and marketing initiatives focuses on identifying, diversifying, developing, and
6
promoting niche products, which includes responsible tourism. Operators must take advantage of
7
efforts such as the Ministry’s Market Development Assistance (MDA) scheme, whose key
8
objective is to tap into the vast economic potential of domestic tourists by developing programs
9
that encourage them to visit unexploited tourist destinations (Annual Report 2015-16, n.d.). In
10
addition, the Ministry’s fourteen overseas marketing offices can play an important role in
11
positioning India as a preferred tourism destination for responsible tourism. The intensified
12
global competition for attracting tourism is particularly prevalent in the context of niche tourism
13
products such as responsible tourism. While the Internet-based economy has allowed niche
14
tourism providers to succeed by providing highly specialized services that are in high-value
15
demand, the levels of uncertainty, competition, and failure are also much higher for such
16
experience providers (Lew, 2008). This requires private firms and governments to re-evaluate
17
their strategies and focus attention on place equity and systematic marketing to weigh-in the
18
global arena with coordinated country-branding campaigns (Papadopoulos, 2004). In this regard,
19
the present study “presents a theoretical and practical model of how the development of a
20
country as a tourism destination brand creates leverage for its products and services in both
21
domestic and export markets” (Gnoth, 2002, p. 262). Appendix B provides evidence from open-
22
ended comments in support of each of the relationships validated in the model.
23
28
1 2
5.3. Limitations and future research The present study’s findings must be viewed in light of certain theoretical and empirical
3
limitations and considerations for future research. First, given the potential for systematically
4
different perceptions between Indian domestic and international travelers, one could argue that
5
modeling the loyalty of these two groups separately would avoid confounding the home country
6
and country of consumption effects that have been discussed in the PCI literature (Jaffe &
7
Nebenzahl, 2006). While sample size limitations precluded such modeling, particularly for the
8
international traveler sample (n = 97), the authors’ joint modeling of the domestic and
9
international traveler samples is consistent with existing research in the PCI domain that has
10
combined the evaluations of consumers from different countries and/or evaluations of
11
brands/products from different countries (e.g. Chung, Pysarchik, & Hwang, 2009; Wang, Li,
12
Barnes, & Ahn, 2012). Second, while the authors found a significant relationship between
13
travelers’ attitudinal and behavioral loyalty, indicating the potential for responsible tourism
14
operators to create truly loyal customers (Baloglu, 2002), one must acknowledge that there are
15
likely to be different segments of travelers that comprise these operators’ customer mixes (e.g. a
16
segment of travelers that is inherently more responsible than others); the relationships between
17
the various constructs in the model may vary across these segments (Castro, Martín Armario, &
18
Martín Ruiz, 2007). In such a case of market heterogeneity, extrapolation of the results to the
19
general travel population is somewhat tenuous. The authors suggest that future research
20
concerning the modeling of loyalty in responsible tourism should be based on larger and
21
potentially multi-country samples to capture the dynamics underlying different socio-
22
demographic and psychographic/behavioral segments of travelers.
29
1
Third, future research on modeling brand loyalty could also include other antecedents of
2
brand image formation, such as the sources of information to which individuals are exposed,
3
accumulated travel experience, and/or sociodemographic characteristics (Beerli & Martin, 2004;
4
Suárez, 2011). Relatedly, the role of satisfaction in effecting brand loyalty has been previously
5
explored (Back, 2005; Back & Parks, 2003; Oliver, 1999), and in the context of responsible
6
tourism (Krantz & Chong, 2009). Additionally, Dick and Basu’s (1994) framework for customer
7
loyalty identifies social norms and situational factors as potential moderators of the relationship
8
between attitudinal and behavioral loyalty. These various relationships can be explicitly modeled
9
in future research. Finally, while the hypotheses for the present study and the resulting structural
10
model have a solid theoretical and empirical foundation, the authors readily advance Martin and
11
Woodside's (2011) suggestion to move beyond conventional, deductive, and hypothesis-driven
12
methods to understand consumer loyalty in international tourism. Hendler and Latour (2008)
13
provide an example of an alternative approach in their use of the Zaltman Metaphor Elicitation
14
Technique (ZMET) to capture the deep meanings and emotions associated with tourists’ slot club
15
loyalty at a Las Vegas mega casino resort. According to the present authors, more inductive
16
approaches to theory construction that combine both emic and etic interpretations of visitor
17
experiences have much to add to our understanding of what is clearly a very complex domain of
18
consumer behavior.
30
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Appendix A. Profile of sampled responsible tourism operators
Founder(s)
The Blue Yonder
Grassroutes
Help Tourism
Grass Routes (Orissa)
Kipepeo
Gopinath Parayil (Gopi)
Inir Pinheiro
Asit Biswas
Claire Prest and Pulak Mohanty
Piran Elavia
Nature/Ecotourism, Heritage Tourism, Cultural Tourism, Tribal Tourism, Rural Tourism, Ethical Tourism,
Nature/Ecotourism, Cultural Tourism, Heritage Tourism, Adventure Tourism
Product categories/ holidays offered (as marketed on website)
Nature/Ecotourism, Cultural Tourism, Heritage Tourism, Adventure Tourism, Voluntourism
Nature/Ecotourism, Cultural Tourism, Rural Tourism,
Nature/Ecotourism, Cultural Tourism, Heritage Tourism, Adventure Tourism, Tribal Tourism
Destinations within India
States of Kerala, Orissa, Rajasthan, West Bengal, Sikkim, Himachal Pradesh, and the Union Territory of the Andaman and Nicobar Islands
Villages of Purushwadi, Valwanda, and Dehna in the state of Maharashtra
States of West Bengal, Arunachal Pradesh, Orissa, Sikkim, Assam, Meghalaya, Tripura, and Nagaland
State of Orissa
States of Assam, Sikkim, and Meghalaya
International destinations
Nepal, Bhutan, Sri Lanka, Bangladesh, and South Africa
N/A
Bhutan, Nepal, Tibet, and Bangladesh
N/A
N/A
Awards received (as mentioned on website)
4
N/A
15
N/A
N/A
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Appendix B. Respondent comments about their experience with responsible tourism operators (open-ended) Structural path
Country Image Cognitive Brand Image (H1)
Respondent comments I'd like to explain my ratings for recommending Blue Yonder. My friends are relatively experienced travelers (usually backpackers, like me). Regardless of whether they've been to India or not, the response is very strong positively or very strong negatively. Some like the adventure; others wouldn't dream of going. So when you ask me whether I'd recommend Blue Yonder, that's kind of like asking me if I'd recommend India. I would, but only to the select few that I think would go to India with an open mind and actually enjoy their experience (customer experience consultant, male, 31). I do not know how foreigners perceive India to be... There is so much to be experienced here culturally as well as in natural beauty even for us - people living here. India can offer so much diversity in terms of language & customs & religions. I always prefer going to unexplored and untouched destinations... places that are not commercial yet (creative manager, male, 35).
Cognitive Brand Image Affective Brand Image (H2)
Excellent experience. Very organized. All information sent on the email was accurate. They conducted the tour very well and with a lot of effort. Our guide was extremely professional and totally knew his job well. Very enthusiastic and jovial. The villagers were well trained by Grassroutes and I had a splendid time. I got much more than what I expected. I am planning my next weekend with them soon. I have recommended them to many people and will keep it going (photographer, male, 34).
Cognitive Brand Image Attitudinal Loyalty (H3)
I contacted Help Tourism via email, had a response immediately, and within an hour I'd booked the trip. Raj [pseudonym] and the others were fantastic to work with. Also, because we were traveling with a teenager who is a wheelchair user, Help Tourism went beyond what any of us expected to make the trip wheelchair accessible and exciting for our son and for all of us. They were wonderful to travel with. We continue to recommend them (social worker, male, 57).
Affective Brand Image Attitudinal Loyalty (H4)
From the moment the cycling guru, Anil Uchil, organized a bike ride to Purushwadi last year (which I missed) and described the fireflies phenomenon to us, I always wanted to visit this place to watch this annual spectacle. This year, deciding not to give this experience a miss, me and two of my friends went there with our families. The whole experience was one of no fuss pure earthy happiness. The kids really enjoyed monkeying around by eating mangoes sitting on a tree.. they were happiest for that liberty. The sheer amount of mangoes we ate, the tasty food served by our village hosts and the fresh cool breeze rejuvenating us boosted everyone’ s energy for more activities. And when night descended -- It was magical and surreal. Millions of fireflies lighting up the entire villages surrounding with their portable LED like lights. The glow sometimes had some strange patterns and frequencies - some flies glowing at some times and then SUDDENLY, as if by some communication, the entire million of them glowing together lighting up the mountain. Nobody except mother nature can put up such a mesmerizing light show like the one we witnessed. Lovely it was and elated was our feeling of having
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been witness to this. Be it the mountain trek or the village activities or any other needs, Ajay [pseudonym], our guide would be always around to help us and answer any queries. It was a great relaxing and bonding time for us friends and families. I look forward for another visit next year to keep my date with this annual spectacle. THREE CHEERS to Inir and his Grassroutes team (telecom services consultant, female, 42).
Attitudinal Loyalty Behavioral Loyalty (H5)
Push Motivation (Responsibility) Cognitive Brand Image (H6)
Both Sanjay [pseudonym] and our driver were delightful people to spend time with. Our trip was an incredible experience. I would heartily recommend Grass Routes to anyone wanting to experience India different than the usual tourist experience. It did not feel like a “tour” - more like a personal visit with local people. I plan to be back again (physician, female, 66). The best part of the experience was our guide Rajesh [pseudonym], you're survey doesn't include any info about the guide. He is an amazing, passionate, respected person who made our experience a truly once in a lifetime adventure. Without Rajesh, this holiday would have been just another holiday, because of him I will be back, volunteer, and spend my time/money traveling to NE India again (physical therapist, male, 36). I was looking for a travel company which contributes in improving the local communities, respects the local culture and aspires to introduce the travelers to off-beat destinations. Traveling with Help Tourism has been a pleasure and an eye-opener. My expectations from travel and responsibility towards the destinations that I have traveled to had a dramatic change (travel consultant, female, 48). Grassroutes believes in sustainable tourism, which is very important for me (journalist, male, 29). What attracted me most was the Blue Yonder’s endeavour to take up ‘responsible tourism’. I wanted to be able to contribute to such an effort (marketing consultant, female, 42).
Push Motivation (Responsibility) Affective Brand Image (H7)
I don't normally travel with tour companies. I did this time because I was travelling by myself (I'm female) and the distances were great in Kerala and too complicated to arrange buses. (I visited Tamil Nadu by myself with trains.) The Blue Yonder managed to do a custom, one-person booking for me. I started out in Kochi (one night), Periyar Wildlife Sanctuary (two nights at a cardamom plantation), and Alleppey (houseboat, one night). I'd never heard of this company before. One of Blue Yonder's team members did a "couch surfing" at my friend's house in the Netherlands; that's how I heard of the company and thought, if they do couch surfing, then that might be the company that fits into my type of travelling. I rarely stay in fancy hotels (or hotel chains) when I travel. The "finest" places I go to would be bed & breakfasts. It's not that I don't have the money; I'd rather spend my money on accommodations and on a trip that I can look back fondly on and say, "that was a good trip" or "that was a great experience" or "I met some really cool people along the way." Even if the experience was not "great", at least I can still remember it instead of some bland, cookie-cutter hotel! (consultant, female, 38).
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*Author Biography
Dr. Makarand Mody, an Assistant Professor of Hospitality Marketing at Boston University’s School of Hospitality Administration, graduated with his Ph.D. from Purdue University. He received his M.Sc in Human Resource Management for Tourism and Hospitality from the University of Strathclyde, and a Higher Diploma in Hospitality Management from IMI University Centre, Switzerland. Dr. Mody has worked in the hotel and airlines industries in the areas of learning and development and quality control. His research focuses on issues pertaining to the supply and demand of responsible tourism, the sharing economy, and the modeling of consumer behavioral pathways. Dr. Jonathon Day, an Associate Professor in Purdue’s School of Hospitality and Tourism Management, has over 20 years experience in destination management and governance. An award winning marketer, Dr. Day has worked with destinations marketing organizations in Australia, New Zealand and the United States. Dr. Day has a Bachelor of Business from Queensland University of Technology, an M.B.A from U.C.L.A.’s Anderson Graduate School of Management and a Ph.D. from James Cook University (Australia). Dr. Day’s research interests focus on strategic destination management and include issues of sustainability and competitiveness within the tourism system. Dr. Sandra Sydnor, an Associate Professor of Hospitality and Tourism Management, received her BS from Michigan State University (Engineering); her MBA from The University of Miami (FL); and her PhD in Hospitality Management from The Ohio State University. Dr. Sydnor has twenty years combined of QSR corporate and entrepreneurial experience; graduate and undergraduate teaching; and senior level experience in market research and advertising firms. Dr. Sydnor’s primary research interests include service and brand management; community and businesses resilience; and entrepreneurship.
Dr. Xinran Lehto is a Professor of Hospitality and Tourism Management at Purdue University. Prior to her academic appointments, Dr. Lehto spent 6 years working in the travel and tourism industry as a marketing executive in China and Singapore. Dr. Lehto’s research expertise area is tourism marketing. Her research addresses how destinations can effectively market experience-based vacation products to unique segments such as family travelers. Much of her work is concerned with developing understanding of how tourists interact with a destination through leisure and hospitality experiences, what outcomes and benefits tourism provides, and how personal, interpersonal and cultural factors influence destination marketing practices and visitor satisfaction. Dr. William Jaffe is an Associate Professor of Hospitality and Tourism Management at Purdue University. He received his BS from University of Wisconsin-Stout, his M.S. from Purdue University, and his PhD from Iowa State University (Professional Studies in Education). Dr. Jaffe has held management positions in the foodservice industry, and has contributed to several industry organizations and associations in the form of community service and funded grants. His research focuses on several aspects of foodservice, including employee satisfaction, effectiveness of purchasing systems, and waste management, as well as issues pertaining to student recruitment, advising, and learning in hospitality management programs.
*Author Photo (to accompany biography)
Dr. Makarand Mody
Dr. Jonathon Day
Dr. Sandra Sydnor
Dr. Xinran Lehto
Dr. William Jaffé
