Market Orientation as a Strategy for the Rural Tourism Sector

Abstract

The aim of the present work is to ascertain the importance of market orientation as a business strategy within the rural tourism sector. To this end, we took a business-to-customer (B2C) perspective. First, the adoption of market orientation was measured from the firm’s point of view. Second, tourist perceptions were analyzed using two variables, perceived value and behavioral intentions. The sample consisted of 100 rural tourism enterprises and 572 of their customers. The findings reveal that the market orientation undertaken by the firm has a direct effect on its outcomes (its financial results, the improvements to the rural destination, and the more personal, intangible impact on the owner-manager) and on perceived value; and that perceived value has a direct effect on consumers’ behavioral intentions toward the firm.

Keywords

rural tourism market orientation perceived value behavioral intentions outcomes multilevel analysis

Introduction

Rural tourism (RT) is an increasingly important diversification activity for the progress of rural destinations (Brandth and Haugen 2011). It is seen as a major asset for the European economy, and has been a key European Union objective since 1997 (European Council 2009). Although major expectations surround the development of RT, it has been identified that (1) greater efforts are required if RT is to contribute effectively to the progress of rural destinations (Brandth and Haugen 2011) and (2) European rural development policy is moving away from a protectionist stance, focusing more on the market and global competition (Ward and Lowe 2004).

This means that rural tourism enterprises (RTEs) must take strategic action that is focused on improving the competitiveness of the sector. One such possible strategy is that of market orientation (MO). MO involves permanently orientating the firm toward the systematic creation and delivery of superior value for its customers (Kohli and Jaworski 1990; Narver and Slater 1990). The MO approach can affect customers’ behavioral intentions¹ (BIs), which, in turn, can translate into better outcomes (Slater and Narver 1994). Hence a strategy of adopting MO can benefit both parties involved in the product exchange, namely customers and firms (Slater and Narver 1994).

These positive benefits have led to the development of numerous works in the literature that, taking the firm’s perspective, evaluate the effect of MO on consumer behavior and on the achievement of firms’ outcomes (Kirca, Jayachandran, and Bearden 2005). Nonetheless, there are aspects that require further attention in the literature, and that are essential for broadening the knowledge base in this area. One such aspect is the fact that evaluation of the positive effects of MO adoption requires a combined approach that takes into account perspectives of both the firm and its customers. This joint perspective can provide a more complete picture when evaluating whether MO constitutes a strategy that maximizes the value of the offer delivered to customers while helping to achieve improved performance on the part of the firm. A firm should be considered as market oriented only when its customers actually perceive it to be so, and thus the appropriate level of a firm’s MO stems from what its customers think it should be (Krepapa et al. 2003). Hence, to evaluate the effects of MO adoption on consumer behavior specifically in the RT context, as well as the RTE’s internal perspective on MO and its impact on outcomes, the tourist perspective also needs to be taken into account. From this, their perception and evaluation of the firm’s offer can be identified.

With the exception of the works of Deshpandé, Farley, and Webster (2000) and Steinman, Deshpandé, and Farley (2000) (works applied in an industrial context) and that of Barroso, Martín-Armario, and Sánchez (2005) (work applied in the retail banking sector, which measures the effect of a firm’s MO, based on its internal perspective, on service quality and satisfaction, based on the perspective of customers), the literature to date has not considered jointly the internal perspective of the firm together with that of its customers when evaluating the effect of MO adoption on consumer behavior.

Although the work of Barroso, Martín-Armario, and Sánchez (2005) makes an extremely valuable contribution, more extensive research into the effects of MO adoption on consumer behavior is necessary, in two directions in particular. First, the study of a firm’s actions (in this case, the adoption of MO) on consumer behavior requires the use of a dyadic business-to-customer (B2C) perspective, embracing both the firm and its customers. When using a B2C sample, it is important to bear in mind its hierarchical structure, which requires a multilevel analysis to be applied (Bryk and Raudenbush 1992). In the work of Barroso, Martín-Armario, and Sánchez (2005) a B2C sample is used but its hierarchical structure is not acknowledged, and nor is a multilevel methodology applied, which raises questions regarding the accuracy of the results (Heck and Thomas 2009, pp. 19-20).

Second, MO is considered to be a strategy capable of giving the firm a competitive advantage in so far as it contributes to generating improved BIs among customers (Slater and Narver 1994). It is therefore of interest to examine the actual mechanisms by which MO contributes to this improvement, considering as a key antecedent of BIs the variable “perceived value” (PV), from the customer’s own perspective.

Third, when examining the effect of MO on tourist behavior and outcomes, the specific characteristics of the RT sector need to be taken into account. For this purpose an MO adoption scale that has been adapted to reflect the particular capacities, resources, and aims of RTEs needs to be used. Similarly, a scale covering the particular outcomes that are of major importance to RTEs is required. In addition to financial results, the scale should include outcomes related to the rural destination itself (Simpson 2008), and outcomes that are less tangible in nature and linked personally to the owner-manager of the RTE (McCartan-Quinn and Carson 2003).

In light of the above, the aims of the present work focus on determining whether MO adoption constitutes a strategy of benefit to tourists (derived from their own perception of whether they are being presented with an offer of greater value) and to the RTEs (derived from the owner-manager’s perception of whether MO contributes to achieving improved tourist BIs and better outcomes), combining both perspectives and applying an appropriate multilevel methodology with a hierarchical structure. More specifically, the objectives of the present study are (1) to measure the RTE’s adoption of MO and the outcomes achieved from RT activity, from the firm’s internal perspective; (2) to measure the tourist BIs achieved using the variable PV—a key antecedent of BIs—from the tourist’s perspective; and (3) to propose a model that determines the effects of MO adoption on the RTE’s performance, examining the effect of MO adoption on outcomes and on the formation process of tourists’ BIs, using the antecedent PV.

The study is of interest for the field given that despite the extensive body of works on MO adoption, it corroborates the effect of MO on both the firm and its consumers, drawing on the perspectives of each. Furthermore, the work demonstrates the peculiarities of MO application in the RT sector (Figure 1).

Figure 1.

Conceptual framework

Theoretical Background

The RT Sector

RT development must be approached from an integrated perspective along with conservation of the rural destination (Hwang, Stewart, and Dong-wan, forthcoming) It is seen as an agent for rural economic regeneration and as a way of raising the value of conservation (Lane 2009). This is an important issue because of the role rural destinations play in many nations as repositories of both natural and historical heritage.

The progress of RT has been possible thanks to the endeavors of various public bodies, implementing ambitious large-scale projects geared toward achieving sustainable development and social well-being (Barke 2004), and to the growth in private initiative based on diversification into RT (Hall 2004). The latter factor has enabled local populations to benefit from the development of RT and integrate it into their daily lives (Simpson 2008).

To achieve these outcomes, members of the local community need to become entrepreneurs. Often, undertaking this entrepreneurial activity means retraining in an entirely new role, that is, in business management within the tourism market (Hernández-Maestro, Muñoz-Gallego, and Santos-Requejo 2009). This situation demonstrates the need for actions to be proposed that can facilitate the progress of RTEs. This constitutes the sphere of study of the present work, which proposes the adoption of MO as a competitive strategy for RTEs that can provide a competitive advantage, contributing to the delivery of an offer of greater value in the market and the generation of improved tourist BIs and better outcomes (Slater and Narver 1994).

MO in the RT Sector: Its Effect on Tourist Behavior and RTEs’ Outcomes

As the philosophical foundation of MO, the marketing concept serves as the primary justification for the preeminent role of customers in the planning and execution of market strategies (Jaworski and Kohli 1993). The literature mainly considers the concept of MO from two perspectives: (1) a cultural perspective, which conceptualizes MO as part of an organizational culture that systematically and continually focuses its efforts on delivering superior value for its customers (Narver and Slater 1990), as outlined in the proposed “MKTOR” MO model (Slater and Narver 1993); and (2) a behavioral perspective, which conceptualizes MO in terms of specific organizational behaviors. For example, Kohli and Jaworski (1990) defined MO as the organization-wide generation of market intelligence pertaining to current and future customer needs, dissemination of the intelligence across departments, and organization-wide responsiveness to it.

As regards the application of MO in the context of RTEs, it is worth noting that there are only a few studies, the majority of them recent, that address the subject of MO in firms with a profile similar to that of RTEs; hence more in-depth knowledge needs to be developed regarding MO and its consequences when applied in a context similar to that of RTEs. By way of example of the works that do exist, Table 1 outlines those that apply MO adoption in smaller-sized companies. Among these studies is the work of Polo-Peña, Frías-Jamilena, and Rodríguez-Molina (2012) that does validate a scale of MO adoption specifically for RTEs.

Table 1.

Literature Review^a

Firm Size	Study	Sector	Geographic Area
Small	Pelham and Wilson (1996)	Industrial	United States
	Martín-Armario, Ruíz and Martín-Armario (2008)	Multisector (exporters)	Spain
	Li et al. (2008)	Multisector	China
	Martin, Martin, and Minnillo (2009)	Industrial (with exception of 2 businesses in the consumer sector)	United States
Small and micro	Blankson and Cheng (2005)	Multisector (owner-managed)	United States
	Kara, Spillan, and Deshields (2005)	Services	United States
	Blankson, Motwani, and Levenburg (2006)	Multisector	United States
	Altinay (2010)	Services (Ethnic hospitality firms)	United Kingdom
	Polo-Peña, Frías-Jamilena, and Rodríguez-Molina (2012)	Rural tourism	Spain
Micro	Blankson and Omar (2002)	Service	United Kingdom (Caribbean and African origin)

Source: Own elaboration.

Adoption of market orientation in small and micro businesses.

The literature offers arguments both from the demand-side and the supply-side perspective to support the fundamental premise that MO adoption constitutes a valid strategy for firms seeking to improve their performance. On the demand side, firms that adopt MO appreciate the relevance of using market information in the formulation of their strategies. Using market information increases the firm’s ability to develop responses to the market that better meet the current needs and wants of customers, and to anticipate their future needs and wants (Kohli and Jaworski 1990; Narver and Slater 1990). Therefore, those firms that adopt an MO approach will be focused on the creation and delivery of superior value for their customers, and this should ultimately be perceived and valued by customers, generating improved BIs toward the firm (Slater and Narver 1994; Steinman, Deshpandé, and Farley 2000).

On the supply side, it can be said that MO is a capability and the principal cultural foundation of learning organizations (Deshpandé and Farley 1998; Slater and Narver 1995). Through constant acquisition of information regarding customers and competition, and the sharing of this information internally, market-oriented firms are well positioned to develop an “organizational memory,” a key ingredient for developing a learning organization.

Furthermore, the implementation of MO encourages a culture of experimentation and a focus on continuously improving the firm’s processes and systems. This implies that developing and improving a firm’s MO may make its capabilities become more distinctive in the sector, and this, in turn, may translate into the achievement of better outcomes (Agarwal, Erramili, and Dev 2003; Slater and Narver 1994).

Hypothesis Development

The Effect of Adopting MO on Tourist Behavior

The adoption of MO provides the firm with a competitive advantage, in that it helps to secure improved BIs among customers (Slater and Narver 1999). When evaluating the effect of MO on BIs, consideration must be given to those mechanisms that enable customers to perceive and evaluate the actions taken by the firm. It should be remembered that when a firm implements an MO approach, the resulting behaviors that it plans internally may or may not be perceived externally, and therefore valued, by customers. There are works that focus specifically on studying the effect of MO adoption on consumer behavior, some of which measure MO adoption and its effect from the firm’s perspective. Table 2 reflects the works on smaller enterprises, and those addressing the service industry. The findings of these works demonstrate that MO adoption has a positive effect on different variables of consumer behavior.

Table 2.

Literature Review^a

Area of Application and Relationships Measured from the Internal Perspective of the Firm		Works and Their Findings Regarding the Relationship in Question
Smaller enterprises (manufacturing industry)	MO → Loyalty	Pelham (1997a, 1997b, 1999, 2000) (+)
Service industry	MO → Service Quality	Barroso, Martín-Armario, and Sánchez (2005) (+); Bennett (2005) (+); Lonial and Raju (2001) (+); Raju and Lonial (2001, 2002) (+); Raju, Lonial, and Gupta (1995) (+); Raju et al. (2000) (+); Voon (2006); Webb, Webster, and Krepapa (2000) (+)
	MO → Satisfaction	Agarwal, Erramili, and Dev (2003) (+); Barroso, Martín-Armario, and Sánchez (2005) (+); Bennett (2005) (+); Camarero (2007) (+); Gainer and Padanyi (2005) (+); Matear et al. (2002) (+); Matear, Gray, and Garrett (2004); Riliang and Ennew (2003) (+); Webb, Webster, and Krepapa (2000) (+)
	MO → BIs	Camarero (2007) (+); Chen and Quester (2006) (+); Kumar, Subramanian, and Yauger (1997, 1998) (+); Kumar and Subramanian (2000) (+); Lonial and Raju (2001) (+); Matear, Gray, and Garrett (2004) (+); Matear et al. (2002) (+); Maydeu and Lado (2003) (+); Riliang and Ennew (2003) (+); Raju, Lonial, and Gupta (1995) (+); Raju and Lonial (2001, 2002) (+); Raju et al. (2000) (+)

Source: Own elaboration.

Note: MO = market orientation; BI = behavioral intention; (+) = significant and positive relationship; n.s. = not significant.

Effects of MO adoption on the customer in the smaller enterprises and service industry.

When measuring the effect of MO on consumers, if only the internal perspective of the firm is taken into account, this can skew the results. It may mean that the effect of MO on customers is overvalued, since the delicate mechanisms used by the consumer to evaluate the service offer—the exogenous indicators—have not been factored in. As a firm should only be considered as market oriented when its customers actually perceive it to be so, the appropriate level of a firm’s MO is based on what its customers think it should be, obliging the firm to take on board the customer’s perspective (Krepapa et al. 2003; Steinman, Deshpandé, and Farley 2000; Webb, Webster, and Krepapa 2000).

Meanwhile the work of Mulyanegara (2010) measures MO adoption and its effects exclusively from the customer’s perspective. His findings show that MO has a positive effect on key variables of consumer behavior. It is worth noting, however, that this exclusive focus on the consumer perspective may mean that the effect of MO adoption on consumer behavior is not appropriately measured. It has to be remembered that MO adoption is an approach internal to the firm rather than an explicitly outward-facing activity that customers directly see. Customers only perceive the consequences of MO adoption once they consume the services delivered by the firm. Therefore, the client’s vision of a firm’s actions does not, alone, capture the full scope of activities that the firm actually undertakes when they adopt an MO approach.

However, it is important to take into account the fact that while adopting an MO approach helps the firm deliver an offer of greater value for customers, it can also imply greater costs for the firm (Tuli, Kohli, and Bharadwaj 2007; Kumar et al. 2011) that can ultimately make an impact on the offer. This impact may, or may not, be felt by the customer, and so in order to evaluate the true effects of MO adoption on consumer behavior, an approach is required that captures all of the perceptions that customers have when consuming the offer delivered by the firm, including perceived benefits and costs.

One such approach that embraces the set of elements that comprise the offer, including the perceived benefits and costs, is PV. The definition of PV proposed by Zeithaml (1988, p. 14), namely, as “the overall assessment of the utility of a product based on the perceptions of what is received and what is given,” is the most universally accepted (Gallarza and Gil-Saura 2006b). This concept of a trade-off between “get” and “give” elements has led to widespread interest in the composite nature of PV (see Babin, Darden, and Griffin 1994; Holbrook 1994; Mathwick, Malhotra, and Rigdon 2001, 2002; Sheth, Newman, and Gross 1991; Woodruff 1997), which refers to both the functional and affective components (Holbrook and Hirschman 1982; Petrick 2002, 2004).

There is strong backing throughout the literature for the theoretical framework proposed by Zeithaml (1988) to address the study of PV; in fact, it is the most widely used framework for applying in the tourism sector (e.g., Gallarza and Gil-Saura 2006b; Sánchez et al. 2006).

In summary, then, the present work proposes that the evaluation of the offer delivered by a firm should include the measurement of (1) the benefits and sacrifices perceived by the tourist, from their point of view, and (2) the MO strategy adopted by the RTE, from an internal point of view. In light of the above, it is proposed that:

Hypothesis 1: MO adoption is an antecedent of tourist PV.

The literature highlights the importance of the effects of PV on consumer behavior (Petrick 2002; Zeithaml 1988), particularly its positive effects on BIs (e.g., Gallarza and Gil-Saura 2006a, 2006b; Woodruff 1997).

Attitudinal definitions of BIs lead to measurements based on preferences, intentions, or affective intensity toward the firm (Iwasaki and Havitz 1998). According to the review of BI measurements undertaken by Rundle-Thiele (2005), word of mouth is the most commonly used indicator, followed by repeat purchase intentions. In fact, Reichheld (2003) states that in many service retailers, the desire to recommend is a good indicator of loyalty and has a high capacity to predict growth. Most recent works apply BI measures (e.g., Barroso, Martín-Armario, and Martín-Ruiz 2007; Van Birgelen, de Jong, and de Ruyter 2006; Yüksel and Yüksel 2007).

The relationship established between PV and BIs is already acknowledged by the literature (Caruana and Fenech 2005; Gallarza and Gil-Saura 2006a; Lai 2004; Lam et al. 2004; Pura 2005; Tam 2004; Terblanche 2006; Wang et al. 2004; Wang, Lo, and Yang 2004; Woodruff 1997). However, this relationship is absolutely central to the present work, the aim being to test whether MO adoption constitutes a strategy capable of giving firms a competitive advantage in so far as it may have a positive effect on consumer behavior and an influence on customers’ BIs. Therefore, it is proposed that:

Hypothesis 2: PV is an antecedent of tourist BIs.

The Effect of Adopting MO on the Outcomes of RTEs

The adoption of MO is seen to positively improve organizational performance (Kohli and Jaworski 1990; Narver and Slater 1990), particularly in terms of improved financial results (Kirca, Jayachandran, and Bearden 2005).

However, given the background origins and characteristics of RTEs, the achievement of financial results alone is rarely their sole objective. Hence, when examining the outcomes of RTEs it is necessary to take into account other objectives that are linked to the expectations and aims of the owner-manager themselves (Galloway and Mochrie 2005; McCartan-Quinn and Carson 2003). At the same time, for the application particular to this study—in which the effect of business activity on sustainable development and specifically on rural destinations is examined—to arrive at a complete evaluation of the outcomes achieved by RTEs, along with financial results the following must be considered:

Outcomes of a personal, intangible nature. RT activity brings with it a series of less tangible assets that are nonetheless very important to the owner-manager, such as their expectations as regards the quality of life they aspire to; the achievement of an enhanced social image in the eyes of other members of their community; cultural enrichment derived from interaction with other cultures by means of liaison with clients; and the sense of pride that comes from undertaking such activities and feeling confident about the business’s potential (Polo-Peña, Frías-Jamilena, and Rodríguez-Molina 2011).

Outcomes relating to improvement of the rural destination itself. Outcomes relating to improvement of the rural destination itself are based on the fact that the development of the RT offer brings with it demand for other complementary goods and services, the use of local labor, and enhanced development of infrastructures in the tourism destination (Hall 2004; Simpson 2008). On the back of entrepreneurial progress, the rural destination is improved and increases in monetary value, as economic and employment opportunities are created that permit the local population to stay in the rural destination rather than having to emigrate to urban settings (Simpson 2008).

These intangible assets are peculiar to RTEs, in which objectives are very much determined by the expectations of the owner-manager, and management of the business is geared toward achieving objectives that are not always financial in nature (McCartan-Quinn and Carson 2003). Thus, the financial results of the enterprise, outcomes linked to the improvement of the rural destination and outcomes of a more personal, intangible nature must all be taken into account when evaluating the outcomes of RT activity.

Although the literature compares and contrasts in great depth the relationship between the adoption of an MO approach and business outcomes, there is a need for empirical evidence that reflects a joint consideration for the impact of MO on both RTE outcomes and tourists. To achieve this complete perspective on the effects of MO adoption on the performance of RTEs, as highlighted above three types of outcomes need to be taken into account, namely, financial results of the RTE, improvements to the rural destination, and outcomes of an intangible nature relating personally to the owner-manager. Within this context, then, it is proposed that:

Hypothesis 3: The adoption of MO by RTEs has a direct and positive effect on the outcomes of RTEs.

Methodology

Sample Used

The Spanish national RT population was taken as the basis of the empirical research carried out. Spain is considered one of the most representative and significant tourist destinations worldwide (UNWTO 2009), in which the RT sector occupies an important position (Spanish Institute of Statistics 2011). The data-matched sample needed to cover both RTEs and tourists. To obtain the data for the study, first the RTE sample was obtained, followed by the tourist sample which was coordinated with the RTE sample. The database chosen to access the Spanish RTE population was that of Clubrural (Clubrural 2009), which offers a number of specific benefits; namely, that it (1) provides a breakdown that separates out those businesses specializing in RT; (2) provides not only the characteristics of the Spanish RTE population but also the contact details for these enterprises; (3) is both detailed and extensive, covering the RT offer of about 10,000 RTEs (Clubrural 2009).

The sample was selected by means of quota sampling as this technique provides a sample structure similar to that of the population, based on its descriptive characteristics. The sampling technique used delivers results similar to those obtained using representative random sampling techniques but with a cost advantage as it allows smaller sample sizes to be used, provided that the sample design is based on the most relevant descriptive characteristics of the population (Malhotra and Birks 2007, pp. 413-14). The sample was made up of groups of RTEs and was scoped in line with three variables: location, classification, and category (those variables that have been found to exert the greatest influence on the competitive activities undertaken by RTEs; Polo-Peña and Frías-Jamilena 2010). The size of each group was determined by the geographical distribution of the RTEs as defined by the Spanish regions. In turn, each group had a number of subgroups that represented the two classifications (hotel and nonhotel) and the categories (higher category and lower category establishments).

Data collection was undertaken by means of telephone surveys with owner-managers of these firms in the period March–April 2009. This involved selecting RTEs at random, from within each of the preestablished subgroups, in light of their location, activity, and category. Finally, a total of 100 valid surveys were obtained that, taken as a whole, were structured on the basis of the aforementioned descriptive characteristics and therefore corresponded with the structure of the national population of RTEs, as can be seen in Table 3.

Table 3.

Distribution of Sample Obtained from the Empirical Study of the Supply Side and Demand Side of Rural Tourism, According to Quotas

				Sample, Nonhotel Accommodation			Sample, Hotel Accommodation
					Category			Category
Region	Rural Accommodation Population	% of the Population	Sample Achieved	Total	High	Basic	Total	High	Basic	Rural Tourist Population	% of the Population	Sample Achieved
Andalucía	1,154	11.68	16	7	4	3	9	4	5	156,374	6.00	63
Aragón	692	7.00	8	4	2	2	4	2	2	136,587	5.20	38
Asturias	1,050	10.63	9	4	2	2	5	3	2	151,929	5.80	32
Cantabria	440	4.45	5	2	1	1	3	1	2	178,753	6.80	45
Castilla La Mancha	883	8.93	8	4	2	2	4	2	2	163,702	6.20	42
Castilla y León	1,843	18.66	14	6	3	3	8	5	3	572,193	21.80	105
Cataluña	1,084	10.97	11	5	3	2	6	3	3	335,882	12.78	65
Comunidad Valenciana	512	5.18	3	1	0	1	2	1	1	120,654	4.60	19
Extremadura	355	3.59	4	2	1	1	2	1	1	110,432	4.20	25
Galicia	505	5.11	3	1	0	1	2	1	1	162,881	6.20	27
La Rioja	156	1.58	3	1	0	1	2	1	1	25,941	1.00	15
Madrid	153	1.55	4	2	1	1	2	1	1	115,020	4.40	24
Murcia	145	1.47	3	2	1	1	1	1	0	42,852	1.60	14
Navarra	374	3.79	5	3	1	2	2	1	1	98,034	3.70	26
País Vasco	239	2.42	4	2	1	1	2	1	1	116,172	4.40	32
Total	9,878	99.97	100	55	27	28	53	28	25	2,626,821	99.98	572

The second phase consisted of selecting the tourist sample. This was obtained by using the RTE sample previously attained, so that paired data could be established, from both the firms and the tourist population (e.g., Barroso, Martín-Armario, and Sánchez 2005; Hernández-Maestro, Muñoz-Gallego, and Santos-Requejo 2009). In this way, each case consisted of one RTE and one of its customers. All participating RTEs were asked to collaborate by distributing questionnaires randomly among their customers on their departure from the establishment.

The sample was generated by applying quota sampling. Quotas were established in respect of the number of tourists to survey in each RTE, in light of the volume of tourists visiting each Spanish region. The quotas were set in line with the structure of demand for RT nationally, for 2008 (Spanish Institute of Statistics 2011) and the RT population of each Spanish region. Establishing quotas in line with volumes of tourists visiting each Spanish region meant that a sample representative of demand for RT could be achieved (Polo-Peña, Frías-Jamilena, and Rodríguez-Molina 2011). The fieldwork was carried out in August and September 2009.

A total of 572 valid questionnaires from tourists were obtained. Taken as a whole, these were structured around the descriptive characteristics previously indicated, thus they could be considered to be representative of the structure of the tourist population for RT, as can be seen in Table 3. The average number of customers per firm was just under six, giving rise to a very similar sample to that used in other studies (Seibert, Silver, and Randolph 2004).

The profile of the respondents corresponded roughly to that of other studies undertaken in RT, in terms of characteristics such as gender, age, and employment status. There was an almost equal number of females (52.10%) and males (47.90%); and most respondents were either under 29 years of age (43.40%) or between 30 and 44 (44.90%), and were employed (54.40%) (e.g., Devesa, Laguna, and Palacios 2010; Hernández-Maestro, Muñoz-Gallego, and Santos-Requejo 2009).

Measurement Instruments

All measures were drawn from previous research and aligned with the conceptual aspects of each construct.

As regards the measurement scales used for the study of the firms, to measure MO, the scale outlined in Polo-Peña, Frías-Jamilena, and Rodríguez-Molina (2012) was used. In their work, an exhaustive literature review was undertaken in the specialized area of MO and the characteristics of RTEs. A qualitative and a quantitative study were carried out in order to validate the MO adoption scale for RTEs. The validated scale was in line with the theoretical framework proposed by Kohli and Jaworski (1990) and their MARKOR (Kohli, Jaworski, and Kumar 1993). The dimensions on the scale were as follows: capturing market information, dissemination of market information within the firm, and response of the firm toward the market (Appendix A shows the set of items used to measure each of the three dimensions of MO, using a 7-point Likert-type scale, where 1 equaled “totally disagree” and 7 equaled “totally agree”).

By means of the literature review, it was identified that the outcomes achieved as a consequence of RTE activity are the firm’s financial results, outcomes linked to the rural destination, and outcomes of a more personal, intangible nature for the owner-manager. On this basis, the “outcomes” scale of Polo-Peña, Frías-Jamilena, and Rodríguez-Molina (2011) was used for the present work. The scale ultimately used covered all three types of outcomes resulting from RTE activity and was made up of three dimensions: the financial results of the RTE (typically these are quantified based on a valuation of sales achieved, profits, and ROI, in relation to the firm’s objectives; e.g., Kara, Spillan, and Deshields 2005; Kohli and Jaworski 1990); the outcomes for the rural destination; and the outcomes of a personal, intangible nature (Polo-Peña, Frías-Jamilena, and Rodríguez-Molina 2011). Appendix A shows the set of items used to measure each of the three dimensions of outcomes, using a 7-point Likert-type scale, where 1 equaled “totally disagree” and 7 equaled “totally agree.”

As regards the measurement scales used in the tourist study, the PV scale was based on the application proposed by Zeithaml (1988). This application was used in the service industry (e.g., Cronin, Brady, and Hult 2000) and in the tourism sector (e.g., Gallarza and Gil-Saura 2006b).

BIs were measured by means of “intention to repeat purchase” and “intention to recommend the firm,” using the scale based on the work of Zeithaml, Berry, and Parasuraman (1996), which has also been applied in studies undertaken in the service industry (e.g., Petrick, Morais, and Norman 2001) and in the tourism sector (e.g., Gallarza and Gil-Saura 2006b). Appendix B shows the set of items used to measure the constructs of PV and BIs, using a 7-point Likert-type scale, where 1 equaled “totally disagree” and 7 equaled “totally agree.”

Analysis

In the present study, there were two nested levels (RTEs and tourists). Use of conventional statistical techniques, such as ordinary SEM, would have resulted in unreliable results because tourists using the same firm shared common influences (e.g., they interacted with the same employees). Therefore, the assumption of independent observations required for ordinary SEM analysis would have been violated (Bryk and Raudenbush 1992). In light of these difficulties, a multilevel SEM was used to deal with hierarchically nested data structures (Hofmann 1997; Van Dolen et al. 2002). Multilevel SEM techniques were deemed the most appropriate approach because they allowed tourist predictors at the individual level and RTE predictors at the group level to be used, without the shortcomings of the aggregation or disaggregation approaches (Heck and Thomas 2009, pp. 19-20).

In addition, in the model proposed in Figure 2, the first hypothesis is a cross-level hypothesis because it involves a relationship between MO at the RTE level and PV at the tourist level. Multilevel SEM is an appropriate approach for testing cross-level models because it allows the analyst to explicitly model both individual (level 1) and group (level 2) level variance in individual outcomes. The intercept and slope from the level 1 (within-group) analysis serve as the dependent variables in the level 2 (between-groups) analysis. A significant parameter estimate for the level 1 predictor indicates an individual-level effect, and a significant parameter estimate for the level 2 predictor of the level 1 intercepts indicates a group-level effect.

Figure 2.

Proposed research model

The estimation of the proposed model was carried out using Mplus software and robust maximum likelihood. In the syntax, the items measuring MO and outcomes were defined as variables of the RTE level, or between groups. On the other hand, the variability of PV and BIs was divided into two parts: that explained by the differences between tourists (within group) and that explained by the differences between RTEs (between groups). To ensure invariance of the PV and BIs measures, a restricted model was used, in which the factor loadings were fixed so as to be equal between the RTE level and the tourist level (Heck and Thomas 2009, pp. 111-12). This model can also be conceptualized in terms of a hierarchical random intercept model.

Findings

The overall fit of the model was adequate as the global fit indices such as the normed chi-square (1.81), comparative fit index (CFI) (0.94), Tucker–Lewis index (TLI) (0.93), and root mean square error of approximation (RMSEA) (0.04) were within the limits recommended by the literature (Figure 3). However, the chi-square statistic was statistically significant, although it is known to be particularly sensitive to sample size (Hair et al. 2008, p. 644).

Figure 3.

Outline of results from the proposed research model

The intraclass correlations (indicating the expected correlation between two randomly drawn units that are in the same group) for the items of the variables included in the tourists level reached values between 0.17 and 0.27 (Table 4). These values indicate that the bias that they can cause, both in the estimation of the parameters and in the standard errors, must be taken into account—as achieved by using multilevel SEM (Muthén 1994; Hox 2002, p. 184).

Table 4.

Intraclass Correlations for Variables of Tourist-Level Constructs

PV
PV1	0.17
PV2	0.21
PV3	0.22
Recommendation intention
REC1	0.21
REC2	0.20
REC3	0.27
Repetition intention
REP1	0.26
REP2	0.23

Next, the convergent validity of the scales used was examined. The dimensions included in the scales for MO, outcomes, PV, and BIs reflect the composition of the scales when their validity and reliability can be confirmed (Devlin, Dong, and Brown 1993). To achieve this, the internal consistency of each one of the dimensions on the first-order scale had to be analyzed. Usually, consistency can be measured by means of Cronbach’s alpha; however, this ceases to be a valid indicator when dealing with variables whose variability is divided into two parts: that explained by the differences between customers (within group) and that explained by the differences between firms (between groups). In such cases, a valid approximation to measure internal consistency is that used by Hox (2002, p. 168), which recognizes the two parts in which the variability is divided (within group and between groups). Finally, composite reliability and variance extracted provided a better evaluation of internal consistency. Table 5 reflects these indicators. In all cases, the values obtained were acceptable, as they were close to, or above, the reference value of 0.70 for composite reliability and 0.50 in the case of variance extracted (Hair et al. 2008, pp. 649-51) (Table 5).

Table 5.

Convergent Validity and Internal Consistency of Scales Used

Dimension	Alpha (Hox, 2002)	Composite Reliability	Variance Extracted
Firm’s level
First-order scales
MO
Information capture	0.65	0.66	0.40
Information dissemination	1.00^a	1.00^a	1.00^a
Response to the market	0.80	0.81	0.60
Outcomes
Financial	0.85	0.88	0.72
Rural Destination	0.62	0.73	0.41
Personal	0.78	0.78	0.55
Second-order scale
MO		0.84	0.64
Outcomes		0.77	0.53
Customer’s level
First-order scales
PV	0.85	0.85	0.65
BIs
Recommendation intention	0.90	0.90	0.75
Repetition intention	0.70	0.70	0.54
Second-order scale
BIs		0.69	0.53

Note: MO = market orientation; BI = behavioral intention.

Its value is 1, as its indicator’s variance error was set at 0.

As regards second-order constructs, Table 5 shows the composite reliability and variance extracted for MO, outcomes, and BIs. It can be seen that the scales offer composite reliability and variance extracted values greater than the minimum acceptable, such that, overall, these results contribute to determining that the second-order scale referring to BIs has a high level of internal consistency. Furthermore, the factors included in the research model can be said to possess discriminant validity, as in all cases the correlation between them does not exceed 0.90 (Kline 2011, p. 72), nor does their confidence interval include one (Steenkamp and van Trijp 1991). The results obtained thus far lead to the conclusion that the set of dimensions proposed to measure MO, outcomes, PV and BIs is valid, given that it allows the existence of adequate validity and reliability to be confirmed.

Returning to the hypotheses, Figure 3 shows the results relating to the relationships between the constructs under consideration. On the basis of these results, the following aspects are to be noted:

Hypothesis 1 proposed that MO is an antecedent of tourist PV. The results show a statistically significant relationship, with a significance level of p < 0.05 (p value = 0.02). Furthermore, the effect detected stands at 0.17. Therefore, there is statistical support for this hypothesis and it can be concluded that MO is an antecedent of tourist PV.

Hypothesis 2 alluded to the relationships between PV and BIs. The results show a statistically significant relationship (p < 0.01). The effect detected stands at 0.66. Therefore there is empirical support for Hypothesis 2. It can be concluded that PV is an antecedent of BIs.

Hypothesis 3 proposed that MO has a significant positive effect on the achievement of outcomes. The results show a statistically significant relationship (p < 0.01). The effect detected stands at 1.33. Therefore there is statistical support for this hypothesis and it can be concluded that MO adoption contributes to the achievement of outcomes.

Conclusions

Contributions to the Literature

The underlying premises of MO models indicate that its adoption constitutes a strategy that can benefit both firms and their customers. Despite the recognized positive effects of MO on the performance of firms, the present study identifies areas in need of further attention in the literature. More specifically, the study contributes to the knowledge base relating to the effect of MO on the performance of RTEs and on their customer, using a dyadic B2C perspective to test that both parties have received a benefit. In jointly reflecting the perspectives of both RTEs and customers, the present work involved: (1) measurement of MO adoption and of the achievement of outcomes, as viewed from the internal perspective of the RTE, and its effect on tourists, from the tourists’ own perspective; (2) a multilevel analysis, considering the nested structure of the matched sample of RTEs and tourists.

In light of the above, one major contribution of the present study is in establishing that MO adoption has a positive effect on consumer behavior (more specifically, on PV), which suggests that MO is a valid strategy for RTEs seeking to compete more effectively in the market. This involves considering the tourists’ perceptions and evaluations when they consume the offer delivered by the RTE, taking into account the perceived benefits and costs, as expressed in the construct “PV.” The findings achieved show that MO adoption constitutes a strategy that helps to generate improved tourist BIs (intention to recommend and repeat) toward the RTE. These findings are in line with the premises behind the original MO models (Kohli and Jaworski 1990; Narver and Slater 1990).

It is also worth highlighting that the present dyadic B2C study has made it possible to measure the effects of MO on customers in a more realistic way, making the results achieved of greater value. The relationships identified between MO adoption and tourist behavior constitute an advancement that links the firm’s perspective with that of customers, given that MO is an approach internal to the RTE rather than an explicitly outward-facing activity that tourists directly see. Tourists only perceive the consequences of MO adoption once they consume the services delivered by the RTE.

Another important contribution of the present study is in establishing that MO adoption is an appropriate internal strategy for RTEs, thanks to its contribution to outcomes. RTEs have particular characteristics that set them apart from other businesses in which MO has been applied. For example, they tend to have limited resources with which to develop activities linked to the market (McCartan-Quinn and Carson 2003; Polo-Peña and Frias-Jamilena 2010), and their objectives cannot be said to be exclusively commercial, given the significant role played by the expectations and objectives of the owner-manager themselves in the running of the business and the outcomes achieved (McCartan-Quinn and Carson 2003). At the same time, implications for business operations undertaken in the rural environment, and specifically their effect on the development of these rural destinations, should be taken into account (Simpson 2008). Therefore, when measuring RTEs’ performance, together with financial results, other outcomes associated with improvement and conservation of the rural destination and with the personal expectations of the owner-manager must be included.

A key contribution of the present work, then, is the submission that MO is valid strategy with which RTEs can more readily achieve these three types of objective. This assertion is of interest in that, given the strategic importance of the success of this kind of enterprise, and despite the extensive body of literature focusing on MO and its effect, until now it has not been proven that MO contributes to outcomes linked to the rural destination and to the personal, intangible objectives of the rural owner-manager.

Implications for the Professional Sector

The conclusions reached in this study hold some interesting implications for practitioners working in RTEs.

First, a competitive strategy is put forward in the form of the adoption of MO. Applying this strategy contributes to improving the performance of RTEs and their competitive capacity in the market. Specifically, MO adoption constitutes a strategy that contributes to delivering an offer deemed by tourists to be of greater value and that helps to generate improved tourist BIs toward the RTE in question. There is a need to increase the level of knowledge of tourists’ needs and preferences so as to adjust services to tourist expectations. In order to achieve this, an MO approach establishes the essential guidelines to be followed in the firm at an operational level to increase the efficiency and effectiveness of its marketing actions. Furthermore, alongside the positive effects of MO adoption on the performance of RTEs, derived from improved tourist BIs, the strategy is also beneficial to the tourist as they gain access to an offer of greater value.

Second, the present study finds that MO adoption constitutes a valuable internal strategy for the RTE given that it has such a major impact on the achievement of outcomes, bearing in mind that in assessing these, as well as financial results the work addresses other outcomes of importance to RTEs in particular, namely improvements to the rural destination, and the more personal, intangible benefits for the owner-manager. This underlines the importance of gearing the RTE’s internal activities toward making the MO philosophy possible. Thus, an important implication for management is the need for greater concern for actions that encourage a suitable organizational climate and behaviors that are oriented toward the market.

Limitations and Future Lines of Research

In this work, there are certain limitations that need to be considered and that themselves constitute possible lines of future research. One such limitation is the cross-sectional nature of the study. A longer-term study would have enabled us to observe with more precision the effects of MO adoption on the performance of RTEs. More specifically, using longitudinal data would have allowed us to assess whether the effect of MO adoption on tourist behavior (using the variables of PV and BIs) has, in turn, an effect on the achievement of outcomes. The literature establishes that a better level of BI on the part of the consumer leads to improved business results (derived from the customer’s stronger intention to repurchase and to recommend the firm). However, given the cross-sectional nature of the sample used in the present study, it was not possible to test this relationship, given that measuring tourist behavior at one moment in time (which can ultimately only represent BIs) does not allow the outcomes achieved by the RTE in that moment to be explained (i.e., outcomes that have been achieved thanks to past actions taken by the RTE). This analysis of the relationship between BIs and outcomes would make for an extremely interesting study in the future, based on longitudinal dyadic B2C data.

A further line of research might be to include a greater number of variables relating to the adoption of MO in RTEs, and to include more effects of MO on the performance of the firm. Specifically, it would be of interest to incorporate other variables that have been included in studies on the application of MO and that can affect its adoption, such as entrepreneurial orientation or different characteristics of the RTE, and to analyze whether these have any effect (moderating or mediating) on the relationship between MO adoption and its effects on outcomes and on tourists’ behavior. Similarly, it would be of interest to include a greater number of effects that the adoption of MO has on the RTE, such as impact on employees, or to study the effect of MO on each of the dimensions that comprise PV when this is considered from a multidimensional perspective.

Another possible line of research of interest is to propose a model whose main aim focuses more on the predictive capacity of PV, rather than its explicative capacity (the latter being the focus of the present work). To achieve this, together with the research model, it is suggested that methodologies suitable for this purpose be employed, such as partial least squares.

A final line of research potentially of interest is the application of the proposed research model to other geographical areas. Despite the choice of a geographical area with an extremely strong presence of the type of firm under study, with regard to maximizing the representativeness of the results obtained, the application of this research model may lead to different conclusions if applied to other geographical areas.

Footnotes

Appendix

Appendix B

Tourist Questionnaire

Dimension	Items
With respect to the service you received from the RTE, please answer the following questions by ticking the box that best reflects your opinion.
PV	PV1. Overall, the value of this RTE’s services has been adequate.
	PV2. On balance, the trade-off between what I have had to sacrifice to have this experience, and the benefits I have received from the RTE’s services, has been fair.
	PV3. Compared to what I have had to give up, the service I have received from the RTE has satisfied my wants and needs adequately.
BIs
Recommendation intention	REC1. Speak positively of the RTE to others.
	REC2. Recommend the RTE to friends and family.
	REC3. Encourage my family and friends to visit RTE.
Repetition intention	REP1. I will repeat-purchase from this RTE in the future.
Repetition intention	REP2. I will consider this same RTE as my number one option if I decide to purchase this type of service again.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The study was carried out with the help of financing received under the research project “Internet, Comercialización Turística y Desarrollo en Andalucía” by the Junta de Andalucía, Spain.

Notes

Bios

Ana Isabel Polo Peña is a lecturer in the Department of Marketing and Market Research at the University of Granada, Spain.

Dolores María Frías Jamilena is a senior lecturer in the Department of Marketing and Market Research at the University of Granada, Spain.

Miguel Ángel Rodríguez Molina is a senior lecturer in the Department of Marketing and Market Research at the University of Granada, Spain.

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