Service Quality Perceptions, Online Visibility, and Business Performance in Rural Lodging Establishments

In the tourism industry, most customer feedback and searches for relevant information take place online. Therefore, it is important to improve understanding of the business consequences of both customers’ online comments and businesses’ online visibility. For this study, the authors collected comments and visibility data (advertising expenditures) from a leading rural tourism infomediary website, related to 408 French rural lodging establishments. A complementary survey provided information about the lodging establishments’ performance (reputation and profitability). The results reveal that tourists’ positive perceptions of global service quality, as reflected in their comments, depend on their dual perceptions of the lodging and the surroundings. In turn, positive global service quality perceptions and visibility on an infomediary website positively affect business performance. These findings have implications for tourism scholars, as well as for establishment owners trying to track the factors that affect tourists’ evaluations of their service provision.


Introduction
Word of mouth has grown more powerful with the advent of the Internet (Hennig-Thurau et al. 2004;Mauri and Minazzi 2013). For tourism providers in particular, customer feedback and searches for relevant information largely take place online, on platforms such as infomediary websites, social networking sites, blogs, forums, or microblogs like Twitter (Nieto, Hernández-Maestro, and Muñoz-Gallego 2014;Racherla, Connolly, and Christodoulidou 2013;Tham, Croy, and Mair 2013;Xiang et al. 2015). Information provided through these channels tends to be accurate, critical, relevant, and timely, as well as reflective of customer voice, so rural tourism establishment owners should not underestimate its impact (Filieri and McLeay 2013;Xiang et al. 2015).
Although extensive analyses investigate online customer reviews of goods (Barnesa and Jacobsen 2014;Reichelt, Sievert, and Jacob 2014;See-To and Ho 2014;Tseng and Kuo 2013) and services (Kim and Hardin 2010;Litvin and Hoffman 2012;Nieto, Hernández-Maestro, and Muñoz-Gallego 2014), studies of tourists' online reviews remain relatively scarce. A better understanding of these interpersonal influences would have great value for the firms in this sector (Nieto 2014). Therefore, we seek to determine which factors drive comments in online reviews, using a content analysis codification. Then we analyze how such comments contribute to positive global evaluations and affect the business performance of French rural lodging establishments, in parallel with the influence of the rural lodging establishment's visibility on an infomediary website.
To (1) identify the main factors that contribute to positive tourist perceptions, (2) measure the contributions of these perceptions to business performance, and (3) assess the influence of visibility on an infomediary website on business performance, we gathered data about rural tourism establishments from Toprural, a rural tourism infomediary website (now part of HomeAway Spain, S.L.). We also conducted a survey to gather information about the business performance of each lodging establishment in the sample. The findings help fill the research gap associated with online reviews (comments) about rural lodging establishments; they also respond to calls from rural lodging establishments for information about the key drivers of customer evaluations and thus their business performance. Our proposed model integrates customers' (online comments) and owners' (visibility on infomediary website and business performance) input at the level of the lodging establishment; it accordingly offers the potential for replication outside the rural tourism industry, because the model variables can be applied to other services too.
After a brief discussion of rural tourism and rural lodging establishments in the next section, we outline the importance of extrinsic cues, and particularly online customer reviews (comments), for services and the rural tourism industry. Next, on the basis of our literature review, we derive hypotheses to detail the relationships among online comments about a particular establishment, its visibility on an infomediary website, and its business performance. We specify our database, sample profile, and measures, then outline the results. Finally, we present some conclusions, implications, study limitations, and possible research extensions.

Rural Lodging Establishments
In rural and low-income countries and regions that previously have relied heavily on agriculture and natural resource extraction, modern tourism provides the dual advantages of generating employment and income while also promoting local cultural heritage and traditions (WTTC 2012). That is, rural lodging establishments improve the quality of life and contribute to the economic rehabilitation of rural areas, because they help decrease underemployment in the rural sector and increase family incomes (Fotiadis, Vassiliadis, and Piper 2014;Hernández-Maestro and González-Benito 2013;Park, Doh, and Kim 2014;Santana-Jiménez et al. 2015).
Although no consensus definition of rural tourism exists, we consider it tourism located in rural areas, or the functional countryside, built on typical features of the rural world, such as small buildings and settlements, businesses owned by local families, open spaces, contact with nature and the natural world, an emphasis on varied cultural heritages and traditional practices, local controls, and a view toward the long-term benefits of the local community (Barbu 2013;Tolstad 2014). Therefore, rural tourism includes both tourism activities (e.g., accommodation, basic services, supplementary services) and other economic activities (mainly agriculture, but also traditional occupations) (Aoki 2014;Kizos and Iosifides 2007). It develops in close connection with the local economy, which leads to interdependence between tourism activities and the local economy (Hernández-Maestro and González-Benito 2013). According to Pierret (2012), rural tourism provides visitors with authentic, traditional experiences that reflect the essence of rural life and integrate rural experiences and rural activities with human-made facilities and rural accommodations. The wide variety of rural lodging facilities includes hotels, hostels, and houses located on farms, in small towns or the countryside. We also note two general categories of facilities: those that rent individual rooms (houses, hostels, and hotels) and those that rent the entire facility or house (Hernández-Maestro, Muñoz-Gallego, and Santos-Requejo 2007).

Extrinsic Cues in Services
Services are dominated by intangible attributes that are difficult to assess prior to purchase, which creates a significant purchase risk (Wirtz, Chen, and Lovelock 2013). Information asymmetries arise because of prepurchase information scarcity and postpurchase information clarity (Kirmani and Rao 2000;Wells, Valacich, and Hess 2011). Customers who purchase hospitality offerings thus suffer some anxiety, because they cannot experience the product beforehand (Reisinger 2009). That is, from an information economics view, tourism services are experience products: They cannot be evaluated before purchase, involve a high degree of prepurchase information scarcity, and require the customer to experience the offering to ascertain its quality (Wells, Valacich, and Hess 2011;Wirtz, Chen, and Lovelock 2013). Customers thus search for information, which is relatively difficult and costly to obtain (Mudambi and Schuff 2010). To reduce their uncertainty (though it cannot be eliminated completely), they try to mitigate their information asymmetry, reduce transaction risks and search costs, and identify an offering that best fits their preferences (Ba and Pavlou 2002).
Signaling theory provides a framework for studying conditions of information asymmetry (Akerlof 1970). Customers use cues (i.e., signals) to make more accurate assessments of quality when faced with limited information about a product (Akerlof 1970;Biswas, Dutta, and Biswas 2009;Shen, Chiou, and Kuo 2011). If they have incomplete information (i.e., lack intrinsic cues), they make inferences based on extrinsic cues that are readily available and easy to evaluate (Wells, Valacich, and Hess 2011;Zeithaml, Varadarajan, and Zeithaml 1988). Extrinsic cues-that is, product-related attributes that are not inherent to the product being evaluated-are especially important to customers who search actively for information-processing shortcuts or heuristics to help them evaluate experience goods (Baker, Grewal, and Parasuraman 1994). Particularly if they suffer from an information overload, customers use heuristic processing to reduce their cognitive strain when forming judgments (Lee, Law, and Murphy 2011;Malhotra et al. 1994;Mitra 1995;Zhang, Wu, and Mattila 2014). They thus rely on combinations of product information (i.e., intrinsic attributes) and signals (i.e., extrinsic attributes) to evaluate product quality (Hu, Zhang, and Pavlou 2009;Richardson, Dick, and Jain 1994).
Tourists can gather such signals and cues from others' behaviors, which they use to understand the decision frame (Matzat 2009). That is, they use a few attributes to infer perceived quality (Huertas-Garcia, Laguna García, and Consolación 2014). Of the various types of extrinsic cues available to tourists, we focus on online customer reviews.
Online customer reviews. Online customer reviews are informal communications that feature user-oriented information about the characteristics, ownership, or usage of a good or service (Pan, McLauren, and Crotts 2007;Park, Lee, and Han 2007). They describe customer experiences, evaluations, and opinions, driven by the customers' own perceptions and emotions (Hyun and Han 2015;Söderlund and Rosengren 2007). Tourists write their online reviews for various reasons, including concern for others (altruistic sharing of experiences), for social interaction (to gain social approval by demonstrating their good purchase decisions), for self-enhancement (recognition as an expert), to help the company (reciprocity for a good experience), or to exert collective power (negative comments to punish companies) (Chena, Fay, and Wang 2011;Gretzel, Yoo, and Purifoy 2007;Söderlund and Rosengren 2007;Tian 2013). Many people also enjoy sharing their rural tourism experiences and expertise with others, such that reviews represent one of the pleasures of tourism (Litvin, Goldsmith, and Pan 2008;Ring, Tkaczynski, and Dolnicar 2014).
Previous literature also suggests that online customer reviews are a primary source of information for consumption decisions (Gretzel and Yoo 2008;Murphy and Chen 2014;Zhang, Wu, and Mattila 2014), because they provide a large amount of product information that is perceived as up-todate, reliable, and trustworthy (Bughin, Doogan, and Vetvik 2010;Gretzel and Yoo 2008;Pai et al. 2013;Sigala, Christou, and Gretzel 2012;Zhang, Wu, and Mattila 2014). The reviews that customers post online also are available for long periods of time and may be consulted by purchasers at any time (Breazeale 2009;Buttle 1998;Mauri and Minazzi 2013). This trend is especially significant for tourism services (Öğüt and Taş 2012), and specifically for rural tourism, which is a high-involvement purchase (Cantallops and Salvi 2014;Nieto, Hernández-Maestro, and Muñoz-Gallego 2014;Ye et al. 2011). Therefore, for rural tourists, online customer reviews can help mitigate their information asymmetry, reduce transaction risks, and encourage trust in sellers (Ba and Pavlou 2002). They also reduce the search costs associated with identifying a product that best fits the tourist's preferences (Chen and Xie 2004).
Attribution theory predicts that the more product attributes a customer mentions in a review of a product's actual performance, the more credible this reviewer seems. Credibility should increase confidence in the accuracy of the review, leading other consumers to believe that the product will have the attributes mentioned in the review. Such reviews also are more persuasive for the purchase decision process (Lee and Youn 2009;Mudambi and Schuff 2010). Several other elements of a review can provide important information to readers too, including the date it was posted, the reviewer's profile, rating methods (Likert scale, number of stars), the presence of pictures or videos, and comments. Comments are unstructured text, often with newly coined phrases (i.e., text speak), which tend to contain nuanced views of the services (from the writers' point of view) that cannot be expressed using just ratings (Ghose and Ipeirotis 2006).
Service providers need to analyze these comments themselves (Nonnecke, Andrews, and Preece 2006;Pai et al. 2013), because the content of the comments can affect performance. Prior studies have investigated the characteristics of online consumer reviews, including the elaborateness of the comments (e.g., counting words) (Chevalier and Mayzlin 2006;Mudambi and Schuff 2010) and their readability (Liu and Park 2015;Mauri and Minazzi 2013). Comments also may be analyzed to identify which service elements have driven the consumers' positive experiences (Barreda and Bilgihan 2013). This study focuses on that latter assessment.

Positive Service Quality Perceptions as Reflected in Online Comments
For services, online reviews, and thus online comments, are primary indicators of perceived service quality (Racherla, Connolly, and Christodoulidou 2013). They include both positive and negative aspects of the service experience (Stringam and Gerdes 2010). In a tourism setting, positive comments tend to refer to service elements such as sleep quality, cleanliness, amenities, or decoration (Barnesa and Jacobsen 2014; Barreda and Bilgihan 2013;Engeset and Elvekrok 2015;Filieri and McLeay 2013). Furthermore, tourism research focused on perceived quality and satisfaction identifies two overriding, key dimensions: the establishment and the surroundings, including complementary offers, local infrastructure, and attractions (Hernández-Maestro and González-Benito 2013; Pandža Bajs 2015; Peña et al. 2015;Stumpf, Park, and Kim 2014). On the basis of this collected prior research, we propose the following: Hypothesis 1: In the comments provided in online reviews, tourists' positive global service quality perceptions of a particular rural establishment reflect their perceptions of the (a) lodgings and (b) surroundings.

Positive Service Quality Perceptions in Online Comments and Their Effects on Performance
Perceived quality and satisfaction, usually strongly linked, are cornerstones of marketing, because of their capacity to generate positive effects for the organization, such as customer retention and profitability (Coţiu 2013). The wellestablished, positive relationship between perceived quality/ satisfaction and profitability also applies in rural tourism. When customers perceive differences in the quality of rural tourism goods and services, those differences also affect the establishments' performance levels (Petroman et al. 2013).
For example, online reviews work as signals, so positive reviews increase readers' awareness and improve customers' attitudes and trust. Therefore, they enhance the firm's reputation, which enables it to charge price premiums and achieve increased sales and profitability (Chen, Dhanasobhon, and Smith 2008;Jarvenpaa, Tractinsky, and Vitale 2000;Sweeney, Soutar, and Mazzarol 2012;Vermeulen and Seegers 2009;Yacouel and Fleischer 2012;Ye, Law, and Gu 2009). We consider positive online reviews, and particularly positive comments, especially significant profitability determinants for rural tourism, which is a niche product without large-scale marketing campaigns. In these settings, customers rely heavily on what other consumers have to say, to assess these experience products with their uncertain quality (Yang et al. 2012). The highest rated businesses also usually appear first in accommodation review lists online, and positioning on such lists is a strong predictor of tourists' use of information in the online comments. Therefore, rural establishment owners assert that positive comments are relevant for them, because "good comments lead to good sales" (Gössling and Lane 2015). In turn, we propose the following: Hypothesis 2: Positive global service quality perceptions, contained in comments, positively influence a rural lodging establishment's (a) business reputation and (b) profitability.

Visibility on Infomediary Website and Business Performance
In our study setting, the rural lodging establishment's visibility on an infomediary website refers to how visible it is to readers of customer reviews sites, which the establishment can manipulate to influence buying behavior (Bronner and de Hoog 2011). That is, this visibility on an infomediary website depends directly on the amount of money an establishment owner allocates to ensure the company's appearance in the top results on an infomediary's website (Pergelova, Prior, and Rialp 2008;Tseng, Kuo, and Chen 2014). Higher online visibility, achieved through greater visibility on an infomediary website, should encourage tourists to pay more attention to the positive features of the establishment (Nieto, Hernández-Maestro, and Muñoz-Gallego 2014). Being well positioned in the results of an Internet search is often an important choice criterion for customers, similar to brand recognition (Smithson, Devece, and Lapiedra 2011). From a resource-based view, online visibility is also a differentiating factor that should lead to superior organizational performance, because it can attract new tourists and increase occupancy rates (Smithson, Devece, and Lapiedra 2011). Consequently, we propose the following: Hypothesis 3: A rural lodging establishment's greater visibility on an infomediary website positively affects its (a) business reputation and (b) profitability.

Methodology
To identify factors that might explain the satisfying experience of rural tourists in France, and thus contribute insights for improving the business performance of establishments that provide rural tourism services, we combined qualitative and quantitative data analyses. We applied content analyses to categorize all online customer comments, using NVivo10 qualitative data analysis software. Thus, we discovered what kinds of thoughts satisfied rural tourists had about the rural tourism service provided, which can help rural tourism establishment owners improve the services they provide. To gather the business performance measures, we used an online questionnaire that revealed the establishment owners' perceptual measures. We analyzed these data with SPSS 21 quantitative data analysis software. Finally, for each rural lodging establishment, we merged information about the visibility on an infomediary website (provided by Toprural), the frequencies for each key comment category (from the qualitative analysis), and the performance measures (from the online questionnaire), then ran the model using SmartPLS 2.0.M3 (Ringle, Wende, and Will 2005).

Data Collection
The data collection process consisted of three phases: indepth interviews with rural tourism experts, analyses of rural tourists' online comments data published on Toprural, and an online survey of rural establishment owners to gather their perceptions of their business performance. First, with indepth expert interviews, we sought to understand the sector, the role of the Internet, and what type of research would be most useful for rural tourism.
Second, we gathered data about the online comments, ordered by country and establishment, from Toprural (http:// www.toprural.com), a specialized, leading site for independently owned rural accommodations in southern Europe (Spain, France, Portugal, Italy, and Andorra), which also has a strong presence in central Europe (Austria, Germany, the Netherlands, and Belgium). We chose to gather data for establishments in France, because it ranks highest in international tourism arrivals (UNWTO 2014). We selected and ordered the comments about French establishments, according to the ratings provided by the customers (1-5) during the period 2008-2010. For this analysis, we note that customers with moderate opinions are less likely to express their opinions, and star ratings usually exhibit truncated distributions, such that most comments indicate positive assessments (Chevalier and Mayzlin 2006;Dellarocas and Narayan 2006;Racherla, Connolly, and Christodoulidou 2013;Talwar, Jurca, and Faltings 2007). Therefore, in line with prior literature (Chevalier and Mayzlin 2006;Hu, Zhang, and Pavlou 2009;Nieto, Hernández-Maestro, and Muñoz-Gallego 2014;Pathak et al. 2010;Racherla, Connolly, and Christodoulidou 2013;Stringam and Gerdes 2010), we selected customer perceptions of good service, as indicated by ratings (4-5), and identify positive customer comments.
Third, we used the owners' perceptions of their performance, measured on a seven-point agreement scale. Prior research on rural tourism shows that most rural lodging establishments are small, family businesses, located in areas that suffer economic and demographic constraints, often because of agricultural production declines, and they enter the tourism industry in response to government incentives (Hernández-Maestro, Muñoz-Gallego, and Santos-Requejo 2009). Because respondents represent small firms, whose entrepreneurship reflects the characteristics and choices of the establishment owner, we chose to use the establishment owners' perceptions of their performance (Buhalis 1996(Buhalis , 1999Buhalis and Main 1998;Middleton and Clarke 2001;Narangajavana, Garrigos-Simon, and Gil-Pechuan 2013;Nieto, Hernández-Maestro, and Muñoz-Gallego 2014). This approach is reasonable, because it is difficult to obtain objective performance measures, and prior evidence cites a positive relationship between owners' perceptions of performance and customers' evaluations (Nieto, Hernández-Maestro, and Muñoz-Gallego 2014). The survey items were adapted from Cooper and Artz (1995), Covin, Prescott, and Slevin (1990), Hmieleski and Corbett (2008), and Walter, Auer, and Ritter (2006).
To collect performance data, we started with a pilot test with 10 randomly chosen establishments, using telephone surveys with establishment owners. We thus confirmed that establishment owners were appropriate respondents, ensured the discriminatory power of the questionnaire, and confirmed the comprehensibility of the questions. We also made a few minor adjustments to the questions, on the basis of their responses.
Our initial sample consisted of 10,047 comments about 2,275 rural lodgings, comprising 614,009 words, posted in 2008-2010. We filtered these data by eliminating any establishments that lacked complete information, duplicate comments, or blank comments, for a filtered sample of 1,618 establishments (71.12%), with a total of 8,628 comments (85.88%). As expected, the vast majority of those comments were positive (i.e., 8,224, or 95.32%). For this filtered sample, we created a separate website to collect survey data from the rural establishment owners. Specifically, we granted rural establishment owners access to an online questionnaire, through an e-mail that contained a password to enable them to access the website, between May 28 and June 8, 2012. We received responses from 408 rural establishment owners (25.22%), which matched 3,034 positive comments (36.89%), on which this research focuses. These data constitute our final sample.
Toprural also offers four levels of promotions that establishments can pay to ensure their appearance on the site: exclusive, prestige, gold, and silver. We excluded the exclusive level from this study, because it represents less than 1% of establishments in the database. We detail the sample characteristics in Table 1.

Measures
Four coders followed a method proposed by Miles and Huberman (1984) to select an initial sample of 50 online customer comments and identified recurring themes, keeping an open mind but also relying on their knowledge of prior research and theory (O'Connor 2010). They iteratively evaluated and examined each comment, with codes allocated to each customer comment; during this process, the coders frequently examined any disparities in their judgments to reach consensus.
In this process, we also established a dictionary of terms in the eight languages (English, Portuguese, Spanish, French, German, Dutch, Italian, and Catalan) that appeared in the online customer comments, by relying on NVivo10 software. The coding assessment was content oriented, focused on the analysis of information provided in each customer comment. Then, we merged the codes into 16 overall categories, as detailed in Table 2.
In turn, the coding method supported further evaluations of the relationships among categories, how these relationships link in a hierarchical order, and their relations to the business performance perceptions expressed by the rural establishment owners. We present these variable measures in Table 3.
To determine establishment owners' performance perceptions, we requested that they indicate the status of their rural lodging establishment on a 1-7 scale (1 = very bad to 7 = excellent) in terms of profitability, growth in the number of reservations, customer satisfaction, and public image of the establishment. They also responded to a 1-7 agreement scale (1 = strongly disagree to 7 = strongly agree) regarding whether they were satisfied with their income from the business. We conducted an exploratory factor analysis (EFA) to consolidate the questions and facilitate their interpretation. All the questions achieved discriminant validity and loaded well in the EFA (as we show subsequently in Table 4), so we retained two constructs: reputation and profitability. We also included two control variables: rural tourism establishment capacity, measured as the number of beds, and type of rental, which is a dichotomous variable (rental of a room or of the whole house). Finally, at the establishment level, we combined owners' perceptions of their business performance with visibility on the infomediary website, the control variable (establishment capacity and rental type) data retrieved from the Toprural database, and the number of positive comments posted on Toprural for each establishment in each category.

Results
First, with the qualitative content analysis, we identified the 16 main themes that tourists mention when they evaluatetheir rural establishment experiences positively in online comments. These 16 categories can be further grouped hierarchically into three latent variables: lodging perceptions (seven categories), surroundings perceptions (five categories), and global service quality perceptions (four categories) (Figure 1). Lodging perceptions pertain to information (quality of the information provided by the establishment and attention to complaints), temperature (appropriateness of the temperature at the establishment), cleanliness, decoration, and multimedia (Internet availability and intensity of the establishment's online presence). Surroundings perceptions involve seasonality, environment (where the establishment is located), and access (good and easy). These factors in turn determine the tourists' global service quality perceptions (host/feeling welcomed, satisfaction/feeling satisfied, comfort/feeling comfortable, rest/feeling tranquil, possibility to rest, sleep quality).
Surprisingly though, tourists' lodging perceptions exhibited a nonsignificant relationship with the space and equipment categories, and surroundings perceptions did not have a significant relationship with the distance and activities categories. In detail, tourists' lodging perceptions explained variability in the five major categories to the following extents: 0.562 for information, 0.313 for temperature, 0.247 for cleanliness, 0.172 for decoration, and 0.129 for multimedia. Their surroundings perceptions explained variability in three major categories: 0.753 for seasonality, 0.345 for environment, and 0.164 for access.
Second, our analysis of the positive evaluations in the online customer comments reveals a global construct, global service quality perceptions, that reflects perceptions resulting from a global evaluation of the establishment and indicates that the establishment fulfills basic requirements. Regarding the effects of lodging and surroundings perceptions on global service quality perceptions, we found that both have similar and significant positive influences, 0.488 (5,423) and 0.441 (5,002), respectively, consistent with hypotheses 1a and 1b. In the proposed model, from tourists' perspective, surroundings and lodging perceptions explain 68.5% of the variance in global service quality perceptions.
Third, the business performance factors we identified can be classified as business reputation and business profitability. Both exhibited excellent composite reliability, of 0.919 and 0.925, respectively (Table 4 and Figure 1).
Tourists' global service quality perceptions also achieved excellent composite reliability (0.941), and they positively affected business performance, measured as both business reputation (hypothesis 2a) and profitability (hypothesis 2b). Visibility on the infomediary website positively affected business performance too, such that business reputation and profitability both increased with greater visibility on the infomediary website, in support of hypotheses 3a and 3b (Figure 1). Among the control variables, we confirmed prior suggestions that a room rental type (vs. whole house rental type) achieves better performance. This outcome might arise because owners who rent single rooms in their establishments, compared with those who rent the whole house, devote more time and effort to their businesses. Capacity instead has a nonsignificant effect on both reputation and profitability.
Finally, the results of the reflective construct assessment in Table 4 reveal internal consistency reliability (ρ c > .7), convergent validity (average variance extracted > .5), no collinearity among indicators, the significance and relevance of the outer loadings, and discriminant validity. That is, the square root of each construct's average variance extracted is greater than its highest correlation with any other construct (Hair et al. 2014). Therefore, we confirm the reliability and validity of the construct measures and affirm the suitability of including them in the path model (Hair et al. 2014). Regarding the formative constructs, when we executed formal detection tolerance and variance inflation factor analyses, we found no multicollinearity among the indicators. The model thus achieved predictive relevance.

Conclusions and Implications
Prior analyses of online reviews tend to take two different approaches. On the one hand, some research uses quantitative measures of online reviews (e.g., number, rank, ranking variance, number of letters or words in the comment) to explain consumers' purchase willingness or business performance. On the other hand, studies that employ content analyses seek to find key terms or different information categories (e.g., content categories) and the links among different types of information. With this study, we attempt to span both approaches, with the understanding that we might gain better explanations of performance by considering the number of online reviews in each key content category (rather than the number of total reviews), because consumers' sensitivity varies with the category to which the online reviews refer. Similarly, business owners and entrepreneurs might not assign the same importance to a particular type of information when strategizing about ways to improve their offers. Therefore, we consider it necessary to assess actual links between specific contents provided in review comments and business performance. In the lodging industry, the content categories that appear on infomediary websites reflect customers' service evaluations, but most infomediary websites define these categories intuitively, rather than undertaking an empirical analysis. Another point of departure for this study is that we combine data from customers, entrepreneurs, and the businesses, namely, online reviews by customers, investments made by entrepreneurs to gain visibility on the infomediary's website, and entrepreneurs' perceptions of their performance (through an online survey). From a theoretical perspective, our results thus address a research gap pertaining to the analysis of content categories in word-of-mouth comments and their impacts on business performance. Our theoretical model helps clarify how performance, measured by reputation and profitability, depends on key service elements mentioned in positive online comments, as well as online visibility. The model also specifies that positive global service quality perceptions result from particular perceptions of the lodging and the surroundings.
From a managerial perspective, this research helps rural business owners understand what drives positive online comments. It is strategically meaningful to explore which key elements tourists use when evaluating a service. In particular, the content analysis identified 12 key factors that drive positive online customer comments, as well as 4 factors with nonsignificant influences. Moreover, we show that tourists' global service quality perceptions are composed of feeling welcome, satisfied, comfortable, and tranquil. Tourists form these holistic perceptions of service quality on the basis of two main groups of perceptions: those related to the lodging and those related to the surroundings.
We also demonstrate that when dealing with different categories in online comments, the approach should be an aggregated one, to reflect the way most people interpret and bind these contents. This approach also reduces the complexity associated with dealing with such abundant information. A group of categories can reflect positive perceived service quality, so they should be primary considerations for controlling the quality of service, from the perspective of both entrepreneurs and infomediaries. Furthermore, the positive relationship between positive overall perceptions of service quality and business results reveals a clear business opportunity for improvement. That is, businesses should devote special effort to obtaining comments and ratings in the pertinent categories, whether directly or through the lodging and surrounding categories that explain them. The result is likely to involve the two effects we discuss herein: (1) generating positive expectations among the target audience that enhance customer attraction and (2) obtaining useful information for guiding improvements to the entrepreneur's offer.
With this knowledge, businesses gain a better understanding of what satisfied tourists think about the service delivery, which should help them improve their own provision of appropriate, necessary, higher quality services. They should pay particular attention to online customer reviews and monitor them, to learn what drives customers' positive perceptions and what they think about service quality, then adjust their service delivery marketing decisions to match tourists' needs and wants. Because of the dynamic nature of tourists' perceptions, managers should track the factors that affect tourist evaluations continuously.
In addition, rural lodging establishments and infomediary websites should use these results as motivation to attend closely to how they ask for information about the key categories on their own websites. The companies should ask tourists to evaluate the establishments according to the most relevant elements that other tourists, seeking information, prefer in ratings and comments. Doing so should facilitate the provision of such information.
Government agencies and rural tourism associations that periodically evaluate the service quality of the establishments in their regions also should note these relevant categories and use them to build their own evaluation frameworks. The categories highlighted in this study should be adequately represented and evaluated independently, to confirm that local establishments adapt to meet customers' current demands.
On the basis of our finding that perceptions of lodgings and surroundings contribute similarly to global service quality perceptions, we recommend that rural lodging establishment owners assess both controllable, key factors, related to their own lodgings, and uncontrollable factors associated with the surroundings. For example, establishments might try to help promote the surroundings, through alliances or cooperative efforts with other local organizations to host special (artistic, cultural, recreational, sports, or culinary) events. In addition, they should provide tourists with appealing information about the surroundings.
This research adopts a demand-driven perspective and identifies which factors lead to better business results. Therefore, it establishes how owners can improve their business performance (reputation and profitability) by making better, more appropriate service delivery decisions. According to the results of this study, tracking comments is a worthwhile endeavor to improve service delivery, provided that the efforts of the establishment owners lead to more positive future comments that influence potential tourists' expectations and decisions. Rural tourist establishment owners must realize that through online reviews, rural tourists can become co-marketers, influencing both other tourists' decisions and the owners' business performance.
With regard to the results pertaining to online visibility, which depends on the rural tourism establishment's online advertising expenditures, our study empirically informs owners that greater website visibility enhances their business's reputation and profitability. Therefore, it is worthwhile to devote some resources and money to online advertising to improve visibility (e.g., presence on main page, better search engine positioning, more attractive presentation), because it will lead to greater customer awareness and better business performance. This effect of increased spending on visibility might proceed through two paths: as a result of the increased number of people who receive the offer, or due to the greater credibility that the offer, as an extrinsic signal of quality, provides for interested individuals (as reflected in their online reviews). Customers generally believe that an establishment that invests capital in increasing its visibility (and thus appears in top positions on the web) is confident of its offer quality, because otherwise, it could not recoup its investment in the medium term.
Finally, some limitations of this research suggest ideas for further studies. First, improved business performance might produce the funds necessary to achieve greater online visibility and thus generate more positive comments. Accordingly, in different models, business performance might be either the antecedent or the cause. Second, we include information posted on Toprural's website. It is the leading infomediary for rural tourism in Europe, but it is a specific site, so these results cannot be generalized to other information sources without careful consideration. Third, this study referred to rural tourism establishments in just one country, France. It is the top destination for international tourism (UNWTO 2014), but again, the generalization of the results to other countries may be limited. It would be interesting to replicate this study using several countries and platforms simultaneously, such as other infomediary or destination websites, blogs, forums, social networking sites, and microblogs, to determine if similar results arise. Another line of research might try to identify "moments of truth" in tourists' experiences. Furthermore, an insightful analysis might review how customers express themselves through the use of adjectives, first-person voice, or grammatical context. Finally, it would be interesting to investigate the inclusion of photos and videos in reviews and comments, as well as the effects of responses posted by the establishment owner.