Farm tourism experiences in travel reviews: A cross-comparison of three alternative methods for data analysis
Introduction
Visitor experiences and customer satisfaction are complex phenomena to measure and analyse. They involve a diverse array of moments of truth, all influenced by the visitors' unique expectations and evaluations (Crotts & Pan 2007). Crotts, Pan, and Raschid (2008) highlight numerous methods to capture consumer likes and dislikes linked to customer loyalty. Though surveys and guest comment cards are efficient, these methods produce generally vague assessments of a guest experience, providing few insights about each attribute's importance to the consumer. Alternatively, open-ended questions evoke richer, more personally meaningful responses (Crotts and Pan, 2007, Pritchard and Havitz, 2006), but these responses can lose their richness and subtle details when summarized for analysis.
The use and popularity of electronic word of mouth have increased over the last few years (Mack, Blose, & Pan 2008), affording researchers access to large amounts of qualitative data for analysing consumer opinions about a tourist destination (Pan, McLauren, & Crotts 2007). Marketing researchers gain insights into consumer experience in a less costly, time-consuming, or intrusive way than focus groups and personal interviews (Kozinets 2002), but the data's sheer volume can be overwhelming.
Among marketing researchers, no single approach prevails as the best method for analysing such qualitative data. Woodside, Sood, and Miller (2008) purport the storytelling method, to create narrative interpretation maps to gain insights about consumer experiences. Kwortnik and Ross (2007) combine the analysis of online forums with consumers' ethnographic and introspective vacation-planning tasks, while Pan et al. (2007) rely on word frequencies and semantic network analysis to investigate consumer opinions related to a tourist destination. Mason and Davis, 2007, Crotts et al., 2009 propose stance-shift analysis as an alternative approach to quantitative content analysis focusing on key language pattern identification. The research presented here adds to this discussion by comparing manual content coding, corpus-based semantic analysis, and stance-shift analysis as applied to a single qualitative dataset. Each method is evaluated based on ability to produce relevant marketing insights efficiently and reliably.
To demonstrate each method, an exploratory study was conducted on consumer reactions to farm stays. This topic was chosen because of the sector's potential to influence rural economies, and the unique and under-researched nature of the product itself. Like bed and breakfasts and small boutique inns of decades past, regional differences exist; however, relatively little is known about cross-national understanding about consumers' values and reactions to farm stay experiences (Ollenburg 2008). The current study attempts to fill this void through detailing the elements and subtle details of both positive and negative guest experiences reported across a variety of national settings.
The paper begins with a brief review of the farm tourism literature, focusing on the customer experience. Next, the study of farm stay guests' online travel reviews provides additional insights about consumers' likes and dislikes employing manual coding of content, corpus-based semantic analysis, and stance-shift analysis. Finally, the paper discusses the potential benefits these three methods offer to glean useful marketing insights in a reliable and efficient way.
Section snippets
Farm entrepreneurs, tourism experiences and customer preferences
The family farm is not only a home, but also a business. The responsibilities of running a rural farm are driven by the cyclical nature of planting and harvesting crops, and the daily responsibilities of caring for livestock (Trussell & Shaw 2007). Opening a working farm to visitors offers a secondary revenue source, but only if the farm's capacity and market demand are sufficient to offset the increased costs (Wilson 2007). Well-designed and well-managed farm stay enterprises potentially
Data collection
Three methods were applied individually to one large qualitative database. This strategy provides broad-based information about farm tourism entrepreneurs, and demonstrates each method's advantages and disadvantages. The narratives were collected with permission from TripAdvisor.com using the travel blog website's search engine. Following Busby and Rendle, 2000, Roberts and Hall, 2001, Weaver and Fennell, 1997, three keywords were identified that reflect the industry: ‘farm stay’,
Discussion and conclusions
This study's purpose is two-fold. First, the results assess consumer sentiments to farm stay experiences across four national settings. Study findings provide meaningful insights about national markets. Second, and most importantly, the study demonstrates three alternative methods to analyze large volumes of qualitative data quantitatively in a relatively efficient and reliable way.
Study results reveal farm stay vacations evoke both universal and nation specific reactions – both positive and
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