بررسی رفتار خرید آنلاین از خریداران مواد غذایی تخصصی

Food producers are experiencing a fast-growing need to use the Internet to enhance competitive advantage. Past researchers have urged the need to understand market segmentation mechanisms as applied to different consumer behavior models to better understand the online buying behavior of consumers. This study integrates the Theory of Planned Behavior and food-related lifestyle to explore consumer's characteristics of online specialty food buying behavior, and the differences in the online buying process among consumers with different FRL. 569 undergraduate students who purchased specialty food online were surveyed. Findings indicated that consumers have positive attitudes toward purchasing specialty food online; more are inclined to heed the suggestions of others, perceive higher levels of control when using a website, and experienced a higher intention to purchase online. The study then classified consumers into ‘traditionalists’ or ‘adventurous and healthy-conscious’ groups based on their FRL via a two-step cluster analysis. These two groups of consumers had significant differences in terms of (a) attitudes toward online specialty food buying, (b) subjective norms, (c) perceived control, (d) behavioral intention, (e) demographics and (f) online specialty food-buying behavior. This investigation explored whether there is a correlation between consumer FRL and online specialty food-buying behavior. Findings reveal relevant ways for managers to enhance their website marketing strategies.

The Internet has established itself as an important marketing tool in the global market, which can transcend time and geographical constraints. Entrepreneurs are continuously able to retail specialty foods to consumers online. Many studies have now shown that e-commerce holds enormous potential business opportunities (Canavan and O’Reilly, 2004). Academics and practitioners alike believe that the Internet phenomenon can create and/or improve competitive advantage based on two perspectives. First, businesses can integrate and establish a rigorous market segmentation mechanism (Ryan et al., 2004), as market segmentation information can help managers learn more about their target market, take better stock of market during the process of product development (Kotler and Keller, 2006) and increase the possibility of creating and delivering customized products and services through a better understanding of the attitudes and motives of the targeted customer segment. Second, studies have often applied different theoretical foundations (e.g., Technology Acceptance Model [TAM] or the Theory of Planned Behavior [TPB]) to understand online consumer behavior and to reach out to diversified consumer segments to improve sales performance (Koufaris, 2002 and Hansen et al., 2004). The many food production companies (particularly small and medium-sized enterprises) that understand consumer demand are better able to classify their customers and to segment them accordingly. However, very few studies have explored customer food consumption patterns or behaviors (Traill and Grunert, 1997 and Ryan et al., 2004), and even fewer studies have explored these patterns in the context of consumer online food-buying behavior. Exploring online consumer behavior provides a better understanding of consumer segmentation in food demand and thus helps to lay the foundation for developing an online marketing strategy for competitive advantage. Kesić et al. (2008) have also suggested that different customer behaviors with respect to different food types should be investigated further. Many segmentation variables are used to discuss customer food-buying behavior in the food domain, such as demographics, socio-demographics (Chisnall, 1994, Peter and Olson, 1994 and Verbeke and Lopez, 2005), motivations and attitudes (McCarthy and Henson, 2005), religious traits (Herndon, 2008), culture/social background (Blundell et al., 2008) and psychographic segmentation (e.g., lifestyle or food-related lifestyle; FRL) (Grunert et al., 1993 and Lin, 2002). FRL is one of the most elaborate segmentation tools within the food research field; it helps illustrate how people evaluate food with respect to their individual life values. Investigating consumer food-buying attitudes, Ryan et al. (2004) surveyed 1000 consumers in order to examine their food-related lifestyles and socio-demographic segmentation. The results indicated that consumer food lifestyles could be divided into: (1) hedonistic food consumers, (2) conservative food consumers, (3) extremely uninvolved food consumers, (4) enthusiastic food consumers, (5) moderate food consumers, and (6) adventurous food consumers. In addition, Wycherley et al. (2008) argued that these categorizations could help in understanding consumer characteristics by segmenting the food market according to FRL and then evaluating positive attitudes and preference levels toward specialty foods in each of the FRL segments. Shim et al.’s (2001) adoption of Fishbein and Ajzen's (1975) Theory of Planned Behavior (TPB) model revealed that online food-buying behavior has three classifications. First, food is purchased not only for survival but also as a means to facilitate communication with others; consumer behavior is thus influenced by the cognition of others (i.e., subjective norms) (Hansen et al., 2004). Second, consumers who have the necessary ability and resources (i.e., perceived behavioral control) develop an online buying behavior (Shim et al., 2001). Third, the consumers will utilize personal cognition resource (e.g., attitudes or beliefs) to deal with difficulties and confront risks in online buying. This study therefore aims to fill this research gap by (i) analyzing market segmentations of consumer demand, (ii) evaluating online food-buying behavior and (iii) developing preliminary online marketing strategy for food retailers. No studies have yet examined the underlying food-related lifestyles of individual consumers with respect to their online specialty food-buying behavior. Therefore, this research, which draws on the food-related lifestyle scale and TPB, seeks to empirically examine online specialty food-buying behavior.

Due to a lack of business resources, few small and medium-sized food companies are able to survey the online food purchase behavior of consumers. This study has examined specialty food specifically, partially in response to the recommendation of Kesić et al. (2008) to examine FRL market segments across different specialty food types. In addition, this study has aimed to successfully combine FRL and the TPB model to explore the online specialty food-buying behavior of consumers. These findings could potentially improve managerial understandings of the online buying behavior of consumers (Canavan and O’Reilly, 2004). The results of this study are similar to the empirical study conducted by Brunsø and Grunert (1995), confirming that different market segments are accompanied by distinct managerial implications. When individuals are more proficient in the use of the Internet (γ11 = 0.46), their willingness to purchase specialty food online is enhanced. Furthermore, consumers with a positive attitude toward purchasing specialty food online (γ11 = 0.27) are more likely to influence other individuals (e.g., friends and family) to adopt similar buying behavior (γ12 = 0.24), thereby developing a greater positive level of purchase intention with respect to specialty food. This is supported by the findings of Hansen et al. (2004). This finding is similar to studies conducted by O’connor and White (2010) and Lam et al. (2007). Meanwhile, perceived control was found to have the greatest level of influence on consumer purchase intentions. This could imply that the website design of food retailers should conform to consumer requirements with respect to ease-of-use and control. Various conditions encourage positive purchase intention, including a positive attitude toward buying specialty food online, the support of friends and relatives, and the use of a website that is perceived as assessable and convenient. Kupiec and Revell (1998) and Lin (2002) suggested that the use of applied psychological market variables in examining consumer FRL could be more appropriate than the use of demographic variables. This study has therefore adopted FRL and TPB to identify consumers with differing FRLs together with variables on online specialty food-buying behavior and demographics. The statistical results indicate that consumers can be classified into two FRL styles, namely, (1) traditionalist consumers and (2) adventurous and health-conscious consumers. Meanwhile, consumers with different FRLs have different perceptions regarding TPB variables (such as subjective norms and perceived control). According to the results of the chi-squared tests (Table 8), adventurous and health-conscious consumers are younger, are more likely to enjoy tasting new things, spend less time browsing specialty food websites, and bought specialty food at a higher frequency than traditionalist consumers.