رفتار انتخابی مصرف کننده در سوپر مارکت های آنلاین و سنتی : اثرات نام تجاری، قیمت، و دیگر ویژگی های جستجو
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|2981||2000||24 صفحه PDF||سفارش دهید||14397 کلمه|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : International Journal of Research in Marketing, Volume 17, Issue 1, 31 March 2000, Pages 55–78
Are brand names more valuable online or in traditional supermarkets? Does the increasing availability of comparative price information online make consumers more price-sensitive? We address these and related questions by first conceptualizing how different store environments (online and traditional stores) can differentially affect consumer choices. We use the liquid detergent, soft margarine spread, and paper towel categories to test our hypotheses. Our hypotheses and the empirical results from our choice models indicate that: (1) Brand names become more important online in some categories but not in others depending on the extent of information available to consumers — brand names are more valuable when information on fewer attributes is available online. (2) Sensory search attributes, particularly visual cues about the product (e.g., paper towel design), have lower impact on choices online, and factual information (i.e., non-sensory attributes, such as the fat content of margarine) have higher impact on choices online. (3) Price sensitivity is higher online, but this is due to online promotions being stronger signals of price discounts. The combined effect of price and promotion on choice is weaker online than offline.
There is increasing interest in understanding the effects of computer-mediated shopping environments (Hoffman and Novak, 1996). An issue of particular interest to both practitioners and academics is in determining whether there are systematic differences in consumer choice behavior between online and regular (offline) stores, and if there are differences, in understanding the reasons for these differences. Put another way, will the same person exhibit different choice behavior online and offline, and if so, why? Identifying and understanding these differences is important for formulating marketing strategies, especially for online marketers. We address these questions by first proposing a general conceptual framework to articulate how various factors influence online and offline choices. Although there are many factors that affect online choice behavior, we focus specifically on assessing whether brand names have more impact on choices online or offline, and whether price and other search attributes have higher impact online or offline. We empirically evaluate the implications of our conceptual framework by analyzing consumer choices in Peapod, an online grocery subscription service, headquartered in Skokie, IL,1 and in traditional supermarkets belonging to the same grocery chain operating in the same geographical area. Few papers have explored how consumer behavior online differs from consumer behavior offline. Exceptions are a conceptual paper on Interactive Home Shopping by Alba et al. (1997) and an experimental study by Burke et al. (1992). Alba et al. point out that a key difference between online and offline shopping is the ability of online consumers to obtain more information about both price and non-price attributes. More information on prices could increase consumer price sensitivity for undifferentiated products. At the same time, having more information on non-price attributes could reduce price sensitivity for differentiated products. Therefore, these authors suggest that an important research question is “What are the true dynamics of price sensitivity in this environment?” We need empirical research to understand how these implications are moderated by type of product, the power of the brand name, and the attributes for which information is available online. Burke et al. (1992) tracked the purchases made by 18 consumers in a traditional supermarket over a 7-month period. Two months later, the same group of consumers participated in laboratory experiments wherein market conditions identical to the in-store environment were created on a computer system for several product classes of interest. Each subject made online purchases in the simulated store during the same weeks in which that subject had made in-store purchases. A comparison of online purchases vs. in-store purchases revealed systematic differences when information relevant to choice decisions was not equivalently available in both store types. Specifically, product-size information is often not conveyed realistically in online stores. Consequently, there were greater discrepancies between the online and offline choice shares for the various product sizes, with larger sizes being purchased more frequently online. At the same time, there were no significant differences in the effects of promotions when the online store presented promotion information graphically in a manner that resembled promotions in the regular store. The authors report mixed results with regard to purchases of store brands. For some product categories (e.g., paper towel and tuna), the proportion of purchases of store brands was greater online than in the traditional supermarkets, whereas in other categories (toilet tissue and soft drinks), the proportion of purchases of store brands was smaller online. They attribute these results to unspecified product-class differences. While the reported results are interesting, these authors do not provide any overall conceptual framework to understand and predict differences between online and offline choice behavior. In the next section, we propose a conceptual framework to help us assess the relative impact of brand names, prices, and other search attributes on consumer choices within a specific product category. Using this framework, we derive specific hypotheses about potential differences we might expect between online and offline choice behavior. In Section 3, we describe the characteristics of our panel data and our methodology for testing the hypotheses. In Section 4, we describe the results of our empirical analyses in three product categories: liquid detergent, soft light margarine spread, and paper towel. In Section 5, we summarize the main insights from our study and suggest further research opportunities in this area.
نتیجه گیری انگلیسی
In Table 9, we summarize our key findings. In Table 9a, we summarize our category-specific hypotheses, and in Table 9b, we report the overall nature of the support we found for our hypotheses. Except for H3, where we found only indirect support, our analyses and results support our hypotheses. We submit that neither the hypotheses nor the implications are obvious a priori.Many executives are very concerned that online consumers will focus on price and this will result in strong price competition (see for example, the Booz Allen survey reported in Financial Times, February 9, 1998). At first glance, our results seemed to support this contention. But, further analyses indicated a more complex story, at least with respect to grocery products. First, people currently online may not be as price sensitive as the general population. Even if the online population becomes comparable to the general population, the combined effects of price and promotion seem to be stronger in regular stores than in online stores. Even after accounting for the fact that online promotions are better signals of price reductions, we find that offline promotions induce larger changes in brand choices. This is partly because of the low correlation between point-of-purchase (POP) activities and price in traditional supermarkets. It is likely that consumers in the traditional supermarkets are buying featured products even when there is little price reduction. Note also that we have “covaried out” the income effects when computing the market share changes due to price promotion. Thus, the price sensitivity coefficients reported in the paper are NOT induced by differences in income across the two samples. Nevertheless, we need controlled field studies in online markets to tease out these effects more precisely — a challenging task we leave for future research. There is also concern in some quarters that online markets would “commoditize” brands, thereby reducing the value of brand names (Burke, 1997). Several executives have suggested to us that online markets make it more difficult to differentiate products, and will therefore reduce the value of brand names. Our study suggests that brands can have more or less impact online than in traditional supermarkets depending on the extent of relevant information available for making choices in these markets. When more total information about product attributes is available online, brand names become less valuable. This is particularly likely if the product category contains few sensory attributes (e.g., margarine). Based on our results, we expect brand names will be more important online in product categories that are differentiated on brand image and other attributes that do not lend themselves to be easily summarized by an online store (e.g., fashion products). On the other hand, brand names will be less important online for functional products (e.g., fax machines, computers) for which online stores can give detailed attribute information, as well as comparative information, online. Finally, our results clearly suggest that sensory attributes, particularly visual cues, will influence choice to a lesser extent online than offline. This implies that marketers who rely strongly on visual cues to influence offline purchases of their brands may be disappointed by the level of online sales that they are able to generate. We see the contributions of this paper along three dimensions: (1) We developed a conceptual framework that will help researchers to better articulate how and why online choices may differ from offline choices. (2) We have proposed a few methodological innovations to help researchers empirically compare offline and online data, even though the two samples may not be equivalent. In particular, our two-stage choice modeling framework and new concepts, such as net market shares, can be applied in other studies. (3) Finally, as the first large-scale study of online choice behavior using field data, we were able to offer several novel insights about how search attributes differentially affect choices online and offline. Even though our results did not fully support H3, they do indicate that there are systematic differential effects of brand name, price, and other search attributes online. An important limitation of our study is that it lacks experimental control, making precise inferences infeasible. We had to exclude random assignment for a longitudinal data collection effort of this type from considerations of both cost and practical feasibility. An important issue not addressed by our research is choice behavior in online markets that are not subscription services like Peapod. The broader Internet market (essentially all sellers linked to the Internet) or online shopping malls, enable consumers to search across sellers to find the products and prices that best meet their needs. In these types of online markets, search can both expand and narrow the consideration sets of some consumers, and the information sources that they use while making choices. Some research initiatives are currently underway to explore consumer decision making and choices in these situations. In particular, several recent studies explore issues related to online price sensitivity Lynch and Ariely, 1998, Shankar et al., 1999 and Brynjolfsson and Smith, 1999.