فرایند تصمیم گیری مصرف کنندگان و رفتار خرید آنها بصورت آنلاین : تجزیه و تحلیل توالی کلیک کردن
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|1776||2005||10 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Journal of Business Research, Volume 58, Issue 11, November 2005, Pages 1599–1608
The objective of this study is to investigate how different online decision-making processes used by consumers, influence the complexity of their online shopping behavior. During an online experiment, subjects were asked to perform a shopping task on a website offering product recommendations. Significant differences were observed between subjects' decision-making process and their online shopping behavior. Subjects who did not consult a product recommendation had a significantly less complex online shopping behavior (e.g., fewer web pages viewed) than subjects who consulted the product recommendation. Surprisingly, no differences were found between the online shopping behavior of subjects who consulted but did not follow the product recommendation and subjects who consulted and followed the product recommendation. Managerial and theoretical implications of these results are provided.
The objective of this paper is to investigate how different online decision-making processes used by consumers to make a product choice influence the complexity of their online shopping behavior. When faced with a product selection, consumers are suggested to perform an internal search (e.g., relying on their prior knowledge of brands) and, if necessary, an external search. The latter may comprise activities such as gathering more information about brands and seeking recommendations from relevant others. Thus, different consumers may use different decision-making strategies to make a consumption decision (Olshavsky, 1985 and Payne et al., 1993). Furthermore, consumers shopping online may modify or change the way they search for information to take advantage of certain unique characteristics of the Internet (Peterson and Merino, 2003). For instance, the presence of new information sources such as recommender systems, intelligent-agent-based systems and less easily accessible sources offline (e.g., opinions of a large group of consumers on a specific product) may modify the way, in which consumers perform their external information search. In this paper, we investigate the effect of different decision-making processes on consumers' shopping behavior (e.g., decision time, pages visited, etc.) while performing an online goal-directed activity, namely, the selection of a product. When applied to the Internet, the effect of various decision-making processes on consumers' shopping behavior leads to interesting questions. For instance, do consumers who consult and follow an online product recommendation have a less complex shopping behavior than consumers who do not consult or who do consult but do not follow a recommendation? Answers to such questions have important managerial and theoretical implications. First, they would help marketers maximize the effectiveness and usability of their websites. For instance, if it were known that after they consult an online product recommendation, consumers usually revisit product detail pages, a link from the product recommendation page to these pages would facilitate consumers' navigation and consequently, their decision-making process. Second, Peterson and Merino (2003) and Cowles et al. (2002) argue that the Internet represents a sufficiently different retail environment where concepts such as consumer information search behavior should be revisited. Thus, by investigating the effect of consumers' decision-making process on their online shopping behavior, this paper contributes to better understand how consumers search for information and make their decisions online.
نتیجه گیری انگلیسی
Results suggest that consumers who decided not to consult a product recommendation during their online shopping have a less complex online shopping behavior than consumers who decided to consult the product recommendation. They were found to have a more linear navigation pattern, visit fewer pages, visit fewer product detail pages and revisit a smaller proportion of pages they visited in order to select a product. When consumers decided to consult an online product recommendation, no differences were found between the online shopping behavior of consumers who followed and consumers who did not follow a product recommendation. Finally, the type of product did not significantly influence consumers' online shopping behavior. This study has important theoretical implications. Results surprisingly suggest that consumers who follow an online product recommendation have a more complex online shopping behavior than those who do not consult the recommendation and have an online shopping behavior similar to consumers who do not follow the recommendation. In consumer research, it has been traditionally assumed that consumers follow a product recommendation in order to limit or minimize their information search effort either because they lack the capacity or motivation to perform an extensive problem-solving task (Olshavsky, 1985). The unique characteristics of the Internet, such as information accessibility, may modify the behavior of consumers who follow an other-based decision making process. We suggest that low information costs associated with the Internet increase the amount of information gathered by consumers even when they use other-based decision-making processes. For instance, in this study, consumers could have visited only two pages to receive a product recommendation, go to the final choice page and select the recommended product. However, consumers who consulted and followed the product recommendation performed their shopping task by visiting an average of 10 pages. Since information is more easily available online than offline, the differences between other-based decision-making process and other decision-making processes that incorporate product recommendations (i.e., own-based or hybrid) become subtler online. Thus, contrary to what Peterson and Merino (2003) suggest, at least in some cases consumers may search more online than offline. Finally, in addition to static clickstream measures (e.g., the number of pages visited), we used compactness and stratum to assess the degree of complexity of consumers' online shopping behavior. These measures, usually used to assess general navigation patterns (Botafogo et al., 1992 and McEneaney, 2001), have been found useful in discriminating between different online decision-making processes. In addition to online shopping behavior, these measures could be used to gauge other consumer-related navigation patterns. For instance, consumers seeking information on a less usable website should exhibit lower stratum and higher compactness scores than consumers seeking information on a more usable website. Thus, these measures could be very useful to assess the usability of websites. This study also has interesting managerial implications. As mentioned, consumers who consult a product recommendation are performing a much more extensive external search than consumers who do not consult product recommendations. Online, consumers who do follow the product recommendation seem to consult a recommendation not to minimize their search effort but to gather more information. Thus, a website offering product recommendations should facilitate the navigation between product recommendation pages and other product related pages, since those who consult product recommendation are also those who visit and revisit more pages including product detail pages. This study has some limitations that should be kept in mind before applying the results to real market situations. First, as with most online studies, this study used a convenience sample. Thus, due to the possible self-selection bias it is not possible to confirm that our set of participants is a representative sample of the population of Internet shoppers. Additional studies should be performed to test the external validity of our findings. Second, the website used in this study only contained seven different pages and four different products. An interesting research avenue would be to increase the number of alternatives to choose from and investigate if the clickstream differences observed in the present study are replicated. For instance, would the online shopping behavior of consumers who consult and follow a product recommendation still be identical to the one exhibited by consumers who do not follow the recommendation? Third, only one search and one experience product were used. Thus, additional studies conducted with different samples, larger websites and different products would contribute to the generalization of the present results and confirmation that they are not idiosyncratic to this study. Finally, this study only investigated consumers' online product choices; it did not investigate online purchases. Thus, additional variables such as product price, product availability or delivery time could also affect consumers' decision-making process.