Comparison of Periodic Behavior of Consumer Online Searches for Restaurants Based on Search Engine

Comparison of Periodic Behavior of Consumer Online Searches for Restaurants Based on Search Engine

Increased knowledge about the online search behavior of restaurant consumers is valuableto restaurant management and marketing professionals. However, people in different countries may demon-strate distinctive online search behaviors. There has been a lack of cross-cultural research on the online searchbehavior of restaurant consumers. In this paper, the periodic nature of online search behavior demonstrated byrestaurant consumers from U.S. and China is analyzed and compared using Fourier transform and Parseval’stheorem. The search interest records from Google and Baidu, respectively, are used. The results reveal thatthe online search behavior of restaurant consumers in the U.S. is strongly governed by weekly cycles but lessdependent on annual cycles; however, the analogous consumer behavior in China exhibits less dependenceon weekly cycles. The theoretical and practical implications of the research are discussed.

As culture so clearly shapes consumer behavior [36], hos-pitality and tourism researchers have sought to identify andunderstand cultural differences to provide useful informa-tion to industry practitioners [39]. For example, Moneyand Crotts [38] indicated that consumers from differentcultures tended to seek out travel and planning infor-mation from different sources; Baeket al.[60] (2006)reported that consumers from different cultures used dis-tinct restaurant selection criteria. Consumers have madeextensive use of search engines to seek out commercialinformation. This makes internet marketing very impor-tant [2], [28], [42], [43], [47], [53], [54], [57] and leadssellers and marketers to compete for higher search enginerankings and to increase their bids for internet advertisementspace. An optimal marketing strategy should consider con-sumer search behavior [17], [29], Nica, [61] (2013). It is thusvery meaningful to study and compare the patterns of onlineinformation search behavior among consumers from differentcountries. However, there has been a lack of research withsuch a focus.In this study, the periodic nature of consumer online searchbehavior, as it applies to restaurant searches in the UnitedStates (U.S.) and China, is analyzed and compared. Thesearch interest records from Google and Baidu, the most pop-ular search engines in the U.S. and China, respectively, areused to generate the material for analysis. Parseval’s theoremis used to quantify the weight of the periodic componentsin the whole search dynamic system obtained by discreteFourier transform (DFT). The results indicate that periodicpatterns exist in the behavior of consumer online searchesfor restaurants in the U.S. and in China, but consumers fromthe U.S. and China exhibit distinctive periodic patterns ofbehavior for online restaurant searches. The cyclic patterns ofconsumer behavior for online restaurant searches identified inthe two study countries are useful to international restaurantmanagement personnel and online marketing professionals.Following this brief introduction, the rest of the study is presented in the following order: literature review, datadescription, method, results, discussion, and conclusion.

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In this research, the cyclic consumer behavior of onlinerestaurant searches in the U.S. and China was analyzed.Parseval’s theorem was used to quantify the weight of cyclicpatterns in the whole searching dynamics. The study showedthat consumers in both the U.S. and China follow cyclicpatterns for online restaurant searches with the same periods,but Americans are more likely to arrange dining activities ona weekly basis, while the Chinese do not arrange this activityas regularly as Americans. This finding agrees with the Hofst-ede’s original finding of an uncertainty avoidance differencebetween the two countries. This work is expected to be usefulfor international restaurant management personnel and onlinemarketing professionals. Future work aimed at analyzing thecyclic patterns of online restaurant search behavior in othercountries is needed.