Critique of 《Longitudinal comparison of Finnish and US online shopping behavior among university students: The five stage buying decision process》
This article is a well-organized research paper that clearly describes the process of the research and expresses the ideas of the authors.
The authors’ purpose is to “investigate different online shopping behaviours” (Charles Comegys, Mika Hannula and Jaani Váisánen, 2006, Journal of Targeting, Measurement and Analysis for Marketing, page 336). They collected samples among university students in the U.S. and Finland, both of which are leading countries in the field of Information and Communication Technology. Finally they found several important factors that exert influence on online purchasing behaviors. Their intended audience may be the people who are not equipped with any ecommerce knowledge but are eager to learn something about it. Though the authors use many professional terms in the paper, they explain them clearly in simple language, which makes the essay scientific and accessible.
The authors arranged the paragraphs logically and the essay is easy to read. First of all, they explain the “five-stage buying decision process” (Charles Comegys, et.al, 2006, page 337), which enables the readers to understand how the writers designed the research for the “five-stage buying decision process” (Charles Comegys, et.al, 2006, page 337) is the writers’ serves as the writers’ unique approach to the investigation. Then the authors went on to describe the hypotheses they made after studying the “five-stage buying decision progress” (Charles Comegys, et.al, 2006, page 337), which is quite reasonable and easy for readers to understand. Later the authors described the methodology of their investigation in detail, discussed the results and drew the conclusion. There are no abrupt turns in the whole process and the whole essay is logical, united and coherent.
Besides that, the authors’ evidences are believable for they never forget to point out the sources. This research paper helps me to understand online shopping behavior better. Though we can predict those factors that might have some impacts on online purchasing behaviors, it’s good to know how the results come out. The sentence: the frequency of need recognition has a greater influence on the number of goods bought from the internet than the frequency of online purchase decisions themselves evokes a strong response from me. People are always delighted about new unexpected prospects so the possibilities of finding useful things on the internet really make me excited. However buying things that you know you will get is not so interesting.
In conclusion, the research enlarges my knowledge, evokes my interest in this field. On the whole, it is a successful essay.
Tuesday, August 7, 2007
Reading Report#4--Summary
Summary of 《Longitudinal comparison of Finnish and US online shopping behavior among university students: The five stage buying decision process》
In “Longitudinal comparison of Finnish and US online shopping behavior among university students: The five stage buying decision process”, in Journal of Targeting, Measurement and Analysis for Marketing, July 2006, the authors Charles Comegys, Mika Hannula, Jaani Váisánen “investigate the online purchasing behavior” (Charles Comegys, et.al, 2006, page 336) by comparing samples collected among university students in the U.S. and Finland, both of which are leading countries in the field of Information and Communication Technology. At the beginning, the authors introduce the “five-stage buying decision process” (Charles Comegys, et.al, 2006, page 337), which consists of “need recognition, information search, evaluation of alternatives purchase decision and postpurchase behavior” (Charles Comegys, et.al, 2006, page 337). By studying the model, the authors come up with several hypotheses focused on different factors’ impact on online shopping behavior and do research in the U.S. and Finland. By analyzing the collected statistics, the authors showed us some important conclusions. They state that online shopping is continuously gaining popularity in both the U.S. and Finland, while Finnish students show a gender gap in online shopping. Besides that, they claim that some products are gaining popularity due to the Internet. The writers also state that the “Net Generation” (Charles Comegys, et.al, 2006, page 353) has contributed a lot to the booming of electronic commerce. Finally they point out cultural differences play a significant role in different online purchase behaviors.
In “Longitudinal comparison of Finnish and US online shopping behavior among university students: The five stage buying decision process”, in Journal of Targeting, Measurement and Analysis for Marketing, July 2006, the authors Charles Comegys, Mika Hannula, Jaani Váisánen “investigate the online purchasing behavior” (Charles Comegys, et.al, 2006, page 336) by comparing samples collected among university students in the U.S. and Finland, both of which are leading countries in the field of Information and Communication Technology. At the beginning, the authors introduce the “five-stage buying decision process” (Charles Comegys, et.al, 2006, page 337), which consists of “need recognition, information search, evaluation of alternatives purchase decision and postpurchase behavior” (Charles Comegys, et.al, 2006, page 337). By studying the model, the authors come up with several hypotheses focused on different factors’ impact on online shopping behavior and do research in the U.S. and Finland. By analyzing the collected statistics, the authors showed us some important conclusions. They state that online shopping is continuously gaining popularity in both the U.S. and Finland, while Finnish students show a gender gap in online shopping. Besides that, they claim that some products are gaining popularity due to the Internet. The writers also state that the “Net Generation” (Charles Comegys, et.al, 2006, page 353) has contributed a lot to the booming of electronic commerce. Finally they point out cultural differences play a significant role in different online purchase behaviors.
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