[논문]상품 범주별 온라인 구매도 -인터넷 동기와 온라인 구매성향 기능-

김은영

doi:10.5850/jksct.2008.32.6.890

상품 범주별 온라인 구매도 -인터넷 동기와 온라인 구매성향 기능-
Online Purchase Intentions for Product Categories -The Functions of Internet Motivations and Online Buying Tendencies- 원문보기

한국의류학회지 = Journal of the Korean Society of Clothing and Textiles, v.32 no.6, 2008년, pp.890 - 901

초록
AI-Helper

본 연구는 소비자의 인터넷 사용동기, 온라인 구매성향과 제품구매의도 사이의 관계를 밝힘으로써 온라인 상품 범주화의 기초 개념을 밝히고자 하였다. 조사대상은 미국 남서부 지역에 거주하는 대학생 총 217명으로 구성되었으며, 자료분석을 위해 요인분석과 경로모델을 추정하였다. 분석결과, 소비자의 인터넷 동기는 기분전환, 경제적, 정보적, 사회적 동기의 4개 요인으로 분류되었다. 또한 온라인 제품은 구매의도에 따라 감각상품, 인지상품과 탐색상품의 3개 범주로 분류되었다. 경로모델의 추정결과, 인터넷 사용의 기분전환과 경제적 동기요인이 충동구매성향에 영향을 주는 반면, 경제적, 정보적, 사회적 동기요인은 계획구매성향에 영향을 주는 것으로 나타났다. 온라인 구매의도에 있어서, 감각상품은 충동구매성향과 더 높은 관계를 나타낸 반면, 인지상품과 탐색상품은 계획구매성향과 더 높은 관계를 나타냈다. 또한, 인지상품은 경제적 동기에 근거한 계획구매성향에 의해 더 강한 효과를 보였으며, 탐색상품은 정보적 동기에 의한 계획구매성향에 의해 더 강한 효과를 나타났다. 따라서 본 연구는 특정 상품 범주에 따른 이론적 정립과적절한I-마케팅 전략의 관리적 측면이 논의되었다.

Abstract ▼ AI-Helper

This study explores an initial framework for online product categorization by examining the relationships among Internet motivations, buying tendencies, and online purchase intentions for product categories. A total of 217 usable questionnaires were obtained from respondents in a southwestern state in the United States. A path model using a correlation matrix with maximum likelihood was estimated using LISREL 8.53. Findings indicated that Internet motivations consisted of four factors: Diversion, Economic, Information, and Social motivations. In addition, online products were classified into three categories based on purchase intentions: Sensory, Cognitive, and Search products. Estimated path model showed that diversion and economic motivations affected impulse buying tendency, whereas economic, information and social motivations influenced planned buying tendency in the online context. Also, the buying tendencies were significantly related to online purchase intentions for the product categories. Purchase intentions for sensory products were more strongly affected by impulse buying tendency, whereas purchase intentions for cognitive and search products were more strongly affected by planned buying tendency. Theoretical and managerial implications were discussed for devising an appropriate e-market strategy for specific product categories.

주제어

AI 본문요약
AI-Helper

* AI 자동 식별 결과로 적합하지 않은 문장이 있을 수 있으니, 이용에 유의하시기 바랍니다.

문제 정의

, 2000). The researchers dealt with product categorization primarily at the conceptual level rather than on empirically tested results based on consumer motivational and behavioral variables in the context of online shopping.
This study also provides managerial implications into e-marketers' efforts for building product category-dependent strategies to simplify marketing decisions in the online consumer market. With a hedonic approach to sensory products, the Internet can be a channel to fulfill diversion motivation by (a) emphasizing sensory experience with online atmospherics(Xia, 2002) using advanced technology(e.
This study explored an online product classification scheme associated with consumers' buying tendencies from a motivational perspective. Based on purchase intentions linked to Internet users' motivations and consumer buying tendencies, this study classified online products into three categories: Sensory , Cognitive, and Search.
Specifically, this study were to: (a) identify dimensions of Internet motivations, (b) classify product categories based on online purchase intentions, and (c) estimate path model for examining causal relationships among Internet motivations, buying tendencies, and online purchase intentions for product categories in the online shopping context. This study provides insight into an online product classification scheme that consumers perceive to be related and/or substitutable, which can assist online retailers develop merchandising strategies.
Therefore, it is necessary to understand an approach to online product depending classification scheme by motivational aspect of buying tendencies and online purchase intentions. This study seeks to categorize online products depending on buying tendencies driven by their motivations in an online retail setting by focusing on college students. Specifically, this study were to: (a) identify dimensions of Internet motivations, (b) classify product categories based on online purchase intentions, and (c) estimate path model for examining causal relationships among Internet motivations, buying tendencies, and online purchase intentions for product categories in the online shopping context.

가설 설정

Hypothesis 1: Consumers' Internet motivations are positively related to online buying tendencies in the context of online shopping. Specifically, hedonic-driven motivation is more strongly related to impulse buying tendency (Hla), while utilitarian-driven motivation is more strongly related to planned buying tendency(Hlb).
Hypothesis 2: Online buying tendencies are significantly related to online purchase intentions for product category. Specifically, impulse buying tendency is more likely to encotirage online purchase intentions for sensory products(H2a); and planned buying tendency are more likely to en-courage online purchase intentions for cognitive and search products(H₂b).

제안 방법

a motivational perspective. Based on purchase intentions linked to Internet users' motivations and consumer buying tendencies, this study classified online products into three categories: Sensory , Cognitive, and Search. Using this categorization scheme, this study found relationship linkages among four motivations for Internet uses(e.
For hypotheses testing, a proposed path model was estimated in order to examine the relationships four motivational factors, two factors of buying tendencies, and online purchase intentions for three product categories. All nine constructs were represented in the model by single indicators using summated scales.
53. Overall model fit was assessed by statistic indexes: Chi-square(%2), Goodness of Fit Index(GFI), Adjusted Goodness of Fit Index (AGFI), Comparative Fit Index(CFI) and Root Mean Squared Residual(RMR).
Based on purchase intentions linked to Internet users' motivations and consumer buying tendencies, this study classified online products into three categories: Sensory , Cognitive, and Search. Using this categorization scheme, this study found relationship linkages among four motivations for Internet uses(e.g., diversion, economic, information, and social), and purchase intentions by the mediating effects of online buying tendencies. Especially for sensory products, diversion and economic motivations were found to be significant driving factors of impulse buying, eventually encouraging purchase intentions via the Internet.

대상 데이터

be interpreted with caution. The sample was limited to college students in one U.S. metropolitan area. Theoretical considerations should be given to the consumers' buying tendencies in conjunction with marketing stimuli and situations for the product-specific nature of purchase behavior.

이론/모형

For measuring online purchase intentions, respondents were asked, "How likely would you be to purchase these products via the Internet in future?^ for products including 11 of the top-ranked online products: books or magazines, computer related products, music tapes, CDs or videos, travel tickets or reservations, electronics, entertainment or leisure, financial services, clothing, accessories and jewelry, and cosmetics and beauty products. All items were measured on a 7-point rating scale(7=vezy unlikely, 7 uo likely).

성능/효과

An exploratory factor analysis revealed four factors with eigenvalues of 1.0 or higher accounted for 67.74% of the total variance. In a confirmatory factor analysis, six items were deleted by using a criterion for factor loadings of .

참고문헌 (43)

Babin, B., Darden, W. R., & Griffin, M. (1994). Work and/or fun: Measuring hedonic and utilitarian shopping value. Journal of Consumer Research, 20(4), 644-656

상세보기
Bakos, J. Y. (1997). Reducing buyer search costs: Implications of electronic marketplaces. Marketing Science, 43(12), 1676-1692
Bagozzi, R. P. & Heatherton, T. F. (1994). A general approach to representing multifaceted personality constructs: Application to state self-esteem. Structural Equation Modeling, 1(1), 57-64
Beatty, S. E. & Ferrell, M. E. (1998). Impulse buying: Modeling its precursors. Journal of Retailing, 74(2), 169-191

상세보기
Bellenger, D. N., Robertson, D. H., & Hirschman E. C. (1978). Impulse buying varied by product. Journal of Advertising Research, 18(6), 15-18
Bloch, P., Ridgway, N. M., & Dawson, S. A. (1994). The shopping mall as consumer habitat. Journal of Retailing, 70(1), 23-42

상세보기
Brandt, M. (2005, March). Young customers: Who, what and Y. Bank Marketing, 37(2), 37-41

상세보기
Cho, Y., Im, I., Fjermestad, J., & Hiltz, S. R. (2003). The impact of product category on customer dissatisfaction in cyberspace. Business Process Management Journal 9(5), 635-651

상세보기
Cobb, C. J. & Hoyer, W. D. (1986). Planned versus impulse purchase behavior. Journal of Retailing, 62(4), 384-409
Donthu, N. & Garcia, A. (1999). The Internet shopper. Journal of Advertising Research, 39(3), 52-58
Girard, T., Korgaonkar, P., & Silverblatt, R. (2003). Relationship of type of product, shopping orientations, and demographics with preference for shopping on the Internet. Journal of Business and Psychology, 18(1), 101-120

상세보기
Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate data analysis (4th ed.). New Jersey: Prentice Hall
Hansen, T. (2005). Perspectives on consumer decision making: An integrated approach. Journal of Consumer Behavior, 4(6), 420-437

상세보기
Hausman, A. (2000). A multi-method investigation of consumer motivations in impulse buying behavior. Journal of Consumer Marketing, 17(5), 403-419

상세보기
Hoffman, D. L. & Novak, T. P. (1996). Marketing in hypermedia computer-mediated environments: Conceptual foundations. Journal of Marketing, 60(July), 50-68

상세보기
Hoffman, D. L., Novak, T. P., & Duhachek, A. (2003). The influence of goal-directed and experiential activities on online flow experiences. Journal of Consumer Psychology, 13(1-2), 3-16

상세보기
Hui, K. L. & Chau, P. Y. K. (2002). Classifying digital products. Communication of ACM, 45(6), 73-79

상세보기
Joines, J. L., Scherer, C. W., & Scheufele, D. A. (2003). Exploring motivations for consumer web use and their implications for e-commerce. Journal of Consumer Marketing, 20(2), 90-108

상세보기
Jones, M. A., Reynolds, K. E., Weun, S., & Beatty, S. E. (2003). The product-specific nature of impulse buying tendency. Journal of Business Research, 56(7), 505-511

상세보기
Korgaonkar, P. K. & Wolin, L. D. (1999). A multivariate analysis of web usage. Journal of Advertising Research, 39(2), 53-68

상세보기
Klein, L. R. (1998). Evaluating the potential of interactive media through a new lens: Search versus experience goods. Journal of Business Research, 41, 195-203

상세보기
Li, Z. G. & Gery, N. (2000). E-tailing-For all products? Business Horizons, 46(6), 49-54
Madhavaram, S. R. & Laverie, D. A. (2004). Exploring impulse purchasing on the Internet. Advances in Consumer Research, 31, 59-66

상세보기
Mowen, J. C. (1995). Consumer behavior (4th eds.). Prentice Hall Inc.: NJ
Overby, J. W. & Lee, E-J. (2006). The effects of utilitarian and hedonic online shopping value on consumer preference and intentions. Journal of Business Research, 59(10/11), 1160-1166

상세보기
Park, E. J., Kim, E. Y., & Forney, J. C. (2006). A structural model of fashion-oriented impulse buying behavior. Journal of Fashion Marketing and Management, 10(4), 433-446

상세보기
Park, J. & Lennon, S. J. (2006). Psychological and environmental antecedents of impulse buying tendency in the multichannel shopping context. Journal of Consumer Marketing, 23(2), 58-68
Park, S. Y. & Lee, E. M. (2005). Net generation: The growing dominant consumer group in network society. Asia Pacific Advances in Consumer Research, 6(1), 239-243
Peterson, R. A., Balasubramanian, S., & Bronnenberg, B. J. (1997). Exploring the implications of the Internet for consumer marketing. Journal of Academy of Marketing Science, 25(4), 326-346
Phau, I. & Lo, C. C. (2004). Profiling fashion innovators: A study of self-concept, impulse buying and Internet purchase intent. Journal of Fashion Marketing and Management, 8(4), 399-411

상세보기
Piron, F. (1991). Defining impulse purchasing. Advances in Consumer Research, 18(1), 509-514
Ramanathan, S. & Menon, G. (2006). Time-varying effects of chronic hedonic goals on impulse behavior. Journal of Marketing Research, 43(4), 628-641

상세보기
Rohm, A. J. & Swaminathan, V. (2004). A typology of online shoppers based on shopping motivations. Journal of Business Research, 57(7), 748-757

상세보기
Rook, D. W. (1987). The buying impulse. Journal of Consumer Research, 14, 189-199

상세보기
Rook, D. W. & Fisher, R. J. (1995). Normative influences on impulse buying behavior. Journal of Consumer Research, 22(3), 305-313

상세보기
Roy, A. (1994). Correlates of mall visit frequency. Journal of Retailing, 70(2), 7-43
Sanchez-Franco, M. & Roldan, J. L. (2005). Web acceptance and usage model: A comparison between goaldirected and experiential web users. Internet Research, 15(1), 21-48

상세보기
Shim, S., Eastlick, M. A., & Lotz, S. (2000). Assessing the impact of Internet shopping on store shopping among mall shoppers and Internet users. Journal of Shopping Center Research, 7(2), 7-43
Stafford, T. F., Stafford, M. R., & Schkade, L. L. (2004). Determining uses and gratifications for the Internet. Decision Science, 35(2), 259-288

상세보기
Smith, A. D. & Rupp, W. T. (2003). Strategic online customer decision making: Leveraging the transformational power of the Internet. Online Information Review, 27(6), 418-432

상세보기
Sorce, P., Perotti, V., & Widrick, S. (2005). Attitude and age differences in online buying. International Journal of Retail and Distribution Management, 33(2), 122-132

상세보기
Taylor, S. L. & Cosenza, R. M. (2001). The impact of e-commerce on the merchandising of women's clothing in traditional shopping centers/mall. Journal of Shopping Center Research, 7(2), 46-66
Xia, L. (2002). Affect as information: The role of affect in consumer online behavior. Advances in Consumer Research, 29(1), 93-99

저자의 다른 논문 :

표제어: PCR

동의어: Packet Collision Rate

용어 설명 출처 목록 (6)

용어 설명: PCR은 세균 특이성이 있는 primer를 이용하여 적은 수의 세균이 있을지라도 쉽게 검출할 수 있는 유용한 방법이며, 이를 이용하여 구강 내 치면세균막이나 타액에서 직접 세균을 검출할 수 있게 되었다[8].

내보내기 구분	파일저장 인쇄 메일전송
구성항목	기본정보 상세정보 관리번호, 논문명, 저널/프로시딩명, 저자 , 발행년, 권, 호, 시작페이지, 끝페이지, 발행기관 관리번호, 논문명, 대등논문명, 저자 , 저널/프로시딩명, 발행기관, 발행년, 발행언어, 권, 호, 시작페이지, 끝페이지, ISBN, ISSN, 주제분야, 키워드, 초록(한글), 초록(영문), 저자(소속기관)
저장형식	Text(ASCII format) Excel format RefWorks Direct Export RIS format (for Reference Manager, ProCite, EndNote), Scholar's Aids, Mendeley
메일정보	받는사람 (필수) @ 보내는사람 (선택) @ 제목 내용 KISTI 검색결과 이메일 서비스
안내	총 건의 자료가 검색되었습니다. 다운받으실 자료의 인덱스를 입력하세요. (1-10,000) 검색결과의 순서대로 최대 10,000건 까지 다운로드가 가능합니다. 데이타가 많을 경우 속도가 느려질 수 있습니다.(최대 2~3분 소요) 다운로드 파일은 UTF-8 형태로 저장됩니다. 파일의 내용이 제대로 보이지 않을실 때는 웹브라우저 상단의 보기 -> 인코딩 -> 자동선택 여부를 확인하십시오. ~ Text(ASCII format) Excel format

연합인증