A MODEL PROPOSAL FOR AFFECTED FACTORS ON CONSUMERS’ INFORMATION SEEKING BEHAVIOR IN DIFFERENT PRODUCT AND SERVICE CATEGORIES

Yıl 2016, Cilt: 12 Sayı: 27, 43 - 66, 01.01.2016

Yeliz Baş Kazım Mert Remzi Altunışık

https://doi.org/10.17130/10.17130/ijmeb.2016.12.27.924

Öz

Information seeking behavior is examined in two dimensions as internal and external. This behavior takes place in desicion-making processes of consumers before purchasing. The aim of this research is to propose a model that shows some of the differences in product categories by determining efficiencies of variables that affect consumers’ information seeking behavior. To this end, data collected from a face-to-face surveys conducted on participants from a convinience sample on two product furniture and hairdresser services categories were used to test the proposed models. According to the findings, demografic characteristics, perceived risk, product involvement and impulse shopping style have no significant effect on density of information seeking behavior. But, according to product categories, functional, hedonistic style and product familiriaty have effects on either

Anahtar Kelimeler

Information, Information Seeking Behavior, Involvement, Risk, Familiarity, Shopping Style

TÜKETİCİLERİN FARKLI ÜRÜN VE HİZMET KATEGORİLERİNDEKİ BİLGİ ARAMA DAVRANIŞLARINDA ETKİLİ UNSURLAR VE BİR MODEL ÖNERİSİ

Öz

Bilgi arama davranışı, literatürde, içsel ve dışsal olarak iki temel boyutta incelenmektedir. Bu davranışlar, tüketicilerin, bir ürünü satınalmadan önceki karar alma süreçlerinde yerini alan davranışlarıdır. Araştırmanın amacı, tüketicilerin bilgi arama davranışlarını etkileyen değişkenlerin etki derecelerini belirlemeye çalışarak, ürün kategorileri bazındaki farklılıkları gösteren bir model sunmaktır. Bu amaca yönelik olarak iki ürün grubu mobilya ve kuaför hizmetleri üzerinde kolayda örnekleme yöntemine göre seçilen katılımcılar üzerinde, yüz yüze anket yöntemi ile elde edilen verilerden yararlanılmıştır. Araştırma bulgularına göre, bilgi arama davranışı yoğunluklarının değişiminde, demografik özelliklerin, algılanan riskin, ürün ilgileniminin ve plansız alışveriş stilinin bir etkisi görülmemektedir. Ürün kategorilerine göre, fonksiyonel, hazcı stil ve ürün aşinalıklarının etkileri görülmektedir.

Anahtar Kelimeler

Bilgi, Bilgi Arama Davranışları, İlgilenim, Risk, Aşinalık, Alışveriş Stili

Kaynakça

• Alba, J. W., & Marmorstein, H. (1987). The effects of frequency knowledge on consumer decision making. Journal Of Consumer Research, 14, 14-25.
• Altunışık, R., & Baş, Y. (2013). Tüketicilerin ürün satınalma kararları öncesi aradıkları bilgi türlerinin sınıflandırılması üzerine bir araştırma. 13. Beykon Kongresi, Malta.
• Altunışık, R., Coşkun, R., Bayraktaroğlu S., & Yıldırım, E. (2007). Sosyal bilimlerde araştırma yöntemleri: Spss uygulamalı. 5. Baskı, Sakarya: Sakarya Yayıncılık.
• Apil, A. R., Kaynak, E., & Yalçın, S. (2007). Foreign product purchase behavior in transition economies: An empiricial analysis of product information sources among Georgian consumers. Journal Of Promotion Management, 13(3-4), 321-337.
• Arjona, A., & Gomes, C. M. (2011). Trial-by-trial changes in a priori informational value of external cues and subjective expectancies in human auditory attention. Ploseone, 6(6), 1-10.
• Barber, N., Almanza, B., & Dodd, T. (2008). Relationship of wine consumers’ self-confidence, product involvement and packaking cues. Journal Of Foodservice Buseiness Research, 11(1), 45-64.
• Baş, Y., & Altunışık, R. (2013). Ürünler aranan bilgi türlerine göre sınıflandırılabilir mi?. Tüketici ve Tüketim Araştırmaları Dergisi, Journal Of Consumer and Consumption Research, 5(2), 23-69.
• Bei, L. T., & Widdows, R. (1999). Product knowledge and product involvement as moderators of the effects of information on purchase decisions: A case study using the perfect information frontier approach. Journal of Consumer Affairs, 33(1), 165-188.
• Bettman, J. R. (1973). Perceived risk and its components: A model and empirical test. Journal of Marketing Research, 10, 184-189.
• Bettman, J. R., & Park, C. W. (1980). Effects of prior knowledge and experience and phase of the choice process on consumer decision processes: A protocol analysis. Journal of Consumer Research, 7, 234-248.
• Broder, A. (2002). A taxonomy of web search. Sıgır Forum, 36(2), 3–10.
• Brown, S. (1988). Information seeking external search and behaviour: Preliminary evidence from a planned shopping centre. Journal of Marketing Management, 4, 33-45.
• Campbell, M. C., & Goodstein, R. C. (2001). The moderating effect of perceived risk on consumers’ evaluations of product incongruity: Preference for norm. Journal of Consumer Behavior, 28, 439-449.
• Ceci, S., Caves, R. D., & Howe, M. J. A. (1981). Childrens’ long-term memory for information that is incongruous with their prior knowledge. British Journal of Pschology, 72, 443- 450.
• Chaudhuri, A. (2000). A macro analysis of the relationship of product involvement and information search: The role of risk. Winter, Journal of Marketing Theory and Practice, University of Connecticut, 11-14.
• Chen, F. P., & Leu, J. D. (2011). Product involvement in the link between skeptism toward advertising and its effects. Social Behavior and Personality, 39(2), 153-160.
• Chen, Y. F., & Wang, Y. J. (2010). Effect of herd cues and product involvement on bidder online choises. Cyberpsychology, Behavior and Social Networking, 13(4), 423-428.
• Chow, A., & Croxton, R. A. (2012). Information-seeking behavior and reference medium preferences. Reference and Services Quarterly, 51(3), 246-262.
• Cochrane, L.,& Quester, P. (2005). Fear in advertising: The influence of consumers’ product involvement and culture. Journal of International Consumer Marketing, 17(2/3), 7-31.
• Connor, L. O., & Lundstorm, K. (2011). The impact of scial marketing stategies on the information seeking behaviors f college students. Reference and Users Services Quarterly, 50(4), 351-365.
• Davey, B., & Kapinus, B. A. (1985). Prior knowledge and recall of unfamiliar information: Readder and text factors. The Journal of Educational Research, 78(3), 147-151.
• Earp, V. J. (2008). Information source preferences of education graduate students. Behavioral & Social Sciences Librarian, 27(2), 73-91.
• Eynon, R., & Maimberg, L. E. (2012). Understanding the online information-seeking behaviors of young people: The role of networks of support. Journal of Computer Assisted Learning, 28, 514-529.
• Fan, W. (2011). Social influences, schoolmotivatin and gender differences: An application of the expectancy-value theory. Educational Pschology, 31(2), 157-175.
• Feick, L., Park, C.W., & Mothersbaugh, D.L. (1992). Knowledge and knowledge of knowledge: What we know, what we think we know and why the difference makes a difference. Advances in Consumer Research, 19, 190-200.
• Fiske, C. A., Luebbenhussen, L. A., Miyazaki, A. D., & Urbany, J. (1994). The knowtedge- search relationship: It depends. In Advances In Consumer Research, 22, Chris T. Atten Ve Deborah Roedder John (1994), Association For Consumer Research, ss.43-50.
• Gao, G., Veeman, M., & Adamowicz, W. (2005). Consumers’ search behavior for gm food information. Journal of Public Affairs, 5, 217-225.
• Grant, R., Clarke, R. J., & Kyriazis, E. (2007). A review of factors affecting online consumer search behavior from an information value perspective. Journal of Marketing Management, 23(5-6), 519-533.
• Hajiha, A., Ghaffari F., & Tehrani, N. G. (2010). A study of the role of perceived risk and user characteristics in intermet purchase intention. World Academy of Science, Engineering And Tehnology, 66, 43-47.
• Halder, S., Ray, A., & Chakrabarty, P. K. (2010). Gender differences in information seeking behavior in three universities in West Bengal, India. The International Information & Library Review, 42(4), 242-251.
• Hallyburton, A., & Evarts, L. A. (2014). Gender and online health information seeking: A five survey meta-analysis. Journal of Consumer Health on The Internet, 18(2), 128-142.
• Hovick, S. R., Liang, M. C., & Kahlor, L. (2014). Predicting cancer risk knowledge and information seeking: The role of social and cognitive factors. Health Communication, 29, 656–668.
• Hupfer, M. E., & Detlor, B. (2006). Gender and web information seeking: A self-concept orientation model. Journal of The Amerıcan Society For Information Science and Technology, 57(8), 1105–1115.
• Huurne, E. T., & Gutteling, J. (2008). Information needs and risk perception as predictors of risk information seeking. Journal Of Risk Research, 11(7), 847–862.
• Jaidi, Yasmina, Van Hooft, E. A. J., & Arends, L. R. (2011). Recruiting highly educated graduates: A study on the relationship between recruitment ınformation sourees, the theory of planned behavior, and actual job pursuit. Human Performance, 24, 135-157.
• Jensen, H. H., & Kesavan, T. (1993). Sources of information, consumer attitudes on nutrition, and consuption of dairy products. The Journal of Consumer Affairs, 27, 357-376.
• Jin, S. A. A. (2009). Modality effects in second life: The mediating role of social presence and the moderating role of product involvement. Cyberrpsychology and Behavior, 12(6), 717-721.
• Kahlor, L. A. (2007). An augmented risk information seeking model: The case of global warming. Media Psychology, 10, 414–435.
• Kahlor, L. (2010), Prism: A planned risk information seeking model, Health Communication, 25, 345–356.
• Kapferer, J. N., & Laurent, G. (1985). Consumers’ Involvement Profile: New Empirical Results,. Advances in Consumer Research Volume 12, Eds. Elizabeth C. Hirschman & Moris B. Holbrook, Provo, Ut: Association For Consumer Research, 290-295
• Kellens, W., Zaalberg, R., & De Maeyer, P. (2012). The informed society: An analysis of the public’s information-seeking behavior regarding coastal flood risks. Risk Analysis, 32(8), 1369-1381.
• Kım, S., & Matthew, S. (2011). Hedonic tendencies and the online consumer: An investigation of the online shopping process. Journal of Internet Commerce, 10(1), 68-90.
• Kim, S. B., Choi, K. W., & Kim, D. Y. (2013). The motivations of college students’ use od social networking sites in travel information search behavior: The mediating effect of ınteracting with other users. Journal of Travel and Trousim Marketing, 30, 238-252.
• Kink, N., & Hess, T. (2008). Search engines as subsitutes for traditional information surces? An investigation of media s-choice. The Information Society, 24, 18-29.
• Korgaonkar, P., & Karson, E. J. (2007). The influence of perceived risk on consumers’ e-trailer shopping preference, Journal of Business Psychology, 22, 55-64.
• Kuhlthau, C. C. (1998). The role of experience in the information search process of an early career information worker: Perceptions of uncertainty, coplexity, construction, and sources. Journal of The American Society for Information Science, 50(5), 399-412.
• Lastovicka, J. L. & Gardner, D. M. (1979). Components Of Involvement. In: Maloney, J.C., Silverman, B. (Eds.), Attitude Research Plays For High Stakes, American Marketing Association Proceedings, 53-73.
• Lee, Y., Park, J., & Widdows, R. (2009). Exploring antecedents of consumer satisfaction and repeated search behavior on e-health ınformation. Journal of Health Communication, 14, 160-173.
• Lin, P. J., Jones, E., & Westwood, S. (2009), Perceived risk and risk-relievers in online travel pruchase intentions, Journal of Hospitality Marketing and Management, 18, 782-810.
• Lo, A., Cheung, C., & Low, R. (2002). Information search behavior of Hong Kong’s inbound travelers-a camperison of business and leisure travelers. Journal of Travel and Tourism Marketing, 13(3), 61-81.
• Lorence, D., & Park, H. (2007). Study of education disparities and health information seeking behavior. Cyberpsychology & Behavior, 10(1), 149-151.
• Michel, D. A. (1994). What is used during cognitive processing in information retrieval and library searching? Eleven sources of search information. Journal of The American Society for Information Science, 45(7), 498-514.
• Moore, J. L., Erdelez S., & He, W. (2007). The search experience variable in information behavior research. Journal of American Society for Information Science and Technology, 58(10), 1529-1546.
• Moorman, C., & Rindfieisch, A. (1995). Divergent perspectives on the role of prior knowledge in consumer information search and processing. Advances in Consumer Research, 22, 564.
• Morrison, E. W., & Vancouver, J. B. (2000). Within-person analysis of information seeking: the effects of perceived costs and benefits. Journal of Management, 26(1), 119-137.
• Newman, J. W., (1977). Consumer External Search: Amount And Determinants. In Consumerand Industrial Buying Behavior, Eds, Arch G, Woodside.
• Niu, X., & Hemminder B. M. (2012). A study of factors affect the information-seeking behavior of academic scientists. Journal of American Society for Information Science and Technology, 63(29), 336-353.
• Ozanne, J. L., Brucks M., & Grewal, D. (1992). A study of information search behavior during the categorization of new products. Journal of Consumer Behavior Research, 18, 452- 463.
• Park, S. V., & Kim, D. Y. (2009). Information search behaviors of colege students for spring break trip in The USA: An applicatin of specialization concept. Journal of Travel and Tourism Marketing, 26(7), 640-655.
• Peterson, R. A., & Merino, M. C. (2003). Consumer information search behavior and the internet. Psychology and Marketing, 20, 99-121.
• Punj, G. N., & Staetin, R. (1983). A model of consumer information search behavior for new automobites. Journal of Consumer Research, 9, 366-380.
• Rose, D. E., & Levinson, D. (2004, May). Understanding user goals in web search. New York, Usa.
• Rose, D. E. (2006). Reconciling information-seeking behavior with search user interfaces for the web. Journal of Amerikan Society for Information Science and Technology, 57(6), 797-799.
• Sacchi, S., & Burigo, M. (2008). Strategies in the information search process: Interaction among task structure, knowledge, and source. The Journal of General Psychology, 135(3), 252-270.
• Sahib, N. G., Tombros A., & Stockman, T. (2012). A comparative analysis of information- seeking behavior of visually impaired and sighted searchers. Journal of The American Society for Information Science and Technology, 63(2), 377-391.
• Sarkar, A. (2011). Impact of utilitairan and hedonic shopping values on individual’s perceived benefits and risks in online shopping. International Management Review, 7(1), 58-65.
• Selnes, F., & Howell, R. (1999). The effect of product expertise on decision making and search for written and sensory information. Advances In Consumer Research, 26, 80-89.
• Siddique, M., & Momin A. (2013). Expaining the role of perceived risk, knowledge, price and cost in dry fish consumption within the theory of planned behavior. Journal of Global Marketing, 25(4), 181-201.
• Smith, J. L. (1996). Expectncy, value and attitudinal semantics. European Journal of Social Pschologh, 26, 301-306.
• Song, H., Cramer, E. M., Mcroy, S., & May, A. (2013). Information needs, seeking behaviors, and support among low-income expectant women. Women & Health, 53(8), 824-842.
• Spence, H. E., Engel, J. F., & Blackwell, R. D. (1970). Perceived risk in mail-order and retail store buying. Journal of Marketing Research, 7, 364-369.
• Taylor, N. J., Dennis, A. R., & Cummings, J. W. (2013). Situation normality and the shape of search: the effects of time delays and information presentation on search behavir. Journal of American Society for Information Science and Technology, 64(5), 909-928.
• Trumbo, C. W., & Mccomas, K. A. (2003). The function of credibility information processing for risk perception. Risk Analysis, 23(2), 343-353.
• Wakebe, T., Sato T., Watamura E., & Takano, Y. (2012). Risk aversion in information seeking. Journal of Cogitive Psychology, 24(2), 125-133.
• Zaickowsky, J. L. (1985, December). Measuring the involvement construct. The Journal of Consumer Research, 350.
• Zhou, Y., Poon, P., & Huang, G. (2012). Corporate ability and corporatte social responsability in a developing country: The role of product involvement. Journal of Global Marketing, 25, 45-56.