Gender and Web information seeking: A self‐concept orientation model

Wiley - Tập 57 Số 8 - Trang 1105-1115 - 2006
Maureen Hupfer1, Brian Detlor1
1DeGroote School of Business, McMaster University, 1280 Main Street West, Hamilton, Ontario, Canada L8S 4M4

Tóm tắt

AbstractAdapting the consumer behavior selectivity model to the Web environment, this paper's key contribution is the introduction of a self‐concept orientation model of Web information seeking. This model, which addresses gender, effort, and information content factors, questions the commonly assumed equivalence of sex and gender by specifying the measurement of gender‐related self‐concept traits known as self‐ and other‐orientation. Regression analyses identified associations between self‐orientation, other‐orientation, and self‐reported search frequencies for content with identical subject domain (e.g., medical information, government information) and differing relevance (i.e., important to the individual personally versus important to someone close to him or her). Self‐ and other‐orientation interacted such that when individuals were highly self‐oriented, their frequency of search for both self‐ and other‐relevant information depended on their level of other‐orientation. Specifically, high‐self/high‐other individuals, with a comprehensive processing strategy, searched most often, whereas high‐self/low‐other respondents, with an effort minimization strategy, reported the lowest search frequencies. This interaction pattern was even more pronounced for other‐relevant information seeking. We found no sex differences in search frequency for either self‐relevant or other‐relevant information.

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Tài liệu tham khảo

Aiken L., 1991, Multiple regression: Testing and interpreting interactions

Andrews P., 2003, Christmas clicking, U.S. News & World Report, 42

Bakan D., 1966, The duality of human existence

Bazeley M., 2004, New Web tools aim to customize searches, San Jose Mercury News, A1

10.1037/h0036215

10.1086/208856

10.1037/0022-0663.89.2.318

10.1525/9780520924086

Choo C.W., 1999, Proceedings of the 62nd Annual Meeting of the American Society for Information Science held in Washington, D.C., 3

10.5210/fm.v5i2.729

Retrieved May 7 2005 fromhttp://firstmonday.org/issues/issue5 2/choo/index.html

10.1007/978-94-015-9405-9

Cohen J., 1983, Applied multiple regression/correlation analysis for the behavioural sciences

10.1002/9780470316948

Cross S.E., 1993, The psychology of gender, 55

Deaux K., 1987, Analyzing gender: A handbook of social science research, 92

Dryburgh H.(2001).Changing our ways: Why and how Canadians use the Internet. Statistics Canada Catalog No. 56F0006XIE.

Retrieved May 7 2005 fromhttp://www.statcan.ca/english/research/56F0006XIE/56f0006 XIE2000001.pdf

Economist, 2004, E‐commerce takes off, The Economist, 371, 9

Ford F.N., 1996, The impact of decision support training on computer use: The effect of prior training, age, and gender, Journal of End User Computing, 8, 15, 10.4018/joeuc.1996070103

Ford N., 1996, Papers From the Third Electronic Library and Visual Information Research (ELVIRA) Conference, 87

10.1002/asi.1165

10.1016/1041-6080(95)90003-9

10.2307/249720

Gilligan C., 1982, a different voice: Psychological theory and women's development

Hays W.L., 1994, Statistics

10.4018/joeuc.2000100102

Hupfer M.E.(2001).Self‐Concept orientation and response to agentic and communal advertising messages. Unpublished Doctoral Thesis University of Alberta Edmonton.

10.1080/019722499128385

10.1002/1097-4571(2000)9999:9999<::AID-ASI1607>3.0.CO;2-F

10.1287/mnsc.1040.0194

10.1016/S0306-4573(01)00034-6

Lee G., 2000, Cybershoppers: A moving target, Women's Wear Daily Internet Supplement, 10

10.1038/scientificamerican0397-58

10.1038/scientificamerican0397-52

Macklem K., 2000, Women to lead new digital gold rush, Financial Post, C1

10.1037/0033-295X.98.2.224

10.1007/978-1-4612-3588-0_6

10.1086/209133

10.1086/209241

10.1177/002224379102800107

Mood A.M., 1974, Introduction to the theory of statistics

Morahan‐Martin J., 1998, Psychology and the Internet: Intrapersonal, interpersonal, and transpersonal implications, 169

Morrison D.F., 1990, Multivariate statistical methods

Nelson C., 1994, Women's market handbook: Understanding and reaching today's most powerful consumer group

PR Newswire, 2004, College women close technology gender gap, PR Newswire Association

10.1002/asi.20018

10.2190/7BR8-VXA0-07A7-8AVN

10.2190/KCGA-3197-2V6U-WUTH

10.1145/506740.506744

Smith S.M., 2001, Men and women online: What makes them click?, Marketing Research, 13, 20

10.1080/019722499128475

Sparck Jones K., 1997, Readings in information retrieval

10.1037/h0076857

Tabachnik B.G., 2001, Using multivariate statistics

Taylor R.S., 1991, Progress in Communication Sciences, 217

10.1145/545151.545155

10.2307/3250981

10.1002/1097-4571(2000)9999:9999<::AID-ASI1046>3.0.CO;2-W

10.1002/asi.20016

10.1089/109493100316012

10.1108/EUM0000000007145

10.1108/10662240310501658

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Wiley

Tập 57 Số 8

1105-1115

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