Dimensão e efeitos da motivação da informação sobre a aceitação dos usuários da publicidade nas redes sociais
Conteúdo do artigo principal
Resumo
Os meios de comunicação produziram modificações significativas no panorama da comunicação. Os sites de rede sociais (SRS) cresceram como uma plataforma comum para a interação social. As empresas de SRS geram receitas de publicidade que aparecem nos SRS. A sobrevivência dessas empresas depende da aprovação dos usuários de publicidade nas redes sociais (PRS). A literatura sobre o marketing indica que os usuários aceitam a publicidade se esta for compatível com as suas motivações para o uso de meios de comunicação sociais. A busca de informações, assim como as pesquisas que avaliam a influência da motivação da informação do SRS sobre a aprovação dos usuários de PRS, é a motivação mais reconhecida dos SRS. Baseado na teoria de usos e gratificações do SRS, este estudo propõe um modelo multidimensional que mostra a influência da motivação da informação do SRS na aprovação de usuários de PRS.
Downloads
Métricas
Detalhes do artigo
A RAE compromete-se a contribuir com a proteção dos direitos intelectuais do autor. Nesse sentido:
- adota a licença Creative Commoms BY (CC-BY) em todos os textos que publica, exceto quando houver indicação de específicos detentores dos direitos autorais e patrimoniais;
- adota software de detecção de similaridades;
- adota ações de combate ao plagio e má conduta ética, alinhada às diretrizes do Committee on Publication Ethics (COPE)
Referências
Al Jenaibi, B. N. A. (2011). Use of social media in the United Arab Emirates: An initial study. Global Media Journal (Arabian Edition), 1(2), 3-27.
Al-Menayes, J. J. (2015). Motivations for using social media: An exploratory factor analysis. Journal of Psychological Studies, 7(1), 43- 50. doi:10.5539/ijps.v7n1p43
Ancu, M., & Cozma, R. (2009). MySpace politics: Uses and gratifications of befriending candidates. Journal of Broadcasting & Electronic Media, 53(4), 567-583. doi:10.1080/08838150903333064
Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411-423. doi:10.1037/0033-2909.103.3.411
Bentler, P. M., & Bonnet, D. C. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88(3), 588-606. doi:10.1037/0033-2909.88.3.588
Bloch, P. H., Sherrell, D. L., & Ridgway, N. M. (1986). Consumer search: An extended framework. Journal of Consumer Research, 13(1), 119- 126. doi:10.1086/209052
Boyd, D. M., & Ellison, N. B. (2007). Social network sites: Definition, history, and scholarship. Journal of Computer-Mediated Communication, 13(1), 210-230. doi:10.1111/j.1083-6101.2007.00393.x
Briggs, R., & N. Hollis, N. (1997). Advertising on the web: Is there response before click-through?. Journal of Advertising Research, 37(2), 33-45.
Burgess, D. (2015). Online banner adverts: More than the final click. Journal of Student Research, 4(2), 94-104.
Byrne, B. M. (2001). Structural equation modeling with Amos: Basic concepts, applications and programming. New Jersey, USA: Lawrence Erlbaum Associates.
Chatterjee, P. (2008). Are unclicked ads wasted? Enduring effects of banner and pop-up ad exposures on brand memory and attitudes. Journal of Electronic Commerce Research, 9(1), 51-61.
Chen, H. (2012). Relationship between motivation and behavior of SNS user. Journal of Software, 7(6), 1265-1272. doi:10.4304/jsw.7.6.1265-1272
Chew, E. (1994). The relationship of information needs to issue relevance and media use. Journalism Quarterly, 71(3), 676-688. doi:10.1177/107769909407100318
Chi, H-H. (2011). Interactive digital advertising vs. virtual brand community: Exploratory study of user motivation and social media marketing responses in Taiwan. Journal of Interactive Advertising, 12(1), 44-61. doi:10.1080/15252019.2011.10722190
Chou, S-Y., Rashad, I., & Grossman, M. (2008). Fast-food restaurant advertising on television and its influence on childhood obesity. Journal of Law and Economics, 51(4), 599-618. doi:10.1086/590132
Chu, S-C. (2011). Viral advertising in social media: Participation in Facebook groups and responses among college-aged users. Journal of Interactive Advertising, 12(1), 30-43. doi:10.1080/15252019.2011. 10722189
Chu, S-C., & Kim, Y. J. (2011). Determinants of consumer engagement in electronic word-of-mouth (eWOM) in social networking sites. International Journal of Advertising, 30(1), 47-75. doi:10.2501/IJA-30-1-047-075
Cisco. (2012). Digital signage for retail: Attract and keep your customers. Recuperado de www.cisco.com/go/retailsolutions
Clark, L. A., & Watson, D. (1995). Constructing validity: Basic issues in objective scale development. Psychological Assessment, 7(3), 309- 319. doi:10.1037/1040-3590.7.3.309
Densten, I. L. (2002). Clarifying inspirational motivation and its relationship to extra effort. Leadership & Organization Development Journal, 23(1), 40-44. doi:10.1108/01437730210414553
Diddi, A., & LaRose, R. (2006). Getting hooked on the news: Uses and gratifications and the formation of news habits among college students in an internet environment. Journal of Broadcasting & Electronic Media, 50(2), 193-210. doi:10.1207/s15506878jobem5002_2
Dunn, S. C., Seaker, R. F., & Waller, M. A. (1994). Latent variables in business logistics research: Scale development and validation. Journal of Business Logistics, 15(2), 145-172
Fabrigar, L. R., Wegener, D. T., MacCallum, R. C., & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4(3), 272-299. doi:10.1037/1082- 989X.4.3.272
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behaviour: An introduction to theory and research. Reading, UK: Addison-Wesley.
Floyd, F. J., & Widaman, K.F. (1995). Factor analysis in the development and refinement of clinical assessment instruments. Psychological Assessment, 7(3), 286-299. doi:10.1037/1040-3590.7.3.286
Fornell, C., & Larcker, D. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. doi:10.2307/3151312
Gefen, D., & Straub, D. (2005). A practical guide to factorial validity using PLS-graph: Tutorial and annotated example. Communications of the Association for Information Systems, 16(5), 91-109
Goldsmith, R. E., & Horowitz, D. (2006). Measuring motivations for online opinion seeking. Journal of Interactive Advertising, 6(2), 214. doi:10.1080/15252019.2006.10722114
Grant, I. C. (2005). Young peoples’ relationships with online marketing practices: An intrusion too far. Journal of Marketing Management, 21(5-6), 607-623. doi:10.1362/0267257054307417
Greer, J. D. (2003). Evaluating the credibility of online information: A test of source and advertising influence. Mass Communication & Society, 6(1), 11-28. doi:10.1207/S15327825MCS0601_3
Ha, H-Y. (2002). The effects of consumer risk perception on prepurchase information in online auctions: Brand, word-of-mouth, and customized information. Journal of Computer Mediated Communication, 8(1). doi:10.1111/j.1083-6101.2002.tb00160.x
Heeler, R. M., & Ray, M. L. (1972). Measure validation in marketing. Journal of Marketing Research, 9(4), 361-370. doi:10.2307/3149297
Hilligoss, B., & Rieh, S. Y. (2008). Developing a unifying framework of credibility assessment: Construct, heuristics, and interaction in context. Information Processing & Management, 44(4), 1467-1484. doi:10.1016/j.ipm.2007.10.001
Hinkin, T. R. (1995). A review of scale development practices in the study of organizations. Journal of Management, 21(5), 967-988. doi:10.1016/0149-2063(95)90050-0
Jansen, B. J., Sobel, K., & Cook, G. (2011). Classifying ecommerce information sharing behavior by youths on social network sites. Journal of Information Science, 37(2), 120-136. doi:10.1177/0165551510396975
Jarvis, C. B., MacKenzie, S. B., & Podsakoff, P. M. (2003). A critical review of construct indicators and measurement model misspecification in marketing and consumer research. Journal of Consumer Research, 30(2), 199-218. doi:10.1086/376806
Johnson, R. E., Rosen. C. C., Chang. C-H. S., Djurdjevic, E., & Taing, M. U. (2012). Recommendations for improving the construct clarity of higher-order multidimensional constructs. Human Resource Management Review, 22(2), 62-72. doi:10.1016/j.hrmr.2011.11.006
Katz, E., Gurevitch, M., & Hass, H. (1973). On the use of mass media for important things. American Sociological Review, 38(2), 164-181. doi:10.2307/2094393
Kim, J. Y., Shim, J. P., & Ahn, K. M. (2011). Social Networking service: Motivation, pleasure, and behavioral intention to use. Journal of Computer Information Systems, 51(4), 92-101. doi:10.1080/08874417.2011.11645505
Kline, R. B. (1998). Principles and practice of structural equation modeling. New York, USA: Guilford Press.
Korgaonkar, P. K., & Wolin, L. D. (1999). A multivariate analysis of web usage. Journal of Advertising Research, 39(2), 53-68
Kuss, D. J., & Griffiths, M. D. (2011). Online social networking and addiction: A review of the psychological literature. International Journal of Environmental Research and Public Health, 8(9), 3528- 3552. doi:10.3390/ijerph8093528
Lancaster, G. A., Dodd, S., & Williamson, P. R. (2004). Design and analysis of pilot studies: Recommendations for good practice. Journal of Evaluation in Clinical Practice, 10(2), 307-312. doi:10.1111/j..2002.384.doc.x
MacCallum, R. C., Browne, M. W., & Sugawara, H. M. (1996). Power analysis and determination of sample size for covariance structure modeling. Psychological Methods, 1(2), 130-149. doi:10.1037/1082-989X.1.2.130
MacKenzie, S. B., Lutz, R. J., & Belch, G. E. (1986). The role of attitude toward the ad as a mediator of advertising effectiveness: A test of competing explanations. Journal of Marketing Research, 23(2), 130- 143. doi:10.2307/3151660
McDonald, R. P., & Ho, M. H. R. (2002). Principles and practice in reporting structural equation analyses. Psychological Methods, 7(1), 64-82. doi:10.1037/1082-989X.7.1.64
Mir, I. A. (2012). Consumer attitudinal insights about social media advertising: A South Asian perspective. The Romanian Economic Journal, 15(45), 265-288
Mir, I. A. (2014). Effects of pre-purchase search motivation on user attitudes toward online social network advertising: A case of university students. Journal of Competitiveness, 6(2), 42-55. doi:10.7441/joc.2014.02.04
Mir, I. A., & Rehman, K. U. (2013). Factors affecting consumer attitudes and intentions toward user-generated product content on YouTube. Management & Marketing, 8(4), 637-654
Mir, I., & Zaheer, A. (2012). Verification of social impact theory claims in social media context. Journal of Internet Banking and Commerce, 17(1). Recuperado de http://www.arraydev.com/commerce/jibc/
Muntinga, D. G., Moorman, M., & Smit, E. G. (2011). Introducing COBRAs: Exploring motivations for brand-related social media use. International Journal of Advertising, 30(1), 13-46. doi:10.2501/IJA-30-1-013-046
Nunnaly, J. (1978). Psychometric theory. New York, USA: McGraw-Hill. O’Donohoe, S. (1994). Advertising uses and gratifications. European Journal of Marketing, 28(8/9), 52-75. doi:10.1108/03090569410145706
Orchard, L. J., Fullwood, C., Galbraith, N., & Morris, N. (2014) Individual differences as predictors of social networking. Journal of Computer Mediated Communication, 19(3), 388-402. doi:10.1111/jcc4.12068
Papacharissi, Z., & Rubin, A. M. (2000). Predictors of internet use. Journal of Broadcasting & Electronic Media, 44(2), 175-196. doi:10.1207/s15506878jobem4402_2
Park, N., Kee, K. F., & Valenzuela, S. (2009). Being immersed in social networking environment: Facebook groups, uses and gratifications, and social outcomes. Cyberpsychology & Behavior, 12(6), 729-733. doi:10.1089/cpb.2009.0003
Pavlou, P. A., & Stewart, D. W. (2000). Measuring the effects and effectiveness of interactive advertising: A research agenda. Journal of Interactive Advertising, 1(1), 61-77. doi:10.1080/15252019.2000.1 0722044
Petter, S., Straub, D., & Rai, A. (2007). Specifying formative constructs in information systems research. MIS Quarterly, 31(4), 623-656. doi:10.2307/25148814
Petrovici, D., & Marinov, M. (2007). Determinants and antecedents of general attitudes towards advertising: A study of two EU accession countries. European Journal of Marketing, 41(3/4), 307-326. doi:10.1108/03090560710728354
Punj, G. N., & Staelin, R. (1983). A model of consumer information search behavior for new automobiles. Journal of Consumer Research, 9(4), 366-380. doi:10.1086/208931
Rieh, S. Y., & Hilligoss, B. (2008). College students’ credibility judgments in the information-seeking process. Digital media, youth, and credibility. In M. J. Metzger & A. J. Flanagin (Eds.), The John D. & Catherine T. MacArthur foundation series on digital media & learning (pp. 49-72). Cambridge, MA: The MIT Press.
Rodgers, S. (2002). The interactive advertising model tested: The role of motives in ad processing. Journal of Interactive Advertising, 2(2), 22-33. doi:10.1080/15252019.2002.10722059
Rodgers, S., Wang, Y., Rettie, R., & Alpert, F. (2007). The web motivation inventory: Replication, extension and application to internet advertising. International Journal of Advertising, 26(4), 447-476. doi:10.1080/02650487.2007.11073028
Rosengren, K. E., Wenner, L. A., & Palmgreen, P. (Eds.) (1985). Media gratifications research: Current perspectives. Beverly Hills, CA: Sage Publications.
Rubin, A. M. (1984). Ritualized and instrumental television viewing. Journal of Communication, 34(3), 67-77. doi:10.1111/j.1460-2466.1984. tb02174.x
Ruggiero, T. E. (2000). Uses and gratifications theory in the 21st century. Mass Communication & Society, 3(1), 3-37. doi:10.1207/ S15327825MCS0301_02
Severin, W. J., & Tankard, J. W. (1997). Communication theories: Origins, methods and uses in the mass media (4th ed.). New York, NY: Longman.
Shore, T. H., Shore, L. M., & Thornton, G. C. III. (1992). Construct validity of self and peer evaluations of performance dimensions in an assessment center. Journal of Applied Psychology, 77(1), 42-54. doi:10.1037/0021-9010.77.1.42
Straub, D. W. (1989). Validating instruments in MIS research. MIS Quarterly, 13(2), 147-169. doi:10.2307/248922
Tavakol, M., & R. Dennick, (2011). Making sense of Cronbach’s alpha. International Journal of Medical Education, 2, 53-55. doi:10.5116/ ijme.4dfb.8dfd
Taylor, D. G., Lewin, J. E., & Strutton, D. (2011). Friends, fans, and followers: Do ads work on social networks? How gender and age shape receptivity. Journal of Advertising Research, 51(1), 258-275. doi:10.2501/JAR-51-1-258-275
Touré-Tillery, M., & Fishbach, A. (2014). How to measure motivation: A guide for the experimental social psychologist. Social and Personality Psychology Compass, 8(7), 328-341. doi:10.1111/spc3.12110
Trusov, M., Bodapati, A. V., & Bucklin, R. E. (2010). Determining influential users in internet social networks. Journal of Marketing Research, 47(4), 643-658. doi:10.1509/jmkr.47.4.643
Weigts, W., Widdershoven, G., Kok, G., & Tomlow, P. (1993). Patients’ information seeking actions and physicians’ responses in gynecological consultations. Qualitative Health Research, 3(4), 398- 429. doi:10.1177/104973239300300402
Wilson, T. D. (1999). Models in information behavior research. Journal of Documentation, 55(3), 249-270. doi:10.1108/EUM0000000007145
Yamane, T. (1967). Statistics: An introductory analysis (2nd ed.). New York, NY: Harper & Row.
Yang, B., Watkins, K. E., & Marsick, V. J. (2004). The construct of the learning organization: Dimensions, measurement, and validation. Human Resource Development Quarterly, 15(1), 31-55. doi:10.1002/ hrdq.1086
Yoo, C. Y. (2008). Unconscious processing of web advertising: Effects on implicit memory, attitude toward the brand, and consideration Set. Journal of Interactive Marketing, 22(2), 2-18.
Zaichowsky, J . L. (1985). Measuring the involvement construct. Journal of Consumer Research, 12(3), 341-352. doi:10.1086/208520