Factors Affecting Location-Based Mobile Advertising Effects : an Integrative Perspective

• Autorzy: Jarosław Woźniczka

Warianty tytułu

Czynniki różnicujące efekty reklamy mobilnej opartej na geolokalizacji odbiorcy : podejście zintegrowane

• Języki publikacji: EN

Abstrakty

EN

Design/methodology/approach: In this conceptual article, previous research on LBMA effects are examined and synthesized, and the hypothesized, integrative model of the factors affecting these effects is developed.

Findings: A growing body of research is dedicated to identifying the communication effects of LBMA and the factors affecting them. Based on the results of that research and utilizing an integrative approach, six groups of variables were distinguished as the contextual framework for further studies on LBMA effects.

Research limitations/implications: The research proposition needs further literature studies and empirical testing. It implies research on the potential impact of various factors on LBA effects, such as multiple consumer traits and behaviors, situational context or marketing actions. The suggestions for further research are presented in the article.

Practical implications: According to forecasts, the contextual advertising, primarily LBMA, will be growing in the future in terms of expenditures and its significance in the integrated marketing communications. Identifying the factors affecting the effects of LBMA will help practitioners to tailor advertising messages to the target customers' location and to improve the effectiveness of their communication programs.

Originality/value: This article synthesizes the results of the previous research on the effects of LBMA and proposes an integrative contextual framework reflecting the hypothesized relationships between the groups of variables and LBMA effects. (original abstract)

Cel: syntetyczny przegląd wyników dotychczasowych badań nad efektami reklamy mobilnej opartej na geolokalizacji odbiorcy oraz przedstawienie propozycji zintegrowanego ujęcia czynników różnicujących te efekty.

Metodologia: artykuł ma charakter koncepcyjny. Przedstawiono w nim i zsyntetyzowano wyniki dotychczasowych badań nad efektami reklamy mobilnej opartej na geolokalizacji odbiorcy oraz zaproponowano hipotetyczny, zintegrowany model obrazujący oddziaływanie różnorodnych czynników na te efekty.

Wyniki: integrując wyniki coraz liczniejszych badań nad efektami reklamy mobilnej opartej na geolokalizacji odbiorcy i ich efektami przedstawiono ramowy model kontekstowy zawierający sześć grup zmiennych oddziałujących na efekty tej reklamy jako propozycję do dalszych badań.

Ograniczenia/implikacje badawcze: przedstawiona propozycja badawcza wymaga dalszych studiów literaturowych i empirycznej weryfikacji. Niezbędne jest badanie potencjalnego wpływu wyróżnionych czynników na efekty reklamy mobilnej opartej na geolokalizacji odbiorcy, takich jak określone cechy i zachowania odbiorców reklamy, kontekst sytuacyjny oraz działania marketingowe. W artykule przedstawiono sugestie dla dalszych badań w tym zakresie.

Oryginalność/wartość: artykuł zawiera syntezę wyników dotychczasowych badań nad efektami reklamy mobilnej opartej na geolokalizacji odbiorcy i propozycję zintegrowanego modelu obrazującego hipotetyczne związki między wyróżnionymi grupami czynników a efektami reklamy mobilnej opartej na geolokalizacji odbiorcy. (abstrakt oryginalny)

Słowa kluczowe

EN

Internet advertising; Multimedia advertising; Geolocalization; Advertising efficiency

PL

Reklama w internecie; Reklama multimedialna; Geolokalizacja; Efektywność reklamy

• Czasopismo: Problemy Zarządzania
• Rocznik: 2021
• Tom: 19
• Numer: nr 1 (91) Digital Transformation - Marketing, Trade, Consumption
• Strony: 107--123

Twórcy

autor

Jarosław Woźniczka

• Uniwersytet Ekonomiczny we Wrocławiu

Bibliografia

• 1. Andrews, M., Andrews, M., Luo, X., Fang, Z., & Ghose, A. (2016). Mobile ad effectiveness: Hyper-contextual targeting with crowdedness. Marketing Science, 35(2), 218-233. http://doi.org/10.1287/mksc.2015.0905.
• 2. Baker W.E., & Lutz, R.J. (2000). An empirical test of an updated relevance-accessibility model of advertising effectiveness. Journal of Advertising, 29(1), 1-14. https://doi.org/10.1080/00913367.2000.10673599.
• 3. Banerjee, S., & Dholakia, R.R. (2008). Mobile advertising: does location-based advertising work? International Journal of Mobile Marketing, 3(2), 68-75.
• 4. Banerjee, S., & Dholakia, R.R. (2012). Location-based mobile advertisements and gender targeting. Journal of Research in Interactive Marketing, 6(3), 198-214. https://doi.org/10.1108/17505931211274679.
• 5. Barry, T.E., & Howard, D.J. (1990). A review and the critique of hierarchy of effects in advertising. International Journal of Advertising, 9(2), 121-135. https://doi.org/10.1080/02650487.1990.11107138.
• 6. Bart, Y., Stephen, A.T., & Sarvary, M. (2014). Which products are best suited to mobile advertising? A field study of mobile display advertising effects on consumer attitudes and intentions. Journal of Marketing Research, 51(3), 270-285. https://doi.org/10.1509/jmr.13.0503.
• 7. Bauer, C., & Strauss, C. (2016). Location-based advertising on mobile devices. A literature review and analysis. Management Review Quarterly, 66(3), 159-194. https://doi.org/10.1007/s11301-015-0118-z.
• 8. Berg Insight (2018). Location-based advertising and marketing report. Retrieved on 26 August 2019 from www.berginsight.com.
• 9. Bruner II, G.C., & Kumar, A. (2007). Attitude towards location based advertising. Journal of Interactive Advertising, 7(2), 3-15. https://doi.org/10.1080/15252019.2007.
• 10. Chang, R.M., Kauffman, R.J., & Kwon, Y. (2014). Understanding the paradigm shift to computational social science in the presence of big data. Decision Support Systems, 63, 67-80. https://doi.org/10.1016/j.dss.2013.08.008.
• 11. Chen, P.-T., Cheng, J.Z., Yu, Y.-W., & Ju, P.-H. (2014). Mobile advertising setting analysis and its strategic implications. Technology in Society, 39, 129-141. https://doi.org/10.1016/j.techsoc.2014.09.004.
• 12. Chen, P.-T., & Hsieh, H.-P. (2012). Personalized mobile advertising: Its key attributes, trends, and social impact. Technological Forecasting and Social Change, 79(3), 543-557. https://doi.org/10.1016/j.techfore.2011.08.011.
• 13. Drossos, D.A., Kokkinaki, F., Giaglis, G.M., & Fouskas, K.G. (2014). The effects of product involvement and impulse buying on purchase intentions in mobile text advertising. Electronic Commerce Research and Applications, 13(6), 423-430. https://doi.org/10.1016/j.elerap.2014.08.003.
• 14. eMarketer. (2014). Global ad spending growth to double this year. Retrieved on 26 August 2019 from https://www.emarketer.com.
• 15. Fang, Z., Yang, Y., Li, W., & Deng, F. (2014). Quantify sales impact of location-based advertising. International Journal of Mobile Communications, 11(5), 513-529. https://doi.org/10.1504/ijmc.2013.056958.
• 16. Fang, Z., Yang, Y., Xu, Y., & Li, W. (2016). Boost movie ticket sales by location-based advertising: a Bayesian VAR approach. Journal of Media Economics, 29(3), 125-138. https://doi.org/10.1080/08997764.2016.1206906.
• 17. Feng, X., Fu, S., & Qin, J. (2016). Determinants of consumers' attitudes toward mobile advertising: The mediating roles of intrinsic and extrinsic motivations. Computers in Human Behavior, 63(C), 334-341. https://doi.org/10.1016/j.chb.2016.05.024.
• 18. Gidofalvi, G., Larsen, H.R., & Pedersen, T.B. (2008). Estimating the capacity of the location-based advertising channel. International Journal of Mobile Communications, 6(3), 357-375. https://doi.org/10.1504/IJMC.2008.017516.
• 19. Gilbert, A.L., & Han, H. (2005). Understanding mobile data services adoption: Demography, attitudes or needs? Technological Forecasting and Social Change, 72(3), 327-337. https://doi.org/10.1016/j.techfore.2004.08.007.
• 20. Hong, S.-J., Thong, J.Y.L., Moon, J.-Y., & Tam, K.-Y. (2008). Understanding the behavior of mobile data services consumers. Information Systems Frontiers, 10(4), 431-445. https://doi.org/10.1007/s10796-008-9096-1.
• 21. Hsieh, A.-Y., Lo, S.-K., Chiu, Y.-P. (2016). Where to place online advertisements? The commercialization congruence between online advertising and web site context. Journal of Electronic Commerce Research, 17(1), 36-46.
• 22. Hühn, A.F., Khan, V.J, Ketelaar, P., van 't Riet, J., Konig, R., Rozendaal, E., Batalas, N., Markopoulos, P. (2017). Does location congruence matter? A field study on the effects of location-based advertising on perceived ad intrusiveness, relevance & value. Computers in Human Behavior, 73, 659-668.
• 23. Islam, M., & Kang, M. (2019). Consumers' cultural attitude toward mobile advertising: An empirical investigation among different national cultures. Journal of Theoretical and Applied Information Technology, 97(5), 1581-1594.
• 24. Izquierdo-Yusta, A., Olarte-Pascual, C., & Reinares-Lara, E. (2015). Attitudes toward mobile advertising among users versus non-users of the mobile Internet. Telematics and Informatics, 32(2), 355-366. https://doi.org/10.1016/j.tele.2014.10.001.
• 25. Jansen, B.J., Sobel, K., & Zhang, M. (2011). The brand effect of key phrases and advertisements in sponsored search. International Journal of Electronic Commerce, 16(1), 77-106. https://doi.org/10.2753/JEC1086-4415160103.
• 26. Kaasinen, A., & Yoon, Y.-I. (2013). Service engagement model for mobile advertising based on user behavior. In International Conference on Information Networking Proceedings (pp. 131-134). Bangkok: IEEE.
• 27. Ketelaar, P.E., Bernritter, S.F., van't Riet, J., Hühn, A.E., van Woudenberg, T.J., Muller, B.C.N., & Janssen, L. (2017). Disentangling location-based advertising: the effects of location congruency and medium type on consumers' ad attention and brand choice. International Journal of Advertising, 36(2), 356-367.
• 28. Ketelaar, P.E., Bernritter, S.F., van Woudenberg, T.J., Rozendaal, E., Konig, R.P., Hühn, A.E., van Gisbergen, M.S., & Janssen, L. (2018). "Opening" location-based mobile ads: How openness and location congruency of location-based ads weaken negative effects of intrusiveness on brand choice. Journal of Business Research, 91, 277-285. https://doi.org/10.1016/j.jbusres.2018.06.018.
• 29. Lee, K.W., & Choo, H. (2016). Predicting user attitudes toward smartphone ads using support vector machine. International Journal of Mobile Communications, 14(3), 226-243. https://doi.org/10.1504/IJMC.2016.076272.
• 30. Lee, S., Kim, K.J., & Sundar, S.S. (2015). Customization in location-based advertising: Effects of tailoring source, locational congruity, and product involvement on ad attitudes. Computers in Human Behavior, 51, 336-343. http://doi.org/10.1016/j.chb.2015.04.049.
• 31. Lee, S.-F., Tsai, C.H., Jih, W.-J. (2006). An empirical examination of customer perceptions of mobile advertising. Information Resources Management Journal, 19(4), 39-55.
• 32. Lee, Y-C. (2018). Comparing factors affecting attitudes toward LBA and SoLoMo advertising. Information Systems & E-Business Management, 16(2), 357-381. https://doi.org/10.1007/s10257-017-0364-9.
• 33. Li, K., & Du, T.C. (2012). Building a targeted mobile advertising system for location-based services. Decision Support Systems, 54(1), 1-8. https://doi.org/10.1016/j.dss.2012.02.002.
• 34. Lin, T.T.C., Paragas, F., & Bautista, J.R. (2016a). Determinants of mobile consumers' perceived value of location-based advertising and user responses. International Journal of Mobile Communications, 14(2), 99-117. https://doi.org/10.1504/IJMC.2016.075019.
• 35. Lin, T.T.C., Paragas, F., Goh, D., & Bautista, J.R. (2016b). Developing location-based mobile advertising in Singapore: A socio-technical perspective. Technological Forecasting & Social Change, 103, 334-349. http://doi.org/10.1016/j.techfore.2015.06.002.
• 36. Luo, X., Andrews, M., Fang, Z.,, & Phang, C. W. (2014). Mobile targeting. Management Science, 60(7), 1738-1756. https://doi.org/10.1287/mnsc.2013.1836.
• 37. Okazaki, S., & Barwise, P. (2011). Has the time finally come for the medium of the future? Research on mobile advertising. Journal of Advertising Research, 51(1), Supplement, 59-71. https://doi.org/10.2501/JAR-51-1-057-071.
• 38. Pedersen, P.E. (2005). Adoption of mobile Internet services: An exploratory study of mobile commerce early adopters. Journal of Organizational Computing and Electronic Commerce, 15(3), 203-222. https://doi.org/10.1207/s15327744joce1503_2.
• 39. Rossiter, J.R., Percy, L., & Bergkvist, L. (2018). Marketing communications. Objectives, strategy, tactics. Sage.
• 40. Shin, W., & Lin, T.T.-C. (2016). Who avoids location-based advertising and why? Investigating the relationship between user perceptions and advertising avoidance. Computers in Human Behavior, 63(C), 444-452. http://doi.org/10.1016/j.chb.2016.05.036.
• 41. Soroa-Koury, S., & Yang, K.C.C. (2010). Factors affecting consumers' responses to mobile advertising from a social norm theoretical perspective. Telematics and Informatics, 27(1), 103-113. https://doi.org/10.1016/j.tele.2009.06.001.
• 42. Statista. (2019). Retrieved on 24 August 2019 from https://www.statista.com.
• 43. Stip, H. (2018). How context can make advertising more effective. Journal of Advertising Research, 58(2), 138-145.
• 44. Trusov, M., Ma, L., & Jamal, Z. (2016). Crumbs of the cookie: user profiling in customerbase analysis and behavioral targeting. Marketing Science, 35(3), 405-426. https://doi.org/10.1287/mksc.2015.0956.
• 45. Tsang, M.M., Ho, S.-C., & Liang, T.-P. (2004). Consumer attitudes toward mobile advertising: an empirical study. International Journal of Electronic Commerce, 8(3), 65-78. https://doi.org/10.1080/10864415.2004.11044301.
• 46. Unni, R., & Harmon, R. (2007). Perceived effectiveness of push vs. pull mobile locationbased advertising. Journal of Interactive Advertising, 7(2), 28-40. https://doi.org/10.1080/15252019.2007.10722129.
• 47. van't Riet, J., Hühn, A., Ketelaar, P., Khan, V. J., Konig, R., Rozendaal, E., & Markopoulos, P. (2016). Investigating the effects of location-based advertising in the supermarket: Does goal congruence trump location congruence? Journal of Interactive Advertising, 16(1), 31-43. https://doi.org/10.1080/15252019.2015.1135089.
• 48. Varnali, K., Yilmaz, C., & Toker, A. (2012). Predictors of attitudinal and behavioral outcomes in mobile advertising: A field experiment. Electronic Commerce Research and Applications, 11(6), 570-581. http://doi.org/10.1016/j.elerap.2012.08.002.
• 49. WARC. (2019). Global ad trends. The adspend outlook: February 2019. Retrieved on 26 August 2019 from https://content. warc.com.
• 50. Wong, C.-H., Tan, G.W.-H., Tan, B.-I., & Ooi, K.-B. (2015). Mobile advertising: The changing landscape of the advertising industry. Telematics and Informatics, 32(4), 720-734. http://doi.org/10.1016/j.tele.2015.03.003.
• 51. Xu, H., Oh, L-B., Teo, H-H. (2009). Perceived effectiveness of text vs. multimedia location-based advertising messaging. International Journal of Mobile Communications, 7(2), 154-177. https://doi.org/10.1504/IJMC.2009.022440.
• 52. Yang, B., Kim, Y., & Yoo, C. (2013). The integrated mobile advertising model: The effects of technology- and emotion-based evaluations. Journal of Business Research, 66(9), 1345-1352. https://doi.org/10.1016/j.jbusres.2012.02.035.
• 53. Zenith (2018). Mobile share of advertising market to exceed 30% in 2020. Retrieved on 26 August 2019 from https://www.zenithmedia.com/insights.

Identyfikatory

DOI

10.7172/1644-9584.91.8