Social media advertising efficiency on higher education programs

  1. Rebeca Cordero-Gutiérrez 13
  2. Eva Lahuerta-Otero 24
  1. 1 School of Languages and Education, Nebrija University, Madrid, Spain,
  2. 2 IME Business School, Salamanca, Spain
  3. 3 Faculty of Computing Science, Pontifical University of Salamanc
  4. 4 Department of Business Administration, Universidad de Salamanca
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Revista:
Spanish journal of marketing-ESIC

ISSN: 2444-9695,  2444-9709

Año de publicación: 2020

Volumen: 24

Número: 2

Páginas: 247-262

Tipo: Artículo

DOI: 10.1108/SJME-09-2019-0075 DIALNET GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: Spanish journal of marketing-ESIC

Resumen

Proposito – El objetivo de esta investigacion es examinar los diferentes resultados y el nivel de éxito obtenido con las campañas publicitarias desarrolladas en Facebook para promover programas de postgrado que aumenten la notoriedad y la participacion de los mismos. Diseño/método/enfoque – Combinamos la técnica de análisis de envolvente de datos (DEA) para medir la eficiencia de la publicidad con la representacion de escalado multidimensional (MDS), ofreciendo alternativas tanto a profesionales como a organizaciones sobre como evaluar el rendimiento de la publicidad social. Hallazgos – Las inversiones en publicidad social pagada son una forma asequible y efectiva tanto para promover programas de postgrado como para crear un compromiso con los posibles estudiantes. Los anuncios en Facebook maximizan la visibilidad, lo que también mejora el posicionamiento social y en línea, fomentando la captacion de estudiantes. Implicaciones prácticas – Las instituciones de educacion superior pueden promover eficazmente sus programas con una inversion social mínima que contribuya a la difusion y el engagement. En comparacion con otras formas de publicidad tradicional o digital, los anuncios de los medios sociales pueden ser eficientes y asequibles, con una segmentacion y opciones de orientacion más amplias. Además, los resultados son inmediatos y cuantificables y las campañas pueden modificarse instantáneamente para adaptarse mejor a las necesidades del público objetivo. Originalidad/valor – Esta investigacion es única ya que ofrece una nueva y alternativa forma de medir la eficiencia, además de los ratios clásicos de los modelos de pago en la publicidad digital que combinan clics e impresiones, en un sector en el que hay pocos estudios empíricos. Además, puede aplicarse fácilmente a muchos otros sectores en organizaciones públicas y privadas

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Información de financiación

This work was supported by the Ministry of Economy and Competitiveness [grant number ECO2017-82107-R] and [grant RTC-2016-5315-6].

Financiadores

Referencias bibliográficas

  • ANA (2019), “Bot baseline 2016-2017. Fraud in digital advertising”, available at: https://cdn2. hubspot.net/hubfs/3400937/2018-2019%20Bot%20Baseline%20Report%20EXECUTIVE %20SUMMARY.pdf
  • Andrews, M. (2017), “Why Facebook ads will make you successful in 2017 and Beyond”, available at: https://blog.hubspot.com/marketing/facebook-ads-successful-2017 (accessed 1 November 2018).
  • Angel, R. and Sexsmith, J. (2011), “Social networking: the corporate value proposition”, Available at: htttp://iveybusinessjournal.com/topics/leadership/social-networking-the-corporate-valueproposition#.VL90JUeG840 (accessed 5 October 2018).
  • Arrosagaray, M., González-Peiteado, M., Pino-Juste, M. and Rodríguez López, B. (2019), “A comparative study of Spanish adult students’ attitudes to ICT in classroom, blended and distance language learning modes”, Computers and Education.
  • Askool, S. and Nakata, K. (2011), “A conceptual model for acceptance of social CRM systems based on a scoping study”,AI and Society, Vol. 26 No. 3, pp. 205-220.
  • Aslam, B. and Karjaluoto, H. (2017), “Digital advertising around paid spaces, E-advertising industry’s revenue engine: a review and research agenda”, Telematics and Informatics, Vol. 34 No. 8, pp. 1650-1662.
  • Awad, N.F. and Krishnan, M.S. (2006), “The personalization privacy paradox: an empirical evaluation of information transparency and the willingness to be profiled online for personalization”, MIS Quarterly, Vol. 30 No. 1, pp. 13-28.
  • Baek, T.H. and Morimoto, M. (2012), “Stay away from me”, Journal of Advertising, Vol. 41 No. 1, pp. 59-76.
  • Beauchamp, M.B. (2013), “Don’t invade my personal space: Facebook’s advertising dilemma”, Journal of Applied Business Research (Jabr), Vol. 29 No. 1, p. 91.
  • Bleier, A. and Eisenbeiss, M. (2015), “The importance of trust for personalized online advertising”, Journal of Retailing, Vol. 91 No. 3, pp. 390-409.
  • Celebi, S.I. (2015), “How do motives affect attitudes and behaviors toward internet advertising and Facebook advertising?”, Computers in Human Behavior, Vol. 51, pp. 312-324.
  • Cho, C.-H. and Cheon, H.J. (2004), “Why do people avoid advertising on the internet?”, Journal of Advertising, Vol. 33 No. 4, pp. 89-97.
  • Cho, V. and Hung, H. (2011), “The effectiveness of short message service for communication with concerns of privacy protection and conflict avoidance”, Journal of Computer-Mediated Communication, Vol. 16 No. 2, pp. 250-270.
  • Choi, S.M. and Rifon, N.J. (2002), “Antecedents and consequences of web advertising credibility: a study of consumer response to banner ads”, Journal of Interactive Advertising, Vol. 3 No. 1.
  • Chu, S.-C. and Kim, Y. (2011), “Determinants of consumer engagement in electronic word-of-mouth (eWOM) in social networking sites”, International Journal of Advertising, Vol. 30 No. 1, pp. 47-75.
  • Cohen, D. (2012), “Brands, maintain a Facebook page, but don’t bother me”, available at: www. allfacebook.com/facebook-page-consumers-2012-02 (accessed 7 October 2018).
  • Colvée, J.L. (2013), Estrategias deMarketing Digital Para Pymes, Valencia: Anetcom.
  • Cordero-Gutiérrez, R. (2018), “Redes sociales horizontales y su impacto en el ámbito empresarial y social”, Tesis doctoral. Universidad de Salamanca. eMarketer (2019), “Digital ad spending worldwide, 2017-2022”, www.emarketer.com/content/emarketer-total-media-ad-spending-worldwide-will-rise-7-4-in-2018 (accessed 29 November 2019).
  • Facebook (2019), “Facebook Q3 2019 results”, available at: https://s21.q4cdn.com/399680738/files/doc_financials/2019/q3/Q3-2019-Earnings-Presentation.pdf (accessed 29 November 2019).
  • García, F., Marcuello, C., Serrano, D., Urbina, O. (1996), “Evaluación de la eficiencia en centros de atención primaria. Una aplicación del análisis envolvente de datos”, Rev Esp Salud Publica, Vol. 70, pp. 211-220.
  • Gotter, A. (2017), “The complete resource to understanding facebook ads cost – 2017 benchmarks!”, available at: https://adespresso.com/blog/facebook-ads-cost/ (accessed 19 October 2018).
  • Hamid, S., Waycott, J., Kurnia, S. and Chang, S. (2015), “Understanding students’ perceptions of the benefits of online social networking use for teaching and learning”, The Internet and Higher Education, Vol. 26 No. 26, pp. 1-9.
  • Heiberger, G. and Harper, R. (2008), “Have you Facebooked Astin lately? Using technology to increase student involvement”, in Junco R. and Timm, D.M. (Eds), Using Emerging Technologies to Enhance Student Engagement: New Directions for Student Services, pp. 19-35, San Francisco, CA: Jossey-Bass.
  • Ho, S.Y. and Bodoff, D. (2014), “The effects of web personalization on user attitude and behavior: an integration of the elaboration likelihood model and consumer search theory”, MIS Quarterly, Vol. 38 No. 2, pp. 497-A10.
  • IAB Spain (2019), “Estudio anual de redes sociales 2019”, available at: https://iabspain.es/estudio/ estudio-anual-de-redes-sociales-2019/ (accessed 29 November 2019).
  • Imlawi, J., Gregg, D. and Karimi, J. (2015), “Student engagement in course-based social networks: the impact of instructor credibility and use of communication”, Computers and Education, Vol. 88, pp. 84-96.
  • Irvine, M. (2018a), “Facebook ad benchmarks for YOUR industry [new data]”, available at: www.wordstream.com/blog/ws/2017/02/28/facebook-advertising-benchmarks (accessed 15 October 2018).
  • Irvine, M. (2018b), “Google ads benchmarks for YOUR industry [updated!]”, available at: www.wordstream.com/blog/ws/2016/02/29/google-adwords-industry-benchmarks (accessed 15 October 2018).
  • Islam, J.U. and Rahman, Z. (2017), “The impact of online Brand community characteristics on customer engagement: an application of stimulus-organism-response paradigm”, Telematics and Informatics, Vol. 34 No. 4, pp. 96-109.
  • Katz, E. and Foulkes, D. (1962), “On the use of the mass media as ‘escape’: clarification of a concept”, Public Opinion Quarterly, Vol. 26 No. 3, pp. 377-388.
  • De Keyzer, F., Dens, N. and De Pelsmacker, P. (2015), “Is this for me? How consumers respond to personalized advertising on social network sites”, Journal of Interactive Advertising, Vol. 15 No. 2, pp. 124-134.
  • Kim, Y.J. and Han, J.Y. (2014), “Why smartphone advertising attracts customers: a model of web advertising, flow, and personalization”, Computers in Human Behavior , Vol. 33, pp. 256-269.
  • Kruskal, J.B. (1964), “Nonmetric multidimensional scaling: a numerical method”, Psychometrika, Vol. 29 No. 2, pp. 115-129.
  • Lahuerta-Otero, E. and Cordero-Gutiérrez, R. (2016), “Looking for the perfect tweet. The use of data mining techniques to find influencers on twitter”, Computers in Human Behavior, Vol. 64, pp. 575-583.
  • Lahuerta-Otero, E., Cordero-Gutiérrez, R. and de la Prieta-Pintado, F. (2018), “Retweet or like? That is the question”,Online Information Review, Vol. 42 No. 5, pp. 562-578.
  • Lam, T., Cho, V. and Qu, H. (2007), “A study of hotel employee behavioral intentions towards adoption of information technology”, International Journal of Hospitality Management, Vol. 26 No. 1, pp. 49-65.
  • Lee, J. and Hong, I.B. (2016), “Predicting positive user responses to social media advertising: the roles of emotional appeal, informativeness, and creativity”, International Journal of Information Management, Vol. 36 No. 3, pp. 360-373.
  • Li, H., Edwards, S.M. and Lee, J.H. (2002), “Measuring the intrusiveness of advertisements: Scale development and validation”, Journal of Advertising, Vol. 31 No. 2, pp. 37-47.
  • Lim, J. and Richardson, J.C. (2016), “Exploring the effects of students’ social networking experience on social presence and perceptions of using SNSs for educational purposes”, The Internet and Higher Education, Vol. 29, pp. 31-39.
  • Luo, X. and Donthu, N. (2005), “Assessing advertising media spending inefficiencies in generating sales”, Journal of Business Research, Vol. 58 No. 1, pp. 28-36.
  • Malhotra, N.K. and Peterson, M. (2001), “Marketing research in the new millennium: emerging issues and trends”,Marketing Intelligence and Planning, Vol. 19 No. 4, pp. 216-235.
  • Manca, S. and Ranieri, M. (2016), “Yes for sharing, no for teaching!: social media in academic practices”, The Internet and Higher Education, Vol. 29, pp. 63-74.
  • Martí-Parreño, J., Sanz-Blas, S., Ruiz-Mafé, C. and Aldás-Manzano, J. (2013), “Key factors of teenagers’ mobile advertising acceptance”, Industrial Management and Data Systems, Vol. 113 No. 5, pp. 732-749.
  • Moe, W.W. (2006), “A field experiment to assess the interruption effect of pop-up promotions”, Journal of Interactive Marketing, Vol. 20 No. 1, pp. 34-44.
  • Ozkan, S. and Koseler, R. (2009), “Multi-dimensional students’ evaluation of e-learning systems in the higher education context: an empirical investigation”, Computers and Education, Vol. 53 No. 4, pp. 1285-1296.
  • Pasadeos, Y. (1990), “Perceived informativeness of and irritation with local advertising”, Journalism Quarterly, Vol. 67 No. 1, pp. 35-39.
  • Peslak, A., Ceccucci, W. and Sendall, P. (2012), “An empirical study of social networking behavior using theory of reasoned action”, Journal of Information Systems Applied Research, Vol. 5 No. 3, p. 12.
  • Pew Research Center (2018), “Social media use in 2018”, Available at: www.pewresearch.org/internet/ wp-content/uploads/sites/9/2018/02/PI_2018.03.01_Social-Media_FINAL.pdf
  • Rueda, L., Benitez, J. and Braojos, J. (2017), “From traditional education technologies to student satisfaction in management education: a theory of the role of social media applications”, Information andManagement, Vol. 54 No. 8, pp. 1059-1071.
  • Russell, R.R. (1985), “Measures of technical efficiency”, Journal of Economy Theory, No. 25, pp. 109-126.
  • Shamdasani, P.N., Stanaland, A.J.S. and Tan, J. (2001), “Location, location, location: insights for advertising placement on the web”, Journal of Advertising Research, Vol. 41 No. 4, pp. 7-21.
  • Shang, J. and Sueyoshi, T. (1995), “A unified framework for the selection of a flexible manufacturing system”, European Journal of Operational Research, Vol. 85 No. 2, pp. 295-315.
  • Shewan, D. (2017), “Does facebook advertising work?”, available at: www.wordstream.com/blog/ws/ 2016/01/25/does-facebook-advertising-work (accessed 30 September 2018).
  • Smit, E.G., Van Noort, G. and Voorveld, H.A. (2014), “Understanding online behavioural advertising: user knowledge, privacy concerns and online coping behaviour in Europe”, Computers in Human Behavior, Vol. 32, pp. 15-22.
  • Speck, P.S. and Elliott, M.T. (1997), “Predictors of advertising avoidance in print and broadcast media”, Journal of Advertising, Vol. 26 No. 3, p. 61.
  • Statista (2019a), “Number of social media users worldwide from 2010 to 2021 (in billions)”, available at: www.statista.com/statistics/278414/number-of-worldwide-social-network-users/ (accessed 29 November 2019).
  • Statista (2019b), “Forecast number of mobile users worldwide from 2019 to 2023 (in billions)”, available at: www.statista.com/statistics/218984/number-of-global-mobile-users-since-2010/ (accessed 29 November 2019).
  • Stelzner, M. (2011), “Social media marketing industry report: how marketers are using social media to grow their businesses”, available at: www.socialmediaexaminer.com/social-mediamarketingindustry-report-2011 (accessed 29 September 2018).
  • Stieglitz, S., Mirbabaie, M., Ross, B. and Neuberger, C. (2018), “Social media analytics–challenges in topic discovery, data collection, and data preparation”, International Journal of Information Management, Vol. 39, pp. 156-168.
  • Tam, K.Y. and Ho, S.Y. (2006), “Understanding the impact of web personalization on user information processing and decision outcomes”,MIS Quarterly, Vol. 30 No. 4, pp. 865-890.
  • Tran, T.P. (2017), “Personalized ads on Facebook: an effective marketing tool for online marketers”, Journal of Retailing and Consumer Services, Vol. 39, pp. 230-242.
  • Truong, Y. and Simmons, G. (2010), “Perceived intrusiveness in digital advertising: strategic marketing implications”, Journal of StrategicMarketing, Vol. 18 No. 3, pp. 239-256.
  • Tucker, C.E. (2014), “Social networks, personalized advertising, and privacy controls”, Journal of Marketing Research, Vol. 51 No. 5, pp. 546-562.
  • Wang, T., Oh, L.-B. and Wang, K. (2009), “Antecedents and consequences of mobile advertising intrusiveness”, paper presented at the 9th International Conference on Electronic Business Macau, China, 30 November – 4 December.
  • Xu, D.J. (2006), “The influence of personalization in affecting consumer attitude toward mobile advertising in China”, Journal Computer Information System, Vol. 47 No. 2, pp. 9-19.
  • Youn, S. and Shin, W. (2019), “Teens’ responses to Facebook newsfeed advertising: the effects of cognitive appraisal and social influence on privacy concerns and coping strategies”, Telematics and Informatics, Vol. 38, pp. 30-45.
  • Yu, J.H. and Cude, B.J. (2009), “Possible disparities in consumers’ perceptions toward personalized advertising caused by cultural differences: US and Korea”, Journal of International Consumer Marketing, Vol. 21 No. 4, pp. 251-269.
  • Obermiller, C. and Spangenberg, E.R. (1998), “Development of a scale to measure consumer skepticism toward advertising”, Journal of Consumer Psychology, Vol. 7 No. 2, pp. 159-186.
Fuente de los datos: Dialnet