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TECHNOLOGY ACCEPTANCE IN SOCIAL MARKETING: AN INVESTIGATION ON PHILANTHROPIC BEHAVIOR

Year 2017, Marketing Congress Special Issue, 1 - 23, 14.06.2017

Abstract

Marketing of social ideas and values to influence behaviors of a target
audience is a challenge for social marketers. It becomes more complicated when
alternative technologies change the acting environment of people, and create
new dynamics to influence their behaviors. Social media, in this context, is a
technology, which invites people to a multi-way communication with an increased
and customized access to a new form of a very dynamic environment. Despite some
challenges, it provides an excessive opportunity to actively communicate and
involve people to social marketing programs, which, at the end, motivates
social behavior change. This power of social media on social marketing programs
recently attracted the attention of practitioners, and thus, several social
campaigns, either by corporate entities or individuals, started to be raised
and communicated through various social media sites. This situation made
consumers, not only the donators but also the organizers of such campaigns,
that is, the actual rule makers, the involvers. This change in the social
marketing practice calls for urgent research in the academy to better
understand the dynamics and the role of online technologies on social marketing
practices. However, research on this field is still left behind the practice.
This study aims to shed light on this area, and focuses specifically on
philanthropic behavior change, which is motivated by online environments.
Research investigates the relationship between technology acceptance dimensions
and people’s involvement activities through online sites. Findings provide
valuable insight to explain the impact of different determinants of technology
acceptance on human behavior for social marketing activities at virtual
platforms. Discussions are raised to both contribute to academic shortfall on
social marketing literature, and to provide more effective programs for the
practice.

References

  • Ajzen, I. and Fishbein, M. (1980) Understanding attitudes and predicting social behaviour.
  • Ajzen, I. (1991) The theory of planned behavior. Organizational behavior and human decision processes 50 (2), 179-211.
  • Andreasen, A. R. (1994). Social marketing: Its definition and domain. Journal of public policy &marketing, 108-114.
  • Andreasen, A. R. (2002). Marketing social marketing in the social change marketplace. Journal of Public Policy & Marketing, 21(1), 3-13.
  • Bagozzi, R. P., and Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74–94.
  • Bandura, A. (1977) Social Learning Theory. Englewood Cliffs, NJ: Prentice Hall.
  • Bandura, A. (1989). Social cognitive theory. In R. Vasta (ed.) Annals of Child Development, Vol. 6, Six theories of child development (pp. 1-60). Greenwich, CT: JAI Press.
  • Bandura, A. (2004) Health promotion by social cognitive means. Health Education Behavior, 31, pp. 143–164.
  • Biernacki, P. and Waldorf, D. (1981) Snowball sampling: Problems and techniques of chain referral sampling. Sociological Methods and Research, 10 (2), 141-163.
  • Bloom, P. N., and Novelli, W. D. (1981). Problems and challenges in social marketing. The Journal of Marketing, 79-88.
  • Browne, K. (2005) Snowball sampling: using social networks to research non‐heterosexual women. International Journal of Social Research Methodology. 8(1), 47-60.
  • Chen, L.-d., Gillenson, M. L., and Sherrell, D. L. (2002). Enticing Online Consumers: An Extended Technology Acceptance Perspective. Information & Management, 39, 705-719.
  • Chin, W. W. and Newsted, P. R. (1999). Structural Equation Modelling: Analysis with Small Samples Using Partial Least Squares’, R. H. Hoyle (Ed.), Statistical Strategies for Small Sample Research, 307-341. Thousand Oaks, CA: Sage.
  • Choi, C. J., Eldomiaty, T. I., and Kim, S. W. (2007). Consumer trust, social marketing and ethics of welfare exchange. Journal of Business Ethics, 74(1), 17-23.
  • Choi, G., and Chung, H. (2013). Applying the Technology Acceptance Model to Social Networking Sites (SNS): Impact of Subjective Norm and Social Capital on the Acceptance of SNS. International Journal of Human-Computer Interaction, 29(10), 619–628. http://doi.org/10.1080/10447318.2012.756333
  • Comegys, C., Hannula, M., and Váisánen, J. (2009). Effects of Consumer Trust and Risk On Online Purchase Decision-Making: A Comparison of Finnish and United States Students. International Journal of Management, 26(2), 295.
  • Dann, S. (2010). Redefining social marketing with contemporary commercial marketing definitions. Journal of Business Research, 63(2), 147-153.
  • Davis, F. D., Bagozzi, R. P., and Warshaw, P. R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management science, 35(8), 982-1003.
  • Fenech, T. (1998). Using perceived ease of use and perceived usefulness to predict acceptance of the World Wide Web. Computer Networks and ISDN Systems, 30(1-7), 629-630.
  • Forsythe, S., Liu, C., Shannon, D., and Gardner, L. C. (2006). Development of a scale to measure the perceived benefits and risks of online shopping. Journal of interactive marketing, 20(2), 55-75.
  • Gefen, D., and Straub, D. W. (2000). The relative importance of perceived ease of use in IS adoption: A study of e-commerce adoption. Journal of the association for Information Systems, 1(1), 8.
  • Gefen, D., Karahanna, E., and Straub, D. W. (2003). Trust and TAM In Online Shopping: An Integrated Model. MIS quarterly, 27(1), 51-90.
  • Goodhue, D. L., and Thompson, R.L. (1995) Task-technology fit and individual performance. MIS quarterly 19 (2), 213-236.
  • Gordon, R. (2012). Re-thinking and re-tooling the social marketing mix. Australasian Marketing Journal (AMJ), 20(2), 122-126.
  • Hill, R. P., and Moran, N. (2011). Social marketing meets interactive media: Lessons for the advertising community. International Journal of Advertising, 30(5), 815-838.
  • Hulland, J. (1999). Use of partial least squares (PLS) in strategic management research: a review of four recent studies. Strategic Management Journal, 20(2), 195–204.
  • Klopping, I. M., and McKinney, E. (2004). Extending the technology acceptance model and the task-technology fit model to consumer e-commerce. Information Technology, Learning, and Performance Journal, 22(1), 35.
  • Kotler, P., and Zaltman, G. (1971). Social marketing: an approach to planned social change. The Journal of Marketing, 3-12.
  • Koufaris, M. (2002). Applying The Technology Acceptance Model and Flow Theory to Online Consumer Behavior. Information Systems Research, 13(2), 205-223.
  • Laroche, M., Yang, Z., McDougall, G. H., & Bergeron, J. (2005). Internet versus bricks-and-mortar retailers: An investigation into intangibility and its consequences. Journal of retailing, 81(4), 251-267.
  • Lefebvre, R. C. (2011). An integrative model for social marketing. Journal of Social Marketing, 1(1), 54-72.
  • Liang, T. P., and Turban, E. (2011). Introduction to the special issue social commerce: a research framework for social commerce. International Journal of Electronic Commerce, 16(2), 5-14.
  • Sashi, C. M. (2012). Customer engagement, buyer-seller relationships, and social media. Management Decision, 50(2), 253-272.
  • Stead, M., Gordon, R., Angus, K. and Mcdermott, L. (2006) A systematic review of social marketing effectiveness. Health Education, 107(2), pp. 126–191.
  • Thackeray, R., Neiger, B. L., Hanson, C. L., & McKenzie, J. F. (2008). Enhancing promotional strategies within social marketing programs: use of Web 2.0 social media. Health promotion practice, 9(4), 338-343.
  • Thackeray, R., Neiger, B. L., and Keller, H. (2012). Integrating Social Media and Social Marketing A Four-Step Process. Health Promotion Practice, 13(2), 165-168.
  • Turan, A. H. (2008): Internet Alışverişi Tüketici Davranışını Belirleyen Etmenler: Geliştirilmiş Teknoloji Kabul Modeli ile Bir Model Önerisi, Akademik Bilişim Dergisi, Ocak-Şubat, ss:723-731.
  • Türker, D. Altuntaş Vural, C. (2016) Kurumsal Sosyal Sorumluluk ve Hayırseverlik (Corporate Social Responsibility and Philanthropy) (s. 149-170). in S. Hoştut ve S.D. Van Het Hof (Eds.) Kurumsal Sosyal Sorumlulukta Güncel Yönelim ve Yaklaşımlar. Ankara: Nobel Yayınevi
  • Van der Heijden, H., Verhagen, T., and Creemers, M. (2003). Understanding online purchase intentions: contributions from technology and trust perspectives. European journal of information systems, 12(1), 41-48.
  • Vinzi, V. E., Trinchera, L., and Amato, S. (2010). PLS Path Modeling: From Foundations to Recent Developments and Open Issues for Model Assessment and Improvement. In. V. Esposito Vinzi, W.W. Chin, J. Henseler & H. Wang (Eds) Handbook of Partial Least Squares: Concepts, Methods and Applications (47-82) Berlin, Germany: Springer Berlin Heidelberg
  • Wong, K. K. (2011). Review of the book Handbook of Partial Least Squares: Concepts, Methods and Applications, by V. Esposito Vinzi, W.W. Chin, J. Henseler & H. Wang (Eds). International Journal of Business Science & Applied Management. 6 (2), 52-54.
  • Yılmaz, C. ve Tümtürk, A. (2015): Internet üzerinden Alışveriş Niyetini Etkileyen Faktörlerin Genişletilmiş Teknoloji Kabul Modeli Kullanarak İncelenmesi ve Bir Model Önerisi, Celal Bayar Universitesi Yönetim ve Ekonomi Dergisi, Cilt 22, Sayı 2, ss: 355-384.
  • http://www.adimadim.org/ (accessed on May 2016)

SOSYAL PAZARLAMADA TEKNOLOJİ KABULÜ: HAYIRSEVERLİK DAVRANIŞLARI ÜZERİNE BİR İNCELEME

Year 2017, Marketing Congress Special Issue, 1 - 23, 14.06.2017

Abstract

Hedef kitlelerin davranışlarını etkilemek
amacıyla topluma fayda sağlayacak fikir, değer veya faaliyetlerin pazarlanması
sosyal pazarlamacıların en temel uğraş alanıdır. Bu uğraş, alternatif
teknolojiler insanların faaliyet alanlarını değiştirdikçe ve davranışlarını
etkileyerek yeni dinamikler yarattıkça daha da karmaşık bir hal almaktadır. Bu
bağlamda sosyal medya insanları oldukça dinamik bir çevreye, kişilere göre
özelleştirilmiş bir giriş yolu sağlayan çift yönlü iletişime davet etmektedir.
Bazı zorluklarına rağmen, en sonunda temel davranış değişikliklerini
gerçekleştirecek şekilde, insanlara sosyal pazarlama programlarını iletmek ve
onları bu programlara dâhil etmek için önemli fırsatlar sunmaktadır. Sosyal
medyanın sosyal pazarlama programları üzerindeki bu gücü yakın zamanda
uygulayıcıların dikkatini çekmiş ve böylece birçok kurumsal veya bireysel
sosyal kampanya sosyal medya kanalları aracılığı ile geliştirilmeye ve
duyurulmaya başlanmıştır. Bu durum “tüketicileri” sadece bağışçı yapmakla
kalmamış, onları bu kampanyaların organizatörü, kural koyucuları haline
getirmiştir. Sosyal pazarlama alanındaki bu değişim çevrimiçi teknolojilerin
sosyal pazarlama üzerindeki rolü ve etkisini araştıracak bilimsel araştırmalara
ihtiyaç doğurmaktadır. Ancak, mevcut haliyle araştırma uygulamanın gerisinde
kalmaktadır. Bu çalışma bu alana ışık tutmayı hedeflemekte ve özellikle
çevrimiçi ortamlar tarafından güdülenen hayırseverlik davranışlarına
odaklanmaktadır. Araştırma, teknoloji kabul modeli boyutları ile insanların sosyal
kampanyalara çevrimiçi kanallar aracılığı ile dâhil olma davranışları
arasındaki ilişkileri incelemektedir. Sonuçlar teknoloji kabul modeli
boyutlarının sosyal pazarlama programları ile hedeflenen davranış
değişikliklerini ne kadar etkilediğini göstermesi açısından önemlidir. Bu
doğrultuda alandaki bilimsel boşluğa katkı yapacak ve uygulayıcılara fikir
oluşturacak bazı öneriler tartışmaya sunulmuştur. 

References

  • Ajzen, I. and Fishbein, M. (1980) Understanding attitudes and predicting social behaviour.
  • Ajzen, I. (1991) The theory of planned behavior. Organizational behavior and human decision processes 50 (2), 179-211.
  • Andreasen, A. R. (1994). Social marketing: Its definition and domain. Journal of public policy &marketing, 108-114.
  • Andreasen, A. R. (2002). Marketing social marketing in the social change marketplace. Journal of Public Policy & Marketing, 21(1), 3-13.
  • Bagozzi, R. P., and Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74–94.
  • Bandura, A. (1977) Social Learning Theory. Englewood Cliffs, NJ: Prentice Hall.
  • Bandura, A. (1989). Social cognitive theory. In R. Vasta (ed.) Annals of Child Development, Vol. 6, Six theories of child development (pp. 1-60). Greenwich, CT: JAI Press.
  • Bandura, A. (2004) Health promotion by social cognitive means. Health Education Behavior, 31, pp. 143–164.
  • Biernacki, P. and Waldorf, D. (1981) Snowball sampling: Problems and techniques of chain referral sampling. Sociological Methods and Research, 10 (2), 141-163.
  • Bloom, P. N., and Novelli, W. D. (1981). Problems and challenges in social marketing. The Journal of Marketing, 79-88.
  • Browne, K. (2005) Snowball sampling: using social networks to research non‐heterosexual women. International Journal of Social Research Methodology. 8(1), 47-60.
  • Chen, L.-d., Gillenson, M. L., and Sherrell, D. L. (2002). Enticing Online Consumers: An Extended Technology Acceptance Perspective. Information & Management, 39, 705-719.
  • Chin, W. W. and Newsted, P. R. (1999). Structural Equation Modelling: Analysis with Small Samples Using Partial Least Squares’, R. H. Hoyle (Ed.), Statistical Strategies for Small Sample Research, 307-341. Thousand Oaks, CA: Sage.
  • Choi, C. J., Eldomiaty, T. I., and Kim, S. W. (2007). Consumer trust, social marketing and ethics of welfare exchange. Journal of Business Ethics, 74(1), 17-23.
  • Choi, G., and Chung, H. (2013). Applying the Technology Acceptance Model to Social Networking Sites (SNS): Impact of Subjective Norm and Social Capital on the Acceptance of SNS. International Journal of Human-Computer Interaction, 29(10), 619–628. http://doi.org/10.1080/10447318.2012.756333
  • Comegys, C., Hannula, M., and Váisánen, J. (2009). Effects of Consumer Trust and Risk On Online Purchase Decision-Making: A Comparison of Finnish and United States Students. International Journal of Management, 26(2), 295.
  • Dann, S. (2010). Redefining social marketing with contemporary commercial marketing definitions. Journal of Business Research, 63(2), 147-153.
  • Davis, F. D., Bagozzi, R. P., and Warshaw, P. R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management science, 35(8), 982-1003.
  • Fenech, T. (1998). Using perceived ease of use and perceived usefulness to predict acceptance of the World Wide Web. Computer Networks and ISDN Systems, 30(1-7), 629-630.
  • Forsythe, S., Liu, C., Shannon, D., and Gardner, L. C. (2006). Development of a scale to measure the perceived benefits and risks of online shopping. Journal of interactive marketing, 20(2), 55-75.
  • Gefen, D., and Straub, D. W. (2000). The relative importance of perceived ease of use in IS adoption: A study of e-commerce adoption. Journal of the association for Information Systems, 1(1), 8.
  • Gefen, D., Karahanna, E., and Straub, D. W. (2003). Trust and TAM In Online Shopping: An Integrated Model. MIS quarterly, 27(1), 51-90.
  • Goodhue, D. L., and Thompson, R.L. (1995) Task-technology fit and individual performance. MIS quarterly 19 (2), 213-236.
  • Gordon, R. (2012). Re-thinking and re-tooling the social marketing mix. Australasian Marketing Journal (AMJ), 20(2), 122-126.
  • Hill, R. P., and Moran, N. (2011). Social marketing meets interactive media: Lessons for the advertising community. International Journal of Advertising, 30(5), 815-838.
  • Hulland, J. (1999). Use of partial least squares (PLS) in strategic management research: a review of four recent studies. Strategic Management Journal, 20(2), 195–204.
  • Klopping, I. M., and McKinney, E. (2004). Extending the technology acceptance model and the task-technology fit model to consumer e-commerce. Information Technology, Learning, and Performance Journal, 22(1), 35.
  • Kotler, P., and Zaltman, G. (1971). Social marketing: an approach to planned social change. The Journal of Marketing, 3-12.
  • Koufaris, M. (2002). Applying The Technology Acceptance Model and Flow Theory to Online Consumer Behavior. Information Systems Research, 13(2), 205-223.
  • Laroche, M., Yang, Z., McDougall, G. H., & Bergeron, J. (2005). Internet versus bricks-and-mortar retailers: An investigation into intangibility and its consequences. Journal of retailing, 81(4), 251-267.
  • Lefebvre, R. C. (2011). An integrative model for social marketing. Journal of Social Marketing, 1(1), 54-72.
  • Liang, T. P., and Turban, E. (2011). Introduction to the special issue social commerce: a research framework for social commerce. International Journal of Electronic Commerce, 16(2), 5-14.
  • Sashi, C. M. (2012). Customer engagement, buyer-seller relationships, and social media. Management Decision, 50(2), 253-272.
  • Stead, M., Gordon, R., Angus, K. and Mcdermott, L. (2006) A systematic review of social marketing effectiveness. Health Education, 107(2), pp. 126–191.
  • Thackeray, R., Neiger, B. L., Hanson, C. L., & McKenzie, J. F. (2008). Enhancing promotional strategies within social marketing programs: use of Web 2.0 social media. Health promotion practice, 9(4), 338-343.
  • Thackeray, R., Neiger, B. L., and Keller, H. (2012). Integrating Social Media and Social Marketing A Four-Step Process. Health Promotion Practice, 13(2), 165-168.
  • Turan, A. H. (2008): Internet Alışverişi Tüketici Davranışını Belirleyen Etmenler: Geliştirilmiş Teknoloji Kabul Modeli ile Bir Model Önerisi, Akademik Bilişim Dergisi, Ocak-Şubat, ss:723-731.
  • Türker, D. Altuntaş Vural, C. (2016) Kurumsal Sosyal Sorumluluk ve Hayırseverlik (Corporate Social Responsibility and Philanthropy) (s. 149-170). in S. Hoştut ve S.D. Van Het Hof (Eds.) Kurumsal Sosyal Sorumlulukta Güncel Yönelim ve Yaklaşımlar. Ankara: Nobel Yayınevi
  • Van der Heijden, H., Verhagen, T., and Creemers, M. (2003). Understanding online purchase intentions: contributions from technology and trust perspectives. European journal of information systems, 12(1), 41-48.
  • Vinzi, V. E., Trinchera, L., and Amato, S. (2010). PLS Path Modeling: From Foundations to Recent Developments and Open Issues for Model Assessment and Improvement. In. V. Esposito Vinzi, W.W. Chin, J. Henseler & H. Wang (Eds) Handbook of Partial Least Squares: Concepts, Methods and Applications (47-82) Berlin, Germany: Springer Berlin Heidelberg
  • Wong, K. K. (2011). Review of the book Handbook of Partial Least Squares: Concepts, Methods and Applications, by V. Esposito Vinzi, W.W. Chin, J. Henseler & H. Wang (Eds). International Journal of Business Science & Applied Management. 6 (2), 52-54.
  • Yılmaz, C. ve Tümtürk, A. (2015): Internet üzerinden Alışveriş Niyetini Etkileyen Faktörlerin Genişletilmiş Teknoloji Kabul Modeli Kullanarak İncelenmesi ve Bir Model Önerisi, Celal Bayar Universitesi Yönetim ve Ekonomi Dergisi, Cilt 22, Sayı 2, ss: 355-384.
  • http://www.adimadim.org/ (accessed on May 2016)
There are 43 citations in total.

Details

Journal Section Articles
Authors

Aysu Göçer

Ceren Altuntaş Vural This is me

Publication Date June 14, 2017
Published in Issue Year 2017 Marketing Congress Special Issue

Cite

APA Göçer, A., & Altuntaş Vural, C. (2017). SOSYAL PAZARLAMADA TEKNOLOJİ KABULÜ: HAYIRSEVERLİK DAVRANIŞLARI ÜZERİNE BİR İNCELEME. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi1-23.
AMA Göçer A, Altuntaş Vural C. SOSYAL PAZARLAMADA TEKNOLOJİ KABULÜ: HAYIRSEVERLİK DAVRANIŞLARI ÜZERİNE BİR İNCELEME. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi. Published online June 1, 2017:1-23.
Chicago Göçer, Aysu, and Ceren Altuntaş Vural. “SOSYAL PAZARLAMADA TEKNOLOJİ KABULÜ: HAYIRSEVERLİK DAVRANIŞLARI ÜZERİNE BİR İNCELEME”. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, June (June 2017), 1-23.
EndNote Göçer A, Altuntaş Vural C (June 1, 2017) SOSYAL PAZARLAMADA TEKNOLOJİ KABULÜ: HAYIRSEVERLİK DAVRANIŞLARI ÜZERİNE BİR İNCELEME. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi 1–23.
IEEE A. Göçer and C. Altuntaş Vural, “SOSYAL PAZARLAMADA TEKNOLOJİ KABULÜ: HAYIRSEVERLİK DAVRANIŞLARI ÜZERİNE BİR İNCELEME”, Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, pp. 1–23, June 2017.
ISNAD Göçer, Aysu - Altuntaş Vural, Ceren. “SOSYAL PAZARLAMADA TEKNOLOJİ KABULÜ: HAYIRSEVERLİK DAVRANIŞLARI ÜZERİNE BİR İNCELEME”. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi. June 2017. 1-23.
JAMA Göçer A, Altuntaş Vural C. SOSYAL PAZARLAMADA TEKNOLOJİ KABULÜ: HAYIRSEVERLİK DAVRANIŞLARI ÜZERİNE BİR İNCELEME. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi. 2017;:1–23.
MLA Göçer, Aysu and Ceren Altuntaş Vural. “SOSYAL PAZARLAMADA TEKNOLOJİ KABULÜ: HAYIRSEVERLİK DAVRANIŞLARI ÜZERİNE BİR İNCELEME”. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, 2017, pp. 1-23.
Vancouver Göçer A, Altuntaş Vural C. SOSYAL PAZARLAMADA TEKNOLOJİ KABULÜ: HAYIRSEVERLİK DAVRANIŞLARI ÜZERİNE BİR İNCELEME. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi. 2017:1-23.

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