Mobile Display Advertising: Perilaku Niat Pembelian Konsumen pada High Involvement vs Low Involvement Product

Jiwangga Hadi Nata, Aries Kurniawan

Abstract


This study uses the theory of Stimulus-Organism-Response (S-O-R) using a quantitative approach. Sampling using non-probability sampling method, using purposive sampling technique. Respondents in this study were 200 respondents in the purchase intention category in the High Involvement product and also 200 in the Low Involvement product category. The analysis technique used in this study is Partial Least Square (PLS). The results showed that browsing activities on Instagram for both the High and Low Involvement categories of the product had a positive influence on flow conditions, online trust, and purchase intentions. Then online trust in an account on Instagram has a positive influence on flow conditions. Likewise, the flow condition variable and online trust also have an influence on the purchase intention of the latest items on Instagram. There is no difference in consumer behavior towards purchase intentions in the online domain between High and Low Involvement products.


Keywords


browsing activity; flow; online trust; purchase intention; instagram

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References


Adam Rapp, Lauren Skinner Bietel Spacher, Dhruv Grewal, Douglas E Hughes. (2013). Understanding Social Media Effect Across Seller, Retailer, and Consumer Interactions. Journal of the Academic Marketing Science. No 41:576-566

Arnold Kamis, Tziporah Stern, Daniel M.Ladik. (2010). A Flow-based Model of Websites Intentions when Users Customize Products in Business-to-Cunsomer Electronic Commerce. Journal of Inf Syst Front. DOI 10.1007

Burns, A. C., & Bush, R. (2014). Marketing Research: Seventh Edition. Harlow, Edinburg Gate: Pearson Education Limited.

Chang, M. K., Cheung, W., & Lai, V. S. (2005). Literature derived reference models for the adoption of online shoping. Information and Management, 42, 543-559.

Chang, M. K., Cheung, W., & Tang, M. (2013). Building trust online: Interactions among trust building mechanisms. Information & Management, 50, 439-445.

Charlas Mathwick and Edward Rigdon. (2004). Play, Flow, and the Online Search Experience. Journal of Consumer Research. Vol 31.

Chia-Lin Hsu, Kuo-Chieng Chang, Mu-Chen Chen. (2012). The Impact of Website Quality on Customer Satisfaction and Purchase Intention : Perceived Playfulness and Perceived Flow as Mediators. Journal of Information System E-Business Managerial. No.10:549-570

Chia-Lin Hsu, Kuo-Chieng Chang, Mu-Chen Chen. (2012). Flow Experience and Internet Shopping Behaviour : Investigating the Moderating Effect of Customer Characteristic. Journal of System Research and Behavioral Science.No.317-332

Chia-Lin Hsu, Kuo-Chien Chang, Nien-Te Kuo, Yi-Sung Cheng. (2016). ResearchThe Mediating Affect of Flow Experience on Social Shopping Behaviour. DOI:10.1177

Ghozali, I. (2014). Structural Equation Modeling: Metode Alternatif Dengan Partial Least Squares (PLS). Semarang: Badan Penerbit Universitas Diponegoro Semarang.

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate Data Analysis: A Global Perspective, Seventh Edition. New Jersey: Pearson Education, Inc.

Hawkins, D. I., & Mothersbaugh, D. L. (2013). Consumer Behavior: Building Marketing Strategy. New York: McGraw-Hill.

Huang, Ming-Hui (2006), “Flow, Enduring, and Situational Involvement in the Web Environment:ATripartite Second-order Examination,” Psychology and Marketing, 23 (5), 383–411.

Huang, E. (2012). Online experience and virtual goods purchase intention. Internet Research, 22(3), 252-274.

Huang, L. T. (2015) . Flow and social capital theory in online impulse buying. Journal of Business Research, 69(6), 2277-2283.

Hsu, C. L., Chang, K. C., & Chen, M. C. (2012). Flow Experience and Internet Shopping Behavior: Investigating the Moderating Effect of Consumer Characteristics. System Research and Behavioral Science, 29, 317-332.

Ibnu Subiyanto. (2000). Metodologi Penelitian. Yogyakarta: UPP AMP YKPN.

Jacoby, J. (2002). Stimulus-Organism-Response Reconsidered: An Evolutionary Step in Modeling (Consumer) Behavior. Journal of Consumer Psychology, 12(1), 51-57.

Jas Raj Bohra and Mallika Bishnoi. (2016). Instagram : The New Edge of Online Retailing. World Journal of Research and Review. Vol 3. Pages 43-46.

Jessica Wongso Putri. (2015). Factors Affecting Customers Online Search Intention and Online Purchase Intention using Social Networks: Case Study of Online Shop on Instagram , iBuss Management Vol. 3, No. 2, 232-240

John L.Sherry. Flow and Media Enjoyment. (2004). Communication Theory. Pages 328-347

Koufaris, M. (2002). Applying the Technology Acceptance Model and Flow Theory to Online Consumer Behavior. Information System research, 13(2), 205-223.

Koufaris, M., & Sosa, W. H. (2004). The development of initial trust in an online company by new customers. Informtion & Management, 41, 377-397.

Koufaris, M., Kambil, A., & Labarbera, P. A. (2001). Consumer Behavior in Web-Based Commerce: An Empirical Study. International Journal of Electronic Commerce, 6(2), 115-138.

Kun Song and Ann Marie Fiore. (2007). Telepresence and Fantasy in Online Appareal Shopping Experience.Journal of Fashion Marketing and Management. Vol.11 No.4 2007

Lin, J., & Chuan, C. H. (2014). A Study on Youth Online Impulse Purchase: The Relationship between Individual Difference, Shopping Enjoyment, Emotion Response and Purchase. Journal of Creative Communication, 8(2&3), 209-229.

Novak, Thomas P., Donna L. Hoffman and Yiu-Fai Yung. (2000). Measuring the Customer Experience in Online Environments: A Structural Modeling Approach. Marketing Science, 19 (1), 22–42.

Nuttamon Amornpashara. (2013). A study of the relationship between using Instagram and purchase intention.. J. Global Business Advancement, Vol. 8, No.3

Ono, A., Nakamura, A., Okuno, A., & Sumikawa, M. (2012). Consumer Motivations in Browsing Online Stores with Mobile Devices. International Journal of Electronic Commerce. 16(4), 153-178.

Park, E. J., Kim, E. Y., Funches, V.M., & Foxx, W. (2012). Apparel product attributes, web browsing, and e-impulse buying on shopping websites. Journal of Business Research, 65, 1583-1589.

Patrick Mikalef, Michael Gianakos, and Admantia Pateli. (2013). Shopping and Word of Mouth Intentions on Social Media. Journal of Theorotical and Applied Electronic Commerce Research. ISSN 0718-1876.

Rene Weber, Ron Tamborini, Amber Westcott=Barker, Benjamin Kantor. (2009). Theorizing Flow and Media Enjoyment as Cognitive Syncronization of Attentional and Rewards Networks.Communication Theory

Smith, D. N., & Sivakumar, K. (2004). Flow and Internet shopping behavior: A conceptual model and research propositions. Journal of Business Research, 57, 1199-1208

Sugiyono., & Susanto, A. (2015). SPSS & Risrel, Teori dan Aplikasi untuk Analisis Data Penelitian. Bandung: Penerbit Alfabeta

Susan Rose. (2012). Online Customer Experience in e-Retailing: An empirical model of, Antecedents and Outcomes, Journal of Retailing 88 (2), 308–322

Yakov Bart, Andrew T. Stephen, Miklos Sarvary. (2014). Which Product are Best Suited to Mobile Advertising? A Field Study of Mobile Display Advertising Effect on Cunsomer Attitudes and Intentions. Journal of Marketing Research. Vol L1, 270-285




DOI: https://doi.org/10.15408/ess.v9i2.9942 Abstract - 0 PDF - 0

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