Abstract
The use of imagination is a dominant strategy for consumers to form evaluations in the e-commerce environments. Online Product Presentation Videos (OPPVs) are vivid information that can facilitate consumers this task. Following the imagery fluency approach, we analyze the impact of OPPVs on consumers’ quality of product-related thoughts, ease of imagining, and responses toward the product. A series of studies combining experimental- and survey-based procedures shows that the presence and type of OPPV improves consumers’ cognitive responses and facilitates imagination about the product, which becomes a strong determinant of attitude and purchase intention. We also control for the OPPV’s trustworthiness to isolate the effects of the content characteristics of video. Moreover, we consider the moderating role of the consumer’s motivation to process information. The results demonstrate that high and low motivated consumers use their imagination differently. In addition, when OPPVs are featured by the brand, ease of imagining does not relate to purchase intention.




Similar content being viewed by others
Notes
Sample versus sample.
At the time the research was carried out, smartphones were at an early introductory stage in the focal market. Participants were not yet knowledgeable of all the characteristics and functionalities of smartphones in general, such as touchscreen, Internet navigation, or GPS functions. Therefore, this uncertainty about the use of a new product is also likely to prompt the use of imagination as a strategy to evaluate the product [2].
The data of the pretests can be requested from the authors.
Although stated otherwise, all the 95% bias-corrected Confidence Intervals were performed using 5,000 bootstrap samples.
The results of an additional study, not reported in this paper, confirmed that the animated OPPV was perceived as more emotionally stimulating and technologically vivid than the factual OPPV; whereas the factual OPPV was perceived as more proximate (concrete, clear, and realistic) than the animated OPPV. In fact, proximity mediated the impact of the type of OPPV on the participants’ thought quality, regardless of their NFC.
ATTCOGN: α = 0.80, 71.76% of explained variance; ATTAFF: α = 0.78, 69.13% of explained variance.
References
Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and interpreting interactions. Newbury Park, CA: Sage.
Alba, J. W., & Hutchinson, J. W. (2000). Knowledge calibration: What consumers know and what they think they know. Journal of Consumer Research, 27(2), 123–156.
Alter, A. L., & Oppenheimer, D. M. (2009). Uniting the tribes of fluency to form a metacognitive nation. Personality and Social Psychology Review, 13(3), 219–235.
Argyriou, E. (2012). Consumer intentions to revisit online retailers: A mental imagery account. Psychology and Marketing, 29(1), 25–35.
Babin, L. A., & Burns, A. C. (1997). Effects of print and pictures and copy containing instructions to imagine on mental imagery that mediates attitudes. Journal of Advertising, 26(3), 33–44. doi:10.1080/00913367.1997.10673527.
Babin, L. A., & Burns, A. C. (1998). A modified scale for the measurement of communication-evoked mental imagery. Psychology and Marketing, 15(3), 261–278.
Batra, R., & Ahtola, O. T. (1990). Measuring the hedonic and utilitarian sources of consumer attitudes. Marketing Letters, 2(2), 159–170.
Bearden, W. O., & Netemeyer, R. G. (1999). Handbook of Marketing Scales: Multi-item Measures for Marketing and Consumer Behavior Research. Newbury Park, CA: Sage Publications Inc.
Block, L. G., & Keller, P. A. (1997). Effects of self-efficacy and vividness on the persuasiveness of health communications. Journal of Consumer Psychology, 6(1), 31–54.
Briñol, P., Petty, R. E., & Tormala, Z. L. (2004). Self-validation of cognitive responses to advertisements. Journal of Consumer Research, 30(4), 559–573.
Briñol, P., Petty, R. E., & Tormala, Z. L. (2006). The malleable meaning of subjective ease. Psychological Science, 17(3), 200–206.
Cacioppo, J. T., & Petty, R. E. (1981). Social psychological procedures for cognitive response assessment: The thought-listing technique. In T. V. Merluzzi, C. R. Glass, & M. Genest (Eds.), Cognitive assessment (pp. 309–342). New York: Guilford Press.
Cacioppo, J. T., von Hippel, W., & Ernst, J. M. (1997). Mapping cognitive structures and processes through verbal content: The thought-listing technique. Journal of Consulting and Clinical Psychology, 65, 928–940.
Chaiken, S. (1980). Heuristic versus systematic information processing and the use of source versus message cues in persuasion. Journal of Personality and Social Psychology, 39(5), 752–766.
Chaiken, S., & Maheswaran, D. (1994). Heuristic processing can bias systematic processing: Effects of source credibility, argument ambiguity, and task importance on attitude judgment. Journal of Personality and Social Psychology, 66(3), 460–473.
Chang, C. (2013). Imagery fluency and narrative advertising effects. Journal of Advertising, 42(1), 54–68.
Chiang, H. S., & Hsiao, K. L. (2015). YouTube stickiness: the needs, personal, and environmental perspective. Internet Research, 25(1), 85–106.
Ching, R. K., Tong, P., Chen, J. S., & Chen, H. Y. (2013). Narrative online advertising: Identification and its effects on attitude toward a product. Internet Research, 23(4), 414–438.
Cho, C. H., Kang, J., & Cheon, H. J. (2006). Online shopping hesitation. CyberPsychology and Behavior, 9(3), 261–274.
Cohen, J., & Cohen, P. (1983). Applied multiple regression/correlation analysis for the behavioral sciences. Hillsdale, NJ: Erlbaum Associates.
Cohen, J. B., & Reed, A. (2006). A multiple pathway anchoring and adjustment (MPAA): Model of attitude generation and recruitment. Journal of Consumer Research, 36, 1–15.
ComScore. ComScore releases February 2015 US online video rankings. Retrieved March 20, 2015, from http://www.comscore.com/Insights/Market-Rankings/comScore-Releases-February-2015-U.S.-Desktop-Online-Video-Rankings.
Coyle, J. R., & Thorson, E. (2001). The effects of progressive levels of interactivity and vividness in web marketing sites. Journal of Advertising, 30(3), 65–77.
Cronbach, L. J. (1970). Essentials of psychological testing. New York: Harper and Row.
Eagly, A. H., & Chaiken, S. (1993). The Psychology of Attitudes. Belmont, CA: Wadsworth Cengage Learning.
Escalas, J. E. (2004). Imagine yourself in the product. Journal of Advertising, 33(2), 37–48.
EMarketer. Digital Video for the Full Advertising Funnel: Touchpoints for Every Objective. Retrieved Marth 15, 2014, from http://www.emarketer.com.
Ertimur, B., & Gilly, M. C. (2012). So whaddya think? Consumers create ads and other consumers critique them. Journal of Interactive Marketing, 26(3), 115–130.
Field, A. (2009). Discovering statistics using SPSS. CA, SAGE: Thousand Oaks.
Fitzsimons, G. J., Hutchinson, J. W., Williams, P., Alba, J. W., Chartrand, T. L., Huber, J., et al. (2002). Non-conscious influences on consumer choice. Marketing Letters, 13(3), 269–279.
Flavián, C., Gurrea, R., & Orús, C. (2010). Effects of visual and textual information in online product presentations: Looking for the best combination in website design. European Journal of Information Systems, 19(6), 668–686.
Fortin, D. R., & Dholakia, R. R. (2005). Interactivity and vividness effects on social presence and involvement with a web-based advertisement. Journal of Business Research, 58(3), 387–396.
Frey, K. P., & Eagly, A. H. (1993). Vividness can undermine the persuasiveness of messages. Journal of Personality and Social Psychology, 65(1), 32–44.
Friestad, M., & Wright, P. (1994). The persuasion knowledge model: How people cope with persuasion attempts. Journal of Consumer Research, 21(1), 1–31.
Griffith, D. A., Krampf, R. F., & Palmer, J. W. (2001). The role of interface in electronic commerce: Consumer involvement with print versus on-line catalogs. International Journal of Electronic Commerce, 5(4), 135–153.
Gupta, P., & Harris, J. (2010). How e-wom recommendations influence product consideration and quality of choice: A motivation to process information perspective. Journal of Business Research, 63(9–10), 1041–1049.
Gurrea, R., Orús, C., & Flavián, C. (2013). The role of symbols signalling the product status on online users’ information processing. Online Information Review, 37(1), 8–27.
Hair, J. F. J. R., Anderson, R. E., Tatham, R. L., & Black, W. C. (1999). Multivariate Data Analysis. Englewood Cliffs, NJ: Prentice Hall.
Haugtvedt, C. P., & Kasmer, J. A. (2008). Attitude change and persuasion. In C. P. Haugtvedt, P. M. Herr, & F. R. Kardes (Eds.), Handbook of consumer psychology (pp. 419–436). New York, NY: Taylor & Francis Group.
Hayes, A. F. (2013). An introduction to mediation, moderation, and conditional process analysis: a regression-based approach. New York: Guilford Press.
Hilligoss, B., & Rieh, S. Y. (2008). Developing a unifying framework of credibility assessment: Construct, heuristics, and interaction in context. Information Processing and Management, 44(4), 1467–1484.
Hsieh, J. K., Hsieh, Y. C., & Tang, Y. C. (2012). Exploring the disseminating behaviors of eWOM marketing: persuasion in online video. Electronic Commerce Research, 12(2), 201–224.
Igartua, J. J. La. (1998). técnica del listado de pensamientos como método de investigación en comunicación publicitaria. Comunicación and Cultura, 3, 43–62.
Jiang, Z., & Benbasat, I. (2007). The effects of presentation formats and task complexity on online consumers’ product understanding. MIS Quarterly, 31(3), 475–500.
Jiang, Z., & Benbasat, I. (2007). Investigating the influence of the functional mechanisms of online product presentations. Information Systems Research, 18(4), 454–470.
Keller, P. A., & Block, L. G. (1997). Vividness effects: A resource-matching perspective. Journal of Consumer Research, 24, 295–304.
Kempf, D. S., & Smith, R. E. (1998). Consumer processing of product trial and the influence of prior advertising: A structural modeling approach. Journal of Marketing Research, 35(3), 325–338.
Kim, D. J. (2014). A study of the multilevel and dynamic nature of trust in e-commerce from a cross-stage perspective. International Journal of Electronic Commerce, 19(1), 11–64.
Kim, H., & Richardson, S. L. (2003). Motion picture impacts on destination images. Annals of tourism research, 30(1), 216–237.
Kisielius, J., & Sternthal, B. (1984). Detecting and explaining vividness effects in attitudinal judgments. Journal of Marketing Research, 21(1), 54–64.
Klein, L. R. (2003). Creating virtual product experiences: The role of telepresence. Journal of Interactive Marketing, 17(1), 41–55.
Lai, Y. L., Kuan, K. K. Y., Hui, K. L., & Liu, N. (2009). The effects of moving animation on recall, hedonic and utilitarian perceptions, and attitude. IEEE Transactions on Engineering Management, 56(3), 468–477.
Lee, A. Y. (2004). The prevalence of metacognitive routes to judgments. Journal of Consumer Psychology, 14(4), 349–355.
Lee, E. J., & Park, J. (2014). Enhancing virtual presence in e-tail: Dynamics of cue multiplicity. International Journal of Electronic Commerce, 18(4), 117–146.
Lee, K. Y. (2012). Consumer processing of virtual experience in e-commerce: A test of an integrated framework. Computers in Human Behavior, 28(6), 2134–2142.
Li, H., Daugherty, T., & Biocca, F. (2002). Impact of 3-D advertising on product knowledge, brand attitude, and purchase intention: The mediating role of presence. Journal of Advertising, 31(3), 43–57.
Li, H., Daugherty, T., & Biocca, F. (2003). The role of virtual experience in consumer learning. Journal of Consumer Psychology, 13(4), 395–407.
Li, T., & Meshkova, Z. (2013). Examining the impact of rich media on consumer willingness to pay in online stores. Electronic Commerce Research and Applications, 12(6), 449–461.
Lian, S. (2011). Innovative Internet video consuming based on media analysis techniques. Electronic Commerce Research, 11(1), 75–89.
Loken, B. (2006). Consumer Psychology: Categorization, inferences, affect, and persuasion. Annual Review of Psychology, 57, 453–485.
MacInnis, D. J., & Price, L. L. (1987). The role of imagery in information processing: Review and extensions. Journal of Consumer Research, 13(4), 473–491.
Menon, G., & Raghubir, P. (2003). Ease-of-retrieval as an automatic input in judgments: a mere-accessibility framework? Journal of Consumer Research, 30(2), 230–243.
Muylle, S., Moenaert, R., & Despontin, M. (2004). The conceptualization and empirical validation of web site user satisfaction. Information and Management, 41(5), 543–560.
Nielsen, J. H., & Escalas, J. E. (2010). Easier is not always better: The moderating role of processing type on preference fluency. Journal of Consumer Psychology, 20(3), 295–305.
Nisbett, R. E., & Ross, L. (1980). Human inference: Strategies and shortcomings of social judgment. Eanglewood Cliffs, NJ: Prentice Hall Inc.
Nowlis, S. M., Mandel, N., & McCabe, D. B. (2004). The effect of a delay between choice and consumption on consumption enjoyment. Journal of Consumer Research, 31(3), 502–510.
Nunnally, J. C. (1978). Psychometric Theory (2nd ed.). New York: McGraw-Hill.
Nurosis, M.J. (1993) SPSS for Windows Base System Users Guide. Release 6.0. Englewood Cliffs, NJ.
Ohanian, R. (1990). Construction and validation of a scale to measure celebrity endorsers’ expertise, trustworthiness, and attractiveness. Journal of Advertising, 19(3), 39–52.
Overmars, S., & Poels, K. (2015). Online product experiences: The effect of simulating stroking gestures on product understanding and the critical role of user control. Computers in Human Behavior, 51, 272–284.
Pagani, M., & Mirabello, A. (2011). The influence of personal and social-interactive engagement in social TV web sites. International Journal of Electronic Commerce, 16(2), 41–68.
Pavlou, P. A., & Stewart, D. W. (2000). Measuring the effects and effectiveness of interactive advertising: a research agenda. Journal of Interactive Advertising, 1(1), 62–78.
Peck, J., Barger, V. A., & Webb, A. (2013). In search of a surrogate for touch: The effect of haptic imagery on perceived ownership. Journal of Consumer Psychology, 23(2), 189–196.
Peracchio, L. A., & Meyers-Levy, J. (1997). Evaluating persuasion-enhancing techniques from a resource-matching perspective. Journal of Consumer Research, 24(2), 178–191.
Petrova, P. K., & Cialdini, R. (2005). Fluency of consumption imagery and the backfire effects of imagery appeals. Journal of Consumer Research, 32(3), 442–452.
Petrova, P. K., & Cialdini, R. (2008). Evoking the imagination as a strategy of influence. In C. P. Haugtvedt, P. M. Herr, & F. R. Kardes (Eds.), Handbook of consumer psychology (pp. 505–523). New York, NY: Taylor & Francis Group.
Petty, R. E., & Cacioppo, J. T. (1986). The elaboration likelihood model of persuasion. Advances in Experimental Social Psychology, 19, 123–205.
Petty, R. E., Briñol, P., & Tormala, Z. L. (2002). Thought confidence as a determinant of persuasion: The self-validation hypothesis. Journal of Personality and Social Psychology, 82(5), 722–741.
Pillai, K. G., Brusco, M., Goldsmith, R., & Hofacker, C. (2015). Consumer knowledge discrimination. European Journal of Marketing, 49(1/2), 82–100.
Preacher, K.J. (2002). Calculation for the Test of the Difference Between Two Independent Correlation Coefficients [Computer software]. Retrieved May 18, 2014, from http://quantpsy.org.
Preacher, K. J., & Hayes, A. F. (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior Research Methods, Instruments, and Computers, 36(4), 717–731.
Raney, A., Arpan, L., Pashupati, K., & Brill, D. (2003). At the movies, on the web: An investigation of the effects of entertaining and interactive web content on site and brand evaluations. Journal of Interactive Marketing, 17(4), 38–53.
Rieh, S. Y., & Danielson, D. R. (2007). Credibility: A multidisciplinary framework. In B. Cronin (Ed.), Annual Review of Information Science and Technology (pp. 307–364). Medford, NJ: Information Today.
SanJosé-Cabezudo, R., Gutiérrez-Arranz, A. M., & Gutiérrez-Cilla, N. J. (2009). The combined influence of central and peripheral routes in the online persuasion process. CyberPsychology and Behavior, 12(3), 299–308.
Scarpi, D. (2012). Work and fun on the internet: The effects of utilitarianism and hedonism online. Journal of Interactive Marketing, 26(1), 53–67.
Schlosser, A. E. (2003). Experiencing products in the virtual world: The role of goal and imagery in influencing attitudes versus purchase intentions. Journal of Consumer Research, 30(2), 184–198.
Schwarz, N. (1998). Accessible content and accessibility experiences: The interplay of declarative and experiential information in judgment. Journal of Personality and Social Psychology Review, 2(2), 87–99.
Schwarz, N. (2004). Metacognitive experiences in consumer judgment and decision making. Journal of Consumer Psychology, 14(4), 332–348.
Schwarz, N., Bless, H., Strack, F., Klumpp, G., Rittenauer-Schatka, H., & Simons, A. (1991). Ease of retrieval as information: Another look at the availability heuristic. Journal of Personality and Social Psychology, 61(2), 195–202.
Senecal, S., & Nantel, J. (2004). The influence of online product recommendations on consumers’ online choices. Journal of Retailing, 80(2), 159–169.
Shiv, B., & Huber, J. (2000). The impact of anticipating satisfaction on consumer choice. Journal of Consumer Research, 27(2), 202–216.
Smith, A. N., Fischer, E., & Yongjian, C. (2012). How does brand-related user-generated content differ across YouTube, Facebook, and Twitter? Journal of Interactive Marketing, 26(2), 71–82.
Song, P., Xu, H., Techatassanasoontorn, A., & Zhang, C. (2011). The influence of product integration on online advertising effectiveness. Electronic Commerce Research and Applications, 10(3), 288–303.
Steuer, J. (1992). Defining virtual reality: Dimensions determining telepresence. Journal of Communication, 42(4), 73–93.
Stewart, D. W., & Pavlou, P. A. (2002). From consumer response to active consumer: Measuring the effectiveness of interactive media. Journal of the Academy of Marketing Science, 30(4), 376–396.
Tormala, Z. L., Petty, R. E., & Briñol, P. (2002). Ease of retrieval effects in persuasion: A self-validation analysis. Personality and Social Psychological Bulletin, 28(2), 1700–1712.
Tsai, C. I., & McGill, A. L. (2011). No pain, no gain? How fluency and construal level affect consumer confidence. Journal of Consumer Research, 37(5), 807–821.
Voss, K. E., Spangenberg, E. R., & Grohman, B. (2003). Measuring the hedonic and utilitarian dimensions of consumer attitude. Journal of Marketing Research, 40(3), 310–320.
Walia, N., Srite, M., and Huddleston, W. Eyeing the web interface: the influence of price, product, and personal involvement. Electronic Commerce Research, in press.
Weathers, D., Sharma, S., & Wood, S. L. (2007). Effects of online communication practices on consumer perceptions of performance uncertainty for search and experience goods. Journal of Retailing, 83(4), 393–401.
Winer, R. S. (2009). New communications approaches in marketing: Issues and research directions. Journal of Interactive Marketing, 23(2), 108–117.
Wood, S. L., & Swait, J. (2002). Psychological indicators of innovation adoption: Cross-classification based on need for cognition and need for change. Journal of Consumer Psychology, 12(1), 1–13.
Xiao, B., & Benbasat, I. (2011). Product-related deception in e-commerce: A theoretical perspective. MIS Quarterly, 35(1), 169–195.
Xu, P., Chen, L., & Santhanam, R. (2015). Will video be the next generation of e-commerce product reviews? Presentation format and the role of product type. Decision Support Systems, 73, 85–96.
Yanovitzky, I., Zanutto, E., & Hornik, R. (2005). Estimating causal effects of public health education campaigns using propensity score methodology. Evaluation and program planning, 28(2), 209–220.
Zhang, K. Z., Zhao, S. J., Cheung, C. M., & Lee, M. K. (2014). Examining the influence of online reviews on consumers’ decision-making: A heuristic–systematic model. Decision Support Systems, 67, 78–89.
Author information
Authors and Affiliations
Corresponding author
Appendices
Appendix 1: socio-demographic data from empirical studies
Pilot study | Study 1 | Study 2a | Study 2b | |
---|---|---|---|---|
N | 66 | 76 | 130 | 97 |
Sex (% male) | 46 | 50 | 42 | 45 |
Age | ||||
18–21 years old | 68.2% | 66.2% | 58.8% | 67.0% |
22–25 years old | 13.8% | 20.3% | 27.5% | 17.5% |
26–30 years old | 8% | 13.5% | 13.7% | 15.5% |
>5 years of internet use experience | 86.4% | 85.1% | 87.7% | 78.9% |
Online purchases in the past 12 months | 69.7% | 71.6% | 70.8% | 61.7% |
Appendix 2
See Table 9.
Appendix 3: measurement instruments and scales validation
3.1 Scales validation
Firstly, an exploratory analysis of data was carried out in order to detect outliers and missing cases. Following the procedures proposed by Hair et al. [38], no outlier data were detected. In addition, given the few number of missing data, the imputation criterion was used to replace missing values for the average of the validated data.
Regarding the scales’ reliability and internal consistency, the Cronbach’s alphas were calculated [24], considering a cut-off minimum value of 0.7 [67], and of 0.3 for item-total correlations [68]. In addition, the scales’ dimensionality was evaluated by means of principal component analysis [38]. Separate factorial analyses, with principal components and Varimax rotation, were conducted. The KMO test and Barlett test of sphericity confirmed the adequacy of the principal components method to determine the unidimensionality of the scales. Moreover, the factorial loadings were required to be greater than 0.5, with a total explained variance higher than 0.6 [38]. Content validity was also confirmed because of the rigor employed to design the scales. A scale’s content is valid if it results from existing theories in relevant literature [8, 10, 66, 69, 100, 103] (see Table 10).
Rights and permissions
About this article
Cite this article
Orús, C., Gurrea, R. & Flavián, C. Facilitating imaginations through online product presentation videos: effects on imagery fluency, product attitude and purchase intention. Electron Commer Res 17, 661–700 (2017). https://doi.org/10.1007/s10660-016-9250-7
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10660-016-9250-7