Abstract
As live streaming becomes more popular, research has not fully explored how and why people donate in live streaming. Current studies examine motivations and need satisfaction to explain why people participate in live streaming. However, these studies do not provide a satisfactory answer to the question of why people continue to donate in live streaming. Studies also fail to show what stimuli perceived in a live stream can generate intense participation, such as subscription and donation. This study clarifies the behavioral mechanism that ‘explains people’s intense participation in live streaming. Applying the Stimulus-Organism-Response (S-O-R) model, this study attempts to answer the research question: How are donation behaviors (R) performed in response to individuals’ sensemaking (O) to environmental stimuli (S)? We conducted an interpretive qualitative research to explore the sponsors’ S-O-R process to clarify the above research question. Our findings indicated that sponsors interpreted the live stream as a party, and they paid more attention to the way they enjoyed the party. Sponsors donated a live stream to heat up the atmosphere and make the party fun. They left messages and attached funny videos to the pop-up window enabled by the donation to show their enthusiasm and support for the live streamer. Research implications are also discussed.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Twitchtrack Homepage: https://twitchtracker.com/statistics. Last accessed 1 Apr 2021
Sjöblom, M., Hamari, J.: Why do people watch others play video games? An empirical study on the motivations of Twitch users. Comput. Hum. Behav. 75, 985–996 (2017)
Li, R., Lu, Y., Ma, J., Wang, W.: Examining gifting behavior on live streaming platforms: an identity-based motivation model. Inf. Manag. 58, 103–406 (2020)
Hu, M., Zhang, M., Wang, Y.: Why do audiences choose to keep watching on live video streaming platforms? An explanation of dual identification framework. Comput. Hum. Behav. 75, 594–606 (2017)
Mehrabian, A., Russell, J.A.: The basic emotional impact of environments. Percept. Mot. Skills 38, 283–301 (1974)
Hilvert-Bruce, Z., Neill, J.T., Sjöblom, M., Hamari, J.: Social motivations of live-streaming viewer engagement on Twitch. Comput. Hum. Behav. 84, 58–67 (2018)
Bründl, S., Matt, C., Hess, T.: Consumer use of social live streaming services: the influence of co-experience and effectance on enjoyment. In: the 25th European Conference on Information Systems (ECIS 2017)
Friedrich, T., Schlauderer, S., Overhage, S.: The impact of social commerce feature richness on website stickiness through cognitive and affective factors: an experimental study. Electron. Commer. Res. Appl. 36, 100861 (2019)
Floh, A., Madlberger, M.: The role of atmospheric cues in online impulse-buying behavior. Electron. Commer. Res. Appl. 12, 425–439 (2013)
Chen, C.C., Yao, J.Y.: What drives impulse buying behaviors in a mobile auction? The perspective of the stimulus-organism-response model. Telematics Inform. 35, 1249–1262 (2018)
Kaur, S., Lal, A.K., Bedi, S.S.: Do vendor cues influence purchase intention of online shoppers? An empirical study using S-O-R framework. J. Internet Comm. 16, 343–363 (2017)
Kuhn, S.W., Petzer, D.J.: Fostering purchase intentions toward online retailer websites in an emerging market: an S-O-R perspective. J. Internet Comm. 17, 255–282 (2018)
Huang, E.: Online experiences and virtual goods purchase intention. Internet Res. 22, 252–274 (2012)
Yuan, S., Liu, L., Su, B., Zhang, H.: Determining the antecedents of mobile payment loyalty: cognitive and affective perspectives. Electron. Commer. Res. Appl. 41, 100–971 (2020)
Cao, X., Sun, J.: Exploring the effect of overload on the discontinuous intention of social media users: an S-O-R perspective. Comput. Hum. Behav. 81, 10–18 (2018)
Kang, K., Lu, J., Guo, L., Li, W.: The dynamic effect of interactivity on customer engagement behavior through tie strength: evidence from live streaming commerce platforms. Int. J. Inf. Manage. 56, 102251 (2021)
Jacoby, J.: Stimulus-organism-response reconsidered: an evolutionary step in modeling (consumer) behavior. J. Consum. Psychol. 12, 51–57 (2002)
Eroglu, S.A., Machleit, K.A., Davis, L.M.: Empirical testing of a model of online store atmospherics and shopper responses. Psychol. Mark. 20, 139–150 (2003)
Tang, J.C., Venolia, G., Inkpen, K.M.: Meerkat and Periscope: I Stream, You Stream, Apps Stream for live streams. In: Conference on Human Factors in Computing Systems (2016)
Hamilton, W., Garretson, O., Kerne, A.: Streaming on Twitch: fostering participatory communities of play within live mixed media. In: CHI 2014: CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, New York, NY (2014)
Lim, S., Cha, S.Y., Park, C., Lee, I., Kim, J.: Getting closer and experiencing together: antecedents and consequences of psychological distance in social media-enhanced real-time streaming video. Comput. Hum. Behav. 28(4), 1365–1378 (2012)
Orlikowski, W.J., Gash, D.C.: Technology frames: making sense of information technology in organizations. ACM Trans. Inf. Syst. 12, 174–207 (1994)
Weick, K.E.: Sensemaking in Organizations. Sage, Thousand Oaks, CA (1995)
Hsu, C.: Frame misalignment: interpreting the implementation of information systems security certification in an organization. Eur. J. Inf. Syst. 18, 140–150 (2009)
Faulker, P., Runde, J.: On the identity of technological objects and user innovation in functions. Acad. Manag. Rev. 34, 442–462 (2009)
Chu, T.H., Robey, D.: Explaining changes in learning and work practice following the adoption of online learning: a human agency perspective. Eur. J. Inf. Syst. 17, 79–98 (2008)
Scheibe, K., Fietkiewicz, K.J., Stock, W.G.: Information behavior on social live streaming service. J. Inf. Sci. Theor. Pract. 4, 6–20 (2016)
Mason, J.: Qualitative Researching. Sage, London (2002)
Strauss, A., Corbin, J.M.: Basics of Qualitative Research: Grounded Theory Procedures and Techniques. Sage (1990)
BusinessofApps: https://www.businessofapps.com/data/twitch-statistics/. Last accessed 21 Mar 2021
Twitch: Thanks to you, we reached a record 1 trillion Minutes Watched in 2020. Twitter (2021)
Johnson, M.R., Woodcock, J.: “And today’s top donator Is”: how live streamers on Twitch.Tv monetize and gamify their broadcasts. Social Media + Society 5, 4–10 (2019)
Strauss, A., Corbin, J.: Grounded theory methodology: an overview. In: Denzin, N.K., Lincoln, Y.S. (eds.) Handbook of Qualitative Research, pp. 273–285. Sage, Thousand Oaks, CA (1994)
Vergura, D.T., Zerbini, C., Luceri, B.: Consumers’ attitude and purchase intention towards organic personal care products. An application of the S-O-R model. Sinergie Italian J. Manag. 38, 121–137 (2020)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 Springer Nature Switzerland AG
About this paper
Cite this paper
Chu, TH., Chu, WH., Lee, YH. (2023). Why Do People Donate for Live Streaming? Examining the S-O-R Process of Sponsors in the Live Streaming Context. In: Nah, F., Siau, K. (eds) HCI in Business, Government and Organizations. HCII 2023. Lecture Notes in Computer Science, vol 14039. Springer, Cham. https://doi.org/10.1007/978-3-031-36049-7_20
Download citation
DOI: https://doi.org/10.1007/978-3-031-36049-7_20
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-36048-0
Online ISBN: 978-3-031-36049-7
eBook Packages: Computer ScienceComputer Science (R0)