Becagli, Claudio

De Masi, Sara

Faraoni, Monica

Zollo, Lamberto

English

Florence Research

PROCEEDINGSIl Marketing per una società miglioreXVII^ SIM ConferenceCastellanza, 29-30 ottobre 2020ISBN 978-88-943918-4-8EXPLORING CONSUMER BEHAVIOR IN THE MUSIC INDUSTRY. EMPIRICAL EVIDENCE FROM SPOTIFY PREMIUM USERS  CLAUDIO BECAGLIª - SARA DE MASI* - MONICA FARAONI• - LAMBERTO ZOLLO§  Abstract This paper develops a conceptual model that identifies the driving mechanisms affecting consumers’ purchase intention to renew their paid subscriptions to music streaming premium services.  Through the analysis of a sample of 306 premium users of the Spotify online music platform, the model shows the significant influences of both users' hedonic motivations and perceived functional quality on the perceived price value (PPV) of the music service. Furthermore, it shows that this relationship is partially mediated by user habits - resulting from their perception of personal innovativeness, conditions of facilitation and social influence. These results provide useful information to managers and researchers for the definition and analysis of marketing actions aimed at pursuing the loyalty of premium customers and reducing the churn rate.  Keywords: music industry, streaming, perceived price value (PPV), consumer habits, Spotify   Introduction  The music industry is facing a challenging time. Although music consumption is globally recognised as a source of entertainment, in the last decade, the way to consume music has radically changed (Nuttall et al., 2011). Physical products are gradually been replaced by digital music downloading or streaming from Internet music providers (Magaudda, 2011). The introduction of the freemium music business model has been seen as an additional source of revenues for companies. Since a basic, or downgraded, version of the service is offered free of charge, this model aims at attracting a large base of users and convert as many as possible into premium subscribers. Our study focuses on the driving mechanisms affecting consumers’ purchase intention to retain their paid subscriptions premium music services. To understand the consumer behavior in the music context, we build on the theory of planned behavior (D’Astous et al., 2005; Plowman and Goode, 2009). We develop a conceptual model and we empirically test it using a sample of 306 Spotify premium users. In particular, we propose an analysis that examines to what extent the habit developed through the repeated use of the application in everyday life could change the relationship between the perceived value of the premium version and the intention to remain on the premium music service. Our                                                         ª Assistant Professor of Management – Univ. of Florence - e-mail: claudio.becagli@unifi.it  * Assistant Professor of Management – Univ. of Florence - e-mail: sara.demasi@unifi.it • Associate Professor of Management – Univ. of Florence - e-mail: monica.faraoni@unifi.it  §Assistant Professor of Management – Univ. of Florence - e-mail: lamberto.zollo@unifi.it reference context is Spotify because it is the only company, among the most important music streaming operators, that adopts a freemium business model.   Literature review and hypothesis development In the context of music as a service (MaaS), few studies have focused on the factors pushing basic users to change their subscription from free to premium. Dörr et al. (2010) surveyed 132 users to understand how different service features affect their willingness to pay for MaaS, concluding that “sound quality and the contract period significantly influence users’ willingness to pay”. Dörr et al. (2013) investigated the intentions of music pirates to use MaaS and pay for such services and noted that this choice is mainly the result of the influence of the users’ closest peers. Despite these important empirical observations, the drivers affecting the customer's renewal of the paid music streaming subscription are still not entirely clear. There are some possible driving mechanisms affecting consumers’ purchase intention to retain their paid subscriptions of premium music services. The Price value (PV) is defined as a “share of a product’s quality compared to its price” (Zeithaml, 1988). With the increasing use of new technologies, price value has been considered a relevant factor (Dodds et al., 1991; Pavlou and Fygenson 2006; Venkatesh et al., 2012). Dodds et al. (1991) define price value in case of innovative technologies as “the consumer's trade-off between the perceived benefits of innovations and the monetary cost that must be sustained for their use”. Functional quality refers to the way in which technical quality is transferred to the consumer (Gronroos, 1990). In music services, the consumer delivering process is crucial in determining the service quality and consequently the price value perception. In music streaming services, users have access to music over the Internet without the need to store songs on their device. However, some streaming platforms, including Spotify, allow premium users to listen to their favorite songs even without a data network, as long as they have previously downloaded the songs they want to play. This feature gives advantages in terms of the availability of the songs and accessibility of the service even in the absence of an internet connection. This is what we refer to as ubiquity. Okazaki and Mendez (2013) define the service perceived ubiquity of four constructs, namely: continuity - the possibility of accessing it without interruption; immediacy - the speed with which it is possible to access a service and use it; portability - the possibility of accessing the service from any device; and searchability - using a service wherever you are. Tojib and Tzarenko (2012) show that the relationship between the ubiquity of a service and the consumer’s experiential value, is positive and statistically significant. Hedonic motivation is the “as the fun or pleasure derived from using technology and it is an important determinant of consumer’s technology acceptance and use” (Tamilmani et al., 2019).  Previous research document the relevant role of hedonic motivation in determining the adoption and the use of a given technology (Van der Heijden, 2004; Wu and Holsapple, 2014; Brown and Venkatesh, 2005). Limayem et al. (2007, p. 709) defined habit as “the extent to which people tend to perform behaviors automatically (in using technology) because of learning”. Their model showed that habit tend to moderate the strength of intention in consumers behavior, suggesting that in situations of repeated, continuous and habitual use, the evaluative and intentional behavior based on users cognition is progressively replaced by habit and automaticity. This is why we consider that the habit has a mediating effect on the relation between the PPV and the intention to retain a premium version of the service. Habits are in turn determined by some antecedents as the social influence (Ajzen, 1991; Sadia, 2011), the personal innovativeness in information technology (PIIT) (Lu, 2014) and facilitating conditions. Figure 1 presents our conceptual framework and result of structural model.  Goals Our study aims to give some insights on the main factors that explain users' intention to renew the subscription to the premium service in order to support managers in identifying the most suitable marketing strategies to obtain the renewal of the subscription and to reduce churn rates.  Methodology A structured questionnaire composed of 40 items and 4 control variables was built in early 2018 and data were gathered from March to June 2018 using a non-probabilistic convenience sampling technique. From a random sample of Italian people, we collected 306 responses (a response rate of 42.5%) related to Spotify “premium” users — namely, subscribers that pay monthly for the whole music platform package and services. All items were ranked on a Likert scale ranging from 1 (completely disagree) to 7 (completely agree). Perceived price value was captured adopting the three-item scale of Sweeney and Soutar (2001). Habit was captured through the three-item scale of Limayem et al. (2007). To assess Hedonic Motivations, the three-item instrument of Brown and Venkatesh (2005) was used. Facilitating Conditions was measured through the three-item scale of Yang and Forney (2013). Ubiquity was captured through the five-item instrument by Okazaki and Mendez (2013). We measured Functional Quality with the three-item scale of Sweeney and Soutar (2001). Innovativeness in New Technologies was captured adopting the three-item of Goldsmith and Hofacker (1991). We measure Social Influence adopting the three-item scale of Mathieson (1991). Finally, Premium Intention was captured through the three-item instrument of Venkatesh et al. (2003). We employed structural equation modeling (SEM) to test our relationships.  Findings The SEM model (see fig. 1) shows a positive and statistically significant influence of the “PPV” on “premium intention”. Regarding the antecedents of the PPV, Functional quality and hedonic motivation have a significant and positive effect on the PPV, while the ubiquity variable seems to have an irrelevant role. The quality of the transmitted sound, the operation without interruptions, and the minimisation of the negative consequences of the use of the music app on the performance and functioning of the device used for listening are crucial conditions for the evaluation of the functional quality by the customer. Hedonic motivation also positively and significantly affects the PPV. The range of a seemingly endless musical universe, the continuous proposal of playlists designed for each user as well as the ability to use the app on many fixed and mobile devices are elements that positively affect the levels of satisfaction and fun deriving from the use of the platform and increase the PPV of the service. Finally, a particular attention concerns the possibility of using the Spotify service anywhere, regardless of the actual availability of an Internet connection, and which we have considered in our model through the ubiquity variable. This aspect falls within the three fundamental benefits that characterises Spotify’s premium service compared to the free one (i.e., “Enjoy endless ad-free music - even offline”; “Play any song. Even on mobile”; “Unlimited skips. Just hit next”1"). The mediating variable used to analyse the influence of the PPV on the premium intention is the habit. The SEM model shows a positive and significant effect on the habit of all three variables considered: facilitating conditions (β=+0.18), personal innovativeness in information technology (β=+0.11) and social influence (β=+0.25). The friendly usage of Spotify is the result of the simple technological competences needed to listen to music through streaming. These facilitating conditions helps to attract consumers and simplify the transition to listen to music easily on different devices. Habit is also influenced by the social influence (β=+0.25). People that may have a social influence on other users are not only the people that directly interact with the user (i.e., classmates, colleagues, friends, relatives, etc.) but also people that belong to same social groups of the user or to a social group to which the user aims to belong.   Figure 1. Conceptual framework and results of structural model2    Conclusions and Discussion                                                         1 https://www.spotify.com/us/ 2 * p<0.01;  Standardized estimates are reported; Dotted lines indicate non-significant paths; The value in parentheses refers to the original path that has been partially mediated; R2 indicates the squared multiple correlation of the latent variable, meaning the % of variance explained. Our results suggest relevant implications for music distributors. Companies should work on the PPV using functional quality and hedonic motivation. In particular, functional quality can be increased, strengthening the relationships with the electronic device producers and with the operating system developers. These relationships will help to maintain a service without buffering time or any other technological problems that could influence the perceived quality of the service. The high satisfaction of hedonic motivation is one of the main drivers of the competitive advantage of Spotify that, thanks to the wide range of its offer and its capability to meet the users’ preferences through the personalised playlists, is able to deliver a pleasant consumer experience. The improvement of this aspect can be achieved through the development of the application to make it work with other devices or simultaneously with other applications, as already happens in the case of listening to Spotify while using the Waze satellite navigation application (owned by Google). To leverage the habit, companies should strengthen the facilitating conditions and work on the social influence. Regarding the facilitating conditions, Spotify should continue to provide a user-friendly music platform that reduces the psychological barriers of non-technological savvy consumers that may be reluctant to listen to music through streaming. Regarding social influence, the use of social networks is one of the most efficient ways to advertise Spotify services, and it should be completely exploited using testimonials and influencers who effect the purchasing decisions of their followers.   References Ajzen, I. (1991) The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. Brown, S. A., & Venkatesh, V. (2005). A model of adoption of technology in the household: A baseline model test and extension incorporating household life cycle. MIS Quarterly, 29(4), 399–426. D’Astous, A., Colbert, F., & Montpetit, D. (2005) Music piracy on the web – How effective are anti-piracy arguments? Evidence from the theory of planned behaviour. Journal of Consumer Policy, 28(3), 289–310.  Dodds, W.B., Monroe, K.B. and Grewal, D. (1991), “Effects of price, brand, and store information on buyers' product evaluations”, Journal of Marketing Research, Vol. 28, pp. 307-19. Dörr, J., Benlian, A., Vetter, J., & Hess, T. (2010) Pricing of content services - An empirical investigation of music as a service, in Proceedings of the 16th Americas Conference on Information Systems, August 12–15, Lima, Peru, ACM Press, 1–9. Dörr, J., Wagner, T. M., Benlian, A., & Hess, T. (2013). Music as a service: An alternative to music piracy? An empirical investigation of the intention to use music streaming services. Business & Information Systems Engineering, 5(6), 383–396.  Goldsmith, R. E., & Hofacker, C. F. (1991). Measuring consumer innovativeness. Journal of the Academy of Marketing Science, 19(3), 209–221. Grönroos, C. (1990). Service management and marketing. Lexington, MA: Lexington Books. Limayem, M., Hirt, S. G., & Cheung, С. M. K, (2007). How habit limits the predictive power of intentions: The case of IS continuance. MIS Quarterly, 31(4), 705–737. Lu, J. (2014). Are personal innovativeness and social influence critical to continue with mobile commerce? Internet Research, 24(2), 134–159. Magaudda, P. (2011). When materiality ‘bites back’: Digital music consumption practices in the age of dematerialization. Journal of Consumer Culture, 11(1), 15–36. Mathieson, K. (1991). Predicting user intentions: Comparing the technology acceptance model with the theory of planned behavior. Information Systems Research, 2(3), 173–191. Nuttall, P., Arnold, S., Carless, L., Crockford, L., Finnamore, K., Frazier, R., & Hill, A. (2011). Understanding music consumption through a tribal lens. Journal of Retailing and Consumer Services, 18(2), 152–159. Okazaki, S., & Mendez, F. (2013). Exploring convenience in mobile commerce: Moderating effects of gender. Computers in Human Behavior, 29(3), 1234–1242. Pavlou, P. A., & Fygenson, M. (2006). Understanding and predicting electronic commerce adoption: An extension of the theory of planned behavior. MIS quarterly, 115-143. Plowman, S., & Goode, S. (2009) Factors affecting the intention to download music: Quality perceptions and downloading intensity. Journal of Computer Information Systems, 49(4), 84–97.  Sadia, S. (2011). User acceptance decision towards mobile commerce technology: A study of user decision about acceptance of mobile commerce technology. Interdisciplinary Journal of Contemporary Research in Business, 2(12), 535–547. Sweeney, J. C., & Soutar, G. N. (2001). Consumer perceived value: The development of a multiple item scale. Journal of Retailing, 77(2), 203–220. Tamilmani, K., Rana, N. P., Prakasam, N., & Dwivedi, Y. K. (2019). The battle of Brain vs. Heart: A literature review and meta-analysis of “hedonic motivation” use in UTAUT2. International Journal of Information Management, 46, 222-235. Tojib, D., & Tsarenko, Y. (2012). Post-adoption modeling of advanced mobile service use. Journal of Business Research, 65(7), 922-928. Van der Heijden, H. (2004). User acceptance of hedonic information systems. MIS quarterly, 695-704. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS quarterly, 157-178. Wu, J., & Holsapple, C. (2014). Imaginal and emotional experiences in pleasure-oriented IT usage: A hedonic consumption perspective. Information & Management, 51(1), 80-92. Yang, K., & Forney, J. C. (2013). The moderating role of consumer technology anxiety in mobile shopping adoption: differential effects of facilitating conditions and social influences. Journal of Electronic Commerce Research, 14(4), 334–347. Zeithaml, V. A. (1988). Consumer perceptions of price, quality, and value: A means-end model and synthesis of evidence. Journal of Marketing, 52(3), 2–22.  

Exploring consumer behavior in the music industry. Empirical evidence from Spotify premium users

https://flore.unifi.it/bitstream/2158/1248114/1/SIM%202020%20-%20Exploring%20consumer%20behavior%20in%20the%20music%20industry.pdf

Exploring consumer behavior in the music industry. Empirical evidence from Spotify premium users

Abstract

Similar works

Full text

Available Versions

Florence Research