Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Electronic Commerce Research
Erschienen in: Electronic Commerce Research 3/2019

12.04.2019

Lowering the pirate flag: a TPB study of the factors influencing the intention to pay for movie streaming services

verfasst von: Domenico Sardanelli, Agostino Vollero, Alfonso Siano, Gianmaria Bottoni

Erschienen in: Electronic Commerce Research | Ausgabe 3/2019

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

The launch of several movie streaming services has raised new questions about how online consumers deal with both legal and illegal options to obtain their desired products. This paper investigates the factors influencing consumers’ intentions to subscribe to online movie streaming services. These services have challenged the dramatic growth in their illegal counterpart in recent years. Taking the theory of planned behavior as a starting point, we extended existing models in the literature by incorporating factors that are specific to consumer behavior in this particular field. A quantitative survey was conducted for the Italian market, and structural equation modeling was used for data analysis. Attitudes, involvement with products, moral judgement and frequency of past behavior were found to be the most important factors in explaining the intention to pay for movie streaming services. The paper provides insights for policy makers and industry managers on the marketing communication strategies needed to minimize the risk of digital piracy.
Vorheriger Artikel The interaction effects of information cascades, word of mouth and recommendation systems on online reading behavior: an empirical investigation
Nächster Artikel Factors affecting consumers’ mobile payment behavior: a meta-analysis

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren
Fußnoten
1
Both the theory of trying (TT) [8] and the model of goal-directed behavior (MGB) [66] have considered problematic behaviors, perceived as goals by the decision makers. However, although TT and MGB represent an expansion of TPB, they fit better with performances involving some kind of learning or trial-and-error process, which may truly make it reasonable to distinguish between intention to try and intention to use (as TT does) or between desire and intention to act (as MGB does). Likewise, a further specification of an attitude (e.g. toward the successful achievement of the goal or toward the failure as in the theory of trying), it is reasonable only for actions connected to a goal and to an arduous trial period. This does not appear to be the case of the subscription of movie streaming services (with the awareness of the easy alternative, i.e. illegal channels).
 
2
The use of a 11-point scale is justified by the need to produce continuous measurements that are more appropriate for the maximum likelihood estimator used in our research (implemented as MLR in Mplus) [45] and are better suited to the socio-cultural context of our research (Italy) in which individuals are quite familiar with this type of scale since they represent the grading system used in the Italian school system.
 
Literatur
1.
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211.CrossRef
2.
Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behaviour. Englewood, Cliffs, NJ: Prentice-Hall.
3.
Ajzen, I., & Fishbein, M. (2000). Attitudes and the attitude-behavior relation: Reasoned and automatic processes. European Review of Social Psychology, 11(1), 1–33.CrossRef
4.
Aldas-Manzano, J., Lassala-Navarre, C., Ruiz-Mafe, C., & Sanz-Blas, S. (2009). The role of consumer innovativeness and perceived risk in online banking usage. International Journal of Bank Marketing, 27(1), 53–75.CrossRef
5.
Al-Rafee, S., & Cronan, T. P. (2006). Digital piracy: Factors that influence attitude toward behavior. Journal of Business Ethics, 63(3), 237–259.CrossRef
6.
Arvola, A., Vassallo, M., Dean, M., Lampila, P., Saba, A., Lähteenmäki, L., et al. (2008). Predicting intentions to purchase organic food: The role of affective and moral attitudes in the theory of planned behaviour. Appetite, 50(2), 443–454.CrossRef
7.
Asparouhov, T. & Muthen, B. (2003). Full-information maximum-likelihood estimation of general two-level latent variable models with missing data. Technical report. Los Angeles: Muthén and Muthén.
8.
Bagozzi, R. P., Davis, F. D., & Warshaw, P. R. (1992). Development and test of a theory of technological learning and usage. Human Relations, 45(7), 659–686.CrossRef
9.
Bagozzi, R. P., Gopinath, M., & Nyer, P. U. (1999). The role of emotions in marketing. Journal of the Academy of Marketing Science, 27(2), 184–206.CrossRef
10.
Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74–94.CrossRef
11.
Beck, L., & Ajzen, I. (1991). Predicting dishonest actions using the theory of planned behavior. Journal of Research in Personality, 25, 285–301.CrossRef
12.
Bentler, P. M. (1990). Fit indexes, Lagrange multipliers, constraint changes and incomplete data in structural models. Multivariate Behavioral Research, 25(2), 163–172.CrossRef
13.
Bentler, P. M. (1992). On the fit of models to covariances and methodology to the Bulletin. Psychological Bulletin, 112, 400–404.CrossRef
14.
Borja, K., Dieringer, S., & Daw, J. (2015). The effect of music streaming services on music piracy among college students. Computers in Human Behavior, 45, 69–76.CrossRef
15.
Byers, S., Cranor, L. F., Cronin, E., Korman, D., & McDaniel, P. (2004). An analysis of security vulnerabilities in the movie production and distribution process. Telecommunications Policy, 28(7), 619–644.CrossRef
16.
Carrington, M. J., Neville, B. A., & Whitwell, G. J. (2010). Why ethical consumers don’t walk their talk: Towards a framework for understanding the gap between the ethical purchase intentions and actual buying behaviour of ethically minded consumers. Journal of Business Ethics, 97(1), 139–158.CrossRef
17.
Cesareo, L., & Pastore, A. (2014). Consumers’ attitude and behavior towards online music piracy and subscription-based services. Journal of Consumer Marketing, 31(6/7), 515–525.CrossRef
18.
19.
Cisco (2012). Cisco visual networking index: Forecast and methodology, 2011–2016. White Paper. San Jose, CA: Cisco.
20.
Cisco (2016), Cisco visual networking index: Forecast and methodology, 2015–2020. White Paper. San Jose, CA: Cisco.
21.
Commuri, S. (2009). The impact of counterfeiting on genuine-item consumers’ brand relationships. Journal of Marketing, 73(3), 86–98.
22.
Cronan, T. P., & Al-Rafee, S. (2008). Factors that influence the intention to pirate software and media. Journal of Business Ethics, 78(4), 527–545.CrossRef
23.
Culiberg, B., Koklic, M. K., Vida, I., & Bajde, D. (2016). Examining the effects of utilities and involvement on intentions to engage in digital piracy. Computers in Human Behavior, 61, 146–154.CrossRef
24.
D’Astous, A., Colbert, F., & Monpetit, D. (2005). Music piracy on the web: How effective are anti-piracy arguments? Evidence from the theory of planned behavior. Journal of Consumer Policy, 28(3), 289–310.CrossRef
25.
Dai, B., Forsythe, S., & Kwon, W. S. (2014). The impact of online shopping experience on risk perceptions and online purchase intentions: Does product category matter? Journal of Electronic Commerce Research, 15(1), 13–24.
26.
Davidov, E., Meuleman, B., Cieciuch, J., Schmidt, P., & Billiet, J. (2014). Measurement equivalence in cross-national research. Annual Review of Sociology, 40, 55–75.CrossRef
27.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982–1003.CrossRef
28.
De Corte, C. E., & Van Kenhove, P. (2017). One sail fits all? A psychographic segmentation of digital pirates. Journal of Business Ethics, 143(3), 441–465.CrossRef
29.
Depoorter, B., Parisi, F., & Vanneste, S. (2005). Problems with the enforcement of copyright law: Is there a social norm Backlash? International Journal of the Economics of Business, 12(3), 361–369.CrossRef
30.
Dunlap, T. M., & Kurtz, N. A. (2011). Electronic evidence in torrent copyright cases. Digital Evidence and Electronic Signature Law Review, 8, 171–178.
31.
Eagly, A. H., & Chaiken, S. (2007). The advantages of an inclusive definition of attitude. Social Cognition, 25(5), 582–602.CrossRef
32.
End, C. M. (2001). An examination of NFL fans’ computer mediated BIRGing. Journal of Sport Behavior, 24(2), 162–182.
33.
Feick, L. F., & Price, L. L. (1987). The market maven: A diffuser of marketplace information. Journal of Marketing, 51, 83–97.CrossRef
34.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.CrossRef
35.
Gefen, D., Karahanna, E., & Straub, D. W. (2003). Inexperience and experience with online stores: The importance of TAM and trust. IEEE Transactions on Engineering Management, 50(3), 307–321.CrossRef
36.
George, J. F. (2004). The theory of planned behavior and Internet purchasing. Internet Research, 14(3), 198–212.CrossRef
37.
Giles, D. C. (2002). Parasocial interaction: A review of the literature and a model for future research. Media Psychology, 4(3), 279–305.CrossRef
38.
Glasman, L. R., & Albarracin, D. (2006). Forming attitudes that predict future behavior: A meta-analysis of the attitude-behavior relation. Psychological Bulletin, 132(5), 778–822.CrossRef
39.
40.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis: A global perspective (7th ed.). Upper Saddle River: Pearson Education.
41.
Hansen, J. M., Saridakis, G., & Benson, V. (2018). Risk, trust, and the interaction of perceived ease of use and behavioral control in predicting consumers’ use of social media for transactions. Computers in Human Behavior, 80, 197–206.CrossRef
42.
Hennig-Thurau, T., Henning, V., & Sattler, H. (2007). Consumer file sharing of motion pictures. Journal of Marketing, 71(4), 1–18.CrossRef
43.
Higie, R. A., & Feick, L. F. (1989). Enduring involvement: Conceptual and measurement issues. Advances in Consumer Research, 16(1), 690–696.
44.
Hox, J. J. (2010). Multilevel analysis: Techniques and applications. London: Routledge.CrossRef
45.
Hox, J. J., Maas, C. J., & Brinkhuis, M. J. (2010). The effect of estimation method and sample size in multilevel structural equation modeling. Statistica Neerlandica, 64(2), 157–170.CrossRef
46.
Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indices in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55.CrossRef
47.
48.
Irdeto (2015), Irdeto piracy and business intelligence quick read report: 2015 Academy Award ® Nominated Films. Available at: http://​irdeto.​com. Last accessed November 24, 2015.
49.
50.
Kassing, J. W., & Sanderson, J. (2009). “You’re the kind of guy that we all want for a drinking buddy”: Expressions of parasocial interaction on Floydlandis.com. Western Journal of Communication, 73(2), 182–203.CrossRef
51.
Katz, E., Blumler, J. G., & Gurevitch, M. (1973). Uses and gratifications research. The Public Opinion Quarterly, 37(4), 509–523.CrossRef
52.
Kozinets, R. V. (2010). Netnography: Doing ethnographic research online. Thousand Oaks: Sage Publications.
53.
Kwong, S. W., & Park, J. (2008). Digital music services: Consumer intention and adoption. The Service Industries Journal, 28(10), 1463–1481.CrossRef
54.
Liang, A., & Lim, W. M. (2011). Exploring the online buying behavior of specialty food shoppers. International Journal of Hospitality Management, 30(4), 855–865.CrossRef
55.
Lin, H. F. (2007). Predicting consumer intentions to shop online: An empirical test of competing theories. Electronic Commerce Research and Applications, 6(4), 433–442.CrossRef
56.
Lin, T. C., Hsu, J. S. C., & Chen, H. C. (2013). Customer willingness to pay for online music: the role of free mentality. Journal of Electronic Commerce Research, 14(4), 315.
57.
Lysonski, S., & Durvasula, S. (2008). Digital piracy of MP3 s: Consumer ethical predispositions. Journal of Consumer Marketing, 25(3), 167–178.CrossRef
58.
Manstead, A. S. R. (2000). The role of moral norm in the attitude–behavior relation. In D. J. Terry & M. A. Hogg (Eds.), Attitudes, behavior and social context: The role of norms and group membership (pp. 11–30). Mahwah, NJ: Lawrence Erlbaum Associates.
59.
Marsh, H. W., & Bailey, M. (1991). Confirmatory factor analyses of multitrait-multimethod data: A comparison of alternative models. Applied Psychological Measurement, 15(1), 47–70.CrossRef
60.
Melancon, J. P., Noble, S. M., & Noble, C. H. (2011). Managing rewards to enhance relational worth. Journal of the Academy of Marketing Science, 39(3), 341–362.CrossRef
61.
Ming-Shen, W., Chih-Chung, C., Su-Chao, C., & Yung-Her, Y. (2007). Effects of online shopping attitudes, subjective norms and control beliefs on online shopping intentions: A test of the theory of planned behaviour. International Journal of Management, 24(2), 296–302.
62.
Mittal, B., & Lee, M. S. (1989). A causal model of consumer involvement. Journal of Economic Psychology, 10(3), 363–389.CrossRef
63.
Nonnecke, B., Andrews, D., & Preece, J. (2006). Non-public and public online community participation: Needs, attitudes and behavior. Electronic Commerce Research, 6(1), 7–20.CrossRef
64.
Oliver, R. L., & Swan, J. E. (1989). Consumer perceptions of interpersonal equity and satisfaction in transactions: A field survey approach. Journal of Marketing, 53, 21–35.CrossRef
65.
Park, C. W., & Young, S. M. (1986). Consumer response to television commercials: The impact of involvement and background music on brand attitude formation. Journal of Marketing Research, 23(1), 11–24.CrossRef
66.
Perugini, M., & Bagozzi, R. P. (2001). The role of desires and anticipated emotions in goal-directed behaviours: Broadening and deepening the theory of planned behaviour. The British Journal of Social Psychology, 40, 79–98.CrossRef
67.
Petty, R. E., & Cacioppo, J. T. (1979). Issue involvement can increase or decrease persuasion by enhancing message-relevant cognitive responses. Journal of Personality and Social Psychology, 37(10), 1915–1926.CrossRef
68.
Petty, R. E., Haugtvedt, C. P., & Smith, S. M. (1995). Elaboration as a determinant of attitude strength: Creating attitudes that are persistent, resistant, and predictive of behavior. In R. E. Petty & J. A. Krosnick (Eds.), Attitude strength: Antecedents and consequences (Vol. 4, pp. 93–130). London: Psychology Press.
69.
Phau, I., Lim, A., Liang, J., & Lwin, M. (2014). Engaging in digital piracy of movies: A theory of planned behaviour approach. Internet Research, 24(2), 246–266.CrossRef
70.
Poort, J., Leenheer, J., van der Ham, J., & Dumitru, C. (2014). Baywatch: Two approaches to measure the effects of blocking access to The Pirate Bay. Telecommunications Policy, 38(4), 383–392.CrossRef
71.
Pucely, M. J., Mizerski, R., & Perrewe, P. (1988). A comparison of involvement measures for the purchase and consumption of pre-recorded music. Advances in Consumer Research, 15(1), 37–42.CrossRef
72.
Randall, D. M., & Gibson, A. M. (1991). Ethical decision making in the medical profession: An application of the theory of planned behavior. Journal of Business Ethics, 10(2), 111–122.CrossRef
73.
Redondo, I., & Charron, J. P. (2013). The payment dilemma in movie and music downloads: An explanation through cognitive dissonance theory. Computers in Human Behavior, 29(5), 2037–2046.CrossRef
74.
Riekkinen, J. (2016). Dissonance and neutralization of subscription streaming era digital music piracy: An initial exploration. In PACIS 2016, proceedings of the 20 th Pacific Asia conference on information systems, Chiayi, Taiwan, June 27–July 1 2016, paper 251. Available at: https://​dblp.​org/​db/​conf/​pacis/​pacis2016.​html. Last accessed October 31, 2018.
75.
Rubin, R. B., & McHugh, M. P. (1987). Development of parasocial interaction relationships. Journal of Broadcasting & Electronic Media, 31(3), 279–292.CrossRef
76.
Schultz, D. E. (2006). Media synergy: The next frontier in a multimedia marketplace. Journal of Direct, Data and Digital Marketing Practice, 8(1), 13–29.CrossRef
77.
Shih, Y. Y., & Fang, K. (2004). The use of a decomposed theory of planned behavior to study Internet banking in Taiwan. Internet Research, 14(3), 213–223.CrossRef
78.
Shim, S., Eastlick, M. A., Lotz, S. L., & Warrington, P. (2001). An online prepurchase intentions model: The role of intention to research. Journal of Retailing, 77(3), 397–416.CrossRef
79.
Shoham, A., & Ruvio, A. D. M. (2008). (Un)ethical consumer behavior: Robin hoods or plain hoods. Journal of Consumer Marketing, 25(4), 200–210.CrossRef
80.
Shoham, A., & Ruvio, A. (2008). Opinion leaders and followers: A replication and extension. Psychology & Marketing, 25(3), 280–297.CrossRef
81.
Simpson, P. M., Banerjee, D., & Simpson, C. L., Jr. (1994). Softlifting: A model of motivating factors. Journal of Business Ethics, 13(6), 431–438.CrossRef
82.
Sinclair, G., & Green, T. (2016). Download or stream? Steal or buy? Developing a typology of today’s music consumer. Journal of Consumer Behaviour, 15(1), 3–14.CrossRef
83.
Steiger, J. H., & Lind, J. C. (1980). Statistically based tests for the number of common factors. Annual Meeting of the Psychometric Society Iowa City, IA, 758, 424–453.
84.
Stevens, J. (1996). Applied multivariate statistics for the behavioral sciences. Mahwah, NJ: Erlbaum.
85.
Tan, B. (2002). Understanding consumer ethical decision making with respect to purchase of pirated software. Journal of Consumer Marketing, 19(2), 96–111.CrossRef
86.
Taylor, S. A., Ishida, C., & Wallace, D. W. (2009). Intention to engage in digital piracy a conceptual model and empirical test. Journal of Service Research, 11(3), 246–262.CrossRef
87.
Venkatraman, M. P. (1989). Opinion leaders, adopters, and communicative adopters: A role analysis. Psychology & Marketing, 6(1), 51–68.CrossRef
88.
Wang, X., & McClung, S. R. (2011). Toward a detailed understanding of illegal digital downloading intentions: An extended theory of planned behavior approach. New Media & Society, 13(4), 663–677.CrossRef
89.
Wu, S. I. (2006). A comparison of the behavior of different customer clusters towards Internet bookstores. Information & Management, 43(8), 986–1001.CrossRef
90.
Yoon, C. (2011). Ethical decision-making in the Internet context: Development and test of an initial model based on moral philosophy. Computers in Human Behavior, 27(6), 2401–2409.CrossRef
91.
Yuan, K. H., & Bentler, P. M. (2000). Three likelihood-based methods for mean and covariance structure analysis with nonnormal missing data. Sociological Methodology, 30(1), 165–200.CrossRef
Metadaten
Titel
Lowering the pirate flag: a TPB study of the factors influencing the intention to pay for movie streaming services
verfasst von
Domenico Sardanelli
Agostino Vollero
Alfonso Siano
Gianmaria Bottoni
Publikationsdatum
12.04.2019
Verlag
Springer US
Erschienen in
Electronic Commerce Research / Ausgabe 3/2019
Print ISSN: 1389-5753
Elektronische ISSN: 1572-9362
DOI
https://doi.org/10.1007/s10660-019-09346-7

Weitere Artikel der Ausgabe 3/2019

Electronic Commerce Research 3/2019 Zur Ausgabe

OriginalPaper

Measuring e-service quality and its importance to customer satisfaction and loyalty: an empirical study in a telecom setting

OriginalPaper

The interaction effects of information cascades, word of mouth and recommendation systems on online reading behavior: an empirical investigation

OriginalPaper

Towards a cooperative security system for mobile-health applications

OriginalPaper

An efficient anonymous remote attestation scheme for trusted computing based on improved CPK

OriginalPaper

Strong anonymous mobile payment against curious third-party provider

EditorialNotes

Editorial: special issue on advances in security and privacy for future mobile communications