The effect of an individual’s age on the perceived importance and usage intensity of communications services—A Bayesian Network analysis

Pekka Kekolahti (), Juuso Karikoski () and Antti Riikonen ()
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Pekka Kekolahti: Aalto University
Juuso Karikoski: Aalto University
Antti Riikonen: Aalto University

Information Systems Frontiers, 2015, vol. 17, issue 6, No 10, 1313-1333

Abstract: Abstract Multiple novel interpersonal communications services have emerged recently, but how their usage and perceived importance are related to the personal characteristics of the users is still relatively unexplored. Therefore, the aim of this study is to explore the effect of an individual’s age on the perceived importance and usage intensity of communications services based on Bayesian Networks using a survey of 3008 Finns during 2011. In the case of Short Message Service (SMS), Instant Messaging (IM), Internet forums and communities (e.g., Facebook & Twitter), and e-mail the results indicate that the perceived importance of the communications services decreases as the age increases. With phone calls and letters, however, no clear dependencies with age were identified. In the causal analysis the importance of Internet forums and communities was the only variable which can be stated to be directly caused by an individual’s age. This variable also acts as a mediator in the path from age towards perceived importance of other communication services and also towards their usage intensity. These results about the central role of Internet forums and communities can be exploited, for example, by device manufacturers when designing their products, and by service providers when designing their consumer services. The study also provides new information for mobile operators about the dependencies between mobile communications services and a documented example workflow for research community to construct a causal Bayesian Network from a combination of observational data and domain expertise.

Keywords: Communications services; Bayesian networks; Machine learning; Causality; Perceived importance; Usage intensity; Individual’s age (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s10796-014-9502-9

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