The Ten Shades of Silver: Segmentation of Older Adults in the Mobile Phone Market

Abstract

With the closing of the age-related gap in mobile phone uptake and the aging of the population, older adults have increasingly become a desirable target group for mobile phone providers. Although abundant literature has accumulated describing the use of mobile phones amongst older adults, segmentation studies on this group of consumers remain scant and inconclusive. Drawing on the benefit and behavioral segmentation this study presents a segmentation model of older adults in the mobile phone market that incorporates a wide variety of consumer behavior, attitudinal, and acceptance variables relevant for the understanding of mobile phone (non-)usage patterns among users of feature phones and smartphones, as well as among mobile phone non-users. The model is based on a hybrid approach with a two-step cluster analysis using data collected by a telephone survey from a representative sample (n=1,581) of adults aged 55 or older in Slovenia in 2015. The analysis yielded two uniquely-profiled clusters within each of the five a priori determined segments, summing to a total of 10 clusters. The results show that older adults still prefer feature phones. Nevertheless, the mobile phone market has become highly heterogeneous, with clusters of older adults having distinguishable feature phone and smartphone use patterns as well as socio-demographic and life-course profiles. Since many of these profiles undermine the notion of older adults as "basic" mobile phone users, our findings represent a solid foundation for scholars and marketers to further investigate their specific needs in relation to more advanced smartphone and mobile internet usage.

Smart for development: Income level as the element of smartphone diffusion

“…The main aim of cluster analysis is to group the observed elements and to see the difference between the level of the impact of different variables. Cluster analysis in the smartphone market is mainly used for summarizing results of a survey (Petrovčič et al, 2018;Sidorchuk et al, 2018). Ward's method (Squared Euclidian Distance) was chosen as a clustering method according to marketing literature as it creates approximately equal sized clusters.…”

Improving the Measurement of Older Adults’ Mobile Device Proficiency: Results and Implications from a Study of Older Adult Smartphone Users

“…To consider the construct and criterion validity of the MDPQ-46 in the context of older adults who are smartphone users, the data were collected in 2017 within a summative usability test aimed at comparing the usability of a standard Android ( Figure 1) and an age-friendly GoLivePhone (GLP) ( Figure 1) smartphone launcher for older adults. 3 The Android operating system was selected because its use was the most prevalent among the target population of participants in Slovenia [27], whereas the selection of GLP was informed by its high-level age-friendly design [28].…”

Predictors of Seniors’ Interest in Assistive Applications on Smartphones: Evidence from a Population-Based Survey in Slovenia

“…Previous research investigating the acceptance and use of smartphone devices and services among seniors points to various factors that pertain to several domains of the C-TAILS model. With reference to the challenges of independent living (e.g., maintenance of social resources, preservation of cognitive ability and mobility issues), it has been shown that smartphone use is to a great extent related to the personal characteristics of seniors (e.g., the instrumental activities of daily living (IADL), chronic diseases, age, and gender) and socio-economic conditions (e.g., education, household income, and living arrangements) [19,20,21]. In addition, the embracement of smartphone devices and services is associated with the intensity of seniors’ engagement with information and communication technology (ICT), requiring a variety of digital skills, including the intensity and breadth of mobile phone features used [5,19,22].…”

“…With reference to the challenges of independent living (e.g., maintenance of social resources, preservation of cognitive ability and mobility issues), it has been shown that smartphone use is to a great extent related to the personal characteristics of seniors (e.g., the instrumental activities of daily living (IADL), chronic diseases, age, and gender) and socio-economic conditions (e.g., education, household income, and living arrangements) [19,20,21]. In addition, the embracement of smartphone devices and services is associated with the intensity of seniors’ engagement with information and communication technology (ICT), requiring a variety of digital skills, including the intensity and breadth of mobile phone features used [5,19,22]. Relatedly, it has been indicated that smartphone-related beliefs and attitudes among seniors are conditioned by compatibility (i.e., the degree to which smartphones and AT are perceived as being consistent with existing values, past experiences, and the needs of potential adopters) [23], as well as negative emotions, such as mobile phone anxiety [10,19,24].…”

“…In addition, the embracement of smartphone devices and services is associated with the intensity of seniors’ engagement with information and communication technology (ICT), requiring a variety of digital skills, including the intensity and breadth of mobile phone features used [5,19,22]. Relatedly, it has been indicated that smartphone-related beliefs and attitudes among seniors are conditioned by compatibility (i.e., the degree to which smartphones and AT are perceived as being consistent with existing values, past experiences, and the needs of potential adopters) [23], as well as negative emotions, such as mobile phone anxiety [10,19,24]. Another important aspect of the C-TAILS model is the resources (i.e., effort and money) that are required to start using new technology [18].…”