Hannu Verkasalo

Analysis of users and non-users of smartphone applications

Purpose: Smartphones facilitate the potential adoption of new mobile applications. The purpose of this research is to study users and non-users of three selected mobile applications, and find out what really drives the intention to use these applications across users and non-users. Design/methodology/approach: The authors measured actual usage of mobile applications in a panel study of 579 Finnish smartphone users, using in-device measurements as an objective way to identify users and non-users. A web-based survey was used in collecting data to test an extended TAM model in explaining intention to use. Findings: Perceived technological barriers negatively affect behavioural control, reflecting peoples assessment of themselves being capable of using the services without trouble. Behavioural control is directly linked to perceived usefulness (except for games) and perceived enjoyment, as hypothesized. Perceived enjoyment and usefulness were generically found to explain intention to use applications for both users and for non-users. Research limitations/implications: With regards to the impact of social norms, the study finds that further research needs to be done in exploring its impact more thoroughly. The dataset of the research, consisting purely of male-dominated, young smartphone users, make the generalization of results difficult. Practical implications: There are differences regarding what drives the usage of different kinds of mobile applications. In this study, map applications and mobile Internet, are driven by more utilitarian motivations, whereas games are more hedonic. It is also clear that not everybody are using applications facilitated by smartphones, and therefore the presented approach of studying users and non-users separately provides a new approach to analyze adoption on a practical level. Originality/value: This research proves that models like TAM should not treat mobile services as a generic concept, but instead to specifically address individual mobile services. The research also demonstrates the unique value of combining objective usage measurements (reflecting actual behaviour) with traditional survey data in more comprehensively modelling service adoption.

Contextual patterns in mobile service usage

Mobile services differ from other services because of their temporal and spatial attributes. Mobile services additionally differ from each other in their value-added to the end-user. Some services—such as emailing and voice—are more business oriented. On the other hand, various free-time oriented services are provided in new smartphones, such as imaging and music playback. The present paper studies how mobile services are used in different contexts. For this, the paper develops a specialized algorithm that can be used with handset-based usage data acquired straight from end-users in an established panel study process. Educated guesses can be drawn on the user context based on the developed algorithm. In the present exercise usage contexts were divided into home, office and “on the move”. The algorithm is used with exemplary data from Finland and the UK covering 324 consumers in 2006. More than 70% of contextual use cases are correctly classified based on raw data. According to exemplary results particularly multimedia services are used “on the move”, whereas legacy mobile services experience more evenly distributed usage across all contexts. The algorithm that identifies context based on raw data provides a new angle to mobile end-user research. In the future, the accuracy of the algorithm will be improved with the integration of seamless cell-id logging and GPS data.

A handset‐based platform for measuring mobile service usage

Purpose – The purpose of the article is to demonstrate the viablity of a handset‐based research platform in measuring mobile service and application usage through various descriptive empirical studies.Design/methodology/approach – A handset‐based research platform was used in measuring mobile usage in an international panel consisting of more than 500 mobile subscribers. The panel took place in 2005‐2006.Findings – The research paper finds various interesting data points which cannot be derived with any other method. In addition, the paper finds that there are significant differences in certain mobile service and application use cases between different demographic groups.Research limitations/implications – The main research limitations are the size of the sample and lack of clear business implications. The main idea of the paper was just to demonstrate the type of measurements and studies that can be done with the developed research platform.Practical implications – 3G technology drives packet data usage ...

Dynamics of Mobile Service Adoption

This study utilized a newly developed handset-based mobile end-user research platform and obtained data from 548 Finnish smartphone users in 2006. In addition to descriptive adoption statistics, a path analysis model is developed that explains mobile service adoption contingent on a set of explanatory variables. The paper finds that user intentions have a strong impact on consequent adoption of the service. What is more, perceived hedonic benefits from the service are the strongest factor driving user intentions to use the service. The perceived technical capability to use the service and the role of the surrounding social network explain little why early-adopter users intend to use services. Interestingly multimedia services are strongly driven by newer more capable handsets and mobile Internet browsing benefits significantly from block or flat-rate (instead of usage-based) pricing plans for transmitted data. The paper develops several indices that measure time-varying characteristics of mobile services.

Measuring Mobile Peer-to-Peer Usage: Case Finland 2007

We study the development of mobile peer-to-peer (MP2P) traffic and the usage of MP2P applications in Finland during 2005-2007. Research data consists of 1) traffic traces measured from three Finnish GSM/UMTS networks covering the Internet-bound mobile data traffic generated by 80-90% of Finnish mobile subscribers (N > 4,000,000), and 2) usage log files collected with a dedicated Symbian handset monitoring application (N = 579). In the traffic trace measurement, we notice almost zero P2P file sharing traffic for handsets, but 9-18% of unidentified traffic, part of which possibly being P2P traffic. Potentially a notable growing trend for computer-based P2P file sharing traffic is visible in GSM/UMTS networks, BitTorrent and eDonkey being the most popular protocols. In the panel study, only Fring, a client to several P2P-based communication services, has significant usage and data volume levels.

Analysis of mobile internet usage among early-adopters

Purpose – The purpose of this paper is to identify several measures that reflect the diffusion of the mobile internet.Design/methodology/approach – The measurements are implemented with a newly developed handset‐based mobile service research platform that provides a novel way to accurately identify trends taking place in mobile service usage. These measures are demonstrated in a case example comparing Finnish early‐adopter smartphone users between 2005 and 2006 (500 and 695 users).Findings – The results indicate that the mobile internet has not yet emerged on a large scale in Finland. On the contrary operators have slightly increased their power, potentially because handset bundling with mobile subscriptions is now allowed in Finland.Research limitations/implications – The measurement framework can be further utilized in both cross‐sectional and longitudinal study settings in evaluating the emergence of the mobile internet. No other empirical research method provides the accuracy and scope of usage measur...

Handset‐based measurement of mobile service demand and value

Purpose – The purpose of this paper is to develop various measures and visualizations that reflect differences in the maturity and characteristics of mobile services. The visualizations and measures support market research processes with a recently developed handset‐based mobile service research tool.Design/methodology/approach – A new handset‐based mobile service research platform was used in the study. This platform provides both questionnaire data and accurate usage‐level measurement data. The dataset included 695 Finnish smartphone users from year 2006, and 565 users from 2005.Findings – Penetration, usage concentration and usage diversity indices illustrate how mobile voice has already reached the mass market and consequently relatively small differences in usage intensities among end‐users exist. On the contrary, many new services such as multimedia and internet browsing still catch quite explorative instead of sustainable usage. User preferences towards emerging mobile services are more heterogeneo...

Unlicensed Mobile Access (UMA) Handover and Packet Data Performance Analysis

UMA is a technology helping cellular operators to retain control over subscribers in the era of converging radio access technologies. By supporting handovers to and from WiFi networks, UMA seems to be a perfect solution as new mobile services require performance and seamless mobility. From the cellular operator point of view UMA does not require enormous investments and is a good choice for extending network coverage. This research paper discusses the technical implications of UMA based on measurement results for GSM to WiFi handovers and packet data performance. The measurements show that UMA works well, and voice handover breaks are similar or lower than those experienced in traditional GSM systems. In addition, UMA provides a considerably higher throughput than GSM systems. The results showed that the average throughput is twice or more than in GSM. Therefore, the user experience for data services improves to 3G-kind of services.

Empirical observations on the emergence of mobile multimedia services and applications in the U.S. and Europe

Mobile multimedia is still at early stages of commercialization, and pioneering solutions are currently adopted by only early-adopter-type of end-users. Accurate handset-based usage-level measurements have been implemented in several panel studies taking place both in the U.S. and Europe (France, England, Germany and Finland) in 2005-2006. These studies have included more than 1 700 Symbian smartphone users, who represent early-adopter subscribers. The results of these studies provide a lot of insights on the current coverage of mobile multimedia services among early-adopters. It seems that the camera application and various games are by far the most widely used multimedia-oriented mobile applications. The role of games reflects particularly in the 3rd party application scene. Various multimedia players were also identified. Many of them deal with offline content (e.g. offline music/movies), but there were quite a number of streaming applications evident in the data, too. 13% of all panelists had actually generated packet data with multimedia applications. People who utilize streaming packet data services usually generate the biggest chunk of their data use with these applications. In multimedia communications it was found that video call usage was very infrequent in Europe (video calls need 3G infrastructure). However, both Bluetooth and MMS messaging have attracted decent masses. Americans utilize mobile emailing and instant messaging very actively. The on-going emergence of instant messaging and other ways of multimedia communications is an observation worth follow-up studies. This empirical study contributes to the current understanding of real usage patterns of mobile multimedia services and applications, at the same time presenting a useful research platform in implementing this kind of studies on end-customer behavior also in the future.

Opportunities and problems with automated data collection via smartphones

Through smartphone measurement software, researchers will be able to collect vast amounts of log data on the use of mobile media and applications. The present paper discusses the opportunities of smartphone measurement software in multi-method research, but also the ethical and methodological issues involved. We provide suggestions on how to deal with obvious privacy issues that arise from using smartphone measurement software. We also discuss how one can deal with sampling and selecting respondents. An illustrative study in which we applied smartphone measurement suggests that methodological and ethical issues can be overcome in practice, although doing so requires a great deal of effort. Still, collecting data through smartphone measurement is highly promising as both the quality and quantity of the resulting data is impressive.