Empirical Analysis of Usage and Acceptance of Software Distribution Methods on Mobile Devices

Saskia Geisler University of Göttingen

Chair of Application Systems and E-Business Göttingen, Germany

sgeisle1@uni-goettingen.de

Martin Zelazny University of Göttingen

Chair of Application Systems and E-Business Göttingen, Germany

mzelazn@uni-goettingen.de

Stefan Christmann University of Göttingen

Chair of Application Systems and E-Business Göttingen, Germany

schrist@uni-goettingen.de

Svenja Hagenhoff University of Applied Sciences St. Pölten

Institute of Media Management St. Pölten, Austria

svenja.hagenhoff@fhstp.ac.at

Abstract—Mobile end devices, such as smartphones, are widely distributed and their technical capacities are increasing. End devices have surpassed the original idea of enabling users to talk to each other. Users are now able to install application software on their devices. This is of special interest to companies, as it portrays a new source of income for stakeholders of the value chain in the mobile internet. However, it is unclear how such applications should be technically transferred to the mobile devices. Different technologies are available for this task. This paper examines the previous use and acceptance of software distribution methods. User preferences for technical transmission ways were furthermore determined with surveys. It was not possible to identify a dominant mode of transmission. Acceptance of software distribution methods especially depends on technical affinity and the user’s gender. Thus, operating systems and producers of end devices should enable usage of multiple ways of transferring data.

Keywords-Empirical analysis, software distribution, mobile end device, mobile applications, usage, acceptance

I. SOFTWARE DISTRIBUTION ON MOBILE DEVICES

An increasing number of mobile devices, especially smartphones, allow for the installation of application software [1]. This software can serve communication, transaction or service provisions within companies [2]. There are different ways to create applications for mobile end devices. With respect to software distribution, one has to differentiate between applications installed on an end device (Fat Client), applications accessed via a web browser as a web application (Web Client) and applications used via a Thin Client [3]. Fat Clients have to be installed on the end device before they can be used. The other two application types require installation of corresponding client applications (web browser, thin client-applications).

Fat Client-applications for mobile end devices can be developed for a specific operating system (“native”) or for a

specific runtime environment (e.g. the Java Micro Edition) [4]. This enables usage by all operating systems and avoids variant diversity. However, the software often still has to be adapted to specific devices and access to system components (e.g. accelerometer, GPS-receiver) is limited [5]. The issue of operating system dependency is relevant because operating system developers generally determine the possible ways of transmission of native applications. However, with runtime environments, any kind of transmission mode can be used.

The transfer of applications to be installed on an end device is called distribution. In business administration, one differentiates between physical and acquisitive distribution [6]. The physical distribution, which is the most specific definition, comprises the technical cargo handling, meaning the transport from the producer to the client. The acquisitive distribution definition is more function-oriented and general. It includes “the sum of the (marketing) activities of all economic agents that are involved in transporting economic goods from the producer to the consumer” [6]. The acquisitive distribution includes business models, such as Mobile Application Stores or portals for mobile applications, which could limit the user's choice of technical transmission ways. Due to the variety in these ways, this paper focuses on the physical distribution. Thus, it is possible to examine whether existing business models offer the ways of transmission desired by users. The study therefore makes it possible for the appropriate members of the value chain (software market operators, hardware and software vendors) to verify if further or other ways of transmission must be allowed and rendered possible.

The distribution of applications to mobile devices can happen through different ways of transmission. This is due to the heterogeneous product and system landscape. There are different interfaces for data transmission, and either the software providers or the application marketplaces regulate their usability. In the following we will present common distribution possibilities for mobile applications.

2011 10th International Conference on Mobile Business

978-0-7695-4434-2/11 $26.00 © 2011 IEEE

DOI 10.1109/ICMB.2011.10

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A. Mobile Network GSM is a standard for mobile networks and stands for “Global System for Mobile Communication“ [7]. GSM uses a transmission rate of a maximum of 13,000 bit/s for speech and 9,600 bit/s for data. Due to the low data transfer rates, high-capacity add-ons were introduced (e.g. GPRS). A further development is UMTS (Universal Mobile Telecommunication System), which currently reaches a data rate of 7.2 mbit/s.

In order to enable the installation of software via the mobile network, the user accesses the internet via a web browser or special software (e.g. AppStore client) and downloads the desired software. In addition, mobile services such as SMS or MMS can be used to signalize the wish to download software. Usually, users not only pay the purchasing price for the software but are also charged fees for using the network. However, these vary between contracts or are nonexistent if a flat rate is booked.

B. Bluetooth Bluetooth is a short-range network (10 to max. 200 meters). The maximum data transfer rate is currently 2 mbit/s. Hotspots can be established via Bluetooth, which grant Bluetooth-compatible devices, such as mobile phones, access to applications.

There are different ways of setting up an installation via a hotspot [8]. The user can automatically receive an application if Bluetooth is active, or he can signalize his wish to do so by a) changing his end device name, b) sending a file to the hotspot or c) choosing the desired application on a stationary terminal.

In addition to this direct communication via the hotspot and the application provider, it is also possible to transfer mobile applications directly between mobile end devices via Bluetooth. However, this is rarely done in practice, as mobile applications are mostly copy protected. There are no further transmission charges involved here.

C. WLAN WLAN is a technology that establishes wireless local

networks (Wireless Local Area Network), which, among other things, enables nomadic internet access. The mobile devices connect to a WLAN-Access-Point and can then obtain applications from the network [7]. Current WLAN-standards allow for a transmission rate of up to 300 mbit/s. This is similar to transmission via a mobile phone.

Using WLAN can also create costs, if the hotspot charges money for transferring data. In general, there are no costs involved with private WLANs.

D. NFC In the near future, Near Field Communication (NFC) should facilitate and speed up data transmission between and with mobile devices [9]. NFC is a short-range technology [9], with a range of about 20 cm. This has the advantage that a high resistance to disturbance can be ensured and that transmission security is higher. The maximum data transferring rate is 424 kbit/s [9].

In order to transfer data between an NFC-compatible end device and a sending station (or another NFC-compatible end device), the end device has to be as close as a few centimeters to the sending station or has to touch it [9]. Data transmission is then initiated automatically and the application is installed either from the sending station or the internet.

E. Personal computer If the mobile end device does not possess an interface for internet communication, or if this would generate extra costs that the user is unwilling to pay, it is also possible to install via a computer. The computer then first connects to the application provider (e.g. to an online shop of a mobile phone producer). Next, the desired software is transferred via the internet onto the computer, according to the software's (and the end device model's) specifications. The application is then transferred onto the mobile end device via a data carrier, USB-cable or wirelessly via Bluetooth. There are no costs involved with this way of transmission.

F. Challenges With stationary end devices there is little need to examine the software distribution scientifically. Applications are transferred via physical data carriers (DVD, CD, floppy disc) or downloaded. The only thing worth analyzing is the use of applications as Software-as-a-Service.

The mobile internet poses special, mainly technical, challenges. Dunlop & Brewster describe five central challenges to developing interfaces and mobile applications: the mobility, the skills of the average user, limits to input and output, use of information via context and the user’s ability of multi-tasking [10]. Johnson, on the other hand, names the mobility, the heterogeneity and the integration of different end devices, network services, as well as applications as areas of research in interactions with mobile systems [11]. De Reuver, Bouwman & De Koning and Banavar, Cohen and Soroker emphasize that the problem of mobility has to be considered when developing mobile services [12][13]. For Maaß and Pietsch, as well as Soroker et al. the heterogeneity in end devices plays a major role [3][14]. Another challenge found in the literature are the limits to mobile end devices, such as display size and calculating capacity [15][16][17].

In the following, we will examine the challenges of heterogeneity (a), mobility (b) and limitations (c) to mobile end devices which can be summarized as the most important challenges that software distribution faces.

Software distribution within the mobile internet is very complex due to the heterogeneity (a) of end devices. Mobile devices differ in their input and output options, as well as in the available resources and transfer technologies. Thus, numerous hardware combinations exist that have to be considered and supported during software distribution [4][13].

However, the software employed is also heterogeneous, especially with regard to the operating systems for mobile end devices and runtime environments. Due to this heterogeneity it is usually necessary to distribute the

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software among several platforms, after it has been developed [14]. This is often time consuming and expensive [18[19].

The mobility (b) of the end devices poses another challenge, as the user also wants to use and install software while on the move [4]. Until recently, mobility when using applications was only possible to a limited extent. However, mobility is gaining in importance, as mobile telecommunication is expanding and devices are becoming smaller and more efficient. There is a fundamental difference between the use of mobile end devices and stationary ones. The user will, for instance, not be able to pay full attention to his device while on the move [20]. Furthermore, mobile end devices, or mobile applications are mostly used spontaneously and ad-hoc and therefore have to be available quickly [4]. Thus, the mobile network has to support the software distribution and the installation process has to be simple. In addition, the end devices' limited input options have to be considered, in order to enable quick installation.

Mobile end devices are limited in several ways (c), e.g. through data transmission, display size, power supply and performance [21][16][17]. Data transmission is of special interest with regard to the software distribution. Even though mobile networks have been greatly developed during the last year and higher data transmission rates are possible, the bandwidth is still relatively low in comparison to cable-based transmission.

Although higher transmission rates through UMTS are already available, the extended GSM-network is still mainly used [22]. It has a very wide coverage, and most mobile end devices do not yet support UMTS. Connection loss is another problem when installing mobile applications [17].

The survey takes these problems into consideration and their consequences are examined.

II. USER SURVEY The user survey was planned and carried out according to Dieckmann [23] and examines the methods of software distribution for mobile devices. Special emphasis is laid on the acceptance of different ways of distribution. In order to gain a bigger sample size, the scenarios were not tested by the subjects. The survey was carried out in Göttingen, Germany.

A. Research question & hypotheses Four research questions were developed (Q1-Q4) from which eight hypotheses (H1-H8) were derived.

Q1: Which distribution method do users of mobile

phones currently use most often and why? Q2: Which distribution method do users prefer and

would like to use in the near future? Q3: What are the experiences of mobile phone users with

installing mobile applications? Q4: What are the effects of demographic factors on

installation processes of mobile applications and future wishes?

Research questions Q1 and Q2 show relationships between currently used and desired software distribution methods.

H1: The majority of users downloads software to a

stationary or mobile PC and installs it from there. H2: Users only prefer to install via mobile network if

their tariff presents them with sufficient data capacity and their mobile device supports mobile web usage very well.

H1 is based on the fact that the mentioned way of

installation is the first possibility to install additional applications onto a mobile device. This could result in people being more acquainted with this method and therefore using it. It can furthermore be expected that the majority of users will not yet own an end device that supports direct transmission onto the device adequately. The additional costs of directly transferring via WLAN could also keep users from choosing this method.

H2 is based on the assumption that the availability of the required hard- and software technologies facilitates mobile web usage and working and therefore also promotes the installation of mobile applications via the mobile network. It was shown that the majority of users do not accept transmission costs [18]. Thus, it can be assumed that users with a flat rate or big enough data capacity will prefer installations via mobile network.

H3: The majority of users would prefer direct installation

on the mobile device. H4: The majority of users does not accept costs for data

transmission, in addition to program costs. H3 is based on the mobile context, in which the user is

placed with his end device. Thus, the user seldom has access to a PC with which transmission is possible while on the move. The use of WLAN or the mobile network seems to make more sense, in order to install something directly. Furthermore, direct transmission onto the end device is generally less time-consuming and simpler than via a PC.

H4 is based on the fact that users are cost-conscious and was already proven in an earlier study [18]. This hypothesis was mentioned again to confirm it with a bigger sample size and to strengthen its validity.

H5: The majority of test persons has never tried to install

software onto their mobile device. H6: Less than half of the installations of each user had

problems leading to abortion. Due to the assumption that many older mobile devices

(non-smartphone mobile phones) are still in use, which support the installation of mobile applications not at all or with great difficulties, H5 was formed. In addition, the trend of using mobile applications is a very recent development and it must therefore be assumed that the majority of users has not yet come into contact with the installation of mobile applications. This is confirmed by the still low usage of the mobile internet [24].

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As mobile applications that cannot be installed successfully or that often have installation problems do not prevail on the market, H6 is assumed.

After all, mobile applications are also tested intensively before being released. It can therefore be assumed that the installation processes are not error-prone. Due to the stable mobile network connection problems are seen as uncommon. This is also true for faulty program versions, as the user can either choose a suitable version before installation or he is only offered the appropriate one.

H7: Users with a higher affinity to technology have less

problems with the installation process and desire an installation technique that is modern and wireless.

H8: Male users install more mobile applications on their end devices.

H7 is based on the assumption that people with an

affinity to technology deal more with technology and are therefore better acquainted with installation processes. It can also be assumed that these people are more open towards modern, wireless technologies. In our user research, these were technologies such as NFC, WLAN, a Bluetooth-hotspot or the mobile network.

H8 is closely linked to H7 and is based on a study which showed that more men than women use the mobile internet [24].

B. User study The user study was conducted within an individual cross-section study, in form of a written questionnaire online. Thus, we were able to reach a large sample size (477 test persons). As we have to assume that younger users deal more with mobile devices, the mobile internet and mobile applications, this age group was targeted specifically and the survey was conducted online [18][24]. In order to reach a representative sample size test persons were chosen randomly [23]. After pretesting and revising the questionnaire, it was put online for eight weeks and advertised through emails, asking people directly in the University of Göttingen and through entries in the Social Web.

The questionnaire collected data on the users' mobile end devices, on distribution ways and on the installation of mobile applications. In addition, it collected data on the users' willingness to pay for data transmission of free or fee-based mobile applications, data on how users evaluate different ways of transmission. Data on the users' future wishes and what way of transmission they would prefer depending on the situation as well as demographic data was also collected. The hypotheses explained before were then tested with t-tests and F-tests using the dataset.

III. SELECTED RESULTS The sample consisted of 43% male and 57% female participants and thus reflects a relatively balanced ratio. The age structure is relatively young, with about 43% of the participants between age 21 and 25.

A total of 75% of the participants think it is important to always have the newest technology. Thus, over 99% own a mobile device. The shares of manufacturers used by the test persons are depicted in Fig. 1. According to these results it may be assumed that, even though the sample is not representative for the population, it is adequate for the purpose of the study. After all, the research aims at people with an affinity to technology who use their mobile devices intensively.

Figure 1. Distribution of mobile end devices

A. Usage of distribution methods (Q1) Hypothesis H1 can only be confirmed with a probability of error of 13%, which is not significant. 54% of the participants install applications through the PC, 42% install applications directly onto their mobile device and 4% obtain their applications from other mobile devices. A significant result with a probability of error of 3% can be reached if the category “Transmission between end devices” is excluded.

This result can be explained by the fact that users lack technical equipment, with 58% having no access to WLAN and 37% not having UMTS.

In the following, the transmission ways used by the participants will be explained in more detail. Fig. 2 shows the previously used transmission ways, according to direct (between end devices) and indirect transmission. Most of the users use a USB-cable when transferring via a PC. There are different direct transmission ways. 43% of the participants who stated that they install applications directly use mainly the mobile network, followed by WLAN. 82% of the participants who transfer data between mobile devices use Bluetooth. Alternatives, such as USB-cables, are rarely used.

Figure 2. Frequently used transmission ways

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Hypothesis H2 could not be confirmed. However, it could be statistically proven with a probability of error of less than 1% that users whose tariff provides them with a sufficiently large data volume and whose mobile device supports mobile web usage well (GPRS- or UMTS-compatible) prefer the mobile network for data transmission more than users, who do not fulfill these criteria.

It is particularly noticeable that many users said they did not know their tariff or did not have one (43%), even though every provider normally has a data tariff.

Figure 3. Usage of transmission ways according to tariff and end

device equipment Fig. 4 shows the used installation methods in greater

detail. The usage scale ranges from 1 (never) to 5 (very often).

Figure 4. Currently used installation methods

The installation figures via NFC, memory card and

transmission between end devices are of special interest, as these are rarely used today. We suspect that the test persons misunderstood the question and thought that the question included the transmission of audio and image files.

B. Acceptance of distribution methods (Q2) Hypothesis H3 was discarded with a level of significance of only 1%. Merely 39% of the participants preferred this installation method. Instead, 50% preferred installing via PC. A possible explanation could be that users are more familiar with a PC, which was the first device to offer the installation of applications onto mobile devices. On the other hand, security issues could also play a role, as the participants generally saw PCs as safer than mobile networks. This could be proven with a probability of error of less than 1%.

When only examining Apple’s iPhone, one notices that there is no “mobile to mobile“ transmission and that 73% of the participants using an iPhone prefer direct transmission and installation. The transmission of applications between end devices is not facilitated by the iPhone so that users are probably not familiar with this. In general, the users especially want to have the already used transmission methods. Only 17% of the participants want to have another transmission method, besides those they used in the past.

Only 47% of the participants accept additional costs for data transmission, besides product costs. Hypothesis H4 can therefore be proven with a probability of error of less than 1%. Thus, users do not accept additional costs. This is especially true for programs that charge a fee, as the statement (no charge) was chosen more often than all of the others put together. Only 42% of the participants accept additional costs. Acceptance is only slightly higher with free programs (52%).

Figure 5. Willingness to pay for mobile applications

The average willingness to pay for the distribution of

applications for mobile devices was 0.50 € in this sample. Even though a negative correlation between program price and willingness to pay for data transmission could not be proven significantly, a tendency is shown. If applications that are free of charge and applications that involve fees are examined separately, users were willing to pay 0.57 € with the former and 0.44 € with the latter.

It is also interesting that participants who knew their data tariff, were willing to pay more (0.56 €) than those who did not know (0.46 €). However, this is not significant (significance 83%), although a trend is visible.

Furthermore, we were able to determine that the participants would install relevant applications via mobile network, while on the move (see Fig. 6). Applications which are not needed right away are installed via PC on returning home. It is noticeable that the second most common way would be to also install relevant applications via PC at home. This can either be explained by users being more used to installing things via PC, by devices that are incompatible with new technologies or by users not being willing to pay for data transfer, as it is mostly free via PC.

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Figure 6. Usage according to relevance

C. Experiences with installation (Q3) 53% of the participants have already installed software on their mobile device. Thus, hypothesis H5, which states that the majority has not installed software on their own mobile end device, could not be verified. The probability of error is 6.5% which speaks in favor of discarding this hypothesis.

The high installation quota can be explained by the fact that the majority of participants were interested in the topic. The high proportion of test persons with an affinity for technology (75%) confirms our suspicion.

Fig. 7 shows, amongst other things, the number of successful installations per user. This shows that there are apparently two groups of users: “occasional users”, that have installed 2-5 applications and “intensive users” that have installed more than 20.

Figure 7. Successful and unsuccessful installations

Hypothesis H6 could roughly be confirmed with a

probability of error of 0%. It can be significantly proven that more than five out of six installations were successful. On average, 15% of the installations created problems, mainly caused by wrong program versions (57%) or connection problems (29%). The total of successful installations of all participants was 2885, while the sum of unsuccessful ones was 496. On average, participants who had previously installed mobile applications carried out 13.4 installations, of which 11.5 were successful.

Most participants thought that the installation process they had chosen was relatively easy to understand (72%). WLAN-users found it very simple, followed by mobile network users (see Fig. 8; 1 = very difficult, 5 = very simple).

Figure 8. Evaluation of the simplicity of installation processes

according to transmission medium An interesting question is why 47% of the participants do

not use mobile applications. 68% of the participants who have not previously installed software to their mobile device are not interested in mobile applications. Another 19% think that mobile applications are too expensive. For more details, see Fig. 9.

Figure 9. Reasons for not using mobile applications

D. Effects of demographic factors (Q4) It comes as no surprise that, with an error probability of less than 1%, people with an affinity for technology have fewer unsuccessful installations and fewer problems. Fig. 10 shows the correlation between technology-affinity and the proportion of successful installations.

Figure 10. Correlation between technology-affinity and the proportion

of successful installations (bubble size shows number of participants)

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The correlation is 0.184 and shows a positive relation with a significance of more than 99%. The first part of hypothesis H7, which states that technology-affine people have fewer problems installing mobile software, can therefore be confirmed.

It can also be confirmed that technology-affine people prefer modern technology for software installation. The probability error of this statement is less than 1%. In this study, new technology was represented by mobile networks, WLAN, Bluetooth hotspot and NFC.

It could also be confirmed that male users install more applications than female ones, with an error probability of less than 1%. Therefore H8 can also be verified. On average, male users carry out 17.2 installations, which is significantly higher than with female users (8.83). This can be explained by the general connection between sex and technology-affinity, which could also be confirmed by this study.

In contrast to female users, male users deem it more important to always have modern technical devices. Possible answers ranged from 1 (very unimportant) to 5 (very important). Men within the sample were more technology-affine, which could also be confirmed significantly on a general scale. However, it cannot be ruled out that the self-assessment of technology-affinity has an expected deviation from the actual technology-affinity (bias), which could lead to the negation of the significance.

Regarding the relationship between technology-affinity and device manufacturers, it can be said that participants with a relatively high technology-affinity prefer end devices made by Apple, RIM (BlackBerry) and HTC (among other manufacturers) (see Fig. 11).

Figure 11. Technology-affinity according to device manufacturer

It is therefore possible to determine the users’ sex, as

men have a higher affinity to technology. Thus, 80% of the Apple or HTC users are male, whereas females prefer other manufacturers. Apparently, there are correlations between sex, technology-affinity and choice of end device.

Partially it was also possible to prove that the preference of transmission method depends on the user's sex (see Fig. 12). There is a significant tendency for women to prefer transmission between mobile devices, over a memory card or via Bluetooth hotspots. On the other hand, men prefer transmission via mobile network or WLAN. The error of probability for these statements is less than 3%. In addition, the men in the sample were willing to pay more (0.52 €) than the women (0.49 €), however this is not significant.

Figure 12. Sex-dependant evaluation of the scenarios

Other findings are related to the participants' age. It could

be shown that people over 36 years are significantly more technology-affine than younger people. The error probability is slightly less than 5%. This is also connected to a higher willingness to pay for data transmission of mobile applications. Thus, people that are older than 36 years are significantly more willing to pay (error probability less than 1%). A higher income could be a possible explanation for this, as people over 36 years generally earn more [26]. Therefore they have better financial opportunities to remain up to date with regard to technical devices, and this group is not only willing to pay more, but also more technology-affine.

Furthermore, the analysis showed that 51% of the 15-20year olds installed more mobile applications onto their end devices than the average. This was only the case with 37% of the 21-30 year olds.

Figure 13. Above average installations of mobile applications

These results resemble the usage behavior, which can

generally be observed in the mobile internet [24]. Accordingly, 43% of the 14-19year olds and 36% of the 20-29year olds use the mobile internet intensively.

E. Implications for future software distribution processes These results have implications for the future distribution

of mobile applications. It can be expected that mobile applications will also become more popular in the future due

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to the availability of compatible end devices. However, women as a target group should be more strongly addressed, as they install less mobile applications than men (see section 4.4). This could be due to an insufficient range of applications. On the other hand, it is also possible that women are generally less interested in mobile applications, as they have a lower affinity for technology (see section 4.4). Thus, application developers should more clearly explain to female users which added value their applications have.

Furthermore, application costs and data transfer costs should be made transparent for customers [25]. Manufacturers should provide free data transmission whenever possible. This is because users rarely accept transmission and program costs, and fees also prevent those users from using the application who install the relevant software at home through their PC (see section 4.2).

In addition, marketing should target the group of over 36year olds more strongly. They are willing to pay more and are more technology-affine (see section 4.4), which basically makes them predestined consumers of mobile software applications requiring a fee. Future installation processes should be fast and simple, as this is very important for the users. The direct transmission onto the end device via WLAN, a mobile network or NFC seems appropriate (see section 4.3).

As the connection can break off while transferring data via the mobile network (see section 2), which interrupts the installation, it has to be ensured that the installation of an application resumes, in order to shorten and simplify the process. In addition, an effort should be made to improve the quality of the applications by increasing compatibility, in order to reduce installation interruptions. However, this is difficult because of the heterogeneity of end devices.

Overall, more transmission options should be offered so that users can choose according to their situation and needs. This means that end devices do not only have to be compatible with as many methods as possible, but that developers and producers of applications accordingly have to offer many different data transmission methods. It must be kept in mind, that these findings are based on a dataset collected in Germany and therefore reflect the local market situation – especially in reference to typical data transmission costs. The findings can therefore not be generalized and applied to the situation in other countries.

IV. CONCLUSIONS This user survey has provided insight into many new findings, especially with respect to the installation process and the detailed evaluation of different distribution scenarios.

It was shown that the majority of users uses and prefers indirect transmission via the PC. More than half of the participants have already installed mobile applications. An average of only 15% reported problems when installing the applications, most of which were caused by incorrect program versions or connection problems. Users choose the installation method depending on the situation, the type of application and the situations it is used in. However, PC, mobile network and free WLAN are mainly chosen. Men have a greater affinity to technology than women, assess

scenarios differently than women and are willing to pay more. People with a higher technology-affinity have fewer problems with installing an application and they wish for innovative transmission methods.

Among the available transmission methods the transfer of data between end devices via Bluetooth received the highest ranking. PC-transmission, free WLAN, memory cards and NFC-transmission were evaluated similarly. These are followed by the mobile network, Bluetooth hotspots and WLAN for which one has to pay.

Even though this sample is not completely representative (due to the high proportion of technology-affine users and younger participants), the results are nevertheless significant. As this study aimed at identifying used and desired installation modes for mobile applications, a technology-affine sample was needed and finally realized.

The great number of new findings should be used to build a research model based on theory in which the hypotheses of the study can be extended. Despite that, there is further need for research in two areas. On the one hand with respect to the acceptability of transmission modes, because there is a high discrepancy between the assessment of experienced and described distribution scenarios [18]. An additional study is recommended in order to test the acceptability of transmission modes by actually testing them. Every transmission scenario would have to be tested by the participants, which is indeed very time-consuming. Nevertheless, the results of the present study make such research look promising. Furthermore, the users' wishes for the future should be examined in more detail and with a higher accuracy. This is necessary because some of the questions asked might not have been precise enough (recording of transmission methods used in the future instead of those wished for). In addition, the actual testing of different transmission methods will probably influence user wishes positively, as they are then able to assess them more precisely.

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