Erasmus Universiteit Rotterdam Willingness to pay for mobile apps
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- 3.2 Data descriptive
2.11 Conceptual modelFigure 2 summarizes the purpose of this thesis: Age Consumer’s Payment mechanism: Creditcard or Click-and-Buy. Figure 2. Conceptual Model Customer Rating: (Customer driven Feature) Top Developer Hallmark: (Platform driven feature) Willingness to pay for paid apps Best Seller Rank: (Customer driven feature) Editor’s Choice (Platform driven feature) Costomer’s involvement: high or low involvement Gender Income Price Chapter 3 Methodology3.1 Empirical ApplicationBecause WTP should be measured as realistically as possible and the fact that Apps are bought in a retail environment where customers need to choose between options, a Choice Based Conjoint (CBC) analysis is used to assess hypothetical WTP for Apps. With CBC analysis we can asses WTP indirectly by including the price as one of the attributes of the Apps(e.g. Srinivasan, 1982; miller et al., 2011). To determine the appropriate attributes and attribute levels for our conjoint study we did an analysis of both Apple’s App Store and Google’s Play Store to identify the most clearly displayed attributes that affect the customers choice and thus WTP. The attributes and their levels are shown in table 3. A web based questionnaire is used for the study. In Appendix A you can find the whole survey. The survey is divided in three parts. The first part describes the relevant attributes. The second part consists of the WTP part, where the respondents are faced with choice sets from which they have to choose their preferred alternative. In the third part of the questionnaire we conducted a brief survey to find the values for the control variables: involvement and payment method. Socio economics and socio demographics were also measured in the last part of the survey. The data was gathered via social networks Facebook and LinkedIn, direct mailing and direct and indirect personal environment. This non-probability sampling method could result in a non-representative sample and therefore the outcomes should be handled with caution. Besides the criteria that respondents should have a smartphone, the sample is randomly taken. Smartphone users are all familiar with Apps and the Application Stores since all App (free or paid) are chosen and downloaded from the Application Stores. It is very likely that respondents understand the different attributes and are able to choose between options. The action ability of the results are therefore likely to be high for Apps. 3.2 Data descriptiveFor this research the data was collected via a web based survey that was spread via Facebook, LinkedIn, direct mailings and direct and indirect personal environment. On social media, personal messages were used to send the link to the web based survey. The respondents were told that they could contribute to a relevant scientific research project of a graduate student. Most of the respondents that were approached for the study have the Dutch nationality and some are international students from Erasmus University. Data was collected from June 8th 2013 till June 15th 2013. In this period 199 respondents have filled in the survey of which 156 respondents were used in the analysis. 43 responses were not completed correctly. All general information of the respondents is reported in the tables of Appendix C : Respondent descriptives. The average age of the respondents was 29.33 years, from which 57% is male and 43% is female. The majority of the respondents is higher educated (87% ), this could be explain by several things. At first the researcher spread the survey in his personal environment, which is represented by a high amount of higher educated people. Secondly, the survey could have been hard to fill in for lower educated Dutch respondents due to the fact it was conducted in English. Another explanation can be found in the fact that more highly educated students and people with higher incomes have higher levels in adoption of Smartphone’s. This corresponds with research that studied the adoption of smartphones in several demographic groups (pewinternet.org, 03-01-2012)5. Moreover, 45% of the population are students against 55% who are working. From all respondents 37.8% have never bought an App against 62.2% who have. From the people who have paid for an App 51% states that they have paid for Apps occasionally and 10.9% states that they have paid for Apps frequently. On average the respondents indicate that they are most likely to pay for Utility/Productivity Apps (mean score: 3.27) followed by Sport/Health Apps and Informational Apps (mean scores: 3.02 and 3.01 respectively). The respondents indicate that they are least likely to pay for Game Apps (mean score: 2.52). For purchasing Apps 37.8% uses their Credit Card to pay in the Application Store and 62.2% use Click-and-Buy. Concerning involvement it is interesting to find that 47% of the respondents state that they are interested in the Mobile Market where only 28% indicate that they are not interested in the mobile market, the other 25% find themselfs neutral. From all respondents 35% have downloaded an App that describes, offers and/or suggest Apps to them. 65% did not have such an App. Finally 31% of the respondents state that they visit their Application Store quite often to very often, 23% state they rarely or never visit their Application store and 46% state they visit the Application store sometimes.
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