The policy drivers for such a comprehensive application will include the legal basis for the operation of sports equipment rental, aggregation and cooperation with sports centers, and a focus on the security of sensitive data entered by users. Economically, for small clubs, gyms, and shops, this generalization will be helpful; however, large networks like Haosa Group or Wellness Group, which are market leaders, for example, gyms and have their applications, may not provide their booking functionality to a third-party application and developer (IBISWorld, 2023). Convenient aggregators for many areas of human life are used as mobile applications: all maps of the world, hotels, taxi services, and much more can be collected under one interface (Huang et al., 2019). This trend can be warmly welcomed from the point of view of the social externalities of such an analysis.
Finally, technological determinants primarily include app availability on all possible devices and operating systems, and second, ergonomic functionality that will offer advantages over instant messengers, diaries, and branded gym and store apps. This issue is critical since this problem is typical for this kind of unifying aggregators: if their content in terms of information or available options does not go beyond similar applications that are already installed on any user’s smartphone, there is no need for them, and the audience will grow weakly (Weichbroth, 2020). Accordingly, not only the quantitative characteristics of the speed of the application will be taken into account by consumers, but also the qualitative content, which may include a workout planner, tips about a healthy lifestyle, search for like-minded people by geolocation with their consent, and much more in mobile applications of this kind (Angosto et al., 2020). Therefore, competitive success largely depends on this issue.
Before launching and developing a mobile application about sports, a developer should ensure that there is a demand for such an application among the target audience. Preliminarily, people of both sexes aged 20 to 45 who visit the gym in the considered launch region were selected as the target audience. The researcher’s activity was a survey on some items about the role of a smartphone in a healthy lifestyle, its functions, and the potential use of the application, which will be described in the questionnaire. Each question can be answered on a five-point Likert scale to make it easier to transform qualitative data into quantitative ones (Jebb, Ng, and Tay, 2021). The research strategy is quantitative, as the resulting data will be translated into coefficients, making it easier to perform statistical processing on quantitative data (Aithal and Aithal, 2020). The demographic information collected in this work will be considered an independent variable in each study iteration (Sileyew, 2019). However, the critical question of the study is the following: Is there a need for the described functionality of the application among people aged 20 to 45 who visit the gym?
The study’s design is comparative or correlational, as independent demographic and other variables will determine the level of need for several features of the intended application. For this, the results of questionnaires of the maximum possible number of people interviewed in gyms are used only with their consent and on the rights of anonymity. Accordingly, the collected data are the answers to the questionnaire questions, then statistical analysis of the data is carried out on them. When several samples differ in age, gender, frequency of attendance, for example, and other selected independent variables, Pearson correlation analysis is best suited due to ease of use and clarity of the output data (Mishra et al., 2019). As a result, with the help of such scientific and, at the same time, marketing research, the company will be able to understand the amount of demand for the functionality of this application and more accurately determine the target audience.
Reference List
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Angosto, S., et al. (2020) ‘The intention to use fitness and physical activity apps: a systematic review’, Sustainability, 12(16), p. 6641. Web.
Huang, Y. C., et al. (2019) ‘Examining an extended technology acceptance model with experience construct on hotel consumers’ adoption of mobile applications’, Journal of Hospitality Marketing & Management, 28(8), pp. 957-980. Web.
IBISWorld (2023) ‘Gym, Health & Fitness Clubs Industry in China – Market Research Report’. Web.
Jebb, A. T., Ng, V., and Tay, L. (2021) ‘A review of key Likert scale development advances: 1995–2019’, Frontiers in Psychology, 12, p. 637547. Web.
Mishra, P., et al. (2019) ‘Selection of appropriate statistical methods for data analysis’, Annals of Cardiac Anaesthesia, 22(3), p. 297. Web.
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Weichbroth, P. (2020) ‘Usability of mobile applications: a systematic literature study’, IEEE Access, 8, pp. 55563-55577. Web.