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Effects of the aesthetic design of icons on app downloads: evidence from an android market

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Abstract

With the rapid development of the mobile app market, understanding the determinants of mobile app success has become vital to researchers and mobile app developers. Extant research on mobile applications primarily focused on the numerical and textual attributes of apps. Minimal attention has been provided to how the visual attributes of apps affect the download behavior of users. Among the features of app “appearance”, this study focuses on the effects of app icon on demand. With aesthetic product and interface design theories, we analyze icons from three aspects, namely, color, complexity, and symmetry, through image processing. Using a dataset collected from one of the largest Chinese Android websites, we find that icon appearance influences the download behavior of users. Particularly, apps with icons featuring higher colorfulness, proper complexity, and slight asymmetry lead to more downloads. These findings can help developers design their apps.

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Acknowledgments

This work is partially supported by the Research Grants Council of the Hong Kong Special Administrative Region, China (Grant CityU 11503115) and City University of Hong Kong (Grant SRG 7004287).

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Authors and Affiliations

  1. Department of Information Systems, College of Business, City University of Hong Kong, Kowloon Tong, Hong Kong

    Mengyue Wang & Xin Li

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  1. Mengyue Wang
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Correspondence to Mengyue Wang.

Appendix

Appendix

1.1 Colorfulness

An image is initially read by a computer as a matrix of pixels with three dimensions in the RGB color space. Supposing that (r, g, b) is the corresponding R, G, and B value matrix for photo I in RGB color space, this algorithm computes the opposite color space. The new coordinates are as follows: rg = r − g and yb = 0.5(r + g) – b.

The colorfulness of photo I can be calculated as follows:

$$Colorfulness(I)\,=\,\alpha_{rgyb}(I)\,+\,0.3\beta_{rgyb}(I)$$

where \(\alpha_{rgyb} (I) = \sqrt {\left[ {\sigma_{rg} (I)} \right]^{2} + \left[ {\sigma_{yb} (I)} \right]^{2} }\) and \(\beta_{rgyb} (I) = \sqrt {\left[ {\mu_{rg} (I)} \right]^{2} + \left[ {\mu_{yb} (I)} \right]^{2} }\).

1.2 Brightness

Lightness refers to the “L” value in the HSL color space and can be calculated as follows:

$$L(x) = \frac{{\max (r(x),g(x),b(x)) + \min (r(x),g(x),b(x))}}{2},$$

where r(x), g(x), b(x) represent the R, G, and B values for pixel x in RGB color space. In our research, we used “L” to represent the brightness of an image. We computed the average brightness for all pixels in the image as follows:

$$Btn_{1} = \frac{1}{\left| I \right|}\sum\limits_{x \in I} {L(x)}$$

1.3 Saturation

The “S” from HSL color space can be calculated as follows:

$$S(x) = \left\{ \begin{array}{ll} 0,& \quad \hbox{if\;max} (r(x),g(x),b(x)) = 0 \hfill \\ 1 - \frac{{\text{min}} (r(x),g(x),b(x))}{\hbox{max} (r(x),g(x),b(x))}, & \quad { \rm otherwise} \hfill \\ \end{array} \right.$$

1.4 Complexity

Figure 4 shows an example of complexity and symmetry. An app icon called Bad Piggies, i.e., in (a), was downloaded from Google Play. We changed the color image into a binary photo, an array of 1 s and 0 s, as shown in (b). An object refers to a set of four connected pixels in this binary photo; c shows a binary image containing only the perimeter pixel of an object. The number of object is 9, and the number of holes represented by the Euler number is −21. Perimeter refers to the sum of non-zero pixels shown in (c), and 7576 non-zero pixels exist in all. The process of computing homogeneity includes iteratively subdividing the gray scale icon into quarters, as shown in (d). A total of 764 blocks exist in all.

Fig. 4
figure 4

Example of complexity and symmetry

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1.5 Symmetry

The first step is to detect the SIFT descriptor, as shown in (e). The similarity matrix is then computed to find matches, as indicated in (f). Matches at different scales are rejected, and the rotation center for satisfactory matches is determined, as indicated in (g).

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Wang, M., Li, X. Effects of the aesthetic design of icons on app downloads: evidence from an android market. Electron Commer Res 17, 83–102 (2017). https://doi.org/10.1007/s10660-016-9245-4

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