Social and Cultural Aspects

The digitization impacts many aspects of modern life by changing long-established processes and structures. In this research context, payment and purchase practices are relevant for the dissemination of mobile payments. The digitization opens up new ways to pay for goods and services. Payment services are now provided on a completely electronic and highly automated basis (Lim, 2008). In order to describe the payment habits of a specific country and the growing relevance of non-cash payments, it is reasonable to compare the inclination towards cash and non-cash payments, respectively. As aforementioned, estimations regarding cash transactions are highly inaccurate. Thus, the number of installed payment card readers at the point-of-sale (EFTPOS machines²⁷) is used as growth descriptor for the importance of non-cash payments. The historical data on the United States of America cover the years 1989-2008 and come from the Bank for International Settlements (2014). The German data come from the European Central Bank (2014) and cover 1989 through 2013.

Figure 10 illustrates the development of the absolute number of EFTPOS machines over time.

At this point it is important to highlight that, in this case, the graphs represent absolute numbers. Therefore, they cannot be directly compared.

27 EFTPOS stands for Electronic Funds Transfer at Point of Sale.

5 Empirical Study

Figure 10. EFTPOS machines in Germany and the USA – Forecast and historical data.

Figure 10 visualizes that both countries are close to having reached the respective ceiling level (MGER = 753.25, MUS = 5469.78). The thick grey line represents the forecast. It is possible to graphically interpret the highest level of this line as the ceiling level of the diffusion. With 9.5% as opposed to 5.2%, the MAD, i.e. the error in the historical data, for Germany is higher than for the US. Therefore, the data points also deviate stronger from the logistic fit in the left figure. The fitted data reveal that the number of EFTPOS machines reached 97% of the forecasted maximum in Germany and 94% in the US. Based on the data, no significant changes are to be expected in the long term since the growth process is close to being complete. A current ratio of 108 people per machine in Germany and 59 people per machine in the US can be calculated²⁸.This can be seen as indication of card payment being more important and thus more common in the United States of America than in Germany.

Furthermore, the digitization influences where people shop. The internet created a whole new outlet to buy goods and services. It is important to understand how and to what extent the population in the USA and Germany embrace new purchase practices. Consequentially, the number of online shoppers is a relevant indicator of a country’s acceptance of e-commerce.

For the USA, data were collected from eMarketer (2009, 2011, 2014) and from Eurostat (2014) for Germany. The data points cover the period from 2008-2013 and 2002-2013, respectively. Figure 11 shows the development of online shopping.

28 United States 316.13 million; Germany 80.62 million (The World Bank, 2014c).

Figure 11. Online shoppers in Germany in the USA – Forecast and historical data.

Despite being measured on different scales, the data can provide valuable information.

According to the logistic fits for the number of online shoppers, so far the diffusion process is 81% complete in Germany and 93% in the US. The logistic fits are both closely aligned with the historical data (MADGER = 3.8%, MADUS = 1%).

For Germany, the data was collected as percentage of the population. The original data source for the United States provides absolute numbers. If both cases are expressed on a relative scale, about 60% of the populations of both countries bought products online in 2013.

According to the forecasts, eventually a higher percentage of the German population is going to use the internet to buy products: by 2030, 64.4% of the US and 73.4% of the German population are expected to shop online.

An essential point must be underscored: While 60% of the population engage in online shopping, the internet is far from being their only outlet to buy goods and products. Internet retail has been growing strongly within the last years. Nevertheless, if the value of retail and online retail is compared, just around 6% and 7.4% of the current retail value are generated online in Germany and the United States, respectively (Euromonitor International, 2014c, 2014d)²⁹. The previous analyses show to what extent the two countries accept the new digital purchase habit. Since the majority of the population (i.e. approximately 60% in both countries) uses the internet to shop, it is reasonable to consider online shopping an essential

29 US total retail value (2013): $2,816.7 billion of which $207.6 billion were generated through internet retailing.

For Germany, €444,359.3 million (total) and €26,536.4 million (internet) were generated.

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part of modern society. Nevertheless, online shopping still accounts for a minor part of the total retail market.

Based on the historical data and the logistic fits, it can be argued that both countries have previously widely accepted new payment and purchase methods. However, since the historical data was partly collected in absolute form, the data cannot be compared. It is possible to solve this issue through standardizing the data, since the slope of a specific straight line can then be interpreted as the rate of efficiency by which a technology or innovation approximates its ceiling level: The steeper the straight line, the faster or rather more efficient is the diffusion. Figure 12 shows the associated graphs. The vertical axis shows Y’(t) and X’(t), i.e. historical data and the forecasted values in standardized form. Since the scale is logistic it is now possible to present the previous S-curves in straightened form. On the logistic ordinate, 0.01 can be understood as 1%, 1 as 50% and 100 as 100% of the ceiling level of the respective technology or innovation.

Figure 12. EFTPOS machines (a) and Online Shoppers (b) – Standardized form.

In both examples the light grey line representing the fitted indicator data for Germany is flatter. The same is expressed by the individual time constants ΔT³⁰: For EFTPOS machines ΔT is 18 years in Germany and 11 years in the USA. According to the standardized data points for online shopping, ΔT for Germany is 24 years and 12 years for the USA. The

30 ΔT was visually assessed an can be found in Appendix C.

average time constant may support the argument that it took an average of 14.5 years for electronic payments at the POS to travel from 10 to 90%. For online shopping practices, the average time constant is 18 years. This means that the process of dissemination of the two specific cases took several years longer in Germany.

Based on the analysis of the time constants and the logistic fits, it may thus be reasonable to conclude that new payment and purchase practices need more time to diffuse in Germany.

This may be interpreted as Germany being more hesitant when it comes to changing established habits and adopting new practices.