The Mobile Internet Economy in Europe

The Mobile Internet Economy in Europe

          
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The Mobile Internet Economy in Europe

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    Appendix: Methodology

    The following describes our approach to sizing the mobile Internet economy.

    Sizing the Value of the Mobile Internet Economy

    To develop an appreciation for the size and importance of the mobile Internet ecosystem, we measured the 2013 revenues associated with each of the layers of the stack shown in Exhibit 9. We chose revenue as an intuitive metric for the level of activity associated with smart devices in order to help illustrate the growing role that the associated ecosystems are playing in the economy.

    Scope. We measured revenues pertaining to the use of smart devices, which we define as smartphones and tablets. The numbers cited reflect revenue flows associated with final consumption at each layer of the stack. The countries surveyed were Australia, Brazil, Canada, China, France, Germany, India, Italy, Japan, South Korea, Spain, the UK, and the U.S.

    We discriminated between those activities uniquely or predominantly performed on a smart device and those performed on other devices, such as feature phones. We therefore excluded voice and SMS activities on smart devices but included other data usage. We also recognized a proportion of fixed-line data use associated with Wi-Fi access via smart devices.

    Approach. As a general rule, we took a conservative approach to quantifying the total revenue of the stack in each market, erring toward the lower end of estimates. We identified five key revenue inflows to the system: m-commerce; consumer (personal and enterprise) spending on apps, digital content, and services; advertiser spending on mobile advertising on smart devices; consumer spending on smart devices and accessories; and consumer spending on smart-device-related access to mobile data. The device revenue recognized was as accrued by the manufacturer of the device. Because of significant differences among countries in the approach to subsidization by carriers, no attempt was made to fully account for device price subsidies. We also measured some revenue flows within the stack (between layers) to identify the value associated with layers that do not have a direct inflow: enablement platforms, mobile operating systems, and network/infrastructure. These layers are ultimately “funded” by the inflows from end users to other layers of the stack. Where possible, these internal flows were apportioned to the appropriate layer, and double counting was avoided by deducting from other layers as necessary.

    Production. Given that our focus was on revenues associated with consumption, we did not specifically measure production revenues (associated with devices, content, and apps, for example). The value of production is included in the final price paid by consumers; therefore this does not affect the measurement of total value. However, differences in the import/export mix might underrepresent regions in which production is an important activity. We have therefore noted this in the report where relevant.

    Investment. We did not include capital expenditures or spending on R&D in our figures. We consider these activities to be funded by revenues generated by consumption and so we did not include them in the total value estimate. We recognized operational expenditures related to the network/infrastructure layer (and discounted service provider revenues accordingly to cover this expenditure and to avoid double counting).


    Sizing Employment 

    The following were our considerations in estimating employment associated with the mobile Internet economy.

    Scope. The scope considerations for measuring employment were exactly the same as those for measuring value. We did not include employment related to capital expenditures owing to the cyclical nature of this activity.

    Approach. We measured the employment associated with consumption in each market. The approach was a mix of company-by-company analysis and cross-market estimates. Where practical, we measured the employment related to smart devices for the major players within a given layer, then extrapolated to the whole market based on the market share of the major players. For activities in which the level of fragmentation within the industry was high or in which it was difficult to isolate employment associated with smart-device activities, we benchmarked the revenue per employee of a subset of representative players and extrapolated for the whole market.


    Calculating Consumer Surplus

    Consumer surplus quantifies the benefit of smart devices to consumers over and above what they pay for devices, data, and content. We measure what is called the equivalent surplus—the amount of additional income that consumers would need to receive to generate the same value as their devices. Quantifying this value is an inherently difficult exercise. To elicit reliable valuations, we used a methodology that asks consumers to choose between keeping their smart device or giving it up in return for a certain amount of money. Each respondent is given several offers in sequence, and by analyzing which ones are accepted and which are rejected, we derive a monetary value for the smart device.

    Two Measures of Consumer Surplus. There are two alternative measures of consumer surplus. The first—compensating surplus—measures the maximum amount consumers are willing to pay for a good or service. Willingness to pay is an appropriate measure for companies trying to optimize pricing (as it represents the maximum amount they can charge for services). However, it can be problematic as a measure of welfare benefit to consumers, because it depends on the ability to pay—and may therefore understate the benefit of a service to lower-income consumers. For this reason, we focus instead on the second measure: the equivalent surplus. This can be interpreted as the minimum amount that consumers would be willing to accept to forgo using their devices.

    Scope. To estimate the value of the mobile Internet, we surveyed a representative sample of around 1,000 smartphone and tablet users in each of the 13 nations surveyed.

    Approach. Estimating the cost to consumers of using their devices is straightforward, but estimating the value they receive from their devices is a more difficult exercise. To extract a reliable valuation, we used a conjoint analysis methodology that asked each respondent to accept or reject a series of “deals.” Each deal involved giving up mobile Internet access for a period of time in return for money. The conjoint analysis questions are very easy for consumers to understand, and they avoid many of the biases associated with open-ended questioning. By varying both the length of time respondents were asked to forgo their mobile devices and the monetary compensation offered, we were able to use statistical methods to calculate the consumer value that each respondent placed on his or her smart device. This value—minus the cost of use—is the consumer surplus that the respondent enjoys from the smart device, which we then scaled up to generate an overall consumer surplus number for the entire country.