Impact of enhanced access to mobile phone charging on mobile phone usage: A pilot investigation in Kenya Prepared for publication by:

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1 Impact of enhanced access to mobile phone charging on mobile phone usage: A pilot investigation in Kenya Prepared for publication by: Micah Melnyk and Simon Collings

2 Context More than half a billion people in developing countries have a mobile phone but have limited or no access to grid-electricity, and are thus unable to charge their phone at their home or place of business. These mobile subscribers instead often charge their phone at a local charging station, often provided by an entrepreneur that charges phones for a variety of customers. However, locations where charging can occur are often not nearby or are limited in scale and thus mobile phone users are required to expend resources for transportation to a location for mobile phone charging, as well as for the cost to charge the mobile phone itself. Approximately one third of the total expenditure by off-grid mobile subscribers on mobile phone usage in for powering their phone, rather than airtime i. Figure 1: Azuri Mobi solar mobile phone charging technology being used in Kenya coastal region As part of working to accelerate access to energy in developing countries in a variety of different energy products and services, including solar, charcoal briquettes and more efficient cook stoves, GVEP International works to develop the market for mobile phone charging by initiating and supporting entrepreneurs that provide charging solutions. By expanding the number of mobile phone charging stations in rural areas across east Africa, GVEP seeks to expand access to communications for social and income-generating activities. 1

3 Specifically, GVEP International has worked to support the deployment of solar mobile phone charging stations across east Africa. This study will examine the impact of just one of those deployments, where GVEP International was piloting the usage of a new solar pay-as-you-go charging technology produced by Azuri Technologies at ten charging locations in the coastal region of Kenya, and the impact that deployment had on mobile phone usage. The new technology was deployed in mid to late June, Previous studies ii have indicated that enhanced charging leads to increased mobile phone usage, however the evidence basis is limited. Field studies by mobile operators, including in Haiti and Madagascar, have indicated that enhanced charging options led to a 10-14% increase in mobile phone revenue iii. This study seeks to add to this evidence base. Study objectives The objective of this study was two-fold: 1) Quantify the impact of enhanced energy access on mobile phone usage, in this particular region of Kenya for a small subset of charging stations. 2) Test out the process of collecting and analyzing the data to make such a quantification, for the purpose of enabling future similar studies by GVEP and GSMA Mobile Enabled Community Services. In this way, this research is meant to pilot future research. Methodology The impact of the enhanced charging is quantified by comparing the usage of customers of stations where the mobile charging was not significantly enhanced ( pre-existing charging) with the usage of customers of stations where access to mobile charging was enhanced ( new charging). For both sets of stations, the usage of customers before the installation of the new equipment is compared to the usage of these customers after installation, and the difference is calculated. The impact of the enhanced access to charging is then taken as the difference in the difference between before and after, for the two set sets of charging stations. 2

4 Step 1: Determine the charging stations to be used and whether they are preexisting or new All of the ten charging stations had new solar mobile phone charging equipment installed, but each charging station differed in what charging options pre-existed before the new technology installation. Four charging stations were used for this study: two charging stations where there were clearly pre-existing charging solutions before the installation of the new solar mobile phone charging equipment, and two charging stations where mobile phone charging had not been done before at that location or nearby. These stations were all located in the Kenya coast region. Figure 2: Map of Kenya coast region showing locations of mobile charging stations included in study 3

5 Step 2: Obtain consent from customers As GVEP had a pre-existing relationship with each of the entrepreneurs in the pilot of the new technology, GVEP was able to use the entrepreneurs themselves to obtain the consent of their customers. Each customer filled out a form that explained the purpose of the study, asked for consent for their mobile network operator to provide their usage data, and asked for supplementary data on their charging behaviour, including distance to the nearest alternate charging station. Step 3: Receive data from the mobile network operator Three Mobile Network Operators (MNOs) in Kenya (Safaricom, Airtel, Yu) agreed to provide data to GVEP for customers that granted consent for their data to be shared. Each of the three MNOs were able to provide three months of data up to the date of their data request. Safaricom was able to provide data for a 12 month period from May 1, 2012 to April 29, Initially, the data request was for a large number of data types, including revenue per user, but in order to enable the data request to be more manageable for the MNOs to process the request was reduced in scope and the following data was received: Number of income SMS messages per day Number of outgoing SMS messages per day Total call volume per day Data usage per day Data used for study Consent was obtained from 142 customers: 100 of whom were subscribers of Safaricom, 28 subscribers of Airtel and 14 subscribers of Yu. However, not all of these customers were of use to the study: only some of the 142 mobile subscribers were customers of the selected mobile phone charging stations used for the comparison, only customers who were subscribers of Safaricom enabled a before and after installation comparison, and some of the subscribers had zero usage. Once the data was limited to i) relevant stations, ii) Safaricom users and iii) active mobile users, the number of customers included in the study was limited to 46, the breakdown between pre-existing and new charging stations below. 4

6 Table 1: Data availability for active customers of relevant stations Type of charging station Number of customers Pre-existing 19 New 27 Analysis and results For each data type, the daily usage for each group of customers (of pre-existing stations and of new stations) was averaged for a period of time before and after the installation of the charging station. The timeframe used for this study was the two months of May and June, 2012 constituting the before installation period, and the two months of July and August, 2012 constituting the after installation period, as the new charging equipment was installed in mid to late June, The choice of timeframe was in part driven by the availability of data, the earliest of which was May 1, For each data type, the difference in the before installation and after installation was calculated for both pre-existing and new stations. The difference in the difference between before and after is then calculated as the impact of enhanced charging, with any change in the usage at pre-existing stations taken as the baseline. The results show that there is a difference in usage change before and after installation between pre-existing stations and new stations, with new stations seeing an increase where pre-existing stations did not or with new stations seeing a larger increase than pre-existing stations. This indicates that new stations, where the access to mobile phone charging has been enhanced, increase the usage of the mobile phone. While there was some variation in the scale of the difference in the change between before and after, the result that new stations increased mobile usage was consistent across SMS messages exchanged, number of voice calls exchanged, and total call length. The specific quantified results for each are outlined below. 5

7 Number of SMS messages +38% -1% Figure 3 : Average daily number of SMS messages (in + out) While the pre-existing stations saw effectively flat usage (-1%) before and after the new equipment was installed, the new stations saw a large increase in usage (+38%). This is a difference in the difference of +39%, which is a substantive increase. Number of calls +25% +19% Figure 4: Average number of calls (in + out) 6

8 While both pre-existing stations and new stations saw an increase in number of daily calls after the new equipment was installed, the increase at new stations (+25%) was greater than the increase at pre-existing stations (+19%). This is a difference in difference of +6%. The factors that caused the overall increase in the number of calls in both pre-existing and new stations cannot be undetermined by the data gathered by this study. Length of voice calls +16% +32% Figure 5: Average daily call time (seconds) As with the number of calls, total daily length of calls at both pre-existing stations and new stations saw an increase after the new equipment was installed. New stations saw twice the increase (+32%) of pre-existing stations (+16%). This is a difference in difference of +16%. Conclusions and limitations Objective 1: Quantify the impact On the objective of quantifying the impact of enhanced access to mobile charging on mobile phone usage, the study concludes that new stations saw an increase in usage compared to pre-existing stations. New station saw an increase of +39% for number of SMS messages, +6% for number of calls, and +16% for length of calls, compared to pre-existing stations. 7

9 On an average basis, mobile phone usage increased by approximately +20% at the new stations when compared to the change at pre-existing stations. This implies that enhanced access to mobile phone changing resulted in enhanced mobile phone usage of approximately +20%, which is similar scale to previous studies discussed earlier. However, these results should be taken as indicative of the scale of the impact and should be given credence with limited reliability. First, the sample size of customers is extremely small, so while the results indicate that the before and after installation are statistically significantly different, the scale of the difference does not have the same confidence level, i.e. we can be confident that there is a difference between our new and pre-existing stations, but cannot be confident in the amount of the difference. Second, the sample size of charging stations is small, and thus it may be that the study has picked up changes in the usage at the different station that would have occurred even in the absence of any change of access to mobile phone charging. While the charging stations used in the study are in the same region of Kenya, they are quite geographically disparate and have the economies of the region are different. This can be seen in the differences in the scale of usage even before installation: for example, the customers of pre-existing stations averaged approximate 0.3 SMS messages per day, while customers of new stations averaged approximately 0.8 SMS messages per day. Clearly, the locations do not have the same starting usage characteristics, let alone economic or social characteristics or trends. A much larger sample of charging stations that have a greater average similarity in starting characteristics would be beneficial for achieving greater confidence in the result. Objective 2: Test the process On the objective of testing out the process of completing this research, this study demonstrates that is it possible to collect and use actual mobile subscriber data from MNOs to quantify the impact of mobile phone charging. However, the process did encounter a number of challenges that resulted in some limitations to the study and delays to completion. 8

10 Challenge of obtaining completed consent forms: Consent forms were distributed through the mobile phone charging entrepreneurs, using GVEP field staff whose primary role is as a business mentor to the entrepreneurs. While instructions were given orally and written in both English and Swahili, neither the field staff nor the entrepreneurs are trained to accurately and completely gather such consent. As a result, a number of consent forms were missing information and considerable effort was applied to obtain the missing information (e.g. phone calls to those with missing information or calls to the entrepreneurs to complete the form). In addition, despite being offered an incentive to fill out the form, the number of customers that actually did so at some stations was less that initially expected. Future studies will require greater resources to be applied to training the field staff and entrepreneurs on how to collect the consent, and facilitate the promotion of the study at the charging station. Challenge of obtaining data: While the MNOs contributed to the study by sharing data there was in practice a challenge in obtaining historical data on the specific mobile subscribers that had given consent. It appears to be relatively easy for the MNOs to share the latest three months of data on a variety of types, but archive data that pre-dates three months prior to the data request date was more difficult for the MNOs to obtain. Given the complexity of the data systems involved and the efforts required by MNOs, there was thus considerable challenge in obtaining full, year long sets of data that were required for the pre- and post-installation comparisons required for this research. All three MNOs that participated in the study (Safaricom, Airtel, Yu) shared data from the previous three months, while only Safaricom was able to provide achival data for a one-year period. Even this data could only be provided after the scope of the data types was reduced. Being able to obtain detailed data on a timely basis once consent has been obtained from mobile subscribers is a primary challenge for future studies to overcome; a more formal and rigorous data sharing procedure will need to be designed and agreed with MNOs from the beginning of any future study, with the process for data extraction aligned to the MNOs operating practice and data management systems. 9

11 Challenge of establishing the baseline: By examining the difference between new and pre-existing stations to evaluate the impact of enhanced charging, the assumption is that no other factors have changed other than access to charging between the two groups of customers, and that the entirety of the difference in the change in usage can be attributed to change in access to charging. However, it could be that other factors that drive usage, such as income levels, are also changing differentially between the two groups. Ideally, these factors could be controlled for, for example by tracking income levels before and after installation and determining if there was a larger change in income levels among customers of pre-existing stations than new stations. However, the customers of stations are not known in advance, so save tracking all individuals in a particular area it is difficult to retroactively track income levels or other factors before that individual became a customer of a particular station. A larger sample of both customers and charging stations will help to counteract this challenge, and any potential bias could additionally be examined by capturing qualitative data from the customers themselves through the supplementary information gathered by the consent form. Recognition and appreciation GVEP International would like to recognize the mobile network operators Safaricom, Yu and Airtel for sharing data for the purposes of this study, with a special recognition to Safaricom for successfully providing a complete year of data. We are grateful to the GSMA for sharing contacts and providing advice and support. GVEP International would also like to thank the mobile phone charging entrepreneurs that assisted with the collection of the consent forms, and thank the customers for consenting to share their data for the purposes of this research. The results of this study were initially shared at the GSMA Mobile Enabled Community Services Africa Working Group meeting in Kampala, Uganda on May 29, i GSMA, Green Power For Mobile: Charging Choices - Off-grid charging solutions for mobile phones. Available at: ii GSMA, Harnessing The Full Potential of Mobile for Off-Grid Energy. Available at: iii GSMA, Green Power For Mobile: Charging Choices - Off-grid charging solutions for mobile phones. Available at: 10

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