Use of mobile technology

The second section of the questionnaire, consisting of sixteen questions, solicited feedback relating to participants’ use of mobile technology and services. Based on the findings derived from the survey of Grahamstown residents, seven key questions were able to be answered:

Ql: How many respondents own or have access to a mobile phone?

Q2: What are the most prevalent brands of mobile phones and mobile platforms amongst re­

spondents?

Q3: What is the average monthly expenditure on mobile phones per earning bracket?

Q4: Which do respondents use most frequently: voice, SMS or data?

Q5: Which online data services do respondents make use of?

Q6: How often do respondents make use of the online data services?

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Q7: How many respondents have experience installing mobile applications?

Collectively, these questions aim to determine how suitable mobile technologies arc to facilitate participation between residents and the Makana Municipality. The answers to each question arc presented next.

Ql: How many respondents own or have access to a mobile phone? Of the 105 participants, 95.24% have access to a mobile phone. 90.48%. have their own handset, while 4.76%. have access to a shared mobile phone. Therefore, of the study participants, only 4.76%.

do not have access to a mobile phone.

Q2: What are the most prevalent brands of mobile phones and mobile platforms amongst respondents? Figure 4.1 provides an overview of the brands of mobile phones that participants own. The most popular mobile phone brands arc Nokia (37.63%.), Samsung (26.88%.) and BlackBerry (11.83%). ‘Other’ encompasses the brands which were less popular amongst respondents surveyed: Alcatel, Huawei, Sony Ericsson and ZTE.

The study sought information relating to the make and model of each respondent’s handset. Each newly identified handset was researched online to determine its operating system and features available. The GSMArcna1 website was used for most makes/models of handsets. In the event that the phone specifications were not available on this site, a simple Google search was used.

In some eases, even though the exact make and model were captured, the operating system was simply referred to as “proprietary”. In these eases, the results were grouped together, with a distinction instead made regarding the operating system’s support for .Java ME.

1 GSMArena.com http://www.gsmcirena.com/

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Proprietary OS (with Java ME)

Android OS

Unknown

BlackBerry OS

o Proprietary OS (without Java ME)

iOS

Figure 4.2: Identified mobile phone platforms (n = 95)

Figure 4.2 shows that the most prevalent mobile platform amongst participants is some form of proprietary OS supporting .Java ME (28.42%); followed by Android OS (23.16%.); and Black­

Berry OS (11.58%). Devices grouped into the “Unknown” category are those where insufficient information was provided by respondents to accurately determine the platform of the device.

The Nokia handsets (37.67%. of mobile devices surveyed, see Figure 4.1) make up part of the following segments: Proprietary OS with .Java ME support; Proprietary OS without .Java ME support; or Windows Phone. This split was included to obtain a better understanding of the capabilities of the wide range of Nokia devices that were prevalent in the study.

When collecting information from participants, assistance was offered to help determine the make and model of the mobile phone. In the case of “Unknown” being recorded, either the handset was not with the participant, and the participant was unsure of the model (so only the make could be recorded), or the handset was with the participant but the model number could not be established.

Q3: What is the average monthly expenditure on mobile phones per earning bracket?

In the survey, respondents were asked to indicate into which earning bracket they fell on a monthly basis (based on brackets given in the 2011 National Census). In addition, respondents were asked to indicate how much money they spent weekly on prepaid airtime (by specifying into which bracket they fell), or on their monthly contract. The weekly airtime expenditure was then extrapolated over the period of a month (approximately four weeks) and correlated to the earning bracket of each respondent.

This was done by grouping together the respondents who chose the same earning brackets, and then calculating the mode of expenditure for prepaid respondents, and the average monetary costs of contract respondents. In some cases where there was no mode for the prepaid brackets

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per earning bracket, the lowest common denominator (in terms of expenditure) was chosen. The results of this arc presented in Table 4.1. It should be noted that blank cells in the “monthly expenditure” column for contract participants reflect that there was no one who fell into this category (rather than an expenditure of RO).

Prepaid (n = 78) n = 15)

Level of income Monthly expenditure Level of income Monthly expenditure

I don’t know More than R16 I don’t know

-No income Less than R5 No income R277.25

R1-R400 R5-R15 R1-R400

Table 4.1: Monthly income versus expenditure on airtime

It is interesting to note that participants who rated their level of income as “no income” were still able to purchase airtime. On closer examination of the results, exactly two thirds of those who said they had no income were also students, so it may be assumed that someone else was paying for their monthly airtime. The remaining third described themselves as temporarily unemployed.

Q4: Which do respondents use most frequently: voice, SMS or data? Participants were asked to rank the frequency which they use the data, voice and SMS services available on their mobile phone. Responses were ranked as most used (most), moderately used (mod) and least used (least). Table 4.2 shows that overall, data was ranked as the most used service by each of the race groups and across female and male respondents. However, for female and Black African/Coloured respondents, this was tied with voice calls.

All Female Male W I/A BA/C

Data Most Most Most Most Most Most

SMS Mod Mod Least Least - Mod

Voice Mod Most Mod Mod Mod Most

Table 4.2: Frequency of use: Data versus SMS versus Voice

Q5: Which online data services do respondents make use of? Participants were asked two questions relating to the services they use on their mobile phones. Firstly, they were asked to

4.5. RESULTS ⁶⁰

specify the messaging services that they currently use. In addition, they were asked to indicate any other online data services they use on their mobile phones.

n = 93) Female Male W I/A BA/C

SMS 74% 69% 80%. 92%. 75% 72%.

W hatsApp 66% 56% 76%. 92%. 75% 61%.

BBM 9% 2% 16%. 8% 50%. 7%

Mxit 16% 13% 20%. 0%. 0%. 19%.

E-mail 30%. 19% 41%. 77% 75% 20%.

Facebook 61% 46% 76%. 92%. 50%. 57%

Twitter 21% 13% 29%. 38%. 25%. 18%

News 26% 19% 33%. 69%. 25%. 18%

Wikipedia 17% 7% 27%. 46%. 0%. 14%.

Table 4.3: Use of messaging services and online data services

Table 4.3 shows that SMS is the most popular messaging service, while Facebook is the most popular online data service across all gender and race groups. Interestingly, female respondents arc less likely to use messaging and data services on their mobile phones when compared with male respondents. This supports the earlier finding where females rated voice as most frequently used, alongside data.

Q6: How often do respondents make use of the online data services? Of the 100 respondents identified as either owning or having access to a mobile phone, 92 answered the question of how often they made use of the online data services. Figure 4.3 shows that most respondents (46.74%) access data services at least once per day, while slightly more than a quarter (28.26%) never make use of any online data services. Slightly less than a quarter (22.83%) access online data services a few times per week, while 2.17%. of respondents access them a few times a month.

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Figure 4.3: Frequency of online data services use (n = 92)

Q7: How many respondents have experience installing mobile applications? Of the 95 participants who own a mobile phone, 66 of these handsets were positively identified as being able to install applications. Out of these, 40 participants answered “ves” to having installed applications on their devices, translating into an installation rate of 60.6%. A distinction was also made between installing applications via the handset’s store (i.e. Apple App Store, Google Play, Windows Store) or manually (i.e. downloading a .Java ME .jar installation file from a website).

Of the 66 participants with handsets capable of installing applications, 40.90%. have installed applications using both their device’s store, as well as manually. These results highlight the importance of providing adequate support and training to residents regarding the installation of the client applications. Additionally, selecting appropriate channels through which to distribute the client applications is vital, whether via the MobiSAM website, platform-specific application stores or a combination of these.