RSS feed

Evaluating the acceptance and usability of Kiswahili localised mobile phone app in Kenya: a case of M-Pesa app

Alfred Sanday Wandera, Kenyatta University, Kenya


Despite the efforts made in localising the M-Pesa app (a mobile money application) from English to Kiswahili, little had been done to evaluate the acceptance and usability of its translated Kiswahili menu in Kenya. During the pilot implementation of M-Pesa (started on October 11, 2005 and ended on May 2007), an extensive research conducted on its users depicted that most of them preferred using the English language menu of the application vis-à-vis the Kiswahili menu (International Finance Corporation 2011:9). Subsequent to that finding, Safaricom Company (the company that operates M-Pesa) is said to have altered the Kiswahili menu with the aim of making it less complex and hoping that it could in turn attract more acceptability and usability among its users.

This paper sought to analyze the findings of a research conducted by Wandera (2014) on the acceptance and usability of the Kiswahili localised mobile phone application in Kenya. Accordingly, this paper aimed at investigating the public’s awareness, attitude and perception of the M-Pesa (mobile money application) Kiswahili menu.

The study found out that generally, the level of acceptance and usability of Kiswahili language menu of M-Pesa app was low. This could be attributed to lack of awareness about the existence of the Kiswahili language menu on the M-Pesa app, use of hard and unfamiliar terms in the Kiswahili menu, and the negative attitude that the public have towards the Kiswahili language. In conclusion, the researcher suggests that the Kiswahili menu would be accepted and used if the message is clear, easily understood, uses common or familiar terms, if single terms are consistently translated, and is functionally suitable in the culture of the target text. Consequently, enough awareness should be created to dispel the public negativity towards Kiswahili language.


Localisation, mobile phone, mobile phone application, software application, acceptance, usability, Kiswahili, Kenya, mobile money.

1. Introduction

In the past couple of years mobile technology has gained in popularity and usage globally, particularly in developing countries (Eulich 2012). The flourishing of mobile technology has equally resulted in an outburst of messaging services that has not only been used as a conduit for personal communication, but also as a platform for communicating valuable information such as healthcare reminders and agricultural reports (Marketsandmarkets 2015). Mobile money is the latest phenomenon produced by mobile technology. Mobile money services are financial services that are offered on the mobile phone platform (Firpo 2009). They can take the forms of mobile payments, mobile money transfer, and mobile banking.

In developing countries, mobile money services have helped to provide money transfer services to millions of individuals who had previously been under-served by banks (Graham 2010). These services allow them to send money, receive money, and pay bills without exclusively relying on cash. It has been claimed that Kenya is a global leader in mobile money services (Michaels 2011). The mobile money service platform in Kenya allows its clientele to transfer money, purchase airtime, pay wages and salaries, pay bills, and buy services and goods from both physical merchants and online traders. The mobile operators in Kenya that offer mobile money services are Safaricom Limited, Airtel Networks Limited, Telkom Kenya, Equitel, and Essar (YU).

The word M-Pesa is a combination of ‘M’ that stands for mobile phone and ‘Pesa’, which is a Swahili term for money (Twomey 2013). M-Pesa is a mobile money application1 and service that is operated by Safaricom Limited Kenya (Neva 2012; James 2014). Safaricom (2014) defines M-Pesa as an innovative platform that was initiated in 2007 and allows individuals with Safaricom lines to use their handsets to send and receive money and make payments. Additionally, even though its customers do not earn interest on their balances, M-Pesa allows its customers to build savings in their accounts (Cull 2010). Safaricom has lately added various value-added services to its M-Pesa services (Kaffenberger 2014). The aim of these added services is to move its clientele from the basic money transfer services to more advanced services. Key and popular among these offerings is the M-Shwari service, a loan and savings product that was launched in 2012 by Safaricom (Vodafone 2012).

The M-Pesa menu includes services such as sending money, withdrawing cash, buying airtime, M-Shwari (as described above), Lipa na M-Pesa (to pay bills), M-Kesho (online banking, credit services and insurance coverage purchase). The menu also has a My Account section, which shows M-Pesa balance and support services, and allows changing of M-Pesa PIN number, secret security word and language preference (between English or Swahili).

Since the launch of M-Pesa in 2007 and up until 2013, it was claimed to have attracted over 19.5 million customers, which accounts for about 83% of the Kenyan adult population (Botsman 2014). This was attributed to M-Pesa’s low-cost and secure means of transferring money (Cull 2010). The other contributing factors to M-Pesa’s growth included: high cost of sending money via other means, Safaricom’s dominant market position, effective marketing strategies, and the Central Bank of Kenya’s decision to allow the service to run on an experimental basis without formal authorisation (Mas and Morawczynski 2009). Initially, the service aimed at enabling urban Kenyans to send money to their friends, relatives and loved ones in the upcountry. Subsequently, as the service opened up its doors to its surging clientele in the villages and enhanced accessibility to its services by certifying many Safaricom agents to transact the transfers for them, the need for localising the M-Pesa register from English to Swahili arose. In fact, some of the M-Pesa app users were illiterate and semi-illiterate and thus were more likely to be comfortable with an app menu in the Kiswahili language.

Nevertheless, a study carried out during the pilot implementation of M-Pesa indicated that the majority of its users preferred the English language menu as compared to the Kiswahili language menu (International Finance Cooperation 2011:9). The reason cited was that the Kiswahili language menu contained complex terminologies, making it hard to understand and to use. From that finding, the Safaricom Company took the initiative of making the Kiswahili language menu less complex to ease its understanding and usage. Despite the efforts made by Safaricom in making the Kiswahili language menu of M-Pesa less complex after its pilot implementation in 2006, little had been done to evaluate whether there had been any change of trend in the users’ acceptance and usability of the Kiswahili language menu in Kenya.

Concerted efforts have been made over the years to localise technology-based products into bilingual and multilingual languages. Various scholars and researchers have given varied views on the localisation of mobile phone apps. Charalampidou quotes the Localisation Industry Standards Association (LISA), operational from 1990 to 2011, which defined localisation as the process that “involves taking a product and making it linguistically and culturally appropriate to the target locale/country/region and language where it will be used and sold” (2006: 2). Sasikumar and Hegde (2004) add that localisation efforts involves linguistic adaptation of all texts used in an app (software). This language localisation as has been referred to by the authors plays an important role in the success of an app (Ankier 2013). Nevertheless, when observing the Kiswahili language menu of the M-Pesa, one can see that its component texts are not fully adapted. The level of its localisation is what Pym (2001) refers to as enabled localisation. This is where the interfaces of the app remain in the default language (English), while other texts are translated in the local language. This paper seeks to find whether or not the enabled level of localisation has influenced user acceptability and hence usability of the Kiswahili translated M-Pesa menu.

Duan (2012) argues that in order for top apps to reach their full potential commercially, they should strive to be fully localised just like what has been achieved in Japan and Korea for their iPhone Top 20 apps. Studies have indeed depicted that localised apps perform better (Kim 2012). Accordingly, this paper seeks to understand why Kenyan Mobile money apps (especially M-Pesa, since it is a global leader in the market) have yet to attain full Kiswahili language localisation, especially now that the Kiswahili language is a national and official language in Kenya. The language acts as a unifying medium of communication because of its easy comprehension, cutting across the majority of the Kenyan populace (Wachira 2006).

2. Localisation

Localisation is one of the concepts that has made its way into translation studies over the recent years (Charalampidou 2006; Pym 2011). Localisation is defined as the process of adapting a software system (including websites) to a particular locale, in order to present an image of a locally developed system. It aims at locale (Sasikumar and Hedge 2004), which can be defined as a group of persons with a common language, writing, and other system features that may require a separate version of a product (Charalampidou 2006). This may be a region, location, country or area. Several aspects to consider emerge from the definition of localisation as generally understood and posited by LISA (Pym 2011).

First, the definition recognises the fact that one language may not be the only one used in an area, location or country. On one hand, for instance in Kenya, there are two official languages, English and Kiswahili, with almost 42 other ethnic languages. Also, Belgium, for example, has 3 official languages (German, French and Flemish). On the other hand, other countries and regions may have only one recognised language.

Second, the definition recognises that appropriateness in localisation extends beyond the consideration of language only (Charalampidou 2006). Despite the fact that people from different regions speak a similar language, there may still be linguistic and non-linguistic differences. For instance, the Kenyan Kiswahili dialect differs from the Kiswahili used in Tanzania, Uganda or Rwanda. Further, cultural symbols such as flags may differ.

Moreover, for any translation and localisation to be successful, not only the source material and the target market have to be understood very well, but the language and the culture have to be understood deeply as well. Sasikumar and Hedge (2004: 2-3) categorise localisation in mobile phones as display localisation, language localisation, cultural localisation and device localisation. Display localisation refers to the capability of rendering a source text into a target language (local language, or locale). It involves the building of modules, which are able to display local text in the script rather than in the pervasive Roman script. Language localisation involves adapting the user interface to the target language. This encompasses translating all of the system text in the locale, and then modifying the software so it uses the localised text instead of its original language material. Cultural localisation involves making the software as culturally convenient and acceptable as possible to the target community. The concern of cultural localisation is in the use of metaphors, icons, and message conventions that resonate with the locals. Great care should be taken during cultural localisation in order to avoid unnecessary confusion. Sasikumar and Hedge (2004: 8) claim that due to the lack of a trash can notion in rural areas, its icon could easily be confused for a file folder or mailbox. Finally, device localisation entails the development and usage of input and output devices that are suited for the local cultures and languages. For instance, the use of QWERTY keyboard has been found unacceptable for entering alphabet and phonetic rich languages such as those in India (Sasikumar and Hedge 2004:3). Therefore, designing keyboard equivalents to enter texts for these kinds of languages have to be considered during the localisation of a mobile phone product. Following the localisation categorisation as proposed by Sasikumar and Hedge (2004), this study focused on language localisation.

2.1. Localisation in Africa

In the recent past, African economies have been making great strides in technological advancements. In fact, according to (Spoone 2011), Africa today is keeping up with the global competition in terms of inventions and marketplace for Information and Communication Technologies (ICTs). One of the standout innovations in Africa has been in the area of apps. It has been argued that most African apps have been developed to meet the local market needs and situations of the African continent (Spoone 2011). One of the apps in Africa that has gained the world’s attention has been the M-Pesa app. Indeed, M-Pesa is heralded as being the most utilised app in the world, given that it is based on the mobile text messaging application and thus is more accessible to many more people. Complementing this argument is the high growth of mobile penetration in Africa.

Despite the great strides made in ICTs in Africa and other developing countries, its benefits might not be reaching the lower rungs of the society. The reason cited for this is the inability to use the technologies because of the mismatch in language and culture (Kamau 2007; Sasikumar and Hegde 2004). Localisation efforts have been cited as one of the ways to alleviate the mismatches and one of the reasons why technological products and services have not yet achieved their full potential in developing nations.

Kamau (2007) argues that since the spread and the usage of technology is language-based and most African countries acquire these technologies in foreign languages, a large percentage of persons end up not understanding them and thus not making use of them. It is in this regard that there is a need to incorporate the African languages in the spread and usage of ICTs. Accordingly, this helps remove language barriers for those who cannot understand the foreign language and helps ensure that the benefits and services of a technology reach every layer of a community. It is against this backdrop that some technological companies operating in Africa have made sure that they localise their products in African locales. One of the African languages that has greatly benefited from those efforts has been the Kiswahili language.

2.2. Localisation into Kiswahili language

In a bid to bring ICT accessibility to East and Central Africa, two renowned computer software developers, Linux and Microsoft, started to localise their software for the Kiswahili language (Kamau 2007). This made Kiswahili the first African language to be utilised in computers. According to Kamau (2007:134), the reasons for this localisation were twofold. First, it was to help bridge the digital divide gap existing between the developed world and Africa, and second, it was to help these two companies expand their African markets. Kamau (2007: 135) enumerates the reasons that made the Kiswahili language the ideal language for spreading and using ICTs in East and Central Africa. Those reasons include:

  1. The Kiswahili language had carved its niche in higher learning institutions globally. The researcher argues that Kiswahili has been the lingua franca in East Africa since the 19th century and that its popularity has tremendously grown beyond its borders to include Europe, the United States, Asia and Far East countries, where it is also taught in universities. This makes it an indigenous language that can easily and efficiently be used for localisation.
  2. It has been claimed that learning the Kiswahili language is easy because it is phonetic and has fewer spelling and pronunciation difficulties (Mwaro-Mwaro 2002; Iraki and Maroa 2008; Katembo 2005). According to Mwaro-Mwaro (2002), Kiswahili has the ability to incorporate and assimilate words from other languages, thus making it easier to understand and learn by individuals from other language groups in Africa. In fact, Amatubi (2002) posits that most European visitors to Kenya get to learn and understand Kiswahili in their first year of stay, just as it was the case with the colonial rulers and missionaries.
  3. Mazrui and Mazrui (1999) argue that Kiswahili is a language which handles technological terminologies much easier through the method of coinage. Already, some universities and companies have made efforts to develop Kiswahili glossaries for the ICT sector (Ryanga 2002).
  4. Further, the Kiswahili language is the only African language that is used by international media houses for broadcasting and publishing (Kamau 2007). The media houses that utilise the Kiswahili language in their broadcasts include the British Broadcasting Corporation (BBC) and Radio Japan.
  5. Finally, Msanjila (2002) states that the Kiswahili language has an estimated 60 million speakers in East and Central Africa and in some other parts of the Sahara desert. Additionally, according to Katembo (2005), the Kiswahili language has an estimated worldwide user base of a 100 million.

In Kenya, the Kiswahili language is “the language of communication almost everywhere between people from different linguistic communities — at home and in public institutions” (Wachira 2006). The author argues that Kiswahili is a lingua franca that is generally spoken and understood by the majority of Kenyans, irrespective of their regional and educational backgrounds. Furthermore, section seven of the Kenyan constitution declares Kiswahili as both a national and an official language (Wahome 2010).The Kiswahili language acts as a unifying medium of communication because of its easy comprehension, cutting across the majority of the Kenyan populace, as argued by Wachira (2006).

The fact that the constitution of Kenya has made it mandatory for most, if not all, government documents to be translated into the Kiswahili language is definitely worth noting. Companies have vigorously increased localisation of their products and services from English to Kiswahili in order to enhance their acceptance and usability among the majority of Kenyans. This product acceptance enhancement arises from the argument that Kiswahili has gained popularity from various groups due to its usage of lexical terms from the local languages (Habwe 2009).

3. Acceptance and usability of Kiswahili-localised products

Various individuals have defined usability in various terms. Nevertheless, there has been no unanimity on one definition of usability within the community of Human Computer Interaction (Osterbauer et al. 2000). According to Preece et al. (1994) (as cited by Deb 2004: 343 and Henke 2001: 195), usability is defined as ”a measure of the ease with which a system can be learned or used, its safety, effectiveness and efficiency, and attitude of its users towards it”. Further, according to Kurosu (2011: 248), usability of a computer system can be defined through the following attributes: efficiency, learnability, memorability, errors, and satisfaction. Additionally, ISO 9241-11 describes usability as “the extent to which a product can be used by specified users to achieve specified goals with effectiveness, efficiency and satisfaction in a specified context of use” (Kurosu 2011: 195).

From the aforementioned definitions, it can be deduced that the concern in the usability of an application is to generally make it acceptable and easy to use (Daniel et al. 2011). One of the ways to enhance acceptance and usability of an application is through localisation of an application into the users’ language (Sandrini 2005). Tractinsky (2000) argues that information that has been localised into the users’ language is more accessible and easily processed than that in a foreign language.

It is from the aforementioned arguments that localisation of technological products and services into the Kiswahili language is seen as a great contribution towards digitising Africa (Kamau 2007). According to Kamau (2007: 138), Linux and Microsoft projects that were localised using the Kiswahili language proved to be popular with the African audience. For instance, Kamau (2007: 138) claims that despite Microsoft Kiswahili Office 2003 only having been launched in December 2005, already 700 downloads were experienced by January of 2006.

3.1. Challenges of Kiswahili localisations

Despite the progress made in Kiswahili localisation, several scholars and professionals have pointed at a number of challenges in implementation, acceptance and usability of technological products by the African publics.

First, research has established that some of the terms used during the localisation process may go way beyond the common understanding of mainstream Kiswahili users (Kamau 2007; Michaels 2011). These terms prove to be complex and thus can only be understood and utilised by scholars and linguists. It is no surprise that market research conducted on the M-Pesa application in 2008 had indicated that most of its trial users had preferred the English version of the menu because it was more easily understandable (International Finance Corporation 2011:9). This made Safaricom Limited alter the M-Pesa Kiswahili language menu in order to make it less complicated, thus encouraging its acceptance and increasing its usability (ibid.). Complex terminologies are capable of fending off prospective users of an application.

Secondly, it has been argued that the usage of different translations for similar terms by related products during localisation tends to cause confusion among the users, leading to low acceptance and usability of a technological product (Kamau 2007; Sasikumar and Hegde 2004). The English term ‘airtime’ is a great example, being translated as Mjazo wa simu (A Phone filler) on the M-Pesa platform app but remaining as ‘Airtime’ on the platform app of other similar service providers.

Thirdly, it has been argued that the usage of mixed language (such as English and Kiswahili) in the localised version of an application tends to reduce its acceptance and usability (Weir and Lepouras 2001). In these applications, it appears that some texts are kept in English while others are translated into the local languages (such as Kiswahili). This leads to a peculiar mix of languages in an application meant to be localised, with no specific rationale. Eventually, this inconsistency in language use places an extra burden of comprehension on the user, who may then resort to using the original, unilingual, English, version of the application (Weir and Lepouras 2001).

Fourthly, according to Kamau (2007:138), most Kiswahili language speakers have a negative attitude towards their own language and tend to prefer to use the English language, especially for technological and official matters. Research has found this to be quite evident in Kenya and Uganda (Kamau 2007:138). In Tanzania, the language is said to be very popular and thus effective when it comes to spreading technological advancements in the lower rungs of its community.

Accordingly, terminology problems have also been identified as another challenge towards achieving acceptance and usability of a localised application platform. The argument posited by Weir and Lepouras (2001) is that whenever the English language software is translated to a local language, decisions are taken on the mapping of English terms to local terms. Some measures of arbitrariness are inevitably attached to this procedure. In consequence, some aspects of the localised software may appear stranger to the local public than the English (foreign language) original. This explains why many users, when faced with a choice between a localised (fully translated) application and an English language original, express a preference for the latter.

4. The M-Pesa app localisation: A case study
4.1. Methodology

To achieve its objectives, this paper relies on a case study carried out in Nairobi (Capital city of Kenya) and aimed at evaluating the acceptance and usability of the Kiswahili localised mobile phone app in Kenya, “A case of M-Pesa app” (Wandera 2014). This case study utilised a mixed-methods research design because it brings together the differing strengths of quantitative and qualitative methods, offsets the weaknesses of each single method, and expands the set of collected data. Mixed-methods research design is the collection and analysis of both quantitative and qualitative data in a single study, in which data is collected or analysed concurrently or sequentially (Creswell and Plano Clark 2007). The mixed-methods design is better than using a single-method research design because it overcomes the limitations of a single-method approach and has complementary strengths and no overlapping weaknesses (Cresswell 2014).

This type of research is categorised as explanatory (where quantitative data is collected first with qualitative data collection following), exploratory (where qualitative data is collected first with quantitative data collection following) and concurrent (where quantitative and qualitative data are collected at the same time to provide a more comprehensive and complete set of data). Specifically, this study applied the concurrent, mixed-methods design, which involves the simultaneous collection of data, independent analysis of each strand of data and then integration of the date during the interpretation stage. This method attempts to confirm, cross-validate, or corroborate findings within a single study (Tashakori and Cresswell 2007). This particular case study made use of a survey questionnaire for the collection of quantitative data and in-depth interviews for the collection of qualitative data. The results of the two methods were then integrated and collated at the interpretation stage. The idea here was to either note the convergence of the findings as a way of strengthening the knowledge claims of the study or to explain any lack of convergence that may result.

4.2. Target population

The main target population was the population inhabiting the Nairobi province, now known as Nairobi County. This population was estimated at 3,138,169 inhabitants as of the 2009 National Census (Kenya National Bureau of Statistics 2013).The study employed random sampling, which involves identifying subjects randomly. A random sampling technique offered this study the best opportunity to achieve unbiased results since it gives all subjects an equal chance of being selected out of the population being researched. In addition, given the financial constraints the study found itself in, random sampling was much faster and less expensive to use. Whereas there is no way to guarantee that the results that come from a sample in a random survey are 100% accurate, they tend to be more accurate than those obtained through other methods. The results from surveying the samples were later used to infer how the population as a whole may have responded and to draw conclusions about the larger group.

4.3. Sampling design and size

A sample is a subset of the population that is used to gain information about the entire population. It is a small collection of units, from a much larger collection or population, which is studied to enable the researcher to make more accurate generalisations about the larger group (Mugenda 2008). Sampling is therefore defined as the process of obtaining information about an entire population by examining only part of it (Kothari 2004; Mugenda 2008). It is generally impossible to study every population and hence researchers usually take a sample from the population for their studies (Wimmer and Dominick 2013).

This study used probability and non-probability sampling methods. In probability sampling, a reasonable number of subjects, objects or cases that represent the target population are selected (Ivankova 2006). In this kind of sampling, a researcher can determine the probability that any element or member of the population will be included in the sample (Mugenda 2008). Probability sampling seeks representativeness of the wider population and is mainly used in quantitative research (Cohen et al. 2007). Non-probability sampling seeks mainly to represent only a particular group or a particular named section of a wider group (Ritchie et al. 2013). Non-probability sampling is used when a sampling population cannot be precisely defined or when a list of the sampling population is unavailable. In a non-probability sampling the researcher cannot specify the probability that any element or member of the population will be included in the sample (Mugenda and Mugenda 2003). Non-probability sampling is used mainly in qualitative data collection while probability sampling is used in quantitative data collection.

Nairobi County as the study area was purposively selected because of its status as a city-county with many of its occupants being mobile users with different backgrounds, gender, age, and levels of education. Probability sampling method (random sampling) was used to select respondents to fill the survey questionnaire while purposive sampling technique was used to select respondents for key informant interviews.

Based on time and financial constraints, this study collected its quantitative data by administering 30 questionnaires to M-Pesa users in Nairobi County and conducted three (3) in-depth interviews of the key informants who were selected through purposive sampling.

4.4. Data Collection, Analysis and Presentation

This study used concurrent mixed method design to collect data. This method collects both quantitative and qualitative data concurrently and then integrates them at the interpretation of the overall results. Qualitative data was collected using observation and in-depth interviews while quantitative data was collected using survey questionnaire.

Data for this study was analysed and interpreted using the concurrent triangulation method. This method involves collecting and analysing the quantitative and qualitative separately, and then integrating both data at the interpretation stage of the study (Creswell 2014). Data analysis, according to Kothari (2004), involves a number of closely related operations, which are performed with the purpose of summarising the collected data and organising it in such a manner that it may answer the research questions. The operations include editing, coding, classifying and tabulating. It also entails categorising, ordering, manipulating and summarising data with the aim of finding answers to the research questions (Marshall and Rossman 2010).

4.5. Findings

The survey questionnaire allowed to establish that the level of acceptance and usability of Kiswahili language menu of M-Pesa app was low. The findings were such that a majority of the respondents (65%) indicated that they had never used the translated Kiswahili M-Pesa language menu. From the respondents that confirmed to have used the translated Kiswahili M-Pesa language menu, 22% reported rarely using it, while 13% of the Kiswahili menu users indicated that they used it because of national pride. Further, a majority of the respondents indicated that the use of unfamiliar terms that are not easy to understand in the Kiswahili M-Pesa menu was the reason for them not using the Kiswahili language menu.

The case study established that 83% of the respondents indicated a preference for using the English M-Pesa language menu. Only 17% of the respondents indicated having used the Kiswahili M-Pesa language menu in their transactions. It was also found that 35% of the respondents pointed to ease of understanding as the reason for their preference of the English language menu vis-à-vis the Kiswahili language menu.

A further look at the reasons for the preference of the English (source) language menu vis-à-vis the Kiswahili (target) language menu allowed to find out that 26% of the respondents did so because the source language menu uses familiar terms. Subsequently, 35% of the respondents pointed at ease of understanding as the reason for their preference.

These figures could be corroborated by the claims of key informants, during the key informant interviews, which stated that the English language menu made use of familiar terms, easy to understand by even those with low levels of education.

It was also established that 17% and 4% of the respondents pointed at ease of usage and proficiency in English, respectively, as the reasons for preferring the English language menu. Accordingly, the case study also revealed that another 4% of the respondents indicated that they preferred using the English menu because they wanted to be sure they made their transactions correctly.

On assessing the public attitude and perception of the translated Kiswahili M-Pesa language menu, the case study established that an important number of respondents (39%) indicated not to be very interested in using the translated Kiswahili M-Pesa language menu, whereas 22% of the respondents indicated a positive attitude towards the translated Kiswahili M-Pesa language menu. However, the majority of the respondents (91%) indicated that the translated Kiswahili M-Pesa language menu was important.

44% of the respondents who used the Kiswahili menu indicated that they were satisfied with its translation, while a similar 35% indicated that they were not satisfied with the translated Kiswahili M-Pesa language menu. The main reason for the satisfaction from the majority of users was that the app menu used familiar terms at 22%.

5. Conclusion

The results of the study show that the level of public awareness about the Kiswahili M-Pesa menu is high. However, the study findings depict that the extent of public acceptance of that same menu is low, which consequently results in its low usability. A majority of M-Pesa users prefer the English menu because of its usage of familiar and understandable terms. Further, even though the majority of users appreciate and view the Kiswahili-localised menu as being important, this has not translated into an increased usage of the Kiswahili menu.

The findings also concur with the arguments of Munday (2012) and Freij (2010:59), who suggests that as far as terminology is concerned, technical terms in source texts are supposed to be clarified (made simple) for the target, non-technical users during translation or localisation. Consequently, just as it has been argued in Translatorial Action Theory, it is only natural that a translation would be accepted and used if the message is clear and easily understood, uses common or familiar terms, consistently translated, and is functionally suitable in the culture of the target text.


From the foregoing conclusions, the author recommends several measures, which if carried out, could enhance public acceptance, usability, and perception of, as well as attitude towards, the Kiswahili M-Pesa language menu.

An awareness campaign should be carried out to sensitise the people about the existence of the Kiswahili M-Pesa language menu. This may increase the number of Kiswahili menu users and offer a platform for the illiterate users who would otherwise seek help to transact with M-Pesa.

The Kiswahili translation of the M-Pesa menu should further be simplified: familiar terms should be used, consistency and clarity in translation of terms should also be adhered to and, if possible, all terms should be translated into Kiswahili, instead of having a mixture of both English and Kiswahili in the Kiswahili version.

If possible, just like what happens with ATMs, the M-Pesa users should be offered an opportunity to choose the language of their choice between English and Kiswahili language menus, from the outset.

Since the new constitution has made the Kiswahili language both a national and official language of Kenya, policy makers and other stakeholders should do much in encouraging and dispelling the negative perception about the language. The acceptance and usage of the Kiswahili language menu of different items will help in the growth of the language.

  • Amatubi, Maurice Nyamanga (2002). “Globalization and the mainstreaming of Kiswahili Research in the 21st Century.” Kenneth I. Simala (ed.) (2002) Utafiti wa Kiswahili (Kiswahili Research). Eldoret: Moi University Press, 2004: 43–48.
  • Ankier (2013). “Localization for Mobile Apps — A Refresher.” Blog. Icanlocalize. (consulted 21.4.2015).
  • Bossman, Rachel (2014). “Mobile Money: The African Lesson We Can Learn.” Financial Review 14.2.2014 (consulted 21.4.2015).
  • Charalampidou, Parthena (2006). “Website Localization.” Ph.D. dissertation, Aristotle University of Thessaloniki.
  • Kenya National Bureau of Statistics (2013). “Nairobi (County, Kenya) - Population Statistics and Location in Maps and Charts.” (consulted 21.4.2015).
  • Cohen, Louise, Lawrence Manion and Keith Morrison (2007). “The ethics of Educational and Social Research." Louise Cohen, Lawrence Manion and Keith Morrison (eds) (2007). Research methods in education. Sixth edition. London: Routledge, 51–77.
  • Creswell, John W. (2014). Research Design. Thousand Oaks: Sage Publications.
  • Creswell, John W. and Vicki L. Plano Clark (2007). Designing and Conducting Mixed Methods Research. Thousand Oaks: Sage Publications.
  • Cull, Robert (2010). “Research - M-PESA:  Mobile Payments, Improved Lives for Kenyans.” Econ.Worldbank.Org. (consulted 21.4.2015).
  • Daniel, Alao Olujimi, Awodele Oludele, Rehema Baguma and Theo van der Weide (2011). “Cultural Issues and their Relevance in Designing Usable Websites.” Computing 1(2): 20–29.
  • Deb, Sagarmay (2004). Multimedia Systems and Content-Based Image Retrieval. Hershey: Idea Group Pub.
  • Duan, Shmuel (2012). “Localization for Mobile Apps.” Net-Translators.Com. (consulted 21.4.2015).
  • Eulich, Whitney (2012). “Developing Countries Lead The Way In Deploying Mobile Technology.” The Christian Science Monitor 27.07.2012 (consulted 21.4.2015).
  • Firpo, Janine (2009). “E-Money – Mobile Money – Mobile Banking – What’s the Difference?” Private Sector Development (consulted 21.4.2015).
  • Freij, Nabil (2010). Enabling Globalization: A Guide to Using Localization to Penetrate International Markets. Westborough: GlobalVision International.
  • Graham, Fiona (2010). “M-Pesa: Kenya's Mobile Wallet Revolution.” BBC News. (consulted 21.4.2015).
  • Habwe, John (2009). “The Role of Kiswahili in the Integration of East Africa.” Journal of Pan African Studies 2(8): 1-10.
  • Henke, Harold (2001). Electronic Books and ePublishing. London: Springer.
  • International Finance Corporation (2011). M-Money Channel Distribution Case-Kenya SAFARICOM M-PESA. (consulted 21.4.2015).
  • Iraki, Frederick K. and Charles R. Maroa (2008). “Towards A Multilingual Learner Software for African Languages.” Journal of Language, Technology & Entrepreneurship in Africa 1(1), doi:10.4314/jolte.v1i1.41765.
  • Ivankova, Nataliya V. (2006). “Using Mixed-Methods Sequential Explanatory Design: From Theory To Practice.” Field Methods 18(1): 3–20, Doi: 10.1177/1525822x05282260.
  • James, Emily Lora (2014). “M-Pesa: Kenya's Mobile Banking App.” (consulted 21.4.2015).
  • Kaffenberger, Michelle (2014). “M-Shwari in Kenya: How is it Really Being used?” (consulted 21.4.2015).
  • Katembo, Baruti (2005). “Kiswahili, the Global Economy and the African American”. Seminar paper presented at the International Symposium on Kiswahili language and Globalization. University of Dar es Salaam, Tanzania, July 4–7, 2005.
  • Kamau, Stephen Njihia (2008). “A Digital Divide: Kiswahili Holds the Key.” Journal of Language, Technology & Entrepreneurship in Africa 1(1). doi:10.4314/jolte.v1i1.41764.
  • Kim, Ryan (2012). “Distimo: App translation can pay off, especially in Asia.” (consulted 21.4.2015).
  • Kothari, Chakravanti Rajagopalachari (2004). Research Methodology. New Delhi: New Age International (P) Ltd.
  • Kurosu, Masaaki (2011). Human Centered Design. Heidelberg: Springer.
  • Marketsandmarkets (2015). “Mobile Money Market by Transaction Mode & By Nature of Payment 2019.” (consulted 21.4.2015).
  • Marshall, Catherine and Gretchen B. Rossman (2010). Designing Qualitative Research. 5th ed. Thousand Oaks: Sage Publications.
  • Mas, Ignacio and Olga Morawczynski (2009). “Designing Mobile Money Services Lessons from M-PESA.” Innovations: Technology, Governance, Globalization 4(2): 77-91. doi:10.1162/itgg.2009.4.2.77.
  • Mazrui, Ali Al'Amin and Alamin B. Mazrui (1999). Political Culture of Language: Swahili, Society and the State. Binghamton: Institute of Global Culture Studies.
  • Michaels, Loretta (2011). Better than Cash: Kenya Mobile Money Market Assessment. Washington DC: United States Agency for International Development. (consulted 21.4.2015).
  • Msanjila, Yohana (2002). “Dhima ya Kiswahili katika karne ya 21.” Kiswahili 65, 16–23.
  • Mugenda, Abel Gitau (2008). Social science research: Theory and principles. Nairobi: Acts Press.
  • Mugenda, Olive and Abel Gitau Mugenda (2003). Research Methods, Qualitative and Quantitative Approaches. Nairobi: Acts Press.
  • Munday, Jeremy (2012). Introducing Translation Studies. Abingdon: Routledge.
  • Mwaro-Mwaro, George (2002). “Mchango wa A.S.Nabhany katika Utafiti na Utandaridhi wa Istilahi za Kiswahili.” Utafiti wa Kiswahili, ed. By I. Simala. Moi University Press. Pp49–56.
  • Neva, Sifa (2012) “The Best: Top 10 Mobile Phone Apps in Africa.” Afritorial (consulted 21.4.2015).
  • Osterbauer, Christian, Monica Kohle and Thomas Grechenig (2000). “Web Usability Testing.” (consulted 21.4.2015).
  • Preece, Jenny, Yvonne Rogers, Helen Sharp, David Benyon, Simon Holland and Tom Carey (1994). Human-Computer Interaction. Essex: Addison-Wesley Longman Ltd.
  • Pym, Anthony (2001). Localization and Linguistics. Tarragona: Universitat Rovira i Virgili. (consulted 21.4.2015).
  • — (2011). Website Localization. Tarragona: Universitat Rovira i Virgili. (consulted 21.4.2015).
  • Ritchie, Jane, Jane Lewis, Carol McNaughton Nicholls and Rachel Ormston (2013). Qualitative Research Practice. 2nd ed. Los Angeles: Sage.
  • Rouse, Margaret (2014). “What Is App? - Definition from Whatis.Com.” Searchconsumerization. (consulted 21.4.2015).
  • Ryanga, Sheila (2002). “The African Union in the Wake of Globalization: The Forgotten Language Dimension.” Kiswahili 65, 1–15.
  • Safaricom (2014). “M-Pesa.” (consulted 21.4.2015).
  • Sandrini, Peter (2005). “Website Localization and Translation.” Heidrun Gerzymisch-Arbogast and Sandra Nauert (eds) (2005) Challenges of Multidimensional Translation. Proceedings. EU High Level Scientific Conferences, Marie Curie Euroconferences. Saarbrucken: Saarland University, 131-138.
  • Sasikumar, Maniyar and Jayprasad J. Hegde (2004). Software Localisation: Some Issues and Challenges. Mumbai: CDAC. (consulted 21.4.2015).
  • Spoone, Samantha (2011). “Apps Take Africa, World by Storm.” (consulted 21.4.2015).
  • Tashakkori, Abbas and John W. Creswell (2007). “Editorial: The New Era of Mixed Methods.” Journal of Mixed Methods Research 1(1): 3-7. Doi: 10.1177/2345678906293042.
  • Tractinsky, Noam (2000). “A Theoretical Framework and Empirical Examination of the Effects of Foreign and Translated Interface Language.” Behaviour and Information Technology 19(1): 1-13. Doi: 10.1080/014492900118759.
  • Twomey, Matt (2013). “Cashless Africa: Kenya’s Success with Mobile Money.” CNBC (consulted 21.4.2015).
  • Vodafone (2012). “Safaricom Launches M-Shwari - Offering Interest and Loans - On M-Pesa - Vodafone.” (consulted 21.4.2015).
  • Wachira, Alice Wanjiru (2006). “Multilingualism in Kenya: Focus on Language Use and its Implications.” Trans 16 (consulted 21.4.2015).
  • Wahome, Thuku (2015). “Kiswahili Becomes Kenya Official Language.” Standard Digital (consulted 21.4.2015).
  • Wandera, Alfred Sanday. “Evaluating the acceptance and usability of Kiswahili localized mobile phone app in Kenya: a case of M-Pesa app.” Masters dissertation, University of Nairobi, 2014.
  • Weir, George R. S. and Lepouras, Giorgos (2001). “Localisation and linguistic anomalies.” Proceeding of HCI International 2001, New Orleans, USA, 2001, 535-539.
  • Wimmer, Roger D. and Joseph R. Dominick (2013). Mass Media Research. Belmont: Wadsworth.

Wandera portraitAlfred Sanday Wandera is an Administrator at Kenyatta University, working in the Directorate of Kenyatta University Television and Radio Services. He has Masters in Communication Studies from the University of Nairobi and another Masters in Translation Studies from the same university. He is also a freelance translator (English to Swahili).


Note 1:
The abbreviation for the word ‘application’ is ‘app’ which is defined as a specialised program software downloaded onto mobile devices (Rouse 2014).
Return to this point in the text