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Posts Tagged ‘ict4d’

Trust Issues and Ride-Hailing Platforms in Lagos, Nigeria.

The idea of building trust is often central to the adoption and use of technology platforms in general such that the processes and governance of these platforms ought to align with the realities of user-groups which are essential for a seamless service. Since 2013, the entry of ride-hailing platforms in Nigeria has increased because of an overall technology awareness in Lagos and continuous successes of existing ride-hailing companies such as Uber and Taxify (see Table 1). Ease of access, trip predictability and ease of fare calculations and payment, amongst other things have improved.

Despite its growing impact on urban transport in Nigeria, the industry has suffered several challenges such as insecurity and lack of safety for user-groups. Prior to ride-hailing platforms, the notion of trust has been integral for taxi businesses or technologies to thrive. For instance, a passenger who builds a bond with a local taxi driver such that the driver runs personal errands such as dropping off school kids.

Trust in simple terms is the belief in the ability of someone or something. There has been increasing interest in the concept of trust in online transactions since the development of the internet and e-commerce in the early 1990s (1). The concept of ‘trust’ encapsulates both offline environments and online environments such that the difference lies in the varying characteristics of these environments as well as the context in which trust is formed and maintained. In technology, “it is a belief that a specific technology has the attributes necessary to perform as expected in a given situation in which negative consequences are possible” (2).Risks and uncertainties are exacerbated because users lack total control of the processes governing ride-hailing apps.

Table 1: Ride-hailing companies in Lagos
Source: Author’s fieldwork

In the ride-hailing industry in Lagos, both drivers and passengers are aware of the risk in engaging with a complete stranger via an app which is monitored by platform companies through data analytics and algorithms. Unlike the conventional taxi industry, user-groups often build trust in platform companies based on the efficiency and reliability of their apps over time. For example, Mr Ayo, the Taxify driver has just accepted his first trip for the day, but later declines because the rider would only pay via an ‘online bank transfer’ and from experience, the driver does not trust this process because it is often a fraudulent tactic used by riders without money. Using a third-party banking app to make a transfer to the driver’s account gives the rider more power in this situation because the payment could be reversed in 24 hours if reported by the rider. If it were a card-paid trip, the driver would feel safer because the ride-hailing app acts as an intermediary between both parties such that if a conflict occurs, it can be resolved amicably.

One of the many instances where the rider loses trust is through trip manipulations by drivers.  Since Uber slashed the base fare of trips by 40% in Lagos, drivers have reacted with strategies for increasing the fare of trips through manipulative techniques (3). In 2017, Lockito, designed for testing geofencing-based apps, was being used in inflating fares by manipulating the distance of a trip.  For example, a trip that should be about 5.9km would be double the distance when the Lockito app is being used (see Figure 1).

Although drivers are responsible for altering the GPS function in the Uber app, riders become aware that the app is also vulnerable to fraudulent activities. Riders frequently monitor the Uber app, drivers’ behaviour and prefer cash payments to card payments to avoid being defrauded during trips. Although there are other factors involved such as low smartphone and card penetration overall (4), the psychological construct of trust remains central to the reliability and predictability of drivers, riders, and the algorithms behind ride-hailing apps.

Figure 1: Incorrect GPS reading vs correct GPS reading
Source: BrandSpurNG (2017)

Regardless of ride-hailing platforms’ success in Nigeria, trust issues surrounding usability and culture remain a stumbling block especially for indigenous start-ups like Oga-Taxi. More research would be needed to understand the implications on user behaviour and what coping strategies are needed to thrive in an increasingly ‘networked’ environment as well as how these strategies may create new realities in the global South.

References.

  1. Li, F., Pieńkowski, D., van Moorsel, A. & Smith, C. (2012). A Holistic Framework for Trust in Online Transactions. International Journal of Management Reviews, 14(1), pp. 85-103
  2. McKnight, D. G., Carter, M., Thatcher, J.B., & Clay, P.F. (2011). Trust in a specific technology: An investigation of its components and measures. ACM Transactions on Management Information Systems, 2(2), pp. 12 – 32.
  3. Adegoke, Y. (2017). Uber drivers in Lagos are using a fake GPS app to inflate rider fares, Quartz Africa, 13 Nov
  4. appsafrica (2015). Can Uber really work in Lagos, Nigeria? appsafrica, 2 Jun
  5. BrandSpurNG (2017). Uber Drivers In Lagos Using Fake GPS App To Inflate Fares – Report, Nairaland Forum, 14 Nov
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An Applied Data Justice Framework for Datafication and Development

Data is playing an ever-growing role in international development.  But what lens can we use to analyse the impact of data on development?

The emerging field of “data justice” offers some valuable ideas but they have not yet been put together into a systematic and comprehensive framework.  My open-access paper – Datafication, Development and Marginalised Urban Communities: An Applied Data Justice Framework, written with Satyarupa Shekhar – provides such a framework, as shown below.

The framework exposes five dimensions of data justice:

  • Procedural: fairness in the way in which data is handled.
  • Instrumental: fairness in the results of data being used.
  • Rights-based: adherence to basic data rights such as representation, privacy, access and ownership.
  • Structural: the degree to which the interests and power in wider society support fair outcomes in other forms of data justice.
  • Distributive: an overarching dimension relating to the (in)equality of data-related outcomes that can be applied to each of the other dimensions of data justice.

The dimensions can be used individually; for example, just to analyse data practices, or just to analyse the impact of context on new data systems in developing countries.  Or the model can be used holistically; for example, to understand the full development impact of a particular data initiative.

The Datafication, Development and Marginalised Urban Communities: An Applied Data Justice Framework paper takes the latter route.  It analyses “pro-equity data initiatives” that were implemented by data activists in four cities: Chennai, Nairobi, Pune and Surakarta.  These initiatives specifically sought to address the data injustices suffered by slum dwellers and other marginalised groups; particularly their invisibility to urban planners and other external agencies.

Using the data justice lens, this research finds that new data flows do have a positive impact in counteracting the injustice of invisibility, but they disproportionately serve those with the motivation and power to use that data.  Results in terms of service improvements and epistemic change are beneficial for slum communities and other marginalised citizens, and these initiatives can be justified on that basis.

However, though there can be no exact calibration from qualitative research, it is likely that these pro-equity initiatives actually increase relative inequalities.  Ordinary community members have seen some benefits but external actors who find the data to match their agenda and capabilities, benefit more.  It is the latter who are more empowered to access, use and control the new data.

If you would like to know more about this research’s findings, framework and recommendations for practice, then take a look at the paper: https://www.tandfonline.com/doi/full/10.1080/1369118X.2019.1599039

The Quest for the Digitisation of Education in Developing Countries: Are we Forgetting Teachers?

The development of every country partly depends on how strong and reliable its educational system is to produce the best minds to innovate and bring new solutions to that country’s challenges. Often, this task automatically falls on teachers who generally get the blame for all failures of the education system but rarely get the praise for its successes. In this modern the era of technology where students’ ICT literacy has come to the fore because of its potential for economic development, teachers are in the firing line of anyone who thinks the education system is not doing enough to prepare learners for the technology skills they need for surviving in today’s digital world.

With the SDGs showing that education will be the key to many of today’s world ills, it is probably high time we stopped and considered exactly what that education will look like in deprived contexts, should we continue to do business as usual. Yes, we want education for all and all that. We certainly want quality education and of course in the 21st century, quality education must respond to the needs of the next generation. In a world permeated with technology though, quality education is increasingly necessitating the use of technology for teaching and learning enhancement. As much as everyone wants children in developing countries to receive education that will enable them to harness the power of technology as the developing world tries to catch up with the rest, learning with technology remains a dream in many developing countries.

All we need is access to ICTs, right?

In developing countries, access to ICTs in schools is limited and costly in the rare instances where it is provided. The expectation is therefore that as soon as technologies—mainly computers—are available in schools, teachers would unreservedly make great use of them and just like a magic wand, improve students learning and overall ICT literacy, all of which are to contribute to the development of the concerned countries. Such has been the thinking behind many developing countries’ investments in the One Laptop Per Child project and similar projects. This technocentrism that has been decried for a while now [1] is yet to bear fruit despite many developing countries still constantly biting the same bait in hope of … well, a different outcome? After all, the $100 One Laptop per Child is no longer seen as the laptop that will save the world as the New York Times once claimed.

A key flaw of the technocentric view of ICT in education is that when the expected outcomes are not obtained, nothing else could be responsible but the teachers. Given the cost of these technologies to the otherwise deprived developing countries, the thought of teachers not making use of them is often intolerable. Why in the world would they not elect to use such equipment that cost so much to get? Are they not aware that some financial sacrifices were made to bring those devices to the schools? Have they forgotten that the country is betting its development on students’ skills to use those technologies creatively? So, teachers are always seen as potentially problematic in efforts to digitise the education sector. This negative image of teachers has not been helped by claims that teachers are a class of less technologically savvy digital immigrants who can hardly use ICTs to the liking of their supposedly technology-savvy, digital native students [2].

But do we really know the teachers?

If as it is now generally assumed, technology literacy skills of the next generation of learners are the responsibility of teachers [3], then understanding who we are entrusting that task with should be a priority. We are expecting great works from teachers in the building of our digital economies and that should mean we know better who they are and how they become the people we give such big responsibilities. Masterpieces don’t paint themselves, neither are they a product of a brush nonchalantly placed in the clumsy hands of an amateur. So, ICT in education ought not to be summed up with handing computers or laptops to teachers and schools before sitting back and awaiting miracles to happen. They surely won’t. The need for a generation of skilled men and women fully equipped with the ‘21st century skills’ of which ICT skills are central should be considered second to the understanding of the men and women who are going to make that ICT literate generation a reality: the technology-using teachers. There is a need to know what teachers are really willing and capable of doing with ICTs before counting unhatched chickens of economic transformations that we will get from ICTs, especially in the developing world.

Let’s take an example of Rwanda where I am currently doing a study on the development of identities as technology users of pre-service teachers. (You can read more about the study in this blog post). Rwanda is a country that has gained international acclaim for its efforts to digitise itself and its ICT-friendly policies. Without any other substantial resources, ICTs have been put at the centre of its economic ambition, and this privileged position has had them dubbed ‘the heart of the education sector’ [4]. As a result, investments in the acquisition of laptops for schools have been ongoing since 2007. Nevertheless, once in schools, these technologies have not been used as initially hoped. In fact, recently the Ministry of Education found itself left with no choice but to instruct school leaders to ensure their teachers are using the resources available or risk losing their jobs, after it was revealed that many of these devices had remained in their original boxes while others just disappeared. The easy question here is why are the teachers not using these resources in the first place? Why would they wait for their head-teachers to lose their jobs before they start using ICT resources given to their schools, for free? But an even better question would be ‘Who are those teachers, who are failing to use technologies given to them for free?’ How did they come to be who they are? What has made them to be the technophobes they are portrayed to be? These are some of the considerations that are the genesis of my ongoing PhD study.

My research wants to understand who the teachers expected to use the increasing number of technologies in schools are, by approaching the problem from a socio-cultural point of view. Teachers’ ICT training and usage don’t happen in a vacuum. So, it is important to understand how the different contexts they grow up in (socially and professionally) shape who they are in relation to ICTs and therefore influence the likelihood of them using and negotiating the use of any technologies in any way with their students.

In this study I am following pre-service teachers during a year-long internship to understand how ICT policies and training programmes translate into actual technology using teacher identities. This means understanding the key influences that teachers-in-training have and the extent of these influences on the end product that ends up in schools. This understanding can already help predict what route will lead to teachers who are most likely to use the technologies that are available to them in the context.

Given the many factors that come into play regarding ICT use in education, I attempt to follow the training line to understand first, what ICT roles teachers are trained for and expected to play in policies and teacher education programmes respectively. Then I look at the support and the influence that come from those directly in charge of student-teachers development process (teacher educators and school-based mentors). How do they guide them in the use of ICTs? Does their practice encourage or discourage the development of ICT skills for these candidates who want to become teachers in a country that counts on technology to achieve its development goals? How does the existing ICT environment allow the teacher-trainees to cultivate and exercise their agency as professionals trying to achieve learning objectives with(out) the support of ICTs?

Answers to these questions will certainly not solve all the challenges related to ICTs for development especially as seen from an education perspective. However, they will give a picture of who the teachers are and what needs to be done to get them using already available technologies in Rwandan schools and also schools in similar contexts.

References
[1] S. Papert, ‘A Critique of Technocentrism in Thinking About the School of the Future’, in Children in the Information Age, Elsevier BV, 1988, pp. 3–18.
[2] M. Prensky, ‘Digital Natives, Digital Immigrants’, On the Horizon, vol. 9, no. 5. pp. 1–6, 2001.
[3] D. Epstein, E. C. Nisbet, and T. Gillespie, ‘Who’s Responsible for the Digital Divide? Public Perceptions and Policy Implications’, The Information Society, vol. 27, no. 2, pp. 92–104, Feb. 2011.
[4] Ministry of Education, ‘Education Sector Policy’, Kigali, 2003.

Analysing the Perceptions of Digital Gig Workers: Mining Emotions from Job Reviews

In a previous post, we provided a discussion of how the analysis of user-generated content (e.g. comments/posts on social media and/or job review sites) can help in understanding perceptions of digital gig workers. The prevailing assumption is that generally, digital gig workers contend with non-standard working conditions, e.g. the lack of social security coverage, long working hours, lower salaries, and the lack of benefits. Nevertheless, it is believed that digital gig workers in the Global South in particular perceive their jobs as being better than local benchmarks (i.e. office-based work).

To test the above assumptions, we developed and employed automatic text analysis methods to answer the following research questions:

  • How do digital gig workers feel about their jobs?
  • Which topics pertaining to decent work standards do they frequently talk about?
  • Are there any differences—in terms of sentiments and topics—across different geographic locations, or across genders?

We hereby present the results of analytics in the way of answering the questions above.

Firstly, we collected online posts published by digital gig workers from Glassdoor, a web-based platform for sharing reviews of companies and their management. Focussing on reviews of the digital gig companies Upwork, Fiverr and Freelancer, we retrieved a total of 567 reviews, 297 of which include geographic metadata (i.e. the geographic location associated with the account/profile of the user posting a review). For our text analysis, we made use of the Pro and Con fields that each review came with.

Based on the NRC Emotion Lexicon, a dictionary-based emotion detection method (implemented in the R statistical package) was applied on the reviews, classifying them according to Robert Plutchik’s eight basic emotions: Joy, Trust, Fear, Surprise, Sadness, Anticipation, Anger, and Disgust. We then grouped the reviews as either coming from the Global North or the Global South based on the geographic metadata attached to them. Shown in the figure below are the 15 most frequent emotion-bearing words found within reviews, represented according to the emotions they express. Bars in amber correspond to words prevalent in reviews from the Global North (GN) while those in blue pertain to those in reviews from the Global South (GS). 

Riza GNGSemotion

It can be observed that there are more words within GS reviews containing emotions that are clearly positive. All of the 15 words associated with Trust were found more often in GS reviews. Furthermore, 10 and 8 words associated with Joy and Anticipation, respectively, were more frequent in GS reviews. These results support the belief that digital gig workers in the Global South (GS) do express positive feelings towards their jobs.

Meanwhile, our results show that digital gig workers from both GN and GS express negative emotions. On the one hand, GS reviews were the source of 11 and 10 words associated with Anger and Fear, respectively. On the other hand, 15 and 11 words associated with Sadness and Disgust, respectively, were contained in GN reviews. This suggests that generally speaking, digital gig workers do have to contend with less than ideal working conditions, which in turn trigger such negative emotions.

Finally, 10 words associated with Surprise came from GN, 5 from GS. It is worth noting though that this particular emotion can either be negative or positive depending on context.

These results are but “teasers” to the full results of our automated analysis. Further details including the topics/themes towards which such emotions are targeted, as well as answers to the second and third research questions stated above, will be presented by Dr Victoria Ikoro in the upcoming 3rd Annual ICT4D North Workshop to be held in the Management School of the University of Liverpool on the 6th June 2019.

 

What can we learn about e-commerce in Africa from Jumia’s IPO filing?

30 April 2019 1 comment

 

There has been growing discussion about the potential of e-commerce in developing countries. This discussion intensified recently when pan-African e-commerce firm Jumia went public in the US, becoming the “first African unicorn”.

The IPO prospectus, a 270-page outline of the firm released as part of this filing, has sparked much debate. Elsewhere, TechCrunch has dug into the financial intricacies of Jumia, and online debates have raged linked to the question “Is Jumia really an African firm?” (see here and here).

I won’t detail those two issues here. Instead, below I will discuss the insights that the prospectus provides us about e-commerce platforms operating in Africa. This is especially useful as we have been struggling with a lack of detail on e-commerce, with firms reluctant to share commercially sensitive information.

 

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1) The market for e-commerce in Africa is already large, and growing rapidly
Jumia announces that it had 4 million active customers in the year 2018, growing rapidly from 2.7 million in 2017. This translates into “Gross Merchandise Volumes”  (GMV) of €828.3m in 2018, from €507m in 2017. As these figures suggest, e-commerce is bringing in a significant number of customers on the continent and is growing at a rate of over 50% in the last year.

Regionally, the largest countries for Jumia’s business are Nigeria (29% of GMV) and Egypt (20.5%). Interestingly, in the largest 5 markets, only 50% of goods are delivered in primary cities with the rest evenly split between secondary cities and rural areas. Most customers are mobile users, which comprise 81% of all traffic in 2018.

 

2) …but making profits is a challenge. Jumia is a loss-making firm
The growing size of e-commerce has not yet translated into profits. Jumia made a €170m loss in 2018.

This is attributed to a number of factors. As a platform, sales are mainly made by third-party sellers (90%). So the €828m GMV translates to just €130.6m revenue for Jumia.  Jumia then faces high costs for operating including warehousing, delivery, sales and advertising and the platform. Once these are considered, the €130.6m turns into a €170m loss.

How does Jumia plan to become profitable in the future? By becoming a market leader in Africa, Jumia will rely on expanding markets to increase sales volumes over the coming years. Alongside this, they describe the potential of reduced costs in fulfilment (storing and delivering goods) and growing use of mobile payments that should make each transaction more efficient over time.

 

3) The role and prospects for Jumia platform sellers
Jumia has 81,000 sellers and the prospectus hints that quite a number of these are African, although there is no data provided. Interestingly, commissions from sellers for sales only contributed moderately to revenues. Jumia makes similar amounts of revenue from services such as fulfilment (delivery costs to buyers) and “value-added services” (premium services for sellers).

As Jumia grows, its aim is to attract ever more sellers to the platform. “Competition between sellers is…essential to our monetization, as it increases the appetite for sellers to use our services”. This statement suggests that the platform will move low margins and high competition, with sellers relying on value-added services as a source of expansion. For local sellers, these future directions suggest concerns about this platform supporting widespread upgrading of local SMEs in Africa.

 

4) Data is an important component of the relationship with sellers
We know that data is vital to many platforms, and Jumia is no different. A seller score “..a data-driven scoring of a seller’s performance” is a key aspect of Jumia’s relationship with sellers. The score is important to the success of sellers, where platform algorithms use this score to determine the order of products in searches. Jumia also gamifies the “seller score”, associating it with a range of other advantages for sellers.

In order to support sellers, Jumia supports third-party financial services for its sellers, using this score as a way to demonstrate creditworthiness. This mirrors alternative credit-scoring schemes we have seen elsewhere in Africa.

 

5) African e-commerce platforms face significant and often unexpected risks
Many of the challenges for Jumia are similar to those challenges of e-commerce elsewhere [1]. One key challenge repeatedly mentioned is the “…failed deliveries, excessive returns, late collections, unrecoverable receivables and voucher abuse”, with 14% of all sales (by revenue) being failed deliveries or returns. These risks particularly emerge from the use of cash payments on delivery (COD), a common approach to payments for online goods in developing countries.

Beyond this challenge, an eye-opening aspect of the prospectus is the unexpected challenges encountered by Jumia:

  • In Kenya, a Jumia warehouse was robbed and €500K of merchandise was stolen
  • In Egypt, a €5000 fine was imposed by authorities due to the platform offering “unlisted drugs”
  • In Kenya, a scam involving electronic payments suppliers led to €550K losses
  • Jumia has undertaken investigations around allegations of internal fraud and bribes in countries such as Nigeria and Morocco connected to relationships with platform sellers

 

6) Policy challenges for e-commerce in Africa are significant
In line with other platforms, Jumia operates a relatively “asset light” way across multiple countries in Africa. Even with close to a billion euro in GMV, and with offices in 18 countries, it is a tiny direct employer with around 4,800 staff in Africa.

This “asset light” approach, however, comes into collision with African governments’ desire to regulate e-commerce. Jumia discusses the challenges faced in a number of countries including taxes, particularly VAT on imports; uneven data protection rules, and restriction of cross-border personal data transfer; and regulation on financial and mobile payments.

There has been pressure for harmonising such rules globally in order to support cross-border business models of digital firms such as Jumia. However, African governments are keen to ensure that they are able to operate their economies appropriately, including collecting taxes and nurturing local firms, in the face of e-commerce imports [2]. It is therefore understandable that policy might vary according to the political goals of different nations in Africa. These challenges are likely to intensify coming years given current disagreements on harmonising e-commerce at the WTO, and African CFTA discussions on e-commerce rules still at an early stage [3].

Platform firms, therefore, require careful mapping of national rules and regulations, and in Africa the “asset light” model may only be viable to well-funded platforms. For smaller platforms, it may be better to focus on a smaller subset of countries.

 

In summary, the Jumia prospectus indicates that digital economies are expanding and we can expect to see a growing set of firms operating across the continent. However, given the challenges encountered by Jumia, easy profit and growth are not a given. For platform sellers, e-commerce provides new potential market opportunities, but careful consideration of how platforms best support them, will be vital to success.

 

References
[1] UNCTAD (2015) Information Economy Report 2015 – Unlocking the Potential of E-Commerce for Developing Countries, UNCTAD, Geneva, Switzerland.
[2] Azmeh, S. & Foster, C. (2018) Bridging the Digital Divide and Supporting Increased Digital Trade: Scoping Study, Discussion Paper, GEG Africa, Pretoria, South Africa. http://www.gegafrica.org/item/782-bridging-the-digital-divide-and-supporting-increased-digital-trade-scoping-study
[3] Foster, C. & Azmeh, S. (2018) E-Commerce and the African Continental Free Trade Agreement (AfCFTA), Discussion Paper, GEG Africa, Pretoria, South Africa. http://infomediation.net/publication-e-commerce-and-the-african-continental-free-trade-agreement-afcfta/

 

Bricolage and the Sustainability of ICT4D Solutions

In  ICT4D, bricolage refers to context-sensitive ways of implementing and sustaining ICT4D solutions [1].  Different from approaches where strategic goals, ways to achieve them, as well as success and failure metrics are defined in advance, bricolage is mostly characterised by improvisation and continuous learning from failures in environments with many uncertainties [2].  People who play key roles in shaping and driving the bricolage process are hereafter referred to as bricoleurs.

Drawing from a particularly successful long-term ICT4D project in Tanzania, for which the author of this post has been part of a team for about 10 years, this article discusses a three-stage process that local bricoleurs have gone through in sustaining the project in the face of scarce resources and diverse interests of stakeholders.  Extended empirical and theoretical insights about the role of bricolage in shaping and sustaining the project were reported in the work of Fruijtier and Senyoni [3], and this post will essentially provide some sound bites from the paper.

Bricolage in ICT4D Projects: Stages

1.    Opportunity Based: During this stage, a project opportunity is identified, its activities are mainly driven by external players, and the local bricoleur gets involved in project activities based on availability and need, as determined by main players. In the case of the Health Information Systems Program (HISP) team at the University of Dar es Salaam in Tanzania (hereafter referred to HISP UDSM), this stage was characterised by the advent of a pilot project for implementing the District Health Information Software (DHIS) in Kibaha and Bagamoyo districts in the Pwani region.  This was around 2002-2010 and the main focus of the project during this period was to demonstrate the capabilities of the then-new DHIS system in handling routine aggregate health data, and to make a case for the endorsement and national rollout of the system by the Ministry of Health (MoH) in Tanzania. The University of Oslo (UiO) (main developers of the DHIS system) mainly influenced the direction of project activities during this period, and the HISP UDSM team supported the pilot districts in activities such as training, user support and data analysis, as was determined by the main team at UiO. 

PhD and MSc scholarships were also established as a result of collaboration between the UiO and HISP UDSM in order to, among other things, strengthen local capacity for supporting project activities in Tanzania. It was the ability to serendipitously survive funding uncertainties and diverse interests of stakeholders, and the partnership with MoH in persuading a variety of stakeholders to pursue the common cause (strengthening HMIS (Health Management Information System) data reporting) that prepared the UDSM team for the would be next phases of the project where it (HISP UDSM) turned out to play a key role that fostered project success.

2.    Locally Owned: During this stage, bricoleurs cultivate the growth of what is already achieved while advancing their knowledge and understanding of practices in the project domain. In the case of the HISP UDSM team, this was the period from 2010-2015 which was characterised by close involvement with MoH in providing technical support during revision of HMIS data collection tools and definition of indicators prior to the national rollout of DHIS, and playing the central training role during the national rollout which was done in December 2013. After the national rollout, HISP UDSM got closely involved in supporting hundreds of users across the country, as well as bringing data for other programs and partners on board. Apart from this close involvement, care was taken to involve MoH and its various departments on every step of the way, to foster ownership and long term sustainability of the project.

3.    Locally Driven: At this stage, bricoleurs assume main control of events in the project. They can proactively anticipate challenges, and provide them with apt solutions. In the case of the HISP UDSM team, this is a period from 2015 onwards. It is characterised by, among other things, new projects and requirements from various stakeholders. Following the successful DHIS national rollout in 2013, the HISP UDSM team was also requested by other ministries in Tanzania to implement similar solutions for them. In response to this, so far, HISP UDSM has customised DHIS to serve the data reporting and analysis requirements of the Ministry of Agriculture and the Ministry of Water in Tanzania. Arrangements are underway to do the same for other ministries and government departments. As well, as they continue using DHIS, various MoH partners keep on requesting new and rather generic functionalities which are not yet implemented by the main DHIS developer base, which is globally led by UiO.  To respond to this, in 2015, the HISP UDSM team devised an innovation strategy which has seen the implementation of generic solutions, in terms of new DHIS functionalities and mobile apps, that have turned out to be useful to other DHIS users across the globe [3]. 

Conclusion

Two key take-aways for other ICT4D projects:

  1. The sustainability likelihood of an ICT4D project increases with an increase in the ability of the bricoleur to create the environment that fosters the prosperity of bricolage. Importantly, to be innovative in unpredictable project envoronments, bricoleurs need to build both social and technological alliances.
  2. Because of the special emphasis on learning, universities can be conducive environments for bricolage to thrive.

References

1.    Ali, Maryam, and Savita Bailur. “The challenge of “sustainability” in ICT4D—Is bricolage the answer.” Proceedings of the 9th international conference on social implications of computers in developing countries. 2007.

2.    Ciborra, Claudio U. “From thinking to tinkering: The grassroots of strategic information systems.” Bricolage, Care and Information. Palgrave Macmillan, London, 2009. 206-220.

3.    Fruijtier, Elisabeth, and Wilfred Senyoni. “The Role of Local Bricoleurs in Sustaining Changing ICT4D Solutions.” International Development Informatics Association Conference. Springer, Cham, 2018.

Measuring the Broadband Speed Divide using Crowdsourced Data

Digital applications and services increasingly require high-speed Internet connectivity. Yet a strong “broadband divide” exists between nations [1,2]. We try to understand how big data can be used to measure this divide. In particular, what new measurement opportunities can crowdsourced data offer?

The broadband divide has been widely measured using subscription rates. However, the broadband speed divide measured using observed speeds has been less explored due to the lack of data in the hands of regulators and statistical offices. This article focuses on measuring the fixed-network broadband speed divide between developed and developing countries, exploring the benefits and limitations of using new crowdsourced data.

To this aim we used measurements from the Speedtest Global Index, generated by Ookla using data volunteered by Internet users verifying the speed of their Internet connections [3]. These crowdsourced tests allow this firm to estimate monthly measurements of the average upload and download speeds at the country level.

The dataset used for this analysis comprised monthly data, from January to December 2018, for a total of 120 countries. Using the income and regional categorisations set by the World Bank we identified 64 developing countries and 54 developed countries in seven regions. Complete data for only two of the least developed countries were available so these were not included in the analysis.

The following table presents the download and upload speed averages on the fixed network, aggregated by region and level of development, and the totals for all the countries in our final sample (n=118), while the figure below shows the download and upload speeds aggregated by level of development.

Table 1. Average upload and download speed by region and development level, fixed network. January – December 2018 (Mbps)

Note: Unweighted averages
Source: Author calculations using data from Ookla’s Speedtest Global Index [3]

Figure 1. Average upload and download speed by level of development, fixed network. January – December 2018 (Mbps)

-Download speeds. We observe that the divide between developed and developing countries is pronounced with average download speeds for the latter being around one-third of the former. However, the divide is also evident within regions: in the developed world, countries in North America have speeds three-times higher than those in the Middle East. Within the developing countries those in Europe & Central Asia have the highest download speeds and those in the Middle East & North Africa have the lowest. Overall, download speeds are much lower in the developing world, thus creating an important impediment to the use of data-intensive digital applications and services.

-Upload speeds. We identify that overall there is an existing divide between developed and developing countries similar in magnitude to the one observed in download speeds. However, when looking at the group of developing countries we see that regional rankings are different compared to those identified using download speeds: the East Asia & Pacific region ranks first and North America ranks third – the latter with speeds that are two-thirds of their download speeds. Across regions, upload speeds are always slower in the developing world, and again the Middle East & North Africa region ranks at the bottom; but the divide between download and upload speeds is lower in the developing world. Considering that faster upload speeds are also required in a data-intensive era, the majority of the countries are far from the ideal of having faster networks with synchronous speeds.

Some benefits and limitations are identified when measuring the broadband speed divide using this type of crowdsourced data.

-Benefits. First, the availability of these types of data allows us to measure the broadband speed divide between developed and developing countries using observed instead of theoretical speeds. Second, these measurements are openly available on a website that can be accessed by the general public at no cost. Third, the divide can be measured and tracked over time more frequently than when using survey or administrative data. Finally, this site reports both download and upload speeds which are important to measure in a data-intensive era.

-Limitations. Even if there are data available for a good number of countries there are no complete data about the least developed countries, leaving behind this group. Also, there might be some bias in the production of data as crowdsourced measurements might be coming from ICT-literate individuals in certain countries [4]. Finally, from this source it is not possible to access complete datasets with additional data points such as the number of observations, medians, and latencies for each country.

These findings derive from a broader research project that, overall, is researching use of big data for measurement of the digital divide.  Readers are welcome to contact the author for details of that broader project: luis.riveraillingworth@manchester.ac.uk

References

[1] ITU (2018). Measuring the Information Society Report 2018. Geneva, Switzerland: International Telecommunication Union.

[2] Broadband Commission (2018). The State of the Broadband: Broadband catalyzing sustainable development. Geneva, Switzerland: Broadband Commission for Sustainable Development.

[3] Ookla. (2018). Speed Test Global Index [Online]. Available: http://www.speedtest.net/global-index/about [Accessed 01/03/2019]

[4] Bauer, S., Clark, D. D. & Lehr, W. (2010). Understanding broadband speed measurements. In,TPRC 2010. Available at SSRN: https://ssrn.com/abstract=1988332

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