The book deals about Information and Communication Technologies for Development (ICT4D) but, provided that ESADE is a business school, the approach heavily relies on the role of businesses in achieving this development through ICTs.
The book begins with two initial chapters on ICTs in social inclusion and the role of global businesses in development under the approach of “inclusive markets”. The second part of the book is made up by an analysis of several cases in the field of e-commerce, e-agriculture, learning and training, e-health, e-governance or online volunteering, to name a few.
Part III devotes three chapters to the conclusions and advice for policy-makers, being Part IV four more chapters written by invited contributors (amongst them, yours truly):
Manuel Acevedo: ICT and human development in Latin America.
Mireia Fernández-Ardèvol: Mobile communication and social development in Latin America.
Ismael Peña-López: Key factors for successful ICT4D projects: How can telecoms contribute.
Vanessa Frías-Martínez: Mobile phones and emergent markets in Latin America.
In what concerns my book chapter, Key factors for successful ICT4D projects: How can telecommunication businesses contribute to the advancement in ICT4D, I begin speaking about general concepts like development, the Information Society and their relationship. I go on stating that digital infrastructures do not necessarily lead to social development, being them “only” a necessary but not sufficient condition that goes in parallel with other important aspects such as a powerful industry, digital literacy, a regulatory framework, or a wide supply of digital content and services.
I end up listing what I think are the three main roles for telecoms in ICT4D:
To lower down the “last” barriers of access in what refers to infrastructures: usability, accessibility and affordability.
Once physical access is no more an issue, to work for utility, capacity and e-awareness. That is, to raise awareness not only on what can ICTs can be used for, but on how they are transforming our lives and creating new arrays of exclusion for those that do not skilfully use them.
Last, but not least, to mind the context: ICTs are a tool and, as such, they multiply the reality they are used in. In this sense, it is very important to remind that ICTs stand for “information” and “communication” technologies, and thus the knowledge gap is a hypothesis that is increasingly been backed up with evidence.
Telco Industry Research in ICTD: Telefónica R&D, mobiles and development Vanessa Frías-Martinez
ICT4D research and private sector research in ICT4D
We have witnessed an evolution in ICT research and ICT4D research. During the 50s, there was ICT research without the ‘D’. It was mainly about governments using computers and measuring their impact. During the mid 90s, governments and NGOs began to use intensivelly ICTs to foster development; we saw the raise of telecentres, PCs and landlines and research around these topics. Lastly, in the mid 2005s, the private sector enters the arena of ICT4D research.
What are the roles of actors in ICT4D?:
Governments: incentive packages to accelerate actors’ involvement; access to population at large and infrastructures.
Private sector: R&D in hardware, software, services, infrastructures to innovate or adapt technology to new uses and users; access to customers base.
NGOs & Intl. organizations, academia: access and understanding of local population and their needs.
Some examples:
Intel PC Classmate: Intel developed a cheap laptop adapted to kids and which came with (not free) educational software also developed within the project. To provide connectivity, partnerships were established with public internet providers.
Nokia Life Tools: C1 and C2 cheap cell phones with an adapted software that cna provide agriculture information, educational content, etc. Again, public-private partnerships are crucial to localize content, etc.
Ineveneo analyses standard solutions in the market and does research on how to adapt them to developing countries.
M-Pesa used the GSM mobile network to turn it into a mobile banking network.
Contributions so far:
Hardware: adapted hardware lowering costs or setting up new specific features, etc.
Software: adapting content in local language, new specific needs for specific users, etc.
Content, services: new specific content and services that make full sense indeveloping countries, after analysing their needs, context, etc.
ICT4D research at Telefónica I+D
At Telefónica I+D, instead of developing new hardware or software, the focus is put on behaviour: as technology usage leaves a large trace of data behind, it is possible to perform quantitative analysis with the huge usage databases available. This quantitative analysis will come to complement many other qualitative researches that are often the ones taking place in developing countries.
In the case of Telefónica, 66% of their customers are mobile users in developing countries, thus their research will be a quantitative one and focused in mobile phones.
Telefónica stores data from each and every call, anonymized, encrypted and always with an opt-out option, so they can be used for research but very difficultly for other unfair purposes.
Data are mainly used for two main purposes:
To improve the service, through usage analysis and pattern recognition.
To provide policy recommendations, by combining data on mobile usage with micro- and macro-economic indicators.
There are, of course some limitations: the representativeness of the sample; the kind of usage (work, personal, etc.) of the mobile phone; the importance of plans or prices; the impact in data and pattern recognition of mobile phone sharing (though mobile sharing is not as usual in Latin America as it is in Africa); etc.
Gender and mobile phones project
Goal: to understand gender-related differences in mobile usage.
Data: behavioural variablesw (number of calls, duration, expenses), social variables (degree of the social network, weight of the contacts, frequency of communications), mobility variables (diameter of mobility, diameter of social network).
The characterization of the results showed that, in general, women (in comparison to men) make/get more out/in-coming calls, make the calls longer, expend more, and have a higher out-degree and weight of their social networks.
Causality tests proved to be less conclusive than characterizations, thus why there is a need to gather more data and define better algorithms.
Socio-economic indicators and cellphones
Goal: to understand the relationship between socio-economic indicators and the usage of mobile phones.
Own data are combined with national statistical institutes’ data.
It is possible, for instance, to know where a telephone is operated by asking the communications tower that handles the call. And this can be compared with geographical data that locates people and wealth indices. Now, we can test the relationships between wealth and telephone usage in a specific geographical area (location of usage is made through towers and not data from billing because only 10% of the users are on contract, being the rest of them users of pre-paid SIM cards).
Research question: does education level influence the SMS/voice/MMS behaviour? does socio-economic levels influence levels of usage or expense? etc.
Mobility patterns
By asking the communication towers we can tell where a phone call was made and, hence, how a calling person moved around while using their mobile phone (side note: 90% of people spent most of the time in just two places).
This can be combined and see where the social network of a person is located, what is the area of influence of a specific user, etc.
Research question: what is the impact of government epidemic alerts in the mobility of people? Can we trace through mobile phones whether people are more likely to stay at home if the government says that there is a high risk of contamination of H1N1 Flu?
The “areas of influence” were modelled during each of these three stages and changes of mobility patterns were looked for.
Results show that 80% of the population only reduced their mobility once in stage 2, but not during stage 1 (medical alert). This shows that the medical alert does not work, but that more interventional approaches (closing common infrastructures) does work, though it is also true that there is a side effect of increased mobility of people visiting other infrastructures (e.g. leisure ones).
Another research that related mobility patterns and urban planning showed that people spend much more time in (and move to) places that are along underground lines.
Discussion
Pablo Arribas: what is the influence of education in mobile phone usage and the other way round? A: It is difficult to find causality with the data available (CDR, or call data records), so we should stay at the correlation or relationship levels.
Marije Geldof: how can you trust the data that comes from third parties (i.e. national statistics institutes)? A: Normally these are official data are validated at the international level, methodologies agreed, etc.
Ugo Vallauri: is data shared or available between companies? A: companies are on their way to share it, but not yet.
Christopher Foster: will these data be publicly available? A: protocols are being set up so that researchers can be visitors at Telefónica’s research centres.
Ismael Peña-López: if Telefónica reaches a quasi-monopolistic situation in a given country, could that influence users behaviours and thus “corrupt” the data set? A: yep, perfectly possible.
