Saturday, 19 January 2019

Published papers 2017 to 2019

A few final papers that came out of this project...

More M and Backhouse J (2019). Smart Governance for Inclusive socio-economic transformation in South Africa: Are we there yet? In Bolivar MPR and Munoz LA (Eds.)E-participation in Smart Cities: Technologies and Models of Governance for Citizen Engagement, Public Administration and Information Technology 34, Springer, pp 179–201.

Cohen J., Bancilhon, J-M., Grace T. (2018). Digitally connected living and quality of life: An analysis of the Gauteng City-Region, South Africa. Electronic Journal of Information Systems in Developing Countries 84:e12010

Manda MI and Backhouse J (2018). Inclusive digital transformation in South Africa: an institutional perspective. Proceedings of the 11th Conference on Theory and Practice of Electronic Governance, Galway, Ireland, April 2019 (ICEGOV’18).

Backhouse J and Myataza L (2017). Smart transport systems in SADC countries. Proceedings of the African Conference on Information Systems and Technology, 10-11 July 2017, Cape Town, South Africa. Paper 17.

Manda MI and Backhouse J (2017). Digital transformation for inclusive growth in South Africa: challenges and opportunities in the 4th industrial revolution. Proceedings of the African Conference on Information Systems and Technology, 10-11 July 2017, Cape Town, South Africa. Paper 21.

Thursday, 31 May 2018

Master's students graduate

Two of the Master's students on our project have graduated. Congratulations to Nalukui Malambo and Daniel Mutale.

Both were awarded MCom degrees by research at the graduation on the 27th March 2018.

Nalukui Malambo

Ms Malambo's thesis was titled: "Adoption of Smart City Agendas: Exploring the cases of Cape Town and Nairobi" and was supervised by Prof Judy Backhouse. Ms Malambo has since been appointed as a lecturer in Information Systems at the University of the Witwatersrand.

Daniel Mutale
Mr Mutale's thesis was titled: "Continued use of e-government services: An expectation confirmation theory and trust theory approach" and was supervised by Jean-Marie Bancilhon.

We are all very proud of their results.

Thursday, 19 October 2017

Public Lecture Presentations

Our concluding public lecture on the 27th September was well attended with over 30 people present including several from the City of Johannesburg.

Attendees at the public lecture listen intently to Prof Cohen

Professor Jason Cohen introduced the project and Professor Judy Backhouse set the scene by discussing the various ways in which Smart Cities are defined and how our project had adopted an inclusive definition.

Prof Backhouse defines a Smart City

There were two strong themes that emerged from the project. The first was the ways in which Smart Cities contribute to equality. Prof Cohen shared work which showed that connected people enjoy far better quality of life than those that are not connected. The second theme was the need for trust between government and citizens which emerged from many of our sub-projects. Mr Jean-Marie Bancilhon presented some of these results.

Mr Bancilhon discussing the importance of trust
As an example of the kind of smart application that would lead to smarter cities, Mr Obakeng Matlhoko showcased the AftaRobot transport app intended to improve the experience of mini-bus taxi commuters and improve the management of taxi fleets.

Mr Matlhoko presents AftaRobot
Thanks to all who attended as well as to all who supported our research over the past four years.

The presentations can be downloaded here:
Smart People, Smart Cities

The event was covered by Wits Vuvuzela. Read their story.

Thursday, 14 September 2017

Public Lecture: Smart People, Smart Cities

You are invited to a Public Lecture
Smart People, Smart Cities

Professor Jason Cohen and Professor Judy Backhouse

The Information Systems for Smart Cities in Africa project ran from 2014 to 2016 and investigated the information needs and preferences of residents of Johannesburg and how these needs mapped to the city’s information services.  This public lecture concludes the project, presenting three of the key themes to emerge from the research.

Our research highlighted the need to move the Smart City discourse from technology-focused to resident-focused. Key themes that emerged as specific to our position in South Africa and Africa included how smartness is understood, how smart cities can be inclusive and the importance of trust in developing the Smart City.

Mr. Obakeng Morapeli Matlhoko

As an example of an African Smart City solution, Sowertech will showcase their AftaRobot smart taxi app and discuss the implementation challenges.

Corner Jan Smuts Avenue and Empire Roads
Wednesday the 27th September
5:30pm to 6:30pm
Registration and refreshments from 5:00pm

Monday, 24 July 2017

Conference paper on Smart Transport

The following conference paper was presented at the ACIST 2017 conference in Cape Town recently.

This paper was based on data that student Lizalise Myataza collected during her BCom honours degree. The paper looks at the transport-related mobile apps that have been developed in SADC countries and the extent to which they exhibit "smart" features. We propose a framework for evaluating the "smartness" of apps that goes beyond only evaluating technological features and incorporates the human user.

Backhouse J and Myataza L (2017). Smart transport systems in SADC countries. Proceedings of the African Conference on Information Systems and Technology, 10-11 July 2017, Cape Town, South Africa. Paper 17.

The paper can be downloaded here.

Thursday, 12 January 2017

Published papers 2014 to 2016

Here is a consolidated list of the papers published by this project in the past three years, with links for you to access the papers. We are expecting a few more during 2017 and will post an updated list later in the year.

Cohen, J., Backhouse, J. and Ally, O. (2016). Youth Expectations of Smart City Living: An Importance-Performance Analysis of Young Residents’ Perspectives of City Government,
Commonwealth Youth and Development, 14(1) 118-128. 

Backhouse, J. and Masilela S (2016). Using personas to understand city residents’ information needs and evaluate city information services. Proceedings of the African Cyber Citizenship Conference 2016, 31 Oct- 1 Nov 2016, Port Elizabeth, South Africa. pp.232-242.

Backhouse, J. and Hughes, M. (2015). An ecological model to understand the variety in undergraduate students’ personal information systems, The African Journal of Information and Communication, Issue 15, pp. 14-24.

Topo, M. and Backhouse, J. (2015). Explaining the Use and Non-Use of Smart Cities Services in Johannesburg: Residents' Perspective. Paper presented at the 12th Prato CIRN Conference 9-11 November 2015, Prato, Italy.

Backhouse, J. (2015). Smart city agendas of African cities. Proceedings of the African Conference on Information Systems and Technology (ACIST) 2015, 7-8 July 2015. Accra, Ghana.

Backhouse, J. and Hughes, M. (2015). An ecological model of the information behaviour and technologies of undergraduate students in a South African university. Southern African Computer Lecturer’s Association conference 2015, 1-2 July, Johannesburg, South Africa

Backhouse, J. and Cohen, J. (2014). 'What is a Smart City for Information Systems Research in Africa? Review Protocol and Initial Results', Proceedings of the African Cyber Citizenship Conference 2014, Port Elizabeth, South Africa. ISBN: 978-1-920505-46-3.

Monday, 19 December 2016

Prof Backhouse participates in the DBSA Urban Safety Dialogue

Prof Judy Backhouse was invited to be a panelist at the Development Bank of South Africa's recent Infrastructure Dialogue on Urban Safety. This Dialogue, held on the 16th November, was subtitled: Safety in our public spaces: Can infrastructural or technological interventions save us, and in what balance?

Students Nalukui Malambo, Lizalise Myataza, Letlotlo Kothane and Bonolo Motsepe joined the discussion and took the opportunity to share information about their research during the round-table discussions. 

Below is the text of Prof Backhouse's input to the panel discussion:

Critical perspectives on the pros and cons of technology as a solution to safety in public spaces

At Wits I have been running a project titled “Information Systems for Smart Cities in Africa” for the past three years.  I've been asked to consider the questions: Can smart city projects provide a city or regional solution to address development and infrastructure problems? Or is Smart City a catchy buzzword used for corporate profit-making with limited benefits for government and the public? My answer to both these questions is a typically South African: yes, and no.

Now it is very cruel to ask an academic to speak for ten minutes. What I want to do in this very short time, is to introduce you to two analytical devices or frames for thinking about these questions. The first is helpful in trying to understand what a smart city is and the second is useful for understanding different information systems that could help in solving city problems.

So, let's start with the question: What is a Smart City? We found that no-one really agrees. But we were able to identify two different kinds of understandings and an easy way to think about them is in terms of definitions of the word smart.

Some definitions of Smart include: “polished, fashionable, indicative of wealth”, “clean, tidy and well-dressed” or “fashionable and upmarket”. So we find that for some the idea of a smart city is a city that is wealthy, successful, clean and with good infrastructure, or modern. With this understanding of a Smart City comes a focus on supporting business (often high-tech and international business), attracting talent to work in those businesses, and improving infrastructure.

Other definitions of the term Smart are: “having quick-witted intelligence” or a device that is “programmed so as to be capable of some independent action”. Such definitions of smart lead to an understanding of smart cities as places where intelligence (both human and machine) is applied to solve city problems. Projects that support research to better understand city problems and the application of technologies in collecting and analysing data to inform solutions emerge from this sense of a smart city. 

So we have these two understandings: one about appearance and wealth and the other about intelligence and understanding. Try to guess which one I favour.

One of the problems with a lot of smart city projects is that they are exclusionary. My colleague Ms Malambo spent time in Nairobi looking at the Khonza City development that is taking place there. This is an initiative to build new cities, on the outskirts of Nairobi, that are intended to be smart cities. These cities are designed with good infrastructure and services, and are promoted as places that are safe, clean and better than Nairobi itself. They clearly target highly-skilled individuals and international business. While there is some benefit for the poor and small or informal businesses in servicing these projects, their needs are not being considered directly. These projects are driven by large international construction and information technology companies and serve their interests. This kind of approach to smart cities is likely to lead to increasing inequality and divert resources away from projects with more equitable goals. 

But if we consider the second understanding of smart city as the application of intelligence to better understanding and solving city problems, we find that information technologies do offer interesting possibilities for addressing the problems of rapid urbanisation.

Now the problem we are particularly interested in today is that of urban safety.

There are many ways that we can apply intelligence (both human and machine) to improve urban safety. Technology enables us to collect information about crime, about how people behave. We can observe what is happening using a range of different kinds of data – visual, audio, and indirect (for example, what phone calls someone makes or the tracking data that results from someone carrying a cellphone or wearing a bracelet). We can collect enormous quantities of data and store it, have special analytical tools that enable us to delve into this data and find patterns in it that increase our understanding. Note that these technology solutions have to be used in conjunction with human intelligence to design, operate and interpret the information that results and to assign meaning and decide on actions that result. 

At this point I want to introduce the second analytical device for our discussion. Recall that the first was the distinction between two ways of looking at smart cities. This second is about two kinds of technology solutions. We have central, top-down technology solutions that are centrally implemented and controlled and we have diffuse, bottom-up technology solutions that are devised and implemented by a range of different stakeholders.

So, for example, we know that safety in public places depends on there being other people around to observe activities. Technology offers us new kinds of “eyes” in the form of  surveillance technologies that have been deployed to increase safety. One example is CCTV cameras that are installed in public spaces. These may be a good idea, but at the moment research into whether these technologies actually reduce crime is inconclusive. Some studies show that crime decreases, in some specific locations like parking lots, but not in city centres (Welsh and Farrington, 2009) others show no change and some even report increases in crime as people feel more secure and take fewer precautions or because crime is displaced to areas that are not monitored (Cerezo, 2013). But these technology solutions depend on people to be effective, so for example one study shows that surveillance systems reduced crime only when there were also effective enforcement activities (Piza, Caplan and Kennedy, 2014). In addition, it is often difficult to conclusively attribute changes in crime levels to the surveillance tools. 

Surveillance cameras are an example of what researchers call a top-down or centralised information system. That is an information system that is designed and run by a central authority, for the benefits of others. But technology also provides bottom-up or decentralised solutions, in which more people participate and shape what the information system is and does.

On this side of the spectrum are apps that help individuals take care of their safety by allowing their friends and family to track their whereabouts and receive emergency signals should the individual feel in danger. The Android apps Personal Safety Panic Alarm and bSafe are examples. The first has been downloaded 50 000 times and the latter 500 000 times and research shows that they give people a greater sense of safety. Such apps are examples of bottom-up approaches to security, where the "eyes" are friends and family members, although in one study of mobile safety apps (in Ireland), people said they would be happy to have police monitor their safety apps, despite privacy concerns (McCarthy, Caulfield and O'Mahoney, 2016). 

Even without apps, people use their cellphones to increase their safety by telling a friend where they are going and asking for a call if they have not checked in by an agreed time. These individual uses of information technology are informal information systems and are also important features of a Smart City.

Bottom-up solutions are designed by a wide range of stakeholders, including residents and small businesses, and so they bring more brains (and other resources) to bear on the problem; they may also make people feel empowered, be more effective and cheaper to implement than top-down solutions, but research in these areas is lacking, so we don't know for sure.

A smart city that wants to make use of bottom-up smart solutions would enable it's residents to be smart by enabling their use of technology. People own cellphones, but they need the skills to use them, and they need to have access to networks in order to be able to use safety solutions or to invent their own. Smart cities in Africa face the problem of getting people connected before they can make use of bottom-up solutions.   

So, I have given you two analytical devices for thinking about smart cities and their possible contribution to urban safety. First to distinguish between a smart city as wealthy and posh or as intelligently seeking understanding. There I unashamedly favour the latter. Second to think about solutions in terms of top-down and bottom-up. Here I favour both, since both have their uses. 

I want to end with three questions for discussion:

  1.  How do we ensure that whatever technology solutions we introduce, the interests that are served are inclusive and not elite?
  2. What are the challenges in deploying effective central, top-down technology solutions for urban safety?
  3.  Can we make better use of distributed, bottom-up systems designed by more stakeholders?

Cerezo A. (2013). CCTV and Crime Displacement: A Quasi-experimental Evaluation. European Journal of Criminology, 10(2), 222–236.
McCarthy O.T., Caulfield B. and O'Mahoney M. (2016). How transport users perceive personal safety apps. Transportation research part F: Traffic psychology and behaviour, 43, 166–182.

Piza E.L., Caplan J.M. and Kennedy L.W. (2014). Analyzing the Influence of Micro-level Factors on CCTV Camera Effect. Journal of Quantitative Criminology, 30(2), 237-264.

Welsh B.C. and Farrington D.P. (2009) Public Area CCTV and Crime RPevention: An Updated Systematic Review and Meta-Analysis. Justice Quarterly, 26(4).