Are Digital Labour Platforms like Uber Significantly Different from the Traditional Taxi Industry?

To respond to this question, I will use three main characteristics to highlight the differences and similarities between the traditional taxi industry and the ride-hailing platform industry in Lagos, particularly regarding drivers’ experiences.[1]

Vehicle Access

Access to taxis such as the Yellow taxis between the 1990s to 2007, was mainly done in-person.  Throughout the city, yellow taxis had designated car parks where each driver had to write down their name on a roster and wait in their vehicles for passengers. For drivers, picking up trips was on a turn-by-turn basis. A passenger walks into the park, identifies a destination of choice, and the driver will state the cost of the journey, usually a little higher than the going rate. For example, a passenger requesting to be taken to Victoria Island, a prominent Central Business District in Lagos, from Victoria Garden City, which is about 20km away. The driver could quote a fee of N10,000 (£18), and the passenger would refute this amount and haggle the price down to an affordable rate of about N4,000 (£7). In certain instances, drivers can get away with this, especially for passengers who are not familiar with the route. In speaking to traditional taxi drivers, they highlight this as a critical strategy for surpassing their daily and weekly targets. However, when a driver refuses to accept a reduced price by a passenger, the job could fall to the next willing driver in the queue.

For ride-hailing platforms such as Uber, which emerged in Nigeria in 2014, accessing the vehicle was done simply via the platform app.[2] The platform app acts as an intermediary between passengers and drivers, removing the need to hail a vehicle, haggle for prices, and track trips. The only resource required is the smartphone, which algorithmically matches passengers’ demand and drivers’ supply. For example, if passenger A requests a trip via the app, the algorithm will sort for the nearest available driver, usually within 2km, and the driver is expected to accept. Sometimes, the driver may cancel the request due to traffic, low fares, or other unforeseen circumstances.

With ride-hailing platforms like Uber, the cost of the trip was often cheaper than traditional taxis, which quickly made it more accessible and popular amongst users.

Networks of Solidarity

Traditional taxi parks were coordinated by unions such as the Road Transport Employers Association (RTEAN), Lagos State Taxi Drivers and Cab Operators (LSTDCOA) and so forth.[3] Drivers are meant to belong to at least one union to access taxi parks as well as pay monthly dues to union executives. Without being part of a faction, drivers often have to ply the road to be accessed by passengers. This would usually mean drivers are operating illegally, according to an interview with the former transport policymaker Mustapha in December 2018.  The dues collected from drivers often do not trickle down to supporting the affairs of drivers in terms of the provision of social security and safety nets.[4] However, the drivers who are part of unions and designated taxi parks undergo monthly meetings with the scope of supporting each other, lobbying for improved recognition from the State and for social protection provisions for taxi drivers.

Ride-hailing platforms entirely dismantle the need for unions and networks of socialisation or solidarity. Being classified as independent contractors or driver-partners, the business model embodies working isolation, such that drivers are typically not attached to traditional unions or taxi parks. Drivers are not required to pay monthly dues because their contributions are institutionalised via the app as commissions per trip. For example, Uber takes 25% of commission after every trip. However, the isolating nature of ride-hailing platform work has led to virtual communities such as social media and communication networks (e.g., Facebook and WhatsApp groups), facilitating collective learning about their work and resistance strategies against algorithmic control. It has further boosted the formation of collective worker groups, associations, and platform unions, and is reducing work isolation and helping the demand for decent working conditions for all drivers.

Payment and Ownership Models

The traditional taxi industry in Lagos operated mainly on three ownership models. One is the hire-purchase model, where an individual purchases a vehicle, does the necessary paperwork and employs a driver who pays to own the vehicle ultimately. The second is the lease or rental model, where drivers pay weekly sums to rent the vehicle, which was not common in the traditional taxi industry. Thirdly, outright ownership, i.e., drivers who bought their vehicles without any financial arrangements with third parties.

In the traditional taxi industry, all three ownership models were common and to some extent facilitated by the Lagos State Government. Taxis were acquired from the Lagos State government and corporate entities. For example, between 2009 to 2015, the former governor of Lagos State, Babajide Tunde Fashola, facilitated jobs for over 1000 drivers with fleets of taxis using funds from the Union Bank of Nigeria and the Lagos-Microfinance Scheme.[5]Drivers are given these vehicles and expected to pay weekly sums to own it after three to four years. Based on the economy between the 1990s to early 2000s, there is no accurate account of how much drivers were meant to remit to vehicle owners. However, based on interviews, there was an agreed weekly remittance to vehicle owners. There were no social media platforms to advertise such opportunities. It was based on trust and, in rare instances, advertisements in newspapers. Trust was only built on a track record of meeting weekly targets with little or no complaints. However, it was not transparent for vehicle owners to see how much drivers made. Vehicle owners manually managed taxis, with guarantors serving as a medium of transparency and accountability, but not enough to facilitate trust. One interviewee (2019), Taiwo (61), an elderly taxi driver, highlighted that taxi drivers made over N30,000 (£52) after costs with only a few daily trips. Taxi drivers did not have to work incessantly to make ends meet. Vehicle owners had to believe the narratives of what drivers were making weekly to negotiate weekly payments. Considering most traditional taxi drivers were under taxi unions, it was easier to collectively agree not to disclose the accurate sum of drivers’ weekly earnings.

While ride-hailing platforms embodied similar ownership models, the labour process was more quantifiable due to data and algorithmic functionalities. For instance, the dashboard on ride-hailing platform interfaces shows detailed breakdown of drivers hourly, weekly and monthly activities which boosts transparency for vehicle owners which can lead to overworking, i.e., working longer hours than expected compared to traditional taxi drivers. From interviews in this study, platform drivers noted the need for their colleagues not to post dashboards showing weekly earnings, because this gives vehicle owners and rental companies more negotiating power to demand higher weekly remunerations. It also facilitated a complicated subcontracting arrangement between drivers and the actual vehicle owner which can be classified as a third-party or proxy ownership. The vehicle owner puts an experienced driver or a non-driver in charge of a fleet of vehicles, with drivers having to make payments via the proxy.[6]  For example, speaking with Ewoma, a legal practitioner, highlighted how the payment structure and works. Ewoma. managed at least 13 Uber/Bolt drivers, where they had to pay N35,000 (£61) weekly to her, and she pays N30,000 (£52) to the vehicle owner and keeps N5000 as the management fee. Within the drivers she managed, she highlighted one driver who also managed two other drivers, which facilitated more precarious pathways in making payments towards vehicle usage or ownership.


I will conclude by noting that while ride-hailing platforms appear to be rather different from the traditional taxi industry of Lagos, they have created new problems and not wholly solved old challenges in the taxi industry. While there are more factors elsewhere that show the differences between platforms and traditional taxis, this blog has only intricately discussed three as summarised in Table 1.

Table 1: The Difference between Traditional Taxis and Ride-hailing Platform Gig Work

  FactorsGig Work in Lagos
Vehicle AccessPassenger access is by hailing a cab or receiving callsA push of a button on a smartphone; trips are assigned based on ratings and as a function of demand and supply
Fare calculation is based on the driver’s discretion or haggling, and payment is often in cashCalculated automatically by algorithms and paid in cash or via the app
Networks of SolidarityUnion dues monthly payment and meetingsNot mandatory for platform drivers.
Union or association membership to boost collective bargaining.Working in isolation due to independent contracts.
Union dues monthly payment and meetingsNot compulsory for drivers.
Assigned to motor parksNo assignment of parks
Managing the labour process outside a taxi park is based on the driver’s discretion and knowledge of the cityAlgorithmically managed with integrated maps and GPS tracking
Payment and Ownership ModelsOwnership models especially hire-purchase and leasing models were straightforward for drivers.Payment and ownership models became transparent but more complicated for drivers.

For instance, the hope that technology and information will improve the insecurity and lack of safety has not happened. Platform drivers are now exposed to higher levels of kidnapping, robbery, assault, and death.[7] This is inherent in the fact that taxi driving, whether online or offline, is risky. Platform drivers still choose to work offline to game the system and improve their earnings, thereby exposing them to similar risks as traditional taxi drivers. Drivers are working more now than 10 to 15 years ago because of more information and avenues for vehicle owners and platform companies to track working behaviours. This does not indicate that platforms earn significantly higher than their counterparts, considering that they often offer cheap fares as a competitive strategy. It indicates that ride-hailing platforms are a different kind of traditional taxis only because of the advantage of technology. While some differences are external to the socio-technical system of platforms as highlighted, the experiences of drivers are often similar. Therefore, the question for the future will be, how can digital labour platforms be significantly better than traditional taxis?

[1] Most of the Insights in this blog draws from my fieldwork between 2018 to 2019, and my PhD thesis.

[2] This was the day Uber arrived in Lagos, Nigeria.

[3] Albert, I. O. (2007). NURTW and the Politics of Motor Parks in Lagos and Ibadan. In L. Fourchard (Ed.), Gouverner les villes d’Afrique. Etat, gouvernement local et acteurs privés. Paris: Karthala.

[4] Agbiboa, D.E. (2017). Mobile Bodies of Meaning: City Life and the Horizons of Possibility. Journal of Modern African Studies, 55(3), pp.371–393.

[5] Nairaland (2009) Fashola Commissions 1,200 Cabs. Pictures – Politics – Nigeria, Available at:  

[6] Interview with Ewoma in July 2019. Ewoma still did this side-gig until 2022, because it was profitable for her. Many of the vehicle owners, were too busy to manage the affairs of drivers.

[7] Fairwork (2022): Working in the Nigerian Ride-hailing Sector: Fairwork Ratings 2021/22. Oxford and Berlin.


Latest Digital Development Outputs (China, Platforms, Transformation, Water) from CDD, Manchester

Image by <a href="">Gerd Altmann</a> from <a href="">Pixabay</a>Recent outputs – on China digital; Digital platforms; Digital transformation; Digital water – from Centre for Digital Development researchers, University of Manchester:


China’s Digital Expansion in the Global South: Systematic Literature Review and Future Research Agenda” by Richard Heeks, Angelica V Ospina, Christopher Foster, Ping Gao, Xia Han, Nicholas Jepson, Seth Schindler & Qingna Zhou, identifies from a review of literature what is already known about China’s digital expansion in the global South and, from this, outlines a future research agenda.

The Effects of R&D and its Different Types on Firm Productivity: Evidence from China” by Yuanyuan Guo, Ping Gao & Daojin Cheng, estimates the effects of R&D and its different types, including research activity and development activity, on productivity using panel data consisting of 1,808 Chinese listed manufacturing firms from the period 2006-2015. Our empirical evidence implies that firms need to optimize the composition of R&D expenditure in order to realize sustained productivity growth.


Gaming the System: Tactical Workarounds and the Production of Antagonistic Subjectivities among Migrant Platform Workers in Italy” (open access) by Gianluca Iazzolino & Amarilli Varesio, examines how migrant food delivery couriers in Italy react to and hijack gamification techniques designed to increase productivity and control. It describes the sharing of accounts among workers and recasts “gaming the system” as a form of everyday resistance.

Gendered Implications of the Waves of COVID-19 and Economic Upgrading Trajectories in Digital Value Chains: Insights from Kenyan Agro-Platforms” (open access) by Aarti Krishnan, Monica Nganga & Tim Foster, attempts to unpack economic upgrading through the different regimes of COVID-19, illustrating the dynamic effects experienced by women living through the shock.


Organisations Lead Digital Transformation for Development: So What?” (blog) by Jaco Renken argues that organisations sit at the heart of Digital Transformation for Development (DX4D) in practice, and a better understanding of their role – their visions, the requisite competencies and the processes they follow – should be included in a future DX4D research agenda.

Technology for Resilience amid COVID-19 Pandemic: Narratives from Small Business Owners in Kenya“ (open access version available) by Joshua Rumo, Leah Mutanu & Christopher Foster, explores claims around transformative digital technology adoption by firms during the pandemic. Using research amongst Kenyan SMEs, the reality of technology adoption involved “frugal innovations” and adaptation for resilience and survival.


Smartening Up: User Experience with Smart Water Metering Infrastructure in an African City” (open access) by Godfred Amankwaa, Richard Heeks & Alison Browne, finds that smart water metering in one African city has been characterised by an incremental and utility-centric approach.

Five Principles for Collective Digital Sovereignty

Photo by Ari He on UnsplashWhat would it mean for digital sovereignty to be collective, rather than individual or national?

Digital sovereignty has been growing as a narrative, arising from the perception of a lack of control over the data, the value, the trajectories, etc of digital systems.  The narrative has principally operated at two levels: the national and the individual[1].  National digital sovereignty looks to secure political and/or economic control for governments.  Individual digital sovereignty seeks to secure control, particularly over data, for individuals.

But there has been a missing middle with very little discussion of collective digital sovereignty[2], defined here as the ability of a group or community to exercise control over its digital environment, including the infrastructure, data, and platforms that are used within it.

Fractions of this can be found, especially if we conceive the collective as a low-income community in which the value of digital data, devices and infrastructure is extracted to the benefit of large corporations and/or the state.  Hence, ideas such as community wireless networks[3] or community data trusts[4].  Putting these and other ideas for the missing middle[5] together, five principles of collective digital sovereignty can be created:

  1. Infrastructure: technology infrastructure is, as far as possible, based around open systems and standards, and owned, deployed and maintained by the collective
  2. Data: a collective data governance model is applied that controls who accesses and who benefits from data generated by those within the collective
  3. Capabilities: digital skills and knowledge are developed within the collective, enabling not just use of the technology but also understanding of the structural context of the technology
  4. Platforms: the apps and platforms that structure economic and social interaction are, as far as possible, based on open software, developed participatively, and owned and managed collectively
  5. Advocacy: the collective will advocate for higher-level discourse and policies and regulations that support the other principles of collective digital sovereignty

[1] Pohle, J., & Thiel, T. (2020) Digital sovereignty, Internet Policy Review, 9(4)

[2] MTST (2023) Homeless Worker Movement in Brazil and the Struggle for Digital Sovereignty, Movimento dos Trabalhadores Sem Teto, Sao Paulo

[3] Keysar, H., Luning, E.C. & Untiedig, A. (2022) Prototypes as agents of transition: the case of DIY wireless technology for advancing community digital sovereignty, Journal of Peer Production, 15

[4] Singh, P.J. (2019) Data and Digital Intelligence Commons (Making a Case for their Community Ownership), Data Governance Network

[5] AdB (2017) Barcelona City Council Technological Sovereignty Guide, Ajuntament de Barcelona, Barcelona; Ricaurte, P. & Grohmann, R. (2021) Data sovereignty and alternative development models, Bot Populi, 22 Oct; MTST (ibid.);

Organisations Lead Digital Transformation for Development: So What?

Interest in digital transformation is growing globally, including developing countries which seek socio-economic advancement. Earlier we have briefly defined digital transformation for Development (DX4D) as radical structural and process changes in development, enabled by digital systems. We have argued that with DX4D, vision matters – a clear vision is required to intentionally deploy digital systems for development purposes – and that with DX4D, visions differ – digital systems and technologies can enable different development outcomes.

But whose vision? Who leads those digital transformations? It is the central argument of this post that, irrespective of different visions of development, it is development sector stakeholder organisations that lead DX4D. Consider the examples tabulated below:

Digital . . .?Transformation?Development?
Financial Services (SDG 8) Fintech (e.g. M-Pesa)  Domination of financial institution-centred models (i.e. banks) disrupted by digitally-enabled peer-to-peer and micro payment models (e.g. mobile money).Financial inclusion of previously excluded poor and marginalised. Well-established direct positive correlation with human development[1].
Labour (SDG 8) Digital labour platforms (e.g. UpWork)  Disruption and transformation of the forms of employment (e.g. micro work, online work, digital work on demand)[2].Positive livelihood outcomes, but also many negative outcomes and contestations for developing country workers[3].
Healthcare (SDG 3) Health data integration platforms (e.g. DHIS2)  Integration of data silos thereby transforming healthcare provision and medical recordkeeping.  Step-change in the effectiveness and reach of healthcare services, including disease surveillance, immunisation campaigns, primary healthcare, cancer tracking, reproductive health, etc.[4]
Education (SDG 4) Digital learning platforms (e.g. Moodle)  Empowering of teachers, transformation of pedagogic processes and structures.Improved access to and quality of learning, leading to positive livelihood outcomes[5].

In each of these DX4D instances, there is a single organisation, or conglomerate of collaborators, that espoused the vision and took the lead:

  • M-Pesa, as a fintech platform, was developed and continues to be operated by private sector organisations Vodafone and Safaricom in Kenya. The platform operates in seven African countries, has more than 50 million users, and reached almost 20 billion transactions by the financial year ending 31 March 2022[6].
  • Upwork, as a freelancing platform, was developed jointly by private sector organisations Elance and oDesk from the USA – a newly formed entity continues to operate the platform. Through the platform, clients and freelancers from over 180 countries (a large share from the global south) interact[7].
  • DHIS2, as an open source health information system platform, was developed through global collaboration led by the HISP Centre at the University of Oslo, but national ministries of health (in more than 75 developing countries) are the organisations that actually implement and use the system[4].
  • Moodle, as a learning management platform, continues to be developed by many open source contributors around the world, but it is organisations, such as schools, universities, businesses and government departments, that adopt and incorporate the system into their operations – 6 of the top 10 countries where Moodle is used the most, are developing countries, representing 48% of the sites across the top 10[8].

From these illustrative examples we can observe how central the role of organisations is to DX4D. In some instances (e.g. M-Pesa and Upwork), it is the same organisation that came up with a vision, went on to develop the digital system, and continues to lead the operation – the developers are therefore directly responsible for leading the transformation. In other instances (e.g. DHIS2 and Moodle), the developers of digital systems differ from the adopters or implementors thereof – the visions of the former are therefore contextualised by the latter, who then take direct responsibility for leading the transformation. Organisations are therefore the structural vehicle for undertaking DX4D.

So, organisations have a pivotal role to play in DX4D, but so what? Recognition of the centrality of organisations in DX4D has at least three implications:

  1. From an organisational perspective, it emphasises the need for those who engage in DX4D to have a clear vision about the desired development outcome, as well as a sufficient change management strategy to pursue the desired transformations.
  2. From a digital systems perspective, organisations require adequate technical competencies to implement new digital systems, as well as a good understanding of how digital systems interact, and disrupt, prevailing structures and processes that relate to development outcomes.
  3. From a development perspective, organisations that lead DX4D must be aware of, and competent to engage with, the political economy in which such initiatives are embedded. For example, the disruptions caused by digital labour platforms have resulted in many unanticipated negative consequences, such as exploitation of gig workers. This gave rise to projects like Fairwork, which advocate gig worker rights, thereby exerting pressure on platform organisations to adjust their ways.

As we pursue a better understanding of DX4D, the illustrations and arguments outlined above prompt at least one action. Organisations sit at the heart of DX4D in practice, and a better understanding of their role – their visions, the requisite competencies and the processes they follow – should be included on a future DX4D research agenda.

It is surprising to discover how little research is available to help development organisations with the knowledge and competencies they need to succeed with DX4D. It is also unthinkable to separate research on the transformational and development outcomes of DX4D without accounting for the role of the organisation.

While this post cannot answer the ‘so what?’ comprehensively, it is hoped that both researchers and development practitioners might develop a stronger sense of the importance and urgency of better understanding the organisational implications of DX4D.


[1] Sarma, M., & Pais, J. (2011). Financial inclusion and development. Journal of International Development, 23(5), 613-628. Available:

[2] International Labour Organisation (2021) World Employment and Social Outlook: The role of digital labour platforms in transforming the world of work. Available:—dgreports/—dcomm/—publ/documents/publication/wcms_771749.pdf (Access: 13-03-2-23).

[3] Graham, M., Hjorth, I., & Lehdonvirta, V. (2017). Digital labour and development: impacts of global digital labour platforms and the gig economy on worker livelihoods. Transfer: European Review of Labour and Research23(2), 135-162. Available:

[4] DHIS2 In Action. Available:

[5] Is technology key to improving global health and education, or just an expensive distraction? Available:

[6] M-Pesa customer numbers from 2017 to 2022. Available:

[7] 60+ Top Upwork Statistics in 2023: Clients, Revenue & More. Available:

[8] Moodle Statistics. Available:

Lessons for Other Countries from China’s Crackdown on Big Tech

What can low- and middle-income countries learn from China’s recent approach to regulation of big tech?

What Happened?

China’s digital economy can be categorised into three phases[1]: a more open phase starting in the 20th century that encouraged foreign investment and collaboration; a focus on state support to build national and then global digital champions; and most-recently some degree of state backlash against the monsters it had helped create.

The straw that broke the camel’s back and made the third phase explicit was a speech by Jack Ma, founder of Alibaba, on 24th Oct 2020 critical of recent attempts at financial regulation by agencies of the Chinese state.  However, plans for tighter regulation of big tech in China had been underway since 2018, and actions on the wider digital economy such as fintech lenders had begun even earlier.[2]  Call it “crackdown” or “rectification”, the Chinese state introduced during 2020 and, especially, 2021 a series of measures that ran alongside a new narrative asserting that action was required in the digital economy in order to “limit the disorderly expansion of capital” and to deliver “common prosperity”.[3]

There were new financial rules, ensuring large fintech firms had much greater funds to cover the loans they were making, and banning edtech firms from accepting foreign investment and, effectively, preventing them from making a profit.  Anti-monopoly guidelines included new legal rules on assets intended to force break-ups and sell-offs, and to open up e-commerce marketplaces for smaller enterprises.

Tighter data rules arose with both the Data Security Law and Personal Information Protection Law coming into effect during 2021 and being used to provide greater state oversight over localisation, export and privacy of data held by big tech. As part of this, more than 100 firms were investigated for claimed illegal collection of data.

Redistributive regulations encouraged or forced redistribution of big tech profits to workers or to other pro-equality projects.  Other actions included restrictions on the number of hours per week minors could spend gaming, bans on cryptocurrency, and tax investigation of online influencers.

What was the Impact?

Overt effects noted so far of the increased regulation have been manifold[4].

Direct impacts have included some delinking from foreign investment with, for example, the suspension of Ant Group’s and ByteDance’s US IPOs.  There has been a substantial loss in market value of China’s big tech firms – hundreds of billions of US dollars-worth of share price losses; particularly hitting foreign investors which, in turn, has led to a significant decrease in foreign investment in China’s digital economy. More specific direct impacts include Didi being blocked from adding new users and having its app removed from app stores; Meituan being made to raise wages and provide insurance for its workers, and Ant Group and others having to share data with public agencies.

Regulatory pressures have encouraged the break-up of big tech firms or their withdrawal from certain investments, the most recent being Alibaba’s March 2023 announcement of its separation into six different business units. While adhering to anti-monopoly rules and signalling a lack of intent to empire-build, these partitions have also hampered firms given “that a crucial aspect of the business model adopted by these tech giants is building an integrated ecosystem involving multiple complementary industries”[5]. Local investment in the digital economy has been reduced, with estimates of more than 200,000 job losses in internet companies in the nine months from mid-2021 to spring 2022, alongside less concrete or quantifiable outcomes in relation to reduced levels of digital innovation.

Other impacts were more notable for their symbolism: the heads of tech firms including Alibaba, Pinduoduo, ByteDance, Meituan and Didi stepping down and/or disappearing from public sight; huge, billion-dollar donations by tech firms to “common prosperity” funds and other philanthropic endeavours; fines costing hundreds of millions or even billions of dollars for many tech firms including Baidu, Alibaba, Tencent, Meituan, ByteDance and Didi for abuse of monopoly or breach of data regulations.

What’s so far unclear is whether the measures taken against big tech have reduced any of the four big inequalities in China: high concentration ratios and monopolies in key digital markets; income/wealth inequalities between rich and poor; geographical inequalities between regions and between urban and rural; distributive inequalities between capital and labour.  Recent papers[6] discuss the relation of digital to common prosperity but so far only show the potential for digitally-enabled reduction in geographical inequalities on the basis of historical data.

Given that a number of the listed impacts have not been in the national interest, some roll-back occurred from 2022 onwards[7]. Early in 2022 there were some more positive statements from government officials about the value of the platform economy, then more explicit support in May for tech firms seeking domestic and overseas listings. By 2023, Didi was allowed to register new users, new licences for gaming firms were being issued, Jack Ma reappeared in mainland China, and officials were explicitly reassuring tech firms about some easing of the earlier regulatory tightening; albeit making clear there would be no return to the pre-2020 situation.

Why did it Happen?

For sure, there may have been economic concerns at the highest levels of the Communist Party about financial instability and economic inequality, but the core rationale for the measures comes down to one word: control.

This came particularly with the run-up to the 20th Party Congress in 2022 that gave Xi Jinping an unprecedented third term, but more generally as part of Xi Jinping’s steady reversal since 2012 of the relatively decentralised and distributed model of power that had existed since the time of Deng Xiaoping[8].  Three different domains of centralisation of control can be identified[9].

Social control: seeking to maintain the legitimacy of the Party by giving at least the appearance, during a period of Covid disruption and slowing growth, of addressing social issues like inequality, digital exclusion, platform lock-in of consumers and small sellers, resentment of middle-class parents paying edtech platforms for education the state did not provide, and social ills like gaming addiction.  Alongside this, alternative, critical narratives were silenced with, for example, initial action against Jack Ma and Ant Group making clear that public dissent against Party policies would not be tolerated.

Economic control: growth of the private sector and the shrinking role of state-owned or -affiliated enterprises within the overall economy has left the state with fewer direct levers of economic control.  The state has thus taken direct stakes in a number of big tech firms and through this and other means, placed party members onto company boards in order to have a measure of direct control.  The financial and other measures have sought to stabilise and control markets.  Alongside this, the measures have sought to reduce the extent of foreign economic control over Chinese big tech, even where there are foreign investors.  They have also sought to help shift resources both within and between tech firms from digital activities with lower national priority (such as e-commerce and social media) to those with higher national priority (such as AI, chip production and quantum computing).

Political control: growth, profile and political connections of big tech leaders and firms in China had made them into new loci of power; something seen as a directly challenge to the Party.  In general, all of the regulatory actions were an assertion of state control over big tech, especially as data – named as a factor of production since April 2020 and a growing source of power – is now being harvested and analysed in huge quantities within these firms.  In parallel, there were even-more covert objectives with action against Ant Group seeking to deny windfall profits that political rivals of Xi Jinping would have gained had the company been listed overseas.  Punitive actions against Didi after it proceeded with an overseas IPO against state wishes also sent a symbolic message about who was in charge.

What are the Lessons?

China is a global digital superpower with unique features including the power and capacity of the state, the size of the national digital economy, and the size and reach of its digital firms.  So the idea that global South governments might replicate what China has done does not make sense.

However, a few lessons can be drawn.

1. Politics Trumps Economics in Policy-Making.  China’s recent policies have damaged its digital multinationals and its digital economy.  But digital policy has been made – as policy often is – for political much more than economic reasons.  Digital policy advice and digital policy research needs to recognise the primacy of politics.

2. Policy Responsiveness is Good; Policy Uncertainty is Bad.  Likely recognising that it had gone too far, the Chinese state reversed direction a bit from 2022.  Changing policy direction in response to the negative impacts of policy is highly recommended.  What is not recommended is the uncertainty created by what can be perceived as two significant changes in direction in three years including a partial backtrack.  That uncertainty is heightened when policy-making is highly-centralised and without transparency.

3. Policy Structures Matter.  Digital policy advice and analysis focuses a lot on the content of policy but much less on policy structures.  China’s experience shows how structures matter[10].  It is not a specific feature of recent policy but China’s digital policy is fragmented across a large number of agencies. This has been partly organic as digital constantly raises new issues that different traditional agencies may try to deal with but which also encourage formation of new agencies.  It has also been partly deliberate to avoid creating a single state agency powerbase for digital policy that could challenge central authority.  But this complicates policy-making and raises the likelihood of policy contradictions that harm the digital economy with, for instance, mixed messages having been given by different agencies during the clampdown.  Likewise, heavy centralisation of policy can give a strong sense of direction if chosen correctly, but it may also amplify policy errors and lead to policy inertia if all decisions have to run through a central point.  Whatever the rights and wrongs, it means that policy needs to be built on appropriate structures as much as appropriate content.

4. Targeted Regulation Works Better than Blanket Regulation.  China’s recent policy initiatives have been somewhat targeted[11].  For example, while cracking down on e-commerce or data issues within the BAT big three of Baidu, Alibaba and Tencent, there has been “little regulatory interference” and, indeed, state support for these companies’ work on the “deep tech” priorities of the state such as AI and high-end chip production.  That differentiated approach to digital policy has helped more than an indiscriminate crackdown would have.

[1] To, Y. (2023) Friends and foes: rethinking the party and Chinese big techNew Political Economy, 28(2), 299-314

[2] Creemers, R. (2023) The Great Rectification: A New Paradigm for China’s Online Platform Economy. Available at SSRN

[3] Economist (2021) China’s government is cracking down on fintech. What does it want?, Economist, 13 Mar; Economist (2021) China’s rulers want more control of big tech, Economist, 8 Apr; Economist (2021) Didi’s removal from China’s app stores marks a growing crackdown, Economist, 5 Jul; Poswal, V. (2022) Xi Jinping’s Crackdown on Big Tech-CompaniesInternational Journal of Multidisciplinary Educational Research, 11(5), 67-70; Wu, Y. (2022) Understanding China’s Digital Economy: Policies, Opportunities, and Challenges, China Briefing, 11 Aug; Collier, A. (2022) China’s Technology War: Why Beijing Took Down Its Tech Giants. Springer Nature; Creemers (2023)

[4] Economist (2021, 8 Apr); Economist (2021, 5 Jul); Pathak, S. (2021) China’s Tech Crackdown: Why Now. Science, Technology and Security Forum, Manipal University, Karnataka; Poswal (2022); Sun, X. (2022) Decoding China’s” Common Prosperity” Drive, LSE Ideas, April; Collier (2022); Interesse, G. (2023) Is China’s ‘Tech Crackdown’ Over? Our 2023 Regulatory Outlook for the Sector, China Briefing, 22 Feb; Economist (2023) Alibaba breaks itself up in six, Economist, 30 Mar

[5] Sun (2022)

[6] E.g. Jiechang, X., & Cheng, L. (2022) Empowerment of Common Prosperity through Digital Economy: Pathways and Policy Design. China Economic Transition5(1), 41-61; Zhao, T., Jiao, F., & Wang, Z. (2023) Digital economy, entrepreneurial activity, and common prosperity: Evidence from China. Journal of Information Economics1(1), 59-71

[7] To (2023); Interesse (2023)

[8] Sun (2022)

[9] Economist (2021, 8 Apr); Economist (2021) What tech does China want?, Economist, 9 Aug; Pathak (2021); Economist (2021) China’s communist authorities are tightening their grip on the private sector, Economist, 20 Nov; Poswal (2022); Sun (2022); To (2023)

[10] Sun (2022)

[11] To (2023)

Why do people use and abandon smartwatch-based activity tracking functionality?

The activity tracking function of wearable devices is becoming more and more popular. A report from Insight indicated that 13 million wearable devices were carrying the activity tracking function, from a total of 19 million such devic [1]. It is clear from this that almost 69% of devices have the activity tracking function, which also shows the huge market for wearable devices, including smartwatches. Users adopt this function to record their daily activities, track their actions, and monitor their sleep duration and quality. Users could use this function to improve their habits and customs or remind them to do some exercise. However, even though the function is popular, some issues still exist. One significant phenomenon is the rapid adoption of activity tracking devices, but with little sustainable and long-term use. For example, a 2017 report found that around 30% to 70% activity tracking products were abandoned after only a few months [2]. This phenomenon – the rapid adoption of activity tracking devices but subsequent limited use of functions – is of interest to study both academically and practically.

The ‘tracker’ was first invented by Dr Yoshiro Hatano in 1956 and aimed to combat obesity by counting users’ steps and thus encouraging them to take more exercise. This is the embryonic form of activity tracking [3]. Modern activity tracking then appeared, applied to various devices, including mechanical machines and wearable devices. In recent years, with the spread of innovation in advanced electronic technology as a new popular lifestyle, Levy notes the increasing interest in and adoption of these tools [4]. Most activity tracking functions are carried on wearable devices, such as smartwatches and smartphones, of which the smartwatch is one of the most notable and widely worn examples [5]. Hence, when investigating activity tracking on wearable devices, studying the smartwatch could be more representative and convenient. Moreover, the research of Harrion argues that participants have started to give up using the activity tracking function on different devices, including the smartwatch [6]. This illustrates that there are barriers to the users adopting the activity tracking on smartwatches. 

My own research investigates the adoption conditions of smartwatch-based activity tracking by identifying the facilitators and barriers. It employed a mixed-methods research approach that contains both quantitive and qualitative research, involving 10 semi-structured interviews and a questionnaire with 213 valid respondents. Through semi-structured interviews, data regarding personal usage from experience on the activity tracking function was gathered and analysed. We obtained key facilitators and barriers from the interview, and then used these as the main questions of the questionnaire, which was administered online with results being analysed using SPSS. 

The survey shows that 96.7% of the responders’ adoption frequency was decreasing. This indicates that most users reduce their usage frequency over time. Also, 47% of participants were not satisfied with the activity tracking function, while only 9% were satisfied. 59% of participants agreed there are barriers that exist to the adoption of smartwatch-based activity tracking.

After the analysis, the identified key facilitators and barriers are detailed in Figure 1. The key facilitators are activity tracking capabilities, design, smartwatch functionality, interaction and improvement of living habits. Among these factors, ‘activity tracking capabilities’ and ‘improving lifestyle’ are the two most important. The main barriers include five perspectives: data, technical, interaction and user-friendliness, design and social comparison. Each of the perspectives contains its own sub-barriers. 

Figure 1 Facilitators and barriers of smartwatch-based activity tracking adoption

Using ANOVA and T-test, we compared the different facilitators and different barriers. ‘Activity tracking capabilities’ and ‘improving living habits’ were regarded as the main points attractive to users, with 89.70% and 64.3% of participants supportive, respectively.

Table 1 Facilitating factors affecting activity tracking adoption.

As the table above indicates, during the long-term usage of smartwatch-based activity tracking, users consider ‘activity tracking capabilities’ as the most vital encouraging factor, while ‘smartwatch functionality’ was the least important. In addition, based on the different mean-values of the other three factors, their mean-value was equal to 4.16, 3.6 and 3.24, respectively (improve living habits > design and appearance > interaction and user-friendliness). In this case, among these five facilitators, ‘activity tracking capabilities’ and ‘improving lifestyle’ had more positive promotional effects of encouraging the users to adopt than the other three.

Table 2 The degree of influence of the barriers

Table 2 above provides evidence to explain the degree of influence of the five barriers. Thus, the mean of each factor shows the degree of influence compared to the others. The data indicate that ‘technology’ and ‘data’ were the most important barriers to users’ adoption of the smartwatch-based activity tracking function. However, according to participants, the barrier ‘social comparison’ had least impact on the use of this function.

Figure 2 shows the degree of influence of all sub-barriers on participants’ adoption of the activity tracking function on smartwatches using ANOVA and T-test. We set 1 to equal ‘strongly not influence’ and 5 to equal ‘strongly influence’.

Figure 2 Users’ sub-barrier scores

To conclude, in order to enhance users’ experience, application producers should develop the facilitators and pay attention to solving the issues of the main barriers. The key factors that encourage users’ long-term adoption of activity tracking are a) activity tracking capabilities, b) design, c) smartwatch functionality, d) interaction and e) improving the living habits. The ‘activity tracking capabilities’ was the best performing factor to motivate the users’ long-term usage. The second most important factor was ‘improving lifestyle’, which indicates that users pay attention to their habits and behaviours via the activity tracking function. Also, to the researcher’s surprise, ‘design and appearance’ and ‘interaction’ were far behind as facilitating factors. However, ‘smartwatch functionality’ was the least important factor that stimulated users’ long-term usage. Also, female users are attracted more by ‘smartwatch functionality’ and ‘interaction and user-friendliness’ factors than male users.

In terms of the research into barriers, ‘technology’ and ‘data’ have the largest influence on usage. Among ‘technology’, ‘battery issues’ and ‘pairing’ factors had quite a large impact on usage. In addition, the second most significant barrier to usage was ‘data’, specifically ‘data inaccuracy’ and ‘insufficient data categories’ being the two most influential factors. Moreover, the perspective of ‘interaction’ and ‘design’ was almost equally as important in preventing users’ adoption. However, ‘social comparison’ fell far behind, which was less than half as important as the most important perspective. This indicates that ‘social comparison’ has not hindered usage too much. Additionally, female users consider ‘data’ and ‘technology’ have more degree of preventing influence than male users. The user who goes to the gym seems to regard ‘data’ and ‘technology’ as the more serious barriers when compared to the users who do not go to the gym.

In practical terms, the product should increase the accuracy and integrity of the data produced by devices. Producers could add more abundant data categories for sports, such as tennis or basketball. The battery issues, including battery life, heating, and rechargeability, were shown to be vital by this study’s respondents. The producers and designers should provide more charging methods, such as solar charging, to increase convenient usage. Employing more smart voice control to replace Bluetooth is another method worthy of further enhancement given pairing issues. The use of holograms could also be seen as an ideal way to solve existent screen size or quality limitations. In improving interaction to enhance lifestyles, designers might, in future, focus on smart or customised feedback to enhance user experience. For example, calculating daily calorie intake and providing recipes or dividing data between aerobic and anaerobic exercise would represent novel developments. More generally, the long-term use of smartwatch-based activity tracking could be enhanced by strengthening the facilitators and addressing the barriers identified by this study.

[1] Berg Insight. 2019. Shipments of connected wearables will reach 168 million in 2019. Berg Insight. Retrieved from:;

[2] H. Lee, and Y. Lee, “A look at wearable abandonment. In MDM 2017: 18th IEEE International Conference on Mobile Data Management,” IEEE, pp. 392-393, 2017.

[3] Maurer, U., Smailagic, A., Siewiorek, D. P., & Deisher, M. (2006). Activity recognition and monitoring using multiple sensors on different body positions. International Workshop on Wearable and Implantable Body Sensor Networks (BSN’06), 4–7. 

[4] Levy, H. (2015). Wearable Technology Beyond Smartwatches. Retrieved from: smartwatches 3/ 

[5] Page, T. (2015). Barriers to the Adoption of Wearable Technology. Journal on Information Technology4(3), 1–13. 

[6] Harrion, D., Marshall, P., Bianchi-Berthouze, N., & Bird, J. (2015). Activity tracking. Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing – UbiComp ’15, 617–621. 

Can social media messaging benefit those in the Global South who are visually impaired?

Globally, 285 million people are visually impaired, a quarter of whom live in India. The disease burden results in significantly lower employment and productivity. The national blindness prevention strategy aims at eyecare promotion through health behaviour change by raising awareness. Traditionally, this strategy relies on healthcare information disseminated through radio, television, mass media campaigns, printed medium, and interpersonal communication. Despite their appeal, these communication channels have constraints related to their cost and infrastructure. Moreover, social remoteness resulting from gender and cultural bias, illiteracy, rigid societal hierarchy, and sociocultural prejudices, acts as a major barrier to accessing this information for people from marginalised and disadvantaged communities.    

Alongside the inadequacies of the traditional information channels, there has been a demographic frameshift in many developing countries like India, which results in differential and patchy developmental practices. Consequently, India is now facing an aging population and an epidemiological change toward non-communicable diseases. This has been further compounded by rapid and unplanned urbanisation, economic migration to larger cities with over-burdened infrastructure, a lack of universal access to healthcare, and a widening digital divide. Unsurprisingly, this is putting enormous pressure on existing inadequate public health services and worsening eye health outcomes for those belonging to socioeconomically challenged backgrounds.  

However, effective public health service providers can address poor eye health outcomes, using simple measures like addressing the knowledge gap amongst disadvantaged members of society, easier access to regular eye check-up clinics, advocating hygienic practices, dispelling myths and unscientific healthcare practices and taboos, provision of cost-effective surgeries, and mobile health services. This approach has the potential of empowering the communities with new knowledge by addressing social determinants that act as a barrier to accessing eye healthcare, and their negative impact on vision. Additionally, this strategy is in alignment with the United Nation’s vision of sustainable developmental goals for 20301, as this will help poverty reduction, increase productivity, and address the inequity of health, education, and gender. This argues for the case of improving eye health care as principally a human developmental issue. Aligned with the UN strategy, is the ambitious goal of the World Health Organisation to provide Universal Eye Care, irrespective of geographical boundaries and socioeconomic divide2.  

Over the past decade, there has been an exponential increase in social media usage in developing nations like India. In particular, the penetration of WhatsApp, a social media platform that allows the exchange of audio-visual material through a free-to-use user-friendly platform, has increased to the extent that this may be regarded as an important communication channel, particularly so for the rural, remote, and socioeconomically challenged communities3. WhatsApp has the potential to reach all communities, rich or poor, urban or rural, and facilitate two-way communication in real-time. In the Indian context, it provides a desirable platform for health communication and can be used in eye healthcare care, to improve outcomes.   

In my thesis titled “WhatsApp In Health Communication: The Case Of Eye Health In Deprived Settings In India” [link to full PDF], I have tried to explore the benefits and challenges of using a social media communication platform like WhatsApp in addressing the knowledge gap on eye health among deprived members of the society4–6. The participants in this project were a large urban tertiary eye care institution (Susrut Eye Hospital) and a group of women residents from a deprived setting in a village near the eastern Indian city of Kolkata. Over a series of educational sessions undertaken at a school close to the deprived community, audio-visual content matter on eye health, carefully prepared by Susrut, was disseminated using WhatsApp as the health communication channel. This process was facilitated by two neo-literate facilitators who were also resident members of the deprived community, and participants were actively encouraged to pose questions and queries to Susrut using the WhatsApp channel.

Fig 1. Conceptual flow of information in the study

Fig 2. The flow of information between the providers and the recipients through WhatsApp

Acceptability of WhatsApp-based information dissemination amongst the study participants was high with reported benefits of increased awareness of eye diseases, their preventative management, remedial measures, and the availability of affordable eye care services. Additionally, study participants found WhatsApp technology appealing and intuitive. The resultant increase in self-confidence, consequent to heightened awareness, boosted social empowerment and enabled study participants to challenge prevalent social and cultural norms.

In conclusion, my study demonstrated that WhatsApp can be effectively used as a suitable vehicle for information dissemination on eye care in mediating behavioural change in deprived settings. Findings from this study may be considered in developing policies that develop and disseminate eye care information. This low-cost technology has the potential of being used as a data collection tool, for information governance and surveillance, and in situations of urgency. The wider implications and impact of this study lie in disseminating healthcare information related to other important public health issues to marginalised populations. 


1.         THE 17 GOALS | Sustainable Development, 

2.         World Health Organization. Universal eye health: a global action plan 2014-2019. Geneva, Switzerland: World Health Organization.

3.         WhatsApp. Statista Research Department.

4.         Maitra C, Rowley J. Delivering eye health education to deprived communities in India through a social media-based innovation. Health Inf Libr J 2021; 38: 139–142.

5.         Maitra C. WhatsApp In Health Communication – The Case Of Eye Health In Deprived Settings In India. Manchester Metropolitan University,  (2021).

6.         Maitra C, Rowley J. Using a social media based intervention to enhance eye health awareness of members of a deprived community in India. Inf Dev 2021;

How are Data used to Create Change? The Case of Violent Attacks on Health Care

On 28 March 2021 Myanmar security forces shot protesters in Yangon city. Some sought refuge in the hospital where soldiers and police followed them and opened fire. Unfortunately, this kind of violence on health care is all too common in contexts affected by armed conflict. Since the full-scale invasion of Ukraine in 2022, the World Health Organization (WHO) Surveillance System for Attacks on Health Care (SSA) has verified over 715 attacks on health. A Safeguarding Health in Conflict Coalition (SHCC) and Insecurity Insight review of five years of data on attacks found ‘more than 4,000 unique incidents of violence against health care in situations of armed conflict—on average more than two incidents a day.’ These attacks threaten health workers, individual health outcomes for patients and conflict-affected populations, and jeopardise access to health services. 

The question in the title may seem relatively straightforward. Scholarly and policy analysis about attacks on health care call for more data and better monitoring to document and understand the issue and to ensure accountability (see here and here). These numbers have gotten headlines about Ukraine and COVID-19, helping to raise awareness about these attacks. 

But do numbers do more than raise awareness? What do we know about their influence? Put another way, what is the relationship between data, often numbers, and changes in policy or behaviour? Scholars have examined the efficacy of transnational advocacy and decision-making but few have examined the specific role of data in these processes. 

In a recent publication, my colleague Róisín Read and I consider the relationship between data and change, as part of a broader effort to research the impact of attacks on health care. In our open-access article, we argue that data about attacks on healthcare are indeed necessary for understanding the scope of the problem and for raising awareness. But the continued occurrence of attacks demonstrates that data are insufficient in creating normative, policy, or behavioural change. To investigate the complex and potential role of data in these processes, we focus on two pathways for change. We call the first pathway ‘operational change,’ designed to prevent or mitigate the impact of attacks on health. The second refers to normative change, often pursued via transnational advocacy aiming to achieve a reduction in the frequency of attacks. The former operates at the level of those affected by attacks, while the latter works at the level of those perpetrating attacks.

Our investigation highlights the institutional, political, and social contexts in which data are produced and used, and how these contexts can be as significant as the evidence they provide for decision-making and advocacy efforts. We find that many issues impact on the role of data related to policy or programmatic change, from the technical (eg related to standards and terminology) to issues of bias and the social or institutional networks that shape data collection and use. To be useful, data should be collected with a clear purpose that is meaningful for those collecting, analysing, and using the data. Moreover, the political context impacts on the framing of data and the incentives to under- or overreport, whether about harms or disease. Even the terminology used in collecting data can be a point of political contention. As we write, ‘Data are never neutral; they privilege particular, subjective realities that are especially contested in fractious political contexts.’ 

Additionally, at the levels of operational and normative change, the role of personal and institutional relationships are crucial. For instance, individuals and organizations bring existing biases and frames of reference to bear on the data they encounter. As a result, data that challenge preconceptions are likely to require a higher burden of proof to become credible. Yet personal and institutional connections also strengthen trust in and interpretation of data. This highlights the crucial role of broad-based networks, which can help to build trust in the underlying data. In doing so, these connections enhance the potential for data to influence change.As academics do, we conclude with a call for more research to investigate the often positive but non-linear role of data in change processes. While our specific focus was on the relationship between data attacks on health, we hope these insights assist other efforts to affect decision-making or create behavioural, policy, or normative change.

How can smart cities shape a happier life? The mechanism for developing a “Happiness Driven Smart City”

Smart cities are expected to provide better solutions for the intensified socio-economic and environmental challenges associated with unprecedented urbanisation by embracing advanced information and communication technologies (ICTs), where challenges like climate change, energy crisis, or social inequality could be addressed through the development and application of state-of-the-art technologies (United Nations, 2019). The idealised narrative of the smart city has been widely accepted and turned into global movement at an appreciable speed for economic expansion and societal transformation, with more than 1,000 cities globally having introduced smart city initiatives with Europe, North America, Japan and South Korea in the leading position (Deloitte, 2018).

However, it appears that smart city’s influence on human happiness has been paid only marginal attention amidst the practices of smart city development. It is often assumed that smart cities may carry both opportunities and risks to human happiness due to its technology-oriented essence, but little information is available to demonstrate which specific aspects of human happiness might benefit or get harmed from the introduction of smart city initiatives. In fact, until we understand how human happiness is affected by smart city initiatives, the holistic benefits of smart city development upon urban inhabitants will remain under question, no matter how much prosperity the advocators promise. The cost of rectifying the progress of smart city development would be huge if any strategy or policy leads to unexpected or unwanted directions which might jeopardise human happiness. Therefore, the big question with regard to the influence upon human happiness brought by smart city development is whether and how smart cities act upon human happiness.

This blog introduces the concept of the Happiness Driven Smart City (HDSC), which will be constructed as a three-layer interrelated functioning structure underpinned by a set of Strategic Measures. For this, four procedures will be conducted, 1) to propose the conceptualisation and principle characteristics of the Happiness Driven Smart City; 2) to construct the key factors contributing to the performance of HDSC characteristics; 3) to build-up the HDSC development mechanism; and 4) to develop the underpinning Strategic Measures and specific application toolkit of the HDSC mechanism.

  1. Happiness Driven Smart City: conceptualisation and characteristics

Figure 1 Happiness Driven Smart City: Conceptualisation and characteristics

2. Key factors contributing to characteristic performance in a Happiness Driven Smart City system

Table 1 Key factors contributing to HDSC characteristic performance

HDSC CharacteristicsFactor 1Factor 2Factor 3Factor 4
Efficient and green physical infrastructure (HDSC1)MobilityEnergyPublic Utilities 
Labour-friendly and innovative economy (HDSC2)EmploymentInnovative SpiritEntrepreneurship 
Inclusive and attractive society (HDSC3)EducationHealthSafetyCulture and Leisure
Sustainable and eco-friendly natural environment (HDSC4)Air qualityPollution and Waste Treatment  

3. Mechanism for developing Happiness Driven Smart City

The synthesised characteristics of a Happiness Driven Smart City presented in Section 1 and the corresponding key factors identified in Section 2 are used to build up the mechanism for developing a Happiness Driven Smart City. The mechanism for developing a Happiness Driven Smart City can be portrayed graphically in Figure 2 and is composed of three components, namely, Overarching objective (top-layer), Characteristics (medium-layer) and Factors (bottom-layer). The working mechanism of HDSC shows the structural relationships between these three components. The bottom-layer Factors are the sources of changing the performance of HDSC Characteristics, which in turn contribute to the Overarching objective of developing a Happiness Driven Smart City. The functions of the HDSC system are underpinned by a set of Strategic Measures which act directly upon the Factors in the HDSC system. By applying various Strategic Measures to change Factors, momentum can be gained to improve the performance of medium-layer Characteristics. Consequently, the Overarching objective of developing a Happiness Driven Smart City can be achieved.

Figure 2 Three-layer mechanism system for developing a Happiness Driven Smart City

4. Strategic measures for the HDSC development mechanism

As shown in Figure 2, the key to make a Happiness Driven Smart City happen is the application of a set of Strategic Measures. These Strategic Measures are developed through examining the interrelationship between the three components in the HDSC system, and the examination and establishment of the Strategic Measures is conducted through a comprehensive literature review. Consequently, a set of Strategic Measures have been developed, which are presented by reference to each of the four HDSC Characteristics, as shown in Tables 2, 3, 4 and 5 respectively. In these tables, a shortlist of Strategic Measures is developed in addressing different factors which exert a driving influence upon the concerned HDSC Characteristic.

Table 2 Strategic Measures for improving the performance of HDSC characteristic “Efficient and green physical infrastructure” (HDSC1)

Factors influencing HDSC1Strategic Measures to act on factors for improving the performance of HDSC1
F11:MobilitySM111: To integrate the principles of green transport into the process of developing smart mobility thus the performance of green infrastructure will be improved. By developing a leveraged mobility paradigm between walking, cycling and driving, greenhouse gas emission will be reduced. SM112: To eliminate possible negative effects caused by the misuse and monopoly of smart mobility technologies which would hurt the users’ benefits and affect negatively the development of HDSC in the long run. For example, regulations shall be formulated to ensure smart mobility service providers take responsibilities in delivering a greener and more equal transport system.
F12:EnergySM121: From the industrial aspect, to take consideration of both the optimisation of energy sources and conservation on the consumption end. For example, integrating smart grids with renewable energy resources is a direct and effective solution for improving green grid management; adopting artificial intelligence and big data analysis into building, manufacture and transportation sectors to forecast and minimize energy consumption is proved effective for minimizing energy consumption and consequently mitigating impacts upon environment and climate. SM122: From the individual aspect, to create an advantageous environment with the facility of technology to encourage individual energy saving behaviours. The potential impact of occupants energy saving behaviour on buildings is evidenced and identified as an essential approach to improve energy efficiency in green buildings and communities without jeopardizing the level of comfort.
F13:Public UtilitiesSM131: To explore resource efficiency and utilization opportunities from both service providers and consumers in smart utility network development. For example, artificial intelligence application in leak detection of water distribution pipelines will increase water resource utilization efficiency. The water/gas consumption feedback technology can help to reduce household wasteful behaviour to trigger the decrease of environmental impact in every step along the whole journey of resources processed by public utility facilities.

Table 3 Strategic Measures for improving the performance of HDSC characteristic “Labour-friendly and innovative economy” (HDSC2)

Factors influencing HDSC2Strategic Measures to act on factors for improving the performance of HDSC2
F21:EmploymentSM211: To prepare solutions and resources to minimize the potential disruptive impact on employment during the dramatic change process and to create a labour-friendly employment market environment to help citizens quickly fit into the new economy. Policies to stimulate education evolution for promptly fulfilling high profile new business requirements and training programs to look after disadvantaged labour shall be taken into full implementation. SM212: To enact labour protection and social protection rules and regulations that are suitable and in favour of employees to keep new digital economy development under a labour-friendly premise. It would be ideal if the policymakers are able to take a longer view and make foreseeable actions on the employment influence arising from the digital economy instead of keeping the legal and social regulation system in a passive adaption situation.
F22:Innovative SpiritSM221: To make the smart city as a nexus for open innovation, which should not just refer to industry but also the ways government and other institutions work and collaborate with society, to jointly create an inclusive, labour-friendly and innovative economy. All sources of innovation from different levels and different sectors shall be encouraged to actualize an innovative and diverse economy where technology plays the catalyst role. SM222: To inspire the potential of new bottom-up approaches based on user-generated content through the experiences of the citizens themselves, which enables citizens to build social capital and the capacity required to become co-creators and co-producers of new and innovative services with the means to ensure that they are delivered in more effective and inclusive ways, taking full advantage of new Internet-based technologies and applications.
F23:EntrepreneurshipSM231: To encourage the utilization of new technologies and promote a strong pro-entrepreneurial state ethos where an innovative economy is nurtured and accelerated. SM232: To encourage and facilitate entrepreneurial citizens to trigger, apply and transform emerging technologies and knowledge into new products, new jobs, and new firms, which in turn enables the creation of a labour-friendly innovative economy. SM233: To promote neo-liberal attempts to inclusively and effectively incorporate the local community into the entrepreneurial city, via the approaches of various participatory ICT projects.

Table 4 Strategic Measures for improving the performance of HDSC characteristic “Inclusive and attractive society” (HDSC3)

Factors influencing HDSC3Strategic Measures to act on factors for improving the performance of HDSC3
F31:EducationSM311: To create an easy environment for innovation during the digital transformation process of education through a participatory approach to enhance social inclusiveness and talent attractiveness in the education sector. All stakeholders in this venturous journey, such as teachers, students, administrators, online platform companies, software and hardware providers etc., shall be encouraged to be more active to innovate and design better solutions to meet the new need. SM312: To address the equity of education resources and opportunities to avoid extreme deprivations caused by the digital transformation to ensure a more inclusive development in cities. For example, online education shall take in consideration of the balance between commercial online education programs and public-free courses so as to benefit the widest audience from the well-educated to the low-skilled learners.
F32:HealthSM321: To improve accessibility to health facilities and services to the widest public for disease prevention and health promotion where technological innovation can be applied as a tool for empowering social inclusiveness. For example, more attention and funding shall be paid to mental health care services where big data and artificial intelligence technology can play an innovative role in prediction and diagnosis. SM322: To encourage the application of new technologies aiming to produce new opportunities to improve the health treatment to a more accurate and effective level where patients can receive higher quality and safer medical service with reduced cost and wastage. The improvement of affordability and effectiveness in medical services and health care driven by smart technology will positively affect the inclusiveness of the society.
F33:SafetySM331: To create a safer social environment by taking actions to prevent the occurrence of crime before it happens via the application of new technology-based crime risk prediction analysis approaches. Safety clearly exerts higher impacts on urban attractiveness.
F34:Culture and LeisureSM341: To create an environment that encourages wide public participation, cultural diversity, digital equity in the context of digital technology to contribute to a city’s attractiveness and social inclusion. The development of a cultural policy that aims for cultural participation may also involve other policy areas such as economic and education sectors. SM342: To provide a pleasant environment and necessary support for both offline and online leisure activities to provide greater opportunities for urban residents to enjoy a higher level of life satisfaction and social inclusion.

Table 5 Strategic Measures for improving the performance of HDSC characteristic “Sustainable and eco-friendly natural environment” (HDSC4)

Factors influencing HDSC4Strategic Measures to act on factors for improving the performance of HDSC4
F41:Air QualitySM411: To monitor and forecast air quality more precisely in both vicinity (building and neighbourhood) and city level through collecting and analysing data with the ubiquitous upgraded devices and advanced algorithms, and to satisfy the evolved need for environment protection and human life by taking more targeted and effective solutions. SM412: To enable citizens to have tailored air quality notification to help prevent any exposure risks amongst vulnerable groups to reduce the ecological threat on public health (ibid).
F42:Pollution and Waste TreatmentSM421: To control emissions and effluents through IoT-enabled smart system in various sectors including building, manufacturing industry and logistics etc. SM422: To modernize traditional waste management systems to prevent the negative effects of incorrect operation on both people and the environment during the whole process including waste collection, disposal, recycling, and recovery (ibid). SM423: To enable citizens to track daily personal pollution footprints via smart approaches to better understand and behave upon reducing waste emission and production towards a sustainable and eco-friendly environment.

The proposed theoretical mechanism can be applied with specific assessment criteria to examine to what extent a smart city initiative implemented in a given city has enhanced urban residents’ happiness and has achieved the goal of a Happiness Driven Smart City. The application of the HDSC mechanism can thus help urban governors to understand the status quo of smart city development and to better guide the design of smart cities towards a happiness-driven and human-centred direction.

Note: This blog is based upon a recent publication on the journal of Sustainable Cities and Society.

Development Transformation as the Goal for Digital Transformation

Richard Heeks, Bookie Ezeomah, Gianluca Iazzolino, Aarti Krishnan, Rose Pritchard & Qingna Zhou

There’s a lot of talk currently about digital transformation for development.  Sometimes styled “DX4D”, a quick definition would be radical change in development processes and structures enabled by digital systems.

Digital transformation is thus not a goal.  Instead, development transformation is the goal and starting point.  But what kind of development transformation?

In this post, we summarise what development transformation would mean under different development paradigms, and some implications for digital.  The table below is not exhaustive of the various paradigms and it rather brutally simplifies rich and complex ideas.  However, it does help clarify two key DX4D tenets:

  • Vision Matters: unless you know where you want to get to, digital can’t help take you there.
  • Visions Differ: different paradigms aim for very different destinations and, hence, different journeys in the application of digital.

If you have paradigms you’d like to add or you have improvements to offer on what’s in the table, do let us know.

Development Paradigm Essence? Transformation? Digital Implications?
Neoliberal Markets and market relations are the central foundation for economic development.  They, and not government regulation or vested interests, are the best way to allocate development resources and to generate productivity improvements and growth.  The state acts to support market-driven development. Neoliberalism is thus about the reformatting of politics, society and individuals according to market logics, the pursuit of profits, and individual responsibility principles. Stabilisation to reduce government expenditure.  Liberalisation to roll back state regulation, subsidies and other interventions in markets and the private sector.  Privatisation to transfer ownership from public to private sector. Digital, particularly via platforms, must enable the formation and presence of markets in all sectors, and a step change in market functioning via datafication and machine-readability of market actors and processes. Digital will also enable the development of private sector responsibility for public service delivery, and major improvements in efficiency of remaining public sector functions.
Structuralist Particular socio-economic structures inhibit development.  For dependency variants, it is unequal relationships of exchange between core and periphery, whether understood in terms of countries, regions, or more immaterial geographies.  For Marxist and related anti-capitalist paradigms, it is unequal relationships of exchange between capital and labour. The exploitative socio-economic structures must be broken away from and/or replaced.  From a dependency perspective, at the extreme, this means autarky and a focus on localised systems of production and consumption.  From a Marxist perspective, it means the end of capitalism and its replacement with structures of common ownership. Digital must support radical structural change based around localised production and/or cooperative or similar ownership structures.
Sustainable Ensuring resource usage does not compromise the ability of future generations to meet their own needs; with variants ranging from green growth through to de-growth. Major reductions in resource usage including improvements in efficiency of resource-using processes.  Major reductions in polluting outputs from processes. Internalisation of negative environmental externalities so as to gauge the true cost of economic growth. Digital must support a step-change in resource usage and polluting outputs of all economic and social processes, including those involving digital itself.  Digital must also support environmental mapping and monitoring to track progress of sustainability. 
Human Development Development as freedom; in particular economic, political, social, security and informational freedom for all so that no-one is left behind and all have the opportunity to be and to do what they wish.     Changing contexts so that there is equality of opportunity and equality of choice; especially for those currently denied those opportunities.     Digital must be not just accessible but usable and appropriable by all.  It must then support the ability of all to choose the kind of lives and livelihoods that they value; thus requiring some customisation to individual contexts rather than a blanket equality of access to assets, institutions and livelihoods.
Decolonisation Reversal of the current and legacy negative impacts of colonisation. Enabling sovereignty and “self-determination of indigenous peoples over their land, cultures, and political and economic systems”[1].  Also understood – and drawing on the post-development roots of one strand of decolonisation – as the identification, challenging and revision or replacements of “assumptions, ideas, values and practices that reflect a colonizer’s dominating influence and especially a Eurocentric dominating influence”[2]. Digital must be accessible, usable and appropriable by indigenous peoples, enabling them to exercise self-determination.  Digital sovereignty will enable local “control over digital assets, such as data, content or digital infrastructure, or over the use of those assets”[3] and prevent uncontrolled extraction of value from these assets by others. For the latter understanding of decolonising transformation, digital must empower those who have been disempowered by Eurocentric domination of epistemics and discourse, and enable them to engage with and challenge that domination.  

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