Workshop on China’s Digital Expansion in the Global South

Credit: ASPI

China is fast-emerging as a global digital superpower and has a rapidly-growing digital presence in other low- and middle-income developing countries of the global South.  Yet research to date has been relatively limited on this rising phenomenon which is having important economic, social, political and geopolitical impacts.

This online workshop – to be held 1000-1730 (UK time/BST) on Thursday 21st July 2022 – will present new findings based on primary research in the global South, and also provide a space to reflect on the agenda and collaborations for future research.

Register here for the workshop:

An opportunity to discuss the future research agenda and actions will follow these presentations:


The Future Research Agenda on China’s Digital Expansion – Richard Heeks, Angelica Ospina, Chris Foster, Ping Gao, Xia Han, Nicholas Jepson, Seth Schindler & Qingna Zhou (University of Manchester)

Learning Along the Digital Silk Road? Technology Transfer, Power, and Chinese ICT Corporations in North Africa – Tin Hinane El Kadi (London School of Economics)

China’s Digital Expansion in Africa: South to South Cooperation or South Dominance? – Grace Wang (Stellenbosch University)


Chinese Digital Platform Companies’ Expansion in the Belt and Road Countries – Yujia He (University of Kentucky)

Global Developments of Chinese E-commerce Livestreaming: Case of AliExpress and Lazada in Southeast Asia – Xiaofei Han (Carleton University)

Transnational Governance behind Chinese Platforms’ Overseas Content Moderation: A Case Study of TikTok’s Global Reach to Southern and South-eastern Asia – Diyi Liu (University of Oxford)


The Chinese Surveillance State in Latin America? Evidence from Argentina and Ecuador – Maximiliano Vila Seoane (National Scientific and Technical Research Council, Argentina) & Carla Álvarez Velasco (Institute of Higher National Studies, Ecuador)

China’s Expansion in Brazilian Digital Surveillance Markets: Between Public Actors and Foreign Enterprises – Esther Majerowicz (Federal University of Rio Grande do Norte) & Miguel Henriques de Carvalho (Federal University of Rio de Janeiro)

Alibaba in Mexico: Adapting the Digital Villages Model to Latin America – Guillermo J. Larios-Hernandez (Universidad Anahuac Mexico)


Future Research Agenda Activity

The workshop is co-hosted by the University of Manchester’s Centre for Digital Development and Manchester China Institute

Graphic credit: ASPI at

COVID-19 and the Unsettled Questions of Digital Governance

A meeting on e-commerce at the World Trade Organisation, source: WTO photos

How will ongoing debates on digital governance shape the future of digital development?

One of the important implications of the COVID-19 pandemic has been the further acceleration of growth in the digital economy and the expansion of cross-border digital flows. Driven by the pandemic, large and small businesses across the world adapted their business models by shifting completely or partially to internet-based models. As a result, digital transactions, within and across countries, increased dramatically over the last couple of years. While measurement of such flows is challenging, some reports estimate that global Internet Protocol (IP) traffic was expected to more than triple between 2017 and 2022 and that domestic and international IP traffic in 2022 will exceed all Internet traffic up to 2016.

This growth has intensified the debates around digital governance. These debates have begun prior to the pandemic as the growth in the digital economy on the one hand and the move by some states to adopt “interventionist” digital policies drove intense discussions on how to govern the digital world and where to draw the line between sovereignty of states on the one hand and the need to adopt international rules and norms to maintain the global nature of the digital world.

The success of some countries, particularly China, in building digital capacities and firms through selective, and often limited, integration in the global digital market have intensified those debates as other countries began to look to the Chinese model as a guidance for their digital strategies. As a result, questions around the appropriate forum to govern digital issues, the limits of state power vis-à-vis international rules and norms, and the applicability of such rules to different economies have dominated digital policy debates for a number of years. Some of those debates have taken place within regional blocs such as the European Union (EU) and the Association of Southeast Asian Nations (ASEAN) while others have taken place within international bodies that are focused on digital governance such as the Internet Governance Forum (IGF).

While these debates continued in different forums, a difficult link between digital governance and the international trading system was established largely as a result of pressure from the advanced economies. Issues such as data flows, source code and algorithms, and cybersecurity, amongst others, became increasingly linked to trade regimes with recent trade agreements adopting digital chapters that include rules on a range of digital issues.

While the link between trade agreements and the digital world is not always clear (while some cross-border flows are trade flows, a huge percentage of these flows are not trade-related, and the two are very difficult to separate), the trade regime offered an established forum with the ability to produce binding and enforceable rules to govern the digital space. Today, negotiations on digital issues continue in a number of multilateral, regional, and bilateral trade forums as states pursue different visions of the digital economy and how to govern digital flows. The advanced economies, in particular the United States, the EU, Japan, and Australia in addition to emerging economies such as India and China are the key drivers of these processes.

The implications of such processes for development issues are profound, and often overlooked. The economic and social value of data, for instance, is not yet fully understood and, as such, it is unclear what adopting binding international rules around data flows will exactly entail. Some argue that developing countries will benefit from global open data policies as it gives them an opportunity to integrate in the digital economy and to achieve technological progress. Others, however, question this position and argue that developing countries should resist any rules that could undermine their policy space to adopt digital policies. As discussions on these issues continue in different forums, more engagement from digital development scholars is needed.

In the context of the dramatic expansion of the digital economy driven by the pandemic, better understanding the implications of digital governance for digital development particularly in lower-income and smaller developing countries is crucial to help shape the processes driving digital governance and to ensure that digital rules do not undermine the objectives of economic and social development that are increasingly tied to digital issues in today’s world.

The Organisational Context for Successful ICT4D Practitioners

How can their organisational context best support those who implement ICT4D projects?

People – designers, builders, operators, champions – are critical to the successful implementation of ICT4D projects.  The digital development organisations that employ these practitioners already know that.  But what they know far less about is how to create a supportive organisational context that will improve ICT4D practitioner performance and, hence, ICT4D project success rates.

I have therefore been undertaking field research in East Africa designed to tease out components of supportive context, based on interviews in five organisations which were a mix of NGOs and social enterprises.  To date, I have identified six “habits of highly-effective digital development organisations”:

1. Reinforcing Mission Congruence

The most-effective contexts were those in which ICT4D practitioners were given a clear sense of how their work fitted with the organisation’s wider mission, which typically related to social impact.  As well as giving practitioners the bigger picture of their contribution, this also helped create a unity of purpose with shared goals of making a difference.

2. Strong Non-Monetary Rewards

Money is tight in most digital development organisations but they can successfully motivate their practitioners with non-monetary rewards.  Flexibility on working hours and opportunities for work-life balance came up repeatedly in this category, alongside recognition from peers of one’s contribution.

3. Involvement in Monetary Reward-Setting

A role for non-monetary rewards does not mean money is unimportant – it is!  But just as important as the amount was the process by which pay was calculated.  Supportive contexts were those where pay was transparently calculated and openly discussed, and hence where ICT4D practitioners felt involved in the process of decision-making.

4. Support for Career Progression

To make their best contribution to ICT4D projects, practitioners needed to feel that they were making progress in their careers.  Though often backed by direct mentoring, organisational support here varied by career stage.  Early-career practitioners had a strong perceived need for skills development: not narrow task-specific skills but a broad and hybrid mix of technical and non-technical capabilities.  This worked best where their organisation offered them a mix of different roles but also ensured access to high-quality digital tools and infrastructure.  Mid-career professionals also wanted growth opportunities but they focused less on technical skills and more on being given the autonomy and responsibility to develop leadership capabilities.

5. Meeting Personal Goals

ICT4D practitioners give their best to their projects and their organisation when they have a perception of reciprocation; particularly in terms of being helped to achieve their personal goals.  Goals of social impact and skills-building for career progression were mentioned already, but supportive contexts could provide other things – networks of stakeholder relations to build social capital for the future, and facilitation of personal development projects.

6. Socio-Emotional Support

ICT4D often has a technical bias but practitioners worked best in cultures attuned to the human side of work, and in which they felt their whole selves were recognised.  These were organisations that were more like “families” than “well-oiled machines”; in which peers and managers cared about wellbeing and would take time to listen and engage with personal problems; and in which socialisation and hence a sense of belonging were actively encouraged.

These findings may themselves have some specificity to East African digital development organisations.  Each organisation may thus need to identify the dimensions of organisational support that will work with its particular ICT4D practitioners.  Nonetheless, these six habits should be a useful starting point for all organisations.

If you would like further details about the six habits, or my ongoing work using these to develop interventions for digital development organisations, then feel free to contact me: epiphania.kimaro[@]

Photo credit: Gladness Mayenga

Global South researchers succeeding against the odds: how are they different?

Understanding the Context

How are some global South researchers able to overcome contextual constraints and become highly cited?

There is a clear research divide between the global South and the global North[1] in terms of research investment and capabilities. The average national expenditure on research and development in Southern countries is 0.38% compared to 1.44% in Northern countries[2]. The number of researchers per million population in 2017 was 713 in the global South and 4,351 in the global North[3]. This had implications on the volume and impact of scientific outputs produced by the global South in comparison to the global North. Excluding China and India, in 2018 global North countries produced an average of more than 35,000 scientific and technical journal articles per country while global South countries produced 4,000 journal articles per country, out of which less than 2% made it to the top 1% most cited articles globally. This can be partially explained by the lower levels of investment and English proficiency, smaller relative populations of researchers, institutional exclusion factors and/or biases against Southern researchers when it comes to accepting their papers in top tier journals or awarding grants.

Despite all of the aforementioned challenges, there are a few Southern researchers who are able to achieve better outcomes than their peers. Such researchers could provide valuable insights and lessons that might help to better understand and even mitigate the current North–South divide in research outputs and citation. This blog post will highlight some of the valuable insights emerging from our recently published study that attempted to uncover publication-level and individual-level factors underlying the outperformance of information systems researchers in Egypt.

The Method

 This study employed the “data-powered positive deviance” (DPPD) methodology that uses digital datasets to identify positive deviants (those performing unexpectedly well in a specific outcome measure that is digitally recorded, mediated or observed) and potentially also to understand the characteristics and practices of those positive deviants (PDs) if digitally recorded.

Three main steps were conducted to identify and characterise PDs, as shown in Figure 1:

  • In the Define step, we defined our study population and the performance indicators that will be used to assign a score for each researcher. The study population comprised 203 information system researchers in Egyptian public universities. Six well-known citation metrics (h-index, g-index, hc-index, hi-index, aw-index and m-quotient) were calculated for each researcher using Publish or Perish and Google Scholar bibliometrics. Several citation metrics were used to avoid putting certain groups at a disadvantage due to factors such as the length of their research career, the size of their research departments, the age of their papers or their publication strategies.
  • The Determine step aims at identifying the PDs based on the scores calculated in the previous step. In this study, PDs or outliers were defined as researchers who significantly outperformed their peers in at least one of the six citation metrics. The interquartile (IQR) method was used to identify those outliers based on their deviation from the median, i.e. lying beyond the 1.5*IQR added to the third quartile in at least one of the six citation metrics.
  • The third step, Discover, consists of three main stages. In Stage 1, primary data was collected through in-depth interviews from a sample of PDs to explore practices, attitudes and attributes that might distinguish them from non-PDs. During Stage 2, the key findings from Stage 1 plus other predictors of research performance drawn from the literature were used to design a survey tool. That survey then targeted the whole population and tested if the proposed differentiators were significantly different between the two groups. Finally, in Stage 3, the Scopus database was used as the basis for analysis of researcher publications; extending and validating some of the findings identified in the previous stages.

Figure 1: Summary of the applied DPPD method

 What we found

 A combination of data sources (interviews, surveys, publications) and analytical techniques (PLS regression, topic modelling) were used to identify significant predictors of positively-deviant information system researchers. One of the key findings was that PDs contributed to the creation of roughly half (48%) of the publications and achieved nearly double (1.7x) the total number of citations of non-PDs despite representing roughly one-eighth (13%) of the study population. While there were significant predictors of outperformance that are structural (e.g. gender, academic rank and role, workplace perceptions), our focus in this post is on highlighting factors that are transferable i.e. practices and strategies that are to some extent within the control of the individual researchers. Table 1 provides a summary of such factors.

Individual-Level Predictors


Positive Deviants

Non-Positive Deviants

Travelling abroad to obtain their PhD degree

More PDs got their PhDs from global North countries 

Fewer non-PDs got their PhDs from global North countries

International research collaborations

Frequently part of multi-country research teams 

Seldom part of multi-country research teams


Published more papers with foreign reputable authors

Published fewer papers with foreign reputable authors

Securing research grants and travel funds 

Secured more grants and travel funds

Secured fewer grants and travel funds

Research approach

Less inclined to do radical research

More inclined to do radical research

Student supervisions

Supervised a larger number of postgraduate students

Supervised a smaller number of postgraduate students

Capacity development  

More PDs took scientific writing and English writing courses

Fewer non-PDs took scientific writing and English writing courses

Publication-Level Predictors

Length of paper

Longer papers

Shorter papers

Length of abstract

Longer abstracts

Shorter abstracts

Length of title

Longer titles

Shorter titles

Number of authors and affiliations

More authors and affiliations

Fewer authors and affiliations

Number of references

More references

Fewer references 

Publication type

More journal articles and fewer conference papers

More conference papers and fewer journal articles

Quality of journals

Higher SJR journals

Lower SJR journals


Published more in Elsevier Journals

Published less in Elsevier Journals


PDs publish fewer papers covering business process management and neural networks and published more papers in wireless sensor networks and hardware systems

Non-PDs publish more papers covering business process management and neural networks and published fewer papers in wireless sensor networks and hardware systems

 Table 1: Significant transferable predictors of outperformance

The analysis also included a visualization of topic prevalence over time for the PD corpus and non-PD corpus as presented in Figure 2. It shows topics, such as Classification Models, where PDs were early movers and then they were followed by NPDs. There is a greater prevalence of Expert Systems and GIS-related topics in the PD corpus in comparison to the NPD corpus. Conversely, there is lower prevalence of Neural Networks and Business Process Management & Process Mining. There are also topics that had very similar proportions over time for both groups, such as Social Network Mining.

Figure 2: Topic proportions of PD corpus (left) and non-PD corpus (right) over time

 Implications for practice and policy

This analysis cannot, of course, guarantee that applying these factors more broadly would lead to the same outcomes achieved by PDs. Nonetheless, there would be value in individual Southern researchers reflecting on the research- and paper-related behaviours that have been shown associated with positively-deviant research profiles. For instance, Southern researchers work in contexts of resource limitation, hence, research grants and travel funds are of outmost importance. Including partners from Northern universities (as PDs do) increases the chances of securing the funds as those partners are more familiar with grant procurement processes and more experienced in writing proposals. Studying abroad also seems to put Southern researchers at an advantage as it does not just equip them with the technical know-how and the degree needed to pursue their academic careers, but also helps them establish channels of collaboration with their supervisors and their PhD granting universities, long after they returned to their home countries. Those long standing relationships provide further access to research grants either directly or via joint grant applications.

In terms of paper-related strategies, Southern researchers could avoid low-visibility local conferences and can select journals instead as they are more likely to deliver citations. Publishing with more authors (domestic and international) could also help pay for journal publication fees, with fees split across more authors or paid from overseas sources. Publishing with foreign authors could also help Southern researchers overcome the institutional biases[4] among editors, reviewers in single-blind or open review systems, and readers. PDs’ preference for working on established research areas rather than on radical research topics may also help in relation to institutional barriers, with research that builds incrementally on existing ideas and literature being more likely to be accepted for publication by referees, and cited by others working in the established area. Hence, Southern researchers seeking more citations could consider contributing to mainstream topics that build on existing work. Along the same lines, having multiple authors and affiliations increases the likelihood of citations, as each author has their own network and bringing those networks together can increase readership. Similarly, publishing papers with a larger number of references increases paper visibility through citation-based search in databases that allow it, such as Google Scholar, and through the “tit-for-tat” hypothesis i.e. authors tend to cite those who cite them.[5]

Higher education institutions and higher education policy makers may also reflect on the findings, and consider strategic implications for training, resource provision, collaborations, etc. For example, English and scientific/formal writing courses were associated with PD performance; such courses could be prerequisites for starting a PhD research. There could be more academic training designed around research grant writing and providing guidance on funding bodies that researchers can apply to. International research collaborations appeared as an important predictor of PDs; so, university senior managers and policy makers can explore ways to reduce barriers and increase opportunities for overseas PhD study, post-PhD return, and ongoing joint research projects with global North universities.

Citation rates are, of course, not the “be all and end all” of research: there are and should be other motivations and indicators of research. However, we hope the findings presented here can provide valuable “food for thought” for global South researchers.


[1] The terms “South” and “Southern” will be used to refer to countries classified as upper-middle income, lower-middle income, and low income. Accordingly, the terms “North” and “Northern” will be used to refer to countries that are members of the OECD (Organisation for Economic Co-operation and Development) or are classified as high-income economies by the World Bank based on estimates of gross national income per capita.

[2] Blicharska, M., Smithers, R. J., Kuchler, M., Agrawal, G. K., Gutiérrez, J. M., Hassanali, A., Huq, S., Koller, S. H., Marjit, S., Mshinda, H. M., & Masjuki, H. (2017). Steps to overcome the North-South divide in research relevant to climate change policy and practice. Nature Climate Change, 7(1), 21–27.

[3] World Bank. (2020). Science & Technology Indicators. World Bank.

[4] Karlsson, S., Srebotnjak, T., & Gonzales, P. (2007). Understanding the North-South knowledge divide and its implications for policy: A quantitative analysis of the generation of scientific knowledge in the environmental sciences. Environmental Science and Policy, 10(7–8), 668–684.; Gibbs, W. W. (1995). Lost science in the third world. Scientific American, 273(2), 92–99.; Leimu, R., & Koricheva, J. (2005). What determines the citation frequency of ecological papers? Trends in Ecology & Evolution, 20(1), 28–32.

[5] Webster, G. D., Jonason, P. K., & Schember, T. O. (2009). Hot topics and popular papers in evolutionary psychology: Analyses of title words and citation counts in evolution and human behavior, 1979–2008. Evolutionary Psychology, 7(3), 147470490900700300.


Understanding smart tourism and smart tourism ecosystems

As a fashionable and novel tourism agenda, the theory of smart tourism is still evolving but the literature brings out three perspectives. First, tourists . The primary starting point of smart tourism is to fully satisfy the tourists’ need for scenic spots and create more value for them. In this sense, smart tourism is seen as a new pattern of tourism operation, which regards the tourist as the basic service object [1][2][3]. Second, managers (e.g., in government and tourism enterprises). Smart tourism is about achieving a comprehensive and thorough system which aims to offer accurate, convenient and ubiquitous tourism information applications, as well as a range of travel services [4]. In this case, the managers refer to the local scenic area managers and staff, government officials, and the company offering the technology  [5]. Third, technology. Although the main point of the smart tourism system is the service, the capabilities and foundation of smart tourism is technology[6]. This refers to the highly systematic, detailed interaction between physical tourism and information resources [7], including digital data exchange[8].

Accompanied by the development of information and communication technologies (ICTs), the evolution of tourism goes through three stages: traditional tourism, e-tourism and smart tourism. Traditional tourism refers to people moving to countries outside their usual environment[9]. With evolution of technology, e-tourism emerged to address users’ interactivity and web-based technology was used to enhance the tourism experience and information governance, which is considered an early step of smart tourism[10].Subsequently, e-tourism evolved into smart tourism, building on technology infrastructure and ICTs (e,g. cloud service, big data). Importantly, smart tourism emphasises explicitly the support of variously smart activities and value-addition through the dynamic interaction between different actors[11]. The difference between e-tourism and smart tourism is detailed in the table below.

  e-Tourism Smart Tourism
Sphere digital bridging digital & physical
Core technology websites sensors & smartphones
Travel phase pre-& post-travel during trip
Lifeblood information big data
Paradigm interactivity technology-mediated co-creation
Structure value chain / intermediaries ecosystem
Exchange B2B, B2C, C2C public-private-consumer collaboration
Table 1 Comparison of e-tourism and smart tourism [12]

Smart tourism systems

Based on the development of ICTs, the smart tourism system (STS) is regarded as a complex system based on a digital service platform to support smart tourism, which addresses the innovation service provided to different stakeholders[7] [9]. Specifically, it emphasizes the actors’ intelligent demands of value-added through information service creation, delivery and exchange[13]. Thereby, the STS is characterized by value co-creation through the integration of sources into both micro and macro levels[3][8]. The table below presents the established system in China based on literature and reality [14][15].

STS Sub-system STS Functionalities STS Instances
Forecasting system Passenger flowWeather forecastQueuing-time forecast Wind speed sensorHumiture sensorImage recognition
Panoramic virtual reality system Virtual tourism experienceVirtual community Panoramic photographyVR 
Intelligent management system Smart vehicle and transportReal-time traffic Crowd handling RFID·        Video surveillanceTourist-flow monitoring 
Smart guide system Scenic spot interpreterPersonalized tours route E/Robot tour map Mobile app Electronic map Voice navigation
Smart recommend system Scenic spot recommendation Recommended route QR codeMobile app
Table 2 Smart tourism systems in China

Figure 1 demonstrates the conceptual model of a non-profit smart tourism system, which is summarized from the current literature[15].The objective is that the STS provides service to government, enterprise, tourists, and residents [16]. Importantly, these applications are not isolated and individual but also service the interaction requirements. For example, from the perspective of tourism, the STS faces the tourist (T), the connection between tourists (T2T), and the interaction needs between the tourist and government (T2G).

Figure 1 A conceptual model of structuring STS adapted from [15]

Smart tourism ecosystem (STE)

When linking the ecosystem with the smart tourism system, an STE can be established, which contains the characteristic of both the smart tourism system and wider ecosystem components. An STE consists of two layers.  The information ecology layer emphasizes the interaction between humans, firms, technology and their environment[9].This indicates the importance of the different actors related to information behaviour and information systems. The service system layer emphasizes the interactions through institutions and technologies to provide services to the beneficiaries, to exchange resources, and to co-create value [12].

Gretzel and Werthner defined the STE as “a tourism system that uses smart technology to create, manage, and provide smart tourism services/ experiences”[17].It is characterized by intensive information sharing and value co-creation. Buhalis and Amaranggana indicated that an STE aims to provide sustainable, enhanced/rich, valuable travel service and experience [6].To reach this, digital ecosystems that provide technical resources and facilitate interactions within and between stakeholders form the core of STE[17]. In other words, the generation of tourism experiences always requires extensive coordination and cooperation between different industry stakeholders and government players [18].

As shown in Figure 2, Gretzel & Werthner proposed a schematic representation of an STE [17].Their study describes an STE as an interactive space supported by a digital ecosystem and containing various types of actors, which are distinguished as tourism consumers (TC), residential consumers (RC), tourism suppliers (TS), other industry suppliers (OS), government agencies, destination marketing organizations (DMO) and intermediaries. These actors are not necessarily discrete, as a single player can play multiple roles. Moreover, this model is also adopted by other researchers like Brandt et al, who proposed an social media analytics (SMA)-enabled STE model, which also indicated the RC, TC, TS and government as vital actors [19]. The tourism consumers (TCs) have resources and, because they have access to the digital ecosystem, can be organized among themselves or mixed with closely related residential consumers (RCs) and act as producers. Through smart technology, tourism providers (TS) or other business-focused groups can connect and create new service offerings. In an ecosystem, the main source of ‘food’ for a ‘species’ is data/information, and the effective conversion of this food into rich tourism experiences can lead to a longer life for the ‘species’. Telecom companies and banking/payment support service providers representing other industry providers (OS) are vital ‘predators’ in the ecosystem and provide essential information to the system. Destination marketing organizations (DMOs) perform traditional information brokering, marketing, and quality control functions, while various intermediaries facilitate transactions through innovative data and devices [9]. Government utilization of social media in the STE could enhance the development and the value co-creation of local tourism [12].

Figure 2 Smart tourism ecosystem [17]

To conclude, STE studies regard the STE as a complex information and service ecosystem, which involves multiple actors like government, tourists, platform providers, residents etc. The main characteristics of STE are 1) the dynamic interactions between multiple actors; 2) the value co-creation during the actors’ interactions; 2) sustainable development; 4) the creation and exchange of tourism resources; 5) the innovation service. Thus, STEs could facilitate the interaction between actors, the exchange and creation of tourism resources, and value creation. This could further improve the tourism experiences and enhance the sustainable development of smart tourism. 


[1] Yao, G. (2012). Analysis of smart tourism construction framework. Nanjing University of Posts and Telecommunications (The Social Sciences Edition), 14(2), 5e9.

[2] Fu, Y., & Zheng, X. (2013). China smart tourism development status and counter- measures. Development Research, 4, 62e65.

[8] Hunter, W. C., Chung, N., Gretzel, U., & Koo, C. (2015). Constructivist research in smart tourism. Asia Pacific Journal of Information Systems, 25(1), 105–120.

[3] Shafiee, S., Ghatari, A. R., Hasanzadeh, A., & Jahanyan, S. (2019). Developing a model for sustainable smart tourism destinations: A systematic review. Tourism Management Perspectives, 31, 287-300.

[4] Jin, W. (2012). Smart tourism and the construction of tourism public service system. Tourism Tribune, 27(2), 5e6.

[5] Huang, C., Goo, J., Nam, K., & Yoo, C. (2016). Smart tourism technologies in travel planning: The role of exploration and exploitation. Information & Management, 54(6), 757-770. doi: 10.1016/

[6] Buhalis, D., & Amaranggana, A. (2013). Smart tourism destinations. In Z. Xiang, & L. Tussyadiah (Eds.), Information and communication technologies in tourism 2014 (pp. 553e564). Cham, New York: Springer.

[7] Law, R., Buhalis, D., & Cobanoglu, C. (2014). Progress on information and communication technologies in hospitality and tourism. International Journal of Contemporary Hospitality Management, 26(5), 727–750.

[9] Gretzel, U., Sigala, M., Xiang, Z., & Koo, C. (2015). Smart tourism: foundations and developments. Electronic Markets, 25(3), 179-188.

[10] Werthner, H., & Ricci, F. (2004). E-commerce and tourism. Communications of the ACM, 47(12), 101-105.

[11] Lamsfus, C., Martín, D., Alzua-Sorzabal, A., & Torres-Manzanera, E. (2015). Smart tourism destinations: An extended conception of smart cities focusing on human mobility. In information and communication technologies in tourism 2015 (pp. 363-375). Springer, Cham.

[12]Park, J. H., Lee, C., Yoo, C., & Nam, Y. (2016). An analysis of the utilization of Facebook by local Korean governments for tourism development and the network of smart tourism ecosystem. International Journal of Information Management, 36(6), 1320-1327.

[13] Buhalis, D., Harwood, T., Bogicevic, V., Viglia, G., Beldona, S., & Hofacker, C. (2019). Technological disruptions in services: lessons from tourism and hospitality. Journal of Service Management. 

[14] Zhu, W., Zhang, L., & Li, N. (2014). Challenges, function changing of government and enterprises in Chinese smart tourism. Information and Communication Technologies in Tourism, 10.

[15] Wang, X., Li, X. R., Zhen, F., & Zhang, J. (2016). How smart is your tourist attraction?: Measuring tourist preferences of smart tourism attractions via a FCEM-AHP and IPA approach. Tourism Management, 54, 309-320. 

[16] Zhang, L., Li, N., & Liu, M. (2012). On the basic concept of smarter tourism and its theoretical system. Tourism Tribune, 27(5), 66–73.

[17]Gretzel, U., Werthner, H., Koo, C., & Lamsfus, C. (2015). Conceptual foundations for understanding smart tourism smart tourism ecosystems. Computers in Human Behavior, 50, 558-563.

[18]Mill, R. C., & Morrison, A. M. (2002). The tourism system. Kendall Hunt

[19]Brandt, T., Bendler, J., & Neumann, D. (2017). Social media analytics and value creation in urban smart tourism  ecosystems. Information & Management, 54(6), 703-713

Sharing Data between Humanitarian Actors and Donor Governments

Across the humanitarian sector, data play an increasingly important role in response efforts. To implement water, shelter, protection, or food assistance programmes, humanitarian actors collect information, such as the gender or age of individual recipients of assistance. As a result, humanitarians need to manage large amounts of data, and recognise the importance of ensuring responsible use and protection of these data (see here and here).

In its recent guidance, the Inter-Agency Standing Committee (IASC) defines data responsibility in humanitarian operations as ‘the safe, ethical and effective management of personal and non-personal data for operational response, in accordance with established frameworks for personal data protection’ (IASC 2021, 7). Managing data responsibly requires comprehensive consideration, encompassing data collection, processing, analysis, use, storage, sharing, retention, and destruction. In a recent report, I investigate one component of data responsibility: data sharing between humanitarian actors and donor governments. The research draws on interviews with donors and humanitarians about data sharing practices and an examination of formal documents. While the report goes into more detail, here I focus on two issues – data and definitions, and expectations and standards – and why they matter for more effective humanitarian response.

Data and definitions

My research finds that references to ‘data’ in the context of humanitarian operations are usually generic and lack a consistent definition or even a shared terminology. Thus, among other definitions, data could refer to quantitative or qualitative, numbers or narratives, personal or non-personal data as well as financial, audit or compliance data, situational reporting, and aggregated or disaggregated indicator data (see table below).

Type of DataExample
Quantitative/numbersNumbers of beneficiaries/aid recipients
Qualitative/narrativeDescriptions of workshops or programme activities
PersonalDemographic data (names or contact information of aid recipients, group information, such as ethnicity)
Non-personalData about groups affected by the humanitarian situation, including needs or the threats they face
GroupData about groups of aid recipients (women, children, disabled), such as location
IndividualAge, sex or gender data about individual aid recipients
FinancialBudget reports
Audit/complianceReporting against legal or regulatory requirements, such as for safeguarding or counter-terrorism or sanctions
SituationalAnalysis of security situation
OrganisationalContact information for project officer
Disaggregated indicatorLocation-specific data for those assisted in a project
Aggregated indicatorTotal number of people assisted in a project
Types of Data

Varying expectations and standards

My research also found that donors have varying expectations of their partners – both among and within donor governments (e.g., at the country or headquarter levels) – and humanitarian actors have differing experiences of data sharing with donors. Expectations are informed by factors such as the complex regulatory frameworks for data (eg. host or donor government law, particularly in the context of privileges and immunities), the type of agreement (eg. grants or contracts), and funding allocations (eg. project-specific vs non-earmarked funding).

Donors varied in terms of the level of detail and the type of markers or indicators they requested. For example, United Nations agencies and Red Cross movement actors often have overarching agreements with donors that cover a range of activities in a country rather than project specific funding, as is often the case for non-government organisations (NGOs). The formal reporting for these overarching agreements is less specific, often requiring less formal sharing of disaggregated programme-related data even if it does not preclude or prevent informal requests for such data.

Both donors and humanitarians agreed that informal requests also occur, more often for context-specific information or aggregated data, and in some cases, for sensitive or personal data. The most common type that interviewees named was requests for data related to monitoring programme delivery, such as disaggregated or aggregated indicators. Even so, donors and humanitarians confirmed that standards varied for partners, indicating that in general NGOs were required to provide the most detailed information. By contrast, donors more often accepted annual reporting statements for the UN and Red Cross, often because of the nature of the funding allocations or agreements.

Why does this matter for more effective humanitarian response?

First, not clearly defining what ‘data’ means makes it possible to have inconsistencies in the logic of handling data, to request data that should not be shared, and to compromise the principle of ‘do no harm.’ To mitigate against this, both donors and humanitarian actors must clearly define the type(s) of data that will be shared in the course of a partnership or contractual relationship. Without clarity on the type of data under discussion, it will be difficult to increase data literacy in the humanitarian sector, or to advance conversations and practice to more responsibly manage and protect data.

Second, an indirect yet mutually-reinforcing relationship exists between requests to share data and the need to collect data. Although my research focused on data sharing as opposed to data collection, the interviews and documentation point to an indirect relationship between the two: data are collected in part because they are meant to be shared. Meaning, humanitarians collect data partly because donors ask them to share data. Requests for data sharing, in turn, are driven by differing needs, which leads to collecting more data than strictly needed, with potentially higher risks to those whose data are collected.

Finally, while humanitarians have the ability to push back against donor requests to share data, this ability is greatly influenced by power dynamics and trust. This in itself is a further dilemma, given that this level of trust is more likely to exist between donors and established humanitarian actors, creating another, largely invisible barrier for newer, less established, usually national or local humanitarian actors – a barrier that undermines efforts to ‘localise’ humanitarian response

Building the practice of responsible data sharing therefore requires a sector-wide effort to increase data literacy across humanitarian actors and donors, and ultimately to protect those who should be at the centre of humanitarian response – those affected by conflict, violence, or disaster.

Return of the “Third World”?

Are we seeing a return to the old notion of a “third world”?

Originating in the 1950s, the term “third world” was used to refer to those nations not aligned to either the bloc of Western democracies or the Eastern bloc of communist states.  Over time, and particularly since the end of the Warsaw Pact and dissolution of the Soviet Union, the term has fallen from use.

Recent events, though, may point to a revival in two senses.  First, politically.  Compare the two maps below: of first, second and third worlds in the 1970s[1]; and of reaction to Russia’s invasion of Ukraine in 2022[2].  Yes, there are plenty of differences but the neutral countries are almost all third world; and very few third world countries have taken a strongly-supporting or strongly-condemnatory stance.

Second, economically.  Resource procurement and global supply chains are being rethought.  Western democracies are seeking to delink from Russian energy[3], and Russia is turning East to find new sales outlets[4].  Russia and China are collaborating more closely on financial and other systems[5].  Western firms are considering moving supply chains closer to home, into domains that are both more secure and less abusive of human rights[6].  China’s “dual circulation” strategy presages less economic interaction with the West[7].  Overall, “democracies are banding together, as are autocracies”[8].

If there is some greater economic and political coalescence into a Western democratic bloc and an Eastern autocratic bloc, what are the implications for the “third world” of those countries outside those blocs?

Some will benefit as the blocs seek economic collaboration and political alliance.  Mexico, Vietnam, Indonesia and others are already benefitting, for example, from US firms’ search for non-Chinese production bases[9].  China’s Belt & Road Initiative and Western responses such as the US Build Back Better World initiative are competitively channelling infrastructure funding to lower-income countries[10].

Some states may be adept enough to play off the two blocs, squeezing concessions and enabling greater attention to local development goals and interests[11].  But many will come under pressure to pick a side, as seems particularly to be happening with Western pressure on states to turn away from Russia and China[12].  Third world history suggests, if they do this, then such states may then face attempts at destabilisation from the other bloc.

The world is different, more complex and more connected than it was during the era in which “Third World” arose as a concept.  The realities of first and second world bloc formation will likely be less than they might be.  Just as in the 1970s, and as the 2022 diagram above illustrates, many countries outside those blocs may be more aligned with one than the other.  But, nonetheless, echoes of the Third World are sufficiently strong to be taken seriously.













The Benefits of Mobile Phone Applications to Women Livestock Keepers in Zimbabwe

Pfavai Nyajeka and Richard Duncombe

Mobile phone applications have offered much value in the livelihoods of women in rural Zimbabwe.  Research conducted in resettlement areas during 2017 and 2018 used mixed methods to collect data on samples of women livestock keepers (Figure 1) who were household-heads (HHHs) or non-household heads (NHHs), providing an understanding of the unique forms of hardship that are imposed on married, single, divorced or widowed women in their pursuance of livelihoods.  The research investigated how women farmers used mobile phones to strengthen their position in livestock keeping and mitigate their vulnerability.

Figure 1. An Interview with a Woman Livestock Keeper in the Mashonaland East Province of Zimbabwe

Zimbabwe, in common with other sub-Saharan African countries, was experiencing a revolution in digital communications prior to and up until the end of the study period; but Zimbabweans, and particularly those in rural areas, remained disadvantaged due to poor electrical grid connections and digital connectivity compared with some other sub-Saharan African countries (Table 1).

Table 1. Digital Landscape: Selected Indicators for 2018

Country/Region % of rural population with access to electricity % of population using the Internet Mobile cellular subscriptions (per 100 inhabitants) (a) Secure internet servers (per 1 million inhabitants)  
Botswana 24 58 150 134
Kenya 58 19.5 96 217
South Africa 67 62.4 160 12,032
Zimbabwe 19 25 89 47
sub-Saharan Africa 22 29 94 794

Sources: Human Development Report (2019) and ITU (2018) Indicators Database; see: World Bank Open Data | Data

(a) including accounts with mobile money service providers.

Women livestock keepers in resettlement areas (Mashonaland East and Midlands) pursued their livelihoods within a challenging vulnerability context, typified by adverse climatic conditions, volatile markets and lack of support services (Figure 2).  Their ability to participate in local economic development was also constrained by their position within the largely patriarchal social structures that govern livestock keeping in Zimbabwe.

Figure 2. Community Meeting Place for Women Livestock Keepers in the Midlands Province of Zimbabwe

Use of mobile phones enabled the women to resolve problems quickly, saving time that could be more profitably spent on other income generating activities.  One HHH commented… “no one likes to be constantly travelling distances to chase buyers or debtors, so you find that a lot of women livestock farmers in this area depend on their mobile phones to remind buyers or debtors about upcoming livestock sales and money owed.  A lot of the time constant mobile phone reminders are enough.  Even when the person on the other end does not answer the phone or respond to a message or post, seeing that missed call, or text, or post, is often enough to put pressure on debtors.  Some (women) will post a reminder on social media group forums such as WhatsApp.  You find that this is very effective and frees up time and money for them (women livestock keepers) to focus their energies on other things”.

WhatsApp was used for group messaging and exchanging of photos and short videos related to problems or threats to livestock.  WhatsApp was particularly useful in instances when livestock farmers used group chats to coordinate an emergency veterinary department’s visit.  One focus group participant in the Midlands province (Figure 3) stated… “we as women farmers can communicate quickly… this also allows us to get advice on livestock disease outbreaks.  Although some women do not have smart phones, due to the expense, everyone knows someone who has access to information through community WhatsApp groups… no one in the community is left out as the message can be spread quickly, meaning we are quickly able to manage disease and risks” (Respondent 49).

Figure 3. A Group Meeting with Woman Livestock Keepers in the Midlands Province of Zimbabwe

In addition to WhatsApp, locally designed applications such as Kurima Mari[1]provided farmers with information on livestock management, livestock market updates and information on crop production, with English, Shona and Ndebele language options.  Another platform service was EcoFarmer[2]– introduced in 2013 as a ‘weather indexed insurance business’ and EcoCash[3]– a mobile payment solution for Econet customers that let farmers carry out financial transactions and pay bills.

The survey suggested a high degree of independent information searching on behalf of married women.  Phones enabled women livestock keepers to enquire about market prices either directly or through the app, ascertain where livestock demand was, quantities, and agreed periods of payment, before travelling to market.  

The survey results also showed significant usage of mobile banking apps (such as EcoCash).  Many women moved to mobile banking due to the cash shortages, but most also viewed mobile money as the safest means of transferring money and conducting transactions.  Mobile banking fees were generally lower compared to bank charges, and some farmers were able to make and receive payments and gain access to credit more easily.  

Some key findings from the study include…

  • A largely positive picture of the use of mobile phones amongst women livestock keepers.  Everyday use of mobile phones and applications has brought considerable benefits associated with better overall communications, helping to meet rural women farmers’ information needs in a timely manner.
  • A divergence of the results according to whether the woman livestock keeper is a HHH or NHH.  HHHs tend to be more active in relation to income generation due to not having to defer to the waged husband in the household.  The use of the phone tends to reinforce and strengthen this income earning activity for HHHs, both in relation to livestock keeping and other income earning opportunities.
  • Various limits and social pressures are placed on the NHHs in the use of their phones, thus restricting the ability of NHHs to accrue the full benefits of phone use.  The ability of NHHs to link with new social networks and other livestock intermediaries is limited.
  • Despite the potential benefits, the cost of accessing information with mobile phones could be prohibitive, even when considering the relatively low initial cost of buying (mostly) second-hand phones.  In part this is dealt with by opting for cheaper phone data bundles that facilitate use of web-based applications such as WhatsApp.

The results of this research will be presented at the International Conference on Information and Communication Technologies and Development (ICTD 2022) in Seattle between June 27th – 29th and published in the Conference proceedings.  International Conference on Information & Communication Technologies and Development (

[1] Kurima Mari is a family farming Knowledge Platform which gathers and digitized quality information on family farming from all over the world; including national laws and regulations, public policies, best practices, relevant data and statistics, researches, articles and publications. Kurima Mari – Apps on Google Play

[2] EcoFarmer provides farmers, government, contracting companies, NGOs and farmer unions a range of digital solutions to assist productivity across the agriculture value chain. Launched in 2013 as a weather indexed insurance and micro insurance product with an SMS based advisory service it has evolved to offering diversified services like Vaya Tractor, logistics, warehousing, cold chain, Hay Bailing, combine harvesting and soil testing. Farmers register to access the application by paying a small charge.  Services for Farmers – EcoFarmer

[3] EcoCash is a mobile payment solution for Econet customers in Zimbabwe. It facilitates financial transactions, like sending money, the purchase of prepaid airtime or data and payments for goods and services, using a mobile phone.


Latest Digital Development Outputs (Data, Labour, Platforms, Society, Ed Tech, MSc) from CDD, Manchester

Recent outputs – on Data-for-Development; Digital Labour; Digital Platforms; Digital Society; Ed Tech; MSc Programme – from Centre for Digital Development researchers, University of Manchester:


Data Powered Positive Deviance: Combining Traditional and Non-Traditional Data to Identify and Characterise Development-Related Outperformers” (open access) by Basma Albanna, Richard Heeks, Julia Handl and colleagues from the DPPD project, presents a new methodology through which datasets can be used to identify “positive deviants” – those who outperform their peers in development – and to identify and scale the factors behind their outperformance.

Publication Outperformance among Global South Researchers: An Analysis of Individual-Level and Publication-Level Predictors of Positive Deviance” (open access) by Basma Albanna, Julia Handl & Richard Heeks, uses interviews, a survey and analysis of online datasets to identify those among a group of global South researchers who outperform their peers.  It identifies characteristics of both the high-performing researchers and their publications.


Systematic Evaluation of Gig Work Against Decent Work Standards: The Development and Application of the Fairwork Framework” (open access) by Richard Heeks, Mark Graham, Paul Mungai, Jean-Paul Van Belle & Jamie Woodcock, explains the development and application of the Fairwork framework, which is used worldwide to rate gig economy platforms against decent work standards.

Stripping Back the Mask: Working Conditions on Digital Labour Platforms during the COVID-19 Pandemic” (open access) by Kelle Howson, Funda Ustek-Spilda, Alessio Bertolini, Richard Heeks and other colleagues from the Fairwork project, analyses the Covid policies of 191 platforms in 43 countries. It finds some positive worker protections but also entrenchment of precarious work as platforms leverage the opportunities arising from the crisis.


Digital Platforms for Development” (open access) by Brian Nicholson, Petter Nielsen & Johan Saebo, provides an editorial introduction to a special issue of Information Systems Journal on the link between digital platforms and development processes.

Driving the Digital Value Network: Economic Geographies of Global Platform Capitalism” (open access) by Kelle Howson, Fabian Ferrari, Funda Ustek-Spilda, Richard Heeks and other colleagues from the Fairwork project, uses insights from global value chain and global production network frameworks to analyse power imbalances and value extraction across territories by gig economy platforms.


“Toolkit for Measuring Digital Skills and Digital Literacy“ (open access) by authors at CSIS Indonesia, supported by Matthew Sharp, offers a comprehensive and original framework for measuring digital skills in Indonesia and other G20 countries. The toolkit incorporates insights from pilot individual and firm-level surveys on digital skills undertaken by CSIS in the Greater Jakarta area.

How can Smart City Shape a Happier Life? The Mechanism for Developing a Happiness Driven Smart City” by Huiying Zhu, Liyin Shen & Yitian Ren, introduces a Happiness Driven Smart City (HDSC) mechanism, composed of a three-layer structure and underpinned by a set of strategic measures. A case study shows the HDSC mechanism’s effectiveness in helping decision makers understand the status quo, strengths and weaknesses of smart city development in their context, so that their SC blueprint can be better aligned towards a happiness-driven direction.


The Effectiveness of Technology‐Supported Personalised Learning in Low‐and Middle‐Income Countries” (open access) by Louis Major, Gill Francis & Maria Tsapali, provides a meta-analysis examining the impact of students’ use of technology that personalises and adapts to learning level.

Evaluating Digital Personalised Learning Tools in Kenya: A New Research Study” (blog) by Becky Daltry, Louis Major and others, reports on a new research study to rigorously evaluate the integration of digital personalised learninginto Kenyan classrooms for young children, aged between 4-8 years old.


Centre for Digital Development staff provide the core directorship and teaching for the University’s new MSc programme in Digital Development, which will launch in Sept 2022.

Has COVID-19 deepened gender digital divides? Insights from platform-driven agricultural value chains in Kenya

Aarti Krishnan, Hallsworth Research Fellow, University of Manchester

The problem: Deepening digital gender divides in platform-driven value chains during COVID-19

The proliferation of digital agricultural platforms (which offer bundling of multiple services) is touted as a way to support women to upgrade in value chains.  However, much research has shown that in platform-driven agricultural value chains, gender digital divides exist. Especially in relation to the inability to ‘access’ or ‘participate’ on platforms, which may arise due to various reasons cited such as digital illiteracy or technophobia.

 There is less evidence to suggest whether gender digital divides are exacerbated post-participation, i.e. once men and women are accessing agricultural services on a platform. Are men and women able to ‘access’ the digital services of the platform equally, i.e. do female farmers experience greater delays in receiving the digital services they need, compared to men? Additionally, do women and men have different experiences in how digital products and services are ‘used’? Studies to date show mixed results in terms of the frequency of engagement and the types of digital services demanded by female farmers, but we know little about how all this has been impacted by COVID-19. Through COVID-19, supply chains have been disrupted, which has possible implications on exacerbating issues related to the ‘access’ and ‘use’ of digital services – with important questions arising on ‘who gets access and how’ to digital services and in turn on ‘what can be used’. Thus, possibly deepening the existing gender digital divides.

The waves of COVID-19 in Kenya

To investigate this issue, analysis was undertaken of agricultural platform transactions, capturing data on five agricultural seasons between March 2019-Aug 2020: two seasons before COVID-19, and three season during the pandemic. The data was gathered from one of Kenya’s largest farmer-owned cooperative platforms which works through SMS and USSD options for cereal, bean, and soybean farmers. In order to unpack implications on whether gender digital divides were exacerbated through COVID-19, the data was divided into three waves, which indicated different stringency measures taken by governments and varied levels of fear amongst the public.

–  The first wave of COVID-19 overlapped with agricultural season 3 (March-Aug 2020): during this time there were major national lockdowns inhibiting movement, closures of workplaces, schools, reducing availability of public services coupled with fast growing new cases and general panic among the population.

– The second wave of COVID-19 overlapped with agricultural season 4 (Sept 2020-Feb 2021): this involved easing of lockdown measures, coupled with a small but steady decrease in number of cases. The levels of panic were also less amongst the public.

– During the third wave of COVID-19 (March-Aug 2021), cases began climbing again and there were intermittent lockdowns across the country. Thus, there was a bit more fear amongst the public, but not at the same level as in the first COVID-19 wave.

Did the waves of COVID-19 deepen gender digital divides?

‘Use’ is explicated as how farmers use the app i.e. the transaction stability (number of transactions farmers perform); and the types of services they demanded (e.g.  pesticides, fertilizers, mechanisation, good agricultural practices etc); while ‘access’ is the time taken by the platform to supply different services that farmers demanded.

Figure 1: Use and access of digital services

Source: Author’s Construction

In terms of ‘use’, both men and women increased the number of transactions on the app during COVID as compared to pre-COVID 19 (figure 1). However, the increase for women was steeper than that for men – this difference was consistent, though the jump in wave 1 is particularly stark. This likely reflected woman being more fearful than men about COVID-19 disrupting their production. As eloquently explained by one women’s group in Meru (Kenyan county):

 “if we don’t get services on time, and in the right quantity, we cannot produce enough, and if we can’t produce, we cannot feed our children or send them to school.”

Simultaneously, female farmers throughout COVID-19 began ‘using’ a more diverse set of services, compared to men, with interviews suggesting that using different services allowed them to maximize their chances of increasing crop productivity and income. Thus, female farmers attempted to reduce risk by trying to ‘produce carefully and efficiently’, while the data for male farmers indicates almost no change in services, thus suggesting no change in production methods.

However, even with an increase in ‘use’, women struggled with ‘access’. This means that despite wanting more services, they were not able to fully receive them. Figure 1 indicates that this digital gender divides already existed pre-COVID, with women having less ‘access’ to services (with longer time lags compared to men). However, during COVID-19 these issues were exacerbated across the waves, with access issues (time lags) increasing to as much as 6 weeks to receive services by women, compared to only 4 weeks for men. ‘Access’ issues were worst felt in wave 1, where lockdown was rampant, and eased slightly in wave 2, only to increase again by wave 3.

Ultimately this shows that not only did gender digital divides deepen during the pandemic, but that even by wave 3, when things were starting to go back to normal, the level of ‘access’ did not reach its pre-pandemic levels.

How can reducing deep gender digital divides promote resilience?

Overarchingly, the results highlight that to support resilience of women through the pandemic requires increasing inclusivity by providing female farmers ‘easier access’ to services. This can in turn considerably increase overall performance of agriculture in times of crisis.