A social network analysis of ICTD conferences (2006–2017)

Mukerji, Maitrayee; Chauhan, Unnati

doi:10.1080/02681102.2019.1685930

Cited by 11 publications

(5 citation statements)

References 34 publications

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“…The average path length is 1.0, which gives a proportion of correspondence effectiveness for a whole system, by estimating the briefest conceivable way between all nodes in the network. The average clustering coefficient here is 0.5, which seems reasonable in consideration of the infancy of the research field; the tendency of a network to have subgroups is measured by the clustering coefficient (Mukerji and Chauhan, 2020;Watts and Strogatz, 1998). 4.3.2 Data clustering.…”

Section: Most Influential Articlesmentioning

confidence: 80%

Human resource analytics: a review and bibliometric analysis

Qamar

Samad

2021

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PurposeThis paper aims to identify the current research trends and set the future research agenda in the area of human resource (HR) analytics by an extensive review of the existing literature. The paper aims to capture state of the art and develop an exhaustive understanding of the theoretical foundations, concepts and recent developments in the area.Design/methodology/approachA portfolio of 125 articles collected from the Scopus database was systematically analyzed using a two-tier method. First, the evolution, current state of the literature and research clusters are identified using bibliometric techniques. Finally, using content analysis, the research clusters are studied to develop the future research agenda.FindingsBased on the bibliometric analysis, network analysis and content analysis techniques, this study provides a comprehensive review of the existing literature. The study also highlights future research themes by identifying knowledge gaps based on content analysis of research clusters.Research limitations/implicationsThe evolution and the current state of the HR analytics literature are presented. Some specific research questions are also provided to help future research.Originality/valueThis study enriches the literature of HR analytics by integrating bibliometric analysis and content analysis to develop a more systematic and exhaustive understanding of the research area. The findings of this study may assist fellow researchers in furthering their research in the identified research clusters.

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Section: Most Influential Articlesmentioning

confidence: 80%

Human resource analytics: a review and bibliometric analysis

Qamar

Samad

2021

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“…If ITU AI for Good demonstrates how a major development actor has moved from one initiative to the other, the case of Microsoft offers a case of a private corporation doing the same. Between 2006 and 2017 Microsoft was one of the top contributors of papers to the annual academic ICT and Development conference (Mukerji and Chauhan, 2020) and Microsoft's involvement with UN-sponsored ICT4D efforts is well documented (e.g. Leye, 2007).…”

Section: Transitions From Ict4d To Ai For Goodmentioning

confidence: 99%

Stepping back from Data and AI for Good – current trends and ways forward

Aula

Bowles

2023

Big Data & Society

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Various ‘Data for Good’ and ‘AI for Good’ initiatives have emerged in recent years to promote and organise efforts to use new computational techniques to solve societal problems. The initiatives exercise ongoing influence on how the capabilities of computational techniques are understood as vehicles of social and political change. This paper analyses the development of the initiatives from a rhetorical slogan into a research program that understands itself as a ‘field’ of applications. It discusses recent academic literature on the topic to show a problematic entanglement between the promotion of initiatives and prescriptions of what ‘good’ ought to be. In contrast, we call researchers to take a practical and analytical step back. The paper provides a framework for future research by calling for descriptive research on the composition of the initiatives and critical research that draws from broader social science debates on computational techniques. The empirical part of the paper provides first steps towards this direction by positioning Data and AI for Good initiatives as part of a single continuum and situating it within a historical trajectory that has its immediate precursor in ICT for Development initiatives.

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“…According to the social network analysis of researchers at the International Conference on Information and Communication Technologies and Development (ICTD), there are fewer collaborative ties among academic institutions in developing countries. 27 Bibliometric studies provide further evidence that collaboration between African countries is weak and that regional integration of collaborative research networks is lacking. 28,29,30 Toivanen and Ponomariov 28 found Europe to be Africa's largest collaboration partner in terms of research outputs, while South Africa and Nigeria were the leading research countries in Africa and integrative hubs in their respective regions (Southern and Western Africa).…”

Section: Research Collaboration In Information and Communication Tech...mentioning

confidence: 99%

Research collaboration in asymmetric power relations: A study of postgraduate students’ views

Biljon¹,

Mwapwele²

2023

TDSA

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Collaboration among researchers and across disciplinary, organisational and cultural boundaries is essential for addressing the increasingly complex challenges and opportunities facing international development. Despite the known advantages and various incentives, research collaboration within Africa (specifically within South Africa) is lacking. To better understand the reasons for this lack of research collaboration, this study explored collaboration between students and supervisors in an information and communication technology for development (ICT4D) postgraduate student project in South Africa. South Africa, a country with major social inequalities and asymmetric power relations, provides an appropriate context. The students’ perspectives provided a space for investigating the collaboration factors by unpacking the capability inputs according to Robeyns’ representation of personal capabilities. Data were captured from a survey and focus groups (FG) with students and supervisors in ICT4D from different universities in South Africa. Thematic analysis was used to identify and link the participants’ expectations of research collaboration with their perceptions of the challenges of such collaborations. The contribution is a conceptualisation of the main components representing research collaboration viewed in terms of personal capabilities, including the factors that influence collaboration.Transdisciplinarity contribution: Research collaboration is fundamental to promoting multi-, inter- and transdisciplinary research. The novelty of this study lies in applying a theoretical lens from the field of human development to explore research collaboration in the transdisciplinary field of ICT4D. Given the research application context and the theoretical lens applied, the findings have implications for initiatives and policies on funding transdisciplinary research collaboration.

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A social network analysis of ICTD conferences (2006–2017)

Cited by 11 publications

References 34 publications

Human resource analytics: a review and bibliometric analysis

Human resource analytics: a review and bibliometric analysis

Stepping back from Data and AI for Good – current trends and ways forward

Research collaboration in asymmetric power relations: A study of postgraduate students’ views

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