All Outputs (7)

Detecting iodine deficiency risks from dietary transitions using shopping data (2024)
Journal Article
Mansilla, R., Long, G., Welham, S., Harvey, J., Lukinova, E., Nica-Avram, G., …Goulding, J. (2024). Detecting iodine deficiency risks from dietary transitions using shopping data. Scientific Reports, 14(1), Article 1017. https://doi.org/10.1038/s41598-023-50180-7

Plant-based product replacements are gaining popularity. However, the long-term health implications remain poorly understood, and available methods, though accurate, are expensive and burdensome, impeding the study of sufficiently large cohorts. To i... Read More about Detecting iodine deficiency risks from dietary transitions using shopping data.

Assessing the value of integrating national longitudinal shopping data into respiratory disease forecasting models (2023)
Journal Article
Dolan, E., Goulding, J., Marshall, H., Smith, G., Long, G., & Tata, L. J. (2023). Assessing the value of integrating national longitudinal shopping data into respiratory disease forecasting models. Nature Communications, 14, Article 7258. https://doi.org/10.1038/s41467-023-42776-4

The COVID-19 pandemic led to unparalleled pressure on healthcare services. Improved healthcare planning in relation to diseases affecting the respiratory system has consequently become a key concern. We investigated the value of integrating sales of... Read More about Assessing the value of integrating national longitudinal shopping data into respiratory disease forecasting models.

Using mobile money data and call detail records to explore the risks of urban migration in Tanzania (2022)
Journal Article
Lavelle-Hill, R., Harvey, J., Smith, G., Mazumder, A., Ellis, M., Mwantimwa, K., & Goulding, J. (2022). Using mobile money data and call detail records to explore the risks of urban migration in Tanzania. EPJ Data Science, 11(8), Article 28. https://doi.org/10.1140/epjds/s13688-022-00340-y

Understanding what factors predict whether an urban migrant will end up in a deprived neighbourhood or not could help prevent the exploitation of vulnerable individuals. This study leveraged pseudonymized mobile money interactions combined with cell... Read More about Using mobile money data and call detail records to explore the risks of urban migration in Tanzania.

Machine learning methods for “wicked” problems: exploring the complex drivers of modern slavery (2021)
Journal Article
Lavelle-Hill, R., Smith, G., Mazumder, A., Landman, T., & Goulding, J. (2021). Machine learning methods for “wicked” problems: exploring the complex drivers of modern slavery. Humanities and Social Sciences Communications, 8, Article 274. https://doi.org/10.1057/s41599-021-00938-z

Forty million people are estimated to be in some form of modern slavery across the globe. Understanding the factors that make any particular individual or geographical region vulnerable to such abuse is essential for the development of effective inte... Read More about Machine learning methods for “wicked” problems: exploring the complex drivers of modern slavery.

Exogenous cognition and cognitive state theory: The plexus of consumer analytics and decision-making (2020)
Journal Article
Smith, A., Harvey, J., Goulding, J., Smith, G., & Sparks, L. (2020). Exogenous cognition and cognitive state theory: The plexus of consumer analytics and decision-making. Marketing Theory, 21(1), 53-74. https://doi.org/10.1177/1470593120964947

We develop the concept of exogenous cognition (ExC) as a specific manifestation of an external cognitive system (ECS). Exogenous cognition describes the technological and algorithmic extension of (and annexation of) cognition in a consumption context... Read More about Exogenous cognition and cognitive state theory: The plexus of consumer analytics and decision-making.

Identifying food insecurity in food sharing networks via machine learning (2020)
Journal Article
Nica-Avram, G., Harvey, J., Smith, G., Smith, A., & Goulding, J. (2021). Identifying food insecurity in food sharing networks via machine learning. Journal of Business Research, 131, 469-484. https://doi.org/10.1016/j.jbusres.2020.09.028

© 2020 Elsevier Inc. Food insecurity in the UK has captured public attention. However, estimates of its prevalence are deeply contentious. The lack of precision on the volume of emergency food assistance currently provided to those in need is made ev... Read More about Identifying food insecurity in food sharing networks via machine learning.

The Smart Home: How Consumers Craft New Service Networks by Combining Heterogeneous Smart Domestic Products (2020)
Journal Article
Harvey, J., Poorrezaei, M., Woodall, T., Nica-Avram, G., Smith, G., Ajiboye, T., …Zhu, K. (2020). The Smart Home: How Consumers Craft New Service Networks by Combining Heterogeneous Smart Domestic Products. Journal of Service Research, 23(4), 504-526. https://doi.org/10.1177/1094670520929095

Service research suggests homes are becoming increasingly connected as consumers automate and personalize new forms of service provision. Yet large-scale empirical evidence on how and why consumers automate smart domestic products is lacking. To addr... Read More about The Smart Home: How Consumers Craft New Service Networks by Combining Heterogeneous Smart Domestic Products.