Using loyalty card records and machine learning to understand how self-medication purchasing behaviours vary seasonally in England, 2012–2014

This paper examines objective purchasing information for inherently seasonal self-medication product groups using transaction-level loyalty card records. Predictive models are applied to predict future monthly self-medication purchasing. Analyses are undertaken at the lower super output area level, allowing the exploration of ~300 retail, social, demographic and environmental predictors of purchasing. The study uses a tree ensemble predictive algorithm, applying XGBoost using one year of historical training data to predict future purchase patterns. The study compares static and dynamic retraining approaches. Feature importance rank comparison and accumulated local effects plots are used to ascertain insights of the influence of different features. Clear purchasing seasonality is observed for both outcomes, reflecting the climatic drivers of the associated minor ailments. Although dynamic models perform best, where previous year behaviour differs greatly, predictions had higher error rates. Important features are consistent across models (e.g. previous sales, temperature, seasonality). Feature importance ranking had the greatest difference where seasons changed. Accumulated local effects plots highlight specific ranges of predictors influencing self-medication purchasing. Loyalty card records offer promise for monitoring the prevalence of minor ailments and reveal insights about the seasonality and drivers of over-the-counter medicine purchasing in England

Exploring the role of smartphone technology for citizen science in agriculture

Citizen science is the involvement of citizens, such as farmers, in the research process. Citizen science has become increasingly popular recently, supported by the proliferation of mobile communication technologies such as smartphones. However, citizen science methodologies have not yet been widely adopted in agricultural research. Here, we conducted an online survey with 57 British and French farmers in 2014. We investigated (1) farmer ownership and use of smartphone technologies, (2) farmer use of farm-specific management apps, and (3) farmer interest and willingness to participate in agricultural citizen science projects. Our results show that 89 % respondents owned a smartphone, 84 % used it for farm management, and 72 % used it on a daily basis. Fifty-nine percent engaged with farm-specific apps, using on average four apps. Ninety-three percent respondents agreed that citizen science was a useful methodology for data collection, 93 % for real-time monitoring, 83 % for identification of research questions, 72 % for experimental work, and 72 % for wildlife recording. Farmers also showed strong interest to participate in citizen science projects, often willing to commit substantial amounts of time. For example, 54 % of British respondents were willing to participate in farmland wildlife recording once a week or monthly. Although financial support was not always regarded as necessary, experimental work was the most likely activity for which respondents thought financial support would be essential. Overall, this is the first study to quantify and explore farmers' use of smartphones for farm management, and document strong support for farm-based citizen science projects. (Résumé d'auteur

'Digital by Default' and the 'hard to reach': Exploring solutions to digital exclusion in remote rural areas

Williams, F., Philip, L., Fairhurst, G., & Farrington, J. (2016). ‘Digital by Default’ and ‘the hard to reach’: exploring solutions to digital exclusion in remote rural areas. Local Economy, 31(7), 757-777. DOI: 10.1177/0269094216670938. Copyright © 2016 SAGE. Reprinted by permission of SAGE Publications.In the UK, the geography of Information and Communication Technology (ICT) infrastructure required for Internet connectivity is such that high speed broadband and mobile phone networks are generally less available in rural areas compared with urban areas or, in other words, as remoteness and population sparsity increase so too does the likelihood of an area having no or very poor broadband connectivity. Against a policy backdrop of UK Government efforts to bring forward network infrastructure upgrades and to improve the accessibility of broadband services in locations where there is a weak commercial investment case, this paper considers the options for the ‘final few’ in the prevailing ‘Digital by Default’ public services context. The paper outlines the Rural Public Access WiFi Services project, a study focused upon enabling Internet connectivity for commercially ‘hard to reach’ rural areas in the UK. The Rural Public Access WiFi Services concept and the experiment are introduced before findings from a pilot deployment of a broadband service to households in a remote rural area, who may be classified as ‘digitally excluded’, are presented. The paper then reflects on our field experiment and the potential of the Rural Public Access WiFi Services model as a solution to overcoming some of the digital participation barriers manifest in the urban–rural divide. Early indications show that the Rural Public Access WiFi Services model has the potential to encourage participation in the Digital Economy and could aid the UK Government’s Digital by Default agenda, although adoption of the model is not without its challenges

Broadband speed equity: A new digital divide?

The availability and performance of broadband connectivity is becoming an increasingly important issue across much of the developed world as the prevalence of richer media services and growing populations have generated increasing demands on existing networks. The heterogeneous geography of broadband infrastructure and investments results in variable service provision, and as such, there exist large disparities in access and performance within different spatio-temporal locations. This paper presents analysis of 4.7 million crowdsourced Internet speed test results that were compiled between 2010 and 2013 alongside various indicators of socio-spatial structure to map disparities in English broadband speed between and within urban areas. Although average speeds have improved over time, inequity is shown to emerge between different societal groups and locations. Short-term dynamics also reveal that in areas of different density, speeds can fall dramatically during peak hours, thus influencing the availability of services. The apparent disparities in access and performance represent a major issue as Internet use becomes increasingly ubiquitous in our everyday lives, with inequalities evoking social and economic disadvantage at local and national scales. This work resonates with UK government policy that has stimulated considerable investment in improving infrastructure, and presents analysis of an expansive crowd sourced “big data” resource for the first time

Measuring the spatial vulnerability of retail centres to online consumption through a framework of e-resilience

This paper presents e-resilience as a framework for assessing the extent to which retail centres have spatially differentiated vulnerability to the impacts of online consumption. This extends the conceptual model of resilience as applied to retail, and is operationalised through a novel methodology that develops two indices that balance both supply and demand influences. We describe the creation of a composite e-resilience indicator, and then calculate it for retail centres across England. Our findings suggest a geographic polarising effect, with least vulnerable centres identified as large and more attractive or as smaller local destinations with a focus on convenience shopping. Mid-sized centres were typically shown to be the most exposed, and are argued as having a less clearly defined function in contemporary retail. Such findings have wide policy relevance to stakeholders of retail interested in the future configuration of sustainable and resilient provision