Robust statistical methods for point of sale designs, the example of healthcare snack and drink vending

Abstract

Purpose The experiment introduces nutritional labelling, healthier products and product placement designs to the hospital vending machines, to promote healthy lifestyles. Design/methodology/approach The site where this experiment happens is a major London hospital, serving over a million patients every year. In the experiment, the hospital’s snack and drink vending machines are redesigned. The impact on product sales are then analysed using robust statistical methods. Findings Nutritional labelling has a statistically significant impact on product sales. Less of the unhealthiest products are sold. Healthier products and product placement designs have a larger impact but with less statistical significance. They require further testing. Research limitations/implications Experts in service operations can use this experiment’s regression modelling methods. The methods are ideal for measuring change over time in counting data sets in complex real world environments. Practical implications There are suggestions for practical vending service change in this research. They are in line and add a practical example to Government policy guidance. Social implications People using the redesigned vending machines have more opportunity for healthy lifestyle choices. Originality/value The experiment provides statistical evidence in support of catering for healthier lifestyles.

Does food import contribute to rising obesity in low‐ and middle‐income countries?

“…In order to understand how it affects the prevalence of obesity, it is then important to disjoint its overall effects from those of food trade and, more importantly, from those of some specific food groups that are associated to unhealthy diets. Second , in doing so, it is essential to account for potential reverse causality, as trade and import flows may be influenced by public health policies to protect domestic population from nutrition‐related diseases when they are widespread (Campbell et al, 2020; Thow et al, 2010; Von Tigerstrom, 2013). Alternatively, food import flows might be affected by consumption preferences which, in turn, are related to dietary patterns; in this regard, a high prevalence of obesity may lead to higher food import, especially for unhealthy items.…”