Overcoming data sparsity

Unilever is currently designing and testing recommendation algorithms that would make recommendations about products to online customers given the customer ID and the current content of their basket. Unilever collected a large amount of purchasing data that demonstrates that most of the items (around 80%) are purchased infrequently and account for 20% of the data while frequently purchased items account for 80% of the data. Therefore, the data is sparse, skewed and demonstrates a long tail. Attempts to incorporate the data from the long tail, so far have proved difficult and current Unilever recommendation systems do not incorporate the information about infrequently purchased items. At the same time, these items are more indicative of customers' preferences and Unilever would like to make recommendations from/about these items, i.e. give a rank ordering of available products in real time. Study Group suggested to use the approach of bipartite networks to construct a similarity matrix that would allow the recommendation scores for different products to be computed. Given a current basket and a customer ID, this approach gives recommendation scores for each available item and recommends the item with the highest score that is not already in the basket. The similarity matrix can be computed offline, while recommendation score calculations can be performed live. This report contains the summary of Study Group findings together with the insights into properties of the similarity matrix and other related issues, such as recommendation for the data collection

Culture modulates implicit ownership-induced self-bias in memory

The relation of incoming stimuli to the self implicitly determines the allocation of cognitive resources. Cultural variations in the self-concept shape cognition, but the extent is unclear because the majority of studies sample only Western participants. We report cultural differences (Asian versus Western) in ownership-induced self-bias in recognition memory for objects. In two experiments, participants allocated a series of images depicting household objects to self-owned or other-owned virtual baskets based on colour cues before completing a surprise recognition memory test for the objects. The ‘other’ was either a stranger or a close other. In both experiments, Western participants showed greater recognition memory accuracy for self-owned compared with other-owned objects, consistent with an independent self-construal. In Experiment 1, which required minimal attention to the owned objects, Asian participants showed no such ownership-related bias in recognition accuracy. In Experiment 2, which required attention to owned objects to move them along the screen, Asian participants again showed no overall memory advantage for self-owned items and actually exhibited higher recognition accuracy for mother-owned than self-owned objects, reversing the pattern observed for Westerners. This is consistent with an interdependent self-construal which is sensitive to the particular relationship between the self and other. Overall, our results suggest that the self acts as an organising principle for allocating cognitive resources, but that the way it is constructed depends upon cultural experience. Additionally, the manifestation of these cultural differences in self-representation depends on the allocation of attentional resources to self- and other-associated stimuli

Knowledge-aware Complementary Product Representation Learning

Learning product representations that reflect complementary relationship plays a central role in e-commerce recommender system. In the absence of the product relationships graph, which existing methods rely on, there is a need to detect the complementary relationships directly from noisy and sparse customer purchase activities. Furthermore, unlike simple relationships such as similarity, complementariness is asymmetric and non-transitive. Standard usage of representation learning emphasizes on only one set of embedding, which is problematic for modelling such properties of complementariness. We propose using knowledge-aware learning with dual product embedding to solve the above challenges. We encode contextual knowledge into product representation by multi-task learning, to alleviate the sparsity issue. By explicitly modelling with user bias terms, we separate the noise of customer-specific preferences from the complementariness. Furthermore, we adopt the dual embedding framework to capture the intrinsic properties of complementariness and provide geometric interpretation motivated by the classic separating hyperplane theory. Finally, we propose a Bayesian network structure that unifies all the components, which also concludes several popular models as special cases. The proposed method compares favourably to state-of-art methods, in downstream classification and recommendation tasks. We also develop an implementation that scales efficiently to a dataset with millions of items and customers

Consumers preferences for dairy-alternative beverage using home-scan data in Catalonia

The changing lifestyles and the growing health concerns towards the negative impact of the saturated fatty acids originating from animals has increased consumers’ preferences for dairy-alternative products. These products belong to the food and beverage classification that is similar to certain types of dairy-based products in terms of texture and flavor, and has similar nutritional benefits. In this context, we seek to identify the willingness to pay (WTP) for the most important attributes that consumers take into account when purchasing the dairy-alternative drinks. A revealed preference discrete choice experiment was carried out using home-scan data belonging to ©Kantar Worldpanel (Barcelona, Spain) regarding the consumption of dairy-alternative drinks in Catalonia (Spain) in 343 households. Furthermore, factors that affect the purchasing frequency of this type of product were analyzed through the Poisson and negative binomial models. Results showed that price was the major driving factor, followed by the original non-dairy beverage flavor attribute. The original non-dairy beverage flavor compared to other added ingredients and tastes showed higher WTP when purchasing the non-dairy alternative. Marketing strategies should promote products by focusing on the “original” and “pure” version of the product without additional ingredients, or through reduction of the undesirable compounds if they exist in these kinds of beveragesPostprint (published version

EBSLG Annual General Conference, 18. - 21.05.2010, Cologne. Selected papers

Am 18.-21. Mai 2010 fand in der Universitäts- und Stadtbibliothek (USB) Köln die „Annual General Conference“ der European Business Schools Librarians Group (EBSLG) statt. Die EBSLG ist eine relativ kleine, aber exklusive Gruppe von Bibliotheksdirektorinnen und –direktoren bzw. Bibliothekarinnen und Bibliothekaren in Leitungspositionen aus den Bibliotheken führender Business Schools. Im Mittelpunkt der Tagung standen zwei Themenschwerpunkte: Der erste Themenkreis beschäftigte sich mit Bibliotheksportalen und bibliothekarischen Suchmaschinen. Der zweite Themenschwerpunkt Fragen der Bibliotheksorganisation wie die Aufbauorganisation einer Bibliothek, Outsourcing und Relationship Management. Der vorliegende Tagungsband enthält ausgewählte Tagungsbeiträge

Customer mobility and congestion in supermarkets

The analysis and characterization of human mobility using population-level mobility models is important for numerous applications, ranging from the estimation of commuter flows in cities to modeling trade flows between countries. However, almost all of these applications have focused on large spatial scales, which typically range between intra-city scales to inter-country scales. In this paper, we investigate population-level human mobility models on a much smaller spatial scale by using them to estimate customer mobility flow between supermarket zones. We use anonymized, ordered customer-basket data to infer empirical mobility flow in supermarkets, and we apply variants of the gravity and intervening-opportunities models to fit this mobility flow and estimate the flow on unseen data. We find that a doubly-constrained gravity model and an extended radiation model (which is a type of intervening-opportunities model) can successfully estimate 65--70\% of the flow inside supermarkets. Using a gravity model as a case study, we then investigate how to reduce congestion in supermarkets using mobility models. We model each supermarket zone as a queue, and we use a gravity model to identify store layouts with low congestion, which we measure either by the maximum number of visits to a zone or by the total mean queue size. We then use a simulated-annealing algorithm to find store layouts with lower congestion than a supermarket's original layout. In these optimized store layouts, we find that popular zones are often in the perimeter of a store. Our research gives insight both into how customers move in supermarkets and into how retailers can arrange stores to reduce congestion. It also provides a case study of human mobility on small spatial scales

Developing a theoretical framework of consumer logistics from a comprehensive literature review

Paper delivered at the 21st Logistics Research Network annual conference 2016, 7th-9th September 2016, Hull. Abstract Purpose: Logistics as a business discipline entered academic consciousness in the mid-1960s when work by marketing academics discussed the integration between marketing and logistics. However, the link with consumers in the point-of-origin to point-of-consumption typology was not explored until Granzin and Bahn’s conceptualisation and model of consumer logistics (CL) in 1989. Since then few contributions have followed and neglecting this aspect of logistics research is difficult to understand. Firstly, the consumer represents a productive resource as an important downstream supply chain member carrying out logistics activities and tasks. Secondly, logistics activities directed towards the consumer also act along a marketing axis, i.e. satisfaction and loyalty for an overall shopping experience both from transaction-specific and cumulative levels are influenced by product quality elements and service-related dimensions. This paper presents a theoretical framework for deeper research into the topic of CL. Research approach: A literature review was conducted first following philosophical or field conceptualization principles as a first step towards theory building. Data bases of major logistics and SCM journals were searched however the publication timeframe was not limited as the concept of CL is relatively new. Selection criteria and Boolean searches were conducted and keywords used within article abstracts and title fields of search. Due to a relative scarcity of contributions obtained by that approach and in-line with the principle of methodological triangulation, additional search strategies were applied using Google/ Google Scholar searches. The majority of the cited contributions were also cross-referenced and included in the analysis if appropriate. Findings and originality: The literature search yielded a mother population of 46 documents of which 24 have been considered relevant for further consideration. The document harvest was analysed using Granzin and Bahn’s original CL issues and additional features in order to explore, structure, articulate, orient, hierarchize and delimit the field of CL in the 21st century. Research impact: This paper updates Granzin and Bahn’s work to outline new and distinctive features of CL given the obvious changes in the retail landscape since their work 27 years ago, such as the Internet and omni-channel retailing. More broadly, conceptualizing CL in a holistic manner enhances SCM theory building by questioning traditional notions of time and space ranges, isolated marketing-merchandizing/logistics considerations, traditional understandings of sites /locations, and equipment (e.g. shopping cart or basket)/ infrastructure/ layout and buying stages that are in-line with external evolutions on organizational, technological and societal levels. Practical impact: Understanding and improving CL contributes to supply chain competitiveness via increased consumer satisfaction and loyalty, better order fulfilment via cost reductions and efficiency increases, and enhanced differentiation targeting consumers receptive for sustainability/ ethics/ mobility/ lifestyle/ life quality issues. A dedicated approach to CL also enhances management of repercussions and interactions with upstream/ B2B logistics, visible through retail stores being both a destination and a source for inventory, the rise of drop-ship vendor relationships and new fulfilment options and related infrastructure

Factors that Impact Access to Quality Food in the Inner City

Food insecurity is an issue that disproportionately affects inner city communities. While food insecurity focuses more on the individual level, food deserts affect the community on a societal level. Food insecurity is an issue of public health significance because it affects food environments and has negative consequences on those living in food insecure communities. This review discusses factors that impact access to quality food in inner city communities such as lack of grocery stores, school environments and food affordability and how these factors can lead to an inadequate food supply, poor nutrition, obesity and chronic diseases. Food insecurity often results in an increase in food related health risks such as malnutrition, obesity, type 2 diabetes and cardiovascular disease among other things which can ultimately result in death. Food affordability, knowledge of school environments and supermarket politics regarding negative outcomes of food insecurity are highlighted. Recommendations are provided to address ways that inner city communities can have better access to nutritional food. These recommendations include mobilizing the community via the Mobilizing for Action through Planning and Partnerships (MAPP) strategic approach, food labeling and diversifying neighborhood income

No. 14: The Impact of Proximity to Wet Markets and Supermarkets on Household Dietary Diversity in Nanjing City, China

Existing studies suggest that despite the proliferation of supermarkets, traditional wet markets have persisted in many countries and have been playing an important role in people’s daily food access. Yet, studies investigating the issue of food access and its influences on food security have mainly focused on food deserts and the proximity to supermarkets, with limited focus on wet markets and other food outlets. This study investigates the influence of the proximity to wet markets and supermarkets on urban household dietary diversity in Nanjing. Based on the data collected through a citywide survey in 2015 and the map data of wet markets and supermarkets, the Poisson regression model was deployed to examine the correlations between geographical proximity to supermarkets and wet markets and household dietary diversity. The results show that the coefficients for the distance to the nearest wet market are not statistically significant. Although the coefficients for the distance to nearest supermarket are statistically significant, they were too minor to be of practical importance. We argue, however, that the insignificant correlations reflect exactly the high physical accessibility to food outlets and the extensive spatially dense food supply network constituted by wet markets, supermarkets and small food stores in Nanjing. This is verified by the survey data that more than 90% of households purchased fresh food items within their neighbourhoods or in walking distance. In addition to the densely distributed food outlets, various other factors contributed to the non-significant influence of the distance to the nearest wet market and supermarket, including the many small food stores within or close to residential communities, the prevalence of three-generation extended households and high household income. This study highlights the importance of allowing mixed land use for food outlets with residential land and integrating wet markets into urban infrastructure planning