TOWARDS HIGH RESOLUTION IDENTIFICATION OF VARIETY-SEEKING BEHAVIOR

Because smartphones are now ubiquitous, it becomes for the first time economically feasible to operationalize personalized marketing measures also for physical grocery retailing. A particularly interesting and high valu target group in this domain is the one of variety seeking, since this group is most likely to respond positively to new offers and recommendations. However, present methods in identifying variety seekers rely on qustionnaires and ignore that variety seeking may differ between product categories. In this paper, we present a model for measuring variety seeking behavior on a high level of granularity, based on a consumer´s purchases in individual product categories. Our study has three main contributions. Firstly, we contribute to the customer segmentation research stream by providing a novel way for identifying customers´ overall extent of variety seeking as well as their specific variety seeking at a category level. Second, for the most important retail categories we characterize the extent of variety seeking and provide a data-driven approach that is easy to operationalize by practitioners “ especially for deploying large-scale personalized marketing measures in social or mobile commerce in physical stores. Finally, we provide a method to reconcile the highly granular category-level results with existing per person typologies

Reality-Mining with Smartphones: Detecting and Predicting Life Events based on App Installation Behavior

Life events are often described as major forces that are going to shape tomorrow\u27s consumer need, behavior and mood. Thus, the prediction of life events is highly relevant in marketing and sociology. In this paper, we propose a data-driven, real-time method to predict individual life events, using readily available data from smartphones. Our large-scale user study with more than 2000 users shows that our method is able to predict life events with 64.5% higher accuracy, 183.1% better precision and 88.0% higher specificity than a random model on average

Collaborative Filtering on the Blockchain: A Secure Recommender System for e-Commerce

In collaborative filtering approaches, recommendations are inferred from user data. A large volume and a high data quality is essential for an accurate and precise recommender system. As consequence, companies are collecting large amounts of personal user data. Such data is often highly sensitive and ignoring users’ privacy concerns is no option. Companies address these concerns with several risk reduction strategies, but none of them is able to guarantee cryptographic secureness. To close that gap, the present paper proposes a novel recommender system using the advantages of blockchain-supported secure multiparty computation. A potential costumer is able to allow a company to apply a recommendation algorithm without disclosing her personal data. Expected benefits are a reduction of fraud and misuse and a higher willingness to share personal data. An outlined experiment will compare users’ privacy-related behavior in the proposed recommender system with existent solutions

Silicon Waveguides and Ring Resonators at 5.5 {\mu}m

We demonstrate low loss ridge waveguides and the first ring resonators for the mid-infrared, for wavelengths ranging from 5.4 to 5.6 {\mu}m. Structures were fabricated using electron-beam lithography on the silicon-on-sapphire material system. Waveguide losses of 4.0 +/- 0.7 dB/cm are achieved, as well as Q-values of 3.0 k.Comment: 4 pages, 4 figures, includes supplemental material

The value of RFID for RTI management

Returnable transport items (RTIs) are key elements for enabling a smooth flow of goods throughout supply chains. Despite their importance, RTIs can be prone to high loss and breakage rates. Today's RTI management processes are rather inefficient and are based on estimates about when, where and how RTIs are utilised. This limited visibility inevitably causes the involved parties to feel less responsible for the proper management of RTIs. As a consequence, inefficiencies created by a single party can result in a significant cost burden for the whole supply chain. The goal of this paper is therefore to explore the impact of increased asset visibility on the RTI management process. We describe a solution based on Radio Frequency Identification (RFID) technology and quantify its financial impact from each individual stakeholder's perspective. Our findings suggest that RFID can provide a powerful means to counter inefficiencies in the RTI management process and improve the overall effectiveness of the RTI supply chain networ

Efficient Encoding and Transmission of Digital Receipts for Mobile Commerce

to discuss products and purchases in real-time. However, the transmission of digital receipts is still a problem, since often Internet connectivity is not available at the point of sale which hampers a real-time interaction. To overcome this problem with current technology, this paper presents a way to efficiently transmit a complete receipt in a QR-code, a certain kind of 2D matrix code (often also called “2D barcode”). Thereby, only a smartphone equipped with a camera is needed and Internet connectivity is not a problem anymore. However, due to size constraints, the encoding of a full receipt needs to be as efficient as possible. We present a custom, domain-specific encoding that was developed exactly for this purpose and show that our prototype implementation performs better than sophisticated, general purpose compression algorithms on this kind of data

SWISS FOODQUIZ: INDUCING NUTRITIONAL KNOWLEDGE VIA A VISUAL LEARNING BASED SERIOUS GAME

Nutritional education programs have been proposed to counter the trend of excessive energy intake, identified as the main driver of overweight. Still, due to lack of resources, only a small part of society can be included in these personnel-intensive programs. Health information systems (HIS) in nutritional education have the potential to overcome these limitations, but still suffer under low end-user acceptance and interaction rates. Their current focus lies in abstract, too generic behavioural recommendations, which the end user cannot directly translate into health-beneficial real-world choices. In order to address these issues, we have built an automatic HIS prototype tailored to support the average consumer in gaining nutritional knowledge by applying paradigms from visual learning and serious gaming, established approaches in related fields to improves users’ acceptance, motivation, intention and ultimately likelihood for health-beneficial behaviour changes. Preliminary results of a study with 350 users show high acceptance rates even for previously uninvolved users and measurable gains in nutritional knowledge over the usage phase. With the approach suggested in this paper, it can be shown that the extension of serious game principles to nutritional education can overcome contemporary HIS shortcomings of low acceptance and interaction rates among average, uninvolved and unhealthy users

Estimating Data Volumes of RFID-enabled Supply Chains

The widespread application of RFID tags in supply chains is said to cause enormous data volume problems and thus unprecedented challenges for systems and infrastructures. In order to unleash the potential of item-level RFID applications, such as data sharing and discovery across company boundaries, an unbiased understanding of emerging data volumes is necessary. However, quantitative data that provides factual argument is still scarce. Therefore, we present a simulation study based on a real-world scenario that reveals quantitative characteristics of the data volumes problem in an RFID-enabled supply chain and discuss its implications. Our results suggest that data volumes will be much lower than currently anticipated, but still bear significant challenges for researchers and developers of RFID infrastructures

FINTECHS AND THE NEW WAVE OF FINANCIAL INTERMEDIARIES

The financial services industry is undergoing a massive transformation similar to what was observed when other industries underwent digitization. The FinTech revolution has given rise to a vast number of technology-oriented market entrants who challenge many parts of the financial services industry. This research seeks to provide a better understanding of how FinTechs across various business functions fundamentally impact the value chain in this industry. To this end, we built on top of financial intermediation theory, and developed a taxonomy of FinTechs’ intermediating functions. The following hierarchical clustering analysis identified six archetypes of FinTech intermediaries as observed in the real world, i.e. the different ways in which FinTechs across business functions act as financial intermediaries by transforming assets, reducing transaction cost, and alleviating information asymmetries. Finally, we discuss how FinTechs impact financial intermediation in itself, and to what extent the notion of FinTechs disintermediating the financial value chain is accurate

From Shopping Aids to Fully Autonomous Mobile Self-checkouts - A Field Study in Retail

Self-checkout terminals allow integrating customers as active co-producers into a retailer’s business processes. They have enjoyed increasing popularity in the past years since they allow saving costs and increasing customer satisfaction. Yet, they cannot be implemented in many retail settings, as the technology relies on retailer provided terminals and does not yet fully utilize the possibilities provided by mobile smartphones, which until recently have mostly served as decision or shopping aids. This paper presents steps towards and results from a field study of a purely mobile self-checkout solution that provides a more time efficient shopping experience to time-constrained users. We show that the time performance of app users is independent of store rush and that the time for a transaction is significantly lower for app users compared to regular shoppers during peak periods