MEASURING INDIVIDUAL SEARCH COSTS ON THE MOBILE INTERNET

The advent of smartphones enables more and more consumers to use the mobile internet. In addition, there is a continuing integration of location-based services (LBS). By means of Global Positioning Systems or WiFi-triangulation LBS provide context-aware information to consumers. This leads to a convergence of online and offline worlds. The usage of LBS delivers additional information to consumers (e.g., alternative offers or detailed product information). Particularly during the search process, information about prices or geographic distances, that are relevant for the purchase, are of importance. The goal of this study is to estimate search costs in a mobile internet context. We first illustrate the relevant literature on search theory (online/offline, mobile/desktop) and consumer behavior. Then we estimate search costs via a choice-based conjoint analysis for a large representative online sample. Our empirical results show that mobile search and LBS have a significant impact on consumer behavior. We quantify search costs in monetary units on an individual level by using geographic distance as a trade-off for price. We find that consumers trade off one extra minute of travel to another store with an average price reduction of 0.87

How Knowledge Stock Exchanges can increase student success in Massive Open Online Courses

Massive Open Online Courses (MOOCs) allow lecturers to overcome spatiotemporal boundaries and reach large numbers of participants. However, the completion rates of MOOCs are relatively low, a critical obstacle to their ultimate success. Existing literature suggests that strengthening student interaction has the potential to increase student commitment. The goal of this study is to develop a novel, market-based knowledge-sharing method that fosters student engagement and interaction in MOOCs, addressing the problem of low completion rates and demonstrating how MOOC engagement can lead to greater student success. The proposed method, "Knowledge Stock Exchange" (KSX), is derived from the concept of crowd-based intelligence mechanisms for incentive-compatible information aggregation. Using a popular MOOC as the focus of our empirical study, we show that the KSX method increases student interaction as well as MOOC completion rates. Moreover, we find that KSX participation has a significant positive effect on participants' exam grades

Measuring the weak mixing angle with the P2 experiment at MESA

The P2 experiment in Mainz aims to measure the weak mixing angle in electron- proton scattering to a precision of 0.13 %. In order to suppress uncertainties due to proton structure and contributions from box graphs, both a low average momentum transfer $Q^2$ of $4.5\cdot 10^{-3}$ GeV$^2/c^2$ and a low beam energy of 155 MeV are chosen. In order to collect the enormous statistics required for this measurement, the new Mainz Energy Recovery Superconducting Accelerator (MESA) is being constructed. These proceedings describe the motivation for the measurement, the experimental and accelerator challenges and how we plan to tackle them.Comment: Proceedings of the PhiPsi15, Sep. 23-26, 2015, Hefei, Chin

Frontiers: The Effect of an Ad Ban on Retailer Sales: Insights from a Natural Experiment

Advertising bans typically target products that deceive consumers in ways that can threaten their physical and mental health. An alternative policy objective might seek environmental protection through a ban on print advertising. Such measures would profoundly affect grocery retailers relying on printed leaflets to communicate weekly promotions. We measure the causal effect of banning advertising on retail performance by studying a temporary advertising ban implemented in a German federal state during the COVID-19 pandemic. The ban resulted in the suspension of all print advertising by grocery retailers, and the exogenous variation in advertising created by this natural experiment serves as our identification strategy. We apply difference-in-differences regressions to data from a national grocery retailer and find that the ban resulted in a 6% sales decrease in the treated state compared with an adjacent state. GfK Household Panel data reveal no effect of the advertising ban on the market level but a negative impact on retailers offering and advertising weekly promotional product assortments. We study the sensitivity of these results to the COVID pandemic and find that neither changes in COVID-19 incidence, vaccination rates, nor customers’ mobility moderate the ad ban effect. The findings offer practical insights for regulators and retailers regarding the impact of ad bans and the value of advertising

Location-Based Advertising and Contextual Mobile Targeting

Understanding how location-based services (LBS) can leverage sales in stores is important for retailers. LBS are a means to target users by making use of their location via GPS-enabled smartphones. Further, the ubiquitous nature of smartphones increases the importance of additional contextual factors such as time and weather. In particular, we analyze how context can be used to improve predicting responses to mobile promotions by applying unique GPS data. We examine the interplay between location, time, weather and co-location and users’ responses to mobile coupons. Our study reveals that context indeed improves predicting users’ responses to mobile promotions. First, distance is negatively correlated to users’ coupon choices. Second, users have different time-specific preferences. Third, temperature is negatively associated to users’ choices. Fourth, the number of co-located users is negatively related to their coupon response. Our results can be seen as input variables for retailers that aim to conduct mobile targeting

The Effect of an Ad Ban on Retailer Sales:Insights from a Natural Experiment

Advertising bans typically target products that deceive consumers in ways that can threaten their physical and mental health. An alternative policy objective might seek environmental protection through a ban on print advertising. Such measures would profoundly affect grocery retailers relying on printed leaflets to communicate weekly promotions. We measure the causal effect of banning advertising on retail performance by studying a temporary advertising ban implemented in a German federal state during the COVID-19 pandemic. The ban resulted in the suspension of all print advertising by grocery retailers, and the exogenous variation in advertising created by this natural experiment serves as our identification strategy. We apply difference-in-differences regressions to data from a national grocery retailer and find that the ban resulted in a 6% sales decrease in the treated state compared with an adjacent state. GfK Household Panel data reveals no effect of the advertising ban on the market level but a negative impact on retailers offering and advertising weekly promotional product assortments. We study the sensitivity of these results to the COVID pandemic and find that neither changes in COVID-19 incidence, vaccination rates, nor customers’ mobility moderate the ad ban effect. The findings offer practical insights for regulators and retailers regarding the impact of ad bans and the value of advertising

The Effect of an Ad Ban on Retailer Sales:Insights from a Natural Experiment

Advertising bans typically target products that deceive consumers in ways that can threaten their physical and mental health. An alternative policy objective might seek environmental protection through a ban on print advertising. Such measures would profoundly affect grocery retailers relying on printed leaflets to communicate weekly promotions. We measure the causal effect of banning advertising on retail performance by studying a temporary advertising ban implemented in a German federal state during the COVID-19 pandemic. The ban resulted in the suspension of all print advertising by grocery retailers, and the exogenous variation in advertising created by this natural experiment serves as our identification strategy. We apply difference-in-differences regressions to data from a national grocery retailer and find that the ban resulted in a 6% sales decrease in the treated state compared with an adjacent state. GfK Household Panel data reveals no effect of the advertising ban on the market level but a negative impact on retailers offering and advertising weekly promotional product assortments. We study the sensitivity of these results to the COVID pandemic and find that neither changes in COVID-19 incidence, vaccination rates, nor customers’ mobility moderate the ad ban effect. The findings offer practical insights for regulators and retailers regarding the impact of ad bans and the value of advertising

Tell Me Where You Are and I’ll Tell You What You Want: Using Location Data to Improve Marketing Decisions

Location data has become more and more accessible. Smartphone applications such as location-based services collect location data on a large scale. Up to now, most approaches have relied on past data, but new developments in machine learning and artificial intelligence will soon enable more dynamic real-time use of location data. Companies that embrace these technologies will be able to create competitive advantages. Location data offers great potential to improve a variety of marketing decisions such as targeted pricing and advertising, store locations and in-store layout. Location based advertising is currently the most common application. It allows targeting all customers within a certain distance of a store. Besides advertising, location data can be used for dynamic pricing decisions. Customers close to competitor’s locations can be charged a lower price for particular products via discounts in order to reduce switching costs. Indoor tracking can help to optimize store design or the positioning of categories and brands. Granular location data about consumers’ movements hence further allows for minimizing potential offline transaction costs based on the distances to stores

Tell Me Where You Are and I’ll Tell You What You Want: Using Location Data to Improve Marketing Decisions

Location data has become more and more accessible. Smartphone applications such as location-based services collect location data on a large scale. Up to now, most approaches have relied on past data, but new developments in machine learning and artificial intelligence will soon enable more dynamic real-time use of location data. Companies that embrace these technologies will be able to create competitive advantages. Location data offers great potential to improve a variety of marketing decisions such as targeted pricing and advertising, store locations and in-store layout. Location based advertising is currently the most common application. It allows targeting all customers within a certain distance of a store. Besides advertising, location data can be used for dynamic pricing decisions. Customers close to competitor’s locations can be charged a lower price for particular products via discounts in order to reduce switching costs. Indoor tracking can help to optimize store design or the positioning of categories and brands. Granular location data about consumers’ movements hence further allows for minimizing potential offline transaction costs based on the distances to stores