Journal Articles (Peer-Reviewed)
Meyners, Jannik, Christian Barrot, Jan U. Becker and Jakob Goldenberg (2016):The Role of Mere Closeness: How Geographic Proximity Affects Social Influence, MSI Report, Marketing Science Institute: Cambridge, MA, 16-106.
Abstract: In the past years, two major trends have created new challenges for marketers. First, consumers have grown to rely on advice from other consumers ─ for instance, through online reviews such as on TripAdvisor, Expedia, or Yelp. Second, consumers increasingly provide marketers with personal data ─ especially geographic information ─ by using their mobile devices (e.g., smartphones or tablet PCs) for shopping purposes or product search. Despite their increasing availability and relevance, companies are uncertain to and in which way they can use geographic data to actively manage product recommendations This report provides insights into the role of geographic proximity for recommendations and online reviews. In four studies that cover both extensive field and experimental data, the authors show that geographic proximity increases social influence and demonstrate its interdependency with social closeness. The results indicate a) that the role of geographic proximity for social influence is not simply a result of the higher likelihood of social interaction and b) that the effect of geographic proximity increases with decreasing tie strength between sender and receiver of a recommendation. In three experiments, the authors demonstrate the monetary value of their findings by analyzing consumers’ willingness to pay more for products recommended by someone geographically close. Additionally, they show that the effect of geographic proximity is mediated by perceived homophily between consumers.The results imply that geographic location may well strengthen the social influence. Consequently, companies could sort reviews so that those from geographically close users are displayed first. By implementing such an individually tailored review order, consumers would receive more helpful reviews that lead to higher conversion rates and purchases of products that suit their needs. Also, companies could use the report’s insights to increase the effectiveness of social media advertising. In online social media such as Facebook, Google+, or Twitter, the users’ geographic location is typically available and can be used to target social ads, i.e., ads that show Internet users the products or services that their contacts like, follow, or use. The report’s results imply that advertising with contacts that live in geographic proximity to the user (e.g., “Bill likes Company X”) could be more influential than advertising with someone geographically distant.
Maecker, Olaf, Christian Barrot and Jan U. Becker (2016):The effect of social media interactions on customer relationship management, Business Research, 9(1): 133-155.
Abstract: In recent years, social media have become a popular channel through which customers and companies can interact. However, companies struggle to assess whether their investments in establishing and maintaining brand pages in social media actually meet their high expectations with respect to developing and retaining customers. Based on three empirical studies, the authors explore the role of interactions through corporate social media channels, such as Facebook brand pages, in customer relationship management. The results indicate that social media interactions indeed ease the upselling efforts and reduce the risk of churn. These positive effects offset the observed increases with regard to the number of service requests and the higher overall service cost. Thus, we ultimately find customers who interact with the brand on social media to be more profitable.
Barrot, Christian, Jan U. Becker, Michel Clement and Dominik Papies (2015):Price Elasticities for Hardcover and Paperback Fiction Books, Schmalenbach Business Review, 67(1): 73-91.
Abstract: Book pricing is problematic for two main reasons. First, because legal restrictions make pricing decisions irreversible. Second, because publishers must set prices for many books every year. Therefore, a sound knowledge of consumer reaction to price is essential for good pricing decisions. Our research examines consumer reactions to prices, provides price elasticities based on a large sample of fiction books, and creates a comprehensive set of quality measures and control variables. Our results show that once price endogeneity is considered, consumers are price elastic. Moreover, we find that the price elasticity for hardcover books is substantially smaller than for paperbacks.
Armelini, Guillermo, Christian Barrot and Jan U. Becker (2015):Referral programs, customer value, and the relevance of dyadic characteristics, International Journal of Research in Marketing, 32(4): 449-452.
Abstract: Referral programs have become a popular tool to use the customer base for new customer acquisition. We replicate the work of Schmitt et al. (2011) who find that referred customers are more loyal and valuable than customers acquired through other channels. While our results confirm that rewarded referrals indeed reduce the risk of customer churn, we do not find that referred customers are necessarily more valuable. Analysis of the relationship between senders and receivers of referrals demonstrates that demographic similarity drives the referred customer value.
Fandrich, Thomas, Christian Barrot and Jan U. Becker (2014):Deckungsbeitragsorientierte Steuerung von Targeting-Kampagnen, Schmalenbachs Zeitschrift für betriebswirtschaftliche Forschung, 66(11): 602-625.
Abstract: Eine Vielzahl von Studien konnte zeigen, dass sich die Konversionsraten in der Neukundenan- sprache durch Targeting steigern lassen. Konkrete Aussagen über den ökonomischen Erfolg von Targeting-Kampagnen können allerdings auf dieser Basis bisher nicht getroffen werden. Der vorliegende Beitrag stellt daher eine deckungsbeitragsorientierte Sichtweise zur Bewer- tung des Targeting vor, so dass eine Einschätzung zur Profitabilität bereits vor der Durchfüh- rung von Targeting-Kampagnen möglich ist. Auf Basis dieser Überlegungen wird erläutert, wie ein deckungsbeitragsorientiertes Targeting in der Unternehmenspraxis anzuwenden ist und wann sich die gezielte gegenüber der ungezielten Kundenansprache auszahlt.
Barrot, Christian, Jan Kuhlmann and Andrea Popa (2013):Influence of Personal Communication Networks on Innovation Adoption – Using Multi-Agent-Simulations to Optimize the Roll-Out of an Innovative Medical Device, International Journal of Innovation and Technology Management, 10(5): 1-19.
Abstract: Adoption processes are often heavily influenced by interpersonal communication. Marketing managers are increasingly trying to use these relationships to foster the market penetration of their products. In an empirical study of the US market for an innovative medical device, we survey the social network of (mostly chief) anesthetists from 151 hospitals. We confirm the influences from personal communication on individual adoption decisions through hazard regressions. We then use a multi-agent modeling framework trying to identify what seeding strategies would have been optimal to achieve a fast market penetration, i.e. which and how many anesthetists should be selected to initiate personal communication processes.
Barrot, Christian, Jan U. Becker and Jannik Meyners (2013):Impact of service pricing on referral behavior, European Journal of Marketing, 47(7): 1052-1066.
Abstract: Purpose – This study seeks to examine the effect of pricing as a marketing instrument to stimulate word‐of‐mouth (WOM) by comparing the influence of two pricing strategies (i.e. a low‐complexity vs a network‐effects tariff) on the referral behaviour.Design/methodology/approach – Using customer data from a German mobile network operator (including information on customer characteristics, referral behaviour, and service usage), the authors develop a logit model.Findings – Surprisingly, the results indicate that it is the low‐complexity tariff that increases the likelihood of referrals and leads to an overall higher referral activity. Despite the lower referral activity, however, the network‐effects tariff generates higher revenues.Research limitations/implications – The results show that companies can use pricing schemes to influence referral behaviour and strongly indicate the need of further research on manageable tools to stimulate word‐of‐mouth marketing. Practical implications – The findings show not only that pricing has an impact on customers' referral behaviour but also that it is the low‐complexity tariffs that trigger referrals. Furthermore, the results underline the importance of considering the monetary value of referrals.Originality/value – In contrast with many previously conducted studies on customer referrals, the paper explicitly analyses the impact of pricing on referral behaviour and empirically shows that firms are able to actively manage WOM among customers.
Schlereth, Christian, Christian Barrot, Bernd Skiera and Carsten Takac (2013):Optimal Product-Sampling Strategies in Social Networks: How Many and Whom to Target?, International Journal of Electronic Commerce, 18(1): 45-72.
Abstract: Using an agent-based model to study the success of product-sampling campaigns that rely on information about social networks, this paper investigates the essential decisions of which consumers and how many of them to target with free product samples. With an unweighted and a weighted real-world personal communication network, we show that the decision of which consumers to target is more important than that of how many consumers to target. Use of social network information increases profits by at least 32 percent. Companies should use a high-degree targeting heuristic to identify the most influential consumers. Use of social network information increases profit for single-purchase products mainly because it supports targeting more influential consumers and therefore speeds up diffusion throughout the network. For repeat-purchase products, social network information decreases the optimal number of samples and thus the cost of the campaign.