Participation vs. Effectiveness of Paid Endorsers in Social Advertising Campaigns: A Field Experiment

We investigate the participation and effectiveness of paid endorsers in viral-for-hire social advertising. We conduct a field experiment with an invitation design in which we manipulate both incentives and a soft eligibility requirement to participate in campaigns. The latter provides a strong and valid instrument to separate participation from outcomes effects. Since likes, comments, and retweets are count variables, and since potential endorsers can self-select to participate in multiple campaigns, we propose a Poisson lognormal model with sample selection and correlated random effects to analyze variations in participation and effectiveness. There are three main findings. (1) Payments higher than the average reward a potential endorser received in the past (gains) do not increase participation, whereas lower payments (losses) decrease participation. Neither gains nor losses affect effectiveness. (2) Potential endorsers who are more likely to participate tend to be less effective. (3) Which endorser characteristics are associated with effectiveness depends on whether success is measured in likes, comments, or retweets. These findings provide new insights on how marketers can improve social advertising campaigns by better targeting and incenting potential endorsers

How to Better Target and Incent Paid Endorsers in Social Advertising Campaigns: A Field Experiment

We investigate paid endorsement as a crowd-sourcing social advertising mechanism that allows advertisers to bypass publishers (e.g., Facebook) and recruit individual endorsers of their own choice at affordable prices. Specifically, we investigate (i) how incentives affect endorsers’ participation and effectiveness, (ii) what types of endorsers are most effective in generating online engagement (likes, comments, and retweets), and (iii) the potential differences between generating different types of engagements. We conduct a large scale field experiment in which we manipulate exogenously pay rates and eligibility to participate. Our findings suggest that increasing financial incentive doesn’t necessarily improve participation rate. In addition, endorsers who are effective are often not responsive. Further, it can be misleading to assess the attractiveness of endorsers simply based on observed engagements. Our findings provide new insights on how marketers can improve the effectiveness of paid endorsement by identifying and incentivizing high potential endorsers

Medical Innovation Revisited: Social Contagion versus Marketing Effort

This article shows that Medical Innovation—the landmark study by Coleman, Katz, and Menzel—and several subsequent studies analyzing the diffusion of the drug tetracycline have confounded social contagion with marketing effects. The article describes the medical community’s understanding of tetracycline and how the drug was marketed. This situational analysis finds no reasons to expect social contagion; instead, aggressive marketing efforts may have played an important role. The Medical Innovation data set is reanalyzed and supplemented with newly collected advertising data. When marketing efforts are controlled for, contagion effects disappear. The article underscores the importance of controlling for potential confounds when studying the role of social contagion in innovation diffusion

Contagion and heterogeneity in new product diffusion: An emperical test

Marketing researchers often assume that innovation diffusion is affected by social contagion. However, there is increasing skepticism about the importance of contagion and, as has long been known, S-shaped diffusion curves can also result from heterogeneity in the propensity to adopt. To gain insight into the role of these two different—though not mutually exclusive—mechanisms, we present substantive conjectures about conditions under which contagion and heterogeneity are more pronounced, and test these conjectures using a meta-analysis of the q/p ratio in applications of the Bass diffusion model. We find that the q/p ratio is positively associated with the Gini index of income inequality in a country, supporting the heterogeneity-in-thresholds interpretation. We also find evidence that q/p varies as predicted by the G/SG diffusion model, but the evidence vanishes once we control for national culture. As to contagion, we find that the q/p ratio varies systematically with the four Hofstede dimensions of national culture, and for three of them in a pattern theoretically consistent with the social contagion interpretation. Furthermore, we find that products with competing standards have a higher q/p ratio, which is again consistent with the social contagion interpretation. Finally, we find effects of national culture only for products without competing standards, suggesting that technological effects and culturally mediated social contagion effects may not operate independently from each other

WHEN DOES SOCIAL NETWORK-BASED PREDICTION WORK? A LARGE SCALE ANALYSIS OF BRAND AND TV AUDIENCE ENGAGEMENT BY TWITTER USERS

Social network-based prediction, more specifically targeting friends and contacts of existing customers, has proven successful in various domains like retail banking, telecommunications, and online advertising. However, little is known about for what types of product categories and brands social network-based marketing is especially effective at predicting brand engagement, both in absolute terms and compared to demographic targeting or collaborative filtering. In this work, we compare the performance of a social network-based recommendation engine against a product network-based recommendation engine of the kind used in collaborative filtering. We do so over 700 brands and 223,000 consumers a novel data set collected from Twitter. We compare the performance of the two approaches by product and user features. Preliminary results indicate that the variance in performance within and across methods is related to differences in brand and user popularity as well as brand audience

New Product Diffusion with Two Interacting Segments or Products

We study the diffusion of a product in two customer segments where the acceptance level in one segment affects the diffusion rate not only in that same segment, but also in the other. The inter-segment influence can be positive or negative, i.e., the acceptance level of the product in one segment can reinforce or impede its diffusion in the other. The model set-up also applies to the diffusion of two products, with independent and market potential, in a single population. Since the diffusion system we study does not have a closed-form solution, we use phrase plane analysis to identify the equilibrium points of the joint diffusion process and to characterize their stability properties. Further, we provide a means to identify the regions with different convergence behavior, i.e., to identify boundaries for regions within which all trajectories converge to a particular equilibrium point For the cases of asymmetric influence (+/-) and mutually impeding influence (-/-), we also provide conditions under which both products can achieve full market potential in equilibrium. Finally, we provide managerial insights into the effectiveness of two strategies in the context of asymmetric (+/-) interaction between two customer segments: (1) seeding, i.e., using free samples to support the launch of a product in one segment being harmed by the adoption in the other, and (2) demand control, i.e., purposely limiting market potential for the customer segment harming product diffusion in the other segment

Credit Scoring with Social Network Data

Motivated by the growing practice of using social network data in credit scoring, we analyze the impact of using network-based measures on customer score accuracy and on tie formation among customers. We develop a series of models to compare the accuracy of customer scores obtained with and without network data. We also investigate how the accuracy of social network-based scores changes when consumers can strategically construct their social networks to attain higher scores. We find that those who are motivated to improve their scores may form fewer ties and focus more on similar partners. The impact of such endogenous tie formation on the accuracy of consumer score is ambiguous. Scores can become more accurate as a result of modifications in social networks, but this accuracy improvement may come with greater network fragmentation. The threat of social exclusion in such endogenously formed networks provides incentives to low-type members to exert effort that improves everyone\u27s creditworthiness. We discuss implications for managers and public policy

Myocardial blood flow under general anaesthesia with sevoflurane in type 2 diabetic patients: a pilot study

BACKGROUND: In type 2 diabetic patients, cardiac events in the perioperative period may be associated with diminished myocardial vasomotor function and endothelial dysfunction. The influence of sevoflurane anaesthesia on myocardial endothelial dysfunction in type 2 diabetic mellitus is investigated in this pilot study. METHODS: Six males with type 2 diabetes mellitus and eight healthy controls were included. Using myocardial contrast echocardiography, myocardial blood flow (MBF) was measured at rest, during adenosine-induced hyperaemia (endothelium-independent vasodilation) and after sympathetic stimulation by the cold pressor test (endothelium-dependent vasodilation). Measurements were performed before and after induction of sevoflurane anaesthesia. RESULTS: Sevoflurane anaesthesia decreased resting MBF in diabetics but not in controls (P = 0.03), while baseline MBF did not differ between diabetics and controls. Without anaesthesia, adenosine-induced hyperaemia increased MBF in both groups compared to resting values. Adenosine combined with sevoflurane resulted in a lower hyperaemic MBF in both groups compared to no anaesthesia. Differences in MBF in response to adenosine before and after sevoflurane administration were larger in diabetic patients, however not statistically significant in this pilot group (P = 0.08). Myocardial blood flow parameters after the cold pressor test were not different between groups. CONCLUSION: These pilot data in type 2 diabetic patients show that sevoflurane anaesthesia decreases resting myocardial blood flow compared to healthy controls. Further, we observed a trend towards a lower endothelium-independent vasodilation capacity in diabetic patients under sevoflurane anaesthesia. Endothelium-dependent vasodilation was not affected by sevoflurane in diabetic patients. These data provide preliminary insight into myocardial responses in type 2 diabetic patients under general anaesthesia. TRIAL REGISTRATION: http://www.clinicialtrials.gov, NCT0086680

Studying Paths of Participation in Viral Diffusion Process

Authors propose a conceptual model of participation in viral diffusion process composed of four stages: awareness, infection, engagement and action. To verify the model it has been applied and studied in the virtual social chat environment settings. The study investigates the behavioral paths of actions that reflect the stages of participation in the diffusion and presents shortcuts, that lead to the final action, i.e. the attendance in a virtual event. The results show that the participation in each stage of the process increases the probability of reaching the final action. Nevertheless, the majority of users involved in the virtual event did not go through each stage of the process but followed the shortcuts. That suggests that the viral diffusion process is not necessarily a linear sequence of human actions but rather a dynamic system.Comment: In proceedings of the 4th International Conference on Social Informatics, SocInfo 201

The choice of Bass model coefficients to forecast diffusion for innovative products: An empirical investigation for new automotive technologies

Bass diffusion models are one of the competing paradigms to forecast the diffusion of innovative products or technologies. This approach posits that diffusion patterns can be modeled through two mechanisms: Innovators adopt the new product and imitators purchase the new product when getting in contact with existing users. Crucial for the implementation of the method are the values assigned to the two parameters, usually referred to as p and q, which mathematically describe innovation and imitation mechanisms. The present paper is based on the findings of a research project about policy measures to promote the diffusion of Electric Vehicles in Germany. It investigates how practitioners could choose adequate values for the Bass model parameters to forecast new automotive technologies diffusion with a focus on Electric Vehicles. It considers parameters provided by the literature as well as ad hoc parameter estimations based on real market data for Germany. Our investigation suggests that researchers may be in trouble in electing adequate parameter values since the different eligible parameter values exhibit dramatic variations. Literature values appear discussible and widely variable while ad hoc estimates appear poorly conclusive. A serious problem is that ad-hoc estimates of the Bass p value are highly sensitive to the assumed market potential M. So for plausible values of M, p varies on a high scale. Unless more consolidation takes place in this area, or more confidence can be placed on ad hoc estimates, these findings issue a warning for the users of such approaches and on the policy recommendations that would derive from their use