Harikesh S. Nair

Bio: Harikesh S. Nair is an academic researcher from Stanford University. The author has contributed to research in topics: Consumer behaviour & Social network. The author has an hindex of 26, co-authored 82 publications receiving 3344 citations. Previous affiliations of Harikesh S. Nair include University of Texas at Austin & University of Chicago.

Advertising Content and Consumer Engagement on Social Media: Evidence from Facebook

Abstract: We describe the effects of social media advertising content on customer engagement using Facebook data. We content-code more than 100,000 messages across 800 companies using a combination of Amazon Mechanical Turk and state-of-the-art Natural Language Processing and machine learning algorithms. We use this large-scale dataset of content attributes to describe the association of various kinds of social media marketing content with user engagement - defined as Likes, comments, shares, and click-throughs - with the messages. We find that inclusion of widely used content related to brand-personality - like humor, emotion and brand’s philanthropic positioning - is associated with higher levels of consumer engagement (like, comment, share) with a message. We find that directly informative content - like mentions of prices and availability - is associated with lower levels of engagement when included in messages in isolation, but higher engagement levels when provided in combination with brand-personality content. We also find certain directly informative content such as the mention of deals and promotions drive consumers’ path-to-conversion (click-throughs). These results hold after correcting for the non-random targeting of Facebook’s EdgeRank (News Feed) algorithm, so reflect more closely user reaction to content, rather than Facebook’s behavioral targeting. Our results suggest therefore that there may be substantial gains from content engineering by combining informative characteristics associated with immediate leads (via improved click-throughs) with brand-personality related content that help maintain future reach and branding on the social media site (via improved engagement). These results inform content design strategies in social media. Separately, the methodology we apply to content-code large-scale textual data provides a framework for future studies on unstructured data such as advertising content or product reviews.

Advertising Content and Consumer Engagement on Social Media: Evidence from Facebook

Abstract: We describe the effect of social media advertising content on customer engagement using data from Facebook. We content-code 106,316 Facebook messages across 782 companies, using a combination of Amazon Mechanical Turk and natural language processing algorithms. We use this data set to study the association of various kinds of social media marketing content with user engagement—defined as Likes, comments, shares, and click-throughs—with the messages. We find that inclusion of widely used content related to brand personality—like humor and emotion—is associated with higher levels of consumer engagement (Likes, comments, shares) with a message. We find that directly informative content—like mentions of price and deals—is associated with lower levels of engagement when included in messages in isolation, but higher engagement levels when provided in combination with brand personality–related attributes. Also, certain directly informative content, such as deals and promotions, drive consumers’ path to conversio...

Asymmetric Social Interactions in Physician Prescription Behavior: The Role of Opinion Leaders

Abstract: We quantify the impact of social interactions and peer effects in the context of prescription choices by physicians. Using detailed individual-level prescription data, along with self-reported social network information, we document that physician prescription behavior is significantly influenced by the behavior of research-active specialists, or "opinion leaders" in the physician's reference group. We leverage a natural experiment in the category, whereby new guidelines released about the therapeutic nature of the focal drug generated conditions where physicians were more likely to be influenced by the behavior of specialist physicians in their network. We find important, statistically significant peer effects that are robust across model specifications. We use the estimates to measure the incremental value to firms of directing targeted sales-force activity to these opinion leaders, and present estimates of the social multiplier of detailing in this category.

Intertemporal price discrimination with forward-looking consumers: Application to the US market for console video-games

Abstract: Firms in durable good product markets face incentives to intertemporally price discriminate, by setting high initial prices to sell to consumers with the highest willingness to pay, and cutting prices thereafter to appeal to those with lower willingness to pay A critical determinant of the profitability of such pricing policies is the extent to which consumers anticipate future price declines, and delay purchases I develop a framework to investigate empirically the optimal pricing over time of a firm selling a durable-good product to such strategic consumers Prices in the model are equilibrium outcomes of a game played between forward-looking consumers who strategically delay purchases to avail of lower prices in the future, and a forward-looking firm that takes this consumer behavior into account in formulating its optimal pricing policy The model outlines first, a dynamic model of demand incorporating forward-looking consumer behavior, and second, an algorithm to compute the optimal dynamic sequence of prices given these demand estimates The model is solved using numerical dynamic programming techniques I present an empirical application to the market for video-games in the US The results indicate that consumer forward-looking behavior has a significant effect on optimal pricing of games in the industry Simulations reveal that the profit losses of ignoring forward-looking behavior by consumers are large and economically significant, and suggest that market research that provides information regarding the extent of discounting by consumers is valuable to video-game firms

Modeling social interactions: Identification, empirical methods and policy implications

Abstract: Social interactions occur when agents in a network affect other agents’ choices directly, as opposed to via the intermediation of markets. The study of such interactions and the resultant outcomes has long been an area of interest across a wide variety of social sciences. With the advent of electronic media that facilitate and record such interactions, this interest has grown sharply in the business world as well. In this paper, we provide a brief summary of what is known so far, discuss the main challenges for researchers interested in this area, and provide a common vocabulary that will hopefully engender future (cross disciplinary) research. The paper considers the challenges of distinguishing actual causal social interactions from other phenomena that may lead to a false inference of causality. Further, we distinguish between two broadly defined types of social interactions that relate to how strongly interactions spread through a network. We also provide a very selective review of how insights from other disciplines can improve and inform modeling choices. Finally, we discuss how models of social interaction can be used to provide guidelines for marketing policy and conclude with thoughts on future research directions.

The Design and Analysis of Experiments

Abstract: THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

Evolution and Rationality Some Recent Game-Theoretic Results. Identification and Estimation of Local Average Treatment Effects

Abstract: We investigate conditions sufficient for identification of average treatment effects using instrumental variables. First we show that the existence of valid instruments is not sufficient to identify any meaningful average treatment effect. We then establish that the combination of an instrument and a condition on the relation between the instrument and the participation status is sufficient for identification of a local average treatment effect for those who can be induced to change their participation status by changing the value of the instrument. Finally we derive the probability limit of the standard IV estimator under these conditions. It is seen to be a weighted average of local average treatment effects.

Learning About a New Technology: Pineapple in Ghana

Abstract: This paper investigates the role of social learning in the diffusion of a new agri cultural technology in Ghana. We use unique data on farmers' communication patterns to define each individual's information neighborhood. Conditional on many potentially confounding variables, we find evidence that farmers adjust their inputs to align with those of their information neighbors who were surpris ingly successful in previous periods. The relationship of these input adjustments to experience further indicates the presence of social learning. In addition, applying the same method to input choices for another crop, of known technol ogy, correctly indicates an absence of social learning effects. (JEL D83, 013, 033, Q16)

Impact of Online Consumer Reviews on Sales: The Moderating Role of Product and Consumer Characteristics

Abstract: This article examines how product and consumer characteristics moderate the influence of online consumer reviews on product sales using data from the video game industry. The findings indicate that online reviews are more influential for less popular games and games whose players have greater Internet experience. The article shows differential impact of consumer reviews across products in the same product category and suggests that firms' online marketing strategies should be contingent on product and consumer characteristics. The authors discuss the implications of these results in light of the increased share of niche products in recent years.