Advertising and Word-of-Mouth Effects on Pre-launch Consumer Interest and Initial Sales of Experience Products

This study examines how consumers' interest in a new experience product develops as a result of advertising and word-of-mouth activities during the pre-launch period. The empirical settings are the U.S. motion picture and video game industries. The focal variables include weekly ad spend, blog volume, online search volume during pre-launch periods, opening-week sales, and product characteristics. We treat pre-launch search volume of keywords as a measure of pre-launch consumer interest in the related product. To identify probable persistent effects among the pre-launch time-series variables, we apply a vector autoregressive modeling approach. We find that blog postings have permanent, trend-setting effects on pre-launch consumer interest in a new product, while advertising has only temporary effects. In the U.S. motion picture industry, the four-week cumulative elasticity of pre-launch consumer interest is 0.187 to advertising and 0.635 to blog postings. In the U.S. video game industry, the elasticities are 0.093 and 1.306, respectively. We also find long-run co-evolution between blog and search volume, which suggests that consumers' interest in the upcoming product cannot grow without bounds for a given level of blog volume

Facebook and extension of social ties: Implications on group norms and purchasing behavior

Facebook and extension of social ties: Implications on group norms and purchasing behavio

eWOM: the effects of online consumer reviews on purchasing decision of electronic goods

Internet has become the primary source of information for a large number of consumers and it has dramatically changed the consumer behaviour. One of the main changes in modern consumer behaviour has been the transition from a passive to an active and informed consumer. Internet enables customers to share their opinions on, and experiences with, goods and services with a multitude of other consumers. Online consumer reviews are used by prospective buyers of related products who are interested in obtaining more information from people who have purchased and used a product of interest. Word-of-mouth (WOM) is one of the most important information sources when a consumer is making a purchase decision. The arrival and expansion of the Internet has extended consumers' options for gathering product information by including other consumers' comments, posted on the Internet, and has provided consumers opportunities to offer their own consumption-related advice by engaging in electronic word-of-mouth (eWOM). eWOM can be defined as all informal communications directed at consumers through Internet-based technology related to the usage or characteristics of particular goods and services, or their sellers. The aim of this study is to assess the impact of, one type of electronic word-of-mouth (eWOM), the online consumer review, on purchasing decision of electronic products. This empirical study also focuses on the relationship between reviews and purchasing behaviour. An instrument was prepared to measure the proposed constructs, with questionnaire items taken from prior studies but adapted to fit the context of e-commerce. The survey was applied to academicians in Turkey through internet. The data was analyzed using the SPSS package. The results show that consumer reviews have a causal impact on consumer purchasing behaviour and they have an effect on choosing the products by consumer. Finally, the results and their implications are discussed

Consumer judgment and forecasting using online word-of-mouth

Empowered by information technology, modern consumers increasingly rely upon online word-of-mouth (WOM--e.g., product reviews) to guide their purchase decisions. This dissertation investigates how WOM information is processed by consumers and its downstream consequences. First, the value of specific types of word-of-mouth information (e.g., numeric ratings, text commentary, or both) was explored for making forecast. After proposing an anchoring-and-adjustment framework for the utilization of WOM to inform consumer forecasts, I support this framework with a series of experiments. Results demonstrate that the relative forecasting advantage of different information types is a function of the extent to which consumer and reviewer have similar product-level preferences ('source-receiver similarity'). Second, I investigate the process by which dispersion--the degree to which opinions are divided for a product or service--in WOM is interpreted. Using an attribution-based approach, I argue that the effect of WOM dispersion is dependent on the perceived cause of that dispersion, which is systematically related to perceptions of preference heterogeneity in a product category. For products for which preferences are expected to vary, dispersion is likely to be attributed to the reviewers rather than the product itself, and therefore tolerated. I provide evidence for my hypotheses in a series of experiments where WOM dispersion is manipulated and respondents make choices and indicate purchase intentions.PhDCommittee Chair: Bond, Samuel D.; Committee Member: Feldman, Jack M.; Committee Member: Hamilton, Ryan; Committee Member: Lurie, Nicholas H.; Committee Member: Van Ittersum, Koer

On the motivating impact of price and online recommendations at the point of online purchase

This is the post-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2011 ElsevierDo online recommendations have the same motivating impact as price at the point of online purchase? The results (n = 268) of an conjoint study show that: (1) when the price is low or high relatively to market price, it has the strongest impact (positive and negative) on the likelihood of an online purchase of an mp3 player, (2) when the price is average to market price, online recommendation and price are equal in their impact at the point of online purchase, and, (3) the relative impact from price increases when online shopping frequencies increases. The implications these results give are that online retailers should be aware that online recommendations are not as influential as a good offer when consumers purchase electronics online. However, other customer recommendations have a stronger impact on novice online shoppers than towards those consumers that shop more frequently online

A responsive framework for optimal advertising policy in the digital music market

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Using Online Search Data to Forecast New Product Sales

This dissertation focuses on online search as a measure of consumer interest. Internet use is at an all-time high in the United States, and according to the Pew Internet & American Life Project, 91% of Internet users use search engines to find information. Consumers' choices of search terms are not well understood. However, we argue that people will focus their searches on terms that are of interest to them. As such, data on the search terms used can provide valuable measures and indicators of consumer interest in a market. This can be particularly valuable to managers in search of tools to gauge potential product interest in a new product launch. In this research, we develop a model of pre-launch search activity. We find search term usage to follow rather predictable patterns in the pre-launch and post-launch periods. As such, we extend our pre-launch search model to link pre-release search behavior to release-week sales - providing a very valuable forecasting tool. We illustrate this approach in the context of motion pictures. Our modeling framework links search activity to sales and incorporates product characteristics. Our results indicate consistent patterns of search over time and systematic relationships between search volume, sales, and product attributes. We extend our model by studying the role of advertising. This allows us to better understand the relationship between advertising and online search activity and also allows us to compare the forecasting performances of each of the two approaches. We find that search data offers significant forecasting power in opening-weekend box-office revenues. We further find that advertising, combined with search data, offers improved forecasting ability

A little bluebird told me : social media conversation effects on business outcomes-evidence from the movie industry

textIn this dissertation, I examine how online conversations as electronic word-of-mouth (eWOM) information via social media networks affect business outcomes. Using data from the movie industry, my goal is to show how conversation quantity and quality, defined here as volumes and valence, on social network sites affect important business outcomes such as sales. Using a dynamic simultaneous equation system, I find that social media conversations can be a precursor to and an outcome of sales. Aggregated data from multiple sources show how social media variables and other key variables—volume, valence, and other information related to movies such as YouTube views, ratings, advertising, production budget, number of screens—contribute to box-office and home video sales through eWOM via social media. Findings highlight that eWOM volume correlates with box-office performance and home video sales: the more positive and strong the conversation, the higher the box office and home video sales. The study extends prior research on WOM and offers insight into how film studios can strategically manage social media to enhance box office and home video revenue.Advertisin