UNDERSTANDING THE MASSIVE ONLINE REVIEWS: A NOVEL REPRESENTATIVE SUBSET EXTRACTION METHOD

Online review hasalready been recognized as an important sales assistant for consumers to make their purchase decision. However, with the rapid development of electronic commerce,overwhelming informationoverloads and review manipulation make consumers lost in ocean of reviews and face huge cognitive stress. To address this issue, different types of online review have been developed by online marketplaces. Especially, except traditional types of online reviews (positive, neutral and negative), several new types of online review (review with picture and additional review) do not only contain plain text, but also pictures. Consumers could attach additional reviews to the original reviews to further share their experience sometimes later. Few studies have focused on which types of online reviews are able to influence consumers’ decisions more efficiently. Especially, research on new types of reviews is still unanswered.Using data from Taobao.com, the biggest electronic marketplace in China,this study conducts an empirical investigation to bridge the gap. Weinvestigatethat whether and howtraditional text reviewsand new types of reviews influence consumers’ purchase decision making. The results show that under the context of information overload and review manipulation, traditional reviewsare still influential, but less effective than new types of reviews. Although review with picture and additional review don’t show valence directly, they present more reliable references towards product quality and attract consumers’ attention more efficiently.And it is more interesting that new types of online review provide an effective channel for consumers to alleviate their dissatisfaction to effect potential consumers purchase decision making. The findings of this study can provide useful implications for researchers by highlighting the roles of different types of online review in consumers’ decision making. Also, the empirical investigation in this paper will remind business vendors to focus on online reviews especially new types of online reviews and conduct targeted marketing strategies to increase competitive advantage and improve their sales performance

Post Claims Underwriting and Rescission Practices

Based on case studies in four states, examines the effectiveness of regulation of the individual health insurance market and consumer protections against insurers canceling, rescinding, or limiting coverage after claims are submitted. Recommends reforms

Sharing Information

Customers write book reviews for Amazon.com and rate stores at BizRate.com. Car drivers call up radio stations to report traffic jams or radar traps. In many cases individuals share their information to the benefit of an unknown group of recipients, even though doing so is costly for the provider. In contrast to a standard public good, providers have no immediate benefit from information public goods. The paper reports the results of an experimental study on information sharing under two payoff conditions (opportunity announcement and hazard warning) and two information conditions (anonymous and identified provider). The experimental results show a substantial degree of information sharing. Information on extreme opportunities and extreme hazards is significantly more often provided than information on moderate prospects. Identification only plays a role in case of extreme opportunities and not in case of hazard warnings.Information public good; online recommendation; consumer rating; word-of-mouth communication; altruism; other-regarding behavior

The rise of the sharing economy: estimating the impact of Airbnb on the hotel industry

Peer-to-peer markets, collectively known as the sharing economy, have emerged as alternative suppliers of goods and services traditionally provided by long-established industries. We explore the economic impact of the sharing economy on incumbent firms by studying the case of Airbnb, a prominent platform for short-term accommodations. We analyze Airbnb's entry into the state of Texas, and quantify its impact on the Texas hotel industry over the subsequent decade. We estimate that in Austin, where Airbnb supply is highest, the causal impact on hotel revenue is in the 8-10% range; moreover, the impact is non-uniform, with lower-priced hotels and those hotels not catering to business travelers being the most affected. The impact manifests itself primarily through less aggressive hotel room pricing, an impact that benefits all consumers, not just participants in the sharing economy. The price response is especially pronounced during periods of peak demand, such as SXSW, and is due to a differentiating feature of peer-to-peer platforms -- enabling instantaneous supply to scale to meet demand.Accepted manuscrip

Personality in Computational Advertising: A Benchmark

In the last decade, new ways of shopping online have increased the possibility of buying products and services more easily and faster than ever. In this new context, personality is a key determinant in the decision making of the consumer when shopping. A person’s buying choices are influenced by psychological factors like impulsiveness; indeed some consumers may be more susceptible to making impulse purchases than others. Since affective metadata are more closely related to the user’s experience than generic parameters, accurate predictions reveal important aspects of user’s attitudes, social life, including attitude of others and social identity. This work proposes a highly innovative research that uses a personality perspective to determine the unique associations among the consumer’s buying tendency and advert recommendations. In fact, the lack of a publicly available benchmark for computational advertising do not allow both the exploration of this intriguing research direction and the evaluation of recent algorithms. We present the ADS Dataset, a publicly available benchmark consisting of 300 real advertisements (i.e., Rich Media Ads, Image Ads, Text Ads) rated by 120 unacquainted individuals, enriched with Big-Five users’ personality factors and 1,200 personal users’ pictures

Using a Discrete Choice Experiment to Elicit Consumers’ WTP for Health Risk Reductions Achieved By Nanotechnology in the UK

We present research findings on consumers’ willingness to pay (WTP) for reductions in the level of foodborne health risks. The research addresses how such valuations are affected by the means of which the risk reduction is delivered and the methods of risk presentations used in choice tasks. In this case, the research has two treatments. In the first treatment, the comparison is between risk reductions achieved by an improvement in the food system in general (e.g., more stringent regulations and inspection regimes) within the slaughter and meat processing stages of the food chain, as opposed to a risk reduction achieved via innovations in food packaging using nanotechnology, which is the use of nanosensors in packaging. If there is a contamination in packaging, nanosensors reveal a colour change on the packaging material. In the second treatment, the comparison is between valuations of risk reductions in which reductions in risks are presented via absolute values and grids and absolute values together. Both comparisons are achieved via split sample Discrete Choice Experiment surveys. The difference between consumers’ valuations of foodborne risk reductions provides an implicit value for nanotechnology (i.e., WTP to avoid) and the effect of risk grids on choices people make. General results show the existence of heterogeneity in British consumers’ preferences. The effects of nanosensors and risk grids on consumers’ choices are not strong across the models. The valuations of health risk reductions show some variations across the models in both treatment groups.Discrete Choice Experiments, Nanotechnology, Nanosensors, Health Risks, Grids, UK, Health Economics and Policy,

Linking Research and Policy: Assessing a Framework for Organic Agricultural Support in Ireland

This paper links social science research and agricultural policy through an analysis of support for organic agriculture and food. Globally, sales of organic food have experienced 20% annual increases for the past two decades, and represent the fastest growing segment of the grocery market. Although consumer interest has increased, farmers are not keeping up with demand. This is partly due to a lack of political support provided to farmers in their transition from conventional to organic production. Support policies vary by country and in some nations, such as the US, vary by state/province. There have been few attempts to document the types of support currently in place. This research draws on an existing Framework tool to investigate regionally specific and relevant policy support available to organic farmers in Ireland. This exploratory study develops a case study of Ireland within the framework of ten key categories of organic agricultural support: leadership, policy, research, technical support, financial support, marketing and promotion, education and information, consumer issues, inter-agency activities, and future developments. Data from the Irish Department of Agriculture, Fisheries and Food, the Irish Agriculture and Food Development Authority (Teagasc), and other governmental and semi-governmental agencies provide the basis for an assessment of support in each category. Assessments are based on the number of activities, availability of information to farmers, and attention from governmental personnel for each of the ten categories. This policy framework is a valuable tool for farmers, researchers, state agencies, and citizen groups seeking to document existing types of organic agricultural support and discover policy areas which deserve more attention

Income, Inequality, and Food Prices: A Critique of Broda, Leibtag, and Weinstein's "The Role of Prices in Measuring the Poor's Living Standards"

In "The Role of Prices in Measuring the Poor's Living Standards," Christian Broda, Ephriam Leibtag, and David E. Weinstein (2009) use proprietary data -- the 2005 Nielsen Homescan dataset -- to analyze differences by income level in the prices paid for food. They find that Nielsen households with incomes above $60,000 pay somewhat more for the same food items than most households with lower incomes, with Nielsen households with incomes above$100,000 paying the most. Based on this finding and additional regression analyses, they conclude broadly that the "poor pay less -- not more -- for the goods they purchase" and that not accounting for this suggests that income inequality may be between 2.5 to 5 percent less than shown by national statistics