VOX POPULI: THREE ESSAYS ON THE USE OF SOCIAL MEDIA FOR VALUE CREATION IN SERVICES

Prior research shows that electronic word of mouth (eWOM) wields considerable influence over consumer behavior. However, as the volume and variety of eWOM grows, firms are faced with challenges in analyzing and responding to this information. In this dissertation, I argue that to meet the new challenges and opportunities posed by the expansion of eWOM and to more accurately measure its impacts on firms and consumers, we need to revisit our methodologies for extracting insights from eWOM. This dissertation consists of three essays that further our understanding of the value of social media analytics, especially with respect to eWOM. In the first essay, I use machine learning techniques to extract semantic structure from online reviews. These semantic dimensions describe the experiences of consumers in the service industry more accurately than traditional numerical variables. To demonstrate the value of these dimensions, I show that they can be used to substantially improve the accuracy of econometric models of firm survival. In the second essay, I explore the effects on eWOM of online deals, such as those offered by Groupon, the value of which to both consumers and merchants is controversial. Through a combination of Bayesian econometric models and controlled lab experiments, I examine the conditions under which online deals affect online reviews and provide strategies to mitigate the potential negative eWOM effects resulting from online deals. In the third essay, I focus on how eWOM can be incorporated into efforts to reduce foodborne illness, a major public health concern. I demonstrate how machine learning techniques can be used to monitor hygiene in restaurants through crowd-sourced online reviews. I am able to identify instances of moral hazard within the hygiene inspection scheme used in New York City by leveraging a dictionary specifically crafted for this purpose. To the extent that online reviews provide some visibility into the hygiene practices of restaurants, I show how losses from information asymmetry may be partially mitigated in this context. Taken together, this dissertation contributes by revisiting and refining the use of eWOM in the service sector through a combination of machine learning and econometric methodologies.

ESSAYS ON THE WTO ACCESSION, HOUSEHOLD INCOME AND MULTIDIMENSIONAL POVERTY: EVIDENCE FROM CHINA

In the course of integrating into the global market, especially since China’s WTO accession, China has achieved remarkable GDP growth and has become the second largest economy in the world. These economic achievements have substantially increased Chinese incomes and have generated more government revenue for social progress. However, China’s economic progress, in itself, is neither sufficient for achieving desirable development outcomes nor a guarantee for expanding peoples’ capabilities. In fact, a narrow emphasis on GDP growth proves to be unsustainable, and may eventually harm the life quality of Chinese citizens. Without the right set of policies, a deepening trade-openness policy in China may enlarge social disparities and some people may further be deprived of basic public services and opportunities. To address these concerns, this dissertation, a set of three essays in Chapters 2-4, examines the impact of China's WTO accession on income distribution, compares China’s income and multidimensional poverty reduction and investigates the factors, including the WTO accession, that predict multidimensional poverty. By exploiting the exogenous variation in exposure to tariff changes across provinces and over time, Chapter 2 (Essay 1) estimates the causal effects of trade shocks and finds that China’s WTO accession has led to an increase in average household income, but its impacts are not evenly distributed. Households in urban areas have benefited more significantly than those in rural areas. Households with members working in the private sector have benefited more significantly than those in the public sector. However, the WTO accession has contributed to reducing income inequality between higher and lower income groups. Chapter 3 (Essay 2) explains and applies the Alkire and Foster Method (AF Method), examines multidimensional poverty in China and compares it with income poverty. It finds that China’s multidimensional poverty has declined dramatically during the period from 1989-2011. Reduction rates and patterns, however, vary by dimensions: multidimensional poverty reduction exhibits unbalanced regional progress as well as varies by province and between rural and urban areas. In comparison with income poverty, multidimensional poverty reduction does not always coincide with economic growth. Moreover, if one applies a single measure ─ either that of income or multidimensional poverty ─ a certain proportion of those who are poor remain unrecognized. By applying a logistic regression model, Chapter 4 (Essay 3) examines factors that predict multidimensional poverty and finds that the major factors predicting multidimensional poverty in China include household size, education level of the household head, health insurance coverage, geographic location, and the openness of the local economy. In order to alleviate multidimensional poverty, efforts should be targeted to (i) expand education opportunities for the household heads with low levels of education, (ii) develop appropriate geographic policies to narrow regional gaps and (iii) make macroeconomic policies work for the poor.