Investigating the effect of customer-generated content on performance in online platform-based experience goods market

As COVID-19 persists, a new normal has emerged in our lives and consumption patterns. The rapid rise in demand for online consumption without physical contact is a prime example of this shift. Online platform-based markets have evolved into retail channels, allowing consumers to purchase both search goods and experience goods without contact. The platform provides an environment where customers can encounter a diverse range of customer-generated content (CGC) and gain insights into the purchasing experiences of others. However, despite the growing trading volume and diversification of products traded, relatively few studies exist on purchasing tangible experience goods in the online platform-based market. Therefore, this study investigates the impact of CGC (i.e., content and valence) on the market performance of experience goods, such as sales and sales rank in the platform-based market. We first examine the customer experience-related content in CGC in this market and then investigate the effect of CGC on market performance, such as sales and search ranks. We use crawled data from a platform that sells and rents artwork for empirical analysis. LDA topic modeling findings reveal that CGC has three primary topics (i.e., basic, artist, and style). The regression analysis results show that only style-related content improves performance, whereas basic-related content negatively affects search ranks. The valence of CGC does not significantly impact either performance measure. Additionally, we consider the role of rental services in this market and find that rental volume and search rank have an inverted U-shaped relationship. This study has important implications because it proposes a research framework and empirical model for examining the impact of CGC on performance in the online platform-based market for experience goods. It also has important managerial implications for platforms and sellers looking to enhance their market performance by monitoring CGC.     

Connectedness and Worthiness for the Embedded Self: A Material Culture Perspective

This article is based on a study of intergenerational transfers of contaminated objects, colloquially referred to as “heirlooms.” Motivations and processes are described within the central dialectic of an individual actor seeking positive affect through the pursuit of connectedness and worthiness and in the context of the larger social order. Object symbolism is examined from the perspectives of the individual actor, society, and culture. The family is conceptualized as a special case of the “other.” A theoretical framework is developed that draws extensively on Walter Goldschmidt’s notion of “The Culturally Embedded Self” in The Human Career: The Self in a Symbolic World (1990) and on Sidney Levy’s work as presented in Brands, Consumers, Symbols, and Research (1999). This framework is referred to with the acronym MOSES for Motivations, Object Symbolism, and the Embedded Self.     

截面特征差异、投资者情绪与企业投资

投资者情绪影响企业投资决策,在此基础上进一步检验企业截面特征差异对投资者情绪与企业投资关系的影响作用。以2004～2009年沪深两市上市公司为研究样本,采用主成分分析法构建投资者情绪综合指数,使用动态面板回归方法,研究发现换手率越高、规模越小、成长性越高、收益波动程度越大、现金持有量越多以及资产负债率越低的上市公司,其投资行为对投资者情绪越敏感。     

Daily market news sentiment and stock prices

In recent years there has been a tremendous growth in readily available news related to traded assets in international financial markets. This financial news is now available through real-time online sources such as Internet news and social media sources. The increase in the availability of financial news and investor’s ease of access to it has a potentially significant impact on market stock price movement as these news items are swiftly transformed into investors sentiment which in turn drives prices. In this study, we use the Thomson Reuters News Analytics (TRNA) data set to construct a series of daily sentiment scores for Dow Jones Industrial Average (DJIA) stock index constituents. We use these daily DJIA market sentiment scores to study the influence of financial news sentiment scores on the stock returns of these constituents using a multi-factor model. We augment the Fama–French three-factor model with the day’s sentiment score along with lagged scores to evaluate the additional effects of financial news sentiment on stock prices in the context of this model using Ordinary Least Square (OLS) and Quantile Regression (QR) to analyse the effect around the tail of the return distribution. We also conduct the analysis using the seven-day simple moving average (SMA) of the scores to account for news released on non-trading days. Our results suggest that even when market factors are taken into account, sentiment scores have a significant effect on Dow Jones constituent returns and that lagged daily sentiment scores are often significant, suggesting that information compounded in these scores is not immediately reflected in security prices and related return series. The results also indicate that the SMA measure does not have a significant effect on the returns. The analysis using Quantile Regression provides evidence that the news has more impact on left tail compared to the right tail of the returns.     

Bounded rationality,anchoring-and-adjustment sentiment,and asset pricing

This paper presents a framework that incorporates an investor’s limited attention and anchoring and adjustment sentiment and their joint effects on asset pricing, with endogenous cost of neglecting part of the dividends and the asymmetric rationality levels of investors. We find that the combined effect of the two bounded rationality factors is often embodied in the “loss”, and the retail investors are insensitive to market sentiment and forced to pay more cognitive loss. A higher level of investor rationality and bullish market sentiment will jointly increase demand and then prices, while the effects of different bounded rationality factors are asymmetric.     

Market manipulation with sentiment traders

This article offers a new perspective for traders’ sentiment by bridging the relationship between feedback effect and market manipulation. Allowing access to information regarding manipulated orders confuses sentiment traders, leading to an overestimation of the true asset value which actually remains the same. We find that sentiment factor has a nonmonotonic impact on the responsiveness to order information and price informativeness. Furthermore, it is shown that informed traders behave like a contrarian, and can use order information to reassess the price, which results in the multiplicity of equilibria.     

From measurement scale to sentiment scale: Examining the effect of sensory experiences on online review rating behavior

The crucial role of sensory dimensions in customer experiences has been supported in literature. However, traditional self-reported sensory measurements have limited capacity in capturing the multi-dimensional experiences sensed by individuals and articulating the distinct effect of different sensory dimensions on actual behavior. This study is the first attempt to test the effects of positive and negative experiences involving all five senses (sight, smell, sound, taste, and touch) on customer ratings. The sensory experiences reported in social media reviews were captured and explored using text mining and sentiment analysis. The findings show that although the majority of customers’ experiences were positive, the negative sensory experiences had higher effect on customer rating. Furthermore, the five senses had different weights in forming overall experience, which provides theoretical contributions to the literature on sensescapes, prospect theory, and discourses on satisfiers and dissatisfiers.     

News media analytics in finance: a survey

We survey the works applying text analytics to the study of news media in financial markets beyond intraday horizons, and expand into the fundamental economic theory and concepts relevant to the field. We compare and contrast the news sources, textual analysis methods and empirical modelling approaches adopted within the literature. We distil and categorise the key empirical insights, and summarise the bibliographic history of the literature so far. While this rapidly growing field has yielded many exciting discoveries, there are a number of promising avenues for future research which will only benefit from continued advances in computational technology.     

Sentiment and art prices

We hypothesize the existence of a slow-moving fad component in art prices. Using unique panel survey data on art market participants’ confidence levels in the outlook for a set of artists, we find that sentiment indeed predicts short-term returns.     

Economic Sentiment and Yield Spreads in Europe

According to Harvey (1988) , the forecasting ability of the term spread on economic growth is due to the fact that interest rates reflect investors' expectations about the future economic situation when deciding their plans for consumption and investment. Past literature has used ex post data on output or consumption growth as proxies for their expected value. In this paper, we employ a direct measure of economic agents' expectations, the Economic Sentiment Indicator elaborated by the European Commission, to test this hypothesis. Our results indicate that a linear combination of European yield spreads explains a surprising 93.7\% of the variability of the Economic Sentiment Indicator. This ability of yield spreads to capture economic agent expectations may be the actual reason for the predictive power of yield spreads about future business cycle.