Shared Prosperity (or Lack Thereof) in the Sharing Economy

2022 | Information Systems Research | Citations: 13

Authors: Alyakoob, Mohammed; Rahman, Mohammad S.

Abstract: This paper examines the potential economic spillover effects of a home-sharing p ... Expand

Abstract: This paper examines the potential economic spillover effects of a home-sharing platform—Airbnb—on the growth of a complimentary local service—restaurants. By circumventing traditional land-use regulations and providing access to underutilized inventory, Airbnb attracts visitors to locales that are not traditional tourist destinations. Although visitors generally bring significant spending power, it is unclear whether visitors use Airbnb primarily for lodging and thus do not contribute to the adjacent economy. To evaluate this, we focus on the impact of Airbnb on the restaurant employment growth across locales in New York City (NYC). Specifically, we focus on areas in NYC that did not attract a significant tourist volume prior to the emergence of a home-sharing service. Our results indicate a salient and economically significant positive spillover effect on restaurant job growth in an average NYC locality. A one-percentage-point increase in the intensity of Airbnb activity (Airbnb reviews per household) leads to approximately 1.7% restaurant employment growth. Since home-sharing visitors are lodging in areas that are not accustomed to tourists, we also investigate the demographic and market-structure-related heterogeneity of our results. Notably, restaurants in areas with a relatively high number of White residents disproportionately benefit from the economic spillover of Airbnb activity, whereas the impact in majority Black areas is not statistically significant. We validate the underlying mechanism behind the results by evaluating the impact of Airbnb on Yelp visitor reviews, revealing that areas with increased Airbnb activity experience a surge in their share of NYC visitor reviews. This result is further validated by evaluating the impact of a unique Airbnb neighborhood-level exogenous policy recently implemented in New Orleans. Collapse

Topics: Airbnb sharing platform criminality online review open data

Methods: product review Yelp review longitudinal research propensity score matching propensity score method

Theories: theory of economic growth theory of economic development

A comparative assessment of sentiment analysis and star ratings for consumer reviews

2020 | International Journal of Information Management | Citations: 0

Authors: Al-Natour, Sameh; Turetken, Ozgur

Abstract: Electronic word of mouth (eWOM) is prominent and abundant in consumer domains. B ... Expand

Abstract: Electronic word of mouth (eWOM) is prominent and abundant in consumer domains. Both consumers and product/service providers need help in understanding and navigating the resulting information spaces, which are vast and dynamic. The general tone or polarity of reviews, blogs or tweets provides such help. In this paper, we explore the viability of automatic sentiment analysis (SA) for assessing the polarity of a product or a service review. To do so, we examine the potential of the major approaches to sentiment analysis, along with star ratings, in capturing the true sentiment of a review. We further model contextual factors (specifically, product type and review length) as two moderators affecting SA accuracy. The results of our analysis of 900 reviews suggest that different tools representing the main approaches to SA display differing levels of accuracy, yet overall, SA is very effective in detecting the underlying tone of the analyzed content, and can be used as a complement or an alternative to star ratings. The results further reveal that contextual factors such as product type and review length, play a role in affecting the ability of a technique to reflect the true sentiment of a review. Collapse

Topics: Google+ application programming interface accounting online review Python

Methods: sentiment analysis post-hoc analysis computational algorithm product review machine learning

Theories: information foraging theory

Impact of Average Rating on Social Media Endorsement: The Moderating Role of Rating Dispersion and Discount Threshold

2018 | Information Systems Research | Citations: 37

Authors: Li, Xitong

Abstract: This paper examines how a restaurant’s online review ratings affect consumers to ... Expand

Abstract: This paper examines how a restaurant’s online review ratings affect consumers to endorse deal vouchers sold by the restaurant via social media before they redeem the vouchers. While the effect of the average of review ratings is straightforward, we focus on examining how the effect is moderated by the dispersion of review ratings and the discount threshold set for the group-buying deals. A comprehensive literature review suggests that a large rating dispersion can deliver two different messages to consumers (uncertainty in product quality and uniqueness of product taste) and thus may either positively or negatively moderate the effect of average rating on social media endorsement. Discount threshold may serve as a quality signal, reinforcing the effect of average rating. The empirical results show that the effect of average rating is greater when review ratings are more dispersed and the discount threshold is relatively large. The findings generate important managerial and research implications.The online appendix is available at https://doi-org.tudelft.idm.oclc.org/10.1287/isre.2017.0728. Collapse

Topics: social media Facebook online review user-generated content marketing management

Methods: robustness check Yelp review mathematical model Kolmogorov-Smirnov test linear regression analysis

How e-WOM and local competition drive local retailers' decisions about daily deal offerings

2017 | Decision Support Systems | Citations: 0

Authors: Bai, Xue; Marsden, James R.; Ross, William T.; Wang, Gang

Abstract: Local retailers considering offering daily deals must take into account possible ... Expand

Abstract: Local retailers considering offering daily deals must take into account possible impacts of both electronic-word-of-mouth (e-WOM) and local competition. However, how e-WOM, local competition, and their interactions affect local retailers' decisions to offer daily deals remains unclear. Here we examine these effects utilizing a data set that contains details of daily deals, online reviews, and local competition measures for restaurants in the Chicago area. With a propensity score matching (PSA) method, we show: 1) local retailers with high ratings and high number of reviews were more likely to initiate daily deals; 2) local retailers in an area with a low level of local competition were more likely to initiate daily deals; and 3) the strength and direction of the impact of e-WOM depend on the level of local competition. Our results enhance understanding of local retailers' decisions to offer daily deals and yield important implications related to daily deal sites. Collapse

Topics: online word of mouth online review user-generated content application programming interface advertising management

Methods: experimental group Yelp review descriptive statistic propensity score method sensitivity analysis

Could Deal Promotion Improve Merchants’ Online Reputations? The Moderating Role of Prior Reviews

2016 | Journal of Management Information Systems | Citations: 0

Authors: Li, Xitong

Abstract: It is by now almost accepted as a stylized fact that offering deal promotion (su ... Expand

Abstract: It is by now almost accepted as a stylized fact that offering deal promotion (such as via Groupon or LivingSocial) deteriorates local merchants’ online reputations (e.g., the average of Yelp review ratings). However, in this paper we show that the stylized fact is not true in certain circumstances. We theorize that the valence and volume of prior reviews can play an important moderating role in the effect of deal promotion. Empirically, we show that restaurants with a relatively low prior average rating and a relatively small review volume have improved their online reputations by offering Groupon promotion. The proportion of such restaurants is substantial. The findings are robust to multiple identification strategies and econometric specifications. The results underscore the substantial heterogeneity in the effect of deal promotion on local merchants’ online reputations. Merchants need to understand the moderating role of prior reviews (e.g., the valence and volume of prior reviews) and design appropriate strategies to maximize the returns from offering deal promotion. Collapse

Topics: online review marketing management logistics management anonymity user-generated content

Methods: Yelp review experimental group propensity score method econometric modeling longitudinal research

Thumbs Up, Sales Up? The Contingent Effect of Facebook Likes on Sales Performance in Social Commerce

2015 | Journal of Management Information Systems | Citations: 58

Authors: Lee, Kyunghee; Lee, Byungtae; Oh, Wonseok

Abstract: In this study we investigate whether social reference systems, such as Facebook ... Expand

Abstract: In this study we investigate whether social reference systems, such as Facebook “likes” (FBLs), promote sales in social commerce, wherein adverse selection and quality uncertainty often severely damage consumer trust and impede efforts to achieve sustainable growth. We also examine the extent to which product characteristics (product uncertainty and product franchising) and deal characteristics (tipping points, discount rates, and deal durations) moderate the social selling stimulated by FBLs. On the basis of 1,327 samples collected from a major social commerce platform provider, we identify several interesting empirical regularities regarding the relationship between FBLs and social commerce sales. The findings suggest that FBLs drive traffic and increase sales. Information technology artifacts and social technologies, such as FBLs, can endow a consumer’s shopping experience with a socialization component and induce social selling in collective buying platforms. Nevertheless, significant variations occur across products and deals. For example, consumers who purchase experience goods more frequently depend on FBLs than do those who buy search goods. FBLs exert a far greater influence on the sales of goods from independent stores than those from franchise chains. Social commerce consumers are unaffected by heavy discount rates as they make purchase decisions, but they extensively rely on FBLs, particularly when purchasing products that have low tipping points. Our results suggest that social commerce can be a powerful marketplace when the economic utility that is driven by price incentives is further strengthened and protected by the social utility that originates from trust and sharing. Collapse

Topics: social commerce experience good online review Facebook social network

Methods: econometric modeling Yelp review descriptive statistic experimental group product review

Theories: lemon market theory information integration theory