An Empirical Analysis of Platform Regulation in the Sharing Economy

Author(s):  
Zhijie Lin ◽  
Yong Tan
2020 ◽  
pp. 1-28
Author(s):  
Yifeng Peng

Over the years, as people's lives have improved, our need for transportation and accommodation has increased, driving the rapid growth of the sharing economy. Some well-known network sharing platforms, such as Uber, Drip and Airbnb, provide a large number of convenient options for users with transactional needs, make more use of idle tourism, accommodation and other resources. Sharing economy platforms continue to improve the content and format of their products, but at the same time, the future of sharing platforms and the difficulty of competition is a concern as more platform companies become involved and prices become more transparent. Under this circumstance, optimizing product pricing has become an urgent need for many sharing economy platforms. In this paper, we take Airbnb as the starting point and conduct an empirical analysis of the blocking behavior of homeowners based on proprietary data to explore the factors that affect their product supply. We find that price, number of beds, and listing type all have a significant impact on blocking houses. After that, we conducted further research on price factors and developed a model aiming at profit maximization to obtain the best pricing range for the region and provide suggestions for pricing strategies. Keywords: Sharing Economy, Blocking behavior, Pricing Strategy, Airbnb


2021 ◽  
Vol 5 (1) ◽  
pp. 3
Author(s):  
Miguel Ángel Ruiz Reina

In the socio-economic field, it is not surprising that decision-making is based on asymmetric information. Economic agents make decisions to forecast in primary and secondary industries related to the tourism sector. This study aims to provide knowledge in situations of asymmetric information with increasing randomness using time series for tourism accommodation markets. We are trying to solve the question of how consumers exchange their preferences for tourist accommodation between tourist apartments and hotel accommodation in Spain. The emergence of the sharing economy concept has emerged as a competitor to the traditional hotel accommodation in the tourist market. To do this, we will develop a theoretical framework to measure situations of uncertainty and their temporal evolution. Information Theory (IT) is the central axis of the study, particularly the concept of entropy. The Shannon entropy (SE) concept is a static measure of information. This work proposes to model the temporal arrangement of SE to discover the behaviors of the systems. The study in the domain of time and frequency allows us to understand the cycles of uncertainty between systems. To apply the theoretical framework, we will work with data from official Spanish sources for tourist accommodation from January 2008 to December 2019. The results of the empirical analysis show the decision changes of economic agents according to a seasonal pattern. Consumers have new accommodation options, and the answer we get from this work is that consumers have different preferences depending on seasonality. The use of SE allows us to make better predictions compared to SARIMA models, the traditional modelling of seasonal dummy variables, and VAR models. The results of the Matrix U1 Theil verify this hypothesis. The theoretical framework and empirical analysis find an answer to asymmetric information. The implications of this work contribute to the field of social sciences related to the tourism sector, in particular to thermodynamics, statistical mechanics, and IT. The modelling of uncertainty allows for the forecasting and control of accommodation tourist markets in random situations. The applications of this study can be tested in other areas of the economy such as finance, transportation, or investment.


2007 ◽  
Vol 23 (4) ◽  
pp. 248-257 ◽  
Author(s):  
Matthias R. Mehl ◽  
Shannon E. Holleran

Abstract. In this article, the authors provide an empirical analysis of the obtrusiveness of and participants' compliance with a relatively new psychological ambulatory assessment method, called the electronically activated recorder or EAR. The EAR is a modified portable audio-recorder that periodically records snippets of ambient sounds from participants' daily environments. In tracking moment-to-moment ambient sounds, the EAR yields an acoustic log of a person's day as it unfolds. As a naturalistic observation sampling method, it provides an observer's account of daily life and is optimized for the assessment of audible aspects of participants' naturally-occurring social behaviors and interactions. Measures of self-reported and behaviorally-assessed EAR obtrusiveness and compliance were analyzed in two samples. After an initial 2-h period of relative obtrusiveness, participants habituated to wearing the EAR and perceived it as fairly unobtrusive both in a short-term (2 days, N = 96) and a longer-term (10-11 days, N = 11) monitoring. Compliance with the method was high both during the short-term and longer-term monitoring. Somewhat reduced compliance was identified over the weekend; this effect appears to be specific to student populations. Important privacy and data confidentiality considerations around the EAR method are discussed.


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