the case of accommodation sharing

Thesis(Doctoral) --KDI School:Ph.D in Public Policy,2019The purpose of this study is to provide implications on policy preparation and amendments on laws and regulations in accommodation sharing in Korea by exploring the current status of demand and supply sides. This study consists of four parts to investigate i) perceived characteristics of accommodation sharing, ii) the impact of attributes of accommodations sharing on business performance, iii) individuals’ perceptions of policy reactions, and iv) exploratory research of current laws and regulations of different countries. First, this study finds that actual preferences of accommodation sharing conflicts with the issues on laws and regulations regarding property and sharing types. Guests who prefer to share entire houses consider instrumental attributes related to properties, while guests who prefer a portion of the house consider relatively more about social interactions, sustainability, and community benefit. Sharing a portion of the houses is legal and more suitable for policy intentions because the policies promote the local economy and community recovery by maximizing the utility of resources and interactions with the community. Further, this study finds that individuals with experience of accommodation sharing tend to have more positive attitudes toward accommodation sharing and perceive more necessity of policy reactions. Among proposed policy instruments, individuals perceive local ordinances, government publicizing and campaign, trust marks, taxation, penalties, and government controls are effective to build trust in accommodation sharing. Individuals evaluate that policies geared toward the majority of the public are more effective, and governments should establish a strategic approach as to which policies are introduced in public and which role the government plays in the departments. Currently, governments have been required the incompatible roles of eliminating regulatory barriers for newly introduced sharing economy business and minimizing the damages to existing industries. This study provides policy and managerial implications what is the most important for the citizen satisfaction associated with proper preparations and amendments of laws and regulations.I. Introduction II. Literature Reviews III. Study 1: Qualitative Research using Secondary Data IV. Study 2: Quantitative Research using Secondary Data V. Study 3: Quantitative Research using Primary Data VI. Study 4: Comparative Study on Policies in Various Societies VII. ConclusiondoctoralpublishedEun Joo LEE

Sharing Economy as Innovative Paradigm Towards Sustainable Development: A Conceptual Review

Sharing economy has been widely described by scholars as diverse phases towards sustainable development concerning its concept, functions, and goals in recent studies. Historically, the concept of "new capitalism" has been aroused the widespread concerns by scholars when defining the concept of sharing behavior of idle resources back to the year 1961. Moreover, scholars considered further the theoretical perspectives of sharing economy from the year 1978 to 2005. And many scholars started conducting the empirical analysis with the impact of sharing economy on specific industries such as tourism, hotel, mobility and financing sectors by the year 2010. However, there were still only a few scholars studied the field of sustainable development of sharing economy particularly in the mobility sectors and potential implication addressed the implementation of governing policies regarding case of the Chinese government. This article is first to review the previous studies on overall development of sharing economy in current situation, conceptualizing and providing the new sustainable model of sharing economy (particularly in sharing Mobility), led to further address the sharing economy in which regarded such an innovative paradigm towards sustainable development concerning with reviews and empirical studies conducted by previous scholars. Significantly, this study provided significant references to the stakeholders (operators), consumers (users), and administering (Chinese government) the sharing platform such potential issue, bringing the government concerned. Theoretically, it also provides such a new research direction with the sustainable model of sharing economy and potential regulating issues for the future research

Viewing Airbnb from Twitter: factors associated with users’ utilization.

Airbnb is a peer-to-peer accommodation website in the sharing economy. Past studies have examined the factors associated with Airbnb utilization from various platforms, but not exclusively from Twitter. A total of 21,097 tweets was collected in a period of two months, and the tweets were qualitatively analyzed with the help of text analysis tools to verify the discourse of discussion. Literature was reviewed for common factors attracting clients to an Airbnb accommodation. Factors were then qualitatively analyzed and compiled using Wmatrix, and the themes that emerged were: Price and status, social interaction and communication, location, reputation, amenities and a pet-friendly environment. This result provides a deeper insight to Airbnb hosts to strategize and add value to their current market situations

The spatial penetration of Airbnb in the main tourist cities of Spain : Extent and Determinants

Uneven spatial distribution of rented accommodation offered on Airbnb has potential to create spatial inequalities in host cities. In this regard, the claim of the proponents of Airbnb that 'it increases spatial equality in the cities by creating opportunities for the house-owners in peripheral areas' requires scientific analysis and empirical evidence. Using the data obtained from the Inside Airbnb website, 2011 census, the municipal register of Spain and OpenStreetMap, this article first measures the degree of penetration and spatial clustering (with LISA statistics) of the Airbnb listings in seven main tourist cities of Spain (Barcelona, Madrid, Valencia, Seville, Mallorca and Malaga). Second, it analyses (with multiple linear regression models) the spatial, socio-economic, demographic and cultural determinants of the spatial clustering of accommodation offered on Airbnb in the selected cities; and finally, it compares the growth of Airbnb and its impact on spatial inequalities in the selected cities.La desigual distribució espacial dels allotjaments llogats que s'ofereixen a Airbnb té el potencial de crear desigualtats espacials a les ciutats amfitriones. En aquest sentit, l'afirmació dels defensors d'Airbnb que «augmenta la igualtat espacial a les ciutats en crear oportunitats per als propietaris d'habitatges a les zones perifèriques» requereix una anàlisi científica i evidències empíriques. Utilitzant les dades obtingudes de la pàgina web Inside Airbnb, del cens de 2011, del padró municipal d'Espanya i d'OpenStreetMap, aquest article mesura, en primer lloc, el grau de penetració i d'agrupament espacial (amb estadístiques LISA) de les llistes d'Airbnb en set de les principals ciutats turístiques d'Espanya (Barcelona, Madrid, València, Sevilla, Mallorca i Màlaga); en segon lloc, analitza (amb múltiples models de regressió lineal) els determinants espacials, socioeconòmics, demogràfics i culturals de l'agrupació espacial dels allotjaments oferts a Airbnb a les ciutats seleccionades; i finalment, compara el creixement d'Airbnb i el seu impacte en les desigualtats espacials a les ciutats seleccionades.La desigual distribución espacial de los alojamientos alquilados que se ofrecen en Airbnb tiene el potencial de crear desigualdades espaciales en las ciudades anfitrionas. En este sentido, la afirmación de los defensores de Airbnb de que «aumenta la igualdad espacial en las ciudades al crear oportunidades para los propietarios de viviendas en las zonas periféricas» requiere un análisis científico y evidencias empíricas. Utilizando los datos obtenidos del sitio web Inside Airbnb, del censo de 2011, del padrón municipal de España y de Open- StreetMap, este artículo mide, en primer lugar, el grado de penetración y de agrupamiento espacial (con estadísticas LISA) de los listados de Airbnb en siete de las principales ciudades turísticas de España (Barcelona, Madrid, Valencia, Sevilla, Mallorca y Málaga); en segundo lugar, analiza (con múltiples modelos de regresión lineal) los determinantes espaciales, socioeconómicos, demográficos y culturales de la agrupación espacial de los alojamientos ofrecidos en Airbnb en las ciudades seleccionadas; y finalmente, compara el crecimiento de Airbnb y su impacto en las desigualdades espaciales en las ciudades seleccionadas.Une répartition spatiale inégale des logements loués proposés sur Airbnb peut créer des inégalités spatiales dans les villes hôtes. À cet égard, l'affirmation des partisans d'Airbnb selon laquelle « Airbnb accroît l'égalité spatiale dans les villes en créant des opportunités pour les propriétaires des zones périphériques » nécessite une analyse scientifique et des preuves empiriques. À partir des données obtenues du site Web Inside Airbnb, du recensement de 2011, du registre municipal d'Espagne et d'OpenStreetMap, cet article mesure d'abord le degré de pénétration et de clustering spatial (avec les statistiques LISA) des annonces Airbnb dans sept principales villes touristiques d'Espagne (Barcelone, Madrid, Valence, Séville, Majorque et Malaga). Ensuite, il analyse (avec de multiples modèles de régression linéaire) les déterminants spatiaux, socio-économiques, démographiques et culturels du regroupement spatial des hébergements proposés par Airbnb dans les villes sélectionnées. Enfin, il compare la croissance d'Airbnb et son impact sur les inégalités spatiales dans les villes sélectionnées

An ensemble-based decision tree approach for educational data mining

Nowadays, data mining and machine learning techniques are applied to a variety of different topics (e. g., healthcare and disease, security, decision support, sentiment analysis, education, etc.). Educational data mining investigates the performance of students and gives solutions to enhance the quality of education. The aim of this study is to use different data mining and machine learning algorithms on actual data sets related to students. To this end, we apply two decision tree methods. The methods can create several simple and understandable rules . Moreover, the performance of a decision tree is optimized by using an ensemble technique named Rotation Forest algorithm. Our findings indicate that the Rotation Forest algorithm can enhance the performance of decision trees in terms of different metrics. In addition, we found that the size of tree generated by decision trees ensemble were bigger than simple ones. This means that the proposed methodology can reveal more information concerning simple rules

Business set-up, transfer and closure

The report deals with the key drivers of business set-ups, transfers and closures. It considers innovative new business models and entrepreneurial activity. It also examines a wide range of regulatory, institutional and financial factors that influence primarily set-ups, but ultimately can also impact on the manner and ease with which businesses close. Finally, the report examines the closure of businesses - through voluntary exits, personal insolvency (bankruptcy) or corporate insolvency. This report was released on 21 May 2015. You are invited to examine the draft report, to make written submissions by Friday 3 July 2015 and to register to participate in public hearings. Key Points Businesses are set-up for a variety of reasons and in any one year there is a churn of entries and exits that is comparable with other countries. Most businesses are small and a very low proportion are innovative, producing a product or service new to Australian or international markets. The propensity to be innovative is highest amongst larger businesses. While it is generally relatively easy to start a business, a number of longstanding issues with specific regulatory requirements and regulator engagement and funding remain unaddressed and are making new business entry unnecessarily complex or costly. Some new business models - particularly those that exploit digital technology to make better use of information - are challenging existing regulatory arrangements or causing others to operate in regulatory grey areas. Regulators should have the capacity to exempt businesses for a fixed period, from particular regulatory requirements where these deter entry but exemption does not threaten consumer, public health and safety, or environmental outcomes. Government assistance to business set-ups should not be directed at particular business models, technologies, sectors or locations - criteria based on desired outcomes (such as technology transfer and spillovers) with matching private sector investment, are less likely to distort incentives and behaviours, particularly in a rapidly evolving environment. Any assistance should focus on those areas where there are economy-wide net benefits, and in the absence of a business set-up, there would be a justifiable need for other forms of government assistance. Access to finance is generally not a significant barrier to business set-up. New debt financing platforms, such as peer-to-peer lending, are helping to fill the gap in unsecured debt finance available from the major financial institutions. The voluntary participation by lenders in comprehensive credit reporting should be reviewed. A two-tier regulatory structure should be introduced for crowd-sourced equity to balance the financing needs of business against the risk preferences of different types of investors. Most businesses are closed or transferred without financial failure. Governments\u27 role in such situations should be limited to provision of clear guidelines for businesses, associations and advisers on exit and succession planning, and ensuring government processes are timely. While some specific reforms to Australia\u27s corporate insolvency regime are warranted, a wholesale change to the system, such as the adoption of the United States \u27chapter 11\u27 framework, is not justified. Formal restructuring of companies through voluntary administration should be enabled as an option for when a company may become, but is not yet, insolvent. There should be provision for a \u27safe harbour\u27 to allow company directors to explore restructuring options without liability for insolvent trading. A simplified liquidation process should be introduced to reduce the time and expense toward winding up businesses with little or no recoverable assets. All directors should be required to obtain a director identification number to enable the easier detection of disqualified or fraudulent directors. The default exclusion period and associated restrictions applying to bankrupts in relation to access to finance, employment (including being a company director) and overseas travel should be reduced from 3 years to 1 year, with the trustee and courts retaining the power to extend this period where necessary to prevent abuse of the bankruptcy process

The Collaborative Economy in Action: European Perspectives

The book titled The Collaborative Economy in Action: European Perspectives is one of the important outcomes of the COST Action CA16121, From Sharing to Caring: Examining the Socio-Technical Aspects of the Collaborative Economy (short name: Sharing and Caring; sharingandcaring.eu) that was active between March 2017 and September 2021. The Action was funded by the European Cooperation in Science and Technology - COST (www.cost.eu/actions/CA16121). The main objective of the COST Action Sharing and Caring is the development of a European network of researchers and practitioners interested in investigating the collaborative economy models, platforms, and their socio-technological implications. The network involves scholars, practitioners, communities, and policymakers. The COST Action Sharing and Caring helped to connect research initiatives across Europe and enabled scientists to develop their ideas by collaborating with peers. This collaboration opportunity represented a boost for the participants' research, careers, and innovation potential. The main aim of this book is to provide a comprehensive overview of the collaborative economy (CE) in European countries with a variety of its aspects for a deeper understanding of the phenomenon as a whole. For this reason, in July 2017, an open call for country reports was distributed among the members of the COST Action Sharing and Caring. Representatives of the member countries were invited to produce short country reports covering: definition(s) of the CE; types and models of the CE; key stakeholders involved; as well as legislation and technological tools relevant for the CE. Submitted reports varied in length and regarding the level of detail included, in accordance with how much information was available in each respective country at the time of writing. Editors of the book have compiled these early reports into a summary report, which was intended as a first step in mapping the state of the CE in Europe. The Member Countries Report on the Collaborative Economy, edited by Gaia Mosconi, Agnieszka Lukasiewicz, and Gabriela Avram (2018) that was published on the Sharing and Caring website, represented its first synergetic outcome and provided an overview of the CE phenomenon as interpreted and manifested in each of the countries part of the network. Additionally, Sergio Nassare-Aznar, Kosjenka Dumančić, and Giulia Priora compiled a Preliminary Legal Analysis of Country Reports on Cases of Collaborative Economy (2018). In 2018, after undertaking an analysis of the previous reports' strengths and weaknesses, the book editors issued a call for an updated version of these country reports. Prof. Ann Light advised the editorial team, proposing a new format for country reports and 4000 words limit. The template included: Introduction, Definition, Key Questions, Examples, Illustration, Context, Developments, Issues, Other Major Players, and Relevant Literature. The new template was approved by the Management Committee in October 2018. The task force that had supported the production of the first series of country reports (Dimitar Trajanov, Maria del Mar Alonso, Bálint Balázs, Kosjenka Dumančić, and Gabriela Avram) acted as mentors for the team of authors in each country. The final reports arrived at the end of 2018, bringing the total number of submissions to 30 (twenty-nine European countries plus Georgia). A call for book editors was issued, and a new editorial team was formed by volunteers from the participants of the COST Action: Andrzej Klimczuk, Vida Česnuityte, Cristina Miguel, Santa Mijalche, Gabriela Avram, Bori Simonovits, Bálint Balázs, Kostas Stefanidis, and Rafael Laurenti. The editorial team organized the double-blind reviews of reports and communicated to the authors the requirements for improving their texts. After reviews, the authors submitted updated versions of their country reports providing up-to-date interdisciplinary analysis on the state of the CE in 2019, when the reports were collected. During the final phase, the chapters were again reviewed by the lead editors together with all editorial team members. At the time, the intention was to update these reports again just before the end of the COST Action Sharing and Caring in 2021 and to produce a third edition. However, the COVID-19 pandemic changed these plans. Thus, this final volume was created by 82 scholars-editors and contributors-and consists of reports on 27 countries participating in the COST Action

DATA ANALYTICS FOR CRISIS MANAGEMENT: A CASE STUDY OF SHARING ECONOMY SERVICES IN THE COVID-19 PANDEMIC

This dissertation study aims to analyze the role of data-driven decision-making in sharing economy during the COVID-19 pandemic as a crisis management tool. In the twenty-first century, when applying analytical tools has become an essential component of business decision-making, including operations on crisis management, data analytics is an emerging field. To carry out corporate strategies, data-driven decision-making is seen as a crucial component of business operations. Data analytics can be applied to benefit-cost evaluations, strategy planning, client engagement, and service quality. Data forecasting can also be used to keep an eye on business operations and foresee potential risks. Risk Management and planning are essential for allocating the necessary resources with minimal cost and time and to be ready for a crisis. Hidden market trends and customer preferences can help companies make knowledgeable business decisions during crises and recessions. Each company should manage operations and response during emergencies, a path to recovery, and prepare for future similar events with appropriate data management tools. Sharing economy is part of social commerce, that brings together individuals who have underused assets and who want to rent those assets short-term. COVID-19 has emphasized the need for digital transformation. Since the pandemic began, the sharing economy has been facing challenges, while market demand dropped significantly. Shelter-in-Place and Stay-at-Home orders changed the way of offering such sharing services. Stricter safety procedures and the need for a strong balance sheet are the key take points to surviving during this difficult health crisis. Predictive analytics and peer-reviewed articles are used to assess the pandemic\u27s effects. The approaches chosen to assess the research objectives and the research questions are the predictive financial performance of Uber & Airbnb, bibliographic coupling, and keyword occurrence analyses of peer-reviewed works about the influence of data analytics on the sharing economy. The VOSViewer Bibliometric software program is utilized for computing bibliometric analysis, RapidMiner Predictive Data Analytics for computing data analytics, and LucidChart for visualizing data

Data Analytics for Crisis Management: A Case Study of Sharing Economy Services in the COVID-19 Pandemic

This dissertation study aims to analyze the role of data-driven decision-making in sharing economy during the COVID-19 pandemic as a crisis management tool. In the twenty-first century, when applying analytical tools has become an essential component of business decision-making, including operations on crisis management, data analytics is an emerging field. To carry out corporate strategies, data-driven decision-making is seen as a crucial component of business operations. Data analytics can be applied to benefit-cost evaluations, strategy planning, client engagement, and service quality. Data forecasting can also be used to keep an eye on business operations and foresee potential risks. Risk Management and planning are essential for allocating the necessary resources with minimal cost and time and to be ready for a crisis. Hidden market trends and customer preferences can help companies make knowledgeable business decisions during crises and recessions. Each company should manage operations and response during emergencies, a path to recovery, and prepare for future similar events with appropriate data management tools. Sharing economy is part of social commerce, that brings together individuals who have underused assets and who want to rent those assets short-term. COVID-19 has emphasized the need for digital transformation. Since the pandemic began, the sharing economy has been facing challenges, while market demand dropped significantly. Shelter-in-Place and Stay-at-Home orders changed the way of offering such sharing services. Stricter safety procedures and the need for a strong balance sheet are the key take points to surviving during this difficult health crisis. Predictive analytics and peer-reviewed articles are used to assess the pandemic\u27s effects. The approaches chosen to assess the research objectives and the research questions are the predictive financial performance of Uber & Airbnb, bibliographic coupling, and keyword occurrence analyses of peer-reviewed works about the influence of data analytics on the sharing economy. The VOSViewer Bibliometric software program is utilized for computing bibliometric analysis, RapidMiner Predictive Data Analytics for computing data analytics, and LucidChart for visualizing data