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

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Data Analytics for Crisis Management :/
其他題名:	A Case Study of Sharing Economy Services in the COVID-19 Pandemic.
作者:	Haciibrahimoglu, Bahri.
面頁冊數:	1 online resource (278 pages)
附註:	Source: Dissertations Abstracts International, Volume: 84-06, Section: A.
Contained By:	Dissertations Abstracts International84-06A.
標題:	Library science. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30244200click for full text (PQDT)
ISBN:	9798363508127

Data Analytics for Crisis Management : = A Case Study of Sharing Economy Services in the COVID-19 Pandemic.
Haciibrahimoglu, Bahri.

Data Analytics for Crisis Management :A Case Study of Sharing Economy Services in the COVID-19 Pandemic. - 1 online resource (278 pages)

Source: Dissertations Abstracts International, Volume: 84-06, Section: A.

Thesis (Ph.D.)--Long Island University, C. W. Post Center, 2022.

Includes bibliographical references

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's 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.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798363508127Subjects--Topical Terms:

539284
Library science.
Subjects--Index Terms:

COVID-19 pandemicIndex Terms--Genre/Form:

542853
Electronic books.

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