Transition pathway of consumer perception toward a sharing economy: Analysis of consumption value for behavioral transition to laundromats

Author(s):  
Dami Moon ◽  
Eri Amasawa ◽  
Masahiko Hirao
2018 ◽  
Vol 5 (1) ◽  
pp. 1-4
Author(s):  
Ji-Young Park ◽  
◽  
Seong-Yeon Park ◽  

2021 ◽  
Vol 13 (24) ◽  
pp. 13911
Author(s):  
Tatjana Tambovceva ◽  
Jelena Titko ◽  
Anna Svirina ◽  
Dzintra Atstaja ◽  
Maria Tereshina

The overwhelming goal of large-scale cross-country research is to evaluate consumers’ perception of a sharing economy. The research was limited by the number of respondents, as well as by the countries represented in the survey. Latvia, Russia, Ukraine, and Belarus were mostly represented, and only these responses (757) were analyzed. The study used multilevel modelling of sharing economy elements (dependent variable) in relation to personal characteristics (age, gender, income, industry) nested by the self-assessed level of eco-friendliness (a key predictor for the attitude towards sharing economy). Findings: The key personal characteristics, which influence a person’s intention to be involved in the sharing economy practices, are level of income, education, and also self-perceived ecological friendliness. The sharing economy is not only a topic for investigation among academicians, but also an issue on the agenda of the European Commission, because it is considered as a driver for growth and job creation in the European Union. Despite an increasing interest and many studies, there is a limited number of studies focused on difference in perception of sharing economy depending on personal characteristics of respondents. This indicates the necessity of conducting such surveys, involving participants from different European countries. The given paper could be used as a methodological framework for other European researchers who are interested in the exploration of the topic regarding perception of the sharing economy.


2019 ◽  
Author(s):  
Hanna Lee ◽  
Sung-Byung Yang ◽  
Chulmo Koob
Keyword(s):  

2019 ◽  
Vol 2 (4) ◽  
pp. 260-266
Author(s):  
Haru Purnomo Ipung ◽  
Amin Soetomo

This research proposed a model to assist the design of the associated data architecture and data analytic to support talent forecast in the current accelerating changes in economy, industry and business change due to the accelerating pace of technological change. The emerging and re-emerging economy model were available, such as Industrial revolution 4.0, platform economy, sharing economy and token economy. Those were driven by new business model and technology innovation. An increase capability of technology to automate more jobs will cause a shift in talent pool and workforce. New business model emerge as the availabilityand the cost effective emerging technology, and as a result of emerging or re-emerging economic models. Both, new business model and technology innovation, create new jobs and works that have not been existed decades ago. The future workers will be faced by jobs that may not exist today. A dynamics model of inter-correlation of economy, industry, business model and talent forecast were proposed. A collection of literature review were conducted to initially validate the model.


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