The relationship of cultural and non-cultural characteristics of countries with the sharing economy size

• Thesis title in Czech: Vztah mezi kulturními a dalšími charakteristikami zemí a velikostí sdílené ekonomiky
• Thesis title in English: The relationship of cultural and non-cultural characteristics of countries with the sharing economy size
• Key words: Sharing Economy, Digital Platforms, Hofstede, Cultural Dimensions, Internet Penetration, Economic Freedom
• English key words: Sharing Economy, Digital Platforms, Hofstede, Cultural Dimensions, Internet Penetration, Economic Freedom
• Academic year of topic announcement: 2017/2018
• Thesis type: Bachelor's thesis
• Thesis language: angličtina
• Department: Institute of Economic Studies (23-IES)
• Supervisor: doc. PhDr. Julie Chytilová, Ph.D.
• Author: hidden - assigned by the advisor
• Date of registration: 28.05.2018
• Date of assignment: 28.05.2018
• Date and time of defence: 10.09.2019 09:00
• Venue of defence: Opletalova - Opletalova 26, O206, Opletalova - místn. č. 206
• Date of electronic submission: 31.07.2019
• Date of proceeded defence: 10.09.2019
• Opponents: doc. Ing. Tomáš Cahlík, CSc.

References

1. PriceWaterhouseCoopers. “Assessing the Size and Presence of the Collaborative Economy in Europe.” EU Publications, Apr. 2016, publications.europa.eu/en/publication-detail/-/publication/2acb7619-b544-11e7-837e- 01aa75ed71a1/language-en.
2. Hofstede, Geert H., et al. Cultures and Organizations: Software of the Mind. McGraw-Hill, 2010, testrain.info/download/Software%20of%20mind.pdf.
3. Directorate-General for Communication. “Flash Eurobarometer 438: The Use of Collaborative Platforms - Ecodp.common.ckan.site_title.” EU Open Data Portal, 22 July 2016, data.europa.eu/euodp/en/data/dataset/S2112_438_ENG. Database
4. TNS Political & Social. “Flash Eurobarometer 438: Report - The Use of Collaborative Platforms.” European Commission, European Commission, Directorate-General for Internal Market, Industry, Entrepreneurship and SMEs, June 2016, ec.europa.eu/commfrontoffice/publicopinion/index.cfm/ResultDoc/download/DocumentKy/72885. Report
5. PricewaterhouseCoopers. “Future of the Sharing Economy in Europe 2016.” PwC, 2015, www.pwc.co.uk/issues/megatrends/collisions/sharingeconomy/future-of-the-sharing-economy-in-europe-2016.html.
6. Neunhoeffer, Frieder, and Timm Teubner. Between Enthusiasm and Refusal: A Cluster Analysis on Consumer Types and Attitudes towards Peer‐to‐Peer Sharing. onlinelibrary.wiley.com/doi/pdf/10.1002/cb.1706.
7. Nielsen. “Is Sharing the New Buying?” www.nielsen.com/content/dam/corporate/us/en/reports- downloads/2014%20Reports/global-share-community-report-may-2014.pdf.
8. PwC. “Share Economy 2017: The New Business Model.” www.pwc.de/de/digitale-transformation/share-economy- report-2017.pdf.
9. Deloitte. “Sharing Economy | Deloitte Czech Republic.” Deloitte, 14 Nov. 2017, www2.deloitte.com/cz/en/pages/deloitte-analytics/articles/sdilena-ekonomika-studie.html.
10. Deloitte. “Deloitte: Sharing Economy in the Czech Republic Has a Potential of up to CZK 60 Billion.” Deloitte, 14 Nov. 2017, www2.deloitte.com/cz/en/pages/press/articles/cze-tz-sdilena-ekonomika-v-cesku-ma-potencial-az-60- miliard-korun.html.
11. PricewaterhouseCoopers. “Outlook for the Sharing Economy in the UK 2016.” PwC, 2015,
www.pwc.co.uk/issues/megatrends/collisions/sharingeconomy/outlook-for-the-sharing-economy-in-the-uk-
2016.html.
12. Lewis, Richard Donald. “The Lewis Model – Dimensions of Behaviour.” CrossCulture, 22 June 2015,
www.crossculture.com/latest-news/the-lewis-model-dimensions-of-behaviour/.
13. Dervojeda, Kristina, et al. “Accessibility Based Business Models for Peer-to-Peer Markets.” Edited by Directorate- General for Enterprise and Industry.
14. European Commission. “European Capital of Innovation (ICapital) 2016.” European Commission, 8 Apr. 2016, ec.europa.eu/info/research-and-innovation/funding/funding-opportunities/prizes/icapital/icapital2016_en.
15. Hofstede, Geert. Culture's Consequences: Comparing Values, Behaviors, Institutions and Organizations Across Nations. Sage Publications, 2001.
16. United Nations Development Programme. “Human Development Report 2016.” United Nations Development Programme: Human Development Reports, 2016, www.hdr.undp.org/sites/default/files/2016_human_development_report.pdf.
17. Dutta, Soumitra, et al. “Thee Global Innovation Index 2014: The Human Factor in Innovation.” The Global Innovation Index, www.globalinnovationindex.org/userfiles/file/reportpdf/GII-2014-v5.pdf.
18. Central Intelligence Agency. “COUNTRY COMPARISON: GDP - PER CAPITA (PPP).” Central Intelligence Agency, 2017, www.cia.gov/library/publications/the-world-factbook/rankorder/2004rank.html.
19. Hamari, Juho, et al. “The Sharing Economy: Why People Participate in Collaborative Consumption.” Journal of the Association for Information Science and Technology, vol. 67, no. 9, 2015, pp. 2047–2059., doi:10.1002/asi.23552.
20. Heinrichs, Harald. “Sharing Economy: A Potential New Pathway to Sustainability.” GAIA - Ecological Perspectives for Science and Society, vol. 22, no. 4, 2013, pp. 228–231., doi:10.14512/gaia.22.4.5.
21. Schor, Juliet. “Debating the Sharing Economy.” Great Transition Initiative, Oct. 2014, www.msaudcolumbia.org/summer/wp-content/uploads/2016/05/Schor_Debating_the_Sharing_Economy.pdf.

Preliminary scope of work in English

Research question and motivation

In my Bachelor’s Thesis, I would like to investigate how cultural characteristics and other attributes, such as GDP per capita, Human Development Index (HDI), Global Innovation Index (GII), Internet Penetration and others, of a given population influence the adoption of sharing economy in a country.
Research question:
- Does cultural background and other relevant characteristics of a population influence the pace of adoption of sharing economy in a country?
Hypotheses:
1. There is a correlation between adoption of sharing economy practices and cultural characteristics of a population.
2. Cultural attributes are more significant than non-cultural ones in the case of adoption of sharing economy.
3. The Individualism Index is the most significant variable that influences adoption of sharing economy in a country.
4. Other non-cultural attributes, such as GDP per capita, are also significant in relation to the adoption of sharing economy in a country.
The end goal of this research would be to create a profiling of countries based on pace and likelihood of adoption of sharing economy. Each of the studied countries will have a rating from 0 to 100, which will indicate how quickly and how likely the country is to adopt sharing economy practices (with 100 being the fastest scenario with the highest likelihood). It will be possible to see which countries will be trendsetters, which ones will be followers and which ones will be late adopters of sharing economy. Graphing the profiled countries will also be an option with, for example, X-axis representing one of the cultural characteristics, such as individualistic cultures on one side and collectivist cultures on the other one, and Y-axis having the results of the research on the pace and likelihood of adoption of sharing economy.

Contribution

In April 2016, European Commission has published a report concluding that ‘their findings strengthen their point of view that the collaborative economy has now become a deep socio-economic trend that is fundamentally changing the way we live our lives.’1 However, I have not seen anything that has investigated the relationship between its adoption and cross-cultural characteristics.
In one paper, there was a one page part on “Success and adoption rate of peer-to-peer business models is dependent on the culture and features of local markets”2. It was stated that culture plays a crucial role, because it influences the extent to which the business models are accepted by the community, and that more positive disposition towards online activities also has a positive effect on adoption. This confirms my hypothesis regarding the fact that there is a correlation between cultural characteristics and sharing economy’s adoption. I have also decided to potentially include Internet Penetration into the model due to the second point in the article.
I believe that my contribution of tying sharing economy adoption to cultural background and other relevant characteristics will be valuable in the global community. It will also be very useful for start-ups or already existing businesses in the sharing economy industry as it will help them to decide where to launch or to which countries to expand to in order to gain the most.

1 PriceWaterhouseCoopers. “Assessing the Size and Presence of the Collaborative Economy in Europe.” EU Publications, Apr. 2016, publications.europa.eu/en/publication-detail/-/publication/2acb7619-b544-11e7-837e-01aa75ed71a1/language-en.
2 Dervojeda, Kristina, et al. “Accessibility Based Business Models for Peer-to-Peer Markets.” Edited by Directorate-General for Enterprise and Industry.

Methodology

I will take the data from the reports on sharing economy and combine it with the findings on cultural characteristics and other related statistics.
It will be possible to construct various models with the dependant variable being sharing economy preferences and/or size of sharing economy market. By preferences, I mean variables like awareness, participation, willingness and whether people are willing to participate by making use of the assets and services offered or supplying these. The attributes, so the explanatory variables in the model, can include cultural characteristics of the populations, but also other relevant parameters such as GDP per capita, Human Development Index (HDI), Global Innovation Index (GII), Internet Penetration etc.
I will use reports by PwC UK, TNS Political & Social and Nielsen on choices and preferences of people in Europe, and data on the size of sharing economy markets collected by PwC and Deloitte. Hofstede’s model will be used for cultural characteristics, and non-cultural characteristics are going to be taken from officials reports and investigations that I have already found and cited in the bibliography.
In Hofstede’s Cultural Dimensions Model, the relevant dimensions are:
a. Power Distance, which shows how people deal with inequalities between their status and status of others. I think that sharing economy activities put the population in a ‘sharing’ state of mind and therefore lead to fairer distribution of power.
b. Individualism versus Collectivism, which explains that some prefer to support others more and some focus more on their own lives. I believe that collectivism should imply faster and more likely adoption of sharing economy.
c. Uncertainty Avoidance, which talks about some people feeling more stressed in new situations that others. Sharing economy will bring some uncertainty into people’s lives, because it is new. I think that countries with lower uncertainty avoidance will have faster and more likely adoption.
d. Long-Term Orientation versus Short-Term Orientation, which shows that some people think and focus more on the future and vice versa. I think that more long-term oriented countries will have faster and more likely adoption, because sharing can greatly transform societies in the long term.

Outline

1. Outline
2. Sharing Economy
a. Definition
b. Types of Sharing Economy activities
c. Advantages
d. Its development
e. Barriers for its growth
f. Expectations for its development in the future
3. Cross-Cultural Characteristics
a. What influences Sharing Economy adoption
b. Differences of countries
i. Hofstede’s Cultural Dimensions
ii. Explanation of other cultural models used for further understanding
4. Description of Other Variables and Explanation of their Possible Effects
a. GDP per capita
b. Human Development Index (HDI)
c. Global Innovation Index (GII)
d. Internet Penetration
e. Others
5. Data Analysis
a. Data Possessed
b. Different Models
c. Regression
d. Regression Results
e. Summary and Conclusion of Data Analysis
6. Conclusion of the study
7. Bibliography
8. Data Sets