research-article

Behavioural and technical factors of influence on purchase behaviour of mobile consumers

Authors:

AcademicMindTrek '14: Proceedings of the 18th International Academic MindTrek Conference: Media Business, Management, Content & Services

Pages 110 - 117

https://doi.org/10.1145/2676467.2676494

Published: 04 November 2014 Publication History

Get Access

Abstract

The article includes the analysis of consumer behaviours within the framework of mobile consumer communities. As an introduction to the issue in question, the purpose is to present the impact of modern technologies on purchase behaviour and decision-making process of consumers, against the background of which the characteristics of mobile consumer communities will be discussed. The original model of purchase behaviours of mobile consumer communities was created, on the basis of which the factors having impact on consumer behaviours, in the break-up into technical and behavioural factors, have been identified and described. The purpose of the considerations undertaken is to present the method of influencing particular factors on purchase decisions taken by a mobile consumer and to emphasize the significance of the impact of belonging to mobile consumer communities for taking appropriate decisions.

This article is a part of the project, funded by the National Science Centre awarded on the basis of the decision number DEC-2011/03/B/HS4/04291.

References

[1]

http://www.stat.gov.pl/cps/rde/xbcr/gus/nts_spolecz_inform_w_polsce-2013.pdf

Google Scholar

[2]

Shelly, G., and Frydenberg, M., 2011. Web 2.0: Concepts and Applications, Boston: Cengage, pp. 8--9.

Digital Library

Google Scholar

[3]

Court, D., Elzinga, D., Mulder, S., and Vetvik, O. J., 2009. The consumer decision journey, {online} http://www.mckinsey.com/insights/marketing_sales/the_consumer_decision_journey

Google Scholar

[4]

Solis, B., 2013. What's the Future of Business: Changing the Way Businesses Create Experiences, John Wiley & Sons, New Jersey.

Google Scholar

[5]

Toffler, A., 1997. Trzecia fala, PIW, Warszawa.

Google Scholar

[6]

Tapscott, D., Williams, A., 2008. Wikinomia. O globalnej współpracy, która zmienia wszystko, WAiP, Warszawa.

Google Scholar

[7]

Łysik, Ł., Kutera, R., and Machura P., 2014. Zero Moment of Truth: a new Marketing Challenge in Mobile Consumer Communities, Proceedings of European Conference on Social Media (ECSM 2014), The Journal of Information, Communication and Ethics in Society (JICES), Emerald, Brighton (UK) (to be published)

Google Scholar

[8]

Łysik, Ł., and Kutera, R., 2011. Mobilne społeczności w procesach komunikacji marketingowej, in: Wiedza i komunikacja w innowacyjnych organizacjach. M. Pańkowska (Ed.), Komunikacja elektroniczna, Wydawnictwo UE Katowice, Katowice, pp.243--257.

Google Scholar

[9]

Rheingold, H., 2000. The Virtual Community: Homesteading on the Electronic Frontier, Addison-Wesley Publishing Company, Reading.

Digital Library

Google Scholar

[10]

Mobile Marketing Association, 2013. Mobile: The Great Connector. Bridging The Physical & Digital Worlds To Boost Your Marketing Effectiveness, MMA White Paper {online}, http://www.mmaglobal.com/bridging-digital

Google Scholar

[11]

Amerland, D., 2013. Google Semantic Search: Search Engine Optimization (SEO) Techniques That Get Your Company More Traffic, Increase Brand Impact, and Amplify Your Online Presence, Que Publishing, Indianapolis.

Digital Library

Google Scholar

[12]

Lecinski, J., 2011. Winning the Zero Moment of Truth, Google.

Google Scholar

[13]

Google/IPSOS OTX MediaCT, 2011. Think Mobile with Google {online} http://www.google.com/think/research-studies/the-mobile-movement.html

Google Scholar

Cited By

View all

Gkikas DTheodoridis P(2021)AI in Consumer BehaviorAdvances in Artificial Intelligence-based Technologies10.1007/978-3-030-80571-5_10(147-176)Online publication date: 3-Oct-2021
https://doi.org/10.1007/978-3-030-80571-5_10
Carvalho ASantos ACunha C(2019)Using Data Analytics to understand visitors online search interests: the case of Côa MuseumAdvances in Tourism, Technology and Smart Systems10.1007/978-981-15-2024-2_4(37-46)Online publication date: 25-Nov-2019
https://doi.org/10.1007/978-981-15-2024-2_4

Index Terms

Behavioural and technical factors of influence on purchase behaviour of mobile consumers
1. Applied computing
  1. Law, social and behavioral sciences

Recommendations

Prediction method of e-commerce consumers' purchase behaviour based on social network data mining

In order to effectively improve the prediction accuracy of e-commerce consumers' purchase behaviour and shorten the prediction time of e-commerce consumers' purchase behaviour, a prediction method of e-commerce consumers' purchase behaviour based on ...
Determinant Factors of Purchase Intention in E-Marketplace during COVID-19 Pandemic
IC3INA '21: Proceedings of the 2021 International Conference on Computer, Control, Informatics and Its Applications

COVID-19 has a changing impact on customers when making purchases. Generally, purchases are made in traditional or modern markets, but because of this pandemic, purchases are made in the e-marketplace. Trust and the information quality of a product ...
Research on Influencing Factors of Consumer Behavior Based on Wechat Stores
ISBDAI '18: Proceedings of the International Symposium on Big Data and Artificial Intelligence

With the continuous improvement of Internet technology, Internet users growing, online shopping consumers continue to increase, electric business platform number and size are also on the increase, the ensuing competition is more and more teeth. One of ...

Comments

Information & Contributors

Information

Published In

AcademicMindTrek '14: Proceedings of the 18th International Academic MindTrek Conference: Media Business, Management, Content & Services

November 2014

316 pages

ISBN:9781450330060

DOI:10.1145/2676467

General Chair:
Artur Lugmayr
Tampere Univ. of Technology (TUT), FIN

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

In-Cooperation

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 04 November 2014

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

Narodowe Centrum Nauki

Conference

AcademicMindTrek '14

Sponsor:

Mindtrek Association
UTA
EMMi Lab.
iAMEA

AcademicMindTrek '14: Media- Business, Content, Managment, and Services

November 4 - 6, 2014

Tampere, Finland

Acceptance Rates

Overall Acceptance Rate 110 of 207 submissions, 53%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

2
Total Citations
View Citations
306
Total Downloads

Downloads (Last 12 months)4
Downloads (Last 6 weeks)0

Reflects downloads up to 05 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

View all

Gkikas DTheodoridis P(2021)AI in Consumer BehaviorAdvances in Artificial Intelligence-based Technologies10.1007/978-3-030-80571-5_10(147-176)Online publication date: 3-Oct-2021
https://doi.org/10.1007/978-3-030-80571-5_10
Carvalho ASantos ACunha C(2019)Using Data Analytics to understand visitors online search interests: the case of Côa MuseumAdvances in Tourism, Technology and Smart Systems10.1007/978-981-15-2024-2_4(37-46)Online publication date: 25-Nov-2019
https://doi.org/10.1007/978-981-15-2024-2_4

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Abstract

References

Cited By

Index Terms

Recommendations

Prediction method of e-commerce consumers' purchase behaviour based on social network data mining

Determinant Factors of Purchase Intention in E-Marketplace during COVID-19 Pandemic

Research on Influencing Factors of Consumer Behavior Based on Wechat Stores

Comments

Information

Published In

Sponsors

In-Cooperation

Publisher

Publication History

Permissions

Check for updates

Author Tags

Qualifiers

Funding Sources

Conference

Acceptance Rates

Contributors

Other Metrics

Bibliometrics

Article Metrics

Other Metrics

Citations

Cited By

Login options

Full Access

View options

PDF

eReader

Share

Share this Publication link

Share on social media

Affiliations