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Assessing pre-purchase risk attributes towards used-products: Evidence from E-shoppers in the Czech Republic

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dc.title Assessing pre-purchase risk attributes towards used-products: Evidence from E-shoppers in the Czech Republic en
dc.contributor.author Kwarteng, Michael Adu
dc.contributor.author Jibril, Abdul Bashiru
dc.contributor.author Botchway, Raphael Kwaku
dc.contributor.author Owusu, Victor Kwarteng
dc.contributor.author Pilík, Michal
dc.contributor.author Chovancová, Miloslava
dc.relation.ispartof ACM International Conference Proceeding Series
dc.identifier.isbn 9781450372329
dc.date.issued 2019
dc.citation.spage 15
dc.citation.epage 20
dc.event.title 3rd International Conference on Business and Information Management, ICBIM 2019
dc.event.location Paris
utb.event.state-en France
utb.event.state-cs Francie
dc.event.sdate 2019-09-12
dc.event.edate 2019-09-14
dc.type conferenceObject
dc.language.iso en
dc.publisher Association for Computing Machinery
dc.identifier.doi 10.1145/3361785.3361815
dc.relation.uri https://dl.acm.org/doi/10.1145/3361785.3361815
dc.subject Czech Republic en
dc.subject Non-Hierarchical clustering (k-means) en
dc.subject Risk en
dc.subject Used product en
dc.description.abstract Recent years have witnessed a marked increase in research focusing on risk in online transactions. Partly, these research efforts have been situated within the context of risk in online transactions in general with scant evidence considering the risk in the online used goods market in the Czech Republic. Less is also known about the level of risk associated with the customer to embark on online transactions of second-hand goods. Against this background, this paper is aimed at eliciting the magnitude of risky components aligned with the tendency to connect via online in search of second-hand goods. To achieve this, the research proposes a Non-Hierarchical (K-means) algorithm to glean relevant patterns in the data accrued from the Czech Republic. Hence, a simple random technique geared towards demographic variables was adopted to gather data; with 329 out of 411 respondents eligible for our analysis. Consequently, the research revealed through the K- means clustering algorithm that, consumers or respondents in these regions, namely, Pardubicky, Vysocina, and Kralovehradecky regions in the Czech Republic are more circumspect concerning the zeal to connect via online specifically second-hand goods. The findings from this shed light on a significantly ignored research area for researchers and provide a managerial strategy for online used goods vendors. © 2019 Association for Computing Machinery. en
utb.faculty Faculty of Management and Economics
dc.identifier.uri http://hdl.handle.net/10563/1009539
utb.identifier.obdid 43880867
utb.identifier.scopus 2-s2.0-85077513252
utb.source d-scopus
dc.date.accessioned 2020-01-24T13:28:14Z
dc.date.available 2020-01-24T13:28:14Z
utb.contributor.internalauthor Kwarteng, Michael Adu
utb.contributor.internalauthor Jibril, Abdul Bashiru
utb.contributor.internalauthor Botchway, Raphael Kwaku
utb.contributor.internalauthor Owusu, Victor Kwarteng
utb.contributor.internalauthor Pilík, Michal
utb.contributor.internalauthor Chovancová, Miloslava
utb.fulltext.sponsorship This work was supported by Internal Grant Agency of the Czech Republic– through TBU in Zlín No. IGA/FaME/2019/008, further by the financial support of research project NPU I no. MSMT-7778/2018 RVO - Digital Transformation and its Impact on Customer Behaviour and Business Processes in Traditional and Online markets.
utb.scopus.affiliation Tomas Bata University in Zlin, Faculty of Management and Economics, Nam T.G. Masaryka 5555760 01, Czech Republic
utb.fulltext.projects IGA/FaME/2019/008
utb.fulltext.projects MSMT-7778/2018
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