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

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28120%2F19%3A63524002" target="_blank" >RIV/70883521:28120/19:63524002 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/70883521:28140/19:63524002

Výsledek na webu

<a href="https://dl.acm.org/doi/10.1145/3361785.3361815" target="_blank" >https://dl.acm.org/doi/10.1145/3361785.3361815</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1145/3361785.3361815" target="_blank" >10.1145/3361785.3361815</a>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

50204 - Business and management

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

ACM International Conference Proceeding Series

ISBN

978-1-4503-7232-9

ISSN

—

e-ISSN

—

Počet stran výsledku

6

Strana od-do

15-20

Název nakladatele

Association for Computing Machinery

Místo vydání

New York

Místo konání akce

Paříž

Datum konání akce

12. 9. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—