Risk and restitution: Assessing how users establish online trust

Lacohée, Hazel; Phippen, Andy; Furnell, Steven

doi:10.1016/j.cose.2006.09.001

Cited by 29 publications

(10 citation statements)

References 3 publications

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“…The advertised guarantees to account holders and the relatively low likelihood of any particular individual becoming a victim versus the obvious convenience of online banking can reasonably account for the popularity of online banking. Lacohee et al discuss similar points in relation to e-commerce transactions: confidence in third-party restitution, assurances in relation to guarantees, and fallback procedures should things go wrong (Lacohee et al, 2006). The issues with CAs and SSL simply do not pose a sufficient problem for these users to decline to use online banking and similar services.…”

Section: Risk Managementmentioning

confidence: 99%

User-visible cryptography in email and web scenarios

Brooke

Paige

2015

Information &Amp; Computer Security

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Purpose – This paper aims to classify different types of “user-visible cryptography” and evaluate the value of user-visible cryptographic mechanisms in typical email and web scenarios for non-expert IT users. Design/methodology/approach – The authors review the existing literature, and then identify user stories typical to their users of interest. They analyse the risks, mitigations of risks and the limits of those mitigations in the user stories. Findings – The scenarios identified suggest that background, opportunistic encryption has value, but more explicit, user-visible cryptographic mechanisms do not provide any further mitigation. Other mechanisms beyond technological mitigations provide the required mitigation for the users. Research limitations/implications – Further work should be carried out on the trust issues with trusted third parties, as they are intrinsic to global, automated cryptographic mechanisms. The authors suggest that deployed systems should rely on automation rather than explicit user involvement; further work on how best to involve users effectively remains valuable. Practical implications – Deployed systems should rely on automation rather than explicit user dialogues. This follows from recognised aspects of user behaviour, such as ignoring dialogues and unconsciously making a holistic assessment of risk that is mostly mitigated by social factors. Social implications – The user populations concerned rely significantly on the existing legal and social infrastructure to mitigate some risks, such as those associated with e-commerce. Guarantees from third parties and the existence of fallback procedures improve user confidence. Originality/value – This work uses user stories as a basis for a holistic review of the issues surrounding the use of cryptography. The authors concentrate on a relatively large population (non-expert IT users) carrying out typical tasks (web and email).

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Section: Risk Managementmentioning

confidence: 99%

User-visible cryptography in email and web scenarios

Brooke

Paige

2015

Information &Amp; Computer Security

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“…There is extensive research [39,41,48,54,66] examining the factors which affect the level of trust needed by a purchaser for participating in an e-commerce transaction. These include the purchaser's perception of the risks (based on his experience, that of others, peer evaluated reputation and so forth) [64], the purchaser's motivation for buying, and the reputation of the seller [66].…”

Section: Introductionmentioning

confidence: 99%

E-commerce: protecting purchaser privacy to enforce trust

Antoniou

Batten

2011

Electron Commer Res

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It has been well documented that lack of trust between commercial entities and purchasers can restrict the potential of e-commerce. This may be because the purchaser is required to provide personal information to the commercial entity, which may then be abused, or because the purchaser may be suspicious that after payment has been processed, the goods purchased will not arrive. The challenge for the researcher is to determine the e-commerce model which maximizes the trust a purchaser has when shopping online.In this paper, we focus on the personal information which must be revealed by the purchaser when purchasing online and we present the first comprehensive analysis of personal information distributed in an e-commerce setting from the point of view of the purchaser and his perception of trust in an online transaction. We introduce a measure of trust based on the information distributed to the parties in the transaction and isolate the instances which maximize trust for the purchaser relative to the personal information revealed. This leads us to the establishment of a theoretical framework on which to compare e-commerce protocols and to the development of four new models, all of which, as we demonstrate, are better in concrete ways than the traditional e-commerce model based on secure e-payment protocols. While the overall cost of implementation to the parties remains the same as in the traditional protocols, there is a slight overall decrease in cost to the seller but a slight increase in cost to the deliverer. However, the small additional costs to the deliverer are mitigated by the opportunity for new capabilities and business. Implementation of our work is likely to improve consumer trust and therefore lead to an increase in on-line commerce, especially in countries where privacy recognition is not strong.

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“…Informační management PRE Number of the user's previous positive experiences with online interaction (Gefen & Straub, 2004;Flavian et al, 2006;Casalo et al, 2008) TEC Perceived technological trustworthiness of the site/company (GrabnerKraeuter, 2002;Corbitt et al, 2003;Lacohee et al, 2006) …”

Section: Tab 1: Scenarios Before and After Entering An Interrelationmentioning

confidence: 99%

“…Qualitative modeling can be seen as one of the "uncertainty calculi", such as fuzzy sets (Zadeh, 1965;Dubois & Prade, 1991;Hub & Zatloukal, 2009), rough sets (Pawlak, 1982) and order of magnitude reasoning (Raiman, 1991). Such calculi can be helpful when dealing with online trust (Song et al, 2005;Chakraborty & Chakraborty, 2007;Li et al, 2009;Li et al, 2012), especially under information shortage, measurement diffi culties, time pressure to make decisions and/or uncertainty, or when several novel, subjective and/or diffi cult to measure (e.g. qualitative only) variables are being considered.…”

Section: Introductionmentioning

confidence: 99%

Formalized Qualitative Modeling of Online Trust: Introduction of the Method and a Detailed Example

Veselý¹,

Dohnal²

2016

E+M

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The paper presents a simple qualitative model of online trust in the context of e-commerce. Qualitative models use just three values: Positive/Increasing, Zero/Constant and Negative/ Decreasing. Such quantifi ers of trends are the least information intensive. Qualitative models can be useful, since models of online trust include such variables as e.g. Perceived website quality and ease of use (SIT) or Company’s positive reputation (REP) that are sometimes diffi cult or costly to quantify. Hence, a signifi cant fraction of available information about online trust is not of numerical nature, e.g. if SIT is decreasing then online trust is decreasing as well. Such equationless relations are studied in this paper. The model has 13 variables and 32 pair-wise interrelations among them. The set of variables and interrelations was established based on discussions with experts and internet users. The model is solved and 23 solutions, i.e. scenarios are obtained (thus, we reduce a vast set of all “imaginable” scenarios concerning online trust to a manageable list of scenarios). All qualitative states, and the fi rst and second qualitative derivatives of all variables are specifi ed for each scenario. Many modifi cations, upgrades and extensions of the present model are easy within the methodological framework introduced in the paper. Qualitative modeling can be seen as one of the uncertainty calculi, such as fuzzy sets and rough sets, that can be helpful e.g. under information shortage (for example when new website is about to be launched and/or when novel, subjective or diffi cult to measure variables are considered). The paper is self-contained and no a priori knowledge of qualitative modeling is required on the reader’s part.

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Risk and restitution: Assessing how users establish online trust

Cited by 29 publications

References 3 publications

User-visible cryptography in email and web scenarios

User-visible cryptography in email and web scenarios

E-commerce: protecting purchaser privacy to enforce trust

Formalized Qualitative Modeling of Online Trust: Introduction of the Method and a Detailed Example

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