Recommender Systems from an Industrial and Ethical Perspective

Paraschakis, Dimitris

doi:10.1145/2959100.2959101

Cited by 25 publications

(16 citation statements)

References 13 publications

(17 reference statements)

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“…This, the authors predict, could be made achievable through the use of interlinked big data structures. Finally, Paraschakis (2016Paraschakis ( , 2017Paraschakis ( , 2018 provides one of the most detailed accounts. Focusing on e-commerce applications, Paraschakis suggests that there are five ethically problematic areas:…”

Section: Inappropriate Contentmentioning

confidence: 99%

Recommender systems and their ethical challenges

2020

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This article presents the first, systematic analysis of the ethical challenges posed by recommender systems through a literature review. The article identifies six areas of concern, and maps them onto a proposed taxonomy of different kinds of ethical impact. The analysis uncovers a gap in the literature: currently user-centred approaches do not consider the interests of a variety of other stakeholders—as opposed to just the receivers of a recommendation—in assessing the ethical impacts of a recommender system.

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Section: Inappropriate Contentmentioning

confidence: 99%

Recommender systems and their ethical challenges

2020

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“…Finally, (Paraschakis, 2016(Paraschakis, , 2017(Paraschakis, , 2018 provides one of the most detailed accounts.…”

Section: Ethical Contentmentioning

confidence: 99%

Recommender Systems and their Ethical Challenges

2019

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This article presents the first, systematic analysis of the ethical challenges posed by recommender systems. Through a literature review, the article identifies six areas of concern, and maps them onto a proposed taxonomy of different kinds of ethical impact. The analysis uncovers a gap in the literature: currently user-centred approaches do not consider the interests of a variety of other stakeholders-as opposed to just the receivers of a recommendation-in assessing the ethical impacts of a recommender system.

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“…Furthermore, Paraschakis (2016) surveyed more than 30 current shopping cart solutions and compared the performance of popular recommendation algorithms on e-commerce data sets. Results revealed that the systems rarely go beyond trivial bestseller lists.…”

Section: Literature Reviewmentioning

confidence: 99%

A new model for assessing the role of customer behavior history, product classification, and prices on the success of the recommender systems in e-commerce

Wakil

Alyari²,

Ghasvari

et al. 2019

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Purpose This paper aims to propose a new method for evaluating the success of the recommender systems based on customer history, product classification and prices criteria in the electronic commerce. To evaluate the validity of the model, the structural equation modeling technique is employed. Design/methodology/approach A method has been suggested to evaluate the impact of customer history, product classification and prices on the success of the recommender systems in electronic commerce. After that, the authors investigated the relationship between these factors. To achieve this goal, the structural equation modeling technique was used for statistical conclusion validity. The results of gathered data from employees of a company in Iran is indicated the impact of the customer history on the success of recommender systems in e-commerce which is related with the user profile, expert opinion, neighbors, loyalty and clickstream. These factors positively influence the success of recommender systems in ecommerce. Findings The obtained results demonstrated the efficiency and effectiveness of the proposed model in term of the success of the recommender systems in the electronic commerce. Originality/value In this paper, the effective factors of success of recommender systems in electronic commerce are pointed out and the approach to increase the efficiency of this system is applied into a practical example.

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Recommender Systems from an Industrial and Ethical Perspective

Cited by 25 publications

References 13 publications

Recommender systems and their ethical challenges

Recommender systems and their ethical challenges

Recommender Systems and their Ethical Challenges

A new model for assessing the role of customer behavior history, product classification, and prices on the success of the recommender systems in e-commerce

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