This paper reports a solution to the inverse problem when using indicators in several calculation functions. Such problems arise during the formation of a multi-level scorecard; solving them makes it possible to determine the value of arguments in order to achieve the specified value of the...

Two-sided platforms rely on their recommendation algorithms to help visitors successfully find a match. However, on platforms such as VolunteerMatch - which has facilitated millions of connections between volunteers and nonprofits - a sizable fraction of website traffic arrives directly to a...

This paper considers whether the increased use of pricing algorithms presents issues that existing merger control frameworks and practices are inadequate to address, particularly in relation to pre-merger disclosure of pricing algorithms and the suitability of current tests, frameworks and...

This paper investigates pricing in laboratory markets when human players interact with an algorithm. We compare the degree of competition when exclusively humans interact to the case of one firm delegating its decisions to an algorithm, an n -player generalization of tit-for-tat. We further vary...

This chapter examines the intersection of dynamic pricing algorithms and U.S. price gouging laws. Recently, an increasing number of companies, particularly online retailers and technologically- enabled service providers, implemented pricing algorithms that dynamically update prices in real time...

In the world of business, firms have started adopting technologies to develop and grow their businesses. To sustain in this competitive market there is a dire need for better performance and precision in prediction .To achieve this goal various businesses, require to accurately analyze and...

Algorithms are inherently centralised processes, from coding, to training, to deployment and maintenance. Meanwhile, blockchain communities are experimenting with “Decentralised Autonomous Organisations” (DAOs) as a participatory institutional framework for individual autonomy to organise...

This paper addresses a new electricity-charging station location problem for congested intercity or regional networks, in which electric vehicles with a limited driving range require recharges for their long-distance trips. When the distribution of charging stations does not sufficiently cover...

Training effective machine learning algorithms requires inhomogeneous data from different sources, which may violate data protection regulations. Federated learning (FedL), emerged as a privacy-aware alternative, enables collaborative model training without accessing the original data. One of...

Recent studies have proven that pricing algorithms can autonomously learn to coordinate prices, and set them at supra-competitive levels. The growing use of such algorithms mandates the creation of solutions that limit the negative welfare effects of algorithmic coordination. Unfortunately, to...