Purpose - In this research, the main purpose is to use a suitable structure to predict the trading signals of the stock market with high accuracy. For this purpose, two models for the analysis of technical adaptation were used in this study. Design/methodology/approach - It can be seen that...

Artificial Intelligence (AI) increasingly becomes an indispensable advisor. New ethical concerns arise if AI persuades people to behave dishonestly. In an experiment, we study how AI advice (generated by a Natural-Language-processing algorithm) affects (dis)honesty, compare it to equivalent...

Fairness is a crucial concept in the context of artificial intelligence (AI) ethics and policy. It is an incremental component in existing ethical principle frameworks, especially for algorithm-enabled decision systems. Yet, unwanted biases in algorithms persist due to the failure of...

With the development of the internet and the availability of smart phones, online shopping and the number of digital buyers have increased enormously under the present social context (COVID-19). The major pitfall of this marketing system is the random non-availability of/refusal by customers....

Single-period dynamic assortment planning involves the retailer's decision of selecting a set of products to offer and determining their initial inventory levels, considering stochastic demand and dynamic substitution. The objective is to maximize the expected revenue, subject to a capacity...

We present a new mixed-integer program for a multi-depot, multi-vehicle capacitated location-allocation routing problem (LARP). The model simultaneously selects the locations of facilities, allocates customers to the intermediate facilities, and identifies the optimal number of capacitated...

Artificial intelligence algorithms are increasingly used by firms to set prices. Previous research on pricing algorithms shows that they can exhibit collusive behavior, but it has so far remained an open question whether they can do so in a reasonably short time. I develop a deep reinforcement...

Large e-commerce retailers and department stores function as marketplaces for millions of sellers, and consumers rely on the platform's assortment and display decisions to examine different sellers and make purchase decisions. Traditionally, the primary objective of these marketplaces for...

Classic artificial intelligence (Q-learning) algorithms have been capable of consistently learning supra-competitive pricing strategies in infinitely repeated Nash-Bertrand pricing games without human communication. Such algorithms have been able to converge due to the temporal correlation of...