A Customer Confusion Environment in Telecommunication Networks: Analysis and Policy Impact

Abstract

In this paper, we have studied the impact of customer confusion on the decision-making strategies of Internet service providers (ISP) in the network and telecommunications market. This confusion may come from several factors, e.g. incomplete information on the offer, non-transparent advertising, the ability of the analysis, etc.; but that sure varies over time since yesterday’s customer is no longer today’s. In this work, we have developed a simple oligopolistic model, using non-cooperative game theory, to formalize the interactions between service providers and end-users by considering that the rationality of customers varies over time. We assessed the impact of the dynamics of consumer confusion on the competition and profitability of service providers who are considered rational and competitive with one another to maximize their respective gains in the face of a confused fraction of consumers while others are not confused. We have shown the existence and uniqueness of the Nash equilibrium. We used the best response dynamic algorithm for learning Nash equilibrium. On the one hand, we have shown that when the number of confused customers is large, the ISP is interested in that and they offer moderately high prices with low quality of service. On the other hand, over time, rationality increases, forcing the ISPs to change their strategies by offering better services so that their demand increases. We also add that when customer behavior changes quickly, the ISPs follow clearer strategies with customer satisfactory services.

Analysis of the Chaotic Dynamics Duopoly Game of ISPs Bounded Rational

“…e demand of ISP j is a linear function with respect to the network access price p s j , price to access to the content in cache p c j , quality of service q s j , and number of cached items k j (see [2,8,49]).…”

“…In last years, game theory has been used to solve many problems in communication networks [1][2][3][4][5][6][7]. It has been used to propose new pricing strategies for Internet services [8,9]. Many other issues relating to wireless networks have been modeled and analyzed using game theory, such as resource allocation [10,11], power control [12], network routing [13], network caching [14], security [15], etc.…”

“…e authors in [26] considered bounded rationality in the telecommunication networks. e authors in [8,27,28] studied competition between service providers where end-users are bounded rational. In [29], the authors investigated a batch matching system with boundedly rational end-users.…”

A Non-cooperative Game-Theoretic Framework for Sponsoring Content in the Internet Market

“…The authors in [18] studied competition between ISP in Information Centric Network using mathematical tools game theory. In [19], the authors modeled and studied competition between ISP where end-users are bounded rational. The authors [20] model and analyze ISPs best strategies in terms of quality offered to a big CP in a competitive context.…”