Mobilizing a pluralist theoretical approach to understand microlending digital platforms: the AfricaMC case

Purpose This study aims to explore how a microlending digital platform connects social investors in developed countries and micro-entrepreneurs in Africa. However, additional research is necessary to discuss how online auction models are designed and implemented and how existing theories can explain their use in the so-called developing countries. Design/methodology/approach The research is based on a single case study: an online auction model for microlending named AfricaMC. Two main methods collected empirical data, namely, online participant observation, i.e. real-time participation in the online auction market and in the forum of discussions, where the authors observed the processes of microlending transactions as registered members; analysis of online documents, by reviewing forum discussions, analyzing reports, blogs, chats and other materials. Findings The results suggest that using sociological and information systems theoretical lenses in a complementary manner could provide greater value than using economics. Originality/value The study makes two main contributions. First, it mobilizes a pluralist theoretical approach based on economic, sociological and information systems perspectives to improve the understanding of microlending digital platforms using online auction models. Second, it uses the understanding produced from data analysis of one particular African case to validate propositions derived from these three theoretical approaches that might be applied to other cases.

Emerging Methods of Auction Design in Social Networks

In recent years, a new branch of auction models called diffusion auction has extended the traditional auction into social network scenarios. The diffusion auction models the auction as a networked market whose nodes are potential customers and whose edges are the relations between these customers. The diffusion auction mechanism can incentivize buyers to not only submit a truthful bid, but also further invite their surrounding neighbors to participate into the auction. It can convene more participants than traditional auction mechanisms, which leads to better optimizations of different key aspects, such as social welfare, seller’s revenue, amount of redistributed money and so on. The diffusion auctions have recently attracted a discrete interest in the algorithmic game theory and market design communities. This survey summarizes the current progress of diffusion auctions.

Extreme Value Theory and Auction Models

The objective of this article is to develop a parametric approach to estimating auctions with incomplete data using Extreme Value Theory (EVT). The methodology is mainly theoretical: we first review that, when only transaction prices can be observed, the distribution of private valuations is irregularly identified. The sample bias produced by nonparametric estimators will affect all functionals of practical interest. We provide simulations for a best-case scenario and a worst-case scenario. Our results show that, compared to nonparametric approaches, the approximation of such functionals developed using EVT produces more accurate results, is easy to compute, and does not require strong assumptions about the unobserved distribution of bidders' valuations. It is recommended that financial operators working with auctions use this parametric approach when facing incomplete datasets. Given the difficult nature of the analysis, this work does not provide large sample properties for the proposed estimators and recommends the use of bootstrapping. This article contributes originally to the literature of structural estimation of auction models providing a useful and robust parametric approximation.

The rise of the policy-takers: Universal service policy adoption in Jordan and Morocco

In the late 1990s, Jordan and Morocco revised their telecommunications regulation drastically. Though these regulations were first largely inspired by the European Union policy models, each country gradually developed more autonomy, individually tailoring their regulatory frameworks overtime. The case of Universal Service Obligation (USO) policies show that while Jordan remained aligned with the European Union, Moroccan policy-makers diverged from the European Union by adopting alternative policies, inspired by the Latin American reverse-auction models. Research focusing on Euro-Mediterranean regulatory contexts commonly expect neighbouring countries to converge with EU regulatory models. Yet, borrowing on policy diffusion literature and specifically the mechanisms of learning and imitation, this article shows that policy-takers intentionally decided on the (non)adoption of USO policies. Thus, research needs to take the role of policy-takers seriously and acknowledge avenues for bidirectional convergence.

A cloud priority-based dynamic online double auction mechanism (PB-DODAM)

Double auctions are considered to be effective price-scheduling mechanisms to resolve cloud resource allocation and service pricing problems. Most of the classical double auction models use price-based mechanisms in which determination of the winner is based on the prices offered by the agents in the market. In cloud ecosystems, the services offered by cloud service providers are inherently time-constrained and if they are not sold, the allocated resources for the unsold services are wasted. Furthermore, cloud service users have time constraints to complete their tasks, otherwise, they would not need to request these services. These features, perishability and time-criticality, have not received much attention in most classical double auction models. In this paper, we propose a cloud priority-based dynamic online double auction mechanism (PB-DODAM), which is aligned with the dynamic nature of cloud supply and demand and the agents’ time constraints. In PB-DODAM, a heuristic algorithm which prioritizes the agents’ asks and bids based on their overall condition and time constraints for resource allocation and price-scheduling mechanisms is proposed. The proposed mechanism drastically increases resource allocation and traders’ profits in both low-risk and high-risk market conditions by raising the matching rate. Moreover, the proposed mechanism calculates the precise defer time to wait for any urgent or high-priority request without sacrificing the achieved performance in resource allocation and traders’ profits. Based on experimental results in different scenarios, the proposed mechanism outperforms the classical price-based online double auctions in terms of resource allocation efficiency and traders’ profits while fulfilling the double auction’s truthfulness pillar.