A Hybrid Simulation Framework of Consumer-to-Consumer Ecommerce Space

In the past decade, ecommerce transformed the business models of many organizations. Information Technology leveled the playing field for new participants, who were capable of causing disruptive changes in every industry. Web 2.0 or Social Web further redefined ways users enlist for services. It is now easy to be influenced to make choices of services based on recommendations of friends and popularity amongst peers. This research proposes a simulation framework to investigate how actions of stakeholders at this level of complexity affect system performance as well as the dynamics that exist between different models using concepts from the fields of operations engineering, engineering management, and multi-model simulation. Viewing this complex model from a systems perspective calls for the integration of different levels of behaviors. Complex interactions exist among stakeholders, the environment and available technology. The presence of continuous and discrete behaviors coupled with stochastic and deterministic behaviors present challenges for using standalone simulation tools to simulate the business model. We propose a framework that takes into account dynamic system complexity and risk from a hybrid paradigm. The SCOR model is employed to map the business processes and it is implemented using agent based simulation and system dynamics. By combining system dynamics at the strategy level with agent based models of consumer behaviors, an accurate yet efficient representation of the business model that makes for sound basis of decision making can be achieved to maximize stakeholders\u27 utility

Crowdlending: mapping the core literature and research frontiers

[EN] Peer-to-peer (P2P) lending uses two-sided platforms to link borrowers with a crowd of lenders. Despite considerable diversity in crowdlending research, studies in this area typically focus on several common research topics, including information asymmetries, social capital, communication channels, and rating-based models. This young research field is still expanding. However, its importance has increased considerably since 2018. This rise in importance suggests that P2P lending may offer a promising new scientific research field. This paper presents a bibliometric study based on keyword co-occurrence, author and reference co-citations, and bibliographic coupling. The paper thus maps the key features of P2P lending research. Although many of the most cited papers are purely financial, some focus on behavioral finance. The trend in this field is toward innovative finance based on new technologies. The conclusions of this study provide valuable insight for researchers, managers, and policymakers to understand the current and future status of this field. The variables that affect new financial contexts and the strategies that promote technology-based financial environments must be investigated in the future.Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature.Ribeiro-Navarrete, S.; Piñeiro-Chousa, J.; López-Cabarcos, MÁ.; Palacios Marqués, D. (2022). Crowdlending: mapping the core literature and research frontiers. Review of Managerial Science. 16(8):2381-2411. https://doi.org/10.1007/s11846-021-00491-82381241116

Crowdlending: mapping the core literature and research frontiers

Peer-to-peer (P2P) lending uses two-sided platforms to link borrowers with a crowd of lenders. Despite considerable diversity in crowdlending research, studies in this area typically focus on several common research topics, including information asymmetries, social capital, communication channels, and rating-based models. This young research field is still expanding. However, its importance has increased considerably since 2018. This rise in importance suggests that P2P lending may offer a promising new scientific research field. This paper presents a bibliometric study based on keyword co-occurrence, author and reference co-citations, and bibliographic coupling. The paper thus maps the key features of P2P lending research. Although many of the most cited papers are purely financial, some focus on behavioral finance. The trend in this field is toward innovative finance based on new technologies. The conclusions of this study provide valuable insight for researchers, managers, and policymakers to understand the current and future status of this field. The variables that affect new financial contexts and the strategies that promote technology-based financial environments must be investigated in the futureOpen Access funding provided thanks to the CRUE-CSIC agreement with Springer NatureS

Online Fundraising Through the Lenses of Law, Economics, and Sociology: Examples from American P2P Lending and Thai Rotating Savings and Credit Association

In recent years, online lending has become a new method of financing that allows people to lend and borrow anywhere anytime. Yet, due to its complex and wide-ranging operation, the online lending phenomena has become one of the most buzzing regulatory concerns. Online lending not only challenges incumbent loan providers like commercial banks by providing loans to unserved borrowers at attractive rates, it also presents unprecedented investment opportunities for individual lenders who are often referred to as ‘peer’ or ‘crowd’ to lend out their money commercially. In this dissertation, I explore how two different online lending methods help individual lenders who often lack financial sophistication to make safe investment and how laws and regulations may affect online lending businesses and their consumers. This dissertation includes two essays that examine two examples of online lending practices: peer-to-peer (P2P) lending in the United States and online rotating savings and credit association (ROSCA) in Thailand. The first essay argues P2P lending platforms originally endorsed interpersonal relationships in lending and adopted many peer-to-peer features, such as social networks, personal profiles and group affiliations because interpersonal relationships are valuable and imperative for individual lenders and borrowers on P2P lending platforms. Nevertheless, the laws and regulations on P2P lending in the United States have caused P2P lending platforms to relinquish their commitments to utilize interpersonal relationships. The disappearance of interpersonal relationship on P2P lending platforms results in worse economic and sociological outcomes for individual lenders.The second essay argues that interpersonal relationship is paramount to the success of ROSCAs in Thailand. Traditionally, ROSCA participants rely on their interpersonal relationships to lend and borrow from each other. Recently, an online form of ROSCAs has emerged and spread. Online ROSCAs allow strangers, who have no interpersonal relationship to easily create a virtual ROSCA. Such a risk alarms the financial regulators, lawmakers, and the public. Nevertheless, the current regulatory landscape on ROSCAs have also been developed based on a long concern of frauds created by informal fundraising methods. While the current regulatory regime aims to ban and restrict ROSCAs which are operate beyond a local and personal level, the regulations effectively deem the whole category of online ROSCAs illegal and drove them to operate outside to the formal financial system. Both P2P lending in the United States and ROSCAs in Thailand utilize interpersonal relationships among parties of lending transaction to address four fundamental concerns in lending: uncertainty, information asymmetry, interpersonal trust, and institutional trust. From an economic perspective, Ronald Coase’s proposition suggests that personal relationships may help reduce uncertainty and information asymmetry in economic transactions including lending. From a sociological perspective, Francis Fukuyama and Linda Molm acknowledge the importance of interpersonal trust and institutional trust within financial exchanges. Interpersonal relationships among actors of a financial transaction can build and maintain interpersonal trust and institutional trust. This dissertation also applies both the economic and sociological perspectives to understand how laws and regulations might affect P2P lending platforms, and traditional and online ROSCAs. The studies of P2P lending platforms and online ROSCAs exemplify how the current laws and regulations which were developed based on more traditional financial methods can shift new financial services, particularly online lending, into a worse position

Decentralized Finance – A Systematic Literature Review and Research Directions

Decentralized Finance (DeFi) is the (r)evolutionary movement to create a solely code-based, intermediary-independent financial system—a movement which has grown from $4bn to$104bn in assets locked in the last three years. We present the first systematic literature review of the yet fragmented DeFi research field. By identifying, analyzing, and integrating 83 peer-reviewed DeFi-related publications, our results contribute fivefold. First, we confirm the increasing growth of academic DeFi publications through systematic analysis. Second, we frame DeFi-related literature into three levels of abstraction (micro, meso, and macro) and seven subcategories. Third, we identify Ethereum as the blockchain in main academic focus. Fourth, we show that prototyping is the dominant research method applied whereas only one paper has used primary research data. Fifth, we derive four prioritized research avenues, namely concerning i) DeFi protocol interaction and aggregation platforms, ii) decentralized off-chain data integration to DeFi, iii) DeFi agents, and iv) regulation

Fintech and the future of financial services: What are the research gaps?

New financial technologies (FinTech) have erupted around the world. Consequently, there has been a considerable increase in academic literature on FinTech over the last five years. Research tends to be scantily connected with no coherent research agenda. Signi - cant research gaps and important questions remain. There is much work to be done before this area becomes an established academic discipline. This paper offers coherent research themes formulated through focus group meetings with policymakers and academics, and also based on a critical assessment of the literature. We outline seven key research gaps with questions that could form the basis of academic study. If these are addressed it would help this area become an established academic discipline

Essays on trust and online peer-to-peer markets

The internet has led to the rapid emergence of new organizational forms such as the sharing economy, crowdfunding and crowdlending and those based on the blockchain. Using a variety of methods, this dissertation empirically explores trust and legitimacy in these new markets as they relate to investor decision making

Disrupting Finance

This open access Pivot demonstrates how a variety of technologies act as innovation catalysts within the banking and financial services sector. Traditional banks and financial services are under increasing competition from global IT companies such as Google, Apple, Amazon and PayPal whilst facing pressure from investors to reduce costs, increase agility and improve customer retention. Technologies such as blockchain, cloud computing, mobile technologies, big data analytics and social media therefore have perhaps more potential in this industry and area of business than any other. This book defines a fintech ecosystem for the 21st century, providing a state-of-the art review of current literature, suggesting avenues for new research and offering perspectives from business, technology and industry

A Trust Management Framework for Decision Support Systems

In the era of information explosion, it is critical to develop a framework which can extract useful information and help people to make “educated” decisions. In our lives, whether we are aware of it, trust has turned out to be very helpful for us to make decisions. At the same time, cognitive trust, especially in large systems, such as Facebook, Twitter, and so on, needs support from computer systems. Therefore, we need a framework that can effectively, but also intuitively, let people express their trust, and enable the system to automatically and securely summarize the massive amounts of trust information, so that a user of the system can make “educated” decisions, or at least not blind decisions. Inspired by the similarities between human trust and physical measurements, this dissertation proposes a measurement theory based trust management framework. It consists of three phases: trust modeling, trust inference, and decision making. Instead of proposing specific trust inference formulas, this dissertation proposes a fundamental framework which is flexible and can be adapted by many different inference formulas. Validation experiments are done on two data sets: the Epinions.com data set and the Twitter data set. This dissertation also adapts the measurement theory based trust management framework for two decision support applications. In the first application, the real stock market data is used as ground truth for the measurement theory based trust management framework. Basically, the correlation between the sentiment expressed on Twitter and stock market data is measured. Compared with existing works which do not differentiate tweets’ authors, this dissertation analyzes trust among stock investors on Twitter and uses the trust network to differentiate tweets’ authors. The results show that by using the measurement theory based trust framework, Twitter sentiment valence is able to reflect abnormal stock returns better than treating all the authors as equally important or weighting them by their number of followers. In the second application, the measurement theory based trust management framework is used to help to detect and prevent from being attacked in cloud computing scenarios. In this application, each single flow is treated as a measurement. The simulation results show that the measurement theory based trust management framework is able to provide guidance for cloud administrators and customers to make decisions, e.g. migrating tasks from suspect nodes to trustworthy nodes, dynamically allocating resources according to trust information, and managing the trade-off between the degree of redundancy and the cost of resources