We will review some of the major results in random graphs and some of the more challenging open problems. We will cover algorithmic and structural questions. We will touch on newer models, including those related to the WWW.

Random graphs

Open Innovation: The New Imperative for Creating and Profiting from Technology

A systematic literature review of blockchain-based applications: Current status, classification and open issues

หนงสอ Behavioral Game Theory: Experiments in Strategic Interaction เขยนโดย Colin F. Camerer มวตถประสงคเพอนำเสนอหลกฐานเชงประจกษจากผลการวจยจำนวนมากมายทยนยนอทธพลของปจจยทางจตวทยาทมผลตอการตดสนใจตามทฤษฎเกม หนงสอ เลมนไดนำเสนอแนวคดทฤษฎทเพมความสามารถในการอธบายพฤตกรรมการตดสนใจตามทฤษฎเกม (Game theory) ซง von Neumann; & Morgenstern ไดเสนอไวในป ค.ศ. 1944 โดยชใหเหนวา ปจจยทางจตวทยามอทธพลทำใหการตดสนใจทเกดขนจรงคลาดเคลอนจากการคาดการณของทฤษฎเกม

Behavioral Game Theory: Experiments in Strategic Interaction

Models and Methods in Social Network Analysis presents the most important developments in quantitative models and methods for analyzing social network data that have appeared during the 1990s. Intended as a complement to Wasserman and Faust’s Social Network Analysis: Methods and Applications, it is a collection of original articles by leading methodologists reviewing recent advances in their particular areas of network methods. Reviewed are advances in network measurement, network sampling, the analysis of centrality, positional analysis or blockmodeling, the analysis of diffusion through networks, the analysis of affiliation or “two-mode” networks, the theory of random graphs, dependence graphs, exponential families of random graphs, the analysis of longitudinal network data, graphic techniques for exploring network data, and software for the analysis of social networks.

/pdf/models-and-methods-in-social-network-analysis-46f9pqfov7.pdf

Models and methods in social network analysis

The limits of trust-free systems : A literature review on blockchain technology and trust in the sharing economy

Trust has been in the focus of research on business-to-consumer (B2C) e-commerce in the last decade. The rise of consumer-to-consumer (C2C) markets in the context of the sharing economy, however, has posed new challenges and questions regarding the dimensionality and role of trust in online transactions. We outline a conceptual research model for the role of trust with regard to the consumers’ and suppliers’ intentions to engage in this economy. Our model differentiates between three substantial targets of trust, that is, trust towards peer, platform, and product (3P). We propose and evaluate a questionnaire, which addresses these targets in their dimensions ability, integrity, and benevolence.

https://www.nomos-elibrary.de/10.5771/0042-059X-2016-1-26.pdf

Trust in the Sharing Economy

As peer-to-peer coordinated products and services increasingly constitute competition for traditional businesses in many areas, understanding the underlying user motives of provision and consumption is key -- not only for business operators, but also for researchers investigating such markets. In this article, we develop a questionnaire for assessing motives for and against participating in what is casually referred to as the "Sharing Economy." More specifically, we focus on peer-to-peer rental services and investigate drivers and impediments for user activity in such markets by means of an online survey with over 600 participants.

/pdf/understanding-the-sharing-economy-drivers-and-impediments-inu9k49y4p.pdf

Understanding the Sharing Economy -- Drivers and Impediments for Participation in Peer-to-Peer Rental

Trust is a crucial prerequisite for peer-to-peer rental and sharing. Therefore, platform operators such as Airbnb have implemented a plethora of trustbuilding mechanisms, user interface (UI) artefacts, and reputation systems. While the role of reputation systems for establishing trust is well-understood, little is known about how reputation actually translates into tangible economic value, either by attracting more demand or by enabling the enforcement of higher prices. In this paper, we consider the economic value of trust-building artefacts on Airbnb by quantifying price effects of common reputation features from a signaling theory perspective. Our analysis is based on hedonic price modeling and a large-scale dataset from 86 German cities that provides insights in the price effects of a diverse set of variables (average rating score, number of ratings, Superhost status, ID verification, photos, and duration of membership). Employing hedonic price regression modeling, we find that index signals such as the hosts’ rating scores and duration of membership are associated with economic value. Moreover, also conventional signals such as accommodation photographs consistently translate into price premiums. We discuss implications for platform operators, users, and the general design of Information Systems (IS) artefacts intended to facilitate peer-to-peer platform interactions.

Price Determinants on Airbnb: How Reputation Pays Off in the Sharing Economy

A growing body of research from various domains has investigated Airbnb, a two-sided market platform for peer-based accommodation sharing. The authors suggest that it is due time to take a step back and assess the current state of affairs. This paper aims to conflate and synthesize research on Airbnb.,To facilitate research on Airbnb and its underlying principles in electronic commerce, the authors present a structured literature review on Airbnb.,The findings are based on 118 articles from the fields of tourism, information and management, law and economics between 2013 and 2018. Based on this broad basis, the authors find that: research on Airbnb is highly diverse in terms of domains, methods and scope; motives for using Airbnb are manifold (e.g. financial, social and environmental); trust and reputation are considered crucial by almost all scholars; the platform’s variety is reflected in prices; and the majority of work is based on surveys and empirical data while experiments are scarce.,Based on the present assessment of studied topics, domains, methods and combinations thereof, the authors suggest that research should move toward building atop of a common ground of data structures and vocabulary, and that attention should focus on the identified gaps and hitherto scarcely used combinations. The set of under-represented areas includes cross-cultural investigations, field experiments and audit studies, the consideration of dynamic processes (e.g. based on panel data), Airbnb’s “experiences” and automated pricing algorithms and the rating distribution’s skewness.,This study provides a comprehensive overview of work on the accommodation sharing platform Airbnb, to the best of the auhtors’ knowledge, representing the first systematic literature review. The authors hope that researchers and practitioners alike will find this review useful as a reference for future research on Airbnb and as a guide for the development of innovative applications based on the platform’s peculiarities and paradigms in electronic commerce practice. From a practical perspective, the general tenor suggests that hotel and tourism operators may benefit from: focusing on their core advantages over Airbnb and differentiating features and aligning their marketing communication with their users’ aspirations.

Timm Teubner

Papers

The limits of trust-free systems : A literature review on blockchain technology and trust in the sharing economy

Trust in the Sharing Economy

Understanding the Sharing Economy -- Drivers and Impediments for Participation in Peer-to-Peer Rental

Price Determinants on Airbnb: How Reputation Pays Off in the Sharing Economy

Poster child and guinea pig – insights from a structured literature review on Airbnb