Domain ontology for digital marketplaces

Recently the sharing economy has emerged as a viable alternative to fulfilling a variety of consumer needs. As there is no consensus on the definition of ‘sharing economy’ we use the term ‘marketplace’ to refer more specifically to Internet/software-based sharing economy platforms connecting two different market segments. In the field of sharing economy and marketplaces we found a research gap concerning the (socio)technological aspects and the development of marketplaces. A marketplace ontology can help to have a clear account of marketplace concepts which will facilitate communication, consensus and alignment. In this paper we design this marketplace ontology in four steps. First the selection of UFO as foundation and UFO-S as core ontology. Second the search for a set of minimal conditions and properties common for marketplaces and the derivation into competency questions. Third, use the competency questions to identify fragmented sub-ontology pieces called Domain-Related Ontology Patterns (DROPs) and apply them informally by extending UFO-S concepts to design a marketplace domain ontology. This marketplace domain ontology is represented in OntoUML. The last step is the validation of the OntoUML model using expert knowledge

Do genetic factors protect for early onset lung cancer? A case control study before the age of 50 years

<p>Abstract</p> <p>Background</p> <p>Early onset lung cancer shows some familial aggregation, pointing to a genetic predisposition. This study was set up to investigate the role of candidate genes in the susceptibility to lung cancer patients younger than 51 years at diagnosis.</p> <p>Methods</p> <p>246 patients with a primary, histologically or cytologically confirmed neoplasm, recruited from 2000 to 2003 in major lung clinics across Germany, were matched to 223 unrelated healthy controls. 11 single nucleotide polymorphisms of genes with reported associations to lung cancer have been genotyped.</p> <p>Results</p> <p>Genetic associations or gene-smoking interactions was found for <it>GPX1(Pro200Leu) </it>and <it>EPHX1(His113Tyr)</it>. Carriers of the Leu-allele of <it>GPX1(Pro200Leu) </it>showed a significant risk reduction of OR = 0.6 (95% CI: 0.4–0.8, p = 0.002) in general and of OR = 0.3 (95% CI:0.1–0.8, p = 0.012) within heavy smokers. We could also find a risk decreasing genetic effect for His-carriers of <it>EPHX1(His113Tyr) </it>for moderate smokers (OR = 0.2, 95% CI:0.1–0.7, p = 0.012). Considered both variants together, a monotone decrease of the OR was found for smokers (OR of 0.20; 95% CI: 0.07–0.60) for each protective allele.</p> <p>Conclusion</p> <p>Smoking is the most important risk factor for young lung cancer patients. However, this study provides some support for the T-Allel of <it>GPX1(Pro200Leu) </it>and the C-Allele of <it>EPHX1(His113Tyr) </it>to play a protective role in early onset lung cancer susceptibility.</p

Scalability and robustness of business models for sustainability: A simulation experiment

Entrepreneurial ventures increasingly aim at developing viable business models for solving societal or ecological challenges. Such business models for sustainability (BMfS) build on reinforcing mechanisms of value creation and capture that allow achieving financial and sustainability objectives simultaneously. To date, we do not know much about the successful design of such business models. This research aims to reduce this gap by experimentally exploring their scalability and robustness in different environmental conditions. Rooted in the literature on business models and innovation adoption, we develop a simulation model that integrates various dimensions of BMfS. We apply the simulation to Coursera, an entrepreneurial venture with the social mission of making high-quality education globally accessible. The simulation allows us to test hypotheses about the venture's financial and sustainability performance over time. We find that the business model is highly scalable but shows limited robustness to strong competitive pressure. We derive implications for the effective design of business models and discuss how the findings contribute to sustainability literature

A reference architecture for customizable marketplaces

A broader term used for a platform in the sharing economy is 'marketplace'. This is a type of e-commerce site or app where transactions for services of-fered by multiple providers are processed by the marketplace operator (e.g. Uber, Airbnb, eBay). Lately the number and popularity of marketplaces has exploded, with more variety and focus on niche markets. Software products like Sharetribe make it possible to create a customized marketplace quick and with few resources. It is, however, not known whether such products cater for the needs of all possible varieties of marketplace, nor how such products can be selected and/or customized to provide the best fit with a particular marketplace. The goal of this PhD project is to design a Software Reference Architecture (SRA) for marketplaces which can be used to select or create the most suitable software product. Our first step in the project is to design a conceptual data model for this SRA based on a marketplace do-main ontology

Towards a reference ontology for digital platforms

Digital platforms can be categorized into different types including ‘multi-sided platform’, ‘digital marketplace’, ‘crowdfunding platform’, ‘sharing economy platform’ and ‘on-demand platform’. As there is a lack of knowledge regarding the requirements and design of these digital platform types, we developed a method to design a digital platform reference ontology based on a taxonomy. The taxonomy provides an overview of digital platform properties, with the property values expressing the possible variations between digital platforms depending on their type. For each property value, we can create a digital platform reference ontology module using the five-step approach proposed by Ruy et al. [1] based on the patterns of the Unified Foundational Ontology (UFO). UFO is a high-level ontology that provides us with basic concepts for objects, events, social elements and their types, relations and properties. These digital platform reference ontology modules can be combined as building blocks to compose our reference ontology for expressing the functionality for digital platforms of all types. We believe this reference ontology can be a step towards a better understanding of digital platform functionality, better communication between stakeholders and eventually may facilitate future research and development of digital platforms