Models of everywhere revisited: a technological perspective

The concept ‘models of everywhere’ was first introduced in the mid 2000s as a means of reasoning about the environmental science of a place, changing the nature of the underlying modelling process, from one in which general model structures are used to one in which modelling becomes a learning process about specific places, in particular capturing the idiosyncrasies of that place. At one level, this is a straightforward concept, but at another it is a rich multi-dimensional conceptual framework involving the following key dimensions: models of everywhere, models of everything and models at all times, being constantly re-evaluated against the most current evidence. This is a compelling approach with the potential to deal with epistemic uncertainties and nonlinearities. However, the approach has, as yet, not been fully utilised or explored. This paper examines the concept of models of everywhere in the light of recent advances in technology. The paper argues that, when first proposed, technology was a limiting factor but now, with advances in areas such as Internet of Things, cloud computing and data analytics, many of the barriers have been alleviated. Consequently, it is timely to look again at the concept of models of everywhere in practical conditions as part of a trans-disciplinary effort to tackle the remaining research questions. The paper concludes by identifying the key elements of a research agenda that should underpin such experimentation and deployment

Tracking Uncertainty Propagation from Model to Formalization: Illustration on Trust Assessment

International audienceThis paper investigates the use of the URREF ontology to characterize and track uncertainties arising within the modeling and formalization phases. Estimation of trust in reported information, a real-world problem of interest to practitioners in the field of security, was adopted for illustration purposes. A functional model of trust was developed to describe the analysis of reported information, and it was implemented with belief functions. When assessing trust in reported information, the uncertainty arises not only from the quality of sources or information content, but also due to the inability of models to capture the complex chain of interactions leading to the final outcome and to constraints imposed by the representation formalism. A primary goal of this work is to separate known approximations, imperfections and inaccuracies from potential errors, while explicitly tracking the uncertainty from the modeling to the formalization phases. A secondary goal is to illustrate how criteria of the URREF ontology can offer a basis for analyzing performances of fusion systems at early stages, ahead of implementation. Ideally, since uncertainty analysis runs dynamically, it can use the existence or absence of observed states and processes inducing uncertainty to adjust the tradeoff between precision and performance of systems on-the-fly

Data Credence in IoR: Vision and Challenges

As the Internet of Things permeates every aspect of human life, assessing the credence or integrity of the data generated by "things" becomes a central exercise for making decisions or in auditing events. In this paper, we present a vision of this exercise that includes the notion of data credence, assessing data credence in an efficient manner, and the use of technologies that are on the horizon for the very large scale Internet of Things

Data Credence in IoT: Vision and Challenges

As the Internet of Things permeates every aspect of human life, assessing the credence or integrity of the data generated by "things" becomes a central exercise for making decisions or in auditing events. In this paper, we present a vision of this exercise that includes the notion of data credence, assessing data credence in an efficient manner, and the use of technologies that are on the horizon for the very large scale Internet of Things

Channel Choice Determinants; an exploration of the factors that determine the choice of a service channel in citizen initiated contacts

Citizens have various service channels at their disposal to interact with governmental agencies. In this paper we explore citizens’ motives to choose a certain channel in a certain situation. We conducted a qualitative study to accumulate the most important behavioral determinants. Six groups of determinants were found; habit, channel characteristics, task characteristics, situational constraints, experiences and personal characteristics. People appear to generally follow two lines of decision making when choosing channels, the first is based on habits. When task complexity and ambiguity increase, people start reasoning and follow the second line; channel choice based on a thorough elaboration between task and channel characteristics

Economic Experiments and Neutrality in Internet Access

Economic experiments yield lessons to firms that can be acquired only through market experience. Economic experiments cannot take place in a laboratory; scientists, engineers, or marketing executives cannot distill equivalent lessons from simply building a prototype or interviewing potential customers and vendors. The historical record illustrates that economic experiments were important for value creation in Internet access markets. In general, industry-wide returns from economic experiments exceed private returns, with several important exceptions. Those conclusions motivate an inquiry into whether regulatory policy can play a role in fostering the creation of value. The net neutrality debate is reinterpreted through this lens. A three part test is proposed for encouraging economic experiments from both broadband carriers and providers of complementary services.

Regulating Financial Innovations Without Apology

This paper views the housing and credit bubble 2001-2008 in a stylized manner, namely as a sequence starting with a financial innovation in 2001 followed by the superimposition of other financial innovations leading to the prevalence of uncertainty in Knight’s sense and ending in the last quarter of 2008 with both market failure and regulation failure. This ‘debt bubble sequence’ is just a slice of a dynamic process of stupefying complexity involving ignorance in a fundamental way. Few analysts would deny that a financial innovation, namely the sub-prime mortgage,combined with market participants’ ignorance about the size and location of the risk underlying complex financial products was a critical factor conducive to the financial meltdown 2007-2008. To the extent that financial innovation does bear the blame, the most obvious question is whether anything can be done to help reduce the degree of public’s ignorance about financial innovations and to prevent destabilizing innovations from entering the market.The main claim of this paper is that society should be involved in exercising directive intelligence through an appropriate institutional arrangement over the intricacies and technicalities inherent to financial innovations. Specifically, the paper proposes a new institutional arrangement conceived with the aim of strengthening financial system reliability and breaking the ‘government regulation-financial innovation’ vicious circle.Toxic financial innovations, Knightian uncertainty, debt bubble 2001-2008, relevant regulation

A conceptual model of channel choice: measuring online and offline shopping value perceptions

This study tries to understand how consumers evaluate channels for their purchasing. Specifically, it develops a conceptual model that addresses consumer value perceptions of using the Internet versus the traditional (physical) channel. Previous research showed that perceptions of price, product quality, service quality and risk strongly influence perceived value and purchase intentions in the offline and online channel. Perceptions of online and offline buyers can be analyzed to see how value is constructed in both channels. This model enables comparisons between online and offline shoppers perceptions. As such, it is possible to determine the factors that encourage or prevent consumers to engage in online shopping.