Why IT Managers Don\u27t Go for Cyber-Insurance Products

Despite positive expectations, cyber-insurance products have failed to take center stage in the management of IT security risk. Market inexperience, leading to conservatism in pricing cyber-insurance instruments, is often cited as the primary reason for the limited growth of the cyber-insurance market. In contrast, here we provide a demand-side explanation for why cyber-insurance products have not lived up to their initial expectations. We highlight the presence of information asymmetry between customers and providers, showing how it leads to overpricing cyber-insurance contracts and helps explain why cyber insurance might have failed to deliver its promise as a cornerstone of IT security-management programs

Applying bi-random MODM model to navigation coordinated scheduling: a case study of Three Gorges Project

The aim of this paper is to deal with the optimal navigation coordinated scheduling (NCS) problem in ship transportation of the Three Gorges Project in China, i.e. the Three Gorges Dam and the Gezhouba Dam. The NCS includes operational scheduling for two five-step locks in Three Gorges Dam and three single-step locks in Gezhouba Dam. A birandom multiple objective decision-making model is first proposed for the NCS problem to cope with hybrid uncertain environment where twofold randomness exists in practice. Then, particle swarm optimization is applied to search for the optimal solution. Based on real execution data, the results generated by a computer validate effectiveness of the proposed model and algorithm in solving large-scale practical problems is presented

Genomic epidemiology of SARS-CoV-2 in a UK university identifies dynamics of transmission

AbstractUnderstanding SARS-CoV-2 transmission in higher education settings is important to limit spread between students, and into at-risk populations. In this study, we sequenced 482 SARS-CoV-2 isolates from the University of Cambridge from 5 October to 6 December 2020. We perform a detailed phylogenetic comparison with 972 isolates from the surrounding community, complemented with epidemiological and contact tracing data, to determine transmission dynamics. We observe limited viral introductions into the university; the majority of student cases were linked to a single genetic cluster, likely following social gatherings at a venue outside the university. We identify considerable onward transmission associated with student accommodation and courses; this was effectively contained using local infection control measures and following a national lockdown. Transmission clusters were largely segregated within the university or the community. Our study highlights key determinants of SARS-CoV-2 transmission and effective interventions in a higher education setting that will inform public health policy during pandemics.</jats:p

Allocating Spending Between Advertising and Information Technology in Electronic Retailing

This study examines coordination issues that occur in allocating spending between advertising and information technology (IT) in electronic retailing. Electronic retailers run the risk of overspending on advertising to attract customers but underspending on IT, thus resulting in inadequate processing capacity at the firm's website. In this paper, we present a centralized, joint marketing-IT model to optimally allocate spending between advertising and IT, and we discuss an uncoordinated case where marketing and IT make suboptimal advertising and capacity decisions. We show how these decisions can be coordinated either by reducing the value of a customer session or by designing an optimal processing contract between marketing and IT. Both the coordination methods can be implemented with only local knowledge of the IT function, yet they generate a solution that almost matches the quality of the centralized solution. We extend our basic model to consider demand uncertainty, lagged advertising effects, and uncertainties in the lead time to acquire IT capacity. With demand uncertainty, electronic retailers should reduce spending on advertising and increase IT capacity if there is potential for a demand upswing and the cost of IT capacity is relatively low. The value of a customer session should be further reduced when uncertainties exist. This is required to share the risk of excess or inadequate IT capacity.coordination schemes, capacity planning, demand generation, electronic retailing

MEAN-RISK TRADEOFFS IN INDUCTIVE EXPERT SYSTEMS

Notably absent in previous research on inductive expert systems is the study of mean-risk tradeoffs. Such tradeoffs may be significant when there are asymmetries such as unequal classification costs, and uncertainties in classification and information acquisition costs. The objective of this research is to develop models to evaluate mean-risk tradeoffs in value based inductive approaches. We develop a combined mean-risk measure and incorporate it into the Risk Based induction algorithm. The mean-risk measure has desirable theoretical properties (consistency and separability) and is supported by empirical results on decision making under risk. Simulation results using the Risk Based algorithm demonstrate: (i) an order of magnitude performance difference between mean based and risk based algorithms and (ii) an increase in the performance difference between these algorithms as either risk aversion, classification cost uncertainty or classification cost asymmetry increase given modest thresholds of the other two factors. 1