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The implied volatility surface is the collection of volatilities implied by option contracts for different strike prices and time-to-maturity. We study factor models to capture the dynamics of this three-dimensional implied volatility surface. Three model types are considered to examine desirable features for representing the surface and its dynamics: a general dynamic factor model, restricted factor models designed to capture the key features of the surface along the moneyness and maturity dimensions, and in-between spline-based methods. Key findings are that: (i) the restricted and spline-based models are both rejected against the general dynamic factor model, (ii) the factors driving the surface are highly persistent, and (iii) for the restricted models option Δ is preferred over the more often used strike relative to spot price as measure for moneyness.

This paper describes the application of, enhancements to, and use of surface fire spread models in predicting and mitigating fire risk in the Wildland–Urban Interface (WUI). Research and fire management strategies undertaken in the East Bay Hill region (containing the 1991 Tunnel Fire) of the San Francisco Bay area over the past decade are reported. We ascertain that surface fire spread modeling has impacted policy and decision making, resulting in a regional strategic plan where large landowners and public agencies are able to implement fire mitigation practices. Although these practices involve extensive fuel management within a buffer zone between the wildland and residential properties, the residential property owners are still at risk, as no strategy within neighborhoods can be accurately mapped using the current scale of the data and models. WUI fires are eventually extinguished by fire fighters on the ground, up close, and at the backyard scale. We argue that large-scale (backyard scale) mapping and modeling of surface fire spread is necessary to engage the individual homeowner in a fuels management strategy. We describe our ongoing research and strategies, and suggest goals for future research and development in the area of large-scale WUI fire modeling and management.

Purpose – The UK road freight sector is an example of an economically important sector that can be viewed from two different perspectives with regards to climate change: firstly, as a significant contributor to the problem in terms of greenhouse gas emissions, and secondly as a likely recipient of significant impacts (both positive and negative) of any resulting change in climate, especially any increase in extreme weather. It is this relatively neglected second perspective, freight as a vulnerable sector, which is explored.

Methodology/approach – The way in which the freight sector develops in the future will be explored both in terms of the future type of freight operations and potential changes in vehicle technology.

Findings – There is a need to understand how the overlying socio-economic scenario influences the development of the freight sector.

Originality/value – The examination of the impact of climate change on the freight sector is a particularly original aspect of this chapter.

In this chapter, we develop and present the Multi-Perspective Multilevel Model of emotional labor in organizations. This model is based on three perspectives: (1) a service requirement, (2) an intra-psychic process, and (3) an emotional display, each involving five levels of analysis: within-person, between persons, in interpersonal exchanges, in groups, and across the organization as a whole. Our model is differentiated from earlier characterizations of emotional labor in that we propose that the phenomenon begins with energy generation instead of energy depletion; and is neither a one-way nor a one-by-one service episode. We further proffer that the intra-psychic processes embedded in emotional labor represent a form of social self-regulation that impacts across multiple levels within service organizations. We conclude by discussing the implications and limitations of our model for emotional labor research.

Previous research on emotional labor has typically been conducted at the individual level of analysis, despite the fact that many organizations have incorporated work teams into their business model. The use of work teams turns emotional management into a group task on which employees work as a collective. The present chapter proposes a conceptual model that describes the antecedents and consequences of team-level emotional labor. We propose that work groups often impose positive display rules (express integrative emotion) and negative display rules (suppress differentiating emotions) on their members. Positive display rules generally trigger group-level deep acting, whereby teammates seek to change their internal feelings. Negative display rules generally trigger surface acting, whereby teammates retain their actual emotions but do not actually express differentiating feelings. These two dimensions of emotional labor, for their part, impact emotional exhaustion. Deep acting one's positive emotions lowers emotional exhaustion and surface acting increases it. We discuss the consequences of our model for workplace behavior, such as performance. We also discuss how the relationships involving emotional labor change when one considers these constructs at the group-level of analysis.

An interdisciplinary model network consisting of the regional agricultural economic model RAUMIS and the hydro(geo)logical models GROWA/WEKU is used to analyze the effect of different scenarios of maximum agricultural nitrogen balance surplus on water quality. The study area is the federal state of Lower Saxony, Germany, which features heterogeneous natural site conditions as well as agricultural production structures. A focus of the study is the modeling of supra-regional manure transports that, according to the model's results, considerably increase due to a lowering of maximum nitrogen balance surpluses. The assessment of the examined nitrogen reduction measures reveals that adequate indicators have to be applied. In this regard, the model results show that even though the analyzed measure leads to a substantial overall reduction of agricultural nitrogen surpluses, nitrogen discharges into surface and groundwater can regionally increase.

In this chapter it is shown how economic evaluation algorithms of water use can be integrated into a long-term water management model such that surface-water availability and economic evaluation of various levels of water availability to different uses can be modeled simultaneously. This approach makes it possible to include essential features of economic analyses of water use into water resource modeling and thus improves the capability of such models to support decision making in water management. This is especially relevant for the implementation of the Water Framework Directive, which requires economic analyses to be included in the decision process about future water management strategies.

The water management simulation model WBalMo is presented and the integration of economic-evaluation algorithms is demonstrated for the examples of surface-water use for fish farming and for filling open-cast mining pits in order to achieve acceptable water-quality levels in the emerging pit lakes. Results of applying this integrated evaluation approach are shown for different water management scenarios under conditions of global change in the East German Spree and Schwarze Elster river basins, where water scarcity is an urgent issue. Among the lessons which are drawn by the authors one lesson reads that integrating economic evaluation algorithms into a pre-existing model might bring enormous problems. Therefore, such model approaches should be developed together by water engineers and economists in an interdisciplinary endeavor right from the start.

While it is widely recognized that firms in an era of technological ferment exist under conditions of significant uncertainty and ambiguity, little is known about the exact processes through which firms explore their ideas and resolve uncertainty. Arguing that our understanding of the era of ferment is much less developed than other aspects of the technology life cycle, we examine the micro-dynamics of technology-based entrepreneurial firms during this period. We focus on the role of purposeful experimentation as a key form of learning for start-ups firms in the era of ferment. Our approach contrasts with the prevailing view in the literature in which the era of ferment is characterized by extensive experimentation across firms, with each firm representing a single data point in an industry-level experiment. It also extends the learning literature by focusing on start-ups and taking the perspective that learning can encompass purposeful experimentation as well as local search and chaotic adaptation in the era of ferment. Building on the literature on experimental design, we propose a definition and taxonomy of purposeful experimentation. The taxonomy defines the experimental landscape as having three domains – technological, product and business model; and two dimensions – degree of simultaneity and degree of parameter manipulation. We examine this framework using data from a technology-based start-up and find evidence for purposeful experimentation as a key element of the firm’s learning strategy. We also highlight the organizational constraints and challenges that are associated with experimentation. Our findings emphasize the importance of entrepreneurial action, choice and internal experimentation processes.