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This study proposes a new methodology to quantify the efficiency dynamics of a port over time. While efficiency evaluation has gained full attention in port management, researchers conducting related studies are challenged by temporal variations observed in the collected data. Existing approaches have almost exclusively relied on multivariate normal distributional assumptions of the input and output data, but empirical evidence from real data shows that the port operations data demonstrate long-tail distributions and violate the distributional assumptions. In addition, many existing models are intractable (non-convex) or lack interpretability. Motivated by these challenges, we develop an optimization-based approach for efficiency measurement under uncertainty that is compatible with the conventional non-parametric method. In particular, inspired by the coherent risk measure, we create a risk-based index to measure the efficiency of any operating unit by comparing its observations against a benchmark that is guaranteed to be production possible under a certain risk level. To facilitate the computation of the index, we develop a risk-based port efficiency evaluation (RPE) model, which can be reformulated as an exponential cone program (ECP) and solved efficiently by off-the-shelf solvers. We test our model for a multipurpose port on a real dataset of 3,394 observations showing the proposed approach's merits. We find that the port productivity peaks on Tuesday and Saturday and troughs on Friday. We also provide evidence for the Chinese New Year effect from a port management perspective and draw managerial insights from the study. • This study provides an analytical tool to quantify port efficiency dynamics over time. • A new approach for efficiency measurement under uncertainty is developed. • The model does not require parametric distributional assumptions. • The model can be formulated as an exponential cone program and solved efficiently. • We provide evidence for the Chinese New Year effect and draw managerial insights. [ABSTRACT FROM AUTHOR]

In this paper we extend the notion of stochastic efficiency and inefficiency in portfolio optimization to the case of incomplete information by means of set-valued probabilities. The notion of set-valued probability models the concept of incomplete information about the underlying probability space and the probability associated with each scenario. Unlike other approaches in literature, our notion of inefficiency is introduced by means of the Monge–Kantorovich metric. We provide some numerical examples to illustrate this approach. [ABSTRACT FROM AUTHOR]

Data envelopment analysis (DEA) is a method for evaluating the performance of a set of homogenous decision-making units (DMUs) with multiple inputs and multiple outputs. There are various models for efficiency calculation in DEA, one of which is based on determining a common set of weights (CSW), which is used extensively by DEA experts. In classical data envelopment analysis, all input and output values are clearly specified. However, this assumption might not always be true in realworld applications. One of the important methods for dealing with imprecise data is to explore the use of stochastic data in DEA. This manuscript extends the CSW model to stochastic inputs and outputs. Next, the stochastic CSW model is transformed into a nonlinear model, and then, the deterministic model is transformed into a quadratic programming model. The efficiency obtained using stochastic data is called stochastic efficiency. Finally, the concept presented in this article is demonstrated through a numerical example involving a number of Iranian banks. [ABSTRACT FROM AUTHOR]

The objective of this study was to assess how payments for ecosystem services could assist plantation forestry's integration into pastoral dairy farming in order to improve environmental outcomes and increase business resilience to both price uncertainty and production limits imposed by environmental policies. Stochastic Dominance (SD) criteria and portfolio analysis, accounting for farmers' risk aversion levels, were used to rank different land-use alternatives and landscapes with different levels of plantation forestry integration. The study was focused on a modal 200-ha dairy farm in the Lake Rotorua Catchment of the Central North Island region of New Zealand, where national environmental policies are being implemented to improve water quality and reduce greenhouse gas emissions. Nitrogen and carbon payments would help farmers improve early cash flows for forestry, provide financial leverage to undertake afforestation projects and contribute to improved environmental outcomes for the catchment. The SD criteria demonstrated that although dairy farming generates the highest returns, plantation forestry with nitrogen and carbon payments would be a preferred alternative for landowners with relatively low risk aversion levels who consider return volatility and environmental limits within their land-use change criteria. Using the confidence premium concept, environmental payments to encourage plantation forestry into the landscape were shown to be lower when the majority of landowners are risk averse. The certainty equivalence approach helped to identify the optimal dairy-forestry portfolio arrangements for landowners of different levels of risk aversion, intensities of dairy farming (status quo and intensified) and nitrogen prices. At low nitrogen prices, risk neutral farmers would choose to afforest less than half of the farm and operate at the maximum nitrogen allowance, because dairy farming at both intensities provides the highest return among the different land uses available. However, at relatively low risk aversion levels, farmers would operate at levels below the maximum nitrogen allowance by including plantation forestry to a greater extent, compared to risk neutral farmers, due to its more certain returns. At a high nitrogen price of $400/kg, plantation forestry would completely subsume dairying, across risk aversion and intensity levels. These results confirm that plantation forestry as well as being an environmentally sound land-use alternative, also reduces uncertainty for landowners that are exposed to volatile international markets for dairy commodities. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to develop an analytical model to value traits at different developmental phases and to determine the value of drought tolerance (DT) in wheat using GM technology. Design/methodology/approach – A stochastic binomial real-options model of GM traits was developed to estimate the value of a DT wheat trait. Findings – The results indicate that the value of DT wheat using GM technology is in-the-money at each development phase. The greatest value would accrue for the Prairie Gateway and Northern Great Plains regions in the USA. Research limitations/implications – The approach is useful for valuing high-cost risky investments in technology and results provide guidance for development strategies. Originality/value – The model is original and its applications to wheat are unique. [ABSTRACT FROM AUTHOR]

Abstract: In economic terms, resilience in farming has to do with the capacity of a farm business to survive various risks and other shocks. Despite its importance, resilience has seldom been directly considered in evaluations of economic sustainability. A whole-farm stochastic simulation model over a 6-year planning horizon was used to analyse organic and conventional cropping systems using a model of a representative farm in Eastern Norway. The relative economic sustainability of alternative systems under changing assumptions about future technology and price regimes was examined in terms of financial survival to the end of the planning period. The same alternatives were also compared in terms of stochastic efficiency. To model the risk of business failure adequately there is a need to deal with the risk of bankruptcy, and a modification of traditional analysis was used for that purpose. The organic farming system was found to be somewhat less economically sustainable than the conventional system, especially if the organic price premiums and the organic area payments were to be phased out. The results illustrate possible conflicts between pursuit of risk efficiency and economic sustainability. The model developed could be used to support farmers’ choices between farming systems as well as to help policy makers develop more sharply targeted policies. [Copyright &y& Elsevier]

This research generated stochastically efficient farm plans in the relevant range of risk aversion and calculated the efficiency measures for the three representative farm sizes in the central Anatolian region of turkey. Utility-efficient programming was used to determine an efficient set of farm plans. Research results showed that total net farm revenue increases for all farm sizes as risk aversion decreases. An economic efficiency score of 0.54 for both small and medium size farms indicated that there is considerable scope for farmers to increase their total net farm revenue using existing technology without additional inputs. Allocative and technical inefficiencies of sampled farms were 0.22 and 0.24, respectively. Thus, supplying complete technical packages for farms may stimulate the adoption of new technologies. Focusing on production practices and marketing efficiency in farmers' training and extension programmes may also help to increase economic efficiency in the research area. [ABSTRACT FROM AUTHOR]