The Effects of Uncertainty Risks on Consumption of Migrant Workers under the Economic New Normal

Based on the precautionary theory,this paper established a framework for consumption of migrant workers from the perspective of the uncertainty risk,and analyzed the effects of uncertain income risk on consumption of migrant workers using the quantile regression method.Results indicated that the income uncertainty significantly inhibits the consumption of migrant workers. The lower the consumption level or the lower the income level,the stronger the inhibitory effect will be. Uncertainty of expenditure also has a significant inhibitory effect on the consumption of migrant workers. Promoting urbanization of migrant workers and accelerating the reform of the household registration system can reduce the uncertainty risks faced by migrant workers,so as to raise the consumption expectation of migrant workers,release the consumption potential of migrant workers,and improve the living standards of migrant workers.

Risks and Uncertainty Analysis on International Logistics

With the development of globalization, more and more companies are under global operation. What coming with it, on one hand is chance and opportunity; on the other hand is risk and uncertainty. This paper aims to specify the potential and current risks and uncertainty that may be met in international logistics, then seeks some practical methods to dodge and solve them.

Optimal Decision-Making of Trans-Provincial Electricity Market Subjects with Risks under Renewable Portfolio Standards

The randomness and uncertainty of renewable energy generation are expected to significantly change the optimal decision-making of trans-provincial electricity market subjects.Therefore,it is beneficial to optimize the interests of each of these subjects,considering the unpredictable risks of renewable energy under the renewable portfolio standards(RPS)and researching their effects on the optimal decision-making of transprovincial electricity market multi-subjects.First,we develop a trans-provincial trading market mechanism for renewable energy and clarify the electricity supply and demand relation and the green certificates supply and demand relation of trans-provincial electricitymarketmulti-subjects.Then,under the RPS,we construct a multi-subject game model of the power supply chain that recognizes the risks,and adopt the reverse induction method to discuss the optimum risk-taking judgment of each subject in the trans-provincial electricity market.Finally,we useMATLAB to verify the viability and efficacy of the proposed gamemodel,and obtain a certain reference value for the optimal decision-making of trans-provincial electricity market subjects.In summary,we consider the uncertainty risks of renewable energy under RPS,study the effects of the green certificate price and risk aversion coefficient in the RPS mechanism on the optimal decisionmaking of trans-provincial electricity market subjects,and obtain the changing trends of two different power products and those of different electricity market subjects under the influence of the green certificate price and risk aversion coefficient,which have a certain reference value for studying the factors affecting the optimal decision-making of trans-provincial electricity market subjects.

Quantification and assessment of fault uncertainty and risk using stochastic conditional simulations

The effect of geological uncertainty on the development and mining of underground coal deposits is a key issue for longwall mining, as the presence of faults generates substantial monetary losses. This paper develops a method for the conditional simulation of fault systems and uses the method to quantify and assess fault uncertainty. The method is based on the statistical modelling of fault attributes and the simulation of the locations of the centres of the fault traces. Fault locations are generated from the thinning of a Poisson process using a spatially correlated probability field. The proposed algorithm for simulating fault traces takes into account soft data such as geological interpretations and geomechanical data. The simulations generate realisations of fault populations that reproduce observed faults, honour the statistics of the fault attributes, and respect the constraints of soft data, providing the means to thereby model and assess the related fault uncertainty.

Geological uncertainty and risk:implications for the viability of mining projects

Computerized geological models are the basis of modern mine design,planning and production.A sound,validated geological model is essential to the success of a min- ing project.However,due to the complexity of geology surrounding deposits,geological models inherit uncertainty,or error.This geological uncertainty may significantly affect the risk profile of a mining project during its design and operational phases.Methodologies for quantifying geological uncertainty and risk have been developed by CRC Mining and the University of Queensland,Australia and successfully applied to case studies.This paper discussed the implications of geological uncertainty and risk to a coal mining project,and presents advances for quantifying geological/geotechnical uncertainty and risk.A case study is presented to demonstrate the application of the technology developed.

A newfangled study using risk silhouette and uncertainty approximation for quantification of acyclovir in diverse formulation

Risk assessment and uncertainty approximation are two major and important parameters that need to be adopted for the development of pharmaceutical process to ensure reliable results.Additionally,there is a need to switch from the traditional method validation checklist to provide a high level of assurance of method reliability to measure quality attribute of a drug product.In the present work,evaluation of risk profile,combined standard uncertainty and expanded uncertainty in the analysis of acyclovir were studied.Uncertainty was calculated using cause-effect approach,and to make it more accurately applicable a method was validated in our laboratory as per the ICH guidelines.While assessing the results of validation,the calibration model was justified by the lack of fit and Levene＇s test.Risk profile represents the future applications of this method.In uncertainty the major contribution is due to sample concentration and mass.This work demonstrates the application of theoretical concepts of calibration model tests,relative bias,risk profile and uncertainty in routine methods used for analysis in pharmaceutical field.

Higher-order dynamic effects of uncertainty risk under thick-tailed stochastic volatility

Sudden and uncertain events often cause cross-contagion of risk among various sectors of the macroeconomy.This paper introduces the stochastic volatility shock that follows a thick-tailed Student’s t-distribution into a high-order approximate dynamic stochastic general equilibrium(DSGE)model with Epstein–Zin preference to better analyze the dynamic effect of uncertainty risk on macroeconomics.Then,the high-dimensional DSGE model(DSGE-SV-t)is developed to examine the impact of uncertainty risk on the transmission mechanism among macroeconomic sectors.The empirical research found that uncertainty risk generates heterogeneous impacts on macroeconomic dynamics under different inflation levels and economic states.Among them,a technological shock has the strongest impact on employment and consumption channels.The crowding-out effect of a fiscal policy stimulus on consumption and private investments is relatively weakened when considering uncertainty risk but is more pronounced during periods of high inflation.Uncertainty risk can partly explain the decline in investments and the increase in interest rates and employment rates,given the impact of an agent’s risk preferences.Compared with external economic conditions,the inflation factor has a stronger impact on the macro transmission mechanism caused by uncertainty risk.

Competence Set Analysis Under Risk and Uncertainty

The competence set analysis technology can be applied to solve the decision making problems successfully and satisfactorily. This paper mainly focuses on the expanding strategy research and development of the competence set under risk and uncertainty. A systematic expression of the competence set analysis is described, several expanding principles and strategies with regard to several different cases are presented, and their applications in the personnel training program are discussed, some conclusions and suggestions to be developed in a further work are included.

Managing project risks and uncertainties

This article considers threats to a project slipping on budget,schedule and fit-for-purpose.Threat is used here as the collective for risks（quantifiable bad things that can happen）and uncertainties（poorly or not quantifiable bad possible events）.Based on experience with projects in developing countries this review considers that（a）project slippage is due to uncertainties rather than risks,（b）while eventuation of some bad things is beyond control,managed execution and oversight are stil the primary means to keeping within budget,on time and fit-for-purpose,（c）improving project delivery is less about bigger and more complex and more about coordinated focus,effectiveness and developing thought-out heuristics,and（d）projects take longer and cost more partly because threat identification is inaccurate,the scope of identified threats is too narrow,and the threat assessment product is not integrated into overall project decision-making and execution.Almost by definition,what is poorly known is likely to cause problems.Yet it is not just the unquantifiability and intangibility of uncertainties causing project slippage,but that they are insufficiently taken into account in project planning and execution that cause budget and time overruns.Improving project performance requires purpose-driven and managed deployment of scarce seasoned professionals.This can be aided with independent oversight by deeply experienced panelists who contribute technical insights and can potentially show that diligence is seen to be done.

Fuzzy logic applied to value of information assessment in oil and gas projects

The concept of value of information(VOI)has been widely used in the oil industry when making decisions on the acquisition of new data sets for the development and operation of oil fields.The classical approach to VOI assumes that the outcome of the data acquisition process produces crisp values,which are uniquely mapped onto one of the deterministic reservoir models representing the subsurface variability.However,subsurface reservoir data are not always crisp;it can also be fuzzy and may correspond to various reservoir models to different degrees.The classical approach to VOI may not,therefore,lead to the best decision with regard to the need to acquire new data.Fuzzy logic,introduced in the 1960 s as an alternative to the classical logic,is able to manage the uncertainty associated with the fuzziness of the data.In this paper,both classical and fuzzy theoretical formulations for VOI are developed and contrasted using inherently vague data.A case study,which is consistent with the future development of an oil reservoir,is used to compare the application of both approaches to the estimation of VOI.The results of the VOI process show that when the fuzzy nature of the data is included in the assessment,the value of the data decreases.In this case study,the results of the assessment using crisp data and fuzzy data change the decision from"acquire"the additional data(in the former)to"do not acquire"the additional data(in the latter).In general,different decisions are reached,depending on whether the fuzzy nature of the data is considered during the evaluation.The implications of these results are significant in a domain such as the oil and gas industry(where investments are huge).This work strongly suggests the need to define the data as crisp or fuzzy for use in VOI,prior to implementing the assessment to select and define the right approach.

Risk Assessment Based on Fault Tree Analysis for Damaged Pipe Repair During Operation in Petrochemical Plant

In petrochemical plant, the in-operation repairing is usually a repairing strategy with pressured inoperation repairing for avoiding huge economic losses caused by unplanned shutdown when some slight local leakage happens in pipes. This paper studies the effects of repairing strategies on the failure probability of the pipe systems in process industries based on the time-average fault tree approach, especially the in-operation repairing strategies including pressured in-operation repairing activities. The fault tree model can predict the effect of different repairing plans on the pipe failure probability, which is significant to the optimization of the repairing plans. At first pipes are distinguished into four states in this model, i.e., successive state, flaw state, leakage state and failure state. Then the fault tree approach, which is usually applied in the studies of dynamic equipment, is adopted to model the pipe failure. Moreover, the effect of pressured in-operation repairing is also considered in the model. In addition, this paper proposes a series of time-average parameters of the fault tree model, all of which are used to calculate node parameters of the fault tree model. At last, a practical case is calculated based on the fault tree model in a repairing activity of pipe thinning.

Handling epistemic uncertainties in PRA using evidential networks

In order to overcome the limitations of traditional methods in uncertainty analysis, a modified Bayesian network(BN), which is called evidence network(EN), was proposed with evidence theory to handle epistemic uncertainty in probabilistic risk assessment(PRA). Fault trees(FTs) and event trees(ETs) were transformed into an EN which is used as a uniform framework to represent accident scenarios. Epistemic uncertainties of basic events in PRA were presented in evidence theory form and propagated through the network. A case study of a highway tunnel risk analysis was discussed to demonstrate the proposed approach. Frequencies of end states are obtained and expressed by belief and plausibility measures. The proposed approach addresses the uncertainties in experts' knowledge and can be easily applied to uncertainty analysis of FTs/ETs that have dependent events.

LIVESTOCK PRODUCTION PLANNING UNDER ENVIRONMENTAL RISKS AND UNCERTAINTIES

In this paper we demonstrate the need for risk-adjusted approaches to planning expansion of livestock production. In particular, we illustrate that under exposure to risk, a portfolio of producers is needed where more efficient producers co-exist and cooperate with less efficient ones given that the latter are associated with lower, uncorre, lated or even negatively correlated contingencies. This raises important issues of cooperation and risk sharing among diverse producers. For large-scale practical allocation problems when information on the contingencies may be disperse, not analytically tractable, or be available on aggregate levels, we propose a downscaling procedure based on behavioral principles utilizing spatial risk preference structure, It allows for estimation of production allocation at required resolutions accounting for location specific risks and suitability constraints. The approach provides a tool for harmonization of data from various spatial levels. We applied the method in a case study of livestock production allocation in China to 2030.

Explaining farmers’reluctance to adopt recommendations for sustainable ecosystem management

Introduction:The lower Syr Darya River Basin is an integral part of the Aral Sea Basin that is shared by four riparian countries.In Kazakhstan,the water is mainly used for agricultural purposes.However,the poor quality and insufficient quantity of water and the overall degradation of natural resources due to unsustainable management practices threaten the profitability of the sector.The situation is even worse for downstream users.Three alternative scenarios for sustainable water and land management were developed using the RIOS and SWAT models as decision support tools.The scenario that offered the highest water and land productivity was presented to farmers to assess their willingness to forgo their current practices and adopt proposed management practices.We introduce willingness to forego(WTF)—a qualitative approach and a variant of the concept of opportunity costs to look beyond hypothetical markets to trading current benefits for future returns.We also tap into literature on agricultural risk management to provide additional insight into farmers’rationale behind their choices.Result:Generally,despite their stated preference to conserve ecosystem services,farmers’actions were found to be inconsistent with the proposed sustainable management.WTF analysis revealed that farmers’desire to maximize current benefits and more importantly to minimize future risks override all sustainability considerations.Their WTF current benefits mainly depended on their location along the canal and hence their access to water and land,overall cost of production,market conditions that informed their crop choices,and the cost of adopting recommended packages.While the results remain specific to this case,they are consistent with the literature that links farmers’behaviors to ecological performances.Conclusions:The study highlights the limitations of decision support tools and other valuation approaches including willingness to pay(WTP)and willingness to accept(payment)(WTA),to capture the delicate trade-offs that need to be considered to ensure household food and income security and encourage adoption of sustainable ecosystem management practices.Adequate information on potential effects of proposed conservation measures on yield,markets and hence farm profits,and availability of other alternatives are critical in shaping farmers’decisions.