Computer Simulation as a Tool for Planning and Management of Visitor Use in Protected Natural Areas

The United Nations Environment Programme’s Principles on Implementation of Sustainable Tourism suggest that implementing sustainable tourism must include monitoring visitor use of protected natural areas and directing it to areas where the environmental and social impacts of tourism are minimised. Thus, sustainable tourism management requires information about the spatial and temporal flow of visitor use in protected natural areas to help identify potential tourism-related threats to the natural and cultural resources of an area and the quality of visitors’ experiences. Recent research has identified at least four ways in which simulation modelling of visitor use can facilitate more informed planning and management of sustainable tourism in protected natural areas, including (1) describing existing visitor use flows; (2) monitoring the condition of ‘hard to measure’ indicator variables; (3) testing the effectiveness of alternative visitor use management practices; and (4) guiding the design of research on public attitudes. The purpose of this paper is to demonstrate, using findings from studies conducted in the Inyo National Forest and Isle Royale National Park, USA, each of these four potential contributions of computer simulation to sustainable tourism management and planning. The paper concludes with an assessment of the limitations of existing applications of computer simulation to nature-based tourism and recommendations for future research.     

Forecasting China's Monthly Inbound Travel Demand

Summary

China is currently expecting a growth in inbound travel demand as the result of China's “open door policy,” participation in World Trade Organization (WTO), success in hosting the Olympics in Beijing in the year 2008 and political stability. This paper focused on two issues: (1) forecasting China's monthly inbound travel demand and (2) seasonally and seasonal ARIMA model selection for monthly tourism time-series. In this paper following seasonal ARIMA models were considered: the seasonal ARIMA model with first differences and 11 seasonal dummy variables, the conventional seasonal ARIMA model with first and the fourth differences. In order to select the best forecasting model, finally both seasonal ARIMA models were compared with the AR model with fourth differences, the basic structural model (BSM) and the naive “No Change” model. In the one-step ahead forecasting comparison, the conventional seasonal ARIMA model with first and the fourth differences becomes the best forecasting model for both inbound foreign visitor demand and total visitor demand. This may be due to the nature of monthly seasonal variations in visitor arrivals, which is less marked. Our forecasts indicate that China foreign visitor arrivals and total visitor arrivals are expected to grow by 14% and 27% respectively from 2002 to 2005.     

Wildlife viewing: The impact of money-back guarantees

Wildlife sightings are not always guaranteed. To address this risk, tour operators often offer a money-back guarantee as a refund mechanism. However, studies have overlooked the influences of such refund mechanisms on tourists' tour participation decisions and tourism revenue. We conducted choice experiments to examine the impact of such mechanisms using a case of Amami rabbit tourism in Japan. We found that the guarantee significantly influences the tourists’ decision-making and tour revenue. In particular, we found that the expected tourist participation rate and tour guide revenue vary drastically depending on the probability of the rabbit encounter. The maximum expected revenue from the tour with a 90% chance was about 20 times larger than that with a 10% chance. This indicates that conserving wildlife to maintain the sighting probability raises tour benefits, creating a win-win situation by balancing conservation and tourism development.     

建筑业常见事故防范

建筑业的劳动条件和作业环境比其他行业艰苦恶劣,从事建筑业的工作人员的劳动强度大,在工作中要面对众多危险因素。文章对建筑业典型事故案例进行研究分析,希望能帮助从事建筑业的人员牢固地树立安全生产意识,并掌握、防范事故的方法和措施,做好本岗位的安全生产工作。     

Measuring the impact of the approach to migration in the quality of web service interfaces

There is a good consensus on the strategic value of service-oriented architecture (SOA) as a way of structuring systems, and a common trend is to migrate legacy applications that use outdated technologies and architectures to SOA. We study the effects in the resulting Web Service interfaces of applying two traditional migration approaches combined with common ways of building services, namely, direct migration with code-first and indirect migration with contract-first. The migrated system was a 35-year-old COBOL system of a government agency that serves several millions of users. In addition, we provide a deep explanation of the trade-offs involved in following either combinations. Results confirm that the ‘fast and cheap’ approach to move into SOA, which is commonplace in the industry, may deliver poor service interfaces, and interface quality is also subject to the tools supporting the migration process.     

油田井下作业事故分析及应对措施探讨

石油行业是我国工业发展的命脉,能够为国家创造更高的经济价值。但是,这个行业也同样伴随着较高的安全风险。石油井下作业过程往往复杂多变,具有极高的危险性。本文首先列举了石油井下作业事故的类型,接着详细分析了安全事故的发生原因,最后针对发现的问题,提出了相应的应对措施,希望可以对油田井下作业安全防治问题有所帮助。     

Interest rates,inflation, and the Fisher effect in China

The paper estimates the relationship between the nominal Treasuries rate and inflation in China. The dynamic econometric analysis yields a preferred, automatically reduced, empirical model revealing a Fisher effect. But the results are sensitive to using different sub-samples encompassed in the decade-and-a-half period following the disassociation of Treasuries from the People’s Bank of China administered interest rates at the end of the 1990s.     

Spatial statistical modelling of insurance risk: a spatial epidemiological approach to car insurance

Spatial models, such as the Besag, York and Mollie (BYM) model, have long been used in epidemiology and disease mapping. A common research question in these subjects is modelling the number of disease events per region; here the BYM models provides a holistic framework for both covariates and dependencies between regions. We use these tools to assess the relative insurance risk associated with the policyholders geographical location. A Bayesian modelling approach is presented and an elastic net is used to reduce the large number of possible geographic covariates. The final inference is performed using Integrated Nested Laplace Approximation. The model is applied to car insurance data from If P&C Insurance together with spatially referenced covariate data of high resolution, provided by Insightone. The entire analysis is performed using freely available R-packages. Including spatial dependence when modelling the number of claims significantly improves on the result obtained using ordinary generalised linear models. However, the support for adding a spatial component to the model for claims cost is weaker.     

Dependence calibration and portfolio fit with factor-based subordinators

The paper explores the properties of a class of multivariate Lévy processes used for asset returns. We focus on describing both linear and non-linear dependence in an economic sensible and empirically appropriate way. The processes are subordinated Brownian motions. The subordinator has a common and an idiosyncratic component, to reflect the properties of trade, which it represents. A calibration to a portfolio of 10 US stock indices returns over the period 2009–2013 shows that the hyperbolic specification has a very good fit to marginal distributions, to the overall correlation matrix and to the return distribution of both long-only and long-short random portfolios, which also incorporate non-linear dependence. Their tail behaviour is also well captured by the variance gamma specification. The main message is not only the goodness of fit, but also the flexibility in capturing dependence and the ease of calibration on large sets of returns.     

Using Forecasting Criteria to Identify Value Relevance in the Relationship Between Accounting Numbers and Market Value

We explain and demonstrate a disciplined and systematic approach to repeatable modelling using forecast criteria, in addition to the usual statistical estimation criteria, to identify value relevance in regressions of the market‐accounting relation. The method was used in Cooke et al. ( 2009 ). It is illustrated here in the case of a single firm over a 59‐year period. Market and accounting data for the U.S. firm Abbott Laboratories Inc. from 1955 are modelled using a testing‐down, error correction approach. Hold‐out samples of 10 to 15 years are used to assess forecasting performance relative to a random walk. Emphasis is placed upon the use of simple, directly observable and theory‐independent model variables that can be replicated with other sample data. In this case, logarithmic transformations of all variables have to be computed in order to achieve correct statistical specification, implying a multiplicative relationship in the raw data. The strongest cointegrating accounting variable with forecasting ability for Abbott's market value is earnings. The model parameters exhibit long‐run stability and the accounting regressor marginally improves forecasts of market value compared to a random walk, demonstrating ‘value relevance’.