Land use optimization in watershed scale

Managing a watershed for satisfying the inhabitant's demand is a difficult task if one has to maintain a reasonable balance between usually conflicting environmental flows and demands. The solution to these complex issues requires the use of mathematical techniques to take into account conflicting objectives. Many optimization models exist for general management systems but there is a knowledge gap in linking practical problems with the optimum use of all land resources under conflicting demands in a watershed. In the present study, an optimization problem has been formulated for the Brimvand watershed, Iran, comprising ca. 9572 ha to find out the most suitable land allocation to different land uses, viz. orchard, irrigated farming, dry farming and rangeland targeting soil erosion minimization and benefit maximization.     

MODELLING THE ADAPTATION OF BUSINESS CONTINUITY PLANNING BY BUSINESSES USING NEURAL NETWORKS

Business continuity planning is an important element of business continuity management and is regarded as a fundamental step towards reducing the negative impacts of business disruptions caused by internal and external hazardous events. Many businesses are not prepared for such events, and very few studies have tried to examine and model the factors that contribute to business continuity management planning by various companies. In this paper we propose and develop a feed‐forward neural network for modelling businesses continuity planning by businesses based on a dataset of 283 businesses operating in the Greater Toronto Area in Ontario, Canada. The fully connected neural network applied was trained on 65 % of the dataset records using different subsets of input variables. In order to preserve the generalization ability of the trained network, 15 % of the dataset records were used as a validation set for early stopping during the network's training process. Prediction capability of the trained networks was evaluated on 20 % and never‐seen records of the dataset. The classification ability of the networks was then analysed using receiver operating characteristic and detection error trade‐off curves, where the results obtained were promising. The equal error rate for the best models was 12 %, which reflects a very good accuracy of these models in predicting the existence of business continuity planning for a generic company. Copyright © 2011 John Wiley & Sons, Ltd.     

Estimating the cost of equity for private firms using accounting fundamentals

Finance literature suggests the use of the Accounting Beta (BACC) as a proxy for the Capital Asset Pricing Model (CAPM) market beta to estimate the cost of equity capital when the stock price is not available. Previous researchers have aimed to achieve this objective by determining the correlation between accounting variables and the market beta. However, the magnitude of the resulting error in this correlation has remained unknown. The current study is an attempt to test the performance of the BACC as a proxy measure for the market risk and to examine the extent of the statistical error in the correlation between these two measures. Our findings indicate that BACC overestimates the market beta by between 20% and 50%. Applying some corrective measures, such as operational earnings scaled by equity, may lessen this difference to a range of 22%–25%; however, it does not eliminate the error. Our output also suggests that the BACC might be biased when used to assess the risk of small firms.     

Measurement of Satisfaction with ICT Services Implementation and Innovation in Restaurants (Case Study: Isfahan,Iran)

Nowadays, Restaurant is one of the most important factors in the choice of holiday destinations for tourists and contributes to the development of the local economy. This research is an initial attempt to investigate consumer behavior (tourist behavior) and the attitude of restaurant managers to the application of innovation and information and communication technology (ICT) in hotel restaurants. On the basis of the results of this study it can be concluded that tourists and restaurant managers in the city of Isfahan are interested in exploiting the application of innovation and ICT in hotel restaurants.     

Energy productivity and greenhouse gas emission intensity in Dutch dairy farms: A Hicks–Moorsteen by-production approach under non-convexity and convexity with equivalence results

The agricultural sector is currently confronted with the challenge to reduce greenhouse gas (GHG) emissions, whilst maintaining or increasing production. Energy-saving technologies are often proposed as a partial solution, but the evidence on their ability to reduce GHG emissions remains mixed. Production economics provides methodological tools to analyse the nexus of agricultural production, energy use and GHG emissions. Convexity is predominantly maintained in agricultural production economics, despite various theoretical and empirical reasons to question it. Employing non-convex and convex frontier frameworks, this contribution evaluates energy productivity change (the ratio of aggregate output change to energy use change) and GHG emission intensity change (the ratio of GHG emission change to polluting input change) using Hicks-Moorsteen productivity formulations. We consider GHG emissions as by-products of the production process by using a multi-equation model. Given our empirical specification, non-convex and convex Hicks-Moorsteen indices can coincide under certain circumstances, which leads to a series of theoretical equivalence results. The empirical application focuses on 1,510 observations of Dutch dairy farms for the period of 2010–2019. The results show a positive association between energy productivity change and GHG emission intensity change, which calls into question the potential of on-farm, energy-efficiency-increasing measures to reduce GHG emission intensity.     

MONEY AND INFLATION IN INDIA: EVIDENCE FROM P‐STAR MODEL

This study uses P‐star model to examine the role of money in explaining inflation in India. In particular, we compare the performance of traditional Phillips curve approach against P‐star model in forecasting inflation. Moreover, the study estimates P‐star model using the alternative measures of money such as simple sum and Divisia M3, to examine the relevance of aggregation theoretic monetary aggregates in explaining inflation. The empirical results indicate that P‐star model with real money gap has an edge over traditional Phillips curve approach in forecasting inflation. More importantly, we found that the P‐star model estimated with Divisia real money gap performs better than its simple sum counterpart. These empirical findings suggest that the changes in real money gap play a crucial role in explaining inflation in India.     

The application of proxy methods for estimating the cost of equity for unlisted companies: evidence from listed firms

Review of Quantitative Finance and Accounting - The Campbell and Vuolteenaho (Am Econ Rev 94(5):1249–1275, 2004) two–beta model decomposes the systematic risk in the sensitivity of cash...     

Asymmetric impact of relative price shocks in presence of trend inflation

This study examines whether skewness of cross-sectional distribution of relative price shocks has asymmetric impact on aggregate inflation. The empirical evidence from major economies suggests that the positively skewed shocks have different impact from that of negatively skewed shocks on aggregate inflation. In particular, the empirical results indicate that this asymmetry in the impact of relative price shocks mainly depends on the nature of trend that inflation exhibits for a given period. The crucial inference that emerges from the empirical findings is that the traditional approach of using a simple linear regression model, to examine the relationship between inflation and skewness in presence of trend inflation, is not appropriate as it may lead to misleading conclusions.     

Testing the Olson Hypothesis within the Australian Context

This article seeks to empirically test whether the Olson hypothesis is applicable in the Australian context. Both cointegration and regression analyses which are utilised for this purpose provide strong support for this hypothesis; that is, the existence of a statistically significant negative relationship between import protection and the proportion of manufactured goods exported. More specifically, it is revealed that falling levels of import protection have underpinned an increase in the proportion of manufacturing goods exported and hence assisted in improving the manufacturing sector's export orientation in the period 1980:1–1996:2. A particularly important dimension of the empirical results is the strengthening of this relationship in the more recent years to 1996:2. This phenomenon probably indicates the favourable impact of the accumulated reduction in the protection levels since the early 1970s.