ABSTRACTIn current perspective, farmers’ participatory behavior toward conservation of water resources (FPBCWR) is one of the most important strategies under water resource management in rural Iran. In this regard, understanding the predictors of farmers’ participatory-based water conservation behaviors and attitudes is gaining more importance than earlier. Among different dimensions of farmers’ participatory behavior, the potential of temporal frames was examined rarely. Thus, 322 Iranian farmers were investigated to examine the potential of their time perspectives in predicting their participatory-based water conservation behavior and attitude. According to the study results, the effects of present orientation on attitude and behavior were negatively significant, while the effects of future orientation on attitude and behavior were positively significant, whereas its effects (path coefficients) were stronger than present orientation effects. Past orientation did not have a significant effect on attitude, though attitude positively and significantly affected farmers’ participatory behavior. The results of causal analysis revealed that presented model accounted for 58% of variance in farmers’ ‘behavior’ and 42% of variance in “attitude.” In conclusion, a few demonstrable illustrations of policy implications are presented to enable utilizing the important findings and concluding results of this study that is linked further with water resource management domain. 相似文献
Partnerships like the delegated management model (DMM), in which a utility delegates management of infrastructure and service delivery to slum residents, are being promoted to improve services to the urban slums in sub‐Saharan Africa. However, there is little empirical evidence of the benefits that DMM offers beneficiaries and its potential limitations. This study, conducted in 2013, compared water service in two slums in the city of Kisumu in Kenya where DMM has been implemented with another where it has not been implemented. Results showed that DMM had lowered the cost of water compared to water kiosks in neighbourhoods in which DMM had not been implemented. The study findings contribute toward an evidence base for stakeholders and regulators who see an opportunity in the integration of DMM into local drinking water provision solutions in urban slums. 相似文献
Multi-criteria inventory classification groups inventory items into classes, each of which is managed by a specific re-order policy according to its priority. However, the tasks of inventory classification and control are not carried out jointly if the classification criteria and the classification approach are not robustly established from an inventory-cost perspective. Exhaustive simulations at the single item level of the inventory system would directly solve this issue by searching for the best re-order policy per item, thus achieving the subsequent optimal classification without resorting to any multi-criteria classification method. However, this would be very time-consuming in real settings, where a large number of items need to be managed simultaneously.
In this article, a reduction in simulation effort is achieved by extracting from the population of items a sample on which to perform an exhaustive search of best re-order policies per item; the lowest cost classification of in-sample items is, therefore, achieved. Then, in line with the increasing need for ICT tools in the production management of Industry 4.0 systems, supervised classifiers from the machine learning research field (i.e. support vector machines with a Gaussian kernel and deep neural networks) are trained on these in-sample items to learn to classify the out-of-sample items solely based on the values they show on the features (i.e. classification criteria). The inventory system adopted here is suitable for intermittent demands, but it may also suit non-intermittent demands, thus providing great flexibility. The experimental analysis of two large datasets showed an excellent accuracy, which suggests that machine learning classifiers could be implemented in advanced inventory classification systems. 相似文献
This research provided background for surveys and interviews in later stages of a 3 part project. It aimed to identify, from secondary research, sociodemographic characteristics which tend to support registered clubs and their machine gaming activities in the Sydney Statistical Division. Using multiple methods including Pearson's Product Moment correlation, Principal Components factor analysis, and stepwise regression, the study profiled Sydney populations which spend highly on gaming machines. The most important sociodemographic predictors of Sydney statistical local areas where per capita gaming machine expenditure is high are large proportions of the adult resident population who were born in Malta, Greece, Lebanon, China, Italy, Vietnam, Yugoslavia, India or the Philippines; have no vocational or tertiary qualifications; or are unemployed. 相似文献