Cost-effectiveness evaluations can be performed from different perspectives, but in general a societal perspec- tive is recommended [4-6]. From this perspective, the time spent on exercise is usually one of the greatest inputs in any intervention to promote physical activity. Guidelines for cost-effectiveness analysis seldom discuss the costs of patients' leisure time, though they often include the time spent on informal care and volunteer time, which both have a number of similarities with patients' leisure time. Different sets of guidelines do not always agree on whether informal care should be included in analyses, but volunteer time should always be identified and included unless deemed to be minimal . Hence, timecosts of exercise should be considered, or at
The survey starts with general questions regarding the travel behavior of the respondent. With these general characteristics, sub models can be estimated for specific trip motives or travel frequencies. These questions are placed at the start of the survey since most of the respondents of the NS panel are familiar with these questions. Therefore, such questions are relatively simple to answer which decreases the burden to start, resulting in a higher response rate. The next set of questions asks the respondent about the latest train trip where BTM is used as access or egress mode, which is considered as an RP observation. The specific mode (bus, tram or metro) and the type of transfer (access or egress) are used in the further questions which are based on this trip. Furthermore, travel time, costs and trip motive are asked, since this is an input for the SP experiment. Because the SP experiment can be quite a burden for respondents, the experiment is placed as soon as possible, thus after the needed attribute values from the recent trip are obtained. Elaborate information on the SP experiment is provided in the next sections.
The observed differences in energy and timecosts be- tween marine and terrestrial foraging should be taken into account when assessing the potential responses of gull populations to environmental change, which in- volves short-term changes in human behavior, such as the European ban on discards, implemented from 2019 onwards , as well as climate change. Since marine foraging is energetically more costly than its terrestrial counterpart, it may be more vulnerable to changes in en- vironmental factors that affect foraging energetics, such as wind conditions. Conversely, the more time demand- ing terrestrial foraging may be more sensitive to factors that affect search, wait and handling times, such as hu- man behavior or environmental conditions that affect the accessibility of food. These factors could be partly responsible for the large unexplained variation in time and energy costs within habitats reported here, both at the daily scale and over the full chick rearing period. In this context, characterizing individual responses to day- to-day environmental variability may help further eluci- date the sources of variation in parental energy and time investment during chick rearing.
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Since the pioneering work of McFadden (1974), a large number of studies on the choice of travel mode have appeared in the transport economics literature. According to these studies, time and monetary costs are the structural com- ponents of the travel mode choice, although other components (convenience and so on) certainly have a strong inﬂuence. One ﬁnding of this travel mode literature is that income is among the relevant explanatory variables deter- mining mode choice (Train, 1980; Kitamura, 1989; Jara Diaz and Videla, 1989; Dargay and Hanly, 2004). 1 Low-income travellers apparently choose a lower speed level to economise on monetary costs (Jara Diaz and Videla, 1989). 2 The implication is that the value of time depends positively on income (Wardman, 2001) and that the chosen speed level depends positively on income. One aim of this paper is to model this relationship more explicitly. In another strand of transport economics literature, the focus is on the cost of transport for the user as an element in the determination of demand (Quinet and Vickerman, 2004). For example, Littman (1999) shows in an analysis of automobile costs in a Canadian urban context, that the timecosts are about twice the variable monetary vehicle costs. The current study also contributes to this literature, by showing that information on the travellers’ time and monetary costs can be derived given observations of their chosen speed level and income.
In addition to these new-equipment life-cycle costs, it is possible explore other “what if?” spreadsheet scenarios representing a range of choices. These might include buy- ing the lowest cost versus a midrange and a top-of-the- line model, or a quality used one. It is also possible to weight the purchase decision in relation to projected needs and demands. Buying a cheaper model may show up negatively in lost productivity over the long run, as well as in higher repair costs and in shorter equipment life. “It’s unwise to pay too much,” Barringer observes, “and it’s foolish to pay too little.” (Hawkins, 2002)
The literature on bankruptcy design highlights two important goals for the bankruptcy procedure (see e.g. White, 1989, or Aghion, Hart and Moore, 1992): (i) to preserve the bonding role of debt, and (ii) to filter out the economically sound firms that deserve to be reorganized (whereas the economically unsound firms should be liquidated). Accordingly, we can assess the quality of a bankruptcy procedure along three dimensions: (i) its ability to maintain the same priority among claimholders before and after reorganization (cf. the bonding role of debt), (ii) its ability to reorganize firms with high going concern value, and (iii) the costs incurred to pursue these two goals.
The second step to estimate the Heckman model is to add the transport costs associated with these zero-value observations. This requires making two assumptions. The first assumption is related to the port of shipment. Since we do not observe the export, we do not know from which port the output would have been shipped out of the country. This implies that we do not have a route in order to assign a transport cost. To address this issue we make the conservative assumption that the good would have been shipped from the municipality of origin to the port in the country that gives the cheapest route. The second assumption has to do with the weight-to-value ratio employed in the calculation of the ad valorem transport costs (see equation 5). Since we do not observe the export value or its weight, we do not have the second term in equation 5 which is necessary to estimate the ad valorem transport costs. However, weight-to-value ratios are mainly determined by factors not necessarily associated with location: the weight is an intrinsic characteristic of the commodity and its export value is, for the most part, determined by international prices. Therefore, the weight-to-value ratio used in the calculation of the ad valorem transport costs for any good produced and not exported is the average weight-to-value ratio of all the exports of that good with positive values. For the cases in which the good was never exported, the weight-to-value ratio is the average weight-to-value ratio of the exports of the immediate more aggregated level of classification (1 digit less). 7
This chapter investigated a number of approaches to solving the Bulk Port Cargo Throughput Optimisation Problem (BPCTOP) introduced in Chapter 3, including several user-defined search strategies for the CP solver, a comparison against a new MIP model and MIP solver, a number of improvements to the CP model that took into account CP solver implementation details, and finally a Benders decomposition approach. While not all approaches were effective at solving the problem quickly, some approaches were found that significantly improved calculation time, and al- lowed problems with 9 ships sailing on one high tide to be solved within 5 minutes – this is 50% more than the current record of 6 ships sailing on one high tide at Port Hedland, the world’s largest bulk export port [Port Hedland Port Authority, 2013d]. The results in this chapter showed that the choice of solver, model and search strategy all significantly influenced the solution time for this problem, and more importantly, that the interaction between these three factors also had a significant effect. Some approaches to modelling the problem resulted in problem instances being solved faster due to aspects of the model being implemented more efficiently in the solver, and some variations to the model also changed which search strategy was more effective. Similar results are observed for another CP model for a different maritime transportation problem discussed in Chapter 7, so the more general result of this chapter is that the choice of model, solver, and search strategy needs to be considered as an interacting system, rather than in isolation.
Each decision taken by any department is assumed to cause two dierent types of costs. The rst cost term represents those costs that originate from implementing the chosen decision while, on the other hand, there are some opportunity costs that arise from the dierence between the actually chosen output and the theoretical optimal output with respect to the input.
in order to generate large savings, the management of an enterprise should analyse and compare on a continuous basis the real costs with assumed costs or the implementation of the plan. The presented re- sults of empirical studies prove that the costs of the logistic infrastructure form a significant part of the general costs, which can be reduced through a proper management. consequently, as far as the creation of the competitive edge is concerned, it is important to identify and control these costs precisely in the struc- ture of the enterprise operation costs. There are many possibilities to generate better results arising from the decision-making process. The management should choose between the alternatives such as: rental of the storage area or the construction of its own warehouses, hiring of the additional transport or the expansion of its own transport base, an increase of deliveries or goods, or the automation of the order and information processing system. in order to make such decisions, it is necessary to have the information concerning the segments such as sellers, recipients, products, territory, distribution channels. The currently existing integrated management systems make it possible to receive the information quickly and to perform detailed analyses and evaluations of the enterprise’s operations, and the obtained results make it possible to use alternative solutions in the management process.
mented individuals with cognitive problems that have been studied differ in their range of impairment. We use the term “preclinical” to refer to individuals who do not yet meet clinical criteria for probable AD. These individuals clearly have clinical expression of AD, even though they are not demented. In our recent MRI study, there were 21 such “questionable” subjects who subsequently progressed to overt dementia. We used the Sum of Boxes from the CDR scale to quantify their degree of functional difficulty at baseline. Of the 21 questionable subjects (mean Sum of Boxes ⫽ 1.8), one had a Sum of Boxes of 3.0, while all others had a Sum of Boxes of 2.5 or lower. None had a box score of 3.5 or higher. Thus, our evaluation of these individ- uals indicated that they were not demented at the time the baseline MRI scans were obtained. Clearly, it will be important for groups studying such individuals to reach a consensus on terminology and methodology in order to facilitate examination of individuals with prodromal AD.
The price of electricity in the United States depends on the marginal costs of generating the electricity . Two factors are considered when calculating the total price of electricity. For a consumer one factor is power (1kW = 1000 s J ) which is the rate of using electricity per time unit, also called demand. The other factor is total energy used (1kWh = 3,600J). For most residential customers, the consumption charge and demand charge are considered in a single rate, charged per kWh . This is because there is little variation in the demand (kW) used from home to home. However, for industrial and commercial users, power requirements can vary greatly within a day and across customers. Since electricity cannot be stored and must be generated and supplied to each customer instantly, meeting these customer requirements calls for a vast array of expensive equipment and resources. To account for the cost of this equipment and resources, utilities have determined that customers who require large instantaneous power (kW) requirements must pay for its availability . An example depicting the difference between the demand charge or peak load (kW) and the total energy consumption (kWh) is shown in Figure 1. The area under the curve represents the total energy consumption in kWh, while the highest instantaneous demand (demand charge), or 8 kW represents the peak load. However, according to the U.S Department of Energy , utility companies do not use the value of the instantaneous peak load to calculate the demand charge, instead they use a rolling window of fifteen to sixty minutes where the maximum average demand is the average power (kW) over a period of time specified by the rolling interval. The maximum average demand after scanning over an entire month is used to calculate the demand charge .
The EuroQol EQ-5D measure of HRQoL did not improve over the trial time-period in either of the trial arms and no statistically significant difference in decrement was evi- denced. For men within this age range in a prostate cancer post-treatment care pathway, it is not surprising that adjust- ments to their lifestyle impact negatively on their HRQoL. That a significant difference in decrement was not evidenced is most likely a function of the small sample size and so should be interpreted with caution. However, the cohort receiving the NLPI yielded a smaller reduction in mean utility over the time-period of the trial, i.e., approximately 32% lower utility decrement than the UCA group. This could suggest that the intervention is acting as a support, diminishing some of the overall impact of treatment and side effects on HRQoL. There is also evidence building across the literature, which suggests the EQ-5D instrument may not be sensitive enough to pick up changes in HRQoL for men with prostate cancer given the average age range of diagnosis (26, 27). Hence the EQ-5D VAS scores may be more applicable to this analysis, which, when utilised, highlighted cost effectiveness.
Once the machine is commissioned, the same AFBs can be used to monitor the current measurement results with integrated power meters (Energy Dashboard). You no longer have to “fl y blind” when it comes to monitoring your energy consumption: This tool gives your engineering team a powerful energy effi ciency tool in the design phase. For machine operators, this feature makes it possible to read off the HMI the energy expenditure for each product packaged at any time, and optimize the system based upon this information.
Considerable intellectual power has already been brought to bear on these issues. In the United Kingdom, these include a Royal Commission on Long Term Care for the Elderly (Department of Health 1999) and the response to this report within the National Health Service Plan (Department of Health 2000). These two documents provide a useful anchor point for the data reported here. One of the Royal Commission’s recommendations was that the government should ascertain precisely how much money is spent on supporting people in their own homes and in residential care. The government’s response to this recommendation is that there is a need to ‘ get the right incentives in the system to promote older people’s independence and to provide care closer to home ’, and that, in this regard, the promotion of ‘ intermediate care ’ is seen as a positive step (Department of Health 2000). Clearly, the calculation of precise costs for all support for older people would be a gargantuan task. However, with- out such information, it is impossible to estimate the cost eﬀectiveness of intermediate care or any alternative provision.
Delivering programmes to standard personal com- puters through the internet would reduce the cost per session from about £177 to £5 (excluding the cost of software). This assumes equipment costs of £1500 over three years, with a fairly low utilisation rate (two users per weekday) and lower space and staff costs commen- surate with a less dedicated technology. Thus this type of interactive decision aid, which provides a realistic and practical solution to the problem of achieving informed patient choice at low cost, could easily be incorporated into multiple access points for infor- mation such as those envisaged for NHS Direct Online. Our trial was not designed to determine the extent to which patients would seek out and use a decision aid if they were not referred to it; however the rapid rise in numbers of visitors to health information sites on the internet 25 confirms previous evidence on the wide-