The objectives of this study are to quantify the extent to which domestic transportcosts act as a friction for the international trade of goods and to examine how improvements in road quality impact trade performance. We employ a methodology that combines real freight costs and Geographic Information System (GIS) analysis to obtain a realistic measure of the domestic transportcosts. The methodology is applied to the case of Colombia, a developing country with significant regional disparities in terms of trade performance (see Figure 1). The analysis consists on estimating a model in which regional exports depend on the freight costs of shipping the exports from their location of production to their ports of shipment (ports, airports or borders) controlling for several other factors. The model is then used to predict how changes in road quality affect export performance. Our study is somewhat related to Albarran, Carrasco and Holl (2009) which also uses GIS analysis to examine how transport network improvements affect the likelihood of exporting among Spanish firms. One of the main differences with our study, however, is the measure of transportcosts. While these authors use travel time to proxy for transportcosts, we significantly improve this measure by explicitly estimating the transportcosts associated with travel time and also with distance. This is important because the effects of improvements in the transport network are not limited to time-related costs but are also associated with distance-related costs, as we will show in the analysis.
In the European Commission’s White Paper “Fair payment for infrastructure use” (3), costs caused by transport delays, accidents and environmental effects of transport are estimated to be the three major causes of external transportcosts. In the category 'congestion costs', the costs of delay and delay-caused additional operating costs are estimates. The loss of lives and the reduction of health and prosperity through transport accidents are of major concern. The health related accident costs are calculated by assessing the loss of production, the risk value and the medical and non-medical rehabilitation of accident victims. The external part of accident costs, defined here as accident costs imposed by transport users on the rest of society, is included but total accident costs, however, include a substantial proportion of costs imposed by one user on others and these are included as well where possible.
before it would pay the firm to switch to the equilibrium with a plant located in the country with no environmental policy. Thus the introduction of transportcosts, which is needed to rationalise a multinational pattern of production, provides a degree of protection to a country to set a tougher environmental policy than other countries without fear of losing plants to rival countries. So this contradicts claims 1 and 5. MMO again compare the policies governments would set after the firm has made its choice of plant location, with the policies governments would set prior to the firm deciding where to locate its plant(s). MMO reach the same conclusion as Hoel about the possibility of a NIMBY outcome - with high enough damage costs both governments will set prohibitive environmental policies to deter any plant being located in their countries, despite the fact in terms of global welfare it would be desirable that the product be produced. But there is an interesting twist to the ‘race- to-the-bottom’ case. When governments set their policies after the firm has chosen its plant locations (so, as in the simple model, there is no strategic competition between governments) there will be two possibilities - the firm chooses a single plant and exports to the other country or it locates a plant in each country, with the first outcome being chosen when the fixed cost of setting up a plant is relatively high. In both cases when we switch to having the governments set environmental policies before the firm chooses plant locations then there will be competition to weaken environmental policies, so claims 3 and 4 remain true. But if in the non-strategic case, the outcome involved the firm setting up a single plant, then in the process of competition the firm may decide to switch to having two plants, while if the non- strategic outcome involved the firm having two plants this will remain the outcome when the governments compete strategically. Thus strategic competition may lead to the firm proliferating plants, but, except in the NIMBY outcome, not to it reducing the number of plants. The rationale is this. The firm is trading off the fixed costs of setting up plants against the transportcosts of having to export. Suppose in the non- strategic case governments set tough environmental standards so that production costs are high; then output will be relatively low, transportcosts will be low relative to total production costs and it will not be economic for the firm to carry two sets of fixed plant costs; however as the governments compete and weaken environmental policies this will reduce production costs relative to transportcosts, expand sales in each country and make it more attractive for the firm to set up a second plant.
Up to 86% of the changes in net income were significantly determined by six cost variables as a group (i.e., land area under sugarcane, tillage costs, seedcane costs, transportcosts, yield, and farmer’s education level). The main factors that enhance farmers’ income are acreage under sugarcane, actual yield per unit land area, and education level of farmers. Expert opinion on acreage suggested that sugarcane would be more profitable if farmers had at least three acres of land. In addition, negative income was mainly associated with farmers with primary level education. By implication the higher the education level, the more likely are farmers to adopt sugarcane farming from an entrepreneurial perspective, including proper land and crop husbandry practises, which could boost yields and hence income. Therefore, from a CSR perspective, the company and government through their extension services should encourage farmers with less land to diversify into other crops or alternative income generating activities, rather than be trapped in poverty due to being psychologically obsessed with sugarcane. Further, to maximize profits, farmers should be empowered with regard to the control of farm inputs as demonstrated by some ‘‘model’’ farmers.
To determine the optimal location for a warehouse under the different future growth ratios, we formulated an ILP-model both for Zuivelhoeve Vers and Van der Poel Desserts. In this ILP-model the future stock levels, transportcosts to each group of customers, transportcosts and storage costs can be inserted. The output of the ILP- model gives the operational costs as objective and indicates where the goods should be stored every week of the year. In theILP-model we also inserted renting storage space as option if just in a few weeks of the year the capacity level of a warehouse is exceeded. So by using this model, we came to the following with regard to the optimal location for a warehouse under the different future growth scenarios: Van der Poel Desserts:
2. Although at the moment the model of spatially located market as a fiber bundle, developed in this paper, is a theoretical one, empirical studies within the framework should not encounter problems. However, detailed empirical tests, as well as further practical application of the approach and the model, is rather a complex and tedious task for several technical reasons. First, while the model, built in previous sections, is quite simple and thus tractable, extending it from the market to the economy, from one commodity to the variety and from modeling only transportcosts impact to considering several transport variables will significantly complicate all the required calculations. Second, according to (1) – (13), all the given data must be spatially located, that means economic statistics needs to be structured geographically. Probably, commercial distribution of geographic information systems itself will either solve or ease the latter problem.
3. Economies of scale: Another condition affecting transportcosts is related to economies of scale or the possibilities to apply them as the larger the quantities transported, the lower the unit cost. Bulk commodities such as energy (coal, oil), minerals and grains are highly suitable to obtain lower unit transportcosts if they are transported in large quantities. A similar trend also applies to container shipping with larger containerships involving lower unit costs (Jean, Claude and Brian, 2006). If goods are transported in large quantity, more fuel will be required. Therefore, the advantage incurred on transporting large volumes of goods is a disadvantage to the amount of fuel to be consumed. If fuel is been subsidized, the cost of fuel to be consumed when transporting large volumes of goods will be minimal but in the case of subsidy removal, the cost of fuel to be consumed will be at a very high rate and transport service provider must be critical and analytical in taking decisions of cost (Adeniran, 2016d);
“Price” may be what companies decide to charge for their products, but “cost to the customer” represents the real cost that customers will pay, including, for example, in the case of “bricks” retail, their own transportcosts. For “clicks” e-retail, there are also the costs of carriage and perhaps taxes to be added to the quoted prices. High carriage charges may be one reason for the high rate of carts abandoned at the checkout. Customers also need to consider the possible costs of internet access. Consumers have a perception that prices should be lower online than in store, and this can cause problems when customers buying via other channels realise that they are paying more than online customers. For example, Screwfix (www.screwfix.com), a well-known supplier of tradesperson‟s supplies via paper catalogue and telesales, have a number of attractive special offers available only online. Customers, who have looked up what they want online, and then telephone to order, can be irritated to learn that the extra discounts are not available when ordering by phone.
To address this limitation, we revisit the question of free and optimal en- try in a setting where customer demand is price-sensitive and where, in contrast to previous contributions, transportcosts to customers are on a per-unit basis. This means that customers have to incur a transport cost (disutility costs) for each unit they purchase. As such, our setup can thus be interpreted in two ways. First, it may represent product differentiation along a taste dimension where a transport cost per unit representing the mismatch of product characteristic and a customer’s preference is a suit- able assumption. Second, it may reflect a situation where a customer incurs actual transportation costs per unit shipped (geographical interpretation), i.e., shipping a greater number of items results in an increase in the shipping
Finally, economic considerations have been dealt with in some papers. Santos et al. , for instance, analysed the effect of some transport policies with the aim of pro- moting rail-road intermodal transport in Europe. One of these policies regards the internalization of the external costs related to the drayage length, which is also an im- portant aspect in our paper. They proposed, through a practical application in Belgium, an innovative mixed in- teger intermodal freight location-allocation model, based on the hub-location theory, and deal with non-linear transportcosts in order to replicate the economies of distance. Mostert and Limbourg  presented the state of the art about the external costs of freight transport, while Kos et al.  focused their research on the con- tainer transport chain. The former work also compared the total costs of road and rail-road combined transport, using Janic’s fomulas , by varying the drayage length. Their results did not show the trend of the costs related to a single component (drayage, terminals and rail), but only the amount of each. The above-mentioned paper by Janic  considered the externalities by means of a model that was proposed to calculate the internal and external costs of intermodal and road freight transport networks. His interesting approach considered a network with several origins and destinations that converged in two main terminals. The author found significant results using some assumptions and detailed formula and con- sidering the time components. His paper was focused on the door-to-door distance, but the influence of the dray- age length did not emerge. Janic found that the full costs decrease more than proportionally as the door-to-door distance increases, thus suggesting economies of scale.
For some events comprised in the Swiss flood and land- slide damage database it is difficult to comprehend the exact course of event and thus to identify whether bedload trans- port deposition or erosion played a crucial role in the damage process or not. We have introduced a process uncertainty in- dex ranging from 1 to 3 to provide a qualitative evaluation of the reliability of our data regarding the significance of bed- load transport during an event. The mean process uncertainty index calculated for the bedload damage cost estimations per pentad varies between 1.27 (1992–1996), which is a very good score, and 2.27 (1972–1976), which has to be rated as a rather poor score, while the 40 yr long-term average amounts to 1.78 (Fig. 5 and Table 2). Early pentads of our data set show higher process uncertainty indices than the later pen- tads, and overall it seems that the process uncertainty is de- creasing with time. As a matter of fact, data acquisition and recording has improved in the Swiss flood and landslide da- mage database during the last 40 yr. First, the quality of the raw data (mainly newspaper articles) has increased notably. Due to an increasing public awareness of natural hazards, the completeness and accuracy of media coverage has im- proved over time, even for events that occur in remote parts of the country. However, regional variations in the quality of
Due to new funding through the Global Fund against AIDS, tuberculosis and malaria, ACT is now available in the Nouna Health District as in all of Burkina Faso since the end of 2007. These drug regimens can be purchased from all governmental health facilities at a subsidized prize, which is however several times above the former prize for chloroquine. Moreover, long distances to rural health centres, transport problems and lack of money to pay for transport, services and opportunity costs will cer- tainly continue to limit early access of young children with malaria to modern health facilities in Burkina Faso, as in most of rural SSA [21,27,30,41,81,82]. Strengthen- ing the role of CHW or other volunteers trained to distrib- ute anti-malarials may thus remain the only short-term solution for increasing access to early effective malaria treatment in rural SSA.
A quantification for the 550 ton/day biogas plant of the monetised externalities is shown in table 3.3. The table shows the annual costs and benefits taken into account at the four levels of the socio - economic analysis. A socio-economic rate of calculation of 6% p.a. has been used, and the analysis covers the period 2001-2020. Values shown are in year 2000 price level. (1€ = 7.43 DKK).
3 tons had a very small effect on the fuel consumption related to amount of transported material. Fuel consumption was nearly the same. Increasing of the carrying capacity of the semi-trailers has caused only the increase of fuel consumption of the tractor-machine sets related to one hour of operation. Fuel consumption was increased also due to the higher transport performance. Based on results obtained it is very important to make maximum use of carrying capacity of the semi-trailers in order to obtain maximum efficiency of the tractor power.
The secondary data collected on tariffs paid for transpor- tation of agricultural produce and fares paid for the transportation of humans on each road of the district road network were converted into Agricultural Produce Trans- port Tariff in GH¢ per tonne-kilometer and Passenger Transport Fare in GH¢ per passenger-kilometer respec- tively. The transportation tariffs paid for the transporta- tion of agricultural produce were converted to those moved by a 10-tonne truck equivalent. This is in accor- dance with the practice among the GPRTU drivers who will never move their loaded truck unless loaded to ca- pacity and sometimes even beyond capacity.
The figures in Table 3 are based on assumptions and have to be regarded with caution. However, they show COOP’s willingness to take precautionary measures such as the em- ployment of extra staff to manage the intermodal road-rail concept and the investment in more expensive transferable trailers that can be used to reduce the costs in case of major train delays. They also show that COOP paid additional opera- tional costs when the trains were heavily delayed or cancelled, largely explaining the difference between precautionary costs and operative costs. As mentioned above, there is clearly a trade-off between the precautionary and operational costs; it also has to be taken into account that the combined road-rail concept is quite new and there are probably learning curves for all stake holders. As an example, in October 2011 COOP engaged a rail operator for the shuttle train that uses more powerful locomotives than the operator that ran the shuttle train 2009–2011. This is expected to reduce the delays caused by leaves on the track. 18
The government business environment is influenced by internal and external factors such as economic factors, legal factors and socio-political factors. Before de- regulation in the 1980’s the government had a monopoly in the transport industry where it owned infrastructures, equipment and operated transport entities. After de- regulation and liberalisation of trade in which fair and free competition dominates the trade, the government became a policy and regulatory body. Most of the local industries, which produce traditional commodities, gain the exposure of the international markets; this results in the growth of import and export trade. The same changes are taking place in Tanzanian neighbouring countries thus, creating the demand for good infrastructure and equipment and transparency in facilitation of efficiency and flexibility with optimum cost services to foster the international trade in the area. Therefore, it is the government’s duty to concentrate on the provision of law and order, strategic planning, policy provision, monitoring and putting in place the regulatory regime and institutional framework to facilitate the development process.
The Devil’s Quadrangle is an often used theory to describe the trade off between different main forces in a company. The Devils Quadrangle in this study is used to select the main dimensions. The main criteria to judge on the business process of renting out and resale are Time, Quality, Flexibility and Costs. Since other dimensions like innovation can easily be arranged under these main dimensions, these criteria can well be projected on the activities at De Meeuw. The theory about the quadrangle describes the model and its factors but does not contain a suitable method to actually create a redesign. It is theoretical model and not suitable for operational use. To make the redesign operational it is opted for a BPR framework developed by S. Limam Mansar and H.A. Reijers (2005). The framework is a synthesis of different methods and techniques and will be used to group and analyse the results in this study. This framework distinguishes the behavioral and the operational view. These two views will be influenced and interact with the factors: organization (structure and population), information and technology. The structure of this framework will also be used to describe the current business process in chapter 4. The advantage of this approach is that the description of the current process will be structured and made comparable with the best practices from the theory. Although the framework is an excellent way to structure and analyze the study, it is not a method for redesign.
Costs will be collected from health system and patient perspectives, and will consider the healthcare resource requirements and patient expenses associated with each treatment arm. Speci ﬁ cally, we will collect data in two resource use areas: (1) healthcare services costs, which include the use of all hospital facilities over the course of the trial, including drugs, medical supplies and laboratory; and (2) patient out-of-pocket expenses, which include the individual ’ s own time (lost time) in the treatment process and associated travel expenses. Health systems costs will include costs incurred at facil- ities, by each study arm. Patient costs that will be esti- mated are those incurred in seeking services for MDR-TB healthcare. The trial is expected to report its main outcomes in 2017, so all costs will be in ﬂ ated to 2017 values using the relevant consumer price indices from the International Monetary Fund, and converted from local currency units to international dollars using purchasing power parity exchange rates.
This means of representation is useful in that only three levels of demand are needed. However, on closer examination of the form of function used, it can be seen that there are some difficulties in the use of this type of function for the purpose of representing traffic delay where at traffic levels greater than 7 million pcu-km (4,349,800 pcu-mi) the function reaches a discontinuity. Such discontinuities cause difficulties during optimization of the TRENEN model. Possible improvements to this relationship were investigated, although compatibility with the TRENEN model was ensured by maintaining units similar to those of De Borger et al (5) (i.e. pcu-km rather than trips). [The unit to represent demand in standard network models is trips whereas in the TRENEN model transport demand is represented in pcu-km]. To improve on the function form of the flow-delay relationship developed by De Borger et al , a trip table factorization method was used for development of the relationships for the peak and off-peak periods, where the trip table in both case was factored from 0.5 to 1.0 in steps of 0.1. The table