Policy options promoting market participation among smallholder livestock producers: a case study from the Phillipines

We investigate the factors precipitating market entry where smallholders make decisions about participation (a discrete choice about whether to sell quantities of products) and supply (a continuous-valued choice about how much quantity to sell) in a cross-section of smallholders in Northern Luzon, Philippines, in a model that combines basic probit and Tobit ideas, is implemented using Bayesian methods, and generates precise estimates of the inputs required in order to effect entry among the non-participants. We estimate the total amounts of (cattle, buffalo, pig and chicken) livestock input required to effect entry and compare and contrast the alternative input requirements. To the extent that our smallholder sample may be representative of a wide and broader set of circumstances, our findings shed light on offsetting impacts of conflicting factors that complicate the roles for policy in the context of expanding the density of participation.

Exploring options for managing strategies for pea-barley intercropping using a modeling approach

A modeling Study was carried out into pea-barley intercropping in northern Europe. The two objectives were (a) to compare pea-barley intercropping to sole cropping in terms of grain and nitrogen yield amounts and stability, and (b) to explore options for managing pea-barley intercropping systems in order to maximize the biomass produced and the grain and nitrogen yields according to the available resources, such as light, water and nitrogen. The study consisted of simulations taking into account soil and weather variability among three sites located in northern European Countries (Denmark, United Kingdom and France), and using 10 years of weather records. A preliminary stage evaluated the STICS intercrop model's ability to predict grain and nitrogen yields of the two species, using a 2-year dataset from trials conducted at the three sites. The work was carried out in two phases, (a) the model was run to investigate the potentialities of intercrops as compared to sole crops, and (b) the model was run to explore options for managing pea-barley intercropping, asking the following three questions: (i) in order to increase light capture, Would it be worth delaying the sowing dates of one species? (ii) How to manage sowing density and seed proportion of each species in the intercrop to improve total grain yield and N use efficiency? (iii) How to optimize the use of nitrogen resources by choosing the most suitable preceding crop and/or the most appropriate soil? It was found that (1) intercropping made better use of environmental resources as regards yield amount and stability than sole cropping, with a noticeable site effect, (2) pea growth in intercrops was strongly linked to soil moisture, and barley yield was determined by nitrogen uptake and light interception due to its height relative to pea, (3) sowing barley before pea led to a relative grain yield reduction averaged over all three sites, but sowing strategy must be adapted to the location, being dependent on temperature and thus latitude, (4) density and species proportions had a small effect on total grain yield, underlining the interspecific offset in the use of environmental growth resources which led to similar total grain yields whatever the pea-barley design, and (5) long-term strategies including mineralization management through organic residue supply and rotation management were very valuable, always favoring intercrop total grain yield and N accumulation. (C) 2009 Elsevier B.V. All rights reserved.

Directed search with real options

While search is normally modelled by economists purely in terms of decisions over making observations, this paper models it as a process in which information is gained through feedback from innovatory product launches. The information gained can then be used to decide whether to exercise real options. In the model the initial decisions involve a product design and the scale of production capacity. There are then real options to change these factors based on what is learned. The case of launching product variants in parallel is also considered. Under ‘true’ uncertainty, the model can be seen in terms of heuristic decision-making based on subjective beliefs with limited foresight. Search costs, the values of the real options, beliefs, and the cost of capital are all shown to be significant in determining the search path.

Risk pricing practices in finance, insurance and construction

A review of current risk pricing practices in the financial, insurance and construction sectors is conducted through a comprehensive literature review. The purpose was to inform a study on risk and price in the tendering processes of contractors: specifically, how contractors take account of risk when they are calculating their bids for construction work. The reference to mainstream literature was in view of construction management research as a field of application rather than a fundamental academic discipline. Analytical models are used for risk pricing in the financial sector. Certain mathematical laws and principles of insurance are used to price risk in the insurance sector. construction contractors and practitioners are described to traditionally price allowances for project risk using mechanisms such as intuition and experience. Project risk analysis models have proliferated in recent years. However, they are rarely used because of problems practitioners face when confronted with them. A discussion of practices across the three sectors shows that the construction industry does not approach risk according to the sophisticated mechanisms of the two other sectors. This is not a poor situation in itself. However, knowledge transfer from finance and insurance can help construction practitioners. But also, formal risk models for contractors should be informed by the commercial exigencies and unique characteristics of the construction sector.

Entropy application to improve construction finance decisions

In financial decision-making processes, the adopted weights of the objective functions have significant impacts on the final decision outcome. However, conventional rating and weighting methods exhibit difficulty in deriving appropriate weights for complex decision-making problems with imprecise information. Entropy is a quantitative measure of uncertainty and has been useful in exploring weights of attributes in decision making. A fuzzy and entropy-based mathematical approach is employed to solve the weighting problem of the objective functions in an overall cash-flow model. The multiproject being undertaken by a medium-size construction firm in Hong Kong was used as a real case study to demonstrate the application of entropy. Its application in multiproject cash flow situations is demonstrated. The results indicate that the overall before-tax profit was HK$ 0.11 millions lower after the introduction of appropriate weights. In addition, the best time to invest in new projects arising from positive cash flow was identified to be two working months earlier than the nonweight system.

Selection of funding schemes by a borrowing decision model: a Hong Kong case study

In financial decision-making, a number of mathematical models have been developed for financial management in construction. However, optimizing both qualitative and quantitative factors and the semi-structured nature of construction finance optimization problems are key challenges in solving construction finance decisions. The selection of funding schemes by a modified construction loan acquisition model is solved by an adaptive genetic algorithm (AGA) approach. The basic objectives of the model are to optimize the loan and to minimize the interest payments for all projects. Multiple projects being undertaken by a medium-size construction firm in Hong Kong were used as a real case study to demonstrate the application of the model to the borrowing decision problems. A compromise monthly borrowing schedule was finally achieved. The results indicate that Small and Medium Enterprise (SME) Loan Guarantee Scheme (SGS) was first identified as the source of external financing. Selection of sources of funding can then be made to avoid the possibility of financial problems in the firm by classifying qualitative factors into external, interactive and internal types and taking additional qualitative factors including sovereignty, credit ability and networking into consideration. Thus a more accurate, objective and reliable borrowing decision can be provided for the decision-maker to analyse the financial options.