Towards a demand model for maritime passenger transportation in the Caribbean: a regional study of passenger ferry services

In this paper, the main factors that influence the demand for maritime passenger transportation in the Caribbean were studied. While maritime studies in the Caribbean have focused on infrastructural and operational systems for intensifying trade and movement of goods, there is little information on the movement of persons within the region and its potential to encourage further integration and sustainable development. Data to inform studies and policies in this area are particularly difficult to source. For this study, an unbalanced data set for the 2000-2014 period in 15 destinations with a focus on departing ferry passengers was compiled. Further a demand equation for maritime passenger transportation in the Caribbean using panel data methods was estimated. The results showed that this demand is related to the real fare of the service, international economic activity and the number of passengers arriving in the country by air.

Urban water demand model: the case study of Emilia Romagna (Italy)

Water is the driving force in nature. We use water for washing cars, doing laundry, cooking, taking a shower, but also to generate energy and electricity. Therefore water is a necessary product in our daily lives (USGS. Howard Perlman, 2013). The model that we created is based on the urban water demand computer model from the Pacific Institute (California). With this model we will forecast the future urban water use of Emilia Romagna up to the year of 2030. We will analyze the urban water demand in Emilia Romagna that includes the 9 provinces: Bologna, Ferrara, Forli-Cesena, Modena, Parma, Piacenza, Ravenna, Reggio Emilia and Rimini. The term urban water refers to the water used in cities and suburbs and in homes in the rural areas. This will include the residential, commercial, institutional and the industrial use. In this research, we will cover the water saving technologies that can help to save water for daily use. We will project what influence these technologies have to the urban water demand, and what it can mean for future urban water demands. The ongoing climate change can reduce the snowpack, and extreme floods or droughts in Italy. The changing climate and development patterns are expected to have a significant impact on water demand in the future. We will do this by conducting different scenario analyses, by combining different population projections, climate influence and water saving technologies. In addition, we will also conduct a sensitivity analyses. The several analyses will show us how future urban water demand is likely respond to changes in water conservation technologies, population, climate, water price and consumption. I hope the research can contribute to the insight of the reader’s thoughts and opinion.

The demand for light duty trucks: the Wharton EFA Motor Vehicle Demand Model (Mark II). Final report.

National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.

An analysis of the automobile market: modeling of the long-run determinants of the demand for automobiles. Volume III: appendices to the Wharton E.F.A. Automobile Demand Model. Final report.

Transportation Department, Washington, D.C.

Revisions to the Wharton EFA Automobile Demand Model (Mark I). Final report.

National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.

An analysis of the automobile market: modeling of the long-run determinants of the demand for automobiles. Volume II: simulation analysis using the Wharton E.F.A. Automobile Demand Model. Final report.

Transportation Department, Washington, D.C.

An analysis of the automobile market: modeling of the long-run determinants of the demand for automobiles. Volume I: the Wharton E.F.A. Automobile Demand Model. Final report.

Transportation Department, Washington, D.C.

An empirical model to estimate the demand for primary care in urban settings

Objective. To measure the demand for primary care and its associated factors by building and estimating a demand model of primary care in urban settings.^ Data source. Secondary data from 2005 California Health Interview Survey (CHIS 2005), a population-based random-digit dial telephone survey, conducted by the UCLA Center for Health Policy Research in collaboration with the California Department of Health Services, and the Public Health Institute between July 2005 and April 2006.^ Study design. A literature review was done to specify the demand model by identifying relevant predictors and indicators. CHIS 2005 data was utilized for demand estimation.^ Analytical methods. The probit regression was used to estimate the use/non-use equation and the negative binomial regression was applied to the utilization equation with the non-negative integer dependent variable.^ Results. The model included two equations in which the use/non-use equation explained the probability of making a doctor visit in the past twelve months, and the utilization equation estimated the demand for primary conditional on at least one visit. Among independent variables, wage rate and income did not affect the primary care demand whereas age had a negative effect on demand. People with college and graduate educational level were associated with 1.03 (p < 0.05) and 1.58 (p < 0.01) more visits, respectively, compared to those with no formal education. Insurance was significantly and positively related to the demand for primary care (p < 0.01). Need for care variables exhibited positive effects on demand (p < 0.01). Existence of chronic disease was associated with 0.63 more visits, disability status was associated with 1.05 more visits, and people with poor health status had 4.24 more visits than those with excellent health status. ^ Conclusions. The average probability of visiting doctors in the past twelve months was 85% and the average number of visits was 3.45. The study emphasized the importance of need variables in explaining healthcare utilization, as well as the impact of insurance, employment and education on demand. The two-equation model of decision-making, and the probit and negative binomial regression methods, was a useful approach to demand estimation for primary care in urban settings.^

The demand for intensity versus frequency of alcohol consumption: Evidence from rural Australia

This paper develops a theoretical model for the demand of alcohol where intensity and frequency of consumption are separate choices made by individuals in order to maximize their utility. While distinguishing between intensity and frequency of consumption may be unimportant for many goods, this is clearly not the case with alcohol where the likelihood of harm depends not only on the total consumed but also on the pattern of use. The results from the theoretical model are applied to data from rural Australia in order to investigate the factors that affect the patterns of alcohol use for this population group. This research can play an important role in informing policies by identifying those factors which influence preferences for patterns of risky alcohol use and those groups and communities who are most at risk of harm.

Tourism Demand in Catalonia: detecting external economic factors

There is a lack of studies on tourism demand in Catalonia. To fill the gap, this paper focuses on detecting the macroeconomic factors that determine tourism demand in Catalonia. We also analyse the relation between these factors and tourism demand. Despite the strong seasonal component and the outliers in the time series of some countries, overnight stays give a better indication of tourism demand in Catalonia than the number of tourists. The degree of linear association between the macroeconomic variables and tourism demand is also higher when using quarterly rather than monthly data. Finally, there are notable differences between the results obtained for the different countries analysed. These results indicate that the best way to model tourism demand in Catalonia is to specify a quarterly model of overnight stays, differentiating between an aggregate demand model for the total number of tourists and specific models for each of the countries analysed.

Coordinating Inventory Control and Pricing Strategies with Random Demand and Fixed Ordering Cost: The Finite Horizon Case

We analyze a finite horizon, single product, periodic review model in which pricing and production/inventory decisions are made simultaneously. Demands in different periods are random variables that are independent of each other and their distributions depend on the product price. Pricing and ordering decisions are made at the beginning of each period and all shortages are backlogged. Ordering cost includes both a fixed cost and a variable cost proportional to the amount ordered. The objective is to find an inventory policy and a pricing strategy maximizing expected profit over the finite horizon. We show that when the demand model is additive, the profit-to-go functions are k-concave and hence an (s,S,p) policy is optimal. In such a policy, the period inventory is managed based on the classical (s,S) policy and price is determined based on the inventory position at the beginning of each period. For more general demand functions, i.e., multiplicative plus additive functions, we demonstrate that the profit-to-go function is not necessarily k-concave and an (s,S,p) policy is not necessarily optimal. We introduce a new concept, the symmetric k-concave functions and apply it to provide a characterization of the optimal policy.

Identified consumers: an experiment on the informativeness of cross-demand price effects

Often, firms have no information on the specification of the true demand model they are faced with. It is, however, a well established fact that trial-and-error algorithms may be used by them in order to learn how to make optimal decisions. Using experimental methods, we identify a property of the information on past actions which helps the seller of two asymmetric demand substitutes to reach the optimal prices more precisely and faster. The property concerns the possibility of disaggregating changes in each product’s demand into client exit/entry and shift from one product to the other.

Towards diversification of the tourism sector: A recreational demand study of yachting and marina services in the Caribbean

Includes bibliography.

The effect of demand distributions on the performance of inventory policies

Inventory policies provide instructions on how to calculate stock levels and order quantities. This paper examines the effect of the demand distribution on the performance of several well-known policies. Their performance is compared in terms of achieved service levels. As a conclusion from these comparisons, a nonparametric demand model is proposed to be used in inventory policies.