The Act of July 5, 2018 on Facilitating of Preparation and Implementation of Housing and Accompanying Investments allows such investments irrespective of the existence of a local development plan or determination of use of land in the local development plan. In other words, the abovementioned investments may be implemented on land with a completely different designation according to the local development plan, as for example the mining of minerals. The location of the investment is decided by a resolution of the municipal council. If the planned location is to be situated within the boundaries of documented mineral deposits and the so-called „mining areas”, it needs, among others, to be agreed with the appropriate geological administration authority. Not taking a position within 21 days is considered as a consent. With reference to the deposits not covered by mining licenses, the Act does not indicate the premises that should be taken into consideration while providing such consent. There is a concern that this may lead to the development of the land in a way that will cause the subsequent extraction of the mineral impossible.
The problems related to construction production are multi-faceted and complex. This has promoted the search for different methods/approaches for analizing the data which supports the decision-making process in the construction industry. In the article the authors focus their attention on well-known methods and tools, and on some new approaches to solving decision-making problems. The aim of the article is to analyze the methods used to analyse data in a construction company, convey their advantages and disadvantages, and specify the degree of efficiency in the discussed area.
The paper considers the modeling and estimation of the stochastic frontier model where the error components are assumed to be correlated and the inefficiency error is assumed to be autocorrelated. The multivariate Farlie-Gumble-Morgenstern (FGM) and normal copula are used to capture both the contemporaneous and the temporal dependence between, and among, the noise and the inefficiency components. The intractable multiple integrals that appear in the likelihood function of the model are evaluated using the Halton sequence based Monte Carlo (MC) simulation technique. The consistency and the asymptotic efficiency of the resulting simulated maximum likelihood (SML) estimators of the present model parameters are established. Finally, the application of model using the SML method to the real life US airline data shows significant noise-inefficiency dependence and temporal dependence of inefficiency.