Relevant bibliographies by topics / Research, Industrial – Econometric models

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Research, Industrial – Econometric models'

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Published: 10 March 2023

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Journal articles on the topic "Research, Industrial – Econometric models"

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Ismagilova, Larisa, and Elvira Arylbaeva. "Labor productivity management: cognitive models of contradictions." Vestnik BIST (Bashkir Institute of Social Technologies), no. 2(55) (June 30, 2022): 154–61. http://dx.doi.org/10.47598/2078-9025-2022-2-55-154-161.

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The analysis of the research, demonstrating the interrelation between the efficiency of human resources management and economic results of the enterprise has been conducted. Causal relationship between human resource management and productivity is shown. Contradictions in the formation of human and labor resources are revealed. The defining role of human capital in the structure of intangible resources. The procedure of substantiation of the choice of HR-practices that involves the construction of a generalized cognitive model of the impact of intangible resources on productivity was formed. The structure of the system of labor productivity management is developed. The structure of the blocks of imitation model on the basis of econometric research data, the procedure of selection of the most important HR-factors is proposed. The possibility of substantiating the choice of control actions based on modeling results is shown. Causal scheme of labor productivity management through intangible resources of industrial enterprise is proposed. A set of econometric models built on the basis of generalization of empirical research and statistical data of specific enterprises was used to develop the model.
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Ploegmakers, Huub, and Friso de Vor. "Determinants of industrial land prices in The Netherlands: a behavioural approach." Journal of European Real Estate Research 8, no. 3 (November 2, 2015): 305–26. http://dx.doi.org/10.1108/jerer-04-2015-0016.

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Purpose – The purpose of this paper is to demonstrate how the specification of hedonic pricing models can be improved by using insights generated from qualitative research. In doing so, it seeks to address one of the main problems in the specification of hedonic models, namely that theory yields little guidance in the selection of the characteristics that should be included on the right-hand side. Design/methodology/approach – Building on the behavioural tradition in real estate research, this paper introduces a research approach that integrates insights from qualitative analysis in an econometric model of land values. The empirical segment explores the way in which asking prices of building plots for industrial purposes are determined in The Netherlands. It draws from interviews with municipal land developers, who dominate supply in this market. The information secured during these interviews relates to the characteristics considered important and the kind of information used in the valuation process. Based on these qualitative data, an econometric model is developed and estimated. Findings – The estimation results confirm qualitative evidence that the typical developer considers only a limited number of features of the land in the valuation process and that the primary source of information in setting asking prices relates to the prices charged in neighbouring municipalities. Originality/value – This paper represents a novel attempt to examine the determination of land and property values by merging qualitative and quantitative, econometric analyses.
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Lin, MeiTing, and Chun Xu. "Research on the Influence of Digital Economy on the Upgrading of Industrial Structure." Advances in Economics and Management Research 3, no. 1 (December 30, 2022): 82. http://dx.doi.org/10.56028/aemr.3.1.82.

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Based on the provincial panel data of China from 2013 to 2019, this paper calculates the comprehensive index of digital economy development, constructs a variety of econometric models, and discusses the effect and influence mechanism of digital economy on industrial structure upgrading. It is found that the digital economy has a significant positive effect on the upgrading of industrial structure; Digital economy promotes the upgrading of industrial structure by promoting technological innovation; According to the regional inspection, the effect of digital economy on industrial structure upgrading in central, eastern and western regions is gradually decreasing. Finally, according to the results of empirical research, some policy suggestions are put forward.
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Turlakova, Svitlana. "Research of mathematical methods and models of long-term industrial development." Economy of Industry 4, no. 100 (December 1, 2022): 53–77. http://dx.doi.org/10.15407/econindustry2022.04.053.

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The importance of the study of relevant mathematical methods and models of long-term development of the national industry is substantiated. It has been proven that causal econometric models of production are relatively simple and convenient to use in practice, as well as the most common tools for researching the long-term economic future. It was defined that the production functions, adapted to individual circumstances, proved their ability to solve the assigned tasks. However, the problem of more accurate adjustment to the features of the simulated object of research is particularly relevant in the current conditions of development of Ukraine, in the conditions of concentration of attention on certain sectors, on particular branch of industry, and in connection with the revolutionary transformations of production forces and relations, in accordance with the spread of cyber-physical technologies of the Fourth Industrial revolution.In such specific circumstances, it makes sense to ask for more sophisticated models. On the one hand, they are better, as they allow more accurate tuning of the modeled object, including by adding important factors that are outside the production system. On the other hand, they are worse because they complicate the analysis and significantly increase the number of variables needed to describe the dynamics of economic growth. In this connection, expert research methods cannot be neglected. Choosing the type of model, the range of influencing factors, possible development scenarios, etc., usually requires expert assessments (often implicit). Therefore, when analyzing long-term factors and development trends, it is important to adhere to the main methodological message of expert approaches in the construction of foresights: for long time horizons in conditions of significant uncertainty, it is appropriate to ask questions not about the calculation of the "correct future", but about the assessment of the spectrum of probable scenarios of development, expansion and rethinking its new opportunities and challenges, in particular – to avoid potentially harmful ideas and expectations, embedded in the current policy.
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Xu, Shuang. "Application and Analysis of Spatial Spillover Effects of an Improved Panel Data Econometric Model in Universities, Population, and Industrial Parks in Guiyang." Mobile Information Systems 2022 (August 29, 2022): 1–10. http://dx.doi.org/10.1155/2022/9654342.

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In the field of econometrics, panel data are an extremely important type of data. In macroeconomic research, panel data models are widely used in exchange rate determination theory, testing of cross-border economic growth and convergence theory, analysis of industrial structure, research on technological innovation, etc. The agglomeration and population distribution of colleges and universities, and the economic support of industrial parks play an important role in economic and social development as a source of research and development and a source of talents. The panel data model usually assumes that the error term follows a normal distribution, but the actual data are difficult to satisfy this assumption, and the estimation obtained by traditional methods may be biased or even invalid. This paper proposes a more robust and effective estimation method (ELS-EL) based on the panel data mean regression model, and extends this method to complex panel data models such as generalized linear models and partial linear models; in addition, this paper is based on panel data. We proposed a two-stage instrumental variable method (2S-IVFEQR) to reduce the computational complexity and generalized the new method to the quantile regression model of dynamic panel data. At the same time, this paper uses the above-improved panel data econometric model to analyze the spatial spillover effects of college aggregation, population distribution, and industrial parks in Guiyang. This study found that the agglomeration of colleges and universities has significantly promoted the economic growth of our country. These promotion effects come from both the direct contribution of college agglomeration and the positive external spillover effect of college agglomeration.
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Kudryavtseva, T. Yu, and A. E. Skhvediani. "An econometric analysis of the regional industrial specialization: The Russian manufacturing industry case study." Economic Analysis: Theory and Practice 19, no. 9 (September 29, 2020): 1765–90. http://dx.doi.org/10.24891/ea.19.9.1765.

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Subject. The article reviews the manufacturing industry in Russian regions, calculates the indicators of regional industrial specialization needed for development of econometric models of spatial panel data. Objectives. The purpose is to create a methodology for analyzing the regional industrial specialization based on econometric tools; to test it, using the case of the manufacturing industry, for determining the type of externalities in the Russian Federation. Methods. To build econometric models, we use methods of least squares and maximum likelihood. We apply localization ratios to assess regional industrial specialization in terms of the volume of employment, revenue and investment in manufacturing, workforce productivity, etc. Results. The findings show the clustering of regions by the level of productivity. The localization of manufacturing industry in regions in terms of localization of employment and localization of productivity is negatively related to productivity in the region. This can be explained by the transition of regional economies to the post-industrial mode, where the service sector becomes more important, and by possible over-industrialization and specialization of certain regions in the context of the need to develop related sectors and to build links between them. The presence of direct negative MAR externalities may indicate a need for further research in positive Porter and Jacobs externalities for Russian regions manufacturing industry. Conclusions. The developed methodology enables to identify and analyze relationships between regional industrial specialization and regional indicators; to specify the type of externalities and determine the existence of indirect and direct effects of industry localization.
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Zrailo, Ivan, and Svitlana Hynkevych. "Modern Trends in the Functioning of Grain-Product Subcomplex of the Agricultural Sector of Ukraine in the Context of Implementing Its External Economic Potential." Economic and Regional Studies / Studia Ekonomiczne i Regionalne 13, no. 3 (September 1, 2020): 328–41. http://dx.doi.org/10.2478/ers-2020-0024.

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SummarySubject and purpose of work: The main purpose of the article is to research the state of grain-product subcomplex of the agro-industrial complex and identify the main trends in its functioning as a prerequisite for the implementation of the external economic potential of Ukraine.Materials and methods: The research used methodical tools for analysis, construction of econometric models, as well as open information sources of the State Statistics Service of Ukraine.Results: A set of factors (independent variables) were determined and the existence of theoretically their relationship with the production profitability of cereals and legumes (dependent variable) was substantiated. The regression equations for the investigated factors dependence were formed. The reliability of the econometric model was proved using Fisher’s criterion and Student’s t-criterion test.Conclusions: To increase the external economic potential of the grain-product subcomplex of the agro-industrial complex, it is advisable to focus on building rational mechanisms for managing the identified determinants of efficiency ensuring of the latter.
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Akbulaev, Nurkhodzha, Basti Aliyeva, and Shehla Rzayeva. "Analysis of the Influence of the Price of Raw Oil and Natural Gas on the Prices of Indices and Shares of the Turkish Stock Exchange." Pénzügyi Szemle = Public Finance Quarterly 66, no. 1 (2021): 151–66. http://dx.doi.org/10.35551/pfq_2021_1_8.

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This article is a review on the impact of prices and their dependence on the cost of oil and natural gas on the world stock markets. The main studies and results achieved in the field of the impact of prices on both the stock index and industrial stocks and the dependence on the level of oil prices are presented. The paper presents an econometric study on the choice of offers on the securities market that allows us to identify the main specifics of changes in prices for the stock index and industrial shares in the daily period from 13. 05. 2012 to 01. 12. 2019. The article uses methods for estimating the impact of the price of natural gas and WTI crude oil using the Gretl statistical program, taking into account the selection of the main correlation features of the price matrix. Of the 13 proposed research models, only one model showed its statistical insignificance. A paired linear model of the CocaCola share price dependence and its dependence on NGFO prices was presented and analyzed in detail. Based on the results of econometric modeling, linear regression models were constructed for the dependence of stock prices on the NGFO and WTISPOT prices. The Gretl environment allows you to evaluate the situation in the econometric environment and make a forecast based on the obtained models of the dependence of stock prices and make appropriate conclusions.
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Feshchur, R. V., N. O. Kolinko, S. V. Shyshkovskyi, and D. I. Skvortsov. "Applied Aspects of Industrial Production Research in Ukraine." Business Inform 4, no. 519 (2021): 73–81. http://dx.doi.org/10.32983/2222-4459-2021-4-73-81.

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Industry is one of the important sectors of the economy of any country in the world. At the same time, statistics show that the industrial complexes of many countries are developing unevenly, with periodic changes in the structure and volume of production under the influence of many internal and external factors. Ukraine's industrial complex is also undergoing spatial and structural distortions, but these trends do not always correspond to those formed in the world's leading countries in the direction and pace of change, although today the industrial complex of Ukraine is the most important structural part of Ukraine's economy, a third of fixed assets and more than 30% of the employed population. As one of the largest spheres of social production in the country, industrial production determines the level of its socio-economic development, the specialization of the economy and the extent of participation in the territorial division of labor. Properly chosen strategy for the development of industrial production, the appropriate volume and structure of production, a reasonable volume of sales allows all participants in production to achieve their financial goals. This is due to the importance of studying the activities of industrial enterprises. The article constructs nonlinear models of multiple regression, which describe the main trends in industrial production, the effect of external and internal factors on the economic performance of industry in general and industrial enterprises in the western region of Ukraine. It is established that innovative transformations in industrial production have led to the renewal of fixed assets and have had a positive effect on the dynamics of economic results. At the same time, this process was accompanied by a reduction in the number of people employed in industry. It is revealed that the influential factors of the external environment include economic conditions of management, and among the factors of the internal environment – the management of innovation and innovation activity of economic entities. It is recommended to expand the set of tools at the expense of distribution-lag, autoregressive, simulative and other econometric models to describe the relationship between the economic performance of enterprises and factor characteristics.
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Lam, Ka Chi, and Olalekan Shamsideen Oshodi. "Using Univariate Models for Construction Output Forecasting: Comparing Artificial Intelligence and Econometric Techniques." Journal of Management in Engineering 32, no. 6 (November 2016): 04016021. http://dx.doi.org/10.1061/(asce)me.1943-5479.0000462.

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Dissertations / Theses on the topic "Research, Industrial – Econometric models"

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Papa, Gianluca. "Essays on econometrics of panel data and treatment models." Doctoral thesis, Universite Libre de Bruxelles, 2013. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209408.

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In this thesis, I apply the sophisticated tools made available by the econometrics of panel data and treatment models to a range of different issues. In the first Chapter, an ECM model is used to test on the existence of financing constraints in firms’ investment and R&D, taken a proxy for the efficiency of market institutions and governance rules in different countries. In the second chapter we test an agency model linking pay-performance contracts of CEOS to the financial situation of a firm by using a UK panel data. In the third chapter I use a sophisticated treatment model to evaluate the effectiveness of Italian public subsidies to R&D. Finally, in the fourth chapter I try to evaluate the efficiency of Italian regional systems of public healthcare by controlling for socio-economic factors and quality of healthcare in a composite model using panel data estimation and efficient frontier techniques.

The first Chapter analyzes the investment behavior of a sample of R&D intensive firms which are quoted on the stock market from USA, UK and Japan for the period 1990-1998. By using an error correction model we test the elasticity of investment and R&D to cash flow in these countries to see by which measure different market institutions and corporate governance rules affects the cost of external financing. Contrary to previous studies, we find significant differences in the sensitivity to cash flow of the two types of investment, with R&D expenditure being much less sensitive than ordinary investment. This is not surprising given the more long-term nature of R&D expenditures. For what concerns the comparison between the different systems/countries, the USA stock markets confirms as the most efficient market providing outside financing at a much lower cost compared to other markets, especially for young, smaller firms.

The second Chapter is a joint work with Biagio Speciale. It uses the data on a panel of quoted UK firms over the period 1995–2002 to study the effects of financial leverage on managerial compensation. The change in the investors’ expectations that caused the recent collapse of the stock market tech bubble is a perfect example of natural experiment that has been used as a source of plausibly exogenous variation in the firm’s debt. The estimates show that pay-for-performance sensitivity is increasing in financial leverage, with the exception of the 10% most levered firms, giving rise at the end to a non-linear (inverted U-shape) relationship between the two variables. The chapter includes also a theoretical model accounting for this relationship where an higher leverage increases both the expected returns and the expected variance of investment returns: the first effect (determining increased pay-performance sensitivity) prevails for low leverage values and the second effect (determining decreased pay-performance sensitivity) prevails for high leverage values.

The third Chapter undertakes an empirical estimation of the additionality of public funding on both the propensity to initiate R&D activity and the intensity of R&D spending of Italian enterprises for the period 1998-2000, using data from the Third Community Innovation Survey and from firms' financial accounts. The chosen methodology (Endogenous Switching Type II-Tobit) takes into account the possibility that decisions about both starting an R&D activity (sample selection effect) and applying for/obtaining public funding (essential heterogeneity) are influenced by private knowledge of enterprises' idiosyncratic propensities in R&D spending. The present analysis shows that both these effects are indeed important and that they contribute to explain most of the additionality found with less sophisticated models.

The fourth Chapter investigates the underlying causes of variability of public health expenditure per capita (SSPC henceforth) between Italian regions. A fixed-effect panel data estimate on the SSPC (for the period 1997-2006) is used in the first part of the paper to account for regional differences in terms of physical, demographic, socio-economic characteristics and in terms of other variables that affect demand and supply of health services. In the second part, we take the ‘adjusted’ SSPC and proceed to estimate an "efficient production function" of the quality of health services through Data Envelopment Analysis. This procedure allows us to separate the share of expenditure used for the improvement of the quality from the one that can be traced only to an inefficient use of financial resources. A comparison of regional SSPC after factoring out the socio-economic factors and the quality of healthcare shows that big differences still remain and are even exacerbated, signalling big pockets of inefficiency and correspondingly a huge potential for cost savings. Finally, a preliminary analysis shows a positive correlation between the efficiency of regional public spending in healthcare and the level of social capital.
Doctorat en Sciences économiques et de gestion
info:eu-repo/semantics/nonPublished

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Ngomba, Peter Njoh. "The developmental impact of public investment in education, science and technology in Cameroon, 1960-1980 /." Thesis, McGill University, 1987. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=75784.

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Linking education, science and technology with national development is a subject of increasing concern in many developing countries. In this dissertation, we have studied empirically the contribution, or lack of it, which public investment in education, science and technology has made to the attainment of development objectives in Cameroon since 1960. Using a small computable macroeconometric model of Cameroon incorporating some major relevant quantitative aspects of the knowledge sector, we have investigated the effects on that sector and on the overall economic system of increased education- and research-service resources. We have also analyzed some of the major qualitative factors that are important in this sector.
Our results suggest that, given existing patterns of education, science and technology in Cameroon, the contribution of public investment in this sector may be small compared to the potential contribution suggested in the literature. The implications of these results are examined for policy-making and planning at the national level.
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Bhuiyan, Farina. "Dynamic models of concurrent engineering processes and performance." Thesis, McGill University, 2001. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=38153.

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Mathematical and stochastic computer models were built to simulate concurrent engineering processes (CE) in order to study how different process mechanisms contribute to new product development (NPD) performance. Micro-models of various phenomena which occur in concurrent engineering processes, such as functional participation, overlapping, decision-making, rework, and learning, were included, and their effects on the overall NPD process were related to process span time and effort. The study focused on determining under what conditions CE processes are more favorable than sequential processes, in terms of expected payoff, span time, and effort, as dependent variables of functional participation and overlapping, and the corresponding trade-offs between more upfront effort versus span time reduction.
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Lillis, Anne M. "Customer costing responsiveness - an analytical framework." Melbourne, Vic. : University of Melbourne, Dept. of Accounting and Business Information Systems, 2002. http://wff2.ecom.unimelb.edu.au/accwww/research/papers/0202%20ALillis&MAAbernethy.pdf.

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"January 2002" Includes bibliographical references: (p. 31-34). The primary purpose of this study is to develop a framework for identifying the primary drivers of the costs of being customer responsive. The authors' aim is to develop an understanding of the causal drivers of the costs of responsiveness as these costs are considered to be an important input to strategic and tactical decisions. In developing this framework, the paper links the characteristics of responsive manufacturing from the operations management literature with the insights from studies in the accounting literature relating to the drivers of cost. The paper attempts to model the cost impact when a firm responds to ad hoc demands involving the product customization, variation in product mix, or changes to delivery schedules. The costs emerge as a function of the type of responsiveness and the resource capacity management strategy implemented by the firm. The magnitude and dynamics of market demands and firm response, as well as the inherent flexibility of the firm's resources are seen as influencing the magnitude of the costs of responsiveness. disper
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Kummerow, Max F. "A paradigm of inquiry for applied real estate research : integrating econometric and simulation methods in time and space specific forecasting models : Australian office market case study." Thesis, Curtin University, 1997. http://hdl.handle.net/20.500.11937/1574.

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Office space oversupply cost Australia billions of dollars during the 1990-92 recession. Australia, the United States, Japan, the U.K., South Africa, China, Thailand, and many other countries have suffered office oversupply cycles. Illiquid untenanted office buildings impair investors capital and cash flows, with adverse effects on macroeconomics, financial institutions, and individuals. This study aims to develop improved methods for medium term forecasting of office market adjustments to inform individual project development decisions and thereby to mitigate office oversupply cycles. Methods combine qualitative research, econometric estimation, system dynamics simulation, and institutional economics. This research operationalises a problem solving research paradigm concept advocated by Ken Lusht. The research is also indebted to the late James Graaskamp, who was successful in linking industry and academic research through time and space specific feasibility studies to inform individual property development decisions. Qualitative research and literature provided a list of contributing causes of office oversupply including random shocks, faulty forecasting methods, fee driven deals, prisoners dilemma game, system dynamics (lags and adjustment times), land use regulation, and capital market issues. Rather than choosing among these, they are all considered to be causal to varying degrees. Moreover, there is synergy between combinations of these market imperfections. Office markets are complex evolving human designed systems (not time invariant) so each cycle has unique historical features. Data on Australian office markets were used to estimate office rent adjustment equations. Simulation models in spreadsheet and system dynamics software then integrate additional information with the statistical results to produce demand, supply, and rent forecasts. Results include models for rent forecasting and models for analysis related to policy and system redesign. The dissertation ends with two chapters on institutional reforms whereby better information might find application to improve market efficiency.Keywords. Office rents, rent adjustment, office market modelling, forecasting, system dynamics.
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Vickers, John. "Patent races and market structure." Thesis, University of Oxford, 1985. http://ora.ox.ac.uk/objects/uuid:9e3df3d2-b58a-48cc-b639-78c7c48bd3cd.

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This thesis is a theoretical study of relationships between patent races and market structure. The outcome of a patent race can be an important determinant of market structure. For example, whether or not a new firm enters a market may depend upon its winning a patent race against an incumbent firm already in that market. Moreover, market structure can be a major influence upon competition in a patent race. In the example, the asymmetry between incumbent and potential entrant has an effect upon their respective incentives in the patent race. Chapter I discusses models of R and D with uncertainty. We show that, as the degree of correlation between the uncertainties facing rival firms increases, R and D efforts increase under some, but not all, conditions, and the number of active competitors falls. Chapter II discusses the approach of representing patent races as bidding games. We examine a model in which several incumbent firms compete with a number of potential entrants in a patent race, and ask whether the incumbents have an incentive to form a joint venture to deter entry. They do so if and only if the patent does not offer a major cost improvement. In Chapter III we examine the strategic interactions between competitors during the course of a race, in an attempt to clarify (for different types of race) the idea that a race degenerates when one player becomes 'far enough ahead' of his rivals, in a sense made precise. In Chapter IV we examine the evolution of market structure in a duopoly model when there is a sequence of patent races. The nature of competition in the product market is shown to determine whether one firm becomes increasingly dominant as industry leader, or whether there is 'action - reaction' between firms.
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Mitwasi, Mousa George. "Mathematical models for the deterministic, capacitated, single kanban system." Diss., The University of Arizona, 1991. http://hdl.handle.net/10150/185523.

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The kanban system is the most popular technique for implementing the Just-In-Time philosophy. In this dissertation we develop mathematical models for the deterministic, capacitated, single kanban system. Three different production structures are studied. The models are used to analyze the system, understand the need and behavior of kanbans, and compute good solutions for the number of kanbans to allocate for each part. The first model applies to the single-stage, single-item system. Optimal solutions for the number of kanbans for this system are developed. The second and third models are built for the multi-stage, single-item system and the single-stage, multi-item system respectively. Necessary and sufficient conditions for the feasibility of a set of kanbans are developed for the last two models. The conditions are used to develop heuristic and optimal solution procedures. The heuristic procedures are tested over randomly generated problems and are shown to perform very well compared to the optimal solution procedures.
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Yapo, Patrice Ogou 1967. "A multiobjective global optimization algorithm with application to calibration of hydrologic models." Diss., The University of Arizona, 1996. http://hdl.handle.net/10150/290649.

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This dissertation presents a new multiple objective optimization algorithm that is capable of solving for the entire Pareto set in one single optimization run. The multi-objective complex evolution (MOCOM-UA) procedure is based on the following three concepts: (1) population, (2) rank-based selection, and (3) competitive evolution. In the MOCOM-UA algorithm, a population of candidate solutions is evolved in the feasible space to search for the Pareto set. Ranking of the population is accomplished through Pareto Ranking, where all points are successively placed on different Pareto fronts. Competitive evolution consists of selecting subsets of points (including all worst points in the population) based on their ranks and moving the worst points toward the Pareto set using the newly developed multi-objective simplex (MOSIM) procedure. Test analysis on the MOCOM-UA algorithm is accomplished on mathematical problems of increasing complexity and based on a bi-criterion measure of performance. The two performance criteria used are (1) efficiency, as measured by the ability of the algorithm to converge quickly and (2) effectiveness, as measured by the ability of the algorithm to locate the Pareto set. Comparison of the MOCOM-UA algorithm against three multi-objective genetic algorithms (MOGAs) favors the former. In a realistic application, the MOCOM-UA algorithm is used to calibrate the Soil Moisture Accounting model of the National Weather Service River Forecasting Systems (NWSRFS-SMA). Multi-objective calibration of this model is accomplished using two bi-criterion objective functions, namely the Daily Root Mean Square-Heteroscedastic Maximum Likelihood Estimator (DRMS, HMLE) and rising limb-falling limb (RISE, FALL) objective functions. These two multi-objective calibrations provide some interesting insights into the influence of different objectives in the location of final parameter values as well as limitations in the structure of the NWSRFS-SMA model.
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Qureshi, Muhammad Akber 1964. "Construction and solution of Markov reward models." Diss., The University of Arizona, 1996. http://hdl.handle.net/10150/290583.

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Stochastic Petri nets (SPNs) and extensions are a popular method for evaluating a wide variety of systems. In most cases, the interesting measures regarding the system's characteristics can be defined at the net level by means of reward variables. Depending on the measures, these net-level reward models are solved either by first generating a state-level reward model or by directly generating paths from the net-level description. In this thesis, we propose algorithms for the generation of state-level reward models as well as for directly obtaining solutions from net-level reward models when the net-level reward models are specified as stochastic activity networks (SANs) with "step-based reward structure." Moreover, we propose algorithms for computing the expected value and the probability distribution function of a reward variable at specified time instants, and for computing the probability distribution function of reward accumulated during a finite interval. The interval may correspond to the mission period in a mission-critical system, the time between scheduled maintenances, or a warranty period; whereas the time instants may be critical instances during these intervals. The proposed algorithms avoid the construction of state-level representations and the memory growth problems experienced when applying previous approaches to large models. Furthermore, we study the effect of workload on the availability and response time of voting algorithms. Voting algorithms are a popular way to provide data consistency in replicated data systems. Many models have been made to study the degree to which replication increases the availability of data, and some have been made to study the cost incurred in maintaining consistency. However, little work has been done to evaluate the time it takes to serve request, accounting for server and network failures, or to determine the effect of workload on these measures. In this thesis, we use stochastic activity networks (SANs) to study the effect of work load on availability and mean response time of two variant models of a replicated file system to maintain data consistency, one using a static voting algorithm, the other using a dynamic voting algorithm.
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Kummerow, Max F. "A paradigm of inquiry for applied real estate research : integrating econometric and simulation methods in time and space specific forecasting models : Australian office market case study." Curtin University of Technology, School of Economics and Finance, 1997. http://espace.library.curtin.edu.au:80/R/?func=dbin-jump-full&object_id=11274.

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Office space oversupply cost Australia billions of dollars during the 1990-92 recession. Australia, the United States, Japan, the U.K., South Africa, China, Thailand, and many other countries have suffered office oversupply cycles. Illiquid untenanted office buildings impair investors capital and cash flows, with adverse effects on macroeconomics, financial institutions, and individuals. This study aims to develop improved methods for medium term forecasting of office market adjustments to inform individual project development decisions and thereby to mitigate office oversupply cycles. Methods combine qualitative research, econometric estimation, system dynamics simulation, and institutional economics. This research operationalises a problem solving research paradigm concept advocated by Ken Lusht. The research is also indebted to the late James Graaskamp, who was successful in linking industry and academic research through time and space specific feasibility studies to inform individual property development decisions. Qualitative research and literature provided a list of contributing causes of office oversupply including random shocks, faulty forecasting methods, fee driven deals, prisoners dilemma game, system dynamics (lags and adjustment times), land use regulation, and capital market issues. Rather than choosing among these, they are all considered to be causal to varying degrees. Moreover, there is synergy between combinations of these market imperfections. Office markets are complex evolving human designed systems (not time invariant) so each cycle has unique historical features. Data on Australian office markets were used to estimate office rent adjustment equations. Simulation models in spreadsheet and system dynamics software then integrate additional information with the statistical results to produce demand, supply, and rent forecasts. Results include ++
models for rent forecasting and models for analysis related to policy and system redesign. The dissertation ends with two chapters on institutional reforms whereby better information might find application to improve market efficiency.Keywords. Office rents, rent adjustment, office market modelling, forecasting, system dynamics.
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Books on the topic "Research, Industrial – Econometric models"

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Jovanovic, Boyan. Research and productivity. Cambridge, MA: National Bureau of Economic Research, 1995.

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Crépon, Bruno. Research, innovation, and productivity: An econometric analysis at the firm level. Cambridge, MA: National Bureau of Economic Research, 1998.

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Mairesse, Jacques. Estimating the productivity of research and development: An exploration of GMM methods using data on French and United States manufacturing firms. Cambridge, MA: National Bureau of Economic Research, 1996.

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Bond, Stephen. Corporate R & D and productivity in Germany and the United Kingdom. [London]: Centre for Economic Performance, London School of Economics and Political Science, 2003.

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Hall, Bronwyn H. Exploring the relationship between R&D and productivity in French manufacturing firms. Cambridge, MA: National Bureau of Economic Research, 1992.

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Lichtenberg, Frank R. R&D investment and international productivity differences. Cambridge, MA: National Bureau of Economic Research, 1992.

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Coe, David T. International R&D spillovers. Cambridge, MA: National Bureau of Economic Research, 1993.

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Adams, J. D. Bounding the effects of R&D: An investigation using matched establishment-firm data. Cambridge, MA: National Bureau of Economic Research, 1996.

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Branstetter, Lee. Japanese research consortia: A microeconometric analysis of industrial policy. Cambridge, MA: National Bureau of Economic Research, 1997.

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Jones, Charles I. Too much of a good thing?: The economics of investment in R&D. Cambridge, MA: National Bureau of Economic Research, 1999.

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Book chapters on the topic "Research, Industrial – Econometric models"

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Brodie, Roderick J., Peter J. Danaher, V. Kumar, and Peter S. H. Leeflang. "Econometric Models for Forecasting Market Share." In International Series in Operations Research & Management Science, 597–611. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/978-0-306-47630-3_27.

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Lacombe, Donald J., and Stuart G. McIntyre. "Hierarchical Spatial Econometric Models in Regional Science." In Regional Research Frontiers - Vol. 2, 151–67. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-50590-9_9.

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Manning, W. G. "Alternative econometric models of alcohol demand." In The science of prevention: Methodological advances from alcohol and substance abuse research., 101–21. Washington: American Psychological Association, 1997. http://dx.doi.org/10.1037/10222-004.

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Seo, S. Niggol. "Econometric Models of Yield Changes with Weather Shocks." In Advances in Global Change Research, 59–66. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-15946-1_5.

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Kim, Soon-Gwan, and Fred L. Mannering. "Panel Data and Activity Duration Models: Econometric Alternatives and Applications." In Transportation Research, Economics and Policy, 349–73. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4757-2642-8_14.

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Tan, Raymond R., Kathleen B. Aviso, Michael Angelo B. Promentilla, Krista Danielle S. Yu, and Joost R. Santos. "Future Research Prospects for Input–Output Models." In Lecture Notes in Management and Industrial Engineering, 139–43. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1873-3_10.

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Gadyatskaya, Olga, and Rolando Trujillo-Rasua. "New Directions in Attack Tree Research: Catching up with Industrial Needs." In Graphical Models for Security, 115–26. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-74860-3_9.

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Richter, Alexander, and Marion Steven. "On the Relation Between Industrial Product-Service Systems and Business Models." In Operations Research Proceedings 2008, 97–102. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-00142-0_16.

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Zholtkevych, G. N., K. V. Nosov, Yu G. Bespalov, L. I. Rak, E. V. Vysotskaya, Y. B. Balkova, and V. K. Kolomiychenko. "Descriptive Models of System Dynamics." In Information and Communication Technologies in Education, Research, and Industrial Applications, 97–114. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-69965-3_6.

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Alobaidi, Mizal, Andriy Batyiv, and Grygoriy Zholtkevych. "Abstract Quantum Automata as Formal Models of Quantum Information Processing Systems." In ICT in Education, Research, and Industrial Applications, 19–38. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35737-4_2.

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Conference papers on the topic "Research, Industrial – Econometric models"

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Xin, Tong, Li Xuesen, and Tong Lin. "How can industrial structure affect carbon emissions: Facilitating or inhibiting? Research based on spatial panel econometric models: Direct effects and spatial spillover." In 2018 Chinese Control And Decision Conference (CCDC). IEEE, 2018. http://dx.doi.org/10.1109/ccdc.2018.8407376.

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Tay, C. "Econometric Models to Estimate the Impact of Social Media Platforms On E-commerce: Pre- and Post- COVID." In 2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). IEEE, 2021. http://dx.doi.org/10.1109/ieem50564.2021.9672899.

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Kunyang, Wan, and Yu Shujuan. "University Knowledge Spillover and Large & Medium-sized Industrial Enterprises New Products Development: Spatial Econometric Models Based on Panel Data." In 2010 International Conference on Information Management, Innovation Management and Industrial Engineering (ICIII). IEEE, 2010. http://dx.doi.org/10.1109/iciii.2010.402.

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Frischknecht, Bart, Katie Whitefoot, and Panos Papalambros. "Methods for Evaluating Suitability of Econometric Demand Models in Design for Market Systems." In ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/detc2009-87165.

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This paper articulates some of the challenges for what has been an implicit goal of design for market systems research: To predict demand for differentiated products so that counterfactual experiments can be performed based on changes to the product design (i.e., attributes). We present a set of methods for examining econometric models of consumer demand for their suitability in product design studies. We use these methods to test the hypothesis that automotive demand models that allow for nonlinear horizontal differentiation perform better than the conventional functional forms, which emphasize vertical differentiation. We estimate these two forms of consumer demand in the new vehicle automotive market, and find that using an ideal-point model of size preference rather than a monotonic model has model fit but different attribute substitution patterns. The generality of the evaluation methods and the range of demand model issues to be explored in future research are highlighted.
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Adámek, Pavel, and Lucie Meixnerová. "Changes and Adaptations of Business Models Caused by the Crisis Scenario." In Seventh International Scientific-Business Conference LIMEN Leadership, Innovation, Management and Economics: Integrated Politics of Research. Association of Economists and Managers of the Balkans, Belgrade, Serbia, 2021. http://dx.doi.org/10.31410/limen.s.p.2021.9.

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Due to the fast-changing environment caused by the impact of the pandemic, a response to companies’ behavior is inevitable. These pan­demic crisis scenario triggers searching for changes, adjustment, and adap­tation of business models to seek new opportunities for competitive advan­tage. Therefore, the paper aims to analyze, identify and evaluate the impact of a pandemic on a firm´s business model, specifically to changes in its busi­ness elements. The research methodology applies a statistical apparatus mainly the Mann-Whitney U test, using the econometric software EViews for identifying the significance of individual business model elements within national economy sectors and branches before the pandemic and the cur­rent post-pandemic crisis. Data were obtained from 173 Czech and Slovak companies’ owners (executives). The findings represent the perception and view of businesses on the current post-pandemic crisis and their priorities changes in specific elements of business model
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Asensio, Omar Isaac, Daniel J. Marchetto, Sooji Ha, and Sameer Dharur. "Extracting User Behavior at Electric Vehicle Charging Stations with Transformer Deep Learning Models." In CARMA 2020 - 3rd International Conference on Advanced Research Methods and Analytics. Valencia: Universitat Politècnica de València, 2020. http://dx.doi.org/10.4995/carma2020.2020.11613.

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Mobile applications have become widely popular for their ability to access real-time information. In electric vehicle (EV) mobility, these applications are used by drivers to locate charging stations in public spaces, pay for charging transactions, and engage with other users. This activity generates a rich source of data about charging infrastructure and behavior. However, an increasing share of this data is stored as unstructured text—inhibiting our ability to interpret behavior in real-time. In this article, we implement recent transformer-based deep learning algorithms, BERT and XLnet, that have been tailored to automatically classify short user reviews about EV charging experiences. We achieve classification results with a mean accuracy of over 91% and a mean F1 score of over 0.81 allowing for more precise detection of topic categories, even in the presence of highly imbalanced data. Using these classification algorithms as a pre-processing step, we analyze a U.S. national dataset with econometric methods to discover the dominant topics of discourse in charging infrastructure. After adjusting for station characteristics and other factors, we find that the functionality of a charging station is the dominant topic among EV drivers and is more likely to be discussed at points-of-interest with negative user experiences.
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Chen, Guiliang, and Yongheng Li. "Comparison Research on Bottom-up Visual Attention Models." In 2015 International Conference on Industrial Technology and Management Science. Paris, France: Atlantis Press, 2015. http://dx.doi.org/10.2991/itms-15.2015.131.

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Peng, Yan, and Yuan Zhao. "Comparative research on operation models of reverse logistics." In 2015 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). IEEE, 2015. http://dx.doi.org/10.1109/ieem.2015.7385698.

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Ramczyk, Marek. "Application of Econometric Model for Water Economy Management." In Environmental Engineering. VGTU Technika, 2017. http://dx.doi.org/10.3846/enviro.2017.042.

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The econometric model can be a precise instrument for the analysis of the impact of the natural environmental degradation on the fishing economy. This paper aims at analysing the influence of the water quality changes in Charzykowskie Lake on the fishing economy. The economic-ecological models have been constructed, explaining the changes of economic effects of the lake fishery in the conditions of an increasing water pollution in the hypolimnion on the example of the catch of Rutilus rutilus, Blicca bjoerkna, Coregonus lavaretus, Anguilla anguilla and Esox lucius in Charzykowskie Lake. Performed empirical research focuses on the influence of the environmental factors on the size of fish catch. Calculations and analysis show clearly that even though the habitat factors have an influence on the catch size of each studied fish species, they do it with different intensity and in various combinations. Both, lake water quality and climate factors changes, cause measurable effects on fishing industry of Charzykowskie Lake. Among the examined Rutilus rutilus and Blicca bjoerkna, Blicca bjoerkna has the highest high environmental requirements regarding the water quality. Empirical calculations showed as well that Coregonus lavaretus has considerably higher water cleanness requirements than Rutilus rutilus and Blicca bjoerkna. While considering Rutilus rutilus and Blicca bjoerkna, most water characteristics still rather stimulate a development of these species, but when it comes to Coregonus lavaretus, in general they suppress its development. The model has also proved quite high habitat requirements for Anquilla anquilla and correctness of the thesis that Esox lucius avoids polluted water. Climatic factors influence is significant for the endogenous variables. The above prejudges the itineration of Rutilus rutilus, Blicca bjoerkna, Coregonus lavaretus, Anquilla anquilla and Esox lucius catch in Charzykowskie Lake. The results of the modelling can be used in managing the fishing economy of the lake.
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Srivichitranond, Sarunyoo, and Ryosuke Saga. "Comparison of Neural Network Models for LDA Inferring." In 2022 7th International Conference on Business and Industrial Research (ICBIR). IEEE, 2022. http://dx.doi.org/10.1109/icbir54589.2022.9786386.

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Reports on the topic "Research, Industrial – Econometric models"

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Hlushak, Oksana M., Svetlana O. Semenyaka, Volodymyr V. Proshkin, Stanislav V. Sapozhnykov, and Oksana S. Lytvyn. The usage of digital technologies in the university training of future bachelors (having been based on the data of mathematical subjects). [б. в.], July 2020. http://dx.doi.org/10.31812/123456789/3860.

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This article demonstrates that mathematics in the system of higher education has outgrown the status of the general education subject and should become an integral part of the professional training of future bachelors, including economists, on the basis of intersubject connection with special subjects. Such aspects as the importance of improving the scientific and methodological support of mathematical training of students by means of digital technologies are revealed. It is specified that in order to implement the task of qualified training of students learning econometrics and economic and mathematical modeling, it is necessary to use digital technologies in two directions: for the organization of electronic educational space and in the process of solving applied problems at the junction of the branches of economics and mathematics. The advantages of using e-learning courses in the educational process are presented (such as providing individualization of the educational process in accordance with the needs, characteristics and capabilities of students; improving the quality and efficiency of the educational process; ensuring systematic monitoring of the educational quality). The unified structures of “Econometrics”, “Economic and mathematical modeling” based on the Moodle platform are the following ones. The article presents the results of the pedagogical experiment on the attitude of students to the use of e-learning course (ELC) in the educational process of Borys Grinchenko Kyiv University and Alfred Nobel University (Dnipro city). We found that the following metrics need improvement: availability of time-appropriate mathematical materials; individual approach in training; students’ self-expression and the development of their creativity in the e-learning process. The following opportunities are brought to light the possibilities of digital technologies for the construction and research of econometric models (based on the problem of dependence of the level of the Ukrainian population employment). Various stages of building and testing of the econometric model are characterized: identification of variables, specification of the model, parameterization and verification of the statistical significance of the obtained results.
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Mathew, Sonu, Srinivas S. Pulugurtha, and Sarvani Duvvuri. Modeling and Predicting Geospatial Teen Crash Frequency. Mineta Transportation Institute, June 2022. http://dx.doi.org/10.31979/mti.2022.2119.

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This research project 1) evaluates the effect of road network, demographic, and land use characteristics on road crashes involving teen drivers, and, 2) develops and compares the predictability of local and global regression models in estimating teen crash frequency. The team considered data for 201 spatially distributed road segments in Mecklenburg County, North Carolina, USA for the evaluation and obtained data related to teen crashes from the Highway Safety Information System (HSIS) database. The team extracted demographic and land use characteristics using two different buffer widths (0.25 miles and 0.5 miles) at each selected road segment, with the number of crashes on each road segment used as the dependent variable. The generalized linear models with negative binomial distribution (GLM-based NB model) as well as the geographically weighted negative binomial regression (GWNBR) and geographically weighted negative binomial regression model with global dispersion (GWNBRg) were developed and compared. This research relied on data for 147 geographically distributed road segments for modeling and data for 49 segments for validation. The annual average daily traffic (AADT), light commercial land use, light industrial land use, number of household units, and number of pupils enrolled in public or private high schools are significant explanatory variables influencing the teen crash frequency. Both methods have good predictive capabilities and can be used to estimate the teen crash frequency. However, the GWNBR and GWNBRg better capture the spatial dependency and spatial heterogeneity among road teen crashes and the associated risk factors.
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Kim, Changmo, Ghazan Khan, Brent Nguyen, and Emily L. Hoang. Development of a Statistical Model to Predict Materials’ Unit Prices for Future Maintenance and Rehabilitation in Highway Life Cycle Cost Analysis. Mineta Transportation Institute, December 2020. http://dx.doi.org/10.31979/mti.2020.1806.

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The main objectives of this study are to investigate the trends in primary pavement materials’ unit price over time and to develop statistical models and guidelines for using predictive unit prices of pavement materials instead of uniform unit prices in life cycle cost analysis (LCCA) for future maintenance and rehabilitation (M&R) projects. Various socio-economic data were collected for the past 20 years (1997–2018) in California, including oil price, population, government expenditure in transportation, vehicle registration, and other key variables, in order to identify factors affecting pavement materials’ unit price. Additionally, the unit price records of the popular pavement materials were categorized by project size (small, medium, large, and extra-large). The critical variables were chosen after identifying their correlations, and the future values of each variable were predicted through time-series analysis. Multiple regression models using selected socio-economic variables were developed to predict the future values of pavement materials’ unit price. A case study was used to compare the results between the uniform unit prices in the current LCCA procedures and the unit prices predicted in this study. In LCCA, long-term prediction involves uncertainties due to unexpected economic trends and industrial demand and supply conditions. Economic recessions and a global pandemic are examples of unexpected events which can have a significant influence on variations in material unit prices and project costs. Nevertheless, the data-driven scientific approach as described in this research reduces risk caused by such uncertainties and enables reasonable predictions for the future. The statistical models developed to predict the future unit prices of the pavement materials through this research can be implemented to enhance the current LCCA procedure and predict more realistic unit prices and project costs for the future M&R activities, thus promoting the most cost-effective alternative in LCCA.
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Guidati, Gianfranco, and Domenico Giardini. Joint synthesis “Geothermal Energy” of the NRP “Energy”. Swiss National Science Foundation (SNSF), February 2020. http://dx.doi.org/10.46446/publication_nrp70_nrp71.2020.4.en.

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Near-to-surface geothermal energy with heat pumps is state of the art and is already widespread in Switzerland. In the future energy system, medium-deep to deep geothermal energy (1 to 6 kilometres) will, in addition, play an important role. To the forefront is the supply of heat for buildings and industrial processes. This form of geothermal energy utilisation requires a highly permeable underground area that allows a fluid – usually water – to absorb the naturally existing rock heat and then transport it to the surface. Sedimentary rocks are usually permeable by nature, whereas for granites and gneisses permeability must be artificially induced by injecting water. The heat gained in this way increases in line with the drilling depth: at a depth of 1 kilometre, the underground temperature is approximately 40°C, while at a depth of 3 kilometres it is around 100°C. To drive a steam turbine for the production of electricity, temperatures of over 100°C are required. As this requires greater depths of 3 to 6 kilometres, the risk of seismicity induced by the drilling also increases. Underground zones are also suitable for storing heat and gases, such as hydrogen or methane, and for the definitive storage of CO2. For this purpose, such zones need to fulfil similar requirements to those applicable to heat generation. In addition, however, a dense top layer is required above the reservoir so that the gas cannot escape. The joint project “Hydropower and geo-energy” of the NRP “Energy” focused on the question of where suitable ground layers can be found in Switzerland that optimally meet the requirements for the various uses. A second research priority concerned measures to reduce seismicity induced by deep drilling and the resulting damage to buildings. Models and simulations were also developed which contribute to a better understanding of the underground processes involved in the development and use of geothermal resources. In summary, the research results show that there are good conditions in Switzerland for the use of medium-deep geothermal energy (1 to 3 kilometres) – both for the building stock and for industrial processes. There are also grounds for optimism concerning the seasonal storage of heat and gases. In contrast, the potential for the definitive storage of CO2 in relevant quantities is rather limited. With respect to electricity production using deep geothermal energy (> 3 kilometres), the extent to which there is potential to exploit the underground economically is still not absolutely certain. In this regard, industrially operated demonstration plants are urgently needed in order to boost acceptance among the population and investors.
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Zhang, Renduo, and David Russo. Scale-dependency and spatial variability of soil hydraulic properties. United States Department of Agriculture, November 2004. http://dx.doi.org/10.32747/2004.7587220.bard.

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Water resources assessment and protection requires quantitative descriptions of field-scale water flow and contaminant transport through the subsurface, which, in turn, require reliable information about soil hydraulic properties. However, much is still unknown concerning hydraulic properties and flow behavior in heterogeneous soils. Especially, relationships of hydraulic properties changing with measured scales are poorly understood. Soil hydraulic properties are usually measured at a small scale and used for quantifying flow and transport in large scales, which causes misleading results. Therefore, determination of scale-dependent and spatial variability of soil hydraulic properties provides the essential information for quantifying water flow and chemical transport through the subsurface, which are the key processes for detection of potential agricultural/industrial contaminants, reduction of agricultural chemical movement, improvement of soil and water quality, and increase of agricultural productivity. The original research objectives of this project were: 1. to measure soil hydraulic properties at different locations and different scales at large fields; 2. to develop scale-dependent relationships of soil hydraulic properties; and 3. to determine spatial variability and heterogeneity of soil hydraulic properties as a function of measurement scales. The US investigators conducted field and lab experiments to measure soil hydraulic properties at different locations and different scales. Based on the field and lab experiments, a well-structured database of soil physical and hydraulic properties was developed. The database was used to study scale-dependency, spatial variability, and heterogeneity of soil hydraulic properties. An improved method was developed for calculating hydraulic properties based on infiltration data from the disc infiltrometer. Compared with the other methods, the proposed method provided more accurate and stable estimations of the hydraulic conductivity and macroscopic capillary length, using infiltration data collected atshort experiment periods. We also developed scale-dependent relationships of soil hydraulic properties using the fractal and geostatistical characterization. The research effort of the Israeli research team concentrates on tasks along the second objective. The main accomplishment of this effort is that we succeed to derive first-order, upscaled (block effective) conductivity tensor, K'ᵢⱼ, and time-dependent dispersion tensor, D'ᵢⱼ, i,j=1,2,3, for steady-state flow in three-dimensional, partially saturated, heterogeneous formations, for length-scales comparable with those of the formation heterogeneity. Numerical simulations designed to test the applicability of the upscaling methodology to more general situations involving complex, transient flow regimes originating from periodic rain/irrigation events and water uptake by plant roots suggested that even in this complicated case, the upscaling methodology essentially compensated for the loss of sub-grid-scale variations of the velocity field caused by coarse discretization of the flow domain. These results have significant implications with respect to the development of field-scale solute transport models capable of simulating complex real-world scenarios in the subsurface, and, in turn, are essential for the assessment of the threat posed by contamination from agricultural and/or industrial sources.
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Atkinson, Dan, and Alex Hale, eds. From Source to Sea: ScARF Marine and Maritime Panel Report. Society of Antiquaries of Scotland, September 2012. http://dx.doi.org/10.9750/scarf.09.2012.126.

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The main recommendations of the panel report can be summarised under four headings: 1. From Source to Sea: River systems, from their source to the sea and beyond, should form the focus for research projects, allowing the integration of all archaeological work carried out along their course. Future research should take a holistic view of the marine and maritime historic environment, from inland lakes that feed freshwater river routes, to tidal estuaries and out to the open sea. This view of the landscape/seascape encompasses a very broad range of archaeology and enables connections to be made without the restrictions of geographical or political boundaries. Research strategies, programmes From Source to Sea: ScARF Marine and Maritime Panel Report iii and projects can adopt this approach at multiple levels; from national to site-specific, with the aim of remaining holistic and cross-cutting. 2. Submerged Landscapes: The rising research profile of submerged landscapes has recently been embodied into a European Cooperation in Science and Technology (COST) Action; Submerged Prehistoric Archaeology and Landscapes of the Continental Shelf (SPLASHCOS), with exciting proposals for future research. Future work needs to be integrated with wider initiatives such as this on an international scale. Recent projects have begun to demonstrate the research potential for submerged landscapes in and beyond Scotland, as well as the need to collaborate with industrial partners, in order that commercially-created datasets can be accessed and used. More data is required in order to fully model the changing coastline around Scotland and develop predictive models of site survival. Such work is crucial to understanding life in early prehistoric Scotland, and how the earliest communities responded to a changing environment. 3. Marine & Maritime Historic Landscapes: Scotland’s coastal and intertidal zones and maritime hinterland encompass in-shore islands, trans-continental shipping lanes, ports and harbours, and transport infrastructure to intertidal fish-traps, and define understanding and conceptualisation of the liminal zone between the land and the sea. Due to the pervasive nature of the Marine and Maritime historic landscape, a holistic approach should be taken that incorporates evidence from a variety of sources including commercial and research archaeology, local and national societies, off-shore and onshore commercial development; and including studies derived from, but not limited to history, ethnology, cultural studies, folklore and architecture and involving a wide range of recording techniques ranging from photography, laser imaging, and sonar survey through to more orthodox drawn survey and excavation. 4. Collaboration: As is implicit in all the above, multi-disciplinary, collaborative, and cross-sector approaches are essential in order to ensure the capacity to meet the research challenges of the marine and maritime historic environment. There is a need for collaboration across the heritage sector and beyond, into specific areas of industry, science and the arts. Methods of communication amongst the constituent research individuals, institutions and networks should be developed, and dissemination of research results promoted. The formation of research communities, especially virtual centres of excellence, should be encouraged in order to build capacity.
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Friedman, Shmuel, Jon Wraith, and Dani Or. Geometrical Considerations and Interfacial Processes Affecting Electromagnetic Measurement of Soil Water Content by TDR and Remote Sensing Methods. United States Department of Agriculture, 2002. http://dx.doi.org/10.32747/2002.7580679.bard.

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Time Domain Reflectometry (TDR) and other in-situ and remote sensing dielectric methods for determining the soil water content had become standard in both research and practice in the last two decades. Limitations of existing dielectric methods in some soils, and introduction of new agricultural measurement devices or approaches based on soil dielectric properties mandate improved understanding of the relationship between the measured effective permittivity (dielectric constant) and the soil water content. Mounting evidence indicates that consideration must be given not only to the volume fractions of soil constituents, as most mixing models assume, but also to soil attributes and ambient temperature in order to reduce errors in interpreting measured effective permittivities. The major objective of the present research project was to investigate the effects of the soil geometrical attributes and interfacial processes (bound water) on the effective permittivity of the soil, and to develop a theoretical frame for improved, soil-specific effective permittivity- water content calibration curves, which are based on easily attainable soil properties. After initializing the experimental investigation of the effective permittivity - water content relationship, we realized that the first step for water content determination by the Time Domain Reflectometry (TDR) method, namely, the TDR measurement of the soil effective permittivity still requires standardization and improvement, and we also made more efforts than originally planned towards this objective. The findings of the BARD project, related to these two consequential steps involved in TDR measurement of the soil water content, are expected to improve the accuracy of soil water content determination by existing in-situ and remote sensing dielectric methods and to help evaluate new water content sensors based on soil electrical properties. A more precise water content determination is expected to result in reduced irrigation levels, a matter which is beneficial first to American and Israeli farmers, and also to hydrologists and environmentalists dealing with production and assessment of contamination hazards of this progressively more precious natural resource. The improved understanding of the way the soil geometrical attributes affect its effective permittivity is expected to contribute to our understanding and predicting capability of other, related soil transport properties such as electrical and thermal conductivity, and diffusion coefficients of solutes and gas molecules. In addition, to the originally planned research activities we also investigated other related problems and made many contributions of short and longer terms benefits. These efforts include: Developing a method and a special TDR probe for using TDR systems to determine also the soil's matric potential; Developing a methodology for utilizing the thermodielectric effect, namely, the variation of the soil's effective permittivity with temperature, to evaluate its specific surface area; Developing a simple method for characterizing particle shape by measuring the repose angle of a granular material avalanching in water; Measurements and characterization of the pore scale, saturation degree - dependent anisotropy factor for electrical and hydraulic conductivities; Studying the dielectric properties of cereal grains towards improved determination of their water content. A reliable evaluation of the soil textural attributes (e.g. the specific surface area mentioned above) and its water content is essential for intensive irrigation and fertilization processes and within extensive precision agriculture management. The findings of the present research project are expected to improve the determination of cereal grain water content by on-line dielectric methods. A precise evaluation of grain water content is essential for pricing and evaluation of drying-before-storage requirements, issues involving energy savings and commercial aspects of major economic importance to the American agriculture. The results and methodologies developed within the above mentioned side studies are expected to be beneficial to also other industrial and environmental practices requiring the water content determination and characterization of granular materials.
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