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Embodied energy is the total amount of energy required to produce a product, and is significant because it occurs immediately and can be equal over the life cycle of a building to the transient requirements for operational energy. Methods for embodied energy analysis include process analysis, input‐output analysis and hybrid analysis. Proposes to improve the reliability of estimating embodied energy based on input‐output models by using an algorithm to extract systematically the most important energy paths for the “other construction” sector from an Australian input‐output model. Demonstrates the application of these energy paths to the embodied energy analysis of an individual commercial building, highlighting improvements in reliability due to the modification of energy paths with process analysis data. Compares materials and elements for the building, and estimates likely ranges of error.

The purpose of this paper is to be limited to provide an overall economic structure linked with a particular hospitality industry by identifying the economic structure of relations between the two hotel industries and other industries within a particular state in the USA.

The analyses of output, labor income and employment multipliers from the input–output system were performed using the IMPLAN 3.0 software. The study attempted to compare the hotel/motel industry (industry code 411) and the accommodations industry (industry code 412) with the top ten industries and averages of each set of multipliers to estimate the relative importance and contribution of the two hotel industries to the economy of Texas. After this comparison, the aggregated input–output tables and multipliers were prepared to determine the economic inter-relationship between the two combined hotel industries (industry code 411 plus industry code 412) and the non-hotel industries, using the criteria of the NAICS (North American Industry Classification System).

The three findings of this study are summarized as follows. First, the two hotel industries impacted the state economy due to a high induced effect from output and a considerable direct, indirect and induced effect from labor income and employment, despite their relatively lower multipliers and the economic downturn in the state. Second, the hotel-related industry had a strong inter-dependent relationship with the finance and insurance-related industries. Finally, while the hotel industry generated more labor income and employment than did the other accommodations industry, it is interesting that the other accommodations industry created more output than did the hotel industry.

Other than limitations pertaining to assumptions of input-output model, an input-output analysis alone cannot become the best analytical method for decision-making. The study was a cross-sectional study with 2009 data and did not incorporate a time-series flow of the state economic structure over several decades. A study of the inter-relationship among varied states bordering the state could be worthwhile to identify the flow of inputs and outputs.

Despite a considerable number of research in measuring the economic impacts, this paper was of great significance, in that the economic impact of the hotel industry that has never been performed in a particular state of the USA was analyzed. Additionally, these quantified economic data and results should be helpful to future plans and policies associated with the hotel industry.

This paper aims to investigate the issue of performance measurement of social enterprises with main particular focus on economic performance approach reflecting local aspect, since the local aspect plays a significant role in social entrepreneurship concept. Thus, comparison of two instruments that consider local aspects: local multiplier 3 (LM3) and Input-Output analysis is examined. Input-Output analysis is empirically used to calculate social enterprises’ impact on the Czech economy and to confirm the assumption to be more suitable instrument for economic performance measurement of social enterprises in comparison to local multiplier 3 method.

The research adopted two-phase approach. At first a qualitative approach was used to compare the two selected instruments (LM3 and Input-Output analysis). Consequently, a quantitative research was applied to determine the impact of social enterprises’ activities on the economies of individual regions. The research was carried out on a sample of social enterprises (143 subjects) in the Czech Republic covering the year 2015. For this approach, Symmetric Input-Output tables and multipliers were calculated and revenue data from each observed social enterprise were used.

The findings of the research indicate effects of social enterprises’ activities on the economy in individual regions of the Czech Republic. The results clearly show that the impact of social enterprises on the Czech economy is not negligible. Calculated impacts differ in sectors as well as in regions. Besides, of these findings, the assumption that the Input-Output analysis is more appropriate instrument for economic performance measurement of social enterprises, especially in situation of a larger sample of social enterprises in different regions, in comparison to LM3 method, was confirmed.

The limitations of this study is the dependence on the Symmetric Input-Output tables, which are usually published by local statistical offices and it takes some time to construct them. A more significant limitation and future research direction relates to the lack of generally accepted measurement framework in the sector of social enterprises and lack of the data, especially quantitative, in the Czech Republic.

The findings of the research represent a significant contribution to the process chain of understanding the role of social enterprises in (local) economy. The lack of proven impact of social enterprises to economy is considered as important limit of this sector development, not only from the perspective of investors and donors but also from the perspective of policymakers and even social enterprises themselves. The Input-Output analysis can be applied for any region of any country and can contribute to reduce scepticism about economic performance of social enterprises, thus to support putting social and environmental goals of social enterprises into practice.

This research has been carried out on the so far largest identified sample of social enterprises in the Czech Republic and provides data for discourse among stakeholders about social enterprises’ impact; thus, it enables to understand their impact and make capable to enlarge their support network and development.

This research is a pioneering attempt to provide data about economic impact of social enterprises using Input-Output analysis in the Czech Republic. No previous research identifies such a large sample of Czech social enterprises and collects quantitative data about them, as well as considers Input-Output analysis as an option instead of LM3 method. The effort of this research has been to react on a research gap in studies related to the impact of social enterprises (reflecting local aspect). This paper could be understood as beneficial not only from the perspective of the Czech Republic but also worldwide.

Known as the major capital providers in Belt and Road countries and the largest carbon emitter in the world, what role China's outward direct investment (ODI) plays in carbon neutralization has become a matter of concern. This study aims to measure the impact of China's ODI on the carbon emissions of Belt and Road countries.

Based on an econometric model and an inter-regional input–output model, a new model measuring the carbon emission effects of ODI is developed.

The empirical results show that (1) in general, China's ODI generates an emission-reduction effect in Belt and Road countries; (2) The relationship between the emission-reduction effect and income level of host countries shows an approximate inverted U-shaped trend; and (3) China's ODI generates stronger emission-reduction effects on capital-intensive industries.

This study quantitatively measures the scale of carbon emission-increase and reduction effect, which is relatively lacking in previous studies. This study explores the heterogeneity from the perspectives of regions, countries and industries. The authors have compiled an inter-regional input–output table for the Belt and Road countries for 2014 to provide a broad basis for the study of related issues.

Economic modeling issues for measuring damages and losses from disasters and their impacts are complex. The questions surrounding the potential economic effects of a disaster have been studied and discussed in various aspects. Input‐output analysis has been employed in many studies to measure and evaluate the economic impacts of disasters, mainly because of the ability to reflect the structure of regional economy in great detail. Whereas they provide useful information regarding the economic impacts and consequences and about the resource allocation strategies to minimize the losses and impacts, many of these studies have failed to investigate the dynamic nature of impact path over space and time, due to the difficulties to obtain such data and also to the static nature of input‐output framework. In order to analyze the spatial impacts of a disaster, Miyazawa's extension to the conventional input‐output framework is employed and is applied for the case of the Great Hanshin Earthquake.

The purpose of this paper is to evaluate and improve the current methodology of securing and collecting data sources for use in the Impact Analysis for Planning (IMPLAN) model to more accurately use, and be able to support, inputs and outputs from economic impact models, specifically those generated by IMPLAN.

Primary expenditure data were derived from an extensive mail survey conducted during the 2005-2006 Mississippi waterfowl-hunting season. Survey results were analyzed using the IMPLAN software model default data and comparing it with new, more localized state data that were collected in 2010. Industry sectors were sorted and ranked after analysis based on sector importance to the economy and IMPLAN default data were replaced by localized data.

Economic contributions generated from the survey-based default model were $158 million (2010 USD) supporting 1,981 full- and part-time jobs. Economic contributions using survey-based data replacement model were $153 million (2010 USD) supporting 1,517 full- and part-time jobs. Separate model runs of the survey-based data replacement model yielded vastly different results, making the case for changing as many sectors with larger impacts as possible.

The makeup and components of sectors used and described by the IMPLAN model were at times not clearly labeled which at times hindered the process of comparing and replacing data. It was evident that IMPLAN sectors were too highly aggregated.

This project will contribute to efforts within Mississippi aimed at protecting and promoting its natural resources for conservation and use for both the private and public sector.

The onset of climate change is expected to result in variations in weather patterns which can exacerbate water scarcity issues. This can potentially impact the economic productivity of nations as economic activities are highly dependent on water especially for agricultural countries. In response to this, the concepts of virtual water and water footprint have been introduced as metrics for measuring the water intensity of products, services and nations. Researchers have thus looked into virtual water trade flows as a potential strategy for alleviating water scarcity. The paper aims to discuss these issues.

Environmentally extended input-output models (IOMs) are often used to analyze interactions between economic and ecological systems. This work thus develops a multi-regional input-output model for optimizing virtual water trade between different geographic regions in consideration of local environmental resource constraints, product demands and economic productivity.

A case study on agriculture crop production and trade in different regions of the Philippines is utilized to demonstrate the capabilities of the model. The results show that the optimal strategy does not necessarily limit a water-scarce region to produce less water-intensive crops.

The model uses an input-output framework whose fixed coefficients reflect a fixed technological state. As such, the model is best used for short-term projections, or projections for mature technological state (i.e. where no major gains in efficiency or yield can be foreseen).

The proposed modeling framework can be used in any geographic region (provided relevant statistical data are available for calibration) to provide decision support for optimal use of limited water resources.

The model proposed in this work has general applicability to the optimal planning of agro-industrial systems under water footprint constraints. This modeling approach will be particularly valuable in the future, as climate change causes changes in precipitation patterns and water availability.

Nowadays, automotive engines are controlled by electronic control units (ECUs), and the engine idle speed performance is significantly affected by the setup of control parameters in the ECU. The engine ECU tune‐up is done empirically through tests on a dynamometer (dyno). In this way, a lot of time, fuel and human resources are consumed, while the optimal control parameters may not be obtained. The purpose of this paper is to propose a novel ECU setup optimization approach for engine idle speed control.

In the first phase of the approach, Latin hypercube sampling (LHS) and a multi‐input/output least squares support vector machine (LS‐SVM) is proposed to build up an engine idle speed model based on dyno test data, and then a genetic algorithm (GA) is applied to obtain optimal ECU setting automatically subject to various user‐defined constraints.

The study shows that the predicted results using the estimated model from LS‐SVM are in good agreement with the actual test results. Moreover, the optimization results show a significant improvement on idle speed performance in a test engine.

As the methodology is generic it can be applied to different vehicle control optimization problems.

The research is the first attempt to integrate a couple of paradigms (LHS, multi‐input/output LS‐SVM and GA) into a general framework for constrained multivariable optimization problems under insufficient system information. The proposed multi‐input/output LS‐SVM for modelling of multi‐input/output systems is original, because the traditional LS‐SVM modelling approach is suitable for multi‐input, but single output systems. Finally, this is the first use of the novel integrated framework for automotive engine idle‐speed control optimization.

The aim of this paper is to introduce uncertainty analysis within an environmentally extended input‐output technological model of life cycle costing. The application of this approach will be illustrated with reference to the ceramic floor tiles manufacturing process.

Input‐output analysis (IOA) provides a computational structure which is interesting for many applications within value chain analysis and business processes analysis. A technological model, which is built bottom‐upwards from the operations, warrants that production planning and corporate environmental accounting be closely related to cost accounting. Monte Carlo methods have been employed to assess how the uncertainty may affect the expected outcomes of the model.

It has been shown, when referring to a vertically‐integrated, multiproduct manufacturing process, how production and cost planning can be effectively and transparently integrated, also taking the product usage stage into account. The uncertainty of parameters has been explicitly addressed to reflect business reality, thus reducing risk while aiding management to take informed actions.

The model is subject to all the assumptions characterizing IOA. Advanced issues such as non linearity and dynamics have not been addressed. These limitations can be seen as reasonable as long as the model is mostly tailored to situations where specialized information systems and competences about complex methods may be lacking, such as in many small and medium enterprises.

Developing a formal structure which is common to environmental, or other physically‐driven, assessments and cost accounting helps to identify and to understand those drivers that are relevant to both of them, especially the effects different design solutions may have on both material flows and the associated life cycle costs.

This approach integrates physical and monetary measures, making the computational mechanisms transparent. Unlike other microeconomic IOA models, the environmental extensions have been introduced. Uncertainty has been addressed with a focus on the easiness of implementing the model.

This is a preliminary study on the modal split of reducing environmental contaminants to a minimum. In this paper, we focus on NO_x as a typical air pollutant and make clear the structure of energy flow with regard to freight transport using input‐output analysis. Then we present a mathematical model for the optimal modal split considering the input‐output structure of energy flow. The goal of this model is to minimize NO_x which is emitted in the processes of freight transport, energy transport and energy production subject to maintaining the status quo of freight volume transported in Japan. This model is applied to the actual freight transport problem in Japan and the validity of this model is evaluated. As the result of that, we could suggest a policy of the modal shift, which can reduce the volume of NO_x emissions in the transportation sector by approximately 30 per cent compared to the current circumstances in Japan.