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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 propose a service-dominant (S-D) logic-based input-output analysis approach to systematically measure the effects of technology spillover in the service sector.

This study uses a case to demonstrate the feasibility and contributions of the S-D logic-based input-output analysis approach.

This study adopted the idea of customer involvement to formulate the S-D logic-based input-output analysis approach. Service providers can apply this systematical approach to find potential opportunities to spread information technology and co-create values with customers.

The S-D logic-based input-output analysis approach has elasticity to dynamically employ different perspectives to evaluate the effects of technology spillovers in order for integrity and precision. The proposed approach is to delineate the possible target values that related to specific services based on the notions of operant resources and customer involvement in a selected service sector. Service providers within the service sector have to offer innovative service activities and manage existing services for customers to participate in.

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.

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.

An informal survey conducted by Arthur D. Little, Inc., about three years ago showed that there were 200 corporations in the United States that, at one time or another, have used input‐output in some form in their corporate planning work. Of these 200 corporations, all of which have sales in excess of $500 million annually, 60 firms indicated that they used input‐output regularly and intended to continue to do so. From some other informal questionnaires that ADL circulated among some 50 or so major United States' corporations for whom it had undertaken input‐output studies, it was found that input‐output analysis was typically used in connection with forecasting work. A few other types of application have been made that tie directly into corporate planning.

The evolution of six sigma has morphed from a method or set of techniques to a movement focused on business‐process improvement. Business processes are transformed through the successful selection and implementation of competing six sigma projects. However, the efforts to implement a six sigma process improvement initiative alone do not guarantee success. To meet aggressive schedules and tight budget constraints, a successful six sigma project needs to follow the proven define, measure, analyze, improve, and control methodology. Any slip in schedule or cost overrun is likely to offset the potential benefits achieved by implementing six sigma projects. The purpose of this paper is to focus on six sigma projects targeted at improving the overall customer satisfaction called Big Q projects. The aim is to develop a mathematical model to select one or more six sigma projects that result in the maximum benefit to the organization.

This research provides the identification of important inputs and outputs for six sigma projects that are then analyzed using data envelopment analysis (DEA) to identify projects, which result in maximum benefit. Maximum benefit here provides a Pareto optimal solution based on inputs and outputs directly related to the efficiency of the six sigma projects under study. A sensitivity analysis of efficiency measurement is also carried out to study the impact of variation in projects' inputs and outputs on project performance and to identify the critical inputs and outputs.

DEA, often used for relative efficiency analysis and productivity analysis, is now successfully constructed for six sigma project selection.

Provides a practical approach to guide the selection of six sigma projects for implementation, especially for companies with limited resources. The sensitivity analysis discussed in the paper helps to understand the uncertainties in project inputs and outputs.

This paper introduces DEA as a tool for six sigma project selection.

The purpose of this study is to examine the total economic impact of tourism at the regional level in Central Finland. This paper aims to clarify the extent to which tourism contributes to regional output, employment, income and taxes in tourism-related sectors.

This study is based on a regional input–output analysis. The author calculates the effects of tourism on regional output, demand, wages, employment and national and regional taxes in Central Finland.

The author’s regional input–output analysis reveals that tourism has a substantial impact on production in Central Finland (including the direct and indirect effects of consumption by tourists in different sectors). Moreover, the effects of tourism expenditures on employment and residents’ incomes in tourism-related sectors in Central Finland are quite significant.

Many limitations of this study stem from the assumptions of the input–output model. Other limitations relate to the analysis of the impacts of tourism on household taxes, savings, consumption and net income. Our study uses average figures, which may overstate the effect of tourist expenditures on taxes because tourism jobs are often low paying.

The study yields results that can be used to frame regional policy. The results may be useful for policymakers in planning for tourist attractions. Furthermore, local authorities may use the results to guide decisions regarding infrastructure investments or improvements to the operating environment of tourism industries.

Many studies analyse the economic impact of events at the regional level using input–output analysis. National-level tourism impact studies using the input–output technique have also been conducted. Studies focussed on the economic impact of tourism at the regional level typically examine the macroeconomic (income, output and employment) effects of tourism. Consequently, these studies have focussed on estimating output, employment and income multipliers (Mazumder et al., 2012). The author’s contribution is a regional input–output analysis of direct and indirect impacts of tourism expenditures on production, demand, wages, income and employment in the whole economy at the regional level (in Central Finland). The author also analyses the impacts of tourism on national and regional taxes. The results of this study could be used by planners and policymakers involved in regional planning and development.

This paper seeks to rediscover the most suitable efficiency evaluation variables (input and output variables) for digital libraries and to employ the data envelopment analysis (DEA) model to measure the resource utilization efficiency of university libraries.

In order to analyze and evaluate university library efficiency, the paper introduces the DEA‐CCR Model and the DEA‐BCC Model. Based on these research tools, the Technical Efficiency (CCR*BCC) was determined. First, a reference group was created with a 100 percent efficiency rate, then the factors contributing to inefficient DMUs were analyzed, and the difference in the efficiency rate compared according to the different governing bodies of the libraries. Finally, the difference of efficiency according to the introduction and rejection of electronic resources was analyzed. It was possible to measure the technical efficiency, pure‐technical efficiency, and scale efficiency.

The results showed that the efficiency of university libraries varied significantly according to whether or not electronic resources were included in the evaluation. In addition, the findings confirmed decision making units (DMUs) have a 100 percent efficiency rate and a low efficiency rate as well as proposed benchmarking DMUs for inefficient DMUs and a direction for future improvements.

The paper identifies that there was a significant difference in efficiency, according to the presence of electronic resources in university libraries.

This chapter provides an empirical assessment of the effects of infrastructure provision on structural change and aggregate productivity using industrylevel data for a set of developed and developing countries over 1995–2010. A distinctive feature of the empirical strategy followed is that it allows the measurement of the resource reallocation directly attributable to infrastructure provision. To achieve this, a two-level top-down decomposition of aggregate productivity that combines and extends several strands of the literature is proposed. The empirical application reveals significant production losses attributable to misallocation of inputs across firms, especially among African countries. Also, the results show that infrastructure provision has stimulated aggregate total factor productivity growth through both within and between industry productivity gains.