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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 value adding of each industry represents the value difference between the outputs and inputs of that industry. The purpose of this paper is to investigate the effect of international outsourcing on the value adding of industries.

Input output analysis and linear programming are used as for the research methodology. Australian Motor Vehicle and Parts Manufacturing (AMVPM) industry as an outsourcer and its main suppliers were selected for ten alternative international outsourcing scenarios in a case study.

In all international outsourcing scenarios except the baseline scenario, the reduction in the value adding of Australia would be approximately three times more than the value adding reduction of the AMVPM industry. Moreover, the international outsourcing ratio has negative relationships with the value adding of the Australian industries and positive relationship with the international industries. Finally, it was found that the degree of supplier's dependency on the orders of the outsourcer effects the percentage reduction of supplier's value adding.

The aggregated data and the uncertainties in the technical coefficients are the main limitations of this research. The social and environmental costs, other tangible and intangible costs, as well as benefits of international outsourcing need to be further analysed in future research.

This study would help decision makers at the macro level to analyse and control the effect of international outsourcing on the value adding of their economies.

This study expands the current research at the industry level of international outsourcing by quantifying the effect of international outsourcing upon the value adding of all respected industries.

The aim of this paper is to learn about some patterns of sectoral and industrial structural change of the Chinese economy over the 1995-2010 period, which also complements a previous paper of the author. The chosen period is about (and conveniently) bounded by two international crises: the Southeast Asian crisis of 1997 and the world crisis that started in 2007/2008.

To such a purpose, this paper set up a quantitative methodology via input-output modelling, which allows us to decompose gross output into some key demand sources or contributions. These are then analyzed over the full period.

It can be shown that the trajectory of the main structural patterns over the period was not smooth and was pretty unbalanced and that they generally responded to both domestic policy and international shocks. Export demand and heavy industry appeared to be the main engines of the economy, which showed massive increases in their share of output, at the expense of domestic demand, services and agriculture. Despite the high growth rates over this period, the Chinese economy seemed to be in need of rebalancing, which seems to have started toward the end of the authors’ period.

The decomposition method has been applied before by the author and others, but the variations in this paper are original, just as original is the application to China (never been done before), which in addition is not confined to two or so snapshots separated by many years, as is the usual use, but to the full year-after-year change of the sectoral and industrial structure over this study’s focus period.

The purpose of this paper is to benchmark the operational and financial performances of the major Indian seaports to help derive useful insights to improve their performance.

A two-stage data envelopment analysis (DEA) methodology has been used with the help of data collected on the 13 major seaports of India. The first stage of the DEA captured the operational efficiencies, while the second stage the financial performance.

A window analysis over a period of three years revealed that no port was able to score an overall average efficiency of 100 per cent. The study identified the better performing units among their peers in both the stages. The contrasting results of the study with the traditional operational and financial performance measures used by the ports helped to derive useful insights.

The data used in the study were majorly limited to the available sources in the public domain. Also, the study was limited to the major seaports which are under the Government of India and no comparisons were carried out with other local or international ports.

There is a need to prioritize investments and improvement efforts where they are most needed, instead of following a generalized approach. Once the benchmark ports are identified, the port authorities and other relevant stakeholders should work in detail on the factors causing inefficiencies, for possible improvements in performance.

This paper carried out a two-stage DEA that helped to derive useful insights on operational efficiency and financial performance of the India seaports. A combination of the financial and operational parameters, along with a comparison of the DEA results with the traditional measures, provided a different perspective on the Indian seaport performance. Considering the scarcity of research papers reported in the literature on DEA-based benchmarking studies of seaports in the Indian context, it has the potential to attract future research in this field.

The purpose of this paper is to introduce cybernetic systems in defence management applications, to meet new challenges of the information society and use of system modelling for decision making.

The paper defines basic terms for understanding the complexity of the defence management applications, which is simplified using input‐output modelling.

The paper illustrates the interdisciplinary nature of cybernetics, systems and management sciences. The defence system is analysed and a general input‐output model for defence system development recommended.

New data technology and data availability provide perspective for applied research using scientific approach.

Cybernetic systems for defence provide analytical modelling for management applications.

The paper presents a concept and empirical evidence for defence system analysis and a new way of thinking that affects defence planning and defence management. A cybernetic, systemic and input‐output methodology provides solutions for defence management applications.

The determination of input and output factors is a well-known source of pitfalls when applying data envelopment analysis (DEA). The purpose of this paper is to contribute to overcome the respective problems of input/output factor determination related to factor selection, dual-role factors and undesirable factors.

The problems of input/output factor determination are discussed from a goal-oriented perspective, shedding a new light on the role of input/output factors in DEA. This is exemplified by the case of measuring pharmacy stores’ efficiency concerning their goal of customer retention.

The findings suggest to applying a generalized DEA (GDEA). The three steps of this approach include the development of a system of objectives, the derivation of corresponding performance criteria as well as the construction of cost and benefit functions. These functions build the basis for GDEA models, of which one is exemplarily described and applied to the customer retention case.

While traditional DEA implicitly assumes linear cost and benefit functions, GDEA requires to explicitly specifying these functions. In doing so, the approach contributes to solve the problem of factor selection, the problem of dual-role factors and the problem of undesirable factors.

For determining input/output factors in a consistent and transparent manner, it is recommended to apply GDEA in practical benchmarking studies.

GDEA integrates well-known concepts of multi-criteria decision making into traditional DEA. The new approach helps to cope with the challenges of input/output factor determination in DEA.

This chapter examines the main methodological issues involved in the comprehension of the cost structure of the airport industry and suggests considerations for future airport cost analyses. Such understanding has become a crucial concern for policy makers, regional planners, and managers in order to deal with optimal market design (e.g., regulation and market configuration) and airport strategies (e.g., pricing, investments, and alliances). An in-depth analysis of the economics of cost functions is presented, together with a description of the relevant multi-output cost economies measures (average incremental costs, scale and scope economies, and cost complementarities). We also discuss the assumptions underlying estimates of total versus variable cost functions and the importance of estimating a sufficiently flexible functional form. Moreover, we provide a critical survey of the international empirical literature on the cost structure of the airport industry, which highlights how econometric estimates strongly depend on the sample choice and the empirical model considered. Indeed, while econometric studies on international samples based on long-run cost function estimates show that long-run scale economies are never exhausted, single country studies mostly estimate variable cost functions and find lower values for scale economies at median sample points that tend to decrease with size. We discuss why we believe that studies based on the estimation of short-run variable cost functions offer more reliable results, given the reasonable assumption of airport overcapitalization in the short run. We conclude our work by noting that underlying policy issues related to planning and regulation, as well as to the optimal market structure of the airport sector, need to take into account the role played by vertical relationships between airports and airlines.

Previous studies on tourism input-output (IO) primarily focus on a single year’s snapshot or utilize outdated IO coefficients. The purpose of this paper is to analyze the multi-period development of regional tourism capacities and its influence on the magnitude of the industry’s regional economic contribution. The paper highlights the importance of applying up-to-date IO coefficients to avoid estimation bias typically found in previous studies on tourism’s economic contribution.

For the period 2008-2014, national IO tables are regionalized to estimate direct and indirect economic effects for output, employment, income and other value-added deffects. A comparison of Leontief inverse matrices is conducted to quantify estimation bias when using outdated models for analyzing tourism’s economic contribution.

On the one hand, economic linkages strengthened, especially for labour-intensive sectors. On the other hand, sectoral recessions in 2012 and 2014 led to an economy-wide decline of indirect effects, although tourists’ consumption was still increasing. Finally, estimation bias observed after applying an outdated IO model is quantified by approximately US$4.1m output, 986 jobs full-time equivalents, US$24.8m income and US$14.8m other value-added effects.

Prevailing assumptions on IO modelling and regionalization techniques aim for more precise survey-based approaches and computable general equilibrium models to incorporate net changes in economic output. Results should be cross-validated by means of qualitative interviews with industry representatives.

Additional costs for generating IO tables on an annual base clearly pay off when considering the improved accuracy of estimates on tourism’s economic contribution.

This study shows that tourism IO studies should apply up-to-date IO models when estimating the industry’s economic contribution. It provides evidence that applying outdated models involve the risk of estimation biases, because annual changes of multipliers substantially influence the magnitude of effects.

In response to calls for conceptual frameworks and generic theory building toward the advancement of sustainability in supply chain resource utilization and management, the purpose of this paper is to advance a circular framework for supply chain resource sustainability (SCRS), and a decision-support methodology for assessing SCRS against the backdrop of five foundational premises (FPs) deduced from the literature on resource sustainability.

Taking a conceptual theory-building approach, the paper advances a set of SCRS decision-support criteria for each of the theoretical premises advanced, and applies the theory of constraints to illustrate the conceptual and practical applications of the framework in SCRS decision making.

This study uses recent conceptualizations of supply chains as “complex adaptive systems” to provide a robust and novel frame and a set of decision rules with which to assess the interconnectedness of environmental, economic, and social capital of supply chain resources from pre-production to post-production.

The paper contributes to theory building in sustainability research, and the SCRS decision framework developed could be applied in tandem with existing quantitative hybrid life-cycle and input-output approaches to facilitate targeted resource sustainability assessments, with implications for research and practice.

The novel SCRS framework proposed serves as a template for evaluating SCRS and provides a decision-support methodology for assessing SCRS against the five theorized FPs.

This paper aims to examine the performance efficiency of 56 real estate assets within the rental sector in the UAE to evaluate the relative operation efficiency in relation to revenue generation.

The data envelopment analysis (DEA) approach was used to measure the relative operational efficiency of the studied assets in relation to the revenue performance. This method could produce a more informed and balanced approach to performance measurement.

The outcomes show that scores of efficiencies ranging from 7% to 99% in some of the models. The results showed that on average buildings are 75% relatively less efficient in maintenance, in term of revenue generation, than the benchmark set. Likewise, on average, the inefficient buildings are 60% relatively less efficient in insurance. Result also shows that 95% of the building assets in the sample are by and large operating at decreasing returns to scale. This implies that managers need to considerably reduce the operational resources (input) to improve the levels of revenue.

This study recommends that the FM operational variables that were found to inefficiently contribute to the revenue should be re-examined to test the validity of the findings. This is necessary before generalising or interpolating the results that are presented in this study.

The information obtained about operational performance can help FM managers to understand which improvements in the productivity of inefficient FM resources are required, providing insight into how to reduce operating costs and increase revenue.

This paper adds value in using new FM operational parameters to evaluate the efficiency of the performance of built assets.