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Many important constructs of business and social sciences are conceptualized as composites of common factors, i.e. as second-order constructs composed of reflectively measured first-order constructs. Current approaches to model this type of second-order construct provide inconsistent estimates and lack a model test that helps assess the existence and/or usefulness of a second-order construct. The purpose of this paper is to present a novel three-stage approach to model, estimate, and test second-order constructs composed of reflectively measured first-order constructs.

The authors compare the efficacy of the proposed three-stage approach with that of the dominant extant approaches, i.e. the repeated indicator approach, the two-stage approach, and the hybrid approach by means of simulated data whose underlying population model is known. Moreover, the authors apply the three-stage approach to a real research setting in business research.

The study based on simulated data illustrates that the three-stage approach is Fisher-consistent, whereas the dominant extant approaches are not. The study based on real data shows that the three-stage approach is meaningfully applicable in typical research settings of business research. Its results can differ substantially from those of the extant approaches.

Analysts aiming at modeling composites of common factors should apply the proposed procedure in order to test the existence and/or usefulness of a second-order construct and to obtain consistent estimates.

The three-stage approach is the only consistent approach for modeling, estimating, and testing composite second-order constructs made up of reflectively measured first-order constructs.

The study constructs a composite indicator to rank macroeconomic performance of countries and a separate composite indicator to rank countries by inequality using the TOPSIS methodology of Multiple Criteria Decision-Making Analysis. The intuitive idea of TOPSIS is to formulate an ideal solution with respect to each individual policy variable; the relative rank of any country is then determined, using a suitable distance metric, such that the best performer simultaneously has the shortest distance from the ideal solution and the farthest distance from the non-ideal. It uses the composite indicator based rankings together with the KOF Globalization Index and sub-indices based rankings to examine the overall relationship between globalization and macroeconomic performance of countries and reduction in inequality; the impacts of trade and financial globalization for 1990–2018 across countries and groups of the globe. It shows that though highly correlated with growth, globalization may not necessarily lead to an improvement in overall macroeconomic performances of countries when one also takes into account unemployment and inflation. Economic globalization is seen here to mostly coincide with rise in income inequality. Observations also support the fact that countries, even if they are not highly integrated may reap sufficient benefits of globalization for macroeconomic performance and inequality diminution given supportive policies.

The purpose of this paper is to advance a model that relates the criteria of sustainable development with the construction engineering of buildings. Moreover, a method to evaluate the building sustainability is suggested.

The method is based on calculating the weighted expected utility function of a building with respect to composite indicator.

Based on this integrated approach, a tentative index to evaluate the sustainability of buildings is proposed.

The study is limited to the assessment of the sustainable development of the built environment.

The feasibility of assessing the sustainability of a building using the sustainable index of buildings (SIB) is that it permits the decision-makers to study the potential improvement in the sustainable development of buildings in the long and short run. Moreover, the role of benchmarking in improving the sustainability performance of buildings is discussed in view of the suggested method.

The present method is practical and easy to use for ranking building (or a part of a building) according to the sustainable performance.

New methodology based on integrating the value-focused thinking together with the composite indicators is used to evaluate the sustainable development.

This paper aims to study through a comprehensive set of socioeconomic indicators the regional level of well-being achieved in Romania, and monitor the improvements and disparities in well-being after a decade of accession to the European Union.

A dashboard of 20 socioeconomic indicators for measuring nine dimensions of well-being for Romanian counties is proposed. Using the Adjusted Mazziotta-Pareto method are built composite indicators, which allow us to assess the trend of overall welfare scores for each county. The data are collected at the county level, for 42 counties, and each year from 2006 to 2017, from administrative sources.

The overall well-being index has an increasing trend for all counties, but the growth rate varies from one county to another. The economic factors, geographic location and share of the urban population matter. For most counties, the evolution of well-being scores is below that recorded at the country level. Romania has registered significant improvements in health, housing, income and access to public utilities dimensions. The counties are ranked by level of well-being. Some empirical measures suggest a slight tendency of socioeconomic disparities to increase over time.

The paper attempts to fill some gaps in measuring the level and disparities of welfare in a fast-growing emerging economy. The Romanian regional context is to a lesser extent explored in a multidimensional approach, from spatial and temporal points of view.

Sustainable development calls for concerted efforts towards building an inclusive, sustainable and resilient future for people and planet. The approach that considers sustainable development as the fight against poverty, through the promotion of a sustainable and equitable economy, as the attempt to reduce polluting emissions to promote environmental protection and as the satisfaction of social goals to increase the well-being of populations is adopted. Sustainability development is therefore a complex and subjective concept, considering the three dimensions that define the phenomenon: economic, environmental and social.

The authors have chosen subjective variables, which provide information on the perception of the ‘sustainable development’ in the European countries. Data come from the database of ‘Eurofound’, the European Foundation for the Improvement of Living and Working Conditions. The authors applied a formative measurement model, according to which indicators are considered as the cause of the phenomenon analysed, unlike with the reflective model. To conduct the quantitative analysis, the authors have adopted a non-compensatory approach: Mazziotta and Pareto index which summarising a set of individual indicators that are assumed to be not fully substitutable. The authors place at the centre of the analysis, variables deriving from the perceptive state of the different European populations, offering new hints to measure sustainable development on the basis of subjective assumptions.

Partial least squares (PLS) path modeling is a variance-based structural equation modeling (SEM) technique that is widely applied in business and social sciences. Its ability to model composites and factors makes it a formidable statistical tool for new technology research. Recent reviews, discussions, and developments have led to substantial changes in the understanding and use of PLS. The paper aims to discuss these issues.

This paper aggregates new insights and offers a fresh look at PLS path modeling. It presents new developments, such as consistent PLS, confirmatory composite analysis, and the heterotrait-monotrait ratio of correlations.

PLS path modeling is the method of choice if a SEM contains both factors and composites. Novel tests of exact fit make a confirmatory use of PLS path modeling possible.

This paper provides updated guidelines of how to use PLS and how to report and interpret its results.

The study aims to examine corporate governance issues in India and establish the relationship between corporate governance and financial performance.

The sample comprises 141 companies belonging to the “A” group stocks listed in the Mumbai Stock Exchange of India. Considering the institutional uniqueness in India, a composite measure of corporate governance is developed comprising three indicators – legal, board and proactive indicators. Data on the three indicators and financial performance were procured from secondary sources. In the step-wise multiple regression analysis, the influence of these three indicators and the composite measure of corporate governance was examined on firm performance after controlling the confounding effects of firm size.

The board and the proactive indicators influence the firm performance significantly whereas legal compliance indicator does not do so. The composite corporate governance measure is a good predictor of firm performance.

This study has two contributions: one, it proposes a composite measure of corporate governance considering the unique institutional characteristics of the Indian economy. Two, the study establishes the predictability of the new measure of corporate governance on firm performance as a tool to boost investors' confidence and financial health of firms.

This paper aims to develop and implement a new approach of ranking countries according to their level of economic competitiveness.

Competitiveness is conceptualized as the degree of participation in global integration, measured by the levels of exports, capital inflows and immigration. Based on a wide range of development indicators, composite indicators are constructed by means of a principal component analysis. In turn, these composites enter a canonical correlation analysis and estimated canonical weights are used as weights in the calculation of index scores.

Measures of institutional and political quality are shown to be most closely connected to a country’s ability to export and to attract foreign factors of production. Inflows of foreign capital turn out to correlate much less with our weighting composites than export volumes.

Regarding prospects for future research, a broad range of further applications of this approach in the macro area is conceivable, including measures of a country’s quality of schooling, the quality of its health care system or of its governmental institutions.

In comparison to prevailing macroeconomic indices, this method of index construction is superior in at least two respects. First, direct measures of a country’s performance are methodologically separated from mere performance drivers, contributing to higher clarity concerning the concept to be measured. Second, weights of performance drivers are not determined arbitrarily or based on subjective judgment, but emerge from a transparent and well-established statistical procedure.