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The purpose of this study is threefold: (1) to propose partial least squares path modeling (PLS-PM) as a way to estimate models containing composites of composites and to compare the performance of the PLS-PM approaches in this context, (2) to provide and evaluate two testing procedures to assess the overall fit of such models and (3) to introduce user-friendly step-by-step guidelines.

A simulation is conducted to examine the PLS-PM approaches and the performance of the two proposed testing procedures.

The simulation results show that the two-stage approach, its combination with the repeated indicators approach and the extended repeated indicators approach perform similarly. However, only the former is Fisher consistent. Moreover, the simulation shows that guidelines neglecting model fit assessment miss an important opportunity to detect misspecified models. Finally, the results show that both testing procedures based on the two-stage approach allow for assessment of the model fit.

Analysts who estimate and assess models containing composites of composites should use the authors’ guidelines, since the majority of existing guidelines neglect model fit assessment and thus omit a crucial step of structural equation modeling.

This study contributes to the understanding of the discussed approaches. Moreover, it highlights the importance of overall model fit assessment and provides insights about testing the fit of models containing composites of composites. Based on these findings, step-by-step guidelines are introduced to estimate and assess models containing composites of composites.

Research on international marketing usually involves comparing different groups of respondents. When using structural equation modeling (SEM), group comparisons can be misleading unless researchers establish the invariance of their measures. While methods have been proposed to analyze measurement invariance in common factor models, research lacks an approach in respect of composite models. The purpose of this paper is to present a novel three-step procedure to analyze the measurement invariance of composite models (MICOM) when using variance-based SEM, such as partial least squares (PLS) path modeling.

A simulation study allows us to assess the suitability of the MICOM procedure to analyze the measurement invariance in PLS applications.

The MICOM procedure appropriately identifies no, partial, and full measurement invariance.

The statistical power of the proposed tests requires further research, and researchers using the MICOM procedure should take potential type-II errors into account.

The research presents a novel procedure to assess the measurement invariance in the context of composite models. Researchers in international marketing and other disciplines need to conduct this kind of assessment before undertaking multigroup analyses. They can use MICOM procedure as a standard means to assess the measurement invariance.

The construction and use of composite indicators has recently increased considerably because such indicators permit the comparison and ranking of countries with respect to complex phenomena of global importance. Together with the diffusion of these composite indicators, a major debate has emerged over their real capacity to produce objective and reliable results. The paper aims to discuss these issues.

In this paper, an analysis of the results of the Gender Gap Labour Market Index (GGLMI) – an ad hoc composite indicator constructed by the authors to analyse the gender gap in European labour markets – is proposed, in order to identify the most appropriate choices in the construction of composite indicators, to obtain reliable results. This is a sensible approach, especially when various aspects (some of them controversial) have to be synthesised.

In addition to highlighting the greater robustness of non-compensatory methods, this analysis confirms the variability of countries’ rankings on graded positional lists, and suggests the need to use a procedure based on a set of alternative methods conveniently combined in each step of the composite indicator construction.

The research identifies the weak steps in composite indicator construction and the data characteristics which increase the volatility. Only an approach based on various alternative paths can control for it.

It offers some reflections on the extent to which gender disparities in labour market still persist in European countries and the different ways in which it manifests.

The analysis of characteristics and policies activated in countries at the top of the ranking can suggest initiatives to promote gender equality.

Besides of testing the robustness of results, an effort in order to identify the best way to obtain a synthetic and reliable single rank is made. Further, the results produced by the GGLMI for the year 2011 are presented and discussed.

A major consequence of global environmental change is projected to be the alteration in flood periodicity, magnitude, and geographic patterns. There are a number of extant methods designed to help identify areas vulnerable to these consequences, the construction of composite vulnerability indices prominent among them. In this paper we have implemented the Order Rated Effectiveness (ORE) model (Klimberg & Ratick, 2020) to produce composite flood vulnerability indicators through the aggregation of six constituent vulnerability indicators future projected for 204 hydrologic subbasins that cover the contiguous US. The ORE aggregation results, when compared with those obtained using the Weighted Linear Combination and Data Envelopment Analysis, provided a more robust and actionable distribution of composite vulnerability results for decision-makers when prioritizing Hydrologic Unit Codes for further analysis and for effectively and efficiently implementing adaptation and mitigation strategies to address the flooding consequences due to global climate change.

As technology in tourism and hospitality (TTH) develops technical artifacts according to visitors’ demands, it must deal with both behavioral and design constructs in the context of structural equation modeling (SEM). While behavioral constructs are typically modeled as common factors, the study at hand introduces the composite into TTH to model artifacts. To deal with both kinds of constructs, this paper aims to exploit partial least squares path modeling (PLS-PM) as a confirmatory approach to estimate models containing common factors and composites.

The study at hand presents PLS-PM in its current form, i.e. as a full-fledged approach for confirmatory purposes. By introducing the composite to model artifacts, TTH scholars can use PLS-PM to answer research questions of the type “Is artifact xyz useful?”, contributing to a further understanding of TTH. To demonstrate the composite model, an empirical example is used.

PLS-PM is a promising approach when the model contains both common factors and composites. By applying the test for overall model fit, empirical evidence can be obtained for latent variables and artifacts. In doing so, researchers can statistically test whether a developed artifact is useful.

To the best of the authors’ knowledge, this is the first study to discuss the practical application of composite and common factor models in TTH research. Besides introducing the composite to model artifacts, the study at hand also guides scholars in the assessment of PLS-PM results.

因为旅游酒店科技（TTH）根据游客需求而定制科技产品, TTH必须在结构方程模型（SEM）下结合游客行为和设计等变量。一般行为变量在模型中是常见因子, 本研究将这些变量编入TTH结构成为模块。本研究采用PLS-PM方法来预估含有隐性变量和模块的模型。.

本研究设计PLS-PM模式, 即确定性全变量方法。TTH学者们通过引进结构形成模型模块, 使用PLS-PM研究方法, 以回答研究问题“模块xyz有用吗？”, 因此对TTH进一步理解。为了展示复合模型, 本论文采用实际验证。.

PLS-PM在面对模块内存在常见因子和复合模块的结构时是有力方法。实际验证结果通过整体最佳模型参数, 得到隐性变量和模块。为此, 研究者们能够在统计方法上测量是否开发的模型模块是否有用。.

据作者所知, 本论文是首个研究在TTH领域上应用模块和常见因子模型。本研究引进显性变量在模型模块中, 以指导学者评估PLS-PM结果报告。.

The purpose of this study is to provide a series of indicators to determine the limits to urban tourism growth, tourism gentrification and overtourism. The study addresses overtourism within the frame of urban liveability through a proxy analysis of tourism-relevant indicators for major European tourist cities.

Based on the various indicators, a composite overtourism indicator is derived. The following dimensions are considered for the composite indicator: total number of overnight stays per relevant tourist area in km²; number of museum visitors per population; average annual change in total nights between 2009 and 2017; and foreign nights per population.

Based on the results, Venice is the city with the highest degree of overtourism, followed by Florence, Seville and Lisbon. The remaining cities have a lower than average overtourism potential as indicated by the negative z-score.

This study and the composite overtourism indicators are only a starting point that can lead to further research in the field. Recommendations for further studies include the assessment of visitor flow and overtourism at different times of the year and to expand the study to other European urban destinations.

The paper suggests that policymakers should use these indicators when managing urban tourism development and monitoring visitor growth. Furthermore, they can be a starting point from which to assess the impact of tourism on the quality of life of local residents.

This study provides a starting point from which to assess the causes for social unrest tied to overtourism. If the city under study is found to have a lower than average overtourism potential, this indicates that there may be other social or psychological issues at play apart from sheer overcrowding.

To date, there has been no composite indicator that considered the different numerical aspects of overtourism altogether. This study provides a set of key indicators and a composite overtourism indicator to provide a preliminary appraisal of overtourism as a demand-side phenomenon with evidence from a range of established European urban destinations.

Governments and funders are increasingly linking the funding of higher education institutions (HEIs) to their performance. Performance indicators (PIs) provide a means to measure and track performance of HEIs. The purpose of this paper is to provide a structured framework for mapping out key PIs and developing a composite index for measuring performance in HEIs.

The paper makes use of the analytic hierarchy process to develop the framework. The application of the framework is demonstrated through a case study.

A structured approach to determining key PIs and developing a composite index in HEIs is elaborated. The framework developed in this paper is consensus-based, knowledge-intensive, and allows input to and ownership of the decision process and its output.

While there are numerous PIs; organizational resources and capabilities to manage these PIs are usually limited. HEIs must manage and improve their performance within their unique contexts. This paper provides a methodology to do so.

The process of mapping out key PIs and developing composite indices for integrated performance measurement are not adequately understood and need further research. The framework discussed in this paper has not been elaborated on in previous publications.

To introduce the systemic approach towards measuring globalization of the economy that is based on the theory of systemic framework of national competitiveness and economic growth.

Construction of a composite index of global economy by the principal components analysis (PCA) on the basis of 83 individual indicators, linked into the seven spheres of national competitiveness in the period of contemporary globalization. The weights of single indicators in the composite index are determined by two levels: on the first level, the weights of the indicators in the subindices are determined, whereas on the second level the weights of the sub‐indices in the joint composite index of global economy are determined. Reliability of the composite indices is verified by Cronbach's α.

The results of the PCA indicate the high reliability of the joint composite index on the basis of five subindices, whereas the inclusion of the remaining two subindices – international business activities and government role – has lowered the reliability of the joint composite index. This finding is combined with many statistical limitations in the field of measuring globalization of economies.

The unavailability and incomparability of statistical data in the field of international business activities presented great obstacles to deeper analysis. Such analysis would be attainable above all by the international harmonization of hard data collecting and greater emphasis on development of qualitative surveys in the field of activities of transnational enterprises.

This paper develops the concept for monitoring and benchmarking globalization of economies which is founded on the comprehensive theory and solid methodology. It offers a useful tool for national policymaking.

This paper demonstrates an application of the Arbitrage Pricing Theory using canonical analysis as an alternative to the conventional factor analysis. Following the traditional view that asset prices are influenced by unanticipated economic events, the systematic effects of the major composite economic indices on a wide spectrum of industry returns are explored. The main conclusion is that profitability may be considered as the single most important factor that influences security returns. Also, the composite lagging economic indicators appear to be more useful to investors in forming market expectations than the composite leading economic indicators. Finally, it is argued that the composite index of coincident economic indicators do not exhibit any significant influence in the pricing of capital assets.

The purpose of this paper is to construct, for the first time, composite index for Egypt that measures the economic and social rights fulfillment (ESRF) based on socioeconomic surveys at the household/individual levels.

The paper highlights some of the statistical debatable issues about composite indices and focuses mainly on six of them. Those issues are indicators selection, handling missing data, identification of and dealing with outliers, scale of measurement, computing the margin of error, weights assigned for indicators and domains and aggregation method. Handling these problematic issues gave rise to a rigorous index.

The quality of economic and social rights fulfillment index (ESRFI) is judged by its bootstrap standard error. Based on these margin of errors, confidence intervals can be computed and rigorous comparisons across all disaggregation levels of the ESRFI can be made. The results shows that the overall index is accurate and representative in measuring the ESRF in Egypt. Comparisons between rural and urban regions indices show that the rural areas are always worse than the urban areas in all levels of dimensions, especially for the Right to Education and Adequate Housing.

The ESRFI is not very current because it is based on the 2010 Egyptian Household Conditions Observatory Survey (EHCOS), which is the latest published version of the survey with complete variables for the index data. When the next EHCOS becomes available, an updated ESRFI can be easily and quickly constructed.

The ESRFI could strengthen policy formulation that takes into account ESRF, especially by highlighting the situation in different regions and disaggregation levels.

The proposed ESRFI would strengthen policy formulation that takes into account ESRF, especially by highlighting the situation in different regions and different disaggregation levels.

The paper emphasizes the importance of recognizing and handling of the six problematic issues that arise when constructing composite indices. The paper presents the first ESRFI for Egypt and demonstrates the rigor of its construction.