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This paper aims to investigate the debated nexus of financial inclusion (FI) and financial stability (FS) in a comprehensive way, with several indicators of FI, considering nonlinearity and cross-country heterogeneity.

The authors introduce several indexes for FI by applying principal component analysis (PCA) and explore their impact on stability for a sample of 108 countries and subsamples based on income grouping as well as for pre- and post-crisis episodes over the period 2004–2017. To address the heterogeneity and endogeneity, the authors use the two-step quantile regression (2SQR), three-stage least square (3SLS) and two-step system-GMM (System-GMM).

The findings reveal that the relationship of FI and stability depends on the measurement of FI used and the heterogeneity of different macroeconomic factors. Besides, there is nonlinearity, irrespective of the measurement of inclusion used. The findings also confirm that the effect of FI is more prominent in countries with strong governance. The results are robust to several robustness validations, which could be useful for policymakers to align the divergence of these policies and ensure FS while expanding access to formal financial services.

This study makes an attempt to explore the reasons behind the debated empirical findings of the existing literature by revisiting the nexus using several disaggregated indexes, each representing individual dimension and a multidimensional index, examine the possible nonlinearity and investigate the conditioning effect of different macroeconomic factors that might play a significant role in this relationship.

The purpose of this paper is to measure and map the potential transportation network impedance to last-mile delivery (LMD) using spatial measures representing attributes of road network and planning controls.

The transport network impedance is estimated as the potential hindrance to LMD as imposed by the characteristics of the built and regulatory environment. A matrix of key transport and planning measures are generated and overlaid in geographical information systems to compute and visualise the levels of transportation network impedance to LMD using a composite indexing method.

The mapped outputs reveal significant spatial variation in transportation network impedance to LMD across different part of the study area. Significant differences were detected along the road segments that connect key industrial hubs or activity centres especially along tram routes and freight corridors, connecting the Port of Melbourne and logistic hub with the airport and the Western Ring Road.

The use of static measures of transport and urban planning restricts the robustness of the impedance index, which can be enhanced through better integration of dynamic and real-time movements of business-to-business LMD of goods. Spatial approach is valuable for broader urban planning at a metropolitan or council level; however, its use is somewhat limited in assisting the daily operational planning and logistics decision making in terms of dynamic routing and vehicle scheduling.

The built and regulatory environment contributes to the severity of LMD problem in urban areas. The use of land use controls as instruments to increase city compactness in strategic nodes/hubs is more likely to deter the movement of urban freight. The mapped outputs would help urban planners and logisticians in mitigating the potential delay in last-mile deliveries through devising localised strategies such as dedicated freight corridors or time-bound deliveries in congested areas of road network.

This is the first study that measured the potential transport network impedance to LMD and improved understanding of the complex interactions between urban planning measures and LMD. Micro-scale mapping of transportation network impedance at the street level adds an innovative urban planning dimension to research in the growing field of city logistics.

The purpose of this paper is to examine the causal relationship between Chinese housing and stock markets. The authors discuss the three transmission mechanisms between the two markets: wealth effect, modern portfolio theory and credit-price effect. Moreover, the authors focus on the effects of inflation on the relationship between the two markets.

This paper uses wavelet analysis to test the housing and stock markets relationship both in the frequency domain and time domain.

The empirical results indicate that housing prices have a positive effect on stock prices, and these have the same effect on housing prices. Moreover, this positive effect means that stock prices have a wealth effect on housing prices and these have a credit-price effect on stock prices.

These results provide information to financial institutions and individual investors in China to assist them in constructing investment portfolios within these two asset markets.

The authors first use wavelet analysis to analyze Chinese housing and stock markets and to provide information both on the frequency domain and time domain. Moreover, the authors take the inflation factor as a control variable in the causal relationship between the housing and stock markets.

Poverty is one of the most significant economic and social problems that European countries have to face. In recent years, it has become widely accepted that poverty is a multidimensional concept and now many studies use indicators of deprivation to examine the phenomenon. The focus on financial resources alone does not capture people’s quality of life as being poor means a lack of access to resources enabling a minimum standard of living and participation in the society within which one belongs. The paper aims to discuss this issue.

Using a longitudinal component (2006-2010) of EU Statistics on Income and Living Conditions data on 26 European countries, the author apply a second-order confirmatory factor analysis to estimate deprivation. To describe the patterns of change over time and to evaluate the role of household characteristics in deprivation level, the author employ a set of multilevel growth curve models.

Three findings clearly stand out from my analysis. First, there is great variability in deprivation between European countries. Second, European countries show various patterns of change in deprivation over time. Third, households with different characteristics have quite different deprivation levels; moreover, the impact of household characteristics on deprivation can vary over time and between countries.

This paper sheds light on the importance of analysing deprivation from a longitudinal perspective and that financial resources alone does not capture people’s quality of life.

The Tata owned Coastal Gujarat Power Limited is seeking to reopen Power Purchase Agreements (PPAs) with state owned distribution utilities because of increase in imported coal prices resulting from a change in Indonesian laws. The Central Electricity Regulatory Commission (CERC) has decided to provide relief through a “compensatory tariff”. This is opposed by the power purchasers. Simultaneously, another Reliance Energy owned power project is seeking relief from unprecedented change in exchange rates using the CGPL decision as a precedent. The CERC and the power purchasers have to decide what to do next.

Ranking and grading of architectural heritage (AH) are common for the conservation process. Decision-makers are often intuitively made decisions for the selection of the AH. However, on many occasions, these decisions are not transparent and sometimes focused only on a few aspects of the AH.

A transparent and robust methodology must be adopted to select and manage AH for the present and future generations. Selecting the list of parameters that are affecting the AH, and assessing their significance can strengthen the holistic assessment. From the literature, parameters and dimensions are identified for the evaluation of AH and its application for Odishan temple architecture (OTA). For minimizing biasedness associated with assessment, the research considered the opinion of experts, researchers and various stakeholders. For objective decision-making, the Delphi, the analytical hierarchy process (AHP) and the technique for order preference by similarity to ideal solutions (TOPSIS) methods were adopted.

Later, by observing the dimension-wise ranks and comparing the obtained grading of OTA with the existing state of protection, it was found that some temples, though having higher values with distinct dimension, lack significantly in other dimensions. However, for unbiased evaluation, all the possible dimensions should be considered. This methodology will also be useful for other decision-making processes concerning the same.

This research is limited to the OTA. However, this methodology can be adopted by changing the definitions of the parameters according to the contextual needs.

This methodology may be helpful for the further policy-making process for the conservation and management of such AH.

To date, OTA is not graded through such a methodology. Also, limited studies are found in similar line worldwide.

The purpose of this paper is to examine how the ranking of countries based on the World Economic Forum's (WEF') competitiveness index is changed when the underlying primitive data dimensions of this composite index are aggregated using weights that are endogenously determined for each country, instead of aggregated using the WEF's fixed set of weights applied to all countries.

The paper presents a method based on data envelopment analysis to determine weights for aggregating the underlying primitive data dimensions of any composite indicator. The approach determines endogenously the “best” weights a given observational unit (e.g. country) on the basis of its revealed performance on each primitive sub‐dimension underlying a composite index. The ranking of countries based on the values of a composite competitiveness index that uses the proposed endogenous weight method is then compared to the ranking based on the WEF's competitiveness index for the year 2006. The rankings are then compared and assessed to determine if the observed difference in the rankings are statistically significant.

A comparison of the ranking of countries on the basis of the value of each index reveals that countries do undergo a change in their competitiveness rank when endogenous weights are used. The results suggest the WEF's competitiveness index, which uses the same fixed weights applied to every country (or group of countries), creates a bias that favors countries that score high on the “technology” sub‐dimension of the index.

The study presents an alternative to the current practice of using a fixed set of weights applied uniformly to the basic unit of analysis. The method serves as a starting‐point for further research on the biases created by different weighting schemes to construct a composite indicator that aggregates primitive data, with the resulting composite index values then used to rank entities.

The method to determine endogenously the weights to be applied to each unit of analysis when constructing a composite indicator is novel and has wide applicability to the general issue of comparing performance across different units of analysis based on a composite index of performance (i.e. benchmarking).

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.

This work aims to establish the relationship between painting art and sustainability, which allows for highlighting implications likely to improve sustainability for humanity's welfare.

To achieve this objective, painting art is measured by a composite index aggregating the quantity and quality represented by the market value. As for sustainable development, it is represented by a composite index comprising three variables: the climate change performance index (ecological dimension), the wage index reflecting distributive justice (social dimension) and the gross domestic product (economic dimension). The composite indices were determined through adjusted data envelopment analysis. In addition, two other methods are used in this work: correlation analysis and a neural network method. These methods are applied to data from 2007 to 2021 across the world.

The correlation method highlighted a perfect positive correlation between painting art and sustainability. As for the neural network method, it revealed that the quality of painting has the greatest impact on sustainability. The neural network method also showed that the most positively impacted variable of sustainability by painting art is the social variable, with a pseudo-probability of 0.90.

The relationship between painting art and sustainability is underexplored, in particular in terms of statistical analysis. Therefore, this research intends to fill this gap. Moreover, analysis of the relationship between both using composite indices computed via an original method (adjusted data envelopment analysis) and a neural network method is nonexistent, which constitutes the novelty of this work.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-01-2023-0006

Most composite indicators of national performance limit their scope to only economic performance criteria and aggregate primitive performance data using subjective fixed weight values applied uniformly to all countries. This paper proposes a weighting method to correct for biases inherent in the use of fixed and uniform weights, and it presents a composite performance indicator that encompasses both economic and non‐economic performance criteria.

The paper presents a method that endogenously determines country‐specific weights that explicitly take account of a country's own choices and achievements across primitive dimensions of performance. The method is then used to construct a composite inclusive index that combines economic performance with two other performance dimensions: environmental sustainability and governance.

Comparison of the endogenous weight method with the method of using fixed and uniform weights indicates a bias in the latter that penalizes countries, in terms of indicating lower relative performance, which are more diverse in their achievements among primitive performance dimensions. When the endogenous weight method is used, the performance ranking of countries is altered such that countries with greater diversity improve their relative performance while the relative performance of countries having less diversity may either rise or fall.

The weighting method discussed in this paper: is applicable at any level of analysis (e.g. nations, companies, business units, etc.), obviates objections about the “importance” of alternative primitive dimensions that can arise when subjective fixed weights are used; and indicates more accurately relative performance since each unit of analysis is first allowed to obtain its best performance before relative performance is assessed. The method can therefore assist policy makers, companies, etc. to more accurately benchmark performance and it can, in particular, assist companies to respond to perceptions of low performance or compliance among different performance dimensions when performance has been determined using the traditional method of fixed and uniform weights.