Search results

Assessing inputs and outputs is a significant aspect of taking decisions while there are complex and multistage processes in many examinations. Due to the presence of interval performance measures in various real-world studies, the purpose of this study is to address the changes of interval inputs of two-stage processes for the perturbations of interval outputs of two-stage systems, given that the overall efficiency scores are maintained.

Actually, an interval inverse two-stage data envelopment analysis (DEA) model is proposed to plan resources. To illustrate, an interval two-stage network DEA model with external interval inputs and outputs and also its inverse problem are suggested to estimate the upper and lower bounds of the entire efficiency and the stages efficiency along with the variations of interval inputs.

An example from the literature and a real case study of the banking industry are applied to demonstrate the introduced approach. The results show the proposed approach is suitable to estimate the resources of two-stage systems when interval measures are presented.

To the best of the authors’ knowledge, there is no study to estimate the fluctuation of imprecise inputs related to network structures for the changes of imprecise outputs while the interval efficiency of network processes is maintained. Accordingly, this paper considers the resource planning problem when there are imprecise and interval measures in two-stage networks.

The authors' work aims to identify the employer-specific drivers of the college (or university) wage gap, which has been identified as one of the major determinants of the dynamics of overall wage and income inequality in the past decades. The authors focus on three employer-level features that can be associated with asymmetries in the employment relation orientation adopted for college and non-college-educated employees: (1) size, (2) the share of standard employment and (3) the pervasiveness of incentive pay schemes.

The authors' establishment-level analysis (data from the Basic Survey on Wage Structure (BSWS), 2005–2018) focusses on Japan, an economy characterised by many unique economic and institutional features relevant to the aims of the authors' analysis. The authors use an adjusted measure of firm-specific college wage premium, which is not biased by confounding individual and establishment-level factors and reflects unobservable characteristics of employees that determine the payment of a premium. The authors' empirical methods account for the complexity of the relationships they investigate, and the authors test their baseline outcomes with econometric approaches (propensity score methods) able to address crucial identification issues related to endogeneity and reverse causality.

The authors' findings indicate that larger establishment size, a larger share of regular workers and more pervasive implementation of IPSs for college workers tend to increase the college wage gap once all observable workers, job and establishment characteristics are controlled for. This evidence corroborates the authors' hypotheses that a larger establishment size, a higher share of regular workers and a more developed set-up of performance pay schemes for college workers are associated with a better capacity of employers to attract and keep highly educated employees with unobservable characteristics that justify a wage premium above average market levels. The authors provide empirical evidence on how three relevant establishment-level characteristics shape the heterogeneity of the (adjusted) college wage observed across organisations.

The authors' contribution to the existing knowledge is threefold. First, the authors combine the economics and management/organisation literature to develop new insights that underpin the authors' testable empirical hypotheses. This enables the authors to shed light on employer-level drivers of wage differentials (size, workforce composition, implementation of performance-pay schemes) related to many structural, institutional and strategic dimensions. The second contribution lies in the authors' measure of the “adjusted” college wage gap, which is calculated on the component of individual wages that differs between observationally identical workers in the same establishment. As such, the metric captures unobservable workers' characteristics that can generate a wage premium/penalty. Third, the authors provide empirical evidence on how three relevant establishment-level characteristics shape the heterogeneity of the (adjusted) college wage observed across organisations.

The tourism multiplier effect (TME) is the total economic impact of tourism demand, representing the linkages between tourism and other businesses in an area. However, study about it is limited in Indonesia, especially at the provincial level and after the COVID-19 crisis. This study aims to estimate the TME in all provinces of Indonesia, test its differences in priority and non-priority areas before and after the COVID-19 crisis, analyze its spatial distribution and examine the determinant factor of TME

This study applies an input-output model to measure the TME of all provinces in Indonesia, an independent sample t-test to examine the similarity of TME in priority and nonpriority areas, a paired sample t-test to examine the similarity of it before and after the COVID-19 crisis, and spatial analysis to check its spatial relationship.

The result shows that regional TME ranges from 1.25 to 2.05 in 2019, which changed slightly over time. The empirical result shows the TME difference before and after the COVID-19 crisis, and there is a spatial correlation in terms of TME with the hot spots are clustered in the eastern region of Indonesia, However, there was a slight change in the position of hot spots during the COVID-19 crisis. Moreover, the spatial model shows that value-added and employment in agriculture, manufacturing, trade and transportation affect the size of TME.

This study contributes to the academic literature by providing the first estimate of the TME at the provincial level in Indonesia, comparing the it in priority and non-priority areas before and after the COVID-19 crisis, and mapping its spatial distribution.

The purpose of this study is to analyse the gender wage gap (GWG) in Spain adopting a labour market segmentation approach. Once we obtain the different labour segments (or idiosyncratic labour markets), we are able to decompose the GWG into its observed and unobserved heterogeneity components.

We use the data from the Continuous Sample of Working Lives for the year 2021 (matched employer–employee [EE] data). Contingency tables and clustering techniques are applied to employment data to identify idiosyncratic labour markets where men and/or women of different ages tend to match/associate with different sectors of activity and occupation groups. Once this “heatmap” of labour associations is known, we can analyse its hottest areas (the idiosyncratic labour markets) from the perspective of wage discrimination by gender (Oaxaca-Blinder model).

In Spain, in general, men are paid more than women, and this is not always justified by their respective attributes. Among our results, the fact stands out that women tend to move to those idiosyncratic markets (biclusters) where the GWG (in favour of men) is smaller.

It has not been possible to obtain remuneration data by job-placement, but an annual EE relationship is used. Future research should attempt to analyse the GWG across the wage distribution in the different idiosyncratic markets.

Our combination of methodologies can be adapted to other economies and variables and provides detailed information on the labour-matching process and gender wage discrimination in segmented labour markets.

Our contribution is very important for labour market policies, trying to reduce unfair inequalities.

The study of the GWG from a novel labour segmentation perspective can be interesting for other researchers, institutions and policy makers.

Using bibliometrics, this study aims to explore the intellectual structure of social segregation research, key contributors, thematic areas and hotspot topics.

A bibliometric analysis was performed for more than 15,000 research papers listed in one of the famous, rich and widely used scientific databases: Web of Science (WoS). This review approach was used to identify social research hotspots on segregation, intellectual structure, borders and development trends. VOSviewer and Gephi software were employed for mapping and analysis.

The study indicates a marked increase in segregation research, particularly from a spatial/urban perspective. The study reveals the interrelationship between segregation and many other social concepts, such as social equality, cohesion, integration and inclusion. In conclusion, addressing the ramifications resulting from the multiple forms of segregation will help in implementing social policies and evaluating their impact on achieving inclusive social development in general and the 2030 agenda of Sustainable Development Goals (SDGs) in specific.

This study remains limited to the precision and thoroughness of the bibliographic data gained from WoS.

This study is valuable for readers to gain rich insights into the state of research on social segregation. It also provides ideas for future research that prospective authors and interested research and academic institutions can investigate.

This article aims to evaluate the entry and exit of companies from local productive structures, with a specific focus on the sectoral complexity of these activities and the complexity of these portfolios. The study focuses on empirically demonstrating the thesis that related economic diversification exacerbates the development gap between more and less complex regions.

The article uses indicators formulated by the economic complexity approach. They allow a relevant descriptive analysis of the economic diversification process in Brazilian micro-regions and provide the foundation for the econometric tests conducted. Through three distinct estimation strategies (OLS, logit, probit), the influence of complexity and relatedness on the entry and exit events of firms from local portfolios is tested.

In all estimated models, the stronger relationship between an activity and a portfolio significantly increases its probability of entering the productive structure and, at the same time, acts as a significant factor in preventing its exit. Furthermore, the results reveal that the complexity of a sector reduces the probability of its specialization in less complex regions while increasing it in more complex regions. On the other hand, sectoral complexity significantly increases the probability of a sector leaving less complex local structures but has no significant effect in highly complex regions.

Due to the data used, the indicators are calculated considering only formal job numbers. Additionally, the tests do not detect the influence of spatial issues. These limitations should be addressed by future research.

The article characterizes a prevailing process of uneven development among Brazilian regions and brings relevant implications, primarily for policymakers. Specifically, for less complex regions, policies should focus on creating opportunities to improve their diversification capabilities in complex sectors that are not too distant from their portfolios.

The article makes an original contribution by proposing an evaluation of regional diversification in Brazil with a focus on complexity, introducing a more detailed differentiation of regions based on their complexity levels and examining the impact of sectoral complexity on diversification patterns within each group.

The present study examines the significance of financial inclusion in reducing income inequality in the Asian context.

This study uses panel estimation techniques such as the Pedroni cointegration test, Kao residual-based test, FMOLS, ARDL and Granger causality, a dataset consisting of the Gini coefficient index, three dimensions of financial inclusion measures and one added variable on financial depth, spanning from 2005 to 2019.

The study finds that in the long-run, income inequality disparity is highly influenced by financial inclusion indicators, such as the number of bank branches, deposit accounts, outstanding loans and domestic credit to the private sector. Whereas in the short run, disparities in income are unaffected by all the indicators of financial inclusion. Further, unidirectional causality from financial inclusion indicators to income inequality necessitates the need for policymakers to design policies and programs that would enhance access to financial services as an essential mechanism to reduce income disparity.

Studies based on a panel of Asian countries that have undergone impressive growth of financial inclusion initiatives since the past decade—but are still facing widening income inequality—are conspicuously rare in the literature. The empirical analysis fills this void by showing the significant role financial inclusion indicators play in steering the Asian economies toward income equality throughout the study period.

The study aims to delve into the influence of tourism on the happiness of city residents, grounded in the overarching concept of livability. It posits that prioritizing residents’ happiness is crucial for effectively addressing cities’ challenges in balancing development and distinctiveness. The study pursues three primary objectives: first, establishing a potential correlation between city tourism and residents’ happiness; second, examining the contributing factors to this correlation and third, identifying potential mediators that influence the connection between tourism development and residents’ happiness.

Using a quantitative single-case design and partial least square analysis, the study underscores the intricate nature of various tourism development components. It specifically explores the roles of cognitive flexibility and social comparison in shaping the relationship between city tourism and happiness.

The findings make a distinctive contribution by revealing that not all tourism domains contribute positively to happiness. Furthermore, it sheds light on how tourism development impacts the emotional and cognitive dimensions of happiness, emphasizing the adverse effects of inequality and feelings of insecurity.

The study acknowledges certain constraints, including its employment of a cross-sectional design, the issue of generalizability, potential sampling bias and the reliance on subjective measurements when evaluating constructs like happiness and satisfaction with life. Using self-reported data introduces susceptibility to social desirability bias and individual perceptual differences, potentially resulting in measurement inaccuracies. Nevertheless, despite these limitations, the study’s findings offer valuable insights that contribute to both theoretical advancement and the realm of urban management.

The findings elucidated through the mediation analyses conducted for hypotheses three to seven shed light on the significant roles played by mental adaptation and social comparison mechanisms in shaping individuals’ happiness. These insights substantially enhance our understanding of this field. Particularly, the dimensions of social and environmental impact within tourism appear to counterbalance the positive effects stemming from the economic and cultural aspects. This suggests a scenario where an excessive focus on tourism development could potentially undermine the overall livability of the city. These outcomes further indicate the necessity for proactive interventions by destination managers. Their efforts should be directed toward enhancing the environmental and social domains, aiming to reinvigorate the sense of community among residents, which appears to be gradually waning.

The outcomes of this study emphasize the utmost significance of prioritizing residents’ happiness above mere considerations of economic growth when formulating efficacious strategies for tourism. By concentrating on the happiness of the local population, a harmonious resonance is established with Sustainable Development Goal 11, which advocates for the creation of habitable cities founded upon the principle that “a city that is not good for its citizens is not good for tourists.” This alignment underscores the interconnected nature of residents’ happiness and the sustainable development of tourism. Moreover, residents’ happiness plays a pivotal role in addressing the challenge that cities face in harmonizing growth and their uniqueness, ensuring competitiveness and sustainability.

The research underscores the need for a people-oriented perspective in urban planning and tourism development initiatives. The study identifies diverse factors impacting residents’ happiness in city tourism, highlighting the complex interplay of environmental, cultural and socioeconomic elements. It emphasizes income’s role but underscores nonmaterial factors and individual preferences. Overall, the study offers timely and valuable insights into the intricate connection between tourism development, residents’ happiness, living conditions and human perception, guiding urban planners and stakeholders.

This study aims to analyze and compare the relationship between international trade in global value chains (GVC) and greenhouse gas (GHG) emissions for Brazil and China from 2000 to 2016.

The input-output method apply to multiregional tables from Eora-26 to decompose the GHG emissions of the Brazilian and Chinese productive structure.

The data reveals that Chinese production and consumption emissions are associated with power generation and energy-intensive industries, a significant concern among national and international policymakers. For Brazil, the largest territorial emissions captured by the metrics come from services and traditional industry, which reveals room for improving energy efficiency. The analysis sought to emphasize how the productive structure and dynamics of international trade have repercussions on the environmental dimension, to promote arguments that guide the execution of a more sustainable, productive and commercial development strategy and offer inputs to advance discussions on the attribution of climate responsibility.

The metrics did not capture emissions related to land use and deforestation, which are representative of Brazilian emissions.

Comparative analysis of emissions embodied in traditional sectoral trade flows and GVC, on backward and forward sides, for developing countries with the main economic regions of the world.

The principal aim of this study is to examine the relationship between financial development and income inequality in India using the financial Kuznets curve (FKC) hypothesis.

This study uses the autoregressive distributed lag (ARDL) model and the Toda–-Yamamoto causality test to investigate the long-run and short-run relationship and causality between financial development and income inequality. In addition, this study employs a principal component analysis (PCA) to construct a comprehensive financial development index.

The study found a long-run relationship between financial development and income inequality in India for the period under consideration. Trade is found to improve the income distribution, while inflation worsens income distribution. Moreover, the empirical results revealed a feedback causality between financial development and income inequality. The study results confirm an inverted U-shaped relationship between financial sector development indicators and income inequality, thus validating the FKC hypothesis for the Indian economy.

The study draws attention of the government and policymakers, urging them to focus on building a strong financial sector by improving its efficiency. This, in turn, will lead to enhanced financial stability and a reduction in income inequality. They should prioritise the development of high-quality and sustainable financial products and services to ensure the robust growth of the financial sector.

To the best of our knowledge, this study is the latest of its kind to empirically test the financial development on income inequality and the FKC hypothesis simultaneously for the Indian economy using financial proxy variables from financial institutions (FIs) and financial markets (FMs) for the measurement of financial depth.