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This study explores the direct and indirect effects of two components of food-related consideration of future consequences (CFCs), including CFC-Immediate and CFC-Future, on sustainable food attitudes (SFA) via food-related health and environmental concerns.

Partial least squares structural equation modeling technique was used on a data set of 664 Vietnamese consumers collected in Central Vietnam to evaluate measurement and structural models.

CFC-Immediate and CFC-Future as well as health and environmental concerns have positive effects on SFA. Indirect effects of CFC-Immediate on SFA via health concerns and CFC-Future on SFA via health/environmental concerns are also discovered.

Future studies should examine the impact of environmental values on CFCs, forming a more comprehensive understanding regarding the relationship between the two variables, especially by including a wider range of sustainable food types to gain diverse knowledge about sustainable food consumption.

Communicative messages should focus on both health and environmental concerns while emphasizing both immediate and more distant outcomes of sustainable food (fish) consumption for individuals with different dominant temporal orientations.

This study sheds light on the direct and hierarchical relationships among food-related CFCs, health and environmental concerns and SFA to better understand the intricate psychological process of sustainable food consumption.

This study aims to investigate the efficiency of Indian commercial banks from 2002 to 2018 using the stochastic frontier analysis.

This study uses the parametric approach of the stochastic frontier to examine the technical efficiency of banks acknowledging exogenous shocks, omitted variables and measurement errors, filling a gap in the existing financial literature. The scope of this study was constrained to 71 scheduled commercial banks to make it manageable and productive with 1,036 observations.

The results show that the mean technical efficiency of new private banks remained constant at 92.7% during the study period because of technology diffusion in banking systems. The technical efficiency of the nationalized, old private and foreign banks has enhanced over the period because of the efficient utilization of various innovative information technology services such as mobile banking, cheque truncation system, magnetic ink character recognition. However, the foreign banks are still laggards with a mean technical efficiency of 81.7%. The empirical findings suggest that new private sector banks depict higher efficiency than nationalized, old private and foreign banks.

This study’s sample represents all categories of banks (public, private and foreign) including the banks that merged or consolidated during the period of study. To achieve the desired results, the authors incorporate the consolidated and merged banks in their data set. Further, the authors excluded all scheduled small finance banks and scheduled payment banks from their analysis, as these entities commenced operations post-2015. Additionally, the authors also excluded regional rural banks because of their distinct mandate aimed at servicing the rural populace and agricultural sector.

This study contributes to the literature on the performance of conventional banks in general and emerging markets, in particular, using the most recent data and covering a relatively long period using the stochastic frontier approach.

Recent advances in stochastic frontier analysis (SFA) suggest two alternative approaches to account for unobserved heterogeneity and to distinguish between persistent and transient inefficiency. The first approach is the generalized true random effects (GTRE) model, and the second approach is an autoregressive inefficiency (ARI) model. This study compares them to highlight whether they capture similar inefficiency aspects.

Using recent methodological advances in SFA, the authors estimate the GTRE and the ARI models using a Monte Carlo experiment and two real datasets from two industries (banking and agriculture).

The authors find that the two models provide quite different results in terms of inefficiency persistence and overall inefficiency (combination of transient and persistent inefficiency), regardless of the dataset considered.

The study findings suggest that researchers should be careful when referring to these two models because they do not capture the same inefficiency aspects, even though they have the same conceptual basis. This work is a warning about the empirical aspects of the persistent and transient efficiency framework, in order to convey a consistent story to the reader on firms' performance.

Even though they are used in a large number of studies, the present paper contributes to the productivity and efficiency literature by providing the first comparison of the GTRE and the ARI models.

While firms in developing countries are increasingly adopting lean practices of inventory management, there is limited evidence showing the impact of lean practices on firm performance in countries such as India. Lean practices improve the financial performance of the firms through superior cost-reduction measures and operational efficiencies. This paper examines the impact of inventory leanness in Indian manufacturing firms on their financial performance.

The authors measure inventory leanness based on stochastic frontier analysis (SLA), apart from using conventional measures available in the literature. The authors analyze the impact of inventory leanness on the financial performance of firms by examining data for 12,334 unique Indian manufacturing firms for the period 2009–2018. The authors present a comparative analysis using different methods of inventory leanness and study the effects on firm performance.

First, the authors find that only 68 industries out of 411 industries follow lean practices, i.e. most industries do not follow lean practices. Second, the estimation results show that there exists a positive relationship between inventory leanness and firm performance. The results suggest that an inverted U-shaped relationship exists between inventory leanness and firm performance for the entire sample. In particular, 17% of the industries in the sample exhibit such a relationship, and it is sufficiently strong to show up in the average regression results for the entire sample.

The authors introduce a novel measure of inventory leanness named stochastic frontier leanness based on the SFA method used in production economics. It measures leanness by benchmarking the inventory levels against the industry “frontier”. Furthermore, the authors conduct an empirical study of the lean-financial performance relationship with a large panel dataset of Indian firms instead of the survey-based methods that were previously used in the literature.

This paper aims to analyze the technical efficiency of Indian State governments in providing elementary education (EE) and to identify the determinants of their technical inefficiency.

The Generalized Stochastic Frontier Approach (GSFA) is used in the context of the Inefficiency Effects Model to simultaneously estimate the frontier production function and the technical inefficiency model. Panel data of 28 Indian States from 2009–10 to 2018–19 is used.

The mean efficiency of States stands at 86%. Efficiency varied between 67 and 97%. 96% of the inter-state disparity in EE outcomes can be explained by inefficiency. Arunachal Pradesh is the least efficient State, followed by Sikkim and Tripura. Efficiency estimates were observed to change across States over the study period. Proportion of government schools, rural population, and proportion of Schedule Caste and Schedule Tribe children are the major determinants of inefficiency.

This study emphasizes that efficient resource management is as important as adequate resource allocation for achieving positive EE outcomes. It distinguishes resource-poor States from inefficient ones, providing insights to enhance States’ efficiency, and aiding policymakers in formulating strategies for ensuring equitable and quality EE.

This is the first paper to apply GSFA (for Indian States), providing a more robust estimation of efficiency. The Inefficiency Effects Model is employed that address the limitations inherent in the two-stage approach.

The study seeks to shed light on the estimates of the carbon shadow price in the literature relying on frontier techniques. The shadow price of undesirable outputs, such as greenhouse gas emissions, assists policymakers in determining the most cost-effective methods for reducing emissions.

The study relies on the PSALSAR and PRISMA approaches for a systematic literature review. The Web of Science and Scopus databases were used for the references.

Both parametric and nonparametric methods have been employed in the literature to estimate the shadow prices of undesirable outputs. Also, results were discussed according to the methodological and application aspects, and broad conclusions on obtained results were provided, bridging climate change mitigation policies and the shadow price of undesirable outputs.

The present study applies an integrated method, PSALSAR, to conduct a systematic review of 53 studies published between 2014 and 2023 in which efficiency models were applied to estimate the shadow price of undesirable outputs, especially CO₂. After presenting the most applicable parametric and nonparametric estimation models, a systematic summary of included articles was provided, highlighting the key features of publications.

This study aims to investigate whether the changes in gender composition of bank board affects Vietnamese bank stability efficiency.

This research covers a panel of 27 commercial banks in Vietnam over a 14-year period from 2007 to 2020. The two-step system generalized method of moments is used to estimate the gender diversity–Vietnamese bank stability efficiency nexus.

The authors find that a greater degree of board gender diversification enhances bank stability efficiency and reduces bank risk-taking in Vietnam. The relationship between gender diversity and the stability efficiency of Vietnamese banks is still valid under the influence of regulatory capital sufficiency and during the financial crisis. These findings are robust to alternative proxies for risk indicators and consistent with the perspectives of stakeholder and behavior theory.

Although this research revisits the relationship between gender diversity and bank risk-taking, it is the first attempt to explore the role of women on board in enhancing the stability efficiency of banks, using the stochastic frontier approach. These findings shed light on the function of gender diversity as a governance instrument for mitigating risk in an emerging market context.

The study aims to enhance energy efficiency within the high-energy consuming construction industry. It explores the spatial-temporal dynamics and distribution patterns of total factor energy efficiency (TFEE) across China’s construction industry, aiming to inform targeted emission reduction policies at provincial and city levels.

Utilizing a three-stage super-efficiency SBM-DEA model that integrates carbon emissions, the TFEE in 30 Chinese provinces and cities from 2004 to 2019 is assessed. Through kernel density estimation and exploratory spatial data analysis, the dynamic evolution and spatial patterns of TFEE are examined.

Analysis reveals that environmental investments positively impact TFEE, whereas Gross Regional Product (GRP) exerts a negative influence. R&D expenditure intensity and marketization show mixed effects. Excluding environmental and random factors, TFEE averages declined, aligning more closely with actual development trends, showing a gradual decrease from east to west. TFEE exhibited fluctuating growth with a trend moving from inefficient clusters to a more even distribution. Spatially, TFEE demonstrated aggregation effects and characteristics of space-time transition.

This research employs the three-stage super-efficiency SBM-DEA model to measure the total factor energy efficiency of the construction industry, taking into account external environment, random disturbances, and multiple effective decision-making units. It also evaluates energy efficiency changes before and after removing disturbances and comprehensively examines regional and temporal differences from static and dynamic, overall and phased perspectives. Additionally, Moran scatter plots and LISA cluster maps are used to objectively analyze the spatial agglomeration and factors influencing energy efficiency.

Disasters are occurring worldwide, and Sri Lanka has also become a victim of multiple disasters. Though there is a disaster management mechanism from the national level to the local level in Sri Lanka, several gaps are identified in pre- and postdisaster management activities. Among them, the responsibilities of local-level stakeholders in flood management activities are not performing at a satisfactory level. Therefore, the flood damage from the previous events was too great. Accordingly, the purpose of this study is to assess the roles, responsibilities and performance of stakeholders involved in local-level flood risk management activities.

The Deduru Oya basin in Sri Lanka was selected as the study area. The study hypothesized that “ineffective roles, responsibilities and performance of local level stakeholders have weakened the flood risk management in the Deduru Oya basin.” The stratified random sampling method selected the sample (n = 425) from the flood-vulnerable population. Primary data were collected through a questionnaire survey, key informant interviews and field observations. Secondary data were collected from reports, work plans, journal papers and published maps. Descriptive data analysis methods and thematic data analysis methods were used in the study.

About 69% of the respondents state that they are not satisfied with the involvement of government agencies in local-level flood risk management activities, while 10% of the respondents state that they are satisfied. The thematic analysis reveals several gaps, such as the lack of reservations in the Deduru Oya, improper land use practices, no inundation areas are identified and mapped out and the effects of illegal sand mining in the Deduru Oya. In addition to that, the lack of legal power vested in local governments in disaster management and the weaknesses of current legislation on flood risk management are the other major courses of local-level ineffectiveness.

The current research was limited to studying the involvement of local-level stakeholders in flood risk management, but the involvement of subnational and national-level stakeholders should be studied in future research.

This paper examines the involvement of local-level stakeholders in flood risk management. The results of the study confirm that the roles and responsibilities of local-level stakeholders are not well-defined and mandated, and therefore, the performance of stakeholders involved is minimal. Therefore, the results highlight the need for a well-established community-based flood risk management mechanism.

This paper aims to examine how the rise of financial technology (Fintech) lending affects bank competition. Moreover, this study also identifies the structure of Indonesian commercial banking sector and the different behaviour of competition among bank groups (based on their size, type and ownership) and the joint impact of COVID-19 due to the rise of Fintech lending.

Using an unbalanced panel data set of 118 commercial banks in Indonesia over the period 2018–2022, both static panel and 2SLS/IV data analysis were used and found that random effect model is the best model.

The results show that the Indonesian commercial banking sector can be considered as monopolistic competition. Moreover, using the Lerner index reveals that the entry of the Fintech lenders increases bank competition. Furthermore, there were different responses to the impact of Fintech lending on bank competition among state-owned banks, private banks, regional development banks and foreign banks. Greater efficiency and stability lead to greater market power. In the meantime, higher level of asset growth, capitalisation and cost-to-income ratio increase the competition. Lastly, higher bank credit growth and lower inflation boost overall bank competitiveness.

This study highlights some policy recommendations for commercial banks to be aware of the coming of Fintech lenders because they have started to increase the market competition. The government should create a more collaborative ecosystem between banks and Fintech lending to anticipate unhealthy competition.

This study will contribute to the literature by expanding the determinants of bank competition by considering the rise of Fintech lending in the market.