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This study aims to treat a novel system of Volterra integro-differential equations with multiple delays and variable bounds, constituting a generic numerical method based on the matrix equation and a combinatoric-parametric Charlier polynomials. The proposed method utilizes these polynomials for the matrix relations at the collocation points.

Thanks to the combinatorial eligibility of the method, the functional terms can be transformed into the generic matrix relations with low dimensions, and their resulting matrix equation. The obtained solutions are tested with regard to the parametric behaviour of the polynomials with $\alpha$, taking into account the condition number of an outcome matrix of the method. Residual error estimation improves those solutions without using any external method. A calculation of the residual error bound is also fulfilled.

All computations are carried out by a special programming module. The accuracy and productivity of the method are scrutinized via numerical and graphical results. Based on the discussions, one can point out that the method is very proper to solve a system in question.

This paper introduces a generic computational numerical method containing the matrix expansions of the combinatoric Charlier polynomials, in order to treat the system of Volterra integro-differential equations with multiple delays and variable bounds. Thus, the method enables to evaluate stiff differential and integral parts of the system in question. That is, these parts generates two novel components in terms of unknown terms with both differentiated and delay arguments. A rigorous error analysis is deployed via the residual function. Four benchmark problems are solved and interpreted. Their graphical and numerical results validate accuracy and efficiency of the proposed method. In fact, a generic method is, thereby, provided into the literature.

The aim of this research, which uses the theories of social identity and social exchange, is to investigate the relationship between responsible leadership, prosocial behavior and the mediating role of psychological ownership in this relationship. In addition, the moderating role of ethical and social responsibility in the relationship between responsible leadership and psychological ownership is tested in the study.

The sample of the research consists of 246 participants who work full-time at İstanbul Sabiha Gökçen Airport in ground handling services (GHS). The convenience sampling method was used in the research, and the research data were collected by the face-to-face survey method. The hypotheses of the research were tested with the partial least squares structural equation model (PLS-SEM) and SPSS Process Macro.

According to the results, it was determined that responsible leadership affects prosocial behavior positively and significantly, and psychological ownership plays a mediating role in this relationship. In addition, the moderating effect of ethical and social responsibility on the relationship between responsible leadership and psychological ownership was determined. When ethical and social responsibility is perceived as high by the employees, it was revealed that the conditional indirect effect of responsible leadership on prosocial behavior through psychological ownership was strong.

When responsible leadership encourages employees to take psychological ownership, they are more likely to engage in prosocial behavior. This study contributes to the field by evaluating the structures discussed with social identity and social exchange theory. In the management practice of organizations, responsible leadership should be strengthened and training should be given to develop responsible leadership.

In the literature review, it was observed that although there are studies conducted with responsible leadership, the concept was not examined with prosocial behavior, and it was not studied in the aviation sector, which has become indispensable for the world economy. With these features, the study distinguishes itself from others and constitutes a source of motivation for researchers.

Competition in the banking sector is more complex than in the past, and survival has become more difficult than before. The purpose of this paper is to propose a grey methodology for evaluating, clustering and ranking the performance of bank branches with imprecise and uncertain data in order to determine the relative status of each branch.

In this study, the two-stage data envelopment analysis model with grey data is applied to assess the efficiency of bank branches in terms of operations. The result of grey two-stage data envelopment analysis model is a grey number as efficiency value of each branch. In the following, the branches are classified into three grey categories of performance by grey clustering method, and the complete grey ranking of branches are performed using “minimax regret-based approach” and “whitening value rating”.

The results show that after grey clustering of 22 branches based on grey efficiency value obtained from the grey two-stage DEA model, 6 branches are assigned to “excellent” class, 4 branches to “good” class and 12 branches to “poor” class. Moreover, the results of MRA and whitening value rating models are integrated, and a complete ranking of 22 branches are presented.

Grey clustering of branches based on grey efficiency value can facilitate planning and policy-making for branches so that there is no need to plan separately for each branch. The grey ranking helps the branches find their current position compared to other branches, and the results can be a dashboard to find the best practices for benchmarking.

Compared with traditional DEA methods which use deterministic data and consider decision-making units as black boxes, in this research, a grey two-stage DEA model is proposed to evaluate the efficiency of bank branches. Furthermore, grey clustering and grey ranking of efficiency values are used as a novel solution for improving the accuracy of grey two-stage DEA results.

The purpose of this paper is to develop a blockchain-based data capture and transmission system that will collect real-time power consumption data from a household electrical appliance and transfer it securely to a local server for energy analytics such as forecasting.

The data capture system is composed of two current transformer (CT) sensors connected to two different electrical appliances. The CT sensors send the power readings to two Arduino microcontrollers which in turn connect to a Raspberry-Pi for aggregating the data. Blockchain is then enabled onto the Raspberry-Pi through a Java API so that the data are transmitted securely to a server. The server provides real-time visualization of the data as well as prediction using the multi-layer perceptron (MLP) and long short term memory (LSTM) algorithms.

The results for the blockchain analysis demonstrate that when the data readings are transmitted in smaller blocks, the security is much greater as compared with blocks of larger size. To assess the accuracy of the prediction algorithms data were collected for a 20 min interval to train the model and the algorithms were evaluated using the sliding window approach. The mean average percentage error (MAPE) was used to assess the accuracy of the algorithms and a MAPE of 1.62% and 1.99% was obtained for the LSTM and MLP algorithms, respectively.

A detailed performance analysis of the blockchain-based transmission model using time complexity, throughput and latency as well as energy forecasting has been performed.

This study aims to fill several gaps in the literature. First, it examines the Umrah industry from the supply side, investigating the pivotal factors for travel agencies’ performance. Second, it empirically investigates service leaders’ competencies specific to the hospital and tourism industry. Third, it clarifies whether there is a direct impact of organisational service orientation on business performance. Fourth, it explores the influence of network capabilities in a service context, specifically in travel agencies, which has rarely been discussed.

This is a mixed-method study with sequential explanatory research design. First, a quantitative approach was conducted with 150 authorised travel agencies in Indonesia, with two manager-level employees representing each agency. The data were analysed using descriptive statistics and structural equation modelling. A qualitative study was conducted to enrich the findings by interviewing the Director of Umrah and Hajj Development of the Ministry of Religious Affairs of the Republic of Indonesia and three other respondents.

Service leaders’ competencies and resource capacity significantly influence organisational service orientation, leading to enhanced perceived service quality and performance. In addition, resource capacity influences network capabilities, improving performance.

This study identifies factors affecting the performance of Umrah travel agencies in an intensely competitive environment, which has rarely been discussed. This sheds light on how travel agencies can survive and succeed in this competitive industry. Moreover, this study provides evidence regarding the role of network capabilities in the tourism industry and the impact of organisational service orientation, both directly and indirectly, on performance.

The risks and uncertainties of public–private partnership (PPP) projects threaten their sustainability. Contract flexibility, which is based on the theory of incomplete contract and transaction cost, may be a viable solution to this issue. The purpose of this study is to investigate the relationship between contract flexibility and the sustainability performance of PPP projects. The multiple mediating roles of justice perception and cooperation efficiency are assessed, thereby allowing the pathways and conditions to be understood more comprehensively for improving the sustainability performance of PPP projects.

Nine hypotheses in the proposed research model are tested via structural equation modeling using data acquired from 218 Chinese PPP professionals.

Results show that contract flexibility positively affects PPP project sustainability performance. Justice perception and cooperation efficiency play direct and sequential mediating roles in this effect.

This study validates that contract flexibility positively impacts the sustainability performance of PPP projects, where justice perception and cooperation efficiency serve direct and sequential mediating roles. The findings of this study contribute to an improved understanding of the effect of contract flexibility on the sustainability performance of PPP projects. Furthermore, they provide important theoretical and practical insights into contract management as well as beneficial information and valuable initiatives for improving the sustainability of PPP projects.

Food loss and wastage is an issue of global concern and the household sector is one of the biggest contributors to this. Solar drying has been explored by many eminent researchers as a solution to this problem but there have been concerns about the lack in designs, higher cost, lower performance, and consumer acceptability. The present research aims to design a small-scale domestic solar dryer by using computer software.

Response surface methodology (RSM) and computational fluid dynamics (CFD) are used to design the domestic solar dryer. Initially, design variables (inlet and outlet vent height) are identified and a design of experiments has been created using RSM for set of experimental runs. The experimental runs suggested by RSM were carried out using CFD simulation in COMSOL Multiphysics software and the results were used for optimization of response variables (outlet velocity and drying chamber temperature) in RSM.

Outlet vent height was found to be most significantly affecting parameter to both the responses. The optimum values of inlet and outlet vent heights were 0.5 and 2.5 cm, respectively with the overall desirability of 0.728. The model accuracy was tested by conducting a confirmation test as post processing in design expert software.

Designing a solar dryer is a complex, costly and time consuming process, this study presents an easy, economic and fast method to design a new solar dryer. It would help researchers to design and develop new domestic as well as large size industrial solar dryer.

The global resolution of embracing dynamic and intertwined production systems has made it necessary to adopt viable systems like circular economy (CE) to ensure excellency in the business. However, in emerging countries, it is challenging to implement the CE practices due to the existing problems in the supply chain network, as well as due to the vulnerable financial condition of the business after the deadly hit of COVID-19. The main aim of this research is to determine the barriers to implementing CE considering the recent pandemic and suggest strategies to organizations to ensure CE for a cleaner environment and greener economy.

After an extensive literature review and validation from experts, 24 sub-barriers under the class of 6 main barriers are finalized by Pareto analysis, which is further analyzed via the best-worst method to determine the weight and rank of the barriers Further, fuzzy-Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method is used to rank the proposed startegies to overcome the analysed barriers.

The results identified “unavailability of initial funding capital”, “need long time investment”, “lack of integrating production system using advance technology” and “lack of strategic planning” as the most acute sub-barriers to CE implementation. Further, fuzzy TOPSIS method is used to suggest the best strategy to mitigate the ranked barriers. The results indicated “integrated design facility to CE”, “ensuring large scale funding for CE facility” as the best strategy.

This study will motivate managers to implement CE practices to enjoy proper utilization of the resources, sustainable benefits in business, and gain competitive advantage.

Periodically, a lot of work is done on CE practices but none of them highlighted the issues in the domain of the leather products industry (LPI) and COVID-19 toward achieving sustainability in production and consumption. Thus, some significant barriers and strategies to implement CE for achieving sustainability in LPI are highlighted in this study, which is a unique contribution to the literature.

Social determinants of stressful events (SE) play an important role in justifying the cause of inequality in the experience of SE. The purpose of this study is to investigate the determinants that impact on inequality in the experience of SE.

The statistical population of this study includes all residents of Tehran. The statistical sample was 5,895 people who were selected by multistage cluster method and were proportional to the population size. The research tool is a researcher-made questionnaire designed to measure SE in Tehran, which includes 11 psychological stressors. The Oaxaca–Blinder decomposing method was used to analyze data.

In a total of 11 psychological SE, in 6 of those events, there was significant inequality in the experience of SE. Concentration Index (CI) of political SE is (CI = −0.27, 95% CI: −0.47, −0.07) and in favor of the rich (pro-rich). Education (OR = 1.60) in poor group and region development in poor and rich (respectively in all of the following) (OR = 0.42–0.73) are the main determinants of inequality in this stressor. CI of neighborhood underdevelopment SE is (CI = −0.47, 95% CI: 0.66, −0.28) and pro-rich. Education (OR = 1.26–1.27) and region development (OR = 1.18–2.24) are the main determinants of inequality in this stressor. CI of livelihood problems SE is (CI = −0.58, 95% CI: 0.68, −0.32) and pro-rich. Education (OR = 1.40) and health status (OR = 1.63) in poor group are the main determinants of inequality in this stressor. CI of future uncertainty SE is (CI = −0.12, 95% CI: 0.34, −0.08) and pro-rich. Gender (OR = 1.22) in poor group and region development (OR = 0.24–0.58) are the main determinants of inequality in this stressor. CI of education problems (CI = 0.19, 95% CI: 0.05, 0.32) and pro-poor. Age (OR = 0.32–0.34) and education (OR = 3.65–3.30) are the main determinants of inequality in this stressor. CI of housing problems is (CI = −0.29, 95% CI: −0.49, −0.08) and pro-rich. Education (OR = 1.31) and region development (OR = 1.64) in poor group are the main determinants of inequality in this stressor.

The first limitation is related to the level of data analysis, and the second limitation is the lack of comprehensive data on social determinants.

Social determinants affecting the formation of inequality in the experience of SE. Some social determinants, such as the level of education and development of the region, play a more prominent role in justifying inequality in the experience of stress between rich and poor groups.

Inequality in the experience of SE is a serious threat to mental and social health. One of the ways to reduce the experience of psychological and social stress is to pay attention to social determinants that play a role in the formation of stress.

This original paper was conducted by examining the effect of social determinants on the formation of inequality in the experience of stress, which draws the serious attention of policymakers.