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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.

This paper investigates a problem in a reverse logistics (RLs) network to decide whether to dispose of unsold goods in primary stores or re-commercialize them in outlet centers. By deducting the costs associated with each policy from its revenue, this study aims to maximize the profit from managing unsold goods.

A new mixed-integer linear programming model has been developed to address the problem, which considers the selling prices of products in primary and secondary stores and the costs of transportation, cross-docking and returning unwanted items. As a result of uncertain nature of the cost and time parameters, gray numbers are used to deal with it. In addition, an innovative uncertain solution approach for gray programming problems is presented that considers objective function satisfaction level as an indicator of optimism.

According to the results, higher costs, including transportation, cross-docking and return costs, make sending goods to outlet centers unprofitable and more goods are disposed of in primary stores. Prices in primary and secondary stores heavily influence the number of discarded goods. Higher prices in primary stores result in more disposed of goods, while higher prices in secondary stores result in fewer. As a result of the proposed method, the objective function satisfaction level can be viewed as a measure of optimism.

An integral contribution of this study is developing a new mixed-integer linear programming model for selecting the appropriate goods for re-commercialization and choosing the best outlet center based on the products' price and total profit. Another novelty of the proposed model is considering the matching percentage of boxes with secondary stores’ desired product lists and the probability of returning goods due to non-compliance with delivery dates. Moreover, a new uncertain solution approach is developed to solve mathematical programming problems with gray parameters.

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.

As global issues such as climate change, economic growth, social equality and the wealth gap are widely discussed, education for sustainable development (ESD) allows every human being to acquire the knowledge, skills, attitudes and values necessary to shape a sustainable future. It also requires participatory teaching and learning methods that motivate and empower learners to change their behavior and take action for sustainable development. Teachers have begun rating pupils based on peer assessment for open evaluation. Peer assessment enables students to transition from passive to active feedback recipients. The assessors improve critical thinking and encourage introspection, resulting in more significant recommendations. However, the quality of peer assessment is variable, resulting in reviewers not recognizing the remarks of other reviewers, therefore the benefits of peer assessment cannot be fulfilled. In the past, researchers frequently employed post-event questionnaires to examine the effects of peer assessment on learning effectiveness, which did not accurately reflect the quality of peer assessment in real time.

This study employs a multi-label model and develops a self-feedback system in order to use the AIOLPA system in the classroom to enhance students' learning efficacy and the validity of peer assessment.

The research findings indicate that the better peer assessment through the rapid feedback system, for the evaluator, encourages more self-reflection and attempts to provide more ideas, so bringing the peer rating closer to the instructor rating and assisting the evaluator. Improve self-evaluation and critical thinking for the evaluator, peers make suggestions and comments to help improve the work and support the growth of students' learning effectiveness, which can lead to more suggestions and an increase in the work’s quality.

ESD consequently promotes competencies like critical thinking, imagining future scenarios and making decisions in a collaborative way. This study builds an online peer assessment system with a self-feedback mechanism capable of classifying peer comments, comparing them with scores in a consistent manner and providing prompt feedback to critics.

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.

The purpose of this paper is to propose a scenario-based grey methodology using clustering and optimizing with imprecise and uncertain body size data in an emergency assembly point area to assign the people on a campus to reach the emergency assembly points under uncertain disaster times.

Grey clustering and a new grey p-median linear programming model are developed to determine which units to assign to the pre-determined assembly points for a main campus in case of a disaster. The models have two scenarios: 70 and 100% occurrence capacities of administrative and academic personnel and students.

In this study, the academic and administrative units have been assigned to determine five different emergency assembly points on the main campus by using the numbers of the academic and administrative personnel and student and distances of the units to the assembly point areas of each other. The alternative solutions are obtained effectively by evaluating capacity utilization rates in the scenarios.

It is often unclear when disasters can occur and therefore, a preliminary preparation time must be required to minimize the risk. In the case of natural, man-made (unnatural) or technological disasters, the people are required to defend themselves and move away from the disaster area as soon as possible in a proper direction. The proposed assignment model yields a final solution that effectively eliminates uncertainty regarding the selection of emergency assembly points for administrative and academic staff as well as students, in the event of disasters.

Grey clustering suggests an assignment plan and concurrently, an investigation is underway utilizing the grey p-median linear programming model. This investigation aims to optimize various scenarios and body sizes concerning emergency assembly areas. All campus users who are present at the disaster in units of the campus are getting uncertainty about which emergency assembly point to use, and with this study, the vital risks aim to be ultimately reduced with reasonable plans.

Hepatitis C is one of the major health issues in both developed and developing countries. Hepatitis C virus (HCV) infection is more common in prisoners than in the general population. The purpose of this study was to determine the prevalence of HCV and its associated risk factors in Iranian male prisoners in Tehran.

In this cross-sectional study, the authors investigated the frequency and risk factors of hepatitis C infection among male prisoners in the Great Tehran Prison. Information on risk factors including the length of imprisonment, previous history of imprisonment, history of drug injection, history of tattooing, history of piercing, history of high-risk sex and family history of hepatitis C were extracted from patients’ records. To evaluate HCV status, blood samples were collected and tested.

In this study, 179 participants were included. Nine participants (5.0%, 95% CI, 2.3-9.3) were positive for hepatitis C. HCV infection was not significantly associated with age, marital status, education, previous history of imprisonment, length of imprisonment, piercing and high-risk sex; however, there was a significant association between a history of tattooing and a history of injecting drug use and Hepatitis C.

The prevalence of hepatitis C among male prisoners in Great Tehran Prison was 5% in this study, similar to recent studies on prisoners in Tehran. A history of drug injections as well as tattooing were the most important risk factors for hepatitis C in male prisoners.

The objective of this paper is to employ a model to expand the literature's comprehension of the organisational citizenship behaviour (OCB) phenomenon in the Indian banking sector. The authors examine OCB as a mediator of the relationship between job embeddedness (JE), self-efficacy (SE) and organisation effectiveness (OE). The authors also verify the moderating role of affective commitment (AC) on the JE, SE and OE relationship.

Data for the purpose of this paper are collected from 568 employees in 89 branches of banks located in North and Central India using a survey questionnaire. The data collected were analysed using structural equation modelling (SEM).

The findings confirm the positive association between JE, SE and OE. The results also suggest that OCB mediates the association between the independent and dependent variables. Furthermore, the authors observed that AC moderates the OCB and OE relationship.

The results of this examination will assist the employees to realise the substance of OCB in directing their performance towards OE. This investigation will inspire bank managers to notice that employee readiness to put in extra effort in a bank is primarily the effect of apt individual characteristics, namely JE and SE, that can be shaped and developed. Furthermore, this study draws the attention of bank managers towards the significance of AC, as an essential phenomenon to emotionally attach the employees to their organisation.

This study contributes to the existing literature on OCB by examining how OCB leads to desired outcomes and the conditions that promote the effect of OCB. The authors address these questions by building on a more contemporary perspective, i.e., PsyCap.