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A major source of external funding for US airports comes from issuing municipal bonds. Credit rating agencies evaluate the bonds using multiple factors, but the judgments behind the ratings are not well understood. This paper examines if airport rate-setting methods affect the bond ratings of US airports.

Using a set of unbalanced panel data for 58 hub airports from 2010 to 2019, we examine the effect of the rate-setting methods and other airport characteristics on Fitch’s airport bond rating.

We find that compensatory airports consistently receive a very high bond rating from Fitch. The probability of getting a very high Fitch rating increases by ∼28 percentage points for a compensatory airport. Additionally, the probability of getting a very high rating is about 33 percentage points higher for a legacy hub.

The study uses Fitch bond ratings. Future studies could examine if S&P’s and Moody’s ratings are also influenced by airport rate-setting methods and legacy hub status.

The results uncover the linkage between bond ratings and their determinants for US airports. This information is important for investors when assessing airport creditworthiness and for airport operators as they manage capital project financing.

This is the first study to evaluate the effects of rate-setting methods on airport bond rating and also the first to document a statistically significant relationship between airports’ legacy hub status and bond ratings.

Expanding on the real-world financial market framework and considering the current market turmoil, with cryptocurrencies (where contracts for difference (CFDs) are extremely common) (Hasso et al., 2019) displaying unprecedented volatility, the authors aim to test in an online laboratory setting whether displaying a risk warning message is truly effective in reducing the level of risk taken and whether the placement of this method makes a difference.

To explore the impact of risk disclosure framing on risk-taking behavior, the authors conducted an online pair-wise lottery choice experiment. In addition to manipulating risk awareness through the presence or absence of risk warning messages of varying intensity, the authors also considered dynamic inconsistency, cognitive ability and questionnaire-based financial risk tolerance (FRT) scores. The authors aimed to identify potential relationships between these variables and experimentally elicited risk aversion. The authors' study offers valuable insights into the complex nature of risky decision-making and sheds light on the importance of considering dynamic inconsistency in addition to risk awareness and aversion.

The authors' results provide statistical evidence for the efficacy of informative and very salient messages in mitigating risky decision, hinting at several policy implications. The authors also provide some statistical evidence in support of the relationship between cognitive abilities and risk preferences. The authors detect that individual with low cognitive abilities scores display great risk aversion.

This study investigates the impact of risk warning messages on investment decisions in an online laboratory setting – a unique approach. However, the authors go beyond this and also examine the potential influence of dynamic inconsistency on decision-making, adding further value to the literature on this topic. To ensure a comprehensive understanding of the participants, the authors collect data on cognitive ability and FRT using questionnaires. This study provides a simple and cost-effective framework that can be easily replicated in future research – a valuable contribution to the field.

This paper aims to give an oversight of what is being done by researchers in GIS and remote sensing (field) to explore minerals. The main objective of this review is to explore how GIS and remote sensing have been beneficial in identifying mineral deposits for easier and cost-effective mining.

The approach of this research used Web of Science to generate a database of published articles on the application of GIS and remote sensing techniques for mineral exploration. The literature was further digested, noting the main findings, adopted method, illustration and research scales.

When applied alone, each technique seems effective, but it is important to know that combining different methods is more effective in identifying ore deposits.

This paper also examined and provided possible solutions to both current and future perspective issues relating to the application of GIS and remote sensing to mineral exploration. The authors believe that the conclusions and recommendations drawn from case studies and literature review will be of great importance to geoscientists and policymakers.

This study aims to investigate how social entrepreneurial role models influence social entrepreneurial self-efficacy, social entrepreneurial intent and social entrepreneurial action, with moral obligation as a moderator.

A cross-sectional survey of 261 pupils in the South African province of the Eastern Cape was used in the research study. Structural equation modeling was used to test hypotheses.

The research revealed that having social entrepreneurial role models has a positive impact on both social entrepreneurial self-efficacy and social entrepreneurial intent. In addition, a connection was found between social entrepreneurial intent and entrepreneurial action. The influence of moral obligation was found to be a positive and a significant moderator. Moreover, the association between social entrepreneurial role models and social entrepreneurial intent was mediated by social entrepreneurial self-efficacy.

The findings are not generalizable to nonstudent samples because students constituted the sample for gathering data. Future study therefore requires considering nonstudents to generalize the outcomes. This research should be replicated in other South African provinces and other developing countries for comparative outcomes.

Since social entrepreneurial role models have been practically linked to social entrepreneurship intent and entrepreneurial efficacy, understanding the factors that influence student’s decision to start a social enterprise is critical in South Africa to develop targeted interventions aimed at encouraging young people to start new businesses. Policymakers, society and entrepreneurial education will all benefit from the findings.

This study contributes to bridging the knowledge gap as it investigates how social entrepreneurial role models influence social entrepreneurial self-efficacy, social entrepreneurial intent and social entrepreneurial action, with moral obligation as a moderator. Encouraging social entrepreneurship among South African youth would also help address societal issues. This is a pioneering study in the context of an emerging economy such as South Africa, where social entrepreneurship is so integral.

This study aims to investigate the potential of an empathetic mindset aimed at empowering undergraduate students to work toward sustainable development (SD), addressing both theoretical and practical dimensions.

A mixed quantitative and qualitative research method was used in this study. Cross-sectional quantitative survey data on students’ mindsets and actions toward SD was collected to examine the theoretical relationship between belief and behavior. Qualitative inquiry using focus-group interviews explored students’ on-site learning experiences.

This study provides evidence for the impact of an empathetic mindset on education for sustainable development (ESD). Results showed that students with a more empathetic mindset showed better attitudes and behaviors toward SD actions. Findings suggest that developing an empathetic mindset improves students’ attitudes toward taking substantial action to protect the environment.

This study introduces a novel perspective extending the application of empathetic mindset in ESD.

This study illustrates the economic and financial dynamics of the sector, analysing the evolution of the main ratios of profitability and financial structure of 1,559 Italian real estate companies divided into the three macro-regions: North, Centre and South, in the period 2011–2020. In this way, it is also possible to verify the responsiveness to the 2020 pandemic crisis.

The analysis uses descriptive statistics tools and the ANOVA method of analysis of variance, supplemented by the Tukey–Kramer test, to identify significant differences between the three Italian macro-regions.

The study shows the increase in profitability after the 2008 crisis, despite its reverberation in the years 2012–2013. The financial structure of companies improved almost everywhere. The pandemic had modest effects on performance.

In the future, other indices should be considered to gain a more comprehensive view. This is a quantitative study based on financial statements data that neglects other important economic and social factors.

Public policies could use this study for better interventions to support the sector. In addition, internal management can compare their company's performance with the industry average to identify possible improvements.

The research analyses an economic field that employs a large number of people, especially when considering the construction and real estate services covered by this analysis.

The study contributes to the literature by providing a quantitative analysis of industry dynamics, with comparative information that can be deduced from financial statements over the years.

Listening is often considered the cornerstone of the communication process, with feedback being a crucial skill for effective management. The primary objective of this article was to investigate the relationship between managers’ listening skills and feedback skills from their subordinates’ perspectives. Moreover, it explores the mediating effect of message-sending skills and the ability to deal with interference in this relationship.

This article deployed a quantitative, descriptive research design. The authors developed and distributed a self-administered questionnaire via non-probability convenience sampling, resulting in 304 useable responses.

The results of the main direct effect test (model 1) indicate that listening is positively associated with feedback. Model 2 established that message-sending skills did not directly mediate that relationship. On the other hand, the ability to deal with interference was found to mediate the relationship. Finally, model 4 showed the multi-mediating effect of message-sending skills and the ability to deal with interference in the relationship between listening and feedback.

As far as the researchers are aware, this paper is the first of its kind to show the ability to deal with interference as a mediating factor in a statistical model. Moreover, this study is the first to present a continuous intermediary role played by message-sending skills and the ability to deal with interference in the relationship between listening and feedback.

This study aims to evaluate the advantages and disadvantages of auditor mandatory suspicious activity reporting versus the exercise of professional judgement in the anti-money laundering regimes of the UK and the USA.

The research draws upon the following sources. Firstly, statistics provided by the UK National Crime Agency, 2019 (NCA) regarding suspicious activity report (SAR) filing rates. Secondly, anti-money laundering legislation in the USA and UK. Thirdly, statements made in the political domain in the USA, particularly those which raised constitutional concerns during the progress of the Patriot Act 2001. Finally, statements and recommendations by a UK Parliamentary Commission enquiring into the effectiveness of the suspicious activity reporting regime.

The UK reporting regime does not accommodate professional judgement, resulting in the filing of SARs with limited intelligence value. This contrasts with discretionary reporting in the USA: voluntary reporting guides and influences auditor behaviour rather than mandating it. Defensive filing by UK auditors (defence to anti-money launderings [DAMLs]) has increased in recent years but the number of SARs filed has declined.

The study evaluates auditor behavioural responses to legislative regimes which mandate or alternatively accommodate discretion in the reporting suspicion of money laundering. Consideration of constitutional and judicial activism in this context is a novel contribution to the literature. For its theoretical framework the study uses Foucault’s concept of discipline of the self to evaluate auditor behaviour under both regimes.

Recent studies have observed rise in consumer’s ethical concerns about the online retailers while making a purchase decision. The impetus for businesses to use corporate social responsibility (CSR) is evident, but the effects of CSR motives on corresponding processes underlying cause-related marketing (CRM) patronage intention have not been thoroughly examined. This study, anchored on attribution theory, established a research model that better explains the influence of CSR motives on patronage intentions toward CRM-oriented online retailers. Additionally, this study aims to examine the moderating role of spirituality (SPT) on CSR motives and CRM patronage intention (CPI).

Primary data has been collected from 722 respondents and analyzed by using deep neural-network architecture by using the innovative PLS-SEM-ANN method to predict/rank the factors impacting CPI.

The results revealed the normalized importance of the predictors of CPI and found that value-driven motive was the strongest predictor, followed by strategic motive, SPT, age and stakeholder-driven motive. In contrast, egoistic motive, education and income were found insignificant.

The pandemic has transformed the way consumers shop and fortified the online economy, thereby resulting in a paradigm shift toward usage of e-commerce platforms. The results offer valuable insights to online retailers and practitioners for predicting patronage intentions by CSR motives and, thus, effectively engage CRM consumers by designing promotions in a way that would deeply resonate with them. This study assessed and predicted the factors influencing the CPI s, thereby guiding the online retailers to design CSR strategies and manage crucial CRM decisions.

This study aims to minimize the transportation-related cost in distribution while utilizing a heterogeneous fixed fleet to deliver distinct demand at different geographical locations with a proper workload balancing approach. An increased cost in distribution is a major problem for many companies due to the absence of efficient planning methods to overcome operational challenges in distinct distribution networks. The problem addressed in this study is to minimize the transportation-related cost in distribution while using a heterogeneous fixed fleet to deliver distinct demand at different geographical locations with a proper workload balancing approach which has not gained the adequate attention in the literature.

This study formulated the transportation problem as a vehicle routing problem with a heterogeneous fixed fleet and workload balancing, which is a combinatorial optimization problem of the NP-hard category. The model was solved using both the simulated annealing and a genetic algorithm (GA) adopting distinct local search operators. A greedy approach has been used in generating an initial solution for both algorithms. The paired t-test has been used in selecting the best algorithm. Through a number of scenarios, the baseline conditions of the problem were further tested investigating the alternative fleet compositions of the heterogeneous fleet. Results were analyzed using analysis of variance (ANOVA) and Hsu’s MCB methods to identify the best scenario.

The solutions generated by both algorithms were subjected to the t-test, and the results revealed that the GA outperformed in solution quality in planning a heterogeneous fleet for distribution with load balancing. Through a number of scenarios, the baseline conditions of the problem were further tested investigating the alternative fleet utilization with different compositions of the heterogeneous fleet. Results were analyzed using ANOVA and Hsu’s MCB method and found that removing the lowest capacities trucks enhances the average vehicle utilization with reduced travel distance.

The developed model has considered both planning of heterogeneous fleet and the requirement of work load balancing which are very common industry needs, however, have not been addressed adequately either individually or collectively in the literature. The adopted solution methodologies to solve the NP-hard distribution problem consist of metaheuristics, statistical analysis and scenario analysis are another significant contribution. The planning of distribution operations not only addresses operational-level decision, through a scenario analysis, but also strategic-level decision has also been considered.

The planning of distribution operations not only addresses operational-level decisions, but also strategic-level decisions conducting a scenario analysis.