Search results

The purpose of this paper is to employ stochastic techniques to increase efficiency of the classical algorithms for solving nonlinear optimization problems.

The well-known simulated annealing strategy is employed to search successive neighborhoods of the classical trust region (TR) algorithm.

An adaptive formula for computing the TR radius is suggested based on an eigenvalue analysis conducted on the memoryless Broyden-Fletcher-Goldfarb-Shanno updating formula. Also, a (heuristic) randomized adaptive TR algorithm is developed for solving unconstrained optimization problems. Results of computational experiments on a set of CUTEr test problems show that the proposed randomization scheme can enhance efficiency of the TR methods.

The algorithm can be effectively used for solving the optimization problems which appear in engineering, economics, management, industry and other areas.

The proposed randomization scheme improves computational costs of the classical TR algorithm. Especially, the suggested algorithm avoids resolving the TR subproblems for many times.

This paper aims to model and analyze Jeffery Hamel’s channel flow with the magnetohydrodynamics second-grade hybrid nanofluid. Considering the importance of studying the velocity slip and temperature jump in the boundary conditions of the flow, which leads to results close to reality, this paper intends to analyze the mentioned topic in the convergent and divergent channels that have significant applications.

The examination is conducted on a EG-H_2 O <30%–70%> base fluid that contains hybrid nanoparticles (i.e. SWCNT-MWCNT). To ensure comprehensive results, this study also considers the effects of thermal radiation, thermal sink/source, rotating convergent-divergent channels and magnetic fields. Initially, the governing equations are formulated in cylindrical coordinates and then simplified to ordinary differential equations through appropriate transformations. These equations are solved using the Explicit Runge–Kutta numerical method, and the results are compared with previous studies for validation.

After the validation, the effect of the governing parameters on the temperature and velocity of the second-grade hybrid nanofluid has been investigated by means of various and comprehensive contours. In the following, the issue of entropy generation and its related graphical results for this problem is presented. The mentioned contours and graphs accurately display the influence of problem parameters, including velocity slip and temperature jump. Besides, when thermal radiation is introduced (Rd = +0.1 and Rd = +0.2), entropy generation in convergent-divergent channels decreases by 7% and 14%, respectively, compared to conditions without thermal radiation (Rd = 0). Conversely, increasing the thermal sink/source from 0 to 4 leads to an 8% increase in entropy generation at Q = 2 and a 17% increase at Q = 4 in both types of channels. The details of the analysis of contours and the entropy generation results are fully mentioned in the body of the paper.

There are many studies on convergent and divergent channels, but this study comprehensively investigates the effects of velocity slip and temperature jump and certainly, this geometry with the specifications presented in this paper has not been explored before. Among the other distinctive features of this paper compared to previous works, the authors can mention the presentation of velocity and temperature results in the form of contours, which makes the physical analysis of the problem simpler.

Higher education institutions draw up codes of ethics, but in several countries there are no standards to follow. Most universities have autonomy and can freely draw up their codes of ethics in terms of structure and content. The purpose of this paper is to understand the main ethics issues that universities identify in their codes of ethics and what activities they implement to respond to these issues toward appropriate educational management of their institutions in ethical terms.

This study was performed through content analysis of codes of ethics of Italian public universities (64 codes), and may be considered a single in-depth case study. The main ethics issues and related activities were inductively codified in relation to the research purpose. The four constitutive aspects of business ethics (individual, managerial, organizational and societal ethics) proposed by Melé were chosen as the framework to investigate the main ethical needs and related activities implemented by universities to respond to these ethical issues.

This research has identified nine main ethical issues and related activities that contribute to guarantee the ethical compliance of universities under the four interrelated aspects different individual behaviors, managerial initiatives, organization strategies and responsibilities toward society. The analysis shows some relevant differences among Italian universities that have important implications in the ethical vision of academic communities and of managerial role in universities.

The research can help managers of higher education institutions to identify the main ethical issues to draw up codes of ethics and to formulate consistent development strategies that are able to improve the conditions of collaboration, work and productive participation in activities for all members of academic communities.

To the best of the authors’ knowledge, this is one of the first studies that connect codes of ethics and higher education. This research brings to light the main ethical issues and related activities that universities can consider to orient their strategic choices toward the public interest as well as educational management improvement.

The traditional failure mode and effect analysis (FMEA) has some limitations, such as the neglect of relevant historical data, subjective use of rating numbering and the less rationality and accuracy of the Risk Priority Number. The current study proposes a machine learning–enhanced FMEA (ML-FMEA) method based on a popular machine learning tool, Waikato environment for knowledge analysis (WEKA).

This work uses the collected FMEA historical data to predict the probability of component/product failure risk by machine learning based on different commonly used classifiers. To compare the correct classification rate of ML-FMEA based on different classifiers, the 10-fold cross-validation is employed. Moreover, the prediction error is estimated by repeated experiments with different random seeds under varying initialization settings. Finally, the case of the submersible pump in Bhattacharjee et al. (2020) is utilized to test the performance of the proposed method.

The results show that ML-FMEA, based on most of the commonly used classifiers, outperforms the Bhattacharjee model. For example, the ML-FMEA based on Random Committee improves the correct classification rate from 77.47 to 90.09 per cent and area under the curve of receiver operating characteristic curve (ROC) from 80.9 to 91.8 per cent, respectively.

The proposed method not only enables the decision-maker to use the historical failure data and predict the probability of the risk of failure but also may pave a new way for the application of machine learning techniques in FMEA.

In the study, a five-dimensional-safety risk assessment model (5D-SRAM) is developed to improve the construction safety risk assessment approaches available in the literature. To that purpose, a hybrid multi-dimensional fuzzy-based model is proposed, which provides a comprehensive ranking system for the safety risks existing in a project by considering the contextualization of the construction-related activities resulting in an accident.

The developed 5D-SRAM is based on an amalgamation of different fuzzy-based techniques. Through the proposed fuzzy analytic hierarchy process (AHP) method, the importance weights of essential risk dimensions playing role in defining the magnitude of the construction-related risks are obtained, while a precise prioritized ranking system for the identified safety risks is acquired using the proposed fuzzy technique of order preference similarity to the ideal solution (FTOPSIS).

Through the application of the proposed 5D-SRAM to a real-life case study – which is the case of green building construction projects located in Hong Kong – contributions are realized as follows: (1) determination of a more complete range of risk dimensions, (2) calculation of importance weightings for each risk dimension and (3) obtainment of a precise and inclusive ranking system for safety risks. Additionally, the supremacy of the developed 5D-SRAM against the other safety assessment approaches that are commonly adopted in the construction industry is proved.

The developed 5D-SRAM provides the concerned safety decision-makers with not only all the crucial dimensions that play roles toward the magnitude of safety risks posing threats to the workers involved in construction activities, but also they are given hindsight regarding the importance weights of these dimensions. Additionally, the concerned parties are embellished with the final ranking of safety risks in a more comprehensive way than those of existing assessment methods, leading to sagacious adoption of future prudent strategies for dealing with such risks occurring on construction sites.

Numerous studies have documented the safety risks faced by construction workers including proposals for risk assessment models. However, the dimensions considered by such models are limited, generally constrained to risk event probability combined with risk impact severity. Overlooking other dimensions that are essential towards the calculation of safety risks' magnitude culminates in overshadowing the further adoption of fruitful mitigative actions. To overcome this shortcoming, this study proposes a novel 5D-SRAM.

The purpose of this study is to investigate the essential analytical skills required by accounting students to succeed in a rapidly evolving data-driven job market. Specifically, the study explores the role of data analytics, visualisation and software proficiency (e.g. Excel, Power BI) in the contemporary Australian accounting industry. The scope extends to providing recommendations for academia, professional bodies and employers on how accounting education can better align with the dynamic needs of the business environment by integrating these skills into curricula and professional development programmes.

Data was collected from Australian job listings incorporating accounting and data analytics tasks from popular job advertisement websites such as Seek, Indeed and Monster. Using the keyword “Data Analyst”, information was gathered on skills demanded, technology proficiency, industry sectors, professional qualifications and salary expectations. The data set comprised 73 observations across various job requirements and characteristics variables.

Critical analytical skills sought by accounting professionals in the current job market include extracting insights from big data, solving complex business problems, effective communication and data visualisation. Proficiency in tools like Microsoft Excel, SQL and Power BI is paramount.

This study enriches the literature by providing comprehensive insights into the contemporary demands for accounting analytics skills. It highlights the importance of integrating technology into accounting education and the varying skill requirements across industries. Additionally, it offers implications for professional qualifications and underscores the necessity for continuous monitoring and adaptation of accounting curricula to meet evolving industry needs.

The current study examines the effect of fraud training on auditors' ability to identify fraud risk factors. This is important because most auditors have little or no direct experience with fraud; thus, research that investigates the potential effect of indirect experience through training is vitally important to fraud detection and audit quality. A total of 369 experienced auditors completed a complex audit simulation task that involved 15 seeded fraud risk red flags. A total of 143 auditors participated in a 30-minute training session focused specifically on fraud risk, while the remaining 226 auditors learned about general internal control risk during this time block. The results indicate that auditors with fraud training identified significantly more red flags and obtained greater knowledge about fraud risk than auditors who did not receive the training. Considering that the fraud training consumed only 30 minutes out of a 64-hour training session, the findings suggest that even modest exposure to fraud training is quite effective.

Building upon institutional pressures on firms to deal with corruption, this study aims to investigate the association between a firm's engagement with anti-corruption disclosure quality (ACD_Q) and earnings management (EM). Also, this study examines the moderating role of audit quality in the association between ACD_Q and EM.

The authors constructed an ACD_Q index based on the 2010 UK Bribery Act and taking into account a wide range of rules on corruption and bribery, including those of the OECD, World Bank, UNCTAD, UNGC, UNCAC and GRI. Generalized method of moments and panel regression were used to examine the association between ACD_Q and EM.

Using a sample of 2,695 firm‐year observations of the UK’s FTSE-350 from 2008 to 2018, this study finds ACD_Q is negatively associated with EM. In addition, this negative relationship is contingent on audit committee independence and audit committee expertise. This finding is supported by additional robustness and sensitivity analysis.

The empirical evidence reiterates the crucial need for more concerted efforts to ensure corporate engagement in anti-corruption practices with a view to reducing earnings manipulations.

This study contributes to the limited evidence that investigates how ACD Q influences EM in the UK after the introduction of the UK Bribery Act in 2010. Furthermore, by considering the period from 2008 to 2019, this study investigates the potential moderating role of UK corporate governance reforms in EM reduction. In particular, to the best of the authors’ knowledge, this study assesses for the first time the moderating effect of audit committee mechanisms on the ACD Q and EM nexus.

This study aims to investigate the nexus among environmental, social and governance disclosure quality (ESGDQ), corporate governance (COG) and corporate social responsibility strategy (CSRS) in the context of ASEAN, a developing market. Furthermore, carbon emission (CAE) has been considered as a moderation component for the CSRS–ESGDQ link.

With strict selection criteria, five countries in the ASEAN region (ASEAN-5) were selected as the research sample frame, including Vietnam, Thailand, Malaysia, Indonesia and the Philippines. Using the Thomson Reuters Eikon database, the initial sample included 4,735 listed companies in ASEAN-5. After a rigorous screening process, there were a total of 683 companies in the final sample with the 2018–2022 intervals.

By using maximum likelihood structural equation modeling, the finding indicates that COG and CSRS have a favorable effect on ESGDQ in the ASEAN-5 context. Furthermore, CAE plays an outstanding moderation role in the CSRS–ESGDQ link. The fundamental accounting standards are also identified as having an impact on ESGDQ.

The research points up the dominant role of internal components (i.e. COG, CSRS and CAE) and government factor (i.e. fundamental accounting standards) for the sustainable value (i.e. ESGDQ) of firms in ASEAN-5, a developing market. Thus, firm headers should inspect the performance of these internal components at a crucial interval to enhance their environmental, social and governance (ESG) behaviors and make them more sustainable. Furthermore, governments in ASEAN-5 should pay attention to developing areas that have low CAE and have a favorable influence on national sustainable development goals.

The findings of the research provide some social implications by pointing up important factors influencing sustainability practices, and understanding how ESG practices can be improved in developing countries.

The research enlarges ESG documentation by specifying the influences of internal components and government factor, as well as providing actual proof from developing regions. In addition, this study identifies the effectiveness of CAE as well as its moderating role in this context.

This study aims to examine the effect of corporate social responsibility (CSR) adoption on differentiation and cost leadership strategies and how governance structure moderates this CSR–strategy relationship.

The study data were retrieved from Thomson Reuters for non-financial firms between 2013 and 2019, and a fixed-effects panel regression analysis was executed.

The results indicate that CSR fosters cost leadership strategy but weakens differentiation strategy. This result supports the value generation school for cost leaders but also confirms the agency theory perspective for differentiators. Moreover, the governance structure does not moderate the relationship between a firm's CSR engagement and its business strategy, which implies a lack of corporate policies that concurrently consider both its CSR investment and strategies.

The findings of this study imply that cost leaders can integrate CSR practices into their business strategy and use their CSR engagement to increase their competitive position by stimulating cost efficiency and creating greater turnover. On the contrary, for differentiators, there is a trade-off between environmental and social engagement and business strategies. Thus, they are advised to enrich their unique product development abilities through the integration of environmental and social practices and reinforce their competitive position by addressing stakeholders' interests. The practical implication of the moderation analysis is that there is no rooted corporate policy behind the connection between CSR and firm strategy for both cost leaders and differentiators, which constitutes a missing link.

The findings of this study are of critical importance for firms, offering justification for the integration of two vital perspectives: social and environmental sustainability and financial sustainability. The moderating effect of governance performance tests the upper echelon's role in maintaining both sustainability perspectives concurrently and strengthening the legitimacy of the firms in society. Although maintaining a business strategy is important for shareholders' interests, pursuing a social and environmental sustainability strategy is crucial for meeting the expectations of all stakeholders.