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The purpose of this study is to investigate cathodic protection (CP) efficiency in the tidal zone and its associated processes.

Specific features of CP in the tidal zone, that is, persistence of a thin seawater film and insufficient cathodic potential due to ohmic drop, were addressed. In this preliminary study, carbon steel electrodes were polarized at two cathodic potentials (correct or insufficient protection) while immersed in 1 mm or 5 mm thick natural seawater layers. After CP interruption, the protective ability of the layers covering the steel electrodes was studied using various electrochemical methods, including electrochemical impedance spectroscopy. The layers were characterized by XRD.

The protective ability of calcareous deposits was increased in thin seawater films. Insufficient CP could promote protective aragonite/corrosion products layer.

The combined effects of thin seawater film and applied potential were never addressed, and the conclusions drawn from this preliminary study give new insight on the efficiency of CP in the tidal zone.

The purpose of this study is to plan and develop a cost-effective health-care robot for assisting and observing the patients in an accurate and effective way during pandemic situation like COVID-19. The purposed research work can help in better management of pandemic situations in rural areas as well as developing countries where medical facility is not easily available.

It becomes very difficult for the medical staff to have a continuous check on patient’s condition in terms of symptoms and critical parameters during pandemic situations. For dealing with these situations, a service mobile robot with multiple sensors for measuring patients bodily indicators has been proposed and the prototype for the same has been developed that can monitor and aid the patient using the robotic arm. The fuzzy controller has also been incorporated with the mobile robot through which decisions on patient monitoring can be taken automatically. Mamdani implication method has been utilized for formulating mathematical expression of M number of “if and then condition based rules” with defined input X_j (j = 1, 2, ………. s), and output y_i. The inputs and output variables are formed by the membership functions µ_Aij(x_j) and µ_Ci(y_i) to execute the Fuzzy Inference System controller. Here, Aij and Ci are the developed fuzzy sets.

The fuzzy-based prediction model has been tested with the output of medicines for the initial 27 runs and was validated by the correlation of predicted and actual values. The correlation coefficient has been found to be 0.989 with a mean square error value of 0.000174, signifying a strong relationship between the predicted values and the actual values. The proposed research work can handle multiple tasks like online consulting, continuous patient condition monitoring in general wards and ICUs, telemedicine services, hospital waste disposal and providing service to patients at regular time intervals.

The novelty of the proposed research work lies in the integration of artificial intelligence techniques like fuzzy logic with the multi-sensor-based service robot for easy decision-making and continuous patient monitoring in hospitals in rural areas and to reduce the work stress on medical staff during pandemic situation.

This paper aims to contribute to the development of the European Union (EU) regulatory environment for sustainability reporting by analyzing how materiality is defined in the Non-Financial Reporting Directive (NFRD) and Corporate Sustainability Reporting Directive (CSRD) and by examining the added value and challenges of legalizing reporting and materiality requirements from both regulatory and practical company perspectives. It provides insights on whether this is reflected by EU pharmaceutical companies and to what extent companies report information on their materiality analysis process.

Doctrinal analysis was used to examine regulatory instruments. Qualitative document analysis was used to analyze companies’ reports. The added value and challenges were examined using a governance approach. It focused on legalizing reporting and materiality requirements, with a brief extension to corporate management and organization studies.

Materiality has evolved from a vague concept in the NFRD toward double materiality in the CSRD. This was reflected by the industry, but reports revealed inconsistencies in materiality definitions and reported information. Challenges include lack of self-reflection and company-centric perceptions of materiality. Companies should explain how they identify relevant stakeholders and how input is considered in decision-making.

Managers must consider how they conduct materiality assessments to meet society’s expectations. The underlying processes should be explained to increase the credibility of reports. Sustainability reporting should be seen as a corporate governance tool.

This work contributes to the literature on materiality in sustainability reporting and to the debate on the need for a holistic, society-centric approach to enhance the sustainability of companies.

Artificial intelligence (AI) has sparked interest in various areas, including marketing. However, this exhilaration is being tempered by growing concerns about the moral and legal implications of using AI in marketing. Although previous research has revealed various ethical and legal issues, such as algorithmic discrimination and data privacy, there are no definitive answers. This paper aims to fill this gap by investigating AI’s ethical and legal concerns in marketing and suggesting feasible solutions.

The paper synthesises information from academic articles, industry reports, case studies and legal documents through a thematic literature review. A qualitative analysis approach categorises and interprets ethical and legal challenges and proposes potential solutions.

The findings of this paper raise concerns about ethical and legal challenges related to AI in the marketing area. Ethical concerns related to discrimination, bias, manipulation, job displacement, absence of social interaction, cybersecurity, unintended consequences, environmental impact, privacy and legal issues such as consumer security, responsibility, liability, brand protection, competition law, agreements, data protection, consumer protection and intellectual property rights are discussed in the paper, and their potential solutions are discussed.

Notwithstanding the interesting insights gathered from this investigation of the ethical and legal consequences of AI in marketing, it is important to recognise the limits of this research. Initially, the focus of this study is confined to a review of the most important ethical and legal issues pertaining to AI in marketing. Additional possible repercussions, such as those associated with intellectual property, contracts and licencing, should be investigated more deeply in future studies. Despite the fact that this study gives various answers and best practices for tackling the stated ethical and legal concerns, the viability and efficacy of these solutions may differ depending on the context and industry. Thus, more research and case studies are required to evaluate the applicability and efficacy of these solutions in other circumstances. This research is mostly based on a literature review and may not represent the experiences or opinions of all stakeholders engaged in AI-powered marketing. Further study might involve interviews or surveys with marketing professionals, customers and other key stakeholders to offer a full knowledge of the practical difficulties and solutions. Because of the rapid speed of technical progress, AI’s ethical and regulatory ramifications in marketing are continually increasing. Consequently, this work should be a springboard for more research and continuing conversations on this subject.

This study’s findings have several practical implications for marketing professionals. Emphasising openness and explainability: Marketing professionals should prioritise transparency in their use of AI, ensuring that customers are fully informed about data collection and utilisation for targeted advertising. By promoting openness and explainability, marketers can foster customer trust and avoid the negative consequences of a lack of transparency. Establishing ethical guidelines: Marketing professionals need to develop ethical rules for the creation and implementation of AI-powered marketing strategies. Adhering to ethical principles ensures compliance with legal norms and aligns with the organisation’s values and ideals. Investing in bias detection tools and privacy-enhancing technology: To mitigate risks associated with AI in marketing, marketers should allocate resources to develop and implement bias detection tools and privacy-enhancing technology. These tools can identify and address biases in AI algorithms, safeguard consumer privacy and extract valuable insights from consumer data.

This study’s social implications emphasise the need for a comprehensive approach to address the ethical and legal challenges of AI in marketing. This includes adopting a responsible innovation framework, promoting ethical leadership, using ethical decision-making frameworks and conducting multidisciplinary research. By incorporating these approaches, marketers can navigate the complexities of AI in marketing responsibly, foster an ethical organisational culture, make informed ethical decisions and develop effective solutions. Such practices promote public trust, ensure equitable distribution of benefits and risk, and mitigate potential negative social consequences associated with AI in marketing.

To the best of the authors’ knowledge, this paper is among the first to explore potential solutions comprehensively. This paper provides a nuanced understanding of the challenges by using a multidisciplinary framework and synthesising various sources. It contributes valuable insights for academia and industry.

This paper aims to identify the profiles of beginner and experienced consumers (BCs and ECs) of craft beer and evaluate their perception, knowledge and purchase intention.

A total of 291 craft beer consumers including 148 BCs and 143 ECs participated in the study, which was divided into 2 stages: quantitative research through a questionnaire and conjoint analysis.

BCs are mostly female, with a lower age, income and consumption frequency, presented a shallower understanding of International Bitterness Units (IBU) and considered 7.0% alcohol by volume (ABV) as a high-relative value in craft beers. Otherwise, ECs are mostly men with a higher age and consumption frequency, and they don't consider 50 IBU as high bitterness. The results of conjoint analysis indicate that both groups of consumers attribute greater relative importance to ABV and nonalcoholic beers had lower purchase intentions. Finally, the authors show that beer with 30 IBU and 4.5% ABV is preferred by both BCs and ECs.

The authors' identification about the distinct behaviors of different groups of consumers, based on their consumption time of craft beer, as managerial implications for industries producing craft beer and, as a theoretical contribution, the authors have defined “BCs” and “ECs” based on the experiences with and durations of craft beer consumption.

This paper attempts to develop a simple, static model of tax administration that is capable of explaining the widespread collusive petty tax administration corruption observed in developing countries.

This paper utilizes a positivist research framework and adopts a theoretical method of analysis, although secondary data will also be mentioned to support theoretical arguments whenever it is appropriate to do so.

A high rate of collusive tax corruption is inevitable in developing countries.

The model is static and needs to be extended into a dynamic model.

Traditional enforcement tools such as higher audits or a higher penalty regime against tax evasion do not work. Tax simplification can lessen the incidence of tax corruption.

Fighting tax corruption requires significant changes in the attitudes of taxpayers and tax auditors.

This paper combines the literature on Kantian economics and tax compliance in an innovative fashion.

This paper is a dedication to Professor Ngo Van Long who introduced the idea of Kant–Nash equilibrium. The author extends this analysis to the study of adult and child labor markets.

This is a game theoretic analysis of the market for adult and child workers when some firms behave in the neoclassical Nashian way and some firms follow a Kantian social norm.

The presence of Kantian firms in the output market in addition to Nashian lowers industry output and labor demand. This raises the possibility that Kantian behavior in the output market could lower wages sufficiently and increase the incidence of child labor. If firms engage in Kantian behavior in the labor market by not hiring child workers, adult wage rises but could lower child wage as children if they work can only work for Nashian firms. When labor demand is sufficiently high, more Kantians could raise adult wage above subsistence and eliminate child labor supply.

This is the first paper to apply Kant–Nash equilibrium to the labor market. The result that Kantian behavior could have an unintended negative spillover effect in other markets is new. The paper keeps alive the ideas of Professor Long, which hopefully will stimulate further work and build on his ideas.

Infection and cross-contamination have been massive concerns in the medical field. This study aims to investigate consumers’ awareness and their choices of endoscopes, which may deter them from the cross-contamination problem.

A discrete choice experiment survey was administered to 166 respondents in Penang, Malaysia. Participants were asked to make hypothetical choices and estimate their preference for endoscopes. The multinomial logit model was used to estimate the assumptions based on the stated preference data collected.

Only two-fifths of respondents are aware of their rights regarding endoscope selection. The findings are consistent with utility theory, where choices are made to maximise personal satisfaction. If given the choice, consumers preferred the single-use endoscope over the reusable or the doctor’s preferred endoscope. Price, insurance coverage and personal income are significant determinants of the consumer’s choice of endoscopes.

This study only investigates subjects living in Penang. Other possible important attributes to endoscope choices, such as environmental and device availability may be considered in future study.

The findings may create awareness among consumers about their rights when choosing medical devices. It may also improve health-care institutions’ (users’) and device manufacturers’ (industry players’) understanding of consumer needs and demands from socioeconomic perspectives.

The research offers insights into consumer rights and awareness of health-care services. Ultimately leading to better policy to protect consumers’ rights and safety.

This study contributes to the rare literature on consumer rights toward medical devices, in particular, the consumer’s awareness of the choice of endoscopes.

This paper aim to solve the problem of low assembly success rate for 3c assembly lines designed based on classical control algorithms due to inevitable random disturbances and other factors,by incorporating intelligent algorithms into the assembly line, the assembly process can be extended to uncertain assembly scenarios.

This work proposes a reinforcement learning framework based on digital twins. First, the authors used Unity3D to build a simulation environment that matches the real scene and achieved data synchronization between the real environment and the simulation environment through the robot operating system. Then, the authors trained the reinforcement learning model in the simulation environment. Finally, by creating a digital twin environment, the authors transferred the skill learned from the simulation to the real environment and achieved stable algorithm deployment in real-world scenarios.

In this work, the authors have completed the transfer of skill-learning algorithms from virtual to real environments by establishing a digital twin environment. On the one hand, the experiment proves the progressiveness of the algorithm and the feasibility of the application of digital twins in reinforcement learning transfer. On the other hand, the experimental results also provide reference for the application of digital twins in 3C assembly scenarios.

In this work, the authors designed a new encoder structure in the simulation environment to encode image information, which improved the model’s perception of the environment. At the same time, the authors used the fixed strategy combined with the reinforcement learning strategy to learn skills, which improved the rate of convergence and stability of skills learning. Finally, the authors transferred the learned skills to the physical platform through digital twin technology and realized the safe operation of the flexible printed circuit assembly task.

The aim of this paper is to investigate whether a Nash equilibrium of a two-country trading economy is symmetry-breaking or not.

The approach to tackle this topic is a theoretical treatment by the general equilibrium trade theory and game theory.

If each government's domestic policy serving private production is diminishing to the private production scale, the Nash equilibrium is not symmetry-breaking.

In the existing study of Chatterjee (2017), a similar result is derived by focusing on the properties of each country's GDP function. The authors, however, consider an economy where each country's PPF is strictly concave and show that the Nash equilibrium uniquely exists and this equilibrium is symmetry.