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In this chapter, Mousumi De presents the principles and implications of CRT in the context of Asian and Asian American experiences including the perspective, features, strategies, and new directions on how to facilitate the preparation of teacher candidates and work with all teachers to understand the complexity of the Asian and Asian American identity, their racialized experiences, and their sociohistorical, transnational contexts that continue to influence their lived experiences. This chapter highlights the important issues and challenges facing Asians and Asian Americans that have been camouflaged by their stereotypical treatment as model minorities. It also shares the work of many scholars on approaches for promoting diversity and inclusion, such as implementing anti-racist, anti-oppressive, and inclusive history curricula, cultural citizenship education, teaching for social justice, and culturally responsive and culturally sustaining teaching for addressing the marginalization of Asians and Asian Americans.

This paper aims to uncover patterns of Mexican craft beer consumers and guide companies’ decisions in the creation of new products, marketing strategies, advertising and promotion to increase craft beer sales and contribute to faster growth.

This is a conjoint analysis with a selection of attributes for new or renewed products, marginal disposition to pay for particular characteristics through brand-specific choice-based design, and market simulation.

This paper clearly demonstrates consumers’ preferences and willingness to pay in Mexico, with a cutting-edge market research technique combining the prioritization of preferred craft beer characteristics, and the price consumers are willing to pay for such product characteristics.

The study's sample size of 501 responses is relatively small compared to the total number of craft beer consumers in Mexico. To enhance the validity and reliability of the findings, future studies should aim to obtain larger samples and compare their results with those of this study.

This study has important implications for craft beer producers, allowing them to develop targeted craft beers with appealing attributes for Mexican consumers, such as color, aroma intensity, alcohol degree intensity, bitterness, foam level and price.

This study's market forecasting simulation technique is based on assumptions of consumer behavior and market dynamics. Although relevant variables were considered, unanticipated external factors or market changes could impact the forecasts' accuracy. This will allow for a more comprehensive understanding of craft beer consumer preferences in different markets and enhance the reliability of forecasting techniques.

This paper informs craft beer producers by providing valuable knowledge on customers’ preferences and willingness to pay to enhance craft beer companies’ product development processes.

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.

This editorial for the 6th World Conference on Production and Operations Management (P&OM) 2022 Special Issue delves into the transformative role of advanced artificial intelligence (AI)-driven chatbots in reshaping operations, supply chain management and logistics (OSCM). It aligns with the conference’s theme of exploring the intersection between P&OM and strategy during the Technological Revolution.

Utilizing a conceptual approach, this paper introduces the “ERI Framework,” a tool designed to evaluate the impact of AI-driven chatbots in three critical operational dimensions: efficiency (E), responsiveness (R) and intelligence (I). This framework is grounded in disruptive debottlenecking theory and real-world applications, offering a novel structure for analysis.

The conceptual analysis suggests immediate benefits of chatbots in enhancing decision-making and resource allocation, thereby alleviating operational bottlenecks. However, it sees challenges such as workforce adaptation and potential impacts on creativity and sustainability.

The paper suggests that while chatbots present opportunities for optimizing operational processes, organizations must thoughtfully address the emerging challenges to maintain productivity and foster innovation. Strategic implementation and employee training are highlighted as key factors for successful integration.

Bridging the gap between the burgeoning proliferation of chatbots and their practical implications in OSCM, this paper offers a first perspective on the role of AI chatbots in modern business environments. By providing insights into both the benefits and challenges of chatbot integration, it offers a preliminary view essential for academics and practitioners in the digital age.

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.

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.

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.

In recent years, the global consumption of craft beer witnesses remarkable growth. This growth is attributed to the evolving demographics of beer consumers, particularly the emergence of a new generation known as Digitarians or Generation Z. This study aims to analyze the key determinants influencing craft beer consumption among Digitarians.

An online questionnaire is administered, and a total of 296 completed responses are included in the statistical analysis. The methodology uses logistic regressions combined with a backward selection process and variance inflation factor analysis to address multicollinearity. The logistic regressions are conducted in three steps to delve into the research objective and gain insights into the behavior of young consumers. The stepwise backward selection aids in obtaining robust coefficients as a variable selection tool.

The results shed light on how Digitarians’ preferences for craft beer are influenced by various factors, including self-perceived knowledge, alcohol content, gender, food pairings, environment and companionship.

To the best of the authors’ knowledge, this paper contributes novel insights by being the first study to explore the significance of craft beer choices among Digitarians, identifying the role of several predictors in their consumption patterns.

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.