Much prior literature has discussed bioethics from a Confucian perspective in biomedical research, but little has applied Confucianism in examining ethics in social and behavioral…
Abstract
Purpose
Much prior literature has discussed bioethics from a Confucian perspective in biomedical research, but little has applied Confucianism in examining ethics in social and behavioral research involving human subjects. This paper aims to reexamine the Belmont principles in social and behavioral research from a Confucian perspective to discuss their applicability and limitations and propose implications for revising or extending them potentially in the future.
Design/methodology/approach
A comparison is conducted on bioethics and social and behavioral research ethics. Afterward, a critical analysis is conducted on the Belmont principles of respect for persons, beneficence and justice from a Confucian perspective regarding their application in social and behavioral research.
Findings
From a Confucian perspective, the Belmont principles are necessary but may not be sufficient to cover the width and depth of ethical issues in social and behavioral research, such as those in crowd work-based research. This paper proposes that ethical guidelines for social and behavioral research may need to be updated from the Belmont principles adopting or incorporating certain Confucian ethics.
Originality/value
Social and behavioral research ethics have been relatively marginal compared to the bioethics deliberation in the existing literature. Unlike Beauchamp and Childress’s continued efforts in refining ethical guidelines for biomedical research specifically, little similar work has been done in this area since the Belmont report’s publication in 1979. This paper sheds light on building more refined and specific ethical guidelines to navigate the ever-growing numbers and diversities of nonmedical research topics, methodologies and contexts.
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Purpose: This piece delves into the transformative potential of artificial intelligence (AI) in the healthcare field within the emerging realm of Industry 5.0, highlighting a…
Abstract
Purpose: This piece delves into the transformative potential of artificial intelligence (AI) in the healthcare field within the emerging realm of Industry 5.0, highlighting a people-focused and eco-friendly approach.
Need for the study: While Industry 4.0 set the foundation for digitization in healthcare, it frequently overlooked the human factor and concerns about sustainability. Industry 5.0 tackles these deficiencies by giving importance to human welfare, efficiency in resource usage, and societal consequences alongside technological progress.
Methodology: This research utilizes a survey of existing written works on Industry 5.0, AI in healthcare, and associated empowering technologies. It also leans on insights from recent investigations and business actions to pinpoint current patterns and future paths.
Findings: This chapter showcases how AI-driven solutions can greatly alter various facets of healthcare. Some of these healthcare facets encompass personalized medicine and treatment, intelligent diagnostics and decision support, robot-supported surgery and care, and enhanced availability and affordability.
Practical applications: This piece offers valuable perspectives for healthcare investors. These investors cover healthcare suppliers, technology creators, rule creators, and patients. By embracing the standards of Industry 5.0, the merging of AI into healthcare brings significant potential for crafting a more competent, sustainable, and people-centered healthcare network that benefits both patients and society as a complete unit. This research investigates the stance, viewpoints, and potential impacts of machine intelligence (MI) in health with an emphasis on Industry 5.0.
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This study aims to examine how Confucianism influences corporate digital transformation and explore the underlying mechanisms. Meanwhile, this study also seeks to analyze whether…
Abstract
Purpose
This study aims to examine how Confucianism influences corporate digital transformation and explore the underlying mechanisms. Meanwhile, this study also seeks to analyze whether the relationship between Confucianism and corporate digital transformation significantly varies under different contextual conditions.
Design/methodology/approach
This study utilizes a sample of Chinese listed firms from 2012 to 2021 to empirically examine how Confucianism influences corporate digital transformation and validate the mechanisms of informal hierarchies, agency costs and financing constraints. Moreover, it explores the moderating effects of political connection and overseas culture. Subsample regressions assess the influence of corporate internationalization, property rights and regional marketization.
Findings
The findings of this study highlight the crucial role of Confucianism in driving corporate digital transformation. Confucianism contributes to corporate digital transformation by clarifying informal hierarchies, reducing agency costs and alleviating financing constraints. Nevertheless, political connection and overseas culture weaken the positive impact of Confucianism on corporate digital transformation. Further evidence indicates that Confucianism's influence on digital transformation is particularly pronounced in environments characterized by limited internationalization, heightened marketization and among non-state-owned enterprises.
Originality/value
This study elucidates the role of informal institutions in driving corporate digital transformation, enriching the literatures on the intersection of Confucianism and corporate digitalization. Our findings offer a novel perspective and contribute to management practice by exploring the mechanisms and contextual conditions.
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Kwun Hung Li, Dickson K.W. Chiu, Elaine W.S. Kong and Kevin K.W. Ho
This research investigates mobile security awareness among university students in Hong Kong, who increasingly rely on mobile devices for their daily activities and academic needs…
Abstract
Purpose
This research investigates mobile security awareness among university students in Hong Kong, who increasingly rely on mobile devices for their daily activities and academic needs. This research seeks to inform targeted educational strategies and policies to enhance mobile security practices among young adults, particularly in regions similar to Hong Kong, where mobile usage is extensively integrated into everyday life.
Design/methodology/approach
Utilizing an online survey, this research assessed the mobile security awareness of 407 university students from Hong Kong. The Mann-Whitney U-test and other statistical methods were employed to analyze differences in security awareness based on demographic factors such as IT background, gender, educational level and participation in mobile security courses.
Findings
The research revealed a generally high level of mobile security awareness compared to similar research in other regions. It also highlighted that despite no significant difference in awareness between genders, students from IT-related fields or those who participated in mobile security courses exhibit higher awareness levels. These findings underscore the impact of focused education and training on enhancing mobile security awareness.
Originality/value
This research contributes to the limited but growing body of literature on mobile security awareness from the end-user perspective, particularly among university students in the Asia Pacific region. It offers valuable insights for governments, educators and corporate policymakers worldwide, providing a basis for integrating mobile security education into broader academic and professional training programs.
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Abstract
Purpose
This study quantitatively investigates the impacts of digital and learning orientations on supply chain resilience (SCR) and firm performance (FP), aiming to fill the gaps in understanding their specific impacts in the context of Industry 4.0 developments and supply chain disruptions.
Design/methodology/approach
This study utilized survey techniques and structural equation modelling (SEM) to gather and analyse data through a questionnaire based on a seven-point Likert scale. Hypotheses were formulated based on an extensive literature review and tested using Amos software.
Findings
The study confirms SCR’s significant impact on FP, aligning with existing research on resilience’s role in organizational competitiveness. This study uncovers the nuanced impacts of digital and learning orientations on SCR and FP. Internal digital orientation (DOI) positively impacts SCR, while external digital orientation (DOE) does not. Specific dimensions of learning orientation – shared vision (LOS), open-mindedness (LOO) and intraorganizational knowledge sharing (LOI) – enhance SCR, while commitment to learning (LOC) does not. SCR mediates the relationship between DOI and FP but not between DOE and FP.
Research limitations/implications
This research focuses on digital and learning orientations, recommending that future studies investigate other strategic orientations and examine the specific contributions of various digital technologies to SCR across diverse contexts.
Practical implications
The empirical findings emphasize the significance of developing internal digital capabilities and specific learning orientations to enhance SCR and FP, aligning these initiatives with resilience strategies.
Originality/value
This study advances knowledge by distinguishing the impacts of internal and external digital orientations and specific learning dimensions on SCR and FP, offering nuanced insights and empirical validation.
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Xiaochen Yue, Mary Kang and Yanming Zhang
Manufacturing firms must strengthen their supply chain resilience to survive in turbulent business environments. This study explores how artificial intelligence (AI) can be…
Abstract
Purpose
Manufacturing firms must strengthen their supply chain resilience to survive in turbulent business environments. This study explores how artificial intelligence (AI) can be leveraged to enhance supply chain resilience.
Design/methodology/approach
Drawing on organizational information processing theory, the research investigates the impact of AI usage on proactive and reactive supply chain resilience by fostering referent power in the context of demand dynamism. The study analyzes survey data from 285 Chinese manufacturing firms using structural equation modeling and regression analysis.
Findings
The results indicate that AI usage can enhance both proactive and reactive supply chain resilience. Referent power only mediates the relationship between AI usage and reactive supply chain resilience. Furthermore, this mediating effect is stronger under high-level demand dynamism.
Originality/value
This study highlights the value of AI usage in strengthening supply chain resilience and uncovers its underlying mechanisms. Theoretical and practical implications are discussed.
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The purpose of this study is to examine the effect of trust on user adoption of artificial intelligence-generated content (AIGC) based on the stimulus–organism–response.
Abstract
Purpose
The purpose of this study is to examine the effect of trust on user adoption of artificial intelligence-generated content (AIGC) based on the stimulus–organism–response.
Design/methodology/approach
The authors conducted an online survey in China, which is a highly competitive AI market, and obtained 504 valid responses. Both structural equation modelling and fuzzy-set qualitative comparative analysis (fsQCA) were used to conduct data analysis.
Findings
The results indicated that perceived intelligence, perceived transparency and knowledge hallucination influence cognitive trust in platform, whereas perceived empathy influences affective trust in platform. Both cognitive trust and affective trust in platform lead to trust in AIGC. Algorithm bias negatively moderates the effect of cognitive trust in platform on trust in AIGC. The fsQCA identified three configurations leading to adoption intention.
Research limitations/implications
The main limitation is that more factors such as culture need to be included to examine their possible effects on trust. The implication is that generative AI platforms need to improve the intelligence, transparency and empathy, and mitigate knowledge hallucination to engender users’ trust in AIGC and facilitate their adoption.
Originality/value
Existing research has mainly used technology adoption theories such as unified theory of acceptance and use of technology to examine AIGC user behaviour and has seldom examined user trust development in the AIGC context. This research tries to fill the gap by disclosing the mechanism underlying AIGC user trust formation.
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Parminder Singh Kang and Bhawna Bhawna
This paper explores the application of supervised machine learning (ML) classification models to address supplier performance analysis and risk profiling as a multi-class…
Abstract
Purpose
This paper explores the application of supervised machine learning (ML) classification models to address supplier performance analysis and risk profiling as a multi-class classification problem. The research highlights that current applications of machine learning in supplier selection primarily focus on binary classification problems, underscoring a significant gap in the literature.
Design/methodology/approach
This research paper opts for a structured approach to solve supplier selection and risk profiling using supervised machine learning multi-class classification models and prediction probabilities. The study involved a synthetic data set of 1,600 historical data points, creating a supplier selection framework that simulates current supply chain (SC) performance. The “Supplier Analysis and Selection ML Module” guided supplier selection recommendations based on ML analysis. Real-world variability is introduced through random seeds, impacting actual delivery dates, quantity delivered and quality performance. Supervised ML models, with hyperparameter tuning, enable multi-class classification of suppliers, considering past delivery performance and risk calculations.
Findings
The study demonstrates the effectiveness of the supervised ML-based approach in ensuring consistent supplier selection across multi-class classification problems. Beyond evaluating past delivery performance, it introduces a new dimension by predicting and assessing supplier risks through ML-generated prediction probabilities. This can enhance overall SC visibility and help organizations optimize strategies associated with risk mitigation, inventory management and customer service.
Research limitations/implications
The findings highlight the adaptability of ML-based methodologies in dynamic SC environments, providing a proactive means to identify and manage risks. These insights are vital for organizations aiming to bolster SC resilience, particularly amid uncertainties.
Practical implications
The practical implications of this study are significant for both commercial and humanitarian supply chain management (SCM). For commercial applications, the ML-based methodology allows businesses to make more informed supplier selection decisions, reducing risks and improving operational efficiency. In disaster and humanitarian SC contexts, the use of ML can improve preparedness and resource allocation, ensuring that critical supplies reach affected areas promptly.
Social implications
The study’s implications extend to disaster and humanitarian SCM, where timely and efficient delivery is critical for saving lives and alleviating suffering. ML tools can improve preparedness, resource allocation and coordination in these contexts, enhancing the resilience and responsiveness of humanitarian supply chains.
Originality/value
Unlike conventional methods focused on quality, cost and delivery performance aspects, the current study introduces supervised ML to identify and assess supplier risks through prediction probabilities for multi-class classification problems (delivery performance as late, on-time and ahead), offering a refined understanding of supplier selection in dynamic SC environments.
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Elvira Anna Graziano, Flaminia Musella and Gerardo Petroccione
The objective of this study is to investigate the impact of the COVID-19 pandemic on the consumer payment behavior in Italy by correlating financial literacy with digital payment…
Abstract
Purpose
The objective of this study is to investigate the impact of the COVID-19 pandemic on the consumer payment behavior in Italy by correlating financial literacy with digital payment awareness, examining media anxiety and financial security, and including a gender analysis.
Design/methodology/approach
Consumers’ attitudes toward cashless payments were investigated using an online survey conducted from November 2021 to February 2022 on a sample of 836 Italian citizens by considering the behavioral characteristics and aspects of financial literacy. Structural equation modeling (SEM) was used to test the hypotheses and to determine whether the model was invariant by gender.
Findings
The analysis showed that the fear of contracting COVID-19 and the level of financial literacy had a direct influence on the payment behavior of Italians, which was completely different in its weighting. Fear due to the spread of news regarding the pandemic in the media indirectly influenced consumers’ noncash attitude. The preliminary results of the gender multigroup analysis showed that cashless payment was the same in the male and female subpopulations.
Originality/value
This research is noteworthy because of its interconnected examination. It examined the effects of the COVID-19 pandemic on people’s payment choices, assessed their knowledge, and considered the influence of media-induced anxiety. By combining these factors, the study offered an analysis from a gender perspective, providing understanding of how financial behaviors were shaped during the pandemic.
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Junling Wu, Longfei Sun and Long Lin
This study aims to dye silk with natural pigments extract of Coreopsis tinctoria, by treating the fabrics with appropriate mordant under suitable dyeing conditions, to achieve…
Abstract
Purpose
This study aims to dye silk with natural pigments extract of Coreopsis tinctoria, by treating the fabrics with appropriate mordant under suitable dyeing conditions, to achieve good dyeing depth, fastness and ultraviolet (UV) protection.
Design/methodology/approach
Firstly, single factor experiments were used to determine the basic dyeing conditions of Coreopsis tinctoria. The optimal process conditions for direct dyeing were determined through orthogonal experiments. After that, the dyeing with mordant was used. Based on the previously determined optimal process conditions, silk fabrics were dyed with different mordanting methods, with different mordants and mordant dosages. The dyeing results were compared, in terms of the K/S values of the dyed fabrics, to determine the most appropriate dyeing conditions with mordant.
Findings
The extract of Coreopsis tinctoria can dye silk fabrics satisfactorily. Good dyeing depth and fastness can be obtained by using suitable dyeing methods and dyeing conditions, especially when using the natural mordant pomegranate rind and the rare earth mordant neodymium oxide. The silk fabrics dyed with Coreopsis tinctoria have good UV resistance, which allows a desirable finishing effect to be achieved while dyeing, using a safe and environmentally friendly method.
Research limitations/implications
The composition of Coreopsis tinctoria is complex, and the specific composition of colouring the silk fibre has not been determined. There are many factors that affect the dyeing experiment, which have an impact on the experimental results.
Practical implications
The results of this study may help expand the application of Coreopsis tinctoria beyond medicine.
Originality/value
To the best of the authors’ knowledge, this paper is the first report on dyeing silk with the extract of Coreopsis tinctoria achieving good dyeing results. Its depth of staining and staining fastness were satisfactory. Optimum dyeing method and dyeing conditions have been identified. The fabric dyed with Coreopsis tinctoria has good UV protection effect, which is conducive to improving the application value of the dyeing fabric. The findings help offer a new direction for the application of medicinal plants in the eco-friendly dyeing of silk.