Search results

General Data Protection Regulation (GDPR) of the European Union (EU) was passed to protect data privacy. Though the GDPR intended to address issues related to data privacy in the EU, it created an extra-territorial effect through Articles 3, 45 and 46. Extra-territorial effect refers to the application or the effect of local laws and regulations in another country. Lawmakers around the globe passed or intensified their efforts to pass laws to have personal data privacy covered so that they meet the adequacy requirement under Articles 45–46 of GDPR while providing comprehensive legislation locally. This study aims to analyze the Malaysian and Saudi Arabian legislation on health data privacy and their adequacy in meeting GDPR data privacy protection requirements.

The research used a systematic literature review, legal content analysis and comparative analysis to critically analyze the health data protection in Malaysia and Saudi Arabia in comparison with GDPR and to see the adequacy of health data protection that could meet the requirement of EU data transfer requirement.

The finding suggested that the private sector is better regulated in Malaysia than the public sector. Saudi Arabia has some general laws to cover health data privacy in both public and private sector organizations until the newly passed data protection law is implemented in 2024. The finding also suggested that the Personal Data Protection Act 2010 of Malaysia and the Personal Data Protection Law 2022 of Saudi Arabia could be considered “adequate” under GDPR.

The research would be able to identify the key principles that could identify the adequacy of the laws about health data in Malaysia and Saudi Arabia as there is a dearth of literature in this area. This will help to propose suggestions to improve the laws concerning health data protection so that various stakeholders can benefit from it.

By inspecting the special connection between negligence and the causes of negligence, this study evaluates the reasonableness of negligence offenses elements from the perspectives of “modes” and “rules.” This study considers that in the core concept of negligent manslaughter in the Criminal Code of Taiwan, “business” comprises an outstretched legal element; thus, “application by analogy” or “customary laws” should be prohibited as a legal basis or when applying the criminal code because those are not allowed under nulla poena sine lege. Nulla poena sine lege must be respected to release construction professionals from material risks in their judicial rights and interests.

This study used data mining analysis with a database of 204 cases where construction professionals were involved in an accusation of gross negligence manslaughter (GNM) (N = 486) between 1995 and 2021 to explore the reasons and distribution of these cases in the construction industry in Taiwan.

The results showed that the main reasons behind lawful GNM accusations against construction professionals are as follows: (1) the violation of employers' duty of care to prevent hazards caused in workplaces where falling and collapsing are concerns during construction, thus resulting in death; (2) gross negligence during design, construction and supervision, causing damages after natural disasters such as earthquakes and typhoons.

This study discusses the whole life circle of construction, starting from planning, design, construction and completion. However, the involvement of other offenses such as providing false statements, forgery, embezzlement, unjust enrichment and fraudulent tax evasion or criminal responsibilities stipulated in the Building Act or administrative punishments are beyond the scope of this study. Future studies will focus on foreign “business GNM” cases from judicial precedents with similar backgrounds to Taiwan in the construction industry to verify whether similar conclusions can be drawn and to examine their differences.

This study applied data mining and data analysis to the data and explored potential causality and patterns of GNM cases in judicial cases. The results of the analyses can be used as evidence for potential causality and thus facilitate construction professionals' self-reflection and contribute to the sustainable development of working environments for construction.

This study agrees with the removal of GNM titled “business” in the Criminal Code of Taiwan to achieve Sustainable Development Goals (SDGs) in the building industry. By doing so, national judicial and management systems will be in line with international standards, ensuring that everyone has equal access to justice.

Goal 16 of the SDGs by the United Nations aims to promote judicial equality, peace, justice and strong institutions. With this basis, this study collected and analyzed data in the field of criminal law and applied the theory of criminal offenses committed by negligence to real construction-related cases. This study especially discusses whether construction professionals were imposed with excessive responsibilities when a court enforced the “duty of care” that asked the professionals to bear the responsibility of results for events that should be and could be foreseen.

This paper aims to investigate the impact of prolonged work hours and high stress levels on ethical behavior within health-care settings. It evaluates how these factors compromise professional and personal boundaries and examines the efficacy of targeted ethical training programs designed to mitigate these challenges.

This study adopts an integrated conceptual framework combining the interactionist model of ethical decision-making, organizational justice theory and virtue ethics. It uses data from the General Social Survey (GSS) and analyzes trends and insights from existing literature. The study explores theoretical underpinnings and empirical evidence to understand the complex interplay between workplace stress, long hours and ethical behavior in health-care environments, ensuring the validity and reliability of the findings.

The findings highlight a significant correlation between excessive work hours, increased stress levels and ethical lapses in health-care settings. These lapses, including breaches of confidentiality and inappropriate workplace relationships, can have profound implications for patient care and professional satisfaction. The efficacy of ethical training programs in enhancing moral reasoning and ethical judgment among health-care professionals is demonstrated, particularly those programs that mirror real-world complexities. Such training equips health-care workers with the necessary tools to navigate ethical dilemmas effectively, fostering a culture of ethical awareness and integrity.

This paper uniquely contributes to the literature by comprehensively analyzing how stress and work hours influence ethical behavior, specifically in health-care settings. Supported by a robust theoretical framework, it extends previous research by demonstrating the effectiveness of ethical training in improving ethical behavior. The paper provides practical recommendations for health-care organizations to cultivate a culture of ethical awareness and integrity, highlighting the potential for such programs to improve patient care and professional satisfaction significantly.

Due to its ability to support well-informed decision-making, business intelligence (BI) has grown in popularity among executives across a range of industries. However, given the volume of data collected in health-care organizations, there is a lack of exploration concerning its implementation. Consequently, this research paper aims to investigate the key factors affecting the acceptance and use of BI in healthcare organizations.

Leveraging the theoretical lens of the “unified theory of acceptance and use of technology” (UTAUT), a study framework was proposed and integrated with three context-related factors, including “rational decision-making culture” (RDC), “perceived threat to professional autonomy” (PTA) and “medical–legal risk” (MLR). The variables in the study framework were categorized as follows: information systems (IS) perspective; organizational perspective; and user perspective. In Jordan, 434 healthcare professionals participated in a cross-sectional online survey that was used to collect data.

The findings of the “structural equation modeling” revealed that professionals’ behavioral intentions toward using BI systems were significantly affected by performance expectancy, social influence, facilitating conditions, MLR, RDC and PTA. Also, an insignificant effect of PTA on PE was found based on the results of statistical analysis. These variables explained 68% of the variance (R²) in the individuals’ intentions to use BI-based health-care systems.

To promote the acceptance and use of BI technology in health-care settings, developers, designers, service providers and decision-makers will find this study to have a number of practical implications. Additionally, it will support the development of effective strategies and BI-based health-care systems based on these study results, attracting the interest of many users.

To the best of the author’s knowledge, this is one of the first studies that integrates the UTAUT model with three contextual factors (RDC, PTA and MLR) in addition to examining the suggested framework in a developing nation (Jordan). This study is one of the few in which the users’ acceptance behavior of BI systems was investigated in a health-care setting. More specifically, to the best of the author’s knowledge, this is the first study that reveals the critical antecedents of individuals’ intention to accept BI for health-care purposes in the Jordanian context.

The purpose of this study is to address the significant impact AVs will have on public services and the ability of first responders to conduct their jobs safely and effectively. Autonomous vehicles (AVs) are expected to drastically change the transportation industry, and it is vital that first responders be equipped to integrate them into their occupational responsibilities.

A systematic literature review was conducted, and following a multistep exclusion process, 161 articles were selected for detailed review. The impacts of AVs on first responders were identified, classified and categorized into lists of challenges and opportunities. Based on the findings of the literature review, a SWOT (strengths, weaknesses, opportunities and threats) analysis was conducted, and stakeholder management strategies were designed.

Through the examination of the impacts of AVs on first responders, 17 identified challenges and opportunities were classified into the following categories: AV-related emergency response and training, perceptions and acceptance of AVs, technology development and laws and regulations. The study revealed that the optimal benefits of AVs would require stakeholders to focus more on how they interact with first responders; thus, 14 stakeholder management strategies were identified. First responders, AV manufacturers, legislators and future research paths will all benefit from this study, as it can facilitate smooth interactions between AVs and first responders.

A range of studies have been published on the safety of AVs and the public’s perceptions of this new technology; however, the integration of AVs and their interactions with first responders has been neglected. The goal of this study was to fill that research gap by providing a thorough synthesis of autonomous driving systems in the context of their interactions with first responders.

This study aims to identify and assess the factors challenging the integration of artificial intelligence (AI) technologies in healthcare workplaces.

The study utilized a mixed approach, that starts with a literature review, then developing and testing a questionnaire survey of the factors challenging the integration of AI technologies in healthcare workplaces. In total, 46 factors were identified and classified under 6 groups. These factors were assessed by four different stakeholder categories: facilities managers, medical staff, operational staff and patients/visitors. The evaluations gathered were examined to determine the relative importance index (RII), importance rating (IR) and ranking of each factor.

All 46 factors were assessed as “Very Important” through the overall assessment by the four stakeholder categories. The results indicated that the most important factors, across all groups, are “AI ability to learn from patient data”, “insufficient data privacy measures for patients”, “availability of technical support and maintenance services”, “physicians’ acceptance of AI in healthcare”, “reliability and uptime of AI systems” and “ability to reduce medical errors”.

Determining the importance ratings of the factors can lead to better resource allocation and the development of strategies to facilitate the adoption and implementation of these technologies, thus promoting the development of innovative solutions to improve healthcare practices.

This study contributes to the body of knowledge in the domain of technology adoption and implementation in the medical workplace, through improving stakeholders’ comprehension of the factors challenging the integration of AI technologies.

The purpose of this paper is to illuminate the ethical concerns associated with the use of artificial intelligence (AI) in the medical sector and to provide solutions that allow deriving maximum benefits from this technology without compromising ethical principles.

This paper provides a comprehensive overview of AI in medicine, exploring its technical capabilities, practical applications, and ethical implications. Based on our expertise, we offer insights from both technical and practical perspectives.

The study identifies several advantages of AI in medicine, including its ability to improve diagnostic accuracy, enhance surgical outcomes, and optimize healthcare delivery. However, there are pending ethical issues such as algorithmic bias, lack of transparency, data privacy issues, and the potential for AI to deskill healthcare professionals and erode humanistic values in patient care. Therefore, it is important to address these issues as promptly as possible to make sure that we benefit from the AI’s implementation without causing any serious drawbacks.

This paper gains its value from the combined practical experience of Professor Elhassan gained through his practice at top hospitals worldwide, and the theoretical expertise of Dr. Arabi acquired from international institutes. The shared experiences of the authors provide valuable insights that are beneficial for raising awareness and guiding action in addressing the ethical concerns associated with the integration of artificial intelligence in medicine.

Drawing on the time compression diseconomies perspective and business network theory, this study examines how the international expansion of a business group’s pace, scope and rhythm affects its performance.

Panel data (1999–2013) from the top 100 Taiwanese business groups investing in globalization were collected.

The results show that international pace and rhythm have an inverse U-shaped relationship with business group performance, while the relationship between international scope and business group performance is U-shaped. This study highlights that international expansion is multidimensional and nonlinear and that the factors that shape nonlinear relationships between international processes and performance are different. Furthermore, family group involvement positively moderates the link between international scope and performance and negatively affects the relationship between international pace and performance. However, no significant effect is observed between rhythm and performance. High family business group involvement mitigates the impact of outsiders’ liability and managerial costs; moreover, it enhances the positive effects of location-specific advantages and business network resources.

This study combined the time compression diseconomies perspective and business network theory to explain why and how internationalization may not always lead to good performance by examining the effects of different international expansion processes and the interactive effect of family group involvement.

This study explores the influence of the coronavirus disease 2019 (COVID-19) career experience on the investment behavior and risk tolerance of chief executive officers (CEOs). Specifically, this study focuses on CEOs' abilities to allocate financial assets and maintain solvency.

This study adopts a comprehensive approach to analyze financial assets and asset-to-liability ratios. Financial data and individual information of CEOs from listed companies are collected from 2020Q1 to 2021Q4, along with statistics on confirmed COVID-19 cases. Instrumental and alternative variables are used to examine the robustness and endogeneity of the research, ensuring a thorough analysis.

A significant positive correlation is revealed between CEOs' COVID-19 career experience and their capacity to effectively allocate financial assets. However, COVID-19 has a negative effect on firm performance in terms of solvency. These findings contribute to the empirical evidence linking the pandemic to company performance, representing part of the initial research in this area.

The study suggests that the implementation of potential policy implications, such as loose monetary policies and tax and fee reduction measures, may alleviate the tax burden on listed companies.

The aim of this paper is to explore the internationalization of digital platform firms, specifically to investigate the advantages digital platform firms build during the internationalization journey, which helps them overcome the liability of foreignness. More importantly, drawing on network theory and Luo’s framework of new OLI advantages, a new framework of Platform OLI (P-OLI) advantages is developed for digital platform firms.

This study adopts a multi-case method to empirically understand the internationalization phenomenon of digital platform firms in the emerging economy of India, which is a less researched area. Twenty semi-structured interviews from top executives of 12 Indian headquartered digital platform firms were inductively analyzed based on Gioia’s method, and a cross-case examination was conducted to explore the respondent firm’s internationalization journey.

Several novel open resource and linkage advantages were identified for digital platform firms that are not covered by the new OLI advantages proposed by Luo. Furthermore, a new “I” advantage, which is information and knowledge advantage, has evolved from the data. This resulted in enhancing the scope of the new OLI framework and network theory and further enabled us to develop the P-OLI framework, a new framework for digital platform firms that reflects the specific advantages a digital platform firm builds during internationalization.

This is the first study which evaluates the new OLI framework from the perspective of a digital platform firm to develop a novel framework, P-OLI. Further, this study is among the few studies with an Indian digital platform firm focus and relies on primary interview data to study digital platform firms’ internationalization phenomenon.