Advanced Technology Infrastructure Research Articles

A SWOT ANALYSIS OF THE TÜRKİYE HEALTHCARE SYSTEM: A PHYSICIANS' PERSPECTIVE

The aim of this study is to conduct a SWOT analysis of the Türkiye healthcare system from the viewpoint of physicians. The sample for this study consisted of 22 physicians who voluntarily participated. A qualitative research approach was employed, utilizing semi-structured interview forms for data collection. Data were gathered both face-to-face and online. The obtained data were coded, and similar codes were categorized and themed. This study incorporated both SWOT analysis and content analysis methods. When examining the findings, physicians highlighted easy access and availability as the strong aspects of the Türkiye healthcare system. However, the system's weaknesses were predominantly identified as issues concerning healthcare professionals. On the other hand, medical tourism was pointed out as the most significant opportunity awaiting the health system, whereas the escalating violence towards healthcare workers was perceived as the biggest threat. The Türkiye Healthcare System stands out with strengths such as ease of access and advanced technological infrastructure, as well as opportunities like medical tourism. However, it also harbors pressing challenges, including violence against healthcare workers and medication shortages. It is anticipated that many of these issues will be addressed when the balance between demand and supply is achieved.

The Impact of the COVID-19 Pandemic on Students’ Future Online Education Behaviour

BackgroundThe COVID-19-related pandemic has affected education hugely, particularly in terms of the massive shift towards online teaching and learning. Higher education students and professors have faced new challenges, which might improve future online education behaviour, based on online education experience and learning, and pedagogical strategies during the COVID-19 pandemic. Objective/Aim: The aim of this paper is to explore the views of Romanian students towards a possible future online education, highlighting their perceptions regarding the efficacy of digital online learning/pedagogical strategies and of the technological infrastructure, using as support theory the Input-Environment-Outcomes (I-E-O) model. Methods/Instruments: An empirical quantitative-based investigation was implemented; data being collected from almost 800 students in business and economics. Based on the proposed conceptual model, data were analysed with structural equations modelling via SmartPLS 3.0. ResultsThe novelty of the paper is that it tries to address students’ perceptions regarding the future of online education, by using a few constructs, some of them validated in the literature, in order to establish pertinent links between these and the future of digital education. Results reveal that Romanian students prefer face-to-face teaching rather than online courses. Conclusions/implications: In crisis situations, digital education might be the proper solution for future education, as it ensures effective education through efficient teaching-learning strategies and an advanced technological infrastructure.

Assessing Southeast Asia countries’ potential in the semiconductor supply chain: an objectively weighting multi-criteria decision-making approach

The semiconductor industry serves as a key enabler of technological progress and economic growth on a global scale. With Southeast Asia emerging as a region of increasing importance in the global supply chain landscape, understanding the potential for its countries to participate in the semiconductor supply chain becomes crucial. Despite extensive research on global supply chain dynamics, a focused analysis on the role of Southeast Asia within this crucial industry has been notably absent, particularly considering recent geopolitical and economic shifts. This gap has been filled by employing a rigorously designed Multi-Criteria Decision Making (MCDM) approach that integrates the Criteria Importance Through Intercriteria Correlation (CRITIC) method and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Data on fifteen indicators, including economic stability, technological innovation capacity, and infrastructural capabilities, were collected and identified through an extensive literature review and consultations with stakeholders. These indicators were weighted using the CRITIC method to reflect their relative importance, and each country’s position relative to an ideal solution was assessed using the TOPSIS method. It was revealed that countries such as Singapore and Malaysia possess significant potential due to their advanced technological infrastructure and stable economic environments. Other countries, like Vietnam and Indonesia, were also found to exhibit promising capabilities, albeit with certain limitations. The study highlights the varying strengths and strategic areas that should be considered by policymakers and investors to enhance integration into the global semiconductor supply chain. Significant contributions to the strategic decision-making process have been made by providing a nuanced analysis of the region’s readiness and identifying specific areas for investment and policy intervention. By offering a methodological framework that can be adapted to other regions and sectors, not only has an existing research void been filled, but the practical understanding of effectively leveraging Southeast Asia’s potential in the semiconductor industry has also been enhanced.

High school graduates’ perceptions of space studies in formal education

Science, technology, engineering, and mathematics (STEM) subjects are a significant concern in educational systems worldwide. Students who learn these subjects acquire skills and knowledge that enable countries to develop advanced technological infrastructures in industry and academia, ultimately driving local and global economies toward a more advanced future. However, many countries have reported reduced student interest in STEM studies. While students become interested in STEM subjects after joining space education projects, these are often informal activities that occur outside schools. Space education allows students to explore several subjects simultaneously through a multidisciplinary approach and facilitates the development of important skills required in the knowledge-intensive industry and academia. Hence, this research aimed to analyze the perceptions and attitudes of high school graduates exposed to school-based space studies within the formal educational framework in relation to their motivation to undergo STEM studies and other pedagogical issues. The results reveal students’ high degree of motivation to undergo STEM studies through space education, which is an expected but not obvious finding. As for the pedagogical aspect, the issues highlighted by space education include learning activities outside the classroom, the acquisition of skills, and the use of the project-based learning (PBL) approach.

Comparative Analysis of Management System Information Systems in E-learning: A Study of Indonesia and Untied States

This study compares the implementation and effectiveness of Management Information Systems (MIS) in e-learning between Indonesia and the United States, aiming to identify unique challenges and opportunities in each country. A qualitative approach, including a systematic review of academic literature and industry publications, was used to conduct a comparative analysis of e-learning MIS in both countries. The United States benefits from advanced technological infrastructure and high digital literacy, facilitating effective MIS implementation in e-learning. Indonesia, while facing challenges like limited internet connectivity and varying digital literacy, is making progress through initiatives like Rumah Belajar and Google Classroom. This study highlights best practices from the U.S. and adaptive strategies from Indonesia, offering valuable insights for improving e-learning systems globally. It emphasizes the importance of collaboration and knowledge sharing to overcome infrastructural barriers and enhance digital literacy in developing nations.

Effect of Emergency Preparedness on Security in Kenyan Universities: A Case Study of Garissa University

Security emergencies and threats have lately been on the increase, with public universities in Kenya reporting many incidents of insecurity. Despite investigation efforts by university management, the high prevalence of insecurity has continued, pointing to the need to determine the relationship between security emergency preparedness and security management in public universities in Kenya. This paper explores the existing types of emergency situations, the existing types of emergency response approaches, and the level of institutional emergency preparedness and their influence on security at Garissa University. Utilizing the emergency Management Theory, the paper points out that the common type of emergency situation in the study institution is terror-related attacks. Training is the common emergency situation response strategy that the university is utilizing in readiness to face emergency situations, and strict checking at the gate is the most common plan that the university has used to deal with emergency situations within its compound and emergency planning in the study institution has enhanced security through control of movement. The study recommends that the university invest in modern and advanced information technology infrastructure and systems to avert incidences of insecurity.

The impacts of emotional intelligence and IOT on operational efficiency in manufacturing: A cross-cultural analysis of Nigeria and the US

This review paper explores the dual impacts of Emotional Intelligence (EI) and the Internet of Things (IoT) on Operational Efficiency (OE) in the manufacturing sectors of Nigeria and the United States, providing a comprehensive cross-cultural analysis. In an era where manufacturing industries globally are undergoing rapid technological advancements and organizational transformations, understanding the synergistic role of human and technological factors is crucial. EI, which encompasses the ability to recognize, understand, and manage emotions, significantly influences leadership effectiveness, team dynamics, and overall workplace harmony. Concurrently, the integration of IoT technologies facilitates real-time data monitoring, predictive maintenance, and enhanced automation, leading to substantial improvements in OE. The paper first delineates the conceptual frameworks of EI and IoT, highlighting their individual contributions to manufacturing efficiency. Subsequently, it discusses the comparative analysis of the manufacturing environments in Nigeria and the US, examining how cultural contexts shape the application and impact of EI and IoT. In the United States, advanced technological infrastructure and a culture of innovation foster the widespread adoption of IoT and the integration of EI in organizational practices. Conversely, Nigeria's manufacturing sector, while facing challenges such as infrastructural deficits and skill gaps, shows potential for growth through targeted investments in technology and human capital development. Through this cross-cultural lens, the paper identifies key differences in the perceptions and applications of EI, the extent of IoT integration, and the resulting OEs. The findings suggest that while the US benefits from a mature ecosystem for both EI and IoT, Nigeria's unique socio-economic landscape necessitates tailored strategies to harness these tools effectively. The analysis concludes with policy and practical implications, offering insights for enhancing manufacturing efficiency through balanced and culturally sensitive approaches to technological and EI advancements. This comprehensive review underscores the importance of synergizing human and technological capabilities to drive sustainable growth and competitiveness in the global manufacturing sector. Keywords: Emotional Intelligence, Internet of Things, Operational Efficiency, Manufacturing, Cross-Cultural Analysis, Nigeria and United States.

Advancing Robotics and Control Systems in West Africa: Opportunities, Challenges, and Future Directions

Robotics and control systems are poised to significantly impact West Africa's socio-economic landscape, offering transformative potential across various sectors. This review examines the current state, challenges, and future directions of robotics and control systems in the region. Robotics technology, while still in its nascent stage in West Africa, presents opportunities for substantial advancements in agriculture, industry, and healthcare. Key areas of focus include the fundamental algebraic methods used in robotics, such as kinematics, dynamic modeling, and control theory, which underpin the design and optimization of robotic systems. The review highlights the potential applications of robotics in agriculture, where automation can enhance productivity and efficiency, and in healthcare, where surgical robots and rehabilitation devices offer improved patient outcomes. However, significant barriers such as limited access to advanced technology, high costs, and inadequate infrastructure pose challenges to widespread adoption. Training and capacity building are critical for fostering a skilled workforce and advancing the robotics industry. Investment in education, specialized training, and international collaborations can address current limitations and support the development of a robust robotics ecosystem. Looking ahead, emerging technologies like artificial intelligence, collaborative robots, and advanced sensing are expected to drive future innovations. Strategic initiatives, including government policies, infrastructure development, and innovation hubs, are essential to realizing the full potential of robotics in West Africa. By overcoming existing challenges and leveraging opportunities for growth, the region can harness robotics and control systems to drive economic development and improve quality of life. Keywords: Robotics, Control Systems, West Africa, Opportunities, Challenges, Future Directions.

Analysis of Financial Technology Business Innovation: A Case Study of Bank Jago

Bank Jago has developed various innovative digital products and services, such as Jago Invest, Jago Autopilot, and Jago Community. These products and services are designed to meet the needs and lifestyle of the modern and digital Indonesian people. Development of sophisticated technological infrastructure. Bank Jago has invested in developing advanced technological infrastructure, such as cloud computing and artificial intelligence. This sophisticated technological infrastructure allows Bank Jago to provide innovative and safe products and services. Development of quality digital talent. Bank Jago has invested in developing quality digital talent, through training and development programs. This quality digital talent is important for developing innovative digital products and services. Collaboration with various partners. Bank Jago has collaborated with various partners, both from the financial and non-financial industries, to develop its products and services. This collaboration is carried out to expand access and benefits of Bank Jago products and services to the Indonesian people.

SOLUCIONES BASADAS EN INTELIGENCIA ARTIFICIAL PARA EL DESARROLLO DE NEGOCIOS EN ENTORNOS PORTUARIOS

Artificial intelligence (AI) is transforming numerous sectors, including the port industry. This article addresses how AI-based solutions can revolutionize business development in port environments, providing significant competitive advantages. The state of the art reveals that ports face increasing challenges in terms of operational efficiency, resource optimization, and competitiveness. In this context, AI emerges as a powerful tool capable of analyzing large volumes of data and making informed decisions.The content of the article is structured into several key sections. First, it explores the competitive advantages offered by AI in the port sector, such as resource optimization, strategic decision-making, improved security, environmental sustainability, and customer experience. Specific applications such as predictive analytics, process automation, and route optimization are discussed. Case studies of ports that have successfully implemented AI technologies, such as the Port of Rotterdam, the Port of Hamburg, and the Port of Singapore, are presented to illustrate the benefits obtained and the challenges overcome.The development of the research focuses on the algorithms and analysis techniques used, including machine learning, neural networks, and natural language processing. Various applications in the port sector are analyzed, from facility pre-design and space optimization to Capex and Opex estimations and business generation capacity. AI is also used to improve operational efficiency and optimize investments and costs.The conclusions emphasize that, although the adoption of AI presents challenges, such as the need for advanced technological infrastructure and continuous staff training, the potential benefits are significant. AI enables ports to improve operational efficiency, reduce costs, increase security and sustainability, and offer better services to customers. Finally, recommendations for the successful implementation of AI solutions are proposed, emphasizing the importance of detailed strategic planning, collaboration with technology partners, and adequate staff training.article is to provide an extensive comparison of some of them, showing their similarities and also their regulatory differences, as well as possible gaps and inconsistencies.

Enhancing public service delivery efficiency: Exploring the impact of AI

This study aims to investigate the impact of Artificial Intelligence (AI) adoption on public service delivery efficiency in India. It addresses a significant gap in existing literature by investigating the impact of AI adoption on public service delivery efficiency in India, a context that has not been extensively explored. Through a comparative analysis approach, the study assesses the effectiveness of AI applications in enhancing public service delivery. The quantitative research design employed in the study draws on previous literature on AI integration in governance and focuses on Chief Information Officers (CIOs) as primary respondents. The findings reveal significant improvements in citizen-centric services and municipal processes due to AI adoption. However, the impact on human-centric aspects is found to be moderate. The study also underscores the importance of infrastructure readiness for successful AI implementation. Notably, only 25 % of organizations were found to be possessing advanced technological infrastructure. This research is original in its focus on Chief Information Officers (CIOs) as primary respondents and its comparative analysis approach to assess the effectiveness of AI applications in enhancing public service delivery. This study offers valuable insights for policymakers and practitioners. Emphasizing the need for effective policies and infrastructure development, it highlights the potential of AI to eliminate corruption risks and enhance overall efficiency and transparency in public service delivery mechanisms.

Learning manufacturing computer vision systems using tiny YOLOv4.

Implementing and deploying advanced technologies are principal in improving manufacturing processes, signifying a transformative stride in the industrial sector. Computer vision plays a crucial innovation role during this technological advancement, demonstrating broad applicability and profound impact across various industrial operations. This pivotal technology is not merely an additive enhancement but a revolutionary approach that redefines quality control, automation, and operational efficiency parameters in manufacturing landscapes. By integrating computer vision, industries are positioned to optimize their current processes significantly and spearhead innovations that could set new standards for future industrial endeavors. However, the integration of computer vision in these contexts necessitates comprehensive training programs for operators, given this advanced system's complexity and abstract nature. Historically, training modalities have grappled with the complexities of understanding concepts as advanced as computer vision. Despite these challenges, computer vision has recently surged to the forefront across various disciplines, attributed to its versatility and superior performance, often matching or exceeding the capabilities of other established technologies. Nonetheless, there is a noticeable knowledge gap among students, particularly in comprehending the application of Artificial Intelligence (AI) within Computer Vision. This disconnect underscores the need for an educational paradigm transcending traditional theoretical instruction. Cultivating a more practical understanding of the symbiotic relationship between AI and computer vision is essential. To address this, the current work proposes a project-based instructional approach to bridge the educational divide. This methodology will enable students to engage directly with the practical aspects of computer vision applications within AI. By guiding students through a hands-on project, they will learn how to effectively utilize a dataset, train an object detection model, and implement it within a microcomputer infrastructure. This immersive experience is intended to bolster theoretical knowledge and provide a practical understanding of deploying AI techniques within computer vision. The main goal is to equip students with a robust skill set that translates into practical acumen, preparing a competent workforce to navigate and innovate in the complex landscape of Industry 4.0. This approach emphasizes the criticality of adapting educational strategies to meet the evolving demands of advanced technological infrastructures. It ensures that emerging professionals are adept at harnessing the potential of transformative tools like computer vision in industrial settings.

MAIN FACTORS AFFECTING THE FINANCIAL STRUCTURE OF ENTERPRISES

Purpose- The purpose of this study is to reveal which main elements affect financial structures within the fields of activity of businesses and the rules they must comply with. Methodology- In order to carry out profitable and efficient activities in business life, complying with laws and regulations, ensuring safety, trust and motivation among employees, regulating employees' rights, wages and personal development have been tried to be revealed with economic information. The harmony of capital owners, managers and employees and the importance of experience and knowledge in making the company financially profitable are explained. Findings- Occupational health and safety have been determined as the order of the working environment, advanced technological infrastructure, support of communication and cooperation, allocation of meeting and rest areas, implementation of policies that make employees valuable, exchange of information in crises, elements based on experience and knowledge that shape and direct international business life. In addition, detection of errors, arrangements between departments, elimination of negativities due to the time effect, positive contribution of employees to business activities, efficient use of financial instruments and development and implementation of audit mechanisms were also found to be important. Conclusion- The problems created by the incompatibility between business life and managerial elements should be sought and solutions should be sought with new working models to eliminate these problems. It is clear that the financial structure of companies will improve, and they will become profitable with the cooperation between employees and managers.

THE DIGITAL TRANSFORMATION OF SMES: A COMPARATIVE REVIEW BETWEEN THE USA AND AFRICA

The digital transformation of Small and Medium-sized Enterprises (SMEs) is a critical phenomenon shaping the global business landscape. This paper presents a comparative review between the United States and Africa, exploring the diverse trajectories of digitalization within these regions. While the USA is often at the forefront of technological advancements, Africa's SMEs exhibit unique challenges and opportunities in their digital transformation journey. In the United States, SMEs have embraced digital technologies to enhance operational efficiency, improve customer experiences, and gain a competitive edge. The adoption of cloud computing, data analytics, and e-commerce platforms has become ubiquitous, fostering innovation and scalability. This comparative study delves into the specific strategies employed by American SMEs to navigate the complexities of the digital era. On the contrary, African SMEs face distinct hurdles in their digital transformation efforts. Infrastructure limitations, limited access to capital, and a diverse economic landscape present unique challenges. However, this review sheds light on the innovative approaches taken by African SMEs to overcome these barriers. Leveraging mobile technology, localized digital solutions, and collaborative networks, African SMEs are carving out their digital paths. Moreover, this comparative review emphasizes the role of government policies and support mechanisms in shaping the digital transformation landscape for SMEs in both regions. By examining regulatory frameworks, funding initiatives, and skill development programs, this paper provides a comprehensive analysis of the ecosystem supporting SMEs in their digital evolution. The digital transformation of SMEs is a dynamic process with distinct nuances in the USA and Africa. While American SMEs benefit from advanced technological infrastructures, African SMEs showcase resilience and adaptability in leveraging digital tools to overcome challenges. Understanding these diverse trajectories is essential for policymakers, businesses, and researchers seeking to foster inclusive and sustainable digital growth globally.
 Keywords: Digital Transformation, SMEs, USA, Africa, Review.

The Transformative Impact of Big Data in Healthcare: Improving Outcomes, Safety, and Efficiencies

The integration of Big Data analytics into the healthcare sector has initiated a period of unparalleled transformation, significantly influencing patient care, research, and healthcare administration. This detailed synthesis, derived from a systematic literature review of 31 articles published between 2013 and 2023, examines the extensive impact of Big Data within the healthcare industry. It addresses how Big Data enhances personalized medicine and optimizes treatment protocols, promotes the use of predictive analytics for the early detection and management of diseases, and bolsters patient safety through the implementation of real-time monitoring and decision support systems. The review also confronts the challenges and limitations associated with Big Data's application, including concerns over data privacy and security, ethical dilemmas, interoperability issues, and the necessity for both skilled personnel and advanced technological infrastructure. Furthermore, this overview ventures into future prospects and technological advancements, emphasizing the pivotal role of emerging technologies such as artificial intelligence (AI), machine learning, and blockchain in heralding a new era of healthcare. It highlights Big Data's instrumental role in supporting public health measures and preparing for pandemics, alongside forecasting the ongoing influence of Big Data in fostering innovative healthcare paradigms. This analysis advocates for a concerted effort among healthcare professionals, policymakers, and technology experts to fully leverage Big Data's capabilities in healthcare, aiming to enhance health outcomes, increase operational efficiencies, and ensure the long-term viability of healthcare systems.

Business analytics in CRM: A comparative review of practices in the USA and Africa

In the dynamic landscape of global business, Customer Relationship Management (CRM) has emerged as a crucial strategy for organizations aiming to enhance customer satisfaction and loyalty. This study delves into the realm of Business Analytics (BA) within CRM, examining the diverse practices employed in the USA and Africa. The purpose is to identify similarities, differences, and potential areas for improvement, with the overarching goal of fostering more effective CRM strategies. The American business landscape, characterized by advanced technological infrastructure and matured data analytics capabilities, provides a fertile ground for sophisticated CRM practices. A comprehensive analysis of leading companies in the USA reveals a strong reliance on predictive analytics, machine learning, and artificial intelligence to glean actionable insights from vast datasets. Such approaches empower organizations to personalize customer experiences, optimize marketing strategies, and drive overall business growth. In contrast, the African business environment exhibits unique challenges and opportunities. While certain regions may face infrastructural constraints, innovative CRM practices tailored to local contexts are emerging. This study sheds light on the utilization of mobile technology, social media analytics, and localized data collection methods as crucial tools in the African CRM landscape. These adaptive strategies not only address challenges but also present opportunities for leapfrogging traditional CRM models. The comparative review uncovers key areas of convergence and divergence between the two regions, highlighting the need for a nuanced approach to global CRM strategies. By synthesizing insights from the USA and Africa, organizations can develop a more holistic understanding of effective CRM practices. This research contributes valuable insights to the ongoing discourse on global business analytics, offering a roadmap for organizations to navigate the intricacies of CRM implementation in diverse and dynamic markets.

Reviewing the use of big data in supply chain optimization in the USA

This paper provides a succinct overview of the review conducted on the utilization of Big Data in supply chain optimization within the United States. The advent of Big Data analytics has revolutionized traditional supply chain management, offering unprecedented opportunities for enhancing efficiency, reducing costs, and improving overall operational performance. This comprehensive review examines the current state of Big Data applications in supply chain optimization, focusing specifically on the context of the United States. The review begins by outlining the fundamental role of Big Data in transforming supply chain processes. It delves into various aspects, including data collection, processing, and analysis, emphasizing their impact on decision-making and strategic planning. Notably, the study highlights real-world examples of successful Big Data implementations within the U.S. supply chain landscape, showcasing how companies have leveraged data-driven insights to streamline operations and gain a competitive edge. Furthermore, the paper explores the challenges associated with the adoption of Big Data in supply chain management. It addresses concerns related to data security, privacy, and the need for advanced technological infrastructure. Additionally, the review considers the organizational and cultural shifts required for successful integration, emphasizing the importance of a holistic approach to implementation. The paper concludes by pointing towards future trends and potential developments in the use of Big Data for supply chain optimization in the U.S. It underscores the evolving nature of technology and its continued impact on reshaping supply chain strategies. The insights derived from this review contribute to a deeper understanding of the current landscape, offering valuable implications for practitioners, researchers, and policymakers engaged in optimizing supply chain processes through the harnessing of Big Data analytics.

AI in supply chain optimization: A comparative review of USA and African Trends

The integration of Artificial Intelligence (AI) in supply chain management has emerged as a critical driver of efficiency and competitiveness in global markets. This paper provides a comparative review of AI trends in supply chain optimization between the United States and African regions, shedding light on the unique challenges and opportunities faced by each. In the United States, AI adoption in supply chain optimization has been robust, with a focus on predictive analytics, machine learning, and advanced automation technologies. American companies leverage AI to enhance demand forecasting, optimize inventory management, and streamline logistics processes. The integration of AI-driven solutions has allowed U.S. businesses to achieve higher accuracy in demand predictions, reduce lead times, and minimize operational costs. Furthermore, the use of AI algorithms in route optimization has significantly improved delivery efficiency, leading to enhanced customer satisfaction. Contrastingly, African countries are experiencing a more gradual but steadily increasing adoption of AI in supply chain optimization. Limited access to advanced technology infrastructure, coupled with resource constraints, has posed challenges for African businesses. However, innovative approaches are being explored, such as the use of mobile technologies and cloud-based solutions to overcome infrastructure limitations. AI applications in African supply chains focus on improving visibility, minimizing waste, and ensuring timely delivery. The continent's diverse supply chain landscape, encompassing agriculture, mining, and manufacturing, presents a unique set of challenges that AI aims to address. Both the United States and African nations recognize the potential of AI to transform supply chain management. While the U.S. is at the forefront of AI implementation, Africa is forging ahead with tailored solutions that align with its specific context. Collaboration and knowledge exchange between these regions could pave the way for a globalized approach to AI in supply chain optimization. This review underscores the importance of understanding regional nuances in adopting AI technologies, fostering collaboration for mutual benefit, and advancing the global evolution of AI-driven supply chain management.

Identifying Accessibility and Equity Defects of Elderly Care Services in Developing Countries: Insights From Xiamen City

Background: The global aging population has raised concerns about the fair distribution of elderly care resources. China, as the largest developing country, has made efforts to address population aging challenges. However, equitable distribution of elderly care resources remains a concern. This study analyzed the spatial layout and accessibility of elderly care service facilities (ECSFs) in Xiamen City to improve resource allocation and enhance the elderly care system in China. The findings provide valuable insights for other developing countries and regions seeking to improve their own elderly care resource allocation.Methods: Xiamen City was chosen as the research area due to its unique geographical location and advanced information technology infrastructure. The study examined the spatial distribution, accessibility, and equity of ECSFs. Using Python, point of interest (POI) data were collected and evaluated using the kernel density method and two‐step floating catchment area method. Spatial autocorrelation analysis identified areas of aggregation and dispersion in ECSF accessibility.Results: Xiamen currently has 660 ECSFs, including nursing homes, adult day care centers, home care agencies, and rural elderly care homes. The analysis revealed spatial disparities, with ECSFs clustering primarily in the central area of Xiamen Island. Significant differences in accessibility were found among the four types of ECSFs. Spatial autocorrelation analysis identified cold and hot spot areas, indicating variations in accessibility across regions.Conclusion: Xiamen City has made progress in allocating elderly care resources and constructing service facilities. However, equity in resource allocation remains a concern. Areas with limited accessibility were identified, leading to unequal access to elderly care resources and timely physical care. To address these challenges, decision‐making departments should consider increasing facilities, improving transportation, enhancing macro planning, and improving facility service quality and accessibility. These measures will optimize ECSF accessibility and promote equitable distribution of elderly care resources.

GEMİ TRAFİK HİZMETLERİNDE ALGILANAN HİZMET KALİTESİNİN KURUMSAL İMAJ ÜZERİNDEKİ ETKİLERİ: TÜRK BOĞAZLARI ÜZERİNE BİR ARAŞTIRMA

Vessel Traffic Services (VTS) is one of the most important aids for ships in the dangerous waters. Due to the ever-increasing sea transport and thus the number of ships in this service, the importance of the services offered by VTS has increased more in the course of time. Despite the advanced technological infrastructure and the improved VTS, however the safety of sea traffic is still mostly based on human factor. Although in the relevant literature there have been some studies revealing the effects of VTS on the safety, there has been no research on the service quality. The aim of this study is, considering the views of ship masters, to analyze the effects of the VTS service quality perceptions on the corporate image. The process of this study has been two-fold; developing a VTS service quality scale for shipmasters and the required through this scale measuring the perceptions of the service quality of the Turkish Straits Vessel Traffic Services (TSVTS) and the effects of these perceptions on the corporate image. Developing the model of study has been based on the relevant literature, and SERVQUAL model has been chosen. Firstly, in analyzing the perceptions, 20 experts from four diverse field have been interviewed and a pilot study has been carried out with shipmasters (n=72). The questionnaire, which has been conducted through shipmasters (n=192) who have used the Turkish Straits, has comprised 25 statements constituting two dimensions as “Perceived Service Quality (PSQ)” and “Corporate Image (CI)”. The results reveal that there is a strong interrelationship between the perceptions of the TSVTS’ service quality and corporate image for shipmasters. The VTS-PSQ scale develop through this research is expected to contribute to evaluating the VTS service quality and thus to the safe navigation through the relevant sea ways.