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The purpose of this study is to comprehensively explore the impact of digitalization on healthcare supply chains (HcSCs). It seeks to understand how digital technologies enhance efficiency, transparency and responsiveness within these complex logistical systems. The study aims to provide a holistic view of the transformative potential of digitalization in the healthcare sector, with a particular focus on improving patient care and streamlining operational processes.

This research employs a systematic review methodology, carefully curating a selection of 45 relevant articles from 66 articles rigorously screened using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to provide a holistic view. It follows established systematic review protocols, incorporating a meticulous search strategy and precise keyword selection. The chosen research design enables a comprehensive examination of the existing body of knowledge concerning digital platforms, real-time tracking technologies, transparency and responsiveness in the context of HcSCs.

The findings of this study emphasize the pivotal role of digital technologies in reshaping HcSCs. Digital platforms, real-time tracking systems and technological integrations substantially enhance efficiency, transparency and responsiveness. Data-driven decision-making, improved communication and agile responses to dynamic demands are key aspects. These findings underscore the transformative impact of digitalization on healthcare logistics, emphasizing the potential for streamlined operations, enhanced patient care and more efficient resource allocation.

Despite the systematic methodology, this study is subject to certain limitations. It relies on existing literature, which may not cover the most recent developments in the rapidly evolving field of digital HcSCs. Furthermore, the study may be influenced by publication bias. The implications suggest the need for continued research to explore emerging digital technologies and their effects on healthcare logistics, ensuring that supply chains remain agile and responsive.

The practical implications of this research are significant for HcSC managers with insights into digital technologies to enhance transparency and collaboration and improve resource visibility. The integration of data analytics can lead to more effective inventory management and demand forecasting. Blockchain (BC) technology can ensure transparent and secure transactions, fostering trust among stakeholders. For practitioners, this research offers actionable guidance for navigating the digital age, promoting operational efficiency and ensuring a consistent supply of essential medical products. Researchers can use these insights as a foundation for further exploration into the potential of digitalization in HcSCs.

The social implications of digitalization in HcSCs are far-reaching. They encompass improved patient care, as digital technologies enhance the efficiency, transparency and responsiveness of supply chains. This translates to better access to critical medical supplies, potentially reducing healthcare disparities and benefiting underserved populations. Enhanced patient safety is a significant social outcome, as transparent and secure transactions enabled by technologies like BC mitigate the risks associated with counterfeit medications. Furthermore, digitalization builds trust among stakeholders, promotes accountability and fosters resilient healthcare systems, which are capable of responding effectively to crises. It also has the potential to make healthcare more affordable, contributing to increased healthcare access and transparency in decision-making.

The originality and value of this study lie in its comprehensive synthesis of diverse findings related to digitalization in HcSCs. While prior studies have examined isolated facets of digital technology adoption, this research provides a comprehensive overview. It contributes to a deeper understanding of the transformative potential of digitalization within the healthcare sector, offering practical approaches to enhance patient care and streamline operations.

Higher education institutions (HEIs) are crucial in sustainable development. To this end, they must infuse sustainability into all their endeavors. This study aims to delve into the unique vertically integrated project (VIP), a project-based learning approach and its impact on students’ skills and the surrounding community.

The research design was collaborative, reflecting the spirit of the VIP. Step 1 involved an action research approach, where students and instructors worked closely with municipal representatives to identify challenges and devise solutions for local economic development. In Step 2, students' voices were heard through a survey. Step 3 encompassed presentations in scientific and nonscientific events, capturing the community’s perception as a valuable feedback loop.

The authors identified the most effective policies implemented by municipalities that excelled in indices related to the business environment. VIP enhanced students’ soft skills, including critical thinking, teamwork and community spirit. The outcomes of the VIP were effective in identifying public policies aimed at social transformation.

This study’s findings offer significant insights for HEI managers, guiding them in adopting interdisciplinary pedagogical practices. These practices, in turn, foster sustainable development within both internal and external communities. Furthermore, the empirical study’s focus on improving local community governance can potentially enhance the local business environment.

Literature emphasizing the social dimension of sustainability in HEIs is scarce, particularly those practices related to teaching, research and extension linked to projects aimed at community sustainability. This study introduces interdisciplinary practices encouraging student involvement in addressing tangible issues and searching for solutions to community problems.

Social networking sites have become breeding grounds for the spread of fake news and misinformation. At the height of the Covid-19 pandemic, the spread of fake news intensified, causing complications for health communicators by drowning authentic information from verifiable official sources. Looking at the impact of this growing phenomenon on people’s attitudes and behaviour during the pandemic, research in the area must be populated to help governments, supranational organisations, non-governmental organisations as well as civil society organisations to formulate policies to curb the menace. This study was therefore undertaken to unravel current gaps and future research avenues to empower academia in achieving the desired scholarly impact.

The study adopted the systematic review approach, relying on 56 peer-reviewed articles on social media, fake news and misinformation in the Covid-19 pandemic.

The study found that the use of social media during the height of the pandemic led to unhelpful information creation and sharing behaviours such that people’s self-awareness reduced drastically, thereby impeding the fight against the pandemic. The study also established that Entertainment motives, Ignorance and Altruism motives were the dominant factors that influenced the spread of fake news. There was evidence of the marginalization of research on the subject matter from contexts such as Africa, South America and Oceania.

This study has established existing gaps in issues and evidence, methodology, theory and context and consequently discussed future research avenues for social media use and the spread of fake news. The study has also provided practical implications for both governmental and non-governmental organisations in curbing the phenomenon of fake news and misinformation.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-07-2022-0366.

This study looked at the potential applications of geographic information systems (GIS) and remote sensing (RS) for inclusive community development and participation, sustainable tourism, and rural community-based natural resource management (CBNRM) in sub-Saharan Africa and other rural areas worldwide.

To evaluate resource management systems for rural tourism and the environment in Africa and abroad. The study makes use of reviews of relevant literature and documents, and while linking applications for sustainable tourism and local community empowerment with CBNRM and GIS, vital content was manually analyzed.

The study shows a potential affinity between agricultural and tourism businesses that GIS in line with the CBNRM conception can strengthen. In many rural and underdeveloped regions of the continent, this highlights the need for a credible and varied tourism strategy to develop and empower the relevant communities.

Most agricultural communities in Africa are located in low-income regions. Such areas are rich in natural wildlife and have popular tourist destinations. A mix of regional community development initiatives can be built using GIS, sustainable tourism, CBNRM, and community-based tourism (CBT).

This study aims to assess the effects of natural disasters on food security in a sample of 40 sub-Saharan African countries. First, the authors assess the effects of natural disasters on the four dimensions of food security and second, the authors disaggregate natural disaster using the two dimensions that are most representative, namely, hydrological and biological disasters.

The regressions are based on the generalised method of moments on a data set covering the period 2005–2020. Natural disasters are measured by the total number of people affected and food security by its characteristics: access, availability, use and sustainability.

The results show that natural disasters increase the prevalence of undernourishment but reduce dependence on cereal imports. An increase in natural disasters by 1% increases the prevalence of undernourishment by the same proportion. As for import dependency, a 1% increase in natural disasters reduces dependency by 2.2%. The disaggregated effects show that hydrological disasters are more significant than biological disasters in impacting food security. Floods reduce the average energy supply adequacy but also dependence on cereal imports. Policy implications are discussed.

The study complements the extant literature by assessing the effects of natural disasters on food security in a region where food insecurity is one of the worst in the world.

This paper aims to systematically review the application of artificial intelligence (AI) in the tourism industry. By integrating human–computer interaction, machine learning, big data and other relevant technologies, the study establishes a comprehensive research framework that explores the systematic connections between AI and various facets of tourism.

This paper conducts a keyword co-occurrence analysis of 4,048 articles related to AI in tourism. The analysis identifies and classifies dominant topics, which are further refined through thematic literature review and manual coding for detailed discussion.

The analysis reveals five main topics: AI’s impact on tourist experience, AI in tourism marketing and prediction, AI in destination management, AI’s role in tourism enterprises and AI integration in strategic and regulatory framework. Each topic is reviewed to construct an integrated discussion that maps the current landscape and suggests directions for future research.

This paper transcends the fragmented discourse commonly found in the literature by establishing a unified framework that not only enhances understanding of the existing methodologies, theories and applications of AI in tourism but also identifies critical areas for breakthroughs, aiming to inspire a more humane and sustainable integration of AI in the tourism industry.

本文旨在系统回顾人工智能（AI）在旅游业中的应用。通过整合人机交互、机器学习、大数据和其他相关技术, 本研究建立了一个全面的研究框架, 探索人工智能与旅游业各方面之间的系统联系。

本文对4048篇与旅游业人工智能相关的文章进行了关键词共现分析。分析确定了主要议题并对其进行了分类, 然后通过主题文献梳理和手动编码对其进行了进一步完善, 以便进行详细讨论。

分析揭示了五个主要主题：人工智能与旅游体验、人工智能与旅游营销和预测、人工智能与目的地管理、人工智能与旅游企业, 以及人工智能在战略和监管框架中的整合。每个主题都进行了回顾, 以构建一个综合讨论, 勾勒出当前的研究格局, 并提出了未来的研究方向。

研究力图突破目前关于旅游与人工智能的碎片化讨论, 建立了一个统一的框架, 旨在加强对旅游业中人工智能现有方法、理论和应用的理解, 还点明了需要突破的关键领域, 以助力旅游业与人工智能共同创造更加人性化和可持续发展的前景。

Este artículo pretende revisar sistemáticamente la aplicación de la inteligencia artificial (IA) en el sector turístico. Mediante la integración de la interacción humano-ordenador, el aprendizaje automático, big data y otras tecnologías relevantes, el estudio establece un marco de investigación exhaustivo que explora las conexiones sistemáticas entre la IA y diversas facetas del turismo.

Este trabajo realiza un análisis de co-ocurrencia de palabras clave de 4.048 artículos relacionados con la IA en el turismo. El análisis identifica y clasifica los temas dominantes, sobre los que se profundiza mediante una revisión temática de la literatura y una codificación manual para su discusión detallada.

El análisis presenta cinco temas principales: El impacto de la IA en la experiencia turística, la IA en el marketing y la predicción turística, la IA en la gestión de destinos, el papel de la IA en las empresas turísticas y la integración de la IA en el marco estratégico y normativo. Cada tema se revisa para construir un debate integrado que trace el panorama actual y sugiera direcciones para futuras investigaciones.

Este artículo expande el análisis fragmentado que suele encontrarse en la bibliografía al establecer un marco unificado que no sólo mejora la comprensión de las metodologías, teorías y aplicaciones existentes de la IA en el turismo, sino que también identifica las áreas críticas para los avances, con el objetivo de inspirar una integración más humana y sostenible de la IA en la industria turística.

The geographical location of Yazd province has significant potential for religious tourism. To make the most of this opportunity, it is important to develop an interpretive structural modeling. This paper aims to outline a model for the development of religious tourism in Yazd province as a Global Religious Destination by identifying and analyzing the interaction of effective drivers in future religious tourism development.

The research methodology is based on the interpretative paradigm and is developmental in nature. It takes an exploratory-analytical approach through the adoption of an inductive method and uses mixed research (qualitative/quantitative) involving religious tourism experts and tourists. The study consists of three main steps. In the first step, effective drivers in future religious tourism development were identified through content analysis of published articles. In the second step, the identified drivers were finalized through a survey of experts. Using futures research and Micmac software, a model was designed to investigate the interaction of the future drivers of religious tourism development. In the third step of the research, 384 tourists who visited Yazd Global Religious Destination participated to check the accuracy of the presented model.

Content analysis and review of scientific documents have identified 14 effective drivers in future religious tourism development that have finalized in a layered model. The model identified factors from the most influential at level one to the least influential at level eight. the theoretical foundations of this research confirmed by 384 visitors participated.

developing religious tourism, whether in the form of a religious city, a religious value system, a religious ceremony and a religious business, requires a comprehensive view that includes tourist’s mental and visual imagery, destination brand’s ideals and visions, religious belief, governmental and formal activities and the material and spiritual capital that can offer religious life style in the world markets to audiences from all over the world in the best way and in the dynamic conditions of competition between destination brands, occupy the first rungs of the audience’s mental ladder.

The study investigates the intention of adopting solar panels and incorporating renewable energy sources into the electrical mix, providing insightful information on the nuances of this critical topic.

The study used online and offline surveys to gather information on rooftop solar panels from Indian homes. To get reliable findings, the collected responses were analyzed using structural equation modeling using Smart PLS version 3.5 and SPSS version 23.0.

The research examines sustainability difficulties, psychological issues and demographic considerations, yielding a variety of conclusions. Low compatibility and high perceived cost have a detrimental influence on adoption intentions, emphasizing the importance of integrating consumer perceptions with technology while addressing cost concerns. Conversely, relative advantage, awareness, environmental concern, facilitating conditions and observability positively influenced the adoption.

The study underscores the importance of highlighting benefits, raising awareness, providing necessary resources and showcasing visible instances of technology use. By revealing the connection between different factors, the study offers a roadmap for policymakers and stakeholders to accelerate the transition toward sustainable energy practices.

To the best of the authors' knowledge, this study is one of the first to propose an integration of the Theory of Planned Behavior (TPB), the Diffusion of Innovations Theory (DOI) and the Unified Theory of Acceptance and Use of Technology (UTAUT), alongside various independent variables. The research offers a comprehensive perspective on factors that facilitate and obstruct the usage of solar energy.

Accurate mapping is crucial for the positioning and navigation of mobile robots. Recent advancements in algorithms and the accuracy of LiDAR sensors have led to a gradual improvement in map quality. However, challenges such as lag in closing loops and vignetting at map boundaries persist due to the discrete and sparse nature of raster map data. The purpose of this study is to reduce the error of map construction and improve the timeliness of closed loop.

In this letter, the authors introduce a method for dynamically adjusting point cloud distance constraints to optimize data association (ODA-d), effectively addressing these issues. The authors propose a dynamic threshold optimization method for matching point clouds to submaps during scan matching.

Large deviations in LiDAR sensor point cloud data, when incorporated into the submap, can result in irreparable errors in correlation matching and loop closure optimization. By implementing a data association framework with double constraints and dynamically adjusting the matching threshold, the authors significantly enhance submap quality. In addition, the authors introduce a dynamic fusion method that accounts for both submap size and the distance between submaps during the mapping process. ODA-d reduces errors between submaps and facilitates timely loop closure optimization.

The authors validate the localization accuracy of ODA-d by examining translation and rotation errors across three open data sets. Moreover, the authors compare the quality of map construction in a real-world environment, demonstrating the effectiveness of ODA-d.