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A direct correlation exists between waste disposal, disease spread and public health. This article systematically reviewed healthcare waste and its implication for public health. This review identified and described the associations and impact of waste disposal on public health.

This paper systematically reviewed the literature on waste disposal and its implications for public health by searching Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA), PubMed, Web of Science, Scopus and ScienceDirect databases. Of a total of 1,583 studies, 59 articles were selected and reviewed.

The review revealed the spread of infectious diseases and environmental degradation as the most typical implications of improper waste disposal to public health. The impact of waste includes infectious diseases such as cholera, Hepatitis B, respiratory problems, food and metal poisoning, skin infections, and bacteremia, and environmental degradation such as land, water, and air pollution, flooding, drainage obstruction, climate change, and harm to marine and wildlife.

Infectious diseases such as cholera, hepatitis B, respiratory problems, food and metal poisoning, skin infections, bacteremia and environmental degradation such as land, water, and air pollution, flooding, drainage obstruction, climate change, and harm to marine and wildlife are some of the public impacts of improper waste disposal.

Healthcare industry waste is a significant waste that can harm the environment and public health if not properly collected, stored, treated, managed and disposed of. There is a need for knowledge and skills applicable to proper healthcare waste disposal and management. Policies must be developed to implement appropriate waste management to prevent public health threats.

Transaction cost economics sees a broad spectrum of governance structures spanned by two types of economic adaptation: autonomous and cooperative. Stakeholder theorists have drawn much inspiration from transaction cost economics but have not paid explicit attention to the centrality of the idea of adaptation in this literature. This study aims to address this gap.

The authors develop a novel conceptual framework applying the distinction between the two types of economic adaptation to stakeholder theory.

The authors argue that the idea of cooperative adaptation is particularly useful for describing the firm’s collaboration with primary stakeholders in the joint value creation process. In contrast, autonomous adaptation is more relevant for firms interacting with secondary stakeholders who are not directly engaged in joint value creation and may not have formal contractual relationships with the firm. Accordingly, cooperative adaptation can be seen as vital for resolving team production problems affecting joint value creation, whereas autonomous adaptation addresses how the firm maintains legitimacy within the larger stakeholder environment.

Similar to its significance for transaction cost economics, the distinction between the two types of adaptation equips stakeholder theory with a new systematic understanding of a potentially broad spectrum of firm–stakeholder collaboration forms.

Following the imperative for human-centric digital innovation brought by the paradigm of Industry 5.0, the article aims to integrate the dispersed and multi-disciplinary literature on individual risks for workers to define, explain and predict individual risks related to Industry 4.0 technologies.

The paper follows the question, “What is the current knowledge and evidence base concerning risks related to Industry 4.0 technologies, and how can this inform digital innovation management in the manufacturing sector through the lens of the Industry 5.0 paradigm?” and uses the method of systematic literature review to identify and discuss potential risks for individuals associated with digital innovation. N = 51 contributions met the inclusion criteria.

The literature review indicates dominant trends and significant gaps in understanding risks from a human-centric perspective. The paper identifies individual risks, their interplay with different technologies and their antecedents at the social, organizational and individual levels. Despite this, the paper shows how the literature concentrates in studying risks on only a limited number of categories and/or concepts. Moreover, there is a lack of consensus in the theoretical and conceptual frameworks. The paper concludes by illustrating an initial understanding of digital innovation via a human-centered perspective on psychological risks.

Findings yield practical implications. In investing in the adoption, generation or recombination of new digital technologies in organizations, the paper recommends managers ensure to prevent risks at the individual level. Accordingly, the study’s findings can be used as a common starting point for extending the repertoire of managerial practices and interventions and realizing human-centric innovation.

Following the paradigm of Industry 5.0, the paper offers a holistic view of risks that incorporates the central role of the worker as crucial to the success of digital innovation. This human-centric perspective serves to inform the managerial field about important factors in risk management that can result in more effective targeted interventions in risk mitigation approaches. Lastly, it can serve to reinterpret digital innovation management and propose future avenues of research on risk.

This study aims to examine how the initial ambiguity of COVID-19 contributed to tourists' intentions for visiting a once-viral outbreak site in the future.

The present study (N = 248) used partial least-squares structural equation modeling (PLS-SEM) to examine whether perceptions of ambiguity and mismanagement of COVID-19 are indirectly related to intentions to travel to Wuhan in a post-pandemic world through perceptions of risk and tourism value. Further, whether the model effects differed as a function of individual safety orientation was examined.

Perceptions of COVID-19 risk and tourism value serially mediated the effects of perceived COVID-19 ambiguity on post-pandemic travel intentions. Safety orientation did not moderate any paths. Perceived risk was a negative direct correlate of post-pandemic travel intentions.

The current study's strength is rooted in its specific targeting of post-pandemic travel intentions to Wuhan—the first city to experience a widescale outbreak of COVID-19 and subsequent international stigma—compared to general travel inclinations.

The health and environmental hazards associated with synthetic dyes have led to a revival of natural dyes that are non-toxic, environmentally benign and coupled with various functions. The study aims to investigate and develop the potentiality of a popular herb called Chromolaena odorata (C. odorata) as a sustainable and stable dyestuff in textiles.

Natural colorant extracted from C. odorata leaves is used to dye the worsted fabric, which is one of the premier end-use of wool in fashion, via the padding method associated with pre-, simultaneous and post-mordanting with chitosan, tannic acid and copper sulfate pentahydrate. The effects of extraction, dyeing and mordanting processes on fabric’s color strength K/S and color difference ΔE_CMC are investigated via International Commission on Illumination’s L*a*b* color space, Fourier transform infrared spectroscopy, scanning electron microscope, color fastness to washing, rubbing, perspiration and light.

The results obtained indicate extraction with ethanol 90% with a solid/liquid ratio of 1:5 within 1 h, and coloration with a liquor ratio of 1:5 (pH 5) within 2 h under padding pressure of 0.3 MPa are the most effective for coloring worsted fabric.

The C. odorata’s application as a highly effective dyestuff possessing good colorimetric effectiveness has expanded this herb's economic potential, contributing partly to economic growth and adding value to wool in global supply chain.

C. odorata dyestuff has prevailed over other natural colorants because of its impressive color fastness against washing, rubbing, perspiration and especially color stability for pH change.

The Indian pharmaceutical industry has contributed significantly to global healthcare by securing superior-quality, inexpensive and reachable medicines worldwide. However, supply chain management (SCM) has been challenging due to constantly shifting requirements for short lifecycles of products, the convergence of industry and changeable realities on the ground. This study aims to identify, assess and prioritize the strengths, weaknesses and opportunities of the pharmaceutical SCM environment in India.

The paper employs a Strength, Weakness, Opportunity, Threat (SWOT) analysis and recognizes strategies to utilize the advantages of the strengths and opportunities, rectify weaknesses and resolve threats.

A variety of strategies that could have a positive effect on the Indian pharmaceutical business are presented. Findings and suggested strategies can significantly advance knowledge, enhance understanding and contribute to the growth of a successful SCM for the Indian pharmaceutical sector.

This paper would act as a roadmap to greater comprehension of the market leaders and market leaders' operating climate. The findings from this study will offer academic scholars and business practitioners deeper insights into the environment of SCM.

This pragmatic research paper aims to unravel the smart vision-based method (SVBM), an AI program to correlate the computer vision (recorded and live videos using mobile and embedded cameras) that aids in manual lifting human pose deduction, analysis and training in the construction sector.

Using a pragmatic approach combined with the literature review, this study discusses the SVBM. The research method includes a literature review followed by a pragmatic approach and lab validation of the acquired data. Adopting the practical approach, the authors of this article developed an SVBM, an AI program to correlate computer vision (recorded and live videos using mobile and embedded cameras).

Results show that SVBM observes the relevant events without additional attachments to the human body and compares them with the standard axis to identify abnormal postures using mobile and other cameras. Angles of critical nodal points are projected through human pose detection and calculating body part movement angles using a novel software program and mobile application. The SVBM demonstrates its ability to data capture and analysis in real-time and offline using videos recorded earlier and is validated for program coding and results repeatability.

Literature review methodology limitations include not keeping in phase with the most updated field knowledge. This limitation is offset by choosing the range for literature review within the last two decades. This literature review may not have captured all published articles because the restriction of database access and search was based only on English. Also, the authors may have omitted fruitful articles hiding in a less popular journal. These limitations are acknowledged. The critical limitation is that the trust, privacy and psychological issues are not addressed in SVBM, which is recognised. However, the benefits of SVBM naturally offset this limitation to being adopted practically.

The theoretical and practical implications include customised and individualistic prediction and preventing most posture-related hazardous behaviours before a critical injury happens. The theoretical implications include mimicking the human pose and lab-based analysis without attaching sensors that naturally alter the working poses. SVBM would help researchers develop more accurate data and theoretical models close to actuals.

By using SVBM, the possibility of early deduction and prevention of musculoskeletal disorders is high; the social implications include the benefits of being a healthier society and health concerned construction sector.

Human pose detection, especially joint angle calculation in a work environment, is crucial to early deduction of muscoloskeletal disorders. Conventional digital technology-based methods to detect pose flaws focus on location information from wearables and laboratory-controlled motion sensors. For the first time, this paper presents novel computer vision (recorded and live videos using mobile and embedded cameras) and digital image-related deep learning methods without attachment to the human body for manual handling pose deduction and analysis of angles, neckline and torso line in an actual construction work environment.

Growing food insecurity is a leading cause of fatalities, particularly in developing nations like Sub-Saharan Africa and Southeast Asia. However, the rising energy consumption and carbon dioxide (CO2) emissions are mostly associated with food production. Balancing the trade-offs between energy intensity and food security remains a top priority for environmentalists. Despite the critical role of the environment in food security, there is a scarcity of substantial studies that explore the statistical connections among food security, CO2 emissions, energy intensity, foreign direct investment (FDI) and per capita income. Therefore, this study aims to provide more precise and consistent estimates of per capita CO2 emissions by considering the interplay of food security and energy intensity within the context of emerging economies.

To examine the long-term relationships between CO2 emissions, food security, energy efficiency, FDI and economic development in emerging economies, this study employs correlated panel-corrected standard error, regression with Newey–West standard error and regression with Driscoll–Kraay standard error models (XTSCC). The analysis utilizes data spanning from 1980 to 2018 and encompasses 32 emerging economies.

The study reveals that increasing food security in a developing economy has a substantial positive impact on both CO2 emissions and energy intensity. Each model, on average, demonstrates that a 1 percent improvement in food security results in a 32% increase in CO2 levels. Moreover, the data align with the Environmental Kuznets Curve (EKC) theory, as it indicates a positive correlation between gross domestic product (GDP) in developing nations and CO2 emissions. Finally, all experiments consistently demonstrate a robust correlation between the Food Security Index (FSI), energy intensity level (EIL) and exchange rate (EXR) in developing markets and CO2 emissions. This suggests that these factors significantly contribute to environmental performance in these countries.

This study introduces novelty by employing diverse techniques to uncover the mixed findings regarding the relationship between CO2 emissions and economic expansion. Additionally, it integrates energy intensity and food security into a new model. Moreover, the study contributes to the literature by advocating for a sustainable development goal (SDG)-oriented policy framework that considers all variables influencing economic growth.

Despite large bodies of research related to the impacts of e-commerce on last-mile logistics and sustainability, there has been limited effort to evaluate urban freight using an equity lens. Therefore, this study proposes a modeling framework that enables researchers and planners to estimate the baseline equity performance of a major e-commerce platform and evaluate equity impacts of possible urban freight management strategies. The study also analyzes the sensitivity of various operational decisions to mitigate bias in the analysis.

The model adapts empirical methodologies from activity-based modeling, transport equity evaluation, and residential freight trip generation (RFTG) to estimate person- and household-level delivery demand and cargo van traffic exposure in 41 U.S. Metropolitan Statistical Areas (MSAs).

Evaluating 12 measurements across varying population segments and spatial units, the study finds robust evidence for racial and socio-economic inequities in last-mile delivery for low-income and, especially, populations of color (POC). By the most conservative measurement, POC are exposed to roughly 35% more cargo van traffic than white populations on average, despite ordering less than half as many packages. The study explores the model’s utility by evaluating a simple scenario that finds marginal equity gains for urban freight management strategies that prioritize line-haul efficiency improvements over those improving intra-neighborhood circulations.

Presents a first effort in building a modeling framework for more equitable decision-making in last-mile delivery operations and broader city planning.

The purpose of this paper is to analyze the incorporation, prioritization and depth of equity, diversity and inclusion (EDI) initiatives in tourism industry restart policies of Canadian provinces and territories. This study investigates how the detailing of EDI in policies determine the priority in emancipating tourism workers from the inequities exacerbated during the pandemic. Such investigation enables a better understanding of the complexities, tendencies and rationale of involving EDI in the tourism industry’s recovery.

The research investigated the presence and prioritization of equity, diversity, and inclusion using systematic text analytics of 38 publicly available restart plans and statements from 52 government and non-government agencies. Using web-based software Voyant Tools to assist in text analytics, a hybrid deductive-inductive coding approach was conducted.

Key outcomes from the analysis revealed scarce to no full and dedicated content on EDI as a holistic initiative necessary for tourism industry relaunch. This lack of EDI content was a result of the greater impetus to prioritize economic generation and limited data due to practical and ideological issues. Results also suggested the tokenizing of EDI in some policies.

Difficulties in data used for research include the lack and availability of restart policies specifically for tourism; most policies were generalized and referred to economic recovery as a whole. Studies of tourism-specific EDI issues were also limited.

The research is revelatory for investigating EDI prioritizations in restart policies even among well-developed and worker-diverse tourism industries such as in Canada, where inequities and injustices to women, Black, Indigenous, gender-diverse, and newcomer tourism workers among others have been withstanding.