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The aim of this paper is to identify some of the challenges that need to be addressed to accelerate the deployment and adoption of smart health technologies for ubiquitous healthcare access. The paper also explores how internet of things (IoT) and big data technologies can be combined with smart health to provide better healthcare solutions.

The authors reviewed the literature to identify the challenges which have slowed down the deployment and adoption of smart health.

The authors discussed how IoT and big data technologies can be integrated with smart health to address some of the challenges to improve health-care availability, access and costs.

The results of this paper will help health-care designers, professionals and researchers design better health-care information systems.

This study aims to better understand the Islamic consumption incentives because the spectacular flourishing of the halal market in different places around the world has grown the interest in understanding and deciphering the mechanisms behind its development.

Through an exploratory study of some Tunisia-based Islamic groups’ purchasing behavior, this paper investigates factors leading to the purchasing of halal goods (Islamic consumption).

Findings show that the Islamic consumer is more of an Islamist than simply a Muslim. In addition, findings show that halal consumption is not merely related to religious affiliations but also the product of numerous cultural, social and psychological factors.

In addition to Islamism and Islamic activism, this paper puts in evidence the role of some post-structural factors such as identity, nostalgia and hedonism in relation to the buying intention of halal products and services.

Climate change-related weather events significantly affect rice production. In this paper, we investigate the impact of and interrelationships between agriculture inputs, climate change factors and financial variables on rice production in India from 1970–2021.

This study is based on the time series analysis; the unit root test has been employed to unveil the integration order. Further, the study used various econometric techniques, including vector autoregression estimates (VAR), cointegration test, autoregressive distributed lag (ARDL) model and diagnostic test for ARDL, fully modified least squares (FMOLS), canonical cointegrating regression (CCR), impulse response functions (IRF) and the variance decomposition method (VDM) to validate the long- and short-term impacts of climate change on rice production in India of the scrutinized variables.

The study's findings revealed that the rice area, precipitation and maximum temperature have a significant and positive impact on rice production in the short run. In the long run, rice area (ß = 1.162), pesticide consumption (ß = 0.089) and domestic credit to private sector (ß = 0.068) have a positive and significant impact on rice production. The results show that minimum temperature and direct institutional credit for agriculture have a significant but negative impact on rice production in the short run. Minimum temperature, pesticide consumption, domestic credit to the private sector and direct institutional credit for agriculture have a negative and significant impact on rice production in the long run.

The present study makes valuable and original contributions to the literature by examining the short- and long-term impacts of climate change on rice production in India over 1970–2021. To the best of the authors’ knowledge, The majority of the studies examined the impact of climate change on rice production with the consideration of only “mean temperature” as one of the climatic variables, while in the present study, the authors have considered both minimum as well as maximum temperature. Furthermore, the authors also considered the financial variables in the model.

The presence of heavy metals in milk causes many acute and chronic physiological dysfunctions in human organs. The present study aims to investigate the heavy metals in cow's and buffalo's milk of two major cities, Karachi and Gujranwala, Pakistan to estimate metal intake by humans from this source.

In total, 48 milk samples from 2 cities were drawn from animals' udder to avoid contamination. Each sample was digested with nitric acid at 105 ^oC (degree Celsius) on a pre-heated electric hot plate to investigate the metals by atomic absorption spectroscopy (flame type). Air-acetylene technique analyzed chromium, cadmium and lead, and the hydride method analyzed arsenic in the milk samples.

The results revealed the highest mean lead concentration (19.65 ± 43.86 ppb) in the milk samples, followed by chromium (2.10 ± 2.33 ppb) and arsenic (0.48 ± 0.73 ppb). Cadmium was not detected in any sample, assuming cadmium's occurrence was below the detection level. The concentrations of all the metals in the samples of the two cities do not differ statistically. Lead concentrations in the buffalo's milk were higher than in cow's milk (p < 0.05). However, the concentrations of arsenic and chromium between buffalo's and cow's milk do not differ statistically. The present study reveals a lower level of metals in the milk than those conducted elsewhere. The mean concentrations of all the metals met the World Health Organization's (WHO) safety guidelines (1993).

Although cadmium causes toxicity in the human body, cadmium could not be measured because cadmium's concentration was below the detection level, which is 1 ppb.

This study will help reduce the toxic metals in our environment, and the sources of heavy metals, particularly from the industrial sector could be identified. The feed and water consumed by the milking animals could be carefully used for feeding them.

This study will help reduce the diseases and malfunction of human organs and organ systems since these heavy metals cause toxicity and carcinogenicity in humans. Arsenic and chromium cause cancer while lead causes encephalopathy (a brain disease).

The study reports heavy metal concentrations in the two attributes of four independent variables of raw milk samples that were scarcely reported from Pakistan.

Drawing on the natural resource-based view (NRBV) theory, the study aimed to examine the mediating role of green innovation (GI) in the nexus between green human resource management practices (Green HRMPs) and sustainable business performance (SBP).

This study adopted the descriptive time-lagged research design. Data were collected from 278 managerial staff of five mining companies in Ghana at different waves within a 3-month interval. Descriptive and inferential statistics were used to analyse the data received using the statistical package for the social sciences (SPSS) statistics (V. 26.0) and Smart PLS (V.4.0).

The study found that Green HRMPs significantly related more to economic performance (EP) than social performance (SP) but did not significantly relate to environmental performance (EnP). Moreover, the results revealed that GI partially mediated the nexus between Green HRMPs and both SP and EP but fully mediated the link between Green HRMPs and EnP.

The relevance of Green HRMPs in ensuring corporate sustainability has been largely established in the extant literature. However, there is an evidential dearth of studies in the literature concerning the mediating role of GI in the nexus between Green HRMPs and SBP, especially in developing economies context. Hence, this study serves as a significant contributing card from Ghana by advancing the NRBV theory.

This study aims to investigate the impact of trust in the metaverse on the Islamic banking sector, particularly in facilitating market success. Additionally, it seeks to explore the relationship between metaverse-driven brand image, product features, service quality and overall performance in the market.

Data were collected from 187 participants in Jordan, with the SmartPLS software used to test the hypotheses.

The findings reveal a significant impact of metaverse-enhanced brand image, product features and service quality on Islamic banking market performance. Furthermore, customer trust in the metaverse plays a significant role in shaping the relationship between product features, service quality and Islamic banking market performance.

The study’s practical implications still suggest the need for a more holistic metaverse-driven approach. Investing in service quality initiatives alone may not adequately build and sustain customer trust in the metaverse. Instead, transparent communication on ethical practices in the metaverse is required to reinforce trust and magnify the positive influence of superior service quality in the metaverse.

From a technological determinist perspective, machine learning (ML) may significantly contribute towards sustainable development. The purpose of this study is to synthesize prior literature on the role of ML in promoting sustainability and to encourage future inquiries.

This study conducts a systematic review of 110 papers that demonstrate the utilization of ML in the context of sustainable development.

ML techniques may play a vital role in enabling sustainable development by leveraging data to uncover patterns and facilitate the prediction of various variables, thereby aiding in decision-making processes. Through the synthesis of findings from prior research, it is evident that ML may help in achieving many of the United Nations’ sustainable development goals.

This study represents one of the initial investigations that conducted a comprehensive examination of the literature concerning ML’s contribution to sustainability. The analysis revealed that the research domain is still in its early stages, indicating a need for further exploration.

This study aims to evaluate the two-way relationship between management practices and firm innovation along with the dual mediation of business environment, degree of competition and energy policies in Greece, Italy, Turkey and Portugal.

The study has derived data from the World Bank Enterprise Survey 2019 for Greece, Italy, Turkey and Portugal and analyzed through partial least squares structural equation modelling (PLS-SEM) to find results.

The outcomes of PLS-SEM revealed that management practices and firm innovation have two-way positive significant relationship with each other in Greece, Italy, Turkey and Portugal. The results exposed that the management practices and firm innovation have two-way positive significant relationship with the business environment, degree of competition, and energy policies in Greece, Italy, Turkey and Portugal. The findings also clarified that the business environment, degree of competition and energy policies have dual mediating role between management practices and firm innovation in Greece, Turkey and Portugal. Surprisingly, business environment does not have dual mediation in Italy.

These useful insights would enable practitioners and direct policymakers to develop and apply more magnificent management practices to boost up innovation among firms.

Although the topics of management practices and innovation have received a great concern of academia, but this is the first study that offers a comprehensive model of the relationship in these domains.

The study aims to examine the impacts of management practices on innovation along with the mediating and moderating role of degree of competition, business environment and environmental policies.

Data were derived from the World Bank Enterprise Survey 2019 for Greece, Italy, Turkey, Portugal and Jordan and analyzed by using PLS-SEM to find results.

Findings revealed that management practices have positive significant relationship with the innovation among firms for Greece, Turkey, Portugal and Jordan but surprisingly insignificant relationship in Italy. Further, management practices have positive significant relationship with the environmental policies, business environment and degree of competition among firms in Greece, Italy, Turkey, Portugal and Jordan. In addition, environmental policies, business environment and degree of competition have positive significant relationship with innovation among firms in Greece, Italy, Turkey, Portugal and Jordan.

These useful insights would enable practitioners and policy makers to develop and apply more influential management practices to boost up the level of innovation among firms.

Although the topics of management practices and innovation have received a great concern of academia, but this is the first study that offers a comprehensive model of the relationship in these domains.