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Deep learning (DL) is on the rise because it can make predictions and judgments based on data that is unseen. Blockchain technologies are being combined with DL frameworks in various industries to provide a safe and effective infrastructure. The review comprises literature that lists the most recent techniques used in the aforementioned application sectors. We examine the current research trends across several fields and evaluate the literature in terms of its advantages and disadvantages.

The integration of blockchain and DL has been explored in several application domains for the past five years (2018–2023). Our research is guided by five research questions, and based on these questions, we concentrate on key application domains such as the usage of Internet of Things (IoT) in several applications, healthcare and cryptocurrency price prediction. We have analyzed the main challenges and possibilities concerning blockchain technologies. We have discussed the methodologies used in the pertinent publications in these areas and contrasted the research trends during the previous five years. Additionally, we provide a comparison of the widely used blockchain frameworks that are used to create blockchain-based DL frameworks.

By responding to five research objectives, the study highlights and assesses the effectiveness of already published works using blockchain and DL. Our findings indicate that IoT applications, such as their use in smart cities and cars, healthcare and cryptocurrency, are the key areas of research. The primary focus of current research is the enhancement of existing systems, with data analysis, storage and sharing via decentralized systems being the main motivation for this integration. Amongst the various frameworks employed, Ethereum and Hyperledger are popular among researchers in the domain of IoT and healthcare, whereas Bitcoin is popular for research on cryptocurrency.

There is a lack of literature that summarizes the state-of-the-art methods incorporating blockchain and DL in popular domains such as healthcare, IoT and cryptocurrency price prediction. We analyze the existing research done in the past five years (2018–2023) to review the issues and emerging trends.

The purpose of this study is to assess the relationship between patient-centricity, care coordination and delivery of quality care for older people with multiple chronic conditions. Care coordination is defined as a process where physicians, nurses and allied professionals work together to clarify responsibilities, care objectives, treatment plans and discharge plans for delivery of unified care. Patient-centricity is defined as an approach of delivering quality care to patients that focuses on creating a positive experience for them.

A literature review was used to identify measures of care coordination and then partial least square structural equation modeling was used to assess interrelationship among patient-centricity, measures of care coordination and delivery of quality care.

Results reveal that care coordinated pathways consist of IT-enabled coordination, interprofessional teamwork, information sharing and facilitative infrastructure requirements and are influenced by patient-centricity. These are deliberate requisites for delivering of quality care. Results of this study present a validated model of care coordination for older people, which may be further explored to refine the concept of care coordination.

Based on these results, practitioners may develop an overarching strategy to deliver seamless care and to achieve better health outcomes. Measures of care coordination may be used as a performance benchmarking tool and will also help in the process mapping of hospitals.

This paper highlights how patient-centricity may be achieved by focusing on coordinated care processes. This understanding may help in designing processes, which in turn deliver health as a social good in an effective manner.

Results of this study present such a validated model for care coordination, which can be used by researchers.

Considering food waste as a global problem resulting from the wastage of valuable resources that could fulfil the requirements of malnourished people, the current research focusses on understanding consumerism’s impact on this phenomenon. Additionally, the circular economy (CE) approach can be critical in reducing food waste and promoting sustainability.

A systematic literature review was conducted using bibliometrics and network analysis. The study reviewed 326 articles within 10 years, from 2013 to 2023.

The findings reveal four prominent factors – behavioural, environmental, socioeconomic and technological – in managing food waste (FW). Reducing FW at a holistic level can benefit individuals and the environment in several ways.

Consumers are encouraged to be more responsible for their food consumption by reducing food waste, as it affects societies and businesses both economically and environmentally. This can help promote a responsible consumption culture that values quality over quantity and encourages people to make more informed choices about what they eat and how they dispose of it post-consumption. All stakeholders, including firms, the government and consumers, must examine the motives behind inculcating pro-environmental behaviour.

Addressing consumerism and the ability to decrease FW behaviour are complex issues that require a multidimensional approach. This study seeks to fill the gap in understanding consumerism and the capacity to reduce FW using the CE approach and understand the research gaps and future research trends.