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1 – 3 of 3Shivani Bali, Vikram Bali, Rajendra Prasad Mohanty and Dev Gaur
Recently, blockchain technology (BT) has resolved healthcare data management challenges. It helps healthcare providers automate medical records and mining to aid in data sharing…
Abstract
Purpose
Recently, blockchain technology (BT) has resolved healthcare data management challenges. It helps healthcare providers automate medical records and mining to aid in data sharing and making more accurate diagnoses. This paper attempts to identify the critical success factors (CSFs) for successfully implementing BT in healthcare.
Design/methodology/approach
The paper is methodologically structured in four phases. The first phase leads to identifying success factors by reviewing the extant literature. In the second phase, expert opinions were solicited to authenticate the critical success factors required to implement BT in the healthcare sector. Decision Making Trial and Evaluation Laboratory (DEMATEL) method was employed to find the cause-and-effect relationship among the third phase’s critical success factors. In phase 4, the authors resort to validating the final results and findings.
Findings
Based on the analysis, 21 CSFs were identified and grouped under six dimensions. After applying the DEMATEL technique, nine factors belong to the causal group, and the remaining 12 factors fall under the effect group. The top three influencing factors of blockchain technology implementation in the healthcare ecosystem are data transparency, track and traceability and government support, whereas; implementation cost was the least influential.
Originality/value
This study provides a roadmap and may facilitate healthcare professionals to overcome contemporary challenges with the help of BT.
Details
Keywords
Shalini Srivastava, Anupriya Singh and Shivani Bali
This paper aims to investigate the associations between organizational justice dimensions and employees' knowledge sharing (KS) while studying the mediating role of psychological…
Abstract
Purpose
This paper aims to investigate the associations between organizational justice dimensions and employees' knowledge sharing (KS) while studying the mediating role of psychological empowerment (PE) in context of the Indian hospitality industry. It is also aimed to investigate the association between KS and innovative work behavior (IWB).
Design/methodology/approach
A mediation model was verified utilizing three-wave survey data from 293 employees working in hotels situated in northern India. Hypotheses were tested using AMOS and PROCESS Model 4.
Findings
There are significant associations between justice dimensions and KS, and PE mediates these relationships. Additionally, employees' KS has a positive effect on their IWB.
Practical implications
Organizations must promote justice and psychologically empower their employees to facilitate KS. Our study also highlights the significance of employees' KS in encouraging their IWBs. HR leaders and managers have an important role in facilitating the right work environment, in which employees experience fairness and empowerment.
Originality/value
This paper is the first to investigate linkages between justice dimensions, PE, KS and IWB in context of the Indian hospitality industry. Furthermore, this study has made the maiden attempt of asserting the mediating role of PE in the relationship between justice dimensions and KS.
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Keywords
Shefali Arora, Ruchi Mittal, Avinash K. Shrivastava and Shivani Bali
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Originality/value
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.
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