Adoption of Robotics Technology in Healthcare Sector

Bakshi, Garima; Kumar, Anuj; Puranik, Amulay Nidhi

doi:10.1007/978-981-16-2911-2_42

Cited by 11 publications

(3 citation statements)

References 20 publications

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“…Technology ended many challenges for the organization during the lockdown, and it also brought people together (Shaikh et al , 2021). Robotics, as an essential component of technology, helped doctors and nurses maintain a proper distance from their patients (Bakshi et al , 2022). With the help of technology, people connected with each other through online platforms such as Zoom and Microsoft team (Ayedee and Kumar, 2020).…”

Section: Technology Is Not Everyone's Cup Of Teamentioning

confidence: 99%

Life under COVID-19 lockdown: an experience of old age people in India

Kumar

Ayedee²

2022

WWOP

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Purpose The purpose of this paper is to highlight the pain and suffering of elderly age people during the COVID-19 lockdown. It was an unpleasant experience for old age people. Design/methodology/approach In this paper, primarily, the information has been collected through interviews and observation. The researchers interviewed the older people and discussed their experience during the lockdown, and they also observed their activities during that period. Findings The main results of this paper suggested that lockdown appeared as double-edge sword for old age and elderly people. They are not allowed to go outside to safeguard their lives, and inside the home, they are facing issues of anxiety, fear and mental trauma. They are not able to complete their daily routine, and it is hampering their mental strength. Originality/value The paper is based on firsthand information received from an old-age couple.

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Section: Technology Is Not Everyone's Cup Of Teamentioning

confidence: 99%

Life under COVID-19 lockdown: an experience of old age people in India

Kumar

Ayedee²

2022

WWOP

Self Cite

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“…While there are many advancements in clinical robotic-autonomy [ 2 , 3 , 4 , 5 ], the broad application of autonomy as part of the business of healthcare has followed the traditional pace of the industry’s technological adoption [ 6 ]. In a recent life science executives survey, 69% of life science businesses are already piloting or have adopted AI in their solutions and 22% are evaluating or planning to pilot AI solutions [ 7 ].…”

Section: Introductionmentioning

confidence: 99%

Providing Care: Intrinsic Human–Machine Teams and Data

Russell

Kumar

2022

Entropy

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Despite the many successes of artificial intelligence in healthcare applications where human–machine teaming is an intrinsic characteristic of the environment, there is little work that proposes methods for adapting quantitative health data-features with human expertise insights. A method for incorporating qualitative expert perspectives in machine learning training data is proposed. The method implements an entropy-based consensus construct that minimizes the challenges of qualitative-scale data such that they can be combined with quantitative measures in a critical clinical event (CCE) vector. Specifically, the CCE vector minimizes the effects where (a) the sample size is too small, (b) the data may not be normally distributed, or (c) The data are from Likert scales, which are ordinal, so parametric statistics cannot be used. The incorporation of human perspectives in machine learning training data provides encoding of human considerations in the subsequent machine learning model. This encoding provides a basis for increasing explainability, understandability, and ultimately trust in AI-based clinical decision support system (CDSS), thereby improving human–machine teaming concerns. A discussion of applying the CCE vector in a CDSS regime and implications for machine learning are also presented.

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“…A series of scholars have used the established technology adoption theoretical frameworks such as technology-organization-environment (TOE) (Gangwar et al, 2015), technology acceptance model (TAM) (Marakarkandy et al, 2017), theory of reasoned action (TRA), and diffusion of innovation theory (DOI) (Bakshi et al, 2022). While many a factors based on these theoretical frameworks are common across technologies, there may be unique factors specific to a particular technology.…”

mentioning

confidence: 99%

Robotic process automation adoption: contextual factors from service sectors in an emerging economy

Sharma

Bharadwaj

Gupta

et al. 2022

JEIM

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PurposeThe study aimed to examine the robotic process automation (RPA) contextual (center of excellence and scalability) and the multidisciplinary (TOE) determinants of RPA adoption in service industries in the emerging economy.Design/methodology/approachTen factors were identified through literature surveys and popular studies grounded in technology, organization and environment. SPSS AMOS SEM is used for scale measurement and hypotheses testing. A sample of 313 respondents was collected from middle to above middle management executives of service industries from India. The authors tested the hidden layers and non-linear relationships using artificial neural network (ANN) analysis.FindingsThe low complexity, center of excellence (CoE), and industry/business partner pressure were significant to the RPA adoption in service industries in emerging economies. Counterintuitively, the scalability showed a negative influence on the RPA adoption, and the process capability did not show influence. The results of SEM and ANN were consistent.Research limitations/implicationsThis research can unfold the RPA adoption scholarly debate to multiple services industries beyond the telecom sector in emerging economies.Practical implicationsRPA is a disruptive technology on the artificial intelligence (AI) continuum. It has the potential to change the ways of working and enable technology-driven transformation. However, despite having thriving service industries that can benefit from RPA, emerging economies lag in adoption compared to the developed nations.Social implicationsThe RPA and automation can bring transformation to human society. Large economies such as India and China have large-scale demand for services, and the waiting lines are a common issue struggled by society. RPA can address the scalability issues of several services.Originality/valueThis study is among the first to examine technology-organization-environment (TOE) with RPA, including RPA contextual variables such as the CoE and scalability. Literature reports TOE applications on several emerging technologies of Industry 4.0 such as cloud, blockchain, big data and 3 Dimensional Printing (3DP), but no or little reported studies around RPA in services industries in emerging markets.

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Adoption of Robotics Technology in Healthcare Sector

Cited by 11 publications

References 20 publications

Life under COVID-19 lockdown: an experience of old age people in India

Life under COVID-19 lockdown: an experience of old age people in India

Providing Care: Intrinsic Human–Machine Teams and Data

Robotic process automation adoption: contextual factors from service sectors in an emerging economy

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