Next-generation business models for artificial intelligence start-ups in the healthcare industry

Kulkov, Ignat

doi:10.1108/ijebr-04-2021-0304

Cited by 37 publications

(19 citation statements)

References 81 publications

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“…That is why AI is gaining so much importance in all such arenas. Another sector where AI has turned vision into reality is healthcare (Kulkov, 2021). Several apps are quite prominently and frequently used not only to detect human problems in terms of ailments but also to suggest ways to get away from them.…”

Section: Underscoring the Importance Of Artificial Intelligence And B...mentioning

confidence: 99%

Artificial intelligence and big data: ontological and communicative perspectives in multi-sectoral scenarios of modern businesses

Arora

Sharma

2022

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Purpose The purpose of this paper is to see how critical and vital artificial intelligence (AI) and big data are in today’s world. Besides this, this paper also seeks to explore qualitative and theoretical perspectives to underscore the importance of AI and big data applications in multi-sectoral scenarios of businesses across the world. Moreover, this paper also aims at working out the scope of ontological communicative perspectives based on AI alongside emphasizing their relevance in business organizations that need to survive and sustain with a view to achieve their strategic goals. Design/methodology/approach This paper attempts to explore the qualitative perspectives to build a direction for strategic management via addressing the following research questions concerned with assessing the scope of ontological communicative perspectives in AI relevant to business organizations; exploring benefits of big data combined with AI in modern businesses; and underscoring the importance of AI and big data applications in multi-sectoral scenarios of businesses in today’s world. Employing bibliometric analysis along with NVivo software to do sentiment analysis, this paper attempts to develop an understanding of what happens when AI and big data are combined in businesses. Findings AI and big data have tremendous bearing on modern businesses. Because big data comprises enormous information of diverse sorts, AI-assisted machines, tools and devices help modern businesses process it quickly, efficiently and meaningfully. Therefore, business leaders and entrepreneurs need to focus heavily on ontological and communicative perspectives to deal with diverse range of challenges and problems particularly in the context of recent crises caused by COVID-19 pandemic. Research limitations/implications There is hardly any arena of human activity wherein AI and big data are not relevant. The implication of this paper is that of combining both well so that we may find answers to the difficult and challenging multi-sectoral scenarios concerning not just businesses but life at large. Moreover, automated tools based on AI such as natural language processing and speech to text also facilitate meaningful communication at various levels not just in business organizations but other fields of human activities as well. Social implications This paper has layered social implications, as it conceptually works out as to how strategically we may combine AI and big data to benefit modern business scenarios dealing with service providers, manufacturers, entrepreneurs, business leaders, customers and consumers. All the stakeholders are socio-culturally and contextually rooted/situated, and that is how this study becomes socially relevant. Originality/value This paper is an original piece of research and has been envisioned in view of the challenging business scenarios across the world today. This paper underscores the importance of strategically combining AI and big data, as they have enormous bearing on modern businesses. The insights arrived at in this paper have implications for business leaders and entrepreneurs across the globe who could focus more on ontological and communicative perspectives of AI combined with Big Data to deal with diverse range of challenges and problems that modern businesses have been facing particularly in recent times.

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Section: Underscoring the Importance Of Artificial Intelligence And B...mentioning

confidence: 99%

Artificial intelligence and big data: ontological and communicative perspectives in multi-sectoral scenarios of modern businesses

Arora

Sharma

2022

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“…It may be particularly important to analyze these companies, which are similar to social enterprises in the sense that they pursue social and economic ends, to investigate the phenomenon further (Matveeva, 2020;Murphy et al, 2021). Indeed, comparing different types of start-ups is important in order to understand the business model and organizational structure of these organizations (Kulkov, 2022). Moreover, it may be extremely interesting to increase the number of studies that analyze teal organizations (Moreno Romero et al, 2020;Rzepka et al, 2021;Wyrzykowska, 2019).…”

Section: Introductionmentioning

confidence: 99%

In the jungle, the mighty jungle, the zebras are teal tonight: investigating the organizational forms of Generation Z-driven Italian start-ups

de Gennaro,

Mormile,

Piscopo

et al. 2023

JSBED

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PurposeIn light of the new way of interpreting work spearheaded by Generation Z, the objectives of this study are to investigate (1) whether young entrepreneurs identify their start-ups with “zebras” – that is, as a concrete response to the evanescence and fantasy of “unicorns” based on the simultaneous pursuit of profit and social value, mutualism and resilience – and (2) whether they adopt a “teal” organizational configuration – that is, one characterized by evolutionary purpose, self-management and wholeness.Design/methodology/approachThrough a qualitative approach with 41 interviews, this study focuses on start-uppers and companies that are particularly innovative and promising in the Italian context, as selected by Forbes magazine in its ranking of the brightest entrepreneurs, leaders and stars under 30.FindingsThe results suggest that young entrepreneurs recognize the importance of the common themes of the zebra movement and therefore identify their startups with zebras. More specifically, Generation Z entrepreneurs: (1) pursue a dual (economic and social) purpose, (2) are mutualistic and (3) build their organizations with resilience and capital efficiency. In addition, the interviews show that the organizational approach taken follows the paradigm of teal organizations, particularly in terms of evolutionary purpose, distributed leadership and decision-making power, and employee wholeness and empowerment.Originality/valueThis is the first study to analyze the evolutionary trends of animal entrepreneurial “species” led by Generation Z entrepreneurs and organized on the basis of the teal paradigm.

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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%

“…Clearly, benefits can be gained by improving human machine collaboration, such as reducing labor and talent shortages through intelligent recruiting [ 10 ], lowering organizational workloads through automation [ 6 ], and improving decision support for clinical and financial outcomes [ 1 ]. However, limitations in collaborative capabilities often are codified in the data used to create the machine intelligence [ 11 ].…”

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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Next-generation business models for artificial intelligence start-ups in the healthcare industry

Cited by 37 publications

References 81 publications

Artificial intelligence and big data: ontological and communicative perspectives in multi-sectoral scenarios of modern businesses

Artificial intelligence and big data: ontological and communicative perspectives in multi-sectoral scenarios of modern businesses

In the jungle, the mighty jungle, the zebras are teal tonight: investigating the organizational forms of Generation Z-driven Italian start-ups

Providing Care: Intrinsic Human–Machine Teams and Data

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