Preparing for the future: How organizations can prepare boards, leaders, and risk managers for artificial intelligence

Dixit, Arun; Quaglietta, Jennifer; Gaulton, Catherine

doi:10.1177/08404704211037995

Cited by 10 publications

(3 citation statements)

References 8 publications

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“…Once the transaction and operation costs for managers are reduced, teams can coordinate knowledge transfer in a more sensible and structured way and collaborate on projects while outsourcing complex cognitive functions to machines (Dixit et al, 2021). For the relationship between R&D collaboration breadth and innovation outcomes, this means that the diminishing marginal returns to R&D collaboration breadth locally and the negative effect of the R&D collaboration breadth outside of a region can be reduced, increasing innovation outcomes.…”

Section: Theoretical Frameworkmentioning

confidence: 99%

Your innovation or mine? The effects of partner diversity on product and process innovation

Belitski,

Delgado‐Márquez,

Pedauga

2023

J of Product Innov Manag

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Despite a fundamental revolution in digital technology, along with an ancillary reduction in the cost of transmitting knowledge, the innovation literature on knowledge collaboration continues to hold on to the spatial localization of knowledge collaboration as a truism. Drawing on the open innovation literature and knowledge‐based view of firm innovation, this study explores key boundary conditions affecting the relationship between research and development (R&D) collaboration breadth, and product and process innovation. Using a large‐scale survey consisting of 25,813 observations of 14,784 firms in the United Kingdom during 2004–2020, we demonstrate that the breadth of knowledge collaboration with regional, national, and international partners directly affects product and process innovation. However, this relationship depends on the geographical location of the collaboration partner, the type of partner, and the firm's absorptive capacity. We found diminishing marginal returns to knowledge collaboration breadth for regional partners in product innovation, and an inverted U‐shaped relationship in R&D collaboration breadth with regional partners for process innovation and for national and international partners for product and process innovation. While investment in digital technologies only shifts the curve upwards, it is unlikely to change the direction of the relationship between R&D collaboration and a type of innovation outcome. On the contrary, an increase in the share of science, technology, engineering, and math graduates enables firms to leverage the negative effect of R&D collaboration breadth nationally and specifically for process innovation. Investment in digital technology and human capital increases absorptive capacity and reduces the transaction costs associated with over‐search and limited managerial capabilities and resources.

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Section: Theoretical Frameworkmentioning

confidence: 99%

Your innovation or mine? The effects of partner diversity on product and process innovation

Belitski,

Delgado‐Márquez,

Pedauga

2023

J of Product Innov Manag

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“…The healthcare system, notably the leadership, had to develop strategies to contain the changes. Nevertheless, unexpected operational changes have always characterized the healthcare http://dx.doi.org/10.21511/ppm.22 (1).2024.08 environment, and some scholars have suggested the application of Artificial Intelligence (AI) to help "focus on risk identification, management, and mitigation" (Chen & Decary, 2020; Dixit et al, 2021). This study noted three significant concepts related to crisis and leadership practices in managing the pandemic in Jordan -the integration of healthcare reforms, adjusting to COVID-19, and implementing new leadership practices.…”

Section: Management Practices In Running the Daily Operations In Jord...mentioning

confidence: 99%

Challenges and opportunities in healthcare reforms in pre- and post-COVID-19 crisis: A case of Jordan

Alotaiby,

Krenyácz

2024

Problems and Perspectives in Management

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The COVID-19 crisis presented devastating effects on global healthcare, and Jordan was no exception. During such unforeseen challenges, attention shifts to healthcare leadership and management. However, limited research explored the leadership adjustment in Jordanian hospitals during the pandemic. Therefore, this study examined the challenges and opportunities that arose alongside the outbreak of the pandemic in Jordanian hospitals from the leaders’ perspectives. Semi-structured interviews were conducted with healthcare managers in three Jordanian hospitals, focusing on three key areas: healthcare reform integration, the impact of the COVID-19 crisis on hospital performance and healthcare quality, and management practices to handle the pandemic. Interviews were transcribed and thematically analyzed. Eleven hospital managers in seven administrative positions were involved. Three thematic outcomes were noted regarding the integration of healthcare reforms into the Jordanian healthcare system: sources of reforms, challenges of reform integration, and timely integration of the reforms. Positive impacts of the crisis on the Jordanian hospitals’ performance and quality of healthcare service delivery, which are considered opportunities, resulted in three thematic outcomes: infection control protocol, staff education, and patient management. On the other hand, three thematic concepts emerged as challenges of the COVID-19 crisis: workload, stress and fatigue, and staff shortages. Lastly, this study noted three thematic outcomes regarding management practices adopted by the Jordanian healthcare systems to deal with the pandemic: staff training, monitoring, and social support.

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“…More broadly, this research is expected to contribute to addressing the question of whether humans will continue to play a meaningful role in a future likely to be dominated by AI [ 15 ]. The increasing sophistication of algorithms, matched by advances in data acquisition and data storage, is integrating AI into many facets of life [ 16 ]. This presents both opportunities and challenges.…”

Section: Introductionmentioning

confidence: 99%

Human Decision-making in an Artificial Intelligence–Driven Future in Health: Protocol for Comparative Analysis and Simulation

Doreswamy¹,

Horstmanshof²

2022

JMIR Res Protoc

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Background Health care can broadly be divided into two domains: clinical health services and complex health services (ie, nonclinical health services, eg, health policy and health regulation). Artificial intelligence (AI) is transforming both of these areas. Currently, humans are leaders, managers, and decision makers in complex health services. However, with the rise of AI, the time has come to ask whether humans will continue to have meaningful decision-making roles in this domain. Further, rationality has long dominated this space. What role will intuition play? Objective The aim is to establish a protocol of protocols to be used in the proposed research, which aims to explore whether humans will continue in meaningful decision-making roles in complex health services in an AI-driven future. Methods This paper describes a set of protocols for the proposed research, which is designed as a 4-step project across two phases. This paper describes the protocols for each step. The first step is a scoping review to identify and map human attributes that influence decision-making in complex health services. The research question focuses on the attributes that influence human decision-making in this context as reported in the literature. The second step is a scoping review to identify and map AI attributes that influence decision-making in complex health services. The research question focuses on attributes that influence AI decision-making in this context as reported in the literature. The third step is a comparative analysis: a narrative comparison followed by a mathematical comparison of the two sets of attributes—human and AI. This analysis will investigate whether humans have one or more unique attributes that could influence decision-making for the better. The fourth step is a simulation of a nonclinical environment in health regulation and policy into which virtual human and AI decision makers (agents) are introduced. The virtual human and AI will be based on the human and AI attributes identified in the scoping reviews. The simulation will explore, observe, and document how humans interact with AI, and whether humans are likely to compete, cooperate, or converge with AI. Results The results will be presented in tabular form, visually intuitive formats, and—in the case of the simulation—multimedia formats. Conclusions This paper provides a road map for the proposed research. It also provides an example of a protocol of protocols for methods used in complex health research. While there are established guidelines for a priori protocols for scoping reviews, there is a paucity of guidance on establishing a protocol of protocols. This paper takes the first step toward building a scaffolding for future guidelines in this regard. International Registered Report Identifier (IRRID) PRR1-10.2196/42353

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Preparing for the future: How organizations can prepare boards, leaders, and risk managers for artificial intelligence

Cited by 10 publications

References 8 publications

Your innovation or mine? The effects of partner diversity on product and process innovation

Your innovation or mine? The effects of partner diversity on product and process innovation

Challenges and opportunities in healthcare reforms in pre- and post-COVID-19 crisis: A case of Jordan

Human Decision-making in an Artificial Intelligence–Driven Future in Health: Protocol for Comparative Analysis and Simulation

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