Artificial intelligence and business models in the sustainable development goals perspective: A systematic literature review

Vaio, Assunta Di; Palladino, Rosa; Hassan, Rohail; Escobar, Octavio

doi:10.1016/j.jbusres.2020.08.019

Cited by 623 publications

(328 citation statements)

References 98 publications

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“…The sharing of knowledge connected to new ways of creating and delivering value through emerging technologies has a significant role in improving companies' performance as well; regardless of whether it is implemented through organizational platforms for knowledge exchange on the corporate governance level [22], or the use of a specific technology. Authors [23] describe how Artificial intelligence (AI) can be used for building a knowledge management system that changes organizational culture and directs innovation towards creating better business performance. Thereby, the knowledge about how new technologies can contribute to better business models, and consequently better performance, can start as an internal process.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

“…According to [23], innovation challenges that arise from including digital technologies like artificial intelligence in developing sustainable business models can have "ethical, social, economic, and legal aspects", which should be addressed in relation to the Sustainable Development Goals proposed in the United Nations 2030 Agenda. In this context, the collaboration of scholars, professionals, and institutions in continuing research and "implementing a public-private partnership network to anticipate and manage the profound social changes connected to the digital revolution" [23] is mandatory for achieving sustainability. Gaining new competencies, enhancing knowledge and experience, and building alliances and ecosystems with stakeholders can be performed during lockdowns, i.e., when businesses cannot operate.…”

Section: Conclusion Limitations and Future Researchmentioning

confidence: 99%

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The Impact of COVID-19 on Sustainable Business Models in SMEs

2021

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Businesses have been exposed to various challenges during the global pandemic, and their response to this disruption has impacted their resilience as well as their chances to overcome this crisis. Small and medium-sized enterprises (SMEs) are changing their business models in order to adapt to this changing environment. Service-based industries have been hit particularly hard. This research investigates how SMEs operating in service industries have been coping with the disruptions caused by the COVID-19 pandemic. This research aims to gain insights into which transformation drivers they have focused on and which technologies they have selected as a means to respond to the disruption. These insights regarding SMEs are then explored according to their influence on the redefinition of sustainable business models in SMEs. The review data was analyzed via a customized research framework that contains three dimensions and 30 subconcepts. The results show the distribution of drivers and technologies across service sectors. They are organized into a Business Model Canvas and could be considered useful for academia and practitioners. The highly unpredictable environment allows for only a few feasible strategic approaches regarding an SME’s decision on to follow incumbents, to become a challenger, or to reinvent themselves based on their own transformation drivers and readiness to apply digital technologies.

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Section: Theoretical Backgroundmentioning

confidence: 99%

Section: Conclusion Limitations and Future Researchmentioning

confidence: 99%

The Impact of COVID-19 on Sustainable Business Models in SMEs

2021

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“…Despite having garnered less attention, Chui, et al [12] preceded Vinuesa, et al [1] and arguably provided a more comprehensive and balanced evidence-based account of the potential for beneficial use of AI, also connected to the SDGs. Other recent examples of efforts related to the goal of this article are Di Vaio, et al [13] (who mainly consider SDG12 and sustainable business models) and Khakurel, et al [14] (who delve much deeper into the technological aspects of AI and the SDG framework). Others have examined issues related to the sustainability of AI, without explicitly connecting this to the SDGs, or by only focusing on some of the goals, such as Toniolo, et al [15] and Yigitcanlar and Cugurullo [16].…”

Section: Previous Work On Ai and The Sdgsmentioning

confidence: 99%

AI in Context and the Sustainable Development Goals: Factoring in the Unsustainability of the Sociotechnical System

Sætra

2021

Sustainability

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Artificial intelligence (AI) is associated with both positive and negative impacts on both people and planet, and much attention is currently devoted to analyzing and evaluating these impacts. In 2015, the UN set 17 Sustainable Development Goals (SDGs), consisting of environmental, social, and economic goals. This article shows how the SDGs provide a novel and useful framework for analyzing and categorizing the benefits and harms of AI. AI is here considered in context as part of a sociotechnical system consisting of larger structures and economic and political systems, rather than as a simple tool that can be analyzed in isolation. This article distinguishes between direct and indirect effects of AI and divides the SDGs into five groups based on the kinds of impact AI has on them. While AI has great positive potential, it is also intimately linked to nonuniversal access to increasingly large data sets and the computing infrastructure required to make use of them. As a handful of nations and companies control the development and application of AI, this raises important questions regarding the potential negative implications of AI on the SDGs. The conceptual framework here presented helps structure the analysis of which of the SDGs AI might be useful in attaining and which goals are threatened by the increased use of AI.

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“…Many scholars focus on the gains to be made to economic growth via AI, such as Di Vaio et al (2020), but who note business cultural drift in the presence of AI, or, conversely, the dangers of AI, such as to jobs lost or to liability in physical violence (Geisel, 2018). Katsamakas and Pavlov (2020) write that managers can use AI to speed up and enhance business models, lowers prediction costs, and leverages existing data.…”

Section: Literature Reviewmentioning

confidence: 99%

The games of imitation: AI and a philosophy towards future equilibrium

Barry

2020

JIBE

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This brief conceptual article starts with an argument for Artificial Intelligence (AI)’s ability to “think.” This outgrowth relates to human’s and AI’s power over nature, and to AI’s increasing power in its humanness, measured by the results of competing with humans and other AI machines in the Turing Test, and economic “game theory.” Both, and especially the latter challenge, can be quintessentially human by measuring how one values the self as opposed to society, under varying conditions. Given AI’s advancements enabling it to presumably “win” in the most humanness of games, beyond even reaching a universally beneficial “social optimal” outcome, and thus possibly even having more power than humankind, the article argues for an equilibrium of balanced powers in innovation between AI and humans. Therefore, managers, broadly construed, can function as key brokers between government policy makers and innovators as AI and humans continue to develop further into the future.

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Artificial intelligence and business models in the sustainable development goals perspective: A systematic literature review

Cited by 623 publications

References 98 publications

The Impact of COVID-19 on Sustainable Business Models in SMEs

The Impact of COVID-19 on Sustainable Business Models in SMEs

AI in Context and the Sustainable Development Goals: Factoring in the Unsustainability of the Sociotechnical System

The games of imitation: AI and a philosophy towards future equilibrium

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