Internet of Things and Big Data as enablers for business digitalization strategies

Sestino, Andrea; Prete, M. Irene; Piper, Luigi; Guido, Gianluigi

doi:10.1016/j.technovation.2020.102173

Cited by 366 publications

(229 citation statements)

References 95 publications

(120 reference statements)

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“…Manufacturing firms have been at the forefront of the adoption of advanced wireless sensors that provide information about the environment, context, and location of their industrial assets (Leminen et al, 2020;Ng and Wakenshaw, 2017;Zheng et al, 2020). These technologies allowed digital components and electronics to be embedded in various "things" and enabled them to be smarter and progressively more interlinkedoften called the Industrial Internet of things (IIoT) (Porter and Heppelmann, 2014;Sestino et al, 2020;Suppatvech et al, 2019). Today, manufacturers link physical and digital worlds and collect data from diverse objects, devices, and machines (Bilgeri et al, 2019;Leminen et al, 2018;Schroeder et al, 2020).…”

Section: Digital Servitization and Industrial Digital Platformsmentioning

confidence: 99%

Co-evolution of platform architecture, platform services, and platform governance: Expanding the platform value of industrial digital platforms

2022

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Industrial manufacturers increasingly develop digital platforms in the business-to-business (B2B) context. This emergent form of digital platforms requires a profound yet little understood holistic perspective that encompasses the co-evolution of platform architecture, platform services, and platform governance. To address this research gap, our study examines multiple platform sponsors from an industrial manufacturing context. The study demarcates three platform archetypes: product platform, supply chain platform, and platform ecosystem. We argue that each platform archetype involves a gradual development of platform architecture, platform services, and platform governance, which mirror each other. We also find that each platform archetype is characterized by a specific innovation mechanism that contributes to the platform service discovery and expands the platform value. Our study extends the co-evolution perspective of platform ecosystem literature and digital servitization literature.

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Section: Digital Servitization and Industrial Digital Platformsmentioning

confidence: 99%

Co-evolution of platform architecture, platform services, and platform governance: Expanding the platform value of industrial digital platforms

2022

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“…To that end, it is supported by intelligent AI-exploiting technologies, such as chatbots, personal assistants, Bluetooth beacon technologies and other interfaces of the Internet of Things (IoT). Ultimately, these technologies can transform the customer experience by offering convenience, customization and decision support (Sestino et al, 2020;Willems et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

The role of attitude toward chatbots and privacy concern on the relationship between attitude toward mobile advertising and behavioral intent to use chatbots

2021

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Chatbots are technological tools equipped with artificial intelligence that allow companies to interact with their consumers. Through their computers or mobile devices, consumers can use this technology to search for information, make purchases or request after-sales services. This study aims to identify the role of attitude toward chatbots and privacy concern in the relationship between attitude toward mobile advertising and behavioral intent to use chatbots. After reviewing the literature, the study proposes a moderated mediation model. Through a survey, the study shows that attitude toward mobile advertising does not have a direct effect on the behavioral intent to use chatbot, but is rather mediated by one’s attitude toward chatbots. In fact, the interactivity is unidirectional in the case of mobile advertising (from the company to the consumer), but bidirectional in the case of chatbots (in which consumers have an active role in communication). In line with these assumptions, the data analysis shows that internet privacy concerns only negatively moderate the relationship between attitude toward chatbots and behavioral intent to use this technology. These results can be useful for companies and researchers in terms of developing and testing new digital marketing strategies. The paper concludes with a discussion of the results’ theoretical and managerial implications.

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“…Thirdly, business managers could use the model as a conceptual structure to understand which aspects require more attention and display an opportunity for improving the maturity of their firms. Lastly, by considering the recent advances in those technologies able to drive digitalisation (Sestino et al 2020), managers and marketers can leverage the IAM framework to recognise and facilitate the role of AI in supporting their business strategy. We acknowledge some limitations in our study that could offer opportunities for future research.…”

Section: Implications Limitations and Future Workmentioning

confidence: 99%

Leveraging Artificial Intelligence in Business: Implications, Applications and Methods

Sestino

Mauro

2021

Technology Analysis & Strategic Management

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115

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The concept of Artificial Intelligence (AI) as a business-disruptive technology has developed in academic and professional literature in a chaotic and unstructured manner. This study aims to provide clarity over the phenomenon of business activation of AI by means of a comprehensive and systematic literature review, aimed at suggesting a clear description of what Artificial Intelligence is today. The study analyses a corpus of 3780 contributions through an original combination of two established machine learning algorithms (LDA and hierarchical clustering). The review produced a structured classification of the various streams of current research and a list of promising emerging trends. Results have shed light on six topics attributable to three different themes, namely Implications, Applications and Methods (IAM model). Our analysis could provide researchers and practitioners with a meaningful overview of the body of knowledge and research agenda, to exploit AI as an effective enabler to drive business value.

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Internet of Things and Big Data as enablers for business digitalization strategies

Cited by 366 publications

References 95 publications

Co-evolution of platform architecture, platform services, and platform governance: Expanding the platform value of industrial digital platforms

Co-evolution of platform architecture, platform services, and platform governance: Expanding the platform value of industrial digital platforms

The role of attitude toward chatbots and privacy concern on the relationship between attitude toward mobile advertising and behavioral intent to use chatbots

Leveraging Artificial Intelligence in Business: Implications, Applications and Methods

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