A Framework for Investigating the Adoption of Key Technologies: Presentation of the Methodology and Explorative Analysis of Emerging Practices

Abstract

In this article, we present a framework for performing a systematic literature review on the implementation of emerging business practices and the adoption of these key technologies: three-dimensional printing, artificial intelligence, blockchain, computing, digital applications, geospatial technologies, immersive environments, Internet of things, open and crowd-based platforms, proximity technologies, and robotics. Through the content analysis of the full text of scientific papers, emerging practices are captured and then classified within a group of standardized labels. This allows to summarize an emerging practice as the use of a key technology within a business context-represented by industry, business function, and business process adopting the technology-with the aim of achieving improvements in terms of business performance. The adoption of this methodology allows the recognition of the opportunities for companies of enhancing performance through key technologies. With this study, the framework is tested by classifying more than 22 000 scientific articles and extracting 15 708 emerging practices. The explicative power of data collected is demonstrated by performing an explorative analysis aiming at illustrating the state-of-the-art of emerging practices. Moreover, by employing association rules algorithms, 262 practices are found as the most frequent and relevant and are the candidate for becoming future best practices.

Towards a Taxonomy of Industrial Challenges and Enabling Technologies in Industry 4.0

“…However, the mapping of these aspects and subcategories remains unclear. Cammarano et al [32] presented a framework to investigate the adoption of key technologies and emerging business practices in the broader context of I4.0 (also including domains such as e-commerce, food and beverage) based on a systematic literature review of more than 22,000 scientific articles published from 2019 to 2022. The researchers used an inductive approach -without providing a detailed description of its development method-to define a taxonomy of 11 key technologies, resulting in the identification and categorization of 87 specific technologies.…”

“…Another concern (L2) arises from studies that either rely on a limited selection of articles or do not take into account industrial case studies, potentially hindering the representation of multifaceted nature and intricacies of Industry 4.0, as evidenced by [29], [31]. Additionally (L3), some studies do not present a clear methodology for taxonomy [32], [34]), while other studies use the term "taxonomy" merely as a label for their literature categorization, rather than as an actual framework for organizing and classifying concepts or ideas, as observed in [31], [33].…”

“…A further limitation (L4) is the presentation style of some taxonomies, which may not be intuitive or user-friendly, posing challenges for industry professionals aiming to utilize them, as indicated by [32]. Finally (L5), the connection and mapping between the industrial and academic sides of I4.0 are not always clear, which can hinder the identification of appropriate technologies for specific issues, as highlighted by [30].…”

Co-Creating Value With Artificial Intelligence: A Bibliometric Approach to the Use of AI in Open Innovation Ecosystems

“…The three terms included in this subnetwork (Fig. 4), are linked, as the "Implementation" of "Cyber Physical Systems" is one of the cornerstones of "Industry 4.0" [93], [94] and can eventually lead to Industry 5.0 [94], [95]. In this context, "Cyber Physical Systems" are advanced systems inside Internet of things environment that combine physical and computational capabilities [74].…”

Green Supply Chains and Digital Supply Chains: Identifying Overlapping Areas

“…Although digital technologies are currently a key enabler of the efficiency required by green supply chains in order to be "green", the two concepts have different roots. The boom of digital technologies within supply chains has contributed to the blurring of boundaries between the two concepts [12], and yet, despite leading to the same result of more efficient output, they belong to different contexts and have different ultimate goals. One has the grandiose, demanding goal of transforming the global economy to benefit all peoples, communities, and the planet by reducing the environmental footprint of business activities, while the other is nurtured by scientific and technological advancements driven by basic and applied research seeking to advance technological trajectories that fuel economic growth.…”