Mauro Caputo

The interest of companies in social technologies is growing, since case studies are suggesting positive effects on business performance. However, a systematic literature review (SLR) for synthesizing the huge number of individual cases presented is lacking, with negative implications for both theory and practice. It is difficult to theorize the concrete impact of social technologies in all their facets, understand the state of the art and propose future directions, as well as there is a lack of awareness of where social technologies can help business growth, and which emerging practices can be implemented. The purpose of this article is to narrow these gaps by performing an SLR on a sample of 777 scientific papers, proposing a methodology to classify business case studies. The following social technologies are considered: social media & networks, mobile applications, crowdsourcing platforms, crowdfunding platforms, open innovation platforms, open access platforms, open data platforms, open science platforms, and open-source. After the presentation of a comprehensive state of the art of social technologies implementation, by employing a decision tree algorithm 12 relevant models are identified, so that companies could rely on a few models that can drive towards the effective use of social technologies for business.

A theoretical framework for defining sustainable emerging practices (SEPs) is suggested and results are presented with regard to the use of digital technologies in the business context for achieving better business performance and sustainable development advances. The application of 11 Industry 4.0 technologies in different business functions is analysed in terms of their positive effects on the United Nations Sustainable Development Goals (SDGs), as well as market and organizational impacts, the former related to enhancements in relationships with different stakeholders, the latter related to internal efficiency gains. Sustainable emerging practices are captured through the manual content analysis of scientific papers and classified according to standardized terms. Findings show that (1) the technologies most contributing to sustainable development are artificial intelligence (AI), geo-spatial technologies, blockchain and the Internet of Things (IoT); (2) the context of application is mostly within the operations functions; (3) organizational impacts are more pursued than market ones; and (4) the social dimension of sustainable development is under-investigated compared to the environmental dimension. The study of the state of the art of the contribution of digital innovation to the achievement of sustainable development provides valuable insights for both researchers and practitioners in order to understand which digital technologies should be used within business contexts to achieve specific business performances while respecting the SDGs.

Scientific research on emerging technologies underscored the advantages of their implementation within production systems, with a particular focus on artificial intelligence (AI). In particular, the integration of AI with other cutting-edge technologies is a relevant topic which can potentially lead to huge impacts in terms of business performance. Yet, literature on the subject, although rich, is still fragmented, limited to specific cases and applications, but lacking in a comprehensive classification framework. Therefore, using a systematic literature review, this study provides an overview of how the combination of AI and other cutting-edge technologies could potentially improve market and organisational performance in business functions and processes. By classifying the literature of case studies and real-world applications into specific taxonomies, the research considers an indicator, the co-occurrence ratio, highlighting the most significant and emerging combinations between AI and other cutting-edge technologies, also specifying the contexts in which they are used. The study shows that AI is strongly interconnected with other cutting-edge technologies, suggesting a research agenda in which the integration of AI with other emerging technologies is promising within specific production systems contexts, providing benefits and opportunities for companies.

Digital technologies could be key to solving several open issues in the context of supply chain management (SCM) and sustainable development. The purpose of this article is to investigate the linkage between digital technologies and sustainable practices in SCM. Through a systematic literature review, the article aims to identify which technologies favour sustainable emerging practices considering the triple bottom line (3BL) perspective. In particular, the following 11 technologies were considered: 3D printing, artificial intelligence, blockchain, computing, digital applications, geospatial technologies, Internet of Things, immersive environments, open and crowd-based platforms, proximity technologies and robotics. For the purpose of this research, 5011 peer-reviewed scientific articles were analysed and a comprehensive overview of the use of digital technologies in SCM to favour sustainable emerging practices was proposed. Therefore, four indices that measure the environmental, social, economic and total 3BL sustainability of each technology were used to assess sustainable emerging practices. This study could be useful for both academics and practitioners. For the former, it provides a comprehensive understanding of the application of digital technologies in sustainable emerging practices for SCM. It highlights potential research gaps by proposing scenarios of future research developments. For the latter, the article aims to identify opportunities for the implementation of digital technologies within own company to improve operations management and, at the same time, promote sustainable development.

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.

This article aims to identify the features of sustainability-oriented innovation starting from the content analysis of patent abstracts. An automatic tool was developed capable of finding the keywords, or groups of keywords, related to the 169 targets of sustainable development goals (SDGs). Once the patents deemed useful for pursuing SDGs were selected through the tool, they were analyzed to obtain information on their features in terms of breadth, scope, novelty, openness, prior art and scientific base. Among the most significant results, it is found that a larger number of applicants, suggesting the adoption of “open innovation” strategies, contributes to sustainability orientation. Moreover, patent originality contributes to the probability of pursuing sustainable objectives, especially related to environmental issues. On the contrary, claims are inversely correlated with the attitude to pursue SDGs, i.e., the larger number of areas in which a patent claims to intervene, the lower the probability that such innovation is sustainable. The results obtained by adopting a quantitative approach are in line with suggestions proposed by the literature and, so far, only supported by logical arguments or case studies. The potential of the tool developed, applied to the field of innovation and sustainability, is demonstrated as significant.

Blockchain has recently been associated to Supply Chain Management to solve several problems and change operations management processes. The study proposes to analyse three different scenarios of the Parmigiano Reggiano supply chain considering blockchain technology as an enabler for the use of other technologies such as RFID and the Internet of Things (IoT) and for the exploitation of the Vendor Managed Inventory (VMI) strategy. The study is based on the evaluation of three agent-based simulation scenarios, a traditional "as is" scenario, a second "to be" scenario implementing emerging technologies including blockchain, and a third “to be” scenario that combines the second one with the VMI optimization strategy. The results show how the combined adoption of these technologies improves the procurement process and customer satisfaction. Findings highlight the impacts that the different scenarios have on the supply chain operations in a quantitative way and allows to evaluate the changes in supply chain processes. By employing emerging technologies, order management activities are more automated and time to order and lead time order preparation are reduced. However, to achieve these performances, other data capture tools such as RFID and IoT are needed. Finally, the introduction of the VMI strategy, when enabled by blockchain technology, improves the procurement performances and significantly reduces unfilled orders.