How can we make sense of smart technologies for sustainable agriculture? - A discussion paper

This paper discusses the challenges of assessing the benefits and risks of new digital technologies, so-called ‘smart technologies’ for sustainable agri-food systems. It builds on the results of a literature review that was embedded in a wider study on future options for (sustainable) farming systems in Germany. Following the concepts of Actor-Network-Theory, we can conceive of smart technologies in agriculture as networks that can only be understood in their entirety when considering the relationships with all actors involved: technology developers, users (farmers, consumers and others), data analysts, legal regulators, policy makers, and potential others. Furthermore, interaction of the technology and its implementers with nature, such as plants, entire landscapes, and animals, need to be taken into consideration. As a consequence, we have to deal with a highly complex system when assessing the technology – at a time where many of the relevant questions have not been sufficiently researched yet. Building on the FAO’s SAFA guidelines, the paper outlines criteria against which smart technologies could be assessed for their potential to contribute to a sustainable development of agri-food systems. These include aspects of governance, ecology, economy and social issues. We draw some tentative conclusions on the required framework conditions for implementation of digital technology, in particular from the perspective of sustainable agriculture. These are aimed at fuelling further discussion about the potentials and risks of the technology

Knowledge management, innovation and big data: Implications for sustainability, policy making and competitiveness

This Special Issue of Sustainability devoted to the topic of “Knowledge Management, Innovation and Big Data: Implications for Sustainability, Policy Making and Competitiveness” attracted exponential attention of scholars, practitioners, and policy-makers from all over the world. Locating themselves at the expanding cross-section of the uses of sophisticated information and communication technology (ICT) and insights from social science and engineering, all papers included in this Special Issue contribute to the opening of new avenues of research in the field of innovation, knowledge management, and big data. By triggering a lively debate on diverse challenges that companies are exposed to today, this Special Issue offers an in-depth, informative, well-structured, comparative insight into the most salient developments shaping the corresponding fields of research and policymaking

The Role and Value of Data in Realising Circular Business Models – a Systematic Literature Review

Peer reviewe

Competitive advantage during industry 4.0: the case for South African manufacturing SMEs

A research report submitted to the Faculty of Engineering and the Built Environment, Uni- versity of the Witwatersrand, Johannesburg, in partial fullfilment of the requirements for the degree of Master of Science in Engineering. Johannesburg, May 2018With the expected disruption of industry 4.0 and the current challenges that SMEs face in South Africa, there is an increasing threat that SMEs will lose any competitive advantage they currently have. This exploratory study investigates how South African manufacturing SMEs can remain competitive during the fourth industrial revolution. Data, in the form of current literature, was analysed using thematic content analysis. From the analysis process, 8 emergent themes were used to organise the results of the study. Notable findings towards generating competitive advantage included: The location of SMEs within clusters, collaboration with disruption leaders, the sharing of outcomes across the value chain, the shift of business models towards a service and software orientation, the use of data driven insights to find and capture high margin markets and the increased effectiveness of labour through technology use. The study also found that the use of the IoT and cloud computing can significantly reduce infrastructure requirements and promote a competitive advantage.MT 201

Contextual impacts on industrial processes brought by the digital transformation of manufacturing: a systematic review

The digital transformation of manufacturing (a phenomenon also known as "Industry 4.0" or "Smart Manufacturing") is finding a growing interest both at practitioner and academic levels, but is still in its infancy and needs deeper investigation. Even though current and potential advantages of digital manufacturing are remarkable, in terms of improved efficiency, sustainability, customization, and flexibility, only a limited number of companies has already developed ad hoc strategies necessary to achieve a superior performance. Through a systematic review, this study aims at assessing the current state of the art of the academic literature regarding the paradigm shift occurring in the manufacturing settings, in order to provide definitions as well as point out recurring patterns and gaps to be addressed by future research. For the literature search, the most representative keywords, strict criteria, and classification schemes based on authoritative reference studies were used. The final sample of 156 primary publications was analyzed through a systematic coding process to identify theoretical and methodological approaches, together with other significant elements. This analysis allowed a mapping of the literature based on clusters of critical themes to synthesize the developments of different research streams and provide the most representative picture of its current state. Research areas, insights, and gaps resulting from this analysis contributed to create a schematic research agenda, which clearly indicates the space for future evolutions of the state of knowledge in this field

Managing changes initiated by industrial big data technologies : a technochange management model

With the adoption of Internet of Things and advanced data analytical technologies in manufacturing firms, the industrial sector has launched an evolutionary journey toward the 4th industrial revolution, or so called Industry 4.0. Industrial big data is a core component to realize the vision of Industry 4.0. However, the implementation and usage of industrial big data tools in manufacturing firms will not merely be a technical endeavor, but can also lead to a thorough management reform. By means of a comprehensive review of literature related to Industry 4.0, smart manufacturing, industrial big data, information systems (IS) and technochange management, this paper aims to analyze potential changes triggered by the application of industrial big data in manufacturing firms, from technological, individual and organizational perspectives. Furthermore, in order to drive these changes more effectively and eliminate potential resistance, a conceptual technochange management model was developed and proposed. Drawn upon theories reported in literature of IS technochange management, this model proposed four types of interventions that can be used to copy with changes initiated by industrial big data technologies, including human process intervention, techno-structural intervention, human resources management intervention and strategic intervention. This model will be of interests and value to practitioners and researchers concerned with business reforms triggered by Industry 4.0 in general and by industrial big data technologies in particular

A taxonomy of critical factors towards Sustainable Operations and Supply Chain Management 4.0 in developing countries– A systematic review and fuzzy group decision-making

Supply chain disruptions, intensified by black swan events such as the COVID-19 pandemic and the Russia-Ukraine war, have increased the interest in resilient supply chains, which can be achieved by adopting sustainable Industry 4.0 (I4.0) practices. However, the critical success factors (CSFs) for sustainable I4.0 in operations and supply chain management (S-OSCM4.0) are unclear, and there is a lack of a holistic and empirically validated taxonomy of CSFs from multiple stakeholders' perspectives to guide organizations in this transition. Moreover, developing countries face specific challenges that require prioritizing the proper set of CSFs for sustainable digitalization. Therefore, this paper aims to develop a CSFs-based taxonomy for S-OSCM4.0 to help organizations stay current in I4.0 adoption and integrate sustainability in OSCM. We first conducted a systematic literature review (SLR) of 131 papers using bibliometric and content analyses and synthesized the theoretical findings into an alpha taxonomy of CSFs following an inductive approach. Then, we employed a Delphi survey technique combining fuzzy logic to solicit experts' perceptions from a developing country to analyze and validate the taxonomy and determine the most pertinent CSFs, resulting in a beta taxonomy of CSFs for S-OSCM4.0. The developed taxonomy represents a pioneering managerial artefact that can guide sustainable development through an inclusive digital transformation with less environmental impact, contributing to decision-making in S-OSCM4.0, especially for operations in developing countries