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CSR, Sustainability, Ethics & Governance Series Editors: Samuel O. Idowu · René Schmidpeter
Adele Parmentola Ilaria Tutore
Industry 4.0 Technologies for Environmental Sustainability Intended and Unintended Consequences
CSR, Sustainability, Ethics & Governance
Series Editors Samuel O. Idowu, London Metropolitan University, Calcutta House, London, UK René Schmidpeter, Cologne Business School, Cologne, Germany
In recent years the discussion concerning the relation between business and society has made immense strides. This has in turn led to a broad academic and practical discussion on innovative management concepts, such as Corporate Social Responsibility, Corporate Governance and Sustainability Management. This series offers a comprehensive overview of the latest theoretical and empirical research and provides sound concepts for sustainable business strategies. In order to do so, it combines the insights of leading researchers and thinkers in the fields of management theory and the social sciences – and from all over the world, thus contributing to the interdisciplinary and intercultural discussion on the role of business in society. The underlying intention of this series is to help solve the world’s most challenging problems by developing new management concepts that create value for business and society alike. In order to support those managers, researchers and students who are pursuing sustainable business approaches for our common future, the series offers them access to cutting-edge management approaches. CSR, Sustainability, Ethics & Governance is accepted by the Norwegian Register for Scientific Journals, Series and Publishers, maintained and operated by the Norwegian Social Science Data Services (NSD)
Adele Parmentola • Ilaria Tutore
Industry 4.0 Technologies for Environmental Sustainability Intended and Unintended Consequences
Adele Parmentola DISAQ Parthenope University of Naples Napoli, Italy
Ilaria Tutore DISAQ Parthenope University of Naples Napoli, Italy
ISSN 2196-7075 ISSN 2196-7083 (electronic) CSR, Sustainability, Ethics & Governance ISBN 978-3-031-40009-4 ISBN 978-3-031-40010-0 (eBook) https://doi.org/10.1007/978-3-031-40010-0 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland Paper in this product is recyclable.
Introduction
The industry 4.0 technologies are supposed to positively affect the global economy since they promote autonomous interoperability, agility, flexibility, decisionmaking, efficiency or cost reductions, which should also be resource-efficient. Thus, it is not surprising that the new industrial paradigm has been considered a significant step towards more sustainable industrial value creation. However, the new paradigm implies several uncertainties since it involves new and emerging technologies with potential harmful social and environmental impacts that should be considered. The aim of this book is to provide deeper understanding on how Industry 4.0 technologies can help or harm company’s environmental sustainability. To analyse the interaction between these two phenomena, the book employs the perspective of companies that could adopt digital technologies. The value-added of this book stems also from the adoption of a managerial perspective whereas previous studies adopt engineering or computer science lens to analyse digital technologies or ecological economics point of view to evaluate environmental sustainability. Moreover, while other managerial studies focused on social sustainability effects of Industry 4.0 technologies, this manuscript is concentrated on environmental sustainability, evaluating not only the benefits of new technologies adoption but also their potential negative effects. The capability to shed the lights on the two sides of the same coin represents another novelty of this book that offers a valuable synopsis of industry 4.0 technologies effects on environmental sustainability, classified using the environmentalrelated SDGs. The framework derived could represent a practical tool for entrepreneurs, managers and consultants to make a rational choice about the adoption of specific technology that can contemporarily help (or hinder) business to reach sustainability targets. The book is structured in 4 chapters. The first chapter, titled “Environmental Sustainability and Firms’ Competitive Advantage”, analyses the theoretical foundation of environmental sustainability in management studies. In particular, it introduces the discussion on how v
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environmental sustainability can affect firms’ competitive advantage and how companies can adopt green behaviour. A particular emphasis is devoted to the role of technology innovations to drive companies towards environmental sustainability. The second chapter (Fourth Industrial Revolution and Firms’ Digitalization) analyses the foundation of Industry 4.0 paradigm, by focusing the attention on different enabling technologies and on their effects on both companies’ competitiveness and sustainability. The third chapter (I4.0 Technologies Adoption and the Environmental Sustainability) develops a systematic literature review of the studies that simultaneously consider the themes of Industry 4.0 and their effects on environmental sustainability. It emerges that academia is reserving more importance to the topic during the last years: from the descriptive statistics of selected papers, it appears that the number and quality of both theoretical and empirical papers that deal with the topic is increasing. From co-occurrence analysis of recent trend, it has been possible to identify four different themes that link the selected studies. Research included in the first cluster are focused above all on the link between Industry 4.0 technologies and environmental sustainability for macro-economic perspective. Papers that fall into the second Cluster, the “Meso-level”, rather focus the attention on the link between environmental sustainability and fourth industrial revolution from ecosystem point of view. Research comprising the third cluster focuses the analysis on the effect of industry 4.0 technologies on environmental sustainability at supply chain level. Papers that belong to the last cluster rather adopt a micro-economic focus, by analysing specific techniques or models used to implement these technologies with ecological purposes. Lastly, in the fourth chapter, titled “Unveiling the Positive and Negative Effects of Blockchain Technologies on Environmental Sustainability”, we focus the attention on specific Industry 4.0 technology, namely the Blockchain, that is often considered as one of the most remarkable innovations in the twenty-first century. Blockchain is defined as novel and fast-evolving approach to recording and sharing data across multiple data stores (or ledgers). This technology allows for transactions and data to be recorded, shared and synchronized across a distributed network of different network participants. Blockchain is now applied in a variety of fields and many companies have used this technology also to enhance environmental sustainability. Despite the potential advantages, blockchain has also the potentiality to create green challenges and for these reasons companies need to be aware about its implementation. For this reason, starting from the analysis of empirical cases of blockchain adoption, we provide a conceptual framework that identifies the opportunities and challenges of the technology to the achievement of environmental-related SDGs.
Contents
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Environmental Sustainability and Firms’ Competitive Advantage . . . 1.1 “All Roads Lead to Rome”: Environmental Sustainability, Sustainable Development Goals, Circular Economy . . . . . . . . . . . . . . . . . . . . . 1.2 The Rise of the Organizations and the Natural Environment . . . . . . 1.3 Environmental Sustainability and Firms’ Competitive Advantage . . . 1.4 Drivers of Corporate Environmental Sustainability . . . . . . . . . . . . . 1.5 The Role of Innovation in Firms’ Environmental Proactivity . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Fourth Industrial Revolution and Firms’ Digitalization . . . . . . . . . . . 2.1 The Fourth Industrial Revolution . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 The Industry 4.0’s Enabling Technologies . . . . . . . . . . . . . . . . . . . 2.2.1 Big Data and Analytics . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.2 Autonomous Robot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.3 Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.4 Horizontal and Vertical System Integration . . . . . . . . . . . . . 2.2.5 Internet of Things . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.6 Cybersecurity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.7 Cloud Computing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.8 Additive Manufacturing . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.9 Augmented Reality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Fourth Industrial Revolution and Companies’ Competitive Advantage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.1 Possible Benefits of I4.0 Technologies . . . . . . . . . . . . . . . . 2.4 I4.0 Technologies as Instruments to Enhance Companies’ Sustainability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.1 I4.0 and Economic Sustainability . . . . . . . . . . . . . . . . . . . . 2.4.2 I4.0 and Social Sustainability . . . . . . . . . . . . . . . . . . . . . . . 2.4.3 I4.0 and Environmental Sustainability . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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I4.0 Technologies Adoption and the Environmental Sustainability . . . 3.1 A Methodological Approach to Analyze the Rise and Growth of Theoretical Discussions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Descriptive Results of the Bibliographic Research . . . . . . . . . . . . . . 3.3 Co-occurrence Analysis of Recent Trend . . . . . . . . . . . . . . . . . . . . 3.4 Be Digital or Be Green: An Integrative Framework . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Unveiling the Positive and Negative Effects of Blockchain Technologies on Environmental Sustainability in Practice . . . . . . . . . . . . . . . . . . . . 4.1 Blockchain as a Disruptive Technology . . . . . . . . . . . . . . . . . . . . . 4.1.1 Advantages and Disadvantages Associated with the Use of Blockchain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Blockchain for Environmental Sustainability . . . . . . . . . . . . . . . . . 4.3 The Positive and Negative Effect of BC on Environmental Related SDGs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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Chapter 1
Environmental Sustainability and Firms’ Competitive Advantage
1.1
“All Roads Lead to Rome”: Environmental Sustainability, Sustainable Development Goals, Circular Economy
Economy and the natural environment have been always considered two contradictory concepts, based on the mistaken idea that it is not possible to hypothesize economic growth without eroding the availability of natural resources. Moreover, previous academics analyzed two subjects independently by respective disciplines, namely biology or environmental studies and economics or management, often under-evaluating their strong interdependences. Indeed, the devastation of natural resources or their deterioration caused by pollution causes an increase in raw materials’ prices, strongly affects the firm’s capability to create profit, and—at macro-economic level—provides negative externalities in national economies. According to this consideration, environmental problems also become a social problem, its protection being a penalty to be paid by the whole community. For this reason, regulators at different levels had always played a pivotal role in determining the policy to reduce the environmental impact of human activities, traditionally interested in exploiting natural environmental as much as possible. The Brundtland Report that in 1987 provided the most widely cited definition of sustainable development: Sustainable Development “. . .sustainable development is development that meets the needs of the present without compromising the ability of future generations to meet their own needs.”
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Parmentola, I. Tutore, Industry 4.0 Technologies for Environmental Sustainability, CSR, Sustainability, Ethics & Governance, https://doi.org/10.1007/978-3-031-40010-0_1
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(WCED, 1987) has increased the awareness of the importance of the interlinkages between the economy and its dependence on natural resource systems as well as a sense of stewardship for the future and the environment. Recently, the public opinion pushed by the “Fridays for Future” movement has also increased its attention to the protection of natural environment. The United Nations still reinforces a sustainable future defining the “2030 Agenda for Sustainable Development” including its 17 Sustainable Development Goals (SDGs) and 169 targets. The adoption of the 2030 Agenda was a landmark achievement, providing for a shared global vision toward sustainable development for all. Among the 17 targets eight of them focus on environmental sustainability (see Table 1.1), while the other 3 can indirectly affect goals associated with natural environment (Table 1.2). Already in 1994 John Elkington translated this message in a language that resonated with business brains in order to make real environmental progress, by coining the concept of triple bottom line (Elkington 2013) (Fig. 1.1). According to the author, the TBL agenda helps corporations focus not just on the economic value that they add but also on the environmental and social value that they add—or destroy. In other words, a company should consider people, planet, and profit simultaneously. The social pillar (people) refers to values that promote equality and respect for individual rights. The principles upon which this pillar is founded are the fight to social exclusion and discrimination, the promotion of solidarity, and the contribution of the well-being of stakeholders. The economic pillar (profit) is rather based on companies’ ability to contribute to economic development and growth. Finally, the environmental pillar is founded on a commitment to protect the environment by reducing risks and measuring the environmental impacts of companies’ activities by facing several challenges, such as saving and preserving natural energy or agricultural resources, assessing carbon footprint, or preventing water scarcity.▪ Only if a company cares for all three aspects of the triple bottom line can it be called sustainable, because all of them are extremely closely related. Caring for profit and for people makes it equitable and fair, but omitting environmental protection leads the planet to its doom. On the other hand, tending only to the planet and people, and forgetting about the profit, makes CSR policy bearable, but business needs profits to survive. Again, if a company pays attention to the profit and planet, discarding the people, Cane (2013) believes that it is viable and profitable, but in the long term can lead to the fall of employees’ morale and the breach of social contract. These goals are an integral part of corporate social and environmental responsibility (CSER). Consistent with this wave of eco-sustainability, a new model of economy is spreading at theoretical and practical level. This new theoretical framework is in contrast to the general linear economic models, which in the past has helped global industrialization. However, the
1.1 “All Roads Lead to Rome”: Environmental Sustainability,. . .
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Table 1.1 SDGs with direct link with environmental sustainability
Ensure availability and sustainable management of water and sanitation for all Ensure access to affordable, reliable, sustainable, and modern energy
Make cities and human settlements inclusive, safe, resilient, and sustainable
Ensure sustainable consumption and production patterns
Take urgent action to combat climate change and its impacts
Conserve and sustainably use the oceans, seas, and marine resources for sustainable development
Protect, restore, and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss
traditional linear economy model has often been viewed as the main driver of environmental degradation since it implies the unsustainable use of resources. This traditional model postulates a take-make-dispose path of products, generally split into 5 different steps:
1. Raw material extraction 2. Operations and transformation of raw material in product
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Table 1.2 SDGs with indirect link with environmental sustainability
Promote sustained, inclusive, and sustainable economic growth, full and productive employment, and decent work for all Build resilient infrastructure, promote inclusive and sustainable industrialization, and foster innovation
Strengthen the means of implementation and revitalize the global partnership for sustainable development
Fig. 1.1 Triple bottom line (Reproduced from Elkington 2013)
PEOPLE
PLANET
PROFIT
3. Product’s distribution 4. Product’s consumption 5. Product’s disposal According to this logic, the economic model would require a great availability of natural resources, which conversely are scarce in nature. Circular economy then starts to become a dominant logic for environmental sustainability studies, since it is based on a production and consumption model that requires the reuse, repair, and regeneration of used products, products’ sharing, and second life after use. Compared with the traditional model, it is based on the 3R approach “reuse, reduce, recycle” extending the product life cycle, contemporarily reducing the resources and energy consumption.
1.1 “All Roads Lead to Rome”: Environmental Sustainability,. . .
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In other words, the new paradigm of circular economy that supposes a new production and consumption model that ensures sustainable growth over time is becoming relevant in opposition to traditional linear economy. In few words, according to the Ellen MacArthur Foundation that firstly theorized it, the paradigm aims to keep products, components, and materials at their highest utility and value at all times in both biological and technical cycles. The Ellen MacArthur Foundation and McKinsey (2015) focus on restoring the value of used resource in contraposition to traditional linear economy, which uses a take-makedispose model, considered resource intensive with adverse environmental impacts. The CE focuses on maximizing the circularity of resources and energy within production systems, since natural resources are scarce, and that waste at the end of its life may retain some value (Ghisellini et al. 2016). With the circular economy, e.g., we can drive the optimization of resources, reduce the consumption of raw materials, and recover waste by recycling or giving it a second life as a new product. The creation of a framework capable of grouping the concepts belonging to the circular economy passes in most cases through the definition of categories through which it is possible to order the different strategies that aim at maintaining the resources in their life cycle if possible. The first framework to classify different CE strategy is the ReSOLVE (Fig. 1.2). The framework, developed by the Ellen Mac Arthur Foundation jointly with McKinsey & Company, takes the core principles of circularity and applies them to six actions: regenerate, share, optimize, loop, virtualize, and exchange (Ellen Mac Arthur Foundation & McKinsey 2015). The regenerate consists of several actions that maintain and enhance the Earth’s bio capacity, such as land recovery and the ecosystem’s protection. Share activities rely on the full exploitation of the use of goods. According to this strategy, the product’s ownership is not necessarily related to its value. The third action, optimize, asks for a more efficient use of resources. Loop activity rather keeps components and materials in closed loops, in order to reduce or even avoid the waste or ask for its recycling for internal or external reuse. The set of activity that reduces the use of physical asset to exploit dematerialization is virtualize. Finally, exchange actions rely on the development and adoption of new technologies that improve the way society produces goods and services. Many authors and practitioners employed various R frameworks as the “how-to” of CE and thus a core principle of it. From the 3R framework (reduce, reuse, and recycle) often used for coding in academia, the latest popular model to analyze circular economy actions is the 9Rs framework developed by Potting et al. (2017). This 9Rs stands for refuse, rethink, reduce, reuse, repair, refurbish, remanufacture, repurpose, recycle, and recover, ordered by priority according to their levels of circularity (Fig. 1.3). All these theories, concepts, and principles that are recurring in the last few years underline the same issue: environmental sustainability has turned to be one of the most important topics in politic agendas, stakeholder interests, and firm’s strategies.
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Fig. 1.2 ReSOLVE framework (Reproduced from Ellen Mac Arthur Foundation & McKinsey 2015)
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Fig. 1.3 9Rs strategy framework (Reproduced from Potting et al. 2017)
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The reason for this increasing interest is the rise of the awareness that the quality and future of human existence are directly related to the condition of our natural environment. In this field, companies, especially large multinationals, have a unique role to play (UN 2015) to reach sustainability target. It calls for new paradigms and theoretical lens through which to read the complex and problematic links that exist between business management and the natural environment.
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The Rise of the Organizations and the Natural Environment
From a managerial point of view, natural environment is the mother and keeper of raw material needed to start every business activity. Every firm—as a social player—operates in their macro-environment and, therefore, is affected by relative rules that are integrated in business practices. The degeneration of resources—in quantitative and qualitative terms—would mean for companies a rise of raw material costs, because of shortage or the costs of complying with environmental regulations. Following these considerations, the natural environment would represent a limit—because of the extra costs derived—of the company’s free choices—and its protection becomes an issue for managers just when required by law. According to Schumacher (1973), the misunderstanding of considering business activity and natural environment protection as a trade-off starts from the differences between the asset and revenue. In other words, business management practices have always considered the natural environment as a revenue rather than—based on its features—an asset. The consideration of natural resources as a capital would mean to be interested not just on its use but also on its conservation. Moreover, as an asset, the profit derived should be saved in a specific reserve to invest in new environmental innovations. Academics from economics and management disciplines did not consider the issues until it was evident that its wrong management would make economic growth worse. Moreover, during the last few years, environmental sustainability has turned to be one of the most important topics in politic agendas and stakeholder interests, calling for a new approach to manage the complex relationship between business activities and the natural environment. In the last few years, companies are changing their attitude toward the natural environment starting from the idea that the adoption of environmental management strategies creates opportunities for business organizations. In other words, there is an increasing understanding that environmental sustainability can act as a driver for firms’ competitiveness. With an innovative mindset it is
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The Rise of the Organizations and the Natural Environment
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possible to keep and create positive outcomes by the efficient and conscious use of the natural environment. This idea is the basis of a new theoretical paradigm in change management practices and studies since the 1990s. The new field of study, called “organizations and natural environment,” analyzes the antecedents of environmental sustainability and demonstrates its effect in economic, financial, and ecological terms. Porter and Van der Linde (1995) theorized the concept of “innovation offset,” which postulates that stringent environmental regulation drives companies to find innovative ways to manage the trade-off between resource’s depletion and business activities, by contemporarily increasing competitiveness. In the same year, stemming from Penrose’s (1959) discussion of the antecedents of firm growth, Hart (1995) recognized the role of resources and capabilities in driving companies through the environmental sustainability journey, highlighting the links among environmental strategies, capability development, and competitive advantage (Aragón-Correa 1998; Aragón-Correa and Sharma 2003; Sharma and Vredenburg 1998). Other authors rather tried to classify the different steps of the “consciousness path” toward environmental sustainability. Some models identify specific stages with incremental attitude toward environmental sustainability, using a different label. These steps stem from a passive behavior used by companies that simply introduce the necessary transformations in order to comply with regulatory requirements, and a proactive behavior, typical of firms that voluntarily decide to introduce new procedures and actions to reduce their impact on the natural environment (Gonzales-Benito and Gonzales-Benito 2006). At the end of this ideal path, there are the proactive environmental strategies (PES) defined as the reduction of a firm’s environmental impact and managing the interface between business and nature beyond imposed compliance (Aragon-Correa and Sharma 2003; Gonzales-Benito and Gonzales-Benito 2006). Environmental proactivity should not be depicted as a single strategy, but constitutes a range of behavioral actions, such as planning and organizational practices that relate to the EMS, operational practices that imply changes in the production and operations systems, and communication practices. According to Delmas et al. (2011), the PES is characterized by the presence of four basic elements: (a) regulatory proactivity, (b) operational improvements, (c) organizational changes, and (d) environmental reporting (Delmas et al. 2011). The proactive firm is the one that would like to promote its involvement using both internal and external audits or the release of a sustainability report. Moreover, this kind of organization gives importance to the design and production of items that reduce or prevent environmental damage. This proactivity also requires organizational changes since new practices and responsibilities should be defined. Finally, driven by its proactiveness, this firm can influence other stakeholders’ behaviors, even participating in the development of future regulations (Delmas and MontesSancho 2010). A clear link between environmental proactivity and financial or economic performance has not been established yet, but there is a great perception that the
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introduction of environmental protection may be used to develop successful strategies aimed at gaining competitive advantage.
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Environmental Sustainability and Firms’ Competitive Advantage
The academic debate on the relationship between environmental sustainability and firms’ competitiveness is based on two diverse perspectives. According to the traditional perspective, the consciousness management of environmental issue would require enormous investments and complex transformation. These investments could reduce inflows and eventually hinder economic growth (Whitehead and Walley 1994; Cordeiro and Sarkis 2008). It is considered a cost burden to the firm with adverse economic outcomes. However, these researches are often subject to critics for being anecdotal and lacking in rigor and theoretical basis (Ambec and Lanoie 2008; Surroca et al. 2010). On the contrary, the second perspective is based on the idea that the implementation of environmental practices at firms’ level benefits shareholders directly (McWilliams and Siegel 2001) and can enhance competitiveness in several ways. These include cost reduction and optimization achieved by pollution prevention, differentiation strategy achieved through the development of greener products, and innovation taking advantage of the market opportunities created by an increasing demand for environmentally friendly goods and services (Berrone and Gomez-Mejia 2009; López-Gamero and Molina-Azorín 2016; Reinhardt 1999). In addition, environmental proactivity improves stakeholder relations, helping firms manage risks, including those to their reputations (Cordeiro and Tewari 2015), or creating non-market strategies to influence government regulation so that their rivals are at a disadvantage (Shrivastava 1995). Thus, we can posit that the environmental competitive advantage can be categorized into cost and differentiation advantage (López-Gamero and Molina-Azorín 2016). The first typology is linked to the internally driven tangible results that provide cost saving opportunities (Pereira-Moliner et al. 2015) such as reduced materials requirement, efficient production process, reduced liability, and compliance cost. The second strategical alternative is related to intangible and externally driven advantage via seeking social legitimacy and reputational advantage in the society (Melo and Garrido-Morgado 2012; Walsh and Dodds 2017) able to potentially enhance firms’ ability to create value (Miles and Covin 2000). In this regard, Renato Orsato (2006) developed a conceptual framework in order to classify the different archetypes of environmental competitive strategy (Fig. 1.4). The framework helps decouple the elements involved in competitive environmental management, and it is fundamental for identifying in which conditions environmental strategies may improve firm’s competitiveness.
Lower costs
Competitive Advantage
Environmental Sustainability and Firms’ Competitive Advantage
Differentiation
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Strategy I
Strategy IV
Eco-efficiency
Environmental Cost Leader-
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Strategy III
Beyond Compliance Leader-
Eco-branding
ship Organizational Processes
Products and Services
Competitive Focus
Fig. 1.4 Competitive environmental strategy (Reproduced from Orsato 2006)
The two factors that help to define the different quadrants and then the different typologies of environmental management strategy that companies may adopt are the competitive focus and the competitive advantage. These variables depend on several factors, such as the structure of the industry and its position, the specific typology of markets the firm serves. With regard to the competitive focus in which the company operates (organizational processes or products/services), it is worth noting that the demarcation between the two alternatives is imaginable because the strategies can work independently. The main risk of this tricky distinction causes the pursuit of more than one environmental strategy simultaneously. In this case, if the deliberated strategies are not aligned, at first with the overall corporate strategy, it will represent a worthless waste of time and resources. It is also important to underline that the boundaries among the four strategies are not rigid since the archetypes are stylized to make it easier to identify where the competitive focus of environmental strategies might be hidden. In the quadrant I falls the companies that implement “eco-efficiency strategy,” lowering costs at organization process level. This strategy is related to firms’ capabilities to save costs especially in supply industrial market, which generally must sustain higher processing costs and provides higher number of wastes. In this case, if customers are not interested in paying a premium price for environmental sustainability, the focus on internal eco-efficiency makes sense. Environmental protection is considered a way to reduce costs of process-intensive companies. The second quadrant describes the strategy of companies that are still focused on organizational processes but have a focus on differentiation advantage, because it works in some industry where customers recognize the importance of environmental sustainability efforts. The company that adopts the “beyond compliance leadership strategy” invests in environmental management systems or in environmental voluntary disclosure because the main intention is to communicate and publicize these
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environmental efforts. This beyond compliance posture is driven by the possibility of improving firm’s brand image and eventually affecting customers’ behavior. The last two strategies are connected to companies that have a product-based competitive focus. The “eco-branding strategy” is adopted by firms that base marketing differentiation on the environmental features of its products/services. According to Orsato (2006), this strategy is selective since the company that wants to embrace it should consider these three basic requisites: customers have to show the willingness to pay for eco-based differentiation; the information of the environmental outcomes derived from ecological efforts should be disclosed to the customers; and—not less important—this advantage should be hard to imitate by competitors. The last environmental strategy archetype, namely the “environmental cost leadership strategy” shown in Quadrant IV, is maybe the most difficult to replicate. Indeed, if the creation of eco-brand and adding environmental protection features to products and services mean an increase in cost, the creation of customer willingness to pay the environmental premium price can pay off. This is especially true in a specific industry where competition is generally based on creating differentiated offers. What would be the strategy for companies that would like to implement some differentiation based on environmental efforts but operate in an industry where competition is based on prices? In firms that operate in this kind of context, it is worth focusing on radical product innovation and then process innovation. For example, by substituting material or dematerialization, it is possible to improve efficiency and enhance environmental performance. The strategic alternatives developed in Orsato framework (2006) present some subtle trade-off. According to a deep understanding the difference between “ecoefficiency strategy” and “environmental cost leadership strategy” does not make any sense. In reality, firms that achieve environmental cost leadership is also the one that adopts an environmentally sustainable organizational process. It could be useful to interpret the different firms’ posture toward environmental problems by considering the different level of environmental efforts with regard to cost saving or differentiation advantage orientation. In this regard, it can be useful to analyze firms’ posture toward environmental sustainability by using the theoretical framework developed by Calza et al. (2012) for power companies (Fig. 1.5). This model postulates the possibility that companies that are not looking for cost or differentiation advantages are currently acting without any strategic involvement toward environmental proactivity. There are also companies that implement environmental efforts just to optimize resources use and disposal. These companies implement environmental strategy without caring about disclosing their green involvement. These companies are the “efficient seekers” (Quadrant II). With the increasing level of environmentally sensitive customers, willingness to pay for more eco-friendly products or services, and generally the pressures exert by stakeholder toward more sustainable worlds, many firms start to insert some green features into their outputs. In this case, the company risks behaving like a greenwashing player, making an unsubstantiated
Drivers of Corporate Environmental Sustainability
13
Quadrant II
Quadrant IV
Efficient seeking
Effective Environmental Strategy
-
Cost advantage
+
1.4
Quadrant I
Quadrant III
No Environmental Strategy
Greenwashing
-
+ Differentiation Advantage
Fig. 1.5 Environmental strategy’s efforts (Reproduced from Calza et al. 2012)
claim to deceive consumers into believing that a company’s products are environmentally friendly. On the contrary, the company that adopts an effective proactive environmental strategy is the one that contemporarily envisages the opportunities in terms of resource optimization and uses this environmentalism to drive its differentiation advantages.
1.4
Drivers of Corporate Environmental Sustainability
Considering the relevant role of environmental strategy in enhancing the firm’s position in the market and developing the resources and capabilities in order to build a long-term profit potential (Bansal and Roth 2000), several scholars have tried to identify the drivers that push companies toward a proactive environmental management and analyze the pressure exerted by these forces. A stream of research in the organizations and natural environment field becomes really relevant because the identification of these drivers can add policy implications to evaluate the effectiveness of planned actions. Several and varied factors can push firms’ strategy toward ecological engagement: the different pressure exerted by these drivers affects firms’ capability to identify business opportunities related to them, affects the managerial attitude toward the problems, and—consequently—affects the outcomes of implemented environmental strategy. Moreover, the acknowledgment of these factors can help practitioners to understand and forecast competitors’ environmental strategy (Calza et al. 2016). Essentially, drivers of environmental proactivity can be classified as external and organizational or internal factors (Claver-Cortés et al. 2007; González-Benito and González-Benito 2006).
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Environmental Sustainability and Firms’ Competitive Advantage
The pressure exerted by governments represents the most obvious (Paulraj 2009) factor that strongly affects companies to implement environmentally friendly practices. Taxation, legal costs, and penalties represented the coercive forces toward environmental proactivity: the strongest incentive is to comply with legislation (Bansal and Roth 2000). Thus, most of the studies in this field analyzed the effectiveness of the right environmental policies to determine firms’ shift toward sustainability. This driver pushes on the traditional idea that environmental care should be considered just a cost for companies that have to divert money to comply with stringent regulation (Ambec et al. 2011). Thanks to the work of Porter and Van Der Linde (1995), this implicit relationship has been reversed. According to the authors, environmental regulation can drive the “innovation offset” able to trigger innovation and help to increase a firm’s competitiveness which may partially or completely offset the costs of complying with those environmental regulations (Porter and Van Der Linde 1995). This argument, well known as the Porter hypothesis, suggests that under the constraints of regulation, in order to digest the internal environmental costs, enterprises must actively force a company to create better-performing or higherquality products and processes. A second external force in the greening of industries comes from general stakeholder pressure (Buysse and Verbake 2003; Gonzales-Benito and Gonzales-Benito 2006; Madsen and Ulhøi 2001). Henriques and Sadorsky (1999) and Madsen and Ulhøi (2001) have analyzed the different pressures applied by several interest groups, such as government, suppliers, local communities, employees, and environmental organizations, on firms’ strategy and environmental responsiveness. With regard to internal or organizational drivers of the firm’s environmental proactivity, we can list a set of company’s structural features, together with organizational resources and capabilities such as managerial attitude and motivation or leadership capability. The size of the firms graded according to the number of employees or revenue is able to affect its capability to invest in environmental related activities: the bigger is the company the more resources it has and the more pressure it receives from stakeholders and care for reputation. The industry to which the company belongs, as well as the specific position in the value chain, can also differently affect the adoption of proactive environmental strategies. In the same way, at governance level, some studies focused on the corporate ownership or board composition as important factors that drive toward sustainability. Stemming from the resource-based view of the firm, the natural resource-based view developed by Hart (1995) opened the door to the role of internal resources’ availability in driving environmental proactivity. Surroca et al. (2010) pointed out the role of intangible resources in general, Christmann (2000) focused on the role of
1.5
The Role of Innovation in Firms’ Environmental Proactivity
15
complementary assets, Delmas et al. (2011) on the role of absorptive capabilities, or Claver-Cortés et al. (2007) on the role of intellectual capital. The scholars that adopted this point of view have emphasized that an environmental strategy requires the implementation of resources, capabilities, or skills, which often are different or new for the firm since they are far from the firm’s core business (Steinmo and Jakobsen 2013). Therefore, a relevant body of new research is devoted to analyzing how companies collect and acquire the necessary resources. Firms that adopt a proactive environmental strategy often rely on external sources to acquire the necessary resources. Company then uses interorganizational collaborations or partnership to obtain preferential access to the resources they do not possess and to forge new capabilities and achieve performance improvements (Gulati 2007). For instance, Wassmer et al. (2014) classified four interorganizational collaboration types to make firms obtain external resources and capabilities. These collaborations, which differ in terms of the use, primary purposes, and type of benefit sought, can be interfirm, firm–NGO collaborations, firm–government collaborations, and firm–university collaborations. In synthesis, the gap in resources and capabilities represents the main factor that drives environmental collaboration, and this partnership seems even more important for the development of green innovation, in some cases necessary to implement an effective environmental strategy.
1.5
The Role of Innovation in Firms’ Environmental Proactivity
Considering the increasing pressure, companies are finding several methods and practices to deal with environmental issues. It represents an important challenge especially for those operating in non-green industries and want to achieve environmental improvements considering their competitiveness. The contribution exerted by innovation on environmental sustainability has been extensively researched in the literature since innovation, conceptualized by the addition of products, processes, and managerial activities involved in product or service provision, could positively affect firms’ capabilities to reach environmental target. There are different notions/terms used in the literature to describe innovations that have a reduced negative impact on the environment: “green,” “eco,” “environmental,” and “sustainable” innovations (Díaz-García et al. 2015), generally, are used indistinctly because they are related to the same topic. Nowadays, the term “green innovation” is generally used more than the others. During the years, several authors tried to provide a clear definition of what green innovation is.
16
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Environmental Sustainability and Firms’ Competitive Advantage
Already in 1996 referring to eco-innovation, Fussler and James defined it as “new products and processes which provide customer and business value but significantly decrease environmental impacts.” In a similar manner, Kemp and Pearson (2007) defined eco-innovation as “the production, assimilation or exploitation of a product, production process, service or management or business method that is novel to the organization and which results, throughout its life cycle, in a reduction of environmental risk, pollution and other negative impacts of resources use (including energy use) compared to relevant alternatives.” Chen (2008, p. 534) define green innovation “as hardware or software innovation that is related to green products or processes, including the innovation in technologies that are involved in energy-saving, pollution-prevention, waste recycling, green product designs, or corporate environmental management.” Besides the need to provide a definition, literature on the topic also focused on their specific peculiarities, in order to understand whether green innovations differ from the other kinds of innovations and therefore the need to analyze specific theoretical and political interpretation, as well as their drivers and barriers. There are at least two differences from generic innovation. The first is related to the specific externalities they are able to procure and the second relies on the drivers which are the basis of their development. Regarding the first point, Rennings (2000) suggests that environmental innovations produce “double externality problems.” The first is the knowledge spillovers generated that benefit other firms, reducing the incentive for firms to invest in them, as they cannot fully appropriate the value created. Secondly, green innovation results in positive environmental externalities: the value created by cleaner technologies can be appropriated by the entire society (De Marchi 2012). However, firms that invest in such technologies should sustain additional costs that reduce the benefits to invest in such activities (Rennings 2000). The second feature of environmental innovation is related to the specific motivation that drives its development. While general innovation envisages demand-pull and technology push factors, the driver of green innovations is generally considered the policy interventions. It is consistent with the so-called Porter’s hypothesis, according to which environmental regulation is able to trigger innovation that “may partially or more than fully offset the costs of complying with them” (Porter and Van der Linde 1995, p. 98), which enhance company’s competitiveness. This evidence is less strong today, where entrepreneurial and intrapreneurial initiatives and customers’ expectations—besides the effects of other secondary stakeholders—push companies toward a more environmental sustainable approach to activities that require the introduction of specific innovation (technological or not). The point in which the literature agrees is the complexity of green innovation, which includes a vast diversity of capabilities, in some cases far from company’s core competences.
1.5
The Role of Innovation in Firms’ Environmental Proactivity
17
These innovations can be also classified into different dimensions; product, process, organization, and marketing innovations can contribute to enhance environmental sustainability transition (García-Granero et al. 2017). Considering that green innovations are not all the same for every company, different kinds of resources and competences and, consequently, different implementation modes should be considered. Kemp and Pearson (2007), for instance, identify four different eco-innovations, according to the specific nature of the innovation, namely, the “environmental technologies” as pollution control technologies, e.g., wastewater treatment technologies, cleaner process technologies, or green energy technologies; “organizational innovation for the environment” as the introduction of organizational methods and management systems for dealing with environmental issues in production and products; “product and service innovation offering environmental benefits” which are new or environmentally improved products and environmentally beneficial services; and “green system innovations” which are alternative systems of production and consumption that are more environmentally benign than existing systems. According to the EU Community Innovation Survey (CIS), green innovation can be classified according to the environmental benefits derived from the production of goods or services: reduced material use per unit of output; reduced energy use per unit of output; reduced CO2 footprint (total CO2 production); replaced materials with less polluting or hazardous substitutes; reduced soil, water, noise, or air pollution; and recycled waste, water, or materials or according to the benefits derived from the after-sales use of a good or service; reduced energy use; reduced air, water, soil, or noise pollution; and improved recycling of product after use. Using an internal point of view, namely focusing on firms’ attitude toward environmental problem, Chen et al. (2012) distinguished between “proactive green innovation” as new practices or products ahead of competitors, to decrease cost, to seize opportunities, to lead in the market, or to obtain competitive advantages, usually pushed by environmental culture green leadership, environmental capability, and “reactive green innovation” related to firms’ passive attitude toward the issue, to react to the changing environment, or to respond to competitors’ challenges—and then pushed by regulations. Using “The Innovation Landscape Map” elaborated by Pisano (2015) for generic innovations, Calza et al. (2017) classified green innovations into four different typologies, according to their impact on company’s competences and how green innovations can be implemented. In particular, authors recognized as routine green innovation the ones that leverage on existing technical competences and business model. This type of innovation is generally developed by internal R&D and is close to company’s core business. When companies develop disruptive or radical green innovation, they respectively invest in new business model or technical competences. In these cases, companies resort to collaboration to enhance market development or acquire complementary technical/technological competences. Finally, the most complex typology of green innovation is the architectural, where the company explores new
18
1 Environmental Sustainability and Firms’ Competitive Advantage
competences and business model and usually needs to cooperate either to improve technological competences or to enhance market development. This classification confirms the complexity of green innovation and the idea that companies have to leverage on the competences of external partners since they require information and skills that are new, going beyond firms’ core competences (Steinmo and Jakobsen 2013). Empirical studies conducted in Spain and Germany revealed that cooperation with external partners is even more important for environmental innovations than for other types of innovations (De Marchi 2012; Horbach 2008). In this sense, Ghisetti et al. (2015) used the open innovation approach to demonstrate that heterogeneous sources of green knowledge inputs help in green innovation development, especially for SMEs. The authors demonstrated that the set of sources and the numbers of providers positively affect the green innovation performance, defining a new concept, namely the open eco-innovation mode (OEIM). Despite the relevance of this contribution, authors did not focus their attention on the mode through which open innovation is conceived and realized. More recently, Calza et al. (2020) demonstrated that the positive effect on environmental performance through cooperation depends on the specific type of cooperation (with joint venture, higher environmental performances are achieved) especially when the basis of collaboration is the shared environmental goals. These results are more evident for SMEs. Therefore, innovating for the natural environment is a great challenge for companies because of different managerial perceptions and interpretation (Pinkse and Kolk 2010), also because, among the alternatives to reduce the environmental burden, innovation and technologies are widely considered as the most attractive. Technology management can contribute to this transition, but it can become successful when companies bring these innovations to serve global mainstream markets instead of local niche. Moreover, it appears necessary that companies move away from existing comfort zone, by investing in new and sometimes unrelated capabilities, increasing the need to complementary assets development, and making innovating for climate change a key challenge. In this context, the rise of new technological revolution could also create an opportunity for companies to improve their environmental strategy. However, since digital technologies have become pervasive, sustainability scholars also need to understand the full set of direct or indirect consequences for sustainable development. Every company should be aware of these challenges and be cautious in taking decisive steps in facilitating what has been indicated as the market transition needed to address climate change (Pinkse and Kolk 2010).
References
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Delmas, M. A., & Montes-Sancho, M. J. (2010). Voluntary agreements to improve environmental quality: Symbolic and substantive cooperation. Strategic Management Journal, 31(6), 575–601. Díaz-García, C., González-Moreno, A., & Sáez-Martínez, F. J. (2015). Eco-innovation: Insights from a literature review. Innovations, 17(1), 6–3. https://doi.org/10.1080/14479338.2015. 1011060 Elkington, J. (2013). Enter the triple bottom line (1st ed., pp. 1–16). Routledge. Ellen Mac Arthur Foundation. (2015). Towards a circular economy: Business rationale for an accelerated transition. https://ellenmacarthurfoundation.org/. Accessed November 2015. García-Granero, A., Fernández-Mesa, A., Jansen, J. J. P., & Vega-Jurado, J. (2017). Top management team diversity and ambidexterity: The contingent role of shared responsibility and CEO cognitive trust. Long Range Planning, 51(6), 881–893. Ghisellini, P., Cialani, C., & Ulgiati, S. (2016). A review on circular economy: The expected transition to a balanced interplay of environmental and economic systems. Journal of Cleaner Production, 114, 11–32. https://doi.org/10.1016/j.jclepro.2015.09.007 Ghisetti, C., Marzucchi, A., & Montresor, S. (2015). The open ecoinnovation mode. An empirical investigation of eleven European countries. Research Policy, 44(5), 1080–1093. https://doi.org/ 10.1016/j.respol.2014.12.001 Gonzales-Benito, J. C., & Gonzales-Benito, O. C. (2006). A review of determinant factors of environmental proactivity. Business Strategy and the Environment, 15(2), 87–102. https://doi. org/10.1002/bse.450 Gulati, R. (2007). Managing network resources: Alliances, affiliations, and other relational assets. Oxford University. Hart, S. L. (1995). A natural-resource-based view of the firm. Academy of Management Review, 20(4), 986–1014. https://doi.org/10.5465/amr.1995.9512280033 Henriques, I., & Sadorsky, P. (1999). The relationship between environmental commitment and managerial perceptions of stakeholder importance. Academy of Management Journal, 42(1), 87–99. https://doi.org/10.5465/256876 Horbach, J. (2008). Determinants of environmental innovation—New evidence from German panel data sources. Research Policy, 37, 163–173. https://doi.org/10.1016/j.respol.2007.08.006 Kemp, R., & Pearson, P. (2007). Final report MEI project about measuring eco-innovation. UM Merit, Maastricht, 10(2), 1–120. López-Gamero, M. D., & Molina-Azorín, J. F. (2016). Environmental management and firm competitiveness: The joint analysis of external and internal elements. Long Range Planning, 49(6), 746–763. https://doi.org/10.1016/j.lrp.2015.12.002 Madsen, H., & Ulhøi, J. P. (2001). Integrating environmental and stakeholder management. Business Strategy and the Environment, 10(2), 77–88. https://doi.org/10.1002/bse.279 McWilliams, A., & Siegel, D. (2001). Corporate social responsibility: A theory of the firm perspective. Academy of Management Review, 26(1), 117–127. https://doi.org/10.5465/amr. 2001.4011987 Melo, T., & Garrido-Morgado, A. (2012). Corporate reputation: A combination of social responsibility and industry. Corporate Social Responsibility and Environmental Management, 19(1), 11–31. https://doi.org/10.1002/csr.260 Miles, M. P., & Covin, J. G. (2000). Environmental marketing: A source of reputational, competitive, and financial advantage. Journal of Business Ethics, 23, 299–311. https://doi.org/10.1023/ A:1006214509281 Orsato, R. J. (2006). Competitive environmental strategies: When does it pay to be green? California Management Review, 48(2), 127–143. https://doi.org/10.2307/41166341 Paulraj, A. (2009). Environmental motivations: A classification scheme and its impact on environmental strategies and practices. Business Strategy and the Environment, 18(7), 453–468. https:// doi.org/10.1002/bse.612 Penrose, E. T. (1959). The theory of the growth of the firm, 1st ed. Oxford University Press. Pereira-Moliner, J., Font, X., Tarí, J. J., Molina-Azorin, J. F., Lopez-Gamero, M. D., & PertusaOrtega, E. M. (2015). The Holy Grail: Environmental management, competitive advantage and
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Chapter 2
Fourth Industrial Revolution and Firms’ Digitalization
2.1
The Fourth Industrial Revolution
The term Industry 4.0 was first used at the Hannover Fair (Germany) in 2011 by Wahlster et al. to present the project “Zukunftsprojekt Industrie 4.0 literally industry project of future 4.0.” Such an investment program, oriented mainly toward infrastructures, energy, education, and research, was born with the aim of improving the competitiveness of the German industrial system to cope with global pressures from the developing countries, introducing innovative concepts and technologies. After the launch of the project at Hannover, the German government concretely implemented the initiative, establishing a steering group, then called Plattform Industrie 4.0 (Federal Ministry for Economic Affairs and Energy (2018), which coordinates a variety of companies, organizations, and universities. The German government granted until 2014 about 200 million euros, mainly conveyed through the institutional bodies of the Bundesministerium für Bildung und Forschung (German Federal Ministry of Education and Research) and of the Bundesministerium für Wirtschaft und Energie (German Federal Ministry of Economic Affairs and Energy) (Drath and Horch (2014). Following the pioneering activity started by Germany, several developed countries started to promote the potential of integrating IT technologies into manufacturing, giving rise to further medium/long-term investment programs called in various ways: “Advanced Manufacturing Partnership” in the USA, “Industrie du Futur” in France, “Catapult—High Value Manufacturing” in the UK, “Industria Conectada” in Spain, “Made in China 2025” in China, and “National Industry 4.0 Plan” in Italy represent the main programs built around the world. The pervasiveness of the phenomenon, combined with potential change of the whole economic ecosystem due to the new industrial paradigm, makes this particular historical moment a real revolution. Despite the fact that more than ten years have passed, the Industry 4.0 technologies, such as the Internet of Things and big data analysis, still have huge © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Parmentola, I. Tutore, Industry 4.0 Technologies for Environmental Sustainability, CSR, Sustainability, Ethics & Governance, https://doi.org/10.1007/978-3-031-40010-0_2
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margins for development and potential methods of use are not yet imagined. For these reasons, numerous experts, organizations, consulting firms, and institutions have given their definition of the Fourth Industrial Revolution, emphasizing from time to time some aspects over others. According to the GTAI (Germany Trade and Invest, the German Economic Development Agency), Industry 4.0 is a paradigm shift made possible by the technological advances, which constitutes the overthrow of conventional production logics; it represents the evolution toward cyber-physical systems, which merge the physical world with the digital one by connecting technologies of integrated manufacturing and smart manufacturing processes (Deloitte 2016). The consulting firm PricewaterhouseCoopers (PwC), in a report made in 2014, emphasizes that Industry 4.0 is a new paradigm that drives the emergence of a new level of organization and control over the whole life cycle of products: at the base there is the availability of information in real time, the ability to derive an optimal flow of added value, and the connection of people, objects, and systems (PwC 2014). PwC’s definition mainly covers three aspects: • Digitization and growing integration of vertical and horizontal value chains. Leading companies are able to digitize and to connect a function along the value chain both vertically (from the digital procurement process to the development of the customized product, to the transfer of data to planning systems) and horizontally because warehouse and planning data are implemented together with suppliers, customers, and partners. • The integration of digital elements in the offering of products and services. The so-called “digital samples” help companies to enlarge their product range with digital solutions, such as online connectivity. Also, the portfolio of services provided will be extended thanks to connected, automated, or databased services. • The introduction of innovative digital business models. New integrated solutions will be characterized by greater benefits for the consumer and will revolutionize existing product portfolios, as a consequence of a disruptive innovative process. New companies will have the opportunity to enter existing markets by leveraging the traditional entry barriers caused by digitization. The connection of people, objects, and systems is able to create dynamic and value-added links within companies, as well as between them. Optimization of these connections can be achieved according to several key criteria, such as costs, availability of resources, or their consumption. Other authors take positions that in part echo those cited above, arguing that the Fourth Industrial Revolution, as well as representing the technical integration of cyber-physical systems in production, logistics, and industrial processes, consists of a process of evolution that involves the entire value chain, business models, and front-end services (Wolter et al. 2015). Finally, it is appropriate to report the description of the Industry 4.0 concept given on “Plattform Industrie 4.0,” an institutional site of the German government and therefore an undoubted point of reference at the global level considering that Germany is the forerunner of this industrial revolution:
2.1
The Fourth Industrial Revolution
25
Industrie 4.0 refers to the intelligent networking of machines and processes for industry with the help of information and communication technology (Federal Ministry for Economic Affairs and Climate Action, 2018).
Underlining again the concept of intelligent connection between the elements of the industrial processes, some are examples of possible implementation of the new paradigm, between these: • Flexible production: the digital interconnection of the various steps of productive process can improve planning and coordination. • “Convertible” factory: the production lines can take on a modular nature and then be quickly assembled as needed, improving productivity and efficiency even in the case of small quantities produced. • Consumer-oriented solutions: producers and customers will be more in contact with the first who will be able to exploit data from smart products to offer new services, and the second able to choose the design of the product in a personalized way. • Optimized logistics: through algorithms, the machines can calculate themselves the optimal material flows and the most efficient distribution methods. • Use of data: through the combination and above all the analysis of large amounts of data, companies can increase their efficiency. • Resource-efficient circular economy: the whole product life cycle can be redesigned, determining from the design stage which resources are needed and how they can be recycled. Summarizing, the new paradigm providing the interconnection between the physical and digital world opens up a range of opportunities that concern numerous aspects at the micro (individual company) and macro (entire value chains, sectors) level. In other words, digital information duly collected, aggregated, and analyzed can be integrated with the non-virtual world and can contribute to the improvement of physical objects. The term most frequently used to describe the concept of integration between the dynamics of physical processes and those of digital tools (software, networks, etc.) to monitor and improve production is “cyber-physical systems” (Özüdoğru et al. 2018): cyber-physical systems act in an iterative way and through feedback between the physical and digital world, so physical and digital totally overlap so much that they are no longer distinguishable in the final product. The Fourth Industrial Revolution, with its related innovations in the digital field, sets the foundations for Industry 4.0: a new kind of industry that thanks to implementation across the entire value chain of cyber-physical systems communicating with each other via Internet is characterized by methods of interconnected production that make operational processes more efficient, allowing an increase in productivity and at the same time allowing a qualitative improvement of product. The 4.0 paradigm is translated into a substantial modification of the supply chain which, thanks to digital, no longer follows a linear and compartmentalized trend because every phase of it is related to the others (Burke 2017). This generates
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advantages for all actors involved in the production process and at the same time also gives benefits for users of goods and services that have been produced.
2.2
The Industry 4.0’s Enabling Technologies
Industry 4.0 is not a single technology but rather appears as a cluster of different technologies that are de facto agglomerated together by technological leaders, pivotal users, system integrators, and government policy makers. Several authors tried to classify these technologies according to their common traits (SaucedoMartinez et al. 2017) and identify the basic pillars, or building blocks, of the I4.0 framework. These technologies are not completely new, but, compared to two decades ago, when they were first developed, they are more widespread, more sophisticated, and integrated with each other and, consequently, are generating significant transformations in society and in the global economy. In particular, the ability of these new technologies to encode cognitive processes leads to ever greater substitutability between humans and software defined machines (Brynjolfsson and McAfee 2014). The European Commission defines key enabling technologies as “Technologies with a high coefficient of knowledge, associated with high R&D intensity, rapid cycles of innovation, substantial investment costs and highly skilled jobs. They are systemically relevant and have the ability to innovate processes, products and services in all economic sectors.” Boston Consulting Group (BCG) has identified nine enabling technologies (see Fig. 2.1), which can be considered the pillars on which the Fourth Industrial Revolution is founded. This set of technologies comprises big data and analytics, cloud computing, simulation, augmented reality, cybersecurity, additive manufacturing, industrial Internet of Things, horizontal and vertical systems integration, and autonomous robots. Industry 4.0 revolves around communication and information exchange between these technologies within an efficient integrated network. Each innovation can therefore be implemented only if you have a solid state-of-the-art and continuously updated infrastructure. The joint use of these technologies, despite the fact that some of them are already known and applied for many years, is radically transforming the industrial paradigm: every part of the manufacturing process will be fully integrated and automated, and this will allow greater production and management efficiency. They are also changing the traditional relationships between suppliers, producers, and customers, and in the short term the relationship between human and the machine will no longer be as we know it today (Gerbert et al. 2015). The I4.0 enabling technologies will be described in detail in the following paragraphs.
Fig. 2.1 Nine technologies are reshaping production. (Reproduced from BCG analysis 2017)
2.2 The Industry 4.0’s Enabling Technologies 27
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2.2.1
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Fourth Industrial Revolution and Firms’ Digitalization
Big Data and Analytics
The term big data refers to data produced in large quantities, with considerable speed and in the most varied formats, whose processing requires technologies and resources that range well beyond conventional data management and storage systems. To obtain information from this large amount of data that can be used in the decision-making processes of a company, it is necessary to use alternative tools and high computing skills to data analysis (Erevelles et al. 2016). If exploited properly, big data have the potential to give companies an enormous amount of feedback on the market conditions and customer behavior, making decision-making process more effective and faster compared to competitors. This technology is also widely used in quite different sectors, from medical diagnoses to census data, from “customer relationship management” (CRM) to banks. The analysis of this enormous amount of information allows companies that use it to improve the relationship with customers, increase sales, cut time to market, expand the offer of new products and services, reduce costs, and search new markets.
2.2.2
Autonomous Robot
For years, the industry has made use of automated robots that can perform tiring and repetitive multiple functions, but in recent years something is changing. These exceptional machines are starting to become more autonomous, flexible, and cooperative. The innovative element, however, lies in the fact that these machines automatically interact with each other and are able to work side by side with humans and learn from their behaviors. These collaborative robots (CoBots) are also evolving very rapidly both in terms of performance and price, also thanks to the increasing availability of sensors and computational ability in data processing. As technologies evolve, robots therefore leave their fixed position in the factory, to begin to move in the various environments and interact with humans, establishing reciprocal learning relationships with them (El Zaatari et al. 2019). Their use ranges from production to logistics and involves a myriad of new professionals such as analysts, software designers, industrial designers, and application technicians.
2.2.3
Simulation
Simulation is a powerful experimental analysis tool, used in various scientific and technological fields, thanks to which it is possible to reproduce a virtual copy of the real world—including machines, products, and humans. This technology allows managers to test and optimize the setting of machinery virtually before including
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The Industry 4.0’s Enabling Technologies
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them in the reality, reducing errors and increasing efficiency and quality. The continuous reception of data in real time also allows companies to anticipate problems, considerably reducing the costs associated with the inactivity of the machines and guiding the technicians in making the best operational decisions (Eriksson and Hendberg 2021).
2.2.4
Horizontal and Vertical System Integration
The adoption of new information technologies, able to process an enormous amount of data and share information in real time, has allowed digitization and integration of the entire value chain. In this way, it became possible to better coordinate the activities between the various levels of the chain, reducing inventory costs and synchronizing supplies. In this vertical integration, the IT and command processes are increasingly networked and executed in an integrated way, making the production and logistics data available to all company departments. The effect then is to create a horizontal integration throughout the company and establish a networking between machines, plant parts, or production units. Some examples of these technologies, which allow vertical and horizontal integration, are smart labels, automated warehouses, or platforms.
2.2.5
Internet of Things
The Internet of Things is the interconnection via the Internet of computing devices embedded in everyday objects, enabling them to send and receive data. The “thing” is physically present in the real world, at home, at work, in the car, or it is simply worn, receiving continuous input from the surrounding environment. The information received is then transformed into data to be sent on the Internet, so that they are stored and processed by the internal processor (McEwen and Cassimally 2013). The fields of application of the IoT are almost unlimited and range from cars to clocks and from plants to appliances, including anything that can be connected to the network. This phenomenon is rapidly growing and the Internet of Things is now an increasingly common word in the jargon of citizen 4.0.
2.2.6
Cybersecurity
With the advent of Industry 4.0 and the increase of the number of devices suitable for Internet connections, there has been a vigorous increase in both people and companies, which are connected to the network through the use of standard communication protocols. Parallel to these phenomena, the number of cyber-attacks, conducted with
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increasingly sophisticated techniques and systems, is increased. This circumstance has made IT security and the protection of sensitive data priority issues, leading to overturns the concept of cybersecurity. By this term we mean the set of all those processes that allow the protection of information through prevention activities, detection, and response to attacks from the network. These attacks should not only be viewed as a cyber risk, but as a risk that encompasses the entire sphere of our professional and private lives. For businesses the danger is even higher, as their systems are simply not threatened IT professionals and their databases, but their credibility and reputation are also involved (Craigen et al. 2014).
2.2.7
Cloud Computing
In computer science, the term cloud computing indicates a paradigm that implies the storage, processing, or transmission of data, characterized by the availability on demand, through the Internet, of a set of configurable and quickly deliverable resources with minimal management effort and interaction with the service provider (Mell and Grance 2011). This model has the main objective of making usable the functionality of a software without having to purchase the application itself. In this regard, we talk about software as a service (SaaS), meaning the ability to use programs installed on a remote server (i.e., outside the physical computer or LAN). Another benefit of the cloud for businesses is the ability to shrink considerably the costs and to optimize the spaces as there is no longer the need for systems to be physically present in the company and managed by specific personnel. This possibility, defined infrastructure as a service (IaaS), allows some companies to specialize in providing remote resources such as servers, network capacities, storage systems, archive, and backup, leveraging economies of scale and significantly reducing costs.
2.2.8
Additive Manufacturing
Additive manufacturing was born in 1986 thanks to Chuck Hull, founder of 3D Systems, as a quick method to create physical prototypes starting from a digital file. This technology, also called “rapid prototyping” or “3D printing,” is a new way of creating real objects, starting from the data of a digital model created on a computer using software CAD (computer-aided design). 3D printers read three-dimensional mapping of the digital object, then break it down into very thin layers, and finally recreate the model layer after layer, until the desired product is obtained (Sher and Marinoni 2015). In this way, the geometry constraints imposed by the techniques exceed traditional methods, toward the cancelation of the costs of making the variants and the elimination of waste of raw material. Despite these positive sides,
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Fourth Industrial Revolution and Companies’ Competitive Advantage
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the production times and costs pay off this technology, for the moment, unsuitable for mass production. It has established itself mainly where the advantages of an optimized geometry outweigh the cost or disadvantages and where urgency justifies an increase in construction costs. The applications of the additive manufacturing are almost endless, from the military to the bio-medical sector, from construction to food, opening up scenarios that were previously unthinkable, such as the use of expensive alloys, instead of steel in the aerospace industry, or the on-site realization of the object only in case you actually need it.
2.2.9
Augmented Reality
Augmented reality can be defined as a system formed by a set of IT devices capable of enabling a new type of human–computer interaction. The systems of inputs are the technological tools through which the user could interact with the virtual environment and obtain feedback through which to warn in a definite way the presence of that world. These systems adapt increasingly to the user’s body movements, allowing him or her an increasingly realistic and engaging immersion. According to the type of interaction, three types of virtual reality can be distinguished: immersive, non-immersive, and semi-immersive. Immersive virtual reality, mainly composed of viewers, allows you to isolate the user at a sensory level, immersing him or her completely in the virtual world. Non-immersive virtual reality makes use of screens and monitors, through which the user perceives augmented reality and can interact with it. With semi-immersive virtual reality, we mean a hybrid system represented for example by a room on which walls are projected images of the virtual world, isolating the user in an almost complete way (Carmigniani and Furht 2011). As for some of the technologies described above, also for augmented reality the fields of application are very varied; the only limit is the imagination. Nowadays, applications include the world of videogames, medicine, automotive industry, and even that of museums.
2.3
Fourth Industrial Revolution and Companies’ Competitive Advantage
Industry 4.0, compared to the previous industrial model, constitutes a paradigm shift in the sense of moving from the objective of optimizing physical assets toward the optimization of way in which data and information are advantageously used throughout the life cycle of the product. The new way of exploiting technologies constitutes an uninterrupted flow of information, creating a path that follows the entire value chain and finds representation in what Hartmann et al. (2015) defines “digital thread”: this digital path is the guiding thread for the resolution of major
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issues along the life cycle in order to optimize all activities, starting from the digital design of the product, passing through the digitally checked production process, ending with the recycling of the parts at the end of their useful life, and identifying the best methods of reuse through the collected data. At each stage, the digitized information acts as an enabler: data can be easily exchanged, processes can be viewed and controlled with digital interfaces, and the interaction can also take place remotely. The digital data can be considered, in the case of the Fourth Industrial Revolution, as “core all-pervasive low-cost input” (Perez 2010) which unites the various industries and constitutes the widespread basis on which products, technologies, and infrastructures are developed. Also, leveraging information along the digital thread allows greater integration and cooperation between phases of the product life cycle connecting the actors involved (suppliers, customers, other stakeholders). Managing the digital thread according to the 4.0 technological paradigm means mastering four fundamental activities, prerequisites for creating value from data (Hartmann et al. 2015): 1. Collection and recording of information. Inefficiencies can only be eliminated if identified and documented; therefore, it is necessary to map the entire production process through real-time data; this requires switching from traditional measurement modes that are focused on a single action to new tools that are able to completely cover the processes, using sensors and instruments capable of monitoring every element of the work. 2. Transfer of information. The collected data could be more useful in a phase other than that from which they are extracted, making it necessary to share them in real time throughout the value chain; the complexity for companies lies in integrating data from different sources and creating a holistic view of the processes. 3. Analysis and synthesis of information. Moving from data to complex information takes careful elaboration: finding better solutions depends both on reliance on causal relationships derived from historical data and on the optimization of processes based on collected information. Optimization opportunities exist where there are not obvious interrelationships or where the information is not yet fully exploited. 4. Transformation of information into results. The conclusions derived from the data must, in ultimately, lead to recommendations and actions to be taken; several opportunities reside in the partial automation of decision-making processes, still characterized by the strong human involvement. By creating automatic feedback mechanisms, it is possible to establish a continuous cycle that adjusts itself until the desired results are achieved. By exploiting 4.0 technologies to act directly on digital data and information, it is possible for businesses to unlock the potential of the new revolution; however, to optimize information along the digital thread it is necessary to adopt standardized communication systems between the various assets.
2.3
Fourth Industrial Revolution and Companies’ Competitive Advantage
2.3.1
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Possible Benefits of I4.0 Technologies
The term “Industry 4.0” was born to identify the integration between traditional industrial practices and the virtual world, through a series of technologies capable of leading the virtual world to a real one. Although these technologies are now widely known throughout the industrial world, their application opportunities are growing exponentially thanks to a greater reliability and lower costs creating the possibility for all companies, even the smaller ones, to take advantage of smart tools. In addition to representing an opportunity with great potential, the Industry 4.0 paradigm is also a necessity: to digitize processes using technology is the only way to survive in the future. The driving forces behind the whole phenomenon represent value drivers on which companies can base their innovative strategy. In particular, Newman (2018) identifies four major trends in digital transformation that companies need to pay attention to: 1. Connected consumers, personalized experiences. While in the past a product was made for millions of customers, the latter are now connected directly to companies through social networks, interactions in the purchasing process, and data analysis. The producers are increasingly listening to consumers to know what they want, and to realize it by adopting the power inherent in new technologies. Thanks to these technologies, companies can make customized products, which requires an efficient cost as well as batch production. 2. Greater autonomy for workers. Employees have direct access to the information they need for work: new collaboration tools and platforms make it simple to access information, from any device and anywhere, even remotely. The business activity benefits from greater streamlining and total visibility of the logistics chain enabled by technology, also allowing managers to adopt a more informed decision-making process and to be aware of strategic and operational aspects. 3. Optimized production. The new technology has led to a rapid change in the productive process, which can now be dynamically adapted to suit demand. Identify the steps that can be made faster, eliminate waste of material or time, adjust the level of stocks, and check the maintenance of machinery: these and other issues can now be solved, not only by large companies with time dedicated resources and financial availability, but also by small and medium sized enterprises. 4. Processed products. Machinery able to monitor its consumption or the need for maintenance can help companies in saving a lot of money every year. Furthermore, they can give rise to new and improved products through data analytics and technologies as Internet of Things. Other technologies, such as augmented reality, can change the way in which the products themselves are designed, allowing for testing even before reaching the assembly line. These trends clearly indicate that to survive and succeed in the future companies have to follow the path of digital transformation The transition from the physical to the digital world has already been known for at least forty years, when the Third
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Fourth Industrial Revolution and Firms’ Digitalization
Industrial Revolution began to take hold, but it is only recently with Industry 4.0 that the integration between digital and physical world is realized (Deloitte 2016). Each of the I4.0 digital innovations includes, in turn, different technologies connections that correspond to the many possible applications in the industrial world. For this reason, to help companies understand the many opportunities deriving from I4.0 technologies and to drive them in the technologies’ use, Hartmann et al. (2015) elaborates the digital compass, one strategic policy tool that links the possible levers of improvement to each value drivers of Industry 4.0. The 8 value levers of the digital compass are: • Resources and processes: reducing the use of resources or maximizing their performance creating value cutting costs in the first case and increasing revenues in the second. The IoT favors the pursuit of these results, making objects connected and programmable, • Assets utilization: especially in capital-intensive sectors, even a single minute when machinery is idle can represent a huge cost. The use of sensors, for example, can help predict the need for maintenance, optimally planning temporary work interruptions, • Labor: improving productivity is an important source of value, work being one of the main cost items. Physical fatigue and the complexity of the activities performed can be alleviated through the support of collaborative robots, creating a relationship of cooperation between man and machines, • Inventories: holding an excessive amount of inventory in stock is a fixed asset capital with high opportunity costs. Optimization through the use of data obtained in real time or small batch production, for example through 3-D printers, makes the whole logistics chain more flexible. Leading the inventory reduction process to the extreme, the concept of “batch size one” is obtained, corresponding to the product made and customized quickly through additive manufacturing, • Quality: the term refers to the reduction of production inefficiencies (scraps, errors, waste of time, poor distribution, etc.). Advanced control systems, which integrate the various phases of the value chain, can identify the points of greatest criticality and can direct optimization interventions. • Equality between supply and demand: understanding the consumer’s wishes exactly allows companies to completely satisfy them capturing the potential value of the market. Today, companies are supported by data analytics processes, which make it possible to obtain relevant information on an aggregate of potential and current customers and therefore to focus their strategic choices on the most successful products and services. • Time to market: the time it takes from the conception of the product (or service) to its market introduction determines whether the firm will be able to exploit the monopoly profits resulting from being a first mover or if it will be forced to follow other leading companies. Reducing the design, manufacturing, and distribution process is crucial from a strategic point of view and contributes to reducing research and development costs.
2.3
Fourth Industrial Revolution and Companies’ Competitive Advantage
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Fig. 2.2 The Digital Compass. (Reproduced from Hartmann et al. 2015)
• After-sales services: reducing the problems that the customer may encounter after the sale (maintenance, unexpected malfunctions, etc.) increases the quality of the service offered and drastically reduces time and costs. In this sense, predictive and remote maintenance helps to create value by avoiding unnecessary physical movements or non-extraordinary interventions. Furthermore, the set of I4.0 technologies brings the company closer to the customer and opens a range of opportunities down the value chain. Consequently, especially small and mediumsized enterprises, exploiting big data, can develop innovative services in the B2B field (Kagermann et al. 2013). Figure 2.2 illustrates the Digital Compass in its entirety: using this tool as a compass helps companies to extricate themselves within the panorama I4.0. Understanding the value drivers to focus on, depending on the specific reality business, is a factor of competitive and strategic advantage in the medium and long term, which can generate for companies a cost reduction that can reach 50% and a productivity increasing up to 55% (Hartmann et al. 2015).
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2.4
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Fourth Industrial Revolution and Firms’ Digitalization
I4.0 Technologies as Instruments to Enhance Companies’ Sustainability
In 1987, the Brundtland Report defined the concept of sustainable development as a development that meets the needs of the present without compromising the ability of future generations to meet their own needs (World Commission on Environment and Development 1987). The pressing need to achieve sustainable development has become a global priority for both governments and companies. In fact, in 2015 the United Nations General Assembly drew up Agenda 2030, setting out 17 indivisible and self-sufficient objectives that go in the direction of create a more sustainable world. Some of the trends of recent years can be found in growing socio-economic inequality, increasing environmental degradation, climate change, urbanization, and growing dependence on cybernetics. They also give rise to various regional risks, such as social instability, underemployment, involuntary migration, water crises, natural disasters, or resource depletion. To address the causes of these trends and to limit the resulting damage, industrialized countries must cope with numerous challenges (World Economic Forum (WEF) 2017). In this direction, it is necessary for industrial organizations to move toward a new paradigm with an emphasis on sustainable value creation. The three-pillar model (Elkington 1997) includes the environmental, social, and economic dimensions as essential and complementary fields of action: economic sustainability: understood as the ability to generate income and work for the subsistence of the population; social sustainability understood as the ability to guarantee conditions of human well-being (security, health, education, democracy, participation, justice) equally distributed by class and gender; environmental sustainability understood as the ability to maintain quality and reproducibility of natural resources. Because of these considerations, although they are quite recent issues, several studies have been carried out analyzing in parallel Industry 4.0 and sustainability. According to the authors, Industry 4.0 will be able to generate a higher industrial value in terms of sustainability. Inserting itself in the complex context that sees today’s production processes unsustainable for the environment, I4.0, defined as the industrial revolution of the moment, can present an excellent opportunity for sustainable development, thanks to the potential that derives from its technology. Indeed, even if the guiding principle of I4.0 is mainly focused on the increase of productivity along the entire production process and on the growth of revenues, it is appropriate that, in the current scenario, sustainable development becomes one of the main drivers to enable companies to be able to compete in a long-term perspective. In particular, the goal is to identify how the applications of the new industrial revolution can contribute to the creation of sustainable value, interpreted by the three dimensions: economic, social, and environmental. These dimensions, due to their nature of interdependence, often interact, overlap, and conflict, making it more difficult to achieve the SGDs. Pursuing the triple bottom line, therefore, requires a holistic view on the part of the companies. Each dimension is a necessary condition, but not a sufficient one to achieve
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I4.0 Technologies as Instruments to Enhance Companies’ Sustainability
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sustainability. When organizations do not support one of these, they do not do it right and sustainably (Ghobakhloo 2020). It turned out indeed that balancing them through the technology adoption is a critical success factor in achieving sustainable benefits. In general, the digitization and interconnection of industrial processes foreseen by I4.0, facilitated by data analytics, machine learning, and artificial intelligence, could bring potential benefits in all three aspects of sustainability (Müller et al. 2018). Taking into consideration the inseparable nature and cause–effect relationships of the pillars of 3BL, one of the main difficulties is to clearly distinguish the economic benefits from those social and environmental ones.
2.4.1
I4.0 and Economic Sustainability
Referring to the economic perspective of I4.0, the flexibility and interconnection of processes allow their optimization, increasing their efficiency and productivity, the quality, and the possibility of customization, and also reducing costs. I4.0 then offers opportunities to rethink products and business models to respond more effectively to market needs. Intelligent manufacturing technologies indeed help companies to create new value propositions that are more demand oriented, because organizations can meet changing market demands, also through the production of small batches or even a single item (Ghobakhloo and Fathi 2019; Venugopal et al. 2019). As for efficiency and productivity, thanks to automation, interoperability and the intelligence of the CPS process control measures can be improved, facilitating the maintenance in real time, monitoring the performance of the machines, and reducing their times still (Ghobakhloo and Fathi 2019). The adoption of analysis and predictive maintenance helps to reduce errors and defects along the assembly line, allowing an increase in the quality of the final product and a reduction of costs due to errors or rejects. Even in intra- and inter-company logistics processes, I4.0 allow companies to lower costs and increasing efficiency. The potential implications of I4.0 in the context of Kanban systems and Just-in-Time are varied. Even for an already consolidated system such as Just-in-Time (JIT) the benefits derived from I4.0 are diverse helping companies to implement a streamlined, oriented model to a pull-type logic oriented to produce only what is necessary for the purpose to reduce any potential waste (Hofmann and Rüsch 2017). In addition to the examples just presented, the implications of I4.0 in terms of cost reduction also include the optimization of the use of human and material resources, the greater effectiveness of production cycles, and the reduction of human errors in the manufacturing processes and distribution of finished products. Companies can then respond to the growing demand for individualization of products by developing new value propositions, thanks to flexible automation and additive manufacturing, combined with production modularity. Today, they can produce personalized products of higher quality, which allow differentiation in the competitive and selling landscape. Furthermore, the emergence of IoT and IoS (Internet of Service) and data mining capability (exploration and
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extraction from large datasets of potentially useful information) has allowed companies to communicate and interact directly with customers, collecting and analyzing a huge volume of data about their preferences and consumption habits (Ghobakhloo and Fathi 2019). Companies are experimenting with new business models whose purpose is to reduce asymmetries information between the parties involved (e.g., customer-supplier) or which are based on innovations technologies, such as additive manufacturing, which allows the customization of products and the reduction of the costs of generating different productive variants. In particular, thanks to ICT technologies, IoT and big data, organizations have the possibility of adding services to the physical product with the aim of creating greater value added to the end customer. Selling a product service system (PSS) means offering new things to the customer experiences. These, in fact, do not become owners of the product but can use the services related to it. Thus, the concept of servitization as the sale of services is associated with the use of a product, through which the company can forge more lasting relationships with the customer and the latter can avoid product obsolescence without incurring major costs. PSS is subsequently considered to extend the current product life cycle from a sustainable perspective. Through the dissemination of sensors, CPS, and analytics formulas, which allow continuous management of information derived from the data, it is possible to support the OEE (overall equipment effectiveness), e.g., constant and real-time monitoring of the operating status of the well, which makes it possible to reduce assistance and maintenance costs (Doni et al. 2019). Constant monitoring gives producers the possibility to analyze the behavior of the product more effectively, highlighting possible future difficulties and thus supporting the process decision-making, scheduling maintenance, repairs, or replacements, or modifying the product in order to improve its functions.
2.4.2
I4.0 and Social Sustainability
The I4.0 revolution, with the adoption of new technologies and new production models, will bring about profound changes in society and in working conditions. As far as the latter are concerned, I4.0 can contribute to improving the conditions of safety in production cycles, healthiness in the workplace, management of work–life dynamic, reducing accidents and occupational diseases, and improving the corporate welfare and employee well-being. In fact, intelligent and autonomous production systems can be used to carry out more monotonous and repetitive tasks, allowing workers to focus on more satisfying and motivating activities, reducing careless errors, and increasing productivity (Müller et al. 2018). In addition, the implementation of smart devices, robotic assistance systems in workstations, and technologies such as augmented reality allow us to replace and support humans in high-risk activities, preserving their health and limiting the number of accidents. On the one hand, new technologies and digitization can be used to make working hours more flexible and adaptable to the individual needs through, for example, remote work or
2.4
I4.0 Technologies as Instruments to Enhance Companies’ Sustainability
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smart working. On the other hand, however, the impacts of digitization and automation at the occupational level are more ambiguous. While according to some theories, automation and digitization will bring an increase in employment by creating more new qualified jobs, other authors argue that they will lead to massive job losses. The World Economic Forum (WEF) annually draws up a report, Future of Jobs, which concerns the development of the world of work. The 2020 report identified the different impacts that progress technology and the adoption of new production models have on the employment level, providing a global overview of technology growth, emerging skills and jobs, and necessary redevelopment and upgrades. To seize the opportunities created by I4.0, many companies have embarked on a strategy reorientation strategy. Cloud computing, big data, and IoT remain priorities for organizations, with a significant increase in cybersecurity, non-humanoid robots, and artificial intelligence. According to the WEF (2020, p. 8), by 2025, “automation of machines and algorithms will be so widely employed that the hours of work performed by the machines will equal the working time of men.” Technology adoption by businesses will transform therefore tasks, jobs, and skills. The new context will, therefore, require more qualified professional figures, shifting the role of humans from a manual level to a decision-making level, effectively eliminating jobs with low qualification requirements, routine, and limited complexity of action. The adoption of these technologies will revolutionize the employment prospects of many workers sectors. On average, approximately 15% of a company’s workforce is at risk of change up to 2025, and 6% will be completely shifted. Over the medium term, employers expect roles to become increasingly redundant, by 2025 will decrease by 6.4%, and that emerging professions will grow by 5.7%. Between profiles referred to as “job of the future” we can find, for example, IT and AI specialists, data analysts, robotic engineers, programmers, and new product developers. Based on this data, the report estimates that, by 2025, approximately 85 million jobs will be replaced by the use of intelligent machines, while 97 million will be able to emerge and to manage technology integration. This report therefore predicts that, in the medium term, the destruction of jobs will be most likely offset by the growth of “jobs of the future.” However, in the current context, the effects of the global pandemic are such that they are not yet an evident trend. In order to manage this transition, avoiding inequalities and inequities, companies will have to provide retraining and upgrades to a significant portion of their workforce improving transversal ability (e.g., the soft skills), which will require critical thinking, problemsolving skills, teamwork, and digital skills. A significant number of business leaders interviewed in the report believe that the retraining of employees is one of the essential factors for resource optimization and productivity in the medium and long term, bringing benefits not only for the company but also for society in general.
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2.4.3
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Fourth Industrial Revolution and Firms’ Digitalization
I4.0 and Environmental Sustainability
Also, regarding the environmental dimension, the impacts of I4.0 can be ambiguous. On the one hand, I4.0 makes it possible to reduce and monitor energy and material consumption materials and resources by reducing their use. On the other hand, constant connection and communication between the various production processes require large amounts of energy and electronic material. Industry 4.0 technologies can enable the efficient allocation of resources such as materials, energy, water, and products, by using real-time data from production systems and supply chain partners. This results in more sustainable manufacturing decisions (Stock and Seliger 2016). Stock and Seliger (2016) analyze the interaction between I4.0 and environmental sustainability from a macro and a micro perspective. In the first case the potential of I4.0 derives mainly from an optimized value creation network: the cross-linking of value creation networks in Industry 4.0 enables efficient coordination of product, material, energy, and water flows throughout the product life cycle and between different factories, promoting industrial symbiosis and the implementation of new business models. Sustainable business models are able to generate positive spin-offs or reduce negative impacts on the environment or society; moreover, they can also contribute decisively to solve an environmental or social problem. From the micro perspective, they underline the importance of value creation modules (equipment, human, organization, process, product). The core of value creation comes from the implementation of a life-cycle approach and in this direction smart factories are the emblem of sustainability. Those value creation modules, e.g., factories which are embedded in this ubiquitous flow of smart data, will evolve into so-called smart factories. Smart factories are manufacturing smart products and are supplied with energy from smart grids and water from freshwater reservoirs. The material flow along the product life cycle and between adjoining product life cycle will be accomplished by smart logistics. The stream of smart data between the different elements of the value creation networks in Industry 4.0 is interchanged via the cloud. Smart factories are using embedded cyber-physical systems for value creation. This enables the smart product to self-organize its required manufacturing processes and its flow throughout the factory in a decentralized manner by interchanging smart data with the CPS. The smart product holds the information about its requirements for the production processes and manufacturing equipment. Smart logistics are using CPS for supporting the material flow within the factory and between factories, customers, and other stakeholders. They are also being controlled in a decentralized manner according to the requirements of the product. A smart grid dynamically matches the energy generation of suppliers using renewable energies with the energy demand of consumers, e.g., smart factories or smart homes, using short-term energy storages for buffering. Within a smart grid, energy consumers and suppliers can be the same. The development of production models toward greater customization, linked to downstream integration with the end customer (thanks to the cloud), allows the production of small, customized batches, thus avoiding overproduction and reducing waste of
2.4
I4.0 Technologies as Instruments to Enhance Companies’ Sustainability
41
energy and materials, as well as inventory costs. This also reflects a change, from a sustainable perspective of consumer purchasing behavior. The reduction of waste is then closely connected to additive manufacturing processes which, compared to traditional technologies, such as the lathe (subtractive manufacturing), only use the raw material necessary for the creation of the product. Additive production itself, together with other technologies, also has impacts on the smart level life-cycle management, facilitating the development of new products and new respectful uses of the environment. Additive manufacturing can be used, together with an efficient design, to create new and complex lightweight structures that save on materials, maintaining product functionality. This technology is also employed to produce individual spare parts that extend the life cycle of a product or machinery, falling within the typical practices of the circular economy model. The ability to create products equipped with chips and sensors, supported by intelligent systems, allows the company to memorize all data related to the end-of-life phase of the product by supporting closed life cycles that give the possibility to recycle, reuse, or regenerate parts of the product. At the logistics and smart supply chain level, the sharing of data and information between the actors of the supply chain makes it possible to anticipate the demand, thus avoiding bullwhip effects and unnecessary material flows; in addition, the possibility of developing decentralized organizational structures close to the places of consumption reduces transport times. All of these latter aspects determine a reduction of the environmental impact and of logistics costs. Finally, I4.0 can increase the environmental sustainability pushing organizations and consumers toward a paradigm shift, replacing the traditional linear growth model. The technological and economic progress that has characterized the last 250 years has indeed affirmed a linear vision that follows the “take-make-usewaste” model, regardless of long-term resource availability, global biocapacity, and environmental impacts derived from production and consumption waste. This approach has now become unsustainable and requires greater responsibility by companies and consumers. For this reason, efforts have been made in recent years to introduce a new model, consistent and capable of adapting to the dramatic environmental situation. The circular economy (EC) model aims to close the circle of the product life cycle ensuring, through careful design and models of innovative business, a continuous flow of technical and biological materials, safeguarding natural resources and respecting their regeneration. The logic then becomes “make, use, reuse, remake, recycle.” The EC stipulates that biological materials can be replenished into the natural environment, while for technological materials there is a revaluation system. In particular, according to the definition of the EU, the circular economy implies a model of sharing, lending, reusing, refurbishing, and recycling that extends the life cycle of products as far as possible while minimizing waste and generating additional value wherever possible (European Parliament 2021). The technologies connected to I4.0 give the opportunity to pursue these objectives by acting on all stages of the production chain. Among the sustainable benefits presented above, there are several that are also part of a circular economy approach.
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Sensors and microchips embedded in the products and materials can help companies to track, monitor, and collect useful information for the recycling and regeneration processes of the product and its parts. Additive manufacturing then allows the exploitation of new sustainable and recyclable materials, which, combined with proper planning and design, create structures with the least possible number of resources. The useful life of the product or machinery is extended by the possibility of recreating spare parts at sustained costs and the forecast of possible failures and malfunctions with predictive analysis. Finally, the development of product service systems and servitization not only changes the consumption behaviour of consumers but also incentivizes companies to extend useful life profit of the products in order to make the most of the revenues and to strengthen the relationship with the customer for a long time.
References Brundtland, G. H. (1987). Our common future: Report of the world commission on environment and development. Geneva, United Nations-Dokument A/42/427. Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. WW Norton. Burke, T. J. (2017). Opc unified architecture: Interoperability for industrie 4.0 and the internet of things. Opc Foundation, 1, 01–44. Carmigniani, J., & Furht, B. (2011). Augmented reality: An overview. Handbook of Augmented Reality, 3–46. Craigen, D., Diakun-Thibault, N., & Purse, R. (2014). Defining cybersecurity. Technology Innovation Management Review, 4(10). Doni, F., Corvino, A., & Martini, S. B. (2019). Servitization and sustainability actions. Evidence from European manufacturing companies. Journal of Environmental Management, 234, 367–378. https://doi.org/10.1016/j.jenvman.2019.01.004 Drath, R., & Horch, A. (2014). Industrie 4.0: Hit or hype? [industry forum]. IEEE Industrial Electronics Magazine, 8(2), 56–58. Elkington, J. (1997). The triple bottom line. Environmental management: Readings and cases, 2, 49–66. El Zaatari, S., Marei, M., Li, W., & Usman, Z. (2019). Cobot programming for collaborative industrial tasks: An overview. Robotics and Autonomous Systems, 116, 162–180. https://doi. org/10.1016/j.robot.2019.03.003 Erevelles, S., Fukawa, N., & Swayne, L. (2016). Big Data consumer analytics and the transformation of marketing. Journal of Business Research, 69(2), 897–904. https://doi.org/10.1016/j. jbusres.2015.07.001 Eriksson, K., & Hendberg, T. (2021). A case study initiating discrete event simulation as a tool for decision making in I4. 0 manufacturing. In Decision Support Systems XI: Decision Support Systems, Analytics and Technologies in Response to Global Crisis Management: 7th International Conference on Decision Support System Technology, ICDSST 2021, Loughborough, UK, May 26–28, 2021, Proceedings (p 84–96). Springer. European Parliament. (2021). Circular economy: Definition, relevance and advantages. https:// www.europarl.europa.eu/portal/it Federal Ministry for Economic Affairs and Climate Action. (2018). What is Industrie 4.0?, Germany.
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Geissbauer, R., Schrauf, S., Koch, V., & Kuge, S. (2014). Industry 4.0-Opportunities and Challenges of the Industrial Internet, PwC. Accessed December 2014, from https://www.pwc.nl/en/ assets/documents/pwc-industrie-4-0.pdf Gerbert, P., Rüßmann, M., Lorenz, M., Waldner, M., Justus, J., Engel, P., & Harnisch, M. (2015). Industry 4.0: The future of productivity and growth in manufacturing industries. Boston Consulting Group, 9(1), 54–89. Ghobakhloo, M. (2020). Industry 4.0, digitization, and opportunities for sustainability. Journal of Cleaner Production, 252, 119869. https://doi.org/10.1016/j.jclepro.2019.119869 Ghobakhloo, M., & Fathi, M. (2019). Corporate survival in Industry 4.0 era: The enabling role of lean-digitized manufacturing. Journal of Manufacturing Technology Management., 31(1), 1–30. https://doi.org/10.1108/JMTM-11-2018-0417 Hartmann, B., King, W. P., & Narayanan, S. (2015). Digital manufacturing: The revolution will be virtualized. In McKinsey Digital. Available via McKinsey & Company. Accessed August 2015, https://www.mckinsey.com/ Hofmann, E., & Rüsch, M. (2017). Industry 4.0 and the current status as well as future prospects on logistics. Computers in Industry, 89, 23–34. https://doi.org/10.1016/j.compind.2017.04.002 Kagermann, H., Wahlster, W., & Helbig, J. (2013). Securing the future of German manufacturing industry, recommendations for implementing the strategic initiative INDUSTRIE 4.0. Final report of the Industrie 4.0 working group, Frankfurt, Germany. McEwen, A., & Cassimally, H. (2013). Designing the internet of things. Wiley. Mell, P., & Grance, T. (2011). The NIST definition of cloud computing. In: Recommendations of the National Institute of Standards and Technology. Available via NIST, U.S. Department of Commerce. Accessed September 2011, from https://www.nist.gov/ Müller, J. M., Kiel, D., & Voigt, K. I. (2018). What drives the implementation of Industry 4.0? The role of opportunities and challenges in the context of sustainability. Sustainability, 10(1), 247. https://doi.org/10.1016/j.techfore.2017.12.019 Newman, D. (2018). Top 10 Digital Transformation Trends For 2019. Forbes, Jersey City, NJ, USA, Tech. Rep. Özüdoğru, A. G., Ergün, E., Ammari, D., & Görener, A. (2018). How industry 4.0 changes business: A commercial perspective. International Journal of Commerce and Finance, 4(1), 84–95. Perez, C. (2010, January). Technological revolutions and techno-economic paradigm. Cambridge Journal of Economics, 34(1), 185–202. Saucedo-Martínez, J. A., Pérez-Lara, M., Marmolejo-Saucedo, J. A., Salais-Fierro, T. E., & Vasant, P. (2017). Industry 4.0 framework for management and operations: A review. Journal of Ambient Intelligence and Humanized Computing, 9, 789–801. https://doi.org/10.1007/s12652017-0533-1 Sher, D., & Marinoni, D. (2015). Stampa 3D: Tutto quello che c’è da sapere sull’unica rivoluzione possibile. HOEPLI EDITORE. Sniderman, B., Mahto, M., & Cottleer, M. J. (2016). Industry 4.0 and manufacturing ecosystems. Deloitte University Press. https://www2.deloitte.com/content/dam/Deloitte/de/Documents/ consumer-industrial-products/Deloitte-Industry-4-0-and-manufacturing-ecosystems.pdfpw Stock, T., & Seliger, G. (2016). Opportunities of sustainable manufacturing in industry 4.0. Procedia CIRP, 40, 536–541. https://doi.org/10.1016/j.procir.2016.01.129 Wolter, M. I., Mönnig, A., Hummel, M., Schneemann, C., Weber, E., Zika, G., Helmrich, R., Maier, T., & Neuber-Pohl, C. (2015). Industrie 4.0 und die Folgen für Arbeitsmarkt und Wirtschaft: Szenario-Rechnungen im Rahmen der BIBB-IAB-Qualifikations-und Berufsfeldprojektionen in: IAB-Forschungsbericht No. 8/2015. Available via EconStor. http:// hdl.handle.net/10419/126512 World Economic Forum. (2017). The global risks report 2017, 12th ed., Geneva. Accessed January 2017, from https://www.weforum.org/ World Economic Forum. (2020). The future of jobs report 2020, Geneva. Accessed October 2020, from https://www.weforum.org/
Chapter 3
I4.0 Technologies Adoption and the Environmental Sustainability
3.1
A Methodological Approach to Analyze the Rise and Growth of Theoretical Discussions
New industrial revolution can represent a step forward toward more sustainable industrial value creation: the allocation of resources, i.e., products, materials, energy, and water, can be realized in a more efficient way on the basis of intelligent crosslinked value creation modules (Stock and Seliger 2016). Indeed, the capability of Industry 4.0 tools to support environmental sustainability decisions is widely recognized, since they allow a better strategic alignment between the employed information technologies and organizational goals (de Sousa Jabbour et al. 2018). A look at Dimensions scholarly database (see https://app.dimensions.ai) that includes research articles, books, and chapters harvested from different sources shows that the scientific debate on merging Industry 4.0 and environmental sustainability is growing (Fig. 3.1). Indeed, while the scientific debate on Industry 4.0 started on 2011, the roots of theoretical studies on environmental sustainability are older, starting around the 1980 s. The interest of the academic community in the merging of both topics started in 2012 and is increasing among the academic community. Thus, it is evident that academia is reserving more importance to the topic during the last few years. For this reason, it is important to analyze the roots of the scientific interest in the topic and identify the main trend of research that nowadays occupies in the academic community. In order to do so, we carried on a systematic literature review adopting a consolidated approach, the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) (Moher et al. 2015).
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Parmentola, I. Tutore, Industry 4.0 Technologies for Environmental Sustainability, CSR, Sustainability, Ethics & Governance, https://doi.org/10.1007/978-3-031-40010-0_3
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Fig. 3.1 Development of the topic (Reproduced from Dimensions scholarly database) Fig. 3.2 Steps of research protocol (Reproduced from SCOPUS)
Identification Screening Eligibility
Inclusion
This protocol has been already employed for similar analysis because it represents a plan that helps provide the description of the steps taken to ensure the objectivity of the process (Tranfield et al. 2003). The implementation of a research protocol improves the quality of the literature review, since it ensures the replicability, scientific, and transparency of the process. In particular, PRISMA protocol consists of iterative processes of a 27-item checklist and a four-phase flow diagram (Moher et al. 2015). The methodological steps are described in Fig. 3.2. The first step is to identify and select papers to include. In order to define our sample, we have built a query on SCOPUS database, considered one of the most
3.2
Descriptive Results of the Bibliographic Research
47
comprehensive portfolios of scientific journals. The query has been developed not including limit to the time span of research, document, or source type. A set of keywords that fit with our research scope have been identified and searched in keywords, title, or abstract of the papers. In particular, search string consists of two sections, namely the set of words that relate to the theme of Industry 4.0 and the ones that are linked to environmental sustainability. Search String: (TITLE-ABS-KEY (“industry 4.0”) AND TITLE-ABS-KEY (“natural environment*”) OR TITLE-ABS-KEY (“environmental sustainability”) OR TITLE-ABS-KEY (“ecology”) OR TITLE-ABS-KEY (“circular economy”))
The next step of the protocol involves the definition of raw criteria to screen the selected papers. By reading the abstract or keywords, we defined exclusion criteria to screen the documents that fit our scope. The Eligibility and Inclusion steps of the review protocol regard the definition of criteria to assess the fit of each paper. In order to do so, we have carefully read and reviewed all full text articles. Thus, the overall search process resulted in a final sample of 511 bibliographic records.
3.2
Descriptive Results of the Bibliographic Research
The first set of results regards the descriptive characteristics of the selected records. Scientific records tracked in Scopus database that link Industry 4.0 and environmental sustainability started in 2016 and are growing exponentially in the last few years. The number of cited papers is also growing with the same trend, also considering that papers published in 2021 and 2022 could not be already cited (Fig. 3.3). 200
3500
180
3000
160 2500
140 120
2000
100 1500
80 60
1000
40 500
20
0
0 2016
2017
2018
2019
N. OF RECORDS
2020
2021
2022
CITED BY
Fig. 3.3 Time distribution and citations of publications (Reproduced from SCOPUS)
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Fig. 3.4 Document types and open access (Reproduced from SCOPUS)
With regard to the document type category (Fig. 3.4), it emerges that the majority of records are articles (58%), conference papers (24%), and reviews (13%). A residual number of records consist of book chapters (23 records), editorials (4 records), short surveys (2 records), and just one book that—together—cover around the 6% of the sample. It is also interesting to underline that half of the selected records are distributed free of access charges, using different open access types, namely green, gold, bronze, or hybrid options. Going deeply into the time distribution of document types and citations (Table 3.1), it emerges that the number of articles is exponentially growing in the last two years, as well as the number of reviews. These two types of records also received the greater numbers of citations (7754 and 1532, respectively), confirming that they are also the most impactful source of knowledge. On the contrary, despite the number of conference papers on the topic is increasing, its impact in terms of citation is quite weak (0.63).
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Descriptive Results of the Bibliographic Research
49
Table 3.1 Time distribution of document types and citations (Scopus) Year 2016 2017 2018 2019 2020 2021 2022 Tot. Tot. citations Impact
1 9
1 3 1 6 6 6 23 47
Conference paper 2 8 4 19 29 41 17 120 75
9,00
2,04
0,63
Article 3 3 12 20 53 95 109 295 7754
Book
26,28
1
Book chapter
Short paper
Editorial
Review
1
4 88
1 7 5 28 25 66 1532
2 253
22,00
23,21
126,50
3
1 1
Table 3.2 Top 10 journals (Scopus) Journal Sustainability (Switzerland) Journal of Cleaner Production Business Strategy and the Environment Production Planning and Control Resources, Conservation and Recycling International Journal of Production Economics Technological Forecasting and Social Change Operations Management Research Applied Sciences (Switzerland) Int. J. of Logistics Research and Applications
N. of records 44 33 12 12 10 8 8 7 5 4
Publisher MDPI Elsevier Wiley T&F Elsevier Elsevier Elsevier Springer MDPI T&F
Impact factor 3,89 11,07 10,80 6,85 13,72 11,25 13,70 7,03 2,84 5,99
With regard to journals’ articles, we analyze the top ten journals in terms of the number of records and citation (Tables 3.2 and 3.3). Many papers in the topic have been published in open access journals, like Sustainability and Applied Sciences, edited on MDPI. However, the most cited journal is Journal of Cleaner Production that counts 1360 citations. It is worth highlighting that among the top ten cited journals there are also reviews that contain few articles on the topic. This is the case of the papers published on Annals of Operations Research (Lopes de Sousa Jabbour et al. 2018) and Process Safety and Environmental Protection (Stock et al. 2018) that, alone, counts respectively 428 and 207 citations. All the journals ranking among the top ten had a high impact factor in 2021; thus, it means that the topic under study is of interest to significant editors and publishers. With regard to Review, Table 3.4 shows the most cited records. A paper written by Nascimento D.L.M. et al. in 2019 collected 285 citations.
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Table 3.3 Top 10 most cited journals (Scopus) Journal Journal of Cleaner Production Sustainability (Switzerland) Resources, Conservation and Recycling Annals of Operations Research International Journal of Production Economics Business Strategy and the Environment Production Planning and Control International Journal of Production Research Technological Forecasting and Social Change Process Safety and Environmental Protection
Cited by 1360 1103 734 430 330
N. of records 33 44 10 2 8
Publisher Elsevier MDPI Elsevier Springer Elsevier
Impact factor 11,07 3,89 13,72 4,82 11,25
317 265 224
12 12 3
Wiley T&F T&F
10,80 6,85 9,02
209
8
Elsevier
13,70
207
1
Elsevier
7,93
Table 3.4 Top 5 cited review (Scopus) Authors Nascimento D.L.M. et al.
Kerin M., Pham D.T., Sarc R. et al.
Dantas T.E. T.et al.
Wang G. et al.
Title Exploring Industry 4.0 technologies to enable circular economy practices in a manufacturing context: A business model proposal A review of emerging industry 4.0 technologies in remanufacturing Digitalisation and intelligent robotics in value chain of circular economy oriented waste management – A review How the combination of Circular Economy and Industry 4.0 can contribute towards achieving the Sustainable Development Goals Intelligent and ecological coal mining as well as clean utilization technology in China: Review and prospects
Cited by 285
Year 2019
Journal Journal of Manufacturing Technology Management
2019
Journal of Cleaner Production Waste Management
133
2021
Sustainable Production and Consumption
103
2019
International Journal of Mining Science and Technology
91
2019
124
The high number of review articles and relative citations demonstrates a great interest in the topic, despite it being relatively brand new. Looking at the conference proceedings, it appears that the topic has been particularly explored in conferences that relate to both computer science and technology and environmental sciences. The larger number of records comes from IOP Conference Series in the section “Earth and Environmental Science”: it counts 12 records with a limited number of citations.
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Co-occurrence Analysis of Recent Trend
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Table 3.5 Top 5 conference records (Scopus) Conference Name IOP Conference Series: Earth and Environmental Science IEEE Meetings, Conferences & Events Procedia CIRP Procedia Computer Science Procedia Manufacturing IFIP Advances in ICT
N. of records 12 11 11 7 7 5
Cited by 10 30 102 18 138 32
Table 3.6 Top 10 authors in terms of citations (Scopus) Bag S. Chiappetta Jabbour C.J. Lopes de Sousa Jabbour A.B. Godinho Filho M. Singh S.P. Rajput S. Sarkis J. Terzi S. Gupta S. Ferrari A.M.
Cited by 606 582 504 428 392 327 296 294 263 243
% of Articles 88% 100% 99% 100% 100% 100% 100% 92% 100% 100%
N. of records 9 10 6 1 5 4 3 9 3 6
Impact 67,3 58,2 84,0 428,0 78,4 81,8 98,7 32,7 87,7 40,5
In the same way, conference proceedings from Institute of Electrical and Electronics Engineers (IEEE) meetings, conferences, and events are comprehensively 11 with 30 citations. The most cited record in this type of document is Bressanelli et al. (2018). “The role of digital technologies to overcome Circular Economy challenges in PSS Business Models: an exploratory case study” from Procedia Cirp, which alone counts 66 citations (Table 3.5). Descriptive statistics are concluded by the analysis of authors’ productivity. Table 3.6 lists the most cited authors, their productivity, and relative impact. It emerges that the most cited author is Bag Surajit from IMT Ghaziabad, India, and the University of Johannesburg, South Africa, with 8 articles and 1 review.
3.3
Co-occurrence Analysis of Recent Trend
The last part of the analysis of the selected paper is developed with VOSviewer Software. The software (http://www.vosviewer.com) is developed to perform bibliographic coupling and co-occurrence analysis using bibliographic database files (e.g., Clarivate or Scopus), by building network of items connected in function to co-authorship, co-occurrence, citation, bibliographic coupling, or co-citation and grouped into clusters. Generally, every item may belong to only one cluster that is
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labeled using cluster numbers and colors. Each cluster shows the interconnection between one topic and another. We have inserted the Scopus bibliographic file, selecting as unit of analysis all the keywords (author and index) and the fractional counting as counting method. Moreover, we have inserted a thesaurus file to avoid misspelling and synonyms among keywords. Finally, we set up the software with a minimum number of five occurrences of a keyword (of the 3461 keywords, 36 meet the threshold). The network resulting from co-occurrence analysis is presented in Fig. 3.5, while Table 3.7 presents a summary of the items. In addition to the color, assigned by default by VOS, we give a clearer characterization to each cluster assigning a label with a name, according to the specific level of analysis in order to emphasize the features of the items contained in each cluster. The software counted for 4 different clusters: Cluster 1 “red”—containing 13 items—is in a central position in the bibliographic coupling network and the label assigned is “macro”; the second cluster (green) rather comprises 8 items and focuses on connection among topics at meso-level (label: “meso”); the third cluster (yellow) that counts 6 items has been labeled “supply chain level”; and the last cluster is the blue one that contains 7 items and labeled “micro.” Researches included in the first cluster are focused above all on the link between Industry 4.0 technologies and environmental sustainability for macro-economic
Fig. 3.5 Co-occurrence analysis (Reproduced from VOSviewer)
3.3
Co-occurrence Analysis of Recent Trend
53
Table 3.7 Clusters and items (SCOPUS) Clusters 1
Color Red
N° items 13
Cluster label Macrolevel
2
Green
8
Mesolevel
3
Yellow
6
4
Blue
7
Supply chain level Microlevel
Details items (VOSviewer) Case study, design/methodology/approach, digitalization, economic aspect, economic growth, economic system, environment, future research direction, human, industrial economics, innovation, social sustainability 3D printing, business model, cyber-physical systems, ecosystem, life-cycle analysis, production system, SDG, sustainable manufacturing Closed-loop, decision-making, manufacturing, performance assessment, supply chain, sustainable supply chain Bibliometric analysis, construction industry, digital technologies, information systems, Internet of Things, literature reviews, machine learning
perspective (keywords like economic aspect, economic growth, economic system, environment, future research direction, social sustainability). Yang et al. (2018)—for instance—in their research analyze the contribution of Industry 4.0 revolution to unlock the potential of remanufacturing for the process of bringing end-of-life products back to good as new in order to decoupling economic growth from growth in resource use (Yang et al., 2018). Still adopting a macro-economic point of view (Bhatnagar et al., 2021) focuses on the nexus between the green financing and Industry 4.0 for the efficient and environmentally resilient development of the economy for long-term economic growth. Other studies emphasize how proceeding into a more circular economy will offer benefits at economic level, enhancing the protection of raw material supply, increasing competition, promoting productivity, boosting sustainable economic growth, and creating employment. Another paper in this cluster rather analyzes the need for specific policies that drive toward digitalization of the economy. Kondratyev et al. (2022) suggest that Industry 4.0 revolution raises the need for new industrial policies, since structural changes arising in specific industries might have effects on other industries (due to complementarities) and on the whole economic system. Papers that fall into the second cluster, the “meso-level,” rather focus on the link between environmental sustainability and the Fourth Industrial Revolution from an ecosystem point of view. For instance, the paper written by Vimal et al. (2022) provides insights into industrial decision-makers and practitioners to effectively strategize the implementation of I4.0 technologies to enhance performance and complement circular economy principles. By investigating the various driving factors that underpin the adoption of I4.0 technologies in several manufacturing industries, authors employ the ecosystem lens.
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In the tourism industry, Pencarelli (2020) emphasizes the role of several players to drive toward digitalization and natural environmental protection. He highlights that tourism ecosystems and territories must take into account digital innovations, sustainability, circular economy, quality of life, and social value. Also, in the field of service management, Bullinger et al. (2017) suggest that smart services are performed in collaboration among different players, such as technology, software, and service specialists and users, considering value contributions of other actors, when defining their business models and vice versa. Researches in the third cluster focus on analyzing the effect of Industry 4.0 technologies on environmental sustainability at supply chain level. Focusing on manufacturing industry, Piyathanavong et al. (2022) demonstrate that Industry 4.0 technologies contribute to sustainable supply chain development during the COVID-19 pandemic. A literature review that classifies the dynamic changes of drivers and barriers when integrating CE and Industry 4.0 and their related applications in operations and SCM demonstrated to improve operational efficiency and sustainability performance at supply chain level is rather provided by Lu et al. (2022). Papers that belong the last cluster, the blue one, rather adopt a micro-economic focus, by analyzing specific techniques or models used to implement these technologies with ecological purposes. For instance, Delpla et al. (2022) propose a model that meets the sales and collection center (S&C) demands and maximizes total profit by indicating processing to be applied to the end-of-life (EOL) products collected (Turner et al. 2019) rather than exploring the viability of a re-distributed business model for manufacturers employing new manufacturing technologies as part of a sustainable and circular production and consumption system.
3.4
Be Digital or Be Green: An Integrative Framework
Consistent with the academic scientific literature, we thus confirm the existence of positive environmental effect of Industry 4.0 technologies. The interest in the topic is largely shown by the increasing number of publications that try to shed the light on this topic (de Sousa Jabbour et al. 2018; Stock and Seliger, 2016). The potential of digital technologies is related to solving other problems that occur at society level, such as poverty. However, existing studies are mostly focused on the positive side of the new technologies, denying that some innovations may impose unpredictable costs on society, and their transformative nature can make it difficult to anticipate their overall effect once diffused (Binder and Witt 2011). According to Bohnsack et al. (2022) in some cases digitalization may contribute to increased consumption and inequalities. Albeit the substantial improvements that such systems bring into the equation with respect to efficiency, there are also long-term environmental and social
3.4
Be Digital or Be Green: An Integrative Framework
55
impacts not intuitively related to these technologies that should be investigated further. The environmental dark side of these are all the unintended consequences of their adoption, considering all the direct (first-order consequences) and indirect effects (second-order consequences). With regard to the positive effect, it is important to underline how digital technologies help in maximizing resources efficiency. Considering energy consumption, technology like industrial Internet of Things helps optimize or replace specific (non-)digital technologies with digital more energy-efficient alternatives (Beier et al. 2018). Thanks to the smart grids, digital meters that collect data as the power utilization habits of users reduce the volatility of renewable energy systems either by flexibly adapting their energy consumption or by storing or releasing energy depending on the current availability of renewable energy in the market (Beier et al. 2018). As a result, there is a reduction in CO2 emission. Big data and analytics for example can help create a customized product to final customer, aligning firms’ resource use (Etzion and Aragon Correa 2016). Thanks to the horizontal and vertical integration present in the smart factory, the logistic activity follows the pull principle; in other words, raw materials or semi-finished production materials are sent just when it is requested, reducing the total amount of raw materials ordered (Wang et al. 2016). These positive outcomes of Industry 4.0 technology exert their effects at macro-, meso-, supply chain, and company levels. However, these effects are counterbalanced by the emerging negative sides of these technologies that may to be compared with the positive ones. The first and most discussed externality of digital technologies is the increasing level of energy consumption. Remote storage for cloud computing or the implementation of cybersecurity systems (like blockchain) would require a huge amount of energy. Thus, company would sustain higher costs for technology adoption. The indirect effect of such energy consumption is that if the source of this energy comes from fossil fuels such as oil or coal, it can procure a growing amount of CO2 emissions, also affecting the whole society. The impact of physical servers and data centers is not only related to their energy use, but buildings of huge size also have their own negative environmental impact (Parmentola et al. 2021; Lucivero 2020), causing a relevant negative effect at macrolevel. Data centers, as well as other enabling technologies like augmented reality or autonomous robots, require hardware components; it is necessary to assess the lifecycle impact of the material used. Digital devices have generally short life cycle because high obsolescence and their decommissioning may involve several hazardous materials that require specific waste recycling causing some effect at company level (increase of waste management costs) but also at societal level if not well managed. The same argumentation can be applied for battery (used for the IoT) that is not made with biodegradable materials and is hard to dispose.
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Moreover, IoT requires the increasing use of 5G network, considered an essential complementary technology able to improve the performance of IoT devices. The environmental issues associated with the implementation of 5G network will inevitably cause a large increase in energy usage among customers. In sum, the main outcomes from the analysis of the effect of Industry 4.0 paradigm on natural environment are that there are several effects that occur for each specific technology. Thus, practitioners and policy makers must identify the potentiality to reach environmental sustainability targets and—at the same time— assess the major caveats that can arise from their application (Table 3.8).
Table 3.8 Positive and negative effects of key enabling technologies on the natural environment Key enabling technologies Cloud computing
Big data and analytics
Cybersecurity
Industrial Internet of Things Simulation/augmented reality
Autonomous robots
Additive manufacturing
Horizontal and vertical systems integration
Positive effect on natural environment Reduction of physical material used, smart work allows CO2 reduction, energy saving for peripherical use Maximize resource efficiency, align resource usage with multidimensional forces of costumer behaviors, adjusting product characteristics to the willingness of customers Increase efficiency of energy grids, provide accurate info about emission and tracking the actions, enhance carbon market Resource efficiency, sustainable energy, and transparency Reduce the need to physical transportation, improve the understanding of sustainability, maximize resource efficiency (waste and energy) Waste reduction, resource efficiency (i.e., water, energy, pesticide)
Waste reduction, eco-design, pollution and CO2 reduction: reduce the weight of transported product, decentralize production closer to the point of consumption Production efficiency, material saving: energy and waste
Negative effect on natural environment Hazardous material of hardware that has short life cycle, dimensions and localization of data centers, energy consumption of remote storage Energy consumption, quantitative and qualitative impacts of data centers
Energy consumption, CO2 emission
Energy consumption, hazardous waste derived from devices, 5G network’s negative consequences Hazardous material of components, hazardous waste, high obsolescence
Energy consumption, hazardous waste (robots component materials Generally toxic and non-biodegradable), CO2 emissions of robots Additional energy and resource demands, hazardous waste, energy consumption increase due to low productivity Energy consumption, data centers, production of new devices
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Stock, T., Obenaus, M., Kunz, S., & Kohl, H. (2018). Industry 4.0 as enabler for a sustainable development: A qualitative assessment of its ecological and social potential. Process Safety and Environmental Protection, 118, 254–267. https://doi.org/10.1016/j.psep.2018.06.026 Stock, T., & Seliger, G. (2016). Opportunities of sustainable manufacturing in industry 4.0. Procedia CIRP, 40, 536–541. https://doi.org/10.1016/j.procir.2016.01.129 Tranfield, D., Denver, D., & Smart, P. (2003). Towards a methodology for developing evidenceinformed management knowledge by means of systematic review. British Journal of Management, 14, 207–222. Turner, C., Moreno, M., Mondini, L., Salonitis, K., Charnley, F., Tiwari, A., & Hutabarat, W. (2019). Sustainable production in a circular economy: A business model for re-distributed manufacturing. Sustainability, 11(16). https://doi.org/10.3390/su11164291. Vimal, K. E. K., Churi, K., & Kandasamy, J. (2022). Analysing the drivers for adoption of Industry 4.0 technologies in a functional paper – cement – sugar circular sharing network. Sustainable Production and Consumption, 31, 459–477. https://doi.org/10.1016/j.spc.2022.03.006 Wang, S., Wan, J., Li, D., & Zhang, C. (2016). Implementing smart factory of industrie 4.0: An outlook. International Journal of Distributed Sensor Networks, 12(1), 3159805. https://doi.org/ 10.1155/2016/3159805 Yang, S., Raghavendra, A., Kaminski, J., & Pepin, H. (2018). Opportunities for Industry 4.0 to Support Remanufacturing. https://doi.org/10.3390/app8071177.
Chapter 4
Unveiling the Positive and Negative Effects of Blockchain Technologies on Environmental Sustainability in Practice
4.1
Blockchain as a Disruptive Technology
The innovative scope of the Fourth Industrial Revolution is to produce a series of changes and giving rise to a turning point in the evolutionary process of the industrial system. In this scenario, blockchain as a disruptive technology plays the leading role and bases its operations following a revolutionary process in adopting solutions on concepts such as trust, responsibility, decentralization, transparency, and traceability. In a simple way, blockchain is a valuable tool for trading digital assets. As reported by Jaoude and Saade (2019), blockchain is defined as a technology that allows users belonging to the same community to validate, store, and synchronize the contents of one or more transactions within a distributed ledger. Thus, the blockchain consists of a chain of nodes, where each node comprises multiple transactions. Each node belonging to the network can be validated using cryptographic means and all the transactions contained in each node are recorded in a distributed ledger. Thanks to the cryptographic approach, it is possible to create a decentralized network of nodes, whose transactions are connected to each other and an intermediary figure in charge of controlling the operations is not required. Blockchain, therefore, defines a decentralized process in which any information or modification does not pass through a central system, but it is shared directly with all users participating in the network, according to a peer-to-peer logic. In addition to the transactions, each block contains a timestamp, such as the value of the previous block, which is associated with a random number for verifying and validating the transaction. The values attributed to each block are unique and fraud can be effectively prevented because changes made to a node tend to modify the value attributed to subsequent nodes. In fact, if the majority of the nodes in the network agree, through a consensus mechanism, on the validity of the node modification operation, the latter can be added or modified. According to Swason (2015), this mechanism is defined as: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Parmentola, I. Tutore, Industry 4.0 Technologies for Environmental Sustainability, CSR, Sustainability, Ethics & Governance, https://doi.org/10.1007/978-3-031-40010-0_4
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The process in which the majority (or in some cases all) of the participants in the network add an agreement on the operations contained within the distributed ledger.
Operations that modify or add a node to the network, once validated and the users’ consent has been exercised, can no longer be modified subsequently. Blockchain technology was initially introduced by Satoshi Nakamoto for managing the virtual currency Bitcoin. In 2008, in conjunction with the global financial crisis that led to the bankruptcy of one of the most solid investment banks in the USA: Lehman Brother, Nakamoto published the Bitcoin White Paper. The document reports for the first time the concept of cryptocurrency with Bitcoin whose functioning is ensured by the use of blockchain technology. Over the following years, the development of this technology also supported the diffusion of new systems integrated with it, such as smart contracts. Thanks to blockchain technology, smart contracts are becoming more and more popular; they are defined as contracts that are “self-managing,” which once drafted do not require a qualified figure to regulate their execution, but are “self-executed” when pre-established conditions occur. Smart contracts, therefore, allow businesses to set up automated transactions on blockchain, thus playing a fundamental role in the promotion of innovative solutions based on the use of this technology. Once the functioning of the blockchain technology has been defined, it is possible to distinguish two main types of it: public and private. This distinction assumes importance for qualifying and regulating the access of each participant to the network, defining the characteristics that lead to the management of each transaction. Both public and private blockchains are decentralized and require data and transactions to be shared between all users involved. However, some characteristics highlight a difference between the two types: • Public blockchain: transactions do not require any type of authorization and users who join can remain anonymous. • Private blockchain: participants must obtain consent to access transactions, the entry of which is monitored by a consortium of members or a single organization. Therefore, public blockchains, unlike private ones, due to the absence of authorization mechanisms, involve many participants, making the process connected to the elaboration and subsequent validation of transactions less rapid. Currently, however, the applications of blockchain technology are no longer limited to the financial sector, but over time there have been many application areas that have seen the blockchain as a solution, capable of supporting new economic sectors toward a I4.0 transition process. In this regard, Crosby et al. (2016) distinguish between financial and non-financial applications related to the use of the blockchain. However, among the non-financial application areas, this technology is suitable to meet the needs of both the public and private sectors. Atzori (2015) suggests that the whole society and the main activities carried out by public administration may be subject to a process of restructuring and simplification of bureaucratic practices through blockchain. In fact, many of the functions could become obsolete if institutions start implementing decentralized solutions. In the organizational sphere,
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Blockchain as a Disruptive Technology
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Fig. 4.1 How a blockchain works (Reproduced from World economic forum, 2016)
there are numerous applications involving the blockchain as a tool capable of revolutionizing pre-existing business models in order to create new and more efficient ones. Therefore, blockchain technology appears to be an innovative and successful solution able to revolutionize the production systems and the execution of logistics activities in the agri-food sector, in the construction and energy sectors. This will have positive repercussions in terms of sustainability and in encouraging the diffusion of circular business models. According to this vision, we are witnessing the diffusion of blockchain solutions applied not only to the financial sector, but the interest of academic research is progressively enhancing the innumerable advantages that this technology brings, and which make it a valuable tool for facilitating business activities and offering fast and innovative solutions. In this regard, companies through the implementation of this technology are able to trace their product from the origins of its components up to the moment in which it reaches the final consumer, gaining in terms of reliability and credibility (Fig. 4.1).
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Unveiling the Positive and Negative Effects of Blockchain Technologies. . .
Advantages and Disadvantages Associated with the Use of Blockchain
The blockchain represents a rapidly evolving technology, which in an increasingly rapid manner and thanks to innumerable advantages extends its areas of application toward new solutions. The high degree of transparency and trust represents the founding elements of this technology, but in addition to the high level of trust, transparency, and security in the execution of transactions, there are further advantages deriving from the application of the same technology in business activities. Some of these concern the reduction of costs due to the speed and efficiency used in the conclusion of transactions, the reduction of the workload traditionally aimed at document control, or even the verification of errors in the conclusion of transactions. It is therefore possible to summarize the most relevant advantages associated with the use of blockchain technology: • Data management security: is ensured by the cryptographic, decentralization, and consensus principles of blockchain technology but more generally of distributed ledger technologies whose data are structured in blocks and each block connects to the previous ones, creating a cryptographic chain that makes it difficult to tamper with the transactions recorded in them. For this reason, the blockchain contrasts fraudulent phenomena and activities or more generally activities that are not authorized, making it almost impossible to alter the data. The level of security varies according to the type of infrastructure adopted; for this reason, it is possible to distinguish public/permissionless and private/permissioned blockchain. In the public blockchain, access is allowed to all users, without authorization, who can freely join and obtain consent for the validation of transactions; in the private blockchain, there is a more stringent security system; in fact, access requires an identity issued through special certificates confirming membership and the right to access the resulting privileges. Thus, in the latter case, a corporate network was created, reserved only for members who have previously obtained consent to carry out and verify transactions. During the design phase, it is necessary to evaluate the type of network that best suits the needs of the individual or company, considering that private and authorized networks lend themselves to greater security controls, while public and permissionless networks are more decentralized and require less centralized control. Organizations are developing hybrid forms that best suit business needs, capable of simultaneously associating the advantages obtainable from the use of a public blockchain with those of a private blockchain. • Greater transparency: the use of blockchain technology allows transactions to be recorded equally in multiple places and is the use of a distributed ledger that allows participants to have access to the same information at the same time, ensuring a greater level of security and transparency. • Traceability: the blockchain is also particularly important regarding the traceability of products, as it offers accurate documentation about the origin and the
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Blockchain as a Disruptive Technology
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intermediate processes that the good undergoes before reaching the final consumer. This is an important element as it allows the consumer to have all the necessary information on the good he is going to buy, in an easy and detailed way, especially when there are heated debates on environmental or human rights issues. • Efficiency and speed: these two requirements are met due to the fact that compared to traditional processes, blockchain technology is not subject to human errors and does not require the intervention of third parties; transactions are concluded automatically, quickly, and efficiently. All information contained in each transaction will be automatically memorized within the network, without the need to submit paper documents. • Automation: the execution and management of transactions is regulated upstream by the existence of the smart contracts or “intelligent contracts” which, in order to improve the speed and efficiency of the entire process, perform the immediate validation of the transaction and the transition to the subsequent phases automatically upon the occurrence of pre-established contractual conditions. According to the advantages reported, blockchain technology can contribute to the achievement of the SDGs defined by the United Nations Organization on environmental sustainability and to the satisfaction of the requirements for the diffusion of circular economic models. More specifically, the blockchain offers support: for the development of energy from renewable sources (for the reduction of harmful emissions), for the reduction of waste, and for the traceability of products along the entire supply chain. To this end, the technology offers itself, thanks to its calculation capacity, as a valuable tool for controlling and tracking consumption, favoring constant monitoring with the requirement of traceability aimed at creating a cycle based on the continuous reuse of resources. In addition to the positive aspects just explained, it is also necessary to analyze the critical issues associated with the use of the blockchain: • The costs for executing transactions or more generally for accessing this technology are very high; the irreversibility of the transactions, once the connection between the network nodes has been established, will not allow the operation to be canceled. • The risks of disintermediation are connected to the adoption of blockchain solutions and the diffusion of smart contracts. Despite the adoption of such technological solutions leading to an optimization of the practices and the automatic execution of what is contained in the contracts, the risk is configured in the elimination of a central authority in charge of the control of the transactions. In fact, the implementation of smart contracts, in addition to ensuring a fully automated process, reduces human intervention and the dependence on professional figures called to verify that the contractual terms are respected (disintermediation process), • Environmental pollution caused by the intensive use of this technology can generate an increase in energy consumption with the consequent emission of a
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high quantity of CO2, which goes against the environmental goals set by the international community towards sustainable development. To sum up, we can state that blockchain, as a revolutionary technology, is bound to change the economy in the near future, ensuring economic efficiency and transparency on the one hand and playing a crucial role in the future of sustainable development on the other. For this reason, it will be necessary to offer effective solutions to mitigate the negative aspects and create a lasting balance between the advantages and disadvantages that the use of this technology produces.
4.2
Blockchain for Environmental Sustainability
Blockchain applications are being developed according to a peer-to-peer logic through which different players can exchange goods, services, or information without the need of central bodies to verify identity, validate transactions, or enforce commitments, or at least by removing the need of many intermediaries as it happens today. The first and maybe most notable application of this technology is in the development and operation of cryptocurrencies. During the last few years, blockchain has become relevant in other industries, not only in the financial services sector, such as international trade, taxation, supply chain management, business operations, and governance (Kimani et al. 2020; Polvora et al. 2020). In a recent review of blockchain studies in the management field, Centobelli et al. (2021) show that researchers have exploited the benefits of blockchain information technologies in several domains (e.g., supply chain management, security and privacy, edge computing, artificial intelligence, and consortium blockchain). The success of these technologies is in different industries since it is transversal, and it may enable gains in efficiency and lowering of costs for firms and other organizations, by allowing for faster transactions that are disseminated and synchronized digitally across a number of different but fewer parties (Davidson et al. 2016). The blockchain-based application can support transparent data sharing, help optimize business processes, provide the reduction of operating costs, and improve the collaborative efficiency. Moreover, this enabling technology can support environmental sustainability using three key underlying mechanisms relating to resource rights, product origins, and behavioral incentives (Herweijer et al. 2018; Hughes et al. 2019). In particular, thanks to the smart contracts it is possible to monitor and store data related to the activities responsible for pollution and environmental degradation and provide a real-time collection and analysis of information for more green decisionmaking (Saberi et al. 2019; Bai and Sarkis 2019). Moreover, it is demonstrated that applications based on blockchain help to drive sustainable business models, since they can foster and empower sustainability from social and environmental side (Dal Mas et al. 2020).
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Blockchain for Environmental Sustainability
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Several studies have recently shed light on the role played by blockchain technology in the achievement of Sustainable Development Goals (SDGs) developed by the United Nations. Glavanatis (2020), for instance, provided an overview, using some examples about how blockchain or DLT technologies can help to achieve each goal. Focusing on environmental related SDGs, in a recent systematic literature review on the topic, Parmentola et al. (2021) unveil seven different themes that merge blockchain and SDGs that emerged in academia. The most recurring theme is the environmental implications of blockchain on supply chain. Blockchain-based supply chains can improve the way companies do business, ensuring transparency, traceability, and security of logistic processes. The second explored thematic regards the role of BC technology in digital infrastructures. In particular, the integration of BC with technological infrastructures, such as IoT, makes it possible to track several devices and coordinate millions of them with each other, allowing significant savings for IoT industry manufacturers (Rahman et al. 2019). The third theme regards the effect of blockchain on energy. The positive effect is due to the specific peculiarity and complexity of the energy sector, where production, sale, and transmission involve different operators and affect millions of users. Through the BC it is possible to make the flow from producers (even the smaller ones) and consumers of energy automatic and traceable. Another important link between BC and SDGs is related to money. Indeed, this fourth theme regards the climate impact and air pollution due to the mining activities related to the cryptocurrencies. In this case, the effect of BC on environmental related SDGs is negative. The fifth theme that emerged from the literature review is “climate change.” Indeed, this technology can help in mitigating and adapting to climate change with its contribution to the carbon market mechanism, such as the emission trading scheme (ETS). The sixth cluster is focused on technology integration. Indeed, blockchain represents a solution to share data and make them accessible to different players in the value chain, reducing the possibility of error and corruption (Jo et al. 2019; Kumari et al. 2020). The latest cluster regards the emerging trend of using blockchain in several sectors, such as agriculture or logistics for the traceability of the resources and products. As it emerged from the study, it is important to notice that despite the aforementioned positive benefits, blockchain adopting organizations must typically deal not only with high development and implementation costs and risks but also with various technical, managerial, and ethical concerns (Bai and Sarkis 2017). Some of these concerns are specifically related to environmental and sustainability dimensions, including the amount of energy required for key algorithms, processing, and computations within the blockchain (Truby 2018; Saberi et al. 2018), and complex implementation issues, especially in implementation with wide scope.
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More specifically, there are some factors that the scientific literature considers negative impacts. Besides the cost and the energy consumption, BC has the problem of transaction speed that refers to the rate at which transfer of data happens from one account to the other. The stability of the chain requires a fixed speed of use, which is too often affected by various factors, such as block time, block size, transaction fees, and network traffic. The third problem is related to the long-term security of the systems. Technology misuse, intentional attacks on wallets, or data manipulation can affect its reliability. Finally, there also exists a political and economic risk of mining pools. Therefore, there is a need to study what are the effects of this transversal technology on sustainability in general, but specifically on environmental one. To address this issue, the following sections provide several case studies that help to understand the positive contribution—or in some case the challenges—of BC technology to environmental sustainability using the lens of UN SDGs.
4.3
The Positive and Negative Effect of BC on Environmental Related SDGs
In order to explore in a more comprehensive manner the dual effect of blockchain on environmental sustainability, we decided to focus our attention on different dimensions of environmental sustainability, using the framework of Sustainable Development Goals. We decided to concentrate our attention on eight of them that focus on environmental sustainability (see Table 1.1), namely SDGs 6 (clear water and sanitation), 7 (affordable and clean energy), 11 (sustainable cities and communities), 12 (responsible consumption and production), 13 (climate action), 14 (life below water), and 15 (life on land). Case studies allowed us to assess both the intended and the unintended consequences of BC adoption, considering the direct (first-order consequences) and indirect effects (second-order consequences). Goal 6: Clear water and sanitation Above all the basic human need for health and well-being, there is access to safe water, sanitation, and hygiene. Considering the growth of population, and the increasing needs for agriculture and industry in general, the demand for water is rising. Moreover, there are some countries where the shortness of clean water represents an important challenge. The aim of this SDGs is to achieve universal and equitable access to safe and affordable drinking water for all, improve water resources management, and facilitate cooperation among parties to reach the defined targets. Industry 4.0 enabling technologies can provide relevant tools to address the issue.
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In 2019, a new project was launched by the Freshwater Trust (TFT), a non-profit organization, with IBM Research and SweetSense Inc., a provider of low-cost satellite connected sensors. This pilot technology was designed to monitor and track groundwater use in one of the largest and most at risk aquifers in North America. In particular, the sensors transmit water extraction data to orbiting satellites and then to the BC platform of IBM and hosted in their cloud. The technology records exchanges or transactions of data and uses “smart contracts.” Final water users, such as farmers, can visualize through a web-based dashboard their use of groundwater. The disclosure of water consumption represents an important driver of the efficient use of the groundwater. The system also allows individual users the purchase of groundwater share from ones who do not require all their supply. Blockchain is also helping the water purification industry, especially regarding reusing water for industrial purposes. Genesis Research & Technology Group, a company based in Huston, Texas, is purifying the wastewater created by fracking plants, making the water usable for multiple rounds of fracking, drastically reducing waste, consumption, and cost using the blockchain. In this way, it is possible to store all its data and is even leveraging the system to mint Water Token cryptocurrency with which investors can finance these new innovations. Indeed, attaching the purity testing technology to blockchain, everyone is informed as soon as the impurity is detected, and contemporarily there is no opportunity for error to compromise the data along with the water. Everyone with the power to help understands the situation at once and can even take steps to stop or minimize the flow of contaminated water until it can be purified, or at worst, quickly warn the authorities. Blockchain allows us to share data with any stakeholders without concern for security or version control. Thus, in this field smart contract used with BC technologies can enhance the efficient use of groundwater, at the same time supporting the trade of water rights. The major odds of the right implementation of the enabling technology for this specific purpose are the creation of a network of players that collaborate to ensure equal use of the resource “water” and reduce waste. Goal 7: Affordable and clean energy The seventh goal is about ensuring access to clean and affordable energy, a key resource for the development of every business industry. The current demand for energy should be satisfied with a greater share of renewable energy in the global energy mix, in order to reduce the consumption of non-renewable sources (such as oil or coal) and the relative pollution caused by them. With this specific target, the United Nations also wants to support the enlargement of infrastructure, upgrade technology, and enhance the cooperation at every level.
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With regard to this specific SDG, the BC technology found one of its primary contributions. Indeed, energy industry has been one of the first users of the new technologies with smart contacts. One of the applications is related to the disclosure and traceability provided. Iberdrola, a Spanish utility company, have launched a pilot project based on using blockchain to guarantee, in real time, that the energy supplied and consumed is 100% renewable. Using this technology, they have been able to link plants where electricity is generated to specific points of consumption, allowing the source of the energy to be traced. This increases transparency and ultimately encourages the use of renewable energy. Secondly, distributed ledger technology has the potential to improve efficiencies for utility providers by tracking the chain of custody for grid materials. Beyond provenance tracking, blockchain offers unique solutions for renewable energy distribution. Blockchain technologies can allow an automatic and traceable way to bring together small producers and consumers of energy, with obvious benefits for both parties. Using blockchain systems for decentralized energy generation and peer-to-peer transactions can enable local solar power generators to sell power to other consumers with no or poor access to grid-based electricity with intermittent power supply and outages. Blockchain-based energy can be traded through smartphone applications enabling micropayments made by the consumer, thereby creating greater and easier access to energy. This application can also help the affordability of energy production for those people still living without access to reliable power. Therefore, the major challenge is the balance of energy consumption during the use of the technology. Goal 11: Sustainable cities and communities Considering the growing number of people that live in the cities, Goal 11 aims to make cities and human settlements inclusive, safe, resilient, and sustainable. This goal is related to the objective of providing access to safe, affordable, accessible, and sustainable transportation, housing, and basic services by safeguarding the world’s cultural and natural heritage in the cities and their neighborhood. Blockchain technologies can assist a city in becoming smarter. The city ecosystem can benefit from the use of blockchain to maximize energy efficiency and improve the management of energy resources, be used alongside IoT devices and systems for continuous real-time tracking of transportation vehicles and passengers, and assist governments in achieving effective e-administration solutions. With reference to these last points, BC improves the protection of the personal data collection and could guarantee the security, reliability, transparency, and anonymity of public consultations. In 2018 in Japan, the first smart city based on blockchain was born. In the rich city of Daymaruyu, the enabling technology is used as a virtual database that allows data sharing in a safe way. Companies in the area can share information without losing the control of data.
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Several companies have contributed to the project, by creating an open source technology, specifically designed by the Linux Foundation, which is based on specific rules that define the player that can have access to the data and approve the transactions. Fujitsu has rather created the software—Virtuora DX—that serves as a cloud that allows participants to share data and smart contract. In the area of Daymaruyu 106 skyscrapers, 4,300 offices, 40,000 restaurants, 90,000 shops, and 13 train and metro stations are located and are all interconnected. It means that all the economic information that starts from the Mitsubishi building or from the IoT sensor on the bus, regarding the products’ availability on city’s shops or hotel room availability, is shared because everything is connected. People can see all the information they need in real time. The main purpose of the project is to improve the services for the citizen and contemporarily reduce the administrative cost of the city. The systems that automatically switch on or off the city lights according to the city traffic are a good example. Blockchain technologies can help to guarantee more safety in data sharing. However, the use of BC technology to smart city transition presents several challenges. At first, the integration of different technologies and the collaboration among several different player are needed. Thus, it is important to integrate these different partners to be successful by aligning the intentions, objectives, and purposes. Moreover, it is important to address data protection, since with many interconnected systems and smart devices, the entire city can become a target for cyber criminals. Thus, it is important to recognize what data can be shared and to whom. Goal 12: Sustainable production and consumption The goal is to enhance sustainable consumption and production patterns, which is key to sustain the livelihoods of current and future generations. Blockchain technology represents an important tool to improve tracking and traceability in a specific supply chain where these two elements are considered essential, namely the agri-food sector. The use of blockchain allows supply chain visibility till the farm level, enabling upstream actors and policy makers to monitor for environmentally degrading farming activities, detect food contamination, and ease the identification and recall of the contaminated batches in the supply chain (UNDP 2021). Essentially, the benefits related to blockchain adoption in this sector are manifold: 1. Improving agricultural supply chain: traditional problems to this specific supply chain are the quality and safety of the transported goods, food traceability, and supply chain inefficiency. Through BC technologies it is possible to create authenticity certificates that allow consumers to scan QR codes of the product and get information related to it. 2. Improving food production: the combined use of BC with IoT can enhance the quantity and quantity of products from agriculture and farm activities.
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3. Improving environmental sustainability. The digital ledger, which is the basis of blockchain technology, allows building a decentralized system that protects data from corruption and cyber-attacks, helping to achieve sustainable production and distribution. 4. Improving e-commerce agriculture business. Blockchain allows easier access to the online marketplace also for small companies, can enable customers to use cryptocurrencies, and help keep e-commerce platforms secure and all the information stored on them safe. There are several companies that successfully adopt blockchain technology in the field. The dairy product brand from New Zealand—Anchor—employs blockchain to enhance supply chain transparency and traceability, building a trusted trading environment. Again, Demeter and TE-FOOD promote new smart solutions across the supply chain. The BC is also widely used in the wine industry. The technology helps to create trust and transparency between the producer and the final consumer, by controlling the wine production chain from the origin of grapes to the transformation into the bottle. In this way, the relationship among players is reinforced, creating a responsible consumption, since final customers learn more about the final product, increasing awareness of what they are drinking. Goal 13: Climate action Climate change refers to long-term shifts in temperatures and weather patterns, mainly caused by human activities, especially the burning of fossil fuels. It represents a huge and undeniable threat to the entire civilization. There are several effects—some of that already visible—linked to climate change. Actions needed to reduce human impact on climate are manifold, from recycling, composting, use of eco-friendly and reusable products, or offset carbon emissions. Thus, BC technology can help the achievement of this SDG in two ways: indirectly by improving the implementation of CE practices and directly by enhancing the reduction of carbon emissions. With reference to the first point, some companies have already implemented BC technologies to improve waste recycling. Companies that implement such technologies are contemporarily satisfying the main target defined by Goal 12 (sustainable production and consumption). A good example of BC use for this purpose is the project developed by Suez Group. The company developed circular chain, the circular economy blockchain, with the aim of combining the growing need for transparency and trust regarding the health and environmental quality of secondary raw materials. Based on a secure information storage and transfer technology, the system records all the steps needed to process wastewater treatment sludge as they occur, from production to final use (spreading on the soil, waste to energy, etc.). The technology guarantees total transparency for the sector, and the specific peculiarity of the portal allows transparent information sharing among different players involved. The technology promotes material reuse and recycling creating a true virtuous circle, also reducing the
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carbon footprint of both water treatment and agriculture and combating the depletion of organic matter in the soil. The second aim of BC technology with respect to this SDG is to reduce carbon emission thanks to its transparency and traceability: the creation and administration of carbon credits. Generally, it represents a tradable permit that allows the holder to emit a certain amount of greenhouse gases, such as carbon dioxide. To reduce their emissions, businesses and organizations can buy carbon credits, which can be traded on a market. With the use of blockchain, the carbon credit transactions can be tracked in real time and documented using a decentralized ledger. By doing so, fraud can be avoided, and the intended use of carbon credits can be guaranteed. This system can also enhance the adoption of renewable energy sources, since people and companies can buy and sell renewable energy (e.g., solar or wind power) directly from one another using a decentralized energy grid. There are several challenges linked to the effective use of technology for carbon credit transaction: first, the lack of uniform set of rules and protocols for all the stakeholders, and second, the level of scalability of the system, considering the need of a large scale to make the network work. Lastly, the massive use of BC, which means massive energy consumption, could outweigh the positive environmental advantages derived by the energy consumption necessary for blockchain transactions. Goal 14: Life below water The 14th goal is about conserving and sustainably using the oceans, seas, and marine resources since they cover 70 percent of the planet and provide food, energy, and water. Marine habitats are complex and diverse ecosystems that are an essential component of life on earth threatened by climate change, ocean acidification, overfishing, pollution, and several other causes. In the last few years, several governments, NGOs, corporations, and the tech sector are using blockchain solutions in their projects to support healthy oceans and marine life. One way to protect marine environment is to take into account seafood quantity and quality. Fish-coin project is a peer-to-peer network that aims to improve the traceability for the seafood industry, considering the high fragmentation of most seafood supply chain. It allows independent industry stakeholders to harness the power of blockchain using a shared protocol so that data can be trusted, transparent, and secure. Also, the WWF is currently using blockchain to secure data distribution in innovative conservation projects, for instance to monitor wildlife over large areas in addition to tracking the supply chain of a marine species from ocean to dinner plate. Moreover, the organization considered this technology particularly useful to establish trust in data when they are managed by the government, academia, and local environmental groups.
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However, these projects are still in their infancy. The main challenge linked with the effective use of blockchain to protect life below water is the availability of different players to employ such innovative technology. It is the players from different industries that must recognize the reciprocal advantages in investing in this technology and innovative use of it. Goal 15: Life on land This goal is related to the protection, restoration, and promotion of sustainable use of terrestrial ecosystems, sustainable management of forests, combating desertification, and halting and reversing land degradation and halting biodiversity loss. Blockchain can contribute to reach targets related to this SDG by monitoring the status of land or offering small cash payments in exchange for conserving nature. A good example of what BC can do to this target is the Open Forest Protocol (OFP), an innovative open source blockchain-based platform designed to provide smallholders, land users, non-governmental organizations (NGO), governments, and other stakeholders the capacity to measure and verify the carbon on their land so they can recoup results-based payments. The technology improves the traceability and transparency of data reforestation companies that can store and share GPS coordinates, photos, and other specific information about the forest restoration being accomplished. Through a comprehensive suite of tools, Veritree utilizes blockchain technology to provide restoration organizations with an integrated platform to support field-level data collection, site planning, inventory (tree) management, and impact monitoring, all the while delivering sponsors with a world-class experience. Thus, the company represents a platform that connects businesses with verified tree planting projects all around the world. Due to blockchain’s traceability and transparency, Veritree’s platform connects consumers directly to their trees, letting them verify the ownership and observe both the trees’ growth and environmental impact. Restoration projects have historically been very difficult to monitor, measure, and audit. At the same time, the need has never been greater for large-scale restoration projects. Veritree provides the systems to empower the world’s best restoration projects to do what they do best—make an impact. Use of blockchain creates a transparent and secure means to store information, which cannot be changed or altered. Samsung, for instance, disclosed to have planted 2,000,000 verified trees in partnership with Veritree. However, the critical issue related to this application is the communication between players from different industries that must recognize the reciprocal advantages in investing in this technology and innovative use of it.
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Conclusion
Environmental sustainability has turned to be one of the most important topics in politic agendas and stakeholder interests, calling for a new approach to manage the complex relationship between business activities and natural environment. In the last few years, companies are changing their attitude toward the natural environment starting from the idea that the adoption of environmental management strategies creates opportunities for business organizations. In other words, there is an increasing understanding that environmental sustainability can act as a driver for firms’ competitiveness. The environmental competitive advantage can be categorized into cost and differentiation advantage (López-Gamero and Molina-Azorín 2016). The first typology is linked to the internally driven tangible results that provide cost-saving opportunities (Pereira-Moliner et al. 2015) such as reduced materials requirement, efficient production process, reduced liability, and compliance cost. The second strategical alternative is related to intangible and externally driven advantage via seeking social legitimacy and reputational advantage in society (Melo and GarridoMorgado 2012; Walsh and Dodds 2017) able to potentially enhance firms’ ability to create value (Miles and Covin 2000). To catch the potentiality linked to environmental competitive advantage, technology management contributes significantly. Transition toward more environmentally sustainable strategy is successful when companies bring these innovations to serve global mainstream markets instead of local niche. In this context, the rise of new technological revolution could represent an important opportunity. Industry 4.0 is not a single technology but rather appears as a cluster of different technologies that are de facto agglomerated together by technological leaders, pivotal users, system integrators, and government policy makers. Several authors tried to classify these technologies according to their common traits (SaucedoMartinez et al. 2017) and identify the basic pillars, or building blocks, of the I4.0 framework. The foremost considered classification is the one developed by BCG that identifies nine building blocks of the Industrial Revolution: autonomous robots; simulation, horizontal and vertical system integration, the Industrial Internet of Things, cybersecurity, additive manufacturing, augmented reality, and big data and analytics. There are several positive implications of such technologies: at demand level, they improve the connection among consumers, allowing personalized experiences. Secondly, having direct access to information, Industry 4.0 technologies allow greater autonomy for workers contemporarily optimizing the production process. Industry 4.0 will be able to generate a higher industrial value in terms of sustainability. Indeed, even if the guiding principle of I4.0 is mainly focused on the increase of productivity along the entire production process and on the growth of revenues, it is
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appropriate that, in the current scenario, sustainable development becomes one of the main drivers to enable companies to be able to compete in a long-term perspective. In particular, the goal is to identify how the applications of the new industrial revolution can contribute to the creation of sustainable value, interpreted by the three dimensions: economic, social, and environmental. These dimensions, due to their nature of interdependence, often interact, overlap, and conflict, making it more difficult to achieve the SDGs. The impacts of I4.0 can be ambiguous. On the one hand, I4.0 makes it possible to reduce and monitor energy and consumption of materials and resources by reducing their use. On the other hand, constant connection and communication between the various production processes require large amounts of energy and electronic material. As noted by Stock and Seliger (2016), Industry 4.0 technologies can enable the efficient allocation of resources such as materials, energy, water, and products, by using real-time data from production systems and supply chain partners. This results in more sustainable manufacturing decisions (Stock and Seliger 2016). Indeed, the capability of Industry 4.0 tools to support environmental sustainability decisions is widely recognized, since they allow a better strategic alignment between the employed information technologies and organizational goals (de Sousa Jabbour et al. 2018). In order to address the relevance of the topic, we performed SLR using PRISMA protocol, to identify and analyze the rise and growth of theoretical discussions. Besides the descriptive analysis of sample papers extracted from scientific databases, we performed bibliographic coupling and co-occurrence analysis, to identify tendencies and communalities among different researches. VOSviewer identified four different research clusters on the topic: papers that face the problem adopting a “macro-economic perspective”; the second cluster that comprises 8 items and focuses on connection among topics at meso-level; the third has been labeled “supply chain level”; while the last group of papers focuses on organizational level effect of Industry 4.0 adoption for environmental purposes. However, since digital technologies have become pervasive, sustainability scholars also need to understand the full set of direct or indirect consequences for sustainable development. However, existing studies are mostly focused on the positive side of the new technologies, denying that some innovations may impose unpredictable costs on society, and their transformative nature can make it difficult to anticipate their overall effect once diffused (Binder and Witt 2011). According to Bohnsack et al. (2022) in some cases digitalization may contribute to increased consumption and inequalities. Albeit the substantial improvements that such systems bring into the equation with respect to efficiency, there are also long-term environmental and social impacts not intuitively related to these technologies that should be investigated further. The environmental dark side of these are all the unintended consequences of their adoption, considering all the direct (first-order consequences) and indirect effects (second-order consequences).
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Every company should be aware of these challenges and be cautious in taking decisive steps in facilitating what has been indicated as the market transition needed to address climate change (Pinkse and Kolk 2010). In this book, we tried to shed light on this topic, by focusing our attention on a specific Industry 4.0 technology, namely the blockchain. The blockchain consists of a chain of nodes, where each node comprises multiple transactions. Each node belonging to the network can be validated using cryptographic means and all the transactions contained in each node are recorded in a distributed ledger. Thanks to the cryptographic approach, it is possible to create a decentralized network of nodes, whose transactions are connected to each other and an intermediary figure in charge of controlling the operations carried out is not required. The above therefore defines a decentralized process in which any information or modification does not pass through a central system, but it is shared directly with all users participating in the network, according to a peer-to-peer logic. Considering the high degree of transparency and security in the execution of transactions, the blockchain represents a rapidly evolving technology, which in an increasingly rapid manner and thanks to the innumerable advantages extends its areas of application toward new solutions. The first and maybe most notable application of this technology is in the development and operation of cryptocurrencies. During the last few years, blockchain has become relevant in other industries, not only in the financial services sector, such as international trade, taxation, supply chain management, business operations, and governance (Kimani et al. 2020; Polvora et al. 2020). Moreover, it is demonstrated that applications based on blockchain help to drive sustainable business models, since they can foster and empower sustainability from social and environmental side (Dal Mas et al. 2020). Several studies have recently shed light on the role played by blockchain technology in the achievement of Sustainable Development Goals (SDGs) developed by the United Nations. With the aim of exploring in a more comprehensive manner the dual effect of blockchain on environmental sustainability, we decided to focus our attention on different dimensions of environmental sustainability, using the framework of Sustainable Development Goals. We decided to concentrate our attention on 8 of them that focus on environmental sustainability (see Table 1.1), namely SDGs 6 (clear water and sanitation), 7 (affordable and clean energy), 11 (sustainable cities and communities), 12 (responsible consumption and production), 13 (climate action), 14 (life below water), and 15 (life on land). Through the analysis of case studies, we tried to identify both the intended and the unintended consequences of BC adoption, considering the direct (first-order consequences) and indirect effects (second-order consequences). In Fig. 4.2, we summarize the opportunity and challenges for every SDGs derived from the implementation of BC technologies.
Offer small cash payments in exchange for conserving nature Implementation mechanisms to monitor water pollution and preserve marine resources
Offer small cash payments in exchange for conserving nature Monitor and disclosure reforestation projects
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Fig. 4.2 Opportunities and challenges of blockchain to SDGs
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Develop platforms for monitoring and exchange greenhouse gas emissions quotes Help in improving circular economy practices
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Enables tracking and tracing of supply chains and natural resource usage
Monitor energy, water consumption, waste and so on Facilitate the transition to smarter cities: smart mobility, smart energy, public administration and services Improves the protection of the personal data collected Guarantee the security, reliability, transparency and anonymity of public consultations
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Use smart contracts for renewable energy producers and consumers Monitor renewable energy production - Decentralized energy generation
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Monitor water consuption and quality Support peer-to peer trading of water rights
Collaboration between players from different industries Improve information transparency among players
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Collaboration between players from different industries Improve information transparency among players
Standard to ensure a carbon credit transactions Scalability of the technology Negative effects of energy consumption
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Require for a complementary asset to be effective Improve collaboration among supply chain players
Define a blockchain model that integrate different technologies Collaboration among several players: companies, public sector, communities Data security
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Balance energy consumption during the use of Blockchain technology
Creation of a network of players that collaborate to the objectives to ensure equal use of the resource ‘water’ and reduce waste.
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