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The Impacts of Digital Technologies on Innovating for Sustainability

  • Sabrina SchneiderEmail author
Chapter
Part of the Palgrave Studies in Sustainable Business In Association with Future Earth book series (PSSBAFE)

Abstract

To ensure survival along the digital transformation journey, incumbent firms must rethink their ways of doing business. To understand the potential impacts of digital technologies—including artificial intelligence (AI), the Internet of things (IoT), digital manufacturing, augmented reality (AR), blockchain and digital platforms—on economic, environmental and social sustainability, this chapter offers an overview of potential benefits and challenges. Following an introduction to the technologies’ key features, their potential effects on sustainability are discussed in depth, complemented with insights from examples from practice. This balanced view of opportunities and challenges serves as a starting point to leverage these potentials when creating innovative solutions with positive impacts on sustainability along the digital transformation journey.

Introduction

Active engagement in digitalisation has become a priority for most organisations. Digitalisation refers to ‘the social transformation triggered by the mass adoption of digital technologies that generate, process and transfer information’ (Katz and Koutroumpis 2013: 314). Digital technologies have the capability to provide exact replication, infinite times at almost zero marginal cost once the required infrastructure has been established (Iansiti and Lakhani 2014). Their impacts, despite continuous uncertainty, are likely to be tremendous, and they are approaching us at an unprecedented speed (Brynjolfsson and McAfee 2015). The globally created amount of data is expected to increase from the current 25 zettabytes, 1 to more than 150 zettabytes by 2025 (Reinsel et al. 2017). Increasing global connectivity is demonstrated by more than 4 billion active Internet users and 3.3 billion social media users as of April 2018 (Statista 2018) and by a dramatic increase in global data and communication flows (Bughin et al. 2016).

To ensure survival along the digital transformation journey, incumbent firms must rethink their ways of doing business. They are experiencing both the threats of and opportunities for adaptation and innovation provided by digital technologies (Bughin and Van Zeebroeck 2017; Keen and Williams 2013; Yoo et al. 2012). In addition to economically motivated innovation potentials, digital technologies have also displayed the potential for social and environmental contributions. For instance, Ford and Despeisse (2016) recently discussed the sustainability implications of additive manufacturing, while Gauthier and Gilomen (2016) analysed how sustainable business models can contribute to energy efficiency in cities. Bohnsack et al. (2014) looked at business models for sustainable technologies in the electric vehicle field. Despite these potential benefits, the discussion of digital technologies’ impacts on sustainability remains controversial, and the question how to best leverage digital technologies to solve environmental and societal challenges remains critical (Winston 2016).

My objective here is to outline and discuss the potentials of digital technologies that firms can leverage to innovate for sustainability. The discussion follows the three key themes of strategic technology trends for 2018 identified by Gartner (2017): (1) intelligent—opportunities to leverage the potentials provided by AI and IoT, (2) digital—opportunities provided by digital manufacturing technologies such as digital twins or additive manufacturing and AR to blend digital and real worlds, and (3) mesh—opportunities in new connections of people, organisations and technologies. Following a brief introduction to the technologies, I seek to provide a balanced perspective on positive and negative influences as well as opportunities and challenges of digital technologies along the three dimensions of sustainability in hybrid organisations: economic, environmental and social impacts.

Background: Digital Technologies and Their Impacts on Business

Connectivity and recombination, rather than replacement and obsoleteness, frame the digital transformation paradigm (Iansiti and Lakhani 2014). In this environment, firms must understand how digital technologies change social interactions, so as to leverage the technologies’ far-reaching potentials for business and sustainability (Greenstein et al. 2013; Hanelt et al. 2017; Yoo et al. 2012). Gartner (2017) identified three overarching current technology theme trends as the foundation for successful business activities in the digital era: intelligent, digital and mesh. It argues that, in order to achieve competitive advantage, firms must search for opportunities along this ‘intelligent digital mesh’. The first technology trend theme, intelligent, addresses the emergence and spread of AI and its applications in analytics and intelligent things. AI refers to computers’ increasing capacities to perform activities that previously required the involvement of human intelligence (Agrawal et al. 2017; Schoenick et al. 2017). AI can process large amounts of data within shorter times than the human brain permits (Hoffman 2016). Opportunities in this theme include the replacement, augmentation and enhancement of activities and capabilities previously performed by human resources. This theme also comprises the opportunities provided by so-called intelligent things, which link IoT with AI-based analytics. IoT technologies refer to information and communication environments or networks in which objects are equipped with sensors that allow them to interact with one another (Cascio and Montealegre 2016; Dijkman et al. 2015; Lee and Lee 2015) and, potentially, to act autonomously (Gartner 2017). As a result of the increasing connectivity and interaction levels provided by IoT technologies, large amounts of data have become available. The capability to perform big data analytics to effectively use this data has become an increasingly important opportunity for firms, also for those in previously low-tech industries (Davenport 2014; Loebbecke and Picot 2015).

Digital is the second theme (Gartner 2017). It refers to blending the real and the virtual worlds in order to establish a digitally enhanced environment. This includes all forms of integration of digital technologies into manufacturing processes and workflows. Digital manufacturing refers to computer-controlled production processes such as additive manufacturing and the use of digital twins in a production process. Additive manufacturing, or 3-D printing, comprises a layer-upon-layer joining of materials to a solid object based on a digital 3-D model (ASTM 2012; Huang et al. 2013; Jiang et al. 2017). Materials that can be used for additive manufacturing include a wide range of substances, ranging from steel, plastics, cement or even wooden parts (Gibson et al. 2010; Rayna and Striukova 2016). Digital twins are virtual replicas of physical objects during the manufacturing process that can help to predict key variables and allow for rapid and inexpensive digital experiments (Knapp et al. 2017; Tao et al. 2018). Further, immersive experiences created through AR technologies are playing an increasingly important role (Porter and Heppelmann 2017). AR is about enhancing the real world with digital features, with the aim of providing new forms of environmental perceptions. AR technologies also allow users to interact with digital technologies in new forms.

Mesh summarises the third theme (Gartner 2017). Mesh is about establishing a connection between people, organisations and technologies with the objective of generating and delivering digital outcomes. Blockchain technology is central to this theme. This technology refers to a peer-to-peer network that enables and records transactions based on an open, distributed ledger (Crosby et al. 2016; Iansiti and Lakhani 2017; Tapscott and Tapscott 2017). Its potential business impacts range from its original application as the foundation of the cryptocurrency Bitcoin, to the overall digitisation of transactions (Crosby et al. 2016; Tapscott and Tapscott 2017; Zhao et al. 2016). Digital platforms are another relevant technology type that seeks to establish connections. They represent the technological foundations that enable direct communication and interactions between different groups of actors (Edelman 2015; Zhu and Furr 2016). The platform owner usually controls the platform activities and enables interactions and transactions between the producers, who create a platform offering, and the consumers, who buy or use these products and services (van Alstyne et al. 2016). Platforms are characterised by indirect network effects, since the more users either on the producer or the consumer side, the more attractive the platform is for the other side (Casadesus-Masanell and Halaburda 2014). Further, a critical mass of actors on each side is critical for a platform to be potentially successful (Evans and Schmalensee 2010).

Digital Technologies’ Potential Impacts on Sustainable Innovation

Organisations increasingly understand the importance of achieving not only economic value, but also of addressing social and environmental challenges (Rauter et al. 2017; Starik and Kanashiro 2013). Gaining a better understanding of how digital technologies can help to achieve not only economic but also social and environmental benefits is becoming increasingly relevant. Based on insights from practical examples and prior research and along the three aforementioned technology trend themes, I will discuss the potential contributions of digital technologies for sustainability and related challenges through innovation. Table 22.1 provides an overview of the discussion.
Table 22.1

Economic, social and environmental opportunities and challenges of digital technologies

Technologies

Potential benefits

Potential challenges

  

Social

Economic

Environmental

Social

Economic

Environmental

Intelligent

- Leverage AI’s potential to replace and/or augment activities and capabilities of human resources

- Create intelligent things and analytics that collect and process data, react to the information and interact with systems and/or human beings

Artificial Intelligence (AI)

Capacity of IT to perform activities that previously required human intelligence (e.g. speech recognition, problem-solving, decision-making) (Agrawal et al. 2017; Schoenick et al. 2017)

Internet of things (IoT)

Information and communication environments in which objects are equipped with sensors that allow them to communicate and interact with each other (Cascio and Montealegre 2016; Dijkman et al. 2015; Lee and Lee 2015)

Precise predictions of developments and actual needs

Customised solutions to actual needs

Real-time response to information

Efficient and comprehensive data collection

Effective data analysis, precise predictions of developments and actual needs

Real-time response to information

Transparency

Awareness

Smart allocation of resources

Potential misuse of data and manipulation

Loss of work places

Potential misuse of data and manipulation

Loss of control over AI

Rebound effect (energy and consumption)

Additional equipment required

Digital

- Blend real and virtual worlds to establish a digitally enhanced environment

- Create new forms of perceptions and interactions among people

Additive Manufacturing

3-D printing, a layer-upon-layer joining of materials to a solid object based on a digital model (ASTM 2012; Huang et al. 2013; Jiang et al. 2017)

Digital Twins

Virtual copy of physical objects during manufacturing process building on connected data tying the real and the virtual world (Tao et al. 2018)

Augmented Reality (AR)

Superimposes digital data on the physical reality (e.g. blending additional information into visual perceptions of physical reality) (Porter and Heppelmann 2017)

Local availability of products

Customized solutions to actual needs

Employment opportunities through upskilling

Reduction of production, storage and transportation costs

Cost-efficient rapid prototyping and product customization

Increase process efficiency

Enhance job attractiveness

Efficient resource usage

Increased product lifecycles

Awareness

Loss of work places

Potential misuse of data and manipulation

High costs for investments and training

Technological limitations

Dependence on technology

Potential misuse of data and manipulation

Rebound effect (energy and consumption)

Increase of scrap rate

Additional equipment required

Mesh

- Establish connections between people, organizations and technology to generate and deliver digital outcomes

Blockchain

Peer-to-peer network that enables and records transactions based on an open, distributed ledger (Crosby et al. 2016; Iansiti and Lakhani 2017; Tapscott and Tapscott 2017)

Digital Platforms

Technological foundations that enable direct communication and interactions among different groups of actors (Edelman 2015; Zhu and Furr 2016)

Global reach and access

Source of trust

Global reach and access

Source of trust

Transaction efficiencies

Potential leverage of excess capacity

Enabler of crowdfunding and collaboration

Reduced overall consumption to due sharing of goods and services, digital consumption and reduced commuting

Unregulated environment

Digital divide preventing equal access

Shortage of key resources due to economic attractiveness of sharing

Threat to labour market conditions

Unregulated environment

Potential misuse of data and manipulation

Rebound effect (energy and consumption)

Intelligent. Theme 1 refers to digital technologies’ capabilities to provide intelligent solutions and approaches based on AI and IoT technologies. From an economic perspective, these technologies help firms to generate highly accurate insights at a higher pace and to consider more data in a much more efficient way than previously possible (Moore 2016). Provided that firms are capable of analysing this information efficiently and effectively using AI’s potentials, they can make more precise predictions about future developments (Pyle and San José 2015; Watson 2017). Thus, firms can identify both cost savings and additional revenue potentials. For instance, AWhere, 2 a US-based company, leverages these technologies to provide farmers with agricultural intelligence based on real-time assessments of global weather data. Another example from the commercial context is retail stores, such as the US-based retail chain Target, which uses these technologies to locate and communicate with customers the moment they approach its stores. 3 The consumer context, particularly smart home applications, presents another prominent application of these technologies (Risteska Stojkoska and Trivodaliev 2017; World Economic Forum 2018), where they can help to align the de facto energy consumption in private homes to individual needs and preferences. However, there are economic challenges, such as the potential misuse of data or manipulation (Lindqvist and Neumann 2017). Further, since AI often represents a black box of self-learning algorithms (Davenport 2016), loss of control over algorithms represents a potential danger connected to these technologies (Hoffman 2016).

Socially, the value of more precise predictions lies in the reduction of wasted attention spent on alerts and information that recipients receive based on inaccurate or incomplete data analytics. In contrast, receiving highly targeted and timely information in combination with customised solutions to de facto needs can be highly beneficial. One example is the use of IoT technologies by Seebo, 4 a US-based firm that offers intelligent hospital beds that monitor a patient’s temperature and heart rate and alert caregivers when help is needed. However, such technologies are powerful tools to reveal very personal or confidential information that could easily be misused. Further, the increasing use of AI and IoT technologies to collect and analyse data may threaten human labour owing to increasing automation and process efficiencies (Dewhurst and Willmott 2014; Knickrehm 2018).

From an environmental perspective, AI and IoT technologies can help to increase transparency about environmental conditions. One example is Ericsson’s Connected Water initiative, 5 where connected sensors collect and communicate data in order to reduce the cost and efforts required to monitor a river’s water quality. Such transparency can be help to raise awareness for environmental developments. Further, transparency combined with intelligent analytics can allow for smart allocations of resources according to de facto needs, reducing overall resource consumption (Etzion and Aragon-Correa 2016). However, more precise information about de facto needs, leading to additional demand, new equipment requirements (such as sensors or processors) and additional energy required to measure, transfer and analyse data may—in turn—lead to a rebound effect, reducing the overall energy savings.

Digital. Theme 2 refers to the blending of the virtual and the real worlds through digital manufacturing and AR technologies. Economically, these technologies can help to reduce production, storage and transportation costs. They can also enable cost-efficient rapid prototyping and product customisation opportunities (D’Aveni 2015; Rayna and Striukova 2016). The power tool manufacturer Black + Decker 6 has reported a 10% increase in throughput owing to the implementation of digital twins into its operations. 7 One common application of additive manufacturing is the production of genuine spare parts, even many years after a certain product line was produced. Mercedes-Benz for instance uses this for its truck products. 8 The economic impacts of AR, frequently associated with smart glasses that add additional data and information to an environment, builds on AR’s capacity to increase transaction efficiencies by allowing users to act more rapidly and more accurately (Porter and Heppelmann 2017). The logistics provider DHL successfully piloted AR usage in its warehouse context and managed to improve the picking process by 25%. 9 Also, as the case has shown, integrating AR technologies into the workplace can increase a job’s attractiveness for employees. However, employees’ dependence on technological support increases, which makes a firm vulnerable in case of a technology blackout. Further, efficiency savings through digital manufacturing require high initial investment and training costs, since complex technical equipment and high expertise levels are required (Weller et al. 2015). Likewise, technological limitations concerning size and production speed must be considered, and the quality of 3-D-printed goods, particularly surface characteristics, still needs to be improved (Weller et al. 2015). Also, digital production processes could also become a target of misuse and manipulation.

Socially, additive manufacturing allows for local production of physical goods, for instance to produce required spare parts in rural areas (D’Aveni 2015). Additive manufacturing technologies also have applications in the health industry, for producing patient-friendly forms of customised medication (Wainwright 2015; Wang 2015). In 2016, US-based Aprecia Pharmaceuticals 10 offered the first FDA-approved medicine produced using additive manufacturing technology. Further, digital production technologies hold upskilling potential, i.e. workers can perform jobs they were previously underqualified for through expertise becoming embodied in products (O’Reilly 2016). Although this could help to slow down job losses as a result of automation, digital manufacturing technologies can also foster a loss of workplaces owing to increasing automation and efficiency. In addition, individuals may experience misuses of data retrieved illegally from customised digital manufacturing processes.

Environmentally, digital manufacturing processes can improve resource efficiency owing to on-demand production and reduced waste during production (Weller et al. 2015). Transportation-related emissions can be avoided by on-location production. Fast and affordable production of spare parts can further increase product lifecycles (Ford and Despeisse 2016). AR can further help to raise awareness, as displayed by After Ice, 11 an artist intervention that visualises future climate change scenarios based on NASA data. However, digital manufacturing may also create additional demand, enhancing overall consumption. Additional resources and energy are required to run digital production processes and to produce the required equipment. Further, as direct digital fabrication processes may involve less-skilled actors and potentially less-suitable materials, these processes could result in higher scrap rates than standardised mass production (Ford and Despeisse 2016).

Mesh . Theme 3 refers to the connections between people, organisations and technologies through blockchain and digital platform technologies. From an economic perspective, digital platforms expand traditional marketplaces’ geographic reaches. Digital platforms are a driver of the sharing economy concept, which enables resource sharing and the leveraging of excess capacity. Blockchain technology can further serve as an independent facilitator of transactions by making even very small transactions economically viable (Iansiti and Lakhani 2017; Tapscott and Tapscott 2017). The startup Bitbond 12 leverages this opportunity by providing global access to investment and financing opportunities through a peer-to-peer bitcoin-based lending platform for small loans. The firm has managed to create a global marketplace for more than 100,000 borrowers and lenders. Further, the technology can function as a source of trust for valuable assets and transactions owing to its reliable database of historic records (Crosby et al. 2016; Iansiti and Lakhani 2017). Despite a wide range of potential application fields, including medical data, energy generation and consumption or carbon emissions (e.g. Giungato et al. 2017; Walker 2017), both the unregulated nature of the technology’s business applications and potential misuse and manipulation of data on the blockchain as well as on digital platforms represent economic risks (Berke 2017; Iansiti and Lakhani 2017). Blockchain-based payment transaction systems have in the past allowed for illegal trading or money laundering (Foley et al. 2018).

Socially, blockchain technology can help to reduce global inequalities by providing equal access and enabling efficient micro-transactions. Also, using blockchain as a source of trusted origin potentially helps to prevent theft, trafficking and fraud. The startup Everledger 13 has built a blockchain technology-based digital ledger to track and protect the origins of diamonds. Everledger has reportedly uploaded more than one million diamonds’ digital incarnations. Digital platforms further enable engagement and sharing among platform users who may not have met without the platform and who have excess resources. Firms such as the Berlin-based social impact startup LEIHBAR 14 have further shown that digital platforms and the sharing economy concept can also be applied in the social business context. The firm seeks to strengthen sustainable consumption by offering affordable rental services of tools, kitchen utensils or leisure equipment. At the same time, negative social implications may imply a shortage of relevant resources owing to the economic attractiveness of using them as a shared good (Martin 2016). This can potentially negatively impact on urban economies or living conditions (Ricart et al. 2017). In addition to online marketplaces for goods and services, they also affect the labour market, as shown by platforms such as Amazon Mechanical Turk. 15 This platform offers an on-demand marketplace with 24/7 availability and global reach. Such an increase in global collaboration flexibility may also lead to a shift of responsibility from organisations that employ a human workforce to individual responsibility in an increasingly on-demand work context. Global sourcing opportunities may also increase pressures on local wages and salaries. Further, equal access and consideration of all actors in the blockchain or a platform is questioned by the ongoing digital divide (Toyama 2016).

Environmentally, blockchain technology can enable positive contributions, as shown by The Sun Exchange. 16 The firm facilitates a bitcoin-based global marketplace for micro-investments in fractions of solar plants in the developing world in order to enable people across the world to use solar energy. Further, since digital platforms potentially enable more flexibility concerning where and when to work, they can help to reduce the environmental impacts of commuting (Mazmanian et al. 2013). Digital platforms can also help to promote resource sharing among multiple actors. However, peer-to-peer sharing or collaborative consumption may also create additional demands (Botsman and Rogers 2010; Martin 2016). Also, the energy consumption caused by blockchain technologies—at least according to current calculation—is very high (Giungato et al. 2017). According to estimations by Digiconomist, 17 the carbon footprint of one transaction of the cryptocurrency bitcoin is estimated to be more than 116 kg of CO2 (as at 15 December 2017).

Conclusion

Digital technologies have transformative impacts on business and society. However, the paths these transformations will take are still uncertain. This chapter’s main contribution was to establish the links between specific digital technologies and their economic, social and environmental impacts. The discussion revealed a multitude of both positive and negative potential implications. Economic opportunities centre on efficiency gains and business prospects that build on new connections, while potential economic challenges include the misuse and manipulation of data, dependence on technologies, and high investment costs. The social opportunities include customised needs satisfaction and equal individual enablement, while potential social challenges include job market threats, data misuse and continuing inequalities. Environmentally, the opportunities focus on increasing transparency and awareness and reducing consumption, while the potential challenges centre on rebound effects owing to additional consumption and production caused by the availability of digital technologies. Future research should address strategies of how firms can maximise the positive implications while minimising the negative ones, along all three dimensions. Further, researchers should emphasise how these technologies can be used in combination, potentially reinforcing one another in positive ways. For managerial practice, this comprehensive overview displays the manifold innovation opportunities enabled by digital technologies for firms’ current and future business. The simultaneous transparency of economic, social and environmental implications seeks to motivate incumbents and startups to reflect on the full range of consequences when shaping their digital strategies.

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Copyright information

© The Author(s) 2019

Authors and Affiliations

  1. 1.School of Economics and ManagementInstitute of Management and Business Administration, University of KasselKasselGermany

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