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Digitalisation in industry – also called “Industry 4.0” – is seen by numerous actors as an opportunity to reduce the environmental impact of the industrial sector. The scientific assessments of the effects of digitalisation in industry on environmental sustainability, however, are ambivalent. This cumulative dissertation uses three empirical studies to examine the expected and observed effects of digitalisation in industry on environmental sustainability. The aim of this dissertation is to identify opportunities and risks of digitalisation at different system levels and to derive options for action in politics and industry for a more sustainable design of digitalisation in industry. I use an interdisciplinary, socio-technical approach and look at selected countries of the Global South (Study 1) and the example of China (all studies). In the first study (section 2, joint work with Marcel Matthess), I use qualitative content analysis to examine digital and industrial policies from seven different countries in Africa and Asia for expectations regarding the impact of digitalisation on sustainability and compare these with the potentials of digitalisation for sustainability in the respective country contexts. The analysis reveals that the documents express a wide range of vague expectations that relate more to positive indirect impacts of information and communication technology (ICT) use, such as improved energy efficiency and resource management, and less to negative direct impacts of ICT, such as electricity consumption through ICT. In the second study (section 3, joint work with Marcel Matthess, Grischa Beier and Bing Xue), I conduct and analyse interviews with 18 industry representatives of the electronics industry from Europe, Japan and China on digitalisation measures in supply chains using qualitative content analysis. I find that while there are positive expectations regarding the effects of digital technologies on supply chain sustainability, their actual use and observable effects are still limited. Interview partners can only provide few examples from their own companies which show that sustainability goals have already been pursued through digitalisation of the supply chain or where sustainability effects, such as resource savings, have been demonstrably achieved. In the third study (section 4, joint work with Peter Neuhäusler, Melissa Dachrodt and Marcel Matthess), I conduct an econometric panel data analysis. I examine the relationship between the degree of Industry 4.0, energy consumption and energy intensity in ten manufacturing sectors in China between 2006 and 2019. The results suggest that overall, there is no significant relationship between the degree of Industry 4.0 and energy consumption or energy intensity in manufacturing sectors in China. However, differences can be found in subgroups of sectors. I find a negative correlation of Industry 4.0 and energy intensity in highly digitalised sectors, indicating an efficiency-enhancing effect of Industry 4.0 in these sectors. On the other hand, there is a positive correlation of Industry 4.0 and energy consumption for sectors with low energy consumption, which could be explained by the fact that digitalisation, such as the automation of previously mainly labour-intensive sectors, requires energy and also induces growth effects. In the discussion section (section 6) of this dissertation, I use the classification scheme of the three levels macro, meso and micro, as well as of direct and indirect environmental effects to classify the empirical observations into opportunities and risks, for example, with regard to the probability of rebound effects of digitalisation at the three levels. I link the investigated actor perspectives (policy makers, industry representatives), statistical data and additional literature across the system levels and consider political economy aspects to suggest fields of action for more sustainable (digitalised) industries. The dissertation thus makes two overarching contributions to the academic and societal discourse. First, my three empirical studies expand the limited state of research at the interface between digitalisation in industry and sustainability, especially by considering selected countries in the Global South and the example of China. Secondly, exploring the topic through data and methods from different disciplinary contexts and taking a socio-technical point of view, enables an analysis of (path) dependencies, uncertainties, and interactions in the socio-technical system across different system levels, which have often not been sufficiently considered in previous studies. The dissertation thus aims to create a scientifically and practically relevant knowledge basis for a value-guided, sustainability-oriented design of digitalisation in industry.
Das Ziel dieser Arbeit ist die Entwicklung eines Industrie 4.0 Reifegradindex für produzierende Unternehmen (KMU und Mittelstand) mit diskreter Produktion. Die Motivation zu dieser Arbeit entstand aus dem Zögern vieler Unternehmen – insbesondere KMU und Mittelstand – bei der Transformation in Richtung Industrie 4.0. Im Rahmen einer Marktstudie konnte belegt werden, dass 86 Prozent der befragten produzierenden Unternehmen kein für ihr Unternehmen geeignetes Industrie 4.0 Reifegradmodell gefunden haben, mit dem sie ihren Status Quo bewerten und Maßnahmen für einen höheren Grad der Reife ableiten könnten. Die Bewertung bestehender Reifegradmodelle zeigte Defizite hinsichtlich der Industrie 4.0 Abdeckung, der Betrachtung der sozio-technischen Dimensionen Mensch, Technik und Organisation sowie der Betrachtung von Management und Unternehmenskultur. Basierend auf den aktuellen Industrie 4.0 Technologien und Handlungsbereichen wurde ein neues, modular aufgebautes Industrie 4.0 Reifegradmodell entwickelt, das auf einer ganzheitlichen Betrachtung aller sozio-technischen Dimensionen Mensch, Technik und Organisation sowie deren Schnittstellen basiert. Das Modell ermittelt neben dem Overall Industry 4.0 Maturity Index (OI4MI) vier weitere Indizes zur Bewertung der Industrie 4.0 Reife des Unternehmens. Das Modell wurde bei einem Unternehmen validiert und steht nun als Template für darauf aufbauende Forschungsarbeiten zur Verfügung.
Digital transformation (DT) has not only been a major challenge in recent years, it is also supposed to continue to enormously impact our society and economy in the forthcoming decade. On the one hand, digital technologies have emerged, diffusing and determining our private and professional lives. On the other hand, digital platforms have leveraged the potentials of digital technologies to provide new business models. These dynamics have a massive effect on individuals, companies, and entire ecosystems. Digital technologies and platforms have changed the way persons consume or interact with each other. Moreover, they offer companies new opportunities to conduct their business in terms of value creation (e.g., business processes), value proposition (e.g., business models), or customer interaction (e.g., communication channels), i.e., the three dimensions of DT. However, they also can become a threat for a company's competitiveness or even survival. Eventually, the emergence, diffusion, and employment of digital technologies and platforms bear the potential to transform entire markets and ecosystems.
Against this background, IS research has explored and theorized the phenomena in the context of DT in the past decade, but not to its full extent. This is not surprising, given the complexity and pervasiveness of DT, which still requires far more research to further understand DT with its interdependencies in its entirety and in greater detail, particularly through the IS perspective at the confluence of technology, economy, and society. Consequently, the IS research discipline has determined and emphasized several relevant research gaps for exploring and understanding DT, including empirical data, theories as well as knowledge of the dynamic and transformative capabilities of digital technologies and platforms for both organizations and entire industries.
Hence, this thesis aims to address these research gaps on the IS research agenda and consists of two streams. The first stream of this thesis includes four papers that investigate the impact of digital technologies on organizations. In particular, these papers study the effects of new technologies on firms (paper II.1) and their innovative capabilities (II.2), the nature and characteristics of data-driven business models (II.3), and current developments in research and practice regarding on-demand healthcare (II.4). Consequently, the papers provide novel insights on the dynamic capabilities of digital technologies along the three dimensions of DT. Furthermore, they offer companies some opportunities to systematically explore, employ, and evaluate digital technologies to modify or redesign their organizations or business models.
The second stream comprises three papers that explore and theorize the impact of digital platforms on traditional companies, markets, and the economy and society at large. At this, paper III.1 examines the implications for the business of traditional insurance companies through the emergence and diffusion of multi-sided platforms, particularly in terms of value creation, value proposition, and customer interaction. Paper III.2 approaches the platform impact more holistically and investigates how the ongoing digital transformation and "platformization" in healthcare lastingly transform value creation in the healthcare market. Paper III.3 moves on from the level of single businesses or markets to the regulatory problems that result from the platform economy for economy and society, and proposes appropriate regulatory approaches for addressing these problems. Hence, these papers bring new insights on the table about the transformative capabilities of digital platforms for incumbent companies in particular and entire ecosystems in general.
Altogether, this thesis contributes to the understanding of the impact of DT on organizations and markets through the conduction of multiple-case study analyses that are systematically reflected with the current state of the art in research. On this empirical basis, the thesis also provides conceptual models, taxonomies, and frameworks that help describing, explaining, or predicting the impact of digital technologies and digital platforms on companies, markets and the economy or society at large from an interdisciplinary viewpoint.
Traditional organizations are strongly encouraged by emerging digital customer behavior and digital competition to transform their businesses for the digital age. Incumbents are particularly exposed to the field of tension between maintaining and renewing their business model. Banking is one of the industries most affected by digitalization, with a large stream of digital innovations around Fintech. Most research contributions focus on digital innovations, such as Fintech, but there are only a few studies on the related challenges and perspectives of incumbent organizations, such as traditional banks. Against this background, this dissertation examines the specific causes, effects and solutions for traditional banks in digital transformation − an underrepresented research area so far.
The first part of the thesis examines how digitalization has changed the latent customer expectations in banking and studies the underlying technological drivers of evolving business-to-consumer (B2C) business models. Online consumer reviews are systematized to identify latent concepts of customer behavior and future decision paths as strategic digitalization effects. Furthermore, the service attribute preferences, the impact of influencing factors and the underlying customer segments are uncovered for checking accounts in a discrete choice experiment. The dissertation contributes here to customer behavior research in digital transformation, moving beyond the technology acceptance model. In addition, the dissertation systematizes value proposition types in the evolving discourse around smart products and services as key drivers of business models and market power in the platform economy.
The second part of the thesis focuses on the effects of digital transformation on the strategy development of financial service providers, which are classified along with their firm performance levels. Standard types are derived based on fuzzy-set qualitative comparative analysis (fsQCA), with facade digitalization as one typical standard type for low performing incumbent banks that lack a holistic strategic response to digital transformation. Based on this, the contradictory impact of digitalization measures on key business figures is examined for German savings banks, confirming that the shift towards digital customer interaction was not accompanied by new revenue models diminishing bank profitability. The dissertation further contributes to the discourse on digitalized work designs and the consequences for job perceptions in banking customer advisory. The threefold impact of the IT support perceived in customer interaction on the job satisfaction of customer advisors is disentangled.
In the third part of the dissertation, solutions are developed design-oriented for core action areas of digitalized business models, i.e., data and platforms. A consolidated taxonomy for data-driven business models and a future reference model for digital banking have been developed. The impact of the platform economy is demonstrated here using the example of the market entry by Bigtech. The role-based e3-value modeling is extended by meta-roles and role segments and linked to value co-creation mapping in VDML. In this way, the dissertation extends enterprise modeling research on platform ecosystems and value co-creation using the example of banking.