Browsing by Person "Ebersberger, Bernd"

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Corporate entrepreneurship in the public sector
exploring the peculiarities of public enterprises
(2021) Tremml, Timo; Ebersberger, Bernd
Entrepreneurship is predominantly treated as a private-sector phenomenon and consequently its increasing importance in the public sector goes largely unremarked. That impedes the research field of entrepreneurship being capable of spanning multiple sectors. Accordingly, recent research calls for the study of corporate entrepreneurship (CE) as it manifests in the public sector where it can be labeled public entrepreneurship (PE). This dissertation considers government an essential entrepreneurial actor and is led by the central research question: What are the peculiarities of the public sector and how do they impact public enterprises’ entrepreneurial orientation (EO)? Accordingly, this dissertation includes three studies focusing on public enterprises. Two of the studies set the scope of this thesis by investigating a specific type of organization in a specific context—German majority-government-owned energy suppliers. These enterprises operate in a liberalized market experiencing environmental uncertainties like competitiveness and business transformation. The aims and results of the studies included in this dissertation can be summarized as follows: The systematic literature review illuminates the stimuli of and barriers to entrepreneurial activities in public enterprises and the potential outcomes of such activities discussed so far. The review reveals that research on EO has tended to focus on the private sector and consequently that barriers to and outcomes of entrepreneurial activities in the public sector remain under-researched. Building on these findings, the qualitative study focuses on the interrelated barriers affecting entrepreneurship in public enterprises and the outcomes of entrepreneurial activities being inhibited. The study adopts an explorative comparative causal mapping approach to address the above-mentioned research goal and the lack of clarity around how barriers identified in the public sphere are interrelated. Furthermore, the study bases its investigation on the different business segments of sales (competitive market) and the distribution grid (natural monopoly) to account for recent calls for fine-grained research on PE. Results were compared with prior findings in the public and private sector. That comparison indicates that the barriers revealed align with aspects discussed in prior research findings relating to both sectors. Examples include barriers associated with the external environment such as legal constraints and barriers originating from within the organization such as employee behavior linked to a value system that hampers entrepreneurial action. However, the most important finding is that a public enterprise’s supervisory board can hinder its progress, a finding running counter to those of previous private-sector research and one that underscores the widespread prejudice that the involvement of a public shareholder and its nominated board of directors has a negative effect on EO. The third study is quantitative (data collection via a questionnaire) and builds on both its predecessors to examine the little understood topic of board behavior and public enterprises’ social orientation as predictors of EO. The study’s results indicate that social orientation represses EO, whereas board strategy control (BSC) does not seem to predict EO. Regarding BSC, we find that the local government owners in our sample are less involved in BSC. The third study also examines board networking and finds its relationship with EO depends on the ownership structure of the public-sector organization. An important finding is that minority shareholders, such as majority privately-owned enterprises and hub firms, repress EO when engaging in board networking. In summary, this doctoral thesis contributes to the under-researched topic of CE in the public sector. It investigates the peculiarities of this sector by focusing on the supervisory board and social oriented activities and their impact on the enterprise’s EO in the quantitative study. The thesis addresses institutional questions regarding ownership and the last study in particular contributes to expanding resource dependence theory, and invites a nuanced perspective: The original perspective suggests that interorganizational arrangements like interfirm network ties and equity holdings reduce external resource dependency and consequently improve firm performance. The findings within this thesis expose resource delivery to potential contrary effects to extend the understanding of interorganizational action with important implications for practice.
Data-driven innovators – An empirical analysis of data-driven SMEs and start-ups
(2024) Darold, Denilton Luiz; Ebersberger, Bernd
In today's fast-paced technological landscape, the adoption of Big Data Analytics (BDA) goes beyond incremental improvements in productivity and efficiency, enabling the creation of new products, services, and even business models, known as Data-Driven Innovations (DDI). As technology evolves rapidly, reshaping industries and our daily lives, businesses must adapt to survive and innovate to thrive. Entrepreneurs, in particular, have a vast horizon of possibilities to explore through data, opening avenues for new ventures. However, the literature in the field has pointed to a lack of empirical evidence on the actual realization of these possibilities, the so-called ‘deployment gap’. Also, regarding established firms, there is a recurrent call for longitudinal analysis to understand the dynamics of BDA adoption and firm performance. Motivated by these challenges, this study employs a data-driven methodology that integrates data science techniques, like web scraping, natural language processing (NLP), and neural topic modeling (BERTopic), to provide large-scale empirical evidence on the realization of the DDI, focusing on understanding the firms behind them. The objectives range from identifying data-driven firms using website text to analyzing the determinants of adoption, firm performance dynamics, and emerging business models in startups. The study starts by focusing on German knowledge-intensive SMEs and identifying factors influencing BDA adoption, following the Technology-Organization-Environment (TOE) Framework. The findings show that larger, younger firms with international ownership are more likely to adopt BDA technologies, and this adoption is positively associated with innovation indicators such as patents and trademarks. The second study, grounded on Resource-Based-View (RBV), extends the analysis by exploring the timing of DDI deployment and its impact on firm performance over time using panel data. The results show that early adoption confers performance gains, particularly in technology-intensive sectors, but these gains tend to decrease as the technology becomes more widespread. The third study shifts the focus to the global start-up ecosystem, analyzing emerging data-driven business models (DDBMs) by examining the value propositions of start-ups across various sectors. Using neural topic modeling, the research identifies key trends and patterns in DDBMs, confirming the increasing emphasis on AI and data science as central themes. The study also tracks the evolution of these trends over time, identifying a shift towards more specialized technological areas within start-ups' value propositions. The empirical findings contribute to the broader discussion on BDA technologies, innovation, and their influence on firm performance. They offer insights not only to researchers conducting qualitative and theoretical studies but also to practitioners and policymakers involved in technology adoption and entrepreneurship. Methodologically, this work contributes to innovation studies by applying advanced data science techniques to analyze large-scale, unstructured data. These methods introduce a novel approach to uncovering patterns and insights that traditional methods may overlook, thereby advancing the study of digital innovations.
Dedicated innovation systems for local sustainability transformations in the Global South
(2022) Mendoza Barajas, Elena; Ebersberger, Bernd
As our global economic system draws closer to an irreversible breaking point, governments from both the North and South countries are called upon to reduce the environmental and social impacts of our fossil-based production and consumption patterns. From a neo-Schumpeterian view, innovation can prove instrumental in triggering such “transformational change” of our global economic system towards sustainability. This thesis posits that innovation and the largely endorsed theoretical framework of innovation system (IS) give a useful heuristic for the design of the economic policies that foster structural change. However, the promotion of the broader Sustainable Development Goals (SDG) of the 2030 Agenda requires an analytical lens that extends beyond IS technology-centric logic and adapts to respond to the variety of local contexts in both the Global North and South. An application put forward by this thesis is that of the concept of “Dedicated Innovation System (DIS)” (Pyka, A., 2017) as a revised approach to IS framework. DIS allows for the study of the often-overlooked and contextually unique qualitative dynamics that influence innovation processes in the informal and insecure institutional local contexts of developing countries. Specifically, this work focuses on DIS practical application in the Mexican local context. It builds upon the concept of “Dedicated Actors (DAs)” to examine the roles that system actors play in fostering directionality, legitimacy, and responsibility in DIS sustainability transformations. This thesis addresses the overall research question: How can Dedicated Actors (DAs) introduce a commitment to sustainability in DISs in informal and insecure institutional settings in Michoacán, Mexico? To respond to the research question, three sets of sub-questions are explored: (a) what are the characteristics of DAs that allow them to direct IS towards sustainable outcomes in informal and insecure institutional settings in Michoacán, Mexico; (b) what is the role of DAs in the building of collective capabilities in informal and insecure institutional settings in Michoacán, Mexico? and (c) what are the local capabilities that result from DIS in informal and insecure institutional settings in Michoacán, Mexico? As the focus of the thesis has been the study of innovation-led transformations towards sustainability at the local level, the research has prioritised the analysis of Dedicated Grassroots Actors (DGAs) through three practical case studies. A first research finding looks at the characteristics that define DGAs and positions them as agents of systemic change. DGAs are found to be actors that break out of the “paradox of embedded agency” because of their prior exposure to the institutional spheres that contrast local established beliefs; and that are “positively” embedded in local institutions, which allows them to circumvent existing cultural beliefs, and stretch societal norms. A second finding of this research refers to the roles of DGAs in the building of collective capabilities in informal and insecure institutional settings in Michoacán, Mexico. Three main roles have been identified: (1) conscientisation: DGAs create awareness in local people, foster critical reflection on alternatives to perceived feasible possibilities, and inspire a desire to improve their lives; (2) conciliation: DGAs play a strong role in fostering the creation of collective capabilities by enabling linkages between individual needs with wider sustainability communal goals, and coordinating community participation and active voice, as well as facilitating knowledge exchange and skills acquisition; (3) collaboration: DGAs have an active role in facilitating collaboration with regional and external actors. A third research finding relates to the creation of collective capabilities in informal and insecure settings in Michoacán, Mexico. It was observed that a general sense of collective injustice within these institutional settings encourages local communities to adopt collective strategies to resist injustices caused by external conditions. The local communities from the case studies, tended to develop resilience capabilities to face poverty traps, violence, and a lack of social mobilisation. Although the creation of collective capabilities was initially triggered by issues related to economic and social factors (that are generally viewed and valued as high priorities in insecure and informal settings), these capabilities have also served to address other environmental challenges affecting local communities (e.g. climate change, biodiversity loss, deforestation, etc.).
Flooding the landscape of knowledge: perspectives on transitions to artificial intelligence in industry
(2024) Dahlke, Johannes; Ebersberger, Bernd
The progress in artificial intelligence (AI) technology is advancing at an unprecedented pace and its applications increasingly impact economic actors and society at large. As the world enters the fourth industrial revolution, the integration of AI technology into industries promises to become a crucial determinant of economic performance and qualitative change within the economy. It also requires to discuss the roles of humans and machines in the process of value creation. Against this backdrop, this doctoral dissertation investigates the current state and dynamics of AI transitions, with a pronounced focus on industrial regimes. It comprises three empirical studies, each depicting different levels of industrial transitions towards AI—moving from a consideration of micro-level technological niches, to meso-level industrial structures, to macro-level landscape trends. This dissertation contributes to our understanding of socio-technical transitions towards AI by showing that sustainable and just transitions towards AI-based industrial regimes require not only consideration of the technological characteristics, but also the sociomaterial context governing its integration, as well as reversely being altered by the diffusion of the technology itself. The work provides further insights for policymakers, practitioners, and researchers as it emphasizes the need for network-based analyses of complex diffusion dynamics within industries, and the need to integrate systemic socio-economic perspectives into extant concepts of responsible AI.
Sustainability-oriented macro trends and innovation types - Exploring different organization types tackling the global sustainability megatrend
(2021) Gaudig, Anja; Ebersberger, Bernd; Kuckertz, Andreas
The prevailing environmental and social challenges worldwide require comprehensive and sustainability-oriented changes in central areas of society—endeavors that call for more sustainability-oriented innovations. Sustainability can be understood as a megatrend within our society comprising sustainability-oriented macro trends such as Agricultural Innovation, Circular Economy, or Clean Tech. In line with this conceptualization, the current paper analyzes to what extent different types of organizations, such as startups and established companies, have been tackling sustainability-oriented macro trends and how much they have been focusing on sustainability-oriented innovation activities within their organization types. For the study, 758 organizations from the Trendexplorer database were examined through univariate and bivariate analyses. The results underscore that sustainability can be perceived as a key driver of structural change by illustrating that different organization types focus on multiple yet diverse sustainability-oriented macro trends simultaneously while concentrating on a specific type of innovation, whereby all three types of innovations (technological, marketing, and product and service innovations) can be integrated.
Web-based idea management systems – an investigation into better idea quality
(2023) Lehmann, Selina; Ebersberger, Bernd
Unternehmen nutzen webbasierte Ideenmanagementsysteme, um Ideen für neue Produkte, Dienstleistungen oder Prozesse von internen beziehungsweise externen Nutzergruppen zu erhalten. Im Durchschnitt wird nur jede fünfte Idee aus diesen Systemen umgesetzt. Dies zeigt, dass Firmen vor der Herausforderung stehen, qualitativ hochwertige Ideen zu erhalten. Nach dem Prinzip ‚Quantität fördert die Qualität der Ideen‘ haben viele Unternehmen lange Zeit die Generierung von vielen Ideen vorangetrieben. Dieser Ansatz spiegelt sich auch in zahlreichen Studien zum digitalen Ideenmanagement wider, in denen die Anzahl der generierten Ideen als Maßstab für den Erfolg oder die Qualität der Ideenfindung herangezogen wurde. Firmen haben mittlerweile erkannt, dass dieser Ansatz im Konflikt mit ihrer Absorptionsfähigkeit steht. Dieses Problem hat auch die Wissenschaft erreicht und Studien beschäftigen sich zunehmend mit der Frage, was ferner die Entstehung guter Ideen beeinflusst. Viele Themen zur Verbesserung der Ideenqualität sind bis dato unerforscht. Diese Dissertation schließt zentrale Forschungslücken, indem sie untersucht, welche Mechanismen (neben der Generierung großer Ideenmengen) einen Einfluss auf die Qualität von Ideen in webbasierten Systemen haben. Die kumulative Dissertation beinhaltet vier verschiedene Forschungsthemen in vier Forschungsartikeln, die unter dem zentralen Thema ‚Bessere Ideenqualität‘ miteinander verbunden sind. Die Artikel befassen sich mit (I) dem Zusammenhang extremer Erfolgserlebnisse von Ideengebern und deren zukünftigen Innovationsleistungen, (II) dem Effekt der Teamgröße auf die Ideenqualität, (III) Ideenmerkmalen und deren Auswirkungen auf den Ideenerfolg sowie (IV) dem Einfluss von Feedback auf die Qualität zukünftiger Ideen. Bei dem ersten Artikel handelt es sich um eine in Koautorenschaft erstellte quantitative Studie, deren Thema aus unschlüssigen Ergebnissen früherer Forschungen hervorgeht. Studie I geht von der Annahme aus, dass Erfolg im Ideenmanagement in Stufen auftritt, da monetäre Belohnungen für erfolgreiche Ideen variieren können. Mit anderen Worten: Wir gehen davon aus, dass die Erfahrung extremer Erfolge im Ideenmanagement zu ‚Overtrading‘ führt (d.h. zu Verhaltenszwängen, die von extremen Erlösen aus dem Handel mit Aktien an der Börse bekannt sind), was wiederum die Qualität der Ideen verringert. Wir testen unsere Hypothesen in einem Mediationsmodell mit 1.145 Ideen aus einem internen Ideenmanagementsystem. Unsere Ergebnisse zeigen, dass extreme Erfolge zu ‚übermäßigem Selbstvertrauen‘ und ‚Bestätigungsfehlern‘ (hohe Gewissheit über das eigene Denken) führen. Dies wiederum führt zu einer geringeren Innovationsleistung. Aus der Studie ergeben sich wichtige Implikationen zum Einsatz von monetären Belohnungen im Ideenmanagement—einem strategischen Instrument mit langer Tradition, um Mitarbeiter als Ideengeber zu gewinnen und zu motivieren. Der zweite Artikel beruht auf einem quantitativen Ansatz und ist in Alleinautorenschaft entstanden. In Studie II wird eine mögliche Ursache für frühere unschlüssige Ergebnisse zu der Größe von Ideenteams und der Ideenqualität untersucht. Anhand von 12.388 Ideen aus einem internen Ideenmanagementsystem wird untersucht, wie sich die Teamgröße auf zwei Messgrößen der Ideenqualität (die Umsetzungsentscheidung und die Einsparung) auswirkt. Die Ergebnisse der Heckman-Analyse zeigen eine umgekehrte U-förmige Beziehung zwischen der Teamgröße und beiden Messgrößen (Wendepunkt bei drei Teammitgliedern). Die Forschung liefert wichtige Erkenntnisse über die richtige Größe von Ideenteams für erfolgreiche Ideen. Der dritte Artikel ist eine in Mehrautorenschaft verfasste quantitative Studie, deren Thema zu Ideenmerkmalen aus früheren widersprüchlichen Forschungsergebnissen hervorgeht. Wir zeigen, dass Ideen in drei Phasen bewertet werden und dass die Intensität der Auseinandersetzung mit einer Idee phasenabhängig ist. Wir stützen uns auf das Elaborations-Wahrscheinlichkeits-Modell, das besagt, dass Informationen über zwei Wege verarbeitet werden: den zentralen Weg (tiefe Verarbeitung über zentrale Hinweise) und den peripheren Weg (oberflächliche Verarbeitung über Heuristiken). Wir nehmen an, dass Unsicherheit in der frühen Bewertungsphase die Elaboration von Ideen über den peripheren Weg vorantreibt, während der zentrale Weg in den späteren Phasen dominiert, wenn zusätzliche Informationen die Unsicherheit der Ideenbewerter verringern. Unsere Ergebnisse, die auf OLS-Regressionen mit 558 Mitarbeiterideen beruhen, bestätigen unsere Annahmen. Studie III liefert neue Erkenntnisse zu Merkmalen erfolgreicher Ideen. Der vierte Artikel, eine in Koautorenschaft erstellte Mixed-Methods-Studie, befasst sich mit der Rolle des Feedbacks (Charakteristika, Leserlichkeit und Zeitpunkt) und der Qualität zukünftiger Ideen. Wir stützen uns in Studie IV auf die Feedback-Interventionstheorie. Mithilfe einer qualitativen Inhaltsanalyse zu firmeninternen Ideendaten identifizieren wir drei Feedbackcharakteristika: Erfolgsfeedback sowie Misserfolgsfeedback, das sich inhaltlich auf den Einreicher oder auf die Idee selbst bezieht. Die Ergebnisse der anschließenden Probit-Regression mit 1.143 Mitarbeiterideen und die Ergebnisse aus einem Online-Experiment zeigen, dass Erfolgsfeedback und Misserfolgsfeedback, das auf die Idee bezogen und konstruktiv ist, die Qualität zukünftiger Ideen erhöhen. Misserfolgsfeedback, das sich auf den Einreicher bezieht, zeigt einen gegenteiligen Effekt. Feedback, das schlecht lesbar ist, schwächt die positive Wirkung von ideenbezogenem Misserfolgsfeedback. Feedback ist daher ein wichtiges strategisches Element, das die Ideenqualität in Ideenmanagementsystemen beeinflusst. Im Allgemeinen leistet diese Dissertation einen wichtigen Beitrag zur Literatur über die Qualität von Ideen in (internen) webbasierten Ideenmanagementsystemen. Sie macht deutlich, dass Unternehmen einen Stellhebel haben, um die Entstehung guter Ideen zu beeinflussen.