Weekly Science Selections: AI-driven Innovation & NeuroentrepreneurshipWeekly Science Selections

Jan Spruijt

Every week, this section contains newly published scientific articles in the field of innovation & entrepreneurship. This section contains the #EditorsChoice and a list of articles grouped into #MustReads, #ShouldReads and #CouldReads. Subscribe to our newsletter to receive these in your inbox.

Permutated feature importance for the top 20 predictors (Heideman et al, 2024)
  • #MustRead: Complex Problem Solving as a Source of Competitive Advantage (Veríssimo et al, 2024): The study emphasizes the increasing importance of problem-solving skills in today’s complex business environment. Solving complex problems is identified as a crucial skill that can enhance organizational success and competitiveness. Understanding the value of problem-solving and incorporating it into organizational strategy is essential for achieving sustainable competitive advantage in today’s dynamic business landscape.
  • #MustRead: Heterogeneous university funding programs and regional firm innovation: An empirical analysis of the German Excellence Initiative (Krieger, 2024) In a revealing study, researchers unveil the hidden power of university funding in driving regional innovation. Their findings reveal that targeted investment in Excellence Clusters turbocharges firms’ ability to innovate, particularly in regions with a robust cluster presence. However, the impact of Graduate Schools or University Strategies remains underwhelming. This discovery underscores the pivotal role of strategic funding in shaping the innovation landscape, sparking vital discussions on optimizing investment strategies to supercharge regional growth.
Geographical distribution Excellence Cluster funding across regions. (Krieger, 2024)
  • #MustRead: Neuroentrepreneurship: state of the art and future lines of work (Juarez-Varón, Zuluaga & Recuerda, 2024) Neuroentrepreneurship, a field at the intersection of neuroscience and entrepreneurship, has gained traction since 2009, illuminating how brain function influences business decisions. Despite a growing body of literature, a unified understanding of the field remains elusive. This paper addresses this gap by examining key themes in neuroentrepreneurship literature and refining definitions to provide clarity. Understanding the neural mechanisms behind entrepreneurial behavior offers practical insights for decision-making and opportunity recognition. By leveraging biometric techniques like EEG and GSR, entrepreneurs can gain a deeper understanding of risk perception and response. This review not only consolidates existing knowledge but also provides a framework for future research and practical applications in enhancing entrepreneurial decision-making processes.
  • #ShouldRead: Middle Managers’ Relational Dynamics in the Context of Acquisitions: Balancing Strategic Interdependence and Organizational Autonomy (Birollo, Rouleau & Wolf, 2024): Mergers and acquisitions (M&A) pose a challenge in balancing the need for strategic interdependence with the preservation of organizational autonomy. Middle managers (MMs) are identified as key players in this balancing act. Intersubjectivity refers to the mutual understanding and shared meaning that arises between individuals through interaction, enabling effective communication and collaboration. In mergers, intersubjectivity is crucial as it facilitates middle managers’ ability to navigate complex integration tasks by considering the perspectives and goals of both acquiring and acquired organizations, fostering smoother transitions and alignment of objectives. Similarly, in innovation, intersubjectivity fosters a collaborative environment where diverse perspectives and insights can converge, leading to the co-creation of novel solutions and the maximization of creative potential within teams and across organizational boundaries.Figure 2: A process model of actionable intersubjectivity as a crucial ability for balancing strategic interdependance and organizational autonomy (Birollo et al, 2024)
  • #ShouldRead: Age and entrepreneurship: Mapping the scientific coverage and future research directions (Syed et al, 2024) Research interest in understanding the relationship between age and entrepreneurship has surged in recent years, driven by the recognition of age as a significant factor influencing entrepreneurial behavior and career decisions. Various studies have explored the motivational factors shaping self-employment decisions, revealing age’s nuanced impact on entrepreneurial intentions and actions. While younger individuals may exhibit greater enthusiasm for entrepreneurship due to their ambitious nature and future income potential, older individuals leverage their extensive experience and social capital to navigate entrepreneurial ventures successfully. However, age-related preferences, influenced by factors such as cultural views and opportunity costs, also play a role in shaping entrepreneurial pursuits.
  • #ShouldRead: The Double-Edged Sword of Exemplar Similarity (Majzoubi et al, 2024) Ever wondered how your firm’s image relative to industry leaders affects investor perception? New research spills the beans! Aligning with category exemplars boosts your firm’s visibility and initial screening success. But beware: it also triggers comparisons that might not always work in your favor. The key? Understanding your industry’s landscape and positioning strategically. Dive into the study for practical insights to finesse your firm’s approach and ace those investor evaluations!
  • #CouldRead: Evaluating the impact of individual and country-level institutional factors on subjective well-being among entrepreneurs (Gashi et al, 2024): This study explores the relationship between subjective well-being (SWB) and entrepreneurship. Stimuli of well-being are: fostering political stability, reducing bureaucratic hurdles, and promoting economic prosperity to support entrepreneurial ventures and enhance overall satisfaction. The study also offers practical suggestions for entrepreneurs to improve their well-being, such as self-care, meaningful engagement, building strong support networks, prioritizing health, and finding purpose in their work.
  • #CouldRead: Financial stress and quit intention: the mediating role of entrepreneurs’ affective commitment (Kleine, Schmitt & Wisse, 2024) This paper delves into how financial stress impacts entrepreneurs’ desire to quit their businesses, focusing on the emotional connection entrepreneurs have with their ventures. The findings suggest that when entrepreneurs face financial stress, they’re more likely to consider quitting, especially when their emotional attachment to the business decreases. Essentially, the stronger the emotional bond with their venture, the more likely they are to persist through tough times. These insights can guide consultants and decision-makers to support entrepreneurs effectively. For instance, if a business has potential, efforts to boost the entrepreneur’s emotional commitment could increase motivation to overcome challenges. Conversely, if closure seems inevitable, strategies to help entrepreneurs emotionally detach from the business may prevent further losses. Overall, understanding and addressing entrepreneurs’ emotional ties to their ventures can inform practical strategies to navigate financial difficulties and plan for the future effectively.

Chris Freeman: the entrepreneur who created the concept of ‘innovation studies’

Jan Spruijt

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After our deepdive into the story of Ted Levitt last week, we’ll dive into the extraordinary story of Christopher Freeman (1921 – 2010) this week. By many renowned for his substantial conributions to the academic field of innovation, and as such named a ‘social sciences entrepreneur’ (Fagerberg, Fosaas, Bell and Martin, 2011), Chris Freeman was an expert at the intersection of economics and innovation. His legacy included many ‘firsts’, such as being the first director of SPRU – the Science Policy Research Unit at the University of Sussex -, the first Frascati manual (1962), the first studying ‘technology gaps’ (1960s), the first editor of Research Policy and the author of the first textbook on innovation, ‘The Economics of Industrial Innovation’. His contributions to theory also included works on Industrial Waves and Disruption, National Innovation Systems and The Economics of Change. Freeman had a significant contribution to schumpetarian thinking about disruption.

Christopher Freeman (Fagerberg et al, 2010)

Background

Christopher Freeman was born in Sheffield in the United Kingdom. He was raised with liberal ideas: his father Arnold worked for the Webb’s whose ‘Fabian Society’ shaped reformist-socialist left-wing views on democracy. His father later on pioneered with ‘Workers’ Educational Association’ and as such also heavily impacted his son’s radical ideas. Christopher Freeman “was educated at the progressive Abbotsholme School in Staffordshire, where he founded a cell of the Young Communist League” (Independent, 2010). He started studying at the London School of Economics (LSE) in 1941, continued in Cambridge to study economics, which he interrupted to join the Royal Military Academy, after which he returned to LSE to graduate in 1948. At LSE he was part of an extraordinary cohort, which included Norman MacKenzie, Claus and Mary Moser and Marion Stern, the mother of Nicholas Stern, an economist and well-known ambassador of taking early action on climate change. Nicholas later said that his passion was largely due to the discussions that he had been part of when his parents, Freeman and other classmates in his early childhood (Stern, 2017). This also forms the main line in Freeman’s career: on the one hand he followed the line of thinking of Schumpeter, popularizing Schumpeter’s – now widely accepted – idea of creative destruction and the fact that there no boundaries to growth, and on the other hand a critical acclaim to capitalism, claiming that a more institutional approach to innovation systems – an approach that is now classified as neo-schumpeterian economics, which takes ingredients from different economic schools such as the austrian school, lausanne school and keynesiasism.


His ideas and early career expertise on innovation policy, led to one of his most famous contributions to the academic world: the notion of innovation systems, and later on also his work on national systems of innovation (Guardian, 2010). He also argued that science plays an important role in establishing industries, much in line with Bernal’s work on the science-based industry and science policies (Fagerberg et al, 2010). As such, he is widely recognized for being ‘an entrepreneur’ in science, developing innovation science as a separate field of study alongside economics, management and entrepreneurship – which led to him being the first director of SPRU – the Science Policy Research Unit at the University of Sussex. As an academic he supervised many scholars, wrote many articles and books and as such had a lasting impact on the science, economics and industry of innovation.

Key Ideas

  • The Economics of Industrial Innovation: Freeman adopted a dynamic perspective on capitalism, heavily influenced by Marx and Schumpeter. He viewed capitalism as a system characterized by continuous interaction between technological progress, capital accumulation, and social and institutional conditions. Drawing from that, Freeman emphasized the role of technological competition between firms as a driving force behind capitalist development. He focused on understanding the dynamics of technological change within firms and its implications for economic growth and competitiveness. Freeman argued that traditional economic theories often failed to adequately account for the role of research and development (R&D) in driving technological progress and economic development. He highlighted the importance of R&D activities within firms and advocated for policies and management strategies that promote innovation.
  • National Innovation Systems: Freeman, together with i.e. Lundvall, was instrumental in developing the concept of national innovation systems, which emphasizes the interconnectedness of various actors, institutions, and policies within a country that contribute to innovation and economic development. He advocated for a holistic approach to understanding innovation processes, beyond the traditional focus on individual firms or sectors. He emphasized the role of institutions, including government policies, research organizations, universities, and industry associations, in shaping national innovation systems. He argued that effective innovation policies require a deep understanding of the institutional framework within which innovation occurs (Freeman, 1995). In his own words:

“Sectoral systems, regional systems are all very constructive and helpful. (…) You can point to the success of Pakistan in medical instruments or Brazil in boots or shoes or whatever (…) and if you point out the role of innovation in all those micro level studies, that’s very useful. And if you point out certain regions of countries are more innovative, and the north of Italy has contributed more to the growth of the country than Sicily, that’s all very useful. But I don’t think you’ll change the main paradigm of neoclassical economics, I think you have to attack it head on in the centre (…) Most of the people working on innovation systems prefer to work at the micro-level. They are a bit frightened still of the strength of the neoclassical paradigm at the macroeconomic level. But I think that’s where they have to work. You have to have an attack on the central core of macroeconomic theory. It is happening but not happening enough.” (Unpublished interview with Sharif, 2003)

Impact

  • Public impact: Freeman highlighted the importance of knowledge diffusion and learning mechanisms within national innovation systems. He emphasized the role of networks, collaborations, and knowledge spillovers in facilitating innovation and technology transfer. Freeman’s work on national innovation systems had significant policy implications. He advocated for policies that promote collaboration between government, industry, and academia, as well as investments in education, research infrastructure, and technology transfer mechanisms. His ideas contributed to the design of innovation policies aimed at enhancing the competitiveness and resilience of national economies (Fagerberg et al, 2011).
  • Industrial impact: Freeman emphasized the importance of fostering a culture of innovation within industries. He highlighted the role of research and development (R&D) activities, technological competition, and dynamic interactions between firms in driving innovation. By advocating for policies and management strategies that support innovation, Freeman encouraged industry leaders to prioritize investments in R&D, technology development, and knowledge creation.
  • Academic Impact: Under his leadership, SPRU became a global center for innovation research, attracting scholars, policymakers, and industry practitioners from around the world. This collaborative environment facilitated knowledge exchange, interdisciplinary research, and the co-creation of innovative solutions to industry challenges.

Key take-aways

  1. Cross-Disciplinary Collaboration: Embrace collaborative efforts across disciplines to gain comprehensive insights into innovation dynamics.
  2. Emphasize a Systems Approach: Consider the historical, economic, and systemic dimensions of innovation to develop a nuanced understanding of its complexities.
  3. Tap into the Academic Community: Foster an inclusive academic environment that encourages knowledge exchange and inspires new avenues of inquiry in innovation studies.
  4. Explore Macro-Level Analysis: Delve into macroeconomic perspectives to discern broader implications of innovation on national and regional innovation ecosystems.
Unleashing Innovation: Strategic Simulation Games as a solution to the use of AI and ChatGPT in Business Education

Unleashing Innovation: Strategic Simulation Games as a solution to the use of AI and ChatGPT in Business Education

Alwin Maes

In the world of business education, the usage of AI and ChatGPT has severe impact. Not only does it open doors for new ways of learning, it also threatens traditional learning methods, activities and deliverables – and forces educators to update curricula in a fast pace. As became apparent over the last few years, strategic simulation games are immersive learning experiences that go hand-in-hand with the rise of the usage AI and ChatGPT in education. As a premium partner of Innovative Dutch, who is developing and running strategic simulation games in universities worldwide, we’ve experienced during the last year that there are many benefits arising from using strategic simulation games in education, knowing that students will move to AI to ask for help. Interested in learning more about the simulation games of Innovative Dutch? Check their website for the Innovation Management Game and the Business Model Game. Their games are played in over 25 countries by 10K+ students annually.

Here are nine advantages of leveraging strategic simulation games enhanced by AI in business education:

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Regenerative Innovation Process Through Systems Thinking [Infographic]

Regenerative Innovation Process Through Systems Thinking [Infographic]

Jan Spruijt

About a month ago, Kasper Benjamin Reimer Bjørkskov, posted a message on LinkedIn that contained an impressive methodology to look at regenerative systems thinking. The idea sparked my mind and I gave it a lot of thinking during the last few weeks. And, although I explicitly do acknolwedge the strength and simplicity of the model that was proposed, I believe from a theoretical perspective, it could be improved a bit. Let me first paraphrase the initial post and infographic:

🌍 Regenerative System Thinking:
Bridging the Gap Between Intent and Action 🌱

While technology is a powerful tool in our fight against the climate crisis, it alone can’t drive the change we need. We’ve done well in raising awareness about sustainability, but there’s a gap between understanding and action. It’s time to bridge that gap! To truly combat the climate crisis, we must intertwine the realms of technology, humanities, and social sciences. After all, the root of the crisis lies in human behavior. Only by altering our behaviors can we hope to find a solution. 🔗 By merging the insights from social and natural sciences, we can ensure that knowledge isn’t just acquired but acted upon. The current system often makes the effort seem greater than the reward, creating an intention-action gap. But through systemic design, we can offer a holistic understanding of societal and ecological needs. To Translate complex, real world challenges into solutions that creates positive social and  environmental impact, for all, we need regenerative system thinking.

Regenerative System Thinking. 6-step approach to Regenerative System Thinking:

1️⃣ Empathize & Observe:
1A: Empathize: Engage deeply with people to understand their perspectives and identify the barriers they face.
1B: Observe: Delve into the system’s intricacies to comprehend its functioning and dynamics.

2️⃣ Define & Explain:
2ADefine: Pinpoint the specific challenges and problems faced by individuals.
2B:Explain: Grasp and articulate how the system operates, shedding light on the root causes of the problems.

3️⃣ Ideate: Brainstorm innovative solutions that cater to both human needs and the planet’s well-being.

4️⃣ Design: Craft comprehensive strategies and solutions that serve both humanity and our environment.

5️⃣ Prototype: Develop tangible prototypes to test and refine ideas. Remember, action often brings clarity and deeper understanding.

6️⃣ Evaluate: Rigorously assess the impact of the solutions on both the system and its people, ensuring alignment with our regenerative goals.
Together, let’s turn understanding into impactful action. 🌟🌍 #RegenerativeThinking#ClimateActionNow

https://www.linkedin.com/posts/kasper-benjamin-reimer-bj%C3%B8rkskov-660a4899_regenerativethinking-climateactionnow-activity-7117382272009269248-2JEU?utm_source=share&utm_medium=member_desktop

Turning a social model into a hybrid model

  1. My primary feedback pertains to the model’s reliance on a 2P basis, whereas the literature suggests that a 3P basis might lead to more effective outcomes. The Triple P framework is often referred to as People, Planet, Profit, though the latter may be replaced by Progress to encompass a broader perspective on social innovation. Please refer to sources such as Dwivedi & Weerawardena (2018), McMullen & Warnick (2016), Weerawardena et al. (2021), and Saebi et al. (2019).
  2. Another change in perspective is that systems thinking should not be limited to the Planet aspect of innovation. To exclude consideration of people and progress from systems thinking, in my opinion, would not constitute true systems thinking. I believe that the combination of these two (or three) processes could be referred to as systems thinking. You can find further insights in sources like Spender et al. (2017), Shepherd et al. (2015), and Rossignoli et al. (2018).
  3. Lastly, the iteration of processes outlined in the initial model does not align with existing literature and practical execution of innovation. You can reference works such as Crossan & Apaydin (2010), Barney & Felin (2013), Miron-Spektor et al. (2018), Bryan et al. (2021), Gans et al. (2019), and Landry et al. (2002) for a more accurate representation of how innovation is typically executed.

Therefore, I’ve designed a new infographic that more closely resembles regenerative innovation processes using systems thinking. In the dynamic landscape of innovation, the pursuit of regenerative progress stands for merging sustainability, profit, and human-centric principles into viable offerings. In this innovative model, three distinct but interwoven processes unfold in parallel, converging at Step 3 to craft a regenerative future that harmonizes the planet, progress, and people. This model encapsulates the essence of responsible leadership, ambidextrous leadership, and creative leadership, each playing a pivotal role in shaping regenerative innovation.

  1. Responsible Leadership (Planet) requires innovators to study the root causes of environmental and societal challenges, recognizing that regeneration begins with a deep understanding of the issues at hand. At Step 3A, leaders collaboratively formulate design principles that embrace ecological and ethical considerations, creating a blueprint for responsible strategy. This strategy, implemented with meticulous care, ensures that regenerative innovation is continually measured and monitored for its impact on the planet.
  2. Ambidextrous Leadership (Progress/Profit) unfurls a visionary path through diligent market research, seeking opportunities where profit can be harmonized with regenerative principles. At Step 3B, innovators craft bold ideas that resonate with the sustainable future they aspire to create. Within this collaboration, a multilayered business model emerges, serving as a robust platform for regenerative innovation. The model provides the necessary scaffolding to launch regenerative solutions into the market successfully.
  3. Creative Leadership (People) places the human element at the heart of regenerative innovation. By knowing their customers intimately, innovators ensure that solutions are not only ecologically sound but also responsive to the needs, desires, and values of the people they serve. At Step 3C, creative leaders join forces with their counterparts in Ambidextrous Leadership, forging smart solutions that prioritize the well-being of both the planet and humanity. They craft prototypes that are not only effective but also user-friendly, culminating in an evaluation process that centers on the customer experience.

This three-pronged approach to regenerative innovation redefines the boundaries of progress, profit, and sustainability. The magic lies in the convergence of these three leadership paradigms at Step 3, where ideas, strategies, and solutions synergize to create a regenerative force greater than the sum of its parts. Together, they pave the way for a future where responsible, ambidextrous, and creative leaders collaborate to shape a world that is not only profitable but also harmoniously interwoven with the planet and its people.

This infographic is part of the book Innographics: A Visual Guide to Innovation Management

Download a 32-page preview for free
Including 2 infographics, 2 chapters and an overview of 28 innographics.

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Avoid the Toxic Trap: the Toxic Matrix

Avoid the Toxic Trap: the Toxic Matrix

Jan Spruijt

Innovation is the foundation of progress and success in business. A culture of innovation is essential for companies to thrive and stay competitive. One of the biggest challenges for companies is to ensure that the culture of innovation is not overshadowed by a culture of toxicity. There are a number of potential pitfalls that must be avoided in order to create an environment that encourages creativity and collaboration. This blog will discuss these issues, as well as strategies for avoiding the Toxic Trap.

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2 Decades of Open Innovation: an infographic

2 Decades of Open Innovation: an infographic

Jan Spruijt

The rise of open innovation has been a long-standing trend in business. In the early 1990s, companies were starting to realize that they could improve their competitive edge by sharing their ideas and innovations with others. This led to the development of the concept of “open source” software, which allows for free exchange of information among developers. Open innovation is a term first coined by professor Henry Chesbrough in his 2003 book “Open Innovation: The New Imperative for Creating and Profiting from Technology”. It describes the process of organizations leveraging external ideas and resources to drive innovation and growth. This can be done through things like open R&D, corporate venturing, collaborative research, etc.

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Infographic: Innovation Learning Arches

Infographic: Innovation Learning Arches

Jan Spruijt

What if we look at innovation from the perspective of learning? In that case, the sole intention of innovation management is not systematically generating and implementing viable offerings, but optimizing the amount of learning that an organization can handle when dealing with processes of creativity. For the purpose of this infographic I’ve combined the theories on a) stage-gate processes in innovation and technology development, b) organization learning and absorptive capacity and c) learning arches as they are widely used on higher education.

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Inneagram: Stakeholder Collaboration in Innovation Ecosystems

Inneagram: Stakeholder Collaboration in Innovation Ecosystems

Jan Spruijt

The story of this infographic began 16 years ago during a Summer School organized by the University of Cambridge. Not in the City of Perspiring Dreams itself, but on the mystical mountain Uludağ in Turkey, with 15 fellow students in a mountain hut more than 1 hour away from the nearest town with cellphone reception. On this mountain, led by Cambridge professor Jim Platts, we took an ESTIEM traineeship in transformative leadership. Without taking a deep dive into the material of the Summer School, one of the models that we started to work with was the Enneagram. Not only the power of the model itself, but also the history behind it, really intrigued me and so the story began.

Over the years, I’ve read much more about the Enneagram. Mostly used in (business) psychology, the framework is best described as an adaptive approach to recognize your own – and others’- behaviour in interactions with others. So it’s not, as many think, a framework for personality traits, like the Myers-Briggs Type Indicator (MBTI) or the Big-5 personality test. It perhaps holds the middle between these personality tests and the Rose of Leary, a theory of behavioral influence. The theory helps you to find your comfort-spot and from there on explains how your interactions with others happen and could be improved if you learn how to read it. It’s adaptable: it may change under different circumstances, under different preconditions and in different situations.

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Innovation for SDGs

Innovation for SDGs

Jan Spruijt

After its introduction by the United Nations in 2015, the Sustainable Development Goals (SDGs) have started to become increasingly accepted and embraced by both the public sector and the private sector as the ‘horizon’ to focus on when it comes to this world’s grandest challenges. Over the years, public institutes have operationalized and committed themselves to the 17 SDGs – and its 169 measurable targets. In their ambition to be sustainable, large corporates have embedded the SDGs in their annual reporting cycles and have started to (incrementally) change their behaviour for the good.

It is widely accepted that innovation and entrepreneurship are in high need to address these challenges. Innovation and emerging technologies, such as artificial intelligence, will guide the way to a better world. It is therefore that SDGs have become a prior field of interest in science, both in social sciences as in more innovation-related sciences. We believe that developments in science – not in the last place sponsored by large corporates or subsidized by public institutes – will lead to future developments in the private sector. In that way – science will guide us towards are more sustainable world.

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