The last few months gave me some things to think about with respect to which research directions I would like to pursue. To be productive about these reflections, I decided to step back a bit and see what are the emerging topics in technology and innovation management. I wanted to check what conversations are happening currently across the literature and see which conversations I can potentially join.

To do this, I downloaded articles published from 2020 to the present in the Web of Science. I used the keywords “technolog*” and “innovat*”. I narrowed down the articles to the top journals in general management namely: academy of management review, academy of management journal, administrative science quarterly, organization science, journal of business venturing, entrepreneurship theory and practice, strategic management journal, strategic entrepreneurship journal, journal of management, organization studies, journal of management studies. As seen this excludes the top/traditional TIM journals like research policy and technovation as I wanted to see which conversations are diffusing outside of my smaller circle.

I analyzed about 549 articles and did the typical bibliometric analysis. I came up with the following bibliometric coupling map, which shows the different themes.

I quickly browsed through each of the clusters to identify the research themes. In the following table, I describe my findings.

Cluster (Number of Articles)	Top Keywords	Theme	Sample paper
Red (156)	work, organization, organizational, technology, theory, practice, process, digital, actor, social	How the nature of work is changing due to digital technologies	Behavioral Visibility: A new paradigm for organization studies in the age of digitization, digitalization, and datafication
Green (146)	firm, innovation, patent, knowledge, resource, technological, industry, performance, technology, search	How can firms manage innovation in uncertain environments?	Exploring Uncharted Territory: Knowledge Search Processes in the Origination of Outlier Innovation
Blue (127)	venture, entrepreneurship, entrepreneur, entrepreneurial, firm, startup, performance, founder, opportunity, innovation	How does a venture’s business model emerge and evolve over time?	Parallel Play: Startups, Nascent Markets, and Effective Business-model Design
Yellow (52)	platform, ecosystem, design, product, firm, digital platform, business model, network effect, strategy, performance	How can platforms be effectively governed to maximize value for different actors?	From proprietary to collective governance: How do platform participation strategies evolve?
Violet (48)	team, network, creativity, employee, creative, idea, innovation, diversity, individual, project	How can teams and networks be harnessed for creativity?	Networks, Creativity, and Time: Staying Creative through Brokerage and Network Rejuvenation
Light blue (20)	family, family firm, innovation, succession, family business, transgenerational, firm, ownership, woman, role	How can family firms be innovative?	Innovation Motives in Family Firms: A Transgenerational View

Conducting this quick analysis has made me realize that the things I have been working on have been quite different from the interests of top scholars in the general management field. A lot more reflection I need to do then.

Ecosystem types: A systematic review on boundaries and goals – studies the relations between different types of ecosystems (business, innovation, entrepreneurship and knowledge). It offers the following areas for future research:

• Role of external environment of the ecosystem
• Indicators and dimensions to measure performance
• New research methods and designs to study ecosystems
• Take other useful theories to apply in ecosystems

A framework and databases for measuring entrepreneurial ecosystems – explores different databases and how they can provide insights into the various roles of the government in ecosystems. Namely, these four roles are: catalyst (develops human capital and promotes tech venture creation), coordinator (drives and boosts outputs of ventures), certifier (validates the technical and commercial merits of ventures’ outputs) and customer (procures the outputs from ventures).

Ecosystems transformation through disruptive innovation: A definition, framework and outline for future research – explores the processes through which ecosystems transform. They highlight four interlinking phases: (1) the presence of transformational forces such as technology development and changes in customer behaviors, (2) strategic opportunity identification from the different actors, (3) value alignment across actors including providers, creators and users, and (4) ecosystem revitalization through both capability enhancing and destroying.

The emergence of entrepreneurial ecosystems based on enabling technologies: Evidence from synthetic biology – explores the synbio space, looking at the emerging sub-ecosystems within: pharmaceuticals, hardware, smart factories, smart cities, waste management, foodstuffs, and consumer goods. It also identifies the barriers that must be overcome by ecosystems based on such enabling technologies: how to manage IP considering the complex interactions across actors, how to manage the different clock speeds across quintuple helix actors and how to manage the ethical challenges in such a fast-moving technology.

Last week, we organized at ESADE the socioeconomic impact projects for ATTRACT. The main message from the workshop is the need for researchers to experiment and try other methods for impact evaluation, beyond traditional measures.

In line with this, let me go through some interesting articles I have read in the past weeks.

Entrepreneurial experimentation: a key function in systems of innovation – during the ATTRACT workshop, one of the core propositions is that we can systematize serendipity to turn ideas into impactful solutions. Digging deeper, the perception of serendipity arising can just be the side effect of extensive experimentation by entrepreneurs. The successful experiments are the ones that seem like serendipity.

Why the agile mindset matters – agile is one of those terms that are thrown around everywhere. Agile mindset was characterized by the following: learning spirit, collaborative exchange, empowered self-guidance and customer co-creation.

Reconceptualizing Imitation: Implications for Dynamic Capabilities, Innovation, and Competitive Advantage – questioning the current assumptions on imitation:

• imitation is easy (vs. imitation is hard)
• weak firms imitate (vs. strong firms imitate)
• uncertainty promotes imitation (vs. uncertainty hinders imitation)
• there is only one imitation strategy (vs. many imitation strategies)

Structuring the Start-up: How Coordination Emerges in Start-ups through Learning Sequencing – by following five startups over 2 years, the study finds how coordination emerges through the following learning sequence: anticipatory learning (anticipate early coordination problems), vicarious learning (copying ideas and practices from other startups), experimental learning (rolling out new mechanisms and scaling them up when successful), and trial-and-error learning (combine different coordination mechanisms and simplifying them).

Tradition as a resource: Robust and radical interpretations of operatic tradition in the Italian opera industry, 1989–2011 – a cool study of how reinterpretations of Italian opera affect ticket sales. The authors distinguish between different forms of interpretations. Robust interpretation involves preserving the most familiar aspects of a tradition but changing features like time/location. On the other hand, radiccal interpretation means modifying the core features such as altering the dramatic composition. The study finds that season-ticket holders are more likely to enjoy robust interpretations, while single-ticket holders are more likely to enjoy radical interpretations.

Although I read through the new publications every week, I have not posted on my blog for quite a while. Nonetheless, hope to resume again this week.

Let me restart by focusing on research impacts. Two weeks ago, I was lucky to visit Bologna and attend a workshop on entrepreneurship with some of the top scholars, especially in the sub-field of academic entrepreneurship – one of the ways by which research creates impacts.

Here are some of the nice articles I’ve read recently:

Becoming an academic entrepreneur: how scientists develop an entrepreneurial identity – introduces the idea of liminal venturing to explore how individuals who have established a strong identity as academic scientists develop their identities as entrepreneurs.

Managing individual research productivity in academic organizations: A review of the evidence and a path forward – a review of levers impacting research productivity including resource allocation, structural choices, organizational culture and task environment

Incentivizing Effort Allocation Through Resource Allocation: Evidence from Scientists’ Response to Changes in Funding Policy – studies the unintended impacts of policy change on research. They specifically examined how stem cell scientists in the US responded to funding restrictions in human embryonic stem cell (hESC) research. They find that this reduced these scientists’ output even in non-hESC areas, with the top scientists being most affected.

Reaching for the stars: When does basic research collaboration between firms and academic star scientists benefit firm invention performance? – explores academic stars collaborating with pharmaceutical firms. They find that the outcomes of collaborations as measured by patent citations only superior if various conditions are met – if the star scientist is dedicated to the collaboration by not having other simultaneous engagements with other firms or when the collaboration extends beyond basic research toward translational research.