This is a different post from my usual one reviewing the academic literature. It’s the academy of management conference this week and it made me reflect a bit about my research identity and intellectual journey so far. I’ll be joining the junior faculty consortium for TIM and the homework made me think about things like my research positioning, recommendation letter writers, community engagement and impact.

My PhD training was unconventional in that my dissertation centered around an empirical context (the field of fragment-based drug discovery) instead of a social science theoretical lens. I studied various aspects of this niche field in the pharmaceutical sciences from different perspectives – technology transfer, research collaborations, career development, technology adoption and venturing. My research was mainly done with the Science / Innovation department instead of the traditional Business and Economics department. The contacts I gained were mainly from the natural sciences – from academics to practitioners in the pharma industry. Most of my work had been published in practitioner journals in drug discovery. Not knowing any better, I was thinking that if I branded myself as the “business academic with the strong scientific/pharma background” that would be my unique positioning in the job market.

So far, it has worked out. I got my amazing postdoc position at a renowned business school due to my unique background. However, in recent days, with all these talks about the job market in management academia, I’ve been reassessing my research positioning. Subscribed to academic newsletters, I see all these tenure track position ads, making me reflect on whether my profile would be competitive.

For instance, I just learned recently that business schools had their own hierarchy of journals, which tended to discount technology management disciplines. Related to this, business schools do not really hire professors for technology management, you are hired as a researcher in strategy, entrepreneurship, information systems, OB, HR or some other discipline. Thus, I need to start building my name around a particular phenomenon. Moreover, the academic community I’ve built so far has revolved around the pharmaceutical sciences, meaning, that I have to catchup making collaborators in other top business schools.

There are always things that I could have done better in the past. But, finding what those things are generally could only be identified with the benefit of hindsight. Thinking about it, I won’t even be in my current position now if not for my unique trajectory. Moving forward though and knowing better, I have to find the social science topic that I would devote my future research on.

Just to close, I just wanted to share this highlight on ESADE postdocs. I talked about why I chose to do my postdoc in Barcelona and what topics I have been working on. I’m still finding my way in academia but I’m just glad that I am working on projects that I would have never imagined I would be part of before.

“Baby, you can drive my car”: Psychological antecedents that drive consumers’ adoption of AI-powered autonomous vehicles – straightforward study on psychological factors related to potential adoption of autonomous vehicles. They looked at the following factors: effort expectancy, social recognition, hedonism, technology security and privacy concerns.

How Catastrophic Innovation Failure Affects Organizational and Industry Legitimacy: The 2014 Virgin Galactic Test Flight Crash – rich case study relating failure to firm and industry legitimacy. The figure 1 in their article shows an intricate process model of how failures are interpreted to challenge or uphold firm legitimacy.

The rise of ‘ARPA-everything’ and what it means for science – DARPA has always been discussed in the history of innovation as they have been responsible for many advances such as GPS, weather satellites and computing. It functions differently as mentioned in the article:

Its roughly 100 programme managers, borrowed for stints of 3–5 years from academia or industry, have broad latitude in what they fund, and actively engage with their teams, enforcing aggressive deadlines and monitoring progress along the way. By comparison, projects funded by agencies such as the US National Institutes of Health (NIH) typically see little engagement between programme managers and the researchers they fund, beyond annual progress reports

Funding Risky Research – explores the challenges that various actors face in getting risky research funded.

• Research agencies – lack of portfolio approach, interdisciplinary bias, review protocols concealing uncertainty, emphasis on reviewers’ agreement
• Panelists – “insurance agent” view, bibliometric screening, risk-biased reviewers
• PIs – risk and loss aversion,

Artificial intelligence in information systems research: A systematic literature review and research agenda – a systematic review of AI research in IS. They propose the following problems that can be addressed for future studies: lack of consensus around the definition of AI, overemphasis on the technical (instead of social) impact of AI, unhinged use of machine learning as a methodology and more in-depth studies on the impacts of technologies such as robotics, natural language processing and machine vision.

Innovating the product innovation process to enable co-creation – Co-creation is a term I just learned recently and it has been appearing everywhere ever since. In this article, it explores how managers can help transition the product development process towards co-creation. They outline three main phases of unfreezing the organization towards change, co-creation activities with customers and finally, institutionalizing change.

Mapping the “Valley of Death”: Managing Selection and Technology Advancement in NASA’s Small Business Innovation Research Program – With me being involved in a project that aims to commercialize deep tech, NASA’s SIBR program is definitely an inspiration. In this study, the researchers show that the program tends to use varying selection criteria per funding round to manage risk across the portfolio.

Crackpots in science – There’s a fine line between genius and insanity. The term crackpot describes people who believe that they have discovered a new revolutionary theory of reality, without much engagement with academia. I don’t know anything about physics but what’s interesting is how a lot of recent work on a grand theory of everything has been carried out in the public such as Wolfram’s physics project and Weinstein’s Geometric Unity. I think such projects are important though as they can be source of new ideas.

The Economist’s What ifs? Currently, I’m teaching a class on the business of life science. One of our modules is about the future trends in the life sciences and this week’s edition of the Economist explored various future scenarios:

• If biohackers injected themselves with mRNA
• If America tackled its opioid crisis
• If everyone’s nutrition was personalised
• If smartphones became personal health assistants
• If dementia was preventable and treatable
• If an AI won the Nobel prize for medicine
• If germ theory had caught on sooner

How do startups manage external resources in innovation ecosystems? A resource perspective of startups’ lifecycle – Explores how startups manage their ecosystem’s resources at various stages of their lifecycle. They map the different types of resources (innovation, financial, social, human, physical, organizational) across various ecosystem actors (customers, government, university, consultants/mentors, complementors, incubators, business
association and funding Agencies).

Ecosystem management: Past achievements and future promises – explores the management of innovation ecosystems. Reminds me of the recent article on Technovation too defining innovation ecosystems. In the study, they identify various components of an ecosystem: value creation, systematic innovation, actors, interdependence, structure, dynamic, collaboration, competition, hierarchically independence, complementarity, complements, activities, value capture, configuration, flows and identity. They also focus on three perspectives: process view, configurational view and competitive view.

Configurations for corporate venture innovation: Investigating the role of the dominant coalition – fsQCA studies are always fascinating to me. In this study, they explore the different configurations of corporate venture innovation. They identify different ways that the parent firm can relate to the venture subunit, which they name reign, stimulation, sponsorship, and orchestration.

The obesity wars and the education of a researcher: A personal account – I knew that scientific debates can get heated but this story is just on a different level. It’s just one side of the story though so it would be interesting to hear the other side.

Who do we invent for? Patents by women focus more on women’s health, but few women get to invent – Fascinating study in Science from business school academics. The researchers find that all-female inventor teams tend to address problems that women face. This study implies that there is a need for better representation in the sciences across groups; otherwise, major issues faced by marginalized groups may not be addressed adequately.

Venture Idea Assessment (VIA): Development of a needed concept, measure, and research agenda – develops a scale to assess venture ideas, independent of any agents tasked with pushing it forward. I thought the paper would be about various dimensions that one should consider in evaluating an idea. But, the final scale, in the end, was more “academic” than practical. It’s a good thought experiment though to imagine a venture idea devoid of any entrepreneur.

Forecasting AI progress: A research agenda – as someone who doesn’t know much about forecasting, I like how they list all the different methods under three main categories:

• Statistical modeling using indicators or metrics (e.g. extrapolation, simulation, benchmarks, bibliometrics)
• Judgmental forecasting techniques (e.g. delphi, prediction markets, blue team / red team)
• Hybrid methods

Decision making under deep uncertainties: A review of the applicability of methods in practice – didn’t know about DMDU until this paper. It’s a good introduction to the various techniques such as:

• Robust Decision Making (RDM)
• Dynamic Adaptive Planning (DAP)
• Dynamic Adaptive Policy Pathways (DAPP)
• Info-Gap Theory (IG)
• Engineering Options Analysis (EOA)

I am presenting our paper on the Science Mesh this week. FAIR data through a federated cloud infrastructure: Exploring the Science Mesh – it is a research-in-progress on the potential of FAIR data in unlocking new collaborative workflows.

Entrepreneurial space and the freedom for entrepreneurship: Institutional settings, policy, and action in the space industry – a study of the space industry where the researchers introduce the concept of entrepreneurial space. Great play on words. They define entrepreneurial space as the room for entrepreneurial change, which is often limited by policy and institutions.

Never the twain shall meet? Knowledge strategies for digitalization in healthcare – explores digitalization in healthcare through the lens of knowledge strategy. The researchers followed a hospital for almost a decade and then explored how they digitalized, exploring the following components:

• Vision – top management’s understanding of the role of knowledge in the organization
• Knowledge strategy objectives – goals for the organization and the role of knowledge management towards these goals
• Knowledge management tools – methods to enable the creation, application, leveraging and sharing of knowledge
• Implementation support mechanisms – organizational aspects including culture, structure, HR practices

Ecosystem policy roadmapping – combines innovation ecosystems with technology roadmapping. It’s a paper filled with cool illustrations of different frameworks to guide roadmapping. In the end, I really think the value of management research is providing frameworks for thinking about things and this is a great addition to that toolbox.

From ‘publish or perish’ to societal impact: Organisational repurposing towards responsible innovation through creating a medical platform – explores how an academic research project transformed itself to create larger societal impacts. I find it amazing how management academics can see any phenomenon in new light and make everything sound interesting. Definitely will be an inspiration for future studies that I do.

Digital transformation: What we have learned (thus far) and what is next – important review of digital transformation. They identify the following areas needing further research: measurement of success of DT initiatives; skills required for DT; organization of DT and societal impact. They also identified emerging research avenues including: the role of technology, the interaction between physical and digital environment, the interaction between technologies and organizing at a global scale.

The role of skill versus luck in new venture survival – instead of seeing entrepreneurs as gamblers, it’s better to see them as sailors. They cannot change the weather but they can adjust how their sails are positioned, motivate their crew and redirect their ships if needed.

Rapid Validity Testing at the Front-End of Innovation – Researchers explore RVT which aggregates lean innovation, prototyping, design thinking and pretotyping into one framework. It’s the first time I’ve heard of pretotyping which is the stripped-down version of a product to enable rapid testing. RVT’s components include:

• Problem framing
• Prototyping as test
• Prototyping as communication
• User integration
• Product iteration
• Commercial learning
• Business model iteration

Learning on knowledge graph dynamics provides an early warning of impactful research – A paper that got a lot of attention from reddit. The paper aims to predict which papers would be breakthroughs, by aggregating 29 metrics including from author and journal data, paper citations, and network characteristics. Using the method retrospectively, they were able to identify 19/20 seminal biotechnologies from 1980 to 2014. I need to spend more time reading the paper but the first thing that popped into my mind is this joke about economists predicting nine of the last five recessions.

Prestigious European grants might be biased, study suggests – In the study cited in the Nature article, the authors find that “applicants who shared both a home and a host organization with one panellist or more received a grant 40% more often than average.” Not really surprising. Scientists and grant funders are humans in the end.

Waiving IP – I’m teaching a class on life science patents and it’s impossible to talk about patents without discussing the various calls to waive patents for COVID vaccines. I’m also of the opinion that to some extent, patents can be beneficial to society.

Making the hard problem of consciousness easier – the idea of adversarial collaborations is really interesting. It’s when two groups with opposing ideas collaborate to come up with the experiment to test which theory is correct. In this case, it’s two groups having different theories of consciousness. I wouldn’t claim to understand global neuronal workspace theory and integrated information theory though.

Here are the interesting articles I’ve seen in the last 2 weeks.

The effects of university–industry collaboration in preclinical research on pharmaceutical firms’ R&D performance: Absorptive capacity’s role – study based on bibliographic, patent, financial and clinical trial data of big pharma firms. The researchers relate university-industry collaborations to firms R&D performance. Probably, not very surprising considering that big pharma is known to be reliant on public research institutes.

The contribution of Design Thinking to the R of R&D in technological innovation – in the past, design thinking has generally only been applied to the later phases of development. In the article, the researchers introduce the approach called proxemics which they say can be more useful for research (not intended to find product market). It has the following steps:

• scouting
• identification of interaction domains
• design of interaction scenarios
• ideation of interaction concepts
• development of interaction prototypes

Unveiling the role of risk-taking in innovation: antecedents and effects – very counterintuitive finding that having well-established innovation processes lead to worse risk-taking and innovation performance. Authors speculate that “innovation processes can include overly rigid gates and selection criteria, thereby blocking innovation ideas.” Instead, resources, support and clear goals were found to enable it.

Prospective collaborative sensemaking for identifying the potential impact of emerging technologies – I have heard of sensemaking in the past but never really looked much into it. Their article introduced me to the Stigliani and Ravasi (2012) framework on prospective sensemaking:

• Noticing and bracketing – individuals take environmental cues and determines whether these are worth noting.
• Articulating – actors organize information to gain a better understanding of the new situation
• Elaborating – group of actors interact iteratively to give meaning to the cue
• Influence – actors take the collectively created interpretation

Predicting social tipping and norm change in controlled experiments – It’s fascinating how social change can happen quickly, such as the acceptance of gay marriage and the weakening sensitivity towards privacy issues. I remember listening to a podcast episode from 80,000 hours and the theory put forward by the guest on why such changes can be unpredictable was really interesting. This sudden change is attributed to people not sharing their real preference and people having different thresholds of how much action they want to see from others before they themselves act.

Prospera – an experimental city of the future, libertarian paradise, being built on an island in Honduras. It’s based on the concept of charter cities proposed by Nobel prize economist Paul Romer. The idea is that less developed countries can lend a part of their land to countries with stronger institutions or companies who can then develop the land. A really exciting idea that hope works out.

The Invisible Cage: Workers’ Reactivity to Opaque Algorithmic Evaluations – Very timely article as algorithms continue to control our lives – from Youtube recommendations to Google search engine rankings. The article introduces the term Invisible Cage (a nod to Weber’s Iron Cage) which refers to “a form of control in which the criteria for success and changes to those criteria are unpredictable.”

Co-creative entrepreneurship – Having attended the OIS conference, I was introduced to the term co-creation, which refers to a design process where stakeholders like consumers are highly integrated. In this case, the authors depict co-creative entrepreneurship to “interactively construct both supply and demand, gradually resolving uncertainty.”

The role of Proof-of-Concept programs in facilitating the commercialization of research-based inventions – With one of my projects, ATTRACT, being a proof-of-concept fund taken to the next level, this article caught my attention. It highlights three roles of POCs:

• Relational – bridge gap between the stakeholders in tech development and users
• Structural – lower barriers to research development in their specific context
• Cultural – give space to think about external applications and overcome old beliefs