Happy new year everyone! Here are my interesting reads from the holidays up to today.

Developing a unified definition of digital transformation – studies that aim to define a certain concept are always fascinating. In this study, they review the digital transformation literature and complement it with a survey of practitioners and academics to get a unified definition of DT:

A fundamental change process, enabled by the innovative use of digital technologies accompanied by the strategic leverage of key resources and capabilities, aiming to radically improve an entity* and redefine its value proposition for its stakeholders.

Organizing for innovation: a contingency view on innovative team configuration – study on how a team’s expertise should be tailored according to the domain they are trying to innovate in. The researchers explore 4 domains varying by modularity and breadth of application – MRI, RFID, stem cells and nanotubes. Modular domains like MRI and RFID do not need a lot of overlap in knowledge across their inventors. Domains with broad applications benefit from teams with wide knowledge breadth as well.

The front end in radical process innovation projects: Sources of knowledge problems and coping mechanisms – It’s worth the read even just for the review on the difference between complexity, uncertainty, equivocality and ambiguity. These are terms that are thrown around interchangeably and this article builds on previous works to explain them more clearly:

• Uncertainty – refers to the lack of sufficient information needed to get to the desired outcome. Put simply, not knowing the answers.
• Complexity – related to the number of parts in a system and the difficulties in predicting the interactions among them. In other words, not knowing how to find the answers to the question.
• Ambiguity – the inability to interpret. In other words, not knowing what questions to ask in the first place.
• Equivocality – potential for multiple interpretations, even when information is available. Put simply, having multiple answers.

Artificial intelligence in drug discovery: what is realistic, what are illusions? Part 1: Ways to make an impact, and why we are not there yet – despite moving away from pharma research, I still enjoy reading news about the industry. The summary of this article is the classic line garbage in, garbage out. The conclusion perfectly illustrates this: “with our current ways of generating and utilizing data, we are unlikely to achieve the significantly better decisions that are required to make drug discovery more successful… we need to understand what to measure, and how to measure it… Only once these data are available for AI approaches can the field be expected to make real progress.”

Impact for whom? Mapping the users of public research with lexicon‑based text mining – When I moved to the social sciences, the impact of my research became much more difficult to define and perceive. This study maps the various communities that such research can have impact to. Found the visualizations fascinating.

Who Contributes Knowledge? Core-Periphery Tension in Online
Innovation Communities – explores what makes a contribution highly valued in the forum Stack Exchange. They talk about social embeddedness which refers to how connected socially an individual is to their community and epistemic marginality which refers to how different an individual’s knowledge base is compared to their community. Those who are both socially embedded and epistemically marginal are able to contribute highly valued insights as these insights are generally novel compared to the community and at the same time, they are able to communicate well their ideas to their community.

Recommender systems in the healthcare domain: state-of-the-art and research issues – always interesting to see the overlap across healthcare and AI. This review looks at the application of recommender systems in food, drug and exercise recommendation, health status prediction and health care professional search.

It did not work? Unlearn and try again – Unlearning success and failure beliefs in changing environments – it’s important to learn from your mistakes, but it’s also important to unlearn the false beliefs you have formed from previous mistakes. Cool insight considering that people generally focus on learning and not on unlearning.

Experience base, strategy-by-doing and new product performance – When we think of strategy, we usually think of getting a whiteboard and brainstorming on the best plan forward. In contrary, there is strategy-by-doing which is defined as “actions of iterative search for what works in the market.”

In Silico documentary – Nature featured this documentary on the fall of the Human Brain Project. I still haven’t watched it but this seems to be an interesting view on the politics behind science.

Exploring the dynamics of novelty production through exaptation: a historical analysis of coal tar-based innovations – previous theories of serendipity explain that it rises from a need or from theory. This paper offers a new route to serendipity – affordances. I did not know this word before but as the paper explains it is “the perceived or actual properties of the thing, primarily those fundamental properties that determine just how the thing could possibly be used”

Social impacts of additive manufacturing: A stakeholder-driven framework – enumerates and classifies possible impacts of a technology like 3d printing. Since I am doing a social and business impact assessment of cloud computing, this is a paper that would be useful model moving forward.

Failing to Learn from Failure: How Optimism Impedes Entrepreneurial Innovation – a fascinating study that links laboratory experiments with firm data. They measured entrepreneurs’ dispositional optimism – the tendency to think that they will have a favorable outcome. They then linked it to patents or product development success. I like their finding that those who are optimistic by disposition tend to not update their beliefs of future success despite negative outcomes. Everytime I meet with my entrepreneur friends, I really see the difference on how they think and perceive things.

Postdoc challenges – For a few weeks now, Nature has been talking about the issues that postdocs have been facing. As a postdoc myself, I can relate to the issues of uncertainty about the future. Despite this, I have been lucky to find a position in a great research group during the pandemic. I am really worried about how academia would proceed moving forward, so we’ll see.

Lab, Gig or Enterprise? How scientist-inventors form nascent startup teams – groups the startup formation strategies by scientists into three clusters. For some inventors, their startup is basically an extension of their academic laboratories where they can experiment with the commercial applications of their research. The gig model occurs when inventors want to pursue an idea quickly and see if it would be viable enough to be an exit. The enterprise model emphasizes creating a team that would enable the creation of a real sustainable business.

Management Research that Makes a Difference: Broadening the Meaning of Impact – every now and then, I have to remind myself what is the point of management research. This editorial provides five forms of impact: scholarly, practical, societal , policy and educational.

Converting inventions into innovations in large firms: How inventors at Xerox navigated the innovation process to commercialize their ideas – a study from June. Really interesting idea of innovators going around other departments to find a more amenable evaluation criteria so that they can later acquire further resources

The Matthew effect and the halo effect in research funding – The Matthew effect refers to the idea taken from the bible that the rich tend to get richer. The Halo effect is the idea that positive impressions in one area can also lead to positive evaluations of other areas. The study shows that researchers gain cumulative advantages, in that getting a funding grant can lead to them getting another one.

Bridging the gap between invention and innovation: Increasing success rates in publicly and industry-funded clinical trials – a study on the role of PI’s expertise on the success of clinical trials. Fascinating that they find that broad experience across multiple disease fields reduce success rates.

Fiction lagging behind or non-fiction defending the indefensible? University–industry (et al.) interaction in science fiction – My first time to come across a study like this. The study explores how science fiction novels view academia-industry interactions, using these novels as kind of a mirror to how society views such interactions. They find that science fiction has been critical of such relationships.

Developing Improvisation Skills: The Influence of Individual Orientations – another unique study using Live Action Role-Playing as the data collection method. As someone who is not really good with thinking on my feet, I found their three types/stages of improvisation skills useful. Imitative improvisation refers to merely taking inspiration from others. When you can then create an original response guided by some structure, you then evolve to reactive improvisation. When you do not need anymore external triggers and can just easily break existing structures, then you are at the generative improvisation stage.

The sandwich game: Founder-CEOs and forecasting as impression management – with so many people posting about their successes on social media, impression management is becoming more and more relevant. In this study, the authors argue that founders are less likely to oversell their company’s forecasts due to their concern with their long-term relationship with investors. I find this quite unintuitive especially when my top of mind founder CEOs are Elon Musk and Elizabeth Holmes.

Applying advanced technologies to improve clinical trials:
a systematic mapping study – comprehensive review of technologies used in clinical trials. I appreciated Table 3 which talked about the possible contributions of a research paper, adapted from Shaw 2003, which I didn’t know before.

The Emergence of New Knowledge: The Case of Zero‐Reference Patents – when we think of science, we talk about standing on the shoulder of giants. Apparently, there are patents that are just so pioneering that they do not reference previous patents.

Engineering Serendipity: When Does Knowledge Sharing Lead to Knowledge Production? – cool study on serendipity. Researchers were randomly selected to interact with other researchers. Their publications and citations were then tracked afterwards.

Organizing Crisis Innovation: Lessons from World War II– talks about the role of the U.S. Office of Scientific Research and Development led by Vannevar Bush during World War 2 in spurring innovations such as radar, atomic fission, penicillin, and malaria

The long wave of the internet – traces the history of the internet and the paradigms occuring across each phase of its development

Do policy makers take grants for granted? The efficacy of public sponsorship for innovative entrepreneurship – Study finds that while public grants may help in securing further private investment capital, they do not help with revenue over time.

What matters more for entrepreneurship success? A meta‐analysis comparing general mental ability and emotional intelligence in entrepreneurial settings – IQ vs. EQ? This study shows that both are important for entrepreneurship, with emotional intelligence being more crucial.

There are some more articles from AOM that I am looking forward to read but I cannot currently access. I list them here:

• Research movements and theorizing dynamics in management and organization studies
• Heuristic methods for updating small world representations in strategic situations of Knightian uncertainty
• Doomsdays and New Dawns: Technological Discontinuities and Competence Ecosystems

What makes dynamic strategic problems difficult? Evidence from an experimental study – an experimental study showing that “people do poorly even in this complete information condition, and importantly, they show limited improvement compared to the more complex conditions that require complex learning.”

Behavioral Visibility: A New Paradigm for Organization Studies in the Age of Digitization, Digitalization, and Datafication – A lot of people are working online now. The study then explores how we can become “visible” in this digital age. I can identify with the paradoxes they enumerated in their paper: Connectivity paradox where employees who want to connect with their colleagues may cause interruptions. Performance paradox where people who spend time working hard on a task may not have time to make their work visible. Transparency paradox where organizations which want greater communication can end up obscuring activities.

Theorizing Actor Interactions Shaping Innovation in Digital
Infrastructures: The Case of Residential Internet Development
in Belarus – shows the various interactions that occur during infrastructure development. They made a 2×2 matrix mapping these interactions as symbiotic generative, symbiotic mutualistic, parasitic complementary and parasitic competitive

The coauthorship networks of the most productive European researchers – prolific researchers publish with other highly cited collaborators. Not super surprising. Yet, this is something that I always have to remind myself. You have to find productive collaborators who will help you push your research forward.

Sources of innovation for new medicines: questions of sustainability – describes the decline of the pharmaceutical industry. It shows decreasing new company formation, and decrease in number of companies involved in R&D

A skill that is useful for many types of jobs is web scraping. It is useful especially if the data you want to collect is available online but is spread across different pages. Then, instead of just copy and pasting the information one by one, you can then just use a script to automate the task. Based on this pooled data, you can then get some insight into whatever industry or domain that you are interested in studying.

Please note though that before you engage in this, make sure that the website permits this. You probably would not want to have yourself banned if their system detects your activities as abusive. If you want to learn how to do it, I suggest to just search for the term Beautiful Soup on Google (need basic knowhow of Python). There are many quick tutorials on how to use it online. The basic workflow is to retrieve the page, explore the page to find the tags that are associated with the data that you are trying to capture, save the relevant data and then organize the data into some dataframe. Throughout the process, it is just a matter of experimentation to ensure that you are actually downloading the things that you are interested in.

The applications of web scraping are endless. In the past, I have used it to collect the job postings in the specific field I was studying in the pharmaceutical industry every week. The idea was that the job postings would somehow reflect the research priorities and trends in the industry. With the textual data such as the job description, the type of company and the specific instruments used in the job requirement, you can derive many insights about how hot the field is and what directions it is taking. Too bad though that I did not end up pursuing more this area as I had other promising areas that I pursued.

Another application of web scraping (which I have a paper under review) is in order to get a quick overview of the landscape of companies in your niche. You can then scrape the product and service pages of companies. By doing some standard natural language processing techniques (you can google TF-IDF or LDA), you can then get an overview of the words used within the niche and how companies relate to one another. Through this mapping, you can then get a big-picture overview of the types of offerings within the industry.

A (Re)view of the Philosophical Foundations of Strategic Management – explores four meta-paradigms around strategy research: contemporary positivism , contemporary realism, interpretive and critical postmodernism. I’ll be honest, I could only wrap my head around the first and second approach partly.

Social selectivity in aging wild chimpanzees – humans tend to have fewer but stronger relationships as they age. This has been speculated to be our way to cope with the fear of impending mortality. This study suggests that probably this is not the case especially if chimpanzees indeed could not imagine their future death.

SARS-CoV-2 vaccines in development – comprehensive overview of the vaccine development landscape.

Are Inventors or Firms the Engines of Innovation? – ” inventors’ human capital is 5–10 times more important than firm capabilities for explaining the variance in inventor output”

The rise and rise of creativity – Great overview on how society’s conception of creativity has evolved over time. It’s striking how prevalent the term is now. All firms now are creative firms. Apparently, the term only started to take off in the 1950s, being virtually absent before.

The genesis of public-private innovation ecosystems: Bias and challenges – The article mentions that there tends to be a value creation bias towards incumbent firms. As I was part of a Marie Curie ITN and also was involved in setting up one in drug discovery, I can see why this can be so. Large companies add legitimacy to a consortium.

Why Do High-Status People Have Larger Social Networks? Belief in Status-Quality Coupling as a Driver of Network-Broadening Behavior and Social Network Size – people behave differently according to whether they believe that their status is a good measure of their quality. Could not access the article itself but found the idea fascinating.