EINST4INE https://www.einst4ine.eu The European Training Network for InduStry Digital Transformation across Innovation Ecosystems Mon, 04 Mar 2024 23:46:50 +0000 en-AU hourly 1 https://www.einst4ine.eu/wp-content/uploads/2021/09/cropped-EINST4INE-icon-32x32.png EINST4INE https://www.einst4ine.eu 32 32 So, what’s your research about? – Presenting to a non-expert audience https://www.einst4ine.eu/so-whats-your-research-about-presenting-to-a-non-expert-audience/?utm_source=rss&utm_medium=rss&utm_campaign=so-whats-your-research-about-presenting-to-a-non-expert-audience https://www.einst4ine.eu/so-whats-your-research-about-presenting-to-a-non-expert-audience/#respond Thu, 28 Mar 2024 23:22:18 +0000 https://www.einst4ine.eu/?p=11487 The question: “So, what is your research about?” is one that many of us have heard several times during our PhD. Sometimes we are asked this question by other researchers in our field, sometimes by people that are no experts. While all PhDs are trained in how to present their research to other experts – via conferences, academic abstracts, papers, etc. – not all are exposed or learn how to present their research to non-experts.
In this blog post, I will share my thoughts on why knowing how to present your research to a non-expert audience is important and will also share some of my experiences in doing so.

Why it is useful to learn to present your research to a non-expert audience

  • Outreach: give knowledge back
    Speaking to non-experts ensures that you are passing on your knowledge and also give it back to those that have helped you create it. This is not only the case, if you present to your research participants – but also to anybody else. Maybe your funding comes from the government, which actually means taxpayers. Further, the core goal of research is to expand knowledge. However, knowledge expansion only happens if the new knowledge is shared – and this includes also outside of academia! So, I would say for a true academic and researcher it is essential to also share their knowledge outside of their field.
  • Reflect on your research
    When you prepare a talk for a non-expert audience, you have to take a step back from your research and ask yourself what it is really about. This makes you necessarily reflect on your research, makes you see the whole (or at least you can try – it can be hard) and might support you on seeing a storyline that you can extract.
  • Making it concise & easy to digest
    One of the most important things is to make your message clear, to present your research in a concise manner and to make it easy to digest. This can actually be a lot harder than it sounds – but I do think that if you manage to break your research down into easier bits, then you understand your research really well – plus, you won’t lose the attention of your non-expert audience!
  • Asking: why should one care?
    The next important thing to retain the attention of your audience is to make it interesting to them. Why should they care? How is this relevant for them? And if you feel like you just cannot make it relevant for them personally, then why is this relevant for society, knowledge extension etc.? It’s probably good to bring this message across rather early in your talk – then they know why they should continue to listen. Best is, if you manage to bring it up in the end again – this is not only a nice rhetorical closure than, but also leaves them with a take-home message that makes them remember that your research connects to them.
  • Grounding in reality
    I am serious with this – sometimes presenting your research to non-experts does help you ground your research (and maybe yourself) back in reality. Stepping away from very theoretical concepts and abstract ideas and tying them back to things that matter in everyday lives. This might sound hard for some topics, but there is always a connection. Be creative! For example, my master thesis topic on a specific semi-conductor detector and how it is sensitive for specific energy ranges was relevant in reality, because in theory (and more years) this kind of detector could be relevant in medicine.
  • Learning new vocabulary to describe your research
    When you speak with a new audience, you should understand them a bit first: who are they? What might they know already? Based on this, you might know what kind of vocabulary you should use. Here, I don’t only mean field specific vocabulary. Also consider if maybe this word has other connotations for some audiences (e.g., “coding” can mean programming for some audiences and “using the Gioia method” for others). Plus, we know that it is always easier to learn about a new topic, if it is presented in familiar terms.
  • Exposure to other opinions
    Lastly, presenting to non-expert audiences will ensure that you get exposed to other opinions, other perspectives and you might learn about a new way of looking at your research. In addition, especially people who do not know much about your topic are often good at spotting “obvious” inconsistencies or “obvious” questions. Often just because they are curious and don’t know what questions have an easy answer (i.e., you just didn’t mention it because you thought it was not worth the time) and which ones are actually not easy to answer.

While I am always asked to present my research to industry at various events (e.g., through the STIM consortium in Cambridge), this year I was also asked to give talks to non-expert audiences. Thus, I was giving talks to three quite different non-expert audiences. I will shortly share some experiences and insights about each of them.

Industry audience

In this case, I was presenting my research to people from various industries holding different positions (but mostly management level).

  • Really important here: ask yourself, what is important to them? What is interesting for them? Industry people are really busy, if you don’t capture their attention you might lose them quickly. In addition, if you are interested in a collaboration, you also want to show them why they should want to collaborate with you!
  • Use words that they can understand and relate to (linking to my note above). Use terms that are used in companies to explain things, or words that are in everyday use. Of course, you don’t have to through all of your nice-expert-words out of the window, do keep some in – but then make sure to clearly explain them.
  • Graphics and pictures are very powerful. They capture attention and can sometimes simplify things (plus people enjoy having to read less).
  • Highlight how research can be done together, how industry and research can support each other. Speaking of co-creation, action research, etc. is powerful and creates an atmosphere of community.

Newnham Donor Dinner

Non-academic audience

Here I was asked to give a short, easy talk at a dinner for donors of my college. My talk was in between courses and should showcase what different types of research is happening in Cambridge.

  • If you are asked to do something like this – remember, this is not a talk, it is a speech! It was the first time for me too, and was not super easy at first. Concentrate on the story line, and that it really flows. Don’t put too much content in here, it’s more important that people can follow you and that you highlight important things several times.
  • You likely won’t have visuals, so try to make things tangible by giving examples people can relate to, using things that are relevant in everyday life or for this specific audience, etc.
  • You might face different generations in your audience – do consider this and explain your research in terms that can be understood by varying age levels.
  • Likely your goal here is to make people excited about your topic – try to engage a discussion for after your talk. So it is less about presenting yourself or your research, but more about showing that this is relevant.
  • I do think that word games, a catchy phrase etc. can be really helpful to capture attention – plus, it is easier to remember then.

Audience of academics from other fields

Giving a talk to academics outside of my field.

As there are many graduate students in Cambridge, there are also many events organised by students related to research. I was asked by my college and another college to present my research at one of their student-run events. This was for other students from various fields, other researchers – anybody who is interested.

  • Likely you are speaking to other academics in this case. This means that lots of words can have other meanings to them (think of my example of “coding” from above). Consider this when writing your talk. Think about what they might already know and what not. But don’t just leave out the things you think they will know, but still mention them and then add: “as you probably know” – or ask if you should elaborate or not.
  • Do explain concepts and theories in this setting, your audience will be familiar with more abstract explanations. However, still make sure that it is understandable without knowing the details. For example, try to stay away from too much specific vocabulary and only use it when necessary.
  • Again, graphs, symbols, pictures, etc. make it easier to capture and retain attention. And it can also help you to explain things more clearly.
  • A good storyline that people can follow does help a lot. Even if you feel like your research does not have a nice story line (yet) – your talk can still have one. Include an agenda in the beginning and tell people how your talk will be structured. And then of course, follow that structure!
  • Even though the audience consists of academics, you can still give them too much information – try not to create information overload but stick to the important bits.
  • A catchy title can do wonders, do try to think of one, as this can really capture a lot of attention!

You see, speaking to non-experts can be quite diverse and is definitely very useful for you, apart from outreach activity! I encourage everyone to consider presenting outside of academia, it is really rewarding and can be lots of fun.

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Who Cares? Beyond the Hypes of Fast Technology https://www.einst4ine.eu/who-cares-beyond-the-hypes-of-fast-technology/?utm_source=rss&utm_medium=rss&utm_campaign=who-cares-beyond-the-hypes-of-fast-technology https://www.einst4ine.eu/who-cares-beyond-the-hypes-of-fast-technology/#respond Wed, 20 Mar 2024 08:32:41 +0000 https://www.einst4ine.eu/?p=11428

Crowd of visitors at CES. Source: Imagist3ds

Every year in January, Las Vegas becomes the epicentre for tech enthusiasts, innovators, and industry leaders who gather to witness the spectacle of the Consumer Electronics Show (CES). Advertised as ‘the most powerful tech event in the world’ by its organizers, CES stands as a platform for unveiling the latest advancements in consumer electronics. Is between the myriad of products and technologies showcased there that tech giants like Google, Microsoft and Netflix built their bones back in their early days.

The significance of CES goes beyond flashy presentations and product unveilings. It serves as a compass for forthcoming trends and innovations in the consumer electronics industry. The prototypes and concepts showcased at CES often foreshadow the direction of technological development in the coming year. However, amidst the excitement and anticipation, lies the inevitable phenomenon of hype cycles.

The Gartner ‘hype’ cycle, introduced by the IT firm Gartner. Source: Wikipedia.

A hype cycle reflects the evolution of specific technologies over time, encompassing their maturity, adoption rates, and societal impacts. It begins with an initial surge of excitement and inflated expectations, fuelled by media coverage and investor interest. However, this euphoria is often followed by a period of disillusionment and scepticism as the technology fails to meet exaggerated expectations. Over time, as the technology matures and its real-world applications become clearer, a more balanced perspective emerges.

A notable recent example of a hype cycle is the fervour surrounding the metaverse. Presented as the next evolution of the internet, the metaverse captured the imagination of industry leaders and the public alike. However, just a year after its grand unveiling by Mark Zuckerberg, the metaverse faced scrutiny and scepticism. Reality Labs, the division responsible for metaverse-related initiatives, reported an operating loss of $13.7bn last year (1.6 million every hour!) [1], highlighting the challenges of translating hype into tangible market traction. Mark Zuckerberg itself went from “metaverse-first, not Facebook-first” in 2021 [2] to saying that the metaverse is “not the majority of what we’re doing” in 2022 [3].

Meta Platforms CEO Mark Zuckerberg’s avatar speaks during a virtual reality event. Source: Bloomberg.

But the metaverse and its promised marvels are only the most recent hype cycle. Prior to the metaverse, blockchain technology – to name one example – experienced a similar trajectory of hype and disillusionment.

Unsurprisingly, this year at CES was all about artificial intelligence, which has sucked all the air out of the room. The technology you heard about everywhere was AI [4]. Investors are surfing the wave and floods of money are being thrown at AI start-ups [5]. Time will tell us whether AI can deliver on its promises and overcome the challenges that lie ahead.

Hype cycles, while often viewed negatively, are an inherent part of technological progress. They reflect the tumultuous journey from concepts to reality, where expectations collide with the complexities of implementation and adoption. These waves of ‘next big things’ can be bewildering, confusing and erode confidence towards technology. It is true in fact that many of the technology are just “flashes in the pan” and die before reaching any kind of matureness [6].

Introduced by Samsung during the last CES, ‘Ballie: your perfect home AI companion’ (at least for your pet). Source: Samsung electronics.

Amidst the buzz of tech shows and the frenzy of media coverage, it’s essential to adopt a discerning perspective. Rather than succumbing to the appeal of hype, it’s crucial to focus on the core features and affordances of what is presented to us as ‘the next big thing’. Core features represent the essential capabilities that define a technology’s identity [7], while affordances denote the possibilities of action that it offers to users [8]. By evaluating technologies through this lens, we can better discern their true value and potential impact.

For instance, at CES last January Samsung presented an AI (of course) home assistant that follows you in your daily tasks. Is it just an Alexa on wheels or something more? A start-up called Rabbit presented a handheld device capable of control your music, order you a car, buy your groceries, send your messages, and more, all through a single interface. Have they just reinvented the smartphone?

Rabbit R1 from the AI startup Rabbit. It promises to be a universal controller for apps and services without any login. One device to rule them all. Source: The Decorder.

In the vast sea of gadgets and innovations at CES, the question “who cares?” takes on new significance. By interrogating the core features and affordances of emerging technologies, we can identify the tools, services, and devices that truly offer value to users.

What are the core features of the device? What those functionalities afford me to do? Given such functionalities and affordances, should I buy it? Which other tools are available out there with the same features or affordances? This critical perspective enables us to navigate hype cycles with clarity and discernment, separating ephemeral trends from transformative innovations.

As we await the next wave of gadgets from Vegas, let’s embrace a (positively) critical mindset. By focusing on the substance behind the hype, we can uncover the technologies that will shape our digital future in meaningful ways. In a landscape dominated by novelty and excitement, it’s the thoughtful consideration of core features and affordances that ultimately guides us towards genuine progress.

 

[1] https://www.cnbc.com/2023/02/01/meta-lost-13point7-billion-on-reality-labs-in-2022-after-metaverse-pivot.html

[2] https://about.fb.com/news/2021/10/founders-letter/

[3] https://www.businessinsider.com/mark-zuckerberg-metaverse-not-majority-were-doing-facebook-meta-focus-2022-11?r=US&IR=T

[4] https://www.theverge.com/2024/1/13/24035152/ces-generative-ai-hype-robots

[5] https://www.ft.com/content/9c5f7154-5222-4be3-a6a9-f23879fd0d6a

[6] https://www.linkedin.com/pulse/8-lessons-from-20-years-hype-cycles-michael-mullany/

[7] DeSanctis, G. and Poole, M.S. (1994), “Capturing the complexity in advanced technology use: Adaptive structuration theory”, Organization Science, INFORMS, Vol. 5 No. 2, pp. 121–147.

[8] Markus, M.L. and Silver, M.S. (2008), “A foundation for the study of IT effects: A new look at DeSanctis and Poole’s concepts of structural features and spirit”, Journal of the Association for Information Systems, Vol. 9 No. 10, p. 5.

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Selling and monetizing data in B2B markets https://www.einst4ine.eu/selling-and-monetizing-data-in-b2b-markets/?utm_source=rss&utm_medium=rss&utm_campaign=selling-and-monetizing-data-in-b2b-markets https://www.einst4ine.eu/selling-and-monetizing-data-in-b2b-markets/#respond Fri, 08 Mar 2024 06:55:27 +0000 https://www.einst4ine.eu/?p=11464 This blog post is based on the findings of our research article, openly accessible and freely available here: https://doi.org/10.1016/j.technovation.2023.102935

What is data monetization?

Data monetization refers to the process of capturing monetary value from data by generating revenue through selling data, data-based products, and data-based services. It involves converting the intangible value of data into tangible financial returns.

Summary of ‘Demystifying Data Monetization’ (Gandhi et al., 2018). Created by author.

I was actually very new to this topic when I started this project, so as a fun way to get into the literature I generated a few visuals to help concretize the key learnings and takeaway. I share them here (above and below) to help give a snapshot of some of the foundational reading. At this time, I was lucky enough to gain the experienced wisdom from my co-authors, who publish works in this area such as ‘Three Ways to Sell Value in B2B Markets‘ (Keränen et al., 2021) and ‘Growth Reinvented: Turn your data and artificial intelligence into money‘ (Ruokonen, 2020).

Summary of ‘Monetizing Data’ (Liozu & Ulaga, 2018). Created by author.

Data monetization is crucial for organizations as it presents opportunities to create new revenue streams, drive innovation, enhance competitiveness, and unlock the full potential of data assets which can also contribute to environmental and social benefits. Despite the increasing trend towards data-driven offerings, many B2B firms face difficulties in effectively selling and monetizing their data.

How can data be monetized – what did we find?

We studied data-driven value propositions by 14 B2B companies, including ABB Group, Hilti Group, Kemira, Eagle Alpha, Kyndryl, Metso Outotec, Jakamo, and many others. Accumulating evidence from some of the authors’ previous work, the literature, and predominantly the interviews we conducted with key informants from our case companies, we were able to identify four different data-driven value propositions that B2B firms can use to sell and monetize data-driven offerings. These are:

  1. Data as a product – where raw or processed data is sold or shared with customers as a stand-alone offering. In this model, vendors typically sell their own data or data collected from public domains or other companies.
  2. Data-enhanced products – where existing product offerings are enhanced with data-driven features and functionalities. In this model, vendors embed for instance smart sensors, software, and IoT applications into physical products to collect, analyze, and monitor data on how customers use their products.
  3. Data-driven services – where vendors use accumulated data to analyze, predict, and optimize customers’ processes. In this model, vendors sell intangible insights and know-how through consulting services.
  4. Data-enabled performance outcomes where vendors combine data-enhanced products and data-driven services to deliver complete smart solutions that guarantee specific performance outcomes. In this model, vendors take responsibility for specific processes on behalf of their customers and sell measurable and guaranteed performance, capacity, or availability outcomes.

Each of these value propositions has its unique characteristics, capabilities, and challenges, and the study provides insights into how firms can transition between them and develop their data-driven offerings (see Table 2 in the paper).

These four propositions are not a step-by-step progression, as a firm can choose to develop one or more of these propositions and expand in either direction that suits the firm’s capabilities, resources, and goals at any given time. Although, it can be said there is a higher investment of resources and increasing complexity and challenges as you progress from 1 to 4 of the labelled propositions above.

We developed a continuum to visualize how firms often navigate between these different value propositions.

Data-driven value proposition continuum (Source: Ritala et al., 2023)

Data-driven value proposition continuum (Source: Ritala et al., 2023)

For example, Telia told us about their data-driven services such as Crowd Insights, where for instance they work with cities to support decision-making and planning for a more efficient and optimized city. Using aggregated mobile data (meaning it is anonymized and cannot be traced to the individual) the city can understand the movements of people to better organise road traffic and general services such as events. This innovation allows Telia to make use of their otherwise untapped data and open additional revenue streams, while creating both social and environmental benefits with better traffic flow and less crowding.

As another example, at Johnson & Johnson MedTech they design healthcare solutions that are smarter, less invasive, and more personalized. They told us about how they monetize data via their smart product  and technologies (data-enabled products). Ultimately, the goal is to make surgery safer and to reduce complications. Additionally, with data-enabled performance outcomes such as their Surgical Process Manager, they are able to standardize processes better which reduces errors and thus reduces complications in surgery.

Key implications for managers

We suggest that firms need to carefully develop and pilot new data-driven value propositions with their customers.

  • During this process, they should engage in organizational up-skilling, especially in terms of acquiring and developing new capabilities related to data collection and analysis, tech architecture, commercialization, sales, and marketing.
  • While the softer sales and marketing capabilities needed to understand and communicate the value of data-driven value propositions are often possible to learn and (re)train in-house, the more complex technical capabilities related to data collection, analysis, and interpretation usually need to be acquired externally through hiring or partnering with other firms.
  • It’s also important for firms to consider strategically how and to what extent they can monetize the data they can access and to address challenges with customer or industry maturity in terms of accepting and using novel data-driven solutions, which often require extra effort from suppliers to educate and shape those markets.

Our research article is openly accessible and freely available here: https://doi.org/10.1016/j.technovation.2023.102935

References:

Gandhi, S., Thota, B., Kuchembuck, R., Swartz, J., 2018. Demystifying Data Monetization. https://sloanreview.mit.edu/article/demystifying-data-monetization/

Keränen, J., Terho, H. and Saurama, A., 2021. Three ways to sell value in B2B markets. MIT Sloan Management Review, 63(1).

Liozu, S., Ulaga, W., 2018. Monetizing Data: A Practical Roadmap for Framing, Pricing & Selling Your B2B Digital Offers. Value Innoruption Advisors Publishing.

Ritala, P., Keränen, J., Fishburn, J. and Ruokonen, M., 2024. Selling and monetizing data in B2B markets: Four data-driven value propositions. Technovation, 130, p.102935.

Ruokonen, M. 2020. Growth Reinvetned: How to turn your data and artificial intelligence into money. Independently published.

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Transforming Healthcare Work: My experience at the CTWD Conference 2024 https://www.einst4ine.eu/transforming-healthcare-work-my-experience-at-the-ctwd-conference-2024/?utm_source=rss&utm_medium=rss&utm_campaign=transforming-healthcare-work-my-experience-at-the-ctwd-conference-2024 https://www.einst4ine.eu/transforming-healthcare-work-my-experience-at-the-ctwd-conference-2024/#respond Fri, 23 Feb 2024 07:00:59 +0000 https://www.einst4ine.eu/?p=11442 On February 13th and 14th I attended the Centre for Transformative Work Design Conference 2024 in Perth, Australia to enjoy all the presentations and share my research on work design as a catalyst to foster meaningful work during the implementation and use of mobile telepresence robots in healthcare settings. This conference set the stage for dynamic conversations on cultivating healthier, happier workplaces through the art and science of work design. 

EXPERT PANELS

I had the chance to attend different panels of experts where topics related to work design were discussed. It was great to learn from leading scholars and practitioners in the field of work design, gaining invaluable insights and practical knowledge from those at the forefront of innovation.

For example, Rob Baker, Founder of Tailored Thinking, led an engaging conversation with a panel of experts who delved into the current landscape of workplace quality improvements. Dave Burroughs, Chief Mental Health Officer at Westpac Group, highlighted the importance of shifting workplace mental health discussions towards prevention and offered practical advice for successful implementation. Professor Karina Jorristma, a Professor of Practice at the Future of Work Institute, Curtin University, shared insights from her experience implementing the Thrive at Work model and SMART work design across various organizations. Finally, Jim Kelly, Executive Director – Operations & Enforcement at SafeWork NSW, provided a regulatory perspective, discussing innovative initiatives to foster better work designs within industries.

Picture taken by Alejandra Rojas

SYMPOSIUMS

Symposiums were held for group presentations that were topic-related. I was especially interested in a symposium about “A practical approach to SMART work (re)design in the care sector” where multiple projects were presented. However, the one from Dr Jane Chong (University of Western Australia) was particularly interesting for me as it showed the outcomes of a participatory work redesign intervention and its success in alleviating job demands within an aged-care environment, which is related to my Ph.D. project as I am exploring how mobile telepresence robots (MTRs) can/should assist healthcare workers in settings like a nursing home. It was wonderful to explore real-world examples of successful work redesign initiatives that have enhanced employee well-being and organizational performance.

Picture taken by Alejandra Rojas

MY PRESENTATION

My presentation “Enabling Meaningful Work Through Work Design: A Study on Robots in Healthcare Settings” was on the 14th of February in a timeslot shared with Milan Wolffrgamm and Qi Fang, PhD colleagues who are also focused on the use of technologies and work design.

MTRs enable remote interactions between healthcare workers, patients, and family members in healthcare settings. However, it remains unclear how their implementation could affect meaningful work in such settings. Our qualitative study aims to investigate the types of interactions afforded by MTRs in healthcare and their implications on meaningful work. The data consisted of 25 interviews with and observations of healthcare professionals in three types of settings, where two different MTRs were tested. Findings show that substitution and coexistence interactions afforded by MTRs play a multifaceted role in meaningful work, as they simultaneously promote and inhibit it. However, we also find that meaningful work can be promoted through proper work design. Recognizing work design as a catalyst for fostering meaningful work during the implementation of MTRs in healthcare settings offers practical guidance to practitioners seeking to design, develop, implement, and utilize these robots while prioritizing meaningful work.

Picture taken by Henry Gunson

Overall, it was a great conference with lots of learnings and insights that helped me understand work design from different angles. Thanks to the organizers and sponsors!

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Our recent research has been published in a journal! https://www.einst4ine.eu/our-recent-research-has-been-published-in-a-journal/?utm_source=rss&utm_medium=rss&utm_campaign=our-recent-research-has-been-published-in-a-journal https://www.einst4ine.eu/our-recent-research-has-been-published-in-a-journal/#respond Mon, 18 Dec 2023 13:02:33 +0000 https://www.einst4ine.eu/?p=11290 I’m delighted to share our study, “Contamination Detection Using a Deep Convolutional Neural Network with Safe Machine Environment Interaction,” has been accepted for publication in MDPI Electronics Journal. This journey has been an effort of dedication, and I can’t wait to share our groundbreaking findings with you.

Understanding the Problem
Contamination detection is an important issue in many industries, including food processing, healthcare, and others. A primary focus is ensuring product quality and safety, and this is where our research comes in. Manual examination gets laborious and may result in contamination occurring along the production line. To solve this issue, a contamination detection system based on an enhanced deep convolutional neural network (CNN) in a human-robot collaboration framework is proposed.

Deep Learning: The Key to Precision
In our research, we enhanced Deep Convolutional Neural Networks (CNNs) to detect contaminants in food packages. CNNs are well-known for their ability to extract intricate patterns from complex data, making them perfect for tasks like object detection and analysis.

Safe Machine Environment Interaction
To improve our system’s performance, we coded the proximity sensor for “Safe Machine Environment Interaction.” A mechatronic platform with a camera for contamination detection and a time-of-flight sensor for safe machine-environment interaction was used for the experiment. The experiment findings show that the reported system can identify contamination with 99.74% mean average precision (mAP). Figure 1 depicts the experimental results, and the publication can be found here [1].

Figure 1. Experimental trials of real-time detection using the reported CNN [1].

Future Directions
Future work may concentrate on adding more contamination classes in order to create a more thorough and improved contamination detection system. The algorithm might also be applied in a real robot with a conveyor belt to create an industrial quality inspection setup. However, the journey does not finish here. We’re devoted to improving our methodology and investigating new applications. We’re thrilled to be at the forefront of the deep learning revolution.

Acknowledgments
I want to express my heartfelt gratitude to my Supervisor, colleagues, and the entire research team who played a pivotal role in this project. Their expertise, dedication, and collaboration made this achievement possible.

Paper Reference
[1] Hassan, Syed Ali, Muhammad Adnan Khalil, Fabrizia Auletta, Mariangela Filosa, Domenico Camboni, Arianna Menciassi, and Calogero Maria Oddo. “Contamination Detection Using a Deep Convolutional Neural Network with Safe Machine—Environment Interaction.” Electronics 12, no. 20 (2023): 4260.

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What Art can tell us about Digital Societies https://www.einst4ine.eu/what-art-can-tell-us-about-digital-societies/?utm_source=rss&utm_medium=rss&utm_campaign=what-art-can-tell-us-about-digital-societies https://www.einst4ine.eu/what-art-can-tell-us-about-digital-societies/#respond Wed, 06 Dec 2023 12:41:43 +0000 https://www.einst4ine.eu/?p=11123 What Art can tell us about Digital Societies

The representation of our society in cultural forms has fascinated me for a long time. Theatre, opera, dance, film, photography all have shaped my upbringing. It was during years of studying digital and creative media that I learnt more about the versatility of media and its representation of life and society at large—from a practical as well as theoretical lens.

First signs of art go back to the Stone ages. As put by Prof. Xiang Xiong Lin in this article in the Humanities, Arts and Society magazine, “Artistic cells are born within human blood. […] Art is the carrier of human culture, and culture is the platform of human civilization.“ Art holds a mirror to the time when it was created. As highlighted by the MET, “art from the past holds clues to life in the past. By looking at a work of art’s symbolism, colors, and materials, we can learn about the culture that produced it.” Equally, art from this century truly tells a lot about the times we live in today. How does technology change the perception about our identity? How does data drive objectivity and erase individuality? How do robots interact with humans?

I want to highlight here a few contemporary artworks that fascinated me in the past and may tell us, step by step, a little bit more about the era we call ourselves a part of or, at least, provide some thought provoking perspectives—on human civilisation in the digital era:

Exploratory Selfie or Selfiecity.Net, 2014, L.MANOVICH

© Lev Manovich

The presentation of the self. A topic that probably never experienced such a dramatic change like right now and within the digital age. Our self-representation is even so important since Instagram, and selfie-camera that Manovich decided to do an artwork on the topic “selfie”. The project is an interactive web app of 3200 Instagram selfies from different countries in the world (Bangkok, Berlin, Moscow, New York, and Sao Paulo). A software creates a certain visualisation of the photos. Via a computer that shows the web app the visitor can explore the dataset of selfies that is then projected onto the wall infront of the visitor. With other artists and specialists, Manovich wants to discuss the construction of self-representation in the digital age. He started analyzing the selfies with a special software, and visualizes the received data. The portraiture of a single person changes through history – from the art of painting, to the photography, to the selfie. The way the self is portrait changes with its society. The project of Manovich even argues if the selfie can be seen as a new sub-genre of photography.

“Selfie is not only a photographic image that we recognize as a self-portrait and which bears a formal resemblance to numerous canonical photographic self-portraits from the nineteenth and twentieth centuries. Instead, selfie is a product of a networked camera. […] While focusing on Instagram, one of several available platforms of online image-sharing, Selfiecity comments on the social media in general. The project views social media as a vehicle of voluntary interpersonal communication, and discusses the visual component of such communication.” (Tifentale and Manovich, 2015)

Face Cages, 2013-2015, Z.BLAS

© Zach Blas

Face Cages is an artwork that is critizising the biometric industry. Its measuring in an objective way is creating a cage. There is either 1 or 0. If you are too extraordinary for the system what are you then? Do you have to worry if your smile is not detected as a smile – by a software? The face cages are inflexible metal constructions for the face that look like a biometrical measurement of the facial factors. These biometric systems are a generalization of the human individuum that create stereotypes. The result is either discrimination, racism, sexism, transphobia or even homophobia. The discomfort the cages entail, dramatizes the discrepancy of the interaction of biometric norms and the individual person.

“Blas fabricated face masks that resemble iron muzzles based on the shape of biometric diagrams, evoking resonances with prison bars, the Scold’s Bridle, and torture devices used during slavery in the U.S. and in the Medieval period in Europe.”; “The different machinations of faciality […]—as a singular, unique, personal and identifiable security-check, as the imposition of a political norm, as collective empowerment, as a plural, multi-form, malleable and amendable canvas, as a means to play with identity, similarity and difference, and as a source of data extraction—indicate that supra-individual cultural narratives and concerns about policing and governance are braided around the algorithmic capture of the face.” (de Vries, 2020)

 

Drawings by Robot Paul, about 2013, P.TRESSET

© Patrick Tresset, Galleries West

After Tresset lost his passion for his hand drawn paintings he started building robots and he named them Paul. Paul is a robotic arm mounted on a table. Paul uses computer vision to recognize faces he then starts drawing on a paper in about 30 minutes. Through Paul, a robot becomes human. Art used to be made by human kind – what changes now, that even robots know how to draw a portrait? The boarders merge. But what stays is the fascination of only one human-like robotic arm that has the ability to identify a human face and to draw it.

“Paul is a naive drawer: it does not have highlevel knowledge of the structures constitutive of the human face (such as the mouth, nose, eyes) nor the capability of learning expertise based on experience as a human would. However, Paul is able to draw using the equivalent of an artist’s stylistic signature based on a number of processes mimicking drawing skills and technique, which together form a drawing cycle. […] Although the individual algorithms driving Paul are relatively simple and not particularly novel, the way in which they are combined is of interest as the drawings Paul produces are considered by professionals as being of artistic value, which is unusual for computer-generated figurative portraits” (Tresset and Leymarie, 2013)

 

Hysterical Machines, 2006, B.VORN

© Bill Vorn

Vorn creates a huge impressive installation with up to eleven dysfunctional machines hanging from the ceiling of the room. Each machine has eight arms made of aluminium reaching out from a spherical body. The machine works like a nervous system made of motor-, sensing-, and a controlling-system. This allows the machine to detect the visitors and react to them. The Hysterical Machines serve to exemplify the paradoxal nature of artificial intelligence. They provoke the visitor’s empathy as they are reacting to their appearance.

In addition to physically interacting with the audience, Hysterical Machines also initiate or establish an emotional relationship with the audience. Their hybrid status, combining the properties of living organisms (their behavior) and technical machinery (their appearance) causes viewers to re-act with a similarly structured ambiguity and ambivalence, in which affective emotions combine with cognitive interest and empathy mixes with primal anxiety and technophobia.” (Kluszczyński 2018)

 

What artworks do you find most remarkable for our digital lives?

To me, art still represents much about us, our past, our present, and makes us think about our future. To close, I choose the words of a popart legend:

“You need to let the little things that would ordinarily bore you suddenly thrill you.”  – Andy Warhol

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Reflecting on the Power of Platforms: Bridging the Industry-Academia Gap During My PhD Journey  https://www.einst4ine.eu/reflecting-on-the-power-of-platforms-bridging-the-industry-academia-gap-during-my-phd-journey/?utm_source=rss&utm_medium=rss&utm_campaign=reflecting-on-the-power-of-platforms-bridging-the-industry-academia-gap-during-my-phd-journey https://www.einst4ine.eu/reflecting-on-the-power-of-platforms-bridging-the-industry-academia-gap-during-my-phd-journey/#respond Thu, 30 Nov 2023 12:45:18 +0000 https://www.einst4ine.eu/?p=11185 During my academic journey as a PhD student, I’ve come to recognise the crucial role of platforms that facilitate interaction between academia and industry. For students like me, these spaces are not just areas of collaboration—they are realms of revelation. They have been pivotal in shaping my research, thinking, and understanding of how innovation and digital transformation play out in the real world. 

Real-World Context to Theoretical Studies 

Source: own photo.

The world of academia often revolves around theories, models, and conceptual discussions. While this is essential for foundational knowledge, there’s a palpable gap when it comes to understanding how these theories apply to real-world scenarios. This is where industry-academia collaboration platforms come in. They provide PhD students like me with the real-world context, helping us align our research with genuine industrial needs and challenges. 

For instance, at the recent EINST4INE summer school at the Institute for Manufacturing (IfM) I had the incredible opportunity to engage with leading professionals from various sectors. These interactions brought home the stark realities and specific challenges they face; insights that can’t be gleaned from a textbook or a lecture. 

Enabling Impactful Research 

One of the essential goals of any research, especially at the PhD level, is to have a genuine impact. The industry offers a testing ground for our theoretical frameworks and models. By understanding the problems industry actors face, we can tailor our research to propose effective solutions. 

During my interactions at the summer school, discussions on innovation ecosystems and roadmaps as technology strategy tools were incredibly enlightening. This exchange allowed me to consider the application of theoretical constructs in diverse industrial settings, pushing me to think of research areas that truly matter. 

At the recent EINST4INE summer school, I also had the opportunity to discuss some of my research findings with industry experts and gather feedback on managerial tools that translate my research into practical applications. This opportunity is invaluable for PhD students who often lack the ability to directly engage with industry leaders.  

Preparing for a Seamless Transition 

Beyond research, these collaborative spaces prepare us for the eventual transition to the industry (if we choose that path). By understanding industry dynamics first-hand, we are better positioned to add value from day one. For someone like me, keen on ensuring that my research contributes to real-world impact, these platforms have been instrumental in aligning my studies with industry requirements. 

In Conclusion 

In the evolving landscape of innovation and digital transformation, the need for collaboration between academia and industry has never been more critical. Platforms and spaces that foster such collaboration are the bridges that connect theoretical knowledge with practical applications. As a PhD student, I can attest to the immense value they bring—not just in enriching our research but in moulding us to be better contributors to the world of industry and innovation. 

 

 

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“No project is an island” https://www.einst4ine.eu/no-project-is-an-island/?utm_source=rss&utm_medium=rss&utm_campaign=no-project-is-an-island https://www.einst4ine.eu/no-project-is-an-island/#respond Mon, 20 Nov 2023 11:55:46 +0000 https://www.einst4ine.eu/?p=11279 In the world of academic research, it’s common to embark on a journey with a specific destination in mind (at least that was my path). Guided by established theories and prior studies, we often believe we know where our research will take us. My recent experience with a case study on innovation ecosystems, particularly focusing on environmental sustainability, was a humbling reminder of the unpredictable nature of inquiry.

As is the beauty—and sometimes, the frustration—of qualitative research (though it’s worth noting that surprises aren’t exclusive to this methodology), I was in for some revelations, when taking a closer look at how companies carry out projects…

… As I was delving into the practices of companies engaged in green transition projects, I encountered a case that exemplifies this perfectly: the renowned CopenHill facility in Copenhagen.

Source: (Rasmus Hjortshoj, Architect Magazine: https://www.architectmagazine.com/project-gallery/copenhill_o)

CopenHill is an example of a new breed of sustainability projects that are simultaneously functional and hedonistic. With its waste-to-energy plant, ski slope, and restaurant, CopenHill epitomizes the concept of “hedonistic sustainability”, a term brought to life by Bjarke Ingels, the architect behind the facility (Estika et al., 2020). Aimed at merging environmental responsibility with pleasure and aesthetic appeal, many of these new facilities stand as a testament to the interconnectedness of green projects with the social, cultural, and environmental fabric of their communities. They are “history-dependent and organizationally-embedded units of analysis” (Engwall, 2003), each following a unique trajectory influenced by a variety of factors.

Thus, the creation of such multifaceted projects involves a collaborative effort extending beyond the realms of engineering or business. To assess their success or failure, there is an increasing need to adopt inter- or multi-disciplinary approaches, as their implementation and development cannot be fully understood or effectively managed through a single field of knowledge. Instead, it requires the collaboration and integration of diverse disciplines, as I have come to realize. For this reason, the current findings of my case study research are steering me in a more sociological direction, to better understand the complexities of the green transition. In pursuit of this, I have enrolled in an immersive three-day course at Aarhus University, where I’ll delve into various sociological theories, including Actor-Network Theory and Transition Theory, to name a few. My aim is to enrich my comprehension of the historical and environmental contexts that surround my case study.

Of course, I’m eager to share my discoveries along the way, so stay tuned for more updates and revelations!

 

References:

Engwall, M. (2003). No project is an island: Linking projects to history and context. Research Policy, 32(5), 789–808. https://doi.org/10.1016/S0048-7333(02)00088-4

Estika, N. D., Kusuma, Y., Prameswari, D. R., & Sudradjat, I. (2020). The hedonistic sustainability concept in the works of Bjarke Ingels. ARTEKS : Jurnal Teknik Arsitektur, 5(3), 339–346. https://doi.org/10.30822/arteks.v5i3.487

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Oppenheimer: The role of academia in technology innovation processes https://www.einst4ine.eu/oppenheimer-the-role-of-academia-in-technology-innovation-processes/?utm_source=rss&utm_medium=rss&utm_campaign=oppenheimer-the-role-of-academia-in-technology-innovation-processes https://www.einst4ine.eu/oppenheimer-the-role-of-academia-in-technology-innovation-processes/#respond Tue, 07 Nov 2023 11:24:56 +0000 https://www.einst4ine.eu/?p=11226 As a fan of Christopher Nolan and a researcher in the innovation management field, I couldn’t help but be excited by the release of “Oppenheimer”. As you may know, the movie describes the life of the American theoretical physicist J. Robert Oppenheimer, focusing on his time as a student, his leadership role in the Manhattan Project to develop the atomic bomb, and his downfall after World War II.

Atomic Bomb vs AI: similarities and differences

The movie has sparked many conversations in the public opinion about how the development of the atomic bomb resembles the dangers of an uncontrolled Artificial Intelligence (AI) use (Scientific American; Guardian; Wired). While these two innovations have some similarities, it is important to recognize their differences, too.
First, as also Nolan noted: “It’s reassuringly difficult to make nuclear weapons and so it’s relatively easy to spot when a country is doing that. I don’t believe any of that applies to AI.” Second, while AI is a broad term that covers a wide range of tools, nuclear fission is a specific chemical reaction with clear and known applications. Third, in this regard, if the atomic bomb detonation is the expected result of a process controlled by humans, most generative AI models are currently neither explainable nor predictable black boxes (repeating the same prompt may produce different results for which the machine was not even trained).

Thus, what can we learn from this movie that could still be relevant today and for future (revolutionary) innovations?

I believe that the most important takeaway is that the role of academia should not only be limited to develop innovations; rather, academics should also be actively involved in setting the rules and sensitize for a responsible use of the technology they contributed to being invented.
I will tell you more about it in the next paragraphs.

Academic activism

Nuclear activism

“This isn’t a new weapon, it’s a New World.”

After the two atomic bombs were dropped on Hiroshima and Nagasaki, Bohr’s prediction came true. The world changed forever. This is when Oppenheimer joined the already heated debate on using the bomb and began opposing the development of the H-Bomb. On this matter, he says in the movie that:

Having played an active part in promoting a revolution in warfare, I needed to be as responsible as I could with regard to what came of this revolution.

However, this position turned to be more problematic than expected. Several scientists that played a key role during the war were increasingly excluded from influential positions when it came to the future of atomic energy, due to their criticism (Bulletin of the Atomic Scientists). For Oppenheimer, this period reached its peak with the loss of his security clearance (Avalon Project). Nonetheless, academia managed to play a vital role in regulating atomic energy.

Particularly, Linus Pauling, an American chemist that received the Nobel Prize in Chemistry in 1954, had a huge influence on the U.S. public opinion in the disarming process and ban of nuclear weapons tests. In 1958, together with his spouse, he submitted a formal petition to the United Nations, urging the cessation of nuclear weapons testing. This document was signed by 11.021 scientists representing fifty countries. Moreover, Pauling also supported the research known as the “Baby Tooth Survey”, which provided legitimacy and a crucial boost to public opinion demands (Wikipedia).

Public pressure and the results of this research contributed to the signature of the moratorium on above-ground nuclear weapons testing, followed by the Partial Test Ban Treaty in 1963, between John F. Kennedy and Nikita Khrushchev. For his activism, Pauling received in that year the Nobel Peace Prize, which made Pauling the only person to have been awarded two unshared Nobel Prizes.

Linus Pauling debating Edward Teller on the topic of nuclear fallout: "The Nuclear Bomb Tests...Is Fallout Overrated?" KQED-TV, San Francisco. February 20, 1958. - Pictures and Illustrations - Linus Pauling and the

Pauling and Teller TV debate Source: Oregon State University

Other examples

Nevertheless, this is not an isolated case. The scientific community has played a pivotal role in regulating scientific innovations in other instances, too. The regulation of genetic engineering is another example (Krimsky, 2005).

The first publications describing the successful production and intracellular replication of recombinant DNA appeared in 1972 and 1973. Recognizing both the benefits and risks of this innovation, a group of experts (mainly biologists, but also including lawyers and physicians) met at Asilomar in 1975. During this conference, the experts discussed these concerns and a voluntary moratorium on recombinant DNA research was introduced for experiments that were considered particularly risky. These guidelines eventually informed the regulation set by the National Institutes of Health (USA) in the following years, which formally limited rDNA applications (Wikipedia).

Conclusion

The development of new technologies is leading us into an era of rapid transformation across various aspects of our lives. From Large Language Models to Blockchain, the pace of change is accelerating, while regulations often struggle to keep up (GZero).
In light of this, it is evident that academia’s role extends beyond just fostering the development and commercialization of new technologies. It also involves championing a responsible approach to innovation.

Engaged scholarship is a great starting point to increase the likelihood of advancing knowledge for science and practice (Van de Ven, 2007). However, as we have seen, sometimes the role of experts and citizens blur (Hoffman, 2016), making it necessary to reach another level of engagement: an engagement that leads to moving beyond the ivory tower of academia.

 

References

Hoffman, A. J. (2016). Reflections: academia’s emerging crisis of relevance and the consequent role of the engaged scholar. Journal of Change Management16(2), 77-96.

Krimsky, S. (2005). From Asilomar to industrial biotechnology: risks, reductionism and regulation. Science as Culture14 (4), 309-323.

Van de Ven, A. H. (2007). Engaged scholarship: A guide for organizational and social research. Oxford University Press, USA.

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Wasen Beers, Workshop Cheers, and Cobot Gears: Stuttgart’s Workshop Fiesta https://www.einst4ine.eu/wasen-beers-workshop-cheers-and-cobot-gears-stuttgarts-workshop-fiesta/?utm_source=rss&utm_medium=rss&utm_campaign=wasen-beers-workshop-cheers-and-cobot-gears-stuttgarts-workshop-fiesta https://www.einst4ine.eu/wasen-beers-workshop-cheers-and-cobot-gears-stuttgarts-workshop-fiesta/#respond Mon, 30 Oct 2023 11:38:28 +0000 https://www.einst4ine.eu/?p=11235 Hey everyone!

If you think life as a PhD student is just about boring books and endless research, think again! My last few weeks have been a whirlwind of cool events, amazing people, and lots of learning. Let me take you on a quick tour.

A Dive into Enabling Technologies at Stuttgart

In the heart of October, I found myself amidst the historic beauty of Stuttgart, ready to attend a workshop hosted by the University of Stuttgart. The central theme of the event revolved around enabling technologies and their pivotal role in the digital transformation.

The workshop spread over three days, promised – and delivered – a potpourri of informative sessions, panel discussions with industry stalwarts, and glimpses into the future of digital advancements. From discussing AI and data’s role in research to exploring the dynamics of enabling technologies for ecosystems was genuinely enriching.

A personal highlight for me was the chance to present my ongoing research project on the implementation of collaborative robots (or cobots) in SMEs. It’s a subject I’m deeply passionate about, as emphasized in my paper titled “Cobots in SMEs: Processes, Challenges, and Success Factors”. The feedback and interactions that followed the presentation were invaluable, offering diverse perspectives and new angles to consider in my research.

Participants at the EINST4INE Workshop in Stuttgart

Participants at the EINST4INE Workshop in Stuttgart (Source: photo taken by Christina Theodoraki)

A Taste of Local Culture

Before the intellectual marathon began, a few colleagues and I took a cultural detour to the vibrant Wasen event in Stuttgart. It was a delightful amalgamation of tradition, laughter, and shared memories – a perfect start to an intense week.

Reaching Out to the World

Another proud moment was presenting my conference paper remotely at the IEEE TEMs conference in Lithuania. The virtual platform extended the reach of my work to a global audience. Engaging with professionals and academicians from different corners of the world brought forth a myriad of viewpoints, making the experience thoroughly enlightening.

Looking Ahead

The journey, as they say, is never-ending. As I pen down these words, I’m in the midst of preparing a poster presentation for the upcoming World Open Innovation Conference in Bilbao, Spain, this November. I’m eagerly looking forward to further collaborations, feedback, and the joy of sharing my work with a broader audience.

In the world of academia, every day brings new challenges and revelations. These events and interactions have been instrumental in shaping my thought processes and providing direction to my research. I’m grateful for these opportunities and excited for the road ahead.

Until my next update, stay curious and keep exploring!

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Demystifying the academic career https://www.einst4ine.eu/demystifying-the-academic-career/?utm_source=rss&utm_medium=rss&utm_campaign=demystifying-the-academic-career https://www.einst4ine.eu/demystifying-the-academic-career/#respond Thu, 19 Oct 2023 10:29:57 +0000 https://www.einst4ine.eu/?p=11238 The EINST4INE network recently all met in Germany for our ‘Enabling Technologies Workshop’ hosted by the ENI team at the University of Stuttgart. As I reach the end of my second year of doctoral studies, I find myself mulling over career options post-PhD. The final session of this workshop gave us the opportunity to hear from highly successful academics (thank you to our energetic and passionate guest Christina Theodoraki for candidly sharing her career journey) and a safe space to ask many pending academic career questions to our experienced seniors. Here are some of my key takeaways and reflections:

A career in academia can be scary…

Firstly, I often already get asked “what do you actually do?” or “when you are getting a real job? Are you going to be a student forever?” to which I often laugh and even agree. If I can’t even explain what I do, how do I expect anyone to understand it? Perhaps I am on a path of being an eternal student, so what ‘value’ does that bring to the ‘real world’? This is difficult to justify. For some entertaining consolement on this issue, you can read De Vaujany’s (2016) expression of trying to answer what a management researcher does at a dinner party.

Secondly, even if you have figured out how to articulate what you do, you also have to believe it yourself. Many people in general suffer from imposter syndrome, but especially so in academia where we are trying to push the boundaries of knowledge, experiencing feelings of self-doubt regarding our intellect and abilities which is very challenging to overcome. Bothello and Roulet (2019) wrote a provoking essay in Journal of Management Studies, which outlines imposter syndrome in academic life, particularly for PhD students considering a career in management academia, that I recommend anyone in this position to read.

Thirdly, I am sure anyone reading this is familiar with the “publish or perish” culture. Particularly as a PhD student, even more so if publishing is a requirement of your PhD, this culture can feel overwhelming. Not only are we expected to publish, but to publish in highly ranked journals that can take years to develop, in order to advance one’s career. Even once you manage it, you’re then expected to do it more. Working in academia, you can easily fall victim to defining your worth through your h-index or publication output which seldom has positive outcomes, particularly for your mental health.

But it can also be exciting…

Firstly, as scientists, it is our job and our privilege to understand how the world works. Prompted by some wisdom from Calogero Oddo, us junior researchers realised that instead of talking about what we have done, we should perhaps focus on the how and the why. For a number of reasons, we tend to make a habit of reporting the quantitative metrics and measures e.g., I published in X journal, I attended Y conferences, as opposed to reporting on the science we are creating – those valuable insights that will help to push our field(s). I feel like sometimes I forget that I am working in such an exciting domain, and while I am not inventing any breakthrough concept, I am contributing knowledge and understanding to our collective discoveries.

Secondly, while I often get frustrated with the focus on pushing out publications rather than a focus on slow exploration and deep learning, reflecting with peers in industry and often those that completed a PhD themselves, it seems I can still be grateful that in academia we are spending time on questioning the why rather than pushing on with how and doing (sometimes before thinking). Both are vital, but it seems for those with curious minds then academia allows you to play and explore and question which is a wonderful thing.

Thirdly, since this line of work often includes international collaboration with a broad range of people (other scholars, organisations, institutions) we have so many exciting opportunities to explore the world to help understand it and ourselves. It might not be for everyone, and I am also acutely aware of the privileges in the ability to travel and attend conferences both personally and institutionally, but typically a career in academia opens you up to many experiences abroad whether it be through travel or through your colleagues and their diverse backgrounds.

Becoming a researcher or a scholar

A reflective moment I had as a result of some conversations during this workshop was that the terms “researcher” and “scholar” are often used interchangeably, but they can have slightly different connotations. A researcher is primarily focused on the systematic investigation of questions, problems, or phenomena to generate new knowledge, while a scholar is someone deeply engaged in the broader intellectual life of a field, which may include research, teaching, writing, and contributing to the academic community. While you can be both a researcher and a scholar, it is perhaps not often that you have the opportunity to be “scholarly” when you are working outside of academia.

Bottom line – you can make it your own and there are always choices.

There are many different pathways in an academic career, which even differentiates further depending on the country and institution you are based at. In light of this, in the final years of my PhD I will try to focus on:

  • Engaging with different types of scholars and researchers to uncover the more ‘unknown’ or less obvious pathways,
  • Understand what is meaningful to me without all the external pressures, topic hype, and noise,
  • Determine what is realistic for me and which sacrifices I am willing to take or not take (which may look very different to others),
  • Reflect on what my definition of success is,
  • And consider what kind of impact I would like to make (on myself, colleagues, project partners, and even society more generally).

References:

Bothello, J., & Roulet, T. J. (2019). The imposter syndrome, or the mis-representation of self in academic life. Journal of Management Studies, 56(4), 854-861.

de Vaujany, F.-X. (2016). ‘The dinner: How can we explain management research just before dessert?’. Management, 19, 330–334.

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In-between Places: How to work and travel during your PhD https://www.einst4ine.eu/in-between-places-how-to-work-and-travel-during-your-phd/?utm_source=rss&utm_medium=rss&utm_campaign=in-between-places-how-to-work-and-travel-during-your-phd https://www.einst4ine.eu/in-between-places-how-to-work-and-travel-during-your-phd/#respond Sun, 08 Oct 2023 17:24:07 +0000 https://www.einst4ine.eu/?p=11115 In-between Places: How to work and travel during your PhD

Why do you go away? So that you can come back. So that you can see the place you came from with new eyes and extra colors. And the people there see you differently, too. Coming back to where you started is not the same as never leaving.” – Terry Pratchett

Originally, I was convinced that doing a PhD means to sit in a dusty, dark office corner at the end of a long echoing corridor of a university. And that may still hold true for some PhD candidates, frankly, I don’t know. Studying one topic in-depth for 3 to possibly many more years, turning that one coin over and over again, that does not exactly sound like a roller-coaster ride. It sounds like a long sweaty marathon when the skies are grey, everyone else is running in front of you, and the cheerleaders have gone home. But that is not it.

Embarking on a PhD journey may seem like a black box at first. Luckily, in my case, this does not describe my office situation. The black box is rather the many things that you figure out along the journey and that uncover over time and that includes the research output as well as the steps to get there. Against assumptions, two years into the journey, the ride continues to be exciting and somewhat mysterious. The times I spent sitting at a desk are finely interwoven with another trip to book, another chance to mingle and learn, another part of the chain to get to the next step.

The requirement of the EINST4INE program to move into another country was what drew me to it. I moved from Berlin to Barcelona in less than 2 months (the time frame is not my personal recommendation, but it worked out in the end!). Ever since, I get to enjoy an environment that was new to me, I am learning a new language and a new way of living—la vida loca. Aside from finding a new place to call home, the consortium also gets together on a regular basis, be it in Denmark, Italy, recently the United Kingdom – or soon in Stuttgart in southwestern Germany. And, of course, conferences, workshops and similar events are vital for joining the academic community, finding like-minded peers, and exchanging on the most recent findings.

While last year I was able to spend 4 months on an industry secondment in southern Norway, I kicked off this year with a joyful 3-months stay in Melbourne at RMIT. And here are some things that I learnt during my trips away thus far:

  1. Leaving your comfort zone is never easy, but can be very rewarding when you keep an open mind to experiencing something new everyday
  2. Planning early on and ahead of time can help to get adjusted more easily and prepare for the new setting (and safe money of your budget for another trip instead)
  3. Networking and getting to know new people are often the highlights of spending time abroad, especially if you can find people to discuss your topic with and get new ideas for your work, you may even make new friends for life
  4. Balancing to try new things and maintain regular habits (e.g., workout, sleep schedule, etc.) can be helpful to challenge yourself and expand your horizon while also keeping connected with your “home base self” for when your trip ends
  5. Exploring a new city and what it has to offer such as restaurants, museums, sights, and nature will provide many opportunities for experience and insight that can sometimes provide new angles on existing thoughts (especially for your research)—go explore and sleep when you are back home 😉

Looking back on every conference, every seminar, every dinner networking I thus far attended, each event provides such a unique value, adding to the pages of the PhD diary. Finally, my favorite saying goes like this: Don’t wait to be sure—move, move, move!

 

© phdcomics by Jorge Cham

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