This post began as a five-minute conversation during a meeting last week. It was not on the agenda, spontaneous and it stuck with me. It revealed a small but telling glimpse into the more complicated, sometimes darker, side of academia and research assessment.   “I disagree, Mahmoud. I still believe citation counts are one of the most meaningful indicators we have for measuring research impact. They’re tangible and quantifiable, proof that your peers found your work relevant enough to reference.”   “I see your point, Elena” (not her real name), “but don’t you think citations only tell part of the story? Citation practices differ significantly across disciplines. For instance, citation rates in the natural sciences are far higher than those in the humanities, so comparisons become quickly misleading.”   “But Mahmoud, that’s why metrics like the h-index are useful. They balance productivity and impact, at least within the same field.”   “Okay, perhaps. But even the h-index doesn’t explain the why behind a citation. Some papers get cited not because they’re brilliant, but because they’re flawed or controversial. So in my view, citation counts often reflect visibility, not necessarily scholarly value.”     Then... silence. The conversation moved on, but I couldn’t shake it.   Over the following days, I revisited a few articles to better understand what citations actually mean. And that’s where this post comes in. It is a personal attempt to unpack the ongoing debate around the role of citation counts in academic evaluation.   So, What is a Citation Anyway? Citations have long been used as a key indicator of academic impact. They serve as a measurable way to assess how often a piece of research is referenced in other scholarly work. At first glance, they offer clarity: the more cited a publication is, the more influential it appears to be – this is the argument I used also in my PhD about using specific article! Bornmann and Daniel (2008), in their study on citation behaviours, found that a high citation count often suggests a work has significantly contributed to its field, shaping discussions and future research. Hirsch (2005) added to this by proposing the h-index, a metric aimed at capturing both the productivity and the citation impact of a researcher’s publications. On a personal level, I’ve found citations can act as motivation. Knowing that your work might be cited can encourage higher standards of rigour and relevance. And in many cases, highly cited papers do represent foundational or groundbreaking contributions. They help orient new scholars and identify key literature within a field.   But It’s Not That Simple The more I reflected, the more I realised how fragile this metric can be, especially when we consider where a publication appears and in what language. English-language journals, particularly those indexed by platforms like Web of Science and Scopus, dominate the global citation landscape. As van Leeuwen et al. (2001) highlighted, this creates a systemic bias. Research written in other languages (no matter how insightful or locally impactful) is often overlooked in citation databases. This bias doesn’t just marginalise non-English research; it also sidelines entire regions, particularly in Latin America, the Middle East, Africa, and parts of Asia. But the issue goes deeper than language, it’s geopolitical. Top-tier journals are largely situated in the Global North and embedded within Western academic networks. As a result, work that addresses region-specific challenges, employs local epistemologies, or centres non-Western knowledge systems can be left out of mainstream discourse, not because it lacks quality, but because it’s outside the dominant structures of visibility and access. Then there’s the question of disciplinary variation. Comparing a highly cited paper on stem cell research with one exploring the subjectivity of feeling makes little sense, not because one is more important than the other, but because their fields function differently. The very nature of citation behaviour is context-dependent. Let’s not forget questionable practices either. Fong and Wilhite (2017) exposed how self-citation, coercive citation, and citation rings can distort citation counts, undermining their credibility. And as Bornmann (2013) argues, citation metrics primarily capture academic influence, they often ignore broader contributions to society, policy, or practice.   So... What Should We Do? Despite these limitations, citation counts aren’t without value. They can offer a snapshot, one way of looking at research influence. But they shouldn’t be treated as the sole measure of scholarly worth. That’s where alternative metrics (or altmetrics) come into play. These consider mentions in media, social platforms, policy documents, and public discourse. They help broaden the understanding of what impact looks like in practice. Ultimately, combining quantitative tools (like citation counts and h-indexes) with qualitative assessments (like peer reviews and real-world case studies) offers a richer, fairer, and more accurate picture of academic contribution. That five-minute conversation reminded me how much we often rely on numbers to validate our work, and how easily those numbers can mislead us. Citations matter, but so does context. So does equity. So does real-world relevance. If we’re serious about rethinking research impact, we must be willing to look beyond what’s easily counted and start valuing what’s harder to measure.     References Bornmann, L. (2013). What is societal impact of research and how can it be assessed? A literature survey. Journal of the American Society for Information Science and Technology, 64(2), 217–233. https://doi.org/10.1002/asi.22803 Bornmann, L., & Daniel, H.-D. (2008). What do citation counts measure? A review of studies on citing behaviour. Journal of Documentation, 64(1), 45–80. https://doi.org/10.1108/00220410810844150 Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output. Proceedings of the National Academy of Sciences, 102(46), 16569–16572. https://doi.org/10.1073/pnas.0507655102 Van Leeuwen, T. N., Moed, H. F., Tijssen, R. J., Visser, M. S., & van Raan, A. F. (2001). Language biases in the coverage of the Science Citation Index and its consequences for international comparisons of national research performance. Scientometrics, 51(1), 335–346. https://doi.org/10.1023/A:1010549719484 Fong, E. A., & Wilhite, A. W. (2017). Authorship and citation manipulation in academic research. PLOS ONE, 12(12), e0187394. https://doi.org/10.1371/journal.pone.0187394

It has been a while since I defended my PhD thesis—an experience that now feels like both yesterday and a distant dream. The days following the defence were swallowed by a web of administrative requirements, final submissions, and the strange emotional vacuum that comes once the adrenaline wears off.Since then, I’ve been asked one particular question countless times: “How did you manage to complete your PhD in three years?” Well, in fact, a bit less than three years. And while I always try to give an honest answer, I find that the question itself deserves a bit more unpacking. Because, simply put: yes, it is entirely possible to complete a PhD in three years. However, whether one should focus on that specific timeframe is an entirely different argument. So, in this highly personal reflection, I want to talk about the realities—both subtle and stark—of doing a PhD on a fast timeline. Not as a how-to guide, but as a window into what it meant for me, and why I think the timeframe is something we need to talk about more openly.   The Myth of the Three-Year PhD   There’s a kind of unspoken mystique around finishing a PhD “on time,” especially in the UK where three years is often considered the standard. People hear "three years" and assume a kind of academic sprint—where discipline, brilliance, and planning align perfectly to cross the finish line. But in practice, finishing within that window depends on a complex interplay of factors: institutional support, supervision quality, personal motivation, life circumstances, research feasibility, and yes, luck. In my case, one of the most decisive factors was the unwavering support and guidance of my supervisors: Professor Karim Hadjri and Dr. Krzysztof Nawratek. They weren’t just academic mentors—they were allies throughout the process. Their feedback was consistently sharp, constructive, and timely, allowing me to stay on track without the prolonged silences that many doctoral researchers unfortunately experience. They understood the rhythm of the PhD journey, and they respected the intensity of the path I chose to take. I should also acknowledge the significant role of the RE-DWELL project consortium in providing comprehensive support. For example, I didn’t worry too much about data collection, as secondments were already integrated into the project. I always knew there were highly specialised contributors I could consult and ask for help when needed. I was also given the freedom to develop my own ideas while being guided by researchers who genuinely cared about both the research and the researcher. That made a huge difference—not just in finishing on time, but in emerging from the PhD with confidence and clarity. But I want to be very clear: none of this made it easy, nor should it suggest that a PhD should be limited to a three-year timeframe.   What It Actually Feels Like – My Strategy for a Sustained Rhythm   If I were to sum it up, it feels like constantly living in the tension between focus and exhaustion. On the one hand, there’s a deep satisfaction in watching your work come together in a concentrated period of time. There’s clarity that comes from momentum—a rhythm that can carry you forward through difficult patches. On the other hand, it’s intense. The emotional and intellectual toll of sustaining deep engagement with one topic for nearly three years—without long breaks, without fully detaching—is not insignificant. Burnout is a real risk. There were months where writing consumed my weekends, and weeks where I didn’t sleep well because a paragraph or argument just wouldn’t settle. You get to the end, yes—but sometimes, you're not sure which version of you has actually arrived. Balancing both my doctoral work and the demands of the RE-DWELL project required more than just time management—it required clarity. Out of this necessity, I developed a simple but effective framework I now refer to as CPA: Categorise, Prioritise, Act. C – Categorise: I began by classifying my activities into core areas — such as research, teaching, writing, and public engagement. This helped me see the broader picture, rather than drowning in a long, unstructured to-do list. P – Prioritise: I then assigned levels of urgency to each task — immediate, high, medium, or low. This allowed me to be realistic about what needed attention now and what could wait without consequence. A – Act: Finally, I allocated time and energy to each task based on both its urgency and its relevance. I learned to distinguish between what was critical and what was simply noise. Not everything needed to be done right away — and not everything needed to be done by me. CPA became more than a productivity tool. It was a mindset that helped me navigate a high-pressure environment with competing demands. Most importantly, it gave me permission to be selective — to stay focused without feeling guilty for not doing everything, all the time.   Why the Timeframe Matters   Some might ask, “Why not just take longer and reduce the pressure?” And that’s a fair question. But the answer isn’t always so simple. For many of us, time is a structural constraint. Funding runs out. Visas expire. Life commitments press in. The pressure to finish "on time" isn’t just internal—it’s embedded in the system. And yet, I believe we should stop treating the three-year finish line as the gold standard of a successful PhD. It's a milestone, yes, but not a measure of academic worth. Some of the most thoughtful, nuanced, and field-defining PhDs I’ve read were written over four or even five years. Some needed time to mature, to pivot, to deal with life. So when people ask me how I did it, I answer honestly. But I also try to reframe the conversation: “It’s not about how fast you go. It’s about what kind of researcher you become along the way.”   Final Thoughts: It's a Journey, Not a Deadline   Completing a PhD in under three years was a massive achievement, and I’m proud of it. But I’m also aware that it came at a cost. There were things I had to say no to. Moments of rest I had to postpone. Conferences I couldn’t attend, and connections I didn’t build. Would I do it the same way again? Honestly, I’m not sure.  What I do know is this: speed should never be the only lens through which we measure doctoral success. Let’s talk more openly about the different paths through a PhD. Let’s make room for the slow thinkers, the deep feelers, the ones who need time. And for those who choose or need to finish quickly: I see you too. I hope you’re taking care of yourself after the storm.

Spending a month at Casais, a leader in industrialised construction, was an enlightening chapter in my academic journey. This secondment offered a unique opportunity to deepen my understanding on multi-family housing projects built with industrialised methods and explore ways to integrate customisation strategies within their processes. From semi-structured interviews with diverse practitioners to factory and site visits, the experience provided rich insights into both the potential and challenges of industrialised construction.   The cornerstone of my secondment was the series of interviews I conducted with key professionals across Casais and Blufab, its manufacturing division. Engaging with individuals like Miguel Pires, Technical Director, and Filipa Rocha, Project Coordinator, helped me appreciate the transdisciplinary collaboration integral to their operations. These conversations revealed how industrialised construction can optimise time, reduce waste, and enhance environmental sustainability through precision and digitisation.   Highlights included discussions on how prefabricated components, built in controlled environments, become traceable material banks that reduce lifecycle costs. Equally interesting were the efficiency gains from high levels of digitisation, such as Building Information Modelling (BIM), and collaborative tools like a Common Data Environment (CDE). These enable effective coordination, clash control, and integration of learning loops to refine fabrication processes.   However, the interviews also shed light on significant barriers to customisation. A major challenge is the mismatch between traditional design approaches and industrialised systems like CREE or Blufab. Often, projects arriving at Casais are not designed with these systems and their constraints in mind, leading to inefficiencies when attempting to "industrialise" them post-design. Economic limitations and low digitisation further restrict flexibility, highlighting the need for early decision-making and client commitment to reap the full benefits of industrialised methods.   Factory visit to Blufab: Precision and Potential   At Blufab, I observed the production of bathroom pods—a fascinating glimpse into how standardisation and customisation could intersect. Each pod's light steel frame is pre-cut, labelled with unique codes, and mechanically assembled, ensuring both precision and future disassembly potential. Additionally, a Kanban system tracks assembly progress digitally, allowing managers to address delays promptly.   The potential for customisation in Casais’ assembly line lies in a catalogue of standard wall dimensions that enable variability while maintaining efficiency. However, introducing greater diversity in panel sizes can slow production, a challenge that could be addressed with increased automation. Sustainable innovations, such as replacing concrete bases with lightweight solutions and transitioning to horizontal tile installation, demonstrate how Casais continually refines its processes.   On-site at Valença   My visit to a student housing project in Valença offered a firsthand view of industrialised assembly. The structure and façade, built with the CREE system, and 3D bathroom pods exemplified just-in-time delivery and reduced on-site storage needs. Observing the interplay between traditional construction elements and prefabricated components highlighted the importance of understanding tolerances and sequencing for seamless assembly. Furthermore, analysing interconnected systems as a whole, rather than in isolation, proved vital for understanding the complex dynamics of industrialised construction.   Although the project’s standardised design suited its purpose as student housing, it highlighted the trade-offs between flexibility and efficiency. Insights from this visit will inform strategies for balancing standardisation and customisation in more varied housing typologies.   Towards a platform approach   One of the most promising takeaways from my secondment was recognising the potential of the platform approach. Unlike the current focus on standardising entire buildings, standardising individual components, its fabrication processes, controlling its supply chain and storing the company’s expertise, could enable greater flexibility and scalability. This shift could support customisation while maintaining efficiency, allowing  Casais to improve its housing solutions.   Reflections for my research   The secondment built on methodologies I developed during my earlier placements at La Salle and TU Delft. It allowed me to evaluate the industrialisation degree of a multi-family housing case study and identify barriers and enablers to implement mass customisation. By engaging with the professionals at Casais, I gained a deeper understanding of transdisciplinary collaboration’s role in fostering innovation.   These insights will nurture the study I am developing, outlining short-, medium-, and long-term strategies to integrate flexibility into industrialised housing projects. This approach aligns with Casais' broader goals of improving efficiency, sustainability, and adaptability in their construction systems.   All in all, my time at Casais reinforced the importance of bridging traditional construction mindsets with innovative approaches. By fostering collaboration and leveraging digital technologies, we can unlock the full potential of industrialised construction to create more resilient, adaptable housing solutions for the future.