Place Iteration and Integration: How Digital Nomads Navigate the Mobile Worker Paradox

It is a pleasure to have you here! Our question starts with research and content, and the second set will be more about the research process and how you conduct the research, and then the last part is, we call it, flexible questions. We have questions related to our real world. For the first question… I saw your paper mention in the end about the implication to the leaders in the company. Because the leaders, trying to bring those workers to… back to office. There’s a trend after COVID. because they saw that the remote workers or digital nomads are not productive, so they tried to bring them in, or … unfortunately fired them. So, whether they misunderstood about the office space. What do leaders misunderstand, and then why are they making those work environments, and then how we, as scholars, should think about this office space?

Professor Melanie Prengler: What a great question. I feel like I could do a whole paper just on this. So, one of the things that I think leaders misunderstand is the idea around office space. First of all, when they think about office space, what a lot of managers think about is the physical work location as being inherently connected to what workers are doing. Which does make sense, right? Our environment affects us. It’s not a ludicrous assumption for them to have. It also makes sense that, when you take people out of that environment, there would be different challenges about executing their work well that might not have come up in the office environment. I think what leaders have really misunderstood is that the choice isn’t “have people work from home with no structure and no organizational support or guidance”, or “work in this very structured environment between this time and this time on these days of the week, and you have to report here.” There is something to be said about trying to figure out how to support employees who are mobile. So, just the same way that organizations leverage office design, HR, and technology to support employees, there are ways to support people in their home offices, and finding ways to help people navigate work effectively outside of the physical organizational environment is something I think managers should experiment with first before mandating return to work.

“So, just the same way that organizations leverage office design, HR, and technology to support employees, there are ways to support people in their home offices, and finding ways to help people navigate work effectively outside of the physical organizational environment is something I think managers should experiment with first before mandating return to work.”

And then, I think also.. it’s hard to put the toothpaste back in the tube when you give people freedom. So… people have this experience of being able to work remotely, or being able to travel, or being able to just even do the little things during the day, like change the load of laundry, or take their kid to a doctor’s appointment, and make up for that time in the evening. That is helpful for people’s work-life balance, it’s helpful for their life satisfaction, it’s helpful for their organizational commitment. They appreciate when organizations give that to them, and then taking it away and being forced to go back, it’s almost… it stings worse than if they just had this lower degree of autonomy to begin with. And so, my guess is some managers have considered that, and it’s just a calculated cost, like, “People who want to have that flexibility aren’t going to align with our values, and so they’ll leave if they’re not ready to get on board.” And I would say, maybe that’s true for some employees, but younger generations are going to expect a degree of autonomy, and so you have to consider what you want your workforce to look like 5 years down the road.

We are wondering about the deeper experiences of digital nomads that extend beyond the formal framework. Was there anything in your data that genuinely surprised you, something that didn’t make it into the final version but stayed with you?

Professor Melanie Prengler: Oh, I love this question! It’s so hard to let go of those early ideas that are really fun. So for me, what was really exciting that didn’t make it into the model was how people get into digital nomadism. Meaning, “What is it that drives them? How do they navigate that with their boss?” There are tactics that I think could be really practical for employees who are interested in either becoming full-blown digital nomads or just working remotely, or hybrid work—any arrangement where you may have to ask your boss for work arrangement flexibility to any degree. And then exiting nomadism, which I think is super fascinating, because a lot of people upend their entire life to become a digital nomad. They sell everything, or they put everything in storage, they quit their jobs and get a new job they can do remotely. I mean, they make some pretty enormous sacrifices to become digital nomads, and then many of them drop out within less than a year, and they go back to their regular life, or they move back home, or whatever, they can’t do it. And to me, that makes the stakes of place integration pretty significant, because usually people can do place iteration. It’s almost easier to go from place to place to place for a short time, but being able to say, “Actually, I want a bit of balance. I want to be able to slow down and not lose the freedom, but also not burn myself out, not burn through all my money—there’s a more calibrated version that I need to have.” I think, a lot of people just don’t get to a point where they’re willing to consider a more attenuated expression of freedom, so they burn out. I think that makes the stakes of place integration a lot more significant.

I’m looking through the samples; a mix of male and female. Did you see any differences between the two in terms of their levels of wanderlust? Did some groups have higher or lower levels depending on their personal characteristics?

Professor Prengler: I really didn’t. I was kind of surprised. I would have thought I’d find some kind of demographic differences, and I didn’t find differences in gender, I didn’t really find differences in age. Except insofar as people who were digital nomads longer tended to have more moderate wanderlust. But I really didn’t find any demographic differences.

So interesting. Thank you for sharing. So this brings me to the method question (…) I’ve been fascinated with qualitative research most recently. You said you conducted the member check-ins, and you also conducted follow-ups. What did that look like? Did you already have an emergent process model that you showed to respondents? What was that process, and what were the differences between the member check-ins and the follow-ups?

Professor Melanie Prengler: Yes, oh, it’s a great question. So first, I will float the model out in a lot of the interviews informally. So, because I’m doing analysis all along the way, I go into the interviews knowing what my best guess about the model is at the time, and what mysteries exist, what links I’m confused about, and what boxes are thinly supported. So I’m kind of pressure testing the model in subtle ways in every interview, even if I’m not doing a full presentation. But, for the more formal member checks, one of them I did right before submitting the first round. I sat the person down, and I said, “Here’s the purpose of our meeting. I have this big story that I think I’ve put together from talking to everybody, and I have a visual representation of that story to make it succinct, and I don’t know if it’s totally accurate. This is just my best guess, and so I want to talk to an expert who can tell me what’s working, what’s not working, what’s missing, what’s confusing, if there’s any edits you would make.” And I always tell them, “Don’t hold back. A win for me is making an accurate model, and so if you can help me get there, help me get there.” And then I’ll walk through the model piece by piece with them, pausing frequently for feedback.

“I always tell them, “Don’t hold back. A win for me is making an accurate model, and so if you can help me get there, help me get there.” And then I’ll walk through the model piece by piece with them, pausing frequently for feedback.”

This is kind of more general advice, not necessarily specific to this paper. Sometimes, if there are different subgroups, I try to get different people’s perspectives. So I’ll get, for example, one subgroup’s perspective and another and look for if they are describing things differently. They helps make sure it’s not just one person’s opinion that I’m anchoring on. But I did just have one person for this first one, and they said, “This seems pretty accurate, this is really resonating with me.” And then the second member check I did towards the end of data collection, I believe after I did the round of follow-ups. And very similar process with that person, just kind of walking them through the model piece by piece. The follow-up interviews were different from the member checks because the follow-up interviews were data data. Meaning, I’m collecting information that’s going to be germane and foundational to the model, coded and put into the data structure, and what I was looking for was subgroup differences between longtime digital nomads versus newbies. We suspected there were subgroup differences based on earlier interviews and needed to chat with folks more to sus those out.

Since the exploratory stage, you did work on the ground, you went to the restaurant, talking to those individuals

Professor Melanie Prengler: I was so nervous!

Do you include the informal interviews in your research, or was it to help guide your interview protocol? But the way you framed it here… I’m sure you gained so much insight from sitting with those 9 individuals.

Professor Melanie Prengler: Yea I really did! There is so much I didn’t know. The reason I wanted to go to the gathering was because I had been looking at a lot of Instagram and YouTube videos to get a lay of the land, but it’s so different seeing it from the outside versus talking to folks. For example, I had thought digital nomads were changing locations every 3 days. I assumed there was going be a lot of gatekeeperiness like, “Oh, well, so-and-so has been in the same place for 6 months, so they’re not real digital nomads,” but there’s just so much flexibility. People don’t seem to care about how long someone has been in one place for. People still identify as digital nomads, even if they’ve been in one place for a long time. That was the biggest thing I learned from going to the digital nomad group, because as I was looking ahead towards who I should be recruiting for my big data collection wave and wondering if I should require a particular threshold like, “If you’ve been in one place for this long, you’re not allowed to be in the paper.” I learned that according to the community, if you identify as a digital nomad, you count as a digital nomad.

You were the one just really trying to understand the context, and that’s where I’m at in my qualitative work. I’m the one looking at the blogs, listening to podcasts, conducting informal interviews…how do you take this information and then share it with the team so that they could understand the context? Is there a system? How do you take this information and then codify it in a way where your team understands what you just immersed yourself in?

Professor Melanie Prengler: It depends on the particular team’s process and what works for the team’s rhythms. I’ve used triangulating data and other sensitizing data in other studies as well, and probably used it in different ways. For my teammates, I would share, “Here’s what I’m seeing,” and they would ask me questions like “Are you seeing this? Are you not seeing this?” or maybe they would ask something that isn’t yet in the data, and I’d be like, “Oh, actually, this made me think of this YouTube video that I saw the other day, and here’s how they described it,” or “I was looking at some YouTube comments, and here’s what they said.” To answer your question, as you are figuring out what to do, I would suggest asking your co-authors what their expectations are, and establish some norms, like every—whatever number makes sense for the type of sensitizing data—writing up a little paragraph about what you’re seeing, sharing it with the team, see if they have any questions and establish a bit of a rhythm for the back and forth.

Going back to the method and theorizing part, I think you may have already answered it. So you have the models in your mind in the beginning, the exploratory stage… and then you refine it, polish it, through the interview and follow-ups?

Professor Melanie Prengler: So, the first version we submitted was like a digital nomad life cycle. So it started with the beginning when they decided to become digital nomads, and then their first travel. So there was something cyclical that was part of that first submission, but it was basically just a circle that started with becoming a digital nomad. And the reviewers and the AE were extremely helpful and developmental and really drawing out a lot of depth and nuance, and so the place iteration and integration in wanderlust didn’t emerge until, I think, the third round. So they really pushed us to identify subgroup differences to draw out complexities in the data that weren’t being represented in the model.

I was thinking about the digital placemaking, because from the entrepreneurship point of view, the Instagram and YouTuber are one-man entrepreneurs, one-man company. I just want to see the parallel from the physical placemaking and then digital placemaking. And also, there is AI… do you want to answer together or … do you want to…

Professor Melanie Prengler: It’s an interesting question about digital placemaking. So, my sense is that I think it might be something about making comfort portable. So they get to bring their community with them, they get to bring their familiar work process with them, that’s consistent no matter where they go. That’s my guess of how they would experience it. Maybe they have connection or an attachment to the digital place of Instagram or TikTok, because it feels like their “workplace”, and they’re “reporting in” when they log in. I can see that it would bridge the digital to physical gap pretty smoothly for them if that’s how they’re thinking about it.

How do you envision artificial intelligence influencing the paradox of mobile work? For example, If I’m a digital nomad, I’m on Zoom (this co-working space) and I’ve developed relationships with people, and they’re able to help me. I can ask questions, and we can provide each other with feedback, but now you have AI. I don’t necessarily have to engage with individuals who are on this digital platform anymore. I can now engage with artificial intelligence. I wanted to hear your thoughts on how that’s going to change the paradox that you are researching.

Professor Melanie Prengler: Yeah, that’s interesting. I wasn’t thinking about it from that lens. First, the question that you just asked… I haven’t thought about it against the backdrop of community. But I do think that’s interesting, especially for people who are starting out, there’s so much important information that’s shared just by asking questions to people like, “Where are the good co-working spaces, where are the coffee shops with reliable Wi-Fi, where should I go next, where are the cool people going?” If you don’t have community, it’s a recipe for dropping out of the lifestyle, because you can get so lonely.

“I do think that’s interesting, especially for people who are starting out, there’s so much important information that’s shared just by asking questions to people like, “Where are the good co-working spaces, where are the coffee shops with reliable Wi-Fi, where should I go next, where are the cool people going?” If you don’t have community, it’s a recipe for dropping out of the lifestyle, because you can get so lonely.”

And so, if they’re relying on AI for some of these information processes that also function as a relationship building process, they might struggle to stay in it, because they’re not building those kind of help-seeking networks. On top of this, I think there’s a risk around AI because a lot of digital nomads are doing freelance writing or copy editing. These are a lot of tasks that customers might be outsourcing to AI. So if the digital nomad’s income stream is being dried up because people are turning to AI, they’re not going to be able to fund their lifestyle in the same way. The flip side of that is that if they do still have clients who are going to them, they could achieve their work more quickly, and therefore have more time to go play and have fun. And so, it could also be a positive.

I also want to ask one question. Now, this is not really interview-related question, just, because in the email, you mentioned that you had an ASQ student blog before. How was that experience for you, from your side?

Professor Melanie Prengler: Sure! It was great! I was super excited, also very nervous. I wanted it to be a good experience for the person I’m interviewing, and to ask good questions. It was really fun. I loved it. I’m super supportive of the program. I think it’s a great idea to have a student-run blog, and I’m happy to be able to participate from the other side. This will be y’all, too, someday!

All right, well, if there are no final thoughts, I think this is it. We definitely want to be respectful of your time. We will work on questions and quotes for the blog. It is kind of the qualitative part.

Professor Melanie Prengler: Perfect! Well, let me know if you have any follow-ups or anything. I’m happy to chat again! Stay in touch, cheering for you guys, and I am sure we will run into each other at some point!

Thank you so much. Thank you, Dr. Prengler. Have a great day!

Interviewer Bios:
Theodore Kim (Tae.Won.Kim@rice.edu) is a PhD candidate in the Strategic Management at Rice University. His work focuses on entrepreneurship, inequality, and public policy, with particular attention to how systems shape access, participation, and completion. Using quantitative approaches, he studies how variation in institutional operation affects who is able to start and sustain businesses across communities.

Debby Osias (dzo0022@auburn.edu) is a PhD Candidate in the Department of Management and Entrepreneurship at Auburn University’s Harbert College of Business. Her research broadly focuses on entrepreneurial ecosystems and innovation, with particular attention to how universities translate research into the marketplace. Using mixed methods, she examines how university technology transfer offices position themselves to influence commercialization activities.