Construction Management and Economics

ISSN: 0144-6193 (Print) 1466-433X (Online) Journal homepage: www.tandfonline.com/journals/rcme20

Bug or feature? Institutional misalignments
between construction technology and venture
capital

Alexander N. Walzer, Tan Tan, Konrad Graser & Daniel M. Hall

To cite this article: Alexander N. Walzer, Tan Tan, Konrad Graser & Daniel M. Hall
(2025) Bug or feature? Institutional misalignments between construction technology
and venture capital, Construction Management and Economics, 43:2, 130-152, DOI:
10.1080/01446193.2024.2401818

To link to this article:  https://doi.org/10.1080/01446193.2024.2401818

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Bug or feature? Institutional misalignments between construction 
technology and venture capital

Alexander N. Walzera,b , Tan Tanc , Konrad Graserb and Daniel M. Halld 

aInstitute of Construction and Infrastructure Management, ETH Zurich, Zurich, Switzerland; bInstitute for Building Technology and 
Process, Zurich University of Applied Sciences, Winterthur, Switzerland; cDepartment of Real Estate and Construction, The University 
of Hong Kong, Hong Kong SAR; dDepartment of Management in the Built Environment, TU Delft, Delft, The Netherlands 

ABSTRACT 
Despite substantial investments into new technologies, the adoption of systemic innovations 
such as construction robotics remains limited. Therefore, this study investigates the discrepancy 
between the assumed advantages of construction technologies and their actual performance 
during practical implementation, using construction robotics as the empirical case. Through an 
abductive thematic analysis of 127 interviews across Europe and North America, we identify six 
enablers of institutional misalignment: cognitive frame differences, divergent time horizons, con
flicting market strategies, product versus revenue focus, varying risk tolerances, and information 
asymmetry. These misalignments between startup founders’ technological logic and investors’ 
economic logic constrain adoption, emphasizing the influence of institutional dynamics over 
technological feasibility. Our findings suggest these challenges are not unique to construction 
robotics but may extend to other emerging construction technologies. This highlights the critical 
need for aligning institutional logics to fully harness the potential of innovation in construction.

ARTICLE HISTORY 
Received 17 November 2023 
Accepted 3 September 2024 

KEYWORDS 
Institutional logic; 
entrepreneurship; AEC; 
construction robotics; new 
practice   

The game is about how to survive technology cycles 
and economy cycles. You want to perform well on the 
intersections. - Investor.

Introduction

The recent surge in innovation funding from venture 
capital firms highlights a growing interest in the con
struction industry’s potential for disruptive change. While 
this influx of capital offers significant opportunities, it 
also presents notable challenges. A key concern is the 
risk of amplifying the “hype cycle” surrounding new 
technologies. For example, Lideloew et al. (2023) illus
trate using the case of Building Information Modeling 
(BIM) how heightened initial enthusiasm can lead to 
unrealistic expectations. When these expectations are 
unmet, it can hinder the long-term adoption of the tech
nology. Therefore, the critical challenge is ensuring that 
the momentum generated by innovation funding sup
ports sustainable and meaningful technology integration.

The theory of institutional misalignment can explain 
this tension. Institutional misalignment occurs when 

established industry norms, practices, or structures clash 
with emerging developments. Such misalignments can 
amplify conflicts and impede the diffusion of innov
ation (Polzin et al. 2018). Although institutions typically 
provide the stability necessary for industry evolution, 
they can also resist essential change. At the same time, 
misalignments do not always result in adverse out
comes; under certain conditions, they can lead to con
structive realignments as industries are forced to adapt 
(Scott 2013). Indeed, Corsaro and Snehota (2011) and 
Korber et al. (2022) argue that these tensions can some
times ignite creativity, prompting industries to reconfig
ure in ways that ultimately prove productive.

Despite these insights, the root causes of institu
tional misalignments in the context of construction 
innovation remain poorly understood. Addressing or 
mitigating the tensions they create is challenging 
without a deeper understanding of these factors. 
Moreover, the dual role of institutional misalignments 
as both a barrier and a catalyst for innovation is not 
well-defined, especially in mature and well-established 
sectors such as construction. Understanding whether 

CONTACT Alexander N. Walzer awalzer@ethz.ch Stefano-Franscini-Platz 5, 8093 Zurich, Switzerland 
This article has been corrected with minor changes. These changes do not impact the academic content of the article. 
� 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. 
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits 
unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the 
posting of the Accepted Manuscript in a repository by the author(s) or with their consent.

CONSTRUCTION MANAGEMENT AND ECONOMICS 
2025, VOL. 43, NO. 2, 130–152 
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these misalignments hinder progress or foster creativ
ity is crucial for effectively leveraging innovation in 
such mature and entrenched industries.

The emerging interest in construction robotics 
offers an opportunity to further study these dynamics. 
The recent influx of venture capital has accelerated 
advancements in construction robotics, but these 
investments can emphasize short-term, marketable 
gains over sustainable innovation. Funding mecha
nisms that come with the institutional motivations 
and interests of venture capital can risk overshadow
ing the development of resilient technologies that 
address more profound industry challenges. However, 
these financial pressures can also drive the industry to 
reassess entrenched practices and priorities, potentially 
leading to more innovative and effective solutions.

Therefore, this paper seeks to explore how institu
tional misalignments between funders and innovators 
impact technological development, specifically focus
ing on the case of construction robotics. Several con
struction robotics startups have emerged in recent 
years, offering specialized technological solutions on 
and off construction sites. These startups are often 
supported by venture capital, which helps offset the 
initial costs of technological integration. However, 
implementing construction robotics requires signifi
cant changes in operational and strategic practices, 
revealing inherent tensions between technological 
potential and economic realities (Kangari and Halpin 
1990, Katila et al. 2018, Sawhney et al. 2020). These 
challenges and opportunities provide a rich empirical 
context for examining the institutional conditions that 
affect technology adoption in construction.

The paper is structured as follows: First, we exam
ine the context and background, including ongoing 
investments in construction technologies, to develop 

our research rationale. Next, we elaborate on our the
oretical framework, focusing on institutional misalign
ment within organizational fields. We then outline our 
primary research question on potential misalignments 
between venture capital and construction robotics 
companies. Our methodology section describes the 
abductive theme analysis employed, followed by our 
findings, which identify eleven dimensions of misalign
ment between founders and venture capitalists. The 
paper concludes by discussing whether these mis
alignments should be seen as features or bugs1 and 
exploring the broader implications of our research 
findings.

Context and background

Construction technology investments

In recent years, investors have shown increasing inter
est in technology startups within the construction 
industry, leading to a global investment volume of 
5.38 billion USD in 2022, with growing investments 
and average deal sizes (CEMEX Ventures 2023). 
Venture capital has targeted software startups special
izing in artificial intelligence, project scheduling, and 
data capture (Maulana 2023). Despite this interest, the 
percentage of investments in construction technology 
remains low, averaging only 0.08% of total industry 
spending from 2017 to 2021 (U.S. Census Bureau 
2023). Although this investment has a slight upward 
trend, as indicated by the time series’ trend line in 
Figure 1, the coefficient of determination (R2) is 0.179, 
suggesting a modest level of predictive accuracy. In 
comparison, in 2023, the sustainability sector experi
enced an investment percentage of 8.4% relative to its 
total industry spending in the U.S., while the mobility 
sector saw an investment percentage of 4.9% despite 

Figure 1. U.S. construction technology investments relative to industry spending 2017-2021, based on Mostamandy and Ledbetter 
(2022) and U.S. Census Bureau (2023).

CONSTRUCTION MANAGEMENT AND ECONOMICS 131



significantly lower investment volumes in 2022 and 
2023 (Teare 2023, BEA, 2024).

The construction robotics paradox

Construction robotics can transform long-standing 
industry practices by automating labor-intensive tasks 
while improving precision and quality (Bock 2015). 
Adopting robotic technologies in construction can 
enhance worker safety (You et al. 2018), reduce envir
onmental impact (Agusti-Juan and Habert 2017), and 
lead to more cost-effective workflows (Brosque and 
Fischer 2022). Moreover, recent advancements in con
struction robotics have significantly expanded the 
capabilities and applications of these technologies in 
both academic research and industry practice (e.g. Ma 
et al. 2020, Graser et al. 2021, Linner 2023).

Consequently, the construction robotics sector 
saw substantial investments by VC: ICON received 
USD 450m, Built Robotics 112m, Dusty Robotics 
69m, Diamond Age 58m, Monumental 25m, and 
RoboCon 20m (Crunchbase 2024). Investors predict 
a continued rise in venture capital for this sector 
(Zacua Ventures n.d.), further highlighting its poten
tial for efficiency, safety, and cost-saving advance
ments in construction.

However, only 5% of the total construction tech
nology investment volume 2022 was allocated to 
construction robotics (CEMEX Ventures 2023). 
Therefore, in an optimistic calculation assuming an 
average allocation of 0.08% towards construction 
technology investments as a percentage of total U.S. 
construction industry spending (Figure 1), with a 5% 
sub-allocation to construction robotics, only an 
equivalent of 0.004% of U.S. construction industry 
spending is invested in construction robotics today. 
In other words, per every 25,000 USD spent in con
struction activities in the U.S., only 1 USD is invested 
into construction robotics2. This low estimate seems 
paradoxical considering the industry’s predicted labor 
shortages (Agapiou et al. 1995, Dainty et al. 2005, 
Connaughton 2012), which should drive demand for 
automation and technological solutions (Bock 2015). 
As such, construction robotics’ current low adoption, 
implementation, and diffusion rates underscore a dis
connect between theoretical benefits, innovation 
funding, and practical application in the industry 
(Bosch-Sijtsema et al. 2021).

Kangari and Halpin (1990) highlighted the need to 
align societal needs and economic viability with 
technological considerations in construction robotics. 
Since then, research has advanced the understanding 

of socio-technical variables that enable and impede 
robotization in construction environments (Walzer 
et al. 2022, Graser et al. 2023, Wu et al. 2024), but 
less focus has been placed on the socio-economic 
domain (Bademosi and Issa 2021). Economic, organ
izational, personnel, technological, policy, and regula
tory barriers hinder the integration of these 
innovations in the construction industry (Tan et al. 
forthcoming). Comprehensive understanding and 
mitigation of these barriers are essential to unlock 
the development potential of systemic innovation in 
this sector.

Research rationale

Innovation adoption (Tatum 1987, Manley and 
McFallan 2006), implementation (Slaughter 1998, 
Manley et al. 2009), and diffusion (Taylor and Levitt 
2004, Manley 2008) have been studied in construction 
management. Recent studies emphasize engaging 
stakeholders to enhance the adoption of automation 
technology (Atkin and Skitmore 2008, Chen et al. 
2018). Agusti-Juan and Habert (2017) noted that con
struction robotics introduces new work design 
possibilities for handling standardized and non-stand
ardized products within construction projects, signify
ing a significant shift with implications for job roles, 
skills requirements, and project workflows. Therefore, 
exploring construction robotics beyond its techno
logical aspects is essential for anticipating and manag
ing its impact on construction management practices. 
Yet, more evidence is needed on the institutional 
processes facilitating these developments (Scott 2013). 
Given the critical role of institutions in management 
research (Aldrich and Fiol 1994, Bylund and McCaffrey 
2017), misaligned institutional logic in the investor- 
investee relationship can significantly impact the prac
tical application of innovative technologies in con
struction. For instance, other industries show that 
funding partners’ institutional logic can significantly 
influence firm and sector innovation (Pahnke et al. 
2015).

In this regard, using institutional logic as an analyt
ical framework can help understand the gap between 
the theoretical benefits and the actual use of construc
tion robotics, highlighting how varying stakeholder 
logic can hinder technology adoption. Inspired by 
Orlikowski’s (2010) “studying practice” approach, this 
study explores how loose couplings in the construc
tion industry impede coordination and knowledge 
sharing, thus hindering innovation and productivity 
(Dubois and Gadde 2002a). This approach addresses 

132 A. N. WALZER ET AL.



technical, market, cultural, and institutional aspects 
critical for understanding innovation adoption in con
struction management research.

Theoretical point of departure

This research builds upon the observation that mis
alignments exist between the innovative capabilities 
of new technologies and the institutional readiness to 
adopt them within the economic context of the con
struction industry (Bosch-Sijtsema et al. 2021). While 
technological advancements promise significant 
improvements, the primary obstacles to leveraging 
technological innovation may lie not within the tech
nologies themselves but within the broader organiza
tional and socio-economic contexts (Jacobsson and 
Linderoth 2010, Jacobsson et al. 2017).

Given the multiplicity of stakeholders, the construc
tion industry faces diverse institutional pressures 
(Levitt 2011). These misalignments provide a fertile 
ground for exploring mechanisms that impede the 
adoption, implementation, diffusion, and effective util
ization of technological advancements in construction. 
New firms encounter significant challenges in over
coming entrenched industry practices (Hall et al. 
2020). Research highlights the importance of address
ing technological, market, and organizational changes 
(Tidd et al. 2005) and cultural dimensions (Seymour 
and Rooke 1995, Chan and Raeisaenen 2009). This per
spective supports calls for deeper integration of social 
science methodologies into construction management 
research (Koch et al. 2019, Volker 2019).

Organizational fields and institutions

Organizational fields are critical in understanding the 
structure and dynamics of industries and markets 
(DiMaggio and Powell 1983). This perspective, as 
articulated in institutional theory (DiMaggio 1991), 
refers to those organizations that, in the aggregate, 
constitute a recognized area of institutional life. 
Organizational fields are not collections of firms or 
institutions that are similar or directly compete with 
each other (Scott 2013); they include the broader sys
tem of relationships and interactions among various 
actors, such as regulatory bodies, standards agencies, 
suppliers, customers, and financiers. These fields 
define the context within which organizations operate, 
innovate, and compete, shaping the “rules of the 
game”.

North (1990) defines institutions as human con
straints that structure political, economic, and social 

interactions. They guide individual and collective 
behavior through formal rules, informal norms, and 
enforcement characteristics (Burt 2004). As such, insti
tutions profoundly impact economies’ performance 
and the trajectory of societal development (North 
1990, Hargadon and Douglas 2001).

By definition, institutions are relatively resistant to 
change (Jepperson 1991, Scott 2013). Consequently, 
institutional rigidity can stifle innovations, as these 
must overcome ingrained norms and systems to gain 
acceptance, further complicating the alignment of 
practices (Oliver 1991). Lastly, studying how institu
tions operate can reveal ways to make organizational 
fields more resilient and innovative (Ferguson 1998, 
Scott 2013).

Organizations and institutional logic

In the context of organizations, institutional logic can 
help outline the processes by which stakeholders 
assimilate and operationalize the norms and values 
inherent to their institutions. Institutional logic 
explains how belief systems and practices shape 
organizational and individual behaviors, revealing the 
significance of socially constructed historical patterns, 
assumptions, values, and rules within specific institu
tional contexts (Friedland and Alford 1991, Thornton 
et al. 2012). Institutional logic therefore examines how 
organizations and their stakeholders navigate and 
strategize within their institutional environments, influ
enced by broader cultural and societal narratives 
(DiMaggio and Powell 1983, Thornton and Ocasio 
2008). Institutional logics, characterized by their fluctu
ating, co-existing, and potentially conflicting nature 
within a complex organizational landscape, provide a 
valuable lens for examining the dynamics of adapta
tion among organizations (Greenwood et al. 2011, 
Thornton et al. 2012).

Misaligned institutional logics
As institutional logics intersect, organizations find 
themselves in “logic blending” or “hybridity”, where 
conflicting logics are negotiated to accommodate mul
tiple institutional demands (Battilana and Dorado 
2010). The concept of misaligned institutional logic 
suggests that institutional arrangements can create 
inconsistencies and tensions, transforming actors into 
change agents or institutional entrepreneurs capable 
of navigating these challenges (Seo and Creed 2002). 
With an improved understanding of the underlying 
mechanisms, insights can be gained into their causes, 
consequences, and potential resolutions (Sarasvathy 

CONSTRUCTION MANAGEMENT AND ECONOMICS 133



2001). Such inquiry aligns with the recommendations 
of Besharov and Smith (2014), who advocate for man
agement research to explore institutional misalign
ments and their impacts across various organizational 
and sectoral contexts. Further, institutional logic helps 
move beyond the surface-level symptoms to consider 
broader cultural, social, and normative factors 
(Rasmussen et al. 2017, Lundberg et al. 2022).

Organizations have multiple strategic responses to 
these misalignments, such as compartmentalization, 
where different logics are applied in different organ
izational units or projects (Pache and Santos 2010), or 
hybridization, blending elements of competing logic 
to create a more cohesive and innovative approach 
(Battilana and Dorado 2010). As outlined by Pina e 
Cunha et al. (2005), misaligned institutional logic can 
lead both to positive and adverse outcomes and, 
eventually, these contradictions can catalyze organiza
tional change and transformation in the construction 
sector(Gottlieb and Haugbølle 2013).

Institutional logics in construction
Studies on institutional logic in the built environment 
are limited but increasing. Thornton et al. (2005) 
examined how architecture firms balance aesthetic 
and efficiency logic. Gluch and Hellsvik (2023) 
explored the influence of multiple logics on construc
tion stakeholders regarding sustainability. Linderoth 
(2017) highlighted that divergent institutional logic 
can hinder the adoption of Building Information 
Modeling (BIM) in construction. Harty and Leiringer 
(2017) emphasized the need to understand dominant 

institutional logic to resolve conflicts between the 
external environment and internal construction 
dynamics. Bylund and McCaffrey (2017) discussed how 
institutional uncertainty generally influences entrepre
neurship, pointing to the complexity and uncertainty 
when institutional logics intersect.

Economic and technology logic
Entrepreneurship and management scholarship has 
increasingly focused on the dominant interplay between 
economic and technology logic (Shane 2000, Gompers 
and Lerner 2001, Hellmann and Puri 2002, Thornton and 
Ocasio 2008). These studies outline a complex landscape 
venture capitalists and entrepreneurs navigate based on 
these differing yet complementary logics.

Economic logic, emphasizing financial returns and risk 
management, contrasts with technology logic, prioritiz
ing innovation and market disruption (Table 1). Walker 
and Weber (1984) and Kaplan and Stroemberg (2004) 
further explore the implications of these logics for organ
izational behavior and investment strategies, highlighting 
the critical role of transactional dynamics and evaluative 
frameworks in shaping industry trajectories.

Table 1 synthesizes the core findings from current 
scholarship, highlighting each logic’s distinct characteris
tics, motivations, and outcomes. The table aims to clarify 
the general understanding of economic and technology 
logic in literature by presenting these elements.

Empirical setting: construction robotics
Despite the ideal types of institutional logic presented 
in Table 1, an empirical gap persists in examining 

Table 1. Ideal types of institutional logics, based on Thornton et al. (2005).
Characteristics Economic logic Technology logic

Economic system Venture capitalism, focuses on high-risk investments for 
substantial returns

Innovation-driven economy, emphasizing the development 
and commercialization of technologies

Sources of identity Identified by investment vision, portfolio performance, and 
financial expertise

Defined by innovative contributions to technological 
expertise and industry leadership

Sources of legitimacy Financial returns, successful exits, and portfolio growth Technological breakthroughs, patents, and market adoption 
of technological solutions

Sources of authority Investment decisions, financial analysis, and market insights Technological vision, product development prowess, and 
industry knowledge

Basis of mission To maximize investment returns and achieve financial 
growth through strategic funding

To advance technology and achieve market leadership 
through innovation and differentiation

Basis of attention Market trends, investment opportunities, and financial 
forecasts

Technological advancements, R&D breakthroughs, and 
industry needs

Basis of strategy Identifying and investing in high-potential startups, 
financial engineering, and exit planning

Developing cutting-edge technologies, securing intellectual 
property, and strategic market positioning

Logic of investment Allocation of capital to ventures with high growth potential 
for financial returns

Investment in technology development, R&D, and scaling 
production capabilities

Governance mechanism Board participation, financial oversight, and performance 
metrics

Agile development methodologies, technology roadmaps, 
and innovation management

Institutional entrepreneurs Venture capitalists who shape the investment landscape 
and funding models

Entrepreneurs who pioneer new technologies and business 
models in the industry

Event sequencing Key funding rounds, IPOs, and acquisition events that mark 
financial milestones

Technological milestones, product launches, and adoption 
by key markets or sectors

Structural overlap Interactions with financial markets, regulatory bodies, and 
other sectors seeking technological solutions

Collaboration with research institutions, technology 
partners, and cross-industry applications

134 A. N. WALZER ET AL.



them in the context of construction robotics. A deeper 
understanding of these institutional logics is instru
mental in recognizing how different actors within con
struction robotics prioritize certain practices over 
others, aiming to making innovation more “usable” for 
construction professionals (Dossick et al. 2019). As 
such, the principles of institutional logic are instru
mentalized to establish the study’s analytical frame
work and conceptual understanding, providing a 
structured basis for exploring the dynamics at play 
within this empirical setting underexplored by con
struction management research.

Figure 2 presents a conceptual framework illustrat
ing the dynamics between venture capitalists and 
entrepreneurs in construction robotics. It highlights 
potential misalignments between economic logic (ven
ture capitalists) and technology logic (entrepreneurs). 
This framework shows how the systemic innovation 
both shapes and is shaped by human actions (see also 
Linderoth 2017). Integrating these perspectives 
addresses the unique challenges of aligning economic 
and technological goals in construction robotics, 
which is at the core of this study.

Summary of the research gap

Despite the increasing interest in construction robotics, 
research has yet to apply the institutional logic frame
work to analyze stakeholder perspectives in this 
domain. Current studies often overlook the discrepan
cies between the theoretical benefits and actual use of 
construction robotics, particularly the divergent institu
tional logic among venture capitalists and entrepre
neurs. Addressing this gap can provide a deeper 

understanding of the barriers to effective technology 
adoption and integration in construction management.

Research question

The guiding research question, “What are possible 
institutional misalignments between construction 
robotics and venture capital?” aims to clarify some of 
the complexities of these institutional interactions.

Methodology

This study embraces a non-linear and interpretive 
approach anchored in abductive reasoning, drawing 
on the principles of systematic combining. This 
approach fosters a dynamic interplay between theoret
ical constructs and empirical observations (Dubois and 
Gadde 2002b). Characterized by its iterative and adap
tive nature, this methodology permits the ongoing 
refinement of a theoretical framework, ensuring it 
evolves in response to emerging empirical insights 
(Kaplan and Orlikowski 2012, Timmermans and Tavory 
2012). By situating the investigation closer to induc
tion than deduction, systematic combining enables 
integrating empirical data with existing theory and the 
emerging context (Dubois and Gadde 2002b, 
Timmermans and Tavory 2012).

This fluidity in research design enables the iterative 
development and revision of preliminary hypotheses 
or “first suggestions” throughout the research process 
(Bamberger 2018). Abductive reasoning focuses on 
generating plausible explanations and uncovering dis
coveries by leveraging theories to challenge assump
tions and employing data to describe phenomena, 
formulate tentative claims, and narrow down explana
tions. Through contrastive reasoning, abduction identi
fies patterns that reveal alternative dynamics and 
processes, offering a detailed understanding of com
plex subjects (Bamberger 2018).

Abductive thematic analysis

Employing a relatively novel method known as abduc
tive thematic analysis, this study seeks to gain a richer 
understanding of participant perspectives while stay
ing true to the essence of qualitative research 
(Thompson 2022). Thematic analysis is utilized to sys
tematically break down and explain patterns in the 
empirical data, a crucial step in qualitative studies 
(Braun and Clarke 2006). Additionally, quotes from the 
data are employed to draw theoretical linkages abduc
tively (Dubois and Gadde 2002b). Figure 3 summarizes 

Figure 2. Scope of the study.

CONSTRUCTION MANAGEMENT AND ECONOMICS 135



the research method, further elaborated in the follow
ing sections, detailing the individual steps.

Participant selection

This study first utilized a purposive sampling 
approach, followed by a snowball sampling approach. 
Purposive sampling enables a better match between 
the participants and the aims and objectives of the 
research, thus improving the study’s rigor and the 
trustworthiness of the results (Campbell et al. 2020). 
The first set of participants was chosen via the 
author’s professional networks, scouting at in-person 
events, and proactively through communication chan
nels such as e-mails. After each interview, participants 
were asked to recommend other possible candidates 
who could contribute to the study’s aims. This 
approach creates momentum and captures an increas
ing chain of participation, also known as snowball 
sampling (Noy 2008).

The participant selection explicitly targeted two key 
groups to ensure the depth and relevance of the data: 
The first group (n¼ 39) comprises construction technol
ogy startup founders and executives. The aim is to cap
ture firsthand experiences of navigating the startup 
ecosystem and the challenges faced during phases like 
scaling or seeking investment. The second group 
(n¼ 20) is composed of VC investors. The aim is to gain 
insights into the investment criteria and strategies VC 
prioritizes when evaluating construction technology 
startups that focus on robotics. Focusing on these dis
tinct perspectives ensured a more comprehensive under
standing of the dynamics between startups and their 
potential or actual financiers. Additionally, the study 
incorporates other stakeholders (n¼ 36) beyond the 
startup founders and investors, such as clients, partners, 
academics, advisors, etc. (Table 2).

Demographics

The empirical data set includes 127 semi-structured 
and open-ended interviews and conversations with 95 

Figure 3. Flowchart of abductive thematic analysis, based on Thompson (2022).

Table 2. Participant demographics (N¼ 95).
Participant role No. Focus areaa No. Firm status No.

(Co)-Founder 21 Robotics, Automation 28 Operational 91
Investor 20 Offsite, Prefabrication 23 of which in stealth 10
Executive 18 Software, Firmware 21 Defunct 2
Advisor 13 Financing, Equity 20 Exited 2
Otherb 12 Internet of Things 15 Geographical Region No.
Client 11 Climate, Energy 14 Continental Europe 39
Firm Type No. On-Site Construction 13 North America 31
Startup 32 Logistics, Supply Chain 12 Multinational 16
Otherc 23 Additive Manufacturing 12 Asia-Pacific 7
Spinoff 20 Education, Academia 11 South America 2
Venture Capital 14 Real Estate, Property 10 Study Population No.
Corporate VC 4 Artificial Intelligence 9 Interviews (n) 127
Private Equity 2 Facility Management 8 Interviewees (N) 95
if Venture, Stage No. Infrastructure, Civil 8 Data Collection No.
Pre-Seed 25 Incubator, Accelerator 7 Total duration (h) 92
Seed 16 Wearables, Exoskeleton 5 Online (Verbatim) 59
Series A or B 9 Mixed Reality/AR/VR 4 In-person (Field Notes) 56
Acquisition or IPO 2 Policy, Legal 2 Online (Non-verbatim) 12
aNote that most firms are labeled with more than one focus area.
bThese roles include consultants, academics, and government employees.
cThis type includes multinationals, general contractors, and universities.

136 A. N. WALZER ET AL.



industry informants conducted in 2022 and 2023. The 
interviews were conducted in person in Continental 
Europe (39), North America (31), as well as in Asia- 
Pacific (7) and South America (2), using a video call 
format, resulting in verbatim and non-verbatim tran
scribed interviews and field notes (e.g. see DiCicco- 
Bloom and Crabtree 2006) spanning a total duration 
of more than 92 hours. Some participants were avail
able for multiple interviews. Most study participants 
can be described as (co)-founders, investors, and exec
utives working in early-stage startups focusing on 
robotics, automation, and prefabrication (Table 2). 
Most participants identified as having a professional 
background related to the construction industry.

Interview protocol
The interview protocol was pilot-tested using purpos
ive sampling with a small subset of subject matter 
experts (n¼ 6) to pinpoint the essential types of infor
mation required, including the significance of events, 
attributes, and experiences, perceptions regarding 
cause and effect, and viewpoints on potentially sensi
tive issues (Jimenez and Orozco 2021). According to 
Creswell (2013), this methodological choice allows for 
a more holistic data collection process, granting the 
elasticity to explore conversational narratives while 
maintaining an overall structure. Central to this inquiry 
is the provision of a “thick description”, a concept 
coined by Geertz (1973), whereby detailed accounts of 
the collected data are generated (see Appendix B). 
Table 3 displays an excerpt of the prompts; the com
plete set can be found in Appendix A.

Interview coding
The coding procedure adopted in this study reflects 
the methodology Javernick-Will (2009) used in an 
interview study with a similar cohort size. Multiple 
data readings were initially required to comprehen
sively understand the content (familiarization). This 
process was followed by generating initial (open) 
codes, where significant and insightful data segments 
are marked with descriptive labels (Charmaz 2014). 
2998 data segments, including phrases and para
graphs, were coded from the interview data. To 

analyze this qualitative data from transcribed inter
views and field notes (Kuckartz and Raediker 2019), 
computer-assisted qualitative data analysis software 
MAXQDA Analytics Pro 2022 was used. Such software 
tools can assist in organizing, categorizing, and analyz
ing the data more efficiently and rigorously (Gibbs 
2007).

The coding lays the foundation for incremental 
theme identification, examining patterns and correla
tions among various codes and categories (Reyes et al. 
2021). Each emerging theme underwent a review pro
cess to ensure accuracy in reflecting the coded data. 
Subsequently, distinct and descriptive names were 
assigned to each theme to facilitate identification, 
resulting in dozens of working themes. These themes 
were separated to align with the two logics and fur
ther grouped to focus on differences and structural 
overlaps (n¼ 6).

Findings

The thematic analysis identifies six enablers of mis
alignments, each supported by key quotes and dis
cussed in this section. Complementing this analysis, 
Table 4 synthesizes these misalignments across their 
enablers and dimensions and summarizes the findings. 
More comprehensive empirical evidence on the mis
aligned dimensions is detailed in Appendix B.

Further guided by the principles of abductive rea
soning, systematic combining attempts to contextual
ize the empirical findings with existing theory. As 
such, the preliminary mapping within Table 4 aligns 
the identified misalignments with characteristics of 
institutional logic (Thornton et al. 2005).

Enablers of misalignment

Cognitive frames
Founders and investors varied their beliefs, values, and 
business practices. The differences reflect the profes
sional culture, pace, and methodology with which 
each party operates and makes decisions. “The biggest 
hurdles we face are the internal disconnects between 
the organizations”, a later-stage founder highlighted, 
illustrating the impact of diverse backgrounds on 
operational coherence and effectiveness. Furthermore, 
the challenge of aligning these varied perspectives is 
underscored by another founder who asserted, “I can 
tell you that fundraising is a full-time job”, pointing out 
the significant dedication and effort required to bridge 
this gap.

Table 3. Excerpt of interview prompts.
Interview Prompts  

for Founders
How would you define your most significant scaling 

challenges as a firm?
How have your funding needs changed over time?
How do you find the right investor?

Interview Prompts  
for Investors

What is your motivation to invest in construction 
technology?

How do you find the right ventures to invest in?
What are the limitations or pressures of your 

investment strategy?

CONSTRUCTION MANAGEMENT AND ECONOMICS 137



Ta
bl

e 
4.

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at

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ily

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su

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re

tu
rn

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n 

in
ve

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m

en
t

So
ur

ce
s 

of
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eg
iti

m
ac

y,
 B

as
is 

of
 

M
iss

io
n,

 
Lo

gi
c 

of
 In

ve
st

m
en

t, 
In

st
itu

tio
na

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nt

re
pr

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rs

In
te

lle
ct

ua
l P

ro
pe

rt
y

Le
ss

 e
ss

en
tia

l
Es

se
nt

ia
l

Fo
un

de
rs

’ e
m

ph
as

is
 o

n 
IP

 in
di

ca
te

s 
a 

vi
si

on
 t

o 
bu

ild
 a

 s
ol

id
 f

ou
nd

at
io

n 
fo

r 
th

ei
r 

ve
nt

ur
e’

s 
co

m
pe

tit
iv

e 
po

si
tio

n,
 v

al
ui

ng
 t

he
 p

ro
te

ct
io

n 
an

d 
po

te
nt

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l m

ar
ke

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ex

cl
us

iv
ity

 t
ha

t 
IP

 c
an

 p
ro

vi
de

. I
nv

es
to

rs
’ l

es
se

r 
em

ph
as

is
 o

n 
IP

 r
ef

le
ct

s 
a 

m
or

e 
im

m
ed

ia
te

 f
oc

us
, p

ot
en

tia
lly

 v
ie

w
in

g 
IP

 a
s 

a 
se

co
nd

ar
y 

co
nc

er
n

So
ur

ce
s 

of
 L

eg
iti

m
ac

y

138 A. N. WALZER ET AL.



Time horizons
A significant discrepancy is evident in how founders 
and investors conceptualize time horizons regarding 
the rate of robotic technology adoption within the 
construction sector. “I can’t even think of five people 
with robotics experience in the construction space that 
can pull something together today”, an investor admit
ted, revealing a gap in expectations and mutual 
understanding of the required timeline for technology 
adoption and scalability. A founder questions, “Are we 
in the construction industry not innovating enough our
selves, or are we being disrupted by outsiders?” reflect
ing on the industry’s internal versus external sources 
of innovation.

Market strategy
Misalignments in market strategy reflect the two 
stakeholders’ varying understandings of market 
dynamics, customer needs, and industry trends. 
“Investors often confuse their needs with the customer’s, 
placing their own needs above customer feedback”, one 
founder emphasized, showcasing the misalignment in 
priorities between founders and investors. 
Additionally, an investor stated, “We need some kind of 
education for people investing in the space, as well as 
people around the space just to know that construction 
robotics is going to be different from other types of 
robotics and we really can’t make that comparison in 
terms of exits and comparables”, indicating a notable 
difference in market strategy focus for robotics in con
struction. On the other hand, investors are energized 
by seeing the rise of “New Age Construction Firms”. 
One investor captures the sentiment: “I believe new 
players are coming in - not threats - but new players”, 
signaling a welcome wave of fresh ideas and 
innovation.

Product development vs. Revenue generation
Another tension exists between the qualitative and 
quantitative perspectives that impact each party’s stra
tegic decisions regarding the nature of the products 
or services the ventures aim to deliver. “If you develop 
hardware things like robotics, then VC may not even be 
the right thing to do at the beginning”, a founder 
assured, pointing out the conflict between product 
innovation and early revenue generation. “Venture 
capital, as it’s currently practiced, isn’t necessarily the 
best model”, an investor voiced, and that “it can lead 
to inefficiency and isn’t always beneficial for the broader 
economy”, echoing concerns about the focus on rev
enue over product development.

Risk tolerance
Founders and investors are willing to take different 
levels of risk in pursuing their objectives. “After all, 
management is where the mistakes are made, and the 
significant wins and losses are scored”, an investor rec
ognized, pointing out the divergent approaches to risk 
and the impact of decision-making under uncertainty. 
Regarding risk appetite, one investor pointed out that 
“we want to make sure that we’re making the best 
investments, but we also understand that there’s actu
ally a lot more great companies out there than we can 
even invest in ourselves”, indicating that opportunity 
cost is strongly related to making selective, informed 
decisions amidst many opportunities.

Information asymmetry
Founders and investors often approach decision-mak
ing with differing scopes and granularities of informa
tion, leading to divergent perspectives. A founder 
advised, “Startups should conduct due diligence on the 
investor, looking into their portfolio companies - and 
understand what they offer besides money”, highlight
ing the importance of overcoming information asym
metry through thorough research and strategic 
communication. Eventually, a founder stated, “I believe 
it’s not about how much money you’ve got. We boot
strapped for 18 months. An excess of money can make 
a founder lose focus, less money keeps you centered”, 
which challenges the notion of abundant venture cap
ital funding, proposing that a more modest approach 
can be tempting for the organization.

Relation to the characteristics of institutional 
logics

This section presents the findings related to the estab
lished characteristics of institutional logic, as seen in 
Table 4 (Thornton et al. 2005). The economic system 
in construction robotics is driven by market competi
tion (with existing solutions in construction), the pur
suit of innovative research and development (to 
increase novelty and competitiveness), and the 
imperative to generate revenue and profit, mainly 
from the investment side). Organizations derive their 
identity from the traditional customs of their respect
ive institution, which are mirrored in the products and 
services they develop. Legitimacy is generally gained 
through deploying innovation in pilot projects and 
protecting intellectual property. The organization’s 
strategy revolves around scalability, exit strategies, 
and investor profit maximization, and the economic 
logic prioritizes R&D and innovation as key growth 

CONSTRUCTION MANAGEMENT AND ECONOMICS 139



drivers. Institutional entrepreneurs promote innovation 
within and across institutions. These dimensions can 
sometimes be at odds, such as when pursuing profit 
compromises investment in long-term R&D or when 
market pressures conflict with the organization’s 
innovation agenda.

Misalignment occurs when these sources pull in dif
ferent directions, for example, when market demands 
shift away from the products central to an organiza
tion’s identity. Furthermore, the misalignment of prod
uct development priorities complicates this situation. 
In this scenario, investor needs can overshadow cus
tomer feedback, exacerbating the challenges of pursu
ing innovation that conflicts with existing market 
norms or strictly allocates resources to intellectual 
property, stifling collaboration and open innovation. 
Misalignment can occur when product development 
goals do not align with the innovation agenda, poten
tially leading to strategic drift or resource misalloca
tion. Conflicts arise when focusing on exit strategies 
and short-term profits undermines efforts to scale 
operations sustainably. Misalignment is evident when 
short-term financial pressures compromise long-term 
investment in innovation and when their innovation 
agenda conflicts with established institutional norms 
and practices. The sequence of key events, such as 
exit strategies and market entry, plays a critical role.

Lastly, structural overlap involves aligning organiza
tional scalability and strategic focus. For instance, 
unclear regulations and standards can hinder certainty 
for firms in this sector, one example being concrete 3D 
printing technology. Additionally, the need to balance 
fundraising efforts and operational management is 
amplified by companies’ internal challenges, often mag
nified by the pressures of aligning (external) investor 
and (internal) founder visions when market sizes and 
growth rates are uncertain. Organizations’ attention is 
allocated to market trends and risk management. 
Eventually, the founder-investor relationship, further 
strained by differing visions on product development 
and operational management, can create a cascade of 
inefficiencies reflecting misaligned priorities.

Discussion

Implications for construction technology adoption

While centered on construction robotics, this study 
highlights broader institutional dynamics that impede 
the adoption of technologies and novel methods 
within the construction industry. These dynamics can 
manifest as conflicting logics, such as those related to 
Building Information Modeling (BIM), efficiency, 

sustainability, and aesthetics (Thornton et al. 2005, 
Linderoth 2017, Gluch and Hellsvik 2023). In fact, the 
enablers of misalignments identified in this study can 
be traced to the unique characteristics and context of 
the construction industry itself.

Cognitive frames
Stakeholders in the construction industry utilize cogni
tive frames, mental models, and assumptions to inter
pret and understand new technologies. These frames 
significantly shape technology perception and adoption. 
A strong adherence to traditional practices and a prefer
ence for proven methods can result in cognitive frames 
that resist change. This resistance contributes to institu
tional misalignment, wherein new technologies conflict 
with established norms and practices. Such misalign
ment can explain the distinct challenges faced in adopt
ing robotics in construction compared to industries 
more receptive to innovation (Lundberg et al. 2022).

Time horizons
Due to their temporary nature, construction projects 
typically operate on short-term time horizons. This 
focus on immediate project costs and benefits impacts 
the potential long-term advantages of investing in 
technologies. The industry’s short-term orientation 
poses a significant barrier to adopting technologies 
requiring a longer-term perspective to realize full ben
efits (Gottlieb and Haugbølle 2013). This temporal mis
alignment between project timelines and the lifecycle 
of technological adoption is a critical factor in under
standing the industry’s low appetite for innovations.

Market strategy
Adopting new technologies can be a strategic 
endeavor for firms aiming for differentiation or 
enhanced efficiency. However, market strategies within 
the construction industry are distinct from other sec
tors, primarily due to the need to balance innovation 
with cost control. The industry’s typically low margins 
and competitive nature often discourage investment 
in new technologies, emphasizing a conservative 
approach (Barbosa et al. 2017). This context highlights 
the institutional factors that hinder technology adop
tion and innovation.

Product vs. Revenue focus
A significant tension in the construction industry lies 
between the focus on the product (e.g. the building 
or built environment) and the revenue generated (e.g. 
from components or subcontracted services). This dis
tinction impacts the industry’s willingness to adopt 

140 A. N. WALZER ET AL.



new technologies, which may entail higher initial costs 
without immediate revenue benefits. This tension also 
highlights the challenge of balancing costs and profit
ability, affecting decision-making processes and creat
ing potential barriers to technology adoption (Kangari 
and Halpin 1990, Sawhney et al. 2020).

Risk tolerance
Due to high costs, complexity, and potential financial 
losses, construction firms generally exhibit low-risk tol
erance. This cautious approach often leads to a prefer
ence for established technologies and methods, making 
it difficult for innovative solutions to gain traction. This 
low-risk tolerance contributes to institutional misalign
ment, as firms resist adopting new technologies per
ceived as risky (Katila et al. 2018, Polzin et al. 2018).

Information asymmetry
The construction industry is characterized by informa
tion asymmetry, where stakeholders, clients, contrac
tors, and suppliers possess varying levels of information 
and expertise. This uneven distribution can lead to mis
understandings or mistrust regarding the benefits and 
risks of new technologies. As a result, information 
asymmetry can act as a barrier to innovation adoption, 
complicating decision-making and alignment among 
stakeholders. This issue is particularly relevant in con
struction, where complex projects involve multiple par
ties with diverse interests and perspectives (Bosch- 
Sijtsema et al. 2021, Lideloew et al. 2023).

Institutional challenges and opportunities in 
construction robotics

Our findings reveal several challenges and opportunities 
in the organizational field of construction robotics. The 
integration of systemic innovation requires shifts in prac
tices, often highlighting tensions between technological 
potential and economic goals (Sheffer et al. 2013, Bosch- 
Sijtsema et al. 2021). Notably, construction robotics 
amplifies existing institutional barriers such as the sec
tor’s fragmentation and inherent resistance to change.

Our findings align with previous research (Katila 
et al. 2018, Sawhney et al. 2020) in demonstrating that 
the effective integration of construction innovation 
necessitates substantial changes in workforce skills, 
regulatory frameworks, and management practices. 
However, our study deepens this understanding by 
drawing directly from the empirical context of construc
tion robotics, revealing new insights into the unique 
challenges and opportunities within this field. For 
instance, implementing construction robotics may 

necessitate new training programs to develop special
ized skills among the workforce, alongside updated reg
ulations to ensure safety and compliance. While 
management practices may need to adapt to robotic 
systems’ new workflows and operational dynamics, it is 
equally important to consider how robotics can be 
developed to align with existing management struc
tures. This reciprocal approach could lead to more sus
tainable technology integration within construction 
operations, allowing for innovation and the mainten
ance of existing management practices. Furthermore, 
the emergence of construction robotics introduces chal
lenges and opportunities related to innovation diffu
sion. While increased efficiency and reduced labor costs 
offer clear benefits, the construction industry’s conser
vative nature and fragmented structure present signifi
cant challenges (see also Dubois & Gadde, 2002b, 
Manley & McFallan 2006, Bademosi & Issa 2021). The 
following sections will discuss the empirical results sug
gesting that misalignments in the industry can act as 
both obstacles and enablers, ultimately leading to the 
development of new practices in construction robotics.

Misalignments as a “Bug”

Multiple and sometimes conflicting logic (Aldrich and Fiol 
1994) are navigated by new technology-based firms in 
construction. The empirical data from construction 
robotics reveals that misalignments in institutional logic 
are a source of frustration and conflict, loosely mirroring 
the findings in the context of new industry creation by 
Hargadon and Douglas (2001). Such misalignments can 
force founders to diverge from their operational focus in 
pursuit of venture funding, a process that can be viewed 
as a “bug” in the entrepreneurial journey (e.g. Sarasvathy 
2001). Such diversion strains the founder-investor relation
ship and amplifies the conflicts between the pursuit of 
immediate profit and the commitment to long-term 
research and development. Founders must align investor 
expectations with their strategic vision for innovation and 
sustainable growth. Furthermore, the higher the informa
tion asymmetry between founders and investors regarding 
the capabilities and limitations of construction robotics, 
the greater the potential for investment inefficiencies, 
negatively affecting the emerging organizational field.

Misalignments as a “feature”

Understanding misalignments in business relationships 
involves recognizing that they are not inherently and 
exclusively harmful. Instead, they offer insight into the 
complexities of human perceptions and beliefs and 

CONSTRUCTION MANAGEMENT AND ECONOMICS 141



enriching the comprehension of stakeholder interac
tions. Therefore, an alternative understanding of these 
misalignments can also be interpreted as a helpful fea
ture or benefit. For example, a financial misalignment 
can foster focus and operational efficiency in the 
investor-investee dyad in construction robotics, similar 
to the ethos of “bootstrapping”.

Furthermore, the arrival of professionals from varied 
industries into construction leads to a vital discourse on 
possible innovation within the sector. This scenario sug
gests a productive challenge, where the industry’s trad
itional offerings are challenged by novel approaches 
and solutions brought in by these new entrants. 
Investors’ optimism reflects the potential to drive con
struction robotics, recognizing the available opportuni
ties and suggesting that frictions do not necessarily 
impede the pursuit of worthwhile investments.

Corsaro and Snehota (2011) suggest that when 
acknowledged and understood, misalignments in busi
ness relationships can be harnessed to strengthen 
partnerships, particularly when they encourage open 
communication and are free from rigid constraints. 
Paradox theory in organizational studies has pointed 
to an equilibrium model that depicts how cyclical 
responses to paradoxical tensions enable future suc
cess (Lewis and Smith 2000, Smith and Lewis 2011).

Korber et al. (2022) identified three responses of 
entrepreneurs to misalignments: “enduring” due to 
geographic ties, “escaping” to seek opportunities else
where, and “engaging” to constructively navigate and 
reconcile differing institutional logics by fostering new 
organizational fields. As such, positive transformations 
can arise from misalignments when stakeholders view 
them as opportunities for synergy rather than conflict. 
Therefore, misaligned institutional logic can reshape 
the entrepreneurial ecosystem’s systemic and infra
structural conditions in the organizational field of con
struction robotics, which may be aided by the findings 
of this study. Eventually, how stakeholders respond to 
misalignments is pivotal for nascent and emerging 
organizational fields (Thornton et al. 2012, Gottlieb 
and Haugbølle 2013). After all, innovation is a process 
by which institutions are disrupted and overturned, 
giving way to new institutional forms (Scott 2013).

Towards a new practice

As the organizational field of construction robotics 
progresses toward increased formalization, it will inter
sect with or operate alongside several established 
institutions (Williamson 2000, Kraatz and Block 2008, 
Hall and Scott 2019). This process of co-constitution, 

potentially unfolding over decades, can showcase the 
emergence of standardized practices through contin
ued interaction within the emerging organizational 
field of construction robotics. Previous research on the 
early institutionalization of integrated project delivery 
(IPD) (Hall and Scott 2019) highlighted this process as 
a gradual, co-evolutionary journey rather than a static 
outcome. Consequently, this co-constitution could sig
nal the emergence of new practices (Graser et al. 
2021) in construction robotics and warrants further 
longitudinal observation and ethnographic study.

A critical issue in these misalignments arises from 
conflicting priorities between investors and founders, 
diverting strategic focus and stalling innovation (Aldrich 
and Fiol 1994, Sarasvathy 2001). However, these mis
alignments also present an opportunity to enhance 
operational efficiency and drive innovation through 
diverse stakeholder perspectives and adaptive strategies 
(Corsaro and Snehota 2011). Effectively recognizing and 
managing these institutional misalignments can trans
form the entrepreneurial ecosystem in construction 
robotics, fostering a more innovative and resilient field. 
This co-constitution process within construction 
robotics highlights the complex interplay of institutional 
logic shaping new practices. As depicted in Figure 4, 
this figure illustrates the institutional dynamics within 
construction robotics, highlighting how the two domin
ant institutional logics can lead to the co-constitution 
of a new practice. The figure presents a conceptual 
framework for developing construction robotics, high
lighting the interaction between economic and techno
logical logic mediated by human agents. Venture 
capitalists influence and are influenced by economic 
considerations, shaping investment decisions in 
robotics; entrepreneurs are aligned with technological 
logic, bridge advancements with market opportunities, 
and drive commercialization and adoption.

Central to this framework is the concept of longitu
dinal co-constitution, emphasizing the ongoing, 
mutual influence between economic and technological 
logic. This process suggests a more iterative approach 
to innovation. Construction robotics, as the central 
innovation, has the potential to transform workflows, 
labor dynamics, and productivity in the construction 
industry, establishing new practices and advancing the 
role of automation over time.

Limitations

Institutional logic provides a robust framework for 
analyzing organizational behavior but also has limita
tions. The term “logic” suggests a level of coherence 

142 A. N. WALZER ET AL.



that only sometimes exists within or between institu
tions, leading to a risk of oversimplifying complex 
motivations and organizational actions (Pache and 
Santos 2010, McPherson and Sauder 2013). Moreover, 
the focus on macro-level institutional constraints 
might also obscure the role of individual agency, over
looking the potential of individuals or organizations to 
act as “institutional entrepreneurs” capable of effecting 
change (Emirbayer and Mische 1998, Battilana et al. 
2009). Evidently, organizations with more precisely 
defined goals or better-developed technologies are 
less subject to institutionalization than those with dif
fuse goals and weak technologies (Selznick 1957), sug
gesting a need for more sophisticated institutional 
approaches that accommodate multilevel causal proc
esses (Williamson 2000).

While institutional logic offers descriptive richness, 
it requires more prescriptive utility, as identifying mul
tiple logics does not necessarily translate into action
able strategies for organizations to navigate or 
“inhabit” these logics (Hallett and Ventresca 2006). 
Additionally, the study’s strict reliance on typologies 
and binary categorizations risks neglecting the diverse 
lived experiences and practices where such logics are 
enacted (Pache and Santos 2013).

While this study employed institutional logic as a 
lens to examine the empirical data, it remains unclear 
to what extent the suggested logics apply. Further, 
using systematic combining, there is more than one 
way to combine empirical data and theoretical frame
works (Dubois and Gadde 2002b). Lastly, there is a 
remaining gap in institutional logic around 

understanding and evaluating the sources of authority 
and governance mechanisms in the context of con
struction robotics firms, an opportunity for future 
research.

Future research

This study enhances the understanding of investor- 
investee dynamics within construction technologies, 
specifically using construction robotics as the empirical 
case and institutional logic as the analytical lens. 
Several areas require further exploration to expand 
our findings’ theoretical and practical implications.

Firstly, future research can focus on the influence of 
cultural, political, and economic contexts on these 
dynamics. Given the diverse geographical settings 
from which our data were aggregated, there is an 
opportunity to examine how regional factors uniquely 
affect investor decisions and project outcomes in con
struction technology. Comparative studies across dif
ferent countries could surface distinct patterns and 
strategies, providing a more refined understanding of 
the global landscape.

Secondly, while our analysis primarily centers on 
the investor-investee dyad, expanding the scope to 
include other stakeholders is crucial. This includes 
exploring the roles of business angels and examining 
clients and partners along the value chain. These 
stakeholders are instrumental in the diffusion and 
adoption of construction technologies, yet their contri
butions and interactions remain underexplored. 
Employing methodologies such as single case studies, 

Figure 4. Co-constituting existing institutional logic leading to a new practice.

CONSTRUCTION MANAGEMENT AND ECONOMICS 143



mixed methods (Polzin et al. 2018), or quantitative 
approaches (Tidhar and Eisenhardt 2020) could offer 
deeper insights into these complex relationships.

Moreover, the inconsistencies between and within 
social and cultural systems, as highlighted by Seo and 
Creed (2002), deserve further investigation. Future 
research could benefit from ethnographic methodolo
gies and secondary data analysis to capture the subtle
ties of these interactions and their long-term effects.

Lastly, exploring the “shadow of the future” con
cept (Axelrod 1984) through individual-level case stud
ies could provide valuable insights into stakeholders’ 
emotions and expectations. By examining how antici
pation of future interactions influences behavior and 
decision-making, researchers can better understand 
the norms of institutional reciprocity (Scott 2013) and 
their implications for construction technology partner
ships. This approach could examine the long-term 
impacts of institutional misalignments among stake
holders, offering critical insights for theory and 
practice.

In summary, future research can build upon this 
study’s findings by investigating the specificities of 
construction technologies in various contexts. Such 
work can further contribute to developing more 
effective investment strategies within the organiza
tional field of construction robotics and more gener
ally, with and for construction technologies.

Conclusion

This study investigates institutional misalignments 
among key stakeholders in construction robotics, an 
area largely unexplored in construction management 
research. Our analysis identifies six key enablers of mis
alignment in the construction industry: differing cogni
tive frames, divergent time horizons, conflicting market 
strategies, a focus on product versus revenue, varying 
risk tolerances, and information asymmetry. These ena
blers emphasize the deep institutional and operational 
challenges rooted in the construction industry’s conser
vative nature and fragmented structure, which impede 
the adoption, implementation, and diffusion of innova
tive technologies such as robotics.

Accordingly, addressing these misalignments 
demands a sophisticated strategy integrating the con
struction industry’s unique characteristics with broader 
institutional logic. Shifting cognitive frames toward a 
more innovation-friendly mindset and aligning short- 
term project goals with long-term technological 
investments are pivotal strategies for overcoming 
resistance to new technologies. By highlighting these 

critical issues, this study deepens the understanding of 
institutional dynamics within the construction sector, 
setting the stage for future research to develop tar
geted interventions.

The systematic combining approach used in this 
case study of construction robotics has provided both 
specificity and generalizability to our findings, sup
ported by comprehensive empirical data. Our analysis 
suggests that institutional logic in construction 
robotics may lead to co-constituting new practices, 
offering insights into the adoption processes of other 
high-tech construction innovations. However, further 
research, particularly longitudinal and data-centric 
studies, is needed to determine whether these mis
alignments represent temporary challenges (’bugs’) or 
inherently positive aspects (“features”) of the emerging 
organizational field of construction robotics.

Ultimately, these findings emphasize the urgent 
need for the construction industry to adapt workforce 
skills, regulatory frameworks, and project management 
practices to better align with technological advance
ments. Addressing institutional misalignments is cru
cial for the industry to effectively respond to 
increasing societal and environmental demands and 
fully harness the potential of emerging technologies.

Acknowledgments

The authors express their sincere gratitude to all participants 
who contributed directly to this study, the NCCR Digital 
Fabrication and Stanford University for enabling our 
research. We thank Prof. Fischer (CIFE) for hosting ANW and 
Prof. Jimenez (Sociology) for educating ANW and DMH on 
qualitative research methods. We are also thankful for the 
feedback and comments from the anonymous reviewers, 
and our peers during the EPOC 2023 Conference.

Authors’ Contributions

Conceptualization: ANW, DMH; Methodology: ANW, DMH; 
Validation: ANW; Formal Analysis: ANW, TT, KG, DMH; 
Investigation: ANW, DMH; Resources: ANW, DMH; Data 
Curation: ANW; Writing (Original Draft): ANW; Writing 
(Review & Editing): TT, KG, DMH; Visualization: ANW; Project 
Administration: ANW, DMH; Supervision: DMH.

Disclosure statement

No potential conflict of interest was reported by the 
author(s).

Funding

The Swiss National Science Foundation (SNSF) provided 
funding for research mobility to Stanford University via the 

144 A. N. WALZER ET AL.



NCCR Digital Fabrication (51NF40 – 205604). IDEA League 
for the Short-term Research Grant to TU Delft. ETH Zurich 
provides open-access funding.

ORCID

Alexander N. Walzer http://orcid.org/0000-0003-3946- 
7954 
Tan Tan http://orcid.org/0000-0002-3374-8299 
Konrad Graser http://orcid.org/0000-0001-8129-6787 
Daniel M. Hall http://orcid.org/0000-0002-0957-484X 

Data availability statement

Due to ethical restrictions, the raw data is not available. 
Aggregated data may be available from the authors upon 
reasonable request.

Notes

1. In engineering disciplines, a ’bug’ signifies a flaw 
requiring correction, while a ’feature’ is a beneficial 
function. Interestingly, bugs’ first and second-order 
effects can sometimes result in features. First-order 
effects are the immediate consequences of a bug, such 
as a system malfunction. Second-order effects are the 
subsequent impacts that occasionally lead to 
unintended beneficial functions or innovations. One of 
the most famous anecdotes related to the term ’bug’ 
involves Grace Hopper, a pioneer in computer science, 
in the 1940s. While working on the Harvard Mark II 
computer, her team discovered a malfunction caused by 
a deceased moth trapped in the system. They removed 
the deceased bug and humorously noted that they had 
’debugged’ the machine. This incident popularized the 
term ’bug’ in the context of computer science and 
highlighted the ongoing challenges of troubleshooting 
and correcting system flaws (Wills 2022). In addition, this 
study also acknowledges the Kafkaesque journey faced 
by some participants, echoing Kafka’s depiction of a 
protagonist’s abrupt transformation into a bug (Kafka 
1915). This shift illustrates the confusion in modern 
labor and market systems, where individuals face rapid 
changes beyond their control. Consistent with the 
Austrian school of economics, this view highlights the 
subjectivity of personal experiences.

2. Arguably, these assumptions are overly simplistic and 
predominantly U.S.-centric. Incorporating global data 
could potentially adjust the figures downward 
significantly.

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