Electronic Commerce Research
https://doi.org/10.1007/s10660-026-10110-x

Revisiting the shifting landscape of P2P lending: a
systematic review based on the affordance actualization
perspective
Chen-Hao Huang1  · Van-Tan Nguyen1
Received: 4 May 2025 / Accepted: 9 February 2026
© The Author(s) 2026

Abstract
Peer-to-peer (P2P) lending has disrupted traditional financial intermediation, offering an alternative credit system that enhances financial inclusion and investment
accessibility. Despite its rapid growth, challenges related to trust formation, risk
mitigation, and platform governance persist, raising concerns about its long-term
sustainability. This study conducts a systematic review of P2P lending through
the affordance actualization perspective, examining how digital platforms facilitate trust-building via transparency mechanisms, algorithmic risk assessments, and
regulatory governance. Employing Main Path Analysis (MPA), we trace the intellectual evolution of P2P lending research, identifying key shifts from borrowerlender dynamics to machine learning-driven credit scoring and platform regulation.
Our findings highlight the role of technological affordances in reducing information asymmetry and strengthening lending ecosystems. However, regulatory inconsistencies and emerging risks necessitate further research. This study provides a
comprehensive synthesis of P2P lending's development, offering insights into trust
actualization and future directions for sustainable digital lending models.
Keywords  P2P lending · Main path analysis · Trust actualization · FinTech ·
Digital platform


Van-Tan Nguyen
ra8137028@gs.ncku.edu.tw
Chen-Hao Huang
chhuang@gs.ncku.edu.tw
1



Department of Business Administration, National Cheng Kung University, Tainan
701401, Taiwan

1 3

C.-H. Huang, V.-T. Nguyen

1 Introduction
Peer-to-peer (P2P) lending has emerged as a transformative force in the global financial landscape [4], revolutionizing traditional lending paradigms by disintermediating financial institutions and directly connecting borrowers with lenders through
digital platforms. This innovative financing model has gained substantial academic
and industry attention due to its potential to enhance financial inclusion, mitigate
banking inefficiencies, and provide alternative credit options for underserved populations [19, 81]. However, despite the significant impact of P2P lending on the financial industry, its rapid growth may lead to the oversight of several core issues, such
as trust-building, risk mitigation, and platform governance, thereby raising critical
questions about the sustainability and scalability of P2P lending models [54, 86].
These issues also highlight the importance of examining the development and evolution of the P2P lending domain.
The research focus of P2P lending continues to evolve due to the rapid advancement of related concepts, which may lead to ambiguity in its definition. More specifically, initial studies primarily focused on the roles and behaviors of key participants,
including lenders, borrowers, and platform operators, examining trust formation and
decision-making heuristics in an environment lacking institutional safeguards [57,
29]. These early investigations highlighted how borrower characteristics, such as personal narratives and profile images, influenced lender perceptions and funding success [18]. As the field matured, research pivoted toward transparency and information
asymmetry, addressing concerns about credit risk assessment [84], borrower data disclosure [23, 77], and interest rate determination [19, 58]. During this phase, scholars
explored the effectiveness of credit-scoring models and machine learning techniques
in enhancing default prediction and loan evaluation, underscoring the importance of
robust data-driven risk assessment frameworks [86, 69]. More recently, P2P lending
research has expanded to encompass regulatory dynamics, platform governance, and
institutional investor participation, reflecting the industry's increasing complexity
and integration into mainstream financial markets [73, 85]. In summary, the scope of
P2P lending continues to expand as the field evolves. Therefore, this study aims to
review the development of this domain to clarify the evolution of related concepts.
In addition to the trajectory of P2P lending applications, this study argues that trust
also plays a crucial role in the development of P2P lending. Trust remains a cornerstone of P2P lending ecosystems, as these platforms operate without the traditional
safeguards offered by banks and formal financial institutions. Furthermore, this study
suggests that P2P lending may involve different forms of trust at different stages of
its development. Establishing trust between borrowers and lenders is crucial for platform viability, influencing lending decisions, default rates, and market stability [29,
81]. Prior studies have examined various trust-building mechanisms, including borrower transparency, platform reputation systems, and algorithmic risk assessments
[21, 87]. However, while these mechanisms have improved transactional confidence, persistent challenges such as fraudulent borrower activity, adverse selection,
and regulatory inconsistencies continue to undermine trust in P2P lending markets
[54]. Recent advancements in financial technology (FinTech) have introduced novel
approaches to trust-building in P2P lending. Machine learning algorithms now enable

1 3

Revisiting the shifting landscape of P2P lending: a systematic review…

more accurate borrower profiling and fraud detection, while blockchain technology
offers potential solutions for enhancing transactional transparency and security [24,
65]. Nevertheless, empirical evidence on the effectiveness and long-term impact of
these technologies remains limited. This highlights the need for further research into
their role in trust actualization and financial decision-making.
Traditional adoption theories, such as the Technology Acceptance Model (TAM),
Unified Theory of Acceptance and Use of Technology (UTAUT), or diffusion of
innovation, focus primarily on whether individuals or organizations choose to adopt
a technology, emphasizing determinants such as perceived usefulness, ease of use, or
social influence. While these models explain initial uptake, they offer limited insight
into the ongoing processes by which technology is enacted and adapted in practice. In
contrast, affordance actualization emphasizes how actors engage with specific technological features to realize potential actions and outcomes in context [63]. Within
P2P lending, this perspective shifts the focus from explaining why users adopt platforms to examining how platform functionalities such as credit scoring algorithms,
verification tools, or governance mechanisms are leveraged to build credibility, manage risk, and sustain trust. This theoretical distinction highlights the need for a more
dynamic account of technology trust interactions than adoption theories alone can
provide.
Despite the growing body of literature on P2P lending, a systematic analysis of its
intellectual trajectory, particularly in relation to trust formation and risk assessment,
is lacking. Additionally, although prior research has explored various technological
affordances in P2P lending, their actualization in fostering trust and mitigating risk
has not been comprehensively examined. Regulatory and institutional factors influencing the sustainability of P2P lending models remain underexplored, particularly in
emerging markets where financial inclusion initiatives are gaining momentum [13].
These three gaps collectively motivate the two guiding research questions of this
study. RQ1 addresses the first gap by tracing the intellectual evolution of P2P lending
research over time. RQ2 responds to the second and third gaps by examining how
prior studies have shaped the academic understanding of P2P lending, including the
role of technological affordances in trust actualization and the influence of regulatory
or institutional mechanisms on platform sustainability. To achieve these objectives,
the study is guided by the following research questions:
(1) How has P2P lending research evolved over time?
(2) How have previous studies shaped the academic understanding of P2P lending?
In particular, this study examines how prior research has contributed to the understanding of affordance actualization and regulatory or institutional sustainability
in P2P lending. To address these research questions, this study employs Main Path
Analysis (MPA), a citation-based bibliometric method to systematically trace the
knowledge evolution of P2P lending research. By leveraging Key-Route MPA, this
research identifies the most influential studies shaping the discourse on P2P lending trust-building mechanisms and risk mitigation strategies. Furthermore, this study
introduces the concept of affordance actualization in P2P lending, investigating how

1 3

C.-H. Huang, V.-T. Nguyen

platform affordances facilitate trust formation through transparency, algorithmic
credit scoring, and governance structures.
As P2P lending continues to redefine financial intermediation, its long-term sustainability will depend on the effectiveness of trust-building mechanisms, regulatory
frameworks, and technological innovations. By examining the intellectual evolution of P2P lending research, this study sheds light on critical challenges and future
directions for strengthening trust and mitigating risk in digital lending markets. The
subsequent sections delve deeper into the methodological approach, findings, and
discussion, offering a comprehensive analysis of how P2P lending has transformed
over time.

2  Research method
2.1  Main path analysis
Main Path Analysis, originally introduced by Hummon & Doreian [34], is a citationbased methodology used to trace the development trajectory of a scientific domain
by identifying the most influential studies within a citation network. By analyzing the
structural connectivity of citations, MPA extracts the backbone of a research field,
highlighting the primary knowledge flow that has shaped its evolution [5, 14]. This
method has been widely applied across various disciplines, including social network
analysis [49, 68], technological innovation [43], and blockchain research [1]. While
the original MPA approach focused on a single dominant path, more recent enhancements such as the key-route search method, allow for the identification of multiple
significant pathways, ensuring a more comprehensive representation of knowledge
diffusion [46]. Given its capacity to reveal citation trends and pivotal contributions within an academic field, MPA is particularly useful for systematic literature
reviews and bibliometric analyses, providing insights into the intellectual structure
and knowledge accumulation of emerging research areas [8, 39]. In this study, MPA
will be applied to the domain of P2P lending to map the development of trust-related
research and uncover key studies that have influenced its theoretical and practical
advancements.
2.2  Key-route MPA
To enhance the effectiveness of MPA in capturing the evolution of knowledge, KeyRoute MPA was introduced as an advanced approach to overcome the limitations of
traditional MPA. Unlike the conventional method, which primarily identifies a single
dominant trajectory, Key-Route MPA traces multiple significant paths, ensuring a
more comprehensive representation of knowledge diffusion [46]. This approach has
been widely applied in the IS field, such as VR marketing [49], fake news [1], chief
information officer [40], and electronic commerce [27]. This approach is particularly
useful for complex research fields, as it highlights not only the most frequently cited
studies but also the critical links that bridge different streams of thought, offering a
more nuanced perspective on the development of a domain [32, 79].

1 3

Revisiting the shifting landscape of P2P lending: a systematic review…

Key-Route MPA follows a structured two-step process. First, it calculates the traversal counts of citation links, determining their relative significance in the knowledge network. This can be achieved through different algorithms, such as Search Path
Count (SPC), Search Path Link Count (SPLC), and Search Path Node Pair (SPNP),
each varying in how they define source and sink nodes [48]. Among these, SPLC
is often preferred as it not only considers direct citation links but also integrates
intermediate nodes, allowing for a more realistic representation of how knowledge is
transferred and built upon across studies [44]. The second step involves linking these
significant citation connections into coherent paths, ensuring that the most crucial
knowledge trajectories are captured. Unlike traditional MPA, Key-Route MPA initiates this search from both ends of the network, starting from source nodes (articles
that are cited but do not cite others) and extending towards sink nodes (articles that
cite others but are not further cited), with intermediate nodes acting as crucial bridges
in knowledge transmission [46]. This bi-directional approach prevents the omission
of pivotal studies and provides a more detailed view of the intellectual development
within a field.
A key advantage of Key-Route MPA is its ability to control the granularity of
analysis by adjusting the number of key citation links included, making it particularly well-suited for large and interdisciplinary research networks [32, 48]. By leveraging SPLC-based traversal weights, this method ensures that intermediary nodes,
often essential for understanding transitions and innovations which are properly
represented in the final analysis [48]. By applying Key-Route MPA to P2P lending
research, this study aims to map the field's intellectual development, uncover critical
theoretical and empirical contributions, and highlight key phases of evolution. This
approach will provide a systematic and data-driven perspective on how P2P lending
has transformed over time, revealing its core research themes and guiding future
studies in the domain.
2.3  Multiple global MPA
In addition to Key-Route Main Path Analysis, this study also applies Multiple Global
MPA [47] to capture the diversity of research themes within the citation network.
While Key-Route MPA highlights the most influential citation pathways, Multiple
Global MPA traces parallel trajectories of knowledge development, allowing us to
identify clusters of thematic contributions. Including this method provides a more
comprehensive perspective on how different streams of research such as default risk
modeling, credit scoring, and governance have evolved in parallel. Including both
methods ensures that the subsequent thematic analysis (Sect.  3.3) is fully grounded
in the methodological framework.
In this study, we selected Key-Route 10 as the primary setting for analysis, as it
provides an appropriate balance between parsimony and comprehensiveness, highlighting the central citation flows while avoiding unnecessary complexity. To ensure
robustness, we also conducted sensitivity analyses by applying alternative KeyRoute settings (15, and 20). These additional tests consistently reproduced the threephase developmental trajectory of P2P lending research, with only minor variations
in peripheral paths. In addition, we examined the distribution of citation patterns by

1 3

C.-H. Huang, V.-T. Nguyen

journal impact factor and publication year, confirming that the identified paths reflect
a broad and distributed intellectual development rather than biases concentrated in
high-impact outlets or specific time periods. This combined methodological setup
ensures that both the developmental trajectory (via Key-Route MPA) and the broader
thematic structure (via Multiple Global MPA) are analytically established before
their detailed presentation in the findings.
2.4  Data collection and search strategy
As shown in the Table  1, to ensure a comprehensive and rigorous dataset for this
study, we conducted a systematic literature search using the Web of Science (WoS)
database, specifically drawing from the Science Citation Index Expanded (SCIE) and
Social Science Citation Index (SSCI). These databases were selected due to their
extensive coverage of high-quality academic research, spanning finance, information
systems, and management science. To ensure interdisciplinary coverage, we verified
that the dataset includes publications from leading journals in information management (e.g., MIS Quarterly, Information Systems Research, Journal of Management
Information Systems, Decision Support Systems) and management science/operations research (e.g., Management Science, Management Science, Journal of Business
Research, Information and Management). The search strategy was designed to identify relevant literature on peer-to-peer (P2P) lending by utilizing a set of carefully
chosen keywords derived from highly cited academic studies in the field. The final
keyword set included terms such as “P2P lending”, “peer-to-peer lending”, “online
lending”, “platform lending”, “lending platform” and “lending platforms. The search
was limited to articles, review articles, and early access papers, ensuring that only
peer-reviewed, high-quality publications were included.
Unlike other literature reviews that may focus on a specific discipline or journal, this approach allows for a broader cross-disciplinary exploration of P2P lending research, capturing its development across multiple academic fields. The search
results yielded a total of 659 papers published between February 1st, 2009, and
December 13th, 2024. The selection of 2009 as the starting point was based on the
global financial crisis of 2008, which exposed fundamental weaknesses in traditional
financial intermediaries [26]. This period saw a rise in alternative financial models, including P2P lending, leading to increased academic interest in the topic. After
retrieving the relevant publications, citation details for each paper were extracted
from the WoS database, forming the basis for constructing the citation network. This
citation network serves as the foundation for MPA and Key-Route MPA, enabling the
Table 1  Key words and search
strategy

Database
Search Strategy

Document Type
Search Area
Timespan

1 3

Web of Science
TS = (“P2P lending” or “peer-to-peer lending”
or “online lending” or “platform lending” or
“lending platform” or “lending platforms” or
“platforms lending” not “review')
Article, Review Article OR Early Access
All
From February 1st, 2009 to December 13th,
2024

Revisiting the shifting landscape of P2P lending: a systematic review…

identification of key knowledge trajectories and pivotal research contributions in the
field of P2P lending.

3  Findings and analysis
3.1  Growth of P2P lending publications
The expansion of P2P lending research has followed a steady upward trajectory over
the past decade, reflecting the growing importance of this financial innovation. As
shown in Fig.  1, the number of P2P lending publications has grown rapidly since
2010, with a marked acceleration after 2015. The smoothed curve shown in Fig. 1 is
a software-generated logistic curve fitted to the observed historical data (2009–2025)
using LogletLab. It is included solely to visualize the long-term growth pattern. The
extension of the curve beyond 2025 is not a prediction and does not rely on any
forecasting model, fitting procedure, or validation metrics. It is a mathematical continuation of the curve-fitting function and should be interpreted only as an illustrative
smoothing output rather than as a forward forecast. Additionally, this study does not
perform predictive modeling. The curve beyond 2025 has no inferential meaning and
serves only to show how the software's smoothing function behaves at the boundary of the data range. This surge aligns with the rapid evolution of FinTech, the
increasing adoption of alternative lending platforms, and the rising demand for nontraditional credit options, particularly in response to the 2008 financial crisis [6]. The

Fig. 1  Growth of P2P lending publications

1 3

C.-H. Huang, V.-T. Nguyen

elimination of traditional financial intermediaries in P2P lending has further drawn
academic interest, as researchers examine its implications for financial markets, borrower-lender relationships, and credit risk assessment [18]. The continued growth in
research output suggests that P2P lending remains a highly relevant topic, with ongoing studies exploring risk management, financial inclusion, and platform regulation
[19]. Given the expected trajectory, it is anticipated that P2P lending research will
continue to expand, particularly as new technologies such as blockchain-based smart
contracts and AI-driven credit scoring further shape the industry's development [9].
Although the overall trend indicates continuous growth, annual fluctuations in
research output suggest shifts in scholarly focus and external market influences. In
certain years, there has been a notable increase in publications, often corresponding with regulatory changes, financial disruptions, or technological breakthroughs
that affect the P2P lending ecosystem [60]. For example, studies have analysed how
various regulatory frameworks, ranging from strict licensing regulations to more
open-market policies, impact the sustainability and credibility of P2P platforms [6].
Additionally, concerns regarding default rates, fraud risks, and platform stability
have driven shifts in academic interest, with research peaking in response to major
policy updates or economic uncertainties [19]. Despite these periodic fluctuations,
the cumulative growth pattern highlights P2P lending's increasing role in the digital
financial landscape. As the market continues to evolve, future research is likely to
focus on strengthening risk management mechanisms, enhancing transparency, and
integrating advanced financial technologies to ensure the long-term sustainability of
P2P lending platforms.
3.2  The development trajectory of P2P lending
As P2P lending research continues to evolve, identifying the most influential studies
and their intellectual connections is essential for understanding the field's trajectory.
To achieve this, this study applies Key-Route MPA, a method that highlights the most
critical citation pathways by ranking citation links based on their traversal frequency.
This approach consists of two key steps: first, determining the importance of citation links by calculating their traversal counts, and second, constructing a main path
that connects the most frequently traversed citations. With a dataset of 659 research
papers and 4,936 citation links, the analysis uses Key-Route 10, selecting the 10
most significant citation links based on the Search Path Link SPLC algorithm. This
approach ensures that the core intellectual structure of P2P lending research is captured while keeping the visualization clear and interpretable. While increasing the
number of seed links could uncover additional pathways, it would also add complexity, making the developmental trajectory harder to follow. By applying Key-Route 10
MPA, this study maps out the key turning points in P2P lending research, filtering out
less impactful connections and providing a structured view of the field's evolution.
The results offer insights into the thematic progressions and influential contributions
shaping P2P lending. It is noteworthy that the three-phase developmental trajectory
remained stable across robustness checks using different Key-Route settings (10, 15,
and 20). This consistency reinforces the reliability of the results and indicates that the
evolution of P2P lending research is not an artifact of parameter choice but a persis-

1 3

Revisiting the shifting landscape of P2P lending: a systematic review…
Table 2  Highest traversal links

Counts
1
2
3

Traversal
Counts
(SPLC)
354615.00
292016.00
278016.00

4

223661.00

5
6
7
8
9
10

203265.00
154966.00
151961.00
146008.00
146008.00
140866.00

Route
ZhangL2012 ◊ DuarteSY2012
HerzensteinSD2011 ◊ ZhangL2012
Serrano-cincaGL2015 ◊
Serrano-cincaG2016
Serrano-cincaGL2015 ◊
Serrano-cincaG2016
ZhangL2012 ◊ YumLC2012
DuarteSY2012 ◊ EmekterTJL2015
Morse2015 ◊ IyerKLS2016
KohtamäkiPPG2020 ◊ ZhangL2012
PopeS2011 ◊ ZhangL2012
MildWW2015 ◊ Serrano-cincaGL2015

Fig. 2  The development trajectory of P2P lending

tent intellectual pattern confirmed across methodological variations. Table 2 presents
the top citation links, which serve as the foundation of this analysis, reflecting the
most significant studies driving the development of the field.
Figure 2 presents the citation network, highlighting 29 key articles from 2009 to
2024 that have significantly shaped the field. This network is constructed using Pajek
software, which visually represents knowledge flow through node colors, labels,
arrows, and line thickness. In this visualization, green nodes indicate foundational
studies (source articles), red nodes represent intermediate contributions, and blue
nodes signify recent advancements that are pushing the field forward. The thickness
of citation links corresponds to the significance of knowledge transfer, offering a
structured overview of how research themes have evolved over time.
The development of P2P lending research has progressed through distinct phases,
as revealed by the Key-Route MPA conducted in this study. The citation network

1 3

C.-H. Huang, V.-T. Nguyen

identifies three key phases in the intellectual evolution of P2P lending: (1) Actors in
P2P Lending, (2) Transparency in P2P Lending, and (3) Approaches to Cultivating
Trust in P2P Lending. Each phase represents a critical shift in the academic discourse
surrounding P2P lending, illustrating how the field has evolved from understanding
key actors, to addressing transparency and risk assessment, and ultimately, to developing mechanisms for trust cultivation. It is important to note that the three phases,
while analytically distinct, are interconnected. Insights generated in one phase often
serve as the foundation for subsequent developments. For example, early studies on
borrower–lender interactions and personal credibility (Phase 1) informed later work
on transparency mechanisms (Phase 2), while these transparency practices in turn
provided the empirical basis for more advanced trust-building strategies (Phase 3).
Thus, the phases should be understood as overlapping trajectories in a cumulative
process rather than as isolated stages. This study captures the evolution of P2P lending research by highlighting significant developments and academic contributions.
The insights provide a foundation for deeper exploration of its key phases in the following subsequent sections (Fig. 2).
3.2.1  Phase 1: actors in P2P lending
The early development of P2P lending was significantly shaped by the interactions
between key actors, including lenders, borrowers, and the platforms that facilitated
these transactions. At this stage, researchers explored how trust, behavioral patterns,
and decision-making processes influenced lending outcomes. Unlike traditional
financial systems, where banks assess creditworthiness using standardized metrics,
P2P lending introduced a decentralized model in which individual lenders made
funding decisions based on both quantitative data (credit scores, income levels) and
qualitative factors (personal narratives, borrower photos) [57]. This era of research
laid the foundation for understanding the mechanisms that drive participation in P2P
lending and the conditions under which trust is established in this alternative financial
system.
A key theme during this phase was the role of borrower characteristics in influencing lender decisions. Several studies examined how non-financial cues shaped
perceptions of creditworthiness. Pope and Sydnor [57] investigated the impact of
borrower profile pictures on lending behavior, demonstrating that visual appearance
influenced trust perceptions, sometimes leading to discriminatory lending patterns.
Similarly, Duarte et al. [18] found that borrowers who appeared more trustworthy in
their profile images were more likely to secure funding and had better loan repayment
performance. Beyond physical appearance, Herzenstein et al. [29] highlighted the
power of narratives in shaping lender decisions, showing that compelling personal
stories increased the likelihood of receiving funding.
In addition to borrower characteristics, herding behavior among lenders emerged
as a crucial factor in loan allocation. Zhang and Liu [81] introduced the concept of
“rational herding” wherein lenders made funding decisions based on prior lender
activity, using the collective choices of others as a heuristic for borrower quality.
This behavior was also examined by Herzenstein et al. [29], who found that strategic
herding in loan auctions led to higher funding success rates. Yum et al. [80] further

1 3

Revisiting the shifting landscape of P2P lending: a systematic review…

explored the transition from crowd-based decision-making to individual judgment,
showing that lenders initially relied on the “wisdom of the crowd” but gradually
developed independent risk assessment skills as they gained experience. This phase
underscores the key role of trust dynamics and decision-making heuristics in P2P
lending. Early studies on borrower characteristics, narratives, and herding behavior offered insights into trust formation between anonymous lenders and borrowers.
Understanding these interactions is crucial for designing transparent, efficient platforms that balance inclusivity and risk management.
3.2.2  P