Supply Risk Management and Firms' Competitive Advantage: moderating effect of Intellectual Capital and Risk Management Capability

Abstract

In today's dynamic business environment, supply chain disruptions and uncertainties were inevitable, posing significant challenges to firms aiming to maintain a competitive edge. Firms faced increasing risks from global supply chain complexities, geopolitical tensions, and unexpected events such as natural disasters and pandemics. This study addressed a critical knowledge gap by exploring the nuanced interplay between supply risk management (SRM) practices, a firm's competitive advantage, and the moderating influences of intellectual capital (IC) and risk management capability (RMC). Our research investigated these relationships through a survey of 284 Ghanaian SMEs and a comprehensive analysis. The results revealed that effective SRM practices significantly enhanced a firm's competitive advantage by enabling better risk identification, assessment, and mitigation strategies. However, contrary to conventional wisdom, the study found that high levels of intellectual capital could negatively moderate this relationship. This unexpected finding suggested that over-reliance on IC might introduce cognitive biases or resource allocation challenges that undermine SRM effectiveness, potentially leading firms to underestimate risks or misallocate resources. Conversely, the findings confirmed that robust RMC positively moderated the relationship between SRM and competitive advantage. Firms with strong risk management capabilities were better equipped to align their risk management practices with broader organizational strategies, enhancing their ability to respond to and recover from disruptions. This alignment allowed firms to maintain operational continuity and achieve strategic objectives, thereby reinforcing their competitive position in the market. This study contributes to the literature by providing a nuanced understanding of how SRM, IC, and RMC interacted to influence competitive advantage. It offered both theoretical insights into the complex dynamics of supply chain risk management and practical implications for organizations striving to optimize their supply chain strategies amidst a volatile

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Copyright © ISRG Publishers. All rights Reserved.
DOI: 10.5281/zenodo.14049858
30
ISRG PUBLISHERS
Abbreviated Key Title: Isrg J Econ Bus Manag
ISSN: 2584-0916 (Online)
Journal homepage: https://isrgpublishers.com/isrgjebm/
Volume – II Issue - VI (November-December) 2024
Frequency: Bimonthly
Supply Risk Management and Firms’ Competitive Advantage: moderating effect of
Intellectual Capital and Risk Management Capability
Norgbey Ernest Henry1*, Ofori Issah2, Obiri Yeboah Hanson3, Makafui R. Agboyi4
1, 2 PhD candidate KNUST School of Business.
3, 4 Lecturer Accra Technical University.
| Received: 31.10.2024 | Accepted: 03.11.2024 | Published: 07.11.2024
*Corresponding author: Norgbey Ernest Henry
PhD candidate KNUST School of Business.
Abstract
In today's dynamic business environment, supply chain disruptions and uncertainties were inevitable, posing significant challenges
to firms aiming to maintain a competitive edge. Firms faced increasing risks from global supply chain complexities, geopolitical
tensions, and unexpected events such as natural disasters and pandemics. This study addressed a critical knowledge gap by
exploring the nuanced interplay between supply risk management (SRM) practices, a firm's competitive advantage, and the
moderating influences of intellectual capital (IC) and risk management capability (RMC). Our research investigated these
relationships through a survey of 284 Ghanaian SMEs and a comprehensive analysis. The results revealed that effective SRM
practices significantly enhanced a firm's competitive advantage by enabling better risk identification, assessment, and mitigation
strategies. However, contrary to conventional wisdom, the study found that high levels of intellectual capital could negatively
moderate this relationship. This unexpected finding suggested that over-reliance on IC might introduce cognitive biases or
resource allocation challenges that undermine SRM effectiveness, potentially leading firms to underestimate risks or misallocate
resources. Conversely, the findings confirmed that robust RMC positively moderated the relationship between SRM and
competitive advantage. Firms with strong risk management capabilities were better equipped to align their risk management
practices with broader organizational strategies, enhancing their ability to respond to and recover from disruptions. This
alignment allowed firms to maintain operational continuity and achieve strategic objectives, thereby reinforcing their competitive
position in the market. This study contributes to the literature by providing a nuanced understanding of how SRM, IC, and RMC
interacted to influence competitive advantage. It offered both theoretical insights into the complex dynamics of supply chain risk
management and practical implications for organizations striving to optimize their supply chain strategies amidst a volatile

Copyright © ISRG Publishers. All rights Reserved.
DOI: 10.5281/zenodo.14049858
31
1. Introduction
In the contemporary business landscape, characterized by
globalization, interconnected supply chains, and heightened
uncertainties, organizations face an imperative to navigate and
mitigate risks effectively. Central to this endeavor is the discipline
of Supply Risk Management (SRM), which has garnered
increasing attention due to its profound implications for a firm's
competitiveness and sustainability (Tang, 2016; Chopra & Sodhi,
2019). The evolution of Supply Risk Management (SRM) is deeply
entwined with the escalating complexity and interdependence of
global supply chains. Organizations, facing a myriad of risks
ranging from natural disasters to geopolitical disruptions, have
recognized the need for a proactive approach to anticipate, assess,
and mitigate these risks (Chopra & Sodhi, 2018). The traditional
reactive stance has given way to strategic SRM, where
organizations seek to integrate risk management practices
seamlessly into their supply chain strategies (Wagner & Bode,
2018).
Competitive advantage stands as a paramount objective for
organizations striving to outperform rivals and secure sustainable
success (Porter, 1985). In the context of supply chains, competitive
advantage extends beyond traditional cost considerations to
encompass operational efficiency, innovation, and resilience
(Christopher, 2016). Achieving and sustaining competitive
advantage in the supply chain is contingent upon a multifaceted
understanding of risk management and its integration into
organizational strategies (Mentzer et al., 2021).
Intellectual Capital (IC), comprising human, structural, and
relational dimensions, emerges as a critical factor in shaping the
link between SRM and competitive advantage. The knowledge,
skills, and relationships embedded in Intellectual Capital are
posited to act as a dynamic force that influences how organizations
respond to and leverage supply chain risks (Bontis, 1998;
Subramaniam & Youndt, 2017). As organizations navigate
uncertainties, the intellectual resources they possess become
instrumental in not only mitigating risks but also in innovating and
creating a distinctive competitive edge. Beyond SRM, the broader
organizational capacity to manage risks, termed as Risk
Management Capability (RMC), assumes significance. Risk
Management Capability involves the integration of risk
management practices across different levels of the organization,
aligning them with strategic goals (Chapman & Ward, 2017). Risk
Management Capability acts as a comprehensive framework that
extends beyond supply chain-specific risks to encompass a broader
spectrum of uncertainties, enabling organizations to respond to
challenges with agility and resilience.
While the importance of Supply Risk Management and its
relationship with competitive advantage has gained attention, there
exists a notable research gap concerning the nuanced roles of
Intellectual Capital and Risk Management Capability. The
interplay between Intellectual Capital, Risk Management
Capability, and their combined impact on how Supply Risk
Management translates into competitive advantage remains
underexplored. Understanding this intersection is crucial for
organizations seeking a holistic and effective approach to navigate
uncertainties in the supply chain landscape. This research aims to
fill the identified research gap by investigating the roles of
Intellectual Capital and Risk Management Capability in
moderating the relationship between Supply Risk Management and
a firm‘s Competitive Advantage. The study seeks to contribute
theoretical insights and practical implications for organizations
striving to optimize their supply chain strategies in a dynamically
changing environment.
1.1. Problem Statement
In today's dynamic business environment, supply chain disruptions
and uncertainties have become inevitable, posing significant
challenges to firms aiming to maintain a competitive edge. As
organizations increasingly recognize the importance of supply risk
management in navigating these uncertainties, a critical knowledge
gap exists in understanding the nuanced interplay between supply
risk management practices, a firm's competitive advantage, and the
moderating influences of intellectual capital and risk management
capability (Chopra & Sodhi, 2021; Wagner & Bode, 2018).
Despite the growing recognition of the pivotal role of supply risk
management in addressing disruptions, there is a noticeable gap in
the understanding of its direct impact on a firm's competitive
advantage (Chen, Paulraj, & Lado, 2021). Achieving and
sustaining a competitive advantage in today's volatile environment
necessitate a nuanced exploration of how supply risk management
practices contribute to enhanced firm performance and market
positioning (Soni, Kodukula, & Papudesu, 2020).
Moreover, the potential moderating effects of intellectual capital
and risk management capability on the relationship between supply
risk management and competitive advantage remain
underexplored. Intellectual capital, encompassing human,
structural, and relational capital, is increasingly recognized as a
source of competitive advantage (Bontis, 1998; Subramaniam &
Youndt, 2005). Additionally, the role of an organization's risk
management capability in influencing the effectiveness of supply
risk management strategies is an area that merits closer
examination (Cagliano, Caniato, & Spina, 2006).
While studies acknowledge the pivotal role of Supply Risk
Management in mitigating supply chain risks and maintaining
competitiveness (Tang, 2006; Christopher, 2016), there is a paucity
of research that comprehensively explores how Intellectual Capital
and Risk Management Capability, as moderating factors, influence
the relationship between SRM and Competitive Advantage. The
limited research fails to provide a holistic understanding of how
intellectual resources and broader organizational risk management
strategies amplify or attenuate the impact of SRM on a firm‘s
competitive position. Hence this study seeks to determine the
combined effect of Intellectual Capital and Risk Management
business environment. By highlighting the critical roles of intellectual capital and risk management capability, the research
underscored the need for a balanced approach that leverages both intellectual resources and robust risk management practices to
sustain competitive advantage.
Keywords: supply risk management, firms’ competitive advantage, intellectual capital, risk management capability

Copyright © ISRG Publishers. All rights Reserved.
DOI: 10.5281/zenodo.14049858
32
Capability independently moderates the relationship between
supply risk management and firm‘s competitive advantage.
Intellectual Capital, encompassing human, structural, and relational
dimensions, introduces a layer of complexity to the relationship.
The knowledge, skills, and relationships embedded in intellectual
resources have been recognized as influential factors in
organizational success (Bontis, 1998; Subramaniam & Youndt,
2019). However, the specific mechanisms through which
Intellectual Capital interacts with SRM and shapes a firm‘s
Competitive Advantage remain underexplored. Therefore, this
study seeks to assess the moderating effect of Intellectual Capital
on the relationship between supply risk management and firm‘s
competitive advantage.
Similarly, the broader organizational Risk Management Capability,
extending beyond supply chain-specific risks, adds another
dimension to the complexity. Chapman and Ward (2020) argue for
a comprehensive risk management approach that integrates various
levels of the organization and aligns with strategic objectives. Yet,
the literature lacks clarity on how this broader risk management
capability interacts with Supply Risk Management and contributes
to a firm‘s Competitive Advantage. This has then necessitated the
need to examine the moderating effect of Risk Management
Capability on the relationship between supply risk management
and firm‘s competitive advantage.
The overarching problem addressed by this study is the need for a
nuanced understanding of the interplay between Supply Risk
Management, Intellectual Capital, Risk Management Capability,
and a firm‘s Competitive Advantage. The existing gap hinders
organizations from strategically aligning their intellectual resources
and risk management practices with supply chain strategies,
potentially limiting the realization of the full potential of SRM
(Wagner & Bode, 2008; Subramaniam & Youndt, 2005).
This research aims to bridge this gap by investigating the
moderating effects of Intellectual Capital and Risk Management
Capability on the relationship between Supply Risk Management
and a firm‘s Competitive Advantage. The study seeks to provide
insights that not only contribute to theoretical advancements in the
field but also offer practical implications for organizations striving
to optimize their supply chain strategies amidst a dynamic and
uncertain business environment.
Research Gaps
While existing literature recognizes the essential role of SRM in
mitigating supply chain risks (Tang, 2006; Christopher, 2016),
there is a conspicuous lack of comprehensive exploration into the
specific mechanisms through which Intellectual Capital and
broader Risk Management practices interact with and shape the
relationship between Supply Risk Management and a firm‘s
Competitive Advantage. The literature has yet to provide a holistic
understanding of how intellectual resources and organizational risk
management strategies contribute to or hinder the optimization of
SRM for sustained competitive advantage.
Intellectual Capital, consisting of human, structural, and relational
components, introduces an additional layer of complexity. The
knowledge, skills, and relationships embedded within intellectual
resources are recognized as critical drivers of organizational
success (Bontis, 1998; Subramaniam & Youndt, 2019). However,
the specific ways in which Intellectual Capital interfaces with SRM
and influences a firm‘s Competitive Advantage remain
inadequately explored.
In tandem, the broader organizational Risk Management practices
extend beyond the realm of supply chain-specific risks. Chapman
and Ward (2017) advocate for a comprehensive risk management
approach that permeates different levels of the organization and
aligns with strategic objectives. Yet, the literature lacks a clear
understanding of how this holistic Risk Management framework
interacts with SRM and contributes to the broader Competitive
Advantage of the firm.
While the literature acknowledges the critical role of Intellectual
Capital (IC) in organizational success (Bontis, 1998), there is a
noticeable gap in understanding how IC specifically influences the
relationship between Supply Risk Management (SRM) and a firm's
Competitive Advantage. Existing studies often focus on the general
importance of IC but fall short in providing a detailed examination
of the mechanisms through which intellectual resources enhance or
hinder the effectiveness of SRM strategies (Subramaniam &
Youndt, 2015).
The broader organizational Risk Management Capability (RMC),
extending beyond supply chain-specific risks, is an essential aspect
that has not been thoroughly integrated into the literature on SRM
and Competitive Advantage. While Chapman and Ward (2017)
advocate for a comprehensive risk management approach aligned
with strategic objectives, the literature lacks a cohesive
understanding of how RMC interacts with and moderates the
relationship between SRM and a firm's Competitive Advantage.
The current body of literature provides insights into the individual
constructs of SRM, IC, and RMC, but there is a dearth of research
that comprehensively explores their combined impact. There is
limited understanding of how IC and RMC act as moderating
factors in the relationship between SRM and a firm's Competitive
Advantage. A nuanced examination of these moderating effects is
crucial for a holistic understanding of the dynamics at play (Chopra
& Sodhi, 2014; Wagner & Bode, 2018).
Contextual Gaps
Identifying contextual gaps involves highlighting areas within the
existing literature where further research is needed. There are
potential contextual gaps for the study on "Supply Risk
Management and Firm's Competitive Advantage: Moderating
Effect of Intellectual Capital and Risk Management Capability,"
Limited Exploration of Direct Impact on Competitive Advantage
While the importance of supply chain risk management is
acknowledged (Wagner & Bode, 2018), there is a noticeable gap in
understanding the direct impact of supply risk management
practices on a firm's competitive advantage (Chen, Paulraj, &
Lado, 2014). Existing studies often focus on risk mitigation
without explicitly linking it to competitive advantage (Soni,
Kodukula, & Papudesu, 2015).
Neglect of Intellectual Capital as a Moderator
Despite the growing recognition of intellectual capital as a driver
of competitive advantage (Bontis, 2018; Subramaniam & Youndt,
2015), there is a paucity of research exploring its moderating role
in the relationship between supply risk management and
competitive advantage. Understanding how intellectual capital
enhances or hinders the effectiveness of supply risk management
practices is a critical gap in the literature.
Underexplored Role of Risk Management Capability
While risk management capability is acknowledged as essential in
supply chain literature (Cagliano, Caniato, & Spina, 2016), its

Copyright © ISRG Publishers. All rights Reserved.
DOI: 10.5281/zenodo.14049858
33
specific role as a moderator in the relationship between supply risk
management and competitive advantage remains underexplored.
Existing studies often focus on risk management in general terms
rather than examining how an organization's capability to manage
risks influences the outcomes of supply risk management
strategies.
Limited Integration of Moderating Factors
Current research tends to treat intellectual capital and risk
management capability in isolation rather than exploring their
combined moderating effects. There is a need for studies that
integrate these two moderating factors to provide a more holistic
understanding of how intellectual capital and risk management
capability jointly influence the relationship between supply risk
management and competitive advantage (Wagner & Bode, 2018).
Many existing studies in the field tend to be theoretical or
conceptual in nature, with a scarcity of empirical research that
validates the proposed relationships. Empirical studies are essential
to corroborate theoretical frameworks and provide practical
insights into the effectiveness of SRM strategies, considering the
moderating roles of IC and RMC (Tang, 2006; Christopher, 2016).
The problem statement articulates the research gap, highlights the
complexity introduced by Intellectual Capital and Risk
Management Capability, and emphasizes the overarching challenge
of understanding their moderating effects on the relationship
between Supply Risk Management and Competitive Advantage.
2.1. Literature Review
2.2. Concept of Supply Risk Management
Supply chain risk management is the process of identifying,
assessing, and controlling the various risks associated with the
supply chain. Supply chain risk management is becoming
increasingly important for businesses as supply chains have
become more complex and global. It is essential to have an
effective supply risk management strategy to mitigate the risks that
can impact the supply chain. This paper will discuss the supply risk
management concept in detail, including its definition, types of
risks, risk assessment, and mitigation strategies Dullaert (2018).
Supply risk management is the process of identifying, assessing,
and controlling the various risks associated with the supply chain.
It involves managing risks across the supply chain, including
suppliers, manufacturers, distributors, and customers. The aim of
supply risk management is to ensure that the supply chain is
resilient to external and internal disruptions and continues to
operate smoothly even in the face of disruptions (Ibid). There are
various types of risks associated with the supply chain. These risks
can be broadly classified into four categories: Operational risks:
These risks are associated with the day-to-day operations of the
supply chain, such as equipment breakdowns, power outages, and
transportation disruptions. Financial risks: These risks are
associated with the financial aspects of the supply chain, such as
exchange rate fluctuations, credit risk, and supplier bankruptcy.
Reputational risks: These risks are associated with the reputation of
the supply chain, such as negative publicity due to environmental
or social issues (Tang, 2016). Strategic risks: These risks are
associated with the strategic decisions made by the supply chain,
such as mergers and acquisitions, entering new markets, and
changing suppliers.
Currently, supply chain risks are gaining prominence in both
academic research and the business realm, and various
categorizations of these risks exist in the literature. Managing
supply chain risks is a crucial factor in identifying potential threats
in international markets, especially in times of intense competition
(Wieland & Marcus Wallenburg, 2012). This management
approach significantly contributes to reducing operational losses,
enhancing supply chain performance, ensuring timely order
deliveries, and increasing responsiveness (Munir et al., 2020).
Operational supply chain risks, as defined by Lin and Zhou (2011)
and Olson and Wu (2010), encompass internal risks (demand risks)
and external risks (such as natural disasters, wars, terrorism, and
political instability). Ravindran et al. (2010) identified risks related
to late delivery and missing quality requirements, while Samvedi et
al. (2013) classified risks into categories such as supply, demand,
process, and environmental risks. Blackhurst et al. (2008)
described supply chain risks, including supplier dependency,
quality problems, security risks, disruptions in logistics processes,
information systems problems, capacity shortages, and natural
disasters. Analyzing 39 empirical studies, Wuni et al. (2019)
identified 30 critical risk factors. Ho et al. (2015) evaluated supply
chain risk types and reduction strategies based on academic studies
in the field between 2003 and 2013.
Contrarily, Pham et al. (2022) pointed out that while academic
studies primarily focus on identifying risks, there is a scarcity of
research on risk reduction. Waqas et al. (2022) investigated the
moderator effect of knowledge management on the relationship
between food supply chain risks and supply chain performance in
Malaysia. Shenoi et al. (2016) concluded that supply chain risk
management plays a mediating role and has a positive effect on the
relationship between supply chain risks and performance.
Giannakis and Louis (2011) developed a multi-agent-based
decision support system to detect interruptions and disruptions in
supply chain processes, leading to quicker and more reliable
information sharing throughout the supply chain. Risk, when
dealing with the supply chain, is considered an unpredictable
failure or undesirable outcome, encompassing any risks occurring
during information flows, raw material, and production from initial
suppliers to end-users in the entire supply chain (Jüttner et al.,
2003). Previous studies suggest that supply chain risk refers to the
negative deviation from expected performance measures, resulting
in negative consequences for the focal firm (Wagner & Bode,
2008) and the potential variation of outcomes influencing the
decrease of value-added at any activity cell in a chain (Bogataj &
Bogataj, 2007). In the context of supply chain risk management, it
can be defined as the recognition and control of supply chain risks
to decrease susceptibility through a collaborative approach
between supply chain actors (Jüttner, 2005; Jüttner et al., 2003).
Supply chain risk management involves the administration of risks
through allocation and collaboration among participants to ensure
effectiveness and efficiency for the supply chain (Tang, 2006).
Strong collaborations among stakeholders are crucial to identify
and manage risks for reducing supply chain susceptibility within
the supply network (Goh et al., 2007).
2.3. Intellectual capital
Intellectual capital (IC) is a concept that has gained significant
attention in the management literature over the past few decades. It
refers to the intangible assets of an organization that contributes to
its competitiveness and long-term success. These intangible assets
include knowledge, expertise, skills, relationships, and other non-
physical resources that cannot be easily measured by traditional
accounting methods. The purpose of this paper is to provide an
overview of the concept of intellectual capital, its different
components, and its significance in contemporary business
environments. The concept of intellectual capital was first

Copyright © ISRG Publishers. All rights Reserved.
DOI: 10.5281/zenodo.14049858
34
introduced by Stewart (1991) who defined it as "the sum of
everything everybody in a company knows that gives it a
competitive edge". Since then, various scholars have proposed
different frameworks to conceptualize and measure IC. One widely
accepted framework is the one proposed by Bontis (1998), which
categorizes IC into three components: human capital, structural
capital, and relational capital.
Human capital refers to the knowledge, skills, and abilities of the
employees of an organization. It includes their education, training,
experience, and expertise. Human capital is critical for firms
because it enables them to innovate, create new products, and adapt
to changing business environments. Organizations that invest in
their employees' development and well-being can enhance their
human capital, which in turn contributes to their competitiveness
and long-term success (Bontis et al., 2002). Structural capital refers
to the organizational infrastructure that supports knowledge
creation, transfer, and utilization. It includes the organization's
systems, processes, databases, and intellectual property. Structural
capital is critical for firms because it enables them to leverage their
human capital and create value from it. Organizations that invest in
their structural capital can enhance their ability to innovate,
improve efficiency, and respond to market changes (Bontis et al.,
2002).
Relational capital refers to the relationships that an organization
has with its external stakeholders, such as customers, suppliers,
partners, and communities. It includes the organization's
reputation, brand image, and social capital. Relational capital is
critical for firms because it enables them to build trust, loyalty, and
commitment with their stakeholders. Organizations that invest in
their relational capital can enhance their reputation, attract new
customers, and create long-term partnerships that contribute to
their competitiveness and long-term success (Bontis et al., 2002).
The significance of intellectual capital in contemporary business
environments cannot be overstated. In today's knowledge-based
economy, organizations that effectively manage their intellectual
capital can gain a competitive advantage over their rivals. They can
innovate, create new products, and respond to market changes
more effectively than their competitors. Additionally, they can
attract and retain talented employees, create strong relationships
with their stakeholders, and enhance their reputation and brand
image (Bontis et al., 2002). Intellectual capital is a critical concept
in contemporary business environments. It refers to the intangible
assets of an organization that contribute to its competitiveness and
long-term success. These intangible assets include human capital,
structural capital, and relational capital. Organizations that invest
in their intellectual capital can gain a competitive advantage over
their rivals by leveraging their knowledge, skills, and relationships
to create value and respond to market changes. Therefore, the
effective management of intellectual capital is a key driver of
organizational success.
2.4. Risk Management Capability
Risk management capability is essential for firms operating in
today's complex and unpredictable business environment. It refers
to the ability of a firm to identify, assess, and respond to risks in a
proactive and effective manner. In this paper, we will explore the
concept of risk management capability, including its definition,
components, and how firms can develop and improve it (Hillson,
2022). Risk management capability refers to a firm's ability to
anticipate and manage risks across its operations and value chain,
including strategic, operational, financial, and reputational risks
(Hillson, 2002). It involves a range of activities, such as risk
identification, risk assessment, risk mitigation, risk transfer, and
risk monitoring and reporting.Risk management capability can be
broken down into several key components, including
organizational culture, risk assessment processes, risk management
tools and techniques, and risk governance structures (Schoemaker
et al., 2018). Organizational culture refers to the shared values,
beliefs, and norms that shape how a firm approaches risk
management. Risk assessment processes involve identifying and
evaluating risks, including their likelihood and potential impact.
Risk management tools and techniques include risk mitigation
strategies, such as insurance, hedging, and diversification. Risk
governance structures refer to the formal policies, procedures, and
governance mechanisms that guide risk management activities and
decision-making. Firms can develop and improve their risk
management capability through various strategies, such as
investing in risk management education and training, fostering a
risk-aware culture, and implementing robust risk management
processes and tools (Schoemaker et al., 2018). Additionally, firms
can leverage emerging technologies, such as artificial intelligence
and machine learning, to improve their risk management
capabilities.Risk management capability is critical for firms
operating in today's dynamic and uncertain business environment.
By developing and improving their risk management capabilities,
firms can enhance their resilience, reduce their exposure to risks,
and achieve sustainable growth and competitive advantage. As
such, risk management capability should be a top priority for firms
of all sizes and industries.
2.5. Firms’ Competitive Advantage
Competitive advantage is the ability of a firm to outperform its
competitors in terms of profitability, market share, customer
loyalty, and other key performance indicators. It is a critical
concept in the field of strategic management, as firms strive to gain
and sustain competitive advantage in order to achieve long-term
success. One of the most influential frameworks for understanding
competitive advantage is the resource-based theory, which suggests
that a firm's resources and capabilities are the primary drivers of its
competitive advantage. According to this theory, firms can achieve
a sustained competitive advantage by developing and leveraging
resources and capabilities that are valuable, rare, inimitable, and
non-substitutable (Barney, 1991). One key resource that can
contribute to a firm's competitive advantage is its human capital.
Human capital refers to the knowledge, skills, and experience of a
firm's employees, which can enable the firm to innovate, improve
efficiency, and provide superior customer service. Research has
shown that firms with high levels of human capital tend to perform
better than those with lower levels (Hitt et al., 2001).
Another important resource for competitive advantage is
technology. Firms that are able to develop or acquire cutting-edge
technology can gain a significant edge over their competitors, as
they can use this technology to improve their products, processes,
and services. For example, Apple's development of the iPhone and
iPad helped it to gain a significant advantage over its competitors
in the mobile device market. In addition to resources, firms can
also develop capabilities that contribute to their competitive
advantage. One important capability is innovation, which refers to
a firm's ability to develop new products, processes, and business
models. Firms that are able to consistently innovate can gain a
significant advantage over their competitors, as they can introduce
new products and services that meet evolving customer needs.
Another important capability is operational efficiency, which refers

Copyright © ISRG Publishers. All rights Reserved.
DOI: 10.5281/zenodo.14049858
35
to a firm's ability to produce goods and services at a lower cost
than its competitors. This can be achieved through various means,
such as optimizing supply chain management, reducing waste, and
improving production processes. Firms that are able to achieve
high levels of operational efficiency can offer lower prices to
customers, which can help them to gain market share. Competitive
advantage is a critical concept in the field of strategic management,
as it can enable firms to achieve long-term success. By developing
and leveraging valuable resources and capabilities, firms can
outperform their competitors in terms of profitability, market share,
and other key performance indicators. The resource-based theory
provides a useful framework for understanding how firms can
achieve sustained competitive advantage, by identifying resources
and capabilities that are valuable, rare, inimitable, and non-
substitutable.
2.6. Hypothetical model for the Study
2.6.1. Supply Risk Management and Firms’
Competitive Advantage
Supply risk management has become a critical area of focus for
firms across industries due to the growing recognition of its impact
on a firm's competitive advantage. Managing supply risks
effectively cannot only reduce the negative impact of disruptions
but also create a competitive edge for firms. This paper proposes
the hypothesis that effective supply risk management positively
impacts a firm's competitive advantage. Firstly, supply chain
disruptions have a significant impact on firm performance.
According to Kerkhof et al. (2018), supply chain disruptions have
resulted in decreased sales, increased costs, and lost market share
for many firms. The ability to mitigate these risks through effective
supply risk management can prevent such negative impacts on firm
performance, leading to competitive advantages in the long term.
Secondly, effective supply risk management can create
opportunities for firms to innovate and differentiate themselves
from their competitors. For example, firms that develop more
resilient supply chains can deliver higher product quality and
consistency levels, leading to increased customer satisfaction and
loyalty (Kerkhof et al., 2018). Additionally, firms that successfully
manage supply risks can develop new product offerings, expand
into new markets, and create stronger supplier relationships, all of
which can contribute to competitive advantage. Finally, supply risk
management can lead to improved operational efficiency and cost
savings, which can also contribute to a firm's competitive
advantage. By proactively managing risks, firms can reduce costs
associated with supply chain disruptions, such as rush orders,
inventory costs, and production delays (Handfield et al., 2011). In
conclusion, the effective management of supply chain risks can
provide firms with a competitive advantage through improved
performance, innovation, and cost savings. However, ineffective
supply risk management will not have a negative influence on
firms‘ competitive advantage. This study, therefore, hypothesizes
that:
H1: Supply risk management has a positive relationship with
firms’ competitive advantage.
2.6.2. Moderating effect of intellectual capital on the
relationship between supply risk management
and firms’ competitive advantage
The concept of supply chain risk management has become
increasingly important in the contemporary business landscape.
Supply chain disruptions can have severe impacts on firms'
operations, revenue, and reputation. As such, firms have
recognized the need to implement effective supply chain risk
management strategies to mitigate the potential risks. However, the
effectiveness of these strategies in enhancing firms' competitive
advantage is contingent on the moderating effect of intellectual
capital. Intellectual capital refers to the intangible assets that
contribute to a firm's competitive advantage, such as knowledge,
skills, and expertise. The literature has highlighted the crucial role
that intellectual capital plays in enhancing firms' competitiveness
by enabling them to adapt to changes in the business environment
and innovate in response to emerging challenges (Bontis, 2001;
Subramaniam & Youndt, 2005). Therefore, the hypothesis that
intellectual capital positively moderates the relationship between
supply risk management and firms' competitive advantage is both
plausible and worthy of investigation. Previous research has
established a positive relationship between supply chain risk
management and firms' performance (e.g., Wang & Cousins, 2015;
Tang, 2016). However, the effectiveness of these strategies is
contingent on the level of intellectual capital within the firm. Firms
with high levels of intellectual capital are better equipped to
identify and respond to supply chain risks, enabling them to reduce
the negative impact of disruptions on their operations and maintain
their competitive advantage (Srivastava et al., 2008). Conversely,
firms with low levels of intellectual capital are more vulnerable to
supply chain disruptions, which can undermine their
competitiveness and reputation (Tsai et al., 2017). In conclusion,
the study hypothesis that:
H2: intellectual capital positively moderates the relationship
between supply risk management and firms' competitive advantage
is worthy of investigation
Supply Risk
Management Firm‘s Competitive
Advantage
Intellectual Capital Risk Management Capability
H1 [-]
H2 [+] H4 [+] H3 [+]

Copyright © ISRG Publishers. All rights Reserved.
DOI: 10.5281/zenodo.14049858
36
2.6.3. The moderating effect of Risk Management
Capability on the relationship between Supply
Risk management and firms’ competitive
advantage
Effective supply chain risk management (SCRM) is crucial for the
long-term success and competitiveness of firms. Supply chain risks
can have a significant impact on the firm's profitability, reputation,
and customer satisfaction. Many studies have explored the
relationship between SCRM and firm performance, but the
moderating role of risk management capability (RMC) has not
been extensively studied. In this argument, we propose that RMC
positively moderates the relationship between supply risk
management (SRM) and firms' competitive advantage. We will
provide a brief overview of the literature on SCRM, RMC, and
competitive advantage, followed by our argument and evidence
supporting the proposed hypothesis. Supply chain risks can
originate from various sources, including natural disasters,
geopolitical instability, supplier bankruptcy, and technological
disruption. Effective SCRM involves identifying, assessing, and
managing these risks to minimize their impact on the firm's
operations and performance. Many studies have shown a positive
relationship between SCRM and firm performance (e.g., Wu et al.,
2017; Cao and Qin, 2018; Yu et al., 2020). However, these studies
have not considered the moderating role of RMC.
RMC refers to the firm's ability to effectively manage risks by
developing risk management processes, structures, and culture
(Kazancoglu and Tanyas, 2018). RMC can enhance the firm's
resilience to supply chain risks and improve its overall
performance. Several studies have highlighted the importance of
RMC in SCRM (e.g., Yoon and Hong, 2017; Kazancoglu and
Tanyas, 2018; Singhal et al., 2020). Competitive advantage refers
to the firm's ability to outperform its competitors by providing
superior value to customers or reducing costs (Porter, 1985). Many
studies have shown that effective SCRM can enhance firms'
competitive advantage (e.g., Wu et al., 2017; Cao and Qin, 2018;
Yu et al., 2020). However, the moderating role of RMC in this
relationship has not been explored. Based on the arguments raised,
this study proposes that
H3: Risk Management Capability positively moderates the
relationship between Supply Risk Management and firms'
competitive advantage.
2.6.4. Moderating effects of Intellectual capital and
risk management capability
Intellectual capital and risk management capability play crucial
roles in moderating the relationship between supply risk
management and firms' competitive advantage. The following
paragraphs explore the relationship in more detail with supporting
citations.
Intellectual capital refers to the knowledge, skills, and expertise
that enable a firm to innovate and adapt to changes in the business
environment. Research has shown that intellectual capital
positively moderates the relationship between supply chain risk
management and firms' competitive advantage. For example, Tsai
et al. (2017) found that intellectual capital plays a critical role in
mitigating the negative impact of supply chain risk on firms'
performance. Firms with high levels of intellectual capital are
better able to identify and respond to supply chain risks, enabling
them to maintain their competitive advantage. Similarly, risk
management capability is also an essential moderating factor in the
relationship between supply risk management and firms'
competitive advantage. Firms with high levels of risk management
capability are better equipped to identify and manage supply chain
risks, enabling them to maintain their competitive advantage. For
example, Wang and Cousins (2015) found that firms with strong
risk management capabilities were better able to mitigate the
negative impact of supply chain disruptions on their operational
performance.
Furthermore, the combination of intellectual capital and risk
management capability can significantly enhance firms' ability to
manage supply chain risks effectively and maintain their
competitive advantage. Srivastava et al. (2008) found that a
knowledge-based risk management framework can help firms to
manage supply chain risks more effectively, thereby enhancing
their competitive advantage. Such frameworks leverage the firm's
intellectual capital to identify and respond to supply chain risks,
while also enhancing the firm's risk management capability. In
conclusion, intellectual capital and risk management capability
play essential roles in moderating the relationship between supply
risk management and firms' competitive advantage. Firms with
high levels of intellectual capital and risk management capability
are better able to manage supply chain risks effectively, enabling
them to maintain their competitive advantage. As such, firms
should invest in developing their intellectual capital and risk
management capabilities to enhance their ability to manage supply
chain risks effectively and maintain their competitive advantage.
Based on the arguments raised, this study proposes that:
H4: Intellectual capital and risk management capability positively
moderate the relationship between supply risk management and
firms’ competitive advantage.
2.7. Resource-Based View Theory
Resource-based theory (RBT) is a widely used theoretical
framework that explains how firms can achieve a sustained
competitive advantage through their resources and capabilities
(Barney, 1991; Wernerfelt, 1984). In the context of supply chain
management, resource-based theory suggests that firms can use
their unique resources and capabilities to manage supply chain
risks and gain a competitive advantage. This paper explores how
resource-based theory underpins supply risk management and
firms' competitive advantage. Resource-based theory suggests that
a firm's resources and capabilities are the key drivers of its
competitive advantage (Barney, 1991). Resources refer to the
assets, knowledge, and capabilities of the firm, while capabilities
refer to the firm's ability to use its resources effectively to achieve
its goals. In the context of supply chain management, a firm's
resources and capabilities are critical in managing supply chain
risks.
According to resource-based theory, firms that have unique
resources and capabilities are better equipped to manage supply
chain risks than their competitors. For example, a firm with a
highly skilled and experienced supply chain team may be better
equipped to identify and mitigate supply chain risks than a firm
with a less skilled team (Gibson et al., 2005). Similarly, a firm with
strong relationships with its suppliers may be better able to manage
supply chain risks than a firm with weaker relationships (Cousins
et al., 2008).
Moreover, resource-based theory suggests that firms can create
value for their customers and stakeholders by using their unique
resources and capabilities (Barney, 1991). In the context of supply
chain management, firms that are better able to manage supply

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DOI: 10.5281/zenodo.14049858
37
chain risks can provide more reliable and consistent delivery of
products to their customers. This can lead to increased customer
loyalty and improved reputation, which can in turn lead to a
sustained competitive advantage (Mentzer et al., 2001). The
resource-based theory also suggests that the sustained competitive
advantage of a firm is difficult to imitate or replicate by its
competitors (Barney, 1991). In the context of supply chain
management, firms that have unique resources and capabilities for
managing supply chain risks are better able to differentiate
themselves from their competitors (Gibson et al., 2005). For
example, a firm with a strong supply chain risk management
strategy may be able to provide its customers with a level of
assurance that its competitors cannot match.
The resource-based theory provides a theoretical foundation for
understanding how firms can achieve a sustained competitive
advantage in supply chain management by using their unique
resources and capabilities. Through their resources and
capabilities, firms can manage supply chain risks more effectively,
create value for their customers and stakeholders, and differentiate
themselves from their competitors. Firms that use resource-based
theory to underpin their supply chain risk management strategies
are better positioned to achieve a sustained competitive advantage.
Resource-based theory underpins supply risk management and
firms' competitive advantage by suggesting that a firm's resources
and capabilities can lead to a sustained competitive advantage.
Resources refer to the assets, knowledge, and capabilities of the
firm, while capabilities refer to the firm's ability to use its resources
effectively to achieve its goals.
In the context of supply risk management, the theory suggests that
firms that have unique resources and capabilities are better able to
manage supply chain risks than their competitors. For example, a
firm with a highly skilled and experienced supply chain team may
be better equipped to identify and mitigate supply chain risks than
a firm with a less skilled team. In this way, the firm's resources and
capabilities can lead to a competitive advantage in supply chain
risk management. Furthermore, resource-based theory suggests that
firms that have unique resources and capabilities can use them to
create value for their customers and stakeholders. This can lead to
a sustained competitive advantage because it is difficult for
competitors to imitate or replicate these unique resources and
capabilities. According to the RBV theory, an organization is a
collection of resources that may be leveraged to gain a competitive
advantage and deliver strong organizational performance in the
short or long term (Barney, 1991; Penrose, 1959). The RBV
framework is frequently utilized to describe variations in business
marketing tactics and level of competitiveness (Kozlenkova et al.,
2014; Morgan, 2012). The company's RBV offers a theoretical
framework for evaluating internal organizations' capacity to create
competitive advantage (Barney, 1991; Grant, 1991). It was also
conveyed by Penrose (1959) in his research which stated that the
RBV considers that a company is a collection of resources. The
core tenet of RBV is that a company's ability to access, control, and
manage corporate resources determines how competitive it is.
2.8. Dynamic Capability Theory
The dynamic capabilities framework is an approach to strategic
management that seeks to explain how firms acquire and maintain
competitive advantages under conditions of change and uncertainty
in their competitive environments. It is particularly focused on
accounting for why some firms rather than others are able to adapt
or reconfigure resources and operational capabilities to respond to
(and even spark) disruptive, innovative change. Hence, Teece
(2014) defines dynamic capabilities as ―higher-level activities that
can enable an enterprise to direct its ordinary activities towards
high-demand uses and to manage, or ‗orchestrate,‘ the firm‘s
resources to address and shape rapidly changing business
environments.‖ The problem of conceptualizing and explaining
change over time is implicit in several aspects of the dynamic
capabilities framework, from (1) why competitive environments
change in ways that are characterized by rapid innovation and
uncertainty to (2) why some firms develop the ability over time to
more effectively reconfigure resources and capabilities to address
such change to (3) the problem of identifying the ―micro-
foundations‖ by which managers and organizations ―sense‖ the
opportunities inherent in change and ―seize‖ and ―transform‖
resources to intentionally capitalize on it (Teece 2007). In fact, the
intellectual origins of the contemporary dynamic capabilities
framework can be traced to the efforts of strategy researchers to
grapple with the fact that existing theories of competitive
advantage, including conventional resource-based theory (Barney
1991) in addition to those based on industrial organization (Porter
1980) and game theory (Brandenberger and Nalebuff 1995), could
not account for the survival and competitiveness of some firms
over others during periods of rapid and disruptive change.
While the resource-based view (RBV) accounted for the
sustainable competitive advantage of particular firms in relatively
stable markets, it faced the problem that rapid changes in
technologies, markets, and business models could undermine the
value of a firm‘s existing capabilities and require the creation of
new ones. Teece, Pisano, and Shuen (1997) thus explain that ―[t]he
development of this framework flows from a recognition by the
authors that strategic theory is replete with analyses of firm-level
strategies for sustaining and safeguarding extant competitive
advantage, but has performed less well with respect to assisting in
the understanding of how and why certain firms build competitive
advantage in regimes of rapid change.‖ Eisenhardt and Martin
(2000) echoed that the dynamic capabilities framework is designed
to explain ―why certain firms have competitive advantage in
situations of rapid and unpredictable change.‖ In particular,
dynamic capabilities focuses on the challenge managers face in
leading organizations through periods of deep, fundamental change
characterized by Knightian uncertainty (Teece, Peteraf et al. 2016).
3.1. Methodology
3.2. Research Design
Research design refers to the systematic structure and plan that a
researcher employs to conduct a study and address specific
research questions. It encompasses the overall strategy outlining
how the study will be executed, including the methods used, the
process of data compilation, the pathway to reaching logical
conclusions, and an acknowledgment of any inherent limitations in
the research. In essence, it serves as a blueprint for the entire
research process.Wills (2021) emphasizes that a research design is
a carefully organized framework that guides the researcher in
conducting the study. It outlines the steps involved, the methods of
data collection, the analytical procedures, and considerations for
mitigating potential biases or limitations. The goal is to ensure that
the study is conducted in a systematic and rigorous manner,
leading to credible and valid results. In this study, the research
design is explanatory, employing a single cross-sectional survey. A
survey is a methodical approach for collecting information from a
sample to construct quantitative descriptors of the attributes of the

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DOI: 10.5281/zenodo.14049858
38
larger population to which the sample belongs (Avedian, 2014).
The single cross-sectional design involves collecting information at
a single point in time (Churchill and Iacobucci, 2015), offering a
snapshot of the group's status at that specific moment. Typically,
cross-sectional designs are either explanatory or descriptive,
aiming to describe behavior or attitudes (Mathers et al., 2017).
A single cross-sectional survey involves collecting data at one
point in time from a sample representing a larger population,
aligning with the methodology of this study. The ultimate goal of
research is to gather and analyze data for desired outcomes, and the
choice of technique should align with the research problem and
purpose (Nyberg, 2011). Creswell (2014) emphasizes the
importance of researchers questioning their knowledge claims,
theoretical perspectives, and methodological strategies to ensure
awareness of potential biases and their impact on the chosen
approach and data collection tools (Vogt et al., 2012). Research
approaches can broadly be categorized as quantitative, qualitative,
or mixed methods. This study adopts a quantitative method
approach, as the researcher tests hypotheses using inferential
statistics. Quantitative research is deductive, where the researcher
proposes a theory exemplified in a specific hypothesis, subjected to
testing, and conclusions are drawn based on observations and data
analysis (Rovai et al., 2014). This approach involves
mathematically based methods focusing on surveys to gather
numerical data and generalize findings across different groups of
people. A quantitative approach is well-suited for examining
relationships between variables with a high degree of precision and
generalizability (Rovai et al., 2014). In the context of this study,
quantitative method will allow for statistical analysis, enabling the
examination of the magnitude and significance of the relationships
between supply risk management, intellectual capital, risk
management capability, and competitive advantage across a larger
sample. Quantitative research facilitates the use of objective
measures and standardized instruments to assess constructs such as
supply risk management, intellectual capital, and competitive
advantage (Creswell, 2014). This enhances the reliability and
validity of the study, ensuring consistent and comparable data
across participants (Rovai et al., 2014).
The study aims to investigate the moderating effects of intellectual
capital and risk management capability. Quantitative methods,
particularly regression analysis and moderation analysis, provide a
robust framework for statistically modeling and analyzing these
complex relationships (Hayes, 2018). This approach allows for a
nuanced understanding of how these moderating variables
influence the relationships between supply risk management and
competitive advantage. Quantitative research is efficient for large-
scale data collection (Creswell, 2014). Given the multidimensional
nature of the study's variables and the desire to capture a diverse
range of perspectives, a quantitative approach allows for the
collection of data from a sizable sample of firms, contributing to
the generalizability of the findings. The study focuses on business-
related outcomes such as competitive advantage. Quantitative
methods are well-suited for analyzing quantifiable business metrics
and outcomes, providing a clear and measurable understanding of
the impact of supply risk management and its interaction with
intellectual capital and risk management capability on firm
performance (Rovai et al., 2014). The adoption of a quantitative
research approach aligns with the objectives of precision,
generalizability, and statistical modeling required to explore the
relationships and moderating effects in the study. This approach
allows for a rigorous examination of the research questions and
contributes to the advancement of knowledge in the field.
4.1. Results and Discussions
4.2. Exploratory factor analysis (EFA)
To establish the uni-dimensionality of the measurement items,
exploratory factor analysis was conducted in SPSS. Beyond
helping to establish unidimensionality, EFA is also a good
forerunner to the conduct of the more rigorous confirmatory factor
analysis (CFA). The principal components extraction method was
chosen, and the rotation method was varimax rotation. According
to Kline, (2011), the principal component analysis seeks to
examine the total variance and estimate factors as simple linear
combinations of the measured indicators. This technique is
generally considered less complex and it's also psychometrically
sound. The varimax rotation was selected because the aim was to
assess the unidimensionality of the measurement items, and so an
orthogonal rotation method was preferred to an oblique method.
In providing a distinction between the two methods, Field, (2018)
noted that whiles the orthogonal methods (e.g. Varimax,
quatermax, equamax) rotate factors while keeping the independent,
Oblique rotation methods (Direct oblinim and Promax) allow
factors to correlate. The varimax rotation tries to load a smaller
number of variables highly onto each factor, resulting in more
interpretable clusters of factors (Field, 2018). The combination of
principal component extraction and Varimax rotation has been
used in several studies (see e.g. Harris and Ogbonna, 2001; Kuvaas
and Dysvik, 2010; Michaelis et al., 2015; Rahimnia and Sharifirad,
2015). The EFA results shows that all the sub dimensions of the
multi-dimensional constructs loaded together. Hence, supply risk
management (risk identification, risk assessment and risk
mitigation), risk management capability (robustness and resilience
capability), intellectual capital (human capital, structural capital
and relational capital) and firm competitive advantage were put
together showing four. Overall, items from 9 different constructs
were added to the model, made up of 4 general constructs. The
initial results showed that the sub dimensions of supply risk
management, risk management capability and intellectual capital
were loading together, whilest that of firm competitive advantage
also loaded as a separate construct. Due to these initial results, and
because prior knowledge of the items forming each construct was
known beforehand and theoretically validated in other studies,
SPSS was instructed to extract 4 components from the data. The
extraction method was principal component analysis using the
varimax rotation. The results are presented in Table 5.13 below.
The Kaiser-Meyer-Olin (KMO) measure of sampling adequacy
statistic was 0.964. which is above the minimum threshold of 0.6
(Tabachnik & Fidell, 2013).
Sampling adequacy is the ratio of the sum of correlations to the
sum of squared correlations plus the sum of squared partial
correlations. The result around 0.964 indicates that the data is
factorable and good for factor analysis. Bartlett‘s test of sphericity
is significant (Approx. Chi-square = 7435.689, df = 666) at 1%.
Bartlett‘s test of sphericity tests the null hypothesis that
correlations among the items are zero. The significant test indicates
that this null hypothesis is rejected and that there exist correlations
among the items. Items that did not meet a threshold of 0.4 were
taken out and those that loaded on more than one factor were also
taken out. After this, as depicted in Table 5.13, the results of the
EFA indicate that all items loaded sufficiently on their respective
scales and the loading were all above 0.7.

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DOI: 10.5281/zenodo.14049858
39
Table 4.1: Results of exploratory factor analysis
Rotated Component Matrix
FCA
IC
RMC
SRM
FCA1
0.817435
FCA2
0.853112
FCA3
0.8475
FCA4
0.850116
FCA5
0.722057
HC1
0.705503
HC3
0.753447
HC4
0.829567
HC5
0.797611
RC1
0.816982
RC2
0.818221
RC3
0.753953
RC6
0.767238
SC1
0.80495
SC2
0.735136
SC3
0.733435
SC4
0.762409
SC5
0.772528
REC1
0.85628
REC2
0.848563
REC3
0.838558
ROC1
0.760545
ROC2
0.821988
ROC3
0.836292
ROC4
0.797077
RA2
0.715217
RA3
0.739802
RI3
0.771986
RI5
0.746998
RI6
0.73024
RI7
0.771592
RM1
0.768166
RM2
0.762274
RM3
0.805467
RM4
0.784336
Extraction Method: Principal Component Analysis. Rotation
Method: Varimax with Kaiser Normalization.
Kaiser-Meyer-Olkin Measure of Sampling Adequacy = .964,
Bartlett‘s test of spericity (Approx. Chi-Square = 7435.689, df =
666, sig = .000)
4.3. Confirmatory factor analysis (CFA)
Confirmatory factor analysis was used to validate the measurement
scales used in the study. The CFA was applied on items that have
been retained from the exploratory factor analysis. Amos 23 was
employed to conduct the CFA. Following the EFA, 4 contructs
were tested, namely supply risk management, risk management
capability, intellectual capability and firm competitive advantage.
Some items (which had low loading) were removed from their
respective scales during the CFA to ensure model fit. Before
removing the items, the scales were checked to ensure that the
domain of the construct was still captured by the remaining items.
Following the removed items, the CFA model showed good fit
Chi-square (χ2) = 1151.839, degrees of freedom (df) = 550, χ2/df =
2.09, RMSEA = 0.062, IFI = 0.917, CFI = 0.916, SRMR = 0.0431.
Items in the model have high (greater than .70) positive loading on
the theoretical construct.
The loadings are all statistically significant at 1%. The average
variance extracted (AVE) for each construct are higher than the
recommended 0.5 threshold (Hair et al, 2014), and this indicates
that the unique variance of each scale is more than 50%. The AVE
values above 0.5 also indicate that the scales have sufficient
convergent validity. Composite reliability (CR) scores and
Cronbach‘s alpha (CA) values for the scales are above 0.7,
indicating strong internal consistency among the items in the
various scales.
To establish discriminant validity, Hetero Trait Mono Trait
(HTMT) was assessed. The results indicate that the HTMT values
are below 0.9 indicating sufficient discriminant validity.
Table 4.2: Results of confirmatory factor analysis
Construct/Measures (Composite
reliability; Average variance
extracted; Cronbach alpha)
Loadings
T-value
Firm competitive advantage
(CA = 0.877, AVE = 0.672 , CR
= 0.911)
FCA1
0.817
Fixed
FCA2
0.853
14.306
FCA3
0.848
14.165
FCA4
0.850
14.353
FCA5
0.722
10.95
Supply Risk Management (CA
= 0.919 , AVE = 0.578 , CR =
0.932)
RI3
0.772
Fixed
RA2
0.715
12.182
RA3
0.740
11.795
RI5
0.747
12.658

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DOI: 10.5281/zenodo.14049858
40
RI6
0.730
11.152
RI7
0.772
11.75
RM1
0.768
12.482
RM2
0.762
12.614
RM3
0.805
13.495
RM4
0.784
13.037
Risk Management Capability
(CA = 0.921 , AVE = 0.678 ,
CR = 0.936)
ROC1
0.761
Fixed
ROC2
0.822
12.713
ROC3
0.836
12.65
ROC4
0.797
12.239
REC1
0.856
13.118
REC2
0.849
13.091
REC3
0.839
12.893
Intellectual Capital (CA = 0.944
, AVE = 0.599 , CR = 0.951)
HC1
0.706
Fixed
HC3
0.753
11.737
HC4
0.830
13.016
HC5
0.798
12.452
SC1
0.805
12.271
SC2
0.735
11.206
SC3
0.733
11.102
SC4
0.762
11.586
SC5
0.773
11.966
RC1
0.817
12.58
RC2
0.818
12.551
RC3
0.754
11.494
RC6
0.767
11.696
Model fit Indices
Chi-square = 1151.839, degrees of freedom (df) = 550, Chi-
square/df = 2.09, RMSEA = 0.062, IFI = 0.917, CFI = 0.916,
SRMR = 0.0431
Notes:
CA = Cronbach‘s alpha, CR = Composite reliability, AVE =
Average Variance Extracted.
Figure 4.1: CFA results
5.0. Examination of construct validity
Validating the measurement constructs is an important and
necessary part of the research process (Schwab, 1980). According
to Hair et al, (2014) construct validity refers to the extent to which
the indicators are a reflection of the theoretical latent constructs
they are expected to measure. Thus, construct validity is concerned
with the extent to which the construct‘s measures (indicators) are
sufficient measures of the intended concept. That is the extent to
which the measured constructs are free from measurement errors
(O‘Leary-kelly & Vokurka, 1998). Four aspects of construct
validity – content, convergent, discriminant, and nomological are
assessed in this study, and the CFA process together with other
techniques have been used to demonstrate these forms of validity.
5.1.1. Content Validity
Generally, content validity is concerned with the extent to which
the measurement indicators in an instrument reflect the content
universe for which the instrument is generated (Mackenzie et al.,
2011). It is considered by many as the most important test of
validity because its not possible to specify measurement theory if
one does not understand the content of the items (Hair et al., 2014).
Most often, content validity is established using the opinion of
experts, and not statistical analysis (Kline, 2011). In this study, I
established content validity in three ways. First, the measurement
items were largely adapted from the literature following a critical
review (Sousa & Bradley, 2006). Second, a team of peer
researchers was invited to scrutinize and provide their views of the
suitability of the items to the study‘s context. Following the
guidelines of (Mackenzie et al., 2011) the peer researchers were
tasked to undertake two specific analyses – (1) to assess if an
individual item is representative of an aspect of the construct‘s

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DOI: 10.5281/zenodo.14049858
41
domain and (2) if the items altogether capture the entire domain of
the construct. Third, a pilot study was also conducted and the
feedback was used to improve the suitability of the items to the
study context. Using these procedures, the researcher concluded
that the items have content validity.
5.1.2. Convergent Validity
Convergent validity examines the degree of correlation between
measures of the same construct ( Hair et al., 2014). Researchers
demonstrate convergent validity when the indicators of a construct
have a high proportion of shared variance. In the literature,
convergent validity has been demonstrated often using positive and
significant factor loadings (Morgan et al., 2004) Average variance
extracted (AVE) values above 0.5 (O‘Leary-kelly & Vokurka,
1998; Son et al., 2016), and Composite reliability (Hong et al.,
2020). In this study, all the retained items loaded positively and
significantly at 1% on their respective constructs, and factor
loadings were above 0.7. Again, all AVE values were above the
threshold of 0.5. Further, the composite reliability scores were all
above 0.7. Based on these results, there is sufficient demonstration
of convergent validity among the study‘s constructs.
5.1.3. Discriminant Validity
Discriminant validity is the degree to which two conceptually
similar concepts are distinct (Hair et al., 2014). Thus, it is a
measure of the extent to which the underlying factor of one
construct differs from the others. In this study, I demonstrate
discriminant validity in two ways. First, evidence from the
exploratory factor analysis indicates that all items loaded
respectively on their constructs, and cross-loadings were minimal
(SPSS was set to ignore all loadings below 0.4). Second, the
Hetero Trait Mono Trait (HTMT) ratio (Henseler et al., 2015) was
used. HTMT is a criterion to verify that a construct exhibits
stronger relationships with its own indicators than with other
constructs. It uses the heterotrait-monotrait ratio of correlations
(HTMT) to calculate the discriminant validity index. An HTMT
value of less than 0.9 establishes discriminant validity. As depicted
in table 5.15, the hightes value is 0.836, meaning discriminant
validity is established.
Table 4.3: Hetero Trait Mono Trait (HTMT) – Matrix
FCA
IC
RMC
SRM
FCA
IC
0.806
RMC
0.799
0.837
SRM
0.794
0.824
0.836
5.1.4. Nomological Validity
When a construct demonstrates acceptable convergent and
discriminant validities, the test of the structural model then
constitutes a confirmatory assessment of nomological validity
(Anderson & Gerbing, 1988). Nomological validity in this study is
indicated by the good fit of the OLS (process) regression models
(Akter et al., 2016; Kitsis & Chen, 2019). According to (Hair et al.,
2014), examining the correlations among constructs in the
measurement theory can be used to assess nomological validity.
This study uses both approaches in establishing nomological
validity for the study. First, Table 5.20 above shows the inter-
construct correlation between the study‘s main variables is
statistically significant. Second, the model fit results for all the
estimated models are satisfactory.
5.1.5. Common method bias (CMB)
Common method bias has been acknowledged as a potential
problem in all behavioral studies (Podsakoff et al., 2003). CMB is
a major source of measurement error (Podsakoff et al., 2012) and
studies that use self-reported measures are prone to common
method bias (Craighead et al., 2011). Because this study used self-
reported measures and cross-sectional data, several steps were
taken to deal with common method bias. Following
recommendations in (Podsakoff et al., 2012), procedural and
statistical remedies were taken to deal with the potential of CMB.
It is worth noting that one of the key procedural remedies for
dealing with CMB is using different respondents/sources for the
criterion and predictor variables. This method has been used in
some studies (see e.g. Carmeli et al., 2011; Wang et al., 2015).
However, that cannot be applied to this study, as it is conducted to
capture the beliefs and judgment of individuals (Podsakoff et al.,
2012). In this study, the procedural steps taken to deal with CMB
are explained as follows. First, all questionnaire items were
thoroughly reviewed to deal with ambiguous statements or
questions, that can cause respondents to be uncertain about how to
respond to the content, and may lead to idiosyncratic
interpretations. Second, different scale formats (anchor labels)
were used in the questionnaire item to eliminate common scale
properties that may cause ―probability that cognitions generated in
answering one question will be retrieved to answer subsequent
questions.‖ (Podsakoff et al., 2012). Third, respondents were
assured of the confidentiality of their responses the promised
anonymity helped to attenuate the possibility of evaluation
apprehension which could cause respondents to give responses that
they consider as socially desirable.
Several statistical remedies for dealing with CMB have been
reported in the wellbeing literature. These include the use of one
factor CFA measurement model (Ogbonnaya & Messersmith,
2018) and Harman‘s one-factor test (Kuvaas & Dysvik, 2010;
Zhang et al., 2013). In this study, I used both Harman‘s one-factor
test and the latent factor CFA model (Cooke et al., 2016; Jyoti &
Rani, 2019) to statistically test for common method bias.
Harman‘s one-factor test was conducted using exploratory factor
analysis. All the measurement items for the various constructs were
entered in an EFA model. The principal component extraction
method was selected and the solution was unrotated. The results
indicate that the first factor accounted for only 23.65% of the
variance, which is below the maximum threshold of 50%. Also, the
solution delivered 4 factors, which indicates that multiple factors
exist in the data and common method variance is not present in the
data.
The latent factor model was executed following the CFA approach
developed by Cote & Buckley, (1987). Harman‘s one-factor
technique has been labelled ―insensitive‖ (Podsakoff et al., 2003)
and the latent factor approach is more robust. In this approach, I
tested three competing models. In model 1, I estimated a trait-only
model where all the indicators (of the various constructs) were
loaded on a single latent factor. In model 2, a method only model
where the items were loaded on their respective latent constructs.
In the third model, a combination of the method and trait models is
implemented. The results are presented in Table 5.17.

Copyright © ISRG Publishers. All rights Reserved.
DOI: 10.5281/zenodo.14049858
42
Table 4 .4: Results of common method variance test
Measurement model
χ2
DF
χ2/DF
RMSEA
SRMR
IFI
CFI
Measurement set 1 (method-only CMB)
1754.54
356
4.928
0.187
0.156
0.634
0.633
Measurement set 2 (trait-only CMB)
1151.84
550
2.09
0.062
0.043
0.917
0.916
Measurement set 3 (method and trait CMB)
1084.13
549
1.975
0.059
0.0766
0.926
0.926
From the results, the trait-only model (where the items are loaded onto their respective constructs) provides better fit results in comparison with
the method-only model and the combined method and trait model. Again, the method-only model provides a very poor fit of the data, which
indicates that the items do not represent a single factor. These results suggest that common method bias is not an issue in this study.
Table 4.5: Summary of results.
Hypothesis
Path
Β
t-value
Remarks
H1
SRM FCA
.232
3.369
Supported
H2
SRM x IC FCA
-.081
-2.515
Not supported
H3
SRM x RMC FCA
.215
2.641
Supported
H4
SRM x (IC x RMC) FCA
.038
1.303
Not supported
SRM = Supply Risk Management, FCA = Firm Competitive Advantage, IC = Intellectual Capital, RMC = Risk Management Capability.
From the hypothesis tests, the relationship between t supply risk
management and firm competitive advantage was statistically
significant leading to the acceptance of hypothesis one. The tests
have also revealed that intellectual capital moderates the
relationship between supply risk management and firm competitive
advantage negatively whiles risk management culture moderates
the relationship between supply risk management and firm
competitive advantage positively. These provided support for
hypotheses three and a rejection of hypothesis two.
The findings also reveal that intellectual capital and risk
management capability together does not moderate the relationship
between supply risk management and firm competitive advantage,
hence hypothesis four is rejected.
6.0. DISCUSSION OF RESULTS
AND CONCLUSION
6.1. Discussion of the Results
The study sought to achieve three objectives. First, the study
sought to examine the relationship between supply risk
management and firm competitive advantage. Secondly, the study
sought to examine the moderating role of intellectual capital in the
relationship between supply risk management and firm competitive
advantage. Lastly, the study sought to examine the moderating role
of risk management capability in the relationship between supply
risk management and firm competitive advantage. In achieving
these objectives, the study made four hypothesis, first supply risk
management has a positive influence on firm competitive
advantage, secondly, intellectual capital positively moderates the
relationship between supply risk management and firm competitive
advantage, third, risk management capability positively moderates
the relationship between supply risk management and firm
competitive advantage and lastly, both intellectual capital and risk
management culture jointly positively moderates the relationship
between supply risk management and firm competitive advantage.
The findings of the study are discussed below.
The Relationship Between Supply Risk Management and Firm
Competitive Advantage
In the pursuit of the primary objective of this study, which was to
delve into the intricate relationship between supply risk
management (SRM) and firm competitive advantage, a hypothesis
was formulated, suggesting that SRM positively influences firm
competitive advantage. Through meticulous study design and
thorough data analysis, the results unequivocally validated this
hypothesis, providing compelling evidence that effective supply
risk management indeed contributes to the enhancement of firm
competitive advantage.
These findings shed light on the critical role of supply risk
management in bolstering competitive positioning. Specifically,
the results demonstrate that as firms adeptly manage supply risk,
they are better equipped to leverage opportunities and navigate
challenges in the competitive landscape (Nguyen et al., 2024). The
ability to identify, assess, and mitigate supply risk emerges as a
pivotal factor in gaining and sustaining a competitive edge in the
marketplace. This underscores the strategic significance of
integrating robust supply risk management practices into
organizational frameworks.
Moreover, the resonance of these findings within the framework of
the Dynamic Capabilities Theory adds further depth to their
significance (Teece, 2007). According to this theoretical
perspective, organizations must cultivate dynamic capabilities —
encompassing adaptability, innovation, and effective
responsiveness to evolving environments — to thrive amidst
market turbulence. Within the realm of SRM, these dynamic
capabilities manifest in the organization's proactive approach to
identifying, evaluating, and mitigating supply chain risks. By
fostering resilience and strategic agility, organizations can
effectively navigate uncertainties and capitalize on emerging
opportunities, thus fortifying their competitive standing in dynamic
market conditions.
Overall, these results underscore the strategic imperative for
organizations to prioritize supply risk management as a means to

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DOI: 10.5281/zenodo.14049858
43
bolster competitive advantage. They highlight the need for
continuous adaptation and innovation in response to evolving
market dynamics, emphasizing the role of dynamic capabilities in
driving sustained success in today's volatile business landscape
(Shou et al., 2018). By embracing effective SRM practices and
cultivating dynamic capabilities, organizations can position
themselves for long-term competitiveness and resilience in the face
of uncertainty.
The Moderating Role of Intellectual Capital
The second hypothesis posited a positive moderating role of
intellectual capital in the the relationship between supply risk
management and firm competitive advantage. The results hoever
showed a negative moderating role of intellectual capital in the
relationship between supply risk management and firm competitive
advantage. The negative moderation of the relationship between
supply risk management (SRM) and firm competitive advantage by
intellectual capital suggests that the presence of high levels of
intellectual capital within an organization diminishes the positive
impact of SRM practices on competitive advantage. This result is
counter intuitive, as it contradicts a number of studies. For
instance, Khan and Ali (2017) found intellectual capital to
positively moderate the relationship between enterprise risk
management and firm performance. Even though the finding is
counter intuitive, it may be drawing our attention to some
empirical nuances. These results could mean that despite
possessing significant intellectual capital, organizations may still
harbor cognitive biases and blind spots that limit their ability to
effectively manage supply chain risks (Luthra and Muhr, 2023).
Intellectual capital may create a false sense of security, leading
organizations to underestimate the severity of potential risks or
overlook emerging threats, ultimately undermining their
competitive advantage. Again, organizations with high levels of
intellectual capital may face challenges in effectively allocating
resources to support SRM initiatives (Borner et al., 2023). While
intellectual capital is valuable, it may compete with other
organizational priorities for resources such as financial
investments, technology upgrades, or talent development, limiting
the organization's ability to fully leverage SRM practices to
enhance competitive advantage.
The Moderating Role of Risk Management Capability
The third hypothesis of the study posited a positive moderating role
of risk management capability on the relationship between supply
risk management and firm competitive advantage. The findings
show that risk management capability positively moderates the
relationship between supply risk management and firm competitive
advantage. This means that as the risk management capability is
higher, supply risk management better influences firm competitive
advantages. This result is significant when viewed through the
lens of contingency theory, which emphasizes the importance of
aligning organizational practices with contextual factors to achieve
optimal outcomes. In this context, risk management capability
serves as a contingent factor that enhances the effectiveness of
SRM practices. These findings align with that of Singh (2020).
The Joint Moderating Role of Intellectual Capital and Risk
Management Capability
The last hypothesis posited a positive moderating joint role of
intellectual capital and risk management capability on the
relationship between supply risk management and firm competitive
management. The results shows that the joint moderating role of
intellectual capital and risk management capability on the
relationship between supply risk management and firm competitive
advantage. The insignificant moderating role of joint intellectual
capital and risk management capability could mean that the
inefficient management of intellectual capital offsets the positive
influence of risk management capability.
6.2. Theoretical Implications
The study sought to achieve three objectives. First, the study
sought to examine the relationship between supply risk
management and firm competitive advantage. Secondly, the study
sought to examine the moderating role of intellectual capital in the
relationship between supply risk management and firm competitive
advantage. Lastly, the study sought to examine the moderating role
of risk management capability in the relationship between supply
risk management and firm competitive advantage. The findings of
the study has a number contributions to literature.
The study makes a distinctive contribution to existing literature by
shifting the focus from general risk management to a more
specialized examination of supply risk management. While many
studies address risk management broadly, this research delves into
the unique challenges and opportunities presented by supply chain
risks. By honing in on supply risk management, the study provides
a nuanced and detailed understanding of how risks within the
supply chain landscape impact competitive advantage. This
specificity allows for a deeper exploration of the intricacies
involved in managing risks within the supply chain, including
supplier disruptions, inventory shortages, and logistics bottlenecks,
among others. By elucidating the mechanisms through which
supply risk influences competitive advantage, the study offers
valuable insights that can inform strategic decision-making and
operational practices in organizations across various industries.
Additionally, the study unveils a counterintuitive finding: the
negative moderation effect of intellectual capital on the
relationship between supply risk management and firm competitive
advantage. This unexpected outcome challenges conventional
wisdom and underscores the complex interplay between
intellectual capital, risk management, and competitive advantage.
By shedding light on this nuanced relationship, the study advances
the discourse within the risk management literature, offering
valuable insights into the role of intellectual capital in shaping
organizational outcomes. The discovery of this negative
moderation effect prompts a re-evaluation of traditional
perspectives on the management of intellectual capital within the
context of supply chain risk. Rather than viewing intellectual
capital solely as a facilitator of competitive advantage, the study
suggests that its impact may be contingent upon various factors,
including its interaction with supply risk management practices.
This nuanced understanding highlights the need for organizations
to carefully consider how they leverage intellectual capital to
enhance their resilience and competitiveness in the face of supply
chain disruptions.
6.3. Practical Implications
The findings of this study carry significant managerial
implications. First, organizations should carefully consider how
they allocate and leverage their intellectual capital resources. While
intellectual capital is valuable for driving innovation and
competitiveness, its indiscriminate application may inadvertently
hinder the effectiveness of supply risk management practices.
Therefore, organizations should adopt a strategic approach to the
allocation of intellectual capital, ensuring that it is directed towards

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DOI: 10.5281/zenodo.14049858
44
areas where it can enhance, rather than detract from, the
effectiveness of risk management efforts.
Also, organizations need to strike a balance between leveraging
intellectual capital to drive innovation and managing supply chain
risks effectively. Rather than viewing intellectual capital and risk
management as separate domains, organizations should integrate
these functions into a cohesive strategy that maximizes the benefits
of intellectual capital while mitigating the potential downsides in
terms of risk exposure. This requires a holistic approach to risk
management that considers the broader organizational context and
aligns intellectual capital investments with risk management
objectives.
Furthermore, organizations should prioritize investments in robust
SRM practices to proactively identify, assess, and mitigate supply
chain risks. This includes implementing risk assessment
methodologies, establishing contingency plans, and fostering
collaboration with suppliers to enhance supply chain visibility and
responsiveness. By investing in SRM practices, organizations can
safeguard their operations against disruptions and strengthen their
competitive position in the marketplace.
Again, organizations should strategically evaluate their sourcing
decisions to minimize supply chain risks and maximize
competitive advantage. This may involve diversifying supplier
portfolios, sourcing from multiple geographic regions, and
adopting dual-sourcing strategies to mitigate the impact of
potential disruptions. By strategically sourcing materials and
components, organizations can enhance supply chain resilience and
maintain a competitive edge in the face of uncertainty.
6.4. Limitations and recommendations for Future
Research
While the findings of this study offer valuable insights into the
relationship between supply risk management (SRM) and
competitive advantage, it is essential to acknowledge that, like any
research endeavor, this study has its limitations. Identifying and
acknowledging these limitations is crucial as it not only enhances
the transparency and credibility of the research but also provides a
roadmap for future investigations to further refine our
understanding of this critical issue.
One limitation of this study is its focus on a specific set of
contingency variables, namely intellectual capital and risk
management capability, in conditioning the relationship between
SRM and competitive advantage. While these variables were
deemed relevant based on existing literature and theoretical
frameworks, it is important to recognize that there may be
additional variables that could also influence this relationship. For
instance, organizational culture, supply chain structure,
technological infrastructure, and market dynamics are potential
variables that warrant consideration in future studies
Once more, the findings of this study reveal a counterintuitive
result: the negative moderation effect of intellectual capital on the
relationship between supply risk management (SRM) and firm
competitive advantage. This unexpected outcome challenges
conventional assumptions and underscores the complexity of the
relationship between intellectual capital, risk management, and
organizational performance. As such, future studies are encouraged
to delve deeper into the nuances of intellectual capital within the
context of risk management to better understand the underlying
mechanisms at play. Given the unexpected nature of this result, it
is imperative for future research to explore various dimensions of
intellectual capital that may influence its interaction with SRM and
firm competitive advantage. For example, studies may examine the
specific components of intellectual capital, such as human capital,
structural capital, and relational capital, and their respective
impacts on risk management practices and organizational
outcomes. Understanding how different facets of intellectual
capital contribute to or inhibit effective risk management can
provide valuable insights for organizations seeking to optimize
their strategies.
Moreover, it's important to note that data for this study was
collected through a cross-sectional survey. While this methodology
allows for the examination of relationships at a single point in time,
it inherently limits the ability to infer causality. Therefore, future
studies may benefit from undertaking a longitudinal study to
confirm the causal relationships among the variables under
investigation. By employing a longitudinal approach, researchers
can track changes in intellectual capital, supply risk management
practices, and firm competitive advantage over time. This enables a
more comprehensive analysis of how variations in these factors
influence one another and how they ultimately impact
organizational performance.
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