SUPPLY CHAIN RISK MANAGEMENT FRAMEWORKS AND MODELS: A REVIEW

Stavros Ponis - staponis@central.ntua.gr NATIONAL TECHNICAL UNIVERSITY ATHENSAthanasia Ntalla - nasia.ntalla@gmail.com

NATIONAL TECHNICAL UNIVERSITY ATHENSEpaminondas Koronis - ekoronis@lincoln.ac.uk

UNIVERSITY OF LINCOLN

Category: 15 CONFERENCE GENERAL TRACK >> 15_00 CONFERENCE GENERAL TRACK

Acknowledgements: ACKNOWLEDGEMENT This research has been co-financed by the European Union (European Social Fund – ESF) and Greek national funds

through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Resear

Access to this paper is restricted to registered delegates of the EURAM 2014 (European Academy of Management) Conference.

ISBN No: 978-84-697-0377-9.

Supply chain risk management frameworks and models: A review

ABSTRACT

Supply chain risk management (SCRM) is a relatively new scientific discipline aiming to support

management in its everyday struggle against the inherent uncertainty of supply chain operations

propagated mostly by demand and supply fluctuations, in terms of yields, capacity, costs and lead

times. This paper focuses on a literature review of available SCRM frameworks and models.

Identified frameworks and models are studied and analyzed according to their method of

validation and the normative elements that constitute the conceptual construct, be it a

framework or model. In each case, the constraints and limitations of the modeling effort are

identified resulting in the determination of two major issues, which have to be addressed by

researchers in the future, these being the absence of a holistic approach for SCRM and the

frequent oversight of behavioral aspects, such as the risk behavior of decision makers.

Keywords: Supply chain risk management, Models, Review

1

Supply chain risk management frameworks and models: A review

2

Abstract: Supply chain risk management (SCRM) is a relatively new scientific

discipline aiming to support management in its everyday struggle against the inherent

uncertainty of supply chain operations propagated mostly by demand and supply

fluctuations, in terms of yields, capacity, costs and lead times. This paper focuses on a

literature review of available SCRM frameworks and models. Identified frameworks

and models are studied and analyzed according to their method of validation and the

normative elements that constitute the conceptual construct, be it a framework or

model. In each case, the constraints and limitations of the modeling effort are

identified resulting in the determination of two major issues, which have to be

addressed by researchers in the future, these being the absence of a holistic approach

for SCRM and the frequent oversight of behavioral aspects, such as the risk behavior

of decision makers.

Keywords: Supply chain risk management, Supply chain risk management models,

Supply chain risk management frameworks, Risk management, Supply chain

management

3

1. Introduction

Individual firms are no longer competing one against another, but supply chains are

(Trkman & McCormack, 2009). Supply chains are characterized from their

complexity as they are constituted of many inter-related nodes which are affected

form external and internal sources. A supply chain network cannot be studied as a part

of dyadic relationships among the company and the supplier or the company and the

customer (Wathne and Heide, 2004), as it consists of several networks that together

form a dynamic supply chain network. Risk is an inherent element of a supply chain

structure (Jüttner, 2005). However, many firms inadvertently introduce more risks in

the supply chain networks, striving for efficiency or trying to act independently

(Hauser, 2003; Hallikas, 2004).

Risk has various definitions in academic literature and decision theory. It refers to the

―variation in the distribution of possible outcomes, their likelihoods and their

subjective values‖ or if risk is defined in risk management terms, it is ―the probability

of a given event multiplied by the negative business impact it has‖ (March & Shapira,

1987). Risk can also refer to the consequences of risks; the term ―operational risk‖ is

the consequence of risks becoming events. Zsidisin et al. (2000) define supply chain

risk as the potential occurrence of an inbound supply incident which leads to the

inability to meet customer demand. According to Juttner et al. (2003) ―supply chain

risks refer to the possibility and effect of a mismatch between supply and demand‖.

Ritchie & Brindley (2007) delineate the uncertainty of SCs by including the

consequences of risks. Thus risks are categorized to high and low, measuring how

they affect a firm’s performance. Juttner et al. (2003) suggest that supply chain-

relevant risk sources fall into three categories: environmental risk sources, network-

related risk sources and organizational risk sources. Environmental risk sources arise

from the interactions among supply chain and the environment, resulting from

accidents, socio-political actions or natural hazards. Organizational risk sources arise

from supply chain parties, labor and production or IT-system uncertainties. Network-

related sources are created from the interactions among organizations within the

supply chain. Finch (2004) identified that inter-organizational networking increases

risk exposure.

In today’s crisis prone and unstable business environment, risk management has

become a central issue of concern for both researchers and supply chain practitioners.

Supply chain risk management (SCRM) constitutes the field related to the

identification and elimination of elements of uncertainty in the supply chain (SC)

propagated by demand and/or supply related fluctuations, e.g. demand variability,

unstable supply lead times etc. Generally SCRM focuses on three areas to mitigate

risks: (1) the design of the product supported by the supply chain; (2) the supply chain

itself, including location of inventories, transportation modes, and sourcing

arrangements; (3) the operational control of the supply chain, including

emergency/crisis response (Kleindorfer & Saad, 2009). The field has attracted more

and more researchers and practitioners, as in the modern era crises emerge more often

and supply chains have to face them (Manuj & Mentzer, 2008; Ponis & Koronis,

2012). Many researchers coping to develop SCRM strategies introduced SCRM

frameworks and models. Frameworks and models are constituted of functional

4

elements or constructs (Soni & Kodali, 2011). The research presented in this paper, is

concerned with identifying SCRM frameworks and models, acknowledging the

relations that may exist among them and provide guidelines for future research.

In the next section, the research methodology followed during literature review is

presented. In section 3, the SCRM frameworks, revealed from literature, are

evaluated, their modes of verification are presented and their normative elements are

identified. In section 4, the process imposed in section 3, is repeated, but this time,

studying available SCRM models. In Section 5, the major constraints identified in

frameworks and models are examined, followed by a discussion of research

limitations and prospects for further research.

2. Review Methodology

As supply chain risk management has attracted more and more researchers and

practitioners, the numbers of papers published concerning SCRM issues has increased

dramatically, thus making the process of identifying contributions relevant to our

research, rather complex. In the text that follows and after a short, but necessary,

discussion on definitions of frameworks and models, the methodology applied for our

review is presented in more details and until the end of the section.

2.1 Frameworks and models

Models are representations of ―target‖ systems existing in the ambient world, may

they be systems of words, numbers, pictures, programs, actions, and concrete images

that constitute scientific communications (Gilbert, 1991). A framework can be seen as

a structure that provides elements, ideas and guidance in support of a topic area

(Popper, 1994). The terms of frameworks and models are often confused and

perceived as the same notion. Nevertheless, frameworks and models differ mostly on

their objective orientation. Frameworks are developed to answer ―how to‖ questions

whereas models answer ―what is‖ questions (Yusof & Aspinwall, 2000). Specifically,

a framework represents a system with the activities carried out in it and every

empirical relation among them. It provides the guidelines for the steps that should be

followed to a certain discipline from organizations, constructing each step from the

preceding (Popper, 1994; Struebing & Klaus, 1997). Models represent or explain

mechanisms and operations (Yusof & Aspinwall, 2000). Models may be used to

idealize situations in a given framework through assumptions or simplifications

(Crosby, 1979).

In the research described in this paper, frameworks are considered as conceptual

constructs of a sequence of activities, delineating each element they are constituted of,

to serve their original purpose. Models in supply chain risk management, on the other

hand, are non-prescriptive and the elements composing them enhance only decision

making. They exist to explain a certain mechanism or an operation.

2.2 Methodology procedure

The peer-reviewed articles collected cover a decade, from 2003 to 2013. Actually,

supply chain risk management frameworks and models are not mentioned in

references prior to this period. Although organisations that think they have managed

risk have often overlooked the critical exposures along their supply chains (Juttner et

5

al., 2003) in the last fifteen years, supply chain risk management has drawn

significant research attention, acknowledging both the complexity of its structure

(Braithwaite & Hall, 1999) and the multitude of vulnerabilities supply chain networks

present. Despite this swift of academic research towards supply chain risk

management, the focus towards conceptual structures, such as models and

frameworks for SCRM, is limited and thus can be considered as a new and fertile

ground for exploration.

The research presented in this paper utilized information harnessed from three

established academic databases, i.e. Emerald Online, Science Direct and Scopus. The

search combined the keywords ―supply chain risk management‖ and ―framework‖ and

―supply chain risk management‖ and ―model‖, found anywhere in the article to

identify research efforts relative to supply chain risk management frameworks and

models. This approach was selected as being the best alternative for scrutinizing

literature, since the search with the same keywords in the title or in the keywords or

using the words ―supply chain risk management framework‖ or ―supply chain risk

management model‖ gave a really small sample of articles, while a search using only

the words ―supply chain risk management‖ gave a rather large sample of articles. In

total, the search provided us with two hundred and seventy eight research papers.

After reading all the abstracts and assessing the content for relevance with our study,

32 papers were selected for full assessment, from which 6 frameworks and 9 models

were identified, fitting our definitions and analysis criteria. The hard constraint acting

as the very fine grain filter of literature was that the model or framework should

provide a solid case of its empirical validation in practice.

Next, the research papers were studied and categorized according to the validation

methodology, e.g. qualitative analysis, quantitative analysis or case studies. Finally,

the normative elements constituting the proposed frameworks and models were

identified. The elements that constitute each framework and model are identified and

presented regarding their appearing frequency in references. In the case of models, the

relationships of the elements are examined to understand if they can be matched with

elements of other frameworks. Last, the constraints identified in the selected for

analysis models and frameworks are presented.

The current review of SCRM frameworks and models is posed to unveil the

inconsistencies of existing SCRM frameworks and models. After each model and

framework is analyzed and evaluated based on the aforementioned criteria, an agenda

is created to guide further research.

3. Supply Chain Risk Management Frameworks

3.1 Method of validation

The validation methods identified include case studies, interviews, focus groups and

qualitative and quantitative analysis to empirical data collected from industrial

organizations. In Table 1 the methods used in each framework are presented.

[TABLE 1]

3.2 Normative Framework Elements

6

Each framework is constructed according to certain interrelated normative elements

used as building blocks. Hauser (2003) develops the business-case framework which

consists of seven key elements: (1) critical processes and risk identification, (2)

understanding which risks can cause major disruptions, (3) quantification of risk

impacts on individual and aggregated basis, (4) definition of the organization’s risk

profile, (5) identification of key performance metrics, (6) developing of initiatives and

(7) performance measurement and monitoring to reassure the firm’s balance. The risk-

adjusted framework that Hauser (2003) presents is one of the first efforts to alter the

culture of organizations from managing risks by instinct toward a disciplined

procedure supported by information deriving from risk assessment and identification.

Juttner et al.'s (2003) developed framework consists of four critical aspects: (1)

assessing the risks sources for the supply chain; (2) defining the supply chain risk

concept and adverse consequences; (3) identifying the risk drivers in the supply chain

strategy; and (4) mitigating risks for the supply chain. The framework was developed

when SCRM was still at its infancy, introducing the need for incorporating more

aspects to the framework that are decision making relevant.

Ritchie & Brindley (2007) developed a conceptual framework which was constituted

of a pathway of risk and performance drivers, consequences and responses.

Distinctively, the framework introduces the term ―performance‖ and demonstrates the

inherent linkage among risks and performance.

Kleindorfer & Saad (2009) created a disruption management framework named SAM

(Source-Assess-Monitor) based on four major premises that derived from empirical

results of industrial risk management : (a) specification of the nature of the underlying

hazard that gave rise to the risk, (b) risk quantification through a disciplined risk

assessment process, (c) approach solution according to the given supply chain

environment and (d) integration of policies and actions with on-going risk assessment

and coordination among supply chain partners. Those premises activate three major

activities that constitute the framework: specifying the sources of risks, assessment of

risks and mitigating them. The effective implementation of SAM framework though

has to take into consideration two core factors; the diversity of the environments that

lead to different approaches and the significance of the continuous collaboration

among stakeholders.

Pettit et al. (2010) evaluated an adapted framework from Manuele (2005) which is

constituted of 6 elements: identify hazards, assess risks, analyze controls, determine

controls, implement controls, supervise and review. They identified that the major

weakness of the framework is the inability to define the severity of risk consequences

and their probability of occurrence. By defining those factors, unforeseen disruption

can be handled and supply chain will gain a competitive advantage.

Ghadge et al., (2013) developed a SCRM framework adopting a systematic approach.

The framework is constituted of five major activities: risk taxonomy, risk trending,

risk modeling, strategy planning, and risk mitigation. The holistic approach of Ghadge

et al.'s , (2013) framework captures the overall behavior of risks and provides the

opportunity to consider the influence of multiple risks on a SC. The framework

though lacks the inclusion of behavioral aspects, such as decision makers’ risk

behavior.

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In total, fifteen elements were identified in the frameworks. When different terms are

used for the same element, e.g. ―specification of the nature of the underlying hazard‖

vs. ―risk sources identification‖ or ―supervise‖ vs. ―monitor‖, they are integrated in

the term used more frequently. The identified elements are sorted by frequency of

appearance and presented in Figure 1, showcasing the importance of some of them,

e.g. risk identification and potentially highlighting elements with value that have been

ignored and should be studied and discussed in the future, e.g. policies integration and

initiatives development. Despite that, all constructs though are significant in SCRM.

The organization’s profile is crucial in deciding what strategy will be followed

(Manuj & Mentzer, 2008). Key performance metrics and initiatives provide an

operational control in the procedure and assist the implementation of the decided

solution and the monitoring and measure of the organization’s performance (Hauser,

2003). Last, integration is a key part of SCRM, as policies and actions should be

integrated in the procedure to avoid and handle more effectively future risks and

disruptions (Hauser, 2003; Ghadge et al., 2012).

[FIGURE 1]

4. Supply Chain Risk Management Models

4.1 Method of validation

Similarly in models validation methods such as focus groups, interviews and case

studies are used, as presented in Table 2.

[TABLE 2]

4.2 Normative model elements

Each model is constructed according to certain interrelated normative elements used

as building blocks. Lee (2004) developed the idea of the triple-A supply chain; agile,

adaptable and aligned. Those attributes were found the most critical for mitigation of

risks. Agility urges supply chains to respond quickly to sudden changes in supply or

demand, adaptability adjusts supply chain design to accommodate market changes

and alignment is the establishment of incentives for supply chain partners in order to

improve performance of the entire chain.

The surveys conducted to supply chain managers by Jüttner, (2005) indicated that

vulnerabilities are expected to increase throughout the years. Practitioners’ beliefs

showed three dimensions of SCRM; philosophy, principles and processes. Philosophy

derives from the viewpoints of each company. Common views on risks and joint

responsibility is deemed crucial. Principles are more specific and concern operational

and strategic decision. The processes are the lowest conceptual level and refer to

explicit activities and tasks on SCRM.

Wu et al. (2006) proposed a model for risk managing in supply chains that is based on

risk classification, risk identification, risk calculation and risk analysis using an

analytical hierarchy processing (AHP) method. Craighead et al. (2007), through their

empirical research, developed some risk mitigation capabilities for supply chain

disruptions. They identified that supply chain density, complexity and node critically

are important and directly related to the severity of SC disruptions whereas recovery

8

and warning are important for risk mitigation. Furthermore, the interactions and

coordination of resources can proactively manage a disruption.

Manuj & Mentzer (2008) developed a model in a global manufacturing company

context. According to their model, the team composition and supply chain risk

management strategies have to be identified according to the antecedents, which are

temporal focus, SC flexibility and SC environment. The strategies presented in the

model are postponement, speculation, hedging, control/share/transfer, security, and

avoidance. Also the model suggests that inter-organizational learning is important to

handle SCs’ complexity.

Trkman & McCormack (2009) introduced the elements of assessing and classifying

suppliers to mitigate the risks arising from their actions or possible non-performance.

Foerst et al. (2010) are also studying supplier management capabilities regarding

SCRM. Their research indicated that supplier sustainability risk needs identification,

assessment, quantification of the possible consequences, decision of management

responses and performance measurement. Ghadge et al. (2012) identified seven

crucial elements for SCRM: behavioral perceptions in risk management, sustainability

factors, risk mitigation through collaboration contracts, visibility and traceability, risk

propagation and recovery planning, industry impact and a holistic approach to SCRM.

Johnson et al. (2013) studied the role of social capital in the resilience of a supply

chain network through a case study. They identified that social capital can increase a

flexibility and resilience to recover from the consequences of extreme events. Social

capital has structural, cognitive and relational dimensions. The structural dimension

refers to the network ties, their density and connectivity. The cognitive dimension

concerns the communication and the goals within a firm whereas the relational refers

to values such as trust, expectations or obligations. Through the analysis of the case

study, flexibility, velocity, visibility and collaboration were deemed as significant for

the recovery of a supply chain.

In total, twenty five elements were identified, and five of them were identified as

framework elements too, e.g. ―risk identification‖ and ―performance measurement‖.

Most of the elements appear once in the reviewed papers. Fourteen of the elements

that were exclusively identified in models concern conceptual notions of SCRM such

as ―visibility‖, ―collaboration‖ and ―adaptability‖ and their incorporation to the

strategic constructs of frameworks will lead to more effective processes for risk

mitigation in SCs. The rest of the elements are more specific and refer to strategic

processes, e.g. ―suppliers’ assessment‖. In Table 3 the elements are summarized

according to their appearing frequency, their categorization as conceptual or strategic

and their previous existence or non-existence in the reviewed frameworks.

[TABLE 3]

5. Discussion and further research

The aim of the current paper was to review the existing validated SCRM frameworks

and models and identify how they can be developed for further research. Through the

review of the selected frameworks and models, the key elements that constitute them

were identified and gathered, creating a database of SCRM constructs. Two major

research oversights were acknowledged and deemed as crucial for further

9

investigation in incorporation to frameworks and models; the absence of modeling

behavioral aspects and the lack of a holistic approach of SCRM.

Behavioral aspects such as managers’ decision making, team composition, the

decision of the right strategy are often omitted because of their difficulty to be

captured and modeled. Nevertheless, behavioral aspects directly impact risk

mitigation and should constitute a core element of SCRM frameworks and models

(Ghadge et al., 2012; Soni & Kodali, 2012). Behavioral aspects are also critical for

developing common views on risks and joint responsibility, elements which should be

embodied in organizations in order to avoid misguidance and confusions on the

strategies that will be followed (Manuj & Mentzer, 2008). Openness, transparency

and continuous inter-organizational learning are important to raise joint responsibility

and viewpoints in organizations.

Early research efforts approached SCRM through qualitative research and empirical

studies Later on, algorithm based quantitative techniques (e.g. Towill, 2005),

evolutionary algorithms (Chiong, 2009), game theory (e.g. Xiao and Yang, 2008) and

simulation (Kim et al., 2006) have been used for studying SCRM problems and

provide plausible solutions. All of these studies do not follow a holistic approach on

risks management. SCRM frameworks and models lack a holistic viewpoint on the

field and are focused on specific attributes or cases. It is crucial to acknowledge that

different SC environments need different decisions. Some frameworks and models

(Kleindorfer & Saad, 2005; Wu et al., 2006; Ritchie & Brindley, 2007; Manuj &

Mentzer, 2008; Foerst et al., 2010) were validated on a specific industry context.

Apart from the context, the multidimensional aspects of operational and strategic

processes have to be taken under consideration as a whole and not in isolation. In

many studies, are examined in such a fashion (Craighead et al., 2007; Johnson et al.,

2012) and the inter-relations between them are overlooked. Risks derive from various

factors and supply chains are a complex network of inter-related nodes, thus SCRM

becomes a highly complex and sophisticated field with multiple interactions and

stakeholders, making the need of a holistic approach, an imperative.

More dynamic and cross-disciplinary approaches have to be implemented to

incorporate behavioral aspects and approach SCRM holistically (Colicchia & Strozzi,

2012). The systemic framework, proposed by Ghadge et al., (2013), captures the

complexity of the interconnected nodes of a supply chain, as it studies the influence of

multiple risks on a supply system network and proposes a methodology to depict risk

propagation. Ghadge et al.'s , (2013) framework uses two risk modeling platforms for

quantitative risk assessment. The risk modeling process supports qualitative and

quantitative analysis to make the process more robust. The statistical modeling

approach based on historical data, although it is slightly constrained, it provides a

dynamic and predictive assessment of risk performance variables similar to the

simulation model. Quantitative risk modeling captures the fractured points in supply

chains and provides insights on risk behavior. The current model bridges risk

modeling theory and practice, providing a holistic, systematic and quantitative risk

modeling approach to SCRM. However, it fails to adopt the dynamic nature of

decision making and behavioral attributes in the framework. On the other hand,

frameworks and models that adopt behavioral aspects (Jüttner, 2005; Manuj &

Mentzer, 2008; Trkman & McCormack, 2009; Foerst et al., 2010) fail to approach

more systematically and holistically SCRM. A combination of those two elements

10

should be implemented to create a framework that can deal with risk in contemporary

supply chains.

Furthermore, theoretical frameworks and models need a more systematic approach to

successfully identify risk propagation across the network and yet consider the

influences risks have on supply chain network. Supply chains could be benefited by

developing models that are able to model the risks from complex and dynamic

networks (Stecke and Kumar, 2009). Developing dynamic models first needs the

identification of the vulnerable nodes in the supply chain, a deep understanding of the

risks and then modeling risks with constant addition of quantitative and qualitative

data. Distinctive approaches are needed for a proper evaluation of risk; a solid

theoretical background and then an empirical approach through simulation and

systematic thinking.

Our research is presented with several limitations. The relationships among strategic

and conceptual elements should be identified and validated through empirical data of

case studies to gain a deeper understanding of how strategic constructs can be

optimized by the conceptual ones. Furthermore, benchmarking operations can be used

to identify the degree of importance of each element regarding the organization’s

objectives. Finally, each element identified needs the appropriate validation through

exploratory techniques to be considered as reliable and a pillar for future SCRM

frameworks and models development.

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Table 1: Frameworks' validation method

13

Author(s) Article title Year of

Publication

Validation Method

Hauser L. Risk Adjusted Supply Chain

Management

2003 Case study

Juttner et

al.

Supply chain risk

management: outlining

an agenda for future research

2003 Exploratory interviews

Pettit et al. Ensuring Supply Chain

Resilience: Development of

a conceptual framework

2007 Focus group

Kleindorfer

& Saad

Managing Disruption Risks

in Supply Chains

2009 Qualitative analysis of

empirical data

Ritchie &

Brindley

Supply chain risk

management and

performance: A guiding

framework for future

development

2010 Two case studies

Ghadge et

al.

A systems approach for

modelling supply chain risks

2013 Quantitative analysis &

case study

14

Table 2: Models' verification mode

Author(s) Article title Year of

Publication

Validation Method

Lee The triple A SC 2004 Case study

Uta Juttner Supply chain risk management:

Understanding the business

requirements from a practitioner

perspective

2005 Focus group

Wu et al. A model for inbound supply risk

analysis

2006 In-depth interviews

Craighead

et al.

The Severity of Supply Chain

Disruptions:

Design Characteristics and

Mitigation

2007 Case study,

interviews and focus

group

Manuj &

Mentzer

Global supply chain risk

management strategies

2008 focus group, in-

depth interviews

Trkman &

McCormack

Supply chain risk in turbulent

environments—A conceptual

model for managing supply

chain network risk

2009 Case study

Foerstl et al. Managing supplier sustainability

risks in a dynamically changing

environment—Sustainable

supplier management in the

chemical industry

2010 Case study

Ghadge et

al.

Supply chain risk management:

present and future scope

2012 Cross-validation

with text mining

Johnson et

al.

Exploring the role of social

capital in

facilitating supply chain

resilience

2012 Qualitative analysis

of empirical data

from three SC tiers

15

Table 3: Models' elements

Appearing

frequency

Conceptual Strategic Identified in

framework

Collaboration 33% √

Transparency 22% √

Felxibility 22% √

Sustainability 22% √

Suppliers

classification

22% √

Suppliers

Assessment

22% √

Agility 11% √

Alignement 11% √

Adaptability 11% √

Velocity 11% √

Interaction 11% √

Density

identification

11% √

Complexity

definition

11% √

Temporal

focus

11% √

Critical nodes

identification

11% √

Inter-

organizational

learning

11% √

Sources

coordination

11% √

Joint

responsibility

11% √

16

Common risk

view

11% √

Risk

classification

11% √ √

Risk

quantification

11% √ √

Risk

identification

11% √ √

Risk sources

identification

11% √ √

Performance

measurement

11% √ √

The elements that were identified in the models are presented and categorized

according to their appearing frequency, their classification as conceptual or strategic

and their existence or absence in the previously reviewed frameworks.

17

Figure 1: Normative Elements (listed in decreasing frequency of appearance order)