A Systematic Review On Supply Chain Risk Management Using The Strategy-Structureprocess-Performance Framework

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International Journal of Logistics Research and
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A systematic review on supply chain risk
management: using the strategy-structure-
process-performance framework
Mikihisa Nakano & Antonio K. W. Lau
To cite this article: Mikihisa Nakano & Antonio K. W. Lau (2019): A systematic review on supply
chain risk management: using the strategy-structure-process-performance framework, International
Journal of Logistics Research and Applications, DOI: 10.1080/13675567.2019.1704707
To link to this article: https://doi.org/10.1080/13675567.2019.1704707
Published online: 19 Dec 2019.
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A systematic review on supply chain risk management: using the
strategy-structure-process-performance framework
Mikihisa Nakanoa
and Antonio K. W. Laub
a
Faculty of Business Administration, Kyoto Sangyo University, Kyoto, Japan; b
The School of Management, Kyung Hee
University, Seoul, South Korea
ABSTRACT
The purpose of this study is to conduct a systematic literature review on
the supply chain risk management (SCRM) in the concepts of strategy,
structure, process, and performance (SSPP). Using the EBSCO,
ScienceDirect and SCOPUS databases and a combination of SCRM
keywords, 2851 articles were identified from the journals in year 2001–
2017. Using the SSPP framework, 174 articles were reviewed as the basis
for the analysis. This study firstly fits a matrix of ‘redundant-flexible’
organisational design with internal and external organisational structures
and processes. Using this framework, supply chain scholars and
managers may discuss the organisational fit of SCRM operations
comprehensively. It also identifies the new areas for further studies.
ARTICLE HISTORY
Received 14 February 2019
Accepted 8 December 2019
KEYWORDS
Supply chain risk
management; strategy-
structure-process-
performance framework;
systematic literature review
Introduction
Over the past decades, natural and man-made disasters have increased exponentially worldwide
(Wagner and Neshat 2010). Some firms have experienced at least one instance of supply chain dis-
ruption in the previous 12 months, leading to loss of productivity, increased cost of working, custo-
mer complaints, and impaired service outcome (Business Continuity Institute 2016). While more of
the companies are concerned about supply chain risk and resilience (Deloitte Development LLC
2013; Wright 2013), they remain to lack effective supply chain risk management (SCRM) pro-
grammes (Black et al. 2011; Sáenz and Revilla 2014).
SCRM is therefore an important research theme in the supply chain management (SCM) field
that has been analysed using practical management models (Rotaru, Wilkin, and Ceglowski 2014)
and industrial case studies (Ferreira et al. 2018). These analyses were performed from strategic,
financial, and theoretical perspectives (Kilubi and Haasis 2015), and addressed sustainability (Gian-
nakis and Papadopoulos 2016), project management (Thomé et al. 2016), and decision-making
(Yang and Birge 2017). The scholars generally study the nature of supply chain risks and how com-
panies can identify and assess different types of risks, select the right risk management approaches,
properly allocate their resources, examine their SCRM capabilities, evaluate their performance, and
benchmark their SCRM methods.
However, to the best of our knowledge, there is limited SCRM framework built from the concepts
of organisational design, or organisational ‘fit’. It suggests that a fit among strategy, structure, and
process yields superior performance (Galbraith and Nathanson 1978; Miles and Snow 1978). In
other words, firms that have achieved a proper alignment among strategy, structure, and process
can perform better than their competitors that lack such an alignment. This strategy-structure-pro-
cess-performance (SSPP) concept is relevant in SCM research (Nakano 2015; Nakano and Akikawa
© 2019 Informa UK Limited, trading as Taylor & Francis Group
CONTACT Antonio K. W. Lau antoniolau@khu.ac.kr
INTERNATIONAL JOURNAL OF LOGISTICS: RESEARCH AND APPLICATIONS
https://doi.org/10.1080/13675567.2019.1704707

2014) that provides detailed guidelines on how a firms can manage its SCM by aligning strategies
with structures and processes. However, such organisational fit concept has never been adopted
to assess the SCRM, which most of early SCRM models were developed against a backdrop of reason-
able stability in the business environment (Christopher and Holweg 2017). In fact, Deloitte’s study
mentioned above reveals that the top two SCRM challenges pointed out by executives are ‘lack of
acceptable cross-functional collaboration’ and ‘cost of implementing SCRM strategies’ (Deloitte
Development LLC 2013). It is therefore critical to address the practical difficulties of designing
organisational structures and processes appropriate to an SCRM strategy. By adopting the SSPP fra-
mework, we may be better necessary to fit strategy, structure and process together in today’s volatile
business conditions.
This study therefore contributes to the literature by conducting a systematic literature review
(SLR) using the SSPP concept to propose a new SCRM framework. The SLR method is effective
to identify, evaluate and synthesise a large number of management literature in detail (Tranfield,
Denyer, and Smart 2003), which SCM literature has recently called for (Datta 2017; Durach, Kem-
bro, and Wieland 2017). This study extends existing research by developing a new SCRM framework
which is theoretically guided. Specifically, we clarify to what extent the strategy, structure, process,
and performance to be applied in SCRM studies. This clarification helps to identify how to orches-
trate supply chain strategies, structures and/or processes for maximising firm performance (Prajogo,
Mena, and Nair 2017; Ali, Mahfouz, and Arisha 2017). Furthermore, in the SCM field, intra-organ-
isational structure is often treated as part of supply chain integration (SCI) (e.g. Flynn, Huo, and
Zhao 2010). Some existing studies incorporated the observed variables of ‘cross-functional teams’
into SCI (e.g. Alfalla-Luque, Medina-Lopez, and Dey 2013; Huo et al. 2014; Zhao, Feng, and
Wang 2015). Similar trends can be observed in the SCRM field (Chen, Sohal, and Prajogo 2013;
Ellinger et al. 2015; Shao 2013). This approach makes it difficult to deepen the discussion on organ-
isational design in the fields of SCRM as well as SCM. This is an important reason for the authors
adopting the SSPP framework, as this framework distinguishes between structure and process.
This study is organised as follows: the second section introduces the SSPP framework and men-
tions the research trends of prior literature review papers, the third section explains the methodology
of systematic literature review, the fourth section reports the findings, the fifth section points out the
problems of prior studies and proposes a new framework in the SCRM context, and finally, the sixth
section describes conclusion, some implications, and directions for future research.
Theoretical background
Strategy-structure-process-performance (SSPP) framework
The SSPP framework purposes that companies fit their strategy with structure and process to yield
superior business performance (Chandler 1962; Rumelt 1974; Williamson 1975). The concept of fit
means an internally consistent set of practices among strategy, structure, and process (Galbraith and
Nathanson 1978). In other words, after an organisation designs its strategic directions, it should (re-
)structure the business organisation efficiently. The structural design should integrate different
business functions to deal with business environment effectively. Such integration of organisational
strategy and structure needs to align with the business processes, including resource allocation,
evaluation and reward systems. While the organisational strategy, structure and process are inte-
grated, firm performance can be greatly enhanced.
The SSPP framework is useful not only for corporate-level management or strategic business unit-
level management, which is targeted by Galbraith and Nathanson (1978) and Miles and Snow (1978),
but also for functional-level management. For example, the framework has been used in the field of
international marketing (Xu, Cavusgil, and White 2006). Using structural equation modelling of a
co-variation effect model, which views fit as a pattern of internal consistency among a set of related
variables, they found that a fit among strategy, structure, and process is positively associated with
2 M. NAKANO AND A. K. LAU

performance. Barczak (1995), likewise, adopted the framework in the field of new product develop-
ment. She analysed the link between new product strategy and structure, and between new product
strategy and process using chi-square analysis.
In the field of SCM, Chow, Trevor, and Lennart (1995) firstly presented a conceptual framework
on the relationships among logistics strategy, design and performance. Rodrigues, Stank, and Lynch
(2004) adopted the SSPP framework to empirically examine the integration of relational strategy,
information and measurements systems, integrated internal and external operations, and logistics
performance. Stavrulaki and Davis (2010) mentioned some patterns of structure/process that fit
supply chain strategies. Specifically, they have proposed that lean firms adopt a closer, longer-
term relationship and a higher level of information sharing with their suppliers and a smaller num-
ber of customer segments, while agile firms adopt a more flexible supply base and more opportunistic
collaboration with their suppliers and a larger number of customer segments. On upstream external
structure and process, these propositions imply that firms with an efficient strategy should adopt a
long and rigid relationship with a small number of suppliers and a high degree of information shar-
ing with them, while firms with a responsive strategy should adopt a short and flexible relationship
with a large number of suppliers and a low degree of information sharing. Similarly, on downstream
external structure, these propositions imply that firms with an efficient strategy should adopt a stan-
dardised relationship, while firms with a responsive strategy should adopt a customised relationship.
However, their propositions are fragmentary and have not been empirically tested. Further studies
on the SSPP framework in SCM are noticeably insufficient (Rodrigues, Stank, and Lynch 2004).
Recently, Nakano and Akikawa (2014) conducted a literature review on SCM using the SSPP fra-
mework and suggested suitable structure/process and targeted performance metrics by generic
supply chain strategies. In the paper, strategy is defined as patterns of action plans and competitive
priorities. Structure is divided into intra-organisational structure (e.g. organisational form) and
inter-organisational structure (e.g. intensity). Process is divided into intra-organisational integration
mechanisms (e.g. information sharing) and inter-organisational integration mechanisms (e.g. joint
planning). Performance is divided into operational performance (e.g. inventory turnover) and
business performance (e.g. profitability). Using these definitions, Nakano (2015) further conducted
an exploratory analysis and found the patterns of structure/process that fit generic supply chain
strategies. However, SCRM was beyond the scope of these studies.
Prior SCRM literature review
Several authors have recently conducted systematic literature review (SLR) on SCRM. Kochan and
Nowicki (2018) propose a typology of supply chain resilience, while Friday et al. (2018) proposes six
SCRM capabilities including risk information sharing, standardisation of procedures, joint decision
making, risk and benefit sharing, process integration, and collaborative performance systems. Ali,
Mahfouz, and Arisha (2017) propose various kinds of management elements that fit proactive, con-
current, and reactive strategies. Datta (2017) derives seven propositions linking seven mechanisms,
four interventions, three context and four outcomes together. Kilubi (2016) classifies various proac-
tive and reactive strategy elements according to the demand-side and supply-side risks. Hohenstein
et al. (2015) and Tukamuhabwa et al. (2015) propose various kinds of management elements that fit
proactive and reactive strategies. Kilubi and Haasis (2015) suggest some management elements that
fit preventive and responsive strategies. However, these papers do not explicitly treat the constructs
of structure (e.g. supply chain network structure/design and multiple sourcing) and process (e.g. col-
laboration) in such elements from the viewpoint of organisational design. Hohenstein et al. (2015)
and Tukamuhabwa et al. (2015) further proposed that ‘collaboration’ – which means a number of
business operations such as coordination, cooperation, joint-decision making, knowledge sharing,
supplier certification, and supplier development – fits into both proactive and reactive strategies.
These papers do not clarify collaborative process that fits each strategy. Likewise, Kilubi and Haasis
(2015) proposed that ‘multiple sourcing’ – which means using alternative suppliers and maintaining
INTERNATIONAL JOURNAL OF LOGISTICS RESEARCH AND APPLICATIONS 3

slack in utilisation – fits into both preventive and responsive strategies. Similarly, this paper does not
help firms to design their upstream structure to fit each strategy.
In addition, Thomé et al. (2016) propose a synthesis framework composed of complexity and
uncertainty, risks, and resilience. This paper adopts the viewpoint of project management and treats
the construct of strategy (e.g. flexibility and redundancy) alone. Other existing SLR papers explore
future research directions on SCRM (Colicchia and Strozzi 2012; Durach, Wieland, and Machuca
2015; Fan and Stevenson 2018; Ghadge, Dani, and Kalawsky 2012; Zhu, Krikke, and Caniels
2017). These papers fragmentally mention the constructs of strategy (e.g. resistance, avoidance,
agility), structure (e.g. organisation of SCRM process, team building, trust), and process (e.g. prac-
tices and tools for SCRM, visibility, traceability, information sharing, supplier development). How-
ever, they do not try to align different strategies with various structures and processes.
On the other hand, there are some non-SLR studies on SCRM. Kamalahmadi and Parast (2016)
propose a supply chain resilience framework, which includes the constructs of strategy (flexibility
and redundancy), structure (trust), and process (information sharing). Hajmohammad and Vachon
(2016) propose four risk management strategies, including risk avoidance, monitoring-based risk
mitigation, collaboration-based risk mitigation and risk acceptance, to deal with sustainability
risks. Ho et al. (2015) organise the definition, factors, and management procedure of supply chain
risk. Ceryno, Scavarda, and Klingebiel (2015) identified ten drivers, four sources, eight consequences,
and six mitigation strategies in SCRM field and linked the strategies to certain supply chain pro-
cesses, such as global sourcing. Tang and Musa (2011) identify and classify the potential risk associ-
ated with material, cash and information flows. Other existing non-systematic literature review
papers organise approaches to manage supply chain risks (Bandaly et al. 2012, 2013; Diabat, Govin-
dan, and Panicker 2012; Khan and Burnes 2007). These papers partially mention the constructs of
strategy (e.g. avoidance, prevention, and mitigation), structure (e.g. closer working relationships with
suppliers, and multiple sourcing or single sourcing), and process (e.g. communication and early
involvement of suppliers in strategic decisions and supplier improvement programmes). Ellis,
Shockley, and Henry (2011), for example, propose a conceptual framework for supply disruption
risk that considers environment, organisation and individual decision-makers. However, these
studies do not treat the relationships between strategy and structure/process. In short, further
SLR studies on SCRM with the concepts of SSPP are warranted. This research thus comprehensively
examines the complex interrelationships among risk management strategies, managerial structures
and processes.
Methodology
In order to ensure a replicable approach, the SLR process guided by Denyer and Tranfield (2009) and
Durach, Kembro, and Wieland (2017) was adopted. They provide a protocol helping researchers to
formulate research questions, locate studies, select appropriate articles, and analyse and synthesise
the selected articles, as explained below.
Formulating research question
Firstly, according to the SSPP framework, the following research question was formulated to provide
focus in defining which articles should be included in the review:
Our research question: Which variables have been adopted in existing literature to specify or measure SSPP
constructs in SCRM studies? Moreover, how should those variables be incorporated into the SSPP framework?
In order to conduct a well-built SLR, we relate the SSPP framework to the context, intervention,
mechanism, and outcome (CIMO)-logic proposed by Denyer and Tranfield (2009). The CIMO-
logic has been adopted by prior SCRM literature (Colicchia and Strozzi 2012; Datta 2017). On
the CIMO-logic, in a specified context (C), a certain type of intervention (I) works through a set

of mechanisms (M) to produce a certain desired outcome (O). Similarly, with respect to the SSPP
framework, a certain type of structure (I = Structure) is mediated by a set of process (M = Process)
operating in a specified strategy (C = Strategy) to produce a certain desired operational and/or
business performance (O = Performance). For example, in the context of different SCRM strategies,
the SCRM processes that are represented by effective SCRM instruments and practices are developed
according to the strategic alignment with suppliers to improve operational performance and resili-
ence/robustness. Therefore, it is appropriate to adopt the SLR to answer the above research
questions.
Locating studies
Secondly, we searched the articles from three major academic literature databases: EBSCO, Science-
Direct, and Scopus. These databases were selected as they consist of articles published in the major
journals on SCM, operations management, purchasing management, and logistics management.
Therefore, it is possible to search for and locate a significant proportion of the published articles
on SCRM. Several combinations of keywords were adopted to search articles that focus on SCRM
and exclude those that mention SCRM only briefly. The used keywords were a combination of
(supply chain, supplier, buyer-seller, purchasing, sourcing, buying, procur*, supply management,
materials management, channel management, distribution, logistics) AND (risk*, disrupti*, resilien*,
disaster, vulnerab*, robustness, catastrophic), which should be sufficiently broad enough to avoid
limiting results and to select as many articles as possible relevant to the research question. The search
was finished in April 2018 with a publication deadline (before 31 December 2017). To address this
research question, we conducted an extensive systematic literature review on the subject of SCRM.
We ensured quality control by excluding non-academic articles from our review. This, however, led
to the possibility of publication bias based on favouring significant results, availability, cost, or
language bias (Borenstein et al. 2011). However, we propose that our focus on peer-reviewed aca-
demic articles will ensure the article quality, reliability, and relevance of our study (Bastas and Liya-
nage 2018). The selection of databases was consistent with existing literature (Fan and Stevenson
2018; Govindan and Hasanagic 2018). Similar studies have adopted even stricter journal selection
approaches, such as using only EBSCO host and Web of Science (Fan and Stevenson 2018), only
Web of Science and Scopus (Govindan and Hasanagic 2018), or by selecting a list of specific
SCM journals (Friday et al. 2018). The publication bias issue is noted in our ‘limitations’ section.
In addition, only articles published in English language were selected. Consequently, 2851 articles
(duplicated) that contained relevant keywords in the title were identified. Duplicate articles retrieved
from multiple databases were eliminated. This reduced the number of articles from 2851 to 1497.
Selecting articles
Thirdly, a title and abstract analysis was conducted by the two authors independently on the ident-
ified articles on the basis of the following criteria. The articles related to the four constructs of the
SSPP framework have not been accumulated yet because SCRM research has a relatively short his-
tory. Therefore, it is desirable that the selected articles were not only empirical-based (e.g. survey and
case study) but also non-empirical based (e.g. literature review, conceptual, and simulation). Specifi-
cally, the articles that mainly explore (e.g. case study), examine (e.g. survey), review (e.g. literature
review), theorise (e.g. conceptual), and/or simulate (e.g. simulation) at least one of the four con-
structs of the SSPP framework using a set of inclusion criteria (Table 1) were selected.
Referring to the existing papers, the four constructs were defined. Strategy is defined as ‘specific
actions deriving from the strategy formulation process’ (Galbraith and Nathanson 1978, 19), and
specifically, patterns, priorities, and orientations of SCRM. Structure is divided into intra-organis-
ational structure and inter-organisational structure. The former is defined as ‘the segmentation of
work into roles, the recombining of roles into departments or divisions, and the distribution of

power across this role structure’ (Galbraith and Nathanson 1978, 21) and includes, for example,
inter-departmental committee, cross-functional team, organisational form, and the degree of forma-
lisation and centralisation. The latter is defined as ‘the pattern of relationships among firms engaged
in creating a sellable product’ (Choi and Hong 2002, 470) and includes, for example, long-term
relationship, buyer or supplier dependency, number of suppliers, and geographic dispersion. In
terms of process, Galbraith and Nathanson (1978) define as ‘work and information flows linking
the differentiated roles within and between departments of the complex organization’ (21). Including
both intra- and inter-organisational integration mechanisms, the authors define process as ‘work and
information flows linking the differentiated roles within and across firms’. This includes, for
example, information sharing, working together, joint planning, and partner involvement. Referring
to Nakano and Akikawa (2014), which is a literature review paper on SCM using the SSPP frame-
work, performance is defined as ‘operational performance’ (e.g. inventory turnover, cost, and lead
time) and ‘business performance’ (e.g. profitability and market share).
Based on the above definitions, irrelevant articles were excluded according to (1) the lack of rel-
evance to the four constructs of the SSPP framework and (2) very narrow aspects or contexts con-
cerning these constructs. Definition (1) means that the article does not include keyword(s) related to
at least one of the four constructs in its title and/or abstract. Definition (2) means that the article
focuses on very specific things, such as specific risk management (e.g. cyber risk management), a
specific framework (e.g. a GIS framework), a specific application (e.g. a blood supply chain), a
specific area (e.g. a developing country context), a specific task (e.g. inventory management), specific
measures (e.g. seismic performance), or a specific model (e.g. fuzzy model), even though it includes
keyword(s) related to one of the four constructs in its title and/or abstract. The numbers of excluded
articles according to these definitions are 959 and 263 respectively.
Through these procedures, 275 articles were selected. Subsequently, the full text was roughly
assessed in order to find evidence of whether or not an article really fitted with our research objec-
tives. During this procedure, the articles that did not include variables to specify or measure the SSPP
constructs were excluded based on the research question. Consequently, a total of 164 articles were
identified. During the process of extracting these articles, the inter-coder reliability – Cohen’s kappa
Table 1. Inclusion criteria.
Inclusion criteria
. Papers published in peer-reviewed scientific journals in English
. Papers published before 31 December 2017
. Papers containing keywords in the title
. On strategy, patterns, priorities, and orientations of supply chain risk management are included
. On structure, intra-organisational structure (e.g. inter-departmental committee, cross-functional team, organisational form, and
the degree of formalisation and centralisation) and/or inter-organisational structure (e.g. long-term relationship, buyer or
supplier dependency, number of suppliers, and geographic dispersion) are included
. On process, intra-organisational integration mechanisms (e.g. information sharing, working together, and joint planning), and/
or inter-organisational integration mechanisms (e.g. information sharing, working together, and partner involvement) are
included; and
. On performance, operational performance (e.g. inventory turnover, cost, and lead time) and/or business performance (e.g.
profitability and market share) are included

coeﬃcient – was calculated to be 0.838, which shows a high level of agreement between the two
authors (Landis and Koch 1977). In addition, in order to search for other particularly relevant
articles that were missing from such a protocol-driven method, the snowball method (cross-referen-
cing) was adopted as a supplementary strategy and another 10 articles were found. These procedures
were independently conducted by two authors. Their results were compared and discussed interac-
tively. In total, 174 articles formed the basis for the analysis. These articles were published between
2001 and 2017. The article selection process is illustrated in Figure 1.
Analysing and synthesising articles
After the articles were located, selected and reviewed, we tabulated the research methods used in the
articles. We also identiﬁed the journals that published SCRM-based articles. Based on the SSPP fra-
mework, individual articles were analysed and synthesised using the SSPP constructs and their inter-
relationships were shown. The variables that were used to specify or measure each SSPP construct in
the selected articles were extracted. This analysis aimed to produce answers to our research question.
The results of the above analyses were summarised in the next section. These analyses were
Figure 1. Article selection process.

independently conducted using a common data-extraction form (concepts/variables, typology of the
SSPP, and additional notes) by the two authors. Their results were compared and discussed interac-
tively in the event of significant differences in order to reach high levels of agreement. On the basis of
the analyses, a synthesis of the SSPP constructs in the SCRM was reported in the next section.
Findings
Distribution of these articles with respect to the journals is shown in Table 2. The highest proportion
of articles related to the SSPP constructs (28.7%) were published in the International Journal of Pro-
duction Economics (n = 23), the International Journal of Production Research (n = 14), and the Supply
Chain Management: An International Journal (n = 13). 11 articles were published in the Inter-
national Journal of Physical Distribution & Logistics Management.
Generally, SCRM has in the past (from 2001) been studied in logistics and in SCM literature, and
related studies were expanded to other academic outlets after 2008. We adapted the classification
used in Kilubi’s (2016) study – as shown in Table 3 – as the research approach using the SSPP con-
structs rich in variety. Among the selected studies, the primary methodological approach related to
the SSPP constructs was ‘survey’ (48 out of 174). The second most used approach was ‘mathematical
model/simulation’ (35 out of 174), followed by ‘case study’ (32 out of 174), which was the third
approach. Many of the researchers utilised SSPP constructs in their empirical studies. There were
some conceptual (18 out of 174) or literature-based (22 out of 174) articles as well. ‘Mixed methods’
refers to, for example, a mix of a case study and a survey. ‘Others’ refer to, for example, empirical
studies using secondary data and content analysis using interview data. There was only one of the
selected articles that used secondary databases, which was accordingly classified into the ‘Other’
section.
Table 3 shows that since 2001, the volume of SCRM studies published has been increasing. These
were mainly conducted in conceptual and literature review stages. From 2008, studies started to
expand and shift their focus to empirical verification, mathematical modelling, and simulation.
Case studies were now consistently being done in SCRM literature. This trend seems reasonable
as – in the beginning stages – scholars were using a qualitative approach to explore and clarify
the scope, concepts, and components of SCRM, while at a later stage, scholars were able to adopt
a quantitative approach to verify them. As all the methods were consistently used in recent literature,
we propose that SCRM is evolving and that new concepts are consistently proposed and verified.
This may be the result of dynamic changes and the complexity of supply chain risk and business
content (Fan and Stevenson 2018) or advances in technology (Ivanov, Dolgui, and Sokolov 2019).
It can therefore be said that as the SCRM field is maturing, its literature should be regularly re-ana-
lysed to reflect newly added content.
Along the SSPP framework, individual articles were categorised on the basis of the four constructs
(see Table 4) and their interrelationships (see Table 5). The most frequent pattern was ‘strategy’ (33
of the 174). As described later, many articles have proposed various kinds of SCRM strategies. The
second most frequent pattern was ‘structure-process’ (22 of the 174). This means that there are many
articles that have discussed main management elements such as structure and process simul-
taneously. The third most frequent pattern was ‘performance’ (16 of the 174). As described later,
the variables of performance are rich in variety. There were only nine articles on the SSPP that
include all the four constructs (Berg, Knudsen, and Norrman 2008; Datta 2017; Giunipero and Eltan-
tawy 2004; Kilubi and Haasis 2015; Li, Wu, et al. 2017; Revilla and Saenz 2017; Sáenz and Revilla
2014; Wieland and Wallenburg 2012; Zsidisin and Wagner 2010). Among these, Kilubi and Haasis
(2015) are regarded as an article proposing a new framework organising management enablers
including structure and process by SCRM strategies (preventive or responsive) through their SLR.
To address the research question concerning SCRM variable identification in the SSPP frame-
work, we report the variables that have been used for the constructs of strategy, structure, process,
and performance, in that order.

Table 2. Distribution of journals.
Journals / Year 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Total
International Journal of Production Economics 1 2 2 1 1 1 2 7 6 23
International Journal of Production Research 2 2 2 3 3 2 14
Supply Chain Management: An International Journal 1 2 3 2 1 1 3 13
International Journal of Physical Distribution & Logistics
Management
1 3 1 1 1 2 1 1 11
Journal of Business Logistics 2 2 1 3 1 9
International Journal of Logistics Management 1 1 1 1 1 1 1 2 9
International Journal of Logistics Research & Applications 1 1 1 2 1 1 7
International Journal of Logistics Systems and Management 1 1 1 1 2 6
International Journal of Operations & Production
Management
1 1 2 4
Omega 1 2 1 4
Sloan Management Review 1 1 2 4
Computers & Industrial Engineering 1 2 3
Journal of Purchasing & Supply Management 1 1 1 3
Production Planning & Control 1 1 1 3
Supply Chain Forum: International Journal 3 3
Transportation Research: Part E 1 1 1 3
Benchmarking: An International Journal 1 1 2
Industrial Management & Data Systems 1 1 2
International Journal of Business Science & Applied
Management
1 1 2
IUP Journal of Supply Chain Management 1 1 2
Journal of Marketing Channels 2 2
Journal of Operations Management 1 1 2
Journal of Supply Chain Management 1 1 2
Risk Management 1 1 2
Others 1 1 2 1 3 2 2 4 7 5 7 4 39
Total 1 2 1 5 3 4 7 5 7 7 12 9 17 23 22 24 25 174
INTERNATIONAL
JOURNAL
OF
LOGISTICS
RESEARCH
AND
APPLICATIONS
9

Table 3. Distribution of research methods.
Approaches 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Total Per cent
Survey 1 1 1 3 5 3 7 8 5 7 7 48 27.6
Mathematical model/simulation 1 1 1 2 1 2 4 7 5 11 35 20.1
Case study 1 1 1 4 1 4 1 3 1 4 5 3 2 1 32 18.4
Literature review 1 1 3 1 3 5 5 3 22 12.6
Conceptual/theoretical 1 4 1 2 1 1 1 1 3 2 1 18 10.3
Mixed method 2 1 1 1 1 3 1 10 5.7
Others 1 1 2 2 1 2 9 5.2
Total 1 2 1 5 3 4 7 5 7 7 12 9 17 23 22 24 25 174 100
10
M.
NAKANO
AND
A.
K.
LAU

Table 4. Categorisation of the selected articles.
Author(s) Strategy Structure Process Performance
Aigbogun, Ghazali, and Razali (2014) X X
Ali and Shukran (2016) X
Ali, Mahfouz, and Arisha (2017) X
Altay and Ramirez (2010) X
Ambulkar, Blackhurst, and Grawe (2015) X X X
Bandaly et al. (2012) X
Bandaly et al. (2013) X
Bandaly, Satir, and Shanker (2014) X
Behzadi et al. (2017) X
Berg, Knudsen, and Norrman (2008) X X X X
Blackhurst, Dunn, and Craighead (2011) X X
Blos et al. (2009) X X
Bode et al. (2011) X X X
Botes, Niemann, and Kotze (2017) X X
Brandon-Jones et al. (2014) X X
Brusset and Teller (2017) X
Cardoso et al. (2015) X X
Carvalho, Azevedo, and Cruz-Machado (2012) X X
Chang, Ellinger, and Blackhurst (2015) X X
Chen, Sohal, and Prajogo (2013) X X X
Chen, Liu, and Yang (2015) X X
Chen et al. (2017) X
Cheng and Lu (2017) X
Chopra and Sodhi (2004) X
Chopra and Sodhi (2014) X
Chowdhury and Quaddus (2015) X
Chowdhury and Quaddus (2016) X X X
Chowdhury and Quaddus (2017) X X X
Christopher and Lee (2004) X
Christopher and Peck (2004) X X
Craighead et al. (2007) X
Cui and Basnet (2015) X X X
Datta (2017) X X X X
Dekker, Sakaguchi, and Kawai (2013) X X
Diabat, Govindan, and Panicker (2012) X X X
Duhamel, Carbone, and Moatti (2016) X X
Durach, Wieland, and Machuca (2015) X
Durach, Kembro, and Wieland (2017) X X
Elleuch et al. (2016) X
Ellinger et al. (2015) X X X
Elzarka (2013) X
Enyinda, Mbah, and Ogbuehi (2010) X
Faisal, Banwet, and Shankar (2006) X X
Faisal, Banwet, and Shankar (2007) X
Fattahi, Govindan, and Keyvanshokooh (2017) X X
Franck (2007) X X
Fujimoto and Park (2014) X
Gaudenzi and Borghesi (2006) X
Ghadge, Dani, and Kalawsky (2012) X X X
Ghadge et al. (2017) X
Giannakis and Papadopoulos (2016) X
Giunipero and Eltantawy (2004) X X X X
Golgeci and Ponomarov (2015) X
Gong et al. (2014) X
Grötsch, Blome, and Schleper (2013) X X
Guarnaschelli, Chiotti, and Salomone (2013) X
Hahn and Kuhn (2012) X
Hanna, Skipper, and Hall (2010) X X
Ho et al. (2015) X
Hohenstein et al. (2015) X X
Hou, Zeng, and Sun (2017) X
Huong Tran, Childerhouse, and Deakins (2016) X X
(Continued)

Table 4. Continued.
Ivanov, Sokolov, and Dolgui (2014) X
Ivanov et al. (2016) X X X
Ivanov (2017) X
Johnson, Elliott, and Drake (2013) X
Jüttner (2005) X
Jüttner and Maklan (2011) X X X
Jüttner, Peck, and Christopher (2003) X
Kamalahmadi and Parast (2016) X X X
Kamalahmadi and Parast (2017) X X
Kauppi et al. (2016) X X X
Kersten et al. (2011) X
Khan and Burnes (2007) X X
Kilubi and Haasis (2015) X X X X
Kilubi (2016) X X X
Kırılmaz and Erol (2017) X
Kleindorfer and Saad (2005) X
Kurniawan et al. (2017) X X
Kumar, Himes, and Kritzer (2014) X
Lamothe, Mahmoudi, and Thierry (2007) X X
Lassar et al. (2010) X X X
Lavastre, Gunasekaran, and Spalanzani (2012) X X
Lavastre, Gunasekaran, and Spalanzani (2014) X X X
Leat and Revoredo-Giha (2013) X
Lee and Rha (2016) X X
Lee and Ulferts (2011) X
Li et al. (2015) X X X
Li, Fan, et al. (2017) X X X X
Li, Wu, et al. (2017) X X
Liu, Lin, and Hayes (2010) X X
Lockamy III (2014) X X
Lucker and Seifert (2017) X
Macdonald and Corsi (2013) X
Mandal (2012) X
Mandal (2014) X X
Manuj and Mentzer (2008a) X
Manuj and Mentzer (2008b) X X X
Manuj, Esper, and Stank (2014) X
Maslaric et al. (2013) X
Mishra et al. (2016) X X X
Mohammaddust et al. (2017) X
Mohd, Loke, and Ooi (2014) X X
Monroe, Teets, and Martin (2014) X
Neureuther and Kenyon (2009) X X
Nooraie and Parast (2015) X X
Nooraie and Parast (2016) X X
Norrman and Jansson (2004) X X X
Oehmen et al. (2009) X
Oke and Gopalakrishnan (2009) X
Ouabouch and Pache (2014) X
Park, Hong, and Roh (2013) X X
Pereira, Martin Christopher, and Da Silva (2014) X X
Pettit, Fiksel, and Croxton (2010) X
Pettit, Croxton, and Fiksel (2013) X
Prakash et al. (2017) X
Pujawan, Kurniati, and Wessiani (2009) X
Purvis et al. (2016) X
Rajesh and Ravi (2015) X X
Rajesh, Ravi, and Venkata (2015) X X
Revilla and Saenz (2014) X X
Revilla and Saenz (2017) X X X X
Riley et al. (2016) X X X
Ritchie and Brindley (2007a) X
(Continued)

Strategy variables
The Strategy was found in 77 articles (see the bottom of Table 4). As shown in Table 6, the most and
second most frequent types were ‘proactive or preventive’ (22 of the 77) and ‘reactive or responsive’
(21 of the 77). For example, Sharma and Bhat (2014) define ‘proactive’ strategy as ‘reducing the fre-
quency of occurrence of risky events’ and ‘reactive’ strategy as ‘reducing the negative consequences of
risky events after their occurrence’ (1025). Some articles also adopt the same categorisation of ‘proac-
tive-reactive’ (Berg, Knudsen, and Norrman 2008; Chowdhury and Quaddus 2017; Ghadge, Dani,
Table 4. Continued.
Ritchie and Brindley (2007b) X X X
Rotaru, Wilkin, and Ceglowski (2014) X X
Sáenz and Revilla (2014) X X X X
Scholten and Schilder (2015) X X
Scholten, Scott, and Fynes (2014) X X
Shafiq et al. (2017) X X
Shao (2013) X X
Sharma and Bhat (2014) X X
Sharma, Bhat, and Routroy (2014) X
Sheffi (2001) X X X
Sheffi and Rice Jr. (2005) X
Shenoi, Dath, and Rajendran (2016) X X X
Silbermayr and Minner (2016) X
Simchi-Levi et al. (2015) X
Singhal, Agarwal, and Mittal (2011) X
Soni, Jain, and Salmador (2015) X
Speier et al. (2011) X
Sreedevi and Saranga (2017) X X
Stecke and Kumar (2009) X
Svensson (2002a) X
Svensson (2002b) X
Talluri et al. (2013) X X
Tang (2006) X
Tang and Tomlin (2008) X X X
Thomé et al. (2016) X
Thun and Hoenig (2011) X X
Thun, Druke, and Hoenig (2011) X X X
Todo, Nakajima, and Matous (2015) X X
Trkman and McCormack (2009) X X
Trkman, Oliveira, and McCormack (2016) X
Tsai (2016) X X
Tukamuhabwa et al. (2015) X X X
Tummala and Schoenherr (2011) X
Wagner and Bode (2006) X
Wagner and Bode (2008) X X
Wagner and Neshat (2012) X X
Wakolbinger and Cruz (2011) X X X
Wang, Tiwari, and Chen (2017) X X X
Wang et al. (2016) X
Whitney, Luo, and Heller (2014) X
Wieland and Wallenburg (2012) X X X X
Wieland and Wallenburg (2013) X X X
Wiengarten et al. (2016) X X
Xue et al. (2013) X X
Yang and Fan (2016) X
Yang, Wen, and Wang (2011) X X
Yoho and Apte (2015) X
Zhao et al. (2013) X X X
Zhu, Krikke, and Caniels (2017) X X X
Zsidisin and Wagner (2010) X X X X
Total 77 86 86 72

and Kalawsky 2012; Hohenstein et al. 2015; Scholten, Scott, and Fynes 2014; Trkman, Oliveira, and
McCormack 2016; Tukamuhabwa et al. 2015). Among them, Tukamuhabwa et al. (2015) mention
that other strategies have been broadly organised into these two categories. Other articles use syno-
nyms such as ‘preventive-reactive’ (Thun, Druke, and Hoenig 2011; Thun and Hoenig 2011), ‘pre-
ventive-responsive’ (Kilubi and Haasis 2015), ‘robustness-agility’ (Wieland and Wallenburg 2012,
2013), or ‘pre-disruption-post-disruption’ (Ivanov, Sokolov, and Dolgui 2014). Thus, ‘proactive-
reactive’ is regarded as a distinctive SCRM strategy categorisation.
In addition, ‘redundant-flexible’ is also regarded as another distinctive SCRM strategy. These two
strategies are presented in Sheffi and Rice Jr. (2005) for the first time. Chang, Ellinger, and Blackhurst
(2015) clarify the differences between these definitions. Specifically, ‘redundant’ strategy is ‘limiting
or mitigating the negative effects of a risk by keeping some resources in reserve to be used in case of a
disruption’, while ‘flexible’ strategy is ‘building organizational and interorganizational capabilities to
sense threats to supply continuity and to respond to them quickly’ (645). They mention that ‘buffer-
ing’ is similar to a redundant strategy and ‘bridging’ is comparable to a flexible strategy. A few articles
also adopt redundant-flexible categorisation (Kamalahmadi and Parast 2016; Zsidisin and Wagner
Table 5. Typology of the SSPP.
Combination patterns of the SSPP constructs No. of articles
Strategy 33
Structure 15
Process 13
Performance 16
Strategy-structure 6
Strategy-process 2
Strategy-performance 9
Structure-process 22
Structure-performance 5
Process-performance 12
Strategy-structure-process 11
Strategy-structure-performance 4
Strategy-process-performance 3
Structure-process-performance 14
Strategy-structure-process-performance 9
Table 6. Main variables of strategy, structure, and process.
Category Variables No. of articles Per cent
Strategy Proactive/preventive 22 28.6
Reactive 21 27.3
Flexibility 16 20.8
Mitigation 15 19.5
Avoidance 13 16.9
Redundancy 11 14.3
Internal structure Corporate risk management department 9 40.9
Cross-functional supply chain risk management teams 8 36.4
External structure Supply base 38 52.8
Relationship strength 13 18.1
Trust 13 18.1
Dependence 11 15.3
Relationship length 8 11.1
Geographical location 7 9.7
Internal process Risk planning 15 40.5
ICT utlisation 13 35.1
Collaboration 7 18.9
Information sharing 7 18.9
External process Collaboration 41 57.7
Information sharing 39 54.9
Partner involvement 8 11.3
ICT utilisation 6 8.5

2010). ‘Avoidance’ is a specific type of proactive strategy. Jüttner, Peck, and Christopher (2003)
clearly define this strategy as ‘dropping specific products, suppliers or geographical markets if supply
is seen to be unreliable’ (206). ‘Mitigation’, which is the fourth most frequently used strategy, is a
comprehensive type that includes several kinds of SCRM strategies earlier such as proactive, reactive,
redundant, and flexible.
Structure variables
The Structure variables are divided into internal and external. On internal structure, there were not
many articles that used the construct (22 of the 174). From these articles, we can confirm two kinds
of internal departments: corporate risk management department and cross-functional supply chain
risk management teams. For example, Norrman and Jansson (2004) introduced the necessity of such
departments on the basis of a case study of Ericsson, which is a leading telecom company. Here, the
corporate risk management department has the overall responsibility for risk management, has con-
tact with insurance companies, and co-ordinates risk management activities throughout the group.
Cross-functional supply chain risk management teams, called ‘risk management council’ in this case,
consist of representatives from different business areas and functional units. Blackhurst, Dunn, and
Craighead (2011), who identified the teams through their case studies, clearly explain that the role is
to optimise the entire supply chain rather than small portions of the supply chain and thus eliminate
potential bottlenecks in the system. Specifically, the teams enable firms to stabilise their supply chain
after a disruption quickly and more efficiently. Chen, Sohal, and Prajogo (2013), Ellinger et al.
(2015), and Shao (2013) also emphasise their operational role such that the teams solve process-
related problems.
In addition, there were a few articles that mention structural properties of the internal supply
chain: decentralisation and formalisation. In terms of the former, Jüttner and Maklan (2011) intro-
duce a case of a cabling supplier. As a redundant resource, they explain that the decentralised struc-
ture increases the velocity of the shorter operational supply pipelines although the responsibility of
planning remains at the central headquarter. Grötsch, Blome, and Schleper (2013) statistically
demonstrate that there is a significant relationship between mechanic management control system
including formalisation of procedures and a proactive SCRM.
The variables of external structure were found in 72 articles (see Table 6). Most of them treat
upstream structure with suppliers rather than downstream one with customers. In particular, the
overwhelming majority of articles explain ‘supply base’ (38 of the 72), for example, single sourcing
or dual/multiple sourcing, flexible supply base, and back-up/standby/alternative supplier(s). Other
frequent variables are ‘relationship strength’ (e.g. close relationship, collaborative relationship, and
partnerships), ‘trust’, for example, competence trust and goodwill trust, ‘dependence’ including
mutual dependence or interdependence, ‘relationship length’, specifically, long-term relationship,
and ‘geographical location’ such as geographical proximity to partners and supplier dispersity.
Process variables
The Process variables are also divided into internal and external. The variables of internal process
were found in 37 articles. The most frequent variable is ‘risk planning’ (15 of the 37). There are
two kinds: contingency planning, which means disaster-recovery planning, and business continuity
planning, which goes beyond disaster-recovery planning and includes the actions to be taken,
resources required, and procedures to be followed to ensure the continued availability of essential
services, programmes, and operations in the event of unexpected interruptions (Norrman and Jans-
son 2004). These planning processes are carried out under the reactive strategy (Tukamuhabwa et al.
2015; Wieland and Wallenburg 2012). The second frequent variable is ‘information and communi-
cation technology (ICT) utilization’ (13 of the 37). This includes various functions, for example,
tracking/tracing/monitoring (Blackhurst, Dunn, and Craighead 2011; Brusset and Teller 2017;

Chowdhury and Quaddus 2016; Norrman and Jansson 2004), warning/reporting/predicting (Black-
hurst, Dunn, and Craighead 2011; Chowdhury and Quaddus 2016; Wiengarten et al. 2016), planning
such as advanced planning system (APS) (Chowdhury and Quaddus 2015; Lavastre, Gunasekaran,
and Spalanzani 2012, 2014; Shenoi, Dath, and Rajendran 2016), and integrating such as enterprise
resource planning (ERP) (Brusset and Teller 2017; Ellinger et al. 2015; Riley et al. 2016). Other fre-
quent variables are ‘collaboration’ including working together and ‘information sharing’.
The variables of external process were found in 71 articles. In contrast to those of internal process,
‘collaboration’ (41 of the 71) and ‘information sharing’ (39 of the 71) are frequently used as the vari-
ables of external process, particularly upstream process with suppliers. Other frequent variables are
‘partner involvement’ and ‘ICT utilization’. Compared with internal ‘ICT utilization’, the external
one, for example, collaborative supply chain event management system (Guarnaschelli, Chiotti,
and Salomone 2013), collaborative information systems (Lavastre, Gunasekaran, and Spalanzani
2014), and system coupling (Kauppi et al. 2016) do not show specific functions. The variable ‘partner
involvement’ is unique to the external process, which is a partner’s participation in a focal firm’s
activities. For example, Chen, Sohal, and Prajogo (2013) define this as including suppliers in goal-
setting, planning, and new product development activities. The number of articles using ‘joint
risk planning’ was 5 out of 71. Similar to internal process, ‘joint risk planning’ includes contingency
and business continuity aspects.
Performance variables
The Performance variables being used in the articles were also reported (72 of the 174 in Table 4). In
Table 7, these variables were categorised into two groups: ‘operational performance’, referring to the
performance of operational activities such as production and logistics, and ‘business performance’,
referring to the business performance in general. More than 86% of the reviewed articles (62 of the
72) adopt ‘operational performance’, as the SCRM-related activities are operational in nature. We
use six indicators as the sub-categories of operational performance: ‘cost’, ‘asset’, ‘quality/customer
satisfaction’, ‘lead time’, which are based on Handfield and Nichols Jr. (1999), ‘flexibility’, and ‘dis-
ruption impact’, which are often used in the reviewed articles. ‘Disruption impact’ is a specific vari-
able in SCRM, which however, has not been aggregated to a specific index yet. For example, Zsidisin
and Wagner (2010) measure the latent variable called ‘disruption occurrence’ using some observed
variables such as ‘late delivery’, ‘quality problem’, and ‘excess costs’. Similarly, Ambulkar, Blackhurst,
and Grawe (2015) measure ‘disruption impact’ using ‘overall efficiency of operations’, ‘lead time for
delivery’, and ‘purchasing costs for supplies’. Lee and Rha (2016) measure ‘supply chain disruption
negative magnitudes’ using not only ‘procurement costs’, ‘overall efficiency of operations’, and ‘pro-
duct quality’ but also ‘responsiveness to customer demands’, ‘customer satisfaction’, ‘order fulfill
Table 7. Main variables of performance.
Category Sub-category Variables No. of articles Per cent
Operational Cost Total cost/operating costs 19 26.4
performance Asset Inventory level 8 11.1
Quality/customer satisfaction Customer satisfaction/customer value 15 20.8
Customer service level 11 15.3
Delivery dependability/delivery reliability 10 13.9
Product quality 9 12.5
Order fill/stock-outs 8 11.1
On-time delivery 8 11.1
Lead time Delivery lead time 11 15.3
Flexibility Volume, mix, delivery etc. 7 9.7
Disruption impact Late delivery, time-to-recover, excess costs, etc. 10 13.9
Business Financial performance Profitability 10 13.9
performance Sales/revenue 9 12.5
Market performance Market share 5 6.9

capacity’ and so on. In their case study, Simchi-Levi et al. (2015) estimate ‘time-to-recover’ created by
Cisco Systems, which is defined as the time it takes for a node to recover to full functionality after a
disruption, and ‘time-to-survive’ proposed by the authors, which is defined as the maximum amount
of time the system can function without performance loss if a particular node is disrupted. On the
other hand, the articles using ‘business performance’ were sparse (22 of the 72), indicating that the
researchers have not sufficiently discussed the impact of SCRM activities on business performance.
Relatively frequent variables are ‘profitability’, ‘sales/revenue’, and ‘market share’.
We summarise the results of the main variables on SSPP constructs. Regarding strategy, external
structure, internal/external process, and performance, we can find typical variables of each construct.
In contrast, there is a limited number of articles on internal structure. We use these variables to pro-
pose a new SSPP framework in the SCRM context in the following discussion.
Discussion
SCRM variables for the SSPP framework
By adopting the SSPP framework, we identified 36 main variables, including strategy (6 variables),
structure (internal: 2 variables; external: 6 variables), process (internal: 4 variables; external 4 vari-
ables), and performance (operational: 11 variables; business: 3 variables). These variables were ident-
ified individually from the 174 selected articles. For example, while ICT utilisation within internal
departments and for external partners is a critical variable concerning risk management for both
internal and external processes (Guarnaschelli, Chiotti, and Salomone 2013), existing literature on
ICT utilisation focuses mainly on internal processes. Studies concerning ICT utilisation for external
processes to address SCRM are relatively rare.
We also found that the variables of SCRM strategy require further examination. Prior studies have
paid considerable attention to SCRM strategy, but there is no unanimity among researchers in clas-
sifying SCRM strategies (Sharma and Bhat 2014). In fact, there are many discussions on strategy
alone (see Table 5).
As shown in Table 8, we try to organise the relationships of seven major strategy elements, which
are also called abilities or enablers in the reviewed papers, in a matrix of proactive-reactive and
redundant-flexible. On ‘redundancy’, Sharma and Bhat (2014) and Tukamuhabwa et al. (2015)
introduce examples such as excess inventory and spare capacity as a reactive strategy. Hohenstein
et al. (2015) and Kilubi and Haasis (2015) adopt redundancy such as adding safety stock, additional
capacity and multiple sourcing as the elements of both proactive/preventive and reactive/responsive
strategies. Manuj and Mentzer (2008b) define ‘hedging’ as ‘having a globally dispersed portfolio of
suppliers and facilities such that a single event (like currency fluctuations or a natural disaster) will
not affect all the entities at the same time and/or in the same magnitude’ (208). This definition
suggests that hedging is a proactive strategy element.
‘Collaboration’ (or ‘coordination’) can be adopted in both proactive/preventive and reactive/
responsive strategies with different purposes. Collaboration is defined as ‘the ability to work effec-
tively with other supply chain entities for mutual benefit’ (Tukamuhabwa et al. 2015, 10). While
the aim of proactive collaboration is to reduce vulnerability, that of reactive collaboration is to
respond and recover (Tukamuhabwa et al. 2015). Kilubi and Haasis (2015) present concrete
examples of the former such as asset sharing, joint product design, and collaborative research,
and the latter such as joint problem-solving and dynamic pricing and promotion. Jüttner, Peck,
and Christopher’s (2003) ‘co-operation’ is a synonym for collaboration. They introduce examples
such as joint efforts to improve supply chain visibility and understanding, share risk-related infor-
mation, and prepare supply chain continuity plans. These examples suggest that ‘co-operation’ in
their paper is recognised as a proactive strategy element.
‘Postponement’ is regarded as a proactive or preventive strategy element (Ghadge, Dani, and
Kalawsky 2012; Kilubi and Haasis 2015). Elzarka (2013) defines it as ‘delaying the actual

commitment of resources to maintain flexibility and delay the incurring costs’ (485). Similarly, ‘sup-
plier development’ is positioned as a proactive strategy element (Ghadge, Dani, and Kalawsky 2012;
Tukamuhabwa et al. 2015). Tukamuhabwa et al. (2015) define it as ‘facilitating suppliers with incen-
tives, e.g. financial, training and technical knowledge to improve efficiency, commitment and
reliability’ (10). Sharma and Bhat (2014) propose specific elements such as early involvement of
the supplier in product design. On the other hand, ‘flexibility’ is regarded as a reactive or responsive
strategy element (Hohenstein et al. 2015; Kilubi and Haasis 2015; Sharma and Bhat 2014; Tukamu-
habwa et al. 2015). Tukamuhabwa et al. (2015) define it as ‘the ability of a firm and supply chain to
adapt to changing requirements with minimum time and effort’ (11). Some examples include flexible
production systems, flexibility in distribution channels, back-up suppliers, and multi-skilled work-
forces. ‘Agility’ is also a reactive strategy element (Christopher and Peck 2004; Tukamuhabwa
et al. 2015; Wieland and Wallenburg 2012) and is defined as ‘the ability to respond quickly to unpre-
dictable changes in demand and/or supply’ (Tukamuhabwa et al. 2015, 11).
As a result, we believe that ‘redundant-flexible’ is a more appropriate strategy categorisation than
‘proactive-reactive’, as it is practically distinguishable. If we adopt ‘proactive-reactive’ categorisation,
‘collaboration’ closely related to internal/external structure and process is included in both strategies.
‘Redundancy’ closely related to external structure (e.g. multiple sourcing) is also included in both
strategies. Therefore, we cannot clearly explain the difference between proactive and reactive strat-
egies from the viewpoint of organisational design. If we adopt the ‘redundant-flexible’ categorisation,
such problems do not occur.
Organisational fit of the variables in the SSPP framework
Referring to the identification of SSPP variables within SCRM, we match the variables from struc-
ture, process, and performance with redundant and flexible SCRM strategies (see Table 9) to address
the research question.
Referring to Sheffi and Rice Jr. (2005) and Zsidisin and Wagner (2010), ‘redundant’ is defined as a
strategy to limit or mitigate the negative effects of a risk by increasing product availability, while
‘flexible’ is defined as a strategy to build organisational and inter-organisational capabilities to
sense threats to supply continuity and to respond to them quickly. Chang, Ellinger, and Blackhurst’s
(2015) conceptual paper explain the differences between these two strategies on risk contexts and
primary purpose. In low-probability/high-severity risk contexts (e.g. the 9/11 terrorist attack in
New York, Japan’s 2011 earthquake), ‘redundant’ is the optimal strategy to realise reliable and
safe supply. On the contrary, in high-probability/low-severity risk contexts such as transportation
Table 8. Relationships of SCRM strategy elements.
Proactive Reactive
Redundant Redundancy (Hohenstein et al. 2015; Kilubi and Haasis 2015) Redundancy (Hohenstein et al. 2015; Kilubi and
Haasis 2015; Sharma and Bhat 2014; Tukamuhabwa
et al. 2015)
Hedging (Elzarka 2013; Manuj and Mentzer 2008a, 2008b)
Flexible Collaboration (Christopher and Peck 2004; Ghadge, Dani,
and Kalawsky 2012; Hohenstein et al. 2015; Jüttner, Peck,
and Christopher 2003; Kilubi and Haasis 2015;
Tukamuhabwa et al. 2015)
Collaboration (Hohenstein et al. 2015; Kilubi and
Haasis 2015; Tukamuhabwa et al. 2015)
Postponement (Elzarka 2013; Ghadge, Dani, and Kalawsky
2012; Kilubi and Haasis 2015; Manuj and Mentzer 2008a,
2008b; Tang 2006)
Flexibility (Hohenstein et al. 2015; Kilubi and Haasis
2015; Sharma and Bhat 2014; Tukamuhabwa et al.
2015)
Supplier development (Ghadge, Dani, and Kalawsky 2012;
Sharma and Bhat 2014; Tukamuhabwa et al. 2015)
Agility (Christopher and Peck 2004; Tukamuhabwa
et al. 2015; Wieland and Wallenburg 2012)

Table 9. Matching structure, process, and performance with the two SCRM strategies.
Strategy Sources (Comments)
Redundant Flexible
Definition Strategy to limit or mitigate the
negative effects of a risk by
increasing product availability
Strategy to build organisational and inter-
organisational capabilities to sense threats to
supply continuity and to respond to them
quickly
Sheffi and Rice Jr. (2005), Zsidisin and Wagner (2010)
Risk
contexts
Probability Low High Chang, Ellinger, and Blackhurst (2015) (These hypotheses
have not been empirically examined yet.)
Severity High Low
Primary purpose Reliable and safe supply through
redundancy
Greater efficiency in normal situations and
ability to respond quickly to the occurrence
of supply chain risks
Chang, Ellinger, and Blackhurst (2015)
Structure Internal Centralised planning and
decentralised operation
Cross-functional supply chain risk management
teams
Jüttner and Maklan (2011), Norrman and Jansson (2004)
External
(Upstream)
Supply base Dual or multiple supply base; Backup
suppliers
Small (key members) and flexible (easy
switching) supply base; Backup suppliers
Chang, Ellinger, and Blackhurst (2015), Giunipero and
Eltantawy (2004), Hohenstein et al. (2015), Jüttner and
Maklan (2011), Kamalahmadi and Parast (2016), Zsidisin
and Wagner (2010)
Relationship Transactional; Shorter-term Collaborative; Longer-term Bode et al. (2011), Chang, Ellinger, and Blackhurst (2015),
Giunipero and Eltantawy (2004), Mishra et al. (2016)
Dependency/
trust
Lower Higher Bode et al. (2011), Mishra et al. (2016)
Process Internal Information
sharing
Lower Higher (We could not find related articles. Thus, these hypotheses
Collaboration Lower Higher
ICT utilisation Lower Higher
Risk planning High High Wagner and Neshat (2012), Zsidisin and Wagner (2010)
(This hypothesis has not been empirically examined yet.)
External
(Upstream)
Information
sharing
Lower Higher Bode et al. (2011), Mishra et al. (2016), Scholten and
Schilder (2015)
Collaboration Lower Higher Bode et al. (2011), Mishra et al. (2016), Scholten and
Schilder (2015)
ICT utilisation Lower Higher Guarnaschelli, Chiotti, and Salomone (2013), Kauppi et al.
(2016), Lavastre, Gunasekaran, and Spalanzani (2014)
Partner
involvement
Lower Higher Chen, Sohal, and Prajogo (2013), Giunipero and Eltantawy
(2004)
Performance Cost Expensive; Higher capital employed Less expensive, Lower capital employed Chang, Ellinger, and Blackhurst (2015) (These hypotheses
Inventory Deploy significant buffer stocks of raw
materials, components, or finished
products
Generate high-inventory turns and minimise
inventory throughout the chain
Disruption impact Does not decrease as extended supply
chain risk is high (Redundancy does
not moderate the relationship)
Decrease as extended supply chain risk is high
(Flexibility moderates the relationship)
Zsidisin and Wagner (2010)
INTERNATIONAL
JOURNAL
OF
LOGISTICS
RESEARCH
AND
APPLICATIONS
19

breakdowns or temporary infrastructure delays or closures, ‘flexible’ is the optimal strategy to
achieve greater efficiency in normal situations and ability to respond quickly to the occurrence of
supply chain risks.
Supply chain structure is divided into two kinds: internal and external. Regarding internal struc-
ture, there are not many articles that used the construct. As a redundant resource, Jüttner and Mak-
lan (2011) explain a case of a cabling supplier with the combination of centralised planning and
decentralised operation. Ericsson’s case introduced by Norrman and Jansson (2004) is clearly differ-
ent from such a simple structure. At Ericsson, risk management had been handled by a corporate
function. After the fire at a sub-supplier’s plant supplying key parts, which resulted in large-scale
losses, Ericsson developed a new organisation for SCRM called ‘risk management council’. This
organisation is cross-functional supply chain risk management teams including the corporate func-
tion, the SCM/logistics function, the purchasing function, and the different business units. A supply
chain risk manager (SCR manager), placed within the SCM/logistics function, is responsible for the
development and implementation of SCRM by working closely with the council’s members. Supply
chain managers, also placed within the SCM/logistics function, are responsible for the respective
business areas’ supply chains by employing the tools and processes developed by the SCR manager
to analyse, assess, and manage risks in their supply chains. The purchasing department is responsible
for the interfaces with the suppliers and is, therefore, involved in the evaluation of suppliers. The
corporate risk management department has the overall responsibility of risk management in the
Ericsson group, coordinates risk management activities throughout the group, and is in contact
with insurance companies. Such a cross-functional structure wherein many different players are
involved and sharing responsibility would be suitable for firms adopting a ‘flexible’ strategy.
Regarding external structure, most of the selected articles treat upstream one with suppliers. On
‘supply base’, which is the most frequent variable, some conceptual or literature review papers pro-
pose that a dual or multiple supply base is suitable for firms adopting a ‘redundant’ strategy, while a
small (key members) and flexible (easy switching) supply base is desirable for firms adopting a
‘flexible’ strategy (Chang, Ellinger, and Blackhurst 2015; Giunipero and Eltantawy 2004; Hohenstein
et al. 2015; Jüttner and Maklan 2011; Kamalahmadi and Parast 2016). Zsidisin and Wagner (2010)
examine that the variable of ‘dual or multiple supply sources’ is a practice of ‘redundant’ strategy.
The existence of backup suppliers is regarded as both a ‘redundant’ structure (Kamalahmadi and
Parast 2016) and a ‘flexible’ one (Hohenstein et al. 2015). On ‘relationship strength’ and ‘relationship
length’, some conceptual papers propose that firms with a ‘redundant’ strategy adopt transactional,
short-term relationship, while firms with a ‘flexible’ strategy adopt collaborative (closer), long-term
one (Chang, Ellinger, and Blackhurst 2015; Giunipero and Eltantawy 2004). Bode et al. (2011) and
Mishra et al.’s (2016) empirical studies using survey methodology use ‘closer relationship’ as an
observed variable of ‘bridging’ strategy, which is a synonym for ‘flexible’ one. In addition, Mishra
et al. (2016) empirically examine the relationship between ‘dependence’/‘trust’ and SCRM strategy.
Specifically, firms with a ‘redundant’ strategy have a lower dependence and trust with their suppliers,
while firms with a ‘flexible’ strategy have a higher dependence and trust with their suppliers.
Supply chain process is divided into two kinds: internal and external. Regarding external process,
the first and second most frequent variables are ‘collaboration’ and ‘information sharing’. On the
basis of their case studies, Scholten and Schilder (2015) show that ‘information-sharing’, ‘collabora-
tive communication’, ‘joint relationship efforts’, and ‘decision synchronization’ are linked to flexi-
bility. In their survey-based studies, Bode et al. (2011) and Mishra et al. (2016) adopt activities
related to information sharing and collaboration as observed variables of the ‘bridging’ strategy,
which is a synonym for ‘flexible’ one. Thus, in flexible supply chain, the degrees of information shar-
ing and collaboration are relatively higher. In contrast, it may be hypothesised that these degrees are
relatively lower in a ‘redundant’ supply chain. ‘ICT utilization’ such as collaborative supply chain
event management system (Guarnaschelli, Chiotti, and Salomone 2013), collaborative information
systems (Lavastre, Gunasekaran, and Spalanzani 2014), and system coupling (Kauppi et al. 2016)
is more suitable for firms adopting a ‘flexible’ strategy. On ‘partner involvement’, Chen, Sohal,

and Prajogo (2013) adopt activities related to supplier involvement in goal-setting, planning, and
new product development activities as observed variables of ‘supplier collaboration’ in their survey.
Giunipero and Eltantawy (2004) also treat ‘early supplier involvement’ as a practice of risk manage-
ment involving long-term dedication of supply chain members. Therefore, ‘partner involvement’ is
more desirable for firms adopting a ‘flexible’ strategy.
However, there is very little literature on the relationship between the two SCRM strategies and
internal process. As in the case of external process, we propose that firms following a ‘flexible’ strat-
egy may adopt higher degrees of information sharing and collaboration through higher ICT utilis-
ation, while at firms following a ‘redundant’ strategy, the degrees of such activities are lower. These
hypotheses need to be empirically examined. In particular, firms adopting a ‘flexible’ strategy are
expected to utilise not only existing SCM-related ICT such as advanced planning system (APS)
with planning function and enterprise resource planning (ERP) with integrating function but also
advanced ICT realising tracking, tracing, monitoring, warning, reporting, and predicting functions
of supply chain risk. Exceptionally, we think that the importance of ‘risk planning’, which is the most
frequent variable, is no difference between ‘redundant’ and ‘flexible’ strategies. Zsidisin and Wagner
(2010) statistically examine that the variable of ‘supply continuity/contingency plans’ is a practice of
‘redundant’ strategy. On the other hand, Wagner and Neshat (2012) statistically examine that both
‘collaboration with customers and suppliers’, which is suitable for ‘flexible’ strategy, and ‘elaborating
business continuity or contingency plans’ are observed variables of the same latent variable, that is,
‘supply chain risk planning’. Thus, regardless of the SCRM strategy, it may be hypothesised that the
degree of ‘risk planning’ is high. This hypothesis also needs to be empirically examined.
Finally, regarding performance, we use operational performance because a majority of the articles
has adopted it rather than business performance. Based on the extant literature, Chang, Ellinger, and
Blackhurst (2015) propose the differences on efficiency indicators, that is, ‘cost’ and ‘inventory’
between the two SCRM strategies. Specifically, firms adopting the ‘redundant’ strategy implement
expensively, employ higher capital, and deploy significant buffer stocks of raw materials, com-
ponents, or finished products. In contrast, firms adopting the ‘flexible’ strategy implement less
expensively, employ lower capital, generate high-inventory turns, and minimise inventory through-
out the chain. These hypotheses need to be empirically examined. Zsidisin and Wagner’s (2010) sur-
vey-based study is a unique paper that statistically examines the effects of the two SCRM strategy on
‘disruption impact’. As introduced previously, they measure the latent variable called ‘disruption
occurrence’ using observed variables such as ‘late delivery’, ‘quality problem’, and ‘excess costs’.
They found the following results. Specifically, as extended supply risk (e.g. transportation disrup-
tions, natural disasters, and political instability) is high, high flexibility leads to a decrease of disrup-
tion occurrence, while high redundancy does not lead to the same performance. In other words,
flexibility moderates the relationship between extended supply risk and disruption occurrence,
while redundancy does not. As mentioned earlier, ‘disruption impact’ has not been aggregated to
a specific index yet. We need to further examine the relationship between the two SCRM strategies
and other performance indicators.
Conclusion
This study identified 36 variables pertaining to SCRM strategies, internal and external structure,
internal and external processes, and operational and business performance for the SSPP framework.
These variables were identified from 174 articles from the EBSCO, ScienceDirect, and Scopus data-
bases from 2001 to 2017. Following the SSPP framework, we match these variables to explore new
areas for academic research and to provide practical solutions to managers. For example, we suggest
that if a firm deals with low probability but high severity risks, it may adopt a redundant strategy. Its
internal structure may rather adopt centralised planning and decentralised operations, while its
external structure may adopt dual or multiple supply bases. The firm’s internal and external pro-
cesses may include high-risk planning and lower partner involvement (compared with flexible

strategy). The performance implications for the firm may be higher than its capital costs. Conversely,
if the firm adopts a flexible strategy, it may expend more on internal and external processes but may
be compensated by improved cost and inventory performance. These conceptual findings of our lit-
erature review are novel but require further empirical examination.
Academic contributions
There are three contributions of this study. Firstly, this study firstly presents an SLR using the SSPP
framework to propose a new framework of SCRM from the viewpoint of organisational fit. We
demonstrate that the SSPP framework is relevant in SCRM research, but conceptual and empirical
studies that discuss the relationships among strategy, structure, process, and performance in the field
of SCRM are insufficient. We therefore propose a new conceptual framework for it (Table 9).
Secondly, we identified that prior SLR papers have predominantly studied the construct of SCRM
strategy only (Thomé et al. 2016), fragmentally mentioned the constructs of strategy, structure, and
process (Colicchia and Strozzi 2012; Datta 2017; Durach, Wieland, and Machuca 2015; Ghadge,
Dani, and Kalawsky 2012; Zhu, Krikke, and Caniels 2017), and proposed management elements
that confuse structure and process for both proactive (or preventive) and reactive (or responsive)
strategies (Ali, Mahfouz, and Arisha 2017; Hohenstein et al. 2015; Kilubi and Haasis 2015; Kilubi
2016; Tukamuhabwa et al. 2015). In addition, non-SLR literature have not treated the SSPP con-
structs holistically (Ho et al. 2015; Tang and Musa 2011), not focused on the relationship between
strategy and structure/process (Kamalahmadi and Parast 2016), or the constructs of strategy, struc-
ture, and process together (Bandaly et al. 2012; Bandaly et al. 2013; Khan and Burnes 2007). Thus, as
far as we are aware, this is the first SLR study on the organisational design in the SCRM context. The
SSPP framework on SCRM (Table 9) suggests suitable structure/process and targeted performance
by the two SCRM strategies, that is, redundant and flexible. As shown in Table 5, the most part of
prior SCRM literature have separately treated strategy, structure, process, and performance, but not
mentioned the relationships among them. Using this SCRM framework, researchers may discuss
how to fit different risk strategies, management structures and processes together to create better
SCRM performance in a more comprehensive way.
Finally, we suggest that ‘redundant-flexible’ is a more appropriate strategy categorisation than
‘proactive-reactive’. In the process leading to this conclusion, we have organised the relationships
of the main strategy elements in a matrix of proactive-reactive and redundant-flexible (Table 8).
It would be useful to aggregate SCRM strategies that are rich in variety.
Practical implications
Our new SCRM framework in Table 9 has several important implications for practitioners. As
described in the introduction, many firms’ executives do not feel that they manage supply chain
risk effectively. For example, they face challenges in implementing SCRM strategies and acceptable
cross-functional collaboration. Our framework implies that firms should match management
elements such as structure and process with the SCRM strategy adopted. Specifically, a redundant
strategy is suitable for firms with a low-risk probability and a high-risk severity. This strategy
could be appropriate for such firms to conduct a lower level of internal information sharing, collab-
oration, and ICT utilisation on the basis of a decentralised operation structure. External information
sharing, collaboration, ICT utilisation, and partner involvement are also lower on the basis of short-
term, transactional, low dependent relationship. That is, a high level of internal and external colla-
borative activities may not be necessary for such firms if they have dual or multiple supply bases.
Alternatively, a flexible strategy is suitable for firms with a high-risk probability and a low-risk
severity. Firms adopting this strategy need to organise cross-functional supply chain risk manage-
ment teams and conduct a higher level of internal information sharing, collaboration, and ICT util-
isation. External information sharing, collaboration, ICT utilisation, and partner involvement are

also higher on the basis of small supply base and long-term, collaborative, high dependent relation-
ship while flexible supply base, that is, easy switching, in the case of emergency. If firms build such
organisational and inter-organisational capabilities, they can mitigate supply chain disruption
impacts while achieving operational efficiencies.
Future research and limitations
Future research will need to conduct empirical studies to examine our newly proposed SCRM frame-
work. Some hypotheses on the relationship between the two SCRM strategies and risk contexts;
internal process matching with these strategies; and the impact of linkage among strategy, structure,
and process on performance, have not been empirically verified. Further, our conclusion does not
propose the mechanisms that firms match their structure/process with the two SCRM strategies.
We expect to conduct a case study that explores how high-performance firms with SCRM realise
a fit among strategy, structure, and process in its supply chain. Such empirical studies will give us
an in-depth understanding of the complex phenomena of SCRM.
Similar to other SLR studies, we also have some study limitations. In particular, our SLR does not
include ‘grey literature’. According to the guidelines of Adams, Smart, and Huff (2017), SLR
researchers need to include grey literature as supplementary and complementary evidence when
potentially relevant findings are not reported adequately in academic articles. In our SLR, there
was, for example, a limited number of articles on internal structure. By including grey literature –
such as practitioners’ articles, business press reports, consultancy reports, and think-tank reports
– we may improve the findings concerning internal structure and develop the understanding of
structural properties matching with each SCRM strategy, whether redundant or flexible.
Furthermore, while locating the studies, we used comprehensive sets of keywords that combined
‘management’ and ‘risk’ concepts to search for articles across the different databases. By using the
keywords identified from a title, abstract, and keywords, we generated more than 50,000 articles,
which would be an unmanageable number in the SLR approach. We therefore limited our study
to the keywords identified in titles only. This limits our study to articles specific to the focus of
this study and made the number of articles manageable to the authors, who reviewed the abstracts
of 1497 identified articles.
Disclosure statement
No potential conflict of interest was reported by the authors.
Funding
This work was supported by Grant-in-Aid for Scientific Research (C) [Grant Number 17K07968] and the National
Research Foundation of Korea Grant funded by Korean Government (MOE) [Grant Number NRF-
2016S1A2A2912137].
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A Systematic Review On Supply Chain Risk Management Using The Strategy-Structureprocess-Performance Framework

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