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A Cloud-based Supply Chain Management System: Effects on
Supply Chain Responsiveness
Abstract
Purpose: Despite the ongoing calls for the incorporation of the cloud utility model, the effect of
the cloud on elements of supply chain performance is still an evolving area of research. In this
paper, we develop the architecture of a cloud-based supply chain management (C-SCM) ecosystem
and explore how it enhances supply chain responsiveness.
Design/methodology/approach: First, we discuss the potential benefits that cloud computing can
yield compared to existing mature SCM information systems and solutions through a
comprehensive literature review. We conceptualize SCR in terms of the level of visibility in the
supply chain, supply chain flexibility, and rapid detection and reaction to changes and then we
build the detailed architecture of a cloud based SCM system. The proposed ecosystem introduces
a view of SCM and the associated practices when transferred to cloud environments. The potential
to enhance SCR through the cloud is explored with scenarios on a case of supply chain operations
in fashion retail industry.
Findings: Our findings show that the proposed system can enhance all three dimensions of SCR.
Implications for supply chain practice and how companies can migrate to a cloud supply chain are
drawn.
Originality/Value: Given that the development, creation, and delivery of goods and services is
increasingly becoming a joint effort of several parties in a supply chain, we contribute to existing
literature, by introducing a comprehensive cloud-based SCM system and show how companies
can enhance their supply chain responsiveness.
Keywords: Supply Chain Responsiveness; Cloud-based approach; Case Study
1. Introduction
The production and delivery of products or services in a timely fashion and at a minimum total
cost is one the critical objectives for many companies (Christopher, 2016). The adoption of lean
management practices strategies can yield positive outcomes, but the global supply chains of today
are not sufficiently responsive to satisfy the requirements for short lead times needed by lean
strategies (Reichhart & Holweg, 2007). With the substantial advances in Information Technology
(IT) and digital communication platforms over the past decade, there is a growing awareness that
supply chain performance could be improved with the successful adoption of such technologies
(Qrunfleh and Tarafdar, 2014; Hsu et al., 2014; Dwivedi and Mustafee, 2010).
The commercialisation of cloud computing may provide solutions towards these challenges. Cloud
systems turn computing resources (e.g. networks, servers, storage, applications) into a general
utility that can be leased and released by users through the internet in an on-demand manner (Wang,
2012; Mezgár, and Rauschecker, 2014). The shared pool of IT resources are virtualised, allowing
for dynamic reconfiguration, according to various degrees and volumes of user requirements
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(Durowoju et al., 2011). In this way they can serve a wide range of geographically dispersed users,
lead to lower costs of ownership and maximise scalability and rapid deployment (Cegielski et al.,
2012).
Academic studies recognise the potential of cloud computing and suggest their adoption to
improve business performance. Marston et al. (2011) and Garrison et al. (2015) provide a
comprehensive analysis of the business benefits of cloud computing and several recommendations
for policy makers to facilitate the technology, Durowoju et al. (2011) investigate how cloud
computing system can enhance security and scalability of operations and Yang et al. (2015) show
how cloud based systems can enhance performance of complex service operations in healthcare.
Despite the ongoing calls for the incorporation of cloud systems, little research has been
undertaken to explore the effect of cloud systems on elements of supply chain performance
(Bayramusta and Nasir, 2016; DeGroote and Marx, 2013). Given that the development, creation
and delivery of goods and services is increasingly becoming a joint effort of several parties in a
supply chain, we develop the architecture of a cloud based SCM system (CSCM) and explore how
its utilisation can enhance supply chain responsiveness (SCR).
The remainder of the paper is structured as follows. In section 2, we briefly present the fundamental
principles and capabilities of cloud technology and discuss the implications that its adoption can
have on supply chain responsiveness (SCR). We conceptualise SCR in terms of the level of
visibility in the supply chain, supply chain flexibility, and rapid detection and reaction to changes.
In this section we also provide an overview of the growing literature on cloud-based approaches
to supply chain phenomena and draw the main differentiators of C-SCM concerning conventional
supply chain information systems. In section 3 we present the architecture of the proposed C-SCM
system with the use of mature modules, to ensure its compatibility with existing technologies. We
provide a detailed description of each module. In section 4 we explore the utility of the proposed
system with two case studies and consider the effects on SCR. The paper concludes with a
discussion of the contribution and limitations of the study and potential extension of the research.
2. Literature Review
Over the past decade, the long-held dream of computing as a utility of Ambrust et al (2010) and
Sharif (2010), and its disruptive potential to transform a large part of the IT industry (Buyya et al.,
2008; Fox, 2009; Yeo et al., 2009; El Kadiri et al., 2016), has attracted high interest by enterprises.
The cloud disruptive business model (Kiss et al., 2015) of making software as a service and
forming the way IT hardware is designed and purchased; has increased the potentialities to reshape
the way enterprises acquire and manage their computing requirements (El-Gazzar, 2014;
Alshamaila et al., 2013; Armbrust et al., 2010). In line with the shared services, cloud computing
is considered an innovative model for IT sourcing that generates value for the adopting enterprises
(Schneider and Sunyaev, 2016). Garisson et al. (2012; 2015) referring to cloud highlight the fact
that productivity can be increased as the enterprises are able to focus on their core business
activities; additional benefits could be the scalability, flexibility, agility, and simplicity offered to
the adopting enterprises (Garrison et al., 2012; Venters and Whitley, 2012).
Cloud computing has been given numerous definitions (Schneider and Sunyaev, 2016; El-Gazzar,
2014; Alshamaila et al., 2013; Marston et al., 2011). However, the widely known definition of
cloud computing is the one given by the National Institute of Standards and Technology (NIST).
The NIST defines cloud computing as “a model for enabling convenient, on-demand network
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access to a shared pool of configurable computing resources (e.g., networks, servers, storage,
applications, and services) that can be rapidly provisioned and released with minimal
management effort or service provider interaction”(Mell and Grance, 2011).
NIST recognises two primary actors in the cloud context: a) the Cloud Service Provider and b) the
Cloud Service Consumer, there is also the Cloud Service Broker involved in a few cases (Hogan
et al., 2011). Cloud service providers offer various service models depending on the enterprise’s
requirements, whereas the basic service models are providing three types of services (Mell and
Grance, 2011; Senyo et al., 2018) infrastructure, platform, and software services in a pay-as-you-
go manner via the internet (Mahmood and Hill, 2011). Each layer is encapsulated as a service to
respond to the layer above (Dhar, 2012; Zhang et al., 2010).
• Software as a Service (SaaS) offers the capability of providing hosted applications over the
internet in an on-demand manner (Mahmood and Hill, 2011). With SaaS, users do not need to
install applications or services into their own computers but directly them online.
• Platform as a Service (PaaS) offers the capability of the consumer to deploy onto the cloud
infrastructure consumer-created or acquired applications created using programming
languages, libraries, services, and tools supported by the provider (Hogan et al., 2011). This
provides clients or third parties with designing, developing and deploying their own
applications (Mahmood and Hill, 2011). Instead of end users, IT staff and developers in third
parties are the typical consumers of PaaS services (Baun, 2011).
• Infrastructure as a Service (IaaS) offers the capability of provisioning computing services in
the form of storage, processing capability, network connectivity, virtual machines and other
relevant services where the consumer is able to deploy infrastructure and run applications
(Zhang et al., 2010).
One of the challenges for the cloud infrastructure as most of the novel technological advancments
is around their adoption (Williams et al, 2015, Dwivedi and Mustafee, 2010). The cloud adoption
literature (Alshamaila et al., 2013; Garrison et al., 2012; Armbrust et al., 2010) reports that at the
enterprise level, cloud adoption processes vary depending on the layer (SaaS, PaaS, IaaS), the
cloud deployment models and the characteristics of the specific firm (size, industry, etc.). In spite
of its appealing benefits for enterprises, cloud computing raises serious technical, economic,
ethical, legal, and managerial issues (Sultan, 2011; 2013; 2014; Walterbusch et al., 2017). The
cloud literature focuses more on the associated technical issues of with less attention paid to
business issues regarding the adoption of cloud (Lian et al, 2014; Brender & Markov, 2013). A
wider consideration of the challenges and risks should be taken into attention before switching to
a cloud infrastructure (Lian et al., 2014; Hsu et al., 2014).
2.1 Supply Chain Responsiveness (SCR)
There is a profusion of different definitions and dimensions of supply chain responsiveness (SCR)
in the literature. SCR refers to the ability of a supply chain to respond to market demand in time
effective manner (Christopher, 2016). SCR has been classified according to several dimensions,
such as customer sensitivity (Van Hoek et al., 2001), demand transparency (Catalan and Kotzab,
2003), supply chain response lead-time (Holweg, 2005), agility (Blome et al., 2013), flexibility
(Kim et al., 2013), information sharing (Handfield and Bechtel, 2002). The underlying themes that
are common to the majority of classifications found in the literature of SCM can be classified into
three fundamental dimensions of SCR. The recent study of Gonul Kochan et al. (2018), has
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highlighted multiple challenges of the SCR and tried to show that cloud-based information sharing
improves the SC visibility in healthcare supply chains and therefore improving the whole SCR.
SCR denotes the speed of supply chain to deliver demand and can be measured in terms of order
fulfillment cycle time (Supply Chain Council, 2012). If customer demand can be perceived without
distortions and latencies, then companies have more chances to fulfill the orders successfully. The
visibility of information across the supply chain is, therefore, a principal dimension of SCR as it
increases demand sensibility by allowing every organisation along the supply chain to access the
required information with transparency (Chengalur-Smith et al., 2012; Singh, 2015).
The inherent uncertainty of supply and demand and associated supply chain risks stipulate the
need to be able to swiftly change the product mix, volume, delivery sequence, and supply capacity.
Rapid detection of supply chain risks and swift decisions to mitigate them can, therefore, enhance
SCR. Therefore, the second dimension of SCR is the rapid detection and reaction to supply chain
risks.
The third dimension lies in the capability of a supply chain to demonstrate significant flexibility
to adapt to demand uncertainty by restructuring its operations, reconfiguring its capabilities, or
realigning its strategic objectives (Reichhart & Holweg, 2007). Information integration amongst
supply chain partners can enhance supply chain process integration and flexibility through joint
planning, decision-making, and execution in a standard system. An IT system that is able to
reconfigure dynamically supply chain processes according to the changing requirements can
enhance supply chain flexibility. A modularised and service-oriented architecture can enhance the
overall system flexibility by enabling rapid system integration and process configuration
(Sambamurthy et al., 2003).
In traditional models of Information Technology and Systems such as enterprise resource planning
(ERP), supplier relationship management (SRM), and customer relationship management (CRM);
supply chain efficiency is promoted, the timeliness is increased, and accuracy of shared
information is confirmed as well as the coordination and collaboration are improved (Kumar et al.,
2017; Fayoumi, 2016). However, their benefits are often limited only in a single organisation, or
a limited part of the supply chain (Verwijmeren, 2004). Their organisation-central architecture
often increases the complexity and costs to exchange information with trading partners and has
less flexibility to accommodate changes in supply chain structure (Poirier, 2003; Fayoumi, 2016).
In order to achieve end-to-end visibility and high-level collaboration, the SCM application system
should cover several participants of a supply chain. Furthermore, with the on-premise deployment
mode, traditional integration represents a point-to-point pattern, which requires extensive
integration interfaces between each organisation and its partners. The use of Radio Frequency
Identification (RFID) technology can provide a solution to some of these issues by enabling real-
time visibility, eliminating the latency introduced by human intervention, thus increasing
responsiveness. However, challenges such as implementation cost (Lee and Park, 2010), replacing
tracking system, different standards, (Ngai and Gunasekaran, 2009), voluminous data processing,
and timely decision-making (Tiwari et al., 2013) limit its full deployment for SCM
2.2 Cloud-based Approaches: Implications for Supply Chain Responsiveness
Within a manufacturing context, cloud utility model is increasingly gaining attention within the
recent years as one of the major enablers for the manufacturing industry (Babiceanu and Seker,
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2016; Helo et al., 2014; Shamsuzzoha et al. 2016; Schniederians et al., 2016). Industrial
applications of the cloud are often addressed within manufacturing literature under the term of
‘cloud manufacturing’ (Helo and Hao, 2017); which is defined as the “model for enabling
ubiquitous, convenient, on-demand network access to a shared pool of configurable
manufacturing resources” (Xu, 2012). Cloud-based operations management allows firms to
request various services ranging from product design, manufacturing, testing, management, and
all other stages of a production planning and lifecycle management (Wu et al., 2013; Xu, 2012).
Cloud service models share five common essential characteristics that distinguish cloud from other
computing technologies (Mell and Grance, 2011) namely: a) on-demand self-service, b) broad
network access, c) resource pooling, d) rapid elasticity and e) measured service. These
characteristics can be extended to the many implications for the Supply Chain Responsiveness
(SCR) context as it is described in Table 1.
Table 1 - Implications of Cloud in Supply Chain Responsiveness
Cloud
characteristics
Description Implications for Supply Chain Responsiveness
On-demand
self-service
The consumer can unilaterally
provision computing capabilities,
such as server time and network
storage, as needed automatically
without requiring human
interaction with each service
provider.
• IT capital expenses can become operational expenses
by
renting an SCM
system based on usage rather than purchasing
infrastructures and applications licenses. In that way,
costs
become more variable and more in line with revenues
(Jones
& Schramm, 2011).
•
By outsourcing maintenance and technical support to a cloud
service provider, organisations
do not need to hire dedicated
technical staff to support the system
(Schneider and Sunyaev,
2016).
Broad network
access
The capabilities are available
over the network and accessed
through standard mechanisms
that promote use by
heterogeneous thin or thick client
platforms (e.g., mobile phones,
tablets, laptops, and
workstations).
• The organisation
only needs to plug into the cloud, then it can
exchange necessary information and collaborate (processes
orchestration) with all its partners through heterogeneous
platforms (
Jede & Teuteberg, 2016; Shamsuzzoha et al.,
2016; Chengalur-Smith et al., 2012).
• The cloud integration interface supports open standard and
multiple data formats (e.g., EDI, XML, flat files), thus
facilitating rapid integration and real-time information
sharing (Helo et al., 2014).
• Advanced processing and storage capabilities to manage
supply chain requirements and transactions (Zhang et al.,
2014).
• Advanced techniques to understand and process variation of
demand and respond promptly (Zhang et al., 2010).
