Big data and predictive analytics in humanitarian supply chains. Enabling visibility and coordination in the presence of swift trust

Date14 May 2018
Published date14 May 2018
Pages485-512
DOIhttps://doi.org/10.1108/IJLM-02-2017-0039
AuthorRameshwar Dubey,Zongwei Luo,Angappa Gunasekaran,Shahriar Akter,Benjamin T. Hazen,Matthew A. Douglas
Subject MatterManagement science & operations,Logistics
Big data and predictive analytics
in humanitarian supply chains
Enabling visibility and coordination in the
presence of swift trust
Rameshwar Dubey
Montpellier Business School, Montpellier, France
Zongwei Luo
Department of Computer Science and Engineering,
Southern University of Science and Technology, Shenzhen, China
Angappa Gunasekaran
Department of Decision and Information Sciences, Charlton College of Business,
University of Massachusetts Dartmouth, North Dartmouth,
Massachusetts, USA
Shahriar Akter
School of Management, Operations and Marketing,
University of Wollongong, Wollongong, Australia
Benjamin T. Hazen
Department of Operational Sciences, Air Force Institute of Technology,
Wright-Patterson Air Force Base, Ohio, USA and
Department of Marketing and Supply Chain Management,
University of Tennessee, Knoxville, Tennessee, USA, and
Matthew A. Douglas
Department of Operational Sciences, Air Force Institute of Technology,
Wright-Patterson Air Force Base, Ohio, USA
Abstract
Purpose The purpose of this paper is to understand how big data and predictive analytics (BDPA), as an
organizational capability, can improve both visibility and coordination in humanitarian supply chains.
Design/methodology/approach The authors conceptualize a research model grounded in contingent
resource-based view where the authors propose that BDPA capabilities affect visibility and coordination
under the moderating effect of swift trust. Using ordinary least squares regression, the authors test the
hypotheses using survey data collected from informants at 205 international non-government organizations.
Findings The results indicate that BDPA has a significant influence on visibility and coordination. Further,
the results suggest that swift trust does not have an amplifying effect on the relationships between BDPA and
visibility and coordination. However, the mediation test suggests that swift trust acts as a mediating
construct. Hence, the authors argue that swift trust is not the condition for improving coordination among the
actors in humanitarian supply chains.
Research limitations/implications The major limitation of the study is that the authors have used
cross-sectional survey data to test the research hypotheses. Following Guide and Ketokivi (2015), the authors
present arguments on how to address the limitations of cross-sectional data or use of longitudinal data that
can address common method bias or endogeneity-related problems.
Practical implications Managers can use this framework to understand: first, how organizational
resources can be used to create BDPA, and second, how BDPA can help build swift trust and be used to
improve visibility and coordination in the humanitarian supply chain.
Originality/value This is the first research that has empirically tested the anecdotal and conceptual
evidence. The findings make notable contributions to existing humanitarian supply chain literature and may
be useful to managers who are contemplating the use of BDPA to improve disaster-relief-related activities.
The International Journal of
Logistics Management
Vol. 29 No. 2, 2018
pp. 485-512
© Emerald PublishingLimited
0957-4093
DOI 10.1108/IJLM-02-2017-0039
Received 15 February 2017
Revised 8 March 2017
Accepted 13 March 2017
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0957-4093.htm
485
BDPA in
humanitarian
supply chains
Keywords Big data, Information exchange, Coordination, Supply chain management, Predictive analytics,
Confirmatory factor analysis, Resource-based view, Humanitarian supply chain, Humanitarian operations,
Swift trust, Contingent resource-based view, Regression analysis
Paper type Research paper
1. Introduction
Natural and human-made disasters continue to impact society. In 2013, natural disasters
alone cost society more than 192 billion USD (Caulderwood, 2014). The impacts of natural
disasters on human lives and property can be partially attributed to poor management of
relief efforts in the aftermath of an event (Altay, 2008; Soneye, 2014). Major losses can result
from a lack of coordination among humanitarian supply chain actors, which results in
inadequate response in affected areas (Noori et al., 2016).
The complexity of humanitarian supply chains has attracted serious attention from
academics and practitioners (Beamon and Kotleba, 2006; Kovács and Tatham, 2009; Kovacs
and Spens, 2011; Oloruntoba et al., 2017). Benini et al. (2009) argued that survivor
needs assessment is the most important aspect of managing complex disaster relief efforts.
However, information regarding survivor needs or alternative routes leading to affected
areas is often not available (Swanson and Smith, 2013). Therefore, disaster relief teams are
often unable to reach affected areas in time, making getting relief to survivors difficult
(Altay, 2008). Additionally, humanitarian supply chains are often hastily formed due to the
unpredictable nature of the events (Tatham and Kovacs, 2010). Because of these factors, the
design of humanitarian supply chains can be more complicated than the design of
commercial supply chains.
Coordination and collaboration in humanitarian supply chains have been the subject of
debate among humanitarian actors and their workers engaged in disaster relief operations
(Van Wassenhove, 2006; Balcik et al., 2010; Moshtari, 2016; de Camargo et al., 2017). In the
literature, however, the terms coordinationand collaborationare often used
interchangeably. Coordination is often limited to the sharing of information and resources,
whereas collaboration is usually concerned with working together to create something new
(see Balakrishnan and Geunes, 2004; Tsanos et al., 2014; Raue and Wieland, 2015). Hence, in
our study, we restrictour focus to coordination, rather thancollaboration, among actors in the
humanitarian supply chain.
Akhtar et al. (2012) argue that coordination among humanitarian actors is one of the
most critical factors in the overall success of the disaster relief operations. Kabra and
Ramesh (2015) further argue that poor coordination among humanitarian actors often
increases suffering due to a resulting mismatch between demand and supply. Humanitarian
supply chains must avoid duplication of resources and services, whether by filling gaps or
preventing overlaps, and ensure that various organizations are synchronized to achieve a
common objective, thereby enabling a more coherent, effective, and efficient response
(Gillmann, 2009). Akhtar et al. (2012) further note that tangible resources (e.g. finance,
technology, and people) and intangible resources (e.g. leadership, extra efforts, relevant
experiences and education, relationship management skills, research abilities, and
performance measurement techniques) are imperative to ensure coordination among
actors involved in disaster relief operations.
Following Kanda and Deshmukhs (2008) and Akhtar et al.s (2012) arguments, effective,
efficient coordination requires each link of the supply chain to share information and take
into account the impact its actions have on other stages. A lack of coordination is often due
to conflict among the humanitarian actors resulting from information asymmetry and a lack
of trust (Tatham and Kovacs, 2010; Akhtar et al., 2012; Altay and Pal, 2014). Hence,
improving information visibility and accuracy can perhaps improve coordination among
humanitarian supply chain actors (Akhtar et al., 2012). Research has broadly discussed the
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