An exploratory study of Internet of Things (IoT) adoption intention in logistics and supply chain management. A mixed research approach

Published date12 February 2018
Date12 February 2018
DOIhttps://doi.org/10.1108/IJLM-11-2016-0274
Pages131-151
AuthorMengru Tu
Subject MatterManagement science & operations,Logistics
An exploratory study of Internet
of Things (IoT) adoption intention
in logistics and supply
chain management
A mixed research approach
Mengru Tu
Department of Transportation Science,
National Taiwan Ocean University, Keelung, Taiwan
Abstract
Purpose The Internet of Things (IoT) envisions a global infrastructure of networked physical objects that
render radical transparency to supply chain management. Despite the perceived advantages of IoT, industry
has still not widely adopted IoT-enabled logistics and supply chain management. The purpose of this paper is
to understand the incentives and concerns behind firmsdecisions to adopt IoT, explore the determinant
factors affecting IoT adoption in logistics and supply chain management.
Design/methodology/approach This study uses mixed methods research to explore the determinants of
IoT adoption intention in logistics and supply chain management. Qualitative analysis using the Grounded
Theory methodology reveals the underlying perceptions regarding logistic innovation with IoT. Quantitative
hypotheses are then developed based on qualitative investigation and adoption literature. Survey data were
collected from the managerial staff of Taiwanese firms across various industries. Structural equation
modeling with partial least square is used for data analysis.
Findings The results of the qualitative study identify uncertainties and issues regarding firmsintention to
accept or reject IoT technology in logistics and supply chain management, including the benefit and cost
aspects of adopting IoT, uncertainties about the trustworthiness of IoT technology, and the external
motivating force to embrace IoT. The resulting quantitative model shows that perceived benefits, perceived
costs, and external pressure are significant determinants of IoT adoption intention, while technology trust is
not. However, technology trust does indirectly influence IoT adoption intention through perceived benefits.
Practical implications The empirical findings of this study provide some guidelines for logistics and
supply chain managers to evaluate IoT adoption in their firms. Likewise, IoT solution providers can also
benefit from this study by improving their solutions to mitigate the IoT adoption concerns addressed herein.
Originality/value This paper is among the first known to examine IoT adoption intention in logistics and
supply chain management using mixed methods research. The mixed methods approach offers a better
insight in understanding incentives behind firmsdecisions to adopt IoT vs the use of either a qualitative or
quantitative method alone.
Keywords Internet of Things, RFID, Mixed method, Asia, Logistics and supply chain management,
IoT adoption intention, Mixed research approach
Paper type Research paper
1. Introduction
The Internet of Things (IoT) has inspired many innovative applications of logistics and
supply chains in recent years and will have far-reaching influences on future supply chain
management. The ideal IoT vision is that each object has its own digital object identifier
(Gershenfeld et al., 2004), and it is now achievable to create a global network with objects as
the infrastructure through IoT (Kortuem et al., 2010). The goal of IoT is to create a global
network infrastructure to facilitate the easy exchange of commodities, services, and
information (Liu and Sun, 2011). The application of IoT technology in the industry, such as
manufacturing and supply chains, is also known as Industrial IoT (IIoT) (Li et al., 2014).
IoT or IIoT has been applied by some enterprises to assist in the collection of on-site
real-time information, which has successfully improved and promoted operating efficiency.
The International Journal of
Logistics Management
Vol. 29 No. 1, 2018
pp. 131-151
© Emerald PublishingLimited
0957-4093
DOI 10.1108/IJLM-11-2016-0274
Received 23 November 2016
Revised 28 March 2017
7 July 2017
Accepted 31 July 2017
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0957-4093.htm
131
Logistics and
supply chain
management
The innovation of IoT benefits companies in fields related to logistics and affects the
operations of enterprises (Grawe, 2009). Although the overall expenditures of IoT hardware,
such as RFID tags and readers, have dropped significantly in recent years, many firms still
hold hesitant and conservative attitudes toward the application of IoT in supply chain
management. The aim of this paper is thus to explore what factors affect an enterprises
adoption intention of IoT in logistics and supply chain management.
Studying logistics innovation adoption across a supply chain, such as for IoT, is a
relatively new and complex issue. Most studies on IoT or logistics innovation adoption use
only a single research method. In contrast, the mixed research method employs quantitative
and qualitative research methods, either concurrently or sequentially, to understand a
research topic of interest (Venkatesh et al., 2013). Even as the single-method (qualitative or
quantitative alone) approach might be insufficient to describe the complex decision behavior
of IoT technology adoption across multiple supply chain organizations, there are few mixed
research studies in the literature. Although information system (IS) research communities
encourage methodological diversity, there is a scarcity of IS research using mixed research
methods (Venkatesh et al., 2013). Similarly, mixed methods research is rarely used in supply
chain management-related disciplines (Golicic and Davis, 2012). Thus, there is an excellent
opportunity to advance the research discipline by using mixed research methods, which
offer a good avenue to understand and explain how a supply chain strategy is implemented
across organizations interconnected in the supply chain (Golicic and Davis, 2012). Detailed
guidelines for mixed research methods in supply chain management and IS can be
referenced in Golicic and Davis (2012) and Venkatesh et al. (2013), respectively.
The following sections will address this research gap and further explicate the merits for
the use of mixed research methods in studying IoT adoption. This paper explores the key
factors that influence the adoption of IoT in logistics and supply chain management from
the perspective of empirical research using the mixed research method, which combines
qualitative research and quantitative research. Thus, this study is divided into two parts.
The first part is qualitative research, which looks at the perception of Taiwanese enterprises
regarding IoT technology from multiple perspectives through in-depth interviews of
Taiwanese executives. The second part uses questionnaire survey and quantitative analysis
to explore the key factors affecting the adoption of IoT by enterprises in logistics and supply
chain management.
The remainder of this paper is organized as follows. Section 2 reviews related works
about IoT-enabled supply chain and previous literature concerning research methods for
IoT adoption. Section 3 describes the mixed research methodology for this study. Section 4
discusses the qualitative research process and presents the research findings. Section 5 sets
up the quantitative research model and hypotheses and then shows data analysis and
research findings. The last section offers discussions and conclusions.
2. Related studies for IoT-enabled supply chain and IoT adoption
2.1 IoT-enabled supply chain
Massachusetts Institute of Technology established the Auto-ID Center in 1999 and
proposed the infrastructure of the electronic product code (EPC) encoding scheme and
EPCglobal Network to ensure the interconnectedness of radio frequency identification
(RFID) in the supply chain (Thiesse et al., 2009). The design of the EPC Code applies to all
products across the globe, where all codes are unique, and each object (product) has its
own EPC Code; IoT has many choices in product tagging, such as Barcode or RFID
technology, and RFID tagging is often used with EPC encoding scheme. RFID readers
retrieve the information from a RFID tag through radio waves, with no line of sight
operation, which allows for batch scanning of products. Compared with barcode
technology, RFID technology can repeatedly write data into the memory blocks of a tag,
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