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Please cite original: Serkan Karakas, Avni Zafer Acar & Berk Kucukaltan (2021) Blockchain
adoption in logistics and supply chain: a literature review and research agenda, International Journal of
Production Research, DOI: 10.1080/00207543.2021.2012613
Blockchain Adoption in Logistics and Supply Chain: A Literature Review
and Research Agenda
Abstracts
The supply chain is an important source of knowledge that enables potential emerging technologies
and, in this ecosystem, logistics are regarded as an intermediary for disseminating innovative solutions
in a coordinated manner. As an emerging solution in the supply chain area, blockchain has recently
been discussed as a disruptive technology and has received growing attention from academics and
practitioners. Despite this interest, insufficient knowledge on the potential benefits and risks of
blockchain technology causes vagueness for its successful implementation. Therefore, since effective
management of logistics and supply chain operations through advanced solutions is of utmost
importance, adopting an innovative approach rather than providing anectodal evidences or narrative
expressions plays a critical role in blockchain adoption. Accordingly, this research aims to an in-depth
analysis of the blockchain in logistics and supply chain by investigating enablers, barriers, and risks of
this adoption. To this end, through employing both the Methodi Ordinatio and the narrative network
analyses, the future direction of blockchain adoption is presented in light of the presented current state
of knowledge. Consequently, the obtained findings offer academic and practical insights into the
ambiguous, insufficiently explained, and conflicted areas in the relationship between blockchain
technologies and logistics and supply chain contexts.
Keywords – Blockchain Adoption, Logistics, Smart Contracts, Supply Chain Management,
Technology Implementation
1. Introduction
Blockchain has recently been proposed as a novel technology that uses peer-to-peer (P2P) networks
for data verification and sharing purposes (Cole, Stevenson, and Aitken 2019). Initially introduced by
Nakamoto (2008), the first blockchain technology (BT) application was bitcoin, and different
cryptocurrencies emerged over time. However, the distributed ledger technology (DLT) feature
provides the opportunity for registration, verification, and sharing of any contract, enabling the
technology to be applied in different areas besides cryptocurrency (Tijan et al. 2019). In this respect, it
is worthwhile to note that, although Bitcoin is the first application area of the blockchain system,
blockchain-based applications have been developed in various domains such as logistics operations
(Helo and Hao 2019).
From a technical viewpoint, it is evident that decentralized structure of BT makes this platform more
reliable than centralized systems, where the whole system becomes inoperable at a single point failure
(Perboli, Musso, and Rosano 2018; Saberi et al. 2019). Furthermore, the decentralized structure
removes the intermediaries, freeing the partners from the need to ensure the trustworthiness and
reliability of any middleman (Saberi et al. 2019). Known as a secure platform, BT becomes even more
reliable and immutable against data manipulation with the addition of new blocks (Treiblmaier 2018).
In addition to its reliability, the smart contracts mechanism, which enables to store agreement terms
and rules and validates when these terms are met by all participants, is another prominent feature of
BT (Saberi et al. 2019; Dolgui et al. 2020).
BT promises significant benefits on logistics and supply chain management (SCM), such as increased
sustainability, traceability, and verification (Helo and Hao 2019; Tijan et al. 2019). The technology
can be used to provide at least five different types of product-related information to the end-user,
including type, location, quantity, quality, and ownership data to ensure product traceability (Saberi et
al. 2019). Moreover, BT is expected to improve security besides time and cost efficiency by reducing
paperwork (Hoek 2019), facilitating physical container inspections and customs procedures
(Engelenburg, Janssen, and Klievink 2019). The smart contracts mechanism can further reduce costs
by automating and facilitating payment systems between logistics companies and third-party
organizations such as banks and other financial institutions (Wong et al. 2020b).
In addition to its enabling effects on logistics operations, BT also benefits the manufacturing supply
chain; Real-time data traceability and reliability contribute to environmental and social sustainability
through effective measurement of production capacity (Li et al. 2020). Furthermore, technology allows
innovative product design (Rahmanzadeh, Pishvaee, and Rasouli 2020), product customization
(Karamchandani, Srivastava and Srivastava 2020), agile manufacturing practices (Gunasekaran et al.
2019), flexible flow shop scheduling (Dolgui et al. 2020), and effective service composition
(Aghamohammadzadeh and Valilai 2020). Shi, Yao, and Luo (2021) discuss BT as an enabler of
innovative supply chain platforms such as virtual product design systems. Moreover, Zhu,
Kouhizadeh, and Sarkis (2021) focus on the role of BT in product deletion to improve overall
efficiency in SCM. BT can also provide information management capability to enable synchronized
production and logistics (Helo and Shamsuzzoha 2020). Additionally, the benefits of technology are
discussed in various fields, such as healthcare services (Yong et al. 2020) and humanitarian operations
(Dubey et al. 2020; Rodríguez-Espíndola et al. 2020; Ozdemir et al. 2020).
Despite the widespread attention given to the disruptive potential of BT, there is still a gap in BT and
Supply Chain (SC) integration (Wong et al. 2020a). More particularly, it is evident that the extant
literature remains largely technical (Hooper and Holtbrügge 2020) or conceptual (Wong et al. 2020a)
with anecdotal evidence (Dubey et al. 2020). Similar to these academic gaps, from the practical
standpoint, decision-makers do not fully commit to blockchain adoption (Mathivathanan et al. 2021)
since they have insufficient knowledge about how blockchain can add value to their organizations
(Wamba and Queiroz 2020a). From this point forth, notwithstanding its conceptual utility, the full
potential of BT in the SCM has remained underexplored (Wamba et al. 2020; Wamba, Queiroz, and
Trinchera 2020) and, as such makes it indispensable to clarify the potentials of the BT (Helliar et al.
2020). Accordingly, to fill this void, we propose three main research questions based on the following
rationales:
RQ1. What are the enablers and risks of integrating blockchain technology into the logistics and
supply chain industry?
Since the new technologies have both positive and negative disruptions and affect the structural
dynamics of the SC (Dolgui and Ivanov 2020), BT disruptions on SC also need to be investigated in
detail. However, BT's enablers for SCM have not been thoroughly investigated (Helliar et al. 2020).
Moreover, despite its unknown potential, technology should not be treated as a "panacea," and risks
such as privacy and security remain unsolved (Chang and Chen 2020). Therefore, RQ1 will be
examined in two sub-categories: BT enablers RQ1(a) and risks RQ1(b).
The extant literature mainly focused on the benefits of BT whereas adaptation barriers are not
sufficiently addressed (Kouhizadeh, Saberi, and Sarkis 2021). Accordingly, there is a research gap in
examining adaptation barriers in detail. In this sense, Queiroz, Telles, and Bonilla (2019) and later,
Dutta et al. (2020) similarly highlighted this research gap and indicated a detailed examination of
integration challenges as a research direction. Thus, in order to contribute to the research gap
underlined in these reviews and to deepen their findings, we ask the following research question:
RQ2. What are the barriers to the adaptation of blockchain technology to the logistics and supply
chain industry?
Relying on its potential, BT is useful when it is largely used in the SC (Yadav and Singh 2020). This
being the case, there is a need for determining whether practitioners indeed need this technology and,
as such reveals a dimension of BT adoption to be examined (Wamba et al. 2020; Chang and Chen
2020). Yet, the dearth of empirical studies regarding practitioners' perception of blockchain in the SC
(Karamchandani et al. 2021; Queiroz et al. 2020a) causes to ask the following research question to
advance the extant literature and to reveal practitioners' perspectives on identified barriers:
RQ3. How should the convenient adaptation model be designed in light of the identified barriers?
Recent studies discussed BT in logistics and SCM and reviewed articles regarding their themes and
methodologies (Chang and Chen 2020; Lim et al. 2021). For instance, Dutta et al. (2020) examined
challenges, opportunities, and trends for various industries in the supply chain. Wan, Huang, and
Holtskog (2020) analyzed 31 papers assuming BT-enabled information sharing increases collaboration
in the SCM. Likewise, Queiroz, Telles, and Bonilla (2019) analyzed 27 papers on blockchain and
SCM integration. In a similar vein, Wang, Han, and Beynon-Davies (2019) examined BT and SCM
integration-related papers in the descriptive, conceptual, predictive, and prescriptive categories and
developed a research agenda. From a technical perspective, Bodkhe et al. (2020) conducted a review
that deals with smart applications within the scope of Industry 4.0 and BT. Finally, Cheung, Bell, and
Bhattacharjya (2021) conducted a review on logistics management and BT-enabled cybersecurity. Yet,
despite there are several studies focusing similarly on BT adoption in logistics and supply chain, in
comparison with previous studies, our research is different in many aspects, which brings novelty.
First, since prior studies have become insufficient in providing in-depth and thorough research
considering BT's potential disruptions and adoption barriers on the SCM, this study enriches the
literature through a detailed theoretical discussion. Second, we demonstrate potential BT disruptions in
complex network structures rather than a straightforward narrative and, accordingly, we offer
intellectual value through presenting a research agenda. For this purpose, we propose an integrated and
novel research design from the Methodi Ordinarito and Narrative Networks (NN) analysis. In line with
these novelties;
Initially, we study the potential implications of BT on logistics and SCM and visualize the
network structure to fill the research gap on this subject. Therefore, we utilize the NN analysis
by Pentland and Feldman (2007), which offers an alternative approach to technology adoption
and diffusion analysis.
BT adoption barriers are also investigated in detail, and the revealed factors are discussed
under four distinct categories.
The BT phenomenon is investigated at the theoretical level and the explanatory power of
existing theories to explain this phenomenon in the SCM context is scrutinized.
The remainder of this paper is organized as follows. In Section 2, the literature on blockchain and
SCM is discussed under three subheadings according to the proposed research questions: BT benefits
and enablers, risks and threats, and adoption challenges. While the research design is explained in
detail in Section 3, analyzes described in this section are applied in Section 4. Section 4 also includes a
network of BT enablers and risk factors established through narrative network analysis. In Section 5,
the results of the analyzes are discussed under three subheadings. Practical and academic implications,
limitations of the study, and suggestions for future research directions are also discussed in Section 5.
Finally, Section 6 is devoted to conclusions.
2. Literature review
2.1 BT benefits and enablers
Explaining the motivation for digital transformation, these factors are expected to benefit the entire SC
following the BT implementation. The decentralized structure and consensus mechanism eliminate the
need for intermediaries within the system allowing cost reduction (Bai and Sarkis 2020). Increased
and consistent information sharing improves decision synchronization among partners (Rejeb et al.
2021). Smart contracts enable flexible scheduling models to improve delivery reliability and allow
shorter delivery times (Dolgui et al. 2020). Regarding the manufacturing industry, BT-enabled
digitalization eliminates inspection time of end-of-life products to shorten the disassembly process
(Tozanlı, Kongar, and Gupta 2020). Thus, BT promises increased delivery reliability and opportunity
for mass product customization (Karamchandani et al. 2021). In this regard, Dolgui, Sgarbossa, and
Simonetto (2021) more specifically discussed assembly systems from the aspect of mass
customization.
Social manufacturing and cloud manufacturing are considered next-generation networked production
technologies. With a particular emphasis on social manufacturing, Li et al. (2021) proposed a
blockchain-enabled digital twin platform to contribute to heterogeneity-related issues of socialized
manufacturing resources (SMRs) and tested under a 3D printing scenario. In this respect, BT primarily
serves the purpose of establishing a PnP network that enables the organization of SMRs in a
decentralized structure. Cloud manufacturing (CM), another form of recent networked manufacturing
systems, incorporates cloud computing with various engineering applications and constitutes a joint
pool of configurable production capabilities (Barenji 2021). However, as a centralized platform, CM is
criticized for lacking a real-time and effective trust-based framework known as the third-party trust
problem. For a BT incorporated solution, Barenji (2021) proposes a BT embedded CM architecture
that involves a network of elements, including a digital certificate issue operating system (DCIOS)
that provides a digital certificate for a participant firm based on its trust score. Moreover, Wang,
Wang, and Tu (2021) discuss that BT can provide optimal service composition solutions for NP-hard
optimization problems of CM, establishing a BT-based voting mechanism. Smart manufacturing
system design (SMSD) involves various and interdisciplinary expertise and digital production
concepts such as digital twins. However, extant digital twin technologies are criticized for being
centralized and having traceability and security-related issues (Leng et al. 2021). Herein BT proposes
a feasible solution for the known shortcomings of SMSD, as its strength lies in DLT, cryptographic
validating, and consensus mechanism.
Regarding the agri-food industry, BT allows for increased food safety (Casino et al. 2020) and lower
recall rates in food products (Bumblauskas et al. 2020). It is also highlighted that BT contributes food
SC agility and resilience along with other disruptive technologies such as Artificial Intelligence (AI)
and Machine Learning (ML) (Dora et al. 2021). Furthermore, with their game-theoretical model, Shen
et al. (2021) highlight that BT can provide usefulness in an inspection-based quality management
approach to induce low-quality product sellers to increase their product’s quality. Finally, BT-enabled
transparency is highlighted as a driver of BT adoption in the humanitarian SC (Ozdemir et al. 2020;
Dubey et al. 2020).
2.3 BT risks and threats
In addition to its benefits, BT also poses potential threats by disrupting environmental, social and
functional dynamics of SC. Technology is primarily immature (Köhler and Pizzol 2020), and
scalability-related issues cause performance problems and the need for new investments (Helo and
Hao 2019). The high amount of data mining and consensus protocols brings considerable energy
requirements and environmental costs (Astarita et al. 2020; Esmaeilian et al. 2020; Helliar et al. 2020).
In the case of erroneous data entry, the data is resistant to any correction due to the immutable nature
of blockchain (Kamble, Gunasekaran, and Sharma 2020; Esmaeilian et al. 2020). Moreover, losing
cryptographic keys may be resulted in blocking access to critically important data (Biswas and Gupta
2019).
Furthermore, high visibility raises questions about further data security and privacy (Ivanov, Dolgui,
and Sokolov 2019; Wong et al. 2020b). It is stated that the increased level of automation due to the
smart contracts mechanism causes deskilling and disemployment (Hald and Kinra 2019). Finally, it is
argued that disintermediation may remove value bringing intermediaries (Tönnissen and Teuteberg
2020).
2.2 Adoption challenges and barriers
Another emerging theme in BT in SCM literature is adoption barriers. BT implementation is, first and
foremost, a costly investment (Bavassano, Ferrari, and Tei 2020). Moreover, the uncertainty of return
on investment remains an important challenge (Chang, Iakovou, and Shi 2020). One of the striking
points is that organizational culture and business traditions significantly affect BT adoption. In
business environments with strong bilateral relations, it is possible to provide some flexibility in
payments and the terms of agreements. Therefore, organizations operating in such an environment can
be expected to show strong resistance to the implementation of disruptive technology (Papathanasiou,
Cole, and Murray 2020). It is discussed that small and medium-sized logistics companies tend to view
BT as a threat rather than a benefiting factor (Helo and Hao 2019).
In addition to the role of the business environment and organizational characteristics, the managerial
factor is another challenge to technology adoption (Vafadarnikjoo et al. 2021; Kouhizadeh, Saberi, and
Sarkis 2021). Furthermore, Queiroz et al. (2020a) report that perceived barriers to adoption may differ
depending on the geographical region.
3. Methodology
3.1 Research design
In line with the research aim and questions, the research design of this study encapsulates two
consecutive steps. In the first step, a systematic literature review was employed to reveal the studies
contributing to BT in the logistics and SCM literature. In this respect, as used in the systematic
literature review studies, the Methodi Ordinarito, developed by Pagani, Kovaleski, and Resende
(2015), was adopted to capture relevant literature. Following this, we conducted a brief bibliographic
analysis of the indexed studies. The bibliographic analysis presents the distribution of articles by
journals, including quartile ranks of journals.
The Methodi Ordinarito is a novel computational method to compose a scientifically relevant portfolio
of high-quality papers in systematic literature review research. Therefore, we used this method to
create a valid and novel research design. Following the research aim and questions the scope of the
study was determined as logistics and SCM. The research protocol is listed in Table 1.
Table 1. Research Protocol.
Research
Details
Search axes
X = blockchain, Y= logistics & supply chain
Search query
(blockchain OR "digital ledger" OR "distributed ledger" OR "shared ledger" OR "smart contract") AND (
logistics OR "supply chain" OR transportation)
Search fields
Titles, abstracts, and keywords
Databases
Scopus, Web of Science, ScienceDirect, ABI/INFORM, Taylor& Francis, Wiley
Time range
2008- May 2021
Inclusion
Studies published in business and management discipline and investigating blockchain themes within the
logistics & SCM
Exclusion
SCM papers without any emphasis on logistics
Data analysis
The qualitative data derived from the final portfolio is analyzed by narrative network analysis.
Source: Adapted from Queiroz, Telles, and Bonilla (2019).
In the second stage of the research, indexed studies obtained from the first stage are analyzed with
narrative analysis (NN). At this stage, qualitative data are derived from an in-depth reading of indexed
studies, and these are used to construct meaningful and complete visual networks of BT enablers and
risks. Finally, analysis is performed by interpreting the network patterns (i.e., nodes and paths). The
general flow of the research design is shown in Figure 1.
Figure 1. Research design
3.2 The Methodi Ordinatio and InOrdinarito ranking
In this study, a realistic normative approach, the Methodi Ordinatio developed by Pagani, Kovaleski,
and Resende (2015), was utilized to create a bibliographic portfolio within the scope of the systematic
literature review. The method is an improvement of a constructivist approach known as Knowledge
Development Process-Constructivist (ProKnow-C). The Methodi Ordinatio method allows selecting
and ranking of articles according to their scientific relevance by establishing a well-designed balance
between impact factor, citing score, and publishing year. In Figure 2, the flow chart diagram of the
Methodi Ordinarito method is presented.
Figure 2. Flowchart of the Methodi Ordinarito. Source Pagani, Kovaleski, and Resende (2015).
The Methodi Ordinatio suggests calculating an InOrdinatio score, which includes the impact factor
(IF), year of publication, number of citations (ci), and the α coefficient as given in Eq.1. Here, the α
coefficient takes a value between 0 and 10 depending on the researcher's priority. The use of a value
close to 10 indicates that the researcher focuses on recently published studies.
(𝐼𝐹/1000) + α ∗ [10 − (Year of research − Year of publication)] + ∑𝑐𝑖
(1)
The InOrdinatio score calculation is performed on the seventh of the nine-step process. Subsequently,
all papers to be included in the final portfolio are ranked according to their scores (Campos et al.
2018). The most important advantage of this method is that it enables the determination of the final
portfolio according to the scoring system, thus enabling more reproducible quantitative research
compared to other systematic literature review methods. Hence, the required consistency for a
qualitative study is provided. Due to its recognition and reliability in measuring and classifying
academic journals, the SCImago journal rank indicator (SJR) was used as the impact factor value. As
the alpha (α) coefficient, the maximum value of 10 was used to prioritize the most recent papers.
3.3 Narrative Networks (NN)
In the second step of this research, we propose a NN methodology adapted from Pentland and
Feldman's (2007) perspective to handle the implications of the blockchain phenomenon on logistics
and SCM. The strength of this method lies in its ability to represent different scenarios and
possibilities while visualizing interrelated implications on the subject (Yeow and Faraj 2011).
Therefore, NN is an adequate analytical tool for outlining and visualizing the implications of BT on
the SC. The notions of narrative networks are actants, actions, fragments, and ties. Actants express
both human and non-human entities whilst fragments, namely nodes, represent the narrative flow
between two different actants connected by an action (Pentland and Feldman 2007).
A narrative framework can be designed from different viewpoints. For instance, some papers used the
method to compare the before and after work routines and organizational designs when they are
performed in an alternative way (Chao 2016; Yeow and Faraj 2011). However, this study aims to
obtain discrete and partial narratives from the papers that address potential implications of BT
adoption and create a meaningful and compromised visual narrative flow by overlapping these
narratives. The steps of the proposed NN analysis are as follows in Figure 3.
1) Considering our research questions regarding potential disruptions of BT in SC (RQ1a, RQ1b)
authors listed all possible actants (smart contracts, DLT, immutability) and actions (improve,
pose a risk, enhance). The authors provided a valid consensus on the defined actants and
actions.
2) Each paper is thoroughly read for data collection, and authors manually extract fragments and
discrete narrative stories from individual papers. This step involves an agreement and
verification mechanism among authors without software.
3) A whole and coherent narrative network was established by overlapping previously agreed
discrete narrative stories.
4) Authors add new nodes or complete missing connections to achieve a meaningful pattern.
Since narratives do not necessarily need to be actual, they can be hypothetical, empirical,
typical, and even fictional (Riessman 1993).
5) Finally, to provide a concrete and valid analysis, established relations between the nodes are
supported by the reference source of the statement, i.e. [5]. If a missing connection is
completed by the authors' consensus, in this case, it is shown by [a].
6) Analysis results are obtained by interpreting the structure of the narrative network, i.e., nodes
and paths.
Figure 3. From actants and actions to narrative network
4. The application of integrated qualitative analysis
The steps of the Methodi Ordinarito has a nine-step research process, as shown in Figure 2.
Furthermore, in this section, all steps are applied to obtain a scientifically relevant portfolio. Since the
study's main objective is the current blockchain applications in logistics, the research axes are
determined accordingly (x = blockchain y = logistics). After defining the research axes some articles
on the subject were reviewed for preliminary research and the first keywords were determined for the
x-axis: "blockchain" and for the y-axis: "logistics" and "supply chain."
Further, more comprehensive research is carried out for a final decision on keywords and databases.
To ensure maximum coverage, the keywords were determined as "supply chain", "logistics", and
“transportation” for the x-axis; "distributed ledger," "shared ledger," "digital ledger," "smart
contracts," and "blockchain" for the y-axis. For keyword consistency, state-of-the-art literature review
studies on blockchain and logistics and SCM were examined in Table 2.
Table 2. Validity, consistency, and coverage of keyword selection
Keyword
(Pournader et
al. 2020)
(Wang, Han, and Beynon-
Davies 2019)
(Queiroz, Telles, and
Bonilla 2019)
(Gonczol et al.
2020)
Our
study
Supply chain
√
√
√
√
√
Logistics
√
√
√
√
Transportation
√
√
√
Distributed ledger
√
√
√
√
Shared ledger
√
√
Digital ledger
√
√
Smart contract
√
√
√
Blockchain
√
√
√
√
√
In line with Boolean logic the search term is formed as follows: ("blockchain" OR "digital ledger" OR
"distributed ledger" OR "shared ledger" OR "smart contracts") AND ("supply chain" OR logistics OR
transportation). The databases chosen are Scopus, ScienceDirect, Web of Science, Wiley, Taylor &
Francis, and ABI/INFORM.
Since the blockchain concept was first discussed in 2008 (Nakamoto 2008); the date range for search
of the databases is set as 2008-May, 2021. The search is meticulously carried out and without the use
of a reference manager. The results are sorted, compiled, and organized through a spreadsheet,
simultaneously since articles are entered into the spreadsheet one by one, and only articles with a
relevant title are considered. Grey literature, conference papers, and books are not included in the
search due to the non-availability of the SCImago score. After the search of six databases a total of
736 articles were listed. A comparison was made between databases and 197 duplicated results were
removed from the portfolio. The remaining 539 papers were evaluated for the abstract alignment and
the 83 articles agreed on by all authors were subjected to InOrdinarito evaluation. A total of 77 studies
with InOrdinarito scores between 91,00106 and 725,00178 were included in the final portfolio. During
the revision process of the article in July 2021 and October 2021, additional 18 papers were included
and the total number of articles reached to 95. With the authors' consensus, articles with an
InOrdinarito value of less than 90 were excluded. This process is summarized in Table 3.
Table 3. Selection of portfolio
Databases
Search term
ScienceDirect
Taylor&Francis
Scopus
Web of
Science
ABI/INFORM
Wiley
No of
papers
Gross papers
235
25
313
857
149
13
1592
Title Alignment
130
25
178
267
123
13
736
Duplications
197 duplicated records were removed
539
Abstract Alignment
456 papers were removed due to irrelevance
83
Score Alignment
Six papers were removed due to low score
77
Final portfolio
95
The final portfolio includes research published in peer-reviewed top-tier journals and with high
InOrdinarito scores. Considering the SCImago (SJR) system, 95.78 % of papers were found in the Q1
category, supporting the validity of the final portfolio. Instead of an extensive literature review, we
focused on a portfolio of the most relevant studies, with high-quality content, to ensure the validity of
the research. In Table 4, it is shown how the authors ensure validation of the final portfolio.
Table 4. Validation of portfolio
SJR grouping
Citing
SJR quarter
Number of articles
% in total
Avg. # of cites per SJR group
Q1
91
95.78%
56
Q2
2
2.11%
59
Q3
-
-
-
Q4
2
2.11%
260
4.1 Bibliographic overview
The highest contribution to the BT in logistics and SCM is made by the journals International Journal
of Production Research and International Journal of Information Management. Approximately 45
percent of the research in our final portfolio has been published in these journals. This situation shows
that top-tier journals encourage special issues with a particular emphasis on BT in SCM. In Figure 4,
the distribution of the researches by journals is presented.
Figure 4. Distribution of journals
4.2 Literature overview
Considering the InOrdinarito score, the ranking was made among the 95 papers in the final portfolio
and brief information about the first ten articles is given in Table 5. It is noteworthy that predictive
research is predominant.
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
2
2
2
2
3
3
3
4
4
6
6
10
33
Q1, British Food Journal
Q1, European Management Journal
Q1, International Journal of Logistics…
Q1, International Journal of Operations &…
Q1, International Journal of Physical…
Q1, Journal of Cleaner Production
Q1, Journal of Enterprise Information…
Q1, Journal of Intelligent Information…
Q1, Research in Transportation Business…
Q1, Robotics and Computer-Integrated…
Q1, The Journal of Business Logistics
Q1, TrAC Trends in Analytical Chemistry
Q1, Annals of Operations Research
Q1, Journal of Intelligent Manufacturing
Q1, Information Fusion
Q1, Resources, Conservation and Recycling
Q2, Sustainability
Q1, The International Journal of Logistics…
Q4, Logistics
Q1, Computers & Industrial Engineering
Q1, Production Planning & Control
Q1, Journal of Manufacturing Systems
Q1, International Journal of Production…
Q1, Transportation Research Part E
Q1, IEEE Access
Q1, Supply Chain Management
Q1, International Journal of Information…
Q1, International Journal of Production…
Total Papers
SJR Ranking, Journal
Table 5. InOrdinarito rankings
Papers
Industry
Concept
Theme(s)
I.o. score
(Saberi et al. 2019)
SCM
Predictive
Deals with BT adoption, sustainable SC,
adoption barriers.
725,00178
(Ivanov, Dolgui, and
Sokolov 2019)
SCM
Predictive
Deals with BT's role in SC risk analytics and
improving ripple effect control.
477,0018
(Francisco and Swanson
2018)
SCM
Conceptual
Paper deals with revealing SC professionals'
behavioral intentions regarding BT.
433,00011
(Wang, Han, and Beynon-
Davies 2019)
SCM
Predictive
Deals with BT adoption drivers, barriers, and
potential disruptions in SC.
326,00168
(Galvez, Mejuto, and
Simal-Gandara 2018)
Agriculture
SCM
Descriptive
The authors discuss BT-enabled traceability in
Agriculture SC.
320,00215
(Hughes et al. 2019)
SCM
Predictive
Deals with BT adoption barriers, its potential
applications, and future disruptions in SC.
294,00288
(Treiblmaier 2018)
SCM
Conceptual
The paper discusses the potential implications of
BT in SC through a theoretical framework.
294,00168
(Kamble, Gunasekaran,
and Arha 2019)
SCM
Conceptual
The paper discusses BT adoption in SC through
three adoption theories.
265,00178
(Wang et al. 2019)
SCM
Predictive
Deals with BT adoption challenges and
perceived benefits of technology.
254,00238
(Perboli, Musso, and
Rosano 2018)
SCM
Prescriptive
The authors propose a solution for BT
implementation at the strategic level.
238,00078
4.3 Thematic summary and narrative network analysis
4.3.1 Implementation enablers and benefits
Table 6 summarizes the data from studies highlighting the enablers of BT adoption. For simplicity and
readability of the paper, the whole literature is not given here, and constructs will be expressed as
interconnected stories to perform narrative network (NN) analysis. Subsequently, a conceptual
network will be proposed in Figure 5 as a result of the NN.
Table 6. Narrative of BT enablers
Papers
BT Enablers
(Kamble,
Gunasekaran, and
Sharma 2020)
While the decentralized structure allows an increase in trust among the participants, the distributed
database reduces the business risks due to late or missing payments. Smart contracts mechanism and
decentralized structure reduce the need for intermediaries and transaction costs. The BT-enabled
timestamping provides traceability of historical data along the chain, while increased traceability and
transparency allow increased trust throughout SC.
(Sander, Semeijn,
and Mahr 2018)
It is stated that there is a positive correlation between transparency and traceability systems (TTs)
and customers' perceptions of the quality of food products. Accordingly, a BT integration in the
context of TTs is predicted to affect consumers' purchasing decisions positively.
(Papathanasiou,
Cole, and Murray
2020)
Smart contract mechanisms and disintermediation reduce paper-based processes and allow time and
cost-efficiency. The automation provided by the smart contracts and consensus mechanism lead to
better inventory management and subsequently increased efficiency. Thanks to transparency, the
customs authorities can instantly access real-time data, allowing accelerated custom clearance.
(Yang 2019)
Real-time visibility of shipment data significantly benefits the customs processes and increases
efficiency in logistics. BT reduces paper-based transactions and makes some transactions completely
paperless due to the digitalization of processes, contributing to improved SC visibility.
(Helo and Hao 2019)
Reducing information asymmetry through BT allows reducing capacity risk and ultimately bullwhip
effect across the SC. Smart contracts enabled automation allows the effective fulfillment and
verification of contract terms. Moreover, intermediary-related costs and risks arising from late
payments are minimized.
(Choi et al. 2019)
The smart contracts mechanism allows automatic execution of contract terms, thereby increasing
efficiency.
(Hald and Kinra
2019)
BT allows the consumer to ensure the product's origin and consider sustainability-related issues for
purchasing decisions. Visibility allows users to monitor the movement of raw materials and products
and increase SC's planning and coordination capacity. The smart contract mechanism increases the
SC efficiency due to the standardization and automatic execution of contract rules.
(Koh, Dolgui, and
Sarkis 2020)
BT-enabled provenance allows an effective governance mechanism across the SC, such as tracing the
exact origin of valuable and critical goods such as diamonds and medicine. The reliable and fast
information sharing, combined with optimization methodologies, enables efficient warehousing and
reduces the bullwhip effect.
(Tijan et al. 2019)
Visibility provides increased decision-making support to participants involved in logistics activities.
The decentralized nature of BT allows the participation of all users and high SC coordination.
Besides, BT-enabled allows security throughout the SC.
(Perboli, Musso, and
Rosano 2018)
Thanks to increased visibility, effective stock control can be achieved with a better forecast, reducing
the bullwhip effect and subsequent logistics costs. High visibility prevents product counterfeiting,
positively affects customer confidence and purchasing decision.
(Cole, Stevenson,
and Aitken 2019)
Product traceability reduces counterfeiting, and smart contract mechanisms reduce manual
transactions and human errors. Elimination of intermediaries through the smart contract mechanism
reduces SC complexity. BT-enabled automation reduces transaction costs, and automation-enabled
efficiency allows the emergence of new products.
(Saberi et al. 2019)
BT-enabled visibility allows customers to ensure their purchases are green products. Thanks to
improved traceability, effective detection of non-standard products reduces consumption and
environmental costs caused by rework, packaging, and reverse logistics.
(Ivanov, Dolgui, and
Sokolov 2019)
The authors emphasize that the application of big data on SC provides dynamic route optimization
and effective inventory management. BT allows real-time monitoring of container temperature and
ensures food products' safety through data visibility.
(Hughes et al. 2019)
BT significantly increases product traceability, while data visibility increases trust among SC
partners. Thanks to its immutability, customer confidence is ensured by preventing counterfeiting
and, at the same time, eliminating intermediates allows cost reduction.
(Dobrovnik et al.
2018)
Thanks to traceability, the customers can find information about a product's origin and its
manufacturer improving customer's trust and increased profitability. Traceability of data also enables
the monitoring of any vehicle's performance and maintenance records in the fleet.
(Chang, Iakovou,
and Shi 2020)
The smart contracts mechanism ensures that a penalty system is automatically activated by violation
of the predetermined rules, facilitating dispute resolution between SC partners. Reliable and
transparent transaction records enable product provenance and the fight against counterfeiting and
contribute to a sustainable SC.
(Roeck, Sternberg,
and Hofmann 2020)
Immutability and consensus mechanisms prevent any manipulations; reliable and verified data
contributes to the decision-making process. The BT-enabled transparency allows the users on the
network to see and evaluate their partner's performance. Smart contracts-enabled automation reduces
monitoring and coordination costs.
(Wang et al. 2019)
Real-time visibility enables effective demand forecast and customs controls. Together, BT-enabled
reliability and product authenticity allow an increase in security throughout the SC. The smart
contracts mechanism promises high automation throughout SC.
(Wang, Han, and
Beynon-Davies
2019)
Operational costs are reduced through disintermediation and avoiding payment gaps through smart
contract-enabled automation. Blockchain enables the transfer of consistent data to customs
authorities for real-time risk analysis.
(Kamble,
Gunasekaran, and
Arha 2019)
The smart contract mechanism provides a solution to the costly problem of payment gaps originating
from analog contracts. Transparency increases trust in the SC; additionally, data immutability and
visibility enable SC analytics.
(Z. Li et al. 2020)
Particularly in manufacturing, a safe and reliable environment provides an opportunity for enterprise
production capability evaluation. Such an automated performance evaluation system requires real-
time data visibility, as BT provides.
(Dubey et al. 2020)
Since trust and collaboration are predictors of SC resilience, BT-enabled transparency allows for
increased trust among partners and increased collaboration in the SC. Moreover, BT-enabled
transparency and visibility reduce SC complexity.
(Esmaeilian et al.
2020)
BT-enabled traceability allows firms to be taxed with an appropriate carbon tax rate by tracking
product carbon footprint. Additionally, disintermediation reduces verification and networking costs.
(Rejeb et al. 2021)
BT strengthens the decision-making mechanism by providing synchronization between different
nodes in the SC, enabling an increase in performance. Transparency enabled uninterrupted, and
accurate information data flow enables accurate forecasts.
(Dolgui et al. 2020)
In supply chains where multiple logistics service providers are involved, smart contract mechanisms
can increase operational efficiency in time utilization and delivery reliability through flexible flow
shop scheduling.
(Queiroz et al.
2020b)
Digitalization increases the flexibility of the SC, and especially in pandemic situations, response
traceability. This is important for controlling the SC resilience and ripple effect.
(Wang, Chen, and
Zghari-Sales 2020)
Automated contracts mechanism reduces late payments; moreover, it increases efficiency and cost
savings within SC. In addition, visibility through tracking and tracing mechanisms enables
performance management and supplier benchmarking.
(Casino et al. 2020)
Data immutability provides data security, which increases the safety of food products and ultimately
enables the delivery of high-quality products to the end consumer.
(Xu et al. 2021)
The use of blockchain technologies increases consumers’ awareness of green products and increases
the profit of the whole SC network, especially the manufacturer.
(Wu, Fan, and Cao
2021)
BT can provide data traceability for fresh product supply chain consumers and enable companies to
be assured of food quality. The consumer's confidence in product quality may influence the decision
to pay a premium for such a product.
(Guo et al. 2021)
Within the scope of smart manufacturing, BT contributes the industrial dataspace concept by
enabling the transmission of large amounts of data by means of security and transparency.
(Sahoo 2021)
BT can reduce the vulnerability of cyber-physical manufacturing systems (CPS) against hacking and
thereby ensure social acceptance of intelligent manufacturing platforms.
(Zhang et al. 2021)
BT can resolve credibility issues of centralized cloud manufacturing architectures by providing a
secure network structure that is fundamentally based on voting mechanisms and cryptographic
algorithms.
(Shen et al. 2021)
BT provides a decentralized solution to the data sharing problem among untrusted parties of Digital
Twin (DT) technology. Here, cloud technology is also incorporated with BT to deal with a large
amount of DT data that is collected in different forms, such as physical and virtual device data.
(Pérez et al. 2021)
BT-based information systems can coordinate various autonomous CPSs and provide solutions in
case of conflict between these units. In this way, BT enables the efficient implementation of mass
customized productions systems, solving the interoperability problem.
(Manimuthu et al.
2021)
Smart contract mechanism and AI supported data-driven decision-making algorithms such as
Federated Artificial Intelligence (FAI) framework enable industrial automation and advanced
assembly systems.
All qualitative data in Table 6 is visualized by narrative network analysis, as shown in Figure 5. With
an inductive approach, narrative fragments (nodes) will be separately coded for each paper, and then
all patterns will be overlaid to achieve a meaningful pattern. To prove the robustness and reliability of
the network the sources of nodes are specified in the graphic. While visuals expressed in a square
represent BT's fundamental features, the narrative fragments are represented by circles.
[1](Tijan et al. 2019) [9](Dobrovnik et al. 2018) [17](Ivanov, Dolgui, and Sokolov 2019) [24](Dubey et al. 2020) [31] (Xu et al. 2021)
[3](Perboli, Musso, and Rosano 2018) [10](Chang, Iakovou, and Shi 2020) [18](Kamble, Gunasekaran, and Sharma 2020) [25](Esmaeilian et al. 2020) [32] (Wu, Fan, and Cao 2021)
[4](Cole, Stevenson, and Aitken 2019) [11](Koh, Dolgui, and Sarkis 2020) [19](Sander, Semeijn, and Mahr 2018) [26](Rejeb et al. 2021) [33] (Guo et al. 2021)
[5](Saberi et al. 2019) [12](Roeck, Sternberg, and Hofmann 2020) [20](Papathanasiou, Cole, and Murray 2020) [27](Dolgui et al. 2020) [34] (Sahoo 2021)
[6](Yang 2019) [13](Wang et al. 2019) [21](Helo and Hao 2019) [28](Queiroz et al. 2020b) [35] (Zhang et al. 2021)
[7](Hughes et al. 2019) [15](Hald and Kinra 2019) [22](Choi et al. 2019) [29](Wang, Chen, and Zghari-Sales 2020) [36] (Shen et al. 2021)
[8](Kamble, Gunasekaran, and Arha 2019) [16](Wang, Han, and Beynon-Davies 2019) [23](Li et al. 2020) [30](Casino et al. 2020) [37] (Pérez et al. 2021)
[a] Authors’ elaboration [38] (Manimutlu et al. 2021)
Figure 5. Narrative network of enablers
4.3.2 Potential Risks and Threats
Table 7 summarizes the data from studies highlighting the risks of BT adoption. For simplicity and
readability of the paper the whole literature is not given here and constructs will be expressed as
interconnected stories to perform narrative network (NN) analysis. Subsequently, a conceptual
network will be proposed in Figure 6 as a result of the NN.
Table 7. Narratives of BT risks
Papers
Potential Risk and Threats
(Lin et al. 2019)
Processing and storing large amounts of data may cause scalability issues, an increase in operating
costs, with significant performance loss. The need for data sharing between indirect partners (e.g.,
manufacturer and retailer) poses a privacy risk.
(Biswas and Gupta
2019)
Inconsistency due to software updates may cause technology risks. A significant technology risk is
the loss or theft of cryptographic keys, in which case the data in the blocks becomes unrecoverable.
(Helo and Hao
2019)
The BT transactions require high-capacity physical infrastructure. Ultimately, such a scalability
problem can significantly increase operating costs. As another BT risk, existing BT applications
cannot provide sufficient data privacy, and sensitive information can be transmitted to a node outside
the network.
(Hald and Kinra
2019)
Permissioned and private blockchain structures can lead to a monopoly, strengthening the network's
hierarchy. The inflexibility of the smart contracts mechanism and non-compliance with the existing
legal infrastructure are other SC risks. Smart contracts-enabled automation results in deskilling and
disemployment.
(Koh, Dolgui, and
Sarkis 2020)
Privacy emerges as an ethical issue with its different dimensions, such as organizational and
individual privacy. It is also argued that BT-enabled digitalization may cause disemployment for low-
skilled workers.
(Tijan et al. 2019)
BT requires a large amount of energy to function due to the required processing capacity. Every
transaction on the system requires acknowledgment by all users and causes slowdown and
performance loss throughout the SC. The lack of legal and regulatory infrastructure regarding the
smart contract mechanism may cause its users to fall into illegal status.
(Saberi et al. 2019)
In addition to the scalability risk, an effective solution has not yet been proposed for data
manipulation, security, and privacy problems. Although BT provides data security through
immutability, this also means that erroneous data permanently remains in the system where any is
erroneously recorded.
(Ivanov, Dolgui, and
Sokolov 2019)
Besides the advantages they provide, advanced track and trace systems may cause data security
problems.
(Astarita et al. 2020)
Implementing BT technologies can be environmentally costly, as performing the necessary
computing requires large amounts of energy. Additionally, the fact that large amounts of data will be
stored brings scalability problems.
(Wong et al. 2020b)
Data security and privacy issues are considered BT risks by SC professionals. Moreover,
immutability causes erroneous data to remain in the system and poses a threat to data integrity.
(Chang, Iakovou,
and Shi 2020)
The scalability problem caused by the limited processing capacity of existing digital ledger
technologies emerges as a post-implementation risk.
(Kamble,
Gunasekaran, and
Sharma 2020)
The authors express the immutability-based irrevocability of any data in the blockchain system, and
security threats arising from selfish mining pose significant BT risks.
(Roeck, Sternberg,
and Hofmann 2020)
BT-enabled transparency may reveal some partner's incompetencies and reduce their bargaining
power within the network. Additionally, one-way traceability (upstream or downstream) may cause
information asymmetry between users.
(Cole, Stevenson,
and Aitken 2019)
The disintermediation may cause value-creating partners to lose their current positions. Moreover,
automated penalty mechanisms can undermine business relationships and a loss of trust between
organizations. Firms have to rely on a penalty mechanism with complicated algorithms.
(Wang, Han, and
Beynon-Davies
2019)
As well as its technical risks, the smart contracts mechanism also poses social risks as it removes
intermediaries or reduces their numbers, which will result in disemployment.
(Hughes et al. 2019)
Every node on the network separately keeps a record of all transactions and creates a privacy risk
while increasing the computational cost. Additionally, immutability prevents any changes and
corrections of the data, such as adjusting contractual terms, leading to decreased flexibility.
(Dutta et al. 2020)
Lack and inadequacy of legal and regulatory mechanisms may lead to consumer confusion. Another
issue arises in repayment: immutability does not allow for adjustment in the existing transaction, and
a refund requires a new transaction.
(Esmaeilian et al.
2020)
Defining the rules and terms of smart contracts by software developers creates incompatibility
problems with legal regulations. Moreover, smart contract mechanism-related inflexibility brings
along the problem of not adapting to the expectations of different partners and different scenarios.
(Tönnissen and
Teuteberg 2020)
Although different partners in the SC produce benefits as intermediaries, BT-based disintermediation
may cause valuable partners to be excluded from the system.
(Helliar et al. 2020)
Especially in permissionless systems, performing the necessary calculations to solve the algorithms
requires a high amount of energy.
(Liu, Zhang, and
Zhen 2021)
Irrecoverability of the BT data poses the risk that if the system blocks any data, any information and
value associated with this data may be completely lost, ultimately resulting in transactional
uncertainty.
All qualitative data in Table 7 is visualized by narrative network analysis, as shown in Figure 6. With
an inductive approach, narrative fragments (nodes) will be separately coded for each paper, and then
all patterns will be overlaid to achieve a meaningful pattern.
[1](Tijan et al. 2019) [9] (Koh, Dolgui, and Sarkis 2020) [15](Hughes et al. 2019) [20](Chang, Iakovou, and Shi 2020) [25] (Liu, Zhang, and Zhen 2021)
[4](Cole, Stevenson, and Aitken 2019) [10](Hald and Kinra 2019) [16](Ivanov, Dolgui, and Sokolov 2019) [21](Dutta et al. 2020) [A] Authors’ elaboration
[5](Saberi et al. 2019) [11](Biswas and Gupta 2019) [17](Helo and Hao 2019) [22](Esmaeilian et al. 2020)
[7](Lin et al. 2019) [12](Roeck, Sternberg, and Hofmann 2020) [18](Wong et al. 2020b) [23](Tönnissen and Teuteberg 2020)
[8](Astarita et al. 2020) [14](Wang, Han, and Beynon-Davies 2019) [19](Kamble, Gunasekaran, and Sharma 2020) [24](Helliar et al. 2020)
Figure 6. Narrative network of BT risks
ggg
4.3.3 Implementation Barriers and Challenges
The barriers to BT adoption are increasingly investigated in the literature. These include investment
costs, lack of skilled labor, and lack of a legal and regulatory framework. BT adoption barriers
compiled from the literature are shown in Table 8.
Table 8. Implementation challenges
Papers
Implementation Barriers and Challenges
(Kamble,
Gunasekaran,
and Sharma
2020)
The technical inadequacy of the organizations and an inadequate legal and regulatory framework stand
as obstacles to BT adoption.
(Papathanasiou,
Cole, and
Murray 2020)
A qualified and technical workforce is required for the integration of the maritime industry into BT.
The uncertainty caused by the lack of a standard legal infrastructure is another barrier. Additionally,
before blockchain integration, trading partners must be integrated through existing systems such as
ERP.
(Yang 2019)
The lack of globally viable and consistent technical standards and regulatory frameworks is an
obstacle to BT integration. Another finding of the study is that senior-level managers have a sceptical
view of new technologies.
(Helo and Hao
2019)
The very long implementation process and the requirement of highly qualified personnel are expressed
as adaptation barriers.
(Koh, Dolgui,
and Sarkis
2020)
BT-enabled transparency may not be accepted in SC networks where information asymmetry is
common. Additionally, the integration of legacy systems, investment requirements, and the necessity
for inter-organizational change management are other barriers.
(Di Vaio and
Varriale 2020)
Particularly in the airport industry, the lack of expert staff with coding skills and the high setup fee are
considered integration barriers.
(Cole,
Stevenson, and
Aitken 2019)
Given the required investment costs, the authors point out BT adaptation may not be attractive for
local and small supply chains.
(Saberi et al.
2019)
Authors suggest BT adoption barriers into different categories: Intra-organizational barriers, inter-
organizational barriers, system-related barriers, and external barriers.
(Dobrovnik et
al. 2018)
The costs of transition to the new system and the necessity to develop new standards for BT
compliance in the logistics infrastructure are significant barriers.
(Bavassano,
Ferrari, and Tei
2020)
The major obstacle to BT adoption is the lack of interest from authorities and regulators to make the
necessary investment. The need to set up a clear implementation strategy, the absence of overarching
standards for complete SC integration and high investment costs, are other obstacles.
(Wong et al.
2020b)
The lack of trust and sufficient knowledge of SC professionals about BT is a challenge against
integration. Additionally, technical standards are required to integrate different users who provide
services in a wide range of specialties within the SC.
(Chang,
Iakovou, and
Shi 2020)
The uncertainty of return on investment is an obstacle to BT implementation. The lack of
technological knowledge, and the requirement for standardization that will provide interoperability
between SC players, emerges as another challenge.
(Yang 2019)
The requirement of determining technical standards for maritime SC and uncertainty regarding
regulatory governance are expressed as implementation barriers.
(Sternberg,
Hofmann, and
Roeck 2021)
Insufficient knowledge about BT's functionality and benefits, lack of standards developed for SC,
conflicting stakeholder expectations, and existing corporate culture are challenges to adaptation.
(Kouhizadeh,
Saberi, and
Sarkis 2021)
There is a distinct difference between academics and practitioners regarding BT adaptation barriers.
While practitioners' approach to the issue is more technologically oriented, academics evaluate
adaptation barriers within the SC, technology, and sustainability with a more holistic perspective.
(Wan, Huang,
and Holtskog
2020)
Users may be reluctant to share data due to conflicts of interest and the highly competitive
environment, which appears as a barrier to adoption. The lack of awareness towards digitization across
the industry and the need for investment and time cost are other barriers.
(Mathivathanan
et al. 2021)
The business owner's reluctance to use new technologies such as blockchain is an important barrier. In
addition to the unwillingness of companies to share commercial data with their partners, regulatory
uncertainty, insufficient digitalization, and uncertain benefits of technology are other barriers.
(Vafadarnikjoo
et al. 2021)
The use of blockchain in the "underground economy" for illegal purposes such as gambling and money
laundering is an adoption barrier. Moreover, management's commitment and transactional level
uncertainties are identified as other adoption barriers.
(Yadav et al.
2020)
The authors examined ten adaptation barriers for Agri-food SC; the lack of regulatory infrastructure
and regulatory uncertainty and lack of trust among stakeholders are the most significant challenges for
BT adoption. The complexity of system design and the user's negative perception of system use are
other significant barriers.
(Queiroz et al.
2020a)
Facilitating conditions such as organizational infrastructure and IT capabilities are significantly affect
behavioral intention to adopt the technology. Moreover, individuals’ perception of performance
expectancy from BT is considered a significant barrier.
4.3.4 Theorization of BT and SCM relationship
Theorization is crucial to thoroughly investigate any implications of BT on SC and address the
adaptation phenomenon on a solid basis. However, criticism is brought to the existing literature for the
small number of theory-based studies conducted so far (Sternberg, Hofmann, and Roeck 2021; Acar
and Kucukaltan 2021). In this section, we discuss five theories, namely Dynamic Capability View
(DCV), Information Processing Theory (IPT), Resource Orchestration Theory (ROT), Institutional
Theory (IT), and Upper Echelon Theory (UET), for addressing the blockchain phenomenon in the SC.
A well-established and excessively employed theory, the Resource-Based View (RBV), explains how
specific organizational capabilities and resources can lead to competitive advantage (Ketchen Jr and
Hult 2007). However, as a static theory, it falls short of explaining how firms develop their resources
and abilities in dynamic environments (Gupta et al. 2020b). Derived from RBV, DSV can successfully
explain the transformation of traditional SC's into digitally enabled and agile structures by uniting,
building, and reconfiguring a firm's ability to adapt to dynamic environments (Teece, Pisano, and
Shuen 1997). Dynamic capabilities improve organizations' agility, allowing them to generate increased
profits during uncertainty (Dolgui, Ivanov, and Sokolov 2020), enhancing social and environmental
sustainability (Dubey et al. 2019c) and SC resilience (Altay et al. 2018). Martinez et al. (2019)
emphasize that BT is transforming organizations' standard core capabilities into new and dynamic core
capabilities, such as data analytics. The authors further argue that analyzing and using data on
customers' changing consumption habits to gain competitive advantage is a dynamic core capability.
IPT is currently a popular tool for explaining SC-related phenomena, especially for post-covid
scenarios (Yang et al. 2021). The theory addresses the relationship between information processing,
environmental uncertainty, and organizations' adaptation requirements (Saberi et al. 2019). The theory
can adequately explain how organizations gain a competitive advantage through information flow in
high uncertainty (Jia et al. 2020). Accordingly, investing in information processing capability is
considered an effective strategy (Dubey et al. 2019a). BT-based data management prevents
opportunistic behaviors in the SC through accession to reliable and visible data (Karamchandani et al.
2021). As the relationship between big data processing capability and swift-trust is proved (Dubey et
al. 2019a), BT's big data analytics capability reduces behavioral uncertainty through increased data
sharing among members. Further, transparency enables swift-trust building and improves SC
collaboration (Dubey et al. 2020).
Another criticism of RBV is that, while trying to explain firm performance and competitive advantage
through acquiring and developing strategic resources, it is insufficient to explain how similar firms
with similar outputs can differentiate in outputs (Sirmon et al. 2011). At this point, ROT is introduced;
the theory derived from RBV is based on the efficient management of capabilities and resources to
generate value (Sirmon et al. 2011). The theory strongly emphasizes the orchestrator's role and ability
to structure and bundle a firm's resources to maximize the output (Plasch et al. 2020; Chavez et al.
2020). So far, little contribution has been made to the theory in SC studies (Craighead, Ketchen Jr, and
Darby 2020). Drawing from the ROT, Plasch and colleagues (2020) discuss the central orchestrators'
role in utilizing the logistics network through physical internet. Chavez et al. (2020) discussed the
relationship between competitive advantage and the organization's environment, economic and social
performance (three bottom lines -TBL) through ROT. Accordingly, internal lean practices orchestrate
resources as a manufacturing system and improve TBL performance.
The Institutional Theory (IT), which explains organizations' tendency to isomorphism with coercive,
normative, and mimetic mechanisms, can adequately explain how firms respond and adapt to
substantial environmental changes to earn legitimacy (Wamba and Queiroz 2020b). Throughout the
Covid-19 pandemic, large manufacturers and distributors (e.g., General Motors and Amazon) have
faced challenging environmental pressures such as devoting part of their production and distribution
capacity to medical products (Craighead, Ketchen Jr, and Darby 2020). However, institutional
pressure can also be a driving force for organizations to develop new capabilities (Wamba and Queiroz
2020b). And at this point, the integration of the institutional theory with the DSV can explain the role
of environmental pressure in developing the organization's dynamic internal resources (Gupta et al.
2020a). As the fundamental promise of BT lies in big data processing capacity and data analytics,
institutional pressure impacts developing a big data culture through skilled workforce development
and appropriate resource selection (Dubey et al. 2019b). Moreover, drawing on IT, researchers argue
that the BT-enabled transparency provides social legitimacy within the scope of food certification
(Hew et al. 2020; Tan, Gligor, and Ngah 2020).
Upper Echelon Theory (UET) assumes that factors related to top management, such as experience,
age, and even personality traits impact organizational success (Hambrick and Mason 1984).
Accordingly, top management plays a crucial role in solving the organization's problems. As a
successful BT adoption requires a highly skilled technical workforce (Kouhizadeh, Saberi, and Sarkis
2021), the theory can explain the top management's role in hiring, training, coaching, and empowering
such skilled workers (Potter 2021). It is also discussed that organizational leaders have a role in
ensuring the compliance of targets and processes amongst the firms and their suppliers (Potter 2021).
In this respect, UET can address the interoperability issue, one of the obstacles to BT adoption. The
UET has the potential to establish a theoretical basis for studies using technology acceptance models
that aim to explain the intention of system users to accept and use new technologies. In this case,
logistics and SC managers' perspectives on BT adoption can be analyzed in a solid theoretical
framework.
5. Discussion
In this section the research results are discussed under three headings following the analysis level.
First, BT enablers and risks are interpreted as indicated in Figure 5 and Figure 6, which include
visualized narrative networks. Then, the barriers to blockchain adaptation from Table 8 are interpreted
and categorized. Finally, the relationship between BT and the SC is discussed on the theoretical level.
5.1 Enablers and risks
In Figure 5, we proposed a narrative network framework to reveal BT enablers in detail and provide a
concrete answer to RQ1 (a) to contribute extant literature. Our main finding is that BT adoption
ultimately is resultant in increased efficiency across the SC through direct and indirect enablers. The
digitalization of paper-based processes (1), efficient decision-making mechanisms (2), improved SC
coordination (3), and flexibility (4) are prominent driving factors of SC efficiency. As an indirect
effect, transparency enabled real-time visibility improves the efficiency of custom processes. This
outcome supports and enhances previous studies' findings predicting that blockchain adaptation will
increase SC efficiency and performance (Wamba, Queiroz, and Trinchera 2020). Second, research
shows that there is a strong clue for interconnectedness among BT enablers. This finding can explain
the vagueness and confusion about the full potential of BT in the SC (Wamba et al. 2020), providing
an answer to our RQ1(a). Our finding is consistent with recent studies that focus on
interconnectedness among BT constructs such as barriers and enablers (Yadav and Singh 2020;
Ozdemir et al. 2020).
Another finding is BT's most significant impacts on SC are environmental and social sustainability
(Saberi et al. 2019). However, there is a limited contribution to BT adoption in terms of sustainability
(Lim et al. 2021). In a limited number of studies, sustainability is mainly contributed through
traceability and product provenance (e.g., Dobrovnik et al. 2018); thus, we could not find any evidence
for an attempt to establish a link between sustainability and indirect BT enablers such as dispute
resolution, disintermediation, or risk analysis. Köhler and Pizzol (2020) similarly emphasize that the
impact of BT on sustainability has not yet been conclusively proven. The potential consequences of
disintermediation are addressed by scholars (Tozanlı, Kongar, and Gupta 2020; Tönnissen and
Teuteberg 2020); however, it is not adequately discussed in terms of environmental and social
sustainability. To enhance extant literature, we bring the following research proposal:
RP1. What is the relationship between smart contract enabled disintermediation and supply chain
sustainability in the environmental and social sphere?
Another finding of our study is that the connection between customs processes and SC sustainability
has not yet been established. Referring to Figure 5, the existing argument on customs-based risk
analysis does not address its contribution to social and environmental sustainability. Considering
customs processes have a vital role in maintaining an efficient SCM, and there is increasing emphasis
on sustainability (Wamba and Queiroz 2020a; Khan et al. 2021), the intellectual value of investigating
the relationship between these concepts in detail emerges. To take Tian et al.'s (2021) research
question on the development of specific applications of BT in sustainable SCM one step further and to
contribute extant literature, we bring the following research proposal:
RP2. What is the relationship between transparency-based risk analysis (customs) and supply chain
sustainability in the environmental and social sphere?
BT promises prominent advantages regarding manufacturing systems, particularly for smart-intelligent
production techniques. As an enabler of cloud manufacturing (CM), BT provides a trustless
mechanism for secure and reliable data sharing and addresses CM's well-known vulnerability known
as the third-party trust problem. In this case, BT can be used to establish an integrated architecture to
provide trust score-based digital certificates (Barenji 2021) and resolve credibility-related issues of
centralized CM systems (Zhang et al. 2021). Again, BT-based voting mechanisms can provide an
adequate solution for NP-hard optimization problems of CM architectures (Wang, Wang, and Tu
2021). Moreover, BT can function as a data-sharing layer to enable communication and coordination
of various decentralized cyber-physical objects. In spite of all the promises of BT-integrated solutions,
the main drawback of such applications is excessive resource utilization, delay time, and low
throughput due to inefficient consensus algorithms. Despite the recent efforts (e.g., Zhang et al. 2021),
further research is required to exploit enabling effect of BT on advanced production methods, and
particularly for CM architectures. Therefore, to enhance extant literature, we bring the following
research proposal:
RP3. What should be a well-optimized consensus algorithm for BT to enable cloud-based
manufacturing?
Regarding RQ1 (b), we established a narrative network to reveal the blockchain risks in logistics and
SCM to enhance the findings of prior research (Figure 6). The structural dynamics of the SCs are
discussed from different perspectives, such as social, economic, functional, and technical (Dolgui and
Ivanov 2020). Regarding BT's disruptive effect on functional dynamics, we found that inflexibility
emerges as a technology risk resulting in the cooperation of the consensus mechanism, automated
contracts, and immutability; it may ultimately result in business risks such as loss of opportunity to
update contractual terms. To some degree, our findings are in line with papers that discuss the
inflexibility of the technology (e.g., Esmaeilian et al. 2020). Unlike our research, these studies
associate BT-related inflexibility non-holistically and either with only smart contracts or immutability.
This finding reveals that further research is needed to empirically investigate the inflexibility issue by
considering three features of BT.
Transparency is seen as the most crucial feature of BT and promises various enablers unlikely to be
claimed otherwise, such as fraud prevention (Roeck, Sternberg, and Hofmann 2020) and increased
trust (Kamble, Gunasekaran, and Sharma 2020). Our findings show that transparency may also lead to
problems ranging from privacy breaches to loss of organizational reputation and even monopolies
within the SC. Although the BT-enabled transparency has been intensely addressed (e.g., Bai and
Sarkis 2020), the risks arising from transparency have not yet been adequately explained on theoretical
grounds. Therefore, the following research is proposed for a detailed investigation in the light of
management theories:
RP4. On what theoretical basis does BT-based traceability lead to monopolies within the supply
chain?
5.2 Adoption barriers
To provide a concrete answer to the RQ2 regarding BT adoption barriers, we evaluated the literature
findings from Table 8. As a result, adoption barriers are divided into four distinct categories:
governance and regulatory, economic, technical, and business ecosystems. To clarify our findings we
break down these categories into individual adaption factors. First, we found that investing in high-
tech human capital to improve an organization's technical knowledge is the most crucial issue in the
"technical" category. This finding confirms the emphasis in the literature that the lack of technical
knowledge of the organization is one of the most crucial adaptation barriers (Mathivathanan et al.
2021; Orji et al. 2020). Similarly, Kouhizadeh, Saberi, and Sarkis (2021) emphasize the importance of
technical expertise. Another finding is that developing technical standards to integrate different SC
actors emerges as a challenge. This finding is in line with Yadav et al.'s (2020) emphasis on
interoperability, and standardization stands out as a significant challenge against adoption. From a
business ecosystem perspective, we found that the structure of the SC network (i.e., traditional and
reactive or data-driven) is crucial through external stakeholders' support.
From a governance and regulatory perspective, we have few findings. First, the lack of legal and
regulatory infrastructure stands out as a significant external barrier. This corresponds with Yadav et
al.'s (2020) findings on the impact of governmental guidance on BT adoption. Second, from firm
governance, organizations' commitment to digital transformation emerges as an intra-organizational
barrier, which is in line with previous studies' findings (Kouhizadeh, Saberi, and Sarkis 2021). Most
strikingly, the managerial factor is found to be the least highlighted among all adaptation barriers.
However, adaptation is affected by the individual decision-making mechanism, which may vary
according to the characteristics of the decision-maker (Bai and Sarkis 2020). Similarly, consistent with
our findings, Wamba, Queiroz, and Trinchera (2020) report that managers' efforts to understand the
BT and SCM relationship are not sufficient. It is further reported that empirical studies to measure
individual adoption behavior in the SCM are scarce (Queiroz et al. 2020a).
For a detailed investigation on managerial perspective on BT adoption and to provide a comprehensive
answer to the RQ3, we are bringing the following research proposal to the agenda by referring to the
integrated Technology Acceptance Model (TAM) and Upper Echelon Theory (UET) considering four
categories of blockchain adoption. While the TAM model is a popular tool for measuring adaptation to
new technologies (Yang 2019), UET explains the management's role in the organizational success
(Hambrick and Mason 1984).
RP 5. What are the effects of adoption barriers in governance and regulatory, economic, technical,
and business ecosystems categories on the perceived usefulness (1) and perceived ease of use (2) of
logistics managers regarding BT technologies?
5.3 Theoretical lens
There is increasing interest in BT studies within the academic community, while few studies discuss
the subject on a theoretical level. Our finding at this point is that the theoretical grounds of the BT and
SCM relationship were not contributed to in two respects. First, ROT has not received enough
attention from SCM studies (Craighead, Ketchen Jr, and Darby 2020); there is no evidence of any
effort to explain the BT phenomenon in the SCM through ROT. The subjects of disintermediation and
the emergence of blockchain service providers as new intermediaries have recently been discussed
(Tönnissen and Teuteberg 2020); herewith, ROT can adequately explain the BT service provider's role
as a central orchestrator to increase efficiency across the SC. Further, the theory can also explain the
BT service provider's role as a neutral orchestrator in ensuring interoperability between different team
members in the SC. Due to the theory's potential to explain the BT phenomenon within the SC, the
subject needs to be paid attention by researchers. In this context, the following research question is
proposed:
RP6. As a new player in the supply chain, how can the BT service provider's role in improving
efficiency be explained within the scope of ROT?
Second, although it is argued that new products and services will emerge due to the BT integration in
SCM, while these possible innovations have not been discussed in a theoretical framework yet. In this
context, the following research agenda is proposed:
RP 7. Based on Porter (1985)'s competitive advantage strategies, which new products and services
will result in a competitive advantage due to the adoption of blockchain technologies to the supply
chain?
5.4 Academic implications
The research dissimilarly offers several academic contributions through methodological novelty and
theoretical contribution. From the methodological aspect, the Methodi Ordinarito is used as a
systematic literature review technique for the first time in the BT research domain. More particularly,
since the method allows to index high-quality papers considering their scientific relevance, the
findings thus created a convenient portfolio of relevant papers, 95.78 % of which are included in the
top-tier journals indexed in the SJR Q1 category.
Second, although the NN has been used to compare the before and after work routines and test new
organizational designs, in this study, the NN analysis was used for the first time in BT research. The
proposed framework differs this study from extant reviews as it is capable to visually present the story
flow between BT constructs and potential interconnections in the wake of providing clues about the
missing parts of the story. Consequently, we were able to go deeper into different constructs of the BT
phenomenon, such as disintermediation and transparency, and proposed a research agenda to shed
light on future research.
In terms of the theoretical contribution, this study initially set out to advance blockchain adoption in
logistics and SCM literature through a detailed theoretical discussion, including dynamic capability
view (DSV), information processing theory (IPT), resource orchestration theory (ROT), institutional
theory (IT), and upper echelon theory (UET). By doing so, we have proposed a research agenda that
significantly contributed to the theoretical grounds of future blockchain and SCM research. In a
nutshell, the ROT has recently been acknowledged as a poorly employed theory in SCM studies
(Craighead, Ketchen Jr, and Darby 2020). Therefore, to provide a concrete contribution to the issue,
we brought a new discussion that the theory could explain the BT service provider’s role, as a neutral
orchestrator, in solving the interoperability issues among SC members and achieving resource
efficiency throughout the network.
In addition, the UET emerges as another theory capable of explaining BT-related interoperability
through its approach to organizational leaders. Moreover, the UET has proven its potential to
contribute to the theoretical groundings of leader-oriented technology adoption models. Nevertheless,
UET remained underexplored in BT research. In this respect, we have enhanced our RP5 with UET to
explore organizational leaders' adoption behavior and to contribute the theoretical discussion in BT
and SCM research. To sum up, we suggested that BT in SCM research can significantly benefit from
ROT and UET to understand the roles of top management and service provider in BT adoption.
5.5 Practical implications
One of the prominent practical contributions of the research is that BT implications on logistics and
SCM are illustrated as a visualized network structure. Unlike traditional narrative inferences of the
extant literature, the proposed framework is a powerful tool for visually demonstrating the evolving
story of BT disruptions. Therefore, it is ensured that industry practitioners can evaluate the potential
disruptions of the technology more clearly. At this point, the investigation of narrative networks based
on a systematic and valid methodology is quite suitable for industry-oriented applications and can be
used by practitioners.
Another practical contribution of the research is that adaptation barriers are determined in four distinct
and well-designed categories, which provides a significant response to the RQ3. Therefore, by
considering these four categories, firms can develop software-embedded analytical tools and evaluate
their readiness for adaptation. In the transition to this new technology, to reveal and measure
organizational readiness, a detailed mapping can include various factors. Accordingly, the proposed
framework and adaption categories can be used by the firms implementing business process re-
engineering (BPR) for BT adoption. Besides, the proposed research model provides a clear
demonstration that managers should consider the potential risks of the technology and, above all, have
a digital transformation strategy.
From an engineering point of view, the proposed framework provides significant guidance to
engineers in production lines of the certain supply chain to demonstrate BT’s enabling effect on
intelligent manufacturing applications encompassing cloud manufacturing, cyber-physical systems,
and digital twins. In this direction, BT is emerging as a crucial technology to resolve the credibility
and security-related issues of the centralized production methods, particularly digital twins and cloud
manufacturing applications. However, it has also been revealed that technical drawbacks originating
from the consensus mechanism must be eliminated for BT to be fully implemented within the scope of
smart production techniques and to provide its promised benefits. Therefore, it can be beneficial to
develop efficient consensus algorithms such as Proof of Service Power (PoSP) proposed by Zhang et
al. (2021).
5.6 Limitations and future research direction
This study evaluated BT adoption barriers in four categories: governance and regulatory, economic,
technical, and business ecosystems; however, these categories require statistical validation. We
suggest the statistical validation of these categories and their subsequent integration into the
technology adaptation modeling methods in future studies. Second, NN analysis has been applied for
the first time to analyze the structured literature review. For this purpose, the authors manually
performed the data collection and extraction, but for practicality, UCINet and similar software may be
preferred for future studies.
As another limitation of this study, since some theories were not sufficient to address the focus and
scope of the study (e.g., force field theory of change), we just dealt with the limited number of suitable
theories. Although this study is the first approach revealing that the NN analysis is capable of
exhaustively disclosing both drivers and resisting forces of BT adoption in SC, it can further
incorporate Lewin’s force field theory (Lewin 1951), which emphasizes the equilibrium between
forces to and against change. At this point, we suggest that examining the TOE and force field
framework, previously proposed by Kouhizadeh, Saberi, and Sarkis (2021), can be enhanced by means
of the NN methodology and, thus, a holistic decision mechanism can be established.
6. Conclusion
Blockchain promises substantial benefits for logistics and SCM, while industry pioneers have already
started adopting the technology. For instance, IBM and Walmart established a BT partnership to
improve food safety through a distributed contract platform (Dolgui et al. 2020); IBM further joined a
partnership with Maersk for ocean transportation applications (Tönnissen and Teuteberg 2020).
Deloitte in the agri-food business (Kayikci et al. 2020) and Everledger in the luxury supply chain (Bai
and Sarkis 2020) are other examples of industrial initiatives of BT adoption. Nonprofit organizations
also use blockchain for humanitarian purposes; the Building Blocks application of the World Food
Program and the Blockchain Open-Loop Payments Pilot Project are two successful examples in
practice (Ozdemir et al. 2020).
BT promises significant utility for manufacturing industries as the modern production systems are
become shared, decentralized, and encompass the cooperation of various Industrial Internet of Things
(IIoT) objects. Although advanced technologies such as cloud manufacturing, digital twins, and IIoT
enabled cyber-physical systems to promise imminent operational efficiency, stand-alone use of such
technologies has limited applicability to production lines due to data security or interoperability-
related issues. At this point, BT is increasingly highlighted as a prominent information sharing layer
and coordination mechanism to enable advanced production systems and methodologies. Herewith,
this study addresses BT as an enabler of intelligent production and contributes to supply chain
research.
In line with our results on recent intelligent manufacturing practices, we draw a major conclusion that
manufacturers can consider an integrated BT and cloud manufacturing framework to deal with
untrusted parties. Furthermore, such an integrated solution allows overcoming the disadvantages
associated with the transmission of large amounts of digital twin data collected from various sources.
However, the aforementioned integrated framework is required to be supported with efficient
consensus algorithms to avoid excessive use of resources. In this point, this study provides a research
proposal to contribute extant literature with a particular focus on BT in cloud manufacturing.
Furthermore, BT-based information systems can reduce the vulnerability of cyber-physical systems,
provide interoperability between different autonomous cyber-physical system objects, and be used
within customized production. Today, IIoT, AI, and smart contracts incorporate customized intelligent
innovations such as federated learning – AI algorithms are sought to be adopted by manufacturing
industries to improve overall efficiency (Manimuthu et al. 2021).
However, despite all the efforts and enthusiasm shown in academics and practice, BT integration into
the SCM has progressed slowly. To contribute to the extant literature and practitioners' efforts on
integration, this research sets out to present the progress of integrating blockchain with logistics and
SCM in three sub-categories: enablers, threats, and adoption barriers. In addition, the theorization of
the blockchain and SCM relationship was also investigated in detail. Following our research aim, we
adopted an integrated novel research design. The proposed research design allows an in-depth analysis
of the BT disruptions and potentials in SCM as it provides a visual interpretation ability, including
BT-enabled advanced manufacturing. At this point, we have interpreted BT's potential disruptions in
SCM in detail and suggested a future research direction.
The proposed visual framework provides substantial clues to interconnectivity among the different
constructs of BT that will result in positive and negative disruptions to SCM. Therefore, to adequately
analyze the potential disruptions of BT, these interconnected relations should be considered, especially
at the statistical analysis level. Concerning adoption barriers, more research is needed in order to
evaluate BT adoption from a managerial perspective; UET theory can provide a sufficient theoretical
basis in this regard. Finally, although not enough effort has been put into contributing to BT research
on a theoretical level, ROT theory can contribute to this relationship on different grounds.
Data availability statement
The data that support the findings of this study are available from the corresponding author, upon
reasonable request.
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