Utilizing Fuzzy AHP in the Evaluation of Barriers to Blockchain Implementation in Reverse Logistics

Abstract

Digital technologies like blockchain, the Internet of Things, and smart warehouses have been developed due to the fourth industrial revolution, or “Industry 4.0.” Any business’ supply chain includes several stakeholders, including manufacturers, distributors, suppliers, and final consumers. The demand for firms to utilize these technologies to gain competitive advantages has intensified in the modern world due to rising worldwide rivalry. Additionally, the adoption of blockchain technology, in particular, can have a huge impact on a company’s reverse logistics, accelerating processes by decentralizing, tracking, and overseeing the delivery of items to final consumers. The goal of this study is to pinpoint those significant obstacles because several must be overcome for blockchain technology to be successfully implemented in reverse logistics. This study identified 16 impediments to the adoption of blockchain technology after a thorough analysis of the literature and expert opinion. The fuzzy AHP approach was used in this study to rank those barriers as this approach helps to address the complexity and uncertainty associated with decision-making in supply chain management and provides a more robust and reliable ranking of the barriers to blockchain adoption. A case study of Pakistan’s e-commerce industry was carried out. The results show that the high installation cost, stakeholders’ resistance to the blockchain, and the lack of top-management support are the critical success factors in blockchain adoption. From an industrial perspective, the study highlights the need for businesses to carefully evaluate the potential benefits and costs of adopting blockchain technology. It also underscores the importance of addressing the barriers to adoption to ensure successful implementation. By doing so, businesses can enhance their supply chain management and improve their overall competitiveness.

1. Introduction

The requirement to handle the reverse logistics system properly has arisen due to the industry’s shift in focus toward sustainability and the circular economy in the modern world. Reverse logistics is regarded as a crucial component of any supply chain, and businesses are currently developing supply chain improvement strategies, such as better transportation and mobility options, improved information and security protection systems, and increased employee and customer satisfaction [1,2].

The reverse logistics process involves managing the returns of the products and materials in the supply chain and properly disposing of the products. Due to this fact, it is difficult for businesses to pay attention to the supply chain’s reverse flow of materials and respond appropriately. This is because e-commerce businesses pay more attention to forward logistical activities and view reverse logistics as a cost indication. The fourth industrial revolution, however, has had a tremendous impact on corporate processes due to the advancement and evolution of digital technologies like the Internet of Things (IoT), smart sensors, blockchain, automatic guided vehicles (AGV), and drones. Among these digital technologies, blockchain technology has the potential to bring a revolutionary change in the reverse logistics process [3].

The successful application of blockchain technology can achieve supply chain sustainability in terms of social, environmental, and economic aspects. It enables businesses to monitor all stages of the supply chain process in real-time, allowing supply chain partners to collaborate and share information so that the right decision can be made and sustainable products can be produced, delivered, and returned from and to the customer [4]. Blockchain technology was first developed in 1991 as a digital document of data. At its early stage, less attention has been paid but the emergence of Bitcoin in 2009 has given global identity to blockchain technology. The blockchain can be explained as an electronic ledger, or a list of blocks connected by cryptography, that holds data constituting a block header and the block itself. They act as a node in the chain, providing information on the current block and the address of the other blocks [5]. In other words, supply chain partners can collaborate and interact with one another to create any type of record, such as product data, warranty information, and returned product information. The data in these records are checked and verified before being stored in the blockchain. Following that, these records are turned into a block and linked to the previous blocks in the blockchain [6]. When blockchain technology is effectively utilized, it can revolutionize a company’s supply chain and corporate operations and offers enormous advantages. The supply chain sustainability goals can be achieved through the blockchain, and it can be a great tool for enhancing supply chain performance, reducing lead times, improving traceability, handling bottlenecks, managing returns effectively, protecting data privacy, and managing warranty claims [7]. More specifically, blockchain technology enables companies to trace returned goods in real-time, enabling them to manage returns effectively and assisting in the products’ proper disposal to achieve sustainability. Various noteworthy studies have found that while there are significant challenges to the implementation of blockchain technology in e-procurement in the public sector in Pakistan, the potential benefits of blockchain technology make it a promising technology for the sector’s future growth, which could have significant implications for the e-commerce industry in Pakistan [8,9]. However, Amin et al. [10] notes that there are currently no large-scale implementations of blockchain technology in the logistics sector of Pakistan. Their study concludes that while there are significant challenges to adopting blockchain technology in Pakistan’s e-commerce industry, the potential benefits of blockchain technology make it a promising technology for the industry’s future growth.

Therefore, this research paper aims to utilize the fuzzy analytic hierarchy process (AHP) to evaluate the barriers to blockchain implementation in reverse logistics. The fuzzy AHP is a well-established method that is widely used to handle complex decision-making problems that involve imprecise or uncertain data. By using fuzzy AHP, this study aims to provide a comprehensive evaluation of the barriers to blockchain implementation in reverse logistics and to identify the most critical barriers that need to be addressed. Several studies have been conducted in the past that discuss the role of these digital technologies in achieving supply chain sustainability and sustainable production and delivery. However, to the best of our knowledge, no study has been conducted that has highlighted and identified the key barriers to the successful adoption of blockchain technology in Pakistan’s e-commerce industry. This compelled us to conduct this research, and the research gap and main contributions of this paper are given in the section below.

1.1. Research Gap and Contributions

1.1.1. Research Gap

The adoption of blockchain technology in supply chain management, particularly in the e-commerce industry, has gained significant interest in recent years. However, despite this growing interest, the literature on the obstacles to its adoption remains limited. This knowledge gap creates a challenge for decision-makers who wish to implement blockchain technology in their supply chains, particularly in the context of developing countries like Pakistan.

1.1.2. Contribution

(1)

This study aims to contribute to the literature by identifying and ranking the critical barriers to implementing blockchain technology in the reverse logistics of the e-commerce industry in Pakistan. The study employed a multi-criteria decision-making methodology, specifically the fuzzy AHP approach, to rank the barriers due to its ability to handle complexity and uncertainty in decision-making. The study identified 16 significant barriers, which were classified into four categories: organizational, technological, infrastructural, social, and economic barriers.

(2)

The study’s main contribution lies in its identification and ranking of critical barriers to the adoption of blockchain technology in the reverse logistics of the e-commerce industry in Pakistan. The study highlights the need for decision-makers to carefully evaluate the potential benefits and costs of blockchain adoption and address cultural and behavioral aspects of its adoption. Additionally, the study emphasizes the importance of investing in change management strategies, aligning the implementation of blockchain technology with an organization’s strategic objectives, and ensuring the right strategies and human resources are in place.

(3)

Overall, this study’s findings can aid decision-makers in prioritizing these barriers and improving the overall competitiveness of their supply chain management in the e-commerce industry. Additionally, it provides valuable insights for researchers and practitioners seeking to understand and address the challenges associated with blockchain adoption in supply chain management.

This paper’s structure is as follows: the Section 2 of this paper includes a detailed literature review on the benefits of blockchain technology with e-commerce reverse logistics, the current status of blockchain adoption in Pakistan’s e-commerce industry, and the identification of the key barriers to blockchain technology adoption. The Section 3 contains the methodology section, which includes detailed insights into the chosen methodology. The Section 4 explains the application of the proposed methodology. The results and interpretation section are covered in the Section 5 of this paper. Finally, Section 6 discussed the conclusions, recommendations, and future research work.

2. Literature Review

2.1. The Involvement of Blockchain in Supply Chain and Reverse Logistics

The process of controlling the movement of items from the end consumer back to the manufacturer is known as reverse logistics. Product returns, recycling, and disposal are all part of this process. Reverse logistics is an important part of supply chain management that faces several issues, including a lack of transparency and inefficiency. The use of blockchain technology in reverse logistics has the ability to alleviate some of these issues while also improving the overall efficiency and transparency of the operation. However, blockchain is a distributed ledger system that enables safe and transparent transactions without the use of middlemen. Blockchain technology has the potential to transform reverse logistics by offering a transparent and secure means to monitor the flow of items from the end user to the producer.

Zheng et al. [11] investigated the use of blockchain technology in electronic waste recycling. According to the study’s findings, blockchain technology may be used to produce a safe and transparent record of the recycling process, minimizing the danger of fraud and counterfeiting. Similarly, Wang et al. [12] investigated the use of blockchain technology in the administration of e-commerce refunds. According to the report, blockchain technology may be utilized to improve the transparency and efficiency of the returns process by allowing for real-time tracking and tracing of returned items. Wu et al. [13] investigated the usage of blockchain technology in managing end-of-life products in their study. The study discovered that blockchain technology might be utilized to develop a decentralized platform for the managing of end-of-life products, allowing for more transparency and efficiency. The study also discovered that blockchain technology could facilitate information exchange among stakeholders such as manufacturers, recyclers, and regulators. Pathak et al. [14] investigated the usage of blockchain technology in the pharmaceutical supply chain. The study discovered that blockchain technology might be used to track and trace the movement of pharmaceutical supplies, lowering the danger of counterfeit pharmaceuticals and improving overall supply chain transparency. Similarly, Park et al. [15] discovered that blockchain technology might be utilized to improve the transparency and efficiency of the food supply chain by offering real-time food monitoring and tracking. Zhang et al. [16] investigated the potential of blockchain technology in reverse logistics. The study discovered that blockchain technology, by providing a secure and transparent record of transactions, may be utilized to improve the transparency and efficiency of the reverse logistics process. The characteristics of blockchain, such as decentralization, immutability, and traceability, provide an efficient solution for supply chain management. Kouhizadeh & Sarkis [17] investigate the potential of blockchain technology to support sustainable and green supply networks. The authors use a thorough literature study to assess the present level of knowledge on blockchain and its potential uses in sustainable supply chain management. They discussed numerous possible blockchain benefits, such as increased transparency, traceability, and efficiency, and explores the obstacles and prospects of using blockchain in sustainable supply chain management. Furthermore, they offer a framework for blockchain-enabled sustainable supply chain management and emphasize the importance of further study to fully exploit blockchain’s potential in this field. Douladiris et al. [18] proposes a novel solution to the healthcare sector’s challenges in managing the reverse logistics of used medical equipment. The proposed blockchain framework offers a safe and transparent platform for tracking equipment throughout the reverse logistics process, ensuring data integrity and lowering the risk of errors and fraud. Raja et al. [19] demonstrates the potential of blockchain technology in improving the efficiency, transparency, and security of the manufacturing supply chain and logistics. They stipulate several advantages of implementing blockchain technology, including lower transaction costs, better inventory management, and improved data privacy and security. Khan et al. [20] proposes a framework for integrating reverse logistics and circular economy principles in the context of Industry 4.0 to enable sustainable resource management. The authors exhibit how the proposed framework can help reduce waste, optimize resource utilization, and generate new value streams by extending product lifespan through efficient reverse logistics processes. Rejeb [21] discusses the potential benefits of using blockchain technology in the tilapia supply chain in Ghana, such as increased transparency, traceability, and efficiency. The findings of this research suggest that blockchain technology has the potential to transform tilapia supply chain management in Ghana, potentially leading to better economic, social, and environmental outcomes for all stakeholders. Verhoeven et al. [22] provides a thorough analysis of all the potential uses for blockchain technology in the logistics and supply chain sector. The authors provide case studies and illustrations of how blockchain technology can improve transparency, traceability, and efficiency in various supply chain management functions, including product tracking, inventory management, and payment processing. They also point out the difficulties and restrictions related to the application of blockchain technology and recommend that caution is needed to ensure its successful adoption.

2.2. The Main Barriers to the Implementation of Blockchain Technology in Reverse Logistics

Saheb and Mamaghani [23] investigate the elements that impact the adoption of blockchain technology in the banking industry. The study identifies various barriers, including regulatory problems, lack of knowledge of the technology, and the high cost of implementation. It also highlights organizational values like trust, openness, and security as key elements that might help or impede blockchain adoption in banks. Sadhya et al. [24] identify and examine the primary impediments to blockchain technology’s widespread adoption. According to the authors, the key difficulties that impede enterprises from fully using the promise of blockchain technology include a lack of standards, regulatory uncertainty, interoperability issues, and security concerns. Sharma et al. [25] examine the barriers to blockchain technology adoption in India’s healthcare industry. The findings demonstrate that the lack of understanding, interoperability challenges, data privacy concerns, and regulatory restrictions as primary barriers to blockchain technology adoption in healthcare. Xu et al. [26] investigated the barriers and challenges to blockchain technology acceptance in the architecture, engineering, and construction (AEC) industries and offers a theoretical model to better explain the adoption process. The study highlighted key barriers, such as a lack of technical skills, doubt about the advantages of blockchain, and aversion to change. Biswas et al. [27] examine the barriers to blockchain technology application in the industrial and service sectors. According to the study, the biggest challenges to blockchain adoption are a lack of technical competence, high implementation costs, and regulatory uncertainty. Kaur et al. [28] emphasize the difficulties that small and medium enterprises (SMEs) in India encounter while using blockchain technology for supply chain finance. The research highlights challenges such as lack of understanding, high implementation costs, and poor regulatory backing as the key barriers to blockchain adoption. Caldarelli et al. [29] analyze the constraints that limit the use of blockchain technology in the sustainable fashion supply chain. They identified fundamental challenges to blockchain adoption as a lack of interoperability, data privacy issues, and inadequate legal frameworks as key barriers. Nazam et al. [30] investigates the barriers that hinder the adoption of blockchain technology in the textile supply chain from a sustainable business perspective. According to their findings, they identified factors such as lack of interoperability, unclear regulatory frameworks, and data privacy concerns as significant barriers to blockchain adoption. Farooque et al. [31] analyze the barriers to blockchain technology adoption in life cycle assessment in China. Their study reveals that lack of standards, data privacy issues, and insufficient technological infrastructure as important challenges to blockchain adoption in life cycle assessment in China. Subramanian et al. [32] investigate the possible uses of blockchain technology in reverse logistics procedures. Their study found how blockchain might improve transparency, traceability, and accountability in reverse logistics operations, resulting in increased efficiency, lower costs, and more customer satisfaction. Panghal et al. [33] discuss the challenges of using blockchain technology for reverse logistics in the food manufacturing business. Lack of standards, regulatory ambiguity, and data privacy issues, according to the authors, are key barriers to blockchain implementation in reverse logistics. Zkik et al. [34] investigates the barriers and enablers of blockchain adoption in e-enabled agriculture supply chains to enhance long-term performance. The study emphasizes the potential benefits of blockchain, such as increased transparency, traceability, and efficiency, and proposes several strategies to overcome the identified barriers, such as improving stakeholder trust, developing interoperable systems, and addressing regulatory and legal issues. Saberi et al. [35] investigate the potential of blockchain technology to improve long-term supply chain management (SSCM). They also highlight many barriers to blockchain implementation in SSCM, including technological complexity, interoperability, and regulatory ambiguity, and recommend potential solutions. Kaur et al. [36] outlines several significant barriers to adopting green supply chain management techniques in Canadian manufacturing companies. These include a lack of government rules and incentives, high implementation costs, a lack of knowledge and understanding of green practices, and poor supply chain partner collaboration. Based on the DEMATEL analysis, the authors prioritize these barriers, with the lack of government regulations and incentives being identified as the most significant barrier. Huang et al. [37] evaluates the critical success factors that enable successful implementation and examines the potential of blockchain technology to support circular supply chain management. The authors list several major impediments to blockchain adoption, such as technical difficulties, a lack of standards, and resistance to change. The study’s findings show that blockchain technology has a great deal of potential to advance circular supply chain management by enabling greater transparency and traceability. Chaouni et al. [38] examine the potential of blockchain technology to support circular digital supply chains and assesses the barriers to implementation. Several key barriers are identified by the authors, including a lack of trust, resistance to change, a lack of technological infrastructure, and high investment costs. The paper concludes that blockchain technology has significant potential to support circular digital supply chains by increasing transparency and traceability; however, successful implementation requires addressing these identified barriers through collaboration among stakeholders, including policymakers and industry practitioners. Elhidaoui et al. [39] identify key success factors for adopting blockchain technology in green supply chain management using an interpretive structural model. The authors point out several significant obstacles to the use of blockchain technology in green supply chain management, in which lack of standards, a lack of adequate technological infrastructure, and concerns about data privacy are found to be the most critical hindrances. Kazancoglu et al. [40] propose an empirical framework for determining and assessing the obstacles to adopting circular supply chains for sustainability in the textile industry. The lack of technological infrastructure, a lack of consumer awareness, and a lack of adequate regulatory support are the major obstacles found by this study.

From the literature review mentioned above, the common barriers to implementing reverse logistics are pointed out. Moreover, the barriers nominated for this study are categorized into four categories, and each category contains sub-barriers.

Table 1. Identified Barriers to Blockchain Adoption.

Main Barriers	Sub-Barriers	References
Technological and Infrastructure Barriers	Security, and privacy concerns	[28,31,38,39]
	Limited technology infrastructure	[17,30,38,39]
	Complexity	[14,29,35]
	Unavailability of blockchain tools	[24,26,39]
Organizational Barriers	The complexity of relevant parties	[5,23]
	High-level management support	[13,16]
	High investment costs	[12,33,36,38]
	Lack of appropriate organizational strategies and Human Resources	[14,17,31]
	Stakeholder Resistance to blockchain culture	[25,34,37]
Social and economic Barriers	Public fear and suspicion of supply chain technology	[4,40]
	Lack of knowledge and expertise	[29,30]
	Insufficient participation of relevant supply chain members	[15,40]
	High sustainability costs	[3,5]
External Barriers	Lack of involvement of external stakeholders	[27,28]
	Lack of government policies and financial support	[13,34,36]
	Market competition and uncertainty	[5,7]

explains the barriers to blockchain implementations used by this study, along with their references.

3. Method Selection

The AHP is a popular multi-criteria decision-making tool that allows decision-makers to prioritize a set of alternatives based on a set of criteria. It involves constructing a hierarchy of criteria and alternatives, pairwise comparison of the criteria and alternatives using subjective judgments and deriving weights that reflect the relative importance of the criteria and alternatives. The traditional AHP assumes that the decision-makers have precise and crisp judgments and can express them through numerical values. However, in many real-world situations, decision-makers may not have precise information or be unable to express their preferences precisely. This is where fuzzy extent analysis comes in.

Fuzzy extent analysis for AHP was proposed by Chang [41] as an extension to the traditional AHP method. The method allows decision-makers to handle uncertainties and imprecisions in decision-making by expressing their preferences using linguistic terms that are then converted into fuzzy numbers and used to derive weights of criteria and alternatives using fuzzy arithmetic. Fuzzy extent analysis allows decision-makers to express their preferences using linguistic terms, such as “very high,” “high,” “moderate,” “low,” and “very low,” instead of numerical values. These linguistic terms are then converted into fuzzy numbers, which represent the degree of membership of each term in a fuzzy set. The fuzzy numbers are then used to derive the weights of the criteria and alternatives using a fuzzy arithmetic approach. This approach allows decision-makers to deal with uncertainties and imprecisions in their judgments and provides a more robust and flexible decision-making tool.

The importance of fuzzy extent analysis in ranking barriers to blockchain implementation in reverse logistics has been recognized in the literature. For example, in a study by Ar et al. [42], the authors used fuzzy extent AHP to evaluate the barriers to blockchain adoption in logistics. They identified six criteria, including technology, organization, economy, policy, security, and trust, and used fuzzy extent AHP to derive weights for each criterion. The study found that technology-related barriers were the most significant, followed by policy-related barriers.

Another study by Lyu et al. [43] also used fuzzy extent AHP to evaluate the barriers to blockchain adoption in logistics. They identified five criteria, including technology, policy and regulation, trust, cost, and user acceptance, and used fuzzy extent AHP to derive weights for each criterion. The study found that policy and regulation-related barriers were the most significant, followed by technology-related barriers.

These studies demonstrate the importance of fuzzy extent analysis in handling the complexities and uncertainties of blockchain implementation in reverse logistics and deriving meaningful and reliable rankings of barriers. Fuzzy extent AHP allows decision-makers to express their preferences in linguistic terms, which can be more intuitive and reflect their true preferences and provides a more robust and flexible decision-making tool.

However, the overall goal of this study, along with the identified criteria and sub-criteria are presented in the hierarchical structure, shown in the Figure 1 below.

Fuzzy AHP Method

Definition 1. 

If  $\check{A_1}=\left(l_1,m_1,u_1\right)$ and  $\check{A_2}=\left(l_2,m_2,u_2\right)$ are representing two fuzzy triangular numbers, then algebraic operations can be expressed as follows [41,44,45]:

$$\check{A_1}+\check{A_2}=\left(l_1,m_1,u_1\right)+\left(l_2,m_2,u_2\right)=\left(l_1+l_2,m_1+m_2,u_1+u_2\right)$$

(1)

$$\check{A_1}-\check{A_2}=\left(l_1,m_1,u_1\right)-\left(l_2,m_2,u_2\right)=\left(l_1-l_2,m_1-m_2,u_1-u_2\right)$$

(2)

$$\check{A_1}\times \check{A_2}=\left(l_1,m_1,u_1\right)\times \left(l_2,m_2,u_2\right)=\left(l_1{l}_2,m_1{m}_2,u_1{u}_2\right)$$

(3)

$$\check{A_1}÷\check{A_2}=\frac{\left(l_1,m_1,u_1\right)}{\left(l_2,m_2,u_2\right)}=\left(\frac{l_1}{l_2},\frac{m_1}{m_2},\frac{u_1}{u_2}\right)$$

(4)

$${\check{A_1}}^{-1}=\left(l_1,m_1,u_1\right)=\left(\frac{1}{u_1},\frac{1}{m_1},\frac{1}{l_1}\right)$$

(5)

According to the method of extent analysis by Chang (1992) used by [44]

$$M_{gi}^1, M_{gi}^2, M_{gi}^3,\dots , M_{gi}^{m}i=\left(1,2,3,4,5,\dots n\right)$$

Additionally, all $M_{gi}^j\left(j=1,2,3,4,5,\dots ,m\right)$ are triangular fuzzy numbers, which are shown in

Table 2. TFNs of linguistics comparison matrix.

Linguistics Variables	Assigned TFN
Equal	(1, 1, 1)
Very low	(1, 2, 3)
Low	(2, 3, 4)
Medium	(3, 4, 5)
High	(4, 5, 6)
Very high	(5, 6, 7)
Excellent	(6, 7, 8)

.

The following are the steps in Chang’s analysis:

Step 1. The fuzzy synthetic extent $\left(S_i\right)$ value with relation to $ith$ criterion is defined as:

$$\begin{gathered} S_i={\displaystyle \sum }_{j=1}^m{M}_{gi}^j\times {\left[{\displaystyle \sum }_{i=1}^n\left.{\displaystyle \sum }_{j=1}^m{M}_{gi}^j\right]\right.}^{-1} \\ {\displaystyle \sum }_{j=1}^m{M}_{gi}^j=\left({\displaystyle \sum }_{j=1}^m{l}_{ij},{\displaystyle \sum }_{j=1}^m{m}_{ij},{\displaystyle \sum }_{j=1}^m{u}_{ij}\right) \\ {\left[{\displaystyle \sum }_{i=1}^n{\displaystyle \sum }_{j=1}^m{M}_{gi}^j\right]}^{-1}=\left(\frac{1}{{{\displaystyle \sum }}_n^{i=1}{{\displaystyle \sum }}_m^{j=1}{u}_{ij}},\frac{1}{{{\displaystyle \sum }}_n^{i=1}{{\displaystyle \sum }}_m^{j=1}{m}_{ij}}, \frac{1}{{{\displaystyle \sum }}_n^{i=1}{{\displaystyle \sum }}_m^{j=1}{l}_{ij}}\right) \end{gathered}$$

(6)

where $l$ is the lower limit value, $m$ is the most promising value, and $u$ is the upper limit value.

Step 2. The degree of Possibility of $S_2=\left(l_2,m_2,u_2\right)\ge \left(l_1,m_1,u_1\right)$ can be defined as:

$$[V\left(S_2\ge S_1\right){=}_{y\ge x}^{sup}\left[\min \left({\mu }_{s_1}\left(x\right),{\mu }_{s_2}\left(y\right)\right)\right]$$

where x and y indicate the values on an axis of the membership function of each criterion, as shown in Equation (7) below:

$$V\left(S_2\ge S_1\right)=\left\{\begin{array}{ll}1\hfill & if m_2\ge m_1\hfill \\ 0\hfill & if l_1\ge u_2\hfill \\ \frac{l_1-u_2}{\left(m_2-u_2\right)-\left(m_1-l_1\right)}\hfill & otherwise\hfill \end{array}\right.$$

(7)

Figure 2 depicts the graphical depiction of the intersection of fuzzy numbers, where $\mu d$ is the highest intersection point ${\mu }_{s_1}$ and ${\mu }_{s_2}$.

To compare $S_1$ and $S_2$, both $V\left(S_1\ge S_2\right)$ and $V\left(S_2\ge S_1\right)$ are required.

Step 3. The degree of Possibility for a convex fuzzy number $S$ to be greater than $k$ convex fuzzy numbers $S_i=\left(i=1,2,3,\dots k\right)$ can be defined as:

$$\begin{gathered} V(S\ge S_1,S_2,\dots ,\left.S_{k }\right)\hspace{1em}=V\left[\left(S\ge S_1\right),\left(S\ge S_2\right),\dots ,\left(S\ge S_k\right)\right] \\ =\min V\left(S\ge S_i\right),\hspace{1em}\hspace{1em}i=1,2,3,\dots ,k \end{gathered}$$

(8)

$$\mathrm{Assume} \mathrm{that} d^{\prime }\left(A_i\right)\hspace{1em}=\min V\left(S_i\ge S_k\right)$$

For $k=1,2,3,\dots ,n k\ne i,$ the weight vectors are given in Equation (9) as,

$$W^{\prime }={\left(d^{\prime }\left(A_1\right),d^{\prime }\left(A_2\right),\dots ,d^{\prime }\left(A_m\right)\right)}^T$$

(9)

Step 4. Via normalization, the normalized weight vectors are given in Equation (10) as,

$$W=(d\left(A_1\right),d\left(A_2\right),\dots ,d{\left(A_m\right)}^T$$

(10)

where W is the non-fuzzy number.

4. Application of the Proposed Method for Ranking Blockchain Adoption Barriers

Two-Phase Methodology

While the preceding part described the usefulness of fuzzy AHP in many scenarios, this study employed the fuzzy analytical hierarchy process (Fuzzy AHP) for prioritizing and ranking the barriers to blockchain deployment in reverse logistics of the e-commerce business. Moreover, the two-phase approach was adopted in this study. Nonetheless, Figure 3 shows the two-phase process followed in this investigation.

Phase 1: Barrier Identification and Selection

The barriers to blockchain implementation in reverse logistics of the e-commerce industry are found and picked in the first phase by literature research, and then the barriers are screened using expert discussions and opinions. Through screening, this study has found four main barriers to blockchain implementation, which are further subdivided into sixteen barriers. The main barriers to blockchain implementation include technological barriers, infrastructure barriers, organizational barriers, social and economic barriers, and environmental barriers.

Phase 2: Application of fuzzy AHP

This stage entails applying the fuzzy AHP technique to rank the identified barriers to blockchain implementation. The seven experts analyze the major criteria and sub-criteria using triangular fuzzy numbers (TFNs) from the table above.

Table 3. The main criteria computed fuzzy evaluation and the decision matrix.

	TB	OB	EB	SB	Weight	Rank
TB	(1, 1, 1)	(0.2, 0.25, 0.33)	(0.25, 0.33, 0.5)	(4, 5, 6)	0.256303	2
OB	(3, 4, 5)	(1, 1, 1)	(2, 3, 4)	(1, 2, 3)	0.420168	1
SB	(2, 3, 4)	(0.25, 0.33, 0.5)	(1, 1, 1)	(0.33, 0.5, 1)	0.172269	3
EB	(0.16, 0.2, 0.25)	(0.33, 0.5, 1)	(1, 2, 3)	(1, 1, 1)	0.151261	4

,

Table 4. Calculated pairwise comparison and decision matrix of sub-criteria (Technological Barriers).

	TB1	TB2	TB3	TB4	Weight	Rank
TB1	(1, 1, 1)	(1, 2, 3)	(0.2, 0.25, 0.33)	(0.33, 0.5, 1)	0.161392	4
TB2	(0.33, 0.5, 1)	(1, 1, 1)	(3, 4, 5)	(1, 2, 3)	0.316456	1
TB3	(3, 4, 5)	(0.2, 0.25, 0.33)	(1, 1, 1)	(0.33, 0.5, 1)	0.25	3
TB4	(1, 2, 3)	(0.33, 0.5, 1)	(1, 2, 3)	(1, 1, 1)	0.272152	2

,

Table 5. Calculated pairwise comparison and decision matrix of sub-criteria (Organizational Barriers).

	OB1	OB2	OB3	OB4	OB5	Weight	Rank
OB1	(1, 1, 1)	(0.25, 0.33, 0.5)	(3, 4, 5)	(0.33, 0.5, 1)	(0.25, 0.33, 0.5)	0.144928	5
OB2	(2, 3, 4)	(1, 1, 1)	(0.25, 0.33, 0.5)	(3, 4, 5)	(0.33, 0.5, 1)	0.2173913	3
OB3	(0.2, 0.25, 0.33)	(2, 3, 4)	(1, 1, 1)	(0.25, 0.33, 0.5)	(2, 3, 4)	0.2415458	1
OB4	(1, 2, 3)	(0.2, 0.25, 0.33)	(2, 3, 4)	(1, 1, 1)	(0.25, 0.33, 0.5)	0.15942	4
OB5	(2, 3, 4)	(1, 2, 3)	(0.25, 0.33, 0.5)	(2, 3, 4)	(1, 1, 1)	0.236715	2

,

Table 6. Calculated pairwise comparison and decision matrix of sub-criteria (Social & Economical Barriers).

	SB1	SB2	SB3	SB4	Weight	Rank
SB1	(1, 1, 1)	(0.25, 0.33, 0.5)	(3, 4, 5)	(0.33, 0.5, 1)	0.223975	3
SB2	(2, 3, 4)	(1, 1, 1)	(1, 2, 3)	(0.25, 0.33, 0.5)	0.242902	2
SB3	(0.2, 0.25, 0.33)	(0.33, 0.5, 1)	(1, 1, 1)	(3, 4, 5)	0.217666	4
SB4	(1, 2, 3)	(2, 3, 4)	(0.2, 0.25, 0.33)	(1, 1, 1)	0.315457	1

and

Table 7. Calculated pairwise comparison and decision matrix of sub-criteria (External Barriers).

	EB1	EB2	EB3	Weight	Rank
EB1	(1, 1, 1)	(0.25, 0.33, 0.5)	(2, 3, 4)	0.338553	2
EB2	(2, 3, 4)	(1, 1, 1)	(0.33, 0.5, 1)	0.372856	1
EB3	(0.25, 0.33, 0.5)	(1, 2, 3)	(1, 1, 1)	0.288591	3

show the fuzzy pair-wise comparison and decision matrix of the main barriers and sub-criteria barriers, as well as their estimated weight and ranking.

According to Equation (6), the fuzzy synthetic extent values for the four main criteria are calculated and presented in

Table 8. Fuzzy synthetic extent values of criteria.

Criteria		Calculations			Results
TB	=	(5.45, 6.58, 7.88)	×	(1/33.58, 1/25.61, 1/18.52)	(0.162, 0.256, 0.422)
OB	=	(7, 10, 13)	×	(1/33.58, 1/25.61, 1/18.52)	(0.208, 0.390, 0.701)
EB	=	(3.58, 4.83, 6.5)	×	(1/33.58, 1/25.61, 1/18.52)	(0.106, 0.188, 0.350)
SB	=	(2.49, 4.2, 6.25)	×	(1/33.58, 1/25.61, 1/18.52)	(0.074, 0.163, 0.337)

. However,

Table 9. V-values for main criteria.

	TB	OB	EB	SB
TB		1	0.734	0.653
OB	0.616		0.413	0.362
EB	1	1		0.903
SB	1	1	1

expresses the calculated value for the degree of possibility (V-values) by using Equation (7). The minimum (V-values) is also calculated by using Equation (8), which is presented below:

$$\mathrm{m} \left(\mathrm{TB}\right)=\min . V\left(S_1=S_{\mathrm{k}}\right)=\min (1, 0.616, 1,1)=0.616$$

Similarly, the same process is used for other main criteria, so, the minimum (V-values) for other criteria is as follows.

m (OB) = 1, m (EB) = 0.413, m (SB) = 0.362

According to Equation (9), the calculated weight vector of each criterion is presented below

W’ = (0.616, 1, 0.413, 0.362)^T

According to Equation (10), the final weights of the criteria are calculated through normalization are given below

W = (0.256, 0.420, 0.172, 0.151)

The calculation technique for reaming criteria is not described here because it is the same as the process for weight calculation of other criteria. The weights of other criteria, as well as the final results of pairwise comparisons of criteria and sub-criteria, are shown in

Table 10. Final Ranking of the blockchain implementation barriers.

Main Criteria	Weight	Sub-Criteria	Weight	Finalized Weight	Global Weight
Technological Barriers	0.256303	TB1	0.161392	0.04136525	14
		TB2	0.316456	0.08110862	4
		TB3	0.25	0.06407575	7
		TB4	0.272152	0.06975337	5
Organizational Barriers	0.420168	OB1	0.144928	0.06089411	8
		OB2	0.2173913	0.09134087	3
		OB3	0.2415458	0.10148982	1
		OB4	0.15942	0.06698318	6
		OB5	0.236715	0.09946007	2
Environmental Barriers	0.172269	EB1	0.223975	0.03858395	15
		EB2	0.242902	0.04184448	13
		EB3	0.217666	0.0374971	16
		EB4	0.315457	0.05434346	10
Social Barriers	0.151261	SB1	0.338553	0.05120987	11
		SB2	0.372856	0.05639857	9
		SB3	0.288591	0.04365256	12

.

5. Results and Discussion

Through a comprehensive literature review and expert opinions, this study has identified sixteen barriers to adopting blockchain. These barriers have been further classified into four main categories. Determining the significant impact of these barriers on implementing blockchain in reverse logistics of the e-commerce industry and vice versa is challenging. However, adopting blockchain in e-business can offer numerous benefits, such as enhanced traceability, effective warranty claims management, improved monitoring of reverse logistical flow and return management, better integration of supply chain partners, information sharing, and simplified e-contract processes. To aid decision-makers in prioritizing these barriers, this study employed the multi-criteria decision-making methodology, specifically the analytical hierarchy process in a fuzzy environment (fuzzy AHP) method to rank the critical barriers to implementing blockchain in the reverse logistics of the e-commerce industry in Pakistan. Moreover, the study highlights the significance of addressing the identified barriers to ensure the successful adoption of blockchain technology in reverse logistics. By addressing these barriers, businesses can enhance their supply chain management, improve their competitiveness, and ultimately reap the benefits of blockchain technology.

Table 3 displays the outcomes for the primary criteria (barriers) with the highest weight value signifying the most significant barriers. Based on the table, the ranking order for the primary barriers to implementing blockchain is OB > TB > SB > EB, indicating that organizational-related barriers are the most critical, followed by technological and infrastructure barriers and social and economic barriers. Conversely, external barriers are ranked the least, indicating their lesser importance in blockchain adoption. Although external barriers are not the primary hindrance to blockchain adoption, they still need to be addressed to ensure a favorable business environment for its adoption.

Moreover, the results of the fuzzy AHP analysis for the organizational barriers sub-criterion are presented in Table 5 which shows that high investment costs are the most critical sub-criterion that hinders the adoption of blockchain technology in reverse logistics, receiving the highest ranking. This finding suggests that implementing blockchain technology in reverse logistics requires a significant financial investment, which might pose a challenge for businesses operating in this sector, especially for small and medium-sized enterprises. Therefore, it is crucial for businesses to carefully evaluate the potential benefits and costs of blockchain adoption before planning. The second most important barrier identified in this study is stakeholder resistance to blockchain culture, which emphasizes the importance of addressing the cultural and behavioral aspects of blockchain adoption. This finding highlights the need for businesses to invest in change management strategies to help stakeholders understand the potential benefits of blockchain technology and overcome their resistance to change. The third-ranked sub-criterion is high-level management support, indicating that the involvement and support of top-level management are critical success factors in blockchain adoption. This finding underscores the importance of aligning the implementation of blockchain technology with the organization’s strategic objectives and ensuring that top-level management is committed to supporting the adoption process. The fourth-ranked sub-criterion is the lack of appropriate organizational strategies and human resources, which indicates that businesses need to have the right strategies and human resources in place to successfully implement blockchain technology in reverse logistics. This finding highlights the importance of having a clear understanding of the organization’s needs, capabilities, and resources before embarking on the adoption process. Finally, the complexity of relevant parties is identified as the least significant barrier to blockchain adoption in reverse logistics. This finding suggests that although dealing with multiple stakeholders with different interests and needs can be challenging, it is not the most critical factor hindering the adoption of blockchain technology in reverse logistics.

Table 4 displays the ranking order for the sub-criteria of technological and infrastructure barriers. The results reveal that limited technology infrastructure received the first ranking, indicating that it is the most significant barrier to blockchain adoption in reverse logistics. This suggests that the lack of adequate technological infrastructure to support blockchain implementation is a critical challenge that businesses need to overcome to achieve successful implementation. The second-ranked barrier is the unavailability of blockchain tools, indicating that the absence of appropriate tools to support blockchain implementation is also a significant obstacle. The third-ranked barrier is complexity, which suggests that the complex nature of blockchain technology could hinder its adoption. The fourth-ranked barrier is security and privacy concerns, which implies that businesses may be hesitant to adopt blockchain technology due to concerns over security and privacy. These findings highlight the need for businesses to focus on building a robust technological infrastructure and investing in appropriate blockchain tools to support implementation. Additionally, they must address the complexity of the technology and provide adequate security and privacy measures to overcome these barriers.

In Table 6, the sub-criteria ranking for social and economic barriers is presented as SB4 > SB2 > SB1 > SB3. The ranking index shows that high sustainability costs receive the first ranking, indicating that the cost of maintaining sustainable blockchain infrastructure is perceived as a significant obstacle for businesses. The second most critical barrier to blockchain adoption in reverse logistics is a lack of knowledge and expertise, highlighting the importance of developing specialized knowledge and expertise in blockchain technology. This result suggests that businesses must invest in training and education to build the necessary expertise to implement blockchain technology successfully. Public fear and suspicion of supply chain technology are ranked third, indicating that businesses must also address public perceptions and fears related to blockchain technology to gain wider acceptance. Finally, insufficient participation of relevant supply chain members receives the last rank, highlighting the importance of involving all relevant supply chain members in the blockchain implementation process to ensure its success.

Table 7 presents the ranking order for the sub-criteria of external barriers, which are ranked as EB2 > EB1 > EB3. According to the results, the sub-criterion lack of government policies and financial support received the highest ranking among the external barriers, indicating that it is the most significant obstacle to adopting blockchain technology in reverse logistics. This result is not surprising as the lack of government policies and support can make it challenging for businesses to invest in blockchain technology, especially in developing countries like Pakistan. Without clear guidelines and support from the government, businesses may be hesitant to invest in new technology due to the uncertainty and risks associated with it. The second-ranked sub-criterion, lack of involvement of external stakeholders, suggests that the involvement of external stakeholders is essential for the successful adoption of blockchain technology in reverse logistics. This result implies that businesses must consider the opinions and needs of external stakeholders, such as suppliers, customers, and other partners, to ensure that they are on board with the adoption of blockchain technology. The third-ranked sub-criterion, market competition and uncertainty, highlights the importance of understanding the competitive landscape and the uncertainties associated with implementing blockchain technology in reverse logistics. Businesses must carefully evaluate the potential benefits and risks of adopting blockchain technology, considering the competition in the market, and the potential disruption it may cause to their supply chain operations.

Practical and Managerial Implications

The study’s findings have several practical and managerial implications. First, businesses operating in the e-commerce reverse supply chain in Pakistan must focus on creating awareness and understanding of blockchain technology among supply chain partners. Second, building trust among supply chain partners is crucial for successful blockchain adoption. Third, businesses should invest in technical expertise and infrastructure to support blockchain adoption. Fourth, policymakers and government bodies must provide support and incentives to encourage blockchain adoption in the e-commerce reverse supply chain. Overall, addressing the identified barriers can lead to improved efficiency, reduced costs, and greater competitiveness, making blockchain adoption a critical factor in achieving supply chain sustainability.

6. Conclusions

The fourth industrial revolution has seen the rise of digital technologies, such as blockchain, which have the potential to transform supply chain operations, notably in reverse logistics. To successfully apply blockchain technology in reverse logistics, it is critical to identify and overcome the constraints that prevent its widespread acceptance. After a thorough literature analysis, expert comments, and conversations, this study identified 16 impediments to blockchain implementation in the e-commerce reverse supply chain in the context of Pakistan. The impediments are divided into four categories: technological, organizational, economic, and legal.

To rank the identified barriers, the fuzzy analytical hierarchy process (fuzzy AHP) method was employed. The results show that the most significant barriers are the lack of awareness and understanding of blockchain technology, followed by the lack of trust among supply chain partners and the lack of technical expertise. This study provides insights into the key barriers to blockchain adoption in the e-commerce reverse supply chain in Pakistan and presents policymakers, logistics managers, organization officials, and government bodies with the necessary information to make informed decisions. By addressing these barriers, businesses can realize the full potential of blockchain technology and achieve supply chain sustainability, leading to improved efficiency, reduced costs, increased customer satisfaction, and greater competitiveness.

Limitation and Future Research Direction

Despite the contributions of this study in identifying the barriers to blockchain adoption in the context of Pakistan’s e-commerce industry, it has some limitations. First, this study only focused on the e-commerce industry in Pakistan, which may limit the generalizability of the findings to other countries and industries. Second, the expert opinions used in this study were limited to those who are familiar with the e-commerce industry in Pakistan, which may not reflect the opinions of experts in other countries. Third, the identified barriers were only ranked based on their importance, and no further analysis was conducted to determine how they interact with each other.

To address the limitations of this study, future research could explore the barriers to blockchain adoption in other industries and countries. Additionally, future studies could investigate how the identified barriers interact with each other and how they can be addressed simultaneously. Moreover, other MCDM methods will be used, such as TOPSIS, ANP, and DEMATEL, to rank the identified barriers. Finally, future research could explore how blockchain adoption affects the performance and sustainability of the reverse logistics process in the e-commerce industry.