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Blockchain Technology for �Agricultural Supply Chain : �Modeling using DEMATEL – ISM

Presented By-

Akshobhya Theertha R 1JS18IM003

Navneeth S 1JS18IM018

Rahul Krishna D 1JS18IM025

S Naveen 1JS18IM029

Under the Guidance of

Dr. Vijay Kumar M Dr. Vanishree Beloor Associate Prof. Assistant Prof.

Dept. Of IEM

JSS Academy of Technical Education, Bengaluru-60.

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Abstract

Supply Chain Management (SCM) is a crucial component in increasing the competitiveness of any country's agriculture industry.

Many businesses have prioritized the implementation of Blockchain Technology (BT) as a dependable and secure method of digitizing transactions with transparency and traceability.

This Project has been pursued to address the problems of BT adoption in ASC, selected 15 enablers from literature.

Analyzed their cause and effect magnitude via Interpretive Structural Modeling (ISM) and Decision-Making Trial and Evaluation Laboratory (DEMATEL) Analysis respectively.

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Introduction

A Blockchain is a decentralized database that is shared among computer network nodes.
It collects information together in groups, known as blocks and are linked to the previously filled block, forming a chain of data.
BT can reduce risks, increase the efficiency of the ASCs and ensure transparency and traceability in the ASCs (Yiannas, 2018).

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Fig. 1. Representation of a Blockchain

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Introduction

Agriculture supply chain (ASC) is similar to any other consumer product supply chain having suppliers, leading companies, customers, and distribution partners.

The Indian ASC has challenges like as satisfying the demands of an ever-increasing population, inadequate infrastructure for preserving horticulture crops, and quality that result in yearly food losses of up to 40% (Ritchie, Reay, & Higgins, 2018)

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Fig. 2. Typical Blockchain Technology used in Agricultural Supply Chain

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Literature Review

Sl. No.	Author, Title	Findings
1.	Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic cash system. Bocek, T., & Stiller, B. (2018). Smart contracts–blockchains in the wings.	BT eliminates the role of a third party or an intermediary to control and overlook the system and deploys a transparent consensus mechanism which ensures that only valid transactions are executed
2.	Shankar, R., Gupta, R., & Pathak, D. K. (2018). Modeling critical success factors of traceability for food logistics system.	BT adoption in the supply chain enhances visibility and transparency. The critical factors for any logistics and supply chain organizations are transparency and traceability.
3.	Li, J., & Wang, X. (2018). Research on the application of blockchain in the traceability system of agricultural products.	The ability of BT in product traceability, authenticity, and performing real-time transactions will bring tremendous improvements in food traceability which in turn will have a positive impact on food quality, safety, and sustainability
4.	Kamble, S., Gunasekaran, A., & Arha, H. (2019). Understanding the Blockchain technology adoption in supply chains-Indian context.	The supply chain practitioners are found to be least concerned about the lack of control or have any distrust on the potential of blockchain because of highly skilled technical employees and experience in supply chain domain.
5.	Sanghera, A. (2018). How adoption of blockchain technology will disrupt agriculture. Understanding the implications of blockchain technology in agriculture.	By consolidating the links between producers, consumers, farmers, and markets the ASCs can generate higher incomes using BT.

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Problem Statement

Current Agricultural Supply Chain (ASC) in India and developing countries are facing issues on keeping up with sustainability, standards, adopting modern technologies, structure of movement of goods and payments.

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Objectives

To identify key enablers in driving Blockchain Technology for ASC from the literature.
To establish the interaction among identified enablers for BT based ASC and develop a model for the same identified.
To establish a contextual interrelationship between the enablers by classifying into caused and influenced clusters.
To Develop a model helpful theoretically in adoption of BT in ASC.

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Methodology

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Present Softwares/Tools Used

Harzing’s Publish and Perish for sourcing research papers.
Google Scholar.
Microsoft Excel (2016) for DEMATEL Analysis
Online Auto Solver tool for ISM Modeling and MICMAC Analysis [url: http://smartism.sgetm.com]

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Selected Enablers

Sl. No.	Enabler	Supports via LR
1.	Governance and Policy	Wolfert et al. 2017; Armanda et al. 2019; Aryal et al. 2020
2.	QC, Food and Agricultural Standards	Fanzo 2015; Ben-Daya et al. 2019 ; Bosona and Gebresenbet 2013; Van Hulst et al. 2020
3.	Top Mgmt Support	Bauk et al. 2017 ; Bauk et al. 2017 ; Haddud et al. 2017; León-Bravo et al. 2019
4.	3PLs	Fernandez and Kekale 2007; Söderberg and Bengtsson 2010 ; Yang and Zhao 2016
5.	Information Sharing	Min et al. 2005; Wu et al. 2016; Bhattacharya et al. 2010; Marucci et al. 2017; Parry et al. 2016
6.	IoT Infrastructure	Ahmed et al. 2017; Kumar and Patel 2014; Balamurugan et al. 2016
7.	Smart Contracts	Xu et al., 2016; Nakamoto, 2008.
8.	Training	Sharma and Vrat 2018; Kulikov et al. 2020
9.	Co-ordination and Collaboration	Luvisi 2016; Nakandala et al. 2017; Long et al. 2019
10.	Security and Privacy	Nakamoto, 2008; Ying et al., 2018 ; Ølnes, 2016; Huckle et al., 2016; Farell, 2015; Chen et al., 2018
11.	Provenance	Wang et al., 2019; Li & Wang, 2018
12.	Immutability	Tran et al., 2017; Kshetri, 2017
13.	SC Responsiveness	Yan et al. 2017; Adnan et al. 2018; Barenji et al. 2017; Ahmed et al. 2017; Irfan et al. 2019
14.	SC Integration	Hardgrave et al. 2011; Kumar et al. 2016; Jing et al. 2014; Mor et al. 2018a ; Flynn et al. 2010
15.	Traceability and Transparency	Abeyratne & Monfared, 2016; Kshetri, 2017 ; Tian, 2016; Jeppsson & Olsson, 2017

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ISM (Interpretive Structural Modeling)

1. Structural Self-Interaction Matrix (SSIM)

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ISM (Interpretive Structural Modeling)

2. Reachability Matrix (RM)

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ISM (Interpretive Structural Modeling)

3. Level Partitioning (LP)

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ISM (Interpretive Structural Modeling)

4. Reduced Conical Matrix (RCM)

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ISM (Interpretive Structural Modeling)

5. Developed Model

LEVELs
Level 1
Level 2
Level 3
Level 4
Level 5
Level 6
Level 7
Level 8
Level 9
Level 10

Co-ordination and Collaboration

Training

Smart Contracts

Top Mgmt Support

QC, Food and Agricultural Standards

Governance and Policy

Traceability and Transparency

SC Integration

SC Responsiveness

Immutability

Provenance

Security and Privacy

IoT Infrastructure

Information Sharing

3PLs

Dependence Power

Driving Power

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ISM (Interpretive Structural Modeling)

6. MICMAC Analysis

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DEMATEL Analysis

1. Direct Relationship Matrix

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DEMATEL Analysis

2. Normalization of Direct Relationship Matrix

3. Estimation of Total-Relation Matrix

4. Determining Alpha

(Threshold Value)

0.2733

5. Finding enablers that are Cause/Effect

Sl. No.	Ri + Ci	Ri - Ci	Identity
1	8.360688	0.594585	Cause
2	3.972855	-0.24653	Effect
3	8.342536	0.130823	Cause
4	8.643326	-0.83122	Effect
5	9.863861	0.065441	Cause
6	9.154874	-0.05289	Effect
7	9.519321	0.632685	Cause
8	7.726233	0.380558	Cause
9	9.347857	-0.00791	Effect
10	7.854284	0.227404	Cause
11	7.702483	0.121073	Cause
12	5.474048	0.333644	Cause
13	9.580775	-0.14098	Effect
14	9.233458	-0.96863	Effect
15	8.190399	-0.23805	Effect

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DEMATEL Analysis

6. Digraph Plot

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Conclusion

Results

Traceability and Transparency was identified as the most influenced and achievable variable in ISM-MICMAC Analysis.

Information sharing was identified as the most important enabler via DEMATEL Analysis with a rj + dj value of 9.864, which meant that Information Sharing played a critical role in maintaining the stability and success of an agricultural supply chain backed by Blockchain Technology parameters

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Conclusion

Results

SC Integration was found to be influenced the most with an rj – dj value of -0.969 depicting that the overall supply chain integration is successful with correct planning, proper implementation and control of other supply chain factors involved.

Based on the results found and depicted in our project, it will aid the ASC practitioners in adopting Blockchain Technology to their stream of value chain process.

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Thank You!