Blockchain 3.0 for Sustainable Development 3110702452, 9783110702453

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Deepak Khazanchi, Ajay Kumar Vyas, Kamal Kant Hiran, Sanjeevikumar Padmanaban (Eds.) Blockchain 3.0 for Sustainable Development

De Gruyter Frontiers in Computational Intelligence

Edited by Siddhartha Bhattacharyya

Volume 10

Blockchain 3.0 for Sustainable Development Edited by Deepak Khazanchi, Ajay Kumar Vyas, Kamal Kant Hiran and Sanjeevikumar Padmanaban

Editors Deepak Khazanchi College of Information Science and Technology University of Nebraska at Omaha Omaha 68182, NE, USA [email protected] Kamal Kant Hiran Sir Padampat Singhania University (SPSU) Department of Computer Science and Engineering Udaipur-Chittorgarh Rd Bhatewar 313601, Rajasthan, India [email protected]

Ajay Kumar Vyas Adani Institute of Infrastructure Engineering Department of Information and Communication Technology Shantigram Township, Gandhinagar Hwy Ahmedabad 382421, India [email protected] Sanjeevikumar Padmanaban CTIF Global Capsule Department of Business Development and Technology Aarhus University Birk Centerpark 40, 7400 Herning, Denmark [email protected]

ISBN 978-3-11-070245-3 e-ISBN (PDF) 978-3-11-070250-7 e-ISBN (EPUB) 978-3-11-070257-6 ISSN 2512-8868 Library of Congress Control Number: 2021935505 Bibliographic information published by the Deutsche Nationalbibliothek The Deutsche Nationalbibliothek lists this publication in the Deutsche Nationalbibliografie; detailed bibliographic data are available on the Internet at http://dnb.dnb.de. © 2021 Walter de Gruyter GmbH, Berlin/Boston Cover image: shulz/E+/getty images Typesetting: Integra Software Services Pvt. Ltd. Printing and binding: CPI books GmbH, Leck www.degruyter.com

Preface Blockchain is an invaluable tool for achieving transparency and trust but transformative possibilities to benefit society more broadly are emerging that will bring a bright future for sustainable development. These technologies will reduce unsustainability that disturbs societies, financial resources, environment and natural resources for developing as well as developed countries. In the blockchain database, distributed database over peer-to-peer networks and the transaction, data will be packed into blocks by miner nodes, and all blocks are linked together via hash operations. Diffusion and adoption of blockchain in various sectors like finance, healthcare, infrastructure, higher education, environment, renewable energy and communication provide the revolutionary changes in the digital era of the world. The state of the art of blockchain models is most useful for forecasting and prediction of various sectors for sustainable development. This book covers the application of blockchain for supply chain managementbased business. This book also covers blockchain application for health, science, identity, governance, education, public goods and various aspects of culture and communication. The book provides compressive studies about the architecture of blockchain technology, distributed data storage, peer-to-peer transmission, a consensus mechanism, encryption algorithms and smart contracts which will be very useful for sustainable development for architectural design and smart buildings, healthcare services and systems, affordable and sustainable green and clean energy, sustainable development in agriculture, accurate forecasts of air pollution levels through fog computing and sustainable learning and others. This book has 10 intensive chapters on the application of blockchain and relevance as follows: Chapter 1 discusses the components of a blockchain, architecture, protocol and applications. The chapter focuses on the database block, collection of a block, harsh cryptography and consensus protocols. It also presents several consensus protocols such as proof of work, proof of stake and proof of elapsed time with its advantages and disadvantages. In addition, it also discusses the applications of blockchain in Internet of things, cloud computing, healthcare and medicine, storage, smart city development, financial and education briefly. Chapter 2 discusses business applications of blockchain technology in terms of recording, valuing and verifying transactions. It also explores the ramifications of blockchain for the audit of corporate financial reports and associated accounting challenges, especially those involving cryptocurrencies. In this chapter, the implementation of blockchain for auditing is also discussed. Chapter 3 investigates various cases of using blockchain in a smart city environment. This chapter introduces a greater understanding of the current urban crisis that is being tackled in beautiful urban areas. In this way, it reflects the ideas of blockchain innovation and the assessment of its ability to transform power into making our urban communities more prominent. https://doi.org/10.1515/9783110702507-202

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Chapter 4 describes the use of blockchain for removal of supply chain barriers and developing sustainable supply chain management system. It concludes that it can decrease resource consumption and reducing greenhouse gas emissions; can verify the product to be green in terms of greenhouse gas emissions level; can improve recycling, emission trading schemes efficacy, and governance and information management mechanism. Chapter 5 provides the application of blockchain for sustainable development in the energy sector. It includes studies for application case analysis of blockchain technology, and main advantages and consequences for the risks of using blockchain in the energy production industry by posing and discussing two case studies as practicable. Chapter 6 describes the application of blockchain in the field of accounting. It also presents the advantages and challenges to adopting blockchain in accounting and for that purpose, it explores the possibility with the perception of accounting professionals after collecting data through the opinion survey method. The study concluded that BT makes real-time accounting possible soon. The study revealed that the perceived mind-set of professionals may become a big challenge to adopt BT in accounting. Chapter 7 aims at explaining different applications, approaches and models of blockchain 3.0 implementation across the entire value chain of the healthcare system. It discusses the five most important use cases that can lead to transformation and adds to the sustainability of the entire healthcare industry. The chapter discusses the blockchain 3.0 adoption journey from the technological perspective, the viewpoint of challenges, implementation strategies and the way forward. The chapter presents how blockchain technology can impact and affect the five broad categories of the healthcare space and adds to its sustainability. Chapter 8 presents the application of blockchain for enhanced fingerprint authentication. This chapter discusses the implementation of secured automatic log-in based on fingerprint authentication and enhancement of security using blockchain technology. It briefly describes different steps of the user authenticated using fingerprint verification, development of software and enhancement of security. Chapter 9 describes novel feature extraction and classification architecture for emotion recognition using electroencephalography (EEG). These studies are fruitful for researchers who surveyed the methods of emotion recognition using EEG. We have concentrated on machine learning and neural network methods. It also summarizes that the EEG signals and preprocessing techniques, feature extraction and classification techniques can be used for emotion recognition. Chapter 10 describes the application of blockchain for sustainable fashion technology. Sustainable fashion has gained attention nowadays, and it is a recent movement that aims at reducing the environmental pollution caused by the fashion industry. Researchers have been deeply analyzing this fashion industry sustainability. This chapter

Preface

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presents a brief survey about sustainable fashion, the role of blockchain technology and its importance. Deepak Khazanchi Ajay Kumar Vyas Kamal Kant Hiran Sanjeevikumar Padmanaban

Contents Preface

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Editors’ brief bio List of contributors

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Himani Mittal Chapter 1 Blockchain technology: architecture, consensus protocol and applications 1 Sunita Ahlawat, Abhishek Tripathi Chapter 2 Blockchain: implications for accounting and audit practice

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Hemant Kumar Saini, Kusum Lata Jain, Kamal Kant Hiran, Amit Bhati Chapter 3 Paradigms to make smart city using blockchain 21 Vineet Chouhan, Raj Bahadur Sharma, M. L. Vasita, Shubham Goswami Chapter 4 Measuring barriers in adoption of blockchain in supply chain management system 37 Vineet Chouhan, Shubham Goswami, Manish Dadhich, Pranav Saraswat, Pushpkant Shakdwipee Chapter 5 Emerging opportunities for the application of blockchain for energy efficiency 63 Gourav Surana, Shurveer S. Bhanawat, Vineet Chouhan Chapter 6 Measuring professionals’ perception on blockchain-based futuristic accounting 89 Ashok Bhansali, Jolly Masih, Meenakshi Sharma Chapter 7 Blockchain 3.0 for sustainable healthcare 101

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Dipesh Vaya, Teena Hadpawat Chapter 8 Enhanced fingerprint authentication using blockchain

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Manish Jain Chapter 9 Novel feature extraction and classification architecture for emotion recognition using EEG 131 R. Sandhiya, A. M. Boopika, M. Akshatha, S. V. Swetha, N. M. Hariharan Chapter 10 Future of fashion industry: sustainable fashion using blockchain 145 Index

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Editors’ brief bio Kamal Kant Hiran works as an assistant professor at the School of Engineering, Sir Padampat Singhania University (SPSU), Udaipur, Rajasthan, India, as well as a research fellow at the Aalborg University, Copenhagen, Denmark. He is a gold medalist in MTech (Hons.). He has more than 16 years of experience as an academic and researcher in Asia, Africa and Europe. He worked as an associate professor and academics head at the BlueCrest University College, Liberia, West Africa; head of department at the Academic City College, Ghana, West Africa; senior lecturer at the Amity University, Jaipur, Rajasthan, India; assistant professor at the Suresh Gyan Vihar University, Jaipur, Rajasthan, India; and visiting lecturer at the Government Engineering College, Ajmer. He has several awards to his credit such as International travel grant for attending the 114th IEEE Region 8 Committee Meeting at Warsaw, Poland; International travel grant for Germany from ITS Europe, Passau, Germany; Best Research Paper Award at the University of Gondar, Ethiopia and SKIT, Jaipur, India; IEEE Liberia Subsection Founder Award; Gold Medal Award in MTech (Hons.); IEEE Ghana Section Award – Technical and Professional Activity Chair; IEEE Senior Member Recognition, IEEE Student Branch Award, Elsevier Reviewer Recognition Award and the Best Research Paper Award from the University of Gondar, Ethiopia. He has published 35 scientific research papers in SCI/Scopus/Web of Science and IEEE Transactions Journal, conferences, 2 Indian patents and 9 books with internationally renowned publishers. He is a reviewer and editorial board member of various reputed international journals in Elsevier, Springer, IEEE Transactions, IET, Bentham Science and IGI Global. He is an active member in organizing many international seminars, workshops and conferences. He has made several international visits to Denmark, Sweden, Germany, Norway, Ghana, Liberia, Ethiopia, Russia, Dubai and Jordan for research exposures. His research interests focus on cloud computing, machine learning and intelligent IoT. Dr. Deepak Khazanchi is full professor of information systems and quantitative analysis, associate dean for academic affairs, and community engagement and internationalization officer at the College of Information Science & Technology (IS&T), University of Nebraska at Omaha (UNO). Prior to becoming associate dean, he served as chair of the Information Systems and Quantitative Analysis Department at the College of IS&T. He is also an affiliate faculty in UNO’s International Studies and Programs and the Leonard and Shirley Goldstein Center for Human Rights (GCHR). He has served as a visiting/adjunct full professor with the Center for Integrated Emergency Management (CIEM) at the University of Agder (Kristiansand, Norway), University of International Business and Economics (Beijing, China) and Management Center Innsbruck (Innsbruck, Austria). Dr. Khazanchi currently serves on the Board of Management for the Sir Padampat Singhania University (Udaipur, India) and the Executive Council for Bennett University (Noida, India). He is also an active advisor and external examiner for a number of universities around the world.

https://doi.org/10.1515/9783110702507-204

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Ajay Kumar Vyas has more than 15 years of teaching and research experience. He is presently working as assistant professor at Adani Institute of Infrastructure Engineering, Ahmedabad (India). He has completed his BE from Ujjain Engineering College, Ujjain, and MTech for Shri GS Institute of Technology and Science, Indore, with Honors and PhD from Maharana Pratap University of Agriculture and Technology, Udaipur (Raj.). He is a senior member of IEEE and senior member of IACSIT (Singapore). He is a reviewer of international peer-review journals in Springer, IET, OSA, IGI Global and many more. He is author of several research papers in peerreviewed international journals and conferences, textbooks and book chapters published by a renowned publisher.

Sanjeevikumar Padmanaban (Member’12–Senior Member’15, IEEE) received his PhD in electrical engineering from the University of Bologna, Bologna, Italy, in 2012. He was an associate professor at VIT University from 2012 to 2013. In 2013, he joined the National Institute of Technology, India, as a faculty member. In 2014, he was invited as a visiting researcher at the Department of Electrical Engineering, Qatar University, Doha, Qatar, funded by the Qatar National Research Foundation (Government of Qatar). He continued his research activities with the Dublin Institute of Technology, Dublin, Ireland, in 2014. Further, he served as an associate professor at the Department of Electrical and Electronics Engineering, University of Johannesburg, Johannesburg, South Africa, from 2016 to 2018. Since 2018, he has been a faculty member with the Department of Energy Technology, Aalborg University, Esbjerg, Denmark. He has authored over 300 scientific papers. S. Padmanaban was the recipient of the Best Paper cum Most Excellence Research Paper Award from IET-SEISCON’13, IET-CEAT’16, IEEE-EECSI’19, IEEE-CENCON’19 and five best paper awards from ETAEERE’16-sponsored Lecture Notes in Electrical Engineering, Springer book. He is a fellow of the Institution of Engineers, India, the Institution of Electronics and Telecommunication Engineers, India, and the Institution of Engineering and Technology, UK. He is an editor/associate editor/editorial board for refereed journals, in particular the IEEE Systems Journal, IEEE Transaction on Industry Applications, IEEE Access, IET Power Electronics, IET Electronics Letters and Wiley – International Transactions on Electrical Energy Systems, subject editorial board member – Energy Sources – Energies Journal, MDPI, and the subject editor for the IET Renewable Power Generation, IET Generation, Transmission and Distribution, and FACTS journal (Canada).

List of contributors Himani Mittal Goswami Ganesh Dutta Sanatan Dharma College Chandigarh India [email protected]

Raj Bahadur Sharma College of Business Administration Alkharj Kingdom of Saudi Arabia [email protected]

Sunita Ahlawat The College of New Jersey Ewing, NJ USA [email protected]

M. L. Vasita Department of Business Administration Rajasthan University Jaipur, Rajasthan India [email protected]

Abhishek Tripathi The College of New Jersey Ewing, NJ USA [email protected]

Gourav Surana Mohanlal Sukhadia University Udaipur, Rajasthan India [email protected]

Hemant Kumar Saini Manipal University Jaipur, Rajasthan India [email protected]

Manish Dadhich Sir Padampat Singhania University Udaipur, Rajasthan India [email protected]

Kamal Kant Hiran Sir Padampat Singhania University Udaipur, Rajasthan India [email protected]

Pranav Saraswat Nirma University Ahmedabad, Gujarat India [email protected]

Vineet Chouhan Sir Padampat Singhania University Udaipur, Rajasthan India [email protected]

Pushpkant Shakdwipee Pacific Institute of Management Udaipur, Rajasthan India dr.pushpkantshakdwipee@pacific-university. ac.in

Shubham Goswami Sir Padampat Singhania University Udaipur, Rajasthan India [email protected]

https://doi.org/10.1515/9783110702507-205

Shurveer S. Bhanawat Mohanlal Sukhadia University Udaipur, Rajasthan India [email protected]

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Ashok Bhansali O.P. Jindal University Raipur, Chhattisgarh India [email protected]

M. Akshatha Coimbatore Institute of Technology Coimbatore, Tamil Nadu India [email protected]

Meenakshi Sharma Global Group of Institutes Amritsar, Punjab India [email protected]

S. V. Swetha Coimbatore Institute of Technology, Coimbatore, Tamil Nadu India [email protected]

Dipesh Vaya S.S. College of Engineering Udaipur, Rajasthan India [email protected]

N. M. Harihara Coimbatore Institute of Technology Coimbatore, Tamil Nadu India [email protected]

Teena Hadpawat Rajasthan Technical University Kota Kota, Rajasthan India [email protected]

Kusum Lata Jain Manipal University Jaipur, Rajasthan India [email protected]

Manish Jain Mandsaur University Mandsaur, Madhya Pradesh India [email protected]

Amit Bhati Dr. R.M.L. Avadh University Ayodhya, Faizabad, Uttar Pradesh India [email protected]

R. Sandhiya Coimbatore Institute of Technology Coimbatore, Tamil Nadu India [email protected]

Jolly Masih Prestige Institute of Management and Research Indore, Madhya Pradesh India [email protected]

A. M. Boopika Coimbatore Institute of Technology Coimbatore, Tamil Nadu India [email protected]

Sanjeevikumar Padmanaban Aarhus University, Herning, Denmark [email protected]

Himani Mittal

Chapter 1 Blockchain technology: architecture, consensus protocol and applications Abstract: Blockchain technology is a database of transactions. It is immutable, distributed, transparent and secure. Blockchain technology is an upcoming technology that has tremendous scope. This chapter discusses the components of a blockchain and its applications. The components of a blockchain include block, linked list, chain, genesis block and consensus protocol. A block is a single transaction. Blockchain is a collection of blocks linked by hash cryptography. Each user on the blockchain has a dedicated chain. The consensus protocol defines the mechanism using which transactions are added to the blockchain. The design of consensus protocol emphasizes on suitability to fight against network attacks and fast database update. Some consensus protocols included in this chapter are proof of work, proof of stake and proof of elapsed time. The several applications of blockchain as namely, internet of things, cloud computing, healthcare, medicine, storage and education. Smart city development and financial applications are other domains of use. Keywords: blockchain, distributed ledger, consensus protocol, decentralized database, applications of blockchain

1.1 Introduction Blockchain technology became popular in the research fraternity through the introduction of Cryptocurrency. In 2008, the author named Satoshi Nakamoto published a paper entitled “Bitcoin: A Peer-to-Peer Electronic Cash System.” This chapter described a peer-to-peer (P2P) electronic cash system where payments are made directly from one party to another without involving any bank or third party (regulator). These types of cash systems are known as cryptocurrency. Cryptocurrency makes use of cryptography to secure transactions and hence the name. This cryptocurrency is based on blockchain technology. A blockchain is a digital record of transactions or a database of transactions. The name comes from its structure, in which individual records, called blocks, are

Himani Mittal, Goswami Ganesh Dutta Sanatan Dharma College, Chandigarh, India, e-mail: [email protected] https://doi.org/10.1515/9783110702507-001

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linked together in a single list, called a chain. The blockchain is a distributed ledger that ensures immutability, transparency and security. – Immutability means data once saved cannot change. – Distributed means there is no single owner that controls the blockchain database. It is spread across a network of participants. – Transparency means that whatever changes happen in the database are visible to all the participants. This might raise a security concern but the blockchain is transparent, at the same time secure, and hides the identity of participants from each other. These properties make blockchain an open area of research with plenty of active implementations. There lies an unlimited powerful application domain based on blockchain technology [1, 2]. The organization of the chapter is as follows: Section 1.2 includes the architecture of blockchain. The consensus protocols are discussed in Section 1.3. The current applications of blockchain are discussed in Section 1.4, and Section 1.5 concludes the chapter.

1.2 Blockchain architecture The blockchain includes the following components: block, blockchain, hash cryptography, immutable ledger, distributed P2P network and consensus protocol. These components are shown in Figure 1.1. The details are as follows.

1.2.1 Block The most basic unit of a blockchain database is the block. It contains the transactions to store. Figure 1.1 shows the structure of block. It consists of block number, nonce, data, previous hash and hash. The block number is a unique number assigned to each block generated by the user who creates the block. The nonce is a special value mined by the miner algorithms employed by the creator of the block. This value calculation is also known as puzzle solving. Previous hash is the encryption of the previous block. The hash is calculated using SHA-256 algorithm on the combination of the nonce, previous hash and data. To ensure immutability and security of the data, nonce, previous hash and hash, are used. The use of this hash value is that the hash of the previous block is stored in the next block and used in the calculation of new hash. This ensures that if anyone tries to change an intermediary block in the blockchain, then all the hashes of all the blocks will have to be recalculated, which is impossible. This ensures that data once added cannot be changed in the blockchain. This property makes blockchain suitable for applications that are transactional in nature and

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Figure 1.1: Structure of a block.

where the previous data should never be modified. Nonce is utilized to ensure that the hash value generated for a block has a particular format like starting with 3 zeroes or 10 zeroes. After a block is added to the blockchain network, it is immutable. The size of the block limits the amount of data it can hold. The blockchain network decides the block size at the time of the creation of the network. Generally, when a new user is added to the blockchain network, a new chain is started for the user. This chain consists of a genesis or starting block. Then, the subsequent blocks containing user data are stored in a new block and appended to this genesis block, in the form of a linked list. This collection of the genesis block and all subsequent blocks is the blockchain. Collection of these blockchains is the complete database.

1.2.2 Blockchain After the creation of the genesis block of the user, all the transactions of that user are linked to it as shown in Figure 1.2. The previous hash in the genesis block is zero as there is no previous block. Genesis block contains data about the user like name and the hash value assigned to that user. Then the nonce and a new hash are calculated. Then as the transactions happen, the new blocks will be appended to this starting block. However, adding a block to this blockchain is not a simple job. It needs to go to the P2P network through consensus protocol.

1.2.3 Hash cryptography The SHA-256 algorithm used in the blockchain is a one-way and deterministic hashcalculating algorithm. One way means that the original text cannot be recalculated

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Figure 1.2: Blockchain in network.

from the hash. It is unique for each string of characters and always 256 characters long no matter the data is 1 character or 100 characters. The algorithm has an avalanche effect that is a small change in the input data will completely change the output hash value. Therefore, if we hash “aaa” and “aaaa,” the two hash values generated will be completely different. This property makes the hacking of the hash difficult. The calculation of nonce and hash value is further discussed [3].

1.2.4 Immutable ledger Immutable means blockchain allows no change in the data. The linking of blocks using hash values makes the data unchangeable. The distribution of blocks in all the nodes of P2P network ensures the immutability.

1.2.5 Distributed peer-to-peer network As clear from blockchain architecture as shown in Figure 1.3, the blockchain does not have a single copy. Every member of the network has a copy. If a new block is to be added, then it must be added to the whole network and all the peers need to be updated. This updating is ensured by the consensus protocol discussed next. Users, who agree to become the part of the blockchain network, and have a stake in it, can modify it by adding blocks. The identities of the peers are hidden from each other. Whenever a change is made in one peer database, the same change is propagated to the whole P2P network through voting. This distributed network is spread across the globe and connected by internet or some private network or cloud computing.

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blockchain Block

Peer-to-peer network

Figure 1.3: Blockchain architecture.

1.2.6 Consensus protocol After a block is created by a peer, it is sent to all the peers in the network. Whether the network will accept or reject the block depends on the consensus protocol. The consensus protocol develops an agreement between all the peers and decides the condition for a block to be added to the network [4–7].

1.3 Blockchain consensus Originally, when blockchain came into existence with Bitcoin, the consensus protocols used were [7]: proof of stake (PoS), proof of work (PoW) and proof of elapsed time (PoET). These are discussed below: – PoS means the higher value or commodity you possess in the network, the more priority is given to the block added by you and more are the chances of your block being accepted in the network. – PoW means the more number of mining problems (nonce calculation) you are able to solve, the higher are the chances of the block being added to the network. – PoET requires the user to run an algorithm and the speed with which the algorithm runs will decide if the user is the higher stakeholder and hence has the right to add the block. – There are some other consensus protocols namely: proof of existence, delegated proof of stake, proof of activity (hybrid of proof of work and proof of stake), proof of importance and proof of storage [4].

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– There are other voting-based protocol namely, ripple [6] and stellar consensus protocol [4, 6, 8]. – Another consensus protocol, proof of luck, is discussed by Milutinovic [5]. Baliga [7] presents a comparative study between PoW, PoS, PoET and byzantine fault-tolerant consensus protocols. Consensus protocols are important because it decides “how secure the block chain network is?” and “how difficult it will be for a hacker to add a new block?” There are several types of attacks that are made on blockchain networks namely, double spending, eclipse attack and byzantine attack [9]. Stellar and ripple consensus protocol are used in several products of block chain networks to deal with all types of attacks.

1.4 Blockchain applications Some of the applications of blockchain are: – Internet of things (IoT) and cloud computing [10]: IoT data is highly transactional in nature making it suitable for using blockchain. Blockchain makes IoT data secure, immutable and available only to authorized users. – Storage applications [11]: Blockchain is suitable for permanent data namely health records of patients, voting system and digital identity verification. – Encrypted communication method [11]: It is useful in social networking, predictive markets and art. – Education [12]: It is useful in maintaining learning content and learning outcome. It is used for storage of academic certificates and awards. – Healthcare [13]: It can be used in medicine, genomics, telemedicine, telemonitoring, e-health, neuroscience and personalized healthcare applications where again the data is permanent in nature. – The financial application includes storage in banking system and other financial institutions. – Smart city development using IoT and cloud computing based on blockchain technology.

1.5 Conclusions The blockchain technology is secure, transparent, immutable, encrypted and decentralized. It authenticates and authorizes the user. It is suitable for applications where the data is permanent in nature and security is of utmost importance example, IoT, cloud computing, healthcare, education, communication and smart city. Blockchain technology is an upcoming technology that has tremendous scope.

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References [1]

Crosby, M., Pattanayak, P., Verma, S., Kalyanaraman, V. (2016). Blockchain technology: Beyond bitcoin. Applied Innovation, 2(6–10), 71. [2] Underwood, S. (2016). Blockchain beyond Bitcoin. Communications of the ACM, 59(11), 15–17. [3] https://tools.superdatascience.com/Blockchain/hash [4] Sankar, L.S., Sindhu, M., Sethumadhavan, M. (2017, Jan). Survey of consensus protocols on blockchain applications. In 2017 4th International Conference on Advanced Computing and Communication Systems (ICACCS), 1–5. IEEE. [5] Milutinovic, M., He, W., Wu, H., Kanwal, M. (2016, Dec). Proof of luck: An efficient blockchain consensus protocol. In Proceedings of the 1st Workshop on System Software for Trusted Execution, 1–6. [6] Cachin, C., Vukolić, M. (2017). Blockchain consensus protocols in the wild. arXiv preprint arXiv:1707.01873. [7] Baliga, A. (2017). Understanding blockchain consensus models. Persistent, 2017(4), 1–14. [8] Mazieres, D. (2015). The stellar consensus protocol: A federated model for internet-level consensus. Stellar Development Foundation, 32, 1–45. [9] Bissias, G., Levine, B.N., Pinar Ozisik, A., Andresen, G. (2016). An Analysis of Attacks on Blockchain Consensus. arXiv preprint arXiv:1610.07985. [10] Nawawi, A. et al. (2019). Conference Paper August 2018. Finance Research Letters, 11(2), 1–6. [11] Pilkington, M. (2016). 11 Blockchain technology: Principles and applications. Research handbook on digital transformations. Edward Elgar, 225(1). [12] Chen, G., Xu, B., Lu, M., Chen, N.-S. (2018). Exploring blockchain technology and its potential applications for education. Smart Learning Environments, 5(1), 1–10. [13] Siyal, A.A., Junejo, A.Z., Zawish, M., Ahmed, K., Khalil, A., Soursou, G. (2019). Applications of blockchain technology in medicine and healthcare: Challenges and future perspectives. Cryptography, 3(1), 3.

Sunita Ahlawat, Abhishek Tripathi

Chapter 2 Blockchain: implications for accounting and audit practice Abstract: With the advent of blockchain technology (BT), the global business is undergoing a major transformation. This technology originated primarily to support Bitcoin cryptocurrency as a way of providing support for conducting reliable transactions with instantaneous verification. The immutable and supposedly tamper-proof nature of the records, which are the byproducts of blockchain, provide trust between the parties involved in a transaction. Using BT, individuals are able to virtually do business, enter contracts and exchange goods and services with authentication. In addition, this technology establishes a permanent audit trail. In this chapter, we discuss business applications of BT in terms of recording, valuing and verifying transactions. We also explore the ramifications of blockchain for the audit of corporate financial reports and associated accounting challenges, especially those involving cryptocurrencies. Keywords: blockchain, cryptocurrency, Bitcoin, accounting, audit process

2.1 Introduction The blockchain technology (BT) is revolutionizing the business worldwide. The initial foundation was laid by Satoshi Nakamoto whose motivation was to conceptualize and improvise the emerging cryptocurrency concept popularly known as Bitcoin. Without the BT, Bitcoins were just timestamped digital documents used for purchasing goods and services. The BT provided the underlying architecture for Bitcoins by providing support for establishing public tamper-proof ledgers. In addition, BT has changed the digital landscape by introducing concepts such as e-coins, data security, personal identification and the Internet of things. Since traditional methods of payment and data processing are becoming outdated, accounting practices and financial record-keeping are also under pressure to change in order to keep pace with BT. Understanding the intricacies of this technology will be crucial for conducting financial and operational audits, developing effective regulation, especially those addressing a new class of assets (e.g., cryptocurrency) and managing supply chains and financial ledgers.

Sunita Ahlawat, School of Business, Business Building, 114, The College of New Jersey, USA, P.O. Box 7718, 2000 Pennington Rd., Ewing, NJ 08628, USA, e-mail: [email protected] Abhishek Tripathi, School of Business, Business Building, 114, The College of New Jersey, USA, P.O. Box 7718, 2000 Pennington Rd., Ewing, NJ 08628, USA, e-mail: [email protected] https://doi.org/10.1515/9783110702507-002

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Before the onset of the BT, middlemen such as notaries and banks were established as centralized agents to mediate financial transactions and disputes. The advent of Bitcoins and their acceptance over traditional modes of payments has totally eliminated the concept of centralized intermediaries. An everyday example of this is the widespread use of the debit/credit card. Using a credit or debit card, an individual can transfer funds from a secure account that is controlled by a centralized establishment using carefully monitored plastic cards. With the BT, as personified by Bitcoins, there is no need for a centralized authority such as VISA to manage the financial transactions [1].

2.2 Promise of blockchain The entire notion of the BT revolves around the interaction of blocks of data. The data include bits of information, a lengthy identification code and the identification code of another block generated previously. The concept of “chained” comes from the fact that the information codes of shared blocks are connected. In order to ensure security, the identification code is generated using the hash function, which ensures that if the information is changed in a block, then the identification code also changes as well. Each successive block contains information from their chained neighbors. Therefore, any unwanted changes in the blockchain will result in introducing errors within all the participating blocks. In addition to that, blockchains are shared on a peer-to-peer (P2P) network resulting in blockchains being separated and copied to a large number of hosts. Essentially, any changes on one singular block result in the blockchain being alerted throughout the P2P network. These measures ensure a decentralized approach to support security and trust. Here we provide an example of how a decentralized system such as blockchain can be used to send assets overseas. For a customer to send funds overseas, they have to interact with a payment service such as Xoom or PayTm and with the bank in the recipient’s country. First, the customer needs to deposit funds with Xoom. Second, Xoom would then send the funds to a sister office in another nation. Finally, the funds would be deposited into the account of the recipient after converting the funds into the currency of the recipient’s nation. This is an extensive process and takes a few hours or even a day. In addition to that, the customer must bear the transaction cost to complete the exchange. However, with BT, the client needs to upload their assets to a digital wallet and send the asset to the recipient in a matter of seconds with no fees associated with the transaction. To ensure the validity of the transaction, the information is stashed in the P2P network as a block of data. The popularity and dominance of BT have changed entire models of supply chains. In traditional supply chain, intermediaries were used for validating and confirming transactions but with the BT the validation and confirmation of the transaction are supported by the blocks of data chained across in the P2P network. According

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to Korpela et al. [2], the key motivation with the use of BT “is the efficiency associated with minimizing governance costs, including the costs of exchange with other ecosystem participants and with those within the individual organization” (p. 4183). Due to the depreciation of cost and complexity, there is growing interest and demand for the adoption of BT in digital global supply chains. Blockchains enables digital supply chains to be very quick and cost-effective. The P2P method enables trust because the data is publicly shared within the network. However, Korpela et al. [2] argue that “[Blockchain] cannot meet the need for standardization of electronic supply chain documents, international document standards must be relied on it for that purpose” (p. 4186). However, with the advancements in the BT, standardization will not be an issue in the future. In blockchain parlance, transparency of the transactions is realized with a decentralized ledger. For example, buyers can find out and know precisely where their products are coming from and how businesses are treating their suppliers and workers. Referring to the Apple Foxconn scandal, Abeyratne [3] argued that consumers reacted badly to apparent environmental and working conditions abuses and that they wanted to know where their goods were manufactured and sold. The BT can make all this information available to customers using distributed ledger recorded in the P2P network, thereby enhancing transparency for all. Adding to the complication, Abeyratne [3] further notes that “in a large supply chain system, it is challenging to have an overall picture of transactions within the chains. The information is typically stored in multiple locations and are accessible to certain system entities” (p. 4). Overall, the distributed ledger can provide the complete picture of supply chain operations performed by different parties involved in specific transactions.

2.3 Blockchain working The BT makes it simpler to record transactions. For example, a Bitcoin exchange can be completed in two operations within the electronic wallets. Primarily, the sender verifies if he/she has enough funds in their wallet and that the fund has not been used for any other transactions to prevent a double-spending scenario. In the double-spending scenario, the same fund is misused on two different occasions. Once it is confirmed that the funds have not been used for any other transactions, then the new transaction is stored forever in a new block, which is then fused to a continuous blockchain. This blockchain will then be available for the public to verify and remain unhackable. Catalini [4] discussed the role of the Bitcoin miners as one who would take on the “additional computational work required to assemble new, valid blocks and commit them to the shared ledger” (p. A-2). As the miners are involved in validating the transactions, the process is very much shared and secured. Figure 2.1 shows a rough flowchart of how transactions are verified through the blockchain. However, this technology is also

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subject to certain constraints. Initially, blocks were limited to be of a finite number of bits, but due to the popularity of this technology, the number of bits has to be increased to handle high traffic, which invariably increases the transaction time. Unlike the traditional credit and debit card system that can handle hundreds and thousands of transactions per second, the Bitcoin technology can only manage a few hundred transactions every 10 min. Also, the decentralized P2P processing nature of this technology demands an enormous computing power to verify the transactions via the coin mining operations.

Figure 2.1: Blockchain transaction flowchart in a P2P network.

2.4 Blockchain’s implications for auditing Blockchain is a trust-building technology. Auditors serve in the role of maintaining and enhancing public trust and confidence in the capital markets. With all its technological and other challenges, external audits of public corporations remain an important part of the proper functioning of global capital markets. Over a period of time, businesses have gone global, transactions have become more complex and accounting practices have advanced to address the numerous challenges introduced by technological and other factors. Blockchain is one technology that is revolutionizing accounting practice with important implications in auditors and regulators. Earlier, we discussed that the BT is a digital ledger used for capturing transactions initiated by various parties in a network. The digital ledger is composed of blocks that can keep track of all the transactions, which are available to all parties in the private network and are verifiable at any time. The new products created by BT (e.g., cryptocurrencies) pose unique challenges for accountants in terms of measurement, valuation and recording of these products. At the same time, this technology also offers opportunities for more efficient verification of transactions during an audit.

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2.4.1 Auditing Financial reporting and the related audit functions are meant to protect the public interest. An independent audit of financial records of a public company is conducted for regulatory purposes, and culminates in certification (audit opinion) of the veracity of financial statements as fairly representing the company’s state of affairs. Blockchain drastically increases the reliability and accuracy of records. Although digital files are vulnerable to being modified, that is not possible in the blockchain world where digital pieces of information are stored in decentralized databases. According to Andersen [5], companies can write their transactions directly into a joint register, thus creating an interlocking system of everlasting accounting records. “Since all the transaction entries are distributed and cryptographically locked, falsifying or destroying them to conceal activity is practically impossible” (p. 3). Vetter [6] has also emphasized the fact that auditing services can be bolstered via emerging BT. According to Vetter [6], auditors can benefit from this technology by focusing more on designing, reviewing and verifying the information flow between the systems rather than spending time performing audits. Blocks contain information about a transaction (date, time amount), parties to the transaction, and their digital signatures. Each block in the chain has a unique ID called a hash. The hash acts as a digital, timestamped fingerprint or barcode. This can drastically improve auditor efficiency in terms of the speed with which they can verify transactions. For example, the need to confirm customers’ outstanding accounts receivable balances may very well be eliminated. With blockchain, an immutable audit trail that can ensure outstanding receivables nearly instantaneously can be created. This process can be automated so that any mismatched strings would automatically raise a red flag, alert the auditor in a continuous audit. As such, blockchain offers auditors a tool to confirm audit evidence throughout the year, not just periodically. To audit a blockchain shared ledger, a blockchain private network would need to be set up between the auditor, the client, and the client’s third party [7]. Each party would have a different type of access to prevent tampering. For example, an auditor would have access to the full range of accounting data while an accounts receivable clerk only has access to accounting information related to customer accounts, their payment history and outstanding credit transactions. Auditors can view the automatic confirmation of transactions which are validated via consensus, distributed on the private and permissioned network, and are therefore immutable [7]. As the audit evolves with blockchain, audit firms and their clients must generate new internal controls to ensure that entries recorded into the blockchain are appropriately authorized and accurately entered. Compliance with Section 404 of the Sarbanes–Oxley Act would require public companies to identify the key risks related to BT and to model their internal control processes to address those risks. The American Institute of Certified Public Accountants (AICPA) identified four key risks that a transaction in the blockchain is: unauthorized, fraudulent or illegal, executed

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between related parties, linked to a side “off chain” agreement or incorrectly classified in the financial statements (Blockchain Technology and Its Potential Impact).

2.4.2 Accounting of cryptocurrency To realize the potential of the blockchains for accounting, proper implementation of the digital ledgers is required, including government sanction of what is permissible, what is not. Currently, the United States government is not encouraging the use of Bitcoins and cryptocurrency [8]. These virtual currencies are a product of BT that has the potential to disrupt traditional financial institutions. Bitcoin is currently the leader in the cryptocurrency market, with a market capitalization of over 150 billion. With a market that has grown exponentially over the past year, Bitcoin has beat the odds in terms of global adoption and steady growth. Much of its recent growth seems to be due to hype, favorable news and the fear of missing out. Cryptocurrencies have challenging implications for the accounting profession as well. As more businesses begin to accept payments in cryptocurrencies as alternatives to conventional forms such as cash or credit card, accounting rules Generally Accepted Accounting Principles (GAAP) for measuring and recording these transactions will have to be enumerated. There are no cryptocurrency specific GAAP rules as yet. However, the AICPA has attempted to provide some guidance on this issue. Cryptocurrencies are not considered “cash or cash equivalents” or “financial instruments” or “inventory” on the balance sheet. These can best be classified as “intangible assets” with an indefinite life. However, this classification ignores the fact that cryptocurrencies are liquid assets like cash. Additionally, intangible assets with indefinite life must be tested for impairment annually and, more frequently, if an impairment is suspected, impaired losses must be written off. Given the volatility of cryptocurrency markets, this is problematic. Vilner [8] reports that in the previous fiscal year, “crypto investors had more than $1.7 billion in 2018 reported losses, and most of them had no idea how to report losses properly.” Moreover, the crypto speculators are struggling in properly reporting their taxable income using the BT. Under current GAAP, impairment losses (i.e., fair value declines below the carrying value), but not gains or recovery of previous losses on intangible assets, must be recognized. Alternatively, some have proposed that cryptocurrencies should be accounted for as investments. PWC favors a “fair value measurement model, with both realized and unrealized changes reflected currently in the income statement, which will best represent the economics associated with holding cryptocurrencies (Cryptocurrencies: Time to consider plan B, PWC).” The basic argument is that the fundamental nature of cryptocurrencies is different from most intangible assets. Unlike intangible assets like patents, cryptocurrencies are traded on exchanges and could be used as payment for goods and services. Information surrounding the determination

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of the fair values of cryptocurrencies is publicly disclosed as this information will be useful to stakeholders (cryptocurrencies: time to consider plan B). Others have pointed out that “cryptocurrencies are not financial assets because they . . . [lack] ownership interest in an entity, or a contract establishing a right or obligation to deliver or receive cash or another financial instrument” (classification of cryptocurrency holding, Deloitte). Another issue cryptocurrency poses in the accounting profession is the evaluation and recording of mining transactions. Miners incur costs, such as computing equipment and electricity, to mine cryptocurrencies. There is a lack of guidance on how to account for the costs incurred to mine cryptocurrencies, whether these costs be capitalized or expensed. To properly use blockchain as a secure and effective platform, the P2P network needs to utilize miners to verify the transactions and data transfer. Essentially miners validate transactions using high-powered computing to ensure that the data is accurate and inputted correctly in the blockchain. For their trouble, miners have rewarded a segment of the cryptocurrency as payment, with each computer that proceeds with the mining process getting an even smaller segment. Davidson [9] explains that the proof of work model that mining presents is a type of self-sufficient economy as “[blockchain] uses economic incentives to ensure that it keeps going and doesn’t go back in time or incur any other glitch” (p. 4). Because miners are rewarded for recording transactions, there is an incentive for people to mine in their free computing time or to invest in specialized mining equipment to get a share of the pie. As discussed previously, since the establishment of e-coin and Bitcoin, numerous regulatory and internal controls issues have surfaced. Left unaddressed, these issues can lead to misrepresentations or misclassification of assets and cause financial statements to be inaccurate, outdated, or misleading. Barlin [10] instills the issue that the Internal Revenue Service (IRS), Securities and Exchange Commission (SEC) and FinCEN treat cryptocurrency as a currency and a property, which showcases irregularities in classification and regulations. Since certain transactions require the conversion of Bitcoin to USD or other local currency, and others instead treat transactions as trading of property, there are many inconsistencies in the auditing and financial viewing of Bitcoin as an asset. According to Barlin [10], “Unlike with taxes, where an asset must be sold before it is recognized, the receipt of a bitcoin or other virtual currency must be recorded. Furthermore, because bitcoins are treated like real currency, their exchange rate at the balance sheet date must be considered, and adjusting entries must be made to reflect conversion to U.S. dollars.” The apparent discrepancy in the treatment of cryptocurrency between the perspective of accounting rule-making bodies and tax regulatory body as the IRS is noteworthy. The IRS states that virtual currency “operates like ‘real’ currency (i.e., the coin and paper money of the United States or of any other country that is designated as legal tender, circulates, and is customarily used and accepted as a medium of exchange in the country of issuance), but it does not have legal tender status in any jurisdiction” (emphasis added).

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The final big issue in cryptocurrencies is how taxpayers should account for activities (e.g., mining) associated with cryptocurrencies? The IRS released Notice 2014 [11] to guide the tax laws surrounding cryptocurrencies. Notice 2014 [11] states that cryptocurrencies should be treated as investments, and any amount received over the adjusted basis of the cryptocurrency should be included in one’s taxable income. Notice 2014 [11] also states that mining cryptocurrencies should be treated as self-employment, and any the fair value of Bitcoins mined should be included in their taxable income [11]. Providing further guidance on how to calculate income when services are rendered, and payment is received in virtual currency, the IRS notes that “the amount of income you must recognize is the fair market value of the virtual currency, in U.S. dollars when received. In an on-chain transaction, you receive the virtual currency on the date, and at the time the transaction is recorded on the distributed ledger.” As the popularity of blockchain increases and develops, issues of measurement and reporting will continue to be an obstacle to the proper treatment of this new class of assets. Until regulations are standardized, blockchain will not be able to achieve its full potential. Davidson [9] argues that centralized establishments stifle the achievements of decentralized blockchain transactions and that “Centralization brings order, but this order can be brittle, and adaptation toward decentralization begins to make the system more robust, flexible, secure and efficient” (p. 5). Perhaps regulations could be centered on a new dynamic decentralized model, and not be dependent on traditional and outdated centralized establishments. Ali [12] states, “Regulators could remake the financial system by rethinking the best way to achieve policy goals, without diluting standards . . . making the system more transparent reduces intermediation chains and costs to users of the financial system.” With all the confusion surrounding regulation, proper laws need to be written in to ensure transparency and effectiveness. Accounting issues arise when considering the lack of tangible proof that cryptocurrencies provide when being paid. In a sense, mining is like working “under the table” where the currencies are being paid out in e-coins electronically; sure, the records of payment exist online, but these are difficult to find unless the block of data is specified. Because of the anonymity of e-coin wallets, audits may not find proof of these smaller transactions, and miners can escape taxes on the cryptocurrencies due to a lack of federal regulation. The “libertarian and antiestablishment spin” on Bitcoin and blockchain, according to Ali [12], showcase struggles and issues in regulation and auditing for blockchain-based currency. Accountants currently need to create software to search for mining income. On the technology front, the novel combination of the blockchain and machine learning presents the possibility of continuous auditing. Since the technology itself handles complex computations involving validation and verification, it leaves the teams to focus more on establishing connections with internal teams and clients, thus delivering value to the organization. Also, due to the continuous audit taking place in the systems, trends and missing data can be identified proactively, thus giving peace of mind to businesses and the investors, hopefully reducing the number of tasks that accounting

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firms often have written off or not charged for. One has to believe that auditing services can only be improved via blockchain. By efficiently utilizing the artificial intelligence and search algorithms on the blockchain, several transactions and information can be identified quickly and efficiently. The auditors can search for data and accurately calculate the assets. Complete transparency can be guaranteed to the auditors as the data within the blockchain spanning across the P2P network is readily available to them and is reliable. Blockchains promises to shape the future of auditing services by replacing the traditional systems with a more secure and decentralized alternative. In an everchanging world, the accounting services need to adapt and evolve to meet the demands of clients and corporations, and the BT offers a novel solution [13–19].

2.5 Conclusion Blockchain has the potential to revolutionize business processes and accounting practices. It is more than just Bitcoins. This technology represents a dynamic shift in data origination, organization and verification. For accounting firms to harness the benefits of this technology, they, along with their clients, will need to understand the nuances behind data processes fully. Accountants generally expend considerable resources to manage their customer and supplier accounts. Similarly, auditors expend significant resources to verify customer and supplier account balances. With streamlined supply chains and immutable record of transactions related to accounts payable and accounts receivables, BT is likely to reengineer a labor-intensive and time-consuming aspect of an audit as it can show whether a transaction has occurred. However, BT cannot provide assurance on whether the transaction itself can be trusted. The validity of a transaction that the transaction actually happened in the real world is another matter. Even the idea that BT can replace auditors assumes that the transactions between related parties recorded on to blockchains are not fraudulent, unauthorized or due to collusion or side agreements. The problems of hidden accounts and off-book or off-chain transactions may yet persist. However, internal controls or regulations can remedy that – if it is not on the blockchain, it is not included. Regardless, BT does allow an auditor to gather more detailed and timely information about their client’s operations, which arguably improves governance and transparency. The audit function will evolve from one of examining what happened in retrospect to that of learning what is happening in real time. Accountants and auditors can play an important role in the creation, execution, and continuous monitoring of smart contracts and in serving as an arbitrator to settle a dispute among parties participating in the blockchain on a private network. Overall, blockchain is a disruptive force to be dealt with for a profession that serves many stakeholders while tackling more complex transactions ever in a rapidly evolving, technologydriven business landscape.

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Bibliography [1]

[2]

[3]

[4] [5]

[6]

[7] [8]

[9] [10]

[11] [12]

[13] [14]

[15]

[16] [17]

Gupta, V. (2017 March 06). The Promise of Blockchain is a World Without Middlemen. Retrieved March 12, 2019, from https://hbr.org/2017/03/the-promise-of-blockchain-is-aworld-without-middlemen. Korpela, K., Hallikas, J., Dahlberg, T. (2017). Digital supply chain transformation toward blockchain integration. Proceedings of the 50th Hawaii International Conference on System Sciences (2017). Doi: 10.24251/hicss.2017.506. Abeyratne, S. (2016). Blockchain ready manufacturing supply chain using distributed ledger. International Journal of Research in Engineering and Technology, 05(09), 1–10. Doi: 10.15623/ ijret.2016.0509001. Catalini, C., Gans, J. (2016). Some Simple Economics of the Blockchain. Doi: 10.3386/ w22952. Andersen, N. (n.d.). Blockchain Technology A game-changer in accounting? Retrieved March 12, 2019, from https://www2.deloitte.com/content/dam/Deloitte/de/Documents/Inno vation/Blockchain_Agame-changerinaccounting.pdf. Vetter, A. (2018 August 20). Blockchain, machine learning, and a future accounting. Retrieved from https://www.journalofaccountancy.com/newsletters/2018/aug/blockchain-machinelearning-future-accounting.html. Appelbaum, D., Smith, S.S. (2018). Blockchain basics and hands-on guidance: Taking the next step toward implementation and adoption. The CPA Journal, 88(6), 28–37. Vilner, Y. (2019, March 11). Crypto Tax Season 101: The Basics You Should Know About. Retrieved March 12, 2019, from https://www.forbes.com/sites/yoavvilner/2019/03/09/in vested-in-crypto-during-the-craze-tax-season-is-coming-and-you-better-comply /#43e5bd336ed1. Davidson, S., Filippi, P.D., Potts, J. (2016). Economics of Blockchain. SSRN Electronic Journal, Doi: 10.2139/ssrn.2744751. Barlin, R. (2017 November 02). Bitcoin: Rise of Virtual Currency and Its Downfalls. Retrieved from https://www.cpajournal.com/2017/10/02/bitcoin-rise-virtual-currencydownfalls. IRS, Notice 2014. Ali, J. (2017 March 09). The Blockchain Will Do to the Financial System What the Internet Did to Media. Retrieved from https://hbr.org/2017/03/the-blockchain-will-do-to-banks-and-lawfirms-what-the-internet-did-to-media. IRS. Virtual Currencies. https://www.irs.gov/businesses/small-businesses-self-employed/vir tual-currencies. AICPA (2017). Blockchain Technology and Its Potential Impact on the Audit and Assurance Profession. Retrieved from https://www.aicpa.org/content/dam/aicpa/interestareas/frc/as suranceadvisoryservices/downloadabledocuments/blockchain-technology-and-its-potentialimpact-on-the-audit-and-assurance-profession.pdf. Deloitte, classification of cryptocurrency holdings Financial Reporting Alert 18–19. https://www2.deloitte.com/us/en/pages/audit/articles/fra-classification-of-cryptocurrencyholdings.html. PWC, Cryptocurrencies: Time to consider plan B. Khan, S. (2018, August 20). Reinvent your ERP processes with blockchain. Retrieved from https://www.ibm.com/blogs/insights-on-business/oracle-consulting/reinvent-erp-processesblockchain.

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[18] Shankland, S. (2018, February 12). Why should you care about blockchain? It’s the ultimate trust builder. Retrieved March 12, 2019, from https://www.cnet.com/news/blockchainexplained-builds-trust-when-you-need-it-most. [19] IRS, https://www.irs.gov/individuals/international-taxpayers/frequently-asked-questions-onvirtual-currency-transactions.

Hemant Kumar Saini, Kusum Lata Jain, Kamal Kant Hiran, Amit Bhati

Chapter 3 Paradigms to make smart city using blockchain Abstract: We learn in everyday life that data is created and marketed at a rate that could not be seen a few years back. At present, when data is increasing exponentially over the successfully opened media, its consistent quality is crucial. To make the data robust and to promote exchange, we rely on a great figure of mediators, which confirms the details of building “trust” among the working organizations. Confirmation of the exchange rate for banks is another matter to create a system that is maintaining belief. This mediator that people trust had a great deal in our work. Surprisingly, in the day and year when data is readily available, these mediators existence will give new era to utilize the datasets. A newly launched blockchain is an appropriate record development that stores information over different systems securely to enable dispersed trades by making a reliable wellspring of fact disintermediating the indirect legislative body of the trust. This new system understands an adjustment in context in such a way wherein we develop faith and have far-attained penalty. Blockchain is prepared to modify how it will amuse and will influence everyone in trade (banking, power, preparing, social protection, etc.). The open region is no uncommon case. The organization and open fragment have an urgent necessity to be total, safe, credible and dependable in order swap crossways with a variety of fields. Blockchain advancement is ascending as a gadget for administration, mainly to restructure the data based on reasons. Keywords: smart city, blockchain, public safety, advancement

3.1 Introduction Many countries have enacted processes to transform their urban communities into intelligent urban communities to take full advantage of the open doors of urbanization. Savvy urban areas empower workforce, enhance environmental management

Hemant Kumar Saini, Department of CSE, MITRC, Affiliated to Rajasthan Technical University, Alwar, Rajasthan, India; Manipal University Jaipur, India, e-mail: [email protected] Kusum Lata Jain, Manipal University, Jaipur, India, e-mail: [email protected] Kamal Kant Hiran, Department of Computer Science and Engineering, Sir Padampat Singhania University, Udaipur, India, e-mail: [email protected] Amit Bhati, Institute of Engineering & Technology, Dr. R.M.L. Avadh University, Ayodhya, India, e-mail: [email protected] https://doi.org/10.1515/9783110702507-003

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efforts and facilitate the administration of new residents. India also floats its elegant community on 25 June 2015, intending to create a 100 urban communities. Such legislature is a prominent addition to a vibrant city, a huge amount that can be considered looking at the blockchain for improved security, immutability, power and precision. Shen and Penamora [1] offer a greater understanding of the current urban crisis that is being tackled in beautiful urban areas. In this way, it reflects the ideas of blockchain and the assessment of its ability to transform power into making our urban communities more prominent. This also investigates various cases of using blockchain in a smart city environment. Finally, it quickly clarifies the requirements for block-based program selection and the way forward. Understanding what blockchain brings to the table, it is helpful to see the basic card exchanges and to evaluate the situation with the fixed method of installation. Let us imagine a situation where client A needs to pay client B for a card. Unless it seems that this is just a quick connection to A and B; of course, the client allows his/her bank to search through the data to determine if A has enough assets to pay B. In the event of this being permissible, the bank pays B with the checkpoints in bank details to close the transaction. The bank is paying B legally, this way B is paying in the roundabout way. With the origin of blockchain, the assets are now shared in every single important circle as a hidden barrier that remains a record. When keys are sold between installed assemblies, the square that holds the data about the property is not deprecated. Along such lines, foreign employment is aging. Such long confidence that the external end during the time used for the end of the exchange will have the effect, speed and several high-throughput exchanges with high security. Before investigating blockchain applications, it is beneficial to have a process diagram. Basic developments include the following: 1. Client A requests to process an exchange on blocks. 2. The exchange is transferred to the standard system. 3. The exchange is proved by the use of the comment figures. In detail, another site has been attacked to uncover the riddle by using one of the metadata in a kind header. Such a procedure is called mining, which is a major significant factor for the entire blockchain implementation process. This part gives a blueprint of the development of blockchain and how it can talk to the safekeeping challenges that we are looking at during the advancement near the time of the Internet of things (IoT), and thus, to splendid urban regions. From the beginning, we reviewed the utilization of IoT in ordinary everyday presence. It has quite recently started appearing for present day, similarly as business, purposes. It is a free contraption that includes the general framework, which infers that diverse sanctuary issue is raised, dependent upon whether they are set up to agree to the new security system. Slowly, these are moving to the splendid urban zones replica. Other guideline point is to use the pattern setting development to collect the mass volume of data that will be used for the improvement of our fulfilment.

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Good practice habits, for example, unsoiled surroundings, irrigate, vitality as well as framework, are requisites for all residents around the world. However, such interest in important honors is growing rapidly due to the ever-expanding society. Citizens go to urban areas to have easy access to this important luxury and various offices, for example, business openings, healthcare and various offices. In this way, urban migration increases rapidly as urban communities ensure a better and healthier life. Approximately one and a half million candidates becoming deaf in locality per week [2]. The growth of cities is undermining the city’s accessible assets, for example, scope and groundwork [3]. Similarly, urban migration elevated and caused ecological and communal hardships. Urban areas plagued by the depleted property caused problems like power outages, poor water supply, unpaid taxpayer organizations, overpriced costs of necessities, inadequate transportation, inbound traffic, pollution, dumping of ordinary goods and so on. These urban problems are driving urban communities around the world to gain greater wisdom. Administration globally developed and adapted their “sophisticated city systems” to better consider the needs of their citizens. Many urban areas are striving to improve efficiency and maximize environmental management pains in creating a novel inhabitant. Intelligent urban communities have a new influence and use existing and organized assumptions that would offer a superior characteristic of livelihood for citizens with better participation in organizations, as well as to increase the use of assets and understanding of government. Light urban communities can be viewed as a natural combination of structures, IT foundation, body structure and social and business framework. These agencies are working hard to produce sharp and remarkable data for charitable judgments [4]. With the smart cities implementation in 2015, about hundreds of urban communities have become brighter. Department of Housing and Urban Affairs (MoHUA) promotes imperishable and comprehensive urban environments that afford institutional framework which provides personal satisfaction to its residents’ complete and meaningful living, and the use of “Savvy” IS Solutions [5] is important of a vibrant city, known as MoHUA.

3.2 About blockchain Blockchain is a digital, dispersed digital platform storing all transactions on a peer network. A constantly growing and expanding list of records is stored securely in multiple linked systems. This makes the blockchain technology stronger as the system has no risks. Also, each “block” is linked separately with preceding blocks through digital signature changes to the record without interfering with previous records online is impossible, therefore providing proof of interference [6]. The key to building blockchain technology permutes its participants to transport merchandise without any third-party involvement. Blockchain technology has been urbanized as a basic knowledge behind

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a cryptocurrency called Bitcoin. The results of the 2008 events undermined the credibility of the obtainable monetary scheme. Satoshi Nakamoto’s research “Bitcoin’s rule of law” uses a formal ledger and an agreement structure to create heuristics. The Bitcoin rule is printed to interpret customary monetary mediators to facilitate through peer-topeer dealings. With the Internet real money is started earning, but it also failed because of “double use,” which means the hazard caused by spending the digital cash to double the present resolution [3, 7]. Excluding such technology enables us to solve the primary expenditure problem twice devoid of reliable mediators, thus making safe transport of Internet. Such notion was applied in financial-related environments and that is the promise of blockchain technology.

3.2.1 The benefit of blockchain Blockchain is a dispersed net that provisions data in the shape of interference that is not only permitted but can be changed by “legitimate” users. While understanding the basic features of blockchain, one can implement with full potential [8]: Communal hosting: The dispersed arrangement in the trade that enables the network to be updated through removing the solitary peak of malfunction. Harmony: Transactions are merely made while everyone concurs on a system demonstrated by the deal. Laziness: All local account is found beyond the blockchain. Inactivity: Data inaccessible and should not interfere if they commit to a participant, making all information reliable. Smart contracts: The code is built on a computer/node blockchain based on an attack event; either way, ”if this is the default statement.”

3.2.2 How blockchain works? In PwC US [9], blockchain mechanism secures the communication during a dispersed system to create an endless authentication with irrevocable ledger for data as shown in Figure 3.1.

3.2.3 Classifications of blockchain The blockchain arrangement might be public or private based on participant authorization. An important disparity flanked by a public or private blockchain which operates open space partially wherever no limit to the quantity amalgamation Internet, and the supplementary function in areas are defined by the controlling company. Internet compares with the intranet, although traditional computer network knowledge

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Figure 3.1: Transaction of blockchain.

relics the identical, where significant disparity amid the resources connected to local network and Internet. These differences are played out in terms of how nodes promote the presence of part of a network. An important point here is that in the area of social prohibition, the consensus approach is based on the benefit of each member being in the network part. In a private blockchain, there is no demand to do such a promotion [10]. The obvious democratic status may not work in an organization or business with the known parties, and there are different understandings about the numbers of participants in network and their transactions. This compromises while social blockchain attempt in cryptocurrency (Bitcoin) dealings, multiple uses of blockchain technology as a business solution will only happen using integrated control controls connected with a local blockchain unit [11]. Fortunately, in this novel technology, distinctive programs emerge continuously and repeatedly. The inquiry of confidential blockchain could ultimately be tackled in a network wherever a numeral independent blockchain cooperates independently in a network that is openly disseminated. Thus, the solution is a challenging one; it can lounge into a mutual environment where public and private enclosures operate where confidential (network-secluded) networks connect to the Internet.

3.2.4 Important requirements for a blockchain solution Blockchain skill does not solve all evils that occur as a result of statistics acquisition with asset usage. One has to understand the blockchain, its features and see how to use the cases where it will work. Few requirements are necessary for blockchain to provide an effective result. Figure 3.2 shows the features that pertain to the blockchain a key solution. Blockchain technology only works while numerous groups split information along with necessitating to view the same data. Nevertheless, many data distribution groups are not the only effective way for the blockchain to become an effective solution [12]. To gather more learning about the blockchain the three of the following five achievements has been described below:

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1.

Numerous groups to renovate the data: Where events need to be recorded and manipulated according to the groups. 2. Validation requirement: To make the parties sure their records to be legitimate by developing trust between groups. 3. Entrants append complexity: Where a business depends on numerous mediators which add the cost and complexity of the operations. 4. Communication is time sensitive: In the case of business, it helps reduce delays and speed up the process. 5. Delivery is interactive: Where the business does not depend on parties mutually than the three of the above methods can be avoided so the blockchain is also not the mandatory solution. Thus, it is foresaid that blockchain is not the solution to all e-commerce. 6. Ability to revolutionize blockchain: The Internet has had a huge bang in communal. Administration moves to start digital archives to digital archives (public records), creating information and communication platforms to connect people far and wide from the delivery of mobile services to the delivery of digital services the changing changes brought about by the Internet. Blockchain technology is likely to have the same effect on changing government needs and operating on Internet that control and execute the delivery by local adoption which significantly reduces its cost also.

Figure 3.2: Perquisites of the blockchain solution.

The subsequent is a comprehensive record of used ledger due to which the blockchain might affect: The digitalization of fitness proceedings makes important modifications in the community fitness division, except it is criticized for being multifaceted due to the complex and ethical issues associated with it. Blockchain technology disturbs community fitness through a secure and consistent environment for the exchange of electronic health records [13]. Such expertise

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occupies space by creating evidence of sensitive medicines, blood, organs and so on by having all medical licenses on dot blockers, and deceptive surgeons can be prohibited from working. 1. Health: Scholar data, academic logs, academic credential and so on are important resources in the educational environment. Confidential data need to be public with many shareholders and it is important with reliability. Evidence of such data is clarified. Blockchain can also help with the validation. By introducing fundamental similarities in following national metrics, the purpose of education is changing the way. 2. Education: Blockchain can construct public service release further effective by solving interagency communication problem with an integrated truth for every company that competes separately in the aforementioned situations. Establishing a final series of important evidence is often a prerequisite for approval of evidence; blockchain technology can help establish the availability of repositories of such evidence. 3. Public safety and justice: It is a very important point in smart city design. 4. Power: Blockchain technology can be distributed to create an electronic trading platform. Microgeneration of domestic electricity uses solar energy that replaces traditional energy with geothermal powers. Implementing elegant equipment, a log of the production versus consumption of electricity per user on the grid can be kept in blocks with user/debt allocated for more electricity and debts used for energy expenditure. That generates a translucent, consistent, in addition to the competent electrical power market.

3.3 Develop the best of the city through blockchain The idea of a beautiful city can be seen as a structure for applying the concept of modern migration. Elegant cities use the knowledge and make use of obtainable communications that are designed to supply a high standard of living for inhabitants, a good business environment and to allow for greater use of resources and transparency of government [14]. With the natural integration IT framework, virtual framework, communal and commercial framework novel heuristics reorganize the data in an intelligent and sophisticated manner. In India, with the Smart Cities Mission, 100 towns have been structured. MoHUA endorses sustainable towns with a basic framework and citizens survive by a vigorous, spotless and sustainable surrounding through an elegant explanation. Blockchain offers the opening to compose smart city technology extra protected, apparent, capable and robust by aligning the goals of the elegant conurbation assignment, as defined by MoHUA.

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3.4 Paradigm in embedding blockchain As mentioned earlier, the security of the digital twin platform with high-quality data is a major question. Blockchain knowledge incorporates safety from hackers using built-in encryption features, and at the same time, the clarity of information narration as a blockchain block is carefully unlawful. Therefore it provides (1) past transactions tracking system and (2) protect the transactions without single centralized failure due to distributing system. Since the factors – safety and faith – are important in structure and network and draw participants who are accustomed to working together on a single stage, meriting at the scale that best reflects their relationship. Blockchain-user communication model: The predictable power of digital twins presently is partial by a broadly divided IoT. A nationally recognized data policy can assist in conquering these differences. Blockchain builds a multipodium that serves as an exchange podium for a selection of statistics contributor and statistics client, making it transparent and “instilling faith” in programs as well as stakeholders. Blockchain technology solves one important obstacle: interaction only with isolated IoT devices.

Figure 3.3: Blockchain interaction model.

Figure 3.3 highlights how underground ecosystems and processes are building upon the platform of an equally useful guide. It shows how the blockchain–user interaction model integrates IoT priorities among blockchain equipment. Inside the claim stage, a diversity of IT resources by different environmental fields transport real-time statistics with/or virtual progression and nourish their digital twins during precise application interface used. Nevertheless, ecosystem participants incompletely interrelate through their actual ecology. By following the rules and allocation of the dispersed data podium, the client can admit all associated appliances. This may be due to blockchain technology, which allows digital twins to be “pulled out” and entered into smart contracts. Big data center entrée such data and nourish it to original, realistic, economic models. Using smart coin and agreement allows dissimilar clients to choose person limit depending on price, usage or

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distribution. An easy-to-use and resourceful stage by sufficient communications offer ease and motivation to draw more shareholder engagement. Blockchain is the vertebrae of such a program. It works with no requirement for mediators owing to gaze-to-gaze skills with target potential. Also, conviction between participants is not a prerequisite as blockchain technology provides scramble characteristics and fully tracking of the entire chunk. The blockchain–consumer communication representations begin with four key shareholders, users, managers and knowledge and framework industries. The basis of the replica is a user-friendly podium, full of twin digital users, who are accessible to advance the use of other information. Legal and social requirements form the basis of the rules for how the planet and the environment will be worn. In fussy, smart contracts are resolved when doubts arise and the following indicators can alonel be determined by connecting the rigid establishment. Data trade and the importance of using digital twins require consistent standards, set by operating companies around the world, which are regarded as managers in the realm of a universal policy. Such principles have to be urbanized in line with consumer, authoritarian establishment and communications supplier [10]. The concluding is also given to the function that the required bandwidth to convene the user’s need for information transfer both internally and externally. With the addition of blockchain hardware, it is ensured that digital twins are located in a secure chip location and laid up in cryptographic security. It is indeed for many groups with unrelated well-being to communicate following the ordinary faith that information hoard in the normal blockchain environment is reliable. Smart contractual compulsion, for example, data dealings and/or tangible possessions, will be able to resolve owing to faith between blockchains. Enabling IoT with blockchain skill is tasks that necessitate monetary and creature commitment to all stakeholders. As the numbers of blockchain grow as more and more stakeholders, still a competitor in a similar company, work together and construct a communal stage, the formation of a wider ecosystem is becoming increasingly important. Generally, the following should be met: – Corporate commitment – Incorporation of the blockchain podium into commerce procedure, counting staff and customer preparation – Computer systems to attach consumer and corporation procedure with a recently built porter – An infrastructure that ensures integrated organizational communication – The external structure of the environmental system To ascertain international standards in the worldwide bazaar financial system, environmental associates need to be leaders in their markets. The need is built on the fact that quality development requires knowledge, financial commitment and the ability to persuade competitors to accept improved quality. Examples of other industries in which the ecosystem is being developed are e-mobility, automotive distribution

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and indemnity manufacturing. Within any environment, different stakeholders work together and as a result, require being instead of amongst our first environmental partners. For example, without sponsorship law, no stage would be worn for the transaction, and information distribution may be illegal. Companies or consumers will not use such a system as long as the issues are resolved. As a result and most importantly, the first group partners not only basically, excluding a destructive effect so they are predictable effortlessly draw and influence new participants to unite the net. Once the ecology is conventional, every environmental associate determination benefit greatly from this integration, for example: – Users and companies will enjoy greater access to high-quality information. – Technology providers will address the growing need for monitoring the flow of information with soft and hard skills. – Transportation supplier would have the chances to expand their frequency and continue to create new business models. – Law enforcement agencies determine fresh returns torrent from side to side tax deductions supply to the contestant. – Interior recovery of development. While shareholders devoted to investing in the blockchain building are important, it requires an additional attempt to incorporate the operations of the accessible procedure. This comprises not excluding to adapt existing inner procedure and commercial reproduction to be consistent with how to manage data in those new environments. Finally, the parties are involved in the process of development, moreover independently or cooperatively. Blockchain and IoT are still in their infancy so there is still a lot to learn. Entrepreneurship, workshops and a supplementary hold will help drive change and reinforce these innovations at all levels indoors and exterior of the company, with vertical integration becoming an integral constituent. Any business should be responsive for the requirement for low performing skills along with those products and distribution courses are indispensable on this period. Once successful with the realization of IoT-pedestal blockchain key in their companies and their industry processes, they laid the foundation for enduring benefits, for instance: – Aptitude to employ obtainable podium for alternative employ cases. – Construct strategic partnerships with industry stakeholders and streamline and make simpler indenture administration processes among shareholders. – Firmware solution. Whether IT with data elements be able to bring trust is a vital query while raising firmware solutions. There must be ensuring that only relevant information from a

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faith basis is built-in in the program. Similar algorithms build the solutions to work with them, but they are not limited to: – Near-field communication (NFC) statistics – Ultra-high frequency (UHF) transponders – Radio-frequency identification (RFID) labels – Extended microcontrollers – Field programmable gate array structures – Application-specific integrated circuit (ASIC) – IoT gates and storage areas – IT and network segmentation networks The main feature is an amalgamation of digital accelerator and NFC/UHF/RFID receiver. By installing a chip, which is directly linked to Blockchain [5]: – Utilities can be extended by the unexhausted hardware implementations – Conduct mission: exemplify extra opening Starting in 2017, a sharp increase in interest among companies from key industries in creating digital twin ideas directly connected to the blockchain can be viewed. To illustrate the wide range of pilot projects and opportunities in this area, two examples will be presented. Example 1: Power-generating features Bottom line: While the novel smart meters with the features of power tracking and performance are becoming a boon, due to the non-clarified standards between distributor and suppliers, inequality occurs in meters. By this standardization lacking in rules on changing the vendors, the smart meters feature is also lacking in functionality which loses its smartness Why blockchain seems to be an excellent key? With the eye of cyberattacks, blockchain allows being transparent in fees distribution among the producers and consumers storage processes. Also, since it facilitates in a distributed manner, it provides safety to us with the single point of failure risk [5, 15]. Figure 3.4 illustrates the two associated customer action streams and the energy area as an instance of measures while using crypto tags as a metering power key. Explanation advance and benefits: based on customer performance, manufacture and power, utilization varies greatly where sufficient data organization is not incorporated. Determining how much energy is used and the accuracy of data being enhanced by crypto tags. Non-detachable, validated crypto tags ensure the authenticity of the meter (unresolved environment) and thus generate a conviction in the usage statistics offered. With NFC, the proprietor, beforehand licensed for biometric certification, can contact marker data and upload customize data [16]. With establishing such a setup companies provide secure and effective solutions by enabling to:

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combine authorization of power meters with the customer mobiles for the active expense; monitoring with blockchain traceability and engender power consciousness; demonstrate the benefits and maximize the motivation for improving the bequest IT arrangement.

Figure 3.4: Power energy measuring example.

With the case study of a power meter, the blockchain–consumer interface representation is introduced in Figure 3.5. In this case, consumer safety is outlined among the shareholders with their power services and metering services. The infrastructure, which is worn directly for the disseminated procedure, pivot on largely lying on the needs for specific scenarios. For metering power, procedures unite the usage of the good agreement by a huge system that required a favorable flexibility policy. The use of utility installation systems permits intended for easy observation of power flow and billing calculations, elegant bond concurrence and recompense deci-

Figure 3.5: Blockchain interactive model.

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sion. As Figure 3.5 demonstrates, the interconnected excluding separate stage provide diverse shareholders which tackle diverse requirements.

3.5 Conclusion Both the IoT and digital twins have long existence and become a boon in various production industries. Though the implementation faced critical technical and economic barriers. Since IoT devices grew in numbers but the basic platform was no longer available to withstand such limit with any paradigm. Once this has been discovered, use cases such as evidence of concept, pathway and tracking and individuality supervision would be identified, novel commercial projects urbanized and the amount of data to be completely utilized. The IoT system distributes, employs and advertises data digitally, and using distributed IT ledger technology, middleware and analytics tools incorporate the inefficiency, accuracy and safety of environmental participants. This presents several new challenges. To overcome them the companies that intend to introduce safe and transparent tracking and tracking tools are investing in such technology financially. They are also developing soft and hard skills for this. On the other hand, where the additional number of blockchain platforms increases significantly by the number of participants, the new challenge is the shareholder executive acceptance. Such confront is a most determining feature in the verdict-production procedure in structuring a policy that advantageous such chance. The possible benefits are inadequate to greater visibility, safety measures, and effectiveness. As stated, by fastening an e-chip, space can be made market. These innovative backgrounds are key to providing new business skills: – Now the banks act as “custodians” allowing original representation high-quality possession of substantial resources. – Bitcoins are now becoming the core in the IoT scenario. – Within procurement management, digital twins support the transition from static ownership to the necessary machine modification models levy the impact of the forthcoming changes, industries must know their position in the ecosystem and how they work to contribute. IoT empowers digital twins and by teaching blockchain along with sympathetic to the needs and confronting of using this technology, companies are beginning to develop their business strategies for the future. The existing processes will not only work very well but also unknown types of businesses will now emerge and rebuild global industries. One such business model developed by the blockchain Institute in Germany to center the pioneering solutions equipped disseminated ledgers. The center wraps several

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productions moreover be intimately linked to the EMEA and Global Deloitte Blockchain panel [17]. It includes manufacturing and burly tactical acquaintance to work by a diversity of customers and associates, counting expertise and startup providers, institution of higher education, industrial company and authoritarian organization. Another one such as Europe’s leading blockchain interface solutions is RIDDLE & CODE specializing in advanced cryptography plug-in devices.

References [1] [2] [3] [4] [5]

[6]

[7] [8] [9]

[10]

[11]

[12]

[13]

[14]

Shen, C., Pena-mora, F., Blockchain for Cities – A Systematic Literature Review, IEEE Access, Digital Object Identifier 10.1109/ACCESS.2018.2880744. https://www.econstor.eu/bitstream/10419/176432/1/10.1186_s40854-016-0040-y.pdf PwC UK. (n.d.) Rapid urbanization. Retrieved from https://www.pwc.co.uk/issues/mega trends/rapid-urbanisation.html#1 (last accessed on 2 February 2021). PwC. (2015). How smart are our cities? Retrieved from https://www.pwc.in/assets/pdfs/publi cations/2015/how_smart_are_our_cities.pdf (last accessed on 2 February 2021). PwC and FICCI. (2015). India: Surging to a smarter future. Retrieved from https://www.pwcin/ assets/pdfs/publications/2015/india-surging-to-a-smarter-future.pdf (last accessed on 2 February 2021). Government of India. (n.d.). Improving lives: Urban infrastructure. Make in India website. Retrieved from http://www.makeinindia.com/article/-/v/improving-lives-urban-infrastructure (last accessed on 2 February 2021). Bashir, I. (2017). Mastering Blockchain, Mumbai: Packt Publishing. Investopedia. (n.d.) Definition of double-spending. Retrieved from https://www.investopedia. com/terms/d/double-spending.asp (last accessed on 2 February 2021). PwC US. (n.d.). Making sense of bitcoin, cryptocurrency, and blockchain. Retrieved from https://www.pwc.com/us/en/financial-services/fintech/bitcoin-blockchain-cryptocurrency. html (last accessed on 2 February 2021). Staff reporter. (6 October 2016). Dubai government to embrace blockchain technology. Khaleej Times. Retrieved from https://www.khaleejtimes.com/nation/dubai/dubai-toembrace-blockchain (last accessed on 2 February 2021). CXIHUB. (10 October 2017). Indian state partners with blockchain startup for land registry pilot. Retrieved from https://www.cxihub.com/2017/10/10/indian-state-partners-withblockchain-startup-for-land-registry-pilot/ (last accessed on 2 February 2021). IDRBT. (2017). Applications of blockchain technology to banking and financial sector in India. White paper. Retrieved from http://www.idrbt.ac.in/assets/publications/Best%20Practices/ BCT.pdf (last accessed on 2 February 2021). Shin, L. (7 Feb 2017). The first government to secure land titles on the bitcoin blockchain expands project. Forbes. Retrieved from https://www.forbes.com/sites/laurashin/2017/02/07/the-firstgovernment-to-secure-land-titles-on-thebitcoinblockchain-expands-project/#43bb76154dcd (last accessed on 2 February 2021). Dinkins, D. (20 Sep 2017). Delaware approves tracking of stock ownership on blockchain, major effects. Cointelegraph. Retrieved from https://cointelegraph.com/news/delawareapproves-tracking-of-stock-ownership-on-blockchain-majoreffects (last accessed on 2 February 2021).

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[15] Davidson, J. (2 Nov 2017). Increasing trust in criminal evidence with blockchains. MOJ Digital & Technology, Government of UK. Retrieved from https://mojdigital.blog.gov.uk/2017/11/02/in creasing-trust-in-criminal-evidence-with-blockchains/ (last accessed on 2 February 2021). [16] Barzilay, O. (21 Aug 2017). 3 ways blockchain is revolutionizing cybersecurity. Forbes. Retrieved from https://www.forbes.com/sites/omribarzilay/2017/08/21/3-ways-blockchainis-revolutionizing-cybersecurity/#4f5761842334 (last accessed on 2 February 2021). [17] Office of the Registrar General & Census Commissioner, India (n.d.) Civil Registration System Division. Ministry of Home Affairs, Government of India. Retrieved from http://www.censusin dia.gov.in/vital_statistics/CRS/CRS_Division.html (last accessed on 2 February 2021).

Vineet Chouhan, Raj Bahadur Sharma, M. L. Vasita, Shubham Goswami

Chapter 4 Measuring barriers in adoption of blockchain in supply chain management system Abstract: The blockchain technology (BCT) or distributed ledgers is an emergent technology that allows the autonomous and immutable preservation of checked data by offering a revolutionary forum of a modern, decentralized and transparent exchange system for industries and companies. The inherited characteristics of BCT foster trust by clarity and traceability in every transaction involving records, products and financial capital. Through initial concerns, governments and major companies have recently investigated the implementation and improvement of this BCT in different fields of use, including supply chain (SC) networks. Slowly, the community of this sector realizes how profoundly blockchain (BC) could affect their industry. BC’s ability to guarantee accuracy, quality control and authenticity of data, coupled with smart contractual partnerships, represents a major reconsideration of SC and supply chain management (SCM). It provides more and more logistic items with sensors that produce data in the SC, for example, on the shipment status. This data must be processed in an external, open manner. Current practices for the types of obstacles to implementing BCTs are implemented in the fields of interorganizational, intraorganizational, technological and external barriers. Procurement costs, shipping costs, inventory costs and quality costs are the four primary reasons that increased the expenses in the conventional supply chains. In this research, we have identified the barriers against the use or development of sustainable SCM, by taking views of 500 working professionals of various global SC-oriented companies. The study’s outcome by using linear regression reviled economic obstacles, cross barriers, structure barriers and communication threats. Related barriers are BC barriers in general. Similarly, it can limit the use of BCT for SC. To improve these problems and to improve sustainability, the SC should also decrease resource use, reduce greenhouse gas emissions, check that the commodity is renewable in terms of greenhouse gas emissions, increase recycling,

Vineet Chouhan, School of Management, Sir Padampat Singhania University, Udaipur, Rajasthan, India, e-mail: [email protected] Raj Bahadur Sharma, Department of Accounting, College of Business Administration, Prince Sattam bin Abdulaziz University, Kingdom of Saudi Arabia, e-mail: [email protected] M. L. Vasita, Department of Business Administration, Rajasthan University, Jaipur, India, e-mail: [email protected] Shubham Goswami, School of Management, Sir Padampat Singhania University, Udaipur, Rajasthan, India, e-mail: [email protected] https://doi.org/10.1515/9783110702507-004

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improve emissions sharing schemes (ETS) and improve governance using information management mechanism by understanding the barriers. Keywords: blockchain, sustainable blockchain, supply chain management, barriers for sustainable SCM

4.1 Blockchain technology Blockchain technology (BCT) is a central archive of documents or mutual public or private libraries for every recorded activity executed and traded by committed blockchain (BC) officers [1]. It has an origin that can be drawn from the technologies of distributed ledgers. BCT varies with many available evidence management strategies by providing four core features: non-location (delegation), safekeeping, suitability [2] and smart implementation (see Figure 4.1). In the BC, the agent can create a new operation to attach BC. This latest matter is being submitted in system for confirmation and inspecting purposes. Until most lumps in the restraint accept this operation in line with the predefined agreed rules, this payment update will be added as a new slab to BC. The archive of this transaction is stored in a set of distributed security nodes. In the meantime, the smart contract, which is a central feature of the BCT, enables credible transactions to be carried out without the intervention of external parties. The fundamental discrepancy between the present architecture of the Internet and BCT is that the net was built to transfer knowledge (not worth) further to pass versions of items (not initial details). In BC, trust is expressed in contracts registered in a public ledger and protected by having a factual, publicly posted transaction history that offers reliable and auditable evidence [3]. These transfers occur in a testing mechanism compatible with the principles of the network consensus. If the latest transactions are validated and applied to the BC, several versions are generated in a distributed way to develop a series of confidence. Decentralizations are an essential property of BCT that regulates the adulteration of knowledge, thereby growing the information’s authenticity. Collectively managed databases are unworkable and checked databases of each transaction are made available to participants via circulated Federal and State Books [1]. Communication systems are far more vulnerable to abuse, violation or failure [4]. Trust is a significant effect of deregulation because it is easy to test traders or other network members [5], and the proof is readily seen and matched. This process does not consider any organization and is faced on behalf of its members, but the basic framework ensures the credibility of the framework. Participants can make purchases. This functionality provides clarity [4] while at the same time maintaining privacy by retaining cryptographic documents [1]. BC may be extended and familiar with enforcing a negotiated series of rubrics which maybe no one, including the manipulators or the framework

Figure 4.1: Block plan for BCT [6].

Non-Localization

The Block Briadcast to every node in the blockchain

A new transactio is requested with a new Block

Auditability

CONTRACT

The majority of nodes approve the validity of transaction

The Verification process and adding new transaction to the ledger can be executed by smart contracts

Smart Execution

Security

The block is added to the Blockchain A new copy of ledger is saved in distributed networks

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operatives, will alter. They depend on a specific device design model for applications affecting various parties that involve little faith in one another; for instance, fractured execution. Based on design technology implementation, the BC concept is different and can publicly or privately impact books and records and networks [7]. Its architecture is distinct from all the matches on the platform and the guidelines for managing the BC. In a proprietary or closed BC, the stakeholders are identified. Since their is no confidentiality, they can be treated similar, just as in an SC network of established individuals involved in the manufacture and sale of goods. Additional functions, such as certifiers, will include validation to the SC network members and manage. It is a digital platform. As a replacement, in a direct or transparent BC, to maintain many unidentified users’ trust, cryptological approaches are used to allow operators to join the system and track their dealings [8]. In the meantime, the newest cohort of transaction with requests that build loyalty, reliability and efficiency is being promoted by BCT, which is regulated by an alleged smart agreement. A consensus mechanism is a series of rules and regulations for exchanging terms and acts among entities. It shall instantly check that the statutory provisions have been met and that the transfers have been carried out [9]. A smart contract’s reasoning is applied by a consortium of members that come to a conclusion for outcome of the agreement. The agreement executes its coding if it receives an order, perhaps by a network player or from another transaction. The ledgers shall be updated if the provisions of the contract are met [10]. BCT started as a BC-based cryptocurrency management platform [11]. Along with digital resources, BCT is a new paradigm for computing and distributing knowledge [4, 12, 13]. It is the point of view that we derive from much of this essay.

4.2 Supply chain Modern SCs are fundamentally competitive, multistage, geographically disjointed players competing for service customers [14–16]. Globalization, evolving regulatory agendas and difficulties with SC networks render it nearly difficult to assess hazards in this dynamic network [17, 18]. Understaffed sales contribute to a greater level of confidence and honesty, which makes physicians believe you are cheating. Traceability is an important concern in many SC sectors, including the food sector, which includes maintaining track of the procurement of food, pharmaceuticals and surgical materials [13, 19]. Objects that were produced in the past, with specific identifying details, will easily be lost or changed. Lack of clarity in the sector makes it impossible to know the true worth of every good. The costs involved in the collection, reliability and transparency of intermediaries also impede traceability within the SC. Strategic and reputational strategic issues exist because of these threats and

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lack of accountability. And Maradol brand papaya did suffer from a salmonella epidemic that led to thousands of people getting sick in the United States. First, a typhoid vaccine was detected in the Salmonella epidemic but the shipment origin could not be verified. Second, also, dangers and threats were identified. Third, 2015 is another example of this. A widespread, ongoing E. coli outbreak in Chipotle. Mexican Grill outlets, leaving dozens of customers ill and turns an epidemic. The epidemic triggered picture problems for Chipotle. The stock valuation fell by 42%. The lack of transparency and consistency of Chipotle’s SCs has become an issue for Chipotle. This could contribute to more stringent pollution restrictions right after detection. Currently, SCs place a high value on standardized, often disparate, and location proof organization structures inside organizations; as ERP systems that have flaws. SC businesses require considerable faith to rely on a single agency or broker to store their valuable and usable information [12]. One point collapse is another downside of organized information structure that exposes the whole process to fraud, robbery, exploitation, or attack [20]. SC strategies and procedures are now meeting evolving demands for the identification and qualification of SC performance. Sustainability has been characterized by a triple bottom line strategy that includes financial, social and corporate aspects [21–25]. The verification and assurance that SC programs, products and activities conform to these sustainability and acceptance criteria [21, 23, 26] of SC sustainability is a significant strategic and competitive problem. Such questions raise suspicions about whether the current SC knowledge schemes can include the details mandatory for the appropriate origin of goods and services in a reliable manner that is clear and robust enough to be trusted. The solution to these emotional issues is to improve SC’s transparency, security, longevity and reputation. BCT may be the key to this problem. New technological advancements and developments in the concept of BCT allow these development goals to be more organizationally, politically and sparingly available [12, 27]. BCT can allow global transfers and process deregulation and decentralization amongst different parties [1]. Earlyuse examples illustrate how strong BC systems are. One of the most popular collaborations includes Maersk and IBM in handling containers via BCs. In that same use case, IBM indicated billions of savings can be attained by getting better landing bills connected to bins [28]. The savings estimated are billions, but deployment may be feasible due to scalability problems. Provenance, a BC seafood processor, has attempted to introduce BCT into sustainable seafood from a point of view. In this case, the reputation of environmental policies has been central [2]. Thus, several questions pertaining to environmental, technological and social problems have been addressed in the science literature.

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4.2.1 SC cost drivers SC cost drivers are also an integral aspect to be understood because they cannot be applied to BCT. It includes procurement costs; they are, first and foremost, the most apparent costs that will have to be mitigated around the SC, that is, to pay for supplies inside the SC. One point to bear in mind here is that if you have a large business, it is not going to be feasible to run to the supermarket to get all the items. They intend to put back municipal procurement officials to take charge of this. Even if the prices are significant, the extra resources used to invest on the commodity itself are the explanation for this success. It is important to establish a balance between pace and cost. High-speed rail is rather costly. However, low cost will be lost on time, which is just as important, if not more so. Production expenses are the costs of managing inventory. This will save more capital. Here is when things get a little sticky. Many businesses are winding up owing money to banks for inventories. And they still have to pay off the debt, so they still have to pay off interest. It is inefficient to leave your possessions unguarded. The organization’s administrators and protective personnel have to carry on a vital position in the treatment and collection of items. Despite your best intentions, there would be unforeseen challenges, including failure, cracking and robbery. Quality costs: The commodity produced to reach a specified standard has its costs. Overall, having faulty goods can contribute to issues further in the line. However, to carry out those safety tests, the organization has to employ professionally qualified specialists. In addition, just bear in mind that a substantial number of goods would be disposed of at once. Although BC uses approaches that have grown through the years, much as any theoretically destructive process or device, it faces several barriers and hurdles to the acceptance and deployment of SC networks. BC is already at an early stage of growth, with numerous problems resulting from interpersonal, operational, technical or policybased causes [1, 29, 30]. These topics may have been relevant in the context of scientific literature for several years. At this point, the evolving functional problems are the hallmarks of academic discussions and concerns. The issues are yet to be tackled practically and efficiently. In this post, we open a conversation emphasizing BC-based SC issues, hurdles, BC integration advantages and innovative SC applications. Links with existing theories, the need for a possible new approach and study are often discussed; consequently, some concrete theoretical proposals exist. The chapter is formulated as follows. The BCT is presented in Section 4.2, and its use in the management of the SC is defined in Section 4.3. Section 4.4 introduces the benefits of BC in preserving the sustainability aspects of the SC network. In Section 4.5, challenges and obstacles to introducing BCT in the SC and support for sustainability are evaluated and divided into four separate groups. Study directions and suggestions are set out in Section 4.6. Section 4.7 concludes the chapter.

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4.3 BC-based SC BCs are highly distracting innovations for the architecture, structure, execution and general management of SCs. BC’s capacity to maintain accountability and integrity of details, along with smart contractual partnerships for a trustless society, all represent a major rethink of SCs and SC management. In this section, we further discuss BCT’s value strategy and its importance to the SC of goods and development, its construction and possible new elements for SC power. How BC functions within SC is still based on research and development. Unlike Bitcoin and other financial BC apps that may be available, SC BC-based networks require locked-in networks, proprietary and approved database with several restricted players. However, the door could always be accessible to a more public collection of partnerships. Control of the scope of privacy is one of the first decisions to be made. Figure 4.2 presents general graphic of the conventional SC transition to an SC-centered BC.

Figure 4.2: SC cost driver. Source: https://www.dummies.com/business/management/cost-drivers-supply-chainmanagement/.

Four main actors perform positions in BC-based SCs, several of which are not found in conventional SCs. Like suppliers, dealers and consumers, actors must be accredited by a licensed auditor or certifier to retain scheme confidence [2]. There are also effects on the SC commodity and resource movements. Each commodity can have a digital BC presence such that all related parties have clear access to the product profile. Protection protocols can be established to restrict contact where only individuals again with right digital keys have access to objects. A range of specifics can be accessed, including the commodity’s condition, the type of the product and the requirements to be applied to the product [31]. The commodity identification tag is an attribute that connects specific goods for their virtual identity in BC [12]. One fascinating aspect of the arrangement

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and flow control is how a commodity is “managed” or moved by a single actor. Actors are obtaining authorization to insert new details into the profile of another entity or participation. Participation in an exchange with another group is likely to be a significant law where authorization acquisition may require smart contract agreements and a consensus. Once goods are transferred (or shipped) to some other entity, both parties can register a virtual agreement and comply with the specifications of a smart contract to validate the trade. Since all sides have fulfilled their contract agreements and processes, the transaction details will be transferred to the BC servers. Data transaction history must be changed automatically with device when a transition is implemented [12]. BCT should describe and explain several main cryptographic keys, the substance (what is the consistency?; how is the scale?; how much of it is?) and the place (where it is and the presence of it?; who controls it at all time?). In this manner, the BC removes the need for a safe central entity which controls or oversees this phase and helps consumers to monitor the chain of custody and transfer of raw materials to final purchases. This knowledge is documented when transactions arise on these various BC knowledge dimensions, with verifiable changes. BC efficiency and accountability are intended to promote resource and knowledge transfer across the SC more effectively, with integrated governance criteria. This transition may result in the broader change from a sustainable industrial product economy to a knowledge economy, to a customization economy. The output would depend strongly on expertise, contact and details; not merely on postural characteristics [32]. For example, consumers may monitor specific product details to improve the costumers’ confidence in producing qualities [4]. As published guidelines, BC-based SC may help to describe the relationship of the network agent with each other and within the structure. Smart contracts affect the exchange of network data between SC members and continuous process development. Certifiers and standard bodies, for example, digitally check the identities and goods of the actor. Actors and products have their public network profile, which shows definition, venue, qualification and product affiliation. Every SC player will log in crucial details regarding the commodity and its position on the BC system [31]. Smart contract regulation and method laws focused on BC SC will control participants’ registration and consent, what systems are permitted for entering and required for implementation. The rules cannot modify without some kind of agreement [13]. The selection method is another example of a smart contract application. The intelligent deal for two trading parties will lawfully change a digital database of what products have been ordered, exchanged and shipped within required period by the final user throughout business stripe. Smart contract characteristics reflect a possible market mechanism for quality development of SC operations. The opportunity to enhance the SC market environment may be situated in BC details that can collect output indicators in ledgers, binding them to a method agreement. This methodology and knowledge style has tremendous potential for SC design and real-time effects, above just retail distribution and governance issues. BC affects the SC, inventory management systems (Figure 4.3)

Chapter 4 Measuring barriers in adoption of blockchain

45

Supply Chain

Raw Material Supply

Manufacturer

i

Distributors

i

Wholeselers

i

Registrars Blockchain-based Supply Chain

i

i

End User

Retailors

i

i

Standards organizations

Raw Materials Supply

i

Manufacturer

End Users

Products’ Information

i visible to customers

Smart Contract

i

Distributors

Retailers

Ownership change

i

Wholesalers Certifiers

i Figure 4.3: BCT for SCM [6].

and financial transfers between various network members [33]. As significant potential gain for BC, SC is the disintermediation of money markets, namely digital currencies, markets and capital flows [34]. It will allow trade procedures between partners more effectively. SC money market flows’ inefficiencies are abridged using SC finance methods such as reversal and efficient undervaluing [35, 36]; network reductions of huge investment (see Figure 4.3) [37]. Smart systems are in a role to organize financial agreements that guarantee that ample funds are accessible for programs that compensates everybody in due time [38]. It provides a safe and timely connection for

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transactions amongst different type of Capital or combines them from numerous foundations in the worldwide SC [39]. While there could be a large spectrum of BCT implementations throughout the SC, they are based on business, commodity, operation or governance. For demonstrating the practical use of the BC SC, we transform our conversation toward decentralized SCs. Momentum is building on ideas for the climate. Regulatory, consumer and social pressures on businesses and their SCs increase the efficiency of their SCs and products [40]. These details lead us to recognize more the potential consequences of SC by contemplating the effects of BCT on competitive SCs.

4.4 Preparing for BCT implementation with SC: knowing the hurdles As per the chapter’s scope is concerned, it needs to be determined that BCT can affect and hinder SC preparation, activities and motions of items. Benefits and developments have been established. We are now exploring roughly the issues associated with application in this field, particularly concerning the SCs, BCT and sustainability. Efficient usage of BC systems to record environmental actions and monitor SC processes and products around the distribution chain continues by defining the challenges and barriers that need to be addressed. SC participants need to consider and prepare for the implementation and deployment of BCT. The portion that covers related literature, including articles, magazines, conference articles, study papers and online databases, has been reviewed to recognize various hurdles to BCT acceptance, in general, and safe SCs, in particular. Barriers were built based on the literature on supply chain management (SCM) systems, transparent SCs and BCT. References to the collection of obstacles stem from these three primary fields. Expert guidance was also given to help verify the lean of blocks. Obstacles are abridged and listed in five major types of the economic obstacles: intraoperational barriers, device barriers, external obstacles and related expense barriers, taking into account internal and external organizational limitations in introducing new technology. The theoretical model of these obstacles is exposed in Figure 4.4.

4.4.1 Intraorganizational barriers These obstacles emerge from the organizational operations of the company. Top official assistance is a crucial element in the effective execution of every SC activity. However, individual administrators do not have a long-term dedication to endorse the implementation of emerging technologies and environmental principles. Lack of management engagement hinders the credibility of SC systems’ sustainable activities [41]. The shortage of understanding and engagement of managing in the SC will threaten capital

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47

Figure 4.4: A theoretical model of barriers of BC in SC.

distribution [42] and financing choices. BCT adoption includes investment in advanced knowledge processing hardware and software that is expensive for companies and network providers [43]. The absence of the latest corporate policy expected to justify the application of BCT might be a problem. BCT adoption can alter or turn present corporate philosophies [44]. Administrative philosophy describes the principles for working communities, standards and proper actions within companies [45]. Besides, the implementation of BCT in SC systems involves additional positions, obligations and skills to promote various areas of technology adoption [44]. Restricted technological experience and understanding of the application of BCT serve as an obstacle to the introduction of this emerging technology into the SC. While there is an interest in BC in the commercial industry, there is a small number of implementations and professional developers of BC [43]. BCT is a software application [27] that may be destructive and has to be changed or substituted by obsolete systems [43]. Converting to different methods will shift the corporate philosophy or pyramid and contribute for opposition with apprehension on persons and associations [46]. Hypothetically, utilizing the Technology Acceptance model (TAM), the degree of usefulness of modern information technologies in a way of its accessibility and usability for individuals and organizations can be measured and calculated [47, 48]. The BC curriculum may be measured via a TAM point of view. Suppose companies want active SCs to promote emerging information structures that are part of the entire SC network. In that scenario, sustainable activities must be integrated into their business philosophy and purpose [49]. Constructive sustainable initiatives are therefore required across all corporate levels and around the SC [50]. The absence of formal tools, processes and metrics hinders the effective adoption and assessment of sustainable activities [51] in the BC environment for a given company. BCT is in its early stages, and it is challenging to identify the SCs that have effectively adopted this technology to monitor their innovative activities. The scarcity of market frameworks and best practices for applying BCT is a problem [43]. Environmental laws are one of the critical pillars of ecological policies in companies. Organizations are spending and

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trying to fulfill the minimum sustainability requirements but can, at the same time, obstruct their ingenuity and progress in applying sustainable approaches [52]. The desire of consumers for sustainable goods and methods is a catalyst that can boost innovation in sustainability. The lack of consumer understanding and willingness to commit to environmental growth is a threat to sustainability. In this situation, consumers do not recognize green certification programs and are reluctant to adopt conservation measures or spend much on sustainably acquaint products [51, 53].

4.4.2 Interorganizational barriers This group primarily recognizes and removes obstacles to the collaboration between SC stakeholders. SCM is mainly concerned with maintaining partnerships between parties to build benefits for interested parties [15]. However, relations amongst associates may be difficult, particularly at the time of the convergence of information technology and sustainability practices. BCT will allow the exchange of knowledge across the SC. While openness and verifiability of information are required to determine the SC’s reliability efficiency [54], individual companies can take input as a low-cost gain that allows them unlikely to disclose useful and essential information [55]. The reluctance to disclose details as of collaborators could restrict the maximum gains from adopting BCT and delay the practical application of BCT. Different privacy policies relating to the use and release of information and data in SCs may contribute to new problems for exchanging data between stakeholders [55]. The confidentiality of knowledge in BCT exchange regulations and procedures must be specified and handled inside the SC network. The absence of proper knowledge exchange guidelines inevitably affects cooperation between SC stakeholders [45]. Lack of coordination and efficient cooperation between SC stakeholders with different and sometimes conflicting organizational goals and expectations [51] disrupts sustainability [56] and SC activities and the introduction of BC builds sustainability principles. Contact problems might be more substantial if SC participants were widely spread through diverse communities [52]. Finally, merging typical SC strategies with sustainable activities is not a simple task. Present systems, prototypes, products and procedures required change to promote sustainable activities [54, 57]. Reducing carbon impact, greenhouse gas emissions, water pollution, energy usage and waste involves replacing products, machines and installations. It placed expenses on the SC. Similarly, the gathering of knowledge for BCT uses often includes its laboratories and computers. RFID and the Internet of things are two possible answers to this problem.

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4.4.3 System-related barriers New IT resources are required to incorporate BCT and collect SCM knowledge (e.g. Internet of things). It could be a problem for certain actors in SC [12]. Both chain members continue to gain access to the knowledge they need to take advantage of the profit by reducing the time period in their interconnected SC [45, 58]. Consequently, the restriction of technical connectivity to real-time knowledge in SC is an obstacle to adopting BCT. BCT is at its initial phase of development and is known to be an inexperienced scalability and managing technology for a large amount of purchases [30]. The size and number of blocks are a storage problem for processing large data in real-time use, named a “bloat” issue in Bitcoin [27]. SC systems must have much more significant data criteria, which go beyond financial details to provide data relevant to processes and activities. Improvements in resource technology and integrated cloud processing systems would also be required. Information exploitation of SC networks may be a primary task [59]. Although the introduction of BCT allows any participant in the SC networks to validate transactions, deception is still possible through the consent of the contestants [27]. Data confidentiality with safety issues are also the problems linked to BCT usage [43]. Some study has discussed the protection risk of BCT in the Bitcoin network, including breaches with assaults [60]. While many solutions have been introduced to resolve BC security concerns, no evaluation has been made to these strategies’ effectiveness [30]. Currently, BCT is mainly synonymous with cryptocurrency such as Bitcoin and its illicit activity [27], the “dark web” stigma that slows down BCT acceptance in general. Another primary feature of the BCT is the immutability of knowledge. It ensures the experience is unable to be upgraded and erased without a majority in BC. It avoids the falsification and adulteration of data [4]. Though, people are already interested in the implementation of this technology with the risk of providing wrongly reported records. If critical owners are willing to modify and upgrade the papers with additional details, the scar with the incorrect form will still remain in the BC [61].

4.4.4 External barriers This group raises problems from external customers, markets, organizations and states, who do not explicitly benefit economically from SC’s operations. External demands and encouragement for adopting environmental and technology strategies will cause companies to incorporate them into their systems. Lack of effective government and business policies and desire to guide and encourage efficient and healthy practices is an obstacle to innovation and innovative technical support systems [62]. Policy rules and guidelines regarding the use of BCT are also uncertain. Indeed, many governments’ adverse policies on Bitcoin are of interest to businesses and companies and could affect the broader use of BC for corporate purposes [43].

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Governments, NGOs, companies, societies and technical associations can also encourage BCT to build sustainable value. Moreover, the volatility of demand for renewable goods and consumer actions’ complexity will impact market competitiveness [57] and delay the fusion of sustainable and BCTs. Companies are required to provide guarantee to clients that they would pay their developments in renewable goods, sustainable systems and emerging innovations such as BC. The study and clustering of BCT hurdles would pave the way for a successful awareness of emerging technology in SC networks and developing sustainability dimensions of the SC. These variables are not empirically checked nor proven, but the structure and influences offer a starting point for potential studies. More in-depth research is likely to contribute to additional wider theoretical problems outside inter/intraorganizational environment, technological and external contexts, such as political campaigns to globalize SC networks. Building on certain simple understandings, advantages and obstacles to implementing BCT in the SC environment, we are now exploring some of the technical study consequences.

4.4.5 Cost-related barriers For implementing BCT and gathering information for SCM purposes, cost is also one of the significant elements. In every SC, the cost for replacing slow, manual processes for the smooth functioning of the supply of raw materials is required. Under a good SC the cost of strengthening traceability is to be measured carefully to handle a good relationship with the SC partners. Further, the BC-based SC system aims to reduce SC IT transaction costs; this may be possible with the preapproved transaction fees and accurate measurement of the current system with the auditability and audit cost control feature. Under this stage, the primary barrier is the time delays and cost associated with it, which is further subject to human error and its cost, transportation costs, inventory costs and quality cost. To move forward, the research plan for the implementation of the BCT for SCs, we suggest research-based proposals on the effects of adopting the BCT in the SC sense by analyzing the barriers and shedding light on the methods that can be used to overcome this situation.

4.5 Process and methods As per the exploratory nature of the study for the current process, the views of 500 respondents working in various SC-oriented companies were gathered with the google forms; the questions had the five-point Likert close-ended answers with 1 as strongly disagree, and 5 as strongly agree. This is the primary source of gathering the data as shown in Table 4.1-part A. The sample size selected was 1,000, but the

Chapter 4 Measuring barriers in adoption of blockchain

51

responses collected were from 50% of the respondents, due to language and other barriers. Further, the respondents include the supervisor- and manager-level personnel responsible for the improvement of the SC-related problems in their companies. To conclude, the multiple regression method is being implied in this section as under: Table 4.1: Detailed results of regression analysis. A – Descriptive statistics Variables (questions asked to respondents)

SPSS code

Mean

Std. N deviation

Barrier

Barriers

.

. 

Financial constraints

EB_

.

. 

Management commitment and support

EB_

.

. 

Lack of organizational policies for using technology

EB_

.

. 

Lack of knowledge and expertise

EB_

.

. 

Difficulty in changing the organizational culture

EB_

.

. 

Hesitation to convert to the new system

EB_

.

. 

Lack of tool for BCT implementation in sustainable SCs

EB_

.

. 

Luxury and high-value items can easily be lost or altered.

EB_

.

. 

Lake with consumers’ awareness with sustainable development patterns and BCT

IOB_

.

. 

Connection and collaboration issues in the SC

IOB_

.

. 

Policy issues on sharing of knowledge between SC partners

IOB_

.

. 

Challenges in the convergence of environmental activities and BCT by SCM

IOB_

.

. 

Cultural gaps between SC partners

IOB_

.

. 

Missing one block impact of crushing the whole BC

IOB_

.

. 

Security of the device

SB_

.

. 

Entry to innovations

SB_

.

. 

Hesitation on the introduction of BCT owing to low public opinion

SB_

.

. 

Immutability problem for BCT

SB_

.

. 

Application immaturity

SB_

.

. 

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Vineet Chouhan et al.

Table 4.1 (continued) A – Descriptive statistics Variables (questions asked to respondents)

SPSS code

Mean

Std. N deviation

Virus and software-related threat

SB_

.

. 

Improvement in the system with upgradability

SB_

.

. 

Lack of administrative strategies

EXT_B_ .

. 

Lack of participation: participation of external stakeholders

EXT_B_ .

. 

Lack of industry participation in legal and environmental procedures

EXT_B_ .

. 

Lack of rewards and opportunity systems

EXT_B_ .

. 

Use of confidence in the method

EXT_B_ .

. 

Legal acceptability of disruptive technology

EXT_B_ .

. 

Consensus on adoption

EXT_B_ .

. 

Competitor’s policy

EXT_B_ .

. 

Cost for replacing slow, manual processes

CRB_

.

. 

Cost of strengthening traceability

CRB_

.

. 

Reducing supply-chain IT transaction costs

CRB_

.

. 

Preapproved transaction fees

CRB_

.

. 

Auditability and audit cost

CRB_

.

. 

Time delays and cost associated with it

CRB_

.

. 

Human error and its cost

CRB_

.

. 

Transportation costs

CRB_

.

. 

Inventory costs

CRB_

.

. 

Quality cost

CRB_

.

. 

53

Chapter 4 Measuring barriers in adoption of blockchain

Table 4.1 (continued) B – Reg. coefficients Variables

Variable name

Adj. R

ANOVA

Sig.

Economic barriers

EB_

.

.

.g

.

.

.e

.

.

.i

.

.

.e

.

.

.g

EB_ EB_ EB_ EB_ EB_ Interorganizational barriers

IOB_ IOB_ IOB_ IOB_

System-related barriers

SB_ SB_ SB_ SB_ SB_ SB_

External barriers

EXT_B_ EXT_B_ EXT_B_ EXT_B_

Cost-related barriers

CRB_ CRB_ CRB_ CRB_ CRB_ CRB_

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Vineet Chouhan et al.

Table 4.1 (continued) C – Coefficient table Model











Unstand. coeff.

Stand. coeff.

B

Beta

SE

(Constant)

.

.

EB_

.

.

EB_

.

EB_

t

Sig.

Correlations(r) Zero-order

Partial

Part

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

−.

.

−.

−.

.

−.

−.

−.

EB_

.

.

.

.

.

.

.

.

EB_

−.

.

−.

−.

.

−.

−.

−.

EB_

−.

.

−.

−.

.

.

−.

–.

.

.

.

.

IOB_

−.

.

−.

−.

.

−.

−.

−.

IOB_

.

.

.

.

.

.

.

.

IOB_

.

.

.

.

.

.

.

.

IOB_

.

.

.

.

.

.

.

.

(Constant)

.

.

.

.

SB_

.

.

.

.

.

.

.

.

SB_

.

.

.

.

.

.

.

.

SB_

−.

.

−.

−.

.

−.

−.

−.

SB_

–.

.

–.

−.

.

−.

−.

−.

SB_

.

.

.

.

.

−.

.

.

SB_

−.

.

−.

−.

.

−.

−.

−.

(Constant)

.

.

.

.

EXT_B_

.

.

.

.

.

.

.

.

EXT_B_

−.

.

−.

−.

.

−.

−.

−.

EXT_B_

.

.

.

.

.

.

.

.

EXT_B_

.

.

.

.

.

.

.

.

(Constant)

.

.

.

.

CRB_

.

.

.

.

.

.

.

.

−.

.

−.

−.

.

−.

−.

−.

(Constant)

CRB_

55

Chapter 4 Measuring barriers in adoption of blockchain

Table 4.1 (continued) C – Coefficient table Model

Unstand. coeff.

Stand. coeff.

B

Beta

SE

t

Sig.

Correlations(r) Zero-order

Partial

Part

CRB_

.

.

.

.

.

.

.

.

CRB_

.

.

.

.

.

.

.

.

CRB_

.

.

.

.

.

−.

.

.

CRB_

−.

.

−.

−.

.

.

−.

−.

g. Predictors: (constant), EB_6, EB_1, EB_3, EB_7, EB_8, EB_2 e. Predictors: (constant), IOB_6, IOB_5, IOB_4, IOB_1 i. Predictors: (constant), SB_6, SB_1, SB_2, SB_7, SB_4, SB_5 e. Predictors: (constant), EXT_B_5, EXT_B_7, EXT_B_3, EXT_B_1 g. Predictors: (constant), CRB_2, CRB_10, CRB_9, CRB_8, CRB_1, CRB_6

The research confirms that the economic barrier in front of the use of BCT in SCM in global context includes six variables, that is, financial constraints (EB_1), management commitment and support (EB_2), lack of organizational policies for using technology (EB_3), hesitation to convert to the new system (EB_6), lack of a tool for BT implementation in sustainable SCs (EB_7) and luxury and high-value items can easily be lost or altered (EB_8) with the value of adjusted R2 at 65.3%, and the importance of ANOVA is also found to be significant. It means the selected variables are significantly treated as an economic barrier for BC’s application in SC. Further, interorganizational barriers that affect the use of BCT in SCM includes lake with consumers awareness with sustainable development patterns and BCT (IOB_1), challenges in the convergence of environmental activities and BCT by SCM (IOB_4), cultural gaps between SC partners (IOB_5) and missing one block impact of crushing whole BC (IOB_6) with the value of adjusted R2 at 42.1%, and the importance of ANOVA is also found to be significant. The system-related variables include security of the device (SB_1), entry to innovations (SB_2), immutability problem for BCT (SB_4), application immaturity (SB_5), virus and software-related threat (SB_6), improvement in the system with upgradability (SB_7) with the value of adjusted R2 at 11.8% and significant value of ANOVA; the external barriers include lack of organizational strategies (EXT_B_1), lack of industry participation in legal and environmental procedures (EXT_B_3), use of confidence in the method (EXT_B_5) and consensus on adoption (EXT_B_7) with the value of adjusted R2 at 35.5%; ANOVA value is found to be significant. Finally, the cost-related barriers include cost for replacing slow, manual processes (CRB_1), cost of strengthening traceability (CRB_2), time delays and cost associated with it (CRB_6), transportation

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Vineet Chouhan et al.

Figure 4.5: Barriers of BCT for SC model.

costs (CRB_8), inventory costs (CRB_9), quality cost (CRB_10) with the value of adjusted R2 at 50.8%, and ANOVA value is found to be significant. It reveals that the variable selected is significantly treated as an essential barrier that affects BCT in SC management (as shown in Figure 4.5). This managerial application of the research is vast since the variables that are identified in the study will be the barriers against the use of the motion of application of BCT in SC. We have already analyzed the benefits of BCT into SCM, and the management needs to address these variables for implementation of BCT in SC management.

Chapter 4 Measuring barriers in adoption of blockchain

57

4.6 Conclusion In this chapter, we suggested and addressed the implementation of BCT in the SC network. We have tried to identify obstacles that can impede the implementation of the SC BCT. The architecture of BC-based SCM facilitates the generation of open, encrypted and shared ledgers, autonomous digital contracts (smart contracts), and trustworthy and protected networks. It also enables transactions between partners (peer-to-peer) through the location of middlemen/intermediaries on the network. In addition to the description of the BCT and its implementation in the SC, the challenges confronting BCT implementation organizations are summarized in this chapter. Many of these hurdles are focused on hypotheses and literature that found related transformative developments. These are early research that explicitly describe and classify BC blockades with unique to SC usage of technology. The BC hurdles for SC adoption have been reviewed as multi-faceted challenges influencing the relationship with SC participants and the employees of the participants and their stakeholders. Also, technological hurdles relevant to BC acceptance, some branches from BCT irresponsibility and arrangement-related BCT matters, which may restrict its adoption, require more effort in future experiments, and more focus needs to be provided to realistic technical solutions for scalability concerns. Additionally, experiential investigations are compulsory to examine multiple barriers’ implication and assess causal relationship. This analysis would pave the foundations for the effective management of the BC implementation. However, other BCT applications, specifically occupational submissions, have infrequently been explored in past learned studies. Further investigations may also be obligatory to assess the acceptance of BCT for various purposes. In order to promote a fundamental review, we have put forward a variety of available research projects that focus on the comment concerns raised by BC-enabled SCs. In addition to the potential theoretical concepts of analysis, technical and advancement research relevant to various SC themes is also needed. For example, fragmented SC collaboration [63, 64], resource and sharing of knowledge [65], virtual market [66, 67], agile SCM [68, 69] and resilience SC [particularly 69] that provides the wider usage of BCT for commercial purposes has already started. Investigations are required to study case studies and pilot projects and to have useful functional experience to facilitate the application of BC. The successful post-implementation and failure factors of this technology would also be discussed in future studies. We have measured the relative value of BCT to SC resistance. Future studies will also step in this direction where the environmental and social/human aspects of sustainability, including the sustainable development targets and ainable development goals (SDGs) of a particular nation, may be used as an analogy to explore the BC-enabled SC productivity. There are significant opportunities for a deeper understanding and application of this technology beyond traditional knowledge systems and the web-based penetration of SCs. Transdisciplinary activities would be needed to consider the full ramifications of BCT

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in the SC. Technical associations need to be active to collaborate alongside universities to establish guidelines to include realistic success metrics on BCT application. Undoubtedly, there is a significant amount of study in this field toward the potential course of trade and commerce.

References [1] [2] [3]

[4]

[5] [6]

[7]

[8] [9]

[10]

[11] [12]

[13]

[14] [15] [16]

Crosby, M., Pattanayak, P., Verma, S., Kalyanaraman, V. (2016). Blockchain technology: Beyond bitcoin. Applied Innovation, 2. 6–9. Steiner, J., Baker, J. 2015. “Blockchain: The Solution for Transparency in Product Supply Chains.” https://www.provenance.org/whitepaper. English, M., Auer, S., Domingue, J. 2016. “block chain technologies & the semantic web: A framework for symbiotic development.” Computer Science Conference for University of Bonn Students, J. Lehmann, H. Thakkar, L. Halilaj, and R. Asmat, Eds. Tian, F. 2016. “An agri-food supply chain traceability system for China based on rfid & blockchain technology.” 13th International Conference on Service Systems and Service Management (ICSSSM), 2016. Nofer, M., Gomber, P., Hinz, O., Schiereck, D. (2017). Blockchain. Business & Information Systems Engineering, 59(3), 183–187. Saberi, S., Kouhizadeh, M., Sarkis, J., Shen, L. (2019). Blockchain technology and its relationships to sustainable supply chain management, International Journal of Production Research, 57(7), 2117–2135, DOI: 10.1080/00207543.2018.1533261. Ølnes, S., Ubacht, J., Janssen, M. (2017). Blockchain in government: Benefits and implications of distributed ledger technology for information sharing. Government Information Quarterly, 34(3), 355–364. Pilkington, M. 2015. “Blockchain technology: Principles and applications.” Browser Download This Paper. Delmolino, K., Arnett, M., Kosba, A., Miller, A., Shi, E. 2016. Step by Step Towards Creating a Safe Smart Contract: Lessons and Insights from a Cryptocurrency Lab International Conference on Financial Cryptography and Data Security. Peters, G.W., Panayi, E. (2016). Understanding Modern Banking Ledgers Through Blockchain Technologies: Future of Transaction Processing and Smart Contracts on the Internet of Money. In Banking Beyond Banks and Money. 239–278, Cham: Springer. Nakamoto, S. 2008. Bitcoin: A Peer to Peer Electronic Cash System. Accessed 20 March 2018. Abeyratne, S.A., Monfared, R.P. (2016). Blockchain ready manufacturing supply chain using distributed ledger. International Journal of Research in Engineering and Technology, 5(9), 1–10. Maurer, B. (2017). Blockchains Are a Diamond’s Best Friend: Zelizer for the Bitcoin moment. In edited by Nina Bandelj, F.F.W., Zelizer, V.A., Money Talks: Explaining How Money Really Works, 215–230. Princeton: Princeton University Press. Johnson, M.E. (2006). Supply chain management: Technology, globalization, and policy at a crossroads. Interfaces, 36(3), 191–193. Lambert, D.M., Enz, M.G. (2017). Issues in supply chain management: Progress and potential. Industrial Marketing Management, 62(Supplement C), 1–16. Maina, E.M., Chouhan, V., Goswami, S. (2020). Measuring behavioral aspect of IFRS implementation in India and Kenya. International Journal of Scientific & Technology Research, 9(1), 2045–2048.

Chapter 4 Measuring barriers in adoption of blockchain

59

[17] Ivanov, D., Dolgui, A., Sokolov, B. (2018). The impact of digital technology and industry 4.0 on the ripple effect and supply chain risk analytics. International Journal of Production Research, 57(3), 1–18. [18] Sarpong, S. (2014). Traceability and supply chain complexity: Confronting the issues and concerns. European Business Review, 26(3), 271–284. [19] Ojha, A., Chouhan, V., Gupta, L., Goswami, S. (2020), A case study on project performance of railway underpass construction project in Jaipur, India, Proceedings of the 2nd International Conference on Emerging Research in Civil, Aeronautical and Mechanical Engineering (ERCAM)-2019 AIP Conf. Proc. 2204, 020005-1–020005-6. [20] Dong, F., Zhou, P., Liu, Z., Shen, D., Xu, Z., Luo, J. (2017). Towards a fast and secure design for enterprise-oriented cloud storage systems. Concurrency and Computation: Practice and Experience, 29(19), e4177. [21] Chouhan, V., Sharma, R.B., Goswami, S. (2021). Sustainable reporting practices of selected cement companies in India: A case study, Accounting, 7(1), 151–160. [22] Chouhan, V., Sharma, R.B., Goswami, S. (2020). Factor affecting audit quality: A study of the companies listed in Bombay Stock Exchange (BSE). International Journal of Management (IJM), 11(7), 989–999. [23] Chouhan, V., Chandra, B., Saraswat, P., Goswami, S. (2020). Developing sustainable accounting framework for cement industry: evidence from India, Finance India, 34(4), 1459–1474. [24] Khan, S., Chouhan, V., Chandra, B., Goswami, S. (2014). Sustainable accounting reporting practices of Indian cement industry: An exploratory study. Uncertain Supply Chain Management, 2(1), 61–72. [25] Seuring, S., Sarkis, J., Müller, M., Rao, P. (2008). Sustainability and supply chain management – An introduction to the special issue. Journal of Cleaner Production, 16(15), 1545–1551. [26] Grimm, J.H., Hofstetter, J.S., Sarkis, J. (2016). Exploring sub-suppliers’ compliance with corporate sustainability standards. Journal of Cleaner Production, 112. 1971–1984. [27] Swan, M. 2015. “Blockchain: Blueprint for a new economy.” O’Reilly Media, Inc. [28] Groenfeldt, T. 2017. IBM and Maersk Apply Blockchain to Container Shipping. [29] Lemieux, V.L., Lemieux, V.L. (2016). Trusting records: Is blockchain technology the answer? Records Management Journal, 26(2), 110–139. [30] Yli-Huumo, J., Ko, D., Choi, S., Park, S., Smolander, K. (2016). Where is current research on blockchain technology? A systematic review. Plos One, 11(10), e0163477. [31] Tian, F. 2017. “A supply chain traceability system for food safety based on HACCP, Blockchain & Internet of Things.” 2017 International Conference on Service Systems and Service Management (ICSSSM). [32] Pazaitis, A., De Filippi, P., Kostakis, V. (2017). Blockchain and value systems in the sharing economy: The illustrative case of backfeed. Technological Forecasting and Social Change, 125. 105–115. [33] Hofmann, E., Strewe, U.M., Bosia, N. (2018). Discussion – How Does the Full Potential of Blockchain Technology in Supply Chain Finance Look Like? In Supply Chain Finance and Blockchain Technology. 77–87, Cham: Springer. [34] Tapscott, D., Tapscott, A. (2017). How blockchain will change organizations. MIT Sloan Management Review, 58(2), 10. [35] Popa, V. (2013). The financial supply chain management: A new solution for supply chain resilience. Amfiteatru Economic Journal, 15(33), 140–153. [36] Seifert, R.W., Seifert, D. (2011). Financing the chain. International Commerce Review, 10(1), 32–44.

60

Vineet Chouhan et al.

[37] Fanning, K., Centers, D.P. (2016). Blockchain and its coming impact on financial services. Journal of Corporate Accounting & Finance, 27(5), 53–57. [38] Hofmann, E., Strewe, U.M., Bosia, N. (2017). Supply Chain Finance and Blockchain Technology: The Case of Reverse Securitisation, Cham: Springer. [39] Eyal, I. (2017). Blockchain technology: Transforming libertarian cryptocurrency dreams to finance and banking realities. Computer, 50(9), 38–49. [40] Zhu, Q., Sarkis, J., Lai, K.-H. (2018). Regulatory policy awareness and environmental supply chain cooperation in China: A regulatory-exchange-theoretic perspective. IEEE Transactions on Engineering Management, 65(1), 46–58. [41] Govindan, K., Hasanagic, M. (2018). A systematic review on drivers, barriers, and practices towards circular economy: A supply chain perspective. International Journal of Production Research, 56(1–2), 278–311. [42] Fawcett, S.E., Ogden, J.A., Magnan, G.M., Bixby Cooper, M. (2006). Organisational commitment and governance for supply chain success. International Journal of Physical Distribution & Logistics Management, 36(1), 22–35. [43] Mougayar, W. (2016). The Business Blockchain: Promise, Practice, and Application of the Next Internet Technology, Hoboken: JohnWiley & Sons. [44] Mendling, J., Weber, I., Van Der Aalst, W., Brocke, J.V., Cabanillas, C., Daniel, F., Dustdar, S. (2017). Blockchains for business process management-challenges and opportunities. ACM Transactions on Management Information Systems (TMIS), 9(1), 1–16. arXiv Preprint ArXiv:1704.03610. [45] Gorane, S., Kant, R. (2015). Modelling the SCM implementation barriers. Journal of Modelling in Management, 10(2), 158–178. [46] Jharkharia, S., Shankar, R. (2005). IT-enablement of supply chains: Understanding the barriers. Journal of Enterprise Information Management, 18(1), 11–27. [47] Venkatesh, V., Morris, M.G., Davis, G.B., Davis, F.D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. [48] Wallace, L.G., Sheetz, S.D. (2014). The adoption of software measures: A technology acceptance model (TAM) perspective. Information & Management, 51(2), 249–259. [49] Mathiyazhagan, K., Govindan, K., NoorulHaq, A., Geng, Y. (2013). An ISM approach for the barrier analysis in implementing green supply chain management. Journal of Cleaner Production, 47. 283–297. [50] Tseng, M., Lim, M., Wong, W.P. (2015). Sustainable supply chain management. Industrial Management & Data Systems, 115(3), 436–461. [51] Mangla, S.K., Govindan, K., Luthra, S. (2017). Prioritising the barriers to achieve sustainable consumption and production trends in supply chains using fuzzy analytical hierarchy process. Journal of Cleaner Production, 151. 509–525. [52] Sajjad, A., Eweje, G., Tappin, D. (2015). Sustainable supply chain management: Motivators and barriers. Business Strategy and the Environment, 24(7), 643–655. [53] Chkanikova, O., Mont, O. (2015). Corporate supply chain responsibility: Drivers and barriers for sustainable food retailing. Corporate Social Responsibility and Environmental Management, 22(2), 65–82. [54] Sarkis, J., Zhu, Q. (2018). Environmental sustainability and production: Taking the road less travelled. International Journal of Production Research, 56(1–2), 743–759. [55] Sayogo, D.S., Zhang, J., Luna-Reyes, L., Jarman, H., Tayi, G., Andersen, D.L., Andersen, D.F. (2015). Challenges and requirements for developing data architecture supporting integration of sustainable supply chains. Information Technology and Management, 16(1), 5–18. [56] Oliveira, M.P.V.D., Handfield, R. (2018). Analytical foundations for development of real-time supply chain capabilities. International Journal of Production Research, 57(5), 1571–1589.

Chapter 4 Measuring barriers in adoption of blockchain

61

[57] Kaur, J., Sidhu, R., Awasthi, A., Chauhan, S., Goyal, S. (2018). A DEMATEL based approach for investigating barriers in green supply chain management in Canadian manufacturing firms. International Journal of Production Research, 56(1–2), 312–332. [58] Fawcett, S.E., Wallin, C., Allred, C., Magnan, G. (2009). Supply chain information-sharing: Benchmarking a proven path. Benchmarking: An International Journal, 16(2), 222–246. [59] Mishra, B.K., Raghunathan, S., Yue, X. (2007). Information sharing in supply chains: Incentives for information distortion. IIE Transactions, 39(9), 863–877. [60] Lim, I.-K., Kim, Y.-H., Lee, J.-G., Lee, J.-P., Nam-Gung, H., Lee, J.-K. 2014. “The analysis and countermeasures on security breach of bitcoin.” International Conference on Computational Science and Its Applications. [61] Palombini, M. 2017. The Other Side of Blockchain: We Choose What We Want to See Blockchain, General News, Tech Ethics. [62] Mangla, S.K., Luthra, S., Mishra, N., Singh, A., Rana, N.P., Dora, M., Dwivedi, Y. (2018). Barriers to effective circular supply chain management in a developing country context. Production Planning & Control, 29(6), 551–569. [63] Chan, H.K., Chan, F.T. (2010). A review of coordination studies in the context of supply chain dynamics. International Journal of Production Research, 48(10), 2793–2819. [64] Ivanov, D., Dolgui, A., Sokolov, B., Werner, F., Ivanova, M. (2016). A dynamic model and an algorithm for short-term supply chain scheduling in the smart factory industry 4.0. International Journal of Production Research, 54(2), 386–402. [65] Ivanov, D., Sokolov, B., Raguinia, E.A.D. (2014). Integrated dynamic scheduling of material flows and distributed information services in collaborative cyber-physical supply networks. International Journal of Systems Science: Operations & Logistics, 1(1), 18–26. [66] Crispim, J.A., De Sousa, J.P. (2010). Partner Selection in virtual enterprises. International Journal of Production Research, 48(3), 683–707. [67] Sarkis, J., Talluri, S., Gunasekaran, A. (2007). A strategic model for agile virtual enterprise partner selection. International Journal of Operations & Production Management, 27(11), 1213–1234. [68] Cabral, I., Grilo, A., Cruz-Machado, V. (2012). A decision-making model for lean, agile, resilient and green supply chain management. International Journal of Production Research, 50(17), 4830–4845. [69] Sarkis, J., Talluri, S. (2001). Agile Supply Chain Management. In edited by Gunasekaran, A., Agile Manufacturing: The twenty-first Century Competitive Strategy, 359–376. Oxford: Elsevier Science Ltd.

Vineet Chouhan, Shubham Goswami, Manish Dadhich, Pranav Saraswat, Pushpkant Shakdwipee

Chapter 5 Emerging opportunities for the application of blockchain for energy efficiency Abstract: Energy sectors all over the world have begun to discover the possibility of the use of blockchain (BC) or distributed ledgers (DL) as an emerging technology. It is used in various systems like energy-to-peer exchange, project finance, supply chain monitoring and inventory management processes in large scale. This study focuses BC energy market strategies and advises development by a comprehensive analysis of the evidence and current manufacturing cases. This study provides the academic, peer-reviewed work to provide a systematic BC activity-based solution and initiatives in the highly potential growth seeker energy sector. In today’s world, blockchain technology (BCT) is used to develop several applications, including electric charging and sharing of cars and green cryptocurrencies, including automatic bill payments. It is the infrastructure that allows customers, homes to become manufacturers and sellers of energy with a high degree of control as a smart company stand at a structural stage. Conveniences and grid builders are well coordinated because they can already manage supply and demand in real time, by active participation of these prosumers. It encourages the incorporation of green energies. An approximate of €231 billion in energy efficiency projects is invested per year, but for having its full benefits it requires huge investment (world energy outlook, 2019). Although this finance difference is shrinking down as global energy intensity is adopted as a method of nation economy’s energy production, measured by unit energy of GDP, in 2015 it was 1.8%, three times that of the average of 2003 to 2013, but falls short of the critical 2.6% in order to prevent a 2-degree rise of global temperatures or a required 3% improvement of our energy performance. This chapter examines in detail the application case analysis of BCT, main advantages and consequences for the risks of using BC in the energy production industry by posing and discussing two case studies as practicable.

Vineet Chouhan, School of Management, Sir Padampat Singhania University, Udaipur, Rajasthan, India, e-mail: [email protected] Shubham Goswami, School of Management, Sir Padampat Singhania University, Udaipur, Rajasthan, India, e-mail: [email protected] Manish Dadhich, School of Management, Sir Padampat Singhania University, Udaipur, Rajasthan, India, e-mail: [email protected] Pranav Saraswat, Nirma University, Ahmedabad, Gujarat, India, e-mail: drpranavsaraswat@ gmail.com, [email protected] Pushpkant Shakdwipee, Pacific Institute of Management, Pacific University, Udaipur, Rajasthan, India, e-mail: [email protected] https://doi.org/10.1515/9783110702507-005

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Keywords: BC technology, energy sector, renewable energy, power generation, transmission and distribution, energy stakeholders, consumers

5.1 Introduction Energy grids experience rapid improvements to handle growing amounts of embedded renewable production, such as wind and solar photovoltaics. Renewables (RES) have experienced tremendous development in recent years, allowing privatization and disassociating the energy market and improving financial benefits and programs in terms of energy policy. RES accounted for 44.9% and 12.5% of the RES capacity [1], which accounts for 24.6% of Gross Production (GRP) in 2016. This is mostly the product of onshore and offshore wind turbines and solar photovoltaic plants [2]. RES is dynamic and hard to foresee and can present new challenges in the management and maintenance of energy systems based on environmental conditions, so it will take more flexibility to maintain safe operation and stability [3]. Flexibility initiatives include rapid intervention, response to demand and energy storage [2]. Aside from the transformation caused by electricity delivery and green energy sources, energy grids are about to enter the modern era, as seen by the rapid smart meter deployment in a few states [4]. In the United Kingdom, 53 million smart meters, one for every house and every little company, will be installed by 2020 [5]. In order to reach ambitious carbon reduction goals, electricity infrastructure needs considerable investment. The transition to a more sustainable and reliable energy system is expected to produce, network and improve energy efficiency (EE) by €200 billion a year [6]. Improved power networks will take $2 trillion by 2030 [7]. Tasks that are progressively daunting as energy markets evolve to become more active, autonomous, complex and “multiagent” with a growing array of players and potential acts need to be implemented to moderate needed expenditure. Advanced connectivity and data sharing between various areas of the power network is constantly needed, rendering central management and activity increasingly difficult. Local allocated self-control and administration strategies are needed for meeting developments in decentralization and digitalization [8]. Blockchain technology (BCT) recently developed as a crucial knowledge in the energy sector’s digital transition, and many foreign specialists [1–3] described that BC’s promise for improvement as a crucial technology facilitating energy sector decentralization, digitalization and democratization, and will offer energy users tremendous power to understand, generate, track and regulate their energy needs. It would also promote electricity users’ ability to monetize their surplus resources from any production or electricity reserves. We discuss the use of BCT to address existing problems of the energy conservation industry and suggest a framework of energy saving and exchanging on a safe distributed exchange network without any third party requiring.

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Figure 5.1: Basic concept of blockchain.

Blockchain (BC) or distributed ledger technologies (DLTs) is mainly developed to enable distributed transactions by replacing central management. As a consequence, BC may support to solve the problems that dispersed power networks face. BC are decentralized and scattered storage systems or ledgers which, without using a central source of control, will safely store digital transactions. More specifically, BC enables the automated implementation of intelligent contracts in peer-to-peer (P2P) networks [9]. Alternatively, it may be the database that enables several operators to adjust concurrently in the record that can ensue in several iterations of the chain. Instead of handling the ledger from a centralized trustworthy hub, each participant of the person network keeps a copy of the chain of records and achieves a mutual settlement on the valid state of the ledger. A current field of study is the precise process of how agreement is achieved which may change to accommodate a broad variety of fields. Latest operations are bound through cryptography to prior contracts that allows BC systems to be robust with safety. If transfers are legitimate, each network user may verify for themselves, which ensures clarity and faithfulness, safe from manipulation in documents. BCT is mostly recognized by BC implementations that have recently undergone an unparalleled growth in market capitalization, reaching $335 billion [10] at the time of publishing. Although views may be split on the long-term prospects of cryptocurrencies, various outlets have established many main applications. The UK government’s report [11] notes that BC might be able to “reform our capital systems, supply chains, customer and business-to-business networks, and publicly owned registers.” Probable implementations varied from hard asset possession transfers to stable imperceptible asset registry. These properties are envisaged by Swan [9] as any kind of content or credibility method. Investigation in finance area addresses BC implementations in banks and highlighted that BC-empowered systems will allow economic dealings among various economic organizations and render transfers quicker by accelerating authorization periods [12]. Its use may boost clearness in EE with the produced power [13]. In

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reality, diverse use of BC suggested by Tapscott and Tapscott [14] that DLTs will clarify decentralized confidence and abolish intermediaries creating a modern governance model that could theoretically challenge conventional models of governance [15]. The disruptive essence resides in the ability to substitute top-down power with consensus, as well as in the fundamental ideology of shared openness [11]. In addition to usage circumstances in diverse industries, the promise of BC in the energy business has only begun to be understood, and evidenced with the growing start-ups, pilots, trials and test ventures [16, 17]. The study of electricity decision-makers by the German Electricity Agency [18] reveals that almost 20% agree that BCT is a game changer for energy supplies. This study has focused opinions of 70 executives of electricity sector, with power providers, energy producers, networking partners, distributors and aggregates [19]. In addition, further research by Deloitte [20] and PWC [21] revealed that BCs have the ability to dramatically disrupt energy-related goods and merchandises as they develop distributed properties that may be traded interoperable. Early projects and start-ups suggested that BCT may theoretically offer alternatives to some of the problems faced in this sector. Necessities for potential energy markets may be summed with moving toward engaging customers, a foundation for policy in both EU [6] and UK [22]. Nevertheless, the existing configuration of the energy and power marketplaces is insufficient toward the involvement of new players that are essentially eliminated and rewards for successful customer’s adequate involvement [23, 24]. As per PWC, oil producers are steadily posting to improve energy prices and reducing profit [25, 26]. The latest report covers BC research ventures and programs conducted by businesses and research organizations [27, 28]. Current study in this sector is recorded in a variety of latest manufacturing studies [29]. In particular, a detailed 90 companies group exploring its use in the energy field has been released by Solar Plaza [30]. Over 10 BC pilot initiatives, introduced in partnership with a range of local authorities, were addressed in the Energy Cities report [31]. Some notable examples of usage are often addressed in new consultative reports [20, 21]. The current work varies significantly as of such references, by expanding the study to significant expansion in case studies. Further, we officially identify projects in particular area of operation and technological features. Our work presents first, scholarly reviews to include a comprehensive analysis of BC operations for energy systems. Finally, we address the results of our analysis and possible technical advances. We often address the mechanism for technological acceptance, drawbacks, obstacles to the market and the potential for broader consequences that could occur from the widespread usage of BC. This chapter addresses briefly present energy sector and possible views where BC can prove advantageous. This chapter further addresses a comprehensive study of the industrial and analysis operations of BC. We formally define usage cases, pilot programs, experiments and start-ups depending on their area of operation, BC platform, and presents drawbacks, obstacles to the competition and potential trends, and Section 6 ends this job.

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5.2 BC technology conceptual background BC is a shared data system, a hierarchical and distributed directory consisting of an ever-changing transaction log and its sequential sequence. The data layout is otherwise a digital transfer database, including data records and executables. Transactions are clustered into wider classes or blocks and are stamped temporarily and cryptographically associated to previous blocks for the creation of an occurrence series or the BC record chain. In literary terminology, the mechanisms, algorithms or technical contexts of digital consensus are described, apart from the definition of the data structure itself [19]. BC is operating virtual networks. Data replication in these networks is similar to the copying of data in a certain location, for example, in the Bitcoin domain, and is analogous to the electronic wallet copying of digital coins. Having the computer just invest coins once and no double costs is the greatest challenge. The traditional approach is to make a trustworthy interlocutor for negotiation partners who are liable for maintaining banking identity safe to prevent the current documents from being used by the central control body, such as the central bank. The Central Bank is the central management authority. Where many parties must at the same time join the headline, the central entity shall also carry out competition tests and consolidate headline changes. In a vast number of situations, central control cannot be simple or appropriate because indirect costs are involved, and network customers have confidence in the management of the networks by an external party [19]. Central mechanisms also have significant disadvantages, which imply that they are not able to improve the vulnerability of any device glitches or destructive threats [32]. The key goal of BCTs is to eliminate and substitute the needs of those intermediaries with the global digital consumer network that cooperates to verify transactions and maintain the integrity of the registry. Each BC network segment retains or can link an open cloud copy in relation to the central networks (see also Figure 5.1). Thus, anyone inside the network is linked and tracked through the old transaction records of devices that guarantee a high standard of accountability. When central administration is eliminated, the task is to organize and synchronize different copies of the directory. The precise method for checking and unifying the ledger differs in several respects in BC, but overall, the participants of the network evaluate their reproductions in a fashion that is intuitively close to the distributed vote [16] where an agreement has been established on the rightful status of the chief. These validation processes are known as distributed consensus algorithms. Distributed nodes interact and function fairly on game-theoretical advantages or advantages [33]. In reality, without a large part of the network operation, BC may be very challenging to monitor. The effect is a safe and tamper-resistant BC network. Hash functions and public key cryptography are additional components that preserve enhanced security. Crypto-hash functions are math or one-way functions that input and convert them into a particular longitudinal output, such as the 256-bit sequence known as hash output. Their operation is based on the premise that original input data from the hash output alone (collision resistance) are extremely difficult to

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reproduce. In addition, BC uses the asymmetric encryption protocol, the public key cryptography [34]. The consumer has a private, secret key and a public key composed of numeric or alphanumeric characters that can be exchanged with all network consumers. Keys are mathematically intertwined in such a manner where only one aspect of their counterpart’s consciousness can be decrypted. The usage of public–private key cryptography guarantees authentication, which implies that the source appears to be a transaction, and the authorization, which suggests that consumers are empowered to execute the operation. For instance, the network can validate the sender’s identity, since only the public sender’s key (encoded and digitally signed private sender key) can decode the original document. A message processed using a public key can only be decrypted by the intended recipient of a private secret key. The usage of P2P messaging and sophisticated cryptographic technologies in BC networks has carried out these and other normal facets of collaboration, such as data validity and confidentiality. According to the UK Government Science Office [11], the actual possibilities of BCTs will only be completely understood in conjunction with smart contracts, that is, userdefined applications that establish guidelines for writing in the ledger. Smart contracts are implementable structures that make automatic adjustments to ledger if the requirements are met, including the arrangement of the parties to the agreement [9]. Smart contracts may be applied. The terms and conditions of the contract shall be documented in a computer language encoding legal restrictions and contractual terms. Smart contracts are autonomous and deceptive and have major advantages, such as avoiding intermediaries [20] and reducing processing costs, contracting, operating costs and regulatory costs (see also Figure 5.2) [11]. Another advantage is that low-value transactions can be cost-effective, whereas BC can guarantee cross-transactional interoperability [12]. In order to improve the understanding of the working of the BC network, Bitcoin, the first application documented by BC, and Ethereum, a BC framework focused on complex contracts, are implemented in the next segment of the BC network.

Figure 5.2: BC-based key energy applications.

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5.3 BC scope and important usage cases in energy applications Chiefs in the energy sector [18] and administration companies [18] have demonstrated that BC could hypothetically give answers to difficulties in the energy area. The German Energy Agency [18] claims that BC innovations can possibly improve the productivity of current energy tasks and cycles, to encourage the improvement of IoT organizations and computerized applications, and to make propels in P2P energy sharing and decentralized age. What is more, they report that BC advancements can significantly upgrade existing exercises of power utilities and force organizations by improving interior techniques, purchaser offices and costs [18]. Energy networks are confronting a groundbreaking change as an outcome of the development of disseminated energy frameworks and data and availability innovations (ICTs). One of the key issues is the rising decentralization and digitization of the energy framework, requiring consideration, revelation and execution of current standards and dispersed advances. As indicated by its natural plan, BC could offer a likely methodology for observing and keeping up logically decentralized complex energy frameworks and microgrids [15, 35, 36]. The sending of little scope environmentally friendly power, circulated age, versatile foundation and shopper support in the power market is a requesting challenge. Some authors [35] guarantee that BC may have innovative exchanging stages where prosumers and clients can trade their energy surpluses or adaptable interest on a P2P premise on a compatible premise. Dynamic purchaser cooperation can be made sure about and recorded in permanent, straightforward and carefully designed brilliant agreements. Empowering such electronic exchanging frameworks might be a compelling method to convey them. Value signs a data on energy rates to consumers [36], while giving motivating forces to the reaction shrewd guideline of their power needs. BC would permit nearby assets and buyer situated business sectors or microgrids to assist neighborhood with driving creation and consumption [29]. One of the key points of interest of this procedure is to limit spread deferrals and delay costly organization upgrades. On the opposite side, energy is frequently communicated through the genuine framework, request and flexibly should be appropriately controlled and administered so as to confront the genuine specialized requirements and proficiency of the force framework. As per an as of late distributed report by Eurelectric [37], the genuine transmission of power has so far hampered the more extensive reception of BC in the energy business, instead of the selection of BC in the money field. BC ought to securely enlist the proprietorship and wellsprings of the energy utilized or provided. Thus, BC gadgets could be utilized for brilliant charging and force sharing, for example, common stockpiling or microgrids, yet additionally for keen network information stockpiling and digital protection applications [38, 39]. Keeping up assurance of flexibly and improving organization dependability is a fundamental test as RES levels keep on climbing. By supporting

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and speeding IoT appropriation and empowering more open business sectors for flexibility, BC could improve network dependability and gracefully protection [35]. The investigation by the Research Institute of the Finnish Economy [16] contends that BC will guarantee interoperability of brilliant lattice and IoT applications by offering free and straightforward arrangements. As indicated by Deloitte [20], energy market tasks will turn out to be more straightforward and proficient. Therefore, it would improve contention and energize the flexibility of purchasers and the exchanging of energy supplies. Whenever cost-productivity openings are reached, computerization might be used to improve fuel destitution and issues with energy moderateness. Based on the points of interest given, BC might give procedures around the energy trilemma: they could limit costs by advancing energy measures, increment energy wellbeing as far as digital protection, yet additionally go about as a help innovation that could expand security of flexibly and, in the long run, empower manageability by supporting green age and low-carbon systems. In the accompanying areas, we manage the huge use cases proposed in the writing where BC can have significant advantages.

5.3.1 BC potential impact on energy company operations BC innovation could be used in a scope of ventures applicable to the exercises and business cycles of energy firms. Current writing directs future usage and features of market models that could be affected, as sketched out beneath: – Billing: BC, shrewd agreements and keen metering will convey programmed charging for clients and dispersed generators [40]. Service organizations can benefit from the potential for energy micropayments, pay more for high cost arrangements or instalment frameworks for paid ahead of time meters [41]. – Sales and advertising: Sales exercises can contrast dependent on the energy profile of clients, client tastes and ecological concerns [18]. BC, related to manmade brainpower (AI) methods, for example, machine learning, can perceive market energy propensities and consequently permit the arrangement of customized and worth included energy products. – Exchange and markets: BC-empowered appropriated exchanging frameworks may compromise business activities, for example, discount market management [18, 20, 40], item trading [41] and hazard the executives. BC networks are presently being set up for the trading of green certificates [41]. – Automation: BC could help the administration of decentralized energy frameworks and microgrids [18]. The presentation of nearby energy markets permitted by confined P2P energy exchanging or dispersed organizations will drastically build energy self-creation and self-utilization, regularly known as meter activities [40], which could hypothetically affect incomes and taxes.

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– Smart lattice usage and information move: BC can hypothetically be utilized for brilliant framework network, information conveyance or storage [18]. Keen items in the savvy framework incorporate brilliant meters, refined controls, network the executive’s instruments, control energy and the board innovations, yet in addition savvy home energy controllers and building reconnaissance frameworks. Notwithstanding offering safe information conveyance, savvy framework frameworks will likewise profit by the information normalization gave by BC innovation. – Grid control: BC may aid network the board of independent organizations, adaptable utilities or resource the executives. BC may offer interconnected adaptability exchanging networks with insightful organization refreshes. Therefore, BC may likewise affect incomes and taxes for network use [40]. – Security and character the executives: The assurance of exchanges and security can exploit cryptographic methods. BC could make sure about secrecy, security of information [18] and personality the board [41]. – Resource sharing: BC may give charging answers for sharing assets between different members, for example, sharing EV charging framework [41], information or normal concentrated gathering stockpiling. – Competition: Smart agreements could hypothetically improve and accelerate the switchover of energy providers [18, 42]. Upgraded market versatility could improve intensity and inevitably decline energy taxes. – Transparency: Unchangeable records and straightforward cycles can altogether improve reviewing and buyer security consistence [41]. BC can permit and conceivably upset existing plans of action and conventional functions of energy service organizations, as talked about in past [18, 37, 40, 41]. The ensuing subsections expand on the critical utilization of cases introduced in the writing.

5.3.2 Wholesale energy trading and supply a future use includes the usage of wholesale Autonomous processes of distributed leader technologies. In wholesale energy markets, the processes expected by third parties, including dealers, dealers, trade, pricing reporters, storage suppliers, banking agencies and regulators, are complicated. Wholesale energy markets image. Four outlines main financial trading institutions and operations between two businesses. Current processes require post-processing manuals and enhanced correspondence to integrate different details retained from each component of the transaction. The new processes thus require a longer period to check and reconcile transactions many times from the start-up to the final settlement [43]. Low transaction speeds and exchange costs are unfair in terms of friction costs, which are excluded from the market, for small and distributed generators. DLT and intelligent contracts could enable an energy device, through independent trading agents, to directly trade with a customer or a power retail supplier [20].

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The agent is searching for the best price on the market that meets the need for a predicted customer for a certain amount of time. At the specified time of delivery, the agreement is safely documented in the BC and automated. At the point of distribution, payments would take effect immediately as stipulated in the negotiated contract. For all parties and the system operator, transaction data would be made available via the distributed ledger [20] via a single access point. Related cases of usage will entail significant legislative reforms, possibly impacting the positions of mediators as traders, markets and trading companies. There have already been many outlets which have illustrated the potential of BC in wholesale energy trading and some consultant reports [21] argue that they are capable of changing the global energy business system (see also Figure 5.3). But to accomplish this vision in motion, a range of key obstacles and technological problems would have to be addressed. The amount of transactions which can be cleared using BC is always fewer than what work algorithms can achieve agreement. CURRENT MARKET STRUCTURE Large Generators

BLOCKCHAIN MARKET STRUCTURE

Large Generators

Network Operator

Trades

Energy Retailer

BANK

Network Operator

RES

Blockchain

TRADING PLATFORM

Residential Consumer

Meter Operator

Industrial Operator

Residential Consumer

Storage

Industrial Consumer

Electricity Payments DATA

Storage

RES

Figure 5.3: Change of market with BC as indicated by PWC [21].

For example, in order to clear up to 10s of operations every second, an energy network should clear up, more than thousand transactions every second, like banking’s electronical paying systems clarify per day. PoS and Byzantine tolerance schemes for defects

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like Ethereum or Tendermint which provide a feasible remedy, but the deployment of these solutions may be important overall. Second, we agree that reforming current business systems of energy dramatically in a limited amount of time would be a task. This is why many emerging BC ventures that actually operate concentrate just on one aspect of the entire energy sector, which is the most readily applied, such as settling imbalances.

5.3.3 Imbalance settlement The resolution of imbalances in the power markets is the use of BC that has gained substantial interest. Unbalanced situations could take from a few months to 28 months to finalize [44], said Elexon, a British wholesaler on the electricity sector. Long reconciliation procedures, volume updates and validation are key explanations for delays [20]. By minimizing back office operations, BC may minimize costs and delays. In accessible and clear ledgers, electricity produced and consumed can be monitored and registered, which will speed up payment of services rendered. DLT implementations include incorporating BC metering devices, which may be expensive. According to Grewal-Carr and Marshall [20], loan uncertainties and collateral conditions may be reduced by stakeholders. Moreover, with confirmations of near real time, the business process itself will be more straightforward and effective. The BC-enabled framework will aid exchange among various parties, enhance auditing and procedure honesty, the risk reduction for of fraudulent activity (through protected storage of data) and promote interoperability through the standardization formats between different organizations [20]. In addition, usage of BC-enabled agreements, in theory, can permit precise monitoring which generator and user have produced a discrepancy, enabling real-time accounting in the light of the discrepancy settlement. However, although many businesses and utilities have started to investigate the usage of BC for imbalance resolution, the problems of latency and poor performance are still obstacles to be confronted. Another problem involves the assumption that ex-post balance transfers function mostly as an already produced or consumed electricity accounting mechanism, and do not promote real-time performance adjustments.

5.3.4 IoT platforms with digitalization BC will theoretically allow machine-to-machine contact and data transfers between smart devices. This facilitates digital P2P transactions. By 2020, more than 20.8 billion intelligent devices will link to the Internet [18]. In the energy room, intelligent meters and ICT appliances in electricity networks are progressively being used [45]. In a major utilities company [46] the amount of smart meter readings alone could upsurge from 24 million a year to per day 220 million [36]. In combination with automation capacity and big data analytics, this trend shall possibly turn the energy sector’s value chain.

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Useful data knowledge can increase the reliability of the control systems and diagnostics of assets which can minimize costs. Digitalization provides an incentive for electrical utilities to increase network reliability, billing, supply chain and pursue different avenues of competition and new market models [18]. The usage of data could result in customized services for aggregating demand, encouraging the use of virtual power plants (VPPs), with potential for active involvement by customers and the introduction of renewable energy [46]. Major integrations of software, sensor, hardwares, databases, with cloud connectivity can result in reduced digitalization management costs for RES generators in smaller scales [19]. Smart appliances, automatic heater, ventilating and air conditioning (HVAC) systems, the integration of electrical transmission and the development of self-produced prosumers are part of the “smart-grid vision” [23, 24]. The intelligent grid vision says that connected intelligent devices will communicate and respond by changing their energy usage accordingly. When high volumes of high frequency data is generated, scaled to a large number of devices which historically centralized approaches become inefficient. The requirement for computing capital to run potential power systems optimally can be reduced by local decision sharing and distributed management. BC software can promote IoT networks and BC open source, public and distributed networks can ensure IoT interoperability Requests [16]. Mattila et al. [19], who are visualizing a home society’s decentralized local marketplace with rooftop PV, smart and adaptable appliances, EV, battery-powered systems and smart meters capable of monitoring bi-directional energy flows (see Figure 5.4), demonstrate the illustration of a BC-enabled IoT network. BC may differentiate between different devices the electricity created by any computer which makes the trade in electricity. Used expectations and ability to pay are the foundation for the option of optimum bidding strategies for the commercial energy across the network by autonomous trading firms that are an integral part of all intelligent devices. They can be designed to work such that optimal targets such as greater electricity autonomy or decreased electricity purchasing from the main grid can be accomplished. Offers from any system are registered in secure ledgers which are tamperproof. The authors claim that private BC limiting the access of housing society tenants will be better fit for this use. For example, by its position rates, the key grid may even compete in the sector. Intelligent systems must integrate dispersed market data with exchanged energy flows. While this is an exciting field for BC implementation, there are a range of significant obstacles to tackle. Second, this vision calls for the creation of BC-enabled power electronics capable of calculating the demands of each unit (cooler, laundry machine, EV, etc.). If this can be established (and indeed many projects have precisely this goal), substantial customer resistance may be achieved, particularly due to concerns about privacy. In terms of the likely money savings, it is unknown whether the user wishes to publicly report their use in a public directory from, for example, electric tub, automatic washer or EV. The documented data in the heading may thus prove to be one of the main issues for BC deployment of IoT systems in order to secure the confidentiality.

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5.3.5 P2P exchanging and decentralized energy BC could include responses to demand response, synchronization of VPPs, grid and system organization, and regulation of power storing system operation, decentralized energy system regulation, collective power initiatives and RES allocation synchronization centered on the views of energy system stakeholders [18]. Trading among peers may be perceived as an energy sector fully decentralized. This compares with the applications that already follow essentially the current power market systems, such as the disparity settlement. This is an implementation area where BC-enabled technologies will work more naturally, allowing a direct energy exchange mechanism to take care of their generation and demand between consumers of energy (energy producers/prosumers and end users). While in small populations and microgrids, this may typically be done, the main concern being if this is consistent with the current delivery system control and service. In brief, the grid supply is managed and power availability is guaranteed by the device provider firms. So, even in a genuinely decentralized energy industry, BC can theoretically boost other things such as they can play a key role as operations of device.

5.3.5.1 Energy storage systems and consumer-centric economies Neighborhood and shared framework projects and microgrids are extended to have a very critical impact in energy frameworks. As per Berka and Creamer [47], neighborhood energy adventures have an extraordinary capacity to bring financial and ecological advantages to the networks concerned. In microgrids, dispersed turbines, stockpiling frameworks, wild and controllable burdens structure an incorporated structure that may work in a joint effort with the primary network or in full independence while running in island mode [48]. From a control perspective, microgrids work as a solitary structure with particular electrical fringes in contrast with the principle lattice [49]. Notwithstanding the conventional portrayal, virtual microgrids may likewise be known to have total guideline of flexibility and request past electrical and physical cutoff points. Microgrids encourage decentralized energy yield and use, which may add to significant decreases in conveyance and transmission misfortunes [50]. Microgrids, joined with inexhaustible capital, will upgrade more fuses of RES [51]. Neighborhood microgrids may help network dependability, offer subordinate assets, for example, recurrence and voltage help, to maturing power networks with the capacity to postpone exorbitant organization improvement ventures. Moreover, they will offer power supplies to clients in case of network possibilities. Productive microgrid movement at an innovative stage, for example, ideal control systems and gadget models, has been broadly examined [44, 52–54]. Exchange microgrid biological systems at nearby level have likewise been recommended by an assortment of specialists using self-sufficient operators, for example, in an agent-based market [55] where an adaptable market for the coordinated effort of self-intrigued

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people is proposed. Energy buyers, producers and suppliers are seen in a savvy network framework. Security of flexibility issues and deficient organization assets are considered in multi-agent markets [54].

Figure 5.4: Electricity trading platform of a house showing PV panels, smart appliances, EVs and local energy storage devices trade on a P2P fashion [19]. Source: M. Andoni et al. Renewable and Sustainable Energy Reviews 53 (2019) 143–174.

This was the plan of action for new companies including Power Ledger and LO3 Electricity. In the following part, the Brooklyn microgrid contextual investigation worked by LO3 Energy is investigated in more profundity. The situation of transmission and dispersion framework administrators (TSOs/DSOs) and independent system operators is a significant subject in this specific circumstance. These players own the genuine force matrix organizations and are answerable for the dependability of the activity. Network administrators recoup their costs by framework working instalments yet are as yet at risk for guaranteeing that the decentralized energy trades concurred between the gatherings would in the end happen, given the imperatives of the physical structure. As an outcome, TSOs/DSOs would have a focal task to carry out in each BC execution. We consider them to be of BC as twofold: first, they may utilize BC to record more viable utilization of their organization, in this way reassuring the viable collection of framework charges alluding to every energy move. On account of civil power frameworks, the duties or rates spread out in P2P contracts must be thought about for framework costs where the power is conveyed by means of the public lattice. Second, they will utilize subtleties on P2P exchanges archived on BC to help control the limit and force streams on their organization. This, obviously, will involve present day systems for taking care of the structure that can utilize this information put away on the BC in close constant, a troublesome field requiring more examination. In fact, when connected to the primary lattice, all framework shoppers require to organize with framework chiefs and have forecasts of power interest and accessibility.

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5.4 BC in the energy industry: a systematic study As per the objectives of the research, the emerging opportunity offered by the BCT for the EE is measured in five categories, that is, improvement on wholesale energy trading and supply, settlement of imbalance, IoT platforms with digitalization, P2P exchanging and decentralized energy and energy storage systems and consumercentric economies and for which the following hypotheses are being made: H1= Attributes wholesale energy trading and supply significantly influence the improvement with the adoption of BCT. H1= Attributes settlement of imbalance significantly influence the improvement with the adoption of BCT. H1= Attributes IoT platforms with digitalization significantly influence the improvement with the adoption of BCT. H1= Attributes P2P exchanging and decentralized energy significantly influence the improvement with the adoption of BCT. H1= Attributes energy storage systems and consumer-centric economies significantly influence the improvement with the adoption of BCT. To measure the above hypotheses and identifying the variables, the multiple regression analysis is used with SPSS software and the results are shown in Table 5.1. Table 5.1: Regression analysis. Variables

SPSS code

Mean

Std. N deviation

Wholesale energy trading and supply

T_S

.

.



Billing

T_S_

.

.



Sales and advertising

T_S_

.

.



Exchange and market

T_S_

.

.



Automation

T_S_

.

.



Smart lattice usage and information move

T_S_

.

.



Grid control

T_S_

.

.



Security and character the executives

T_S_

.

.



Resource sharing

T_S_

.

.



Competition

T_S_

.

.



Transparency

T_S_ .

.



Energy trading and supply

T_S_ .

.



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Vineet Chouhan et al.

Table 5.1 (continued) Variables

SPSS code

Mean

Std. N deviation

Energy dealers and trading

T_S_ .

.



Storage supplier and single access point delivery

T_S_ .

.



Removal of key obstacles and technological problems

T_S_ .

.



Settlement of imbalance

SI

.

.



Long reconciliation procedures

SI_

.

.



Volume updates

SI_

.

.



Validation in key explanations with delays

SI_

.

.



Loan uncertainties and collateral conditions

SI_

.

.



Confirmations of near real time

SI_

.

.



Precise monitoring of which generator

SI_

.

.



Removal of user produced discrepancy

SI_

.

.



Enabling real-time accounting

SI_

.

.



IoT platforms with digitalization

IoT

.

.



BC allows machine-to-machine (MM) contact

Iot_

.

.



Data transfers between smart devices

Iot_

.

.



Digitalization provides an incentive for electrical utilities

Iot_

.

.



Increases network reliability

Iot_

.

.



Improves online billing

Iot_

.

.



Supply chain and pursue different avenues of competition

Iot_

.

.



Allows applications as new market-based models

Iot_

.

.



Reduced digitalization management costs

Iot_

.

.



PP exchanging and decentralized energy

PP

.

.



Demand response

PP_

.

.



Synchronization of VPPs, grid and system organization

PP_

.

.



Regulation of power storing system operation

PP_

.

.



Decentralized energy system regulation

PP_

.

.



Collective power initiatives

PP_

.

.



RES allocation synchronization centered on the views of energy system stakeholders

PP_

.

.



79

Chapter 5 Emerging opportunities for the application of blockchain

Table 5.1 (continued) Variables

SPSS code

Mean

Std. N deviation

Integration with current power market systems

PP_

.

.



Allowing a direct energy exchange mechanism to take care of their generation and demand between consumers of energy

PP_

.

.



Energy storage systems and consumer-centric economies

ES

.

.



Coordination with uncontrollable and controllable loads

ESS_

.

.



Environmental benefits to the communities concerned

ESS_

.

.



Substantial reductions in distribution and transmission losses

ESS_

.

.



Local microgrids may boost network reliability

ESS_

.

.



Offer ancillary resources, such as frequency and voltage assistance

ESS_

.

.



To aging power networks with the ability to delay costly network improvement investments

ESS_

.

.



B-regression coefficients Variables

Variable name Adj. R ANOVA

Wholesale energy trading and supply

T_S_

Sig.

.

.

.f

.

.

.e

.

.

.e

T_S_ T_S_ T_S_ T_S_ Settlement of imbalance

SI_ SI_ SI_ SI_

IoT platforms with digitalization

Iot_ Iot_ Iot_ Iot_

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Table 5.1 (continued) B-regression coefficients Variables

Variable name Adj. R ANOVA

PP exchanging and decentralized energy

PP_

Sig.

.

.

.c

.

. .e

PP_ Energy storage systems and consumer-centric economies ESS_ ESS_ ESS_ ESS_ C-Coefficients Model

Unstandardized coefficients B

Wholesale energy trading and supply

Settlement of imbalance

IoT platforms with digitalization

Std. error

(Constant)

. .

T_S_

. .

T_S_

Standardized t coefficients

Sig.

Beta .

.

.

.

.

−. .

−.

−.

.

T_S_

. .

.

.

.

T_S_

−. .

−.

−.

.

T_S_

. .

.

.

.

(Constant)

. .

.

.

SI_

. .

.

.

.

SI_

. .

.

.

.

SI_

. .

.

.

.

SI_

. .

.

.

.

(Constant) Iot_

. . . .

.

. .

. .

Iot_

. .

.

.

.

Iot_

−. .

−.

−.

.

Iot_

. .

.

.

.

Chapter 5 Emerging opportunities for the application of blockchain

81

Table 5.1 (continued) C-Coefficients Model

Unstandardized coefficients B

PP exchanging and decentralized energy

(Constant)

. .

PP_

. .

PP_

Energy storage systems and consumer-centric economies

Std. error

−.

.

Standardized t coefficients

Sig.

Beta . . .

.

.

−.

−.

.

.

.

(Constant)

. .

ESS_

. .

.

.

.

ESS_

. .

.

.

.

ESS_

. .

.

.

.

ESS_

. .

.

.

.

The result of the analysis revealed that for variables T_S_3, T_S_4, T_S_6, T_S_9, T_S_12 with adjusted R2 = 78.9% and the model fit ANOVA, f-value is 17.966 which is significant. This means that the above hypothesis is accepted and five variables of T_S_3, T_S_4, T_S_6, T_S_9 and T_S_12 significantly influence the wholesale energy trading and supply with BC for improving efficiency in energy supply. The result of the analysis revealed that for variables SI_3, SI_2, SI_5 and SI_1 with adjusted R2 = 34.5% and the model fit ANOVA, f-value is 49.025 which is significant. This means that the above hypothesis is accepted and four variables of SI_3, SI_2, SI_5 and SI_1 significantly influence the settlement of imbalance with BC for improving efficiency in energy supply. The result of the analysis revealed that for variables Iot_2, Iot_7, Iot_3 and Iot_1 with adjusted R2 = 29.5% and the model fit ANOVA, f-value is 39.221 which is significant. This means that the above hypothesis is accepted and four variables of Iot_2, Iot_7, Iot_3 and Iot_1 significantly influence the P2P exchanging and decentralized energy with BC for improving efficiency in energy supply. The result of the analysis revealed that for variables P2P_2 and P2P_3 with adjusted R2 = 89.8% and the model fit ANOVA, f-value is 43.184 which is significant. This means that the above hypothesis is accepted and two variables of P2P_2 and P2P_3 significantly influence the IoT platforms with digitalization with BC for improving efficiency in energy supply. The result of the analysis revealed that for variables ESS_1, ESS_4, ESS_2 and ESS_5 with adjusted R2 = 59.2% and the model fit ANOVA, f-value is 133.587 which is significant. This means that the above hypothesis is accepted and four variables of ESS_1, ESS_4, ESS_2 and ESS_5 significantly influence the energy

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storage systems and consumer-centric economies with BC for improving efficiency in energy supply (see also Figure 5.5).

Increased Market Sucess

Increased Security and Customer Trust

Increased Reliability

Exchange Energy Saving

Encryption Energy Saving

Property Value Energy Saving

Blockchain Energy Efficiency

Lower Transaction Cost

Improving Transperency

Figure 5.5: Blockchain for energy efficiency.

5.5 Discussion of key challenges and future outlook The BC ventures and research efforts examined in this work demonstrate that BC are a viable tool for a broad variety of services and use cases in the energy sector. The research is apparent that BC solutions successfully cleared concept stage with some implementations but need more advancement in order to meet the required organizational and efficiency intentions. Several recent innovations, including the Energy Web BC, can also be extended to thousands of transactions per second. Similar potential technologies can dramatically decide BC acceptance across a variety of implementations, such as IoT systems and utilities needing very rapid clarification and a substantial number of transactions. Resilience to protection threats resulting from inadvertently poor device architecture or malicious attacks is extremely probable. BC pose additional challenges such as probable early implementation malfunctions owing to lack of familiarity in large-scale implementations [37]. BC may recognize substantial cost advantages by circumventing intermediaries, but in many situations, they may not have a strategic edge over traditional implementations in well-established markets. For example, energy transactions may be documented in traditional databases, such as relational databases configured to understand the connection between stored information items [40]. These technologies are now

Chapter 5 Emerging opportunities for the application of blockchain

83

commonly accessible and are currently quicker and less expensive to operate [21], although they cannot provide immutability of information or accountability. BC networks which need expensive new hardware, such as customized ICT equipment and applications, whose costs must be compensated by the advantages of data confidentiality, improved protection and the absence of the need for a secure intermediary. In the electricity market, smart meters are actually being phased with capacities, which could result in significant costs for the convergence of established smart metering and grid systems with distributed ledgers. Currently, knowledge in BC networks may be transmitted at very low cost, but authentication and testing of evidence is subject to high hardware and energy costs [21, 37]. Increasing to the expense of evidence verification, BC networks often face extra costs for maintaining details in constantly expanding ledgers. Promising strategies suggested to overcome this problem were to store actual data in “sidechains” and to operate the BC as a self-control layer instead of a storage capacity layer. Major obstacles to technological acceptance are important to both the legislative and legal realms. Regulatory bodies promote the active involvement of customers in energy markets [6, 22]. BC framework consumers should be known to account for their obligations while, at the same time, customer or industrial sensitive details should stay private, such as the rates negotiated between the electricity provider and the consumer in the smart contract entered into in the ledger. When knowledge from several users is recorded in shared files, solutions for data protection, security and identity management need to be established. In addition, smart contracts need to be incorporated into the legal code to maintain consistency with the legislation and customer safety. In the design of the distributed society, it is not really obvious who is morally and theoretically responsible for the harmful effects of the acts of the various actors. Further, a difficulty in adoption of BC framework is implemented, all modifications to the governing protocols or code need to be accepted by the system nodes.

5.6 Conclusions In conclusion, BC or DL systems will obviously support energy grid processes, economies, with customers. It provides accountability and safe transfers, yet BC provides innovative ways to motivate customers and miniature renewable producers for taking an accurate position in the electricity industry to monetize their properties. BC also made feasible the usage of energy business and has inspired many scholars to write about emerging business structures and electricity democratization [35]. A variety of academic and industrial parties are actively exploring BC engineering in market. BC is a fast-progressing field and growth, which is why a study of this new technology is essential to increase awareness, educate the information on BC. The paper analyzed numerous theoretical outlets and offered a summary of the foundations

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of BCT, including device structures and distributed consensus algorithms, essential performance elements for BC ecosystems. BCT is not threat for energy providers. The further development programs, experiments, ventures and partnerships can demonstrate if the invention will meet its maximum potential, confirm its market feasibility and, eventually, be accepted in the mainstream.

References [1]

[2]

[3]

[4] [5]

[6]

[7]

[8] [9] [10] [11]

[12] [13] [14]

Department for Business. Energy & Industrial Strategy (BEIS), DIGEST of United Kingdom energy statistics 2017 Chapter 6 Renewable sources of energy, , [accessed 5 Jun 2018] (2017). Luo, X., Wang, J., Dooner, M., Clarke, J. (2015). Overview of current development in electrical energy storage technologies and the application potential in power system operation. Applied Energy, 137, 511–536. Eid, C., Codani, P., Perez, Y., Reneses, J., Hakvoort, R. (2016). Managing electric flexibility from distributed energy resources: A review of incentives for market design. Renewable and Sustainable Energy Reviews, 64, 237–247. Zhou, S., Brown, M.A. (2017). Smart meter deployment in Europe: A comparative case study on the impacts of national policy schemes. Journal of Cleaner Production, 144, 22–32. Office of Gas and Electricity Markets (Ofgem). Transition to smart meters, , [accessed 6 Jan 2018] (2017). Energy Union Package. A framework strategy for a resilient energy union with a forwardlooking climate change policy, , [accessed 30 Jun 2017] (2015). Bronski, P., Creyts, J., Crowdis, M., Doig, S., Glassmire, J., Guccione, L., et al. The economics of load defection: How grid-connected solar-plus-battery systems will compete with traditional electric service-why it matters, and possible paths forward. , [accessed 20 Nov 2017] (2015). Ahsan, U., Bais, A. Distributed big data management in smart grid. In: Wirel Opt Commun Conference (WOCC) 2017, IEEE, 2017, 1–6. Swan, M. Blockchain: Blueprint for a new economy. O’Reilly Media Inc., 2015. CoinMarketCap. Cryptocurrency market capitalizations, , [accessed 5 Jun 2018] (2018). Walport, M. Distributed ledger technology: beyond blockchain. , [accessed 5 Jun 2017] (2016). Guo, Y., Liang, C. (2016). Blockchain application and outlook in the banking industry. Journal of Financial Innovation, 2(1), 24. Lomas, N. Everledger is using blockchain to combat fraud, starting with diamonds. , [accessed 29 Jun 2017] (2015). Tapscott, D., Tapscott, A. Blockchain Revolution: How the technology behind Bitcoin is changing money, business, and the world. Penguin, 2016, [accessed 20 Nov 2017].

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85

[15] Konashevych, O. Advantages and current issues of blockchain use in microgrids. , [accessed 18 Jun 2017] (2016). [16] Mattila, J. The blockchain phenomenon-the disruptive potential of distributed consensus architectures. , [accessed 15 May 2017] (2016). [17] Gartner, Gartner identifies three megatrends that will drive digital business into the next decade. , [accessed 8 Jun 2019] (2017). [18] Burger, C., Kuhlmann, A., Richard, P., Weinmann, J. Blockchain in the energy transition a survey among decision-makers in the German energy industry. , [accessed 15 May 2017] (2016). [19] Mattila, J., Seppala, T., Naucler, C., Stahl, R., Tikkanen, M., Badenlid, A., et al. Industrial blockchain platforms: An exercise in use case development in the energy industry. , [accessed 5 Jun 2017] (2016). [20] Grewal-Carr, V., Marshall, S. Blockchain enigma paradox opportunity. , [accessed 15 May 2017] (2016). [21] PwC global power & utilities, Blockchain – an opportunity for energy producers and consumers? , [accessed 22 Nov 2017] (2016). [22] Office of Gas and Electricity Markets (Ofgem). Consumer empowerment and protection, , [accessed 6 Dec 2017] (2017). [23] US Department of Energy. Smart grid system report, , [accessed 20 Nov 2017] (2009). [24] European Commission. European SmartGrids Technology Platform: Vision and strategy for Europe’s electricity networks of the future, , [accessed 20 Nov 2017] (2006). [25] Competition and Markets Authority. Energy market investigation summary of finalreport, , [accessed 15 May 2017] (2016). [26] HM Government. Cutting the cost of keeping warm – a fuel poverty strategy for England, , [accessed 20 Nov 2017] (2015). [27] Business Electricity Prices. A guide to wholesale electricity pricing, , [accessed 30 Jun 2017] (2017). [28] Andoni, M., Robu, V., Flynn, D. (2017). Blockchains: Crypto-control your own energy supply. Nature, 548(7666), 158. [29] Pinson, P., Baroche, T., Moret, F., Sousa, T., Sorin, E., You, S. The emergence of consumercentric electricity markets. , [accessed 31 Jan 2018] (2018). [30] Solar Plaza, Comprehensive guide to companies involved in blockchain and energy. , [accessed 31 May 2018] (2018). [31] Donnerer, D., Lacassagne, S. Blockchains and energy transition What challenges for cities?. , [accessed 6 Jun 2018] (2018).

86

Vineet Chouhan et al.

[32] Armbrust, M., Fox, A., Griffith, R., Joseph, A.D., Katz, R., Konwinski, A. et al. (2010). A view of cloud computing. Communications of the Association for Computing Machinery, 53(4), 50–58. [33] Back, A., Corallo, M., Dashjr, L., Friedenbach, M., Maxwell, G., Miller, A., et al. Enabling blockchain innovations with pegged sidechains. , [accessed 15 May 2017] (2014). [34] Diffie, W., Hellman, M. (1976). New directions in cryptography. IEEE Transactions on Information Theory, 22(6), 644–654. [35] Mylrea, M., Gourisetti, S.N.G. Blockchain for smart grid resilience: Exchanging distributed energy at speed, scale and security. In: Proceedings of the Resilience Week (RWS) 2017, IEEE, 2017, 18–23. [36] Mengelkamp, E., Garttner, J., Rock, K., Kessler, S., Orsini, L., Weinhardt, C. (2018). Designing microgrid energy markets a case study: The Brooklyn microgrid. Applied Energy, 210, 870–880. [37] Elexon. The electricity trading arrangements A beginner’s guide, , [accessed 30 Jun 2017] (2017). [38] Mylrea, M., Gourisetti, S.N.G. (2017). Cybersecurity and Optimization in Smart ‘Autonomous’ Buildings. In Lawless, W., Mittu, R., Sofge, D., Russell, S. editors, Autonomy and Artificial Intelligence: A Threat or Savior?, 263–294. Springer International Publishing. [39] Mustafa, M.A., Cleemput, S., Abidin, A. A local electricity trading market: Security analysis. In: Proceedings of the IEEE PES Innov Smart Grid Technol Conference Europe, IEEE, 2016, 1–6. [40] Indigo Advisory Group. Blockchain in energy and utilities use cases, vendor activity, market analysis, , [accessed 2 Nov 2017] (2017). [41] Dal Canto, D. Enel. Blockchain: which use cases in the energy industry, CIRED 2017 Glasgow, Round table discussion. [42] Utility Week. Electron reveals blockchain energy platform, , [accessed 13 Jun 2017] (2017). [43] Ernst & Young. Overview of blockchain for energy and commodity trading, , [accessed 20 Nov 2017] (2017). [44] Lasseter, R.H., Paigi, P. Microgrid: A conceptual solution. In: Proceedings of the IEEE35th Annu Power Electron Special Conference PESC 04, IEEE, 2004, 6, p. 4285–4290. [45] Jaradat, M., Jarrah, M., Bousselham, A., Jararweh, Y., Al-Ayyoub, M. (2015). The internet of energy: Smart sensor networks and big data management for smart grid. Procedia Computer Science, 56, 592–597. [46] Sagiroglu, S., Terzi, R., Canbay, Y., Colak, I. Big data issues in smart grid systems. In: Proceedings of the 2016 IEEE International Conference Renew Energy Res Appl (ICRERA), IEEE, 2016, p. 1007–1012. [47] Berka, A.L., Creamer, E. (2017). Taking stock of the local impacts of community owned renewable energy: a review and research agenda. Renewable and Sustainable Energy Reviews, 82(Part (3)), 3400–3419. [48] Marnay, C., Chatzivasileiadis, S., Abbey, C., Iravani, R., Joos, G., Lombardi, P., et al. Microgrid evolution roadmap. In: Proceedings of the 2015 International Symp Smart Electric Distrib Syst Technol (EDST), IEEE, 2015, 139–144. [49] Ton, D.T., Smith, M.A. (2012). The US Department of energy’s microgrid initiative. Electrical Journal, 25(8), 84–94.

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[50] Kamel, R.M., Chaouachi, A., Nagasaka, K. (2010). Carbon emissions reduction and power losses saving besides voltage profiles improvement using microgrids. Low-Carbon Economy, 1(1), 1. [51] Mihaylov, M., Jurado, S., Avellana, N., Razo-Zapata, I., Van Moffaert, K., Arco, L., et al. Scanergy: a scalable and modular system for energy trading between prosumers. In: Proceedings of the 2015 International Conference on Auton Agent Multi Agent Syst, IFAAMAS, 2015, 1917–1918. [52] Hatziargyriou, N. editor. (2014). Microgrids: Architectures and Control, Wiley Online Library, United Kingdom. [53] Stadler, M., Cardoso, G., Mashayekh, S., Forget, T., DeForest, N., Agarwal, A. et al. (2016). Value streams in microgrids: A literature review. Applied Energy, 162, 980–989. [54] Dimeas, A.L., Hatziargyriou, N.D. (2005). Operation of a multiagent system for microgrid control. IEEE Transactions on Power Systems, 20(3), 1447–1455. [55] Lamparter, S., Becher, S., Fischer, J.-G. An agent-based market platform for smart grids. In: Proceedings of the 9th International Conference Auton Agent Multi Agent Syst Industry track, IFAAMAS, 2010, 1689–1696.

Gourav Surana, Shurveer S. Bhanawat, Vineet Chouhan

Chapter 6 Measuring professionals’ perception on blockchain-based futuristic accounting Abstract: This research measures the disruption in accounting triggered by emerging technology: blockchain technology (BT). It analyzes its role in accounting with accounting professionals’ awareness of these technologies and its impact over their working. It also measures the advantages and challenges of adopting BT in accounting. For that purpose, it explores the possibility of accounting professionals’ perception after collecting data through the opinion survey method. To analysis data, t-test with SPSS software was used. For testing the reliability of collected data through opinion survey, Cronbach’s alpha reliability test has been conducted. The study concluded that accounting professions are aware of these technologies. Results also show that BT makes real-time accounting possible soon. Results revealed that this technology may improve monopoly of the big corporation. The study revealed that professionals’ perceived mind-set may become a big challenge to adopt BT in accounting. Keywords: disruptive technologies, blockchain technology (BT), accounting and auditing, socioeconomic impacts, benefits, barriers

6.1 Introduction One of the primary drivers of technical advancement in accounting is blockchain technology (BT) [1–4]. Technological progress has been a significant contributor to the global economy, bringing fundamental changes in our lives [5, 6]. The benefits and drawbacks of this approach are special. BT basically reworks how we live, work and communicate with each other [7]. KPMG 2018 reports that the US CEO. CEOs think a lot with their companies about D&A technologies. It is safe to assume that the three most-discussed innovations, cloud computing, AI and blockchain, also have a significant influence [8, 9]. In accordance with these systems, information on demand is exchanged, activity management is streamlined, risky

Gourav Surana, Department of Accountancy and Business Statistics, Mohanlal Sukhadia University, Udaipur, Rajasthan, India, e-mail: [email protected] Shurveer S. Bhanawat, Department of Accountancy and Business Statistics, Mohanlal Sukhadia University, Udaipur, Rajasthan, India, e-mail: [email protected] Vineet Chouhan, School of Management, Sir Padampat Singhania University, Udaipur, Rajasthan, India, e-mail: [email protected] https://doi.org/10.1515/9783110702507-006

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business transactions are detected and controlled transaction concerns and market concerns are recognized [10]. Blockchain is the abovementioned technology that affects each economic area, but it can be totally disrupted in the accounting and audit sector because of the features of the technology [11, 12]. The blockchain is an incorruptible automated business transaction pioneer that is programmable to monitor not only financial transactions but also nearly all valuables [13]. In blockchain technology, we have a chain of blocks that includes a digital signature, timelines and information, which are then replicated to all nodes on the distributed network and is protected and unchanging from cryptography. Blockchain has the ability to improve the productivity of the accounting industry by reducing the expense of storing and reconciling accounts, offering full clarity about ownership and asset records. Blockchain may allow accountants to become transparent about their organizations’ finances and responsibilities and also provide opportunities to focus on preparation and assessment instead of recordkeeping [14–16]. A detailed analysis of the literature was carried out in order to understand better the position of BT. Nakamoto [17] offers a solely peer form of electronic cash that will allow for direct online transfers without going through a financial institution from one party to another. The coins made from digital signatures have been launched by the normal system, which offers good ownership protection but is incomplete without avoiding replication. Therefore, they suggested a two-way approach via a peer-topeer network [18]. They also argued that the chance was lost. Blockchain technologies will evolve as a big improvement in accounting as double-entry accounting evolves and becomes available [19, 20]. Although double entry has been the increasingly for several years, it seems unbelievable that this is so as the pledge of blockchain innovations approaches the truth of their transformational potential in terms of a change toward triple entry. The objectives of the paper include examination of the futuristic role of blockchain technology in accounting, study the knowledge of blockchain-based accounting accounts accountant professionals and recognize socioeconomic obstacles, benefits and barriers to technology-based blockchain accounting acceptance.

6.2 Reviews of literature The most transformative innovations are currently considered [1, 2]. A mechanical, permanent, global, lead can be interpreted as capturing transactions in real time in the temporal sense [3, 4]. The Internet of money is also known as blockchain [5–7]. Blockchain technology’s first deployment is the popular “Bitcoin” cryptocurrency. Cryptocurrencies allow people to anonymously store their money and make transfers without brokers such as banks. This simplifies money transfer and shopping even more easily and efficiently. Therefore, blockchain offers broad financial framework architecture [8, 9]. That is, you can efficiently store and transfer capital. In reality,

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all sorts of financial assets, stocks, bonds, futures, commodities and immovables can be handled and transacted on blockchains easily in contrast to conventional device implementations [10–12]. The supply chain management [4, 21] is another significant application of blockchain technology. A significant number of organizations are now involved in designing blockchain technologies for real-time distribution management and tracking of the sources and conditions of products that join their supply chains [14–16]. This will aid with verifying the product origin and life cycle. Establish trust in the system, deter abuse and boost performance for providers and customers [13]. The authenticity test function of blockchain is so critical that some unique examples are given including talking of products of luxury [2, 17]. Blockchain diamonds are forever true and so. The first areas in which blockchain projects advance in the areas of openness, protection and trust are works of art and other items of high value. Obviously, such efficiencies can be of considerable benefit by minimizing counterfeiting and encouraging improved corporate practices in the luxury goods industry [18–20]. This is a very creative product. A blockchain feature for the protected registry is that a timestamped blockchain archive can register all kinds of copyright patents or trademarks in an intellectual property [22–24]. Thus, we can search for the legitimacy of virtually any commodity with blockchain. Another big area of use for blockchain is digital identity. The theory of the blockchain platform and technology is focused around the existence of blockchain as a pioneer for Bitcoin transactions, suggesting it is a true accounting mechanism for encoding, storing and publishing transactions details in Bitcoin technically [5, 6, 8]. As blockchain can carry currency transactions without any intermediary trusted third party, notice that currency exchanges are one of the best fields of financial interactions, it can also carry any form of property transactions, such as equities, shares and mortgages [6, 7]. The accounting practitioners are primarily interested in the calculation, coordination and review of financial reports. Often, accountants are concerned with assessing or calculating land rights and responsibilities, or with managing the best financial services should be distributed [12, 13, 15]. Using blockchain technologies, accountants have information on their organizations’ limited financial capital and responsibilities and use limited data, concentrating on preparation and assessment, rather than paperwork. This technology will improve accounting by lowering accountancy costs [2, 21]. Their extensive expertise is also important. BT is factual for land ownership and wealth history [25–27].

6.3 Research methodology The opinion of the respondents has been collected by means of an online opinion polling tool to carry out current research on BT-based accounting. We submitted 700 replies (out of 650), all from different accounting careers, that is, Academics, academic scientists among others, charted accountants (CA). Descriptive reports are provided for

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data analysis. “Cronbach’s alpha” was used with a score of 0.791 to measure accuracy and trustworthiness of opinion. Additional sample t verification of the hypothesis has been used. For the study, emails and social media, are included with questionnaire on google forms. In addition, the respondents were asked to send on their contacts the questionnaire for their views to further extend the reach of the analysis. The questionnaire used in the opinion poll showed the demographic responses and the questions of the age, gender and career of the respondent; digital technologies referred to general questions relating to the experience of the respondents and the understanding of new technological advancement in the accounting profession.

6.3.1 Hypotheses 1. 2.

H1(a): Significant difference exists in the views of respondents regarding technological innovation, its impact and familiarity of BT. H1(b): Socioeconomic impact, advantages for the accounting and auditing industry and barriers significantly influence the acceptance of BT.

6.4 Data analysis The data analysis starts with the demographical profile of the respondents presented in Table 6.1: Table 6.1: Demographical profile. Frequency

Percent

Between  and 



.

Between  and 



.

Between  and 



.

Between  and 



.

Total



.

Male



.

Female



.

Total



.

Age

Gender

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Table 6.1 (continued) Frequency

Percent

CA



.

Academician



.

Research scholar



.

Others



.

Total



.

Profession

6.4.1 Demographic feedback In the opinion poll on age, gender and occupation, demographic questions were posed. The majority (93%) are aged 20 to 40 years, while a limited number of respondents are outside the range. The majority (73%) of respondents were 20–30 years old. And nearly all men (49%) and women (51%) were similarly interested in this poll. This survey was conducted with respondents from the following groups: “Science scholar” (43%), “CA” (26%), “Academic” (26%) and “Other” (5%). The graphical view of information of BT is shown in Figure 6.1.

Figure 6.1: Familiarity with BT.

The respondents’ response to their experience with BT indicated that respondents took this technology seriously and, as seen in the literature review, have considerable disruptive potential. As shown in Figure 6.1, BT is renowned for new accounting technology.

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As per the first objective to analyze the acceptance of respondent’s regarding the technological innovation, its impact and familiarity of BCT the views gathered and to test the differences in the perception following hypothesis were made: H1(a) = Significant difference exists in the views of respondents regarding technological innovation, its impact and familiarity of BT. To test the above hypothesis, the one-sample t-test were being used with SPSS-19 software. The results are provided in Table 6.2. Table 6.2: One-sample t-test opinion of respondents about disruptive technology. One-sample statistics N

Mean

Std. deviation

Sth. error mean

Acc_tech_innov



.

.

.

Tech_imp_Acc



.

.

.

fam_BT



.

.

.

One-sample test Test value =  t

df

Sig. (two-tailed)

Mean difference

% confidence interval of the difference Lower

Upper

Acc_tech_innov

.



.

.

.

.

Tech_imp_Acc

.



.

.

.

.

fam_BT

−.



.

−.

−.

.

The performance of the “one-shot t-test” in Table 6.2 indicates that the predicted test significance is substantially different from the measured survey statistics for acknowledging the technical development and technical effect on accounts (as p < 0.05) at 5% of importance. Furthermore, the respondents decided on the knowledge with BT technologies that they were ignorant of the negative distance being negligible ( p > 0.05) as (tmean difference = −0.38). Hence, it reveals that the responses are in favor that they are aware about technological innovation and its impact but the BT in not familiar to all of them. Further, the respondents were aware about the specific disruptive technology in accounting is also measured. It is clear from one-sample t-test that some where people have heard about these disruptive technologies. In addition the other aim to examine the difference of opinion between respondents regarding the socioeconomic effect, benefits were gathered for the accounting

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and auditing industry and obstacles were established for use of BT’s recognition of the views of respondents and differences of view as follows: H1(b) = Socioeconomic impact, advantages for the accounting and auditing industry and barriers significantly influence the acceptance of BT. To test the above hypothesis, the regression models were being developed with SPSS-19 software. The results are provided in Table 6.3. Table 6.3: Regression result (N = 650). Variable

SPSS code

Mean

Std. deviation

Std. error mean

Loss of jobs

Soci_Eco_

.

.

.

Increased growth of wealth inequality

Soci_Eco_

.

.

.

Offshoring of local jobs

Soci_Eco_

.

.

.

Enhance monopoly of big corporations

Soci_Eco_

.

.

.

Lack of skill and training for new type of accounting job

Soci_Eco_

.

.

.

Real-time accounting and auditing

adv_tech_inn_ .

.

.

Providing new opportunities to accounting professional

adv_tech_inn_ .

.

.

Enhance authenticity of accounting records

adv_tech_inn_ .

.

.

More efficient accounting and auditing

adv_tech_inn_ .

.

.

Enhance transparency in accounting records adv_tech_inn_ .

.

.

Minimize accounting and auditing cost

adv_tech_inn_ .

.

.

People have more control over their own personal data/records

adv_tech_inn_ .

.

.

Lack of trust

barriers_BT_

.

.

.

Perceived data security

barriers_BT_

.

.

.

Lack of compatibility with existing system

barriers_BT_

.

.

.

Lack of interoperability with/ between third parties providing services

barriers_BT_

.

.

.

Perceived mind-sets of accounting and auditing professionals

barriers_BT_

.

.

.

Fear of job loss

barriers_BT_

.

.

.

Lack of technical skills and training

barriers_BT_

.

.

.

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Table 6.3 (continued) Multiple regression analysis result (N = ) Variables

Variable name

Adj. R

Beta

ANOVA

Sig.

Socioeconomic impact

Soci_Eco_

.

.

.

.c

.

.d

.

.d

.

Soci_Eco_ Advantages for the accounting and auditing industry

Barriers in adoption of BT

c

adv_tech_inn_

.

.

adv_tech_inn_

.

adv_tech_inn_

.

barriers_BCT_

.

.

barriers_BCT_

.

barriers_BCT_

.

Two variables are selected. Four variables are selected.

d

The results explained in Table 6.3 revealed that the two variables Soci_Eco_3 and Soci_Eco_5 explains the socioeconomic impact of BT use, three variables adv_tech_inn_5, adv_tech_inn_3 and adv_tech_inn_6 revealed advantages for the accounting and auditing industry and three variables barriers_BCT_7, barriers_BCT_5, barriers_BCT_2 explains the barriers in adoption of BT. With the results, the regression model for the adoption of biotech technology is made as under shown in Figure 6.2. Figure 6.2 revealed that the socioeconomic impact of the blockchain technology is due to offshoring of local jobs (Soci_Eco_3) which means that the local jobs will be available for the foreigners and the skilled foreigners will come for the new bread of the job ad it may improve or hinder the local residents life and further, lack of skill and training for new type of accounting job (Soci_Eco_5) will certainly impact the local people and nation’s citizen’s life. The countries that have well-developed accounting environment with accounting experts will be having an age over the others and will impact on the socioeconomic condition of the respondents with blockchain technology. The advantage for the accounting and audit industry with the use of the BT, it enhances authenticity of accounting records (adv_tech_inn_3) since making change in the written work will not be easy, thus the record made will be more authentic; it enhance transparency in accounting records (adv_tech_inn_5), the use of BT will not only enhance the authenticity but also the transparency as the requirement will always be understood by the maker and in case of any type of ambiguity further with the use of the BT the cost of the accounting and auditing (adv_tech_inn_6) can also be minimized as the system will help in minimizing the errors and sometime stop wrong entries and will provide the auditor with check within the computerized environment reducing the time and efforts.

Chapter 6 Measuring professionals’ perception on blockchain-based

Figure 6.2: Blockchain technology adoption model.

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But the use of the BT cannot always ignore the limitation of the software and technology as perceived data security (barriers_BT_2) is the major barrier in front of the use of BT, further perceived mind-sets of accounting and auditing professionals (barriers_BT_5) will not be changed with the use of the technology and the old experience professionals do not wish to change and easily adopt it as other technologies. Furthermore, lack of technical skills and training (barriers_BT_7) is the major barrier in front of use of any technology including the BT, thus the success of the adoption of BT depends upon proper training.

6.5 Conclusion The use of disruptive technologies such as BT is very important in a computerized period of accountability. It is important that accountants are acquainted with these technologies to make effective use of those technologies. BT plays a key role in accounting. Results also conclude that accountants think that these technologies interrupt the accounting profession, but they do not that they interrupt accounting due to the lack of technical skills. It further showed that with the adoption of the technology, the socioeconomic benefits and socioeconomic benefits of BT technology for the accounting and auditing industry are insignificant differences in barriers to BT acceptance. BT’s greatest advantage is that it can provide real-time accounting. Results reveal that in 5–10 years, this technology may disrupt the accounting profession.

Definitions 1 Blockchain technology – Blockchain is a shared, distributed ledger that can be used to keep accurate, validated, immutable and safety encrypted record of any asset that can be digitized. 2 The theory and development of a computer system able to perform tasks normally requiring human intelligence such as visual perception, speech recognition, decision -making and translation between languages. 3 In 2005, Ian Grigg has given a new concept of accounting which is called Triple Entry Accounting.

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4 The term “Disruptive Technology” refers to the development and implementation of technology that has a disrupting effect, often negative, on existing products & services being provided by companies or individuals.

References [1] [2]

[3]

[4] [5] [6] [7] [8] [9] [10] [11] [12]

[13] [14] [15] [16] [17] [18]

[19]

Johansen, S.K. (2018). A Comprehensive Literature Review on the Blockchain as a Technological Enabler for Innovation, Dept. of Information Systems, Mannheim University. Kokina, J., Mancha, R., Pachamanova, D. (2017). Blockchain: Emergent industry adoption and implications for accounting. Journal of Emerging Technologies in Accounting, 14, 91–100. Doi: 10.2308/jeta-51911. Saberi, S., Kouhizadeh, M., Sarkis, J., Shen, L. (2019). Blockchain technology and its relationships to sustainable supply chain management. International Journal of Production Research, 57(7), 2117–2135. Watson, L.A., Mishler, C. (2017). Get ready for blockchain: Should management accountants add blockchain technology to their professional vocabulary? Strategic Finance, 98(7), 62–64. El-Hussein, M.O.M., Cronje, J.C. (2010). Defining mobile learning in the higher education landscape. Journal of Educational Technology & Society, 13(3), 12–21. Kemp, R. (1994). Technology and the transition to environmental sustainability: The problem of technological regime shifts. Futures, 26(10), 1023–1046. Dinh, T.N., Thai, M.T. (2018). AI and blockchain: A disruptive integration. IEEE-Computer, 51(1), 48–53. Retrieved September 2019. Niranjanamurthy, M., Nithya, B.N., Jagannatha, S. (2018). Analysis of blockchain technology: Pros, cons and SWOT. Cluster Computing, 22(5), 1–15. Zhao, S., Li, S., Yao, Y. (2019). Blockchain enabled industrial Internet of things technology. IEEE Transactions on Computational Social Systems, 6(6), 1442–1453. Jarczyk, D. (2019, March 13). https://www.accountingtoday.com/opinion/cloud-ai-and-blockchainare-transforming-accounting. Retrieved September 2019, from www.accountingtoday.com. Aste, T., Tasca, P., Di Matteo, T. (2017). Blockchain technologies: The foreseeable impact on society and industry. Computer, 50(9), 18–28. Peters, G.W., Panayi, E. (2016). Understanding Modern Banking Ledgers Through Blockchain Technologies: Future of Transaction Processing and Smart Contracts on the Internet of Money. In Banking Beyond Banks and Money, 239–278. Cham: Springer. Tapscott, D., Tapscott, A. (2018). Blockchain revolution. Penguin. Retrieved September 13, 2019. Böhme, R., Christin, N., Edelman, B., Moore, T. (2015). Bitcoin: Economics, technology, and governance. Journal of Economic Perspectives, 29(2), 213–238. Thakker, M. (2018). Blockchain: A Foundational Change In Financial Records (No. 2018-28-14). Wright, A., De Filippi, P. (2015). Decentralized blockchain technology and the rise of lex cryptographia. Available at SSRN 2580664. Nakamoto, S. (2008). Bitcoin: A peer to peer electronic cash system. Retrieved 2018, from bitcoin: https://bitcoin.org Carlin, T. (2018). Blockchain and the journey beyond double entry. Australian Accounting Review, accessed on 2018-11-20, from https://www.x-mol.com/paper/ 1349810352085037056?recommendPaper/1365176288186822656. Carlin, T. (2019). Blockchain and the journey beyond double entry. Australian Accounting Review, 29(2), 305–311.

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[20] Karajovic, M., Kim, H.M., Laskowski, M. (2019). Thinking outside the block: Projected phases of blockchain integration in the accounting industry. Australian Accounting Review, 29(2), 319–330. [21] Francisco, K., Swanson, D. (2018). The supply chain has no clothes: Technology adoption of blockchain for supply chain transparency. Logistics, 2(1), 2. [22] Gürkaynak, G., Yılmaz, I., Yeşilaltay, B., Bengi, B. (2018). Intellectual property law and practice in the blockchain realm. Computer Law & Security Review, 34(4), 847–862. [23] Mainelli, M., Smith, M. (2015). Sharing ledgers for sharing economies: An exploration of mutual distributed ledgers (aka blockchain technology). Journal of Financial Perspectives, 3(3), 1–47. [24] Savelyev, A. (2018). Copyright in the blockchain era: Promises and challenges. Computer law & security review, 34(3), 550–561. [25] Crosby, M., Pattanayak, P., Verma, S., Kalyanaraman, V. (2016). Blockchain technology: Beyond bitcoin. Applied Innovation, 2(6–10), 71. [26] McConaghy, M., McMullen, G., Parry, G., McConaghy, T., Holtzman, D. (2017). Visibility and digital art: Blockchain as an ownership layer on the Internet. Strategic Change, 26(5), 461–470. [27] Ølnes, S., Ubacht, J., Janssen, M. (2017). Blockchain in government: Benefits and implications of distributed ledger technology for information sharing.

Ashok Bhansali, Jolly Masih, Meenakshi Sharma

Chapter 7 Blockchain 3.0 for sustainable healthcare Abstract: With increased digitization, huge amount of data is being generated in relation to patient health information, electronic health records, Internet of things (IoT)based health monitoring systems, insurance data and lot more. Blockchain 3.0 offers huge distributed storage space without much resources at your end, provides scalability without sacrificing security, helps integrating data from different sources without compromising privacy, delivers transparency without revealing ownerships, ensures interoperability without much complexities and establishes provenance with authenticity. Flexibility and multidimensional capability of blockchain technology offers a lot of potential for innovation, integration and sustainability in the healthcare space. Amalgamation of artificial intelligence, analytics and smart contracts helps leveraging core blockchain technology to create better value preposition for all the stakeholders vis-avis entire value chain of healthcare segment. This can be helpful in healthcare audits, clinical research, fighting counterfeit medicines, medical compliances, government regulations, drug supply chain management, claim settlements and many more. This chapter aims at explaining different applications, approaches and models of Blockchain 3.0 implementation across entire value chain of the healthcare system and discusses the most important use cases that can lead to transformation and adds to the sustainability of the entire healthcare industry. This chapter discusses blockchain adoption journey from the technological perspective, viewpoint of challenges, implementation strategies and the way forward. This chapter presents how blockchain technology can impact and affect the broad segments of the healthcare space and improves sustainability. The first and most important use case explains how blockchain helps creating, exchanging and maintaining complete, accurate, secure and transferable healthcare records of patients with all compliances in-place. Smart contracts provide regulated and transparent access to data and can help conflict free faster claim settlement without the need of a middleman. Second use case explains how blockchain can help streamlining the processes of healthcare insurance companies and adds value to the patients as well as to the healthcare business. Blockchain along with artificial intelligence, machine learning and data analytics helps research and clinical trial management by way of drawing inferences from huge amount of data, fixing accountability and distributing research report in an effi-

Ashok Bhansali, O.P. Jindal University, India, e-mail: [email protected] Jolly Masih, Prestige Institute of Engineering Management and Research, India, e-mail: [email protected] Meenakshi Sharma, Global Group of Institutions, India, e-mail: [email protected] https://doi.org/10.1515/9783110702507-007

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cient and cheaper way for faster and better scientific research outcomes. Third case study illustrates the use of Blockchain 3.0 for better management of clinical trials. The fourth use case explains how blockchain improves pharmaceutical supply chain management and mitigates the risk of counterfeit, fake and unapproved drugs and equipment. Of course the adoption of Blockchain 3.0 in medical segment is slow but the value addition offered by the technology to the sustainability of healthcare system have drawn the attentions of researchers, governments and healthcare companies to invest in this domain for a greater and better tomorrow. Keywords: blockchain, DLT, sustainable healthcare, interoperability, pharma supply chain, clinical trial, health insurance, healthcare management

7.1 Introduction The entire world is fast moving toward Industry 4.0. Emerging and disruptive technologies can help improving productivity, and revenue and offers whole lot of opportunities for better economic growth and sustainability of the entire healthcare space. It is believed that with the adoption of emerging technologies, healthcare would be able to save approximately $100 billion per annum and blockchain technology would contribute the most in this. With increased digitization in place, healthcare industry is generating enormous amount of data but the different stakeholders are unable to leverage the benefits because of various issues associated with sharing of data like integrity, privacy, security, authenticity and accountability. Blockchain by its very design addresses these challenges in an effective and efficient manner, and has proven implementations in the financial sector. Blockchain 3.0 with its extended functionality and rich APIs can transform the health sector by enabling effective collaboration, data exchange, mitigating data threats, automating back-office grunt work and improving revenue cycle management. Blockchain has the potential to add to the sustainability of almost all the verticals of healthcare sector like patient health records (PHRs), supply chain, clinical trials, health insurance, pharma R&D and so on. Indeed, Estonia has become the first country to adopt a blockchain-based healthcare system to ensure security and integrity of electronic health records (EHRs) of all of its citizens [1].

7.2 Blockchain technology Blockchain was introduced to the world, by an anonymous person, as the technology for creation of the world’s first virtual currency – Bitcoin [2]. It is a protocol to create a chain of blocks of transactions which are linked sequentially using

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cryptographic hash function of the previous block and uses digital signature to implement a trust less distributed ledger technology [3, 4]. Detailed underpinning of the technology is outside the scope of this chapter but we will introduce the concept and working of technology to understand its usage in healthcare domain. In simplest terms, blockchain is a shared ledger of blocks that contains the record of transactions which could be cryptocurrency, smart contracts, health information, insurance policy or any information for say. Each block along with transactions embeds in itself the message digest of previous block using cryptographic hash to ensure immutability. Each block is attached to the previous with the help of cryptographic protocols over a distributed peer-to-peer (P2P) network over the Internet [5]. Any transaction that takes place is signed by a private key to ensure privacy and nonrepudiation, and is broadcasted to the network. A mining node verifies this transaction, adds to a block and broadcasts to the network [6]. Network nodes verify the validity of the block using consensus protocol and known algorithms, for example, proof of work. Once the transaction block is validated, it is attached on top of the existing blockchain using cryptographic hash functions. Each block is time sequenced using timestamping and blockchain is updated by all the nodes on blockchain. Blockchain is not owned by anybody and it uses proven cryptographic techniques to embed privacy and trust; and allows each user to store, share and look into the block data. Different consensus mechanism and cryptographic functions can be used to address varied privacy, transparency and access usage.

7.2.1 Smart contract Smart contract is a substitute for traditional manual contracts by embedding programing codes over the blockchain network that enables automatic enforcement of the terms of agreement. It is a blockchain-based innovative approach of achieving decentralized automation as shown in Figure 7.1. A smart contract gets executed automatically when predefined contract conditions are met, and thus enhances efficiency, trust, transparency and real-time settlement without any dispute [7]. There exist smart contracts with different natures – deterministic and nondeterministic [8]. Deterministic contracts have all the needed information on blockchain itself, whereas nondeterministic needs information from external data sources. Contract writing facility with first generation of blockchain, that is, Bitcoin is very limited whereas next-generation blockchains, for example, Hyperledger and Ethereum support fully customized smart contracts [9]. Blockchainpowered smart contracts play a central role in eliminating third parties for verification, enforcing the terms and automating complex processes for data management.

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Figure 7.1: Smart contract process flow and benefits.

7.2.2 Taxonomy and evolution of blockchain A blockchain implementation falls into any of the following categories [10], depending on how it can be used and who can use it. Generally, the policy makers decide on the choice of appropriate blockchain for the intended purpose. Table 7.1 illustrates the blockchain taxonomy with its features and usage. Table 7.1: Blockchain taxonomy. Blockchain type

Features

Public blockchain

– – – – –

Fully decentralized public network Permission-less distributed ledger Anybody can add and verify transaction Provides incentives for public to join and support network Bitcoin, Ethereum, Litcoin, etc.

Private blockchain

– – – – –

Owned by an individual organization Restrictive or permission blockchain Selected users are allowed to verify and add transactions Generally, anybody can view the transactions Multichain, Corda, Hyperledger, etc.

Consortium blockchain

– – – –

Semi-decentralized network Shared among group of organizations Permissioned ledger, can be available to all or restricted to few people Controlled by authorized nodes, information can be added only by authorized accounts. R3, Energy Web Foundation, etc.

–

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Table 7.1 (continued) Blockchain type

Features

Hybrid blockchain

– – – – –

Provides the advantages of private and public blockchains Public blockchain for accessing the ledger private blockchain at the back end for access control and updating the ledger Immune to 51% attack VeChain, Ripple network, IBM FoodTrust, etc.

Blockchain technology is continuously evolving with the time and has been categorized into three phases [11]. This first implementation of proposed technology was meant only for cryptocurrency and is called Blockchain 1.0. Subsequently, blockchain introduced the concept of smart contract which is a programming code embedded in distributed ledger and that gets executed when predefined conditions are satisfied [7]. Eris and Ethereum falls under 2.0. The third generation, Blockchain 3.0, extends APIs and functionality for non-financial applications for government and different sectors like energy, health, land and so on. Blockchain 2.0 and 3.0 also introduced newer consensus protocols to serve the purpose like proof of stake, delegated proof of stake, practical byzantine fault tolerance and so on [12] as shown in Figure 7.2.

Figure 7.2: Advancement of blockchain technology.

7.2.3 Blockchain in healthcare space Blockchain can help enhancing sustainability by improving the efficiency and effectiveness of any business process or operation which is characterized as follows: – Huge amount of transaction(information) takes place which needs to be shared with multiple parties.

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– Different unknown parties need to collaborate and trust the transactions. – Intermediaries are not trustful and are inefficient. – Strong security and varied data control are desired to ensure integrity of the system.

Figure 7.3: A high-level overview of blockchain-based healthcare systems.

A high-level overview of Blockchain-based healthcare systems is shown in Figure 7.3. Health sector typically involves multiple stakeholders including patient, pharma companies, insurance providers, hospitals and research and development firms. Every party generates huge amount of data and sustainability of all these depend on time boundinformation flow, maintaining transparency and trust, ensuring the privacy and correctness of data; and collaboratively taking data driven decisions. Blockchain has got huge potential to transform the age-old healthcare system and can really help a lot in data security, privacy, sharing and storage [13, 14]. Considering the current scenario, blockchain seems to be most suitable for the healthcare systems for value addition and making it more sustainable.

7.3 Interoperability Interoperability is the biggest bottleneck in ensuring that right information reaches to the right person/party and it results in loss of millions of lives and billions of dollars every year. Interoperability enables different healthcare information systems and software applications to communicate, exchange and use the shared information within or outside the premises of the organization. Further, the healthcare echo system across the world is evolving into a value-based care model which depends on data driven decision-

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making and collaborative working. Interoperability can save cost and improves the operational effectiveness of the system by minimizing the time and cost of administrative issues like manual entry of data [15]. It improves clinical decision-making capability and response time by prompt and smooth access to the patient’s information.

7.3.1 Levels and challenges of interoperability There exist four different levels of interoperability. Foundation or level 1 deals with the inter-connectivity requirement. It exhibits the ability of one information system to exchange the patient or clinical data with other system. Structural or level 2 suggests the structure of the data. It defines the formats and syntax that needs to the exchanged along with interpretation at the data level. Semantic or level 3 is the most complex level of the interoperability. It includes models, values of datasets, coding, rules of standard vocabulary and significance to the users. Top most level is organizational or level 4 that aims at addressing the legal aspect, governance and policies to ensure the secure and seamless exchange of data. This level also helps defining the workflows and trustworthy collaborations among end users. Adoption of EHR, is the primary phase for enabling interoperability and has already been implemented by many stakeholders. The next phase is the seamless flow of the health related data among all the stakeholders but there exist three main challenges namely technical, marketing and systemic. Different EHR software follows different formats for storing records and making all of them compatible with each other is a big technical challenge. Integrity and privacy of the data is most crucial and interoperability may provide a single point of compromise. Also, hospitals and pathologies have already invested huge amount in legacy system and they are not willing to shed money further just for interoperability. Different EHR solution providers sell their proprietary systems with an array of features and services and interoperability dilutes their competitive edge. Intermediaries play a very significant role across the entire healthcare space and disintermediation is not easy. Also due to lack guidelines and framework, the governments are not in a position to enforce single interoperability standard.

7.3.2 Blockchain 3.0 for interoperability Table 7.2 states the typical interoperability pain points and how blockchain can help addressing the issues. A blockchain-based smart contract driven application can help getting rid of intermediaries. Implementation of Integrating the Healthcare Enterprise protocol plays a very significant role in achieving interoperability. It helps exchanging personal health records (PHRs), EHRs and medical health records (MHRs) with convenience. A transaction on the block can typically store the references of the EHRs and smart contract can embed the rules for accessing of EHRs by different stakeholders. This

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helps fine-tuning who can access what and how long. Also, blockchain, by its nature, contains an unchangeable record of all the activities that takes place with the data. Blockchain can really help in improving processes and compliances, avoiding conflicts, saving cost and efficient data management [16]. It can also help in overcoming single point of failure and helping medical research with faster and reliable data access [17]. Table 7.2: Interoperability challenges and blockchain solutions. Pain points and challenges

Blockchain solutions

Difficult to establish a trusted broker which maintains a complete record of all data transactions.

Trust is implicit part of the network using consensus protocol and cryptographic functions.

For lower number of transactions, cost per transaction is higher.

Removal of intermediaries and distributed network makes blockchain-based system more efficient and reduces cost.

Lots of proprietary standards make interoperability difficult and inefficient.

Real-time data updating on participating nodes makes operations efficient and interoperability feasible.

Privacy and security of the data is a bigger challenge.

Cryptographic hash functions makes data secure and public private key ensure privacy.

Interoperability may create a single point of failure or cyberattack.

Decentralized and distributed network and cryptographic timestamping ensures immutability and better security.

Incorporating changes of proprietary data formats is difficult and time taking.

Smart contracts can be used to incorporate changes in real time basis.

All medical records or their references can be stored directly on to the blockchain for securing and making them visible to others. However, large data, for example, MRI image, slows down the processing speed and so smaller data is stored directly on-chain whereas large data is kept off the chain and a pointer to it can be saved on blockchain. An API can be written that facilitates fetching the data by smart contract. This APIs can be distributed to all participating nodes for enabling frictionless integration with existing digital systems. Similarly, another set of APIs can be used to query information from the blockchain. This API oriented architecture allows organizations to strengthen their internal system and desired data can be fetched automatically over the blockchain for ensuring interoperability.

7.3.3 Example use cases The most significant use case is the Estonia which is the first country in the world to adopt a blockchain system to securely store the medical records of its citizens [1].

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Government of Estonia in association with the Netherlands-based company, Gaurdtime, implemented an e-health record that integrates all the PHRs and EHRs from different healthcare providers. It employs KSI blockchain technology to maintain the integrity of retrieved HERs, MHRs, PHRs and access logs. All citizens are having a smartcard that is used to links their EHR data with their private identity. As soon as an EHR gets updated a new hash is created and record is added to the blockchain. MedRec is a pilot prototype developed by MIT media laboratory and Israel medical center. It uses decentralized system to provide interoperability for sharing data and managing authorization, permission and so on. Patients can upload their data and give or remove access to use it. For secrecy, data is stored on database and only references and permissions are stored on blockchain. It uses Ethereum platform to make information available to people regarding data usage [18]. MedBlock is a blockchain-based application for searching medical records [19]. Records of the patients are maintained and grouped by the healthcare department and the MedBlock contains a reference to each record on the blockchain. Operations and permissions on the data are stored on blockchain and a smart contract is used for the execution purpose. BlocHIE exploits the power and convenience of both off-chain as well as onchain data storage [20]. Health records are stored on the database of providers and blockchain stores reference of off-chain records for verification purpose. In order to improve the performance and fairness, author proposed two transaction-packing algorithms: FAIR-FIRST and TP&FAIR. Fast Healthcare Interoperability Resources (FHIR) chain is a blockchain-based network that implements FHIR standard for convenient sharing of clinical data records [21]. It uses Ethereum for sharing and managing healthcare records data and is meant for the patients who comply with the ONC. An Accenture White Paper with ONC also suggest that blockchain has got implicit features that can help achieving interoperability of health records [22]. BlockCloud is a blockchain application deployed over cloud environment to keep data distributed, safe and offers huge cloud storage space [23]. Gem Health Network was set up using Ethereum to improve patient care and save cost of routine data exchange [24].

7.4 Health insurance With the increased globalization, liberalization and awareness among people, the scope of health insurance is getting wider continuously. In many countries, health insurance is provided by governments as well as by private players. There is huge opportunities for leveraging the technology and authors feel that features of the blockchain can add lot of value to the entire insurance segment and make it more

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sustainable by costs cutting, managing risk, improve customer satisfaction level, grow business and, ultimately, boost value preposition for all the stakeholders.

7.4.1 Health insurance challenges Operative flow of any insurance company is multifaceted and complicated, and the healthcare insurance gets even complex as it directly deals with the lives of the people. Health insurance ecosystem, in today’s scenario, is a multilayer system consists of insurance providers, underwriters, patients, hospitals and, pathologies, third-party administrators (TPAs) and government. All the different parties involved maintain their own records of the EHRs/EMRs/PHRs and are apprehensive of sharing it with others for many different reasons. This authority-driven paper heavy manual system is prone to manipulation and errors. Active interaction and collaboration of everyone is desired for a claim settlement in time but the entire network is highly disorganized and inefficient. As per National Health Care Anti-Fraud Association, US alone lost approximately $300 billion in 2018 due to healthcare frauds and errors. These losses are ultimately born by the insurers and put a question mark on the sustainability of the entire system. In today’s scenario, with cutthroat competition, all the stakeholders of the healthcare insurance segment are facing the issues of trust, transparency, privacy, security, disputes and dissatisfaction more than ever.

7.4.2 Blockchain 3.0 for health insurance system Table 7.3 mentions the typical pain points of health insurance system. Blockchain has all the technological extensions to add lot of value to the entire insurance process chain. It can help remove the bottlenecks aroused out of non-standardization and non-interoperability for seamless data integration across industry. A blockchainbased solution can help automate the complex information flow between different stakeholders. A decentralized distributed blockchain network and cryptographic hash help promote integrity and security while digital signatures and consensus ensure privacy, trust and transparency. A smart contract can maintain an up-todate data depository of dishonest and fake parties by collecting the evidences from all insurers which can be accessed by everyone. This will help reduce frauds and invalid insurance claim by resubmitting claims with many parties, fake identities, false bills and reports and so on. Blockchain smart contracts removes intermediaries from the system and help automating claim settlement process in real time. It fetches all the information from the blockchain ledger like policy terms, tariffs and agreement and ensures that same data is accessed by all the stakeholders thus removes errors or false information. An agreed on predefined claim settlement logics are embedded in the form of a program

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Table 7.3: Blockchain value addition to the existing healthcare insurance system. Pain points and challenge

Blockchain solutions

Lots of manual efforts are involved in claim verification that result in delay and customer dissatisfaction.

Smart contracts can automate the entire end-toend process and claim can be settled in real time without manual intervention

There is always a threat of theft or compromise of policy data stored on central server.

Blockchain’s distributed ledger technology (DLT) and cryptographic hash ensure data integrity and security.

Current system demands a lot of paperwork which is prone to manipulation and accidental errors.

All nodes share the same copy of data. If a data gets changed accidently or intentionally then every node knows it immediately.

Claim settlement requires intermediaries and complex exchange of lot of data.

Interoperability and smart contracts automates entire process and removes intermediaries from the system.

Privacy of the patient’s data is a big challenge.

Blockchain uses digital signature to maintain the privacy and stills haring the data.

which gets executed as soon as the set condition is met. These built-in business rules ensure proper claim settlement in time while maintaining the regulatory compliances and audit reports [25]. Manual efforts of TPAs and underwriters, delay in information access and validation and unnecessary disputes can be resolved automatically in an accountable manner as shown in Figure 7.4.

Figure 7.4: Blockchain-based process flow for healthcare insurance.

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7.4.3 Policy underwriting and claim processing using smart contracts Healthcare insurance segment is evolving fast and adapting digitization for better customer satisfaction and revenue management. Lot of business rules can be embedded in the smart contracts to better manage and record the transactions to the blockchain network [26]. The entire underwriting process can be more transparent, false proof and efficient. Let us now look at the step-by-step process: – Smart contracts can help electronic submission of policy documents along with medical history. Specific policy terms and loading /limits can automatically be set as agreed between parties. – Once the submitted documents are auto-verified, the invoice is raised for the premium payment. – Premium can be made auto-deductible at certain due date. Once it is done, policy documents, network hospitals list and specific terms/conditions become immutable and are made available to all the stakeholders. – Claim submission can be automated to raise a claim request. Once all documents like claim form, bills, reports and so on are submitted, it can be recommended by an authorized doctor. Smart contract ensures the genuineness of the submitted data through seamless integration of all the records from all the stakeholders. – Once the claim is approved by the approver and all conditions in the contract are met, it gets executed automatically and the amount is transferred to the beneficiary account. – All the relevant information, including deductions and so on, are received by the insured person and, if required, a request for the reconsideration can be submitted.

7.4.4 Fraud detection using smart contracts Due to the fake claims and frauds, insurance companies lose a major chunk of their revenue, approximately 8.5%. The current operational mechanism and data management system does not allow a fraud claim to be identified easily. The main reason is that each company maintains its own data and avoids sharing it for different reasons. There are many different types of frauds such as phantom policies, overstatement and claiming of uncovered illnesses. A smart contract-based blockchain system can really be effective in managing frauds [27]. The following system can be useful: – A consortium of the insurance companies assigns a smart contract to each service provider. The smart contract address becomes an identity and is used to uniquely identify a particular service provider.

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– Different insurers give ratings to different service providers and smart contracts manage all these in the blockchain ledger which cannot be tempered with. Also, this is available to all the consortium members for view purpose. – If the aggregated rating points fall beyond a certain value for a provider, then it is blacklisted and is not allowed to do business further. This fact along with the statistics is made available to all the participating consortium members. – The smart contracts have built-in facility to modify the rating and restore the blacklisted provider if all the consortium members reach to a consensus for the same. Frauds can also be limited by authenticating the agents and tracking their history. At present, we do not have an integrated system in place that keeps track of agents involved in misconducts and frauds. A blockchain with smart contract can help achieve transparency and trust for an agent as below: – Agents’ registration on a consortium blockchain can be made mandatory. Whenever an agent gets registered on the network, an account is created and the hash becomes the unique identifier for that agent. – Customers as well as insurer both can assign rating to the agent through their respective accounts using smart contracts. – If anybody wants to see the rating of an agent, a smart contract is executed and the rating is fetched.

7.4.5 Example use cases Healthcare insurance segment is a very critical area that can add a lot of value to the sustainability of entire healthcare ecosystem and smart contracts has a real potential to transform this [28]. However, till date, very limited prototypes or proof of concepts (PoC) have been deployed, even for experimental purpose. MIStore is a blockchain-based medical insurance application [29]. It aims at helping the industry with genuine immutable data that is stored in an encrypted fashion on network. MIStore protocol consists of record nodes and light nodes. Record nodes maintain and store the entire blockchain, and uses PBFT consensus protocol for adding correct block to the chain. Each light node stores only block headers. It was implemented on Ethereum and uses its embedded signature scheme ECDSA with the secp256k1 elliptic curve for signing messages. Culver proposed a smart contract-based blockchain solution that implements FHIR standard [30]. It proposed the use of APIs for real-time claim settlement and suggested to form a consortium to facilitate smart contract based operations and push deployments. Service providers, beneficiary and government, everybody should be part of this to take decision regarding standardization, policy and regulatory issues.

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Nukala et al. developed a working model that provides transparency and data integrity using blockchain-based decentralized environment to handle big data. They used the concept of interoperability across different applications in same framework using IPFS [31].

7.5 Clinical trials Clinical trials cover a broad range of research that involve numerous stakeholders to test the efficacy and safety of new treatments. The process involves trial protocol design and registration, patient enrolment and engagement, data collection and analysis, data sharing and management, and report generation and publication of results [32]. Blockchain can significantly speed up the trial process and improve sustainability by directly authorizing various actors to control the data in a better and greater manner, and embed the trust in the entire trial chain.

7.5.1 Challenges for sustainable clinical trials In a clinical trial process, many stakeholders are involved with different kind of investments, interests and commitments. It generates a complicated and huge amount of data trail and managing this in an effective and efficient manner is the biggest challenge for the sustainability of trials. Clinical trials are susceptible to intentional as well as unintentional errors and data misrepresentation [33], and quite often do not follow the defined steps and/or may record incorrect data related to cases [34]. Lot of funds and efforts go in vain due to poor data analytics, poorly designed trial, publication bias and manipulations of the results. Patient recruitment and retention is most important but most challenging factor for the success of the clinical research [35, 36]. About 86% of clinical trials find it difficult to achieve their enrolment goals on time and 19% of trials were forced to closed or terminated due to poor enrolment. Patient recruitment consumes approximately 30–35% of the budgets, especially at phases II and III, and enrolment failure is reflected in inadequate research outcome, premature trial termination, waste of funds and could double the planned recruitment period [37].

7.5.2 Blockchain 3.0 for clinical trial Table 7.4 states the typical challenges of existing clinical trial process and how blockchain can help in this. Protecting the data, ensuring privacy, integrity, provenance, immutability, traceability and, at the same time, sharing it amongst all the stakeholders in a transparent, trustworthy and automated manner can be addressed

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best by deploying entire clinical trials process onto the blockchain and makes the entire process sustainable [38]. Benchaufi et al. explained how blockchain can be used at every step of trials to make it more sustainable, starting from trial setup, patient enrolment, data collection, trial monitoring, data analysis and publication of results [32]. After designing the trial and consent protocol, before trial starts, regulatory and business rules are programmed into smart contracts and deploy it on to blockchain [39]. Information regarding how the data is to be collated, timeline of occurrence of different events and many other important data can be stored in metadata of blockchain. A blockchain-based setup can assure integrity and secrecy of the data. It helps delegating complete control of the data to the patients who can share it in finely tuned manner and even revoke sharing. It helps building trust and patients are encouraged to share the data for clinical trials [40]. It empowers researchers as well as patients with secure data sharing, ensured privacy and controlling consents for different trials [41]. Table 7.4: Blockchain value addition to the existing clinical trial system. Pain points and challenges

Blockchain solutions

Trial design and consent protocols get deviated during field implementation.

Smart contract-based DApps can help verifying that protocol complies with the regulatory code during the entire cycle.

Patient enrolment and matching is tough and Blockchain provides anonymity and privacy to the has scope for manipulation. patients’ enrolment and smart contract can be used for inclusion/exclusion criteria. Trial volunteers are apprehensive of data collection procedure, its security and usage.

Blockchain transaction data is immutable and always updated. Patient can control data sharing and security with private key.

Errors in data interpretation and research misconduct may be disastrous.

Blockchain consensus algorithm ensures data integrity and DLT can help tracing the origin of data.

Selective reporting and difficulties in collaborative research.

Blockchain trial data is timestamped, transparent and trustful. DApps can help collaborative research with accountability.

Many people have apprehension regarding the use of consent form. This issue can be well addressed by blockchain, wherein a confirmed consent form can be stored as a transaction on the network [42]. Different versions of the consents are linked sequentially, and the latest in the chain is considered for the trial. Inclusion/exclusion protocol can be inserted into a smart contract only by a competent authority like FDA. Eligible party, like sponsors, can send a request to the smart contract for appropriate subjects matching based on genetic, demographic, therapeutic and geographic distribution. Once the eligible subjects are identified, trial process can move

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on with randomization without even knowing the patient’s name. The smart contract can also ensure that the trial is legal, sponsors are reliable and whether the trial is approved or not by the relevant authority [43]. Blockchain can also be used to develop public registries for the speedy disclosure of clinical trial results. Real-time access of this central repository by all stakeholders involved can help reduce trial timeline. It can also help carrying out virtual trials without a centralized trial center.

7.5.3 Example use cases BlockTrial is a smart contract-based trial PoC using Ethereum Blockchain [44]. It contains a patient smart contract (Patient SC) for patient enrolment and permission recording, and a researcher smart contract (Researcher SC) for automatically querying the clinical trial database. All the queries are automatically filtered and fired using smart contracts for registered users according to set permissions. Zhuang et al. proposed a private Ethereum-based model that has got multiple trial-based contracts for patient engagement and trial monitoring [42]. It also has a master smart contract which helps in subject matching, enrolment of patients and trialbased contracts management. To improve the trial performance, four new parallel and distributed components were developed to supplement the core blockchain [45]. These models were meant for diversified collaborative research and include big data analytics, data integration, identity management, privacy protection of Internet of things (IoT) devices and data sharing tools. Choudhury et al. shared a permissioned blockchain with smart contract-based data management framework to automate the administrative tasks and maintain integrity and privacy of data for multisite clinical trials [46]. A very interesting process flow for consent management was proposed on top of clinical trial procedure [32]. They suggested that consent forms are timestamped to manage sequence and smart contracts can be used for enrollment. They illustrated that a master record can contain a proof of existence of the complete consent–collection cycle which can be verified from Internet websites. Wong et al. developed a blockchain prototype for governing and managing the data of a trial. They explained through simulation that cryptographic hash attached with a transaction ensures the security of the data. Also, simulation shows that integrity can be verified even without checking the contents of each file [47]. Similar approach was adopted by Nugent et al. and they showed how blockchain provides an immutable record of a trial history and how it helps getting rid of data manipulation [48].

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7.6 Pharma supply chain management Managing the supply chain, for any industry, is a complex process but effectively managing healthcare supply chain gets complicated by many folds as it directly impacts the lives of the people. It is an n-tier system with flow of data, revenue and drugs from multiple entities starting from manufacturer, distributors, logistics, hospitals, retailers, patients and so on. For example, the USA alone imports approximately 40% of the drugs and 80% of drug manufacturing ingredients from abroad and in 2018 alone has recorded 1,750 cases of counterfeit drugs.

7.6.1 Blockchain 3.0 for pharma supply chain Table 7.5 explains the problems with the existing pharma supply chain and how blockchain can provide a solution for the same. Core feature of blockchain ensures provenance and helps in complete end-to-end tracking of the manufacturing, distribution and consume. It streamlines operations, reduces cost, improves traceability and adds to the sustainability of all the stakeholders. Table 7.5: Blockchain value addition to the pharma supply chain system. Pain points and challenge

Blockchain solutions

Industry is struggling with counterfeit drugs, theft and hoarding issues.

Blockchain can help assigning cryptographic identity to drugs which is verifiable by everybody and fixes accountability.

Figuring out the safety, origin and manufacturing process of a drug is a very difficult task.

Blockchain inherently adds provenance, immutability and visibility at every stage.

Too much and very strict compliances from many different regulators at many stages.

Blockchain . DApps based smart contracts help automating the tasks and raising flags.

Many of the medicines with good selling require cold chain shipping which is prone to manipulation.

Blockchain with Internet of things, machine learning and analytics makes entire cold chain data available in real time with an auto-analysis.

Pharma is a global business but sending consignments and payments across borders is complicated.

Block chain is proven to be a financial tool and smart contracts can help resolve conflicts and generate trust and transparency.

The fundamental concept is very simple and remains the same. A new hash is associated with each product, may be in the form of QR code, and is registered on blockchain network. This product becomes a digital asset on the network and with the help of IoT and other technology its complete movement is recorded as transactions;

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and is traceable and accessible as per set rules. Additional information related to the product can be stored as off-chain or on-chain data depending on the requirement and performance issues.

7.6.2 Example use cases In order to improve the security and delivery of the pharma products, Xie et al. proposed a blockchain mechanism [49]. The smart contract based system uses proof of authority and offers real time visibility of the supply chain data on the blockchain network. Molina et al. also proposed a framework to trace drugs in real time and manage the supply chain efficiently [50]. Each node can track the drugs and check for the delivery status. Kumar and Tripathi used an interesting QR code-based blockchain solution to deal with the counterfeiting of drugs. It helps ensuring the delivery of medicines to the end user [51]. Drugledger is a blockchain network that is aimed at improving the traceability of drugs in the supply chain [36]. It makes use of service-oriented architecture which is considered to be better than P2P network. It also suggests the data storage methods and makes entire drug supply chain efficient. CounterChain was designed to deal with counterfeiting of the drugs in the industry [52]. It connects produces, transporter, supplier, retailers and so on and helps improving trust amongst them. It enhances visibility of drug at any point of time. Drug supply chain management and recommendation system is a very interesting framework [53]. Different users have been provided with the front-end client to interact and log transactions in the blockchain network. Client app communicates with the blockchain network using Hyper-ledger REST server composer. Differential access is provided with access control rules and smart contracts. Framework uses a data storage pool for off-chain storing of all transactions. This pool is mined using AI technologies to provide recommendations regarding most appropriate drugs to the user.

7.7 Conclusion Blockchain is a foundation technology in the sense that it has the potential to revolutionize the entire healthcare ecosystem toward better sustainability. While it holds the promise of doing things differently, it also offers a lot of new things to do. It addresses the most painful points and provides trust, transparency and traceability in the most effective fashion. While usage in cryptocurrencies and financial segment has been proved transformative, the healthcare segment is yet to witness a full-scale solution. Though many frameworks and experimental PoC are available, the adoption is expected to be gradual.

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There are many challenges at the technological front as well. With huge amount of data, there are issues with storage and speed. The biggest advantage, that is, immutability, is the biggest disadvantage as well. With permissioned or private blockchain, the security and manipulation cannot be ruled out. It is anticipated that emerging and innovative computing technologies and will improve speed and security. However, simply deploying a blockchain-based technological solution is not enough, we need to ensure active participation of each stakeholder in the network. It is a data-driven immutable system and so the correctness and genuineness of the data at the very first place is important for system to evolve further and be trustworthy. Apart from solution provider, the role of regulatory bodies and common man is very crucial. IEEE SA is actively involved in educating and driving adoption of emerging technologies for pharmaceutical value chain, and IEEE P2418.6 deals especially with blockchain for health and life sciences.

References [1]

Taavi, E., 2018, Blockchain and healthcare: The Estonian experience, 2018, https://e-estonia. com/blockchain-healthcare-estonian-experience/ [2] Satoshi, N., Bitcoin: A Peer-to-Peer Electronic Cash System, 2008, https://bitcoin.org/bit coin.pdf [3] Kuo, T.-T., Kim, H.-E., Ohno-Machado, L. (2017). Blockchain distributed ledger technologies for biomedical and healthcare applications. Journal of the American Medical Informatics Association, 24(6), 1211–1220. [4] Zheng, Z., Xie, S., Dai, H., Chen, X., Wang, H. “An overview of blockchain technology: Architecture, consensus,and future trends.” In 2017 IEEE International Congress on Big Data (BigData Congress), 557–564. IEEE, 2017. [5] Iansiti, M., Lakhani, K.R. (2017). The truth about blockchain. Harvard Business Review, 95(1), 118–127. [6] Banerjee, M., Lee, J., Raymond Choo, K.-K. (2018). A blockchain future for internet of things security: A position paper. Digital Communications and Networks, 4(3), 149–160. [7] Dwivedi, A.D., Srivastava, G., Dhar, S., Singh, R. (2019). A decentralized privacy-preserving healthcare blockchain for IoT. Sensors, 19(2), 326. [8] Morabito, V. (2017). Smart Contracts and Licensing. In: Business Innovation Through Blockchain, 101–124. Springer. [9] Toshendra, K.S. (2019), Best 5 Blockchain-Based Smart Contract Platforms, https://www. blockchain-council.org/blockchain/best-5-blockchain-based-smart-contract-platforms/ [10] Ray, P.P., Dash, D., Salah, K., Kumar, N. (2020). Blockchain for IoT-based healthcare: Background, consensus, platforms, and use cases. IEEE Systems Journal, 15(1), 85–94, doi: 10.1109/JSYST.2020.2963840. [11] Swan, M. Blockchain: Blueprint for a new economy. ” O’Reilly Media, Inc.”, 2015. [12] Zhang, S., Lee, J.-H. (2020). Analysis of the main consensus protocols of blockchain. ICT Express, 6(2), June 2020 93–97. https://reader.elsevier.com/reader/sd/pii/ S240595951930164X?token=DB758040A0B8119E1E6EA32C8842746373A104BBCE D467E215070674896F893EC1C1AB8224B27F09734E599B10D5594B.

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[13] Engelhardt, M.A. (2017). Hitching healthcare to the chain: An introduction to blockchain technology in the healthcare sector. Technology Innovation Management Review, 7, 22–34. [14] Rawal, V., Mascarenhas, P., Shah, M., Kondaka, S.S. (2017). White Paper: Blockchain for Healthcare an Opportunity to Address Many Complex Challenges in Healthcare, Princeton, NJ, USA: CitiusTech. [15] Zhou, Y., Ancker, J.S., Upadhye, M., Mc Geor Ge, N.M., Guarrera, T.K., Hegde, S. et al. (2013). The impa ct of interoperability of e lectronic hea lth records on ambulator y phys ic ian practices: A discrete-event simulation study. Informatics in Primary Care, 21, 21–29. [16] Mackey, T.K., Kuo, T.T., Gummadi, B., Clauson, K.A., Church, G., Grishin, D., Obbad, K., Barkovich, R., Palombini, M. (2019). ‘Fit-for-purpose?’ – Challenges and opportunities for applications of blockchain technology in the future of healthcare. BMC Medicine, 17, 68. [17] Kuo, T.-T., Ohno-Machado., L. ”Modelchain: Decentralized privacy-preserving healthcare predictive modeling framework on private blockchain networks.” arXiv preprint arXiv:1802.01746 (2018). [18] Azaria, A., Ekblaw, A., Vieira, T., Lippman, A. ”Medrec: Using Blockchain for Medical Data Access and Permission Management.” In 2016 2nd International Conference on Open and Big Data (OBD), 25–30. IEEE, 2016. [19] Fan, K., Wang, S., Ren, Y., Li, H., Yang, Y. (2018). Medblock: Efficient and secure medical data sharing via blockchain. Journal of Medical Systems, 42(8), 136. Doi: 10.1007/s10916-0180993-7. [20] Jiang, S., Cao, J., Wu, H., Yang, Y., Ma, M., He, J.: BlocHIE: a blockchain-based platform for healthcare information exchange. In: IEEE International Conference on Smart Computing (SMARTCOMP), 49–56. IEEE (2018) [21] Zhang, P., White, J., Schmidt, D.C., Lenz, G., Rosenbloom, S.T. (2018). FHIRChain: Applying blockchain to securely and scalably share clinical data. Computational and Structural Biotechnology Journal, 16, 267–278. Doi: 10.1016/j.csbj.2018.07.004. [22] Brodersen, C., Kalis, B., Leong, C., Mitchell, E., Pupo, E., Truscott, A., Blockchain: Securing a New Health Interoperability Experience,(2016),http://www.truevaluemetrics.org/DBpdfs/Tech nology/Blockchain/2-49-accenture_onc_blockchain_challenge_response_august8_final.pdf [23] Kaur, H., Alam, M.A., Jameel, R., Mourya, A.K., Chang, V. (2018). A proposed solution and future direction for blockchain-based heterogeneous medicare data in cloud environment. Journal of medical systems, 42, 156. [24] Park, J., Park, J. (2017). Blockchain security in cloud computing: Use cases, challenges, and solutions. Symmetry, 9(8), 164. [25] Miliard, M. (2017). Blockchain’s potential use cases for healthcare: hype or realit y? Retrieved from http://www.healthcareitnews.com/news/blockchains-potential-use-cases-healthcarehype-or-reality?mkttok=eyJpIjoiTnpBM05XVXlPR0kzWXpZMyIsInQiOiJMYU1TWHZdU VYUCs3SjdKQU9sQURhT3kzY3ZFSFl0Z1dmdmJ6TWMrREdwSXhkZUcrZmRLeWFjNmNtU TAwZGdzT0pYa21KNmcyenVJdlA1VXd1YlB4MGU2RFVzM2F2bzJ5K1BRUjNTRVwvbkVqSVp TYVJpc3ZaVXRoVlwvcjhCNW96In0%3D [26] Christidis, K., Devetsikiotis, M. (2016). Blockchains and smartcontracts for the internet of things. IEEE Access, 4, 22922303. [27] Saldamli, G., Reddy, V., Bojja, K.S., Gururaja, M.K., Doddaveerappa, Y., Tawalbeh, L., “Health care insurance fraud detection using blockchain,” 2020 Seventh International Conference on Software Defined Systems (SDS), Paris, France, 2020, 145–152, doi: 10.1109/ SDS49854.2020.9143900. [28] Gatteschi, V., Lamberti, F., Claudio, D., Víctor, S.: Blockchain and smart contracts for insurance: Is the technology mature enough?, February 2018.

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[29] Zhou, L., Wang, L., Sun, Y. (2018). MIStore: A blockchain-based medical insurance storage system. Journal of Medical Systems, 42(8), 149. [30] Culver, K. (2016). Blockchain Technologies: A Whitepaper Discussing How the Claims Process Can Be Improved. https://www.healthit.gov/sites/default/files/3-47-whitepaperblockchain forclaims_v10.pdf, 2020-08-05. [31] Nukala, P.V.S., Pallav, K.B., Sathya, S.M., Phani, K.K. (2018, Oct). Use of blockchain technology in integrating heath insurance company and hospital. International Journal of Scientific & Engineering Research, 9(10). [32] Benchoufi, M., Ravaud, P. (2017, Dec, 19). Blockchain technology for improving clinical research quality. Trials, 18(1), 335. Doi: 10.1186/s13063-017-2035z. https://trialsjournal.bio medcentral.com/articles/10.1186/s13063-017-2035–z. [33] George, S.L., Buyse, M. (2015). Data fraud in clinical trials. Clinical investigation, 5, 161–173. Doi: 10.4155/cli.14.116 25729561. [34] Romano, C.A., Nair, S., Delphin, E.S. (2018). A retrospective analysis of clinical research misconduct using fda-issued warning letters and clinical investigator inspection list from 2010 to 2014. Anesthesia and Analgesia, 126, 976–982. Doi: 10.1213/ANE.0000000000002694 29239950. [35] Furlong, E.M.J.R.P., Bull, G.U.J. (2016). Barriers to Clinical Trial Recruitment and Possible Solutions: A Stakeholder Survey, 25(2/3), 20–25. [36] Huang, G.D., Bull, J., McKee, K.J., Mahon, E., Harper, B., Roberts, J.N. (2018). Clinical trials recruitment planning: A proposed framework from the Clinical Trials Transformation Initiative, 66, 74–79. [37] Mahon, E., Roberts, J., Furlong, P., Uhlenbrauck, G., Bull, J. (2015). Barriers to clinical trial recruitment and possible solutions: A stakeholder survey. Applied Clinical Trials, 24. [38] Leeza, O. (2019). Blockchain’s potential to improve clinical trials – an essay by Leeza Osipenko. British Medical Journal, 367. l5561. Doi: 10.1136/bmj.l5561. (Published 3 October 2019). [39] Chan, A.W., Tetzlaff, J.M., Altman, D.G., Dickersin, K., Moher, D. (2013). Spirit 2013: New guidance for content of clinical trial protocols. Lancet, 381(9861), 91–92. [40] Sandve, G.K., Nekrutenko, A., Taylor, J., Hovig, E. (2013). Ten simple rules for reproducible computational research. PLoS Computational Biology, 9(10), e1003285. [41] Irving, G., Holden, J. (2016). How blockchain-timestamped protocols could improve the trustworthiness of medical science [version 1; referees: 2 approved]. F1000 Research, 5, 222. [42] Myles, P.S., Williamson, E., Oakley, J. et al. (2014). Ethical and scientific considerations for patient enrollment into concurrent clinical trials. Trials, 15, 470. Doi: 10.1186/1745-6215-15-470. [43] Zhuang, Y., Sheets, L.R., Shae, Z., Chen, Y.W., Tsai, J.J.P., Shyu, C.R. (2020). Applying blockchain technology to enhance clinical trial recruitment. AMIA Annual Symposium proceedings, 2019, 1276–1285. Published 2020 Mar 4. [44] Maslove, D.M., Klein, J., Brohman, K., Martin, P. (2018). Using blockchain technology to manage clinical trials data: a proof-of-concept study. JMIR Medical Informatics, 6(4), e11949. Published 2018 Dec 21 Doi: 10.2196/11949. [45] Shae, Tsai, J.J.P., “On the Design of a Blockchain Platform for Clinical Trial and Precision Medicine,” 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS), Atlanta, GA, 2017, 1972–1980, Doi: 10.1109/ICDCS.2017.61 [46] Choudhury, O., Fairoza, N., Sylla, I., Das, A. (2019). A Blockchain Framework for Managing and Monitoring Data in Multi-Site Clinical Trials. [47] Wong, D.R., Bhattacharya, S., Butte, A.J. (2019). Prototype of running clinical trials in an untrustworthy environment using blockchain. Nature Communications, 10, 917. Doi: 10.1038/ s41467-019-08874-y 30796226.

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[48] Nugent, T., Upton, D., Cimpoesu, M. (2016). Improving data transparency in clinical trials using blockchain smart contracts. F1000Res, 5, 2541. Doi: 10.12688/f1000research.9756.1 28357041. [49] Xie, W., Wang, B., Ye, Z., Wu, W., You, J., Zhou, Q. Simulation-based Blockchain Design to Secure Biopharmaceutical Supply Chain. In Proceedings of the 2019 Winter Simulation Conference (WSC), National Harbor, MD, USA, 8–11 December 2019; 797–808 [50] Molina, J.C., Delgado, D.T., Tarazona, G. Using Blockchain for Traceability in the Drug Supply Chain. In Proceedings of the International Conference on Knowledge Management in Organizations, Zamora, Spain, 15–18 July 2019; Springer: Berlin, Germany, 2019; 536–548 [51] Kumar, R., Tripathi, R. Traceability of counterfeit medicine supply chain through Blockchain. In Proceedings of the 2019 11th International Conference on Communication Systems & Networks (COMSNETS), Bengaluru, India, 7–11 January 2019; 568–570 [52] Chitre, M., Sapkal, S., Adhikari, A., Mulla, S. Monitoring counterfeit drugs using counterchain. In Proceedings of the 2019 International Conference on Advances in Computing, Communication and Control (ICAC3), Mumbai, India, 20–21 December 2019; 1–6 [53] Abbas, K., Muhammad, A., Ahmed Khan, T., Song, W.-C. (2020). A blockchain and machine learning-based drug supply chain management and recommendation system for smart pharmaceutical industry. Electronics, 9, 852. Doi: 10.3390/electronics9050852.

Dipesh Vaya, Teena Hadpawat

Chapter 8 Enhanced fingerprint authentication using blockchain Abstract: Authentication is a major issue nowadays. Fingerprint authentication plays a vital role in the security industry. Blockchain has various benefits such as decentralization and persistency. A major wing of blockchain is its limitless applications in the field of financial industry, risk management, cryptocurrency and security. In this chapter, we propose an approach of secured automatic log-in based on fingerprint authentication. The security is enhanced using blockchain technology in three steps: in the first step, the user is authenticated using fingerprint verification; the second step includes the development of application software SDK; finally, security is enhanced using blockchain technology. Keywords: blockchain, authentication, fingerprint, security, sidechain

8.1 Introduction At present, we are more dependent on passwords for security and authentication. But how much a password is secured depends on the person’s ability to make a password complex enough so that no one can guess it. Password prepared with the combination of first name and date of birth can be guessed by any hacker, so one should avoid this type of practice while choosing any password. But still we cannot be sure that everyone will create or choose a complex phrase for the password. The need for a more complex but easy mechanism is getting high day by day to ensure the security of data. With the technical advancements in the field of biometric security, authentication using fingerprints is used widely in every field. When authentication is a major aspect of any security system, then we have to be more precise about the security of PINs and passwords. We can take the example of the banking sector. A locker at the bank secured with a security PIN can be opened easily by electrical shock or using a PIN stolen by any other person. The proposed method of authentication can remove this type of security threats using enhanced fingerprint authentication using blockchain.

Dipesh Vaya, S.S. College of Engineering, Udaipur, India, e-mail: [email protected] Teena Hadpawat, Rajasthan Technical University, Kota, India, e-mail: [email protected] https://doi.org/10.1515/9783110702507-008

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At present, we are surrounded by many Internet-of-things (IoT)-enabled devices that send and share a massive amount of data. Sometimes these data contain important information like passwords and other authentication-related information. To handle these large amount of data, big data came into existence and now to secure the data we are using blockchain technology for providing a secure platform that uses fingerprint recognition-based authentication using any personal devices like personal computer, tablet, laptop or mobile, which have a fingerprint recognition unit either attached to or embedded to the device. Blockchain provides a more secure way for operations related to transactions and secure communications as it is based on distributed terminology along with an encryption-based storage facility. Thus, the authors are proposing an enhanced fingerprint-based authentication using blockchain. Fingerprints for authentication can be taken through the user’s mobile or laptop having supporting hardware for recognizing fingerprints and using blockchain and sidechain technologies. This chapter focuses on designing robust and “enhanced fingerprint authentication using blockchain” which handles the security vulnerabilities while transferring information in transaction-based operations.

8.2 Related research Various researchers are working in the authentication-based blockchain method for proving a secure and safe way of communication. Schutzer et al. [1] say that blockchain gives a strong sense of security because blockchain proved itself as a cybersecurity solution, which is robust, sustainable and feasible to implement. Blockchain enables decentralization of the communication or data storage. Instead of storing the secret information in a single repository, data are stored at different interlinked computers. Kestenbaum et al. [2] say that saving identical information at various interlinked computers helps us to deal with security breaches when an attacker tries to update the information at one computer in an unauthorized way. The other computer from the network can be used to restore the unusual changes made by the attacker. The most common application of blockchain is Bitcoin and Open Bazaar, where account details of users are never stored in a central database. Decentralized arrangement of information makes it very difficult to access to user wallet without having a security key. If the hacker gets the key unfortunately, even then he/she will not be able to hack anything due to multiple signature mechanisms [3]. We all are abiding by various norms of the government and also submit our important and private information to the various departments of administration such as passport office, airports, and banks. All this information is prone to steal by any hacker. Even we are submitting our personal information to various private companies too. Hence, data security is the most important aspect to discuss and work upon these days [4].

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According to Seth et al. [5], blockchain makes the security full proof by isolating personal data from the server that handles transactions. In a blockchain, any personal data can be viewed after proper authorization. The working of blockchain can be depicted in Figure 8.1. This diagram shows the working terminology of blockchain technology. When multiple parties are involved in a transaction, then information of the new transaction is broadcasted on the network. This transaction is then noted by all the participating parties. And a unique block is prepared. After encrypting these blocks, a hash is generated. Records at all parties are updated according to the newly generated block as shown in Figure 8.1.

Figure 8.1: Working terminology of blockchain.

Along with blockchain, the concept of sidechain is also important to understand before moving forward. Sidechain provides improvements in terms of scalability of performance over the blockchain. The sidechain can be thought of as additional blocks. These additional blocks allow an user to do transactions within the tokens of the main chain. Hence, sidechains improvise the functionality of the main chain without compromising on security [6, 7]. Bahga et al. [8] proposed a platform that constructs a peer-to-peer network and removes trusted intermediaries based on blockchain techniques for industrial IoT. In 2016, Christidis et al. [9] researched the feasibility of smart contracts in IoT systems along with some of the blockchain. Xia et al. [10] studied the concept of controlling, auditing, sharing and provenancing of shared medical data in cloud-based applications. The author researched on providing a trustless medical data sharing scheme. Pawade et al. [11] in their research work proposed secure online voting system using biometric and blockchain, which ensures that only a verified person can cast the vote. Instead of using a fingerprint, they used an iris recognition system with 81.11% of average accuracy rate. In another research, Pawade et al. [12] used blockchain for securing biometric data and implemented a secure authentication system based on fingerprint biometric. Their implantation includes storing biometric information on blockchain in the form of feature vectors after hashing. The accuracy of the system obtained was 82.55%, and the error rate was 17.48%.

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8.3 Implementation overview Process of enhanced fingerprint authentication using blockchain is implemented in three steps: authentication using fingerprint verification, development of application software SDK and use of blockchain technology for enhancing the security.

8.3.1 Authentication using fingerprint verification and application of blockchain This step includes two major steps: first is the registration phase and the second one is the authentication (login) phase.

8.3.1.1 Registration phase This is a traditional phase of any authentication-based system, where an user has to register himself/herself for the first time and provides certain personal details. And the same information is used to authenticate the user at the time of login. At the time of registration, unique information like mobile number or Aadhaar number is taken from every user along with his/her fingerprint. With the combination of extracted features of fingerprint and Aadhaar number, an UID is created and pushed to a blockchain. The user’s fingerprint is also uploaded on the sidechain against the blockchain of UID. Hence, there will be two blockchains: the main blockchain contains blocks for UID, and a sidechain contains blocks for extracted features of the fingerprint. At the time of registration, it is also checked whether the entered Aadhaar number already exists or not. If the Aadhaar number is already registered, then the user is taken to the registration page again with an error message: User already exists.

8.3.1.2 Authentication phase In the authentication phase, the user’s unique information like mobile number or Aadhaar number and fingerprint are used to create an UID and it will be checked for validation. If UID is not present in the system, the user will be redirected to the registration page. On successful validation, the user will be asked to give a fingerprint impression again on a mobile device. Extracted fingerprint features will now be compared with the fingerprint uploaded on the sidechain at the time of the registration phase. Based on a high similarity score, all details of the user will be accessible from the blockchain and visible on the screen. On less matching, an user will be asked to rescan his/her finger. The complete process of registration and authentication can be depicted in Figures 8.2 and 8.3, respectively.

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Figure 8.2: Registration process.

Figure 8.3: Authentication phase.

8.3.2 Development of application software Application software is required for the smooth functionality and proper mobility of the authentication system. For this purpose, many open-source platforms and technologies are available to use. For a web browser-based authentication application program chromium web browser can be used which is available for free. According to Huh et al. [13] for developing it for the mobile user, chromium can be used with GN build and android SDK 23 or SDK 24. For feature extraction from fingerprints, various efficient methods and processes are available. The process depicted in Figure 8.4 can be used for extracting features.

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Figure 8.4: Process to extract features of the fingerprint.

8.3.3 Use of blockchain server for security The implementation of the blockchain contains the communication that can be handled by socket programming. JavaScript Object Notation (JSON) forms can be designed for data collection and data transfers. The system will add a new block in the blockchain whenever a new user is added through registration. Fingerprints are pushed in the sidechain and Unique Identification (UID) is pushed in the main chain and initial proofing of work is done. Proof of work is performed by the miner to allow the system to create a new block on the blockchain. Secure Sockets Layer (SSL) communication and encryption at the server ensures security through Korea Internet & Security Agency (KISA) seed 128 modules. After the successful registration process, all nodes available in the blockchain are notified about the content available. In turn, all nodes will verify the proof of work for its validity. And finally, the new block is added as the last block in the blockchain.

8.4 Conclusion and future scope Blockchain has proved itself as a safe and secure method for a mode of communication in banking and finance and by adding the sense of biometric. The application of blockchain can be enhanced in terms of authenticity and trustworthiness. In the process, we discussed the inclusion of biometric features contained by sidechain and UID or user information in the main blockchain. The use of a sidechain for user authentication is also discussed. The accuracy of the system depends on the algorithm used to extract the features from the fingerprint and also on the matching process. For making the overall process more secure, we can use a combination of two or more biometric security features such as palm print, facial expressions, and iris.

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References [1]

Schutzer, D. (2016) CTO corner: what is a Blockchain and why is it important? FS Round table. Retrieved from http://fsroundtable.org/cto-corner-what-is-a-blockchainand-why-is-it-important/. [2] Kestenbaum, R. (2017) Why bitcoin is important for your business. Forbes. Retrieved from https://www.forbes.com/sites/richardkestenbaum/2017/03/14/why-bitcoinis-important-foryour-business/3/#2da6d4c72b3b. [3] Young, J. (2016) Hackers eye e-commerce platforms, bitcoin-based OpenBazaar to capitalize. The Cointelegraph. Retrieved from https://cointelegraph.com/news/hackerseye-e-commerce -platforms-bitcoin-based-openbazaar-to-capitalize. [4] Kshetri, N. (2014). Big data’s impact on privacy, security and consumer welfare. Telecommunications Policy, 38, 1134–1145. [5] Seth, S. (2017) Banks need to be centralized – could blockchain be the answer? Finance Magnates. http://www.financemagnates.com/cryptocurrency/bloggers/banksneedcentralized-blockchainanswer/. [6] https://www.e-spincorp.com/2017/11/24/pros-and-cons-of-blockchain-technology/ [7] Alex, N., designing a smart-contract application layer for transacting decentralized autonomous organizations, In International Conference on Advances in Computing and Data Sciences (2016). [8] Bahga, A., Madisetti, V.K. (2016). Blockchain platform for industrial internet of things. Journal of Software Engineering and Applications, 9(10), 533–546. [9] Christidis, K., Devetsikiotis, M. (2016). Blockchains and smart contracts for the internet of things. IEEE Access, 4, 2292–2303. [10] Xia, Q. et al. (2017). MeDShare: trust-less medical data sharing among cloud service providers via Blockchain. IEEE Access, 5, 14757–14767. [11] Pawade, D., Sakhapara, A., Badgujar, A., Adepu, D., Andrade, M. (2020). Secure Online Voting System Using Biometric and Blockchain. In Sharma, N., Chakrabarti, A., Balas, V. eds, Data Management, Analytics and Innovation. Advances in Intelligent Systems and Computing. 1042. Singapore: Springer. Doi: https://doi.org/10.1007/978-981-32-9949-8_7. [12] Pawade, D., Sakhapara, A., Andrade, M., Badgujar, A., Adepu, D. (2019). Implementation of Fingerprint-Based Authentication System Using Blockchain. In Wang, J., Reddy, G., Prasad, V., Reddy, V. eds, Soft Computing and Signal Processing. Advances in Intelligent Systems and Computing. 900. Singapore: Springer. Doi: https://doi.org/10.1007/978-981-13-3600-3_22. [13] Huh, J.-H., Seo, K. (2019). Blockchain-based mobile fingerprint verification and automatic log-in platform for future computing. Journal of Supercomputing, 75(6), June 2019 3123–3139. Doi: https://doi.org/10.1007/s11227-018-2496-1.

Manish Jain

Chapter 9 Novel feature extraction and classification architecture for emotion recognition using EEG Abstract: Emotion is a collection of psychological states that includes subjective experience, expressive behaviors and peripheral physiological responses. They play a vital role in the process of creation, natural communications in day-to-day activity. Various physiological signals can measure these emotions. Among the biomedical signals, electroencephalography (EEG) signals are more useful in the analysis of emotions because emotions are the end product of our thinking, feeling, actions, reactions to people and circumstances. In the research of emotion recognition, one of the crucial challenges is to elicit a person’s target emotion and collect the EEG signal in the laboratory. This work is fruitful for researchers who surveyed the methods of emotion recognition using EEG. In this chapter, we have applied machine learning and neural network methods for emotions recognition. We have described EEG signals, preprocessing techniques, feature extraction and classification techniques used for emotion recognition. It is observed that machine learning methods are predominant in getting high-level features automatically from noninvasive EEG signals and they are less dependent on manually created features. Keywords: classification, deep learning, EEG, emotion recognition, feature extraction

9.1 Introduction Emotions play a vital role in our daily life because they affect human cognition, perception, interaction and decision-making ability along with human intelligence [1, 2]. However, they were ignored by human–computer interaction (HCI) systems till the last decade. The HCI systems and digital media find potential applications in biomedical engineering, neuroscience, neuromarketing and other alternate areas of life, which are mainly affected by emotions. Hence, with the increasing demand for HCI, automatic human emotion recognition is gaining researchers’ attention. The emotion recognition can be done with text, speech, gesture movements and facial expressions, but electroencephalogram (electroencephalography (EEG)) gives a better outcome as it directly measures true feelings [3, 4]. Rapid development in new wearable, handy,

Manish Jain, EEE Department, Mandsaur University, Mandsaur, Madhya Pradesh, India, e-mail: [email protected] https://doi.org/10.1515/9783110702507-009

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low-cost wireless headsets measuring EEG and classification of EEG signals without trained professionals has enormously increased its use, like sleep, management and much further combinational arrangement for signals. Emotion reorganization plays an important role in today’s era for research in medical finding for illness issues caused for illness. Further, the advanced signal investigation through feature extraction also holds much application in medical image processing. In emotion reorganization research, the basic challenges are elicited target emotion and collecting EEG signal in the research laboratory. This kind of emotion is generally stimulated with signals like audio, video, text and image [5, 6]. For stability is concerned, the video among these four signals provides more stability. The general brain–computer interface (BCI) system is shown in Figure 9.1.

Figure 9.1: General BCI system.

A BCI system translates human brain activity to commands that can operate a device, such as a computer [7]. Existing BCI systems have many applications. For example, a BCI allows an user to spell with a virtual keyboard to control an orthosis [8], a functional electrical stimulator [9], and navigate the World Wide Web with different degrees of success.

9.2 Importance of emotion recognition process The real-time emotions are physiological, cognitive, behavioral interpretations of humans, which are all correlated. Emotions are playing a vital role in daily human life. Automatically human emotion recognition covers become a necessity with rapidly enhancing emotions of Human Machine Interface (HMI) [10]. Automated retrieval of

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emotional insist from physiological signals like EEG is gaining noticeable usability in the current trend, as computing in the context of human neural responses can lead to development of BCIs. The designed BCIs can be further programmed toward the development of neuroscientific and premedical aspects that progressively contribute to help out medically challenged people suffering from certain psychiatric/ depression disorders. The emotion recognition process is shown in Figure 9.2. Therefore, the development of a competent computer-aided method for advanced automated classification and detection of emotions is based on human response.

Figure 9.2: Emotion recognition process.

9.3 Classifier characteristic analysis based on channels Emotions play an important role in our daily lives as they affect human perception, interaction, decision-making ability and human intelligence [5]. Further till last decade, HCI systems were ignored. The HCI systems with digital media find strongly occupied applications in neuroscience, biomedical engineering, neuromarketing and other aspects of life mainly affected by emotions. Therefore, with the increasing demand for HCI, researchers’ attention is through automated automatic human emotion recognition [11]. Speech, gesture movements, text and facial expressions [6] may build up with the help of an electroencephalogram (EEG), which gives a better outcome as it directly measures true feelings. The nature of signaling in EEG is noninvasive and has high temporal resolution [12]. Rapid development is required in the area of handy, new wearable, low-cost wireless classification of EEG signals that cannot make possible without trained professionals, and enormously increased its use in other areas for today’s life such as Elearning, video processing, cyber securities and sleep management. The different classifier characteristics are given in Table 9.1.

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Table 9.1: Different classifier characteristics. Classifier used

Feature extracted

Support vector machine (used for two, four or eight emotions)

Wavelet and principal component analysis

k-Nearest neighbor (used for two emotions)

No. of Classification Advantages of channels accuracy classifier used 

% . Good results on unstructured data . Better sealing of high-dimensional data %

Hijorth parameter



Frequency features



%

Fractal Dimension



%

Differential entropy



%

Empirical mode decomposition



%

Flexible analytic wavelet



%

Hijorth parameter



Differential entropy



Hijorth Linear parameter Discriminate Analysis (LDA) (used for two or four emotions)



Disadvantages of classifier . Long training time for large dataset

% . Simple to implement and understand % . Good classification for large data

. Sensitive to irrelevant features . Selection of k is difficult

% . Simple implementation . Reduces highdimensional data to low-dimensional data

. Fail to discriminate a variety of features . Fail to work on variance

9.4 Scope of the electroencephalography (EEG) features 9.4.1 Healthcare In today’s era for daily life applications, it is essential to detect changes in emotional patterns at the most primitive for appropriate human interactions. Of course, these interactions are helpful in healthcare to conquer stress-related diseases before the growth of

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long-term mental illness. BCI applications aimed at helping people with limited mobility including those with amyotrophic lateral sclerosis and spinal cord injury. Recently, there is also an emerging interest in BCI with applications targeting stroke individuals. More specifically, investigations have been performed to evaluate the possibility of using BCIs for post-stroke rehabilitation to restore upper and lower limb functions [13].

9.4.2 Entertainment Human being’s EEG features may designate important information for video emotion recognition, and the reason is simply the direct and instant authentic feedback that provides on human perception with uniqueness, which is valuable in the entertainment industry. EEG is being used in the study for neuromarketing that is related to the analysis of connection between electrodes and emotional stress crossways to the businessrelated advertisement. Event related desynchroniation (ERD) for a subject executing Motor Imagery (MI) of right hand, left hand, feet and tongue on the channels C3, Cz and C4 is shown in Figure 9.3.

Figure 9.3: ERD for a subject executing MI of right hand, left hand, feet and tongue on the channels C3, Cz and C4.

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9.5 Research gaps identified in emotion recognition 9.5.1 Deficiency in the feature selection approach to find significant EEG characteristics Feature selection approaches are one of the important steps toward emotion recognition. It processes to involve finding out features that can distinguish a different kind of emotional states. The emotion reorganization plays importantly using physiological signals; various studies have focused on extracting the latest feature reorganizations of the EEG signals.

9.5.2 EEG channel reduction in the algorithm A general bar channel (BC) system having 32 or 64 channels is used in most of the important applications. The study has shown that specific channels are predominant in general specific applications. Therefore, the effective channel selection algorithm would get better performance application-wise. The reason behind the use of the channel selection algorithm is (i) minimization of the computational complexity of processing task performed on EEG signals by particularly analyzing the relevant channels along with the extraction of important concepts, (ii) to overcome the amount of overfitting which may begin because of the utilization of irrelevant channels, and this may inculcate to improve the performance and (iii) try to overcome the setup time in the particular application.

9.5.3 Lack of optimized deep learning classifier in emotion recognition Another specific challenging issue in building types of the emotion recognition system is to choose the most excellent classifier which may accurately categorize various types of emotions. Most of the studies likely to fail to attain the best possible performance using physiological signals such as nonstationary and nonlinear. These emotional signals vary over time and during the sessions of recordings [14]. To capture the inherent temporal organization of EEG, we have to proceed with classifiers that are progressive to learn temporal patterns throughout the signal time. Convolution neural network (CNN) will be apparent in one of the significant advantages due to its competence of feature extractions directly without any source to raw data handcrafted selection, and its success in most of the challenging cataloguing tasks. Along with the physiological signals, EEG signals are preferred for emotion recognition. In the past work, lots of types of descriptions from time, frequency and time–frequency domains have been extracted from EEG signals to

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recognize different emotions, although there is no standardized set of EEG features usually agreed to be most appropriate for emotion recognition.

9.6 Challenges for smooth emotion recognition process This research’s main challenge is to get the gain and impending into the quickly increasing area of BCI research. Approaching the concentration on the EEG signal, as the BCI stimuli input modality, the aim fulfills a deep understanding of the neurophysiologic processes that can be exploited to practice a BCI-based system. To have a smooth EEG which is free from noise, artifacts and interface, preprocessing is carried out initially for various signals. Ideally, the entire channel used in the database proceeds with good accuracy; however, some channels produce redundant values and are not important as far as emotion reorganization purposes. The challenges are as follows: (i) How to expand neurophysiologic concepts of the normal human being? (ii) How to inspect EEG considering as a reorganization of mental action? (iii) How to proceed with a comprehensive analysis of EEG-based BCI systems implementation for imaginary motor works? (iv) How to develop a methodology for identifying the effect caused by motor imaginary on the activity using EEG? (v) How to discuss the impact caused by the above work for developing BCI for physically impaired people? (vi) How convolution network helps in enhancing the accuracy of emotion characterization and reorganization model for the betterment of signal interference?

9.7 Proposed methodology 9.7.1 Hypotheses to be tested Using the approach for suitable features, the EEG-based emotion recognition system is to be optimized for continuous operation in longtime duration. Further by using the reduction in the number of channels may effectively be recognized as three emotions classified as natural, positive and negative. As there is very little effect of accuracies with 64/32 channels and reducing the number of channels, the continuous process of the CNN improves the accuracy with “graph-regularized extreme learning machine” classifier. Process of reducing the number of channels recognizes the four classes of MI properly in imaginary motor classification.

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In the context of EEG signals, the CNN may be recognized for EEG signal-based classification. Yet it may yield better results when compared with other methods such as support vector machine (SVM) technology. The proposed algorithms using CNN methods would be practical for improved estimation of features analyzed in the upgrading of accuracy in MI classification. The information source for analyzing the BCI competition IV-2a EEG dataset are four-class MI features such as left, right, feet and tongue.

9.7.2 Preprocessing techniques The EEG signal is preprocessed to improve the signal-to-noise ratio. The raw EEG signals may consist of line noise artifacts. Artifacts are generated by factors like eye movements, the electrical activity of heart, the muscular activity of the head, environment, electrode attachments and cables. To remove these artifacts, preprocessing is done using the following techniques [15, 16]. (i) PCA (principal component analysis): This process reduces the dimension of the raw data retaining the information. Orthogonal transformations are used to change the group of interrelated vectors for a set of linear uncorrelated vectors classified as principal components [17]. (ii) Common average referencing: The method is known as common average referencing, which causes to remove the random signals like noise using approach classified as referencing. This calculation of the average of electrodes is difficult to find because of finite sample density [18]. (iii) Surface Laplacian: This technique provides a high spatial resolution EEG signal by removing artifacts generated by the electrode cap. It is robust for electrode referencing problem but sensitive to spline parameters [19]. (iv) Independent component analysis: This splits EEG signal into independent components independent of a reference channel and removes noise. It gives better performance for the decomposition of large-size data [20, 21]. (v) Digital filters: Muscle artifacts are removed using bandpass digital filters [22]. The electrical line noise is removed using a notch filter.

9.8 Classification and feature extraction method Machine learning (ML) method: To apply the ML technique to EEG signals, we have to decide the specific EEG feature for identifying the difference among various experimental situations. The EEG data are spontaneous signals in nature and analyzed the frequency domain by separating rhythm with the help of frequency and amplitude [23].

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The selection of an accurate set of EEG features is necessary for the ML technique of EEG data analysis. ML feature selection and dimension reduction: The performance of ML techniques applied in EEG analysis is often limited due to the high dimension of EEG data and the limited number of samples. Feature selection or reduction of dimensionality can be achieved with or without labeling classes (e.g., supervised or unsupervised PCA) [24]. It is usually used for reducing dimension. ML analysis: After identifying samples and important features, a classifier is identified. Classifier represents a function between features identified and class labels required. It is classified into discriminative and generative models [25]. The classifiers separate the points into two classes by using a line called a decision boundary. Jose-Manuel Cano-Izquierdo et al. [26] elaborated neural networks and fuzzy logic-based EEG signal classification for operating noninvasive BCI. It focuses on a three-class problem based on supervised neuro-fuzzy adaptive system Art [27] along with rule pruning and voting strategy for the operation of a BCI system. It allows maintaining stability, which was maintained with plasticity to accommodate new information. The classification accuracy of 76.07% was achieved [23, 28]. The phase synchronization patterns from EEG were recorded from 10 participants [8]. The patterns were specific for each cognitive task. Maximum and minimum number of occurrences were used to extract connectivity pattern networks based on graph theory and fed to the SVM classifier. Classification accuracy obtained was 85%. Sadiq et al. [9] mention that an algorithm is made robust against using multiscale PCA in the preprocessing stage. A sub-band alignment was used along with multivariate empirical wavelet transform to get various components like amplitude and frequency. A feature selection method based on robust correlation was used to reduce system complexity and computational load. BCI-based dataset is used. The accuracy classification achieved is 90% by using multilayer perception, least-square SVM (LS-SVM) and logistic model-free classifier. The improvement in accuracy is 23.5% for earlier methods for subject dependent and 18.14% for subject independent. Table 9.2 shows different classifiers along with dataset. Zhang et al. [7] proposed a common spatial pattern (CSP)/AM-BA-SVM algorithm for classification and future extension. By applying this algorithm on the optimum time interval of every subject, CSP features were extracted from EEG signal and a one versus one classification strategy was applied to get binary CSP. Santamarial, L., James, C. [8] investigated the problem of extraction of extraordinary features from EEG signals, which contains samples for a set of training types. To solve the problems of overfitting and increase the accuracy of classification of CSPbased approaches, select few CSP features and neglect others, resulting in the loss of differentiating information. The algorithm performs FWR (feature weightings and regulation), which replaces some method based on the CSP method. It is applied to CSP,

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Table 9.2: MI EEG classification based on machine learning. Classifier

Features

Dataset

Accuracy

S-dFasArt

Fuzzy

BCI IV IIa

.%

SVM

TSGSP

BCI III IIIa BCI IV IIa BCI IV IIb

.% % .%

SVM

Phase synchronization patterns

 participants

%

MLP, LS-SVM

MEWT (IA and IF)

BCI III

%

LS-SVM

EWT, IA IF

BCI IV IIa

.% .%

SRSG-FasArt

AR-CSP

BCI IV – a

.%

FWR

CSP, CSSP, RSSP

BCI IV – a

Avg. %

SVM []

Phase synchronization, band-pass energy, Hilbert transform

BCI IV – b

.%

SVM []

Common Bayesian network

BCI IV a

%.

TSGSP, temporary constrained sparse group spatial patterns; MLP, multilayer perceptron; MEWT, multivariate empirical wavelet transform; EWT, empirical wavelet transform; LS-SVM, least-square support vector machine; SVM, support vector machine; IF, instantaneous frequency; IA, instantaneous amplitude; CSP, common spatial pattern; BCI, brain–computer interface; FWR, feature weightings and regulation; CSSP, common spatiospectral patterns, S-dFasArt, supervised neuro-fuzzy adaptive system Art; SRSG-FasArt, self-regulated supervised Gaussian fuzzy adaptive system art.

common spatiospectral patterns and regularized CSP on EEG data. The FWR method gives better classification accuracy than previous methods. Sadiq et al. [9] used a new empirical wavelet transform for adaptive data decomposition using nonlinear NI EEG signals and nonstationary signals. For system execution time reduction and simplicity, 18 channels were chosen among 118 channels. Ten frequency-adaptive modes were obtained from each channel, and Welch power spectral density was used to find the most sensitive mode. Hilbert transform was applied on this mode to get the instantaneous frequency and instantaneous amplitude (IF and IA) features and fed to the LS-SVM classifier. Accuracy on BCI IV IIa dataset with IA and IF features was 95.19% and 94.6%, respectively. Zhang et al. [7] mention that interferences due to artifacts were removed in feature extraction by using the AR-CSP algorithm. The nonstationarity in the electroencephalogram (EEG) was resolved in a classifier with the method known as self-regulated supervised Gaussian fuzzy adaptive system art method. This algorithm selected samples on a priority basis and directly upgraded the fuzzy rules. The system has resolved the problem of overtraining and can be used in general.

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9.9 Discussion and future direction Although EEG is used in a variety of applications, it still suffers from some limitations that affect the analysis of a signal. If we compared signal-to-noise ratio, EEG has very little because it measures the brain activity mixed with artifacts. Hence, filtering and noise reduction techniques should be used to extract actual brain signal out of raw EEG. The EEG is a nonstationary signal [7] that varies across time varying signals. Hence, classifier trained on a limited amount of user data may poorly classify generalized data recorded for the same individual. The physiological differences between the individuals generate EEG signals with varying magnitudes. This seriously affects the performance of the algorithms that are developed to generalize across the subjects, which in turn limits the use of EEG applications. To solve some of the problems mentioned above, domain-specific approaches are widely used, which has reduced the flexibility and generalization capability of the system. The neural networks can automatically optimize their parameters; hence, less sophisticated knowledge is required about the dataset for its better performance. This property of deep learning has made it popular in the field of medical applications [26] involving large datasets that are otherwise difficult to explore. The reviewed chapter on neural networks shows that shallow architectures were preferred to achieve good results with the limited amount of data. It was observed that data augmentation had improved the performance of classification; still, more work is required to access the advantages of deep learning [25]. One of the main reasons for using a deep neural network was to use raw EEG for classification. The deep learning algorithms can be generalized across subjects and facilitate learning across the tasks. The popularity of CNN shows a trend of using raw EEG compared to extracted features. The ability of CNN to use spatial and temporal features has given the remarkable improvement inaccuracy. The major outcomes of our analysis with deep learning are: (i) Various architectures like CNN, Recurrent Neural Network (RNN) and Decomposed Convolution Neural Network (DCNN) have been successfully used for MIEEG signal processing. (ii) The quantity of data varies from 1 subject to 53 subjects. (iii) There is growing interest among researchers in using the raw data. Till now the above studies show a small improvement in accuracy with different neural networks as compared to other ML and computer vision methods. To develop a new model using deep learning, one should consider its architecture, training, optimization model inspection, repeatability and reproducibility.

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9.10 Conclusion The design of deep learning classification extensively depends on input formulation and network design. Various studies have been done so far related to BCI competition to compare classification outcome-based accuracy. Different deep learning techniques have their advantages as well as disadvantages. It is observed that by applying CNN’s method, the performance of deep networks such as Clued Attention Recurrent Model (CRAM) and fuzzy deep belief networks will improve. This chapter shows that the success of training a deep neural architecture is still not completely known. Design and characteristic novel architecture for feature extraction of EEG signal using CNN and emotion recognition have been demonstrated. Performance evaluation and comparison between various techniques like graph regularized, SVM, ML and our proposed algorithm have been analyzed. Further, a better algorithm may be developed, which can be utilized to build a better system for emotion recognition and interpretation of raw versus de-noised EEG.

References [1]

Pfurtscheller, G., Muller-Putz, G., Scherer, R., Neuper, C. (2008). Rehabilitation with brain-computer interface systems. IEEE Computer, 41(40), 58–65. [2] Ang, K.K., Guan, C. (2013). Brain-computer interface in stroke rehabilitation. Journal of Computing Science and Engineering, 7(2), 139–146. [3] Zander, T., Kothe, C. (2011). Towards passive brain-computer interfaces: Applying brain-computer interface technology to human-machine systems in general. Neural Engineering Apr, 8(2), 110–120: 025005. doi: 10.1088/1741-2560/8/2/025005. [4] Van Erp, J., Lotte, F., Tangermann, M. (2012). Brain-computer interfaces: beyond medical applications. IEEE Computer, 45(4), 26–34. [5] Kai Keng Ang, K.K., Zhang Yang Chin, Z.Y., Haihong Zhang, H., Cuntai Guan, C., “Filter Bank Common Spatial Pattern (FBCSP) in Brain-Computer Interface,” In 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence), IEEE, June 2008, 2390–2397. [6] Wolpaw, J., Wolpaw, E. (2012). Brain-Computer Interfaces: Principles and Practice, Oxford University Press, Wadsworth Center, New York State, Department of Health and State University of New York DOI:10.1093/acprof:oso/9780195388855.001.00001. [7] Zhang, Y., Nam, C.S., Zhou, G., Cichocki, A. (2019, Sept). Temporally constrained sparse group spatial patterns for motor imagery BCI. IEEE Transactions on Cybernetics, 49(9), 3322–3333. [8] Santamarial, L., James, C. (2018). Using brain connectivity metrics from synchrostates to perform motor imager classification in EEG-based BCI systems. Healthcare Technology Letters, 5(3), 88–93. [9] Sadiq, M.T., Yuly, X., Ullah, I., Xiao, G.,” Motor Imagery EEG Signals decoding by Multivariate Empirical Wavelet Transform Based Framework for Robust Brain-Computer. [10] Van Steen, M., Kristo, G. Contribution to roadmap; 2015 Available online: https://pdfs.seman ticscholar.org/5cb4/11de3db4941dec7ecfc19de8af9243fb63d5.pdf.

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[11] [12]

[13]

[14]

[15]

[16]

[17]

[18] [19] [20] [21]

[22] [23]

[24]

[25]

[26]

[27]

[28]

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Pfurtscheller, G., Lopes Da Silva, F.H., “Event-Related EEG/MEG synchronization and desynchronisation: Basic principles,” 1842–1857, Nov 1999. Wolpaw, J.R., McFarland, D.J., Neat, G.W., Forneris, C.A. (1991). An EEG-based brain-computer interface for cursor control. Electroencephalography and Clinical Neurophysiology, 78, 252–259. Ramoser, H., Muller-Gerking, J., Pfurtscheller, G. (2000). Optimal spatial filtering of single trial EEG during imagined hand movement. Rehabilitation Engineering, IEEE Transaction on, 8(4), 441–446. Hashimoto, Y., Ushiba, J. (2013). EEG-based classification of imaginary left and right foot movements using beta rebound. Clinical Neurophysiological Practices, 124, 2153–2160. Doi: 10.1016/j.clinph.2013.05.006. Wallstorm, G.L., Kass, R.E., Miller, A., Cohn, J.F., Fox, N.A. (2004). Automatic correction of ocular artifacts in EEG: a comparison of regression based component based methods. International Journal of Psychophysiology, 53, 105–119. Ter Braack, E.M., De Jonge, B., Van Putten, M.J. (2013). Reduction of TMS induced artifacts in EEG using principal component analysis. IEEE Transaction. Neural Systems Rehabilitation Engineering, 21, 376–382. Lakshmi, M.R., Prasad, T.V., Chandraprakash, V. (2014). Survey on EEG signal processing method. International Journal of Advance Research in Computer Science and Software Engineering, 4, 84–91. Trejo, L.J., Kevin, R., Rosipal, R., Krupka, M. (2003, Jun). Multimodal neuroelectric interface development. IEEE Transactions on Neural Systems and Rehabilitation, 11(2), 199–204. Lu, J., McFarland, D.J., Jonathan, R. (2013, Feb). Adaptive Laplacian filtering for sensorimeter rhythm-based brain-computer interfaces. Journal of Neural Engineering, 10, 016002. Tangermann, M., Muller, K.R., Aertsen, A., Birbaumer, N., Blankertz, B. (2012). Review of the BCI competition IV. Frontiers in Neuroscience, 6, 55–65. Safieddine,, Kachenoura, A., Algebra, L., Birot, G., Karfoul, A. (2012, Jan). Removal of muscle artifact from EEG data: Comparison between stochastic (ICA and CCA) and deterministic (EMD and wavelet-based) approaches. EURASIP Journal on Advances in Signal Processing, 127, 210–220. Baars, B., Gage, N. (2010). Cognition, Brain and Consciousness, Introduction to Cognitive Neuroscience, Elsevier, Academic press eBook ISBN: 9780123814401. Kevric, J., Subasi, A. (2017). Comparison of signal decomposition methods in classification of EEG signals for motor-imagery BCI system. Biomedical Signal Processing and Control, 31, 398–406. Yu, X., Chum, P., Sim, K.B. (2014). Analysis the effect of PCA for feature reduction in nonstationary EEG based motor Imagery of BCI system. International Journal for Light and Electron Optics, 125(3), 1498–1502. Lu, N., Li, T., Ren, X., Miao,. (2017). A deep learning scheme for motor imagery classification based on restricted Boltzmann machines. IEEE Transaction Neural System Rehabilitation Engineering, 25, 566–576. Jose-Manuel, C.-I., Ibarrola, J., Almonacid, M. (2012, Jan). Improving motor imagery classification with a new BCI design using Neuro-Fuzzy S-dFasArt. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 20(1), 2–7. Carpenter, G., Grossberg, S., Markuzon, N., Reynods, J., Rosen, D. (1992, Sep). Fuzzy ARTMAP: A neural network architecture for incremental supervised learning of analog multidimensional maps. IEEE transaction Neural Networks, 3(4), 69–713. Suefusa, K., Tanka, T. (2017). A comparison study of visually stimulated brain-computer and eye tracking interfaces. Journal of Neural Engineering, 14, 036009.

R. Sandhiya, A. M. Boopika, M. Akshatha, S. V. Swetha, N. M. Hariharan

Chapter 10 Future of fashion industry: sustainable fashion using blockchain Abstract: The term “sustainability” has become a buzzword in recent years. It also turned the researchers toward its side. Sustainable fashion has gained attention nowadays, and it is a recent movement that aims to reduce the environmental pollution caused by the fashion industry. The prime aim is to reduce global pollution in order to run the industry in an eco-friendly manner. Sustainable fashion also ensures the limited consumption of resources in order to make an industry that will be more sustainable in the long run. Researchers are deeply analyzing this fashion industry sustainability since it has got a large scope. This chapter presents a brief survey about sustainable fashion, role of blockchain technology and its importance. Keywords: fashion industry, blockchain, supply management, sustainable fashion

10.1 Introduction Fashion is the most important force for people all over the world because it makes us look good and changes the lifestyle. It makes us perfect with the clothes we wear and the admiration of people by our look. Fashion bears creativity among the designer as well as among the people who choose. It also improves the idea and the way we live. The important categories of fashion depend on groups those accepted, duration which it lasts and size ranges. There are a variety of fashion models, which include:

R. Sandhiya, Department of Information Technology, Coimbatore Institute of Technology, Coimbatore 641014, Tamil Nadu, India, e-mail: [email protected] A. M. Boopika, Department of Information Technology, Coimbatore Institute of Technology, Coimbatore 641014, Tamil Nadu, India, e-mail: [email protected] M. Akshatha, Department of Information Technology, Coimbatore Institute of Technology, Coimbatore 641014, Tamil Nadu, India, e-mail: [email protected] S. V. Swetha, Department of Information Technology, Coimbatore Institute of Technology, Coimbatore 641014, Tamil Nadu, India, e-mail: [email protected] N. M. Hariharan, Department of Information Technology, Coimbatore Institute of Technology, Coimbatore 641014, Tamil Nadu, India, e-mail: [email protected] https://doi.org/10.1515/9783110702507-010

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High fashion Mass fashion Classic Fads Couture

It also includes the dimensions like style, acceptance and time. The fashion industry analysis helps to find the trend every day and improves and satisfies what people require. Sustainable fashion changes the system and product of fashion into a greater view. It completely focuses on the source, design, manufacture and cost that benefits the people and communicates and will impact the environment less. This fashion mainly focuses on the environment and economic acceptance. This only uses natural materials and avoids pollution, and also we will have the safe unchemical fashion with the shortage of wastes and so on. It makes us feel so elegant and comfortable. The most important goal and priority over here are to buy fewer clothes and use them for a longer period. Sustainable fashion has the greatest brand to use and a trustable one. It is also referred to as slow fashion. Moreover, the commitments for sustainability are shared throughout the product life cycle, making us look cool and stylish for a longer period. So our amount would be saved, and this style not only fits women but also men, kids and adults, making them happy and comfortable. It includes all kinds of varieties, and it uses cotton fabric, which is good for health too. It also focuses on ethics and transparency from the outwear to the footwear and accessories. This fashion also accepts reusable things where you can send the unused clothing to the companies. They buy and recycle and provide you with the likable form back to you again. The concept of reducing, reusing and recycling is the main motto of sustainable fashion.

10.2 Sustainable fashion: a brief overview It is a slow fashion movement. It appeared in 1960 with the clothing manufacture, and ethical fashion became known in 1990. This slow fashion movement helps us to make the manufacturers in a perfect and healthy condition, increasing the sustainable fashion. It is also investigated [1] that it constructs social impact, which has two types of “reality.” One is, it is constructed through social interaction, and the other is the circumstances. The underlying principle of sustainable fashion is semistructured interviews and Twitter feeds. These data sets were correctly checked with seven processes like reflection, familiarity, concept, catalog recode and revaluation. To check the coherence and clarity, check the code and recode more than five times. Limitations of this research [1] are the size of the sample, understanding the

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individual target and if the sample size is not correctly represented, it would be avoided. Sustainable fashion is creative, interesting and affordable. A challenging part here is precisely communicating the advantage of this fashion. Many large companies like H&M, STELLA and so on make their fashion perfect and of good quality. Talking about the consumer part, magazines, TV and media have become the huge source of making sustainable fashion as style and perfect. It also includes the environmental surroundings, use of renewable, raw materials, durable time and measures using the things again and again as reusing material. There are two themes playing a role here: one is transparency and another is traceability. Transparency is the original material used for the manufacturing process, and traceability shows the supply chain rather than the original material as transparency does. Both these two themes play a role for the longer term. Though sustainable fashion is a slow fashion, it provides customer satisfaction by providing fair wage to the customers. It also protects us from greenwashing and this was tabled in the fashion matrix to check the progress sustainably. Also, we can understand different persons like customers, marketers and companies, and talk to them individually and make them understand what is a sustainable fashion and what it does and how it will profit them. The fashion matrix chart and table hold all these analyses and priority chart as shown in Figure 10.1.

Figure 10.1: Concern about sustainable clothes buying.

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10.3 Role of blockchain in sustainable fashion Environmental resources like air, water and land are so precious. But nowadays, people are depleting that at an alarming rate. Sustainability becomes the need of the hour to prevent further depletion of the resources. Climatic change, pollution and biodiversity extinction are all major areas to be considered and saved as soon as possible. Fortunately, we have a wide range of technologies to cope with the situation and provide a better solution for the social and environmental problems. One such emerging technology is blockchain, and it has a wide range of scope beyond the bitcoin. Blockchain provides more transparency, like who bought the product and the purpose. Customers also prefer sustainable brands, which is proven by the success of fashion brands like Allbirds and Veja. Aside from transparency, this technology supports traceability. Also, thanks to blockchain technology, consumers can have adequate information about genuinely sustainable products. This enables them in order to make informed choices. Few people say, using blockchain is digitalizing all this information in a decentralized way.

Figure 10.2: Transparency in fashion sustainability.

10.4 Application of blockchain in the fashion industry Cryptocurrencies are one of the most rising applications in fashion technology. They are also used for data storage for multiple transactions with secure entry and exit is also added. Most of the industries, including management, education, computing, the Internet of things (IoT), healthcare, real estate, started to implement this technology. Blockchain in a group can make the fashion technology the best system and progression shopping would be easy, and the education system will be smooth fashion world.

10.4.1 Transparency of supply chain This transparency system is really helpful for garment production. It allows the customer to feedback the brands and production often in a very secure and protected

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way, making the product produced in a cycle and transparent manner. Once the product’s transparency is done, it moves into the production process with the assigned unique token for each product. It also includes technology like Quick Response (QR) code and Near-Field Communication (NFC) label. These are the proof ideas for achieving perfect transparency for fashion technology as mentioned in Figure 10.2.

10.4.2 Product authentication It is an extension of natural transparency for tracking the supply chain using a technology called a blockchain. It clears the completed guide of the particular product; it will naturally predict and prevent the authenticity without any machines and humans’ help.

10.4.3 Inventory, warehouse and distribution This happens with the pathway created for the manufacturers, customers and communicator. It also takes the artificial robust for constant check of fashion cycle for the products that let us become agile technology for clear and perfect communication about the products.

10.4.4 Hardforks It is used to check the validates about the old rule and check the new block with the valid and invalid condition, and privacy for blockchain is private and needs permission to move further.

10.5 Property protection Fashion industry designers can protect their brands with the help of counterfeiting. Each product of the item is tracked with the help of source, records and all these were started with the NFC tags for identifying with the help of a technology called a blockchain. We use IoT and radio-frequency identification chips that help us increase the brand’s identity with better quality standards for tracking. We can track the system with proof and payment method. This blockchain technology is very helpful to track the products of various brands easily and efficiently. This technology has

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Other motives Develop decentral business models Generate new revenue potentials Explore new technology Reduce costs 0

5

10

Figure 10.3: Inspired to use blockchain.

started to grow in many countries for better customer satisfaction, and the producer and employer who works were inspired to use blockchain as shown in Figure 10.3.

10.6 Importance of sustainable fashion Today’s fashion industry is a great money-making business affecting each and everyone around the world in some way! Fashion is the second most polluting industry in the world, which contributes to more pollution and environmental depletion. Due to high production and overconsumption of garments than the required need, the fashion industry has landed itself on an environmentally damaging circle. Thorisdottir and Johannsdottir [2] tried to review the fashion industry’s sustainability in the business model and how they investigate the fashion business model with empirical studies. This is a composition of many kinds of literature about sustainability, and they tried to show the importance of sustainability of fashion in the business model. This sustainability agenda has been developed over the last four decades. The government and other organizations are trying to emphasize this to society by giving more attention to sustainability-related issues. Collaboration between government and society also reduces overconsumption of natural resources and improves its production and marketing strategies. Whereas in recent years, sustainability became a sensitive issue because industries rely on production in low-cost countries, where environmental and safety regulations were demolished. This environmental issue leads to hectic issues in the disposal of huge wastes and products. This lifecycle of the clothing industry has to be in control. Producing new varieties of garments has gained attention because of the fashion concept.

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Due to the issue, members of the fashion industry came up with an idea by creating fashion models’ sustainability over the years. This literature aims to better understand those pieces of literature like how these fashion industries integrate and provide sustainability in business models and sustainability-related practices to measure the transparency and recognition in what way sustainability drives the fashion industry through the business model. This literature’s main motto is to detect and do research in trends of sustainability integrations in the fashion world. Also, the industry measures and gives reports to increase transparency to drive the business model’s fashion. Integrating sustainability-related practices into the fashion industry business models is highly important because it is one of the most important sources in producing pollution in the world. Such action should be beneficial for both society and the environment and provides secure transparency within the industry regarding their massive production volumes causing significant pollution issues. This path opens for understanding the empirical studies on investigating the performance indicators, key elements of sustainability in fashion, transparency and disclosures. Such studies provide a more comprehensive view of what makes to analyze sustainability within the industry, the actions carried out and the societal and importance of environmental benefits.

10.7 Sustainable fashion design innovation The juncture of science and technology is underlying to give an effect on the fashion industry [3]. The sustainable findings in the fashion industry are challenging in recent social development. At this moment of environmental modulation and trend in design, a new positive model is needed for creative design to achieve sustainable fashion and eco-friendly things. In this recent trends and development of fashion, eco-design is the most important part of a sustainable supply chain. With this increasing awareness of sustainability, it has been a major trend in the fashion industry. The design strategies provide a low degree of harm in garment production, reducing the fashion industry’s degradation issues. Sustainable design is the method that gives the best solution for an environmental problem. The objective of this note is to provide a solution of non-sustainability in upcoming and crossed decades. And also, they gave certain analyses related to fashion sustainability. They also answered certain ethical fashion, ethics and aesthetic values (green aesthetics values), and some other analyses are done to check the sustainability. This literature provides overall fashion sustainability, clothing functionalities, industrial impact, garbage waste and uncertain changes in the fashion world. The complete flow clothing from industry to the customer is given in Figure 10.4.

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Textile Industry

Clothing and Fashion Industry

Disposal/Re-use

Use/Consumers

Retail

Distribution centres Fashion shows

Tailoring

Finishing

Dyeing (yarn)

Weaving

Fashion design

Textile design

Spinning

Fibre production

Transport

Textile, Cloth and Fashion Industry Figure 10.4: Flow of clothing from industry to the customer.

10.8 Impact of emerging technology in fashion Science and technology have a great impact on sustainability [4]. This century is an information era and birth year of new technologies like biotechnology, genetics, nanotechnology and artificial intelligence. These emerging technologies have introduced the world to a new art of work. They have contributed to diverse fields such as clothing and manufacturing of novel materials. Also, the manufacturing of eco-friendly biomaterials is in the textile industry. All these technologies are also invoked in the textile industry. It has become the basic component of the fashion and design industry. Nowadays, the scope of room for sustainable fashion has been wide open for researchers to provide better solutions.

10.9 Fast fashion industry: sustainable supply chain management This has been the wide area in all the parts of the world, including developed, developing and non-developed areas of countries, cities and states. But in developing parts of the world, they tend to focus on sustainability to satisfy the quality they are looking at and the condition of the product through the supply chain and constant practices. The most important thing they check [5] in sustainable fashion is to source

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and distribute the fast fashion industry cycle to increase the pressure. Large companies like H&M are producing sustainable practices in management and environmental processes. To choose the data set, their sustainability was reported, which helps us grow in socioeconomic background. The global reporting initiative helps us report the sector in the previous year and upcoming years, including all the company’s conditions and rules in the fast fashion industry. For analyzing, they use replicable and valid points from the text as content according to their comfort. Texts, paragraphs and sentences are first reported in an individual sheet for improvement in further part. A sentence that includes five subcodes was then checked and analyzed and made into a framework that the company then practiced. This process provides a perfect quantitative and qualitative approach. A company also maintained content analysis to check the progress, including their aim, performance, risks, improvement, communication and criteria that need to be followed, and a map for the sustainable chain is also maintained for each sector. Fast industry includes the material, finished and unfinished parts to check the company’s input amount. Supply management conditions are not as good as in developed countries. These risks should be analyzed and start from the initial part to protect the company, and the company carefully follows the supplier’s progress. The single sector can be improved with the help of code. This study includes the size of the sample, their report, document and limitations, their reality of the band and quantitative and qualitative approach and checking their weakness and improving along with the help of map and chart analyses [6–12].

10.10 Conclusion Thus, from the above findings, it is clear that sustainable fashion is an important thing to be considered in this era. The abovementioned survey helps the people who are interested in sustainability to identify the trends in sustainable fashion. Sustainability is extremely important and on everyone’s radar! We came to a situation “Enough is enough!” Overconsumption should come to an end. The fashion industries have taken this statement and are moving to sustainable fashion. We hope that emerging technologies like blockchain must be deeply analyzed since they provide a better solution for sustainable fashion.

References [1] [2]

Henninger, C.E., Alevizou, P.J., Oates, C.J. (2016). What is sustainable fashion? Journal of Fashion Marketing and Management: An International Journal, 20(4), 400–416. Thorisdottir, T.S., Johannsdottir, L. (2019). Sustainability within fashion business models: A systematic literature review. Sustainability, 11(8), 2233.

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[3]

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Kumar, R. (2017). Prospects of sustainable fashion design innovation. International Journal of Textile and Fashion Technology (IJTFT), 7(6), 5 14. [4] Waheed, M.F., Khalid, A.M. “Impact of emerging technologies for sustainable fashion, textile and design.” International Conference on Intelligent Human Systems Integration. Springer, Cham, 2019. [5] Turker, D., Altuntas, C. (2014). Sustainable supply chain management in the fast fashion industry: An analysis of corporate reports. European Management Journal, 32(5), 837–849. [6] Choi, T.-M., Luo, S. (2019). Data quality challenges for sustainable fashion supply chain operations in emerging markets: Roles of blockchain, government sponsors and environment taxes. Transportation Research Part E: Logistics and Transportation Review, 131, 139–152. [7] Gardetti, M.A., Torres, A.L eds. (2017). Sustainability in Fashion and Textiles: Values, Design, Production and Consumption, Routledge, United Kingdom. [8] Choi, T.-M., Li., Y. “Sustainability in fashion business operations.” (2015): 15400–15406. [9] Jordan, A., Rasmussen, L.B. “The role of Blockchain technology for transparency in the fashion supply chain.” (2018). [10] Caniato, F., et al. (2012). Environmental sustainability in fashion supply chains: An exploratory case based research. International Journal of Production Economics, 135(2), 659–670. [11] Kutsenkova, Z. “The Sustainable Future of the Modern Fashion Industry.” (2017). [12] Joy, A., et al. (2012). Fast fashion, sustainability, and the ethical appeal of luxury brands. Fashion Theory, 16(3), 273–295.

Index Academics 91 Acceptance of BT 95 Accounting 90 Accounting and auditing industry 92 Accuracy and trustworthiness 92 Adaptable utilities 71 Adoption of blockchain technology 77 Advanced connectivity 64 Applications of blockchain 6 Artificial intelligence 101, 151 Audit 9 Audit process 9 Barriers 92 Barriers in adoption 37 BC in the energy business 66 BC-based SC 43 BCI system 132 Benefit of blockchain 24 Biometric 125 Bitcoin 9 BlocHIE 109 Blockchain 1, 21, 101–119, 145 Blockchain 1.0 105 Blockchain 2.0 105 Blockchain 3.0 101–102, 105, 107, 110, 117 Blockchain solution 25 Blockchain technology 38, 89 Blockchains 38 BlockCloud 109 BlockTrial 116 Classification 131 Clinical trials 102, 114–116 Consensus protocol 5 Convolution neural network 136 Cost-related barriers 50 CounterChain 118 Counterfeit medicines 101 Cryptocurrency 9 Cryptographic hash 103, 110, 116 Decentralization 38, 124 Decentralized 103–104, 109–110, 114 DEEP 131 Digital identity 91

https://doi.org/10.1515/9783110702507-011

Digital platform 23 Digital signature 90 Digitalization management costs 74 Distributed 103–105, 108–110, 116 Distributed ledger technologies 65 Distributed peer-to-peer network 4 DLT 102–103, 111, 115 DPOS 105 Drug supply chain 118 DSCMR 118 Economic obstacles 46 EHR 107, 109 EHRs 102, 107, 109–110 Electroencephalogram 131 Electronic cash 90 Embedding blockchain 28 Energy 63 Energy and power marketplaces 66 Energy applications 69 Energy metering 32 Energy sectors 63 Estonia 102, 108 Ethereum 103–105, 109, 113, 116 External barriers 49 External party 67 Familiarity of BT 94 Fashion industry 145 Fast fashion industry 152 Feature extraction 131 FHIR chain 109 Financial records 13 Financial statements 14 Fingerprint 124 Framework 23 Fraud detection 112 Garment 148 Genesis block 1, 3 Grid and system 75 Hash cryptography 3 Hash functions 67 Hashing 125 Health 27

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Healthcare audits 101 Hierarchical 67 HIS 106 Human–computer interaction 131 ICT 69 Imbalances in the power markets 73 Information 124 Information structures 41 Innovations approaches 90 Intermediaries 68 Internet and BCT 38 Interoperability 102, 107–110, 114 Interorganizational barriers 46, 48 Inventory 149 Machine learning 138 Machine-to-machine 73 Management 67 MedBlock 109 MedRec 109 MHRs 107, 109 Microgrids 75 MIStore 113 Multiple regression analysis 96 On-chain 108–109, 118 One-sample t-test 94 Operation and technological 66 P2P 103, 118 Patient enrolment 114–116 PBFT 105, 113 Peer-to-peer (P2P) network 10 Pharma supply chain 117 PHRs 107, 109–110 PIN 123 Policy underwriting 112 POS 105 PoW 103 Process and methods 50 Productivity of the accounting industry 90

Proof of elapsed time 5 Proof of stake 5 Proof of work 5 Public key cryptography 67 Public safety 27 Quality costs 42 Renewables 64 Resource movements 43 SC commodity 43 SDK 127 Security 38 Sidechain 125 Smart contract 103, 105, 107–110, 113, 115–116, 118 Smart contract regulation 44 Socioeconomic impact 92, 96 Storage 71 Suitability 38 Supply chain cost driver 43 Sustainability 102, 105–106, 110, 113–114, 117–118 Sustainable fashion 145 System-related barriers 49 Technological innovation 92 Technological progress 89 Trading and supply 77 Transaction 103–105, 107–109, 115–116 Transparency 147 Types of blockchain 24 UID 126 Usage of public–private key 68 Virtual networks 67 Wholesale energy 77 Wholesale energy markets 71

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