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This article explores the potential for applying blockchain technology for regulatory compliance and for reducing compliance costs and easing regulatory burdens. We describe the development of the Project Maison proof-of-concept blockchain system for regulatory reporting of mortgages in the U.K. This case study identified use cases and also the risks of increased supervision and loss of control and the governance challenges and trade-offs inherent in applying a decentralized approach to regulatory reporting.
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Title: | A Case Study of Using Blockchain Technology in Regulatory Technology |
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Case 3. blockchain and smart contracts: regulatory challenges and regulatory approaches.
The pace and scope of innovation are challenging the way governments regulate. Existing regulatory frameworks might not be agile enough to accommodate the fast pace of technological development and, as a consequence, rules might become outdated. Beyond this pacing problem, technological innovation also blurs the traditional definition of markets, challenges enforcement and transcends administrative boundaries domestically and internationally.
This report, which results from a joint project between the OECD and the Korea Development Institute, presents a set of case studies illustrating the different regulatory challenges raised by emerging technologies and the diversity of regulatory responses used to address them. The case studies cover data-driven business models, digital innovation in finance, smart contracts relying on distributed ledger technologies, digital technologies for smart logistics, and the sharing economy.
In recent years, the opportunities and challenges brought by distributed ledger technologies (DLTs) have drawn much attention from media, business, and governments. While they represent a relatively recent technology, DLTs could come to considerably redefine socio-economic systems. These disruptive changes raise a number of significant challenges for governments, who strive to find a balance between fostering this innovation while protecting consumers against potential unintended consequences. This case study documents the range of regulatory challenges raised by the development of smart contracts as well as some of the regulatory responses that have been implemented by governments. It highlights, in particular, the need for guidance and appropriate regulatory action to reduce legal uncertainty and limit risks raised by DLT-based smart contracts. It also shows that international co-operation initiatives appears instrumental in addressing territoriality challenges raised by smart contracts.
Author(s) Miguel Amaral i i OECD
14 Dec 2021
Please note you do not have access to teaching notes, blockchain for compliance: an information processing case study of mandatory supply chain transparency in conflict minerals sourcing.
Supply Chain Management
ISSN : 1359-8546
Article publication date: 18 March 2024
Issue publication date: 24 June 2024
Firms are increasingly pressured to comply with mandatory supply chain transparency (SCT) regulations. Drawing on information processing theory (IPT), this study aims to show how blockchain technology can address information uncertainty and equivocality in assuring regulatory compliance in an interorganizational network (ION).
IPT is applied in a single case study of an ION in the mining industry that aimed to implement blockchain to address mandatory SCT regulations. The authors build on a rich proprietary data set consisting of interviews and substantial secondary material from actors along the supply chain.
The case shows that blockchain creates equality between actors, enables compliance and enhances efficiency in an ION, reducing information uncertainty and equivocality arising from conflict minerals regulation. The system promotes engagement and data sharing between parties while protecting commercial sensitive information. The lack of central authority prevents larger partners from taking control. The system provides mineral provenance and a regulation-compliant record. System cost analysis shows that the system is efficient as it is inexpensive relative to volumes and values of metals transacted. Issues were identified related to collecting richer human rights data for assurance and compliance with due diligence regulations.
The authors provide some of the first evidence in the operations and supply chain management literature of the specific architecture, costs and limitations of using blockchain for SCT. Using an IPT lens in an ION setting, the authors demonstrate how blockchain-based systems can address two key IPT challenges: environmental uncertainty and equivocality.
This paper is dedicated to Dr Alisha Tuladhar, who died in September 2022 as the research for this paper came to an end. Alisha’s desire to see her research have a positive impact on the world was a driving force behind the paper’s development and she contributed to its progress in the way that she contributed to everything she did: whole-heartedly and with intelligence and passion.
The authors would like to thank their respondents at Minespider for their participation and engagement in our research project.
The authors thank Andreas Wieland and Jens Roehrich for their helpful advice, who provided valuable and detailed feedback on drafts of the paper, and attendees of both the International Annual EurOMA Conference in Berlin in June 2022 and the Competitive Advantage in the Digital Economy (CADE) conference in Venice in July 2022, where several questions were asked which caused us to reflect on and improve the paper.
The authors would like to acknowledge the support from the EPSRC Centre for the Decentralised Digital Economy (DECADE) [EP/T022485/1], the European Regional Development Fund through the Interreg NWE project “Blockstart: Blockchain-based applications for SME competitiveness”, and the Bradshaw Research Institute for Minerals and Mining (BRIMM).
Tuladhar, A. , Rogerson, M. , Engelhart, J. , Parry, G.C. and Altrichter, B. (2024), "Blockchain for compliance: an information processing case study of mandatory supply chain transparency in conflict minerals sourcing", Supply Chain Management , Vol. 29 No. 4, pp. 755-777. https://doi.org/10.1108/SCM-11-2023-0585
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Using the security triad to assess blockchain technology in public sector applications, the state of play of blockchain technology in the financial services sector: a systematic literature review, blockchain technology in financial services: a comprehensive review of the literature, demystifying blockchain: a critical analysis of challenges, applications and opportunities, application of blockchain in dealing with sustainability issues and challenges of financial sector, blockchain and insurance: a review for operations and regulation, blockchain adoption in academia: promises and challenges, emerging advances of blockchain technology in finance: a content analysis.
Foresight brief early warning , emerging issues and futures, 11 references, blockchain: blueprint for a new economy, blockchain: : regulating the future of finance, the interplay between decentralization and privacy: the case of blockchain technologies, is disruptive blockchain technology the future of financial services, the invisible politics of bitcoin: governance crisis of a decentralized infrastructure, decentralizing privacy: using blockchain to protect personal data, not-so-open access to legal scholarship: balancing stakeholder interests with copyright principles, virtual currencies; bitcoin & what now after liberty reserve, silk road, and mt. gox, bitcoin: a regulatory nightmare to a libertarian dream, the economics of bitcoin mining, or bitcoin in the presence of adversaries, related papers.
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I n less than a decade, distributed ledger technology (DLT), most notably blockchain, has transformed the way the financial services (FS) sector thinks about payments transactions, and the resulting knowledge is being applied to many other proof-of-concept projects.
There is great potential for other fields to build on initial FS experience and apply DLT to a whole range of business processes and transactions. For some businesses that may be to maximize process efficiencies. For others it could mean a complete re-imagining of traditional operating models.
The levels of interest, activity and investment now being seen across FS and other industries is a clear indicator of belief in the technology’s potential. However, the question remains as to where and when truly transformative impacts will be seen.
So what is DLT, exactly? In simple terms, DLT is a distributed database that allows multiple parties to track transactions transparently and record entries on a shared ledger that is trusted by all parties. A “transaction” in this scenario could relate to financial instruments such as money or stocks and shares, or other assets such as diamonds, houses or land, and could even relate to intellectual property, copyrights or patents. This adaptability is a key reason why, although originating in the field of payments and value exchange, DLT holds such potential for different and diverse sectors.
One of the most important features of DLT is the use of cryptographic technology to prevent tampering, giving confidence to users that the contents of the shared ledger can be trusted by providing a permanent and transparent history of the transactions.
Blockchain may be both the most-hyped and yet least understood of all the technologies disrupting our modern world. In one recent global survey, 80% of those who had heard of blockchain admitted that they didn’t know what it really does.
Many of those who think they do grasp blockchain probably equate it principally with bitcoin, the most prominent of many emerging cryptocurrencies that are shaking up the financial world. Blockchain is the technology that provides the transaction platform to securely record transfers of bitcoins from one party to another, thus the two are often conflated.
It’s not surprising that DLT has come to be seen as a banking-specific technology. But DLT could have profound implications far beyond the world of finance. For example, multinational manufacturers are considering applying DLT to create more efficient, transparent and sustainable global supply chains, and in the pharmaceutical sector, DLT is being investigated as a way to guarantee fully transparent clinical trials of new drugs, and the accounting industry could benefit from a DLT approach to auditing and corporate reporting.
In short, any sector dependent on building trust within the business, and with partners and suppliers, has the potential to improve its operations through DLT.
To help gauge the growing importance of blockchain (and DLT in general) within business, Cambridge University’s Centre for Alternative Finance, with support from EY and Visa.
It surveyed more than 200 DLT infrastructure providers, application developers, service providers and operators across a range of industry sectors. Its findings show that, while the financial sector continues to lead the way in DLT innovation, other sectors are starting to catch up.
When DLT service providers were asked what type of businesses are using their technologies, they confirmed that many sectors and subsectors are already active users. More than a third said they had customers that were regulators or government agencies – indicating the relevance of DLT to the public sector. One quarter cited private individuals, while almost a fifth said that creative artists were customers. Clients as diverse as energy companies, title and real estate companies, airlines, retailers, hospitals and health care organizations are all testing or using DLT applications.
Given the range of potential applications for DLT, it’s not surprising that the technology industry has invested considerably in creating generic platforms and frameworks that can be adapted to any number of projects across a variety of industries. Some enterprise DLT frameworks have been downloaded more than 20,000 times. However, two-thirds of the study participants said they were focused on developing sector-specific solutions that are purposefully designed to serve a particular set of use cases.
Although providers of technology solutions are not yet the largest customer segment for DLT, many are considering DLT to improve and complement their own product offerings. System integrators and Internet of Things (IoT) companies, along with know your customer (KYC) regulatory specialists, all are experimenting with DLT platforms.
From a corporate user point of view, the study looked at 132 different DLT enterprise case studies across all sectors. While it wasn’t surprising to see that 30% are related to banking and financial services, it is notable that the government sector has been more proactive in proof of concept programs than many private industry sectors including insurance, health care and media, entertainment and gaming.
As noted above, and unsurprisingly given DLT’s association with cryptocurrencies, financial services, payments and banking services are the sectors where most DLT activity currently is taking place. Capital markets clearly dominate in terms of the number of existing DLT projects, but insurance and trade finance also are seen as ripe for disruption.
More than half of the DLT service providers surveyed said they were targeting regulatory compliance and audit use cases; the same percentage are focusing on digital identity while just under half are looking at the health care and public sectors. Just over 40% say they are looking at DLT to improve supply chain at the moment – a figure that will surely grow once the technology becomes embedded in mainstream business.
But DLT isn’t just about optimizing existing processes or transactions. Applied effectively, it can bring about new transactions and facilitate new operational models.
Partnering with blockchain leader Guardtime, and multiple industry participants, EY created a blockchain program that connects clients, brokers, insurers and third parties to distributed common ledgers. These capture data about identities, risk and exposures, and integrate this information with insurance contracts. This program is the first to apply blockchain’s transparency, security and standardization to marine insurance.
In doing so, the program brings industry-wide transparency to a traditionally convoluted insurance process through real-time visibility into the location, condition and safety of high-value assets moving around the world. This helps clients to ensure accurate and fair underwriting and pricing as well as more streamlined regulatory reporting and compliance.
Following the proof-of-concept stage the program is now set for commercial use. As more marine companies and insurers adopt blockchain, the ripple effect of efficiencies caused by new technology and processes could transform one of the oldest established area of insurance – one which has grown to become a US$30b global ecosystem.
To help the automotive and transportation industry as it becomes increasingly integrated, on-demand, personalized and autonomous, EY created Tesseract, an integrated mobility platform underpinned by blockchain technology.
The platform facilitates fractional vehicle ownership, shared use and seamless multimodal transport, helping to lay the groundwork for how autonomous vehicle fleets can be owned in the future and providing access to a variety of on-demand mobility options.
Tesseract brings together multiple stakeholders including original equipment manufacturers, mobility and transport companies, cities and infrastructure providers on a single platform to facilitate new value and revenue streams. It can also help consumers gain access to the right type of vehicle for their ideal journey, on demand.
With Tesseract, single vehicles, fleets and other transport services are available on the platform. Vehicles and trips are digitally logged on the blockchain, and transactions are automatically settled between owners, operators and third-party service providers through a single-source, usage-based payment system. Ownership of the assets is flexible and can be on a full or fractional share basis. As new business models and income streams are created, funding of expensive assets such as batteries and charging infrastructure will become much easier.
Sustainable energy and mobility have developed rapidly in the past five years. Tesseract aims to better connect these complementary parts of the intermodal transport ecosystem, to deliver faster and more profound change and build a better world.
Blockchain’s rise began as the platform for a monetary payment solution but was soon embraced by many other parts of the FS sector. That evolution, both in terms of technology and culture, has made FS a leader in DLT experimentation. So what does a business need to consider in order to get the most out of DLT?
Nearly a decade on from blockchain’s introduction to the business world, the depth and breadth of DLT experimentation currently in motion demonstrates just how influential this new way of ensuring transactional trust, credibility and accountability could be across all industries. The FS sector is leading the way. However, despite its potential, the technology still has a long way to travel to full maturity and large scale adoption.
As genuine understanding of this emerging technology grows, now is the time to start asking how it could be most beneficial in the transformation of your own business.
To benefit from DLT, leaders should consider the potential impact on their organizations and test and learn.
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Global investment in blockchain technology is skyrocketing (see Figure 1) because blockchain can enhance data exchange in multi-party processes thanks to:
Blockchain pioneers have a chance to acquire a competitive edge . However, executives have many investment alternatives and maturity of some blockchain based solutions is low. Therefore, executives need to make smart decisions to invest in an optimal manner in blockchain based solutions.
In this article, we present 7 blockchain case studies. Real-world examples can help executives identify solution areas that are mature enough for investment.
Figure 1: Blockchain market size in billion US dollars
1. blockchain ease supplier master data management: trust your supplier.
Business challenge:
Trust Your Supplier saw an opportunity to reduce costs and effort when it came to finding and onboarding a reputable supplier. Supply chain interruptions and quality expectations to comply with regulations or stakeholders’ environmental and social concerns , are two important risk aspects that firms must deal with. Finding a suitable supplier is a time-consuming and expensive process for businesses because verifying and obtaining data from providers is difficult since companies do not want to share their data openly.
Initiative:
Trust Your Supplier collaborated with IBM to create an open source blockchain platform that allows businesses to securely and effectively share data with permissioned partners. Platform allows businesses to have their data confirmed by third-party verifiers such as:
Once your company’s data is confirmed, a blockchain-based corporate digital passport is created, allowing:
For both exporters and importers, international trading can be risky. When an importer pays in advance for goods, the exporter may collect the cash without sending the goods. However, if the exporter agrees to receive payment after delivery, the importer may refuse to pay after receiving the products. To overcome this problem, traders collaborate with third parties such as banks that employ instruments like letters of credit , which guarantee payment once goods are delivered to the importer.
Marco Polo Network utilizes blockchain technology to provide a platform for exporters and importers to transparently share delivery data by integrating with supply chain ERP systems and creating an irrevocable contract for parties that guarantees the exchange of money and goods under specified conditions (e.g. money transferred when goods receives the importer).
Initiative potentially eliminates the need for third party existence that solves “trust issue”. However, third parties also involve and benefit while they are using Marco Polo Network’ solution since the platform increases transparency.
3. blockchain improves compliance: renault .
The automotive sector is highly regulated . Renault, for example, deals with 6,000 regulatory and quality characteristics relating to:
A vehicle must meet certain internal and external compliance criteria in order to be offered on the market. A change in regulations needs to be communicated downstream to suppliers and suppliers of suppliers to ensure that they all build according to the new specifications. Therefore, Renault needed a platform throughout the ecosystem in a transparent manner to ensure compliance.
Renault and IBM collaborated to create the automotive industry’s first extended compliance end-to-end distributed blockchain platform for the traceability of components internal and external regulatory compliance.
After 300,000 newborns were sickened with melamine from powdered milk products in 2008, Chinese parents ‘ trust in infant nourishment products was damaged. Nestle was looking for ways to reassure Chinese parents about the quality of their newborn nourishment product NAN A2 to penetrate the market effectively.
Nestle teamed up with Techrock , a Chinese technology firm, to create a public blockchain platform that integrates with a mobile app . As a result, parents can verify the NAN A2’s following characteristics using their phone:
Etherisc is an insurtech startup that was looking for ways to speed up the claims processing. Traditional claims processing comprises five processes, as shown in Figure 2. Though the time it takes to settle a claim varies by insurance company and type, it usually takes weeks. However, according to EY , nearly 90% of insureds choose an insurer based on the quality and speed of claims processing.
Figure 2: Steps of Claims Processing
To automate claims processing Etherisc uses blockchain technology which enables smart contracts that enforce the agreement when the certain conditions specified on the contract are met.
Etherisc employed third-party data providers to determine if the payment arrangement’s terms were met or not (see Figure 3). Therefore, after alerting the insurance provider, Etherisc evaluates the initial claim investigation and policy check processes in real time, increasing its claims processing efficiency.
Figure 3: Claims processing with blockchain
TenneT , situated in the Netherlands and Germany, is an energy transmission operator. Because energy demand and supply are not always in balance, electricity distribution is difficult. Energy productivity of sustainable energy supplies varies instantly depending on the state of the weather. Wind turbine electricity generation, for example, differs depending on the wind conditions of the day. Similarly electricity demand varies within the day. Thus, optimizing electricity distribution becomes a challenging issue.
To optimize the power grid Tennet cooperated with IBM and Sonnen. IBM deployed blockchain Sonnen, producer of home energy storage systems provides an opportunity for interaction with minor energy producers and consumers.
Energy storage systems linked to the TenneT’s power grid database via blockchain. Thanks to blockchain’s distributed ledger, inaccuracies in the demand and supply of electricity are transparently shared with a variety of stakeholders. Initiative enables the connected energy storage units to collect or release additional electricity as needed in a couple of moments, reducing grid transmission inefficiencies.
Many businesses do not have the opportunity to present the true value of their assets to potential investors so some companies are undervalued. IPwe intended to transform the inefficient old IP system, in which patent holders, lawyers, corporations, intermediaries, and global patent offices lack communication for a variety of reasons, including the inability to transfer information from one source to another transparently.
IPwe teamed up with IBM to create a blockchain that allows IP to be tokenized and stored in the cloud. As a result, traders have easy access to IP and can invest in it based on clear data. IPwe also provides a place for businesses to fairly advertise their intellectual property.
If you think blockchain could help your company, use our data-driven lists to compare the best blockchain platforms and services .
If you have further questions regarding blockchain you can contact us:
This article was drafted by former AIMultiple industry analyst Görkem Gençer.
12 blockchain in supply chain case studies in 2024, process mining blockchain in 2024: top 4 use cases & case studies, is pi network a scam providing no value to users possibly yes.
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This research investigates opportunities for deploying blockchain-based regulatory technology (RegTech) in the real estate industry, particularly the mortgage application process in real estate transactions. The real estate industry entails a broad range of regulatory requirements. Processes to fulfil these requirements are primarily inefficient and costly. Blockchain features many characteristics that can effectively deploy RegTech to make real estate transactions more efficient, accurate, faster and at a lower cost. This paper conducts a literature review and semi-structured interviews with a range of industry stakeholders to reveal four main categories of problems in the sector, examine five use cases of blockchain deployments, study in-depth the mortgage process as the primary target area for blockchain-based RegTech deployment, propose six desired attributes of an ideal mortgage process and offer a solution framework to encompass these attributes. The study also considers the limitations of blockchain-based RegTech solutions and suggests future considerations for such development.
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Blockchain technology in real estate: potential future and challenges, how blockchain technology is transforming the real estate market.
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Ru Ray Raymond Chao, Joseph K. Liu & Kai Su
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Cristina Alcaraz
Concordia University, Montreal, QC, Canada
Suryadipta Majumdar
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Chao, R.R.R., Liu, J.K., Su, K. (2022). Blockchain Based Regulatory Technology Deployment for Real Estate Transaction. In: Yuan, X., Bai, G., Alcaraz, C., Majumdar, S. (eds) Network and System Security. NSS 2022. Lecture Notes in Computer Science, vol 13787. Springer, Cham. https://doi.org/10.1007/978-3-031-23020-2_32
DOI : https://doi.org/10.1007/978-3-031-23020-2_32
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The adoption of digital technologies by small and medium-sized enterprises for sustainability and value creation in pakistan: the application of a two-staged hybrid sem-ann approach.
2.1. social media applications (smas), 2.2. ai-enabled applications (aeas), 2.3. big data analytics (bda), 2.4. iot applications (ioas), 2.5. blockchain applications (bcas), 2.6. economic value (ecv), 2.7. social value (sov), 2.8. sme performance, 3. hypothesis development, 3.1. social media applications (smas) and economic value and social value, 3.2. ai-enabled applications (aeas) and economic value and social value, 3.3. big data analytics (bda) and economic value and social value, 3.4. iot applications (ioas) and economic value and social value, 3.5. blockchain applications (bcas) and economic value and social value, 3.6. economic value (ecv) and sme performance, 3.7. social value (sov) and sme performance, 4. research methodology, 4.1. research design, 4.2. data collection: procedure and sample, 4.3. measures, 4.4. statistical analysis, 5.1. demographic characteristics, 5.2. measurement model evaluation, 5.3. structural model evaluation, 5.4. artificial neural network analysis, 5.5. ranking of predictors, 6. discussion, 6.1. theoretical implications, 6.2. practical implications, 7. conclusions, 7.1. limitations and future research, 7.2. future research directions, author contributions, institutional review board statement, informed consent statement, data availability statement, acknowledgments, conflicts of interest.
SMAs | Social media applications are very popular among younger people. | 1 | 2 | 3 | 4 | 5 |
I believe different social media applications provide business value to our enterprise. | 1 | 2 | 3 | 4 | 5 | |
I think SMEs are dependent on social media to fulfill their marketing requirements. | 1 | 2 | 3 | 4 | 5 | |
I believe that social media helps develop business activities for SMEs. | 1 | 2 | 3 | 4 | 5 | |
AEAs | SMEs apply AI technologies to help them remodel various business activities. | 1 | 2 | 3 | 4 | 5 |
I believe applications of AI can help in the supply chain activities of SMEs. | 1 | 2 | 3 | 4 | 5 | |
Applications of AI can reduce the operational cost of SMEs. | 1 | 2 | 3 | 4 | 5 | |
I believe that SMEs can use AI applications to develop their customer interaction process. | 1 | 2 | 3 | 4 | 5 | |
BDA | I believe that data analytics has gained huge momentum in recent years. | 1 | 2 | 3 | 4 | 5 |
The application of big data analytics helps in the real-time analysis of customer data. | 1 | 2 | 3 | 4 | 5 | |
I believe that applications of big data analytics help in the decision-making process. | 1 | 2 | 3 | 4 | 5 | |
I think SMEs should adopt big data analytics technology to gain a competitive advantage. | 1 | 2 | 3 | 4 | 5 | |
IoT | The IoT can facilitate the rapid exchange of data in a real-time scenario. | 1 | 2 | 3 | 4 | 5 |
I believe that applications of the IoT can help in improving the upscaling process in the SMEs. | 1 | 2 | 3 | 4 | 5 | |
Applications of the IoT can provide a scalable information system that helps SMEs exchange information quickly. | 1 | 2 | 3 | 4 | 5 | |
Applications of the IoT help SMEs sense, seize, and reconfigure external opportunities. | 1 | 2 | 3 | 4 | 5 | |
BCAs | Blockchain is considered a digital ledger, which presents the detailed history of various transactions. | 1 | 2 | 3 | 4 | 5 |
I believe blockchain technology can save operational costs for SMEs. | 1 | 2 | 3 | 4 | 5 | |
I think applications of blockchain are secured for SMEs. | 1 | 2 | 3 | 4 | 5 | |
I believe that SMEs should adopt blockchain technology to gain a competitive advantage. | 1 | 2 | 3 | 4 | 5 | |
ECV | SMEs can gain economic value through profit maximization. | 1 | 2 | 3 | 4 | 5 |
The adoption of different technologies can provide economic value to SMEs. | 1 | 2 | 3 | 4 | 5 | |
The economic value changes if the price of the good or the service changes. | 1 | 2 | 3 | 4 | 5 | |
I believe that SME leadership should focus more on adopting new-edge technologies. | 1 | 2 | 3 | 4 | 5 | |
I believe product development costs can be significantly reduced if SMEs adopt appropriate technologies. | 1 | 2 | 3 | 4 | 5 | |
SOV | SMEs can gain social benefits if they perform their work to benefit society. | 1 | 2 | 3 | 4 | 5 |
I believe that social value emerges from the concept of corporate social responsibility programs. | 1 | 2 | 3 | 4 | 5 | |
Improving social value is an important aspect of SMEs. | 1 | 2 | 3 | 4 | 5 | |
Customers may favor those SMEs that spend more to uplift the society. | 1 | 2 | 3 | 4 | 5 | |
I believe that social values are shared values among the employees of the SMEs. | 1 | 2 | 3 | 4 | 5 | |
SMP | I believe that the performance of SMEs can be improved by appropriately adopting modern technologies. | 1 | 2 | 3 | 4 | 5 |
The social value of SMEs can impact the overall performance of SMEs. | 1 | 2 | 3 | 4 | 5 | |
Leadership support can play a crucial role in improving SME performance. | 1 | 2 | 3 | 4 | 5 |
Click here to enlarge figure
Demographic Characteristics | N (305) | (%) |
---|---|---|
Male | 238 | 78.0 |
Female | 67 | 22.0 |
Total | 305 | 100 |
20–30 years | 81 | 26.6 |
31–40 years | 102 | 33.4 |
41–50 years | 53 | 17.4 |
51–60 years | 55 | 18.0 |
61 years and above | 14 | 4.60 |
Total | 305 | 100 |
Never attended school | 46 | 15.1 |
Primary | 34 | 11.1 |
Secondary | 116 | 38.0 |
Tenth Grade | 40 | 13.0 |
Twelfth Grade | 33 | 10.8 |
Graduation | 15 | 4.90 |
Graduation and higher | 21 | 6.90 |
Total | 305 | 100 |
Sukkur | 164 | 53.8 |
Larkana | 95 | 31.1 |
Jacobabad | 17 | 05.6 |
Khairpur | 29 | 09.5 |
Total | 305 | 100 |
Manufacturing | 60 | 19.7 |
Retail | 91 | 29.8 |
Wholesale | 32 | 10.5 |
Agriculture | 39 | 12.8 |
Livestock | 21 | 6.90 |
Poultry | 24 | 7.90 |
Services | 18 | 5.90 |
Other | 20 | 6.60 |
Total | 305 | 100 |
Constructs | Factor Loading | CR | AVE | A |
---|---|---|---|---|
AI-Enabled Application (AEA) | 0.89 | 0.95 | 0.77 | 0.91 |
0.91 | ||||
0.87 | ||||
0.86 | ||||
Blockchain Application (BCA) | 0.75 | 0.88 | 0.64 | 0.82 |
0.78 | ||||
0.86 | ||||
0.82 | ||||
Big Data Analysis (BDA) | 0.86 | 0.92 | 0.74 | 0.88 |
0.86 | ||||
0.85 | ||||
0.86 | ||||
Economic Value (ECV) | 0.81 | 0.90 | 0.63 | 0.86 |
0.77 | ||||
0.77 | ||||
0.87 | ||||
0.77 | ||||
IoT Application (IoA) | 0.82 | 0.88 | 0.65 | 0.82 |
0.78 | ||||
0.86 | ||||
0.76 | ||||
Social Media Application (SMA) | 0.82 | 0.88 | 0.65 | 0.82 |
0.83 | ||||
0.83 | ||||
0.76 | ||||
SME Performance (SMP) | 0.77 | 0.87 | 0.69 | 0.77 |
0.87 | ||||
0.84 | ||||
Social Value (SOV) | 0.77 | 0.88 | 0.59 | 0.82 |
0.81 | ||||
0.83 | ||||
0.73 | ||||
0.68 |
Constructs | AEA | BCA | BDA | ECV | IoT | SMA | SMP | SOV |
---|---|---|---|---|---|---|---|---|
AEA | ||||||||
BCA | 0.07 | |||||||
BDA | 0.05 | 0.12 | ||||||
ECV | 0.08 | 0.83 | 0.20 | |||||
IoA | 0.05 | 0.70 | 0.15 | 0.78 | ||||
SMA | 0.07 | 0.60 | 0.07 | 0.71 | 0.78 | |||
SMP | 0.07 | 0.64 | 0.12 | 0.78 | 0.75 | 0.63 | ||
SOV | 0.07 | 0.96 | 0.20 | 0.84 | 0.82 | 0.71 | 0.78 |
Constructs | AEA | BCA | BDA | ECV | IoT | SMA | SMP | SOV |
---|---|---|---|---|---|---|---|---|
AEA | ||||||||
BCA | 0.06 | |||||||
BDA | −0.03 | 0.10 | ||||||
ECV | 0.02 | 0.70 | 0.17 | |||||
IoA | 0.02 | 0.58 | 0.13 | 0.66 | ||||
SMA | −0.05 | 0.49 | 0.04 | 0.60 | 0.65 | |||
SMP | 0.01 | 0.51 | 0.10 | 0.63 | 0.60 | 0.50 | ||
SOV | 0.05 | 0.80 | 0.18 | 0.71 | 0.67 | 0.59 | 0.61 |
Variables | R | Adjusted R | Remarks |
---|---|---|---|
Economic Value (ECV) | 0.62 | 0.61 | Substantial |
SME Performance (SMP) | 0.45 | 0.44 | Moderate |
Social Value (SOV) | 0.73 | 0.72 | Substantial |
Hypotheses | β | t-Value | Decision |
---|---|---|---|
H1a = SMAs → ECV | 0.44 | 8.72 | Supported |
H1b = SMAs → SOV | 0.49 | 8.50 | Supported |
H2a = AEAs → ECV | 0.01 | 0.17 | Unsupported |
H2b = AEAs → SOV | 0.02 | 0.65 | Unsupported |
H3a = BDA → ECV | 0.22 | 4.23 | Supported |
H3b = BDA → SOV | 0.16 | 3.07 | Supported |
H4a = IoAs → ECV | 0.25 | 4.07 | Supported |
H4b = IoAs→ SOV | 0.22 | 4.14 | Supported |
H5a = BCAs → ECV | 0.09 | 2.23 | Supported |
H5b = BCAs → SOV | 0.08 | 2.26 | Supported |
H6 = ECV → SMP | 0.40 | 5.34 | Supported |
H7 = SOV → SMP | 0.32 | 4.01 | Supported |
Training | Testing | |||||
---|---|---|---|---|---|---|
N | SSE | RMSE | N | SSE | RMSE | Total Samples |
271 | 79.418 | 1.8472 | 34 | 07.932 | 0.4830 | 503 |
277 | 88.778 | 1.7663 | 28 | 11.026 | 0.6275 | 503 |
278 | 86.833 | 1.7892 | 27 | 10.170 | 0.6137 | 503 |
271 | 83.905 | 1.7971 | 34 | 8.602 | 0.5030 | 503 |
265 | 80.203 | 1.8177 | 40 | 11.350 | 0.5327 | 503 |
275 | 83.102 | 1.8191 | 30 | 12.765 | 0.6523 | 503 |
266 | 79.519 | 1.8289 | 39 | 12.562 | 0.5675 | 503 |
274 | 79.674 | 1.8544 | 31 | 17.014 | 0.7408 | 503 |
271 | 83.813 | 1.7981 | 34 | 07.280 | 0.4627 | 503 |
277 | 87.066 | 1.7836 | 28 | 04.042 | 0.3799 | 503 |
271 | 79.418 | 1.8472 | 34 | 07.932 | 0.4830 | 503 |
277 | 88.778 | 1.7663 | 28 | 11.026 | 0.6275 | 503 |
Mean | 83.231 | 1.8102 | Mean | 10.274 | 0.5563 | |
SD | 3.3075 | 0.0268 | SD | 3.3865 | 0.1001 |
Neural Network (NN) | BCA | BDA | IoA | SMA |
---|---|---|---|---|
NN (i) | 0.15 | 0.56 | 1.00 | 0.52 |
NN (ii) | 0.03 | 0.95 | 1.00 | 0.97 |
NN (iii) | 0.25 | 0.44 | 1.00 | 0.39 |
NN (iv) | 0.04 | 0.70 | 1.00 | 0.59 |
NN (v) | 0.17 | 0.40 | 1.00 | 0.52 |
NN (vi) | 0.10 | 0.95 | 1.00 | 0.83 |
NN (vii) | 0.10 | 0.11 | 1.00 | 0.23 |
NN (viii) | 0.22 | 0.64 | 1.00 | 0.56 |
NN (ix) | 0.08 | 0.35 | 1.00 | 0.48 |
NN (x) | 0.19 | 0.77 | 1.00 | 0.63 |
Average importance | 0.58 | 0.52 | 0.72 | 0.36 |
Normalized importance (%) | 19% | 77% | 100% | 63% |
The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
Soomro, R.B.; Memon, S.G.; Dahri, N.A.; Al-Rahmi, W.M.; Aldriwish, K.; A. Salameh, A.; Al-Adwan, A.S.; Saleem, A. The Adoption of Digital Technologies by Small and Medium-Sized Enterprises for Sustainability and Value Creation in Pakistan: The Application of a Two-Staged Hybrid SEM-ANN Approach. Sustainability 2024 , 16 , 7351. https://doi.org/10.3390/su16177351
Soomro RB, Memon SG, Dahri NA, Al-Rahmi WM, Aldriwish K, A. Salameh A, Al-Adwan AS, Saleem A. The Adoption of Digital Technologies by Small and Medium-Sized Enterprises for Sustainability and Value Creation in Pakistan: The Application of a Two-Staged Hybrid SEM-ANN Approach. Sustainability . 2024; 16(17):7351. https://doi.org/10.3390/su16177351
Soomro, Raheem Bux, Sanam Gul Memon, Nisar Ahmed Dahri, Waleed Mugahed Al-Rahmi, Khalid Aldriwish, Anas A. Salameh, Ahmad Samed Al-Adwan, and Atif Saleem. 2024. "The Adoption of Digital Technologies by Small and Medium-Sized Enterprises for Sustainability and Value Creation in Pakistan: The Application of a Two-Staged Hybrid SEM-ANN Approach" Sustainability 16, no. 17: 7351. https://doi.org/10.3390/su16177351
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