Professor George Saridakis
The Kent University, Business School, Department of Marketing, Entrepreneurship and International Business, UK
Professor Vladlena Benson
Aston University, Business School, Cyber Security Innovation Research Centre, UK
Dr Mamata Parhi
University of Roehampton, Faculty of Business and Law, Centre for Sustainability and Responsible Management, UK
Professor Patrick Mikalef
Norwegian University of Science and Technology, Department of Computer Science, Norway
Motivation
The growth trajectories of nations often correlate to the timeframes of creation and diffusion of new technologies (Craighead & Meredith, 2008) which – time and again, have unleashed ingenuity of the mankind and harnessed the seemingly boundless imagination. Distributed Ledger Technology (DLT) is one such technology, invented recently, it enables the function of a decentralised digital ledger. The foundation of DLT relies on the nature of distributed networks eliminating the need for a centralised authority to preserve records’ integrity. Undoubtedly, in the age of fast-paced data intelligence, the nexus of technology and knowledge of how firms transform information into a new kind of `trust’ capital in a wide range of services, generated a new research agenda (Dubey et al., 2020). The impact of DLT on the enhancement of productivity growth of corporations and optimisation of business resilience, are yet to be fully understood by researchers and practitioners. There are some disconnected research efforts, yet the theoretical mechanism through which DLT is envisaged to unleash sustainability and superiority of productivity growth, underpinned by the enhancement of business resilience (Dubey et al., 2019), is sparse. Still lacking is the rigorous empirical research, relying on primary or secondary data (Fisher et al., 2019). This Special Issue (SI) has a focused objective to bring within one common lens a theoretical architecture and theory-driven empirical design which provide a first-hand mechanism to position various aspects of DLT for productivity growth.
Business resilience, as a concept, has become more important than ever, thanks to an array of risks business organizations have been facing following the pandemic crisis. Resilience encompasses (at least second-best Pareto optimum) pathways of crisis management leading to business continuity and maximum welfare. This responds to all types of risk that an organisation may face, from cyber threat to natural disaster. Besides addressing the consequences of a major incident, business resilience relates to the ability of an organisation to adapt to the new environment and circumstances following that incident. Exhibit 1 presents a generic model (the graphic is adapted from McKinsey (2021) through which we can visualise how DLT can upscale business resilience and contribute to greater level of productivity in enterprises. The optimisation problem can be seen in both ways: maximisation of productivity (y) or minimization of manipulation risk (R). One way to achieve is to make full use of the potential of the distributed network that decentralises digital database (see Choi et al., 2020 with regard to on-demand service platform) and puts a natural check against manipulation. In most organisations, the potential risk of system failure lies in the probability of manipulation by a single ‘source’. The distributive structure of DLT, as well, distributes the risks of manipulation, by improving allocative efficiency of various sources within the main source, in a way, the aggregation of such heterogeneous maximisation of distributed pathways, can lead to higher order optimum than can be achieved with a single agent (in a network context, a potential structural hole). The DLT helps, in natural way of its design, to eliminate the presence of a structural hole in a production or any other form of business optimisation network. Wider transparency offers a strong foundation of business resilience, and therefore, via ‘accountability’ and auditability to every stage of decision making, the transparency can lead to greater productivity1. DLT indeed provides an effective pathway of distinct productivity gains in enterprises through efficacy of operational management and an optimal choice of risk and return at each decision node. Recent applications of DLT include the topics of green bond (to mitigate the problem of wasteful investment in shadow green projects, broadly ‘greenwashing’, see Yoshino et al., 2021).
A particular term that can cause confusion is ‘distributed’, which can lead to the misconception that because something is distributed there is therefore no overall controlling authority or owner. This may or may not be the case — it depends on the design of the ledger. In practice, there is a broad spectrum of distributed ledger models, with different degrees of centralisation and different types of access control, to suit different business needs. These may be ‘unpermissioned’ ledgers that are open to everyone to contribute data to the ledger and cannot be owned; or ‘permissioned’ ledgers that may have one or many owners and only they can add records and verify the contents of the ledger. The key message is that, by fully understanding the technology, enterprises and governments can choose the design that best fits a particular purpose, balancing security and central control with the
A distributed ledger is essentially an asset database that can be shared across a network of multiple sites, geographies or institutions. Because all participants within a network can have their own identical copy of the ledger, any changes to the ledger are reflected in all copies in minutes, or in some cases, seconds. Entries can also be updated by one, some or all of the participants, according to rules agreed by the network.
convenience and opportunity of sharing data between institutions and individuals. The SI call aims to investigate this issue further with both theoretical design and empirical evidence.
1.1 New ways of thinking
Although much has been written to break the conceptual and methodological jinx surrounding DLT, not much is known on how it holds a great predictive power of greater welfare gains in corporations than just appearing as a foremost model of disruptive business. Every new technology is ‘path-breaking’ and its adaptation is slower than would be desired. But DLT is diffusing faster, most possibly because the environment or conditions needed for adoption and diffusion are appropriate. For instance, we are already operating in a digitalised world and most of the conventional modes of operations and management are being steadily replaced by digitalisation. The DLT is challenging our accepted practices and in effect our mental models of how the world works. We are interested in shedding deeper insights into the following sub-themes:
- Shared data. In the current “centralized” paradigm, data and various information on decision making are stored in multiple repositories in which data are duplicated and necessarily continuously updated and reconciled. This results in extra frictional costs in reconciling balances and transferring information between institutions. A shared, distributed ledger would render this system redundant, yet, through responsible auditing and accountability, and most importantly via shared risks, can make the system highly productive.
- New models. The above may lead to new operational management and business optimisation models to maximise productivity gains. Any supply chain based on DLT and smart contracts, in which payments or value transfers are made with the transaction, could significantly affect the need to carry working capital. Already, the music industry is experimenting with such a system to manage the distribution of royalty payments, so that when a piece of music is bought online its associated smart contract could take the money from your bank account and instantly pay the artist.
Objectives
The Special Issue (SI) will welcome papers that try to: - Theme 1: Provide theoretical mechanisms (for example, using network and (mean-variance) decision theory) to lay a testable empirical foundation that can explore the dynamic interlinkages among DLT’s capability, minimisation of manipulation through fraud-mitigation, accountability via auditability, leading to business resilience. This business resilience will lead to superior productivity performance. In this regard, authors may use, for instance, the theory of stochastic dominance and network dynamics, or any other theoretical settings that have strong implications for business productivity growth.
- Theme 2: Strong empirical work, that are theory-driven using both primary and secondary data.
With these two broad interests in our call, we aim to focus on various sub-themes which are strongly interconnected to one or both streams of objectives mentioned above:
i. Explore the block chain technology acceptance, and the adoption of DLTs worldwide. Examine the economic impact of DLT innovation on financial and non-financial sectors.
ii. Gain an understanding of how block chain and cryptocurrency can contribute to economic performance and well-being: this can be both at corporations’ level or aggregate level such as cross-country panel data study (with stochastic frontier mechanism or Data Envelopment Analysis or similar mechanisms).
iii. Investigate the relationships between cryptocurrencies, block chain and DLT technologies.
iv. Explore the DLT related financial and non-financial regulatory and legislation frameworks to prevent fraudulent actions.
v. Examine the effect of blockchain and cryptocurrencies on economic transactions, trade, employment, and smart contracts.
vi. Investigate organisational and institutional barriers and capability difficulties in adjusting to DLTs.
vii. Discuss difference in DLT adoption experience and support between SMEs’ and large firms.
viii. Contrast DLT creativity and innovation between developed and developing countries.
ix. Allow cross-country comparisons in firm technological and cryptocurrency adoption strategies and C-level attitudes as well as in outcomes.
x. Examine Organisational strategies towards facing and reducing cyber risks in the blockchain and crypto assets.
xi. Explain how DLT can strengthen the trust between firms, consumers, and investors.
xii. Examine the link between DLTs, energy markets and sustainable infrastructure.
The papers will have a strong policy-influencing implications for short-, medium- and long-run impacts and strategies, which may lead to informing current global policy making efforts in developing cryptocurrency regulation and digital-informed leadership and education and encouraging the development of DLT firms and reducing associated risks.
To this end, the SI can activate profound changes to support the economy through security, confidentiality, data consistency and improved efficiency. Also, it can highlight the main challenges and opportunities associated with DLT and generalise a set of priority matters for stakeholders which could potentially be addressed through policy development.
References
Choi, Tsan-Ming, Guo, Shu Liu, Na Shi Xiutian (2020) ‘Optimal pricing in on-demand-service-platform-operations with hired agents and risk-sensitive customers in the blockchain era’, European Journal of Operational Research, 284(3):1031-1042.
Craighead, C. W. and Meredith, J. (2008). Operations management research: evolution and alternative future paths. International Journal of Operations & Production Management, 28(8): 710-726.
Dubey, R., Gunasekaran, A., Childe, S. J., Papadopoulos, T., Blome, C. and Luo, Z. (2019).
Antecedents of resilient supply chains: an empirical study. IEEE Transactions on Engineering
Management, 66(1): 8-19.
Dubey, R, Gunasekaran, A, Bryde, DJ, Dwivedi, Y and Papadopoulos, T. (2020) Blockchain technology for enhancing swift-trust, collaboration and resilience within a humanitarian supply chain setting. International Journal of Production Research, 58 (11): 3381-3398.
Fisher, M., Olivares, M. and Staats, B. R. (2019). Why Empirical Research Is Good for Operations
Management, and What Is Good Empirical Operations Management? Manufacturing & Service Operations Management DOI: 10.1287/msom.2019.0812
McKinsey Report (2021). https://www.mckinsey.com/industries/public-and-social-sector/our-insights/rethinking-resilience-ten-priorities-for-governments
Yoshino, N., T. Schloesser, and F. Taghizadeh-Hesary (2021). Social funding of green financing: An application of distributed ledger technologies, International Journal of Finance and Economics, 26:6060–6073.
Add Comment