Disruptive Innovation in Business and Finance in the Digital World: Volume 20

Disruptive digital technological innovation has the potential to dramatically alter the corporate landscape as we know it. The authors explore this premise by examining both industry practices and their conceptual bases in the digital age. The authors then describe cases and trends in the three main mediums of digital innovation – artificial intelligence, fintech, and blockchain. The authors focus on how these innovative technologies can impact the firms by creating values as part of corporate strategy, and by changing the way employees work. However, the impacts will likely go well beyond business and finance, and are likely to be adopted by healthcare, non-government organizations, and governments as well.

In 1971, the patent for the Automated Teller Machine was awarded to David Wetzel. While possibly not the first application of financial technology, since 1971 time, the innovation in the financial industry has grown beyond expectations. However, most studies in innovation ignore the financial sector altogether. In this study, the authors investigate financial technology firms and innovation. After identifying firms that are considered financial technology, the authors collect innovation outcomes such as patents and data breaches associated with those firms. The authors show that patent activity has enjoyed modest growth year over year; however, firms still have challenges to overcome such as market risk and data security. This study serves as a perspective on financial technology.

The authors analyze the expansion of Big Data and artificial intelligence technologies from the perspective of economic theory. The authors argue that these technologies can be viewed from three perspectives: (1) as an intangible asset; (2) as a search and matching technology; and (3) as a forecasting technology. These points of view shed light on how new technologies are likely to affect matching between firms and consumers, productivity growth, price discrimination, competition, inequality among firms, and inequality among workers.

The authors study the relation between a firm’s combinative capability and value creation in the context of technological scope expansion. On a sample of Compustat firms that applied for US patents between 1980 and 2001, the authors find that firm value, measured using Tobin’s q, decreases with increases in technological scope (measured as the number of unique patent classes). However, when firms expand by combining different classes into a single patent, the authors find that this negative effect is significantly diminished. These findings indicate that increasing technological scope likely creates value only when the firm is able to integrate the components into a single technology; simply maintaining different technological components within the firm boundary without integration appears to subject the firm to a discount.

Literature has numerous debates about the relation between emerging financial environmental, social, and governance (ESG) factors and financial performance with mixed results. The authors use a unique data set generated by big data analytics (from web-based data mining) for three environmental areas (water, land, and air) to test hypothesis in the extreme events (defined as those that are over/under ±2.58 multiplied by the standard deviation) have a high chance of predicting equity price movements within an window of −3/+10 days, respectively, prior to and after the event. The authors repeat the similar robustness study for a sample of 2018 and the results still holds. The authors interpret these findings to suggest that: (1) studies using continuously AI-generated data for ESG categories can have significant predictive power for extreme events; and (2) that such high correlations can be used to confirm the materiality of some ESG data. The authors conclude with noting limitation of this initial study, and present specific areas for future research.

The purpose of this chapter is to demonstrate how blockchain technology – which permits the Internet-based exchange of value (digital assets) – enables supply chain finance banks to overcome the challenges they face when attempting to create win–win transactions for supply chain participants. Traditionally, buyers and suppliers linked together in a supply chain have conflicting objectives as manifested by a zero-sum payoff structure. Suppliers want their invoices to be paid quickly in order to reduce their need for working capital. In contrast, buyers want to delay payment of invoices as long as possible in order to reduce their need for working capital. In other words, suppliers want a short cash conversion cycle; buyers want a long cash conversion cycle. This conflict is eliminated by the insertion of a financial intermediary (supply chain finance bank) between the buyer and the supplier. The bank eliminates the conflict by: (1) using its balance sheet to decouple the cash conversion cycles of the buyer and supplier; and (2) providing cheaper financing to impatient suppliers and reluctant buyers (since the bank has a higher credit rating than both the supplier and the buyer).

As trade policy disruption has become more commonplace, so have the calls for blockchain as a solution. But often the reasoning for this link has been unclear. Using the case study of Brexit as a baseline, the authors map four sources of trade-based uncertainty and explore the extent to which blockchain applications could – when implemented – attenuate supply chain disruption, which has lead to firms taking second best options like reducing investment and switching suppliers. Because the law has not kept pace with technology, the discussion also highlights prominent legal questions raised by blockchain in each instance.

This chapter provides a discussion on some issues in blockchain finance that regulators are concerned about – an area which bitcoin promoters have remained silent about. Blockchain technology in finance has several benefits for financial intermediation in the financial system; notwithstanding, several issues persist which if addressed can make the adoption of blockchain technology in finance easier and accepted by regulators. The blockchain issues discussed in this chapter are relevant for recent debates in blockchain finance.

Distributed ledger technologies, and particularly blockchain, have attracted significant attention recently and we believe that it is right time to look back the literature and digest the accumulated knowledge. The purpose of this study is to contribute to the existing knowledge of blockchain technology by surveying the stock of research about this newly rising technology. We conducted a descriptive analysis of current academic and business research on blockchain technology and categorized the studies according to source, field, approach, geography, affiliation, and cryptocurrency-focus. We accompanied this with a global patent publication analysis and presented our insights and takeaways from our analyses.

Using a recent philosophical account of trustworthiness, the author evaluates whether Bitcoin can be considered trustworthy in each of its three most common uses: as a medium of exchange, as a store of value, and as a speculative investment. Primarily because the entity that controls Bitcoin, its community of users, does not take actions to stabilize and secure the cryptocurrency – that is, in the manner that nations’ monetary policies can stabilize and secure national currencies – the author evaluates Bitcoin as untrustworthy. The author then offer an argument that its untrustworthiness undermines Bitcoin’s ability to serve both as medium of exchange and as store of value. Bitcoin’s untrustworthiness does not, however, undermine its usefulness as a speculative investment. Finally, the author discuss the extent to which – and how – other cryptocurrencies can avoid the evaluation that they are untrustworthy.

In this chapter, the authors study how cryptotoken issuance, also referred to as initial coin offerings and security token offerings, may disrupt funding markets such as venture capital, crowdfunding, and private equity. The authors discuss the necessary infrastructure to support this new asset class. The authors analyze the market evolution in terms of volatility, global reach, news events, and types of industries that are issuing or considering to issue tokens. The authors discuss some specific token offerings to highlight lessons learned. the authors summarize the regulatory landscape and challenges going forward. This market crashed in terms of market capitalization at the end of 2018. However, this new asset class along with the underlying technology holds great promise to disrupt various types of intermediaries if adequate financial and regulatory infrastructures are developed.

Cryptocurrencies are hidden monies that are specifically created to be used as digital currencies while assuming the characteristics of real money. Barring the divergent opinions on whether permitted in Islamic law (that is/are halal) or forbidden in Islamic law (that is/are haram), and for which the swing tends to be in favor of its blockchain underlying technology permissibility in Islam, cryptocurrencies are undoubtedly indicating potential for relevance in the global trade, investment, and other contract settlements in some years to come. The potential of the blockchain technology is phenomenal with recent estimates suggesting it will be worth more than $20 trillion in just two years, which is more than the entire American economy. Since fortunes are made by those entrepreneurs and indeed savvy investors who have discerned its future potential earlier on, there exists some great temptation for people to jump on the blockchain bandwagon. Apparently the growing acceptability of digital fiat money as a result of technology development on one hand, and the failure of the paper money to mitigate inflation and other economic disequilibria since the disappearance of the gold standard on the other, various forms of cryptocurrencies including Bitcoins (referred to as the king) appear to roar toward wider recognition. However, an emerging phenomenon associated with cryptocurrency revolution is an observed significant fluctuation (the tide) in its value and thus a subject of discussion within Islamic finance community and beyond. In the midst of this also is the current agitation founded on some of the Islamic law (Sharīʿa) view on the necessity of asset-backed money, to be extended to the current cryptocurrency innovation for its transformation into a Sharīʿa compliant precious metal backed currency. The big question now which this chapter sought to provide the answer is, what are the implications of these developments to a more established and widening global phenomenon of Islamic finance and its development in Muslim world vis-á-vis aspirations for sustained economic development. The work finds that cryptocurrencies would generate three advantages over all forms of money including gold through: establishing a unified financial system through its standard decentralization, being rarer than gold and its significant mitigation of inflation. It is also noted that the prevalent foreign exchange risk resulting from the underlying activities (rather than the currency itself) is free from speculation (Gharar). It is, therefore, recommended that stakeholders in the Islamic Finance world should not be passive but be proactive in commencing processes to develop technical notes, standards, and operational guidelines to partake in the inevitable migration to cryptocurrencies.

One important characteristic of cryptocurrencies has been their high and erratic volatility. To represent this complicated behavior, recent studies have emphasized the use of autoregressive models frequently concluding that generalized autoregressive conditional heteroskedasticity (GARCH) models are the most adequate to overcome the limitations of conventional standard deviation estimates. Some studies have expanded this approach including jumps into the modeling. Following this line of research, and extending previous research, our study analyzes the volatility of Bitcoin employing and comparing some symmetric and asymmetric GARCH model extensions (threshold ARCH (TARCH), exponential GARCH (EGARCH), asymmetric power ARCH (APARCH), component GARCH (CGARCH), and asymmetric component GARCH (ACGARCH)), under two distributions (normal and generalized error). Additionally, because linear GARCH models can produce biased results if the series exhibit structural changes, once the conditional volatility has been modeled, we identify the best fitting GARCH model applying a Markov switching model to test whether Bitcoin volatility evolves according to two different regimes: high volatility and low volatility. The period of study includes daily series from July 16, 2010 (the earliest date available) to January 24, 2019. Findings reveal that EGARCH model under generalized error distribution provides the best fit to model Bitcoin conditional volatility. According to the Markov switching autoregressive (MS-AR) Bitcoin’s conditional volatility displays two regimes: high volatility and low volatility.

This chapter used empirical data from five developed markets and five emerging markets to perform an examination of anomalies using common financial economic approaches along with more innovative econometric models. Of the methodologies used to test for anomalies, the data-driven panel and quantile regressions were empirically found to be better suited over the traditionally common approaches to describe the non-linear, switching behavior of the anomalies. In the developed markets, the statistically significant small firms (size) had the highest average returns. In the developing markets, the lower price-to-earnings (P/E) ratios (value) had the highest average returns. In addition, the research found (1) a small country effect, (2) sales had a negative relationship with returns, and (3) a lower (higher) book-to-market (B/M) was associated with higher returns in the developed (developing) markets, indicating investors received a higher premium for growth (value) equities. The semi-strong form of the efficient market hypothesis was also found to be violated. The anomalies’ behavior varied between sorted portfolios, industries, and developed to emerging markets; though it was found to be consistent through time (not disrupted by bear or bull markets).