Corporate governance implications of disruptive technology: An overview

Journal Pre-proof Corporate Governance Implications of Disruptive Technology: An Overview Niamh M. Brennan, Prof.

PII:

S0890-8389(19)30085-X

DOI:

https://doi.org/10.1016/j.bar.2019.100860

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YBARE 100860

To appear in:

The British Accounting Review

Received Date: 2 September 2019 Revised Date:

16 September 2019

Accepted Date: 19 September 2019

Please cite this article as: Brennan, N.M., Corporate Governance Implications of Disruptive Technology: An Overview, The British Accounting Review, https://doi.org/10.1016/j.bar.2019.100860. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Ltd.

Abstract This position paper introduces the special issue on “Innovative Governance and Sustainable Pathways in a Disruptive Environment”. The paper develops a framework to review the state of the art in disruptive technology and innovations (DTIs). Then the paper reviews the common characteristics of DTIs, and their implications for the principles and design of corporate governance and accounting mechanisms at the organisational level. Following on from that, the paper identifies the defining features of emergent DTI-related structural models that shape the demand for and changes to corporate governance and accounting mechanisms. The contributions of the three papers in the special issue are discussed. The paper concludes by proposing several research themes for future research on designing more innovative and sustainable governance systems, drawing on multidisciplinary theoretical and methodological perspectives. This complements calls for future research in accounting in our special-issue papers.

Keywords: Corporate governance; Disruptive technologies; Innovation

1. Introduction A revolutionary paradigm shift is well under way on how we think about business structures and governance as a consequence of disruptive technology and innovations (DTI). Technological advances such as artificial intelligence (AI), the Internet of Things (IoT), and distributed ledger systems such as blockchains, have led to unprecedented changes, often disrupting the way goods and services have traditionally been produced and consumed (Arnold, 2018; Christensen, Raynor, & McDonald, 2015). The ability to handle large volumes of digitised data in rapid and complex ways through these technologies has also increased our dependency on more open, multi-platform, networked structures that enable other innovations, e.g. shared economies and cryptocurrency markets (Luna, Kruchten, Pedrosa, de Almeida Neto, & de Moura, 2014; Termeer, 2009). Schwab (2016) characterises this as the “fourth industrial revolution”, predicting that it will lead to wholesale changes in entire systems of production, management and governance. Danneels (2004, p. 249) highlights that a “disruptive technology is a technology that changes the bases of competition by changing the performance metrics along which firms compete”. Consequently, for accounting, finance, management and other governance professionals, these developments present extraordinary pressures for information and governance systems that call for more agile, complex and futuristic approaches. In other words, it is imperative that organisations widen their knowledge boundaries about the risks and impacts of DTI and be prepared to respond accordingly, or be destined to fail.

Past research, however, offers limited insights on the design of appropriate governance systems for organisations in relation to DTI. In fact, the rapidly evolving and unpredictable nature of technological innovations are seen to collide with more traditional approaches to governance which are predominantly hierarchical, i.e. top-down and less self-regulated (Gans, 2016; Turnbull, 1997). Research efforts so far appear to focus more on the emergence and management of disruptive technologies, with limited attention paid to the design and effectiveness of extant corporate governance and accounting mechanisms. For example, in their review of 1078 papers on disruption research, Hopp, Antons, Kaminski and Salge (2018) identify only ten papers relating to accounting and finance. Further, they also highlight that there is a distinct difference in the papers dealing with radical and disruptive innovations compared with those calling for more research on organisational capabilities for 1

business model transformations. Further insights on DTI governance systems is vital for effective and efficient policy making by government, governance regulators and related institutions.

The overarching purpose of this special issue, entitled ‘Innovative Governance and Sustainable Pathways in a Disruptive Environment’ is to identify and discuss emergent challenges arising from disruptive technologies and their social impacts for organisational level governance. The aims of our introduction to this special issue are three-fold: 1. To provide an overview of the characteristics common to DTIs, and their implications for the principles and design of corporate governance and accounting mechanisms at the organisational level; 2. To identify the defining features of emergent DTI-related structural models that shape the demand for and changes to corporate governance and accounting mechanisms; and 3. To propose several research themes for future research on designing more innovative and sustainable governance systems, drawing on multidisciplinary theoretical and methodological perspectives.

Our discussion of the literature related to the governance of DTI is aided by a general framework comprising the underlying characteristics of such technologies and innovations, components of governance eco-systems and anticipated outcomes, as depicted in Fig. 1. We begin by giving an overview of the definition and characteristics of DTI, followed by a description of several common types of DTI (namely, Big Data, cryptocurrency, Blockchain, the sharing economy and crowdsourcing (including crowdfunding), and their implications for corporate governance and accountability, including independence and participation in decision-making. We also delineate several emergent or alternate forms of DTI (agile, collaborative, decentralised, and distributed organisational forms) reflecting differing structural and capability dimensions. We then discuss the implications for the (re)design of corporate governance and accounting mechanisms to meet the changing demands. Further, we locate and discuss how the three papers in this special issue (Kurrupu & Lodia, 2019; Leoni & Parker, 2019; Moll & Yigitbasioglu, 2019) add insights on what works and does not

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work within evolving DTI governance systems, and the continuing demands posed by highly dynamic, yet volatile environments.

Fig. 1. General framework - disruptive technology and innovation governance (DTI) issues DTI - Characteristics Unpredictable / Volatile markets: Rapid environmental changes: Complex Technology

Common Technology-based Disruptive Forces Big Data

Blockchain

Sharing Economy

Cryptocurrency

Crowdsourcing/funding

Emergent DTI Attributes and Organisational Forms Agile Collaborative Decentralised Distributive/Distributed

GOVERNANCE ECO-SYSTEM Internal Accountability Mechanisms

External Accountability Mechanisms

• Governing Board • Shareholders

Direct Stakeholders • Regulators • Professional Bodies/ Consultants

Accounting Mechanisms • Financial Reporting • External & Internal Audit • Management Accounting & Performance Evaluation

Indirect Stakeholders • Social Media • Corporate Activists

Corporate Governance Principles • Accountability – Disclosure/Transparency, Independence, Decision-making Participation Accounting Principles • Relevance, Reliability, Consistency

Conceptual Perspectives

3 Stakeholder Theory; Agency theory; Institutional Theory; Critical perspectives; Resource-based Theory; etc

2. Disruptive technology and innovation Issues In this section, we review DTI characteristics, followed by technological disruptive forces.

2.1 DTI characteristics Orlikowski (1992, p. 398) argues that “Early research studies assumed technology to be an objective, external force that would have deterministic impacts on organizational properties such as structure. Later researchers focused on the human aspect of technology, seeing it as the outcome of strategic choice and social action. This paper suggests that either view is incomplete, and proposes a reconceptualization of technology that takes both perspectives into account.”

This statement reflects an early naïve view of technology as neutral of technological determinism: tech does X. The socio technical perspective views the social as important and examines how the technological and the social interact in a bi-directional way. But this stream of research tends to focus more on social determinism: human agents using tech do X. This perspective is also problematic because it affords too much power to the human agents and too little to the tools. Since then, a third wave has risen adopting a sociomaterial lens where a post actor-network theory view of the world is proposed, in which neither the social nor technical can be understood as primary influencers but both are entangled or imbricated or assembled. For example, activity theorists generally “underscore that because of its collective origin, the object of the activity is, by definition, emergent, fragmented, and contradictory” (Nicolini, Mengis, & Swan, 2012, p. 614). The implication of this understanding is that we need to approach the role of technology in diverse ways.1

According to Kostoff, Boylan, & Simons (2004 p. 142), “[d]isruptive technologies can be either a new combination of existing technologies or new technologies whose application to problem areas or new commercialization challenges (e.g., systems or operations) can cause major technology product paradigm shifts or create entirely new ones”. Christensen and Bower (1996, p. 202) define disruptive technologies as “technologies … which disrupt an established trajectory of performance improvement, or redefine what performance means”. 1

We are grateful to Dr Niamh O’Riordan for her assistance with this material.

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Examples of disruptive technologies include blockchain technologies, artificial intelligence, digital technologies, shared economy models, and more. In disruptive environments, innovations (be they technical, processual or commercial) are often unpredictable, ideas are radical, outcomes are uncertain and ill-defined, and the justification for investments in them difficult to make as markets are either not adequately developed or may be non-existent (Evans, 2017).

The core literature on DTI has burgeoned since Christensen, Baumann, Ruggles, & Sadtler (2006) (see also, Christensen et al., 2015; Christensen, McDonald, Altman, & Palmer, 2018) who propose disruptive technology as something that happens when incumbents are blindsided as they are too busy keeping existing customers happy. In their view, you can look to the performance trajectories of potential disruptors to single out the ones you need to worry about. Christensen and colleagues build their arguments based on 77 cases of disruptions that had catastrophic effects on incumbents.2 In his book “Innovator’s Dilemma”, Christensen (1997) concluded that there are two types of technological developments. His first is sustained technology, where the result is improvements in the rate of product performance, ranging in difficulty from incremental to radical, and led by the top-performing firms in the industry. His second is disruptive technology, where innovations disrupted or redefined performance trajectories and arguably resulted in the failure of the industry's leading firms. The general treatise is that successful organisations risk failure if they do not recognize the distinction between sustaining technologies and disruptive technologies, and if they fail to invest in nascent disruptive technologies (Kassicieh et al., 2002). As further highlighted by Kostoff et al. (2004, p. 144): “Possible reasons for their demise include: first, disruptive products are simpler and cheaper; they generally promise lower, not higher, profit margins; second, disruptive technologies typically are first commercialized in emerging or insignificant markets; and third, leading firms’ most profitable customers generally do not want, and indeed initially cannot use, products based on disruptive technologies”.

2

An example is disruption to the mechanical-excavator industry as a result of hydraulics technology. Christensen (1997) argues that established companies that built cable-operated excavators were slow to recognise the importance of the hydraulic excavator.

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In general, the common characteristics of a DTI context involve unpredictable, volatile markets, rapidly changing environments and complex technologies. Consequently, researchers have started querying the association between corporate governance and DTIs with calls for a broader multi-disciplinary, multi-theoretic approaches to designing governance systems that support organisational decision-making in highly volatile, complex and dynamic environments (Buterin, 2014; Cockcroft & Russell, 2018; Piazza, 2017). The evolution of more agile and flexible systems of decision-making also raises issues for basic corporate governance principles such as accountability, transparency and disclosure and their inclusion in the evolving governance structures and processes. Further, DTIs also tend to be enabled by a convergence of technologies which depend on shared networks, alliances and other collaborative structures and processes (Ansell & Gash, 2008; Belk, 2014; Rocco, 2008). As such, participative decision-making and issues related to power and delegation become critical in a DTI eco-system. While some innovations may lead to technology enabled enhancements to governance systems, it is also likely that there are risks related to degradation of governance oversight and quality.

2.2 Common technology-based disruptive forces In this section, we provide an overview of five common technology enabled disruptive forces that have been instrumental in significantly changing business models in unprecedented ways. Table 1 presents prior research related to five common, high-profile aspects associated with DTI: Big Data, cryptocurrency, blockchain, the sharing economy and crowdsourcing. These disruptive forces can be classified in two ways. First, technological developments directly relating to the nature of the digitised data and its potential for reshaping information for business decision-making or financial transactions such as Big Data and cryptocurrency, respectively. Second, disruptive technologies affecting the manner in which business transactions are conducted and recorded through converging technologies such as decentralised and collaborative platforms, e.g., blockchain, the sharing economy and crowdsourcing arrangements.

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Table 1 Prior research on selected features of disruptive technology and innovations (DTI) Type of DTI Big Data

Prior research Appelbaum, Kogan, & Vasarhelyi (2017); Bhimani & Willcocks (2014); Cockcroft & Russell (2018); Payne (2014); Salijeni, Samsonova-Taddei, & Turley (2018); Vasarhelyi, Kogan, & Tuttle (2015); Warren, Moffitt, & Byrnes (2015)

Cryptocurrency

Böhme, Christin, Edelman, & Moore (2015); Lazanis (2015); Piazza (2017); Raiborn & Sivitanides (2015); Ram, Maroun, & Garnett (2016)

Blockchain

Byström (2019); Dai & Vasarhelyi (2017); DuPont (2017); Hsieh, Vergne, & Wang (2018); Lazanis (2015); MacDonald, Allen, & Potts (2016); Piazza (2017); Rückeshäuser (2017); Wang & Kogan (2017); Yermack (2017)

Sharing Economy Belk (2014); Botsman & Rogers (2010); Cheng (2016); Martin (2016); Schor (2016) Crowdsourcing

Bergvall-Kåreborn & Howcroft (2013); Chen, Huang, & Liu (2016); Jame, Johnston, Markov, & Wolfe (2016); Kuppuswamy & Bayus (2017); O'Leary (2015)

2.2.1 Big Data In a rather long but comprehensive definition, Boyd and Crawford (2012, p. 663) define Big Data as: “…a cultural, technological, and scholarly phenomenon that rests on the interplay of: (1) Technology: maximizing computation power and algorithmic accuracy to gather, analyze, link, and compare large data sets. (2) Analysis: drawing on large data sets to identify patterns in order to make economic, social, technical, and legal claims. (3) Mythology: the widespread belief that large data sets offer a higher form of intelligence and knowledge that can generate insights that were previously impossible, with the aura of truth, objectivity, and accuracy.”

While what is “big” for some firms may not be for others (Vasarhelyi, Kogan, & Tuttle, 2015), managing and using information from extremely large data sets can help reveal trends and patterns among people and institutions from various different perspectives. Bhimani and Willcocks (2014) warn that because of Big Data, sequential linear links between corporate strategy, firm structure and information systems can no longer be assumed. Commenting on 7

Bhimani & Willcocks (2014), Payne (2014, pp. 493-494) adds that Big Data will cause the “have lunch, buy a brunch” and HiPPO (Highest Paid Person’s Opinion) practices3 to decrease in favour of more rigorous, data driven decision making. The way risks are identified, assessed and dealt with calls for firms to invest in appropriate information and data management technologies and human resources. For instance, financial data which comprises the standard financial metrics (such as assets, liabilities, equity and income) will be associated with other voluminous enterprise data such as marketing, production and investment portfolios to arrive at decisions, for example, on the nature and amount of investments a firm makes. Thus, while recognising privacy issues, governance systems need to encompass more seamless access to enterprise data, calling for governance professionals to understand the limits and opportunities offered by Big-Data analysis and the need for cooperation and data management capacities within all parts of organisations.

2.2.2 Cryptocurrency Cryptocurrency is a type of digitised currency that can be used for all types of transactions, allowing for instantaneous exchanges. It is disruptive, as there is no single administrator or central bank, and it can be exchanged on a peer-to-peer network without the need for intermediaries. A popular cryptocurrency is Bitcoin, “an online communication protocol that facilitates the use of a virtual currency, including electronic payments” (Böhme, Christin, Edelman, & Moore, 2015, p. 213). Besides using cryptocurrencies for transaction exchanges, entities can also invest in bitcoin, akin to a monetary asset. However, Böhme et al. (2015) warn that bitcoin technology also entails several risks: (i) Bitcoin has no money laundering know-your-customer responsibilities, (ii) Bitcoin does not restrict the sales of questionable products, and (iii) payments are irreversible – errors cannot be corrected, and purchases cannot be cancelled. Grant and Hogan (2015, p. 29) further highlight that “[p]roponents hype the benefits of Bitcoin transactions as being faster and cheaper than traditional methods; however, concerns around the lack of a central governing agency, lack of controls over Bitcoin exchanges, and the volatility of the virtual currency persist”.

3

Meaning data obtained from social interactions over a meal or other intuitive sources in contrast to rigorous objective sources of data.

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2.2.3 Blockchain Blockchain is a digital ledger of transactions (Chartered Professional Accountants (CPA) Canada, 2016) that enables creation of records that are secure, reliable, transparent and accessible. Yermack (2017, p. 7) defines blockchain as “a sequential database of information that is secured by methods of cryptographic proof”. He characterises blockchain as an alternative to traditional financial ledgers based on classic double entry bookkeeping, stating (p. 28) that it appears to represent “a leap forward in financial record-keeping not seen in the introduction of double-entry bookkeeping centuries ago.” CPA Canada (2016) uses the phrase “triple-entry bookkeeping”, which is traditional double-entry bookkeeping; together with parties to a transaction recording each side of the transaction in a shared blockchain ledger, i.e., representing the third entry. Participants in a transaction would confirm the integrity of the transaction.

There are numerous implications of blockchain technology for governance and accounting systems. Yermack (2017) and Piazza (2017) predict the use of blockchain to keep records of share ownership and to keep financial records (possibly through public blockchain as opposed to “permissioned” blockchain). Blockchain would enable real-time accounting. Rather than updating the books and records on a monthly or quarterly basis, blockchain would enable near-instant (daily) updating of accounting information (Byström, 2019). Because Blockchain is a ledger that cannot be altered and cannot be destroyed, it would improve the trustworthiness of financial statements (Byström, 2019). Dai and Vasarhelyi (2017) consider how blockchain could enable real-time, verifiable and transparent accounting ecosystems, while Wang and Kogan (2017) commend blockchain as an accounting information system for its power in real-time accounting, continuous monitoring and continuous auditing, as well as fraud detection.

However, there are limitations to blockchain technology. Rückeshäuser (2017) criticises the application of blockchain in accounting, questioning the immutability of blockchain through decentralisation and its technological rigour. She challenges the notion that blockchain will prevent fraud and discusses ways in which fraud may not be constrained by blockchain, such that senior management will continue to be able to perpetrate fraud. There are also warnings regarding the integrity of a blockchain in that it is only as good as the data that 9

gets recorded in the first place. For blockchains to work well they need to be large, but this could mean transaction costs are higher, and the time taken to process transactions could be relatively slower compared to present systems (Davidson, De Filippi, & Potts, 2016).

2.2.4 Sharing economy While defining the sharing economy can be problematic (Martin, 2016, p. 151), Hamari, Sjöklint and Ukkonen (2016, p. 2047) describe what they call “collaborative consumption” as “the peer-to-peer-based activity of obtaining, giving, or sharing the access to goods and services, coordinated through community-based online services”. Ranchordas (2015) notes that the sharing economy presupposes two elements: the existence of physical shareable goods that systematically have excess capacity, and a sharing attitude or motivation. Also, another fundamental assumption underlying sharing economy is that transaction costs related to the coordination of economic activities will determine sharing behaviours.

Botsman and Rogers (2010) interview business leaders and opinion formers around the world to identify various collaborative or mediated consumption systems. They highlight how in the late 1990s and early-mid 2000s online platforms emerged which enabled individuals to establish peer-to-peer relationships in unprecedented volumes and speed. Martin (2016) notes that early innovations that provided the foundations for the sharing economy concept include: Ebay, Craigslist, Freecycle and Couchsurfing. He notes (p. 151) “business to consumer models of Internet mediated interaction also emerged which enabled individuals to access (rather than own) assets, perhaps the most prominent of these being the car rental/sharing service offered by Zipcar”.

Interestingly, Ranchordas (2015 p. 416, p. 443) also argues that while “Uber, Airbnb, Lyft, and other forms of sharing economy represent growing innovative forms of sharing underused facilities”, governance systems “may either hinder, delay, or advance innovation”. Ranchordas acknowledges concerns on public safety, health, and limited liability of sharing economy practices and that the sharing economy opens the door to unfair competition. Some of the critical risks include misrepresentation or poor service delivery, fraudulent behaviours and public liability with traditional legal boundaries still unclear and legal recourse questionable or uncertain. 10

2.2.5 Crowdsourcing Brabham (2008, p. 76) defines crowdsourcing as “a new web-based business model that harnesses the creative solutions of a distributed network of individuals through what amounts to an open call for proposals.” Examples include: Estimize (Jame, Johnston, Markov & Wolfe 2016) to crowdsource earnings forecasts, Apple’s crowdsourced labour force providing digital content (Bergvall-Kåreborn & Howcroft, 2013) and crowdsourced data for use by external auditors (O’Leary, 2015). Crowdfunding can be used to crowdsource equity through platforms such as Kickstarter (Kuppuswamy & Bayus, 2017) and JD.com in China (Chen, Huang, & Liu, 2016). Gellers (2013) views technology as a means of crowdsourcing global environmental governance, thereby overcoming a democratic deficit. Mattingly and Ponsonby (2016) discuss how crowdsourcing, specifically prediction markets, can improve governance. Prediction markets are tools for channelling a collective intelligence effect, coined the “wisdom of crowds”. Boards of directors could use shareholder prediction markets to crowdsource feedback from shareholders on big corporate strategic decisions such as mergers, disposals, takeover defences, relocations, etc.

3. The governance eco-system In this section, we discuss several structural forms associated with DTI and key corporate governance challenges they face.

3.1 Corporate governance In traditional corporate governance, distinguishing governance and management is critical. The governing board comprises directors who hold both fiduciary and strategic duties. Fama (1980, p. 293) describes directors as “professional referees” overseeing management on behalf of the shareholders who appointed them for that purpose. In enacting corporate governance, directors face “complex multifaceted tasks” but are responsible only for “monitoring and influencing strategy” – not for day-to-day administration and implementation (Forbes & Milliken, 1999, p. 491-92). However, past literature is often replete with examples lacking this distinction, applying the term “governance” to what traditionalists would call management tasks. One such example is use of the term “IT governance”. For instance, Bowen, Cheung and Rohde (2007) state: “Kaplan (2005) defines 11

IT governance as the set of processes used by the organization to manage IT, i.e., aligning IT with business objectives, resourcing IT projects, and monitoring IT performance”. They, and Kaplan (2005) who they cite, clearly do not make the distinction between the management of IT and the governance of IT. Debreceny (2013, p. 129) puts it well when he asks: “What role do governing bodies, such as the Board of Directors, play in the oversight and direction of IT?” and “What roles and responsibilities for IT does the governing body assume and what is delegated to senior and operational management?”.

For the purposes of our paper, we see corporate governance as setting the parameters of the system within which people, institutions and other stakeholders behave so that the organisation (or the social ecosystem) achieves the desired outcomes (Rocco, 2008). For Rocco (2008), governance includes the processes, conventions and institutions that determine: • How power is exercised in view of managing resources and interests; • How important decisions are made and conflicts resolved; and • How various stakeholders are accorded participation in these processes.

Put simply, governance is the replacement of traditional ‘‘powers over’’ with contextual ‘‘powers to.’’ The dominant role of the top-down governing approach is replaced by dominant ‘‘bottom-up’’ and ‘‘horizontal’’ interactions. The Association of Chartered Certified Accountants (ACCA) (2012) contend that governance approaches within a DTI context will evolve away from machine-age metaphors of the organisation, and be increasingly replaced by a biological-era view of the firm as a living, constantly evolving and adapting ecosystem. Hence the stewardship role will extend to monitoring and nurturing the health of the firm’s entire ecosystem of partnerships and relationships.

3.2 Emergent DTI attributes and organisational forms In this section, we delineate several emergent attributes and structural forms arising from DTI that call for specific governance arrangements and capabilities. We discuss four major underpinning attributes commonly cited as fundamental for governance in highly dynamic, volatile

environments:

agile,

collaborative,

decentralised,

and

distributive/global

arrangements. The first two attributes relate to organisational capabilities dealing with 12

agility, adaptiveness, and cooperation which are critical for dealing with uncertainty and rapid market transformations. The latter two relate to authority, power and decisionsharing dimensions. Table 2 summarises governance models commonly associated with DTIs. The rapidly evolving and shifting nature of DTIs has led to a proliferation of terms attempting to define the approaches to their governance (Durston, Pesce & Wenborn, 2018), such as “joined-up”/“shared”/ “collaborative” governance. Labels such as “disrupting governance” (Davidson et al., 2016), “digital-era governance”, (Tassabehji, Hackney & Popovič, 2016), and “global governance” (e.g., Voegtlin & Scherer, 2017) are commonplace.

Table 2 Emergent models of governance Type of model

Description

Capacity Agile governance

“the ability of human societies to sense, adapt and respond rapidly and sustainably to changes in its environment, by means of the coordinated combination of agile and lean capabilities with governance capabilities, in order to deliver value faster, better, and cheaper to their core business.” (Luna et al., 2014, p. 134)

Collaborative governance

“the processes and structures of public policy decision making and management that engage people constructively across the boundaries of public agencies, levels of government, and/or the public, private and civic spheres in order to carry out a public purpose that could not otherwise be accomplished.” (Emerson, Nabachi & Balogh, 2011, p. 2)

Structural Decentralised governance

Blockchain based concept – “… open, distributed, secure, encrypted and programmable digital ledgers and enabling secure and fully decentralized “P2P” [person-to-person] trade. (Arruñada & Garicano, 2018, p. 2)

Distributed governance

“Is realised without the need for a central authority … the balance of integrity and autonomy; decision-rights; control mechanisms; and incentive structures.” (Zachariadis, Hileman, & Scott (2019, p. 110, p. 114).

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3.2.1 Agile governance Agility is a critical characteristic denoting the ability to detect and respond to opportunities in a timely and flexible manner. It supports seizing competitive market opportunities by assembling requisite assets, knowledge and relationships with speed and surprise (Sambamurthy, Bharadwaj & Grover, 2003; Goldman, Nagel & Preiss, 1995). The fast pace of change in technology led to the employment of agile methodologies in software development. The philosophy of agile project management is now spreading beyond software. Similar to the agile responses adopted to software development and business operations more generally, Schwab (2016) recommends embracing ’agile’ governance. Luna et al. (2014) review the literature and identify several definitions of agile governance where the common characteristics of such systems are to be strategic, integrated and fast. For example, Luna, Costa, Maura and Novaes (2010, p. S60) define agile governance as “the process of defining and implementing the ICT infrastructure that provides support to strategic business objectives of the organization, which is jointly owned by ICT and the various business units and instructed to direct all involved in obtaining competitive differential strategic advantage through the values and principles of the Agile Software Development Manifesto”. They further clarify that agile governance does not replace conventional models and frameworks.

3.2.2 Collaborative (Consensual) governance Collaborative governance emphasises the capacity to be able to work together. This capacity involves bringing people together across different levels of decision-making, both within and outside organisations. For example, it “…brings public and private stakeholders together in collective forums with public agencies to engage in consensus-oriented decision making.” (Ansell & Gash, 2008, p. 543). Gaining consensus and moving into new markets or product developments is a critical capacity, which will also support adaptive behaviours needed in disruptive environments.

For example, based on a digital platform perspective, Constantinides, Henfridsson, and Parker (2018) argue that while structural complexity can be managed through technological solutions, governance systems can reduce behavioural complexity within platform structures that often rely on collaborative arrangements. Drawing on Tiwana (2014) who 14

broadly defines governance platforms as dealing with ‘who decides what’, Constantinides et. al. (2018) highlight governance as encompassing three facets: (i) How decision rights are divided between the platform owner and third-party developers, (ii) what types of formal and informal control mechanisms are used by the platform owner (e.g., gatekeeping, performance metrics, processes that developers are expected to follow), and (iii) incentive structures. While the layered, modular “architecture can reduce structural complexity, governance can reduce behavioral complexity” (Tiwana 2014, p. 118).

3.2.3 Decentralised governance Blockchain represents a new “institutional governance technology of decentralization” (MacDonald et al., 2016, p. 284). Atzori (2017, p. 46) argues that blockchain governance would involve citizens self-creating their own systems of governance “in which centralisation, coercion and socio-political hierarchies are replaced by mechanisms of distributed consensus.”

Hsieh, Vergne and Wang (2018) observe that blockchain governance involves clarity on who has authority (internal and external parties) over the blockchain; the nature of the authority of these parties (e.g. ownership rights vs. decision authority), the form of governance (formal and informal) and the level at which it operates (Narayanan, Bonneau, Felten, Miller & Goldfeder, 2016). Hsieh et al. (2018, p. 50) add that blockchain technology may lead to novel organisational forms such as “decentralized autonomous organizations” (DAO) (Buterin, 2014; DuPont, 2017).

For Hsieh et al. (2018), blockchain-based organisations disrupt traditional principal-agent relationships by placing machines (i.e. the blockchain software program) at the core of organisational governance, and stakeholders at the edges (Buterin, 2014). Instead of CEOs or senior managers, it is developers who write the rules (i.e., the software code), in a decentralised fashion. It is miners (or validators), rather than employees, who verify the validity of economic transactions and maintain a digitally shared, distributed ledger recording their history.4 There are no headquarters or subsidiaries, but rather a network 4

Each transaction must be verified. With blockchain, however, that job is left to a network of computers. These networks often consist of thousands (or in the case of Bitcoin, about 5 million) computers spread across

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distributed in cyberspace that is inherently global and borderless. Stakeholders have power and govern the blockchain at varying levels in different ways (Narayanan et al., 2016; Yermack, 2017). Thus, blockchain governance revises understanding about power and control in organisations. Governance is not only borderless but also decentralised (to various extents) (Atzori, 2017; Yermack, 2017). Anyone can “join” a public cryptocurrency organisation, maintain and update the open ledger based on “competitive bookkeeping” such as mining or other consensus mechanisms (Yermack, 2017). Decentralisation distinguishes blockchain-based corporate governance from the traditional model based on hierarchies. With decentralisation, governance decisions are made without centralised authorities, but rather through consensus mechanisms in a non-hierarchical fashion. Blockchain-based corporate governance forms need to be considered in terms of their degrees of decentralisation.

3.2.4 Distributive/distributed governance Detomasi (2002) reflects the machine-age metaphor perspective. In the context of globalisation, Detomasi (2002, p. 423) defines distributive governance (also called “distributed governance”) occurring when: “…formal governing authority is shared by a variety of interested actors operating in the public, private, and nongovernmental spheres. Distributive governance buttresses—but does not replace—independent national or organizational authority with a combination of involved state and nonstate actors that work collaboratively to shape norms, to develop sanctions for governance transgressors …”

Detomasi (2002) describes people working cooperatively in a distributed governance model to shape governance behaviour and outcomes, differentiating distributive governance models from existing models. Detomasi’s (2002) description of the way Japanese firms use relational rather than arms’ length contracting is more like a model based on symbiosis than competition. In a similar vein, the term horizontal governance has been adopted referring to working through networks in place of hierarchies through interdependence rather than

the globe. The cost of this activity (validation or ‘mining’) could be prohibitive and it is not clear how the cost will be covered. Apart from cryptocurrencies, where the result of the mining/validation is a currency unit that can be sold, blockchain has not had much application in practice, despite the benefits claimed. https://www.investopedia.com/terms/b/blockchain.asp

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power relationships; negotiation rather than control; and enablement rather than management (Phillips, 2004).

Another critical aspect of some of the emergent organisational forms such as collaborative, de-centralised and distributed governance is that these models engage stakeholders, but far beyond the traditional approach or the way we currently think about them. The stakeholders themselves can hold a different type of power. They can control data quality and integrity, including how much and what they would like to share. Consequently, this can further shape internal governance mechanisms and their design.

In this special issue, Leoni and Parker (2019) investigate governance and control issues within Airbnb which is a digitised shared-economy platform for hosts offering accommodation to guests. Leoni and Parker contend that sharing economy platforms have recently surged as popular venues of business, enabling people around the world to digitally interact and temporarily exchange their under-utilised assets. Through a netnographic method, their analysis reveals platform owners using predominantly formal bureaucratic control systems as mechanisms to govern and control its host and guest users.5 Through users’ compliance, they and their activities are made visible to the platform owner, which in turn maintains control over the value-creation process. Some key revelations of Leoni and Parker’s study are that accounting systems play a critical role as mechanisms of surveillance, monitoring control over digital host and guest users worldwide, while traditional technologies of governance continue to influence how power and control are maintained by the platform owners.

Kuruppu and Lodhia (2019) deal with changes arising from policy advocacy activism which generate disruptive innovations in a non-governmental (NGO) setting. Guided by Laughlin's (1991) model of organisational change, they review changes in the case NGO's interpretive schemes, design archetypes and organisational sub-systems using a case study of a large NGO operating in Sri Lanka. Drawing on data collected through semi-structured interviews,

5

Netnography is an interpretive research method that adapts traditional, in-person participantobservation techniques of anthropology to the study of interactions and experiences manifesting through digital communication (Kozinets, 1998).

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document analysis and participant and non-participant observations, they find that the NGO's governance systems and processes are being moulded in ways that may not achieve the overall purpose of the organisation. Their paper introduces “protective reconfiguration” as a new change pathway to Laughlin's model of organisational change. They contend that more deliberative, fluid and less organisation-centric governance structures are necessary for NGOs operating in the policy advocacy space.

4. DTI - Governance eco-system In this section, we consider three key corporate governance mechanisms, together with implications for management of DTI.

4.1 Financial reporting Financial reporting is an important accountability mechanism. Directors hold a fiduciary duty of disclosure to report company financial affairs faithfully and in compliance with regulatory requirements. Big Data can strengthen financial reporting measurement processes through new forms of evidence to support how management accounts for transactions (Warren, Moffitt & Byrnes, 2015).

Blockchains could potentially improve the quality of financial reporting in two ways: by making financial statement information (i) more trustworthy and (ii) more timely (Byström, 2019). Blockchain has the potential of enhancing the timeliness of, and access to, accounting information (Piazza, 2017). Also, because users of accounting information could be given access to information, blockchain would increase trust in the quality of the data.

Tan and Low (2017) address the question of how to account for the cryptocurrency bitcoin, noting that no official guidance has come from accounting standard setters, notwithstanding that guidance for tax purposes has been available since 2014. They discuss the challenges for standard setters of accounting for a decentralised currency rather than a reporting currency. Ram, Maroun and Garnett (2016) asked 40 financial accounting experts to complete a correspondence analysis, which is an exploratory tool to present the relations between the characteristics of bitcoin and the themes drawn from an inductive thematic analysis of prior literature on bitcoin. They supplement their analysis with ten semi18

structured interviews. Their correspondence analysis and interviews reveal that although cost and fair value may be conceptual opposites, “in the eyes of respondents, these need to be used to achieve the single goal of communicating the economic rationale for holding the Bitcoin” (p.2). In a detailed analysis, Raiborn and Sivitanides (2015) identify six issues for accounting standard setters to address in accounting for bitcoin: asset classification, mining activity, investment holdings, exchanges, merger and acquisition (M&A) transactions, and disclosure.

4.2 External audit Lazanis (2015) predicts that the accounting profession will be completely transformed because of blockchain. Auditors’ role will be greatly reduced or even completely eliminated. Appelbaum, Kogan and Vasarhelyi (2017) consider the opportunities for auditors to modernise their audit procedures by taking advantage of the capabilities of Big Data.

If companies kept all their transactions and balances on a blockchain, then the blockchain could eliminate the need for auditors to provide an opinion on the financial statements. Since transactions in the blockchain cannot be tampered with, mistrust leading to the requirement for audit is removed (Byström, 2019). The advent of crowdsourcing has led to phrases such as “armchair auditors”, coined by former UK prime minister, David Cameron, “sidewalk auditors” and “social audits” (i.e. using the public as auditors) (O’Leary, 2015). In interviews with Big Four audit partners, Trompeter and Wright (2010) find evidence of the expanded use of more powerful technology in audits resulting in greater use of, and reliance on, analytics. Caringe and Holm (2017) interviewed 15 external auditors to investigate external auditors’ role in a technological environment. They find that the monitoring role of external auditors is reduced by the increased information environment. The technological environment allows auditors to provide assurance services beyond the audit of the financial statements, giving them more opportunities for value-adding activities.

4.3 Internal audit Internal audit relates to assurance activities undertaken by either staff within companies or service providers external to companies with the aim of adding value and improving organisational operations. The key function of internal audit is to improve the effectiveness 19

of risk management, control, and governance processes of organisations. Vasarhelyi, Kogan & Tuttle (2015) predict that auditing will increasingly rely on external sources of information, like blockchain and Big Data. Internal auditors of companies using blockchain could conduct continuous internal audits, with audit trails and account analysis at the push of a button. Rooney, Aiken and Rooney (2017) consider the challenge of blockchain for internal auditors: they will have to access information in new formats, they will have to maximise the value of real-time continuous information, internal auditors from multiple organisations will need to work collaboratively. Zhang, Yang and Appelbaum (2015) predict that with the advent of Big Data, auditing will become a continuous process, while Yoon, Hoogduin and Zhang (2015) call for the use of Big Data as complementary audit evidence. Mattingly and Ponsonby (2016) describe how internal auditing and external auditing could use prediction markets as pre-diagnostic tools for eliciting accurate information and for forecasting.

4.4 Management accounting and performance evaluation Management accounting and performance evaluation systems play a critical role in producing information for decision-making and performance indicators to assess and control performance where possible. However, as highlighted by Beaubien (2013) and Elbashir et al. (2011), such systems (e.g. enterprise-resource planning, and business intelligence systems) have become largely automated, thus enabling access to large amounts of data (Big Data) in a very short period of time, if not instantaneously.

As highlighted by Arnold (2018, p. 14), “once data are entered into the ERP [enterprise resource planning] system, the BI [business intelligence] system can make all of the management accounting and management control information instantly available and disseminate it throughout the organisation, whether it is information for an operational manager’s digital dashboards or CEO’s smartphones”. However, Arnold (2018) also warns that there is a cost to the use of data in this more open manner – which is likely to be a loss of privacy, raising challenges on how good governance principals (e.g. accountability towards data ownership, having a voice in questioning data integrity or privacy around performance evaluations and assurance of such data) become critical.

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5. Future research Overall, the design of governance mechanisms within disruptive environments appears to demand greater flexibility, agility, openness and a multi-layered framework. In this special issue, Moll and Yigitbasioglu (2019) comprehensively review the accounting literature on several potential and actual disruptive impacts caused by four Internet-related technologies: cloud, Big Data, blockchain and artificial intelligence (AI). For example, access to distributed ledgers (blockchain) and Big Data supported by cloud-based analytics tools and AI will automate decision making to a large extent. They argue that these technologies may significantly improve financial visibility and allow more timely intervention due to the perpetual nature of accounting. However, given the number of tasks of which technology has relieved accountants, these technologies may also lead to concerns about the profession's legitimacy and the role of accountants. Their findings suggest that scholars have not given sufficient attention to these technologies and how these technologies affect the everyday work of accountants. Moll and Yigitbasioglu also present several more avenues for further research.

We add to Moll and Yigitbasioglu’s (2019) line of suggestions for future studies in this area by broadening the field of inquiry to include the role of other governance stakeholders who either affect or are affected by accounting mechanisms. In this paper, we offer five areas ripe for the study of disruptive innovation (DTI) and governance.

First: Having the right governance culture for adaptivity Sustaining innovations relative to disruptive innovations entail less uncertainty in both technological and business model change. The use of more traditional monitoring and incentive schemes based on say budget forecasting or waterfall production methods are likely to be matched with information needs and decision-making needs. However, disruptive innovations are much more challenging as both technology and business models that have been successful can become defunct quite suddenly. As such, the cultural aspects of governance that support the capability to rapidly transform to new markets and production that support agile and future-oriented thinking becomes vital. While past studies have focused on governance of sustaining innovations, more research is needed on how organisational learning and change management in disruptive environments can be 21

managed. This will include finding both human and financial resources to have the right leadership and resources to act upon ‘unprecedented’ opportunities.

Second: Technologies themselves need to converge There are a multitude of technologies that shape organisation’s capacity to strategically govern DTIs, and often these technologies need to work in tandem. For example, decision making on investing in a particular technology or market could be supported by the use of Big data aided by artificial intelligence, but that may need data or regulatory support from a blockchain network. Consequently, governance systems involving rights to access data and costs of data-creation and sharing become vital. Rocco (2008) calls for four key functions in a framework for governance of converging technologies: •

Supporting the transformative impact of the new technologies;

•

Advancing responsible development that includes health, safety and ethical concerns;

•

Encouraging national and global partnerships; and

•

Establishing commitments to long-term planning and investments centred on human development.

Research in this area is scant and researchers from multi-disciplinary backgrounds are potentially needed in this area.

Third: Social implications of disruptive technologies While disruptive technology has been hailed for the innovative changes that it brings, some significant (unintended) social implications have already surfaced as a result of the disruptions. A theme recurring in our paper is the distribution of power and its implications for access to the benefits of DTI or related ethical issues. Power relations lie at the heart of corporate governance and DTI is changing these power relations, moving from more hierarchical traditional governance approaches to self-governance approaches. These changing power relations deserve further study.

For example, in terms of changing social implications and the sharing economy, Airbnb (and other accommodation sharing services), while providing interesting and more economic 22

alternatives to hotels for travellers, has led to housing shortages in some tourist cities. A daily rate for accommodation is normally much more attractive for landlords than renting out on a long-term basis to local inhabitants. This resulted in locals not being able to find affordable accommodation in their own neighbourhoods and close to their workplaces. This (unintended) consequence has caused some cities (e.g., Barcelona) to limit the amount of accommodation that can be offered on this basis in order to protect local inhabitants from exorbitant prices and accommodation shortages. Another consequence is that some landlords would vacate their premises over summer months (or in high season) to rent it on an accommodation sharing platform over this period. Again, this causes a lot of disruption for long-term tenants that want continuity of tenancy.6

The appeal of cryptocurrency like bitcoin has been undermined by its reputation as a fringe alternative to traditional financial systems, as well as by volatility, security issues and lack of regulation. For example, Cryptocurrency is often used for illegal transactions, for example transactions on the dark web, due to it being impossible to track. This has been detrimental to its general acceptance as an international currency, replacing for example the US$. Taken with the (high levels of) volatility of cryptocurrency, and the reality that if the code is lost7 the cryptocurrency investment cannot ever be recovered, made cryptocurrency a high-risk proposition with a flavour of illegal activities, without the benefits of a trusted authority or central server. However, cryptocurrencies like Facebook’s Libra, a digital currency that will be accessible via a digital wallet in Messenger and WhatsApp, could change the image of cryptocurrencies by being underwritten by ‘trusted’ companies.8 Facebook's bid to get its 2.4 billion users to use Libra could help legitimize a sector that struggles to garner broader public interest and confidence.

Another issue is the tax implications of some of these disruptive technologies. The nature of the sharing economy often results in the actors (i.e., accommodation providers or ride 6

While the sharing economy also puts pressure on traditional businesses, i.e., accommodation sharing like Air BNB puts pressure on the hotel industry while ride sharing like Uber and Ola put pressure on taxi companies, this is the consequences of more competition in the field. 7 If for example you lose the laptop or USB with the crypto code, you can never recover your cryptocurrency. 8 Facebook is framing Libra as an alternative to traditional financial services for the billions of people worldwide who lack access to banking. It's backed by 28 companies and non-for-profits, including finance and tech giants such as Mastercard and Uber.

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providers) being individuals, not declaring these activities for income tax purposes and/or paying rates and other taxes as commercial operators. While this results in governments and local councils losing out on taxes, it also creates unfair advantage at the cost of the taxpayer as the formal providers of these services (i.e., hotels and taxi companies), being commercial enterprises, have to pay these taxes. In some jurisdictions, governments are trying to tax, for example, private accommodation providers renting out parts of their own homes. Arguably of greater concern is the failure of Big-Tech companies to pay their fair share of taxes (Toplensky, 2018). In July 2019, France introduced a digital services tax (White, 2019).

Fourth: Governance stakeholder challenges More specifically, we propose further study on how three other governance stakeholder groups: board of directors; shareholders and regulatory bodies, may bridge the gap between the needs arising from disruptive technologies and traditional regulatory models and approaches. In addition, further study is required to better understand how corporate governance can support Christensen’s (1997) two types of technological developments: sustained technology and disruptive technology.

Board of directors The board of directors are charged with both fiduciary duties and strategic development responsibilities. Evans (2017, p. 217) argues that “[e]ach company will need to implement effective oversight of the technology to even stay competitive, requiring a much deeper understanding from existing board members than appears within current literature”. Questions boards face include: What are the types of risks faced by my organisation emanating from disruptive technologies? How can boards be better prepared to address these risks? Will boards have to change their composition? Arguably, one suggestion is that the solution to the technological disruption problem is to add a technical expert to the board of directors (e.g., Bravard, 2015; Moyo, 2016). An interesting alternate view is that by Roberts, McNulty, & Stiles (2005, p. S14) in relation to non-executive directors who contend that independence and some distance from day-to-day management can enhance board functioning: “In practice, such experienced ignorance can be a very valuable resource for a

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board”. Overall the question of board composition, culture and board dynamics will need review.

Shareholders Shareholders can function as a critical monitoring mechanism over managerial decisions. However, the benefits of doing so is often proportionately related to the percentage of shares owned (Jensen and Meckling, 1976; Shleifer and Vishny, 1997).

Yermack (2017) and Piazza (2017) predict that blockchain will affect shareholders. If it is used to record shareholdings, it will result in timely and accurate recording of ownership, providing transparency to identify who owns shares and debt in companies, thereby reducing opportunistic behaviour by companies, stock exchanges and regulators. It would not be so easy to build secret positions in companies and make a killing. Yermack (2017) also expects that with blockchain, trading would become cheaper and quicker, with consequent easier entry and exit by major shareholders. Blockchain might also impact managerial stock options, for example, by reducing their ability to use insider information for personal profit.

Regulators Regulators play a critical role in setting the boundaries and standards of governance. How regulators view and deal with disruptive innovations will also need to expand into real-time and ‘agile’ policymaking. For example, regulators could be provided blockchain access to review transactions in real time. (CPA Canada, 2016). Yermack (2017) also cautions that a new model of governance will be required to govern the blockchain itself, with a governance process in which users agree to protocols for the underlying software code to be changed. Society will require new rules, controls, best-practice models and skills to facilitate a smooth transition to a blockchain-enabled future (CPA Canada, 2016).

Some of the issues researchers could focus on include – ‘How will government policies and regulatory changes, say taxation developments, affect approaches by boards to risks from disruptive technology? To what extent with hard laws and soft laws such as rules, international treaties, or codes of conduct remain fit for purpose? For example, regulation of banks focusses on regulations, while the outside world moves on. The regulations are not 25

fit for purpose for the new world and reflect status quo thinking. The regulatory framework is behind, playing catch up, solving yesterday’s problems.

In particular, we consider studies on the social practice and the impacts disruptive technologies and innovations have on governance mechanisms such as the board of directors, financial reporting, audit committees, internal and external auditing, shareholders and regulation.

Fifth: Theoretical development Dealing with DTI involves capacity to adapt and transform appropriately at both the individual and organisational levels. Past studies relating to governance behaviours under highly uncertain and complex environments have adopted multiple conceptual stances in understanding managerial and firm behaviours e.g., agency, organisational psychology, stewardship, stakeholder, and resource dependency theories to name a few (Aghion et. al., 2013; Kapoor and Klueter, 2017; Gans, 2016). However, many studies have not examined how individual predispositions towards risk and accountability affect organisational level outcomes. Given that good governance of DTI is dependent on attributes such as agility and collaboration, individual and organisational-level psychology theories, e.g., adaptive capacity and social network theories (Bhimani and Wilcocks, 2014; Camps and Marques, 2014) may be relevant.

Further, future studies may also use multiple theories to better understand how accounting information and performance indicators may become invalid when transaction processing and business models change dramatically. For example, more rigorous and real-time performance indicators may be needed when using cryptocurrencies. Further, Kapoor and Klueter (2017, p. 86) conclude, based on a two-year field study of the pharmaceutical industry in the US, that “when evaluating emerging technologies, managers should assess not only the new functionality and associated competences that their companies may need to develop but also whether the emerging technology has a significantly different customer value proposition and profit equation”. Their findings signal the need for more research on the different theories of organisational change models to determine how governance mechanisms can help transform business models to make the needed change. Additional 26

research on how managerial incentives, particularly those based on bonuses and financial performance affect the propensity or use of different accountability mechanisms in highly volatile and ambiguous situations, can be helpful for understanding good governance.

Consequently, future studies that research the manner in which risk management at both the individual and organisational levels become important to understand how governance systems can be better designed to help organisations deal with unprecedented business model transformations.

6. Conclusion Disruptive technology poses both challenges and opportunities for enhancing corporate governance. This special issue provides fruit for thought and action, calling on insights from three distinct papers and related literature, on how to better design and utilise corporate governance and accounting mechanisms within DTI contextual settings. Agile, collaborative and expeditious decision-making are not only valuable but necessities for effective and efficient governance. Governance stakeholders both within and external to the organisations need to be knowledgeable and proactive in assessing and responding to the risks and opportunities offered by DTI. The challenge for researchers is to identify and foster governance design and systems that balance human and technical demands created by rapidly shifting waves of technology and societal needs.

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