Preliminary to the feasibility of McCallig’s design

Preliminary research proposalIntroduction and relevanceRecently, there has been much discussion on the applications of blockchain technology.

One such application is the use of blockchain for financial auditing purposes (Querica, 2018). Although there is underlying agreement, that verifying and storing transaction information in a blockchain can bring efficiency gains to the industry (Andersen, 2016; Psaila, 2018; PwC, 2018), many other implications, including the design of such a blockchain register as well as why companies would contribute to such a system remain unclear. To bring direction to the discussion John McCallig (McCallig, 2016) has proposed a concrete blockchain design which can be used for auditing purposes. Contributing to the feasibility of McCallig’s design and to fill a gap in his proposal, this study will investigate: Research question: How can companies be incentivised to participate in the blockchain auditing model as described by John McCallig?Possible answers to this question include both monetary and non-monetary incentive structures.

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All possible answers depend on certain pre-conditions (data security ; privacy etc.), which cannot be analysed due to the limited scope of this research. Monetary incentive structures include direct payments per unit of information to the contributing company by the audited company or the auditor or discounts for the contributing company on future purchases from the audited company (Yunhua et. al., 2018, p. 27326).Non-monetary incentive structures involve reputational considerations or the idea of creating a system based on reciprocal information exchange (Yunhua et.

al., 2018, p.27325). Beneficiaries McCallig and engineers suggesting similar blockchain models would directly benefit from this research as it would contribute to the real-world implementation of their ideas.

In a broader sense, this research contributes towards the innovation of the auditing industry. Methodology We considered different approaches to identify which incentive structures produce the highest contribution from companies to the blockchain. Qualitative interviews: Not useful in identifying a general trend. Also imply a higher cost for less generalizability of results.Experiment:  Data from an idealized setting is not relevant for the purpose of this research.

Case studies: Too specific to identify general trends, which is the goal of this research. Observation: No, simply observing cannot capture the underlying attitudes and opinions involved.  These considerations clarify that we need comparable data on opinions and attitudes from a large number of firms. Consequently, we propose to send surveys to a representative number of firms within particular industries and ask them to rate how likely they would be to partake in the blockchain auditing scheme given different incentives. Example question: “I would put accounting data on a (secure and anonymous) blockchain if I was financially compensated for it”:Strongly Disagree Disagree Undecided Agree Strongly Agree1 2 3 4 5Concerning our methodology, we want to assess whether using a Likert scale as compared to a nominal or metric scale is the most useful means to identify preferences in this context. Furthermore, we are unsure if using a Likert scale limits, us in our analysis. There is some ambiguity concerning whether Likert data can be analysed as more than ordinal data i.

e. a simple ranking of preferences (Urban and Mayerl, 2011; University of Zurich, 2016).ReferencesAndersen, N.

(2016) Deloitte Blockchain Technology: A game-changer in accounting? Available at:

pdf (Accessed 1st October 2018)Callig,J.(2016) The Recording and Secure Audit of Accounting Information Based on a ConsensusPsaila, S. (2018). Deloitte Blockchain: A game changer for audit processes? Available at: (Accessed 3 Oct.

2018). PwC (2018). PwC’s Global Blockchain Survey 2018 Blockchain is here.

What’s your next move? Available at: (Accessed 3 Oct. 2018).

Methodenberatung University of Zurich (2016). Skalenniveau. Available at:

html (Accessed 2 Oct. 2018).Urban, D., Mayerl, J.

(2011) Regressionsanalyse: Theorie, Technik und Anwendung 2nd edn.Wiesbaden: Springer.Querica,R.L.(2018) How Blockchain Is Reshaping External Audit: Crypto Developments by PwC, KPMG, EY and Deloitte.Available at : ).

(Accessed 1st October 2018)Yunhua et. al. 2018 A Blockchain Based Truthful Incentive Mechanism for Distributed P2P Applications, IEEE Access (6),pp.27325-27326BibliographyBible, W et al.

(2017) Blockchain Technology and Its Potential Impact on the Audit and Assurance ProfessionGray, D.E., 2013. Doing research in the real world. Sage.Halaburda, H, (2016) ‘Digital Currencies: Beyond Bitcoin’,  Digiworld Economic Journal, 103 (3), p. 77-92.National Bureau of Economic Research (2018) ‘Some Simple Economics of the Blockchain’.Available at: (Accessed 1st October 2018)


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