07.11 Decentralized Science (DeSci): Promises and Limitations of Blockchain Based Initiatives for Sustainable Value Creation in Academia
Aim of the project
The project has a descriptive and an explanatory aim. The descriptive aim consists in mapping the emerging organizational field of blockchain based Decentralized Science (DeSci) initiatives, in particular DAOs, and their interplay with established or Centralized Science (CeSci) organizations. The second aim is to investigate how variations in the institutional arrangements, including different modes of blockchain governance, of DeSci initiatives affect their capacity to foster sustainable cooperation and value creation within and between the organizations involved.
Theoretical background
The institutions governing the academic system are under pressure. Cut-throat competition for dwindling research funds, pervasiveness of precarious short-term contracts, a merciless publish-or-perish culture, and rising student-to-staff ratios causing endemic overwork are only some of the flaws that according to critics characterize modern Academia. These problems and the detrimental consequences for all involved stakeholders are well-known. Examples are funding institutions being overburdened with an overwhelming number of grant proposals to process; the peer-review system getting clogged; individual scientists entering an increasingly uncertain career path and an ever widening set of performance evaluation criteria. In The Netherlands during the past decade, calls for reform kept intensifying and were fueled both by grass root initiatives (like Science in Transition, a movement run by scientists) and more organized attempts launched by the leadership of Dutch Universities (like the Recognition and Reward framework for evaluating performance of scientific personnel). Many welcome these efforts as an effective first step towards correcting the excesses of an overheated but otherwise functional system of knowledge production. A small but growing group is more skeptical, considering the current system as such as not sustainable in the long run. For them, current reform initiatives remain futile attempts to treat the symptoms, rather than attacking the root cause of the problem. They claim that as long as the organization of science rests on highly centralized structures – dominated by coalitions of gatekeepers who decide who gets access to research funds, to publishing opportunities and to academic positions – the performance of the academic system as a whole will decline, and with it its valuableness to society. This group of stakeholders therefore advocates a more radical approach towards transformation. The Decentralized Science (DeSci) movement explores how blockchain technology can be used not only to solve some of the pressing issues of the current academic system, but also to fundamentally restructure it (Etzrodt, 2018; Ducrée et al, 2022; Wang et al, 2022). Blockchains are a relatively recent invention – the idea was proposed only in 2008 and popularized as their initial applications to cryptocurrencies in alt-finance gained momentum. Bitcoin, its competitors and a wide array of financial experiments slowly formed into what has become known as decentralized finance (DeFi), where many consider the related technology as a true game changer. Decentralized Science applications of blockchain technology are even more recent (Kosmarski, 2020). DeSci is part of the widening applications of blockchains, including to the Internet and knowledge governance in digital society as part of “the latest Web3 Movement” (Hamburg, 2022). The ambitions of this movement are high: “DeSci revolutionizes the structure, norms, incentives, and value allocation of centralized scientific systems….It uses digital tools for funding, organizing, training, planning, coordinating, dispatching, collecting, distributing of supply and demand activities, and resources in cyberspace-based communities. DeSci re-incentivizes the scientific ecosystem through token systems and decentralized power, and returning scientific value and ownership to knowledge producer” (Ding et al., 2022). More and more DeSci initiatives are now launched (Keck et al, 2020), and Decentralized Autonomous Organizations (DAOs) are a key tool to implement them (see e.g. https://ethereum.org/en/desci/). DeSci advocates embrace this new hybrid organizational form not only because it promises to enable “trustless” cooperation, but also because it may allow wiser evaluations, better incentivation and fairer recognition and reward of individual contributions. DeSci DAOs have been launched for almost all facets of academia, ranging from funding to community building to peer review to reputation systems. However, so far we lack a systematic inventory of the initiatives, their core assumptions, ambitions, strategies and progress as a new element of the current academic system and its organizations. This project therefore heeds the recent call for mapping this emerging organizational field and assess under which conditions and how DeSci DAOs succeed in sustaining value creation in science, and which obstacles they may face: “A thorough review of the DeSci landscape and its implications would promote open discussion on the impact of these new technologies on scientific research.” (Hamburg, 2021). Theory Decentralized Science initiatives are relatively recent, and so is theorizing about it. DeSci can be analyzed from a variety of theoretical angles, since it contains aspects of a professional (social) movement, reflects the emergence of a new organizational field (Wooten & Hofmann, 2008; Zietsma & Lawrence, 2010), implies the (de-)institutionalization of deeply engrained established practices (Dacin & Dacin, 2008) and the required processes of frame restructuration (Kim, 2021), and aspires the institutionalization of new forms of governing multi-institutional interdisciplinary research collaborations (Corley et al., 2006) through establishing blockchain networks as polycentric orders (Alston et al., 2022). Though none of these theoretical frameworks so far have touched upon the opportunities and challenges related to blockchain governance, they provide useful pointers to answer the question under which conditions blockchain governance can foster the sustainability of decentralized science organizations and collaborations. For example, Corley et al. (2006) argued that for large-scale, multi-discipline, inter-institutional collaborations to succeed, they need to achieve a high level of refinement either in the epistemic development of the involved disciplines, or of the organizational structure of the collaboration. Drawing on material from two case studies, they propose and show that it is the domain (epistemic vs. organizational) with the highest level of institutionalization that organizes the rules of the cooperation. Studying the development of alternative forms of organization in the face of crises, Kim (2021) makes a strong case for the necessity of developing effective new diagnostic and prognostic cognitive frames replacing established ones that prove increasingly dysfunctional. More generally, these accounts share a concern for the dynamics affecting multiple dimensions of institutional strength. The Theory of Institutional Strength (Hindriks, 2022) allows to integrate these perspectives and serves as a point of departure for this project. Conceiving institutions as norm governed social practices, this approach argues that the strength of institutions is a function of either the degree of compliance to coordination rules that solve problems of information, or of the weight attributed to the cooperation rules that solve problems of motivation. The project will further elaborate the institutional strength approach and apply it to the new realm of Blockchain Governance of the organizational field of DeSci DAOs and their multi-stakeholder relations.
Research design
A mixed method approach will be used to empirically investigate the nascent organizational field of Decentralized Science and the organizations involved in it. A first step consists in mapping Blockchain or Web3 Based Decentralized Science Initiatives and eliciting documents and communications about their institutional arrangements and governance principles, including how these have changed so far. We then follow the empirical strategy developed by Herzog et al. (2022). This empirical strategy collects two types of data. First, it identifies the relevant organizational actors that are part of the organizational field. Exploratory interviews with experts will be used for this mapping exercise. In a second step, documents (e.g. white papers, internal memos) and in-depth interviews with representatives of these organizations will be used to reconstruct the institutional grammar underlying the envisioned DeSci arrangements that are supposed to govern scientific practice in different domains. Coding will follow the procedure elaborated in the Institutional Grammar Tool (IGT, (Bushouse et al, 2021), which allows a fine grained systematic mapping of (changes in) rule systems, including their implications for prescribed interactions. It identifies six components (ibid): “(1) the Attribute which is the actor who is to carry out the rule; (2) the Deontic which identifies whether the action is required, permitted, or forbidden; (3) the aim which specifies the action; (4) Conditions which further specify or limit the aim; conditions typically specify how, when, or where the action is to be taken; (5) Or else, which specifies the penalty for not taking the action; and (6) the object which is the receiver of the action”. The second step consists of a sociometric survey mapping de perceived interactions between stakeholders within and between involved organizations in different domains. During this step, perceived collaborative network structures (rules in use, including perceived interactions) will be elicited. A sociometric survey will be sent to key representatives of the identified organizations. This survey will elicit collaborative relations (e.g. for inter-organizational interactions: “with which organizations has your organization been closely collaborating within the domain of [x] during the past six months”. Respondents will also be asked to indicate which policy instruments, in their view, could improve practices in specific science domains. Also their policy core beliefs will be elicited, i.e. “general principles actors want to see implemented” (Herzog et al., 2022:373) regarding a specific domain (e.g. social justice, competition).
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PhD
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Lidia Yatluk
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Promotors
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Prof. dr. R. P. M. (Rafael) Wittek, Coordinating researcher
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Project Initiators
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Dr. M (Malcolm) Campbell-Verduyn
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Prof. dr. F. A. (Frank) Hindriks
- Discipline
Sociology - Location
University of Groningen, Faculty of Behavioural and Social Sciences, Department of Sociology - Period
September 1, 2023 - Present
Literature
Abramson, C. M., & Dohan, D. (2015). Beyond Text: Using Arrays to Represent and Analyze Ethnographic Data. Sociological Methodology, 45(1), 272–319.https://doi.org/10.1177/0081175015578740
Alston, E., Law, W., Murtazashvili, I., & Weiss, M. (2022). Blockchain networks as constitutional and competitive polycentric orders. Journal of Institutional Economics, 18(5), 707–723. https://doi.org/10.1017/S174413742100093X
Baninemeh, E., Farshidi, S., & Jansen, S. (2021). A Decision Model for Decentralized Autonomous Organization Platform Selection: Three Industry Case Studies. ArXiv:2107.14093 [Cs]. http://arxiv.org/abs/2107.14093
Becker, B. E., & Huselid, M. A. (1992). The incentive effects of tournament compensation systems. Administrative Science Quarterly, 336-350.
Berg, C., Davidson, S., & Potts, J. (2020). Capitalism after Satoshi: Blockchains, dehierarchicalisation, innovation policy, and the regulatory state. Journal of Entrepreneurship and Public Policy, 9(2), 152-164.
Bellavitis, C., Fisch, C., & Momtaz, P. P. (2022). The rise of decentralized autonomous organizations (DAOs): A first empirical glimpse. Venture Capital, 1–17. https://doi.org/10.1080/13691066.2022.2116797
Bernards, N., Campbell-Verduyn, M., & Rodima-Taylor, D. (2022). The veil of transparency: Blockchain and sustainability governance in global supply chains. Environment and Planning C: Politics and Space, 23996544221142764. https://doi.org/10.1177/23996544221142763
Bushouse, B. K., Schweik, C. M., Siddiki, S., Rice, D., & Wolfson, I. (2021). The Institutional Grammar: A Method for Coding Institutions and its Potential for Advancing Third Sector Research. VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations. https://doi.org/10.1007/s11266-021-00423-w
Bustamante, P., Cai, M., Gomez, M., Harris, C., Krishnamurthy, P., Law, W., Madison, M. J., Murtazashvili, I., Murtazashvili, J. B., Mylovanov, T., Shapoval, N., Vee, A., & Weiss, M. (2022). Government by Code? Blockchain Applications to Public Sector Governance. Frontiers in Blockchain, 5, 869665. https://doi.org/10.3389/fbloc.2022.869665
Choi, J., & Hexlant, B. A. and H. of R. at. (2022). DAOs: Empowering the Community to Build Trust in the Digital Age. Stanford Journal of Blockchain Law & Policy. https://stanford-jblp.pubpub.org/pub/dao/release/1
Corley, E. A., Boardman, P. C., & Bozeman, B. (2006). Design and the management of multi-institutional research collaborations: Theoretical implications from two case studies. Research Policy, 35(7), 975–993. https://doi.org/10.1016/j.respol.2006.05.003
Crawford, S. E. S., & Ostrom, E. (1995). A Grammar of Institutions. American Political Science Review, 89(03), 582–600. https://doi.org/10.2307/2082975
Dacin, M. T., Dacin, P. A. (2008). Traditions as institutionalized practice: Implications for deinstitutionalization. The Sage handbook of organizational institutionalism, 327, 352. Ding, W., Hou, J., Li, J., Guo, C., Qin, J., Kozma, R., & Wang, F.-Y. (2022).
DeSci Based on Web3 and DAO: A Comprehensive Overview and Reference Model. IEEE Transactions on Computational Social Systems, 9(5), 1563–1573. https://doi.org/10.1109/TCSS.2022.3204745
Dallyn, S., & Frenzel, F. (2021). The Challenge of Building a Scalable Postcapitalist Commons: The Limits of FairCoin as a Commons-Based Cryptocurrency. Antipode, 53(3), 859-883.
De Filippi, P., Mannan, M., & Reijers, W. (2020a). Blockchain as a confidence machine: The problem of trust & challenges of governance. Technology in Society, 62, 101284. https://doi.org/10.1016/j.techsoc.2020.101284
Ducrée, J., Codyre, M., Walshe, R., & Barting, S. (2022). DeSci-Decentralized Science. ENGINEERING. https://doi.org/10.20944/preprints202205.0223.v1
DuPont, Q. (2018). Experiments in Algorithmic Governance: A History and Ethnography of “The DAO”, a failed Decentralized Autonomous Organization. In Bitcoin and Beyond: Cryptocurrencies, Blockchains and Global Governance, edited by Malcolm Campbell-Verduyn. Routledge.
Etzrodt, M. (2018). Advancing science through incentivizing collaboration, not competition. https://doi.org/10.5281/zenodo.1156360
Faqir-Rhazoui, Y., Arroyo, J., & Hassan, S. (2021). A comparative analysis of the platforms for decentralized autonomous organizations in the Ethereum blockchain. Journal of Internet Services and Applications, 12(1), 9. https://doi.org/10.1186/s13174-021-00139-6
Fenton, A. (2021, August 24). Blockchain is as revolutionary as electricity: Big Ideas with Jason Potts. Cointelegraph Magazine. https://cointelegraph.com/magazine/blockchain-is-as-revolutionary-as-electricty-big-ideas-with-jason-potts/
Fischer, A., & Valiente, M.C. (2021). Blockchain governance. Internet Policy Review, 10(2). https://policyreview.info/glossary/blockchain-governance
Gächter, S., Kölle, F., & Quercia, S. (2017). Reciprocity and the tragedies of maintaining and providing the commons. Nature Human Behaviour, 1(9), 650.
Galloway AR (2004) Protocol: How control exists after decentralization. Cambridge, Massachusetts: MIT press.
Ghavi, A., Qureshi, A., Weinstein, G., Schwartz, J., & Lofchie, S. (2022, September 17). A Primer on DAOs. The Harvard Law School Forum on Corporate Governance. https://corpgov.law.harvard.edu/2022/09/17/a-primer-on-daos/
Hamburg, S. (2021). Call to join the decentralized science movement. Nature, 600(7888), 221–221. https://doi.org/10.1038/d41586-021-03642-9
Hassan, S., & Filippi, P. D. (2021). Decentralized Autonomous Organization. Internet Policy Review, 10(2). https://policyreview.info/glossary/DAO
Herzog, L. (2021). Algorithmisches Entscheiden, Ambiguitätstoleranz und die Frage nach dem Sinn. Deutsche Zeitschrift für Philosophie, 69(2), 197-213.
Herzog, L., Ingold, K., & Schlager, E. (2022). Prescribed by law and therefore realized? Analyzing rules and their implied actor interactions as networks. Policy Studies Journal, 50(2), 366–386. https://doi.org/10.1111/psj.12448
Hindriks, F. (2022). Institutions and their strength. Economics and Philosophy, 38(3), 354–371. https://doi.org/10.1017/S0266267121000195
Hütten, M. (2019). The soft spot of hard code: Blockchain technology, network governance and pitfalls of technological utopianism. Global Networks, 19(3), 329–348. https://doi.org/10.1111/glob.12217
Kellogg, K. C., Valentine, M. A., & Christin, A. (2020). Algorithms at Work: The New Contested Terrain of Control. Academy of Management Annals, 14(1), 366–410. https://doi.org/10.5465/annals.2018.0174
Keck, I.R.; Heller, L.; Blümel, I. Distributed Science Infrastructure Projects, Version 1.1 [Dataset]. Zenodo 2020.
Kim, S. (2021). Frame Restructuration: The Making of an Alternative Business Incubator amid Detroit’s Crisis. Administrative Science Quarterly, 000183922098646. https://doi.org/10.1177/0001839220986464
Kolbjørnsrud, V. (2018). Collaborative organizational forms: On communities, crowds, and new hybrids. Journal of Organization Design, 7(1), 11. https://doi.org/10.1186/s41469-018-0036-3
Kosmarski, A. (2020). Blockchain Adoption in Academia: Promises and Challenges. Journal of Open Innovation: Technology, Market, and Complexity, 6(4), Article 4. https://doi.org/10.3390/joitmc6040117
Kruse, D. P., Rövekamp, G., & Weber, C. (2022). Collaboration of Firms With New Forms of Organizing: Extending the Relational View. Organization Theory, 3(4), 26317877221131584. https://doi.org/10.1177/26317877221131586
Lehdonvirta, V. (20220). "Cryptocracy: The Quest to Replace Politis with Techology." Pp.131-124 in: Cloud Empires: How Digital Platforms Are Overtaking the State and How We Can Regain Control. MIT Press.
Lindenberg, S. (2014). Sustainable cooperation needs tinkering with both rules and social motivation. Journal of Bioeconomics, 16(1), 71–81. https://doi.org/10.1007/s10818-013-9172-6
Lindenberg, S., & Foss, N. J. (2011). Managing Joint Production Motivation: The Role of Goal Framing and Governance Mechanisms. Academy of Management Review, 36(3), 500–525. https://doi.org/10.5465/amr.2010.0021
Lumineau, F., Wang, W., & Schilke, O. (2020). Blockchain Governance—A New Way of Organizing Collaborations? Organization Science. https://doi.org/10.1287/orsc.2020.1379
Morrison, R., Mazey, N. C. H. L., & Wingreen, S. C. (2020). The DAO Controversy: The Case for a New Species of Corporate Governance? Frontiers in Blockchain, 3. https://www.frontiersin.org/article/10.3389/fbloc.2020.00025
Murray, A., Kuban, S., Josefy, M., & Anderson, J. (2021). Contracting in the Smart Era: The Implications of Blockchain and Decentralized Autonomous Organizations for Contracting and Corporate Governance. Academy of Management Perspectives, 35(4), 622–641. https://doi.org/10.5465/amp.2018.0066
Pink, S., Horst, H., Postill, J., Hjorth, L., Lewis, T., & Tacchi, J. (2015). Digital Ethnography: Principles and Practice. Sage.
Puranam, P., Alexy, O., & Reitzig, M. (2014). What’s “new” about new forms of organizing? Academy of Management Review, 39(2), 162–180.
Rea, A., Kronovet, D., Fischer, A., & Du Rose, J. (2020). Colony. Technical Whitepaper.
Rennie, E., Zargham, M., Tan, J., Miller, L., Abbott, J., Nabben, K., & De Filippi, P. (2022). Toward a Participatory Digital Ethnography of Blockchain Governance. Qualitative Inquiry, 10778004221097056. https://doi.org/10.1177/10778004221097056
Rikken, O., Janssen, M., & Kwee, Z. (2019). Governance challenges of blockchain and decentralized autonomous organizations. Information Polity, 24(4), 397–417. https://doi.org/10.3233/IP-190154
Santana, C. & Albareda, L. (2022). Blockchain and the emergence of Decentralized Autonomous Organizations (DAOs): An integrative model and research agenda. Technological Forecasting and Social Change 183. https://doi.org/10.1016/j.techfore.2022.121806
Schirrmacher, N.-B., Jensen, J. R., & Avital, M. (2021). Token-Centric Work Practices in Fluid Organizations: The Cases of Yearn and MakerDAO. Forty-Second International Conference on Information Systems, Austin.
Schreyögg, G., and Sydow, J. 2010. "Crossroads—Organizing for Fluidity? Dilemmas of New Organizational Forms," Organization Science (21:6), pp. 1251-1262 (doi: 10.1287/orsc.1100.0561).
Sharma, P., Shukla, D. M., & Raj, A. (2023). Blockchain adoption and firm performance: The contingent roles of intangible capital and environmental dynamism. International Journal of Production Economics, 256, 108727. https://doi.org/10.1016/j.ijpe.2022.108727
Teng, Y. What does it mean to trust blockchain technology? Metaphilosophy (2022) doi:10.1111/meta.12596.
Termeer, C. J. A. M., Dewulf, A., Breeman, G., & Stiller, S. J. (2015). Governance Capabilities for Dealing Wisely With Wicked Problems. Administration & Society, 47(6), 680–710. https://doi.org/10.1177/0095399712469195
Tse, N. (2020). Decentralised Autonomous Organisations and the Corporate Form. Victoria University of Wellington Law Review, 51(2), 313. https://doi.org/10.26686/vuwlr.v51i2.6573
Vergne, J. P. (2020). Decentralized vs. distributed organization: Blockchain, machine learning and the future of the digital platform. Organization Theory, 1(4), 2631787720977052.
Wang, F.-Y., Ding, W., Wang, X., Garibaldi, J., Teng, S., Imre, R., & Olaverri-Monreal, C. (2022). The DAO to DeSci: AI for Free, Fair, and Responsibility Sensitive Sciences. IEEE Intelligent Systems, 37(2), 16–22. https://doi.org/10.1109/MIS.2022.3167070
Wooten, M., & Hoffman, A. J. (2008). Organizational fields: Past, present and future. The Sage Handbook of Organizational Institutionalism, 131-147.
Zietsma, C., & Lawrence, T. B. (2010). Institutional work in the transformation of an organizational field: The interplay of boundary work and practice work. Administrative Science Suarterly, 55(2), 189-221.