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Going beyond intent to adopt Blockchain: an analytics approach to understand board member and financial health characteristics

  • S.I. : Artificial Intelligence in Operations Management
  • Published:
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Abstract

Blockchain is an emerging, but revolutionary technology. Numerous reports suggest that Blockchain use will bring innovation in various processes and convey plentiful competitive benefits for the companies that adopt it. However, reports suggest that without a complete understanding of its usage and implementation, Blockchain could also expose firms to unknown risks and costs. Despite this ambiguity, some firms tend to be leading the charge to embrace this technology, while others appear highly skeptical. From a scholarly standpoint, there is a little rigorous scholarship that has investigated the characteristics of firms that seek to pursue Blockchain. This study provides a literature review regarding Blockchain and fulfills this research gap by applying a data-driven clustering technique to develop analytics models for the longitudinal financial performance of firms exhibiting an intention to adopt Blockchain. We then use a descriptive approach to investigate such companies’ board member’s characteristics. Key findings suggest that out of 38 firms showing an intent to adopt Blockchains, 23 firms exhibit long-term financial well-being based on Earning Quality and Earnings-per-share Growth. This rate is significantly more in comparison with the pool of publically traded companies. The analysis of board member data for the firms that intended to adopt Blockchains and exhibit long-term financial health demonstrated: (1) higher levels of education among employees, (2) greater longevity at the firm, and (3) larger network size. This study offers data-driven implications for the companies that have demonstrated intent to adopt Blockchain. For being further competitive advantages, such leading organizations may require different decisions or strategic paths for going beyond their initial adoption intent due to inherent variations in their long term financial and board members.

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References

  • Abadi, J., & Brunnermeier, M. (2018). Blockchain economics.

  • Adams, R. B., & Funk, P. (2012). Beyond the glass ceiling: Does gender matter? Management Science, 58(2), 219–235.

    Google Scholar 

  • Agarwala, S. (2017). Blockchain and ERP. Retrieved from https://www.linkedin.com/pulse/blockchain-erp-sanjay-agarwala#:~:text=Unlike%20in%20case%20of%20ERP,alter%20the%20data%20without%20consensus.

  • Akter, S., Michael, K., Uddin, M. R., McCarthy, G., & Rahman, M. (2020). Transforming business using digital innovations: the application of AI, blockchain, cloud and data analytics. Annals of Operations Research, 1–33.

  • Alexandre, A. (2018). Walmart is ready to use blockchain for its live food business. Retrieved from https://cointelegraph.com/news/walmart-is-ready-to-use-blockchain-for-its-live-food-business.

  • Andrevski, G., & Ferrier, W. J. (2016). Does it pay to compete aggressively? Contingent roles of internal and external resources. Journal of Management, 45(2), 620–644.

    Google Scholar 

  • Andrevski, G., Richard, O. C., Ferrier, W. J., & Shaw, J. D. (2010). Managerial racial diversity, competitive aggressiveness and firm performance: A moderated mediation model. Paper presented at the Academy of Management Proceedings.

  • Angelis, J., & da Silva, E. R. (2019). Blockchain adoption: A value driver perspective. Business Horizons, 62(3), 307–314.

    Google Scholar 

  • Aral, S., Brynjolfsson, E. & Wu, D. (2006). Which came first, it or productivity? Virtuous cycle of investment and use in enterprise systems. Paper presented at the ICIS, Milwaukee.

  • Archibugi, D., Filippetti, A., & Frenz, M. (2013). Economic crisis and innovation: Is destruction prevailing over accumulation? Research Policy, 42(2), 303–314.

    Google Scholar 

  • Atkin, D. J., Neuendorf, K., Jeffres, L. W., & Skalski, P. (2003). Predictors of audience interest in adopting digital television. The Journal of Media Economics, 16(3), 159–173.

    Google Scholar 

  • Audia, P. G., & Greve, H. R. (2006). Less likely to fail: Low performance, firm size, and factory expansion in the shipbuilding industry. Management Science, 52(1), 83–94.

    Google Scholar 

  • Awa, H. O., Eze, S. C., Urieto, J. E., & Inyang, B. J. (2011). Upper echelon theory (UET): A major determinant of information technology (IT) adoption by SMEs in Nigeria. Journal of Systems and Information Technology, 13(2), 144–162.

    Google Scholar 

  • Azaria, A., Ekblaw, A., Vieira, T., & Lippman, A. (2016). Medrec: Using blockchain for medical data access and permission management. Paper presented at the 2016 2nd international conference on open and big data (OBD).

  • Babich, V., & Hilary, G. (2020a). OM forum—Distributed ledgers and operations: What operations management researchers should know about blockchain technology. Manufacturing Service Operations Management, 22(2), 223–240.

    Google Scholar 

  • Babich, V., & Hilary, G. (2020b). OM forum—Distributed ledgers and operations: What operations management researchers should know about blockchain technology. Manufacturing & Service Operations Management, 22(2), 223–240.

    Google Scholar 

  • Badhotiya, G. K., Sharma, V. P., Prakash, S., Kalluri, V., & Singh, R. J. M. T. P. (2021). Investigation and assessment of blockchain technology adoption in the pharmaceutical supply chain.

  • Balasubramanian, S., Shukla, V., Sethi, J. S., Islam, N., Saloum, R. J. T. F., & Change, S. (2021). A readiness assessment framework for Blockchain adoption: A healthcare case study. Technological Forecasting and Social Change, 165, 120536.

    Google Scholar 

  • Bandt, C., & Pompe, B. (2002). Permutation entropy: A natural complexity measure for time series. Physical Review Letters, 88(17), 174102.

    Google Scholar 

  • Barber, S., Boyen, X., Shi, E., & Uzun, E. (2012). Bitter to better—How to make bitcoin a better currency (Vol. 7397, pp. 399–414). https://doi.org/10.1007/978-3-642-32946-3_29

  • Barcelo, J. (2014). User privacy in the public bitcoin blockchain. Retrieved May 09, 2016, from http://www.dtic.upf.edu/jbarcelo/papers/20140704UserPrivacyinthePublicBitcoinBlockchain/paper.pdf.

  • Barton, D., Manyika, J., Koller, T., Robert Palter, T., Godsall, J., & Zoffer, J. (2017). Measuring the economic impact of short-termism.

  • Bateman, A., & Cottrill, K. (2017). Blockchain’s garbage in, garbage out challenge. Retrieved from https://supplychainmit.com/2017/10/19/blockchains-garbage-in-garbage-out-challenge/.

  • Berndt, D. J., & Clifford, J. (1994). Using dynamic time warping to find patterns in time series. Paper presented at the KDD workshop.

  • BoardEx. (2018). WRDS data dictionary. Retrieved from https://metalib.ie.edu/ayuda/Varios/BoardExWRDSDataDictionary.pdf.

  • Bobbitt, L. M., & Dabholkar, P. A. (2001). Integrating attitudinal theories to understand and predict use of technology-based self-service. International Journal of Service Industry Management, 12, 423–450.

    Google Scholar 

  • Bogucharskov, A., Pokamestov, I., Adamova, K., & Tropina, Z. N. (2018). Adoption of blockchain technology in trade finance process. Journal of Reviews on Global Economics, 7, 510–515.

    Google Scholar 

  • Brandmaier, A. M. (2011). Permutation distribution clustering and structural equation model trees.

  • Brandmaier, A. M. (2015). pdc: An R package for complexity-based clustering of time series. Journal of Statistical Software, 67(5), 1–23.

    Google Scholar 

  • Browne, R. (2017). There were more than 26,000 new blockchain projects last year-only 8% are still active.

  • Burgess, K., & Colangelo, J. (2015). The promise of bitcoin and the Blockchain. Consumers’ Research.

  • Buterin, V. (2014). A next-generation smart contract and decentralized application platform. White paper.

  • Cai, Y., & Zhu, D. (2016). Fraud detections for online businesses: A perspective from blockchain technology. Financial Innovation, 2(1), 20.

    Google Scholar 

  • Carr Jr, V. (1999). Technology adoption and diffusion. The Learning Center for Interactive Technology.

  • Casey, M., & Wong, P. (2017). Global supply chains are about to get better, thanks to blockchain. Harvard Business Review, 13, 1–6.

    Google Scholar 

  • Cashman, G. D., Gillan, S. L., & Whitby, R. J. (2010). Expertise, connections, and the labor market for corporate directors.

  • Chatterjee, R., & Chatterjee, R. (2017). An Overview Of The Emerging Technology: Blockchain. Paper presented at the 2017 3rd international conference on computational intelligence and networks (CINE).

  • Chen, J.-S., Tsou, H. T., & Huang, A.Y.-H. (2009). Service delivery innovation: Antecedents and impact on firm performance. Journal of Service Research, 12(1), 36–55.

    Google Scholar 

  • Chi, L., Ravichandran, T., & Andrevski, G. (2010). Information technology, network structure, and competitive action. Information Systems Research, 21(3), 543–570.

    Google Scholar 

  • Choi, T.-M. (2020). Supply chain financing using blockchain: impacts on supply chains selling fashionable products. Annals of Operations Research, 1–23.

  • Chuang, T.-T., Rutherford, M. W., & Lin, B. (2007). Owner/manager characteristics, organisational characteristics and IT adoption in small and medium enterprises. International Journal of Management and Enterprise Development, 4(6), 619–634.

    Google Scholar 

  • Cochran, P. L., Wartick, S. L., & Wood, R. A. (1984). The average age of boards and financial performance, revisited. Quarterly Journal of Business and Economics, 23, 57–63.

    Google Scholar 

  • Coletti, P. (2015). Bitcoin’s baby: blockchain’s ‘tamper-proof’revolution’. BBC News, 20.

  • Condos, J., Sorrell, W. H., & Donegan, S. L. (2016). Blockchain technology: Opportunities and risks. Vermont.

  • Croci, E., Gonenc, H., & Ozkan, N. (2012). CEO compensation, family control, and institutional investors in Continental Europe. Journal of Banking & Finance, 36(12), 3318–3335.

    Google Scholar 

  • Croman, K., Decker, C., Eyal, I., Gencer, A. E., Juels, A., Kosba, A., Miller, A., Saxena, P., Shi, E., Sirer, E. G., & Song, D. (2016). On scaling decentralized blockchains. Paper presented at the international conference on financial cryptography and data security.

  • Dai, F., Shi, Y., Meng, N., Wei, L., & Ye, Z. (2017). From Bitcoin to cybersecurity: A comparative study of blockchain application and security issues. Paper presented at 2017 4th international conference on the systems and informatics (ICSAI).

  • Dalziel, T., Gentry, R. J., & Bowerman, M. (2011). An integrated agency–resource dependence view of the influence of directors’ human and relational capital on firms’ R&D spending. Journal of Management Studies, 48(6), 1217–1242.

    Google Scholar 

  • Damanpour, F., & Schneider, M. (2006). Phases of the adoption of innovation in organizations: effects of environment, organization and top managers 1. British Journal of Management, 17(3), 215–236.

    Google Scholar 

  • Deaves, R., Lüders, E., & Luo, G. Y. (2008). An experimental test of the impact of overconfidence and gender on trading activity. Review of Finance, 13(3), 555–575.

    Google Scholar 

  • Dedunu, H., & Anuradha, P. (2020). Impact of board diversity on firm performance: Evidence from Sri Lanka. International Journal of Management, Innovation & Entrepreneurial Research, 6(1), 23–31.

    Google Scholar 

  • Den Hertog, P., Van der Aa, W., & De Jong, M. W. (2010). Capabilities for managing service innovation: Towards a conceptual framework. Journal of Service Management, 21(4), 490–514.

    Google Scholar 

  • Dinh, T. T. A., Liu, R., Zhang, M., Chen, G., Ooi, B. C., & Wang, J. (2018). Untangling Blockchain: A data processing view of blockchain systems. IEEE Transactions on Knowledge and Data Engineering, 30(7), 1366–1385. https://doi.org/10.1109/tkde.2017.2781227

    Article  Google Scholar 

  • Dubovitskaya, A., Xu, Z., Ryu, S., Schumacher, M., & Wang, F. (2018). Secure and Trustable Electronic Medical Records Sharing Using Blockchain. In AMIA ... annual symposium proceedings. AMIA Symposium, 2017 (pp. 650–659). Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/29854130; https://www.ncbi.nlm.nih.gov/pmc/PMC5977675/.

  • Dwivedi, Y. K., & Lal, B. (2007). Socio-economic determinants of broadband adoption. Industrial Management & Data Systems, 107(5), 654–671.

    Google Scholar 

  • Dwivedi, Y. K., Papazafeiropoulo, A., Chuang, T. T., Nakatani, K., & Zhou, D. (2009). An exploratory study of the extent of information technology adoption in SMEs: An application of upper echelon theory. Journal of Enterprise Information Management, 22, 183–196.

    Google Scholar 

  • Elbertsen, L., & Van Reekum, R. (2008). To ERP or not to ERP? Factors influencing the adoption decision. International Journal of Management and Enterprise Development, 5(3), 310–330.

    Google Scholar 

  • Ellis, S. C., Rao, S., Raju, D., & Goldsby, T. J. (2018). RFID tag performance: Linking the laboratory to the field through unsupervised learning. Production and Operations Management, 27(10), 1834–1848.

    Google Scholar 

  • Espinel, V., O’Halloran, D., Brynjolfsson, E., & O’Sullivan, D. (2015). Deep shift, technology tipping points and societal impact. Paper presented at the New York: World Economic Forum–Global Agenda Council on the Future of Software & Society (REF 310815). Google Scholar.

  • Faccio, M., Marchica, M.-T., & Mura, R. (2016). CEO gender, corporate risk-taking, and the efficiency of capital allocation. Journal of Corporate Finance, 39, 193–209.

    Google Scholar 

  • Faleye, O., Kovacs, T., & Venkateswaran, A. (2014). Do better-connected CEOs innovate more? Journal of Financial and Quantitative Analysis, 49(5–6), 1201–1225.

    Google Scholar 

  • Fernandes, C., Farinha, J., Martins, F. V., & Mateus, C. (2017). What explains European banks risk-taking? A simultaneous equations approach.

  • Fosso Wamba, S., Gunasekaran, A., Bhattacharya, M., & Dubey, R. (2016). Determinants of RFID adoption intention by SMEs: An empirical investigation. Production Planning & Control, 27(12), 979–990.

    Google Scholar 

  • Gefen, D., Karahanna, E., & Straub, D. W. (2003). Inexperience and experience with online stores: The importance of TAM and trust. IEEE Transactions on Engineering Management, 50(3), 307–321.

    Google Scholar 

  • Glaser, F., & Bezzenberger, L. (2015). Beyond cryptocurrencies-a taxonomy of decentralized consensus systems.

  • Green, C., & Homroy, S. (2015). Female directors, key committees, and firm performance.

  • Guo, Y., & Liang, C. (2016). Blockchain application and outlook in the banking industry. Financial Innovation, 2(1), 24. https://doi.org/10.1186/s40854-016-0034-9

    Article  Google Scholar 

  • Hackett, R. (2017). Walmart and 9 food giants team up on IBM blockchain plans. Fortune Magazine, 22.

  • Hall, B. H., & Khan, B. (2003). Adoption of new technology.

  • Hastig, G. M., & Sodhi, M. S. (2020). Blockchain for supply chain traceability: Business requirements and critical success factors. Production and Operations Management, 29(4), 935–954.

    Google Scholar 

  • Hitt, L. M., Wu, D., & Zhou, X. (2002). Investment in enterprise resource planning: Business impact and productivity measures. Journal of Management Information Systems, 19(1), 71–98.

    Google Scholar 

  • Holden, W., & Moar, J. (2017). Blockchain Enterprise Survey: Deployments, benefits and attitudes. Juniper Research.

    Google Scholar 

  • Holotiuk, F., Pisani, F., & Moormann, J. (2018). Unveiling the key challenges to achieve the breakthrough of Blockchain: Insights from the payments industry.

  • Horton, J., Millo, Y., & Serafeim, G. (2012). Resources or power? Implications of social networks on compensation and firm performance. Journal of Business Finance & Accounting, 39(3–4), 399–426.

    Google Scholar 

  • Hottenrott, H., & Peters, B. (2012). Innovative capability and financing constraints for innovation: More money, more innovation? Review of Economics and Statistics, 94(4), 1126–1142.

    Google Scholar 

  • Hu, N., Huang, R., Li, X., & Liu, L. (2017). The impact of CEOs’ accounting backgrounds on earnings management and conservatism. Journal of Centrum Cathedra, 10(1), 4–24.

    Google Scholar 

  • Hughes, L., Dwivedi, Y. K., Misra, S. K., Rana, N. P., Raghavan, V., & Akella, V. (2019). Blockchain research, practice and policy: Applications, benefits, limitations, emerging research themes and research agenda. International Journal of Information Management, 49, 114–129.

    Google Scholar 

  • Hunton, J. E., Lippincott, B., & Reck, J. L. (2003). Enterprise resource planning systems: Comparing firm performance of adopters and nonadopters. International Journal of Accounting Information Systems, 4(3), 165–184.

    Google Scholar 

  • Iansiti, M., & Lakhani, K. R. (2017). The truth about blockchain. Harvard Business Review, 95(1), 118–127.

    Google Scholar 

  • IBM. (2017). Bank of Montreal, CaixaBank, Commerzbank, Erste Group, IBM and UBS collaborate to advance an open, blockchain-based trade finance platform. Retrieved from https://www-03.ibm.com/press/us/en/pressrelease/53208.wssv

  • InnoVentures, S., & Wyman, O. (2016). Anthemis Group (2015) The Fintech 2.0 paper: rebooting financial services. Abgerufen am, 7.

  • Jensen, R. (1982). Adoption and diffusion of an innovation of uncertain profitability. Journal of Economic Theory, 27(1), 182–193.

    Google Scholar 

  • Johnson, S. G., Schnatterly, K., & Hill, A. D. (2013). Board composition beyond independence: Social capital, human capital, and demographics. Journal of Management, 39(1), 232–262.

    Google Scholar 

  • Kane, E. (2017). Is Blockchain a general purpose technology? .

  • Kang, H. (2013). The prevention and handling of the missing data. Korean Journal of Anesthesiology, 64(5), 402–406.

    Google Scholar 

  • Kapoor, R., & Lee, J. M. (2013). Coordinating and competing in ecosystems: How organizational forms shape new technology investments. Strategic Management Journal, 34(3), 274–296.

    Google Scholar 

  • Karajovic, M., Narula, H., Pandya, K., Patel, J., & Warring, I. (2017). Blockchain: A manager's guide.

  • Kaufman, L., & Rousseeuw, P. J. (1990). Partitioning around medoids (program pam). Finding Groups in Data: an Introduction to Cluster Analysis, 344, 68–125.

    Google Scholar 

  • Keating, B. W., Coltman, T. R., Fosso-Wamba, S., & Baker, V. (2010). Unpacking the RFID investment decision. Proceedings of the IEEE, 98(9), 1672–1680.

    Google Scholar 

  • Kimberly, J. R., & Evanisko, M. J. (1981). Organizational innovation: The influence of individual, organizational, and contextual factors on hospital adoption of technological and administrative innovations. Academy of Management Journal, 24(4), 689–713.

    Google Scholar 

  • Kitchell, S. (1997). CEO characteristics and technological innovativeness: A Canadian perspective. Canadian Journal of Administrative Sciences/revue Canadienne Des Sciences De L’administration, 14(2), 111–121.

    Google Scholar 

  • Kogan, L., & Tian, M. H. (2012). Firm characteristics and empirical factor models: A data-mining experiment.

  • Kouhizadeh, M., Saberi, S., & Sarkis, J. (2020). Blockchain technology and the sustainable supply chain: Theoretically exploring adoption barriers. International Journal of Production Economics, 231, 107831.

    Google Scholar 

  • Kristiansen, P. (2012). The effect of directors network size on bank performance.

  • Kshetri, N. (2018). 1 Blockchain’s roles in meeting key supply chain management objectives. International Journal of Information Management, 39, 80–89. https://doi.org/10.1016/j.ijinfomgt.2017.12.005

    Article  Google Scholar 

  • Kuo, T.-T., & Ohno-Machado, L. (2018). ModelChain: Decentralized privacy-preserving healthcare predictive modeling framework on private blockchain networks. arXiv:1802.01746.

  • Lacity, M. (2018). Addressing key challenges to making enterprise blockchain applications a reality. MIS Quarterly Executive, 17(3), 201–222.

    Google Scholar 

  • Lacity, M., & Khan, S. (2019). Exploring preliminary challenges and emerging best practices in the use of enterprise Blockchains applications. Paper presented at the proceedings of the 52nd Hawaii international conference on system sciences.

  • Lakhani, K., & Iansiti, M. (2017). The truth about blockchain. Harvard Business Review, 95(1), 119–127.

    Google Scholar 

  • Leopoulos, V., Kirytopoulos, K., & Voulgaridou, D. (2005). ERP systems as a component of the electronic supply chain: Classification of implementation risks. Paper presented at the computational intelligence for modelling, control and automation, 2005 and international conference on intelligent agents, web technologies and internet commerce.

  • Li, Z., Wang, W. M., Liu, G., Liu, L., He, J., & Huang, G. Q. (2018). Toward open manufacturing.

  • Ligus, R. (2005). ERP risk mitigation: An overview. Retrieved from https://csbweb01.uncw.edu/people/ivancevichd/classes/MSA%20516/Extra%20Readings%20on%20Topics/Database/ERP%20Risk%20Mitigation.pdf.

  • Lindman, J., Rossi, M., & Tuunainen, V. K. (2017). Opportunities and risks of Blockchain Technologies–a research agenda. Paper presented at the proceedings of the 50th Hawaii international conference on system sciences Hawaii.

  • Linn, L. A., & Koo, M. B. (2016). Blockchain for health data and its potential use in health it and health care related research. Paper presented at the ONC/NIST Use of Blockchain for healthcare and research workshop. Gaithersburg, Maryland, United States: ONC/NIST.

  • Lohmer, J., & Lasch, R. (2020). Blockchain in operations management and manufacturing: Potential and barriers. Computers Industrial Engineering, 149, 106789.

    Google Scholar 

  • Lyall, A., Mercier, P., & Gstettner, S. (2018). The death of supply chain management. Harvard Business Review, 15, 1–4.

    Google Scholar 

  • Lynall, M. D., Golden, B. R., & Hillman, A. J. (2003). Board composition from adolescence to maturity: A multitheoretic view. Academy of Management Review, 28(3), 416–431.

    Google Scholar 

  • MacDonald, T. J., Allen, D. W., & Potts, J. (2016). Blockchains and the boundaries of self-organized economies: Predictions for the future of banking. In Banking beyond banks and money (pp. 279–296). Springer.

  • Maiya, R. V. (2016). Benefit with Blockchain. Retrieved from http://www.infosysblogs.com/finacle/2016/08/benefit_with_blockchain.html.

  • Manski, S. (2017). Building the blockchain world: Technological commonwealth or just more of the same? Strategic Change, 26(5), 511–522. https://doi.org/10.1002/jsc.2151

    Article  Google Scholar 

  • Mirabelli, G., & Solina, V. (2020). Blockchain and agricultural supply chains traceability: Research trends and future challenges. Procedia Manufacturing, 42, 414–421.

    Google Scholar 

  • Miraz, M. H., & Ali, M. (2018). Applications of Blockchain technology beyond cryptocurrency. arXiv:1801.03528.

  • Mondal, T., & Gupta, S. (2017). HFS blueprint: Enterprise blockchain services. Retrieved from https://www.hfsresearch.com/blueprint-reports/hfs-blueprint-enterprise-blockchain-services.

  • Mori, T. (2016). Financial technology: Blockchain and securities settlement. Journal of Securities Operations & Custody, 8(3), 208–227.

    Google Scholar 

  • Moser, M. (2013). Anonymity of bitcoin transactions.

  • Murray, P. W., Agard, B., & Barajas, M. A. (2015). Forecasting supply chain demand by clustering customers. IFAC-PapersOnLine, 48(3), 1834–1839.

    Google Scholar 

  • Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic cash system.

  • O’Shields, R. (2017). Smart contracts: Legal agreements for the Blockchain. NC Banking Inst., 21, 177.

    Google Scholar 

  • Ølnes, S., Ubacht, J., & Janssen, M. (2017). Blockchain in government: Benefits and implications of distributed ledger technology for information sharing. Elsevier.

    Google Scholar 

  • Ordoobadi, S. M. (2008). Fuzzy logic and evaluation of advanced technologies. Industrial Management & Data Systems, 108, 928.

    Google Scholar 

  • Payne, G. T., Benson, G. S., & Finegold, D. L. (2009). Corporate board attributes, team effectiveness and financial performance. Journal of Management Studies, 46(4), 704–731.

    Google Scholar 

  • Pearce, J. A., II., & Patel, P. C. (2017). Board of director efficacy and firm performance variability. Long Range Planning, 51, 911–926.

    Google Scholar 

  • Peni, E. (2014). CEO and chairperson characteristics and firm performance. Journal of Management & Governance, 18(1), 185–205.

    Google Scholar 

  • Phan, H. (2016). Board of diretor education and firm performance: A dynamic approach.

  • Pilkington, M. (2017). Can Blockchain improve healthcare management? Consumer medical electronics and the IoMT.

  • Queiroz, M. M., Fosso Wamba, S., De Bourmont, M., & Telles, R. (2020). Blockchain adoption in operations and supply chain management: Empirical evidence from an emerging economy (pp. 1–17).

  • Ratanamahatana, C. A., & Keogh, E. (2004). Everything you know about dynamic time warping is wrong. Paper presented at the third workshop on mining temporal and sequential data.

  • Reid, F., & Harrigan, M. (2011). An analysis of anonymity in the bitcoin system. Paper presented at the Privacy, Security, Risk and Trust (PASSAT) and 2011 IEEE third inernational conference on Social Computing (SocialCom).

  • Rogers, E. (1962). Diffusion of innovations. Free Press.

    Google Scholar 

  • Rogers, E. M. (2003). Diffusion of innovations (p. 551). Free Press.

    Google Scholar 

  • Rosen, E. (2018). From furniture to cryptocurrency—Overstock is on a journey. Retrieved from https://www.nytimes.com/2018/06/27/business/dealbook/overstock-cryptocurrency-blockchain-evolution.html.

  • Rossignoli, F., Lionzo, A., & Buchetti, B. (2020). Beyond corporate governance reporting: The usefulness of information on board member profiles. Journal of Management and Governance, 25, 1–34.

    Google Scholar 

  • Saberi, S., Kouhizadeh, M., Sarkis, J., & Shen, L. (2019). Blockchain technology and its relationships to sustainable supply chain management. International Journal of Production Research, 57(7), 2117–2135.

    Google Scholar 

  • Sardá-Espinosa, A. (2017). Comparing time-series clustering algorithms in r using the dtwclust package. R Package Vignette, 12, 41.

    Google Scholar 

  • Savignac, F. (2008). Impact of financial constraints on innovation: What can be learned from a direct measure? Economics of Innovation and New Technology, 17(6), 553–569.

    Google Scholar 

  • Schmidt, C. G., & Wagner, S. M. (2019). Blockchain and supply chain relations: A transaction cost theory perspective. Journal of Purchasing and Supply Management, 25(4), 100552.

    Google Scholar 

  • Schneider, J. (2016). Goldman sachs equity research profiles in innovation. Blockchain Putting Theory into Practice.

  • Schuetz, S., & Venkatesh, V. (2020). Blockchain, adoption, and financial inclusion in India: Research opportunities. International Journal of Information Management, 52, 101936.

    Google Scholar 

  • Sebastian, S.-G., & Alina, B. (2013). Entrepreneurial activity in Romania–A time series clustering analysis at the nuts3 level. The Annals of the University of Oradea, 22, 673.

    Google Scholar 

  • Seebacher, S., & Schüritz, R. (2017). Blockchain technology as an enabler of service systems: A structured literature review (Vol. 279, pp. 12–23). https://doi.org/10.1007/978-3-319-56925-3_2.

  • Segarra, A., García-Quevedo, J., & Teruel, M. (2013). Financial constraints and the failure of innovation projects. Universitat Rovira i Virgili, wp, 06–2013.

  • Sharma, M., & Joshi, S. (2021). Barriers to blockchain adoption in health-care industry: An Indian perspective.

  • Sharma, R., & Mishra, R. (2014). A review of evolution of theories and models of technology adoption. Indore Management Journal, 6(2), 17–29.

    Google Scholar 

  • Sharma, Z. (2016). Board composition and innovation. Applied Finance Letters, 5(2).

  • Shen, L. (2016). Blockchain will be used by 15% of Big Banks by 2017.

  • Simonite, T. (2016). Web Pioneer Tries To Incubate A Second Digital Revolution. Retrieved from https://www.technologyreview.com/s/602731/web-pioneer-tries-to-incubate-a-second-digital-revolution/.

  • Swan, M. (2015). Blockchain: Blueprint for a new economy. O’Reilly Media, Inc.

    Google Scholar 

  • Tapscott, D., & Tapscott, A. (2016). Blockchain revolution: How the technology behind bitcoin is changing money, business, and the world. Penguin Press.

    Google Scholar 

  • Tiwari, A. K., Mohnen, P., Palm, F. C., & van der Loeff, S. S. (2008). Financial constraint and R&D investment: Evidence from CIS. In Determinants of innovative behaviour (pp. 217–242). Springer.

  • Trappey, C. V., Trappey, A. J., Chang, A.-C., & Huang, A. Y. (2010). Clustering analysis prioritization of automobile logistics services. Industrial Management & Data Systems, 110(5), 731–743.

    Google Scholar 

  • Tschorsch, F., & Scheuermann, B. (2016). Bitcoin and beyond: A technical survey on decentralized digital currencies. IEEE Communications Surveys & Tutorials, 18(3), 2084–2123.

    Google Scholar 

  • Venkatesh, V., & Morris, M. G. (2000). Why don’t men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quarterly, 24, 115–139.

    Google Scholar 

  • Viriyasitavat, W., Anuphaptrirong, T., & Hoonsopon, D. (2019). When blockchain meets Internet of Things: Characteristics, challenges, and business opportunities. Journal of Industrial Information Integration, 15, 21–28.

    Google Scholar 

  • Viriyasitavat, W., & Hoonsopon, D. (2019). Blockchain characteristics and consensus in modern business processes. Journal of Industrial Information Integration, 13, 32–39.

    Google Scholar 

  • Walport, M. (2016). Distributed ledger technology: Beyond blockchain. UK Government Office for Science.

  • Wang, H., Chen, K., & Xu, D. (2016). A maturity model for blockchain adoption. Financial Innovation, 2(1), 12.

    Google Scholar 

  • Wang, Q., Zhu, X., Ni, Y., Gu, L., & Zhu, H. (2020). Blockchain for the IoT and industrial IoT: A review. Internet of Things, 10, 100081.

    Google Scholar 

  • Wong, L.-W., Tan, G.W.-H., Lee, V.-H., Ooi, K.-B., & Sohal, A. (2020). Unearthing the determinants of Blockchain adoption in supply chain management. International Journal of Production Research, 58(7), 2100–2123.

    Google Scholar 

  • Wüst, K., & Gervais, A. (2017). Do you need a Blockchain? IACR Cryptology ePrint Archive, 2017, 375.

    Google Scholar 

  • Xu, J. J. (2016). Are blockchains immune to all malicious attacks? Financial Innovation. https://doi.org/10.1186/s40854-016-0046-5

    Article  Google Scholar 

  • Yli-Huumo, J., Ko, D., Choi, S., Park, S., & Smolander, K. (2016). Where is current research on blockchain technology?-A systematic review. PLoS ONE, 11(10), e0163477. https://doi.org/10.1371/journal.pone.0163477

    Article  Google Scholar 

  • Yue, X., Wang, H., Jin, D., Li, M., & Jiang, W. (2016). Healthcare data gateways: Found healthcare intelligence on blockchain with novel privacy risk control. Journal of Medical Systems, 40(10), 218. https://doi.org/10.1007/s10916-016-0574-6

    Article  Google Scholar 

  • Zhang, J., Xue, N., & Huang, X. (2016). A secure system for pervasive social network-based healthcare. IEEE Access, 4, 9239–9250.

    Google Scholar 

  • Zhang, K., & Jacobsen, H. (2018). Towards dependable, scalable, and pervasive distributed ledgers with Blockchains. Paper presented at the IEEE 38th International Conference on Distributed Computing Systems (ICDCS).

  • Zhao, J. L., Fan, S., & Yan, J. (2016). Overview of business innovations and research opportunities in blockchain and introduction to the special issue. Financial Innovation. https://doi.org/10.1186/s40854-016-0049-2

    Article  Google Scholar 

  • Zheng, K., Zhang, Z., & Gauthier, J. (2020). Blockchain-based intelligent contract for factoring business in supply chains. Annals of Operations Research, 1–21.

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Authors and Affiliations

  1. Department of Systems and Technology, Harbert College of Business, Auburn University, Auburn, AL, 36849, USA

    Alireza Farnoush, Ashish Gupta, David Paradice & Shashank Rao

  2. Graduate School of Management, Clark University, Worcester, MA, 01610, USA

    Hamidreza Ahady Dolarsara

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  1. Alireza Farnoush
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Appendix: Company demographics

Appendix: Company demographics

We explored the pool of companies that had their time series data available for the multi variable clustering in this study. Table 7 summarizes the composition of the 704 companies based on the Standard Industrial Classification (SIC) categorization. The top four categories are represented by companies from construction, manufacturing, retail, and finance. However, among the companies that intend to adopt Blockchain, the top industries belong to retail trade, and finance. These are followed by construction, manufacturing, and wholesale (Figs. 2, 3).

Fig. 2
figure 2

Industry classification of all the companies

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Fig. 3
figure 3

Industry classification of the companies that intend to adopt blockchain

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Table 7 Industry classification of the companies
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Farnoush, A., Gupta, A., Dolarsara, H.A. et al. Going beyond intent to adopt Blockchain: an analytics approach to understand board member and financial health characteristics. Ann Oper Res 308, 93–123 (2022). https://doi.org/10.1007/s10479-021-04113-0

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