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Exploring the Relationship Between Blockchain Technology and Corporate Social Responsibility Performance: Empirical Evidence from European Firms

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Abstract

This study analyzes the importance role of blockchain technology to explain the corporate social responsibility performance and additionally the moderating impact of firm life cycle stages on that association. This research based on a sample of 297 European companies listed in the STOXX Europe 600 during 2014–2018 periods; our feasible generalized least squares (FGLS) results show that implemented blockchain technology significantly and positively affects the corporate social responsibility performance enterprises. In addition, this association is in mature life cycle stages. Our results are robust to alternative proxy measures of corporate social responsibility performance and life cycle stages. Our findings extend the literature on the use of BT and the economic consequences engaging in certain types of CSR activity. This study offers a new and integrated theoretical framework to examine the interplay role of BT to explain CSR performance.

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References

  • Aguinis, C. C. (2011). Corporate social responsibility and petroleum development in sub-Saharan Africa: the case of Chad. Resources Policy, 37, 144–151.

  • Aitzhan, N. Z., & Svetinovic, D. (2018). Security and privacy in decentralized energy trading through multi-signatures, blockchain and anonymous messaging streams. IEEE Transactions on Dependable and Secure Computing, 15(5), 840–852.

  • Anthony, J., & Ramesh, K. (1992). Association between accounting performance measures and stock prices: a test of the life cycle hypothesis. Journal of Accounting and Economics, 15(2–3), 203–227.

    Article  Google Scholar 

  • Baumgartner, R. J., & Rauter, R. (2017). Strategic perspectives of corporate sustainability management to develop a sustainable organization. Journal of Clean Production, 140, 81–92.

  • Besharov, M. L., & Smith, W. K. (2014). Multiple logics in organizations: Explaining their varied nature and implications. Academy of Management Review, 39(3), 364–381.

    Article  Google Scholar 

  • Black, E. (1998). Life-cycle impacts on the incremental value-relevance of earnings and cash flow measures. Journal of Financial Statement Analysis, 4, 40–57.

    Google Scholar 

  • Caro, M. P., Ali, M. S., Vecchio, M., & Giaffreda, R. (2018). Blockchain-based traceability inagri-food supply chain management: a practical implementation. Vertical and Topical Summit on Agriculture-Tuscany (IOT Tuscany), 1–4.

  • Castiaux, A. (2009). Responsabilité d’entreprise et innovation: Entre exploration et exploitation. Reflets Et Perspectives De La Vie Économique, 48, 37–49.

    Google Scholar 

  • Chae, H.-C., Koh, C. E., & Park, K. O. (2018). Information technology capability and firm performance: role of industry. Information Management, 55.

  • Chai, S. M., & Kim, M. (2010). What makes bloggers share knowledge? An investigation on the role of trust. International Journal of Information Management, 30(5), 408–415.

    Article  Google Scholar 

  • Chan, H.-L., Wei, X., Guo, S., & Leung, W.-H. (2020). Corporate social responsibility (CSR) in fashion supply chains: a multi-methodological study. Transportation Research Part E: Logistics and Transportation Review, 142. October (2020).

  • Chi, M. M., Wang, W. J., Lu, X. Y., & George, J. F. (2018). Antecedents and outcomes of collaborative innovation capabilities on the platform collaboration environment. International Journal of Information Management, 43, 273–283.

  • Coakes, S. J., Steed, L., & Ong, C. (2010). SPSS: Analysis without anguish: Version 17 for Windows. John Wiley and Sons.

    Google Scholar 

  • Crainic, T. G., Perboli, G., & Rosano, M. (2018). Simulation of intermodal freight transportation systems: A taxonomy. European Journal of Operational Research, 270(2), 401–418. https://doi.org/10.1016/j.ejor.2017.11.061

    Article  Google Scholar 

  • DeAngelo, H., DeAngelo, L., & Stulz, R. M. (2006). Dividend policy and the earned/ contributed capital mix: A test of the life-cycle theory. Journal of Financial Economics, 81, 227–254.

    Article  Google Scholar 

  • Dinh, T. T. A., Liu, R., Zhang, M. H., Chen, G., Beng, C. O., & Wang, J. (2018). Untangling blockchain: A data processing view of blockchain systems. IEEE Transactions on Knowledge and Data Engineering, 30(7), 1366–1385.

    Article  Google Scholar 

  • Fernandez-Carames, T. M., & Fraga-Lamas, P. (2018). A review on the use of blockchain for the internet of things. IEEE Access, 6, 32979–33001.

    Article  Google Scholar 

  • Figorilli, S., Antonucci, F., Costa, C., Pallottino, F., Raso, L., & Castiglione, M. (2018). A blockchain implementation prototype for the electronic open source traceability of wood along the whole supply chain. Sensors, 18(9).

  • Funk, E., Riddell, J., Ankel, F., & Cabrera, D. (2018). Blockchain technology: A data framework to improve validity, trust, and accountability of information exchange in health professions education. Academic Medicine, 93(12), 1791–1794.

    Article  Google Scholar 

  • Gan, L. N., Wei, P. Z., Wang, J. Q., & Zheng, X. S. (2018). The effect of cash flow on the capital structure dynamic adjustment: Evidence from Chinese listed companies. Transformations in Business & Economics, 17(1), 45.

    Google Scholar 

  • Gartner. (2016). Gartner’s 2016 hype cycle for emerging technologies identifies three key trends that organizations must track to gain competitive advantage. Gartner. http://www.gartner.com/newsroom/id/3412017. Accessed 10 January 2017.

  • Greiner, L. M. (2013). Evolution and revolution as organizations grow. Harvard BusinessReview: Boston, MA, USA, July–August 1972. 37–46. 10.

  • Gujarati, D. (2011). Econometric by example. Palgrave Macmillan.

    Google Scholar 

  • Gunasekaran, A., Subramanian, N., & Papadppoulos, T. (2017). Information technology for competitive advantage within logistics and supply chain: A review. Transpiration Research Part E: Logistics and Transpiration Review, 99, 14–33.

    Article  Google Scholar 

  • Gürkaynak, G., Yılmaz, İ, Yeşilaltay, B., & Bengi, B. (2018). Intellectual property law and practice in the blockchain realm. Computer Law & Security Review, 34, 847–862.

    Article  Google Scholar 

  • Hair, J., Black, W., Babin, B., Anderson, R., & Tatham, R. (2006). Multivariate data analysis. (6th ed.). Pearson Prentice Hall, Upper Saddle River, NJ.

  • Helfat, C. E., & Martin, J. A. (2015). Dynamic managerial capabilities: Review and assessment of managerial impact on strategic. Journal of Management, 41(5), 1281–1312. https://doi.org/10.1177/0149206314561301

    Article  Google Scholar 

  • Helfat, C. E., & Peteraf, M. A. (2003). The dynamic resource-based view: Capabilities lifecycles. Strategic Management Journal, 24, 997–1010.

    Article  Google Scholar 

  • Interlogica. (2017). The socio-economic effects of the blockchain. Interlogica. http://www.interlogica.it/en/insight/blockchain-socio-economic-effects/. Accessed 18 April 2017.

  • Jantunen, A., Tarkiainen, A., Chari, S., & Oghazi, P. (2018). Dynamic capabilities, operational changes, and performance outcomes in the media industry. Journal of Business Research, 89, 251–257.

    Article  Google Scholar 

  • Kim, S. K., & Huh, J. H. (2018). A study on the improvement of smart grid security performance and blockchain smart grid perspective. Energies, 11(8).

  • Kirat, M. (2015). Review Corporate social responsibility in the oil and gas industry in Qatar perceptions and practices. Public Relations Review.

  • Kshetri, N. (2018). Blockchain’s roles in meeting key supply chain management objectives. International Journal of Information Management, 39, 80–89.

    Article  Google Scholar 

  • Lacity, M. C. (2018). Enterprise blockchains: eight sources of business value and the obstacles in their way. Retrieved from https://walton.uark.edu/enterprise/downloads/blockchain/LacityBlockchainsExplained.pdf. Accessed 1 February 2018.

  • Leng, K., Bi, Y., Jing, L., Fu, H.-C., & Van Nieuwenhuyse, I. (2018). Research on agricultural supply chain system with double chain architecture based on Blockchain technology. Future Generation Computer Systems, 86, 641–649

  • Liu, S., Felix, T. S., Yang, J. N., & Niu, B. (2018). Understanding the effect of cloud computing on organizational agility: An empirical examination. International Journal of Information Management, 43, 98–111.

    Article  Google Scholar 

  • Lu, C., Rong, K., & You, J. X. (2014). Business ecosystem and stakeholders’ role transformation: Evidence from Chinese emerging electric vehicle industry. Expert Systems with Applications, 41(10), 4579–4595.

    Article  Google Scholar 

  • McWilliams, A., & Siegel, D. (2001). Corporate social responsibility: A theory of the firm perspective. Academy of Management Review, 26, 117–127.

    Article  Google Scholar 

  • Mendling, J., Weber, I., Aalst, W., Brocke, J., Cabanillas, C., Daniel, F., Debois, S., Ciccio, C. D., Dumas, M., Dustdar, S., Al, A., García-Bañuelos, L., Governatori, G., Hull, R., La Rosa, M., Leopold, H., Leymann, F., Recker, J., Reichert, M., Reijers, H. A., Rinderle-Ma, S., Solti, A., Rosemann, M., Schulte, S., Singh, M. P., Slaats, T., Staples, M., Weber, B., Weidlich, M., Weske, M., Xu, X., & Zhu, L. (2018). Blockchains for business process management - challenges and opportunities. ACM Transactions on Management Information Systems (TMIS), 9(0), 17.

  • Miller, D., & Friesen, P. H. (1984). A longitudinal study of the corporate life cycle. Management Science, 30, 1161–1183.

  • Nakasumi, M. (2017). Information sharing for supply chain management based on blockchain technology. 2017 IEEE 19th conference on business informatics, 1, 140–149.

  • Namagembe, S., Ryan, S., & Sridharan, R. (2018). Green supply chain practice adoption and firm performance: manufacturing SMEs in Uganda. Management of Environmental Quality: An international Journal, 30(1).

  • Nelson, K. M., & Cooprider, J. G. (1996). The contribution of shared knowledge to IS group performance. MIS Quarterly, 20(4), 409–432.

    Article  Google Scholar 

  • Pallant, J. (2001). SPSS Survival Manual. Open University Press.

    Google Scholar 

  • Pan, X. F., Zhang, J., & Song, M. L. (2019). Innovation resources integration pattern in high-tech entrepreneurial enterprises. International Entrepreneurship and Management Journal, 14(1), 51–66.

    Article  Google Scholar 

  • Perboli, G., Musso, S., & Rosano, M. (2018). Blockchain in logistics and supply chain: A lean approach for designing real-world use cases. IEEE Access, 6, 62018–62028.

    Article  Google Scholar 

  • Queiroz, M. M., Telles, R., & Bonilla, S. H. (2019). Blockchain and supply chain management integration: A systematic review of the literature. Supply Chain Management: An International Journal. https://doi.org/10.1108/SCM-03-2018-0143(inpress)

    Article  Google Scholar 

  • Quinn, R. E., & Cameron, K. (1983). Organizational life cycles and shifting criteria of effectiveness: some preliminary evidence. Management Science, 29, 33–51.

  • Simen, S. F., & Ndao, A. (2013). L’effet de la mise en place d’une stratégie de Responsabilité Sociale de l’entreprise sur la culture organisationnelle: Analyse, implications et enjeux pour le Sénégal. Revue Congolaise De Gestion, 17, 131–170.

    Article  Google Scholar 

  • Van der Elst, C., & Lafarre, A. (2017). Bringing the AGM to the 21st century: blockchain and smart contracting tech for shareholder involvement. European Corporate Governance Institute (ECGI) - Law Working Paper No. 358/2017 25.

  • Scott, A. J. (1971). Dynamic location-allocation systems: some basic planning strategies. Environment and Planning, 3, 73–82.

    Article  Google Scholar 

  • Song, M. L., Pan, X. F., Pan, X. Y., & Jiao, Z. M. (2018). Influence of basis research investment on corporate performance: Exploring the moderating effect of human capital structure. Management Decision. https://doi.org/10.1108/MD-06-2018-0708

    Article  Google Scholar 

  • Tobin, J. (1958). Estimation of relationships for limited dependent variables. Econometrica, 26, 24–36.

    Article  Google Scholar 

  • Treleaven, P., Brown, R. G., & Yang, D. (2017). Blockchain technology in finance. Computer, 50(9), 14–17.

    Article  Google Scholar 

  • Wamba, S. F., Angappa, G., Papadopoulos, T., & Eric, N. (2018a). Big data analytics in supply chain and logistics: An empirical approach. The International Journal of Logistics Management, 29(2).

  • Wamba, S. F., Kamdjoug, J. R. K., Bawack, R., & Keogh, J. G. (2018b). Bitcoin, blockchain, and fintech: A systematic review and case studies in the supply chain. Production Planning and Control, 6, 54.

    Google Scholar 

  • Wang, Y., Singgih, M., Wang, J., & Rit, M. (2019). Making sense of blockchain technology: How will it transform supply chains? International Journal of Production Economics, 211, 221–236.

    Article  Google Scholar 

  • Weber, I., Xu, X., Riveret, R., Guido, G., Alexander, P., & Jan, M. (2016). Untrusted business process monitoring and execution using blockchain. Lecture Notes in Computer Science, 9850, 329–347.

    Article  Google Scholar 

  • Woo, C., Kim, M. G., & Chung, Y. H. (2016). Supplier’s communication capability and external green integration for green and financial performance in Korean construction industry. Journal of Cleaner Production, 112, 483–493.

    Article  Google Scholar 

  • Xue, L. (2017). Governance–knowledge fit and strategic risk taking in supply chain digitization.

  • Yermack, D. (2015). Deductio Ad Absurdum: CEOs donating their own stock to their own family foundations. Journal of Financial Economics, 94, 107–123.

    Article  Google Scholar 

  • Ying, W. C., Jia, S. L., & Du, W. Y. (2018). Digital enablement of blockchain: Evidence from HNA group. International Journal of Information Management, 39(4), 1–4.

    Article  Google Scholar 

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Correspondence to Ferdaws Ezzi.

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This article is part of the Topical Collection on Enhancing the Adaptability of Family Businesses to the Knowledge-based Economy

Appendix. Variable Definitions and Measurement

Appendix. Variable Definitions and Measurement

Variables

Definition and measurement

Dependent variable

CSR

The annual corporate social responsibility performance. We use the database Datastream to compute CSR performance (derive from Thomson Reuters business-ASSET 4)

HR

Human rights: The society/human rights category measures a company’s management commitment and effectiveness toward respecting the fundamental human rights conventions. It reflects a company’s capacity to maintain its license to operate by guaranteeing the freedom of association and excluding child, forced, or compulsory labor

EQ

Employment quality: The employment quality category measures a company’s management commitment and effectiveness toward providing high-quality employment benefits and job conditions. It reflects a company’s capacity to increase its workforce loyalty and productivity by distributing rewarding and fair employment benefits, and by focusing on long-term employment growth and stability by promoting from within, avoiding lay-offs, and maintaining relations with trade unions

CO

Community: The society/community category measures a company’s management commitment and effectiveness toward maintaining the company’s reputation within the general community (local, national, and global). It reflects a company’s capacity to maintain its license to operate by being a good citizen (donations of cash, goods, or staff time), protecting public health (avoidance of industrial accidents), and respecting business ethics (avoiding bribery and corruption)

DIV

Diversity: The diversity category measures a company’s management commitment and effectiveness toward maintaining diversity and equal opportunities in its workforce. It reflects a company’s capacity to increase its workforce loyalty and productivity by promoting an effective life-work balance, a family-friendly environment, and equal opportunities regardless of gender, age, ethnicity, religion, or sexual orientation

CP

Customer practices: The customer/product responsibility category measures a company’s management commitment and effectiveness toward creating value-added products and services upholding the customer’s security. It reflects a company’s capacity to maintain its license to operate by producing quality goods and services integrating the customer’s health and safety and preserving its integrity and privacy also through accurate product information and labeling

HS

Health and safety: The workforce/health and safety category measures a company’s management commitment and effectiveness toward providing a healthy and safe workplace. It reflects a company’s capacity to increase its workforce loyalty and productivity by integrating into its day-to-day operations a concern for the physical and mental health, well-being, and stress level of all employees

EN

Environment: The environmental pillar measures a company’s impact on living and non-living natural systems, including the air, land, and water, as well as complete ecosystems. It reflects how well a company uses best management practices to avoid environmental risks and capitalize on environmental opportunities in order to generate long-term shareholder value

TD

Training & Develop: The workforce/training and development category measures a company’s management commitment and effectiveness toward providing training and development (education) for its workforce. It reflects a company’s capacity to increase its intellectual capital, workforce loyalty, and productivity by developing the workforce’s skills, competences, employability, and careers in an entrepreneurial environment

Independent variables

BT

Blockchain technology: BTit is a 0–1 categorical variable; the first 2 years, the previous year, the current year, and the following year of the implementation of the BT are the years related to the implementation, where the BTit value is 1 and the BTit value of the other years is 0 year is different

Asset

Assets represents enterprise’s total asset size

Sales

Sales represents enterprise’s sales revenue scale

Staff

Staff represents enterprise’s employee size

R&D

Research and development (R&D) intensity, R&D = R&D expenditure divided by total growth, maturity, and decline which are corporate life-cycle stage dummy values equal to 1 if a firm belongs to the growth, maturity, or decline stage, respectively

Life cycle

Life cycle = DeAngelo et al. (2006)’s life cycle model measured as retained earnings scaled over total assets (RE/TA) or retained earnings scaled over total equity (RE/TE)

GR, MA, and DE

Growth, maturity, and decline are corporate life-cycle stage dummy values equal to 1 if a firm belongs to the growth, maturity, or decline stage, respectively

Leverage

Leverage (LEV), measured as short-term and long-term debt divided by total assets, controls for the level of a firm’s indebtedness

Year

Year dummy variable to control for year effects

IND

Industry sector (IND) dummy variables defined by the two-digit Global Industry Classification Standard (GICS) codes to control for industry effects

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Ezzi, F., Jarboui, A. & Mouakhar, K. Exploring the Relationship Between Blockchain Technology and Corporate Social Responsibility Performance: Empirical Evidence from European Firms. J Knowl Econ 14, 1227–1248 (2023). https://doi.org/10.1007/s13132-022-00946-7

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