Social Network Evolution: The Case of UK Companies Before and After Brexit

Edward Edward, Amjad Fayoumi, Azar Shahgholian, Achmad Hidayanto

Abstract


The Brexit referendum has impacted both the UK and the EU economies in several ways. The uncertainty around Brexit highlighted the importance of a relationships network between directors of companies to access information and resources that are necessary for optimal decision making. It is difficult to develop informed business and economy policies without a deep understanding of the magnitude of Brexit on business-to-business relationships with EU-based firms. This study aims to analyze the impact of the passage of the Brexit referendum on the evolution of board interlock networks. The study uses network analysis to measure the evolution of UK-EU directors’ relationships over the Brexit period, predominantly between the 2010 and 2020 period. The study models the structural changes in dynamic networks by converting this evolving network into static graphs on yearly basis. The analysis indicates that links formation in the UK is affected negatively by the Brexit referendum. It also has a negative impact on forming a new link with potential companies’ directors in the EU, but it shows a rising tendency for shared affiliation bias analysis. Interestingly, the contradicted trend in 2007, the number of directors’ connection in consumer service and food & drug sectors was decreasing in the UK while rocketing in the EU.

 

Doi: 10.28991/ESJ-2022-06-01-01

Full Text: PDF


Keywords


Brexit; Companies Relationship Network; Social Network Evolution; Dynamic Social Network.

References


Tetlow, G., & Stojanovic, A. (2018). Understanding the economic impact of Brexit. Institute for government, 2-76.

Dhingra, S., Ottaviano, G., Sampson, T., & Van Reenen, J. (2016). The impact of Brexit on foreign investment in the UK. BREXIT 2016, 24(2), 1-10.

Fan, Y., Stevenson, M., & Li, F. (2020). Supplier-initiating risk management behaviour and supply-side resilience: the effects of interpersonal relationships and dependence asymmetry in buyer-supplier relationships. International Journal of Operations and Production Management, 40(7–8), 971–995. doi:10.1108/IJOPM-06-2019-0497.

Mills, C. W., & Wolfe, A. (2000). The Power Elite (Vol. 20). Oxford University Press.

Palmer, D., Friedland, R., & Singh, J. V. (1986). The Ties That Bind: Organizational and Class Bases of Stability in a Corporate Interlock Network. American Sociological Review, 51(6), 781. doi:10.2307/2095367.

Withers, M., Youn (Rose) Kim, J., & Howard, M. (2018). The evolution of the board interlock network following Sarbanes-Oxley. Social Networks, 52, 56–67. doi:10.1016/j.socnet.2017.05.005.

Davis, G. F. (1991). Agents without Principles? The Spread of the Poison Pill through the Intercorporate Network. Administrative Science Quarterly, 36(4), 583. doi:10.2307/2393275.

Haunschild, P. R. (1994). How Much is That Company Worth?: Interorganizational Relationships, Uncertainty, and Acquisition Premiums. Administrative Science Quarterly, 39(3), 391. doi:10.2307/2393296.

Haunschild, P. R., & Beckman, C. M. (1998). When do interlocks matter?: Alternate sources of information and interlock influence. Administrative Science Quarterly, 43(4), 815–844. doi:10.2307/2393617.

Hernandez, E., Sanders, W. G., & Tuschke, A. (2015). Network defense: Pruning, grafting, and closing to prevent leakage of strategic knowledge to rivals. Academy of Management Journal, 58(4), 1233–1260. doi:10.5465/amj.2012.0773.

Lang, J. R., & Lockhart, D. E. (1990). Increased Environmental Uncertainty and Changes in Board Linkage Patterns. Academy of Management Journal, 33(1), 106–128. doi:10.5465/256354.

Basadur, M., Graen, G. B., & Green, S. G. (1982). Training in creative problem solving: Effects on ideation and problem finding and solving in an industrial research organization. Organizational Behavior and Human Performance, 30(1), 41–70. doi:10.1016/0030-5073(82)90233-1.

Marsden, P. V. (1990). Network Data and Measurement. In: Annual Review of Sociology, 16, 1990, S. 435-463. Annual Review of Sociology, 435–463,.

Farine, D. R. (2018). When to choose dynamic vs. static social network analysis. Journal of Animal Ecology, 87(1), 128–138. doi:10.1111/1365-2656.12764.

Shahgholian, A., Theodoulidis, B., & Bansal, U. (2012). Social network evolution: A case study of UK directors. Proceedings - 2012 3rd International Conference on Services in Emerging Markets, ICSEM 2012, 107–114. doi:10.1109/ICSEM.2012.22.

Kossinets, G., & Watts, D. J. (2006). Empirical analysis of an evolving social network. Science, 311(5757), 88–90. doi:10.1126/science.1116869.

Bloom, N., Bunn, P., Chen, S., Mizen, P., Smietanka, P., & Thwaites, G. (2019). The Impact of Brexit on UK Firms. doi:10.3386/w26218.

Kee, H. L., & Nicita, A. (2017). Short-Term Impact of Brexit on the United Kingdom’s Export of Goods. Short-Term Impact of Brexit on the United Kingdom’s Export of Goods. doi:10.1596/1813-9450-8195.

Ramiah, V., Pham, H. N. A., & Moosa, I. (2017). The sectoral effects of Brexit on the British economy: early evidence from the reaction of the stock market. Applied Economics, 49(26), 2508–2514. doi:10.1080/00036846.2016.1240352.

Davis, G. F., Yoo, M., & Baker, W. E. (2003). The Small World of the American Corporate Elite, 1982-2001. Strategic Organization, 1(3), 301–326. doi:10.1177/14761270030013002.

Martin, G., Gözübüyük, R., & Becerra, M. (2015). Interlocks and firm performance: The role of uncertainty in the directorate interlock-performance relationship. Strategic Management Journal, 36(2), 235–253. doi:10.1002/smj.2216.

G. S. Becker, (2009). Human capital: A theoretical and empirical analysis, with special reference to education. University of Chicago Press.

Hillman, A. J. (2005). Politicians on the board of directors: Do connections affect the bottom line? Journal of Management, 31(3), 464–481. doi:10.1177/0149206304272187.

Pfeffer, J., & Salancik, G. R. (2003). The external control of organizations: A resource dependence perspective. Stanford University Press.

Coleman, J. S. (2009). Social capital in the creation of human capital. Knowledge and Social Capital, 94, 17–42. doi:10.1086/228943.

Lin, N. (1999). Social networks and status attainment. Annual Review of Sociology, 25(1), 467–487. doi:10.1146/annurev.soc.25.1.467.

Mizruchi, M. S. (1996). What do interlocks do? An Analysis, Critique, and Assessment of Research on Interlocking Directorates. Annual Review of Sociology, 22(1), 271–298. doi:10.1146/annurev.soc.22.1.271.

Deloitte. "Leaving the E.U.: What will it mean for banking and the financial services industry?" Available online: https://www2.deloitte.com/content/dam/Deloitte/cy/Documents/financial-services/CY_FinancialServices_Brexit_Noexp.pdf (accessed on August 2020).

Persico, V., Pescapé, A., Picariello, A., & Sperlí, G. (2018). Benchmarking big data architectures for social networks data processing using public cloud platforms. Future Generation Computer Systems, 89, 98–109. doi:10.1016/j.future.2018.05.068.

Bourigault, S., Lamprier, S., & Gallinari, P. (2016). Representation learning for information diffusion through social networks: An embedded cascade model. WSDM 2016 - Proceedings of the 9th ACM International Conference on Web Search and Data Mining, 573–582. doi:10.1145/2835776.2835817.

Kim, J., & Mohaisen, A. (2017). Distributed and reliable decision-making for cloud-enabled mobile service platforms. International Journal of Distributed Sensor Networks, 13(8), 1–9. doi:10.1177/1550147717726509.

Jheng, G. Y., Chen, Y. C., & Liang, H. M. (2021). Evolution pattern mining on dynamic social network. Journal of Supercomputing, 77(7), 6979–6991. doi:10.1007/s11227-020-03534-1.

Alberti, F. G., Belfanti, F., & Giusti, J. D. (2021). Knowledge exchange and innovation in clusters: a dynamic social network analysis. Industry and Innovation, 28(7), 880–901. doi:10.1080/13662716.2021.1904840.

Song, H. J., Lee, S., & Kang, K. H. (2021). The influence of board interlocks on firm performance: In the context of geographic diversification in the restaurant industry. Tourism Management, 83, 104238. doi:10.1016/j.tourman.2020.104238.

Lu, J., Yu, D., Mahmoudian, F., Nazari, J. A., & Herremans, I. M. (2021). Board interlocks and greenhouse gas emissions. Business Strategy and the Environment, 30(1), 92–108. doi:10.1002/bse.2611.

Li, M. (2021). Exploring novel technologies through board interlocks: Spillover vs. broad exploration. Research Policy, 50(9), 104337. doi:10.1016/j.respol.2021.104337.

Valeeva, D., Heemskerk, E. M., & Takes, F. W. (2020). The duality of firms and directors in board interlock networks: A relational event modeling approach. Social Networks, 62, 68–79. doi:10.1016/j.socnet.2020.02.009.

Zona, F., Gomez-Mejia, L. R., & Withers, M. C. (2018). Board Interlocks and Firm Performance: Toward a Combined Agency–Resource Dependence Perspective. Journal of Management, 44(2), 589–618. doi:10.1177/0149206315579512.

Kurt, Y., & Kurt, M. (2020). Social network analysis in international business research: An assessment of the current state of play and future research directions. International Business Review, 29(2), 101633. doi:10.1016/j.ibusrev.2019.101633.


Full Text: PDF

DOI: 10.28991/ESJ-2022-06-01-01

Refbacks

  • There are currently no refbacks.


Copyright (c) 2022 Edward Edward, Amjad Fayoumi, Azar Shahgholian, Achmad Nizar Hidayanto