Abstract
Unparalleled advances in information technology have resulted in the virtualization of the workplace, as well as in a surge in non-traditional work arrangements based on short-term contracts (“gigs”). Work that is done remotely through online platforms may be hidden by technology. Thus, how could we possibly access information about the social network of workers? What are the business and social values hidden in workers’ underlying informal social networks? Here, we propose applying methods from complex network analysis to have an overview of data from a Brazilian food-delivery company. We present the steps used to make the inference of a social network that relates delivery men according to their co-location patterns. Hence, the obtained network offers a valuable framework to explore, in the future, questions related to the role of informal social networks in the spreading of innovations and the coordination of behaviors and business strategies.
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References
Bakuła, M.; Uradziński, M.; Krasuski, K.: Performance of DGPS smartphone positioning with the use of P(L1) versus P(L5) pseudorange measurements. Remote Sens, 14, 929 (2019). https://doi.org/10.3390/rs14040929
Candia, C., Encarnação, S., Pinheiro, F.L.: The higher education space: connecting degree programs from individuals choices. EPJ Data Sci. 8(39) (2019). https://doi.org/10.1140/epjds/s13688-019-0218-4
Das, K., Samanta, S., Pal, M.: Study on centrality measures in social networks: a survey. Soc. Netw. Anal. Min. 8(13) (2018). https://doi.org/10.1007/s13278-018-0493-2
Epskamp, S., Borsboom, D., Fried, E.I.: Estimating psychological networks and their accuracy: a tutorial paper. Behav. Res. 50, 195-212 (2018). https://doi.org/10.3758/s13428-017-0862-1
Huang, K., Yao, J., Yin, M.: Understanding the skill provision in gig economy from a network perspective: a case study of fiverr. Proc. ACM Human-Comput. Interact. 3(CSCW), 1-23 (2019)
Jabagi, N., Audebrand, L.K., Croteau, A.-M., Marsan, J. (2018). Connecting with Gig-workers: an organizational identification perspective. In: Proceedings of the European Group of Organization Studies (EGOS) 34th Colloquium
Jacobs, A.Z., Watts, D.J.: A large-scale comparative study of informal social networks in firms. Manag. Sci. 67(9), 5489–5509 (2021)
Kalgotra, P., Sharda, R., Luse, A.: Which similarity measure to use in network analysis: impact of sample size on phi correlation coefficient and Ochiai index. Int. J. Inf. Manage. 55 (2020). https://doi.org/10.1016/j.ijinfomgt.2020.102229
Kinder, E., Jarrahi, M.H., Sutherland, W.: Gig platforms, tensions, alliances and ecosystems: an actor-network perspective. Proc. ACM Human-Comput. Interact. 3(CSCW), 1-26 (2019)
Reagans, R., McEvily, B.: Network structure and knowledge transfer: the effects of cohesion and range. Adm. Sci. Q. 48(2), 240–267 (2003)
Ronen, S., Gonçalves, B., Hu, K.Z., Vespignani, A., Pinker, S., Hidalgo, C.A.: Links that speak: the global language network and its association with global fame. Proc. Nat. Acad. Sci. U.S.A. 111(52), E5616–E5622 (2014)
Wagner, C.J., González-Howard, M.: Studying discourse as social interaction: the potential of social network analysis for discourse studies. Educ. Res. 47(6), 375–383 (2018)
Wang, J., Suri, S., Watts, D.J.: Cooperation and assortativity with dynamic partner updating. Proc. Nat. Acad. Sci. 109(36), 14363–14368 (2012)
Watts, D.J., Strogatz, S.H.: Collective dynamics of small-world networks. Nature 393(6684), 440–442 (1998)
Xulvi-Brunet, R., Sokolov, I.M.: Changing correlations in networks: assortativity and dissortativity. Acta. Phys. Pol. B 36(5), 1431–1455 (2005)
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Pilatti, G., Pinheiro, F.L., Montini, A. (2023). Gig Economy and Social Network Analysis: Topology of Inferred Network. In: Cherifi, H., Mantegna, R.N., Rocha, L.M., Cherifi, C., Micciche, S. (eds) Complex Networks and Their Applications XI. COMPLEX NETWORKS 2016 2022. Studies in Computational Intelligence, vol 1078. Springer, Cham. https://doi.org/10.1007/978-3-031-21131-7_37
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DOI: https://doi.org/10.1007/978-3-031-21131-7_37
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