Because of the temporal, spatial, and functional dimensions in distributed organizations, members’ cognitive processes play an important role in executing tasks. Coordination is necessary for successfully finishing tasks in distributed organizations. Meanwhile, interdependence between sub-units is an intrinsic property of distributed organizations. We put forward an interdependent network model and applied simulation experiments to study the collective efficacy evolution of distributed organizations based on the theory of planned behavior. Experiment results show several insights for distributed organizations operation: (1) organizational size has an impact on collective efficacy evolution, and a size that is too small or too large is not helpful; (2) task payoff and task cost affect collective efficacy evolution only slightly, while task difficulty has considerable effect on collective efficacy evolution and distribution; (3) coordinating willingness affects interdependent network structure of distributed organizations, and further influences collective efficacy evolution and distribution; (4) a slightly interdependent weight difference between sub-units can benefit collective efficacy evolution and enhance members’ collective efficacy; (5) imbalance in the size of sub-units decreases the collective efficacy.
BosNShamiNSOlsonJS. In-group/out-group effects in distributed teams: an experimental simulation. In: Proceedings of the 2004 ACM conference on computer-supported cooperative work. ACM, 2004.
2.
CelikNXiHXuD. Simulation-based workforce assignment considering position in a social network. Simulation2012; 88: 72–96.
3.
CummingsJN. Work groups, structural diversity, and knowledge sharing in a global organization. Manage Sci2004; 50: 352–364.
4.
EspinosaJACummingsJNPickeringC. Time separation, coordination, and performance in technical teams. IEEE Trans Eng Manage2012; 59: 91–103.
5.
MortensenMNeeleyTB. Reflected knowledge and trust in global collaboration. Manage Sci2012; 58(12): 2207–2224.
6.
O’LearyMBCummingsJN. The spatial, temporal, and configurational characteristics of geographic dispersion in teams. MIS Q2007; 31: 433–452.
7.
O’LearyMBMortensenM. Go (con) figure: subgroups, imbalance, and isolates in geographically dispersed teams. Organiz Sci2010; 21: 115–131.
8.
ZhangYWuY. How behaviors spread in dynamic social networks. Comput Math Organiz Theory2012; 18: 419–444.
HerbslebJDMoitraD. Global software development. IEEE Software2001; 18(2): 16–20.
11.
KotlarskyJOshriI. Social ties, knowledge sharing and successful collaboration in globally distributed system development projects. Eur J Inf Syst2005; 14: 37–48.
12.
MalhotraAMajchrzakACarmanR. Radical innovation without collocation: a case study at Boeing-Rocketdyne. MIS Q2001: 229–249.
13.
NguyenTWolfTDamianD. Global software development and delay: does distance still matter? In: Proceedings of the 2008 IEEE international conference on the global software engineering. IEEE, 2008.
14.
OshriIKotlarskyJWillcocksL P. Global software development: Exploring socialization and face-to-face meetings in distributed strategic projects. J Strategic Inf Syst2007; 16(1): 25–49.
15.
FioreSMSalasECuevasHM. Distributed coordination space: toward a theory of distributed team process and performance. Theor Issues Ergon Sci2003; 4: 340–364.
16.
EspinosaJACummingsJNWilsonJM. Team boundary issues across multiple global firms. J Manage Inf Syst2003; 19: 157–190.
17.
OrlikowskiWJ. Knowing in practice: enacting a collective capability in distributed organizing. Organiz Sci2002; 13: 249–273.
18.
Watson-ManheimMBChudobaKMCrowstonK. Discontinuities and continuities: a new way to understand virtual work. Inf Technol People2002; 15: 191–209.
19.
GriffithTLSawyerJENealeMA. Virtualness and knowledge in teams: managing the love triangle of organizations, individuals, and information technology. MIS Q2003: 265–287.
20.
WebsterJStaplesDS. Comparing virtual teams to traditional teams: an identification of new research opportunities. Res Personnel Hum Resour Manage2006; 25: 181–215.
21.
MaloneTWCrowstonK. The interdisciplinary study of coordination. ACM Comput Surv1994; 26: 87–119.
22.
MaloneTWCrowstonK. What is coordination theory and how can it help design cooperative work systems? In: Proceedings of the 1990 ACM conference on computer-supported cooperative work. ACM, 1990.
23.
Van AartCJWielingaBSchreiberG. Organizational building blocks for design of distributed intelligent system. Int J Hum Comput Syst2004; 61: 567–599.
24.
RenYArgoteL. Transactive memory systems 1985–2010: an integrative framework of key dimensions, antecedents, and consequences. Acad Manage Ann2011; 5: 189–229.
25.
NigroGLDiegaSPerroneG. Coordination policies to support decision making in distributed production planning. Rob Comput Integr Manuf2003; 19: 521–531.
26.
ChildJRita GuntherM. Organizations unfettered: organizational form in an information-intensive economy. Acad Manage J2001; 44: 1135–1148.
27.
EspinosaJASlaughterSAKrautRE. Team knowledge and coordination in geographically distributed software development. J Manage Inf Syst2007; 24: 135–169.
28.
MarlowJDabbishL. Designing interventions to reduce psychological distance in globally distributed teams. In: Proceedings of the ACM 2012 conference on computer-supported cooperative work companion. ACM, 2012.
29.
StaplesDSHullandJSHigginsCA. A self-efficacy theory explanation for the management of remote workers in virtual organizations. Organiz Sci1999; 10: 758–776.
30.
WhyteG. Recasting Janis’s groupthink model: the key role of collective efficacy in decision fiascoes. Organiz Behav Hum Decis Processes1998; 73: 185–209.
31.
MarksMA. A test of the impact of collective efficacy in routine and novel performance environments. Hum Perform1999; 12: 295–309.
32.
BanduraA. Social foundations of thought and action: a social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall, 1986.
33.
BanduraA. Self-efficacy: the exercise of control. New York: Freeman, 1997.
34.
BuldyrevSVParshaniRPaulG. Catastrophic cascade of failures in interdependent networks. Nature2010; 464: 1025–1028.
GistMEMitchellTR. Self-efficacy: a theoretical analysis of its determinants and malleability. Acad Manage Rev1992: 183–211.
37.
PaskevichDMBrawleyLRDorschKD. Relationship between collective efficacy and team cohesion: conceptual and measurement issues. Group Dyn1999; 3: 210–222.
38.
ZaccaroSJBlairVPetersonC. Collective efficacy. Self-efficacy, adaptation, and adjustment. Springer, 1995, pp. 305–328.
39.
AjzenI. The theory of planned behavior. Organiz Behav Hum Decis Processes1991; 50: 179–211.
40.
AjzenI. Residual effects of past on later behavior: habituation and reasoned action perspectives. Pers Social Psychol Rev2002; 6: 107–122.
41.
WangMHuX. Agent-based modeling and simulation of community collective efficacy. Comput Math Organiz Theory2012; 18: 463–487.
42.
SiggelkowN. Firms as systems of interdependent choices. J Manage Stud2011; 48: 1126–1140.
43.
DrazinRvan de VenAH. Alternative forms of fit in contingency theory. Admin Sci Q1985: 514–539.
44.
MillerDFriesenPH. Organizations: a quantum view. Englewood Cliffs, NJ: Prentice-Hall, 1984.
45.
MillerDFriesenPH. Structural change and performance: quantum versus piecemeal–incremental approaches. Acad Manage J1982; 25: 867–892.
46.
LazerDFriedmanA. The network structure of exploration and exploitation. Admin Sci Q2007; 52: 667–694.
GilbertNDoranJ. Simulating societies: the computer simulation of social processes. London: UCL Press, 1993.
51.
AndersonEGLewisK. A dynamic model of individual and collective learning amid disruption. Organiz Sci2014; 25: 356–376.
52.
GrimmVRevillaEBergerU. Pattern-oriented modeling of agent-based complex systems: lessons from ecology. Science2005; 310: 987–991.
53.
ParshaniRBuldyrevSVHavlinS. Interdependent networks: reducing the coupling strength leads to a change from a first to second order percolation transition. Phys Rev Lett2010; 105: 048701.
54.
RivkinJWSiggelkowN. Balancing search and stability: interdependencies among elements of organizational design. Manage Sci2003; 49: 290–311.
55.
SzabGFathG. Evolutionary games on graphs. Phys Rep2007; 446: 97–216.
56.
PercMGómez-GardeñesJSzolnokiA. Evolutionary dynamics of group interactions on structured populations: a review. J R Soc Interface2013; 10: 20120997.
57.
SzolnokiAPercMSzabG. Topology-independent impact of noise on cooperation in spatial public goods games. Phys Rev E2009; 80: 056109.
58.
SzabGTökeC. Evolutionary prisoner’s dilemma game on a square lattice. Phys Rev E1998; 58: 69.
59.
WangZSzolnokiAPercM. Evolution of public cooperation on interdependent networks: the impact of biased utility functions. Europhys Lett2012; 97: 048001.
60.
PachecoJSantosFSouzaM. Evolutionary dynamics of collective action. In: ChalubFACCRodriguesJF (eds) The mathematics of Darwin’s legacy. Basel: Springer, 2011, pp.119–138.
61.
SampsonRJRaudenbushSWEarlsF. Neighborhoods and violent crime: a multilevel study of collective efficacy. Science1997; 277: 918–924.
62.
CarleyKMPrietulaMJ. Computational organization theory. L. Erlbaum Associates Inc., 1994.
Van DijkumCDe TombeDVan KuijkE. Validation of simulation models. SISWO, 1999.
65.
SeijtsGHLathamGPWhyteG. Effect of self-and group efficacy on group performance in a mixed-motive situation. Hum Perform2000; 13: 279–298.
66.
Katz-NavonTYErezM. When collective-and self-efficacy affect team performance the role of task interdependence. Small Group Res2005; 36: 437–465.
67.
WilsonJO’LearyMBMetiuA. Perceived proximity in virtual work: explaining the paradox of far-but-close. Organiz Stud2008; 29: 979–1002.
68.
WilsonJCrispCBMortensenM. Extending construal-level theory to distributed groups: understanding the effects of virtuality. Organiz Sci2013; 24: 629–644.
