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Patterns of ties in problem-solving networks and their dynamic properties

  • 1.

    Braha, D. & Bar-Yam, Y. Topology of large-scale engineering problem-solving networks. Phys. Rev. E 69, 016113 (2004).

    ADS  Article  CAS  Google Scholar 

  • 2.

    Braha, D. & Bar-Yam, Y. The statistical mechanics of complex product development: Empirical and analytical results. Manag. Sci. 53, 1127–1145 (2007).

    MATH  Article  Google Scholar 

  • 3.

    Simon, H. The sciences of the Artificial 3rd edn. (MIT Press, Cambridge, 1996).

    Google Scholar 

  • 4.

    Braha, D. & Maimon, O. A Mathematical Theory of Design: Foundations. Algorithms and Applications (Kluwer Academic Publishers, Dordrecht, 1998).

    Google Scholar 

  • 5.

    Yassine, A. & Braha, D. Complex concurrent engineering and the design structure matrix method. Concurr. Eng. 11, 165–176 (2003).

    Article  Google Scholar 

  • 6.

    Lazer, D. & Friedman, A. The network structure of exploration and exploitation. Adm. Sci. Q. 52, 667–694 (2007).

    Article  Google Scholar 

  • 7.

    March, J. G. Exploration and exploitation in organizational learning. Organ Sci. 2, 71–87 (1991).

    ADS  Article  Google Scholar 

  • 8.

    Berger-Tal, O., Nathan, J., Meron, E. & Saltz, D. The exploration-exploitation dilemma: a multidisciplinary framework. PLoS ONE 9, 4 (2014).

    Article  CAS  Google Scholar 

  • 9.

    Schumpeter, J. A. The Theory of Economic Development (Harvard University Press, Cambridge, 1934).

    Google Scholar 

  • 10.

    Sutton, R. S. & Barto, A. G. Reinforcement Learning: An Introduction (MIT Press, Cambridge, 1998).

    Google Scholar 

  • 11.

    Azoulay-Schwartz, R., Kraus, S. & Wilkenfeld, J. Exploitation vs exploration: Choosing a supplier in an environment of incomplete information. Decis Support Syst. 38, 1–18 (2004).

    Article  Google Scholar 

  • 12.

    Daw, N. D., O’Doherty, J. P., Dayan, P., Seymour, B. & Dolan, R. J. Cortical substrates for exploratory decisions in humans. Nature 441, 876–879 (2006).

    ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

  • 13.

    Eliassen, S., Jorgensen, C., Mangel, M. & Giske, J. Exploration or exploitation: Life expectancy changes the value of learning in foraging strategies. Oikos 116, 513–523 (2007).

    Article  Google Scholar 

  • 14.

    Uotila, J., Maula, M., Keil, T. & Zahra, S. A. Exploration, exploitation, and financial performance: Analysis of S&P 500 corporations. Strat. Mgmt. J. 30, 221–231 (2009).

    Article  Google Scholar 

  • 15.

    Molina-Castillo, F. J., Jimenez-Jimenez, D. & Munuera-Aleman, J. L. Product competence exploitation and exploration strategies: The impact on new product performance through quality and innovativeness. Ind. Market Manag. 40, 1172–1182 (2011).

    Article  Google Scholar 

  • 16.

    Cohen, J. D., McClure, S. M. & Yu, A. J. Should I stay or should I go? How the human brain manages the trade-off between exploitation and exploration. Philos. Trans. R. Soc. B. 362, 933–942 (2007).

    Article  Google Scholar 

  • 17.

    Berger-Tal, O. & Avgar, T. The glass is half full: Overestimating the quality of a novel environment is advantageous. PLoS ONE 7, e34578 (2012).

    ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

  • 18.

    Shore, J., Bernstein, E. & Lazer, D. Facts and figuring: An experimental investigation of network structure and performance in information and solution spaces. Organ. Sci. 26, 1432–1446 (2015).

    Article  Google Scholar 

  • 19.

    Subrahmanian, E. et al. Equations aren’t enough: Informal modeling in design. AI EDAM. 7, 257–274 (1993).

    Google Scholar 

  • 20.

    Axelrod, R. & Hamilton, W. D. The evolution of cooperation. Science 211, 1390–1396 (1981).

    ADS  MathSciNet  CAS  PubMed  MATH  Article  Google Scholar 

  • 21.

    Banerjee, J., Layek, R. K., Sasmal, S. K. & Ghosh, D. Delayed evolutionary model for public goods competition with policing in phenotypically variant bacterial biofilms. Europhys. Lett. 126, 18002 (2019).

    CAS  Article  Google Scholar 

  • 22.

    Szabó, G. & Fath, G. Evolutionary games on graphs. Phys. Rep. 446, 97–216 (2007).

    ADS  MathSciNet  Article  Google Scholar 

  • 23.

    Nag Chowdhury, S., Kundu, S., Duh, M., Perc, M. & Ghosh, D. Cooperation on interdependent networks by means of migration and stochastic imitation. Entropy. 22, 485 (2020).

    ADS  Article  Google Scholar 

  • 24.

    Axelrod, R. The complexity of cooperation: Agent-based models of competition and collaboration (Princeton University Press, Princeton, 1997).

    Google Scholar 

  • 25.

    Steward, D. V. The design structure system: A method for managing the design of complex systems. IEEE Trans. Eng. Manage. 3, 71–74 (1981).

    Article  Google Scholar 

  • 26.

    Eppinger, S. D., Whitney, D. E., Smith, R. P. & Gebala, D. A. A model-based method for organizing tasks in product development. Res. Eng. Design 6, 1–13 (1994).

    Article  Google Scholar 

  • 27.

    Browning, T. R. Applying the design structure matrix to system decomposition and integration problems: A review and new directions. IEEE Trans. Eng. Manag. 48, 292–306 (2001).

    Article  Google Scholar 

  • 28.

    Eppinger, S. D. & Browning, T. R. Design structure Matrix Methods and Applications (MIT press, Cambridge, 2012).

    Google Scholar 

  • 29.

    Yassine, A., Joglekar, N., Braha, D., Eppinger, S. & Whitney, D. Information hiding in product development: The design churn effect. Res. Eng. Design 14, 145–161 (2003).

    Article  Google Scholar 

  • 30.

    Braha, D. & Bar-Yam, Y. Information flow structure in large-scale product development organizational networks. J. Inf. Technol. 19, 244–253 (2004).

    Article  Google Scholar 

  • 31.

    Braha, D. The complexity of design networks: Structure and dynamics. In Experimental Design Research (eds Cash, P. et al.) 129–151 (Springer, Berlin, 2016).

    Google Scholar 

  • 32.

    Albert, R. & Barabási, A. L. Statistical mechanics of complex networks. Rev. Modern Phys. 74, 47–97 (2002).

    ADS  MathSciNet  MATH  Article  Google Scholar 

  • 33.

    Katz, N., Lazer, D., Arrow, H. & Contractor, N. The network perspective on teams. Small Group Res. 35, 307–332 (2004).

    Article  Google Scholar 

  • 34.

    Balkundi, P. & Harrison, D. A. Ties, leaders, and time in teams: Strong inference about the effects of network structure on team viability and performance. Acad. Manag. J. 49, 49–68 (2006).

    Article  Google Scholar 

  • 35.

    Leenders, R. T. A., Van Engelen, J. M. & Kratzer, J. Virtuality, communication, and new product team creativity: A social network perspective. J. Eng. Tech. Manag. 20, 69–92 (2003).

    Article  Google Scholar 

  • 36.

    Oh, H., Chung, M. H. & Labianca, G. Group social capital and group effectiveness: The role of informal socializing ties. Acad. Manag. J. 47, 860–875 (2004).

    Article  Google Scholar 

  • 37.

    Uzzi, B. & Spiro, J. Collaboration and creativity: The small world problem. Am. J. Sociol. 111, 447–504 (2005).

    Article  Google Scholar 

  • 38.

    Sparrowe, R. T., Liden, R. C., Wayne, S. J. & Kraimer, M. L. Social networks and the performance of individuals and groups. Acad. Manag. J. 44, 316–325 (2001).

    Google Scholar 

  • 39.

    Kearns, M., Suri, S. & Montfort, N. An experimental study of the coloring problem on human subject networks. Science 313, 824–827 (2006).

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 40.

    McCubbins, M. D., Paturi, R. & Weller, N. Connected coordination network structure and group coordination. Am. Polit. Res. 37, 899–920 (2009).

    Article  Google Scholar 

  • 41.

    Enemark, D., McCubbins, M. D. & Weller, N. Knowledge and networks: An experimental test of how network knowledge affects coordination. Soc. Netw. 36, 122–133 (2014).

    Article  Google Scholar 

  • 42.

    Mason, W. A. & Watts, D. J. Collaborative learning in networks. Proc. Natl. Acad. Sci. USA 109, 764–769 (2012).

    ADS  CAS  PubMed  Article  Google Scholar 

  • 43.

    Mason, W. A., Jones, A. & Goldstone, R. L. Propagation of innovations in networked groups. J. Exp. Psychol. Gen. 137, 422–433 (2008).

    PubMed  Article  Google Scholar 

  • 44.

    Levinthal, D. A. Adaptation on rugged landscapes. Manag. Sci. 43, 934–950 (1997).

    MATH  Article  Google Scholar 

  • 45.

    Rivkin, J. W. & Siggelkow, N. Balancing search and stability: Interdependencies among elements of organizational design. Manag. Sci. 49, 290–312 (2003).

    Article  Google Scholar 

  • 46.

    Milo, R. et al. Network motifs: Simple building blocks of complex networks. Science 298, 824–827 (2002).

    ADS  CAS  PubMed  Article  Google Scholar 

  • 47.

    Milo, R. et al. Superfamilies of evolved and designed networks. Science 303, 1538–1542 (2004).

    ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

  • 48.

    Alon, U. An Introduction to Systems Biology: Design Principles of Biological Circuits (CRC Press, Boca Raton, 2019).

    Google Scholar 

  • 49.

    Prill, R. J., Iglesias, P. A. & Levchenko, A. Dynamic properties of network motifs contribute to biological network organization. PLoS Biol. 3, 11 (2005).

    Article  CAS  Google Scholar 

  • 50.

    Wasserman, S. & Faust, K. Social Network Analysis: Methods and applications (Cambridge University Press, Cambridge, 1994).

    Google Scholar 

  • 51.

    Stone, L., Simberloff, D. & Artzy-Randrup, Y. Network motifs and their origins. PloS Comput. Biol. 15, 2 (2019).

    Article  CAS  Google Scholar 

  • 52.

    Holland, P.W. & Leinhardt, S. The statistical analysis of local structure in social networks. National Bureau of Economic Research. No. w0044 (1974).

  • 53.

    Pimm, S. L. Food webs (Springer, Berlin, 1982).

    Google Scholar 

  • 54.

    Stone, L. & Roberts, A. Competitive exclusion, or species aggregation?—An aid in deciding. Oecologia 91, 419–424 (1992).

    ADS  PubMed  Article  Google Scholar 

  • 55.

    Connor, E. F. & Simberloff, D. The assembly of species communities: Chance or competition?. Ecology 60, 1132–1140 (1979).

    Article  Google Scholar 

  • 56.

    Saracco, F., Di Clemente, R., Gabrielli, A. & Squartini, T. Detecting early signs of the 2007–2008 crisis in the world trade. Sci Rep. 6, 1–11 (2016).

    Article  CAS  Google Scholar 

  • 57.

    Saracco, F., Di Clemente, R., Gabrielli, A. & Squartini, T. Randomizing bipartite networks: The case of the world trade web. Sci Rep. 5, 1–18 (2015).

    Article  CAS  Google Scholar 

  • 58.

    Sporns, O. & Kötter, R. Motifs in brain networks. PloS Biol. 2, 11 (2004).

    Article  CAS  Google Scholar 

  • 59.

    Alon, U. Network motifs: Theory and experimental approaches. Nat. Rev. Genet. 8, 450–461 (2007).

    CAS  PubMed  Article  Google Scholar 

  • 60.

    May, R. M. Stability and Complexity in Model Ecosystems (Princeton University Press, Princeton, 2019).

    Google Scholar 

  • 61.

    Gardner, M. R. & Ashby, W. R. Connectance of large dynamic (cybernetic) systems: Critical values for stability. Nature 228, 784–784 (1970).

    ADS  CAS  PubMed  Article  Google Scholar 

  • 62.

    Ravasz, E., Somera, A. L., Mongru, D. A., Oltvai, Z. N. & Barabási, A. L. Hierarchical organization of modularity in metabolic networks. Science 297, 1551–1555 (2002).

    ADS  CAS  PubMed  Article  Google Scholar 

  • 63.

    Bulloch, B. & Sullivan, J. Information—the key to the real estate development process. Cornell Real Estate Rev. 8, 78–87 (2010).

    Google Scholar 

  • 64.

    Scheurmann, E. & Atkinson, L. Strategy Development Process for Meat & Livestock Australia. In Design Structure Matrix Methods and Applications (eds Eppinger, S. D. & Browning, T. R.) 164–168 (MIT press, Cambridge, 2012).

    Google Scholar 

  • 65.

    Osborne, S.M. Product Development Cycle Time Characterization Through Modeling of Process Iteration. Master’s thesis, Massachusetts Institute of Technology, Cambridge, MA. (1993).

  • 66.

    Scheurmann, E. & Samuel, D. Bioscience Facility at University of Melbourne. In Design Structure Matrix Methods and Applications (eds Eppinger, S. D. & Browning, T. R.) 155–159 (MIT press, Cambridge, 2012).

    Google Scholar 

  • 67.

    Yassine, A., Whitney, D. & Zambito, T. Assessment of rework probabilities for design structure matrix (DSM) simulation in product development management in 13thInternational Conference on Design Theory and Methodology (ASME, 2001).

  • 68.

    Tripathy, A. & Eppinger, S. Dover Motion Precision Systems Development Process. In Design structure matrix methods and applications (eds Eppinger, S. D. & Browning, T. R.) 192–195 (MIT press, Cambridge, 2012).

    Google Scholar 

  • 69.

    Tukey, J. W. Exploratory Data Analysis (Addison-Wesley, Boston, 1977).

    Google Scholar 

  • 70.

    Zar, J. H. Biostatistical Analysis (Prentice Hall, New Jersey, 2010).

    Google Scholar 

  • 71.

    Kleiner, B. & Graedel, T. E. Exploratory data analysis in the geophysical sciences. Rev. Geophys. 18, 699–717 (1980).

    ADS  Article  Google Scholar 

  • 72.

    Williamson, D. F., Parker, R. A. & Kendrick, J. S. The box plot: a simple visual method to interpret data. Ann. Intern. Med. 110, 916–921 (1989).

    CAS  PubMed  Article  Google Scholar 

  • 73.

    Ray, A., Rakshit, S., Basak, G. K., Dana, S. K. & Ghosh, D. Understanding the origin of extreme events in El Niño southern oscillation. Phys. Rev. E 101, 062210 (2020).

    ADS  MathSciNet  PubMed  Article  Google Scholar 

  • 74.

    Törnqvist, L., Vartia, P. & Vartia, Y. O. How should relative changes be measured?. Am. Stat. 39, 43–46 (1985).

    Google Scholar 

  • 75.

    Braha, D. & Bar-Yam, Y. From centrality to temporary fame: Dynamic centrality in complex networks. Complexity. 12, 59–63 (2006).

    Article  Google Scholar 

  • 76.

    Braha, D. & Bar-Yam, Y. Time-dependent complex networks: Dynamic centrality, dynamic motifs, and cycles of social interactions. In Adaptive Networks (eds Gross, T. & Hiroki, S.) 39–50 (Springer, Berlin, 2009).

    Google Scholar 

  • 77.

    Bassok, M. & Novick, L. R. Problem Solving. In The Oxford Handbook of Thinking and Reasoning (eds Holyoak, K. J. & Morrison, R. G.) 413–429 (Oxford University Press, Oxford, 2012).

    Google Scholar 

  • 78.

    Nelson, R. R. & Winter, S. G. An Evolutionary Theory of Economic Change (Harvard University Press, Cambridge, 1982).

    Google Scholar 

  • 79.

    Becker, M. C. Organizational routines: A review of the literature. Ind. Corpor. Change. 13, 643–678 (2004).

    Article  Google Scholar 

  • 80.

    Pentland, B. T., Hærem, T. & Hillison, D. The (n)ever-changing world: Stability and change in organizational routines. Organ. Sci. 22, 1369–1383 (2011).

    Article  Google Scholar 

  • 81.

    Feldman, M. S. & Pentland, B. T. Reconceptualizing organizational routines as a source of flexibility and change. Adm. Sci. Q. 48, 94–118 (2003).

    Article  Google Scholar 


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