Soft Computing

, Volume 22, Issue 16, pp 5439–5451 | Cite as

A novel two-sided matching decision method for technological knowledge supplier and demander considering the network collaboration effect

  • Jing Han
  • Bin LiEmail author
  • Haiming Liang
  • Kin Keung Lai


To obtain competitive advantage, the key target for the two-sided matching between technological knowledge supplier and demander is maximizing the individual exchange satisfaction. The structure of the supplier and demander relationship networks means that the two-sided matching approach not only gives point-to-point matching but also gives network-to-network matching. In this paper, supply and demand network characteristics are embedded into a two-phase decision analysis method. First, to select the matching pairs, a matching satisfaction matrix is constructed based on the supply and demand network characteristics, after which a multi-objective optimal model is built to determine the best optimization matching results and the overall improvements illustrated through comparison. Finally, a numerical example is given to show the practicality and validity of the proposed approach.


Network collaboration effect Satisfaction degree optimization Two-sided matching Technological knowledge supply and demand 



This research was supported by the China Postdoctoral Science Foundation (No. 2016M590960), the National Natural Science Foundation of China (NSFC Grant Nos.71403158 and 71601133) and the Fundamental Research Funds for the Central Universities (No. 14SZYB10). The authors would like to thank the anonymous referees as well as the editors.

Compliance with ethical standards

Conflict of interest

Authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with animals performed by any of the authors. It is based on previously published studies.


  1. Alaei S, Jain K, Malekian A (2011) Competitive equilibrium in two sided matching markets with general utility functions. ACM Sigecom Exchanges 10:34–36CrossRefzbMATHGoogle Scholar
  2. Baum JAC, Cowan R, Jonard N (2010) Network-independent partner selection and the evolution of innovation networks. Manag Sci 56:2094–2110CrossRefGoogle Scholar
  3. Boland WP, Phillips PWB, Ryan CD, Mcphee-Knowles S (2012) Collaboration and the generation of new knowledge in networked innovation systems: a bibliometric analysis. Procedia Soc Behav Sci 52:15–24CrossRefGoogle Scholar
  4. Carayol N, Roux P (2009) Knowledge flows and the geography of networks: a strategic model of small world formation. J Econ Behav Organ 71:414–427CrossRefGoogle Scholar
  5. Chen BL, Mo JP, Wang P (2012) Two-sided micro-matching with technical progress. Econ Theory 50:445–462MathSciNetCrossRefzbMATHGoogle Scholar
  6. Chen X, Fan ZP, Li YH (2010) A two-phase decision analysis method for two-sided matching of technological knowledge supply and demand. Ind Eng Manag 15:90–94Google Scholar
  7. Chen X, Li Z, Fan ZP, Zhou X, Zhang X (2016) Matching demanders and suppliers in knowledge service: a method based on fuzzy axiomatic design. Inf Sci 346–347:130–145MathSciNetCrossRefGoogle Scholar
  8. Chen Z, Guan J (2010) The impact of small world on innovation: an empirical study of 16 countries. J Informetr 4:97–106CrossRefGoogle Scholar
  9. Cowan R, Jonard N, Zimmermann JB (2007) Bilateral collaboration and the emergence of innovation networks. Manag Sci 53:1051–1067CrossRefGoogle Scholar
  10. Dassisti M, Carnimeo L (2013) A small-world methodology of analysis of interchange energy-networks: the european behaviour in the economical crisis. Energy Policy 63:887–899CrossRefGoogle Scholar
  11. Deng X, Chi L (2015) Knowledge boundary spanning and productivity in information systems support community. Decis Support Syst 80:14–26CrossRefGoogle Scholar
  12. Díez-Vial I, Fernández-Olmos M (2015) Knowledge spillovers in science and technology parks: how can firms benefit most? J Technol Transf 40:70–84CrossRefGoogle Scholar
  13. Echenique F, Wilson AJ, Yariv L (2016) Clearinghouses for two-sided matching: an experimental study. Quant Econ 7:449–482MathSciNetCrossRefGoogle Scholar
  14. Frankort HTW, Hagedoorn J, Letterie W (2012) R&D partnership portfolios and the inflow of technological knowledge. Ind Corp Change 21:507–537CrossRefGoogle Scholar
  15. Guan J, Zhao Q (2013) The impact of university-industry collaboration networks on innovation in nanobiopharmaceuticals. Technol Forecast Soc Change 80:1271–1286CrossRefGoogle Scholar
  16. Herrero Á, Sáiz-Bárcena L, Manzanedo MA, Corchado E (2016) A hybrid proposal for cross-sectoral analysis of knowledge management. Soft Comput 20:4271–4285CrossRefGoogle Scholar
  17. Huber F (2010) Do clusters really matter for innovation practices in information technology? questioning the significance of technological knowledge spillovers. J Econ Geogr 12:107–126CrossRefGoogle Scholar
  18. Hwang CL, Yoon K (1981) Lecture notes in economics and mathematical system: multiple attribute decision making, methods and application, a state of art survey. Springer, New YorkGoogle Scholar
  19. Jiao ZH, Tian GQ (2015) The stability of many-to-many matching with max–min preferences. Econ Lett 129:52–56MathSciNetCrossRefzbMATHGoogle Scholar
  20. Klumpp T (2009) Two-sided matching with spatially differentiated agents. J Math Econ 45:376–390MathSciNetCrossRefzbMATHGoogle Scholar
  21. Lange DED (2016) A social capital paradox: entrepreneurial dynamism in a small world clean technology cluster. J Clean Prod 139:576–585CrossRefGoogle Scholar
  22. Lazarova E, Borm P, Estévez-Fernández A (2016) Transfers and exchange-stability in two-sided matching problems. Theory Decis 81:53–71MathSciNetCrossRefzbMATHGoogle Scholar
  23. Lazarova E, Dimitrov D (2017) Paths to stability in two-sided matching under uncertainty. Int J Game Theory 46:29–49MathSciNetCrossRefzbMATHGoogle Scholar
  24. Liao TJ (2015) Clusters, technological knowledge spillovers, and performance. Manag Decis 53:469–490CrossRefGoogle Scholar
  25. Li X, Hong KL (2014) An energy-efficient scheduling and speed control approach for metro rail operations. Transp Res Part B 64:73–89CrossRefGoogle Scholar
  26. Li X, Zhou JD, Zhao XD (2016) Travel itinerary problem. Transp Res Part B 91:332–343CrossRefGoogle Scholar
  27. Lindner I, Strulik H (2014) From tradition to modernity: economic growth in a small world. J Dev Econ 109:17–29CrossRefGoogle Scholar
  28. Liu F, Wang L, Gao L, Men SK (2014) A Web service trust evaluation model based on small-world networks. Knowl-Based Syst 57:161–167CrossRefGoogle Scholar
  29. Lou S, Du Y, Liu P, Xuan Z, Wang Y (2015) A study on coevolutionary dynamics of knowledge diffusion and social network structure. Expert Syst Appl Int J 42:3619–3633CrossRefGoogle Scholar
  30. Lovejoy WS, Sinha A (2010) Efficient structures for innovative social networks. Manag Sci 56:1127–1145CrossRefzbMATHGoogle Scholar
  31. Mauleo A, Sempere-Monerris JJ, Vannetelbosch V (2008) Networks of knowledge among unionized firms. Can J Econ 41:971–997CrossRefGoogle Scholar
  32. Miguélez E, Moreno R (2015) Knowledge flows and the absorptive capacity of regions. Res Policy 44:833–848CrossRefGoogle Scholar
  33. Mindruta D, Moeen M, Agarwal R (2016) A two-sided matching approach for partner selection and assessing complementarities in partners’ attributes in inter-firm alliances. Strateg Manag J 37:206–231CrossRefGoogle Scholar
  34. Morizumi Y, Hayashi T, Ishida Y (2011) A network visualization of stable matching in the stable marriage problem. Springer, New York, pp 40–43Google Scholar
  35. Ni Y, Ning L, Ke H, Ji X (2016) Modeling and minimizing information distortion in information diffusion through a social network. Soft Comput 1–13Google Scholar
  36. Noni ID, Ganzaroli A, Orsi L (2017) The impact of intra- and inter-regional knowledge collaboration and technological variety on the knowledge productivity of European regions. Technol Forecast Soc Change 117:108–118CrossRefGoogle Scholar
  37. Noni ID, Orsi L, Belussi F (2017) The role of collaborative networks in supporting the innovation performances of lagging-behind European regions. Res Policy 47:1–13CrossRefGoogle Scholar
  38. Sebestyén T, Varga A (2013) Research productivity and the quality of interregional knowledge networks. Ann Reg Sci 51:155–189CrossRefGoogle Scholar
  39. Su CY, Lin BW, Chen CJ (2015) Technological knowledge co-creation strategies in the world of open innovation. Innov Manag Policy Pract 17:485–507CrossRefGoogle Scholar
  40. Todo Y, Matous P, Inoue H (2016) The strength of long ties and the weakness of strong ties: knowledge diffusion through supply chain networks. Res Policy 45:1890–1906CrossRefGoogle Scholar
  41. Urgal B, Quintas MA, Arevalo Tome R (2011) Technological knowledge, innovation capability and innovative performance: the moderating role of the behavioural environment of the firm. Panel De Innovación Tecnológica 14:53–66Google Scholar
  42. Watts DJ, Strogatz SH (1998) Collective dynamics of ‘small world’ networks. Nature 393:420–440CrossRefzbMATHGoogle Scholar
  43. Winkelbach A, Walter A (2015) Complex technological knowledge and value creation in science-to-industry technology transfer projects: the moderating effect of absorptive capacity. Ind Mark Manag 47:98–108CrossRefGoogle Scholar
  44. Xu X, Zhang W, Li N, Xu H (2015) A bi-level programming model of resource matching for collaborative logistics network in supply uncertainty environment. J Frankl Inst 352:3873–3884MathSciNetCrossRefGoogle Scholar
  45. Zach FJ, Hill TL (2017) Network, knowledge and relationship impacts on innovation in tourism destinations. Tour Manag 62:196–207CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Jing Han
    • 1
    • 2
  • Bin Li
    • 3
    Email author
  • Haiming Liang
    • 4
  • Kin Keung Lai
    • 1
    • 5
  1. 1.International Business SchoolShaanxi Normal UniversityXi’anChina
  2. 2.School of ManagementXi’an Jiaotong UniversityXi’anChina
  3. 3.School of EconomicsXi’an University of Finance and EconomicsXi’anChina
  4. 4.School of Economics and ManagementXidian UniversityXi’anChina
  5. 5.Department of Management SciencesCity University of Hong KongHong KongChina

Personalised recommendations