Skip to main content
SpringerLink
Log in

How to identify metaknowledge trends and features in a certain research field? Evidences from innovation and entrepreneurial ecosystem

  • Published:
Scientometrics Aims and scope Submit manuscript

Abstract

Identifying the trends and features of metaknowledge will help scholars track knowledge through topics. This paper designs a new methodology to make it in a certain field. The proposed novel design performs well in the interdisciplinary domain where there are plenty noisy data and conflicting findings. This study applies this research design to a typical interdisciplinary domain, i.e. innovation and entrepreneurial ecosystems. To identify the scope of research and rationalize data collection process, this paper makes a definition of innovation and entrepreneurial ecosystems based on previous researches. Next, we design two data filtering procedures, which can handle the noisy data and provide the datasets for sequence analyses. Then, we adopt the co-citation analysis and network meta-analysis to clarify the trends and features of multiple metaknowledges. Finally, we draw conclusions about emerging trends, mainstream and hotspots, current situation, future challenges or other features of metaknowledge. We also integrate some conflicting findings, which provide more accurate evidences for the field. Evidences show that this novel research design is an effective tool for analyzing metaknowledges and also suitable for other fields.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Notes

  1. The User Guide of Endnote can be found at: http://endnote.com/training/mats/enuserguide/.

  2. According to Geyskens et al. (2009), unpublished studies should be included to avoid publication bias.

References

  • Adner, R. (2006). Match your innovation strategy to your innovation ecosystem. Harvard Business Review, 84, 98–107.

    Google Scholar 

  • Adner, R. (2012). The wide lens: A new strategy for innovation (p. 2012). London: Portfolio, Penguin.

    Google Scholar 

  • *Adner, R., & Kapoor, R. (2010). Value creation in innovation ecosystems: How the structure of technological interdependence affects firm performance in new technology generations. Strategic Management Journal, 31, 306–333.

    Article  Google Scholar 

  • Adner, R., & Kapoor, R. (2016). Innovation ecosystem and the pace of substitution: Re-examining technology S-curve. Strategic Management Journal, 37, 625–648.

    Article  Google Scholar 

  • Alchian, A. A., & Demsetz, H. (1972). Production, information costs, and economic organization. American Economic Review, 62, 777–795.

    Google Scholar 

  • Autio, E., Kenney, M., Mustar, P., Siegel, D., & Wright, M. (2014). Entrepreneurial innovation: The importance of context. Research Policy, 43, 1097–1108.

    Article  Google Scholar 

  • Barney, J. B. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17, 99–120.

    Article  Google Scholar 

  • Barrios, M., Guileraa, G., & Gómez-Benito, J. (2013). Impact and structural features of meta-analytical studies, standard articles and reviews in psychology: Similarities and differences. Journal of Informetrics, 7, 478–486.

    Article  Google Scholar 

  • Bengtsson, M., Kock, S., Lundgren-Henriksson, E.-L., & Näsholm, M. H. (2016). Coopetition research in theory and practice: Growing new theoretical, empirical, and methodological domains. Industrial Marketing Management, 57, 4–11.

    Article  Google Scholar 

  • Bornmann, L. (2015). Alternative metrics in scientometrics: a meta-analysis of research into three altmetrics. Scientometrics, 103, 1123–1144.

    Article  Google Scholar 

  • Bornmann, L., & Marx, W. (2013). The proposal of a broadening of perspective in evaluative bibliometrics by complementing the times cited with a cited reference analysis. Journal of Informetric, 7(1), 84–88.

    Article  Google Scholar 

  • Bornmann, L., Mutz, R., & Daniel, H.-D. (2007). Gender differences in grant peer review: A meta-analysis. Journal of Informetrics, 1, 226–238.

    Article  Google Scholar 

  • Bornmann, L., Mutz, R., Hug, S. E., & Daniel, H.-D. (2011). A multilevel meta-analysis of studies reporting correlations between the h index and 37 different h index variants. Journal of Informetrics, 5, 346–359.

    Article  Google Scholar 

  • *Boudreau, K. (2010). Open platform strategies and innovation: Granting access vs. devolving control. Management Science, 56, 1849–1872.

    Article  Google Scholar 

  • *Boudreau, K. J. (2012). Let a thousand flowers bloom? An early look at large numbers of software app developers and patterns of innovation. Organization Science, 23, 1409–1427.

    Article  Google Scholar 

  • Boyack, K. W., & Klavans, R. (2010). Co-citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately? Journal of the American Society for Information Science and Technology, 61(12), 2389–2404.

    Article  Google Scholar 

  • Brown, S. L., & Eisenhardt, K. M. (1997). The art of continuous change: Linking complexity theory and time-paced evolution in relentlessly shifting organizations. Administrative Science Quarterly, 42(1), 1–34.

    Article  Google Scholar 

  • Cachon, G. P., & Zipkin, P. H. (1999). Competitive and cooperative inventory policies in a two-stage supply chain. Management Science, 45(7), 936–953.

    Article  MATH  Google Scholar 

  • Carl, S., & Varian, H. R. (1998). Information rules: A strategic guide to the network economy. Brighton: Harvard Business Press.

    Google Scholar 

  • Carlin, B. P., Hong, H., Shamliyan, T. A., Sainfort, F., & Kane, R. L. (2013). Case study comparing bayesian and frequentist approaches for multiple treatment comparisons. Rockville: Agency for Healthcare Research and Quality.

    Google Scholar 

  • *Ceccagnoli, M., Forman, C., Huang, P., & Wu, D. J. (2012). Cocreation of value in a platform ecosystem: the case of enterprise software. MIS Quarterly, 36, 263–290.

    Google Scholar 

  • *Cennamo, C., & Santalo, J. (2013). Platform comprtition: Strategic trade-offs in platform markets. Strategic Management Journal, 34, 1331–1350.

    Article  Google Scholar 

  • Chaimani, A., & Salanti, G. (2015). Visualizing assumptions and results in network meta-analysis: The network graphs package. The Stata Journal, 15, 905–950.

    Google Scholar 

  • Chen, C. M. (2006). CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature. Journal of the American Society for Information Science and Technology, 57(3), 359–377.

    Article  Google Scholar 

  • Chen, C. M. (2014). The citespace manual. http://cluster.ischool.drexel.edu/~cchen/citespace/CiteSpaceManual.pdf.

  • Chen, Y., Chen, C., Hu, Z., & Wang, X. (2014a). Principles and applications of analyzing a citation space. Beijing: Science Press.

    Google Scholar 

  • Chen, C., Dubin, R., & Kim, M. C. (2014b). Emerging trends and new developments in regenerative medicine: A scientometric update (2000–2014). Expert Opinion on Biological Therapy, 14(9), 1295–1317.

    Article  Google Scholar 

  • Chen, C., Dubin, R., & Kim, M. C. (2014c). Orphan drugs and rare diseases: A scientometric review (2000–2014). Expert Opinion on Orphan Drugs, 2(7), 709–724.

    Article  Google Scholar 

  • Chen, C., Hu, Z., Liu, S., & Tseng, H. (2012). Emerging trends in regenerative medicine: A scientometric analysis in CiteSpace. Expert Opinions on Biological Therapy, 12(5), 593–608.

    Article  Google Scholar 

  • Chen, C., Ibekwe-SanJuan, F., & Hou, J. (2010). The structure and dynamics of co-citation clusters: A multiple-perspective co-citation analysis. Journal of the American Society for Information Science and Technology, 61(7), 1386–1409.

    Article  Google Scholar 

  • Chesbrough, H., & Rosenbloom, R. S. (2002). The role of the business model in capturing value from innovation: evidence from Xerox Corporation’s technology spin-off companies. Industrial and Corporate Change, 11(3), 529–555.

    Article  Google Scholar 

  • *Clarysse, B., Wright, M., Bruneel, J., & Mahajan, A. (2014). Creating value in ecosystems: Crossing the chasm between knowledge and business ecosystems. Research Policy, 43, 1164–1176.

    Article  Google Scholar 

  • *Cohen, W. M., & Levinthal, D. A. (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly, 35, 128–152.

    Article  Google Scholar 

  • Cooke, P., Uranga, M. G., & Etxebarri, G. (1997). Regional innovation systems: Institutional and organizational dimensions. Research Policy, 26, 475–491.

    Article  Google Scholar 

  • Cornelius, B., Landström, H., & Persson, O. (2006). Entrepreneurial studies: the dynamic research front of a developing social science. Entrepreneurship Theory and Practice, 30(3), 375–398.

    Article  Google Scholar 

  • *Crosling, G., Nair, M., & Vaithilingam, S. (2015). A creative learning ecosystem, quality of education and innovative capacity: a perspective from higher education. Studies in Higher Education, 40, 1147–1163.

    Article  Google Scholar 

  • Dyer, J. H., & Singh, H. (1998). The relational view: Cooperative strategy and sources of interorganizational competitive advantage. The Academy of Management Review, 23, 660–679.

    Google Scholar 

  • Eisenhardt, K. M. (1989). Making fast strategic decisions in high-velocity environments. Academy of Management Journal, 32(3), 543–576.

    Article  Google Scholar 

  • Eisenhardt, K. M., & Martin, J. A. (2000). Dynamic capabilities: What are they? Strategic Management Journal, 21, 1105–1121.

    Article  Google Scholar 

  • Eisenmann, T., Parker, G., & Alstyne, M. W. (2006). Estrategias para mercados bilaterales. Harvard Business Review, 84, 60–71.

    Google Scholar 

  • Evans, J. A., & Foster, J. G. (2011). Metaknowledge. Science, 331, 721–725.

    Article  MathSciNet  MATH  Google Scholar 

  • *Fabrizio, K. R., & Hawn, O. (2013). Enabling diffusion: How complementary inputs moderate the response to environmental policy. Research Policy, 42, 1099–1111.

    Article  Google Scholar 

  • *Frenkel, A., Israel, A., & Maital, S. (2015). The evolution of innovation networks and spin-off entrepreneurship: The case of RAD. European Planning Studies, 23, 1646–1670.

    Article  Google Scholar 

  • Gawer, A., & Cusumano, M. A. (2008). How companies become platform leaders. MIT Sloan Management Review, 49(Winter), 28–35.

    Google Scholar 

  • Gawer, A., & Cusumano, M. A. (2014). Industry platforms and ecosystem innovation. Journal of Product Innovation Management, 31, 417–433.

    Article  Google Scholar 

  • Gawer, A., & Henderson, R. (2007). Platform owner entry and innovation in complementary markets: evidence from Intel. Journal of Economics and Management Strategy, 16(1), 1–34.

    Article  Google Scholar 

  • Geyskens, I., Krishnan, R., Steenkamp, J.-B. E. M., & Cunha, P. V. (2009). A review and evaluation of meta-analysis practices in management research. Journal of Management, 35, 393–420.

    Article  Google Scholar 

  • Grégoire, D. A., Noël, M. X., Déry, R., & Béchard, J.-P. (2006). Is there conceptual convergence in entrepreneurship research? A co-citation analysis of frontiers of entrepreneurship research, 1981–2004. Entrepreneurship Theory and Practice, 30(3), 333–373.

    Article  Google Scholar 

  • Guilera, G., Barrios, M., & Gómez-Benito, J. (2013). Meta-analysis in psychology: a bibliometric study. Scientometrics, 94, 943–954.

    Article  Google Scholar 

  • Hall, R. E., & Woodward, S. E. (2010). The burden of the nondiversifiable risk of entrepreneurship. American Economic Review, 100, 1163–1194.

    Article  Google Scholar 

  • Harvey, C., Kelly, A., Morris, H., & Rowlinson, M. (2010). Academic journal quality guide, version 4. London: Association of Business Schools.

    Google Scholar 

  • Helfat, C. E., Finkelstein, S., Mitchell, W., Peteraf, M. A., Singh, H., Teece, D. J., et al. (2007). Dynamic capabilities: Understanding strategic change in organizations. Malden, MA: Blackwell Publishing.

    Google Scholar 

  • Henderson, R. M., & Clark, K. B. (1990). Architectural innovation: the reconfiguration of existing product technologies and the failure of established firms. Administrative Science Quarterly, 35(1), 9–30.

    Article  Google Scholar 

  • Huang, M., & Chang, C.-P. (2015). A comparative study on detecting research fronts in the organic light-emitting diode (OLED) field using bibliographic coupling and co-citation. Scientometrics, 102, 2041–2057.

    Article  Google Scholar 

  • Hunter, J. E., & Schmidt, F. L. (2004). Methods of meta-analysis. Correcting error and bias in research findings (2nd ed.). Thousand Oaks, CA: Sage.

    Google Scholar 

  • Iansiti, M., & Levien, R. (2004a). The keystone advantage: What the new dynamics of business ecosystems mean for strategy, innovation, and sustainability. Boston: Harvard Business School Press.

    Google Scholar 

  • Iansiti, M., & Levien, R. (2004b). Strategy as ecology. Harvard Business Review, 82(3), 68–78.

    Google Scholar 

  • Iansiti, M., & Richards, G. L. (2006). The information technology ecosystem: Structure, health, and performance The. Antitrust Bulletin, 51(1), 77–110.

    Article  Google Scholar 

  • Jackson, B. D. J. (2011). What is an innovation ecosystem?, Washington DC. Retrieved from http://erc-assoc.org/sites/default/files/download-files/DJackson_What-is-an-Innovation-Ecosystem.pdf.

  • *Jacobides, M. G., & Tae, C. J. (2015). Kingpins, bottlenecks, and value dynamics along a sector. Organization Science, 26, 889–907.

    Article  Google Scholar 

  • Jenkins, A. S., Wiklund, J., & Brundin, E. (2014). Individual responses to firm failure: appraisals, grief, and the influence of prior failure experience. Journal of Business Venturing, 29(1), 17–33.

    Article  Google Scholar 

  • *Kang, J.-S., & Downing, S. (2015). Keystone effect on entry into two-sided markets: An analysis of the market entry of WiMAX. Technological Forecasting and Social Change, 94, 170–186.

    Article  Google Scholar 

  • *Kapoor, R. (2014). Collaborating with complementors: What do firms do? Collaboration and Competition in Business Ecosystems, 11, 3–25.

    Google Scholar 

  • *Kapoor, R., & Furr, N. R. (2015). Complementarities and Competition: Unpacking the drivers of entrants’ technology choices in the solar photovoltaic industry. Strategic Management Journal, 36, 416–436.

    Article  Google Scholar 

  • *Kapoor, R., & Lee, J. M. (2010). Coordinating and competing in ecosystems: How organizational forms shape new technology investments. Strategic Management Journal, 34, 274–296.

    Article  Google Scholar 

  • *Khavul, S., & Deeds, D. (2016). The evolution of initial co-investment syndications in an emerging venture capital market. Journal of International Management, 22, 280–293.

    Article  Google Scholar 

  • Kim, M. C., & Chen, C. (2015). A scientometric review of emerging trends and new developments in recommendation systems. Scientometrics, 104, 239–263.

    Article  Google Scholar 

  • Kleinberg, J. (2003). Data mining and knowledge discovery. Data Mining and Knowledge Discovery, 7, 373–397.

    Article  MathSciNet  Google Scholar 

  • Klepper, S., & Graddy, E. (1990). The evolution of new industries and the determinants of market structure. Rand Journal of Economics, 21(1), 27–44.

    Article  Google Scholar 

  • *Lichtenthaler, U. (Unpublished). Determinants of proactive and reactive technology licensing: A contingency perspective.

  • Mack, E., & Mayer, H. (2016). The evolutionary dynamics of entrepreneurial ecosystems. Urban Studies, 53, 2118–2133.

    Article  Google Scholar 

  • Mäkinen, S. J., Kanniainen, J., & Peltola, I. (2014). Investigating adoption of free beta applications in a platform-based business ecosystem. Journal of Product Innovation Management, 31, 451–465.

    Article  Google Scholar 

  • March, J. G. (1991). Exploration and exploitation in organizational learning. Organization Science, 2, 71–87.

    Article  Google Scholar 

  • McLevey, J., & McIlroy-Young, R. (2017). Introducing metaknowledge: Software for computational research in information science, network analysis, and science of science. Journal of Informetrics, 11, 176–197.

    Article  Google Scholar 

  • Mills, E. J., Thorlund, K., & Ioannidis, P. A. (2013). Demystifying trial networks and network meta-analysis. British Medical Journal, 346, 1–6.

    Article  Google Scholar 

  • Moore, J. F. (1993). Predators and prey: A new ecology of competition. Harvard Business Review, 71, 75–83.

    Google Scholar 

  • Moore, J. (1996). The death of competition: Leadership and strategy in the age of business ecosystems. New York: Harper Business.

    Google Scholar 

  • Nambisan, S., & Baron, R. A. (2013). Entrepreneurship in innovation ecosystems: Entrepreneurs’ self-regulatory processes and their implications for new venture success. Entrepreneurship Theory and Practice, 37(5), 1071–1097.

    Article  Google Scholar 

  • Neck, H. M., Meyer, G. D., Cohen, B., & Corbett, A. C. (2004). An entrepreneurial system view of new venture creation. Journal of Small Business Management, 42, 190–208.

    Article  Google Scholar 

  • Nelson, R. R., & Winter, S. G. (1982). An evolutionary theory of economic change. Cambridge, MA: Bellknap Press.

    Google Scholar 

  • Newman, M. E. J. (2006). Modularity and community structure in networks. PNAS, 103, 8577–8582.

    Article  Google Scholar 

  • Oh, D.-S., Phillips, F., Park, S., & Lee, E. (2016). Innovation ecosystems: A critical examination. Technovation, 54, 1–6.

    Article  Google Scholar 

  • *Öner, M. A., & Kunday, Ö. (2016). A study on Schumpeterian and Kirznerian entrepreneurship in Turkey: 2006–2013. Technological Forecasting and Social Change, 102, 62–71.

    Article  Google Scholar 

  • Pahnke, E. C., Katila, R., & Eisenhardt, K. M. (2015). Who takes you to the dance? How partners’ institutional logics influence innovation in young firms. Administrative Science Quarterly, 60(4), 596–633.

    Article  Google Scholar 

  • Paradkar, A., Knight, J., & Hansen, P. (2015). Innovation in start-ups: Ideas filling the void or ideas devoid of resources and capabilities? Technovation, 41–42, 1–10.

    Article  Google Scholar 

  • Park, S. H., & Russo, M. V. (1996). When competition eclipses cooperation: An event history analysis of joint venture failure. Management Science, 42(6), 875–890.

    Article  MATH  Google Scholar 

  • Peltoniemi, M. (2006). Preliminary theoretical framework for the study of business ecosystems. Emergence: Complexity & Organization, 8(1), 10–19.

    Google Scholar 

  • *Pierce, L. (2009). Big losses in ecosystem niches: How core firm decisions drive complementary product shakeouts. Strategic Management Journal, 30, 323–347.

    Article  Google Scholar 

  • Pisano, G. P., & Teece, D. J. (2007). How to capture value from innovation: Shaping intellectual property and industry architecture. California Management Review, 50(1), 278–296.

    Article  Google Scholar 

  • *Powell, W. W., Koput, K. W., & Smith-Doerr, L. (1996). Interorganizational collaboration and the locus of innovation: Networks of learning in biotechnology. Administrative Science Quarterly, 41, 116–145.

    Article  Google Scholar 

  • Prahalad, C. K., & Hamel, G. (1990). The core competence of the corporation. Harvard Business Review, 68(3), 79–91.

    Google Scholar 

  • Rousseeuw, P. J. (1987). Silhouettes: A graphical aid to the interpretation and validation of cluster analysis. Journal of Computational and Applied Mathematics, 20, 53–65.

    Article  MATH  Google Scholar 

  • Salanti, G., Giovane, C. D., Chaimani, A., Caldwell, D. M., & Higgins, J. P. T. (2014). Evaluating the quality of evidence from a network meta-analysis. PLoS ONE, 9, e99682.

    Article  Google Scholar 

  • *Samila, S., & Sorenson, O. (2010). Venture capital as a catalyst to commercialization. Research Policy, 39, 1348–1360.

    Article  Google Scholar 

  • Shiau, W.-L., & Dwivedi, Y. K. (2013). Citation and co-citation analysis to identify core and emerging knowledge in electronic commerce research. Scientometrics, 94, 1317–1337.

    Article  Google Scholar 

  • Stam, E. (2015). Entrepreneurial ecosystems and regional policy: A sympathetic critique. European Planning Studies, 23, 1759–1769.

    Article  Google Scholar 

  • Stam, W., Arzlanian, S., & Elfring, T. (2014). Social capital of entrepreneurs and small firm performance: A meta-analysis of contextual and methodological moderators. Journal of Business Venturing, 29, 152–173.

    Article  Google Scholar 

  • Teece, D. J. (1986). Profiting from technological innovation: Implications for integration, collaboration, licensing and public policy. Research Policy, 15, 285–305.

    Article  Google Scholar 

  • Teece, D. J. (1994). The dynamic capabilities of firms: an introduction. Industrial and Corporate Change, 3, 537–556.

    Article  Google Scholar 

  • Teece, D. J. (2007). Explicating dynamic capabilities: the nature and microfoundations of (sustainable) enterprise performance. Strategic Management Journal, 28(13), 1319–1350.

    Article  Google Scholar 

  • Tripsas, M. (1997). Unraveling the process of creative destruction: Complementary assets and incumbent survival in the typesetter industry. Strategic Management Journal, 18, 119–142.

    Article  Google Scholar 

  • Tushman, M. L., & Anderson, P. (1986). Technological discontinuities and organizational environments. Administrative Science Quarterly, 31(3), 439–465.

    Article  Google Scholar 

  • *Vakili, K. (2016). Collaborative promotion of technology standards and the impact on innovation, industry structure, and organizational capabilities: Evidence from modern patent pools. Organization Science, 27(6), 1504–1524.

    Article  Google Scholar 

  • *Wei, Z., Yang, D., Sun, B., & Gu, Meng. (2014). The fit between technological innovation and business model design for firm growth: Evidence from China. R&D Management, 44, 288–305.

    Article  Google Scholar 

  • White, I. R. (2015). Network meta-analysis. The Stata Journal, 4, 951–985.

    Google Scholar 

  • Witte, P., Slack, B., Keesman, M., Jugie, J.-H., & Wiegmans, B. (2017). Facilitating start-ups in port-city innovation ecosystems: A case study ofMontreal and Rotterdam. Journal of Transport Geography. doi:10.1016/j.jtrangeo.2017.03.006.

    Google Scholar 

  • Zhang, Z. (2013). Mutualism or cooperation among competitors promotes coexistence and competitive ability. Ecological Modelling, 164, 271–282.

    Article  Google Scholar 

Download references

Acknowledgements

This study is supported by the Grants from National Natural Science Foundation of China (Nos. 71673261 and 71373254) and from The Research Team of Natural Science Foundation of Guangdong Province in China (2016A030312005). The authors are very grateful for the valuable comments and suggestions from two anonymous reviewers and the Editor-in-Chief of the Journal Scientometrics, which significantly improved the quality of the paper.

Author information

Authors and Affiliations

  1. School of Economics & Management, University of Chinese Academy of Sciences, Beijing, China

    Chao Zhang & Jiancheng Guan

  2. School of Business Administration, South China University of Technology, Guangzhou, China

    Jiancheng Guan

Authors
  1. Chao Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jiancheng Guan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jiancheng Guan.

Appendices

Appendix 1: Search queries for innovation and entrepreneurial ecosystems

(TS = (“ecosystem*”) AND TS = (“innovation” OR “entrepreneur*” OR “value creat* “ OR “business “ OR “platform “ OR “collaborat*” OR “coopetit*” OR “network”)) AND LANGUAGE: (English).

Timespan: 1996–2016. Indexes: SCI-EXPANDED, SSCI, CPCI-S.

(TS = (“ecosystem*”) AND TS = (“innovation” OR “entrepreneur*” OR “value creat* “ OR “business “ OR “platform “ OR “collaborat*” OR “coopetit*” OR “network”)) AND LANGUAGE: (English) AND DOCUMENT TYPES: (Article).

Timespan: 1996–2016. Indexes: SCI-EXPANDED, SSCI, CPCI-S.

(TS = (“ecosystem*”) AND TS = (“innovation” OR “entrepreneur*” OR “value creat* “ OR “business “ OR “platform “ OR “collaborat*” OR “coopetit*” OR “network”)) AND LANGUAGE: (English) AND DOCUMENT TYPES: (Review).

Timespan: 1996–2016. Indexes: SCI-EXPANDED, SSCI, CPCI-S.

Appendix 2: Coding results

Overview of studies in the network meta-analysis (The 24 finalized studies are marked by * in the following reference list).

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, C., Guan, J. How to identify metaknowledge trends and features in a certain research field? Evidences from innovation and entrepreneurial ecosystem. Scientometrics 113, 1177–1197 (2017). https://doi.org/10.1007/s11192-017-2503-y

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11192-017-2503-y

Keywords

Search

Navigation