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Articles

‘Smart building’ technology network analysis: applying core–periphery structure analysis

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Pages 1-11 | Received 10 Nov 2014, Accepted 23 Sep 2015, Published online: 01 Dec 2015

References

  • Abbas, A., Zhang, L., & Khan, S. U. (2014). A literature review on the state-of-the-art in patent analysis. World Patent Information, 37, 3–13.
  • Agarwal, Y., Balaji, B., Gupta, R., Lyles, J., Wei, M., & Weng, T. (2010). Occupancy-driven energy management for smart building automation. In Proceedings of the 2nd ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Building, BuildSys ‘10 (pp. 1–6). New York: ACM.
  • Allerding, F., Mauser, I., & Schmeck, H. (2014). Customizable energy management in smart buildings using evolutionary algorithms. In 17th European Conference, EvoApplications 2014 (pp. 153–164).
  • Balconi, M., & Laboranti, A. (2006). University–industry interactions in applied research: The case of microelectronics. Research Policy, 35(10), 1616–1630.
  • Beaudry, C., & Schiffauerova, A. (2011). Impacts of collaboration and network indicators on patent quality: The case of Canadian nanotechnology innovation. European Management Journal, 29(5), 362–376.
  • Behkami, N. A., & Daim, T. U. (2012). Research forecasting for health information technology (HIT), using technology intelligence. Technological Forecasting & Social Change, 79(3), 498–508.
  • Borgatti, S. P. (2005). Centrality and network flow. Social Networks, 27(1), 55–71.
  • Borgatti, S. P., & Everett, M. G. (1999). Models of core–periphery structures. Social Networks, 21(4) 375–395.
  • Breschi, S., Cassi, L., Malerba, F., & Vonortas, N. S. (2009). Networked research: European policy intervention in ICTs. Technology Analysis and Strategic Management, 21(7), 833–857.
  • Buckman, A. H., Mayfield, M., & Beck, S. B. M. (2014). What is a smart building? Smart and Sustainable Built Environment, 3(2), 92–109.
  • Calero, C., van Leeuwen, T., & Tijssen, R. (2007). Research cooperation within the bio-pharmaceutical industry: Network analyses of copublications within and between firms. Scientometrics, 71, 87–99.
  • Chen, S.-H., Huang, M., & Chen, D. (2012). Identifying and visualizing technology evolution: A case study of smart grid technology. Technological Forecasting & Social Change, 79(6), 1099–1110.
  • Chen, J. K. C., Wang, M.-Y., Chen, Y.-R., & Chen, Y. (2012). Exploring knowledge flows of network on patent of dye sensitized solar cell. In Proceedings of Technology Management for Emerging Technologies (PICMET 2012), 29 July–2 August 2012, Vancouver (pp. 927–940).
  • Chi, R., & Suthers, D. Assessing intercultural communication competence as a relational construct using social network analysis. International Journal of Intercultural Relations 48, 108–119.
  • Choi, C., Kim, S., & Park, Y. (2007). A patent-based cross impact analysis for quantitative estimation of technological impact: The case of information and communication technology. Technological Forecasting & Social Change, 74(8), 1296–1314.
  • Chung, Y.-W., Wang, J., Ajayi, O., Biresaw, G., Cao, J., Hua, D., … Qureshi, F. (2011). Transformative research issues and opportunities in energy efficiency. Current Opinion in Solid State and Materials Science, 15(1), 16–19.
  • Dolfsma, W., & Leydesdorff, L. (2011). Innovation systems as patent networks: The Netherlands, India and nanotech. Innovation: Management. Policy & Practice, 13, 311–326.
  • Duysters, G., Hagedoorn, J., & Lemmens, C. (2003). The effect of alliance block membership on innovative performance. Revue d’Économie Industrielle, 103, 59–70. doi:10.3406/rei.2003.3108
  • EIA. (2014). How much energy is consumed in residential and commercial buildings in the United States? Washington, DC: US Energy Information Administration (EIA).
  • El-hawary, M. E. (2014). The smart grid – state-of-the-art and future trends. Electric Power Components and Systems, 42(3–4), 239–250.
  • Fantacci, R., Pecorella, T., Viti, R., Carlini, C., & Obino, P. (2013). Enabling technologies for smart buildings, what’s missing? In Proceedings of the 2013 AEIT Annual Conference, 3–5 October 2013, Mondello, Palermo, Italy (pp. 1–5).
  • Fontana, R., Nuvolari, A., & Verspagen, B. (2009). Mapping technological trajectories as patent citation networks. An application to data communication standards. Economics of Innovation and New Technology 18(4), 311–336.
  • Gao, X., Guan, J., & Rousseau, R. (2011). Mapping collaborative knowledge production in China using patent co-inventorships. Scientometrics 88(2), 343–362.
  • Golden, B., McMahan, C., Hakim, D., & Shnekendorf, E. (2008). Utility console for controlling energy resources. US20080167756 A1.
  • Grady, C. A., He, X., & Peeta, S. (2015). Integrating social network analysis with analytic network process for international development project selection. Expert Systems with Applications, 42(12), 5128–5138.
  • He, Z.-L., & Wong, P.-K. (2004). Exploration vs. exploitation: An empirical test of the ambidexterity hypothesis. Organization Science, 15(4), 481–494. doi:10.1287/orsc.1040.0078
  • Ho, Y., & Chiu, H. (2011). A social network analysis of leading semiconductor companies’ knowledge flow network. Asia Pacific Journal of Management, 30(4), 1265–1283.
  • Hu, X., Rousseau, R., & Chen, J. (2012). A new approach for measuring the value of patents based on structural indicators for ego patent citation networks. Journal of the American Society for Information Science and Technology, 63(9), 1834–1842.
  • Jun, S., & Park, S. S. (2013). Examining technological innovation of Apple using patent analysis. Industrial Management & Data Systems, 113(6), 890–907.
  • Katila, R., & Ahuja, G. (2002). Something old, something new: A longitudinal study of search behavior and new product introduction. Academy of Management Journal, 45(6), 1183–1194. doi:10.2307/3069433.
  • Kawonga, M., Blaauw, D., & Fonn, S. (2015). Exploring the use of social network analysis to measure communication between disease programme and district managers at sub-national level in South Africa. Social Science & Medicine, 135, 1–14.
  • Kim, E., Cho, Y., & Kim, W. (2014). Dynamic patterns of technological convergence in printed electronics technologies: Patent citation network. Scientometrics 98(2), 975–998.
  • Kim, H., & Song, J. (2013). Social network analysis of patent infringement lawsuits. Technological Forecasting & Social Change, 80(5), 944–955.
  • Kim, H., Stumpf, A., & Kim, W. (2011). Analysis of an energy efficient building design through data mining approach. Automation in Construction, 20(1), 37–43.
  • Lane, M. E. (2009). Method and apparatus for controlling power consumption. US 20090240381 A1.
  • Li, Y., Vanhaverbeke, W., & Schoenmakers, W. (2008). Exploration and exploitation in innovation: Reframing the interpretation. Creativity and Innovation Management, 17(2), 107–126.
  • Lin, H.-C., Chan, T.-Y., & Ien, C.-H. (2013). Mapping of future technology themes in sustainable energy. Foresight, 15(1), 54–73.
  • Lo, T.-W., Yang, W.-G., Hung, T.-S., & Lai, K.-K. (2011). Technological spillovers of transferred inventors from the perspective of Social Network Analysis (SNA). African Journal of Business Management 5(20), 8192–8203.
  • Madani, F., & Khormaei, R. (2013). Overview of evolution in study of external technology search. In Proceedings of Technology Management in the IT-Driven Services (PICMET 2013), 28 July-1 August 2013 (pp. 2058–2060). San Jose, CA: IEEE.
  • Maggioni, M. A., Uberti, T. E., & Usai, S. (2011). Treating patents as relational data: Knowledge transfers and spillovers across Italian provinces. Ind. Innov., 18(1), 39–67.
  • Mauser, I., Feder, J., Müller, J., & Schmeck, H. (2015). Evolutionary optimization of smart buildings with interdependent devices. In Applications of Evolutionary Computation: 18th European Conference, EvoApplications 2015 (pp. 239–251). New York: Springer.
  • Meisel, M. K., Clifton, A. D., MacKillop, J., & Goodie, A. S. (2015). A social network analysis approach to alcohol use and co-occurring addictive behavior in young adults. Addictive Behaviors, 51, 72–79.
  • Morvaj, B., Lugaric, L., Member, G. S., Krajcar, S., & Member, S. (2011). Demonstrating smart buildings and smart grid features in a smart energy city. In: Proceedings of the 3rd IEEE International Conference on Youth 2011 (pp. 1–8).
  • OECD. (2009). Smart sensor networks: Technologies and applications for green growth. Report DSTI/ICCP/IE(2009)4/FINAL.
  • Okamura, K., & Vonortas, N. S. (2006). European alliance and knowledge networks. Technology Analysis and Strategic Management, 18(5), 535–560.
  • Sankar, C. P., Asokan, K., & Kumar, K. S. (2015). Exploratory social network analysis of affiliation networks of Indian listed companies. Social Networks, 43, 113–120.
  • Scott, J. (Ed.). (2002). Social Network Analysis: A Handbook (2nd ed.). London: Sage.
  • Scott, J., & Carrington, P. J. (Eds.). (2011). Sage Handbook of Social Network Analysis. London: Sage. doi:10.4135/9781446294413
  • Shaikh, P. H., Nor, N. B. M., Nallagownden, P., Elamvazuthi, I., & Ibrahim, T. (2014). A review on optimized control systems for building energy and comfort management of smart sustainable buildings. Renewable & Sustainable Energy Reviews, 34, 409–429.
  • Stantchev, V., Prieto-González, L., & Tamm, G. (2015). Cloud computing service for knowledge assessment and studies recommendation in crowdsourcing and collaborative learning environments based on social network analysis. Computers in Human Behavior, Part B, 51, 762–770.
  • Suo, Q., Sun, S., Hajli, N., & Love, P. E. D. (2015). User ratings analysis in social networks through a hypernetwork method. Expert Systems with Applications, 42(21), 7317–7325.
  • Tasdighi, M., Salamati, P. J., Rahimikian, A., Ieee, S. M., & Ghasemi, H. (2012). Energy management in a smart residential building. In 11th International Conference on Environment and Electrical Engineering (EEEIC), (pp. 128–133).
  • Tseng, C.-Y., & Ting, P.-H. (2013). Patent analysis for technology development of artificial intelligence: A country-level comparative study. Innovation: Management, Policy & Practice 15(4), 463–475.
  • von Wartburg, I., Teichert, T., & Rost, K. (2005). Inventive progress measured by multi-stage patent citation analysis. Reseach Policy, 34(10), 1591–1607. doi:10.1016/j.respol.2005.08.001
  • Wang, J.-C., Chiang, C., & Lin, S.-W. (2010). Network structure of innovation: Can brokerage or closure predict patent quality? Scientometrics, 84(3), 735–748.
  • Wang, C., Huang, M., & Chen, D. (2011). Evolution of technology dependence among leading semiconductor companies. Industrial Management & Data Systems, 111(7), 1136–1152.
  • Wang, M.-Y., Lo, H.-C., Liao, Y.-Y., & Lin, P.-Y. (2012). Determinants of patent renewal decisions by patent indicators and social network analysis: The case of the biotech industry in Taiwan and Korea. In Proceedings of the Technology Management for Emerging Technologies Conference (PICMET 2012), 29 July–2 August 2012, Vancouver (pp. 1060–1065).
  • Wassermann, K., & Faust, S. (1994). Social Network Analysis: Methods and Applications. Cambridge, UK: Cambridge University Press.
  • Weng, C. S. (2011). Identifying the core–periphery technological positions from affiliation networks: The network analysis of 2-mode. In Proceedings of the Technology Management for Emerging Technologies Conference ‘Technology Management in the Energy-Smart World’ (PICMET 2011), 31 July–4 August 2011, Portland, OR.
  • Weng, C., & Daim, T. U. (2011). Structural differentiation and its implications – core–periphery structure of the technological network. Journal of the Knowledge Economy, 3(4), 327–342.
  • Weng, C. S., Ou, Y.-K., & Lai, H. (2009). Core–periphery structure of the technological network. In Proceedings of the Technology Management for Emerging Technologies Conference ‘Technology Management in the Age of Fundamental Change’ (PICMET 2009), 2–6 August 2009, Portland, OR, Vols 1–5 (pp. 56–60).
  • Woradechjumroen, D., & Li, H. (2015). Building energy efficiency improvement via smart building solutions : Introduction to methodologies. In International Conference on Computer Information Systems and Industrial Applications (CISIA) (pp. 980–982).
  • Yoon, J., & Kim, K. (2012). TrendPerceptor: A property–function based technology intelligence system for identifying technology trends from patents. Expert Systems with Applications, 39(3), 2927–2938.
  • Yoon, B., & Park, Y. (2004). A text-mining-based patent network: Analytical tool for high-technology trend. Journal of High Technology Management Research, 15, 37–50.

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