The Developmental Routes Followed by Smartphone Technology Over Time (2008-2018 Period)
Year 2024,
, 369 - 395, 30.06.2024
Bilal Kargı
,
Mario Coccia
Abstract
This paper's aim is to identify and examine the key technical attributes that propel product innovation, facilitating the prediction of swiftly evolving technological trajectories. The present study introduces the hedonic pricing method and various other approaches, which have been employed in the context of smartphone technology, comprising a sample of 738 models spanning from 2008 to 2018. The findings indicate that the progression of smartphone technology is primarily steered by technical features related to the perceptual experience of users, including the resolution in total pixels, the first and second camera in megapixels (Mpx), and storage capacity (RAM and memory in gigabytes, Gb). Implications for innovation product management are also deliberated upon.
Supporting Institution
yok
References
- Arthur, B.W. (2009). The Nature of Technology. What it is and How it Evolves, Penguin Books: London.
- Arthur, B.W., & Polak, W. (2006). The evolution of technology within a simple computer model, Complexity, 11(5), 23-31. doi. https://doi.org/10.1002/cplx.20130
- Bhalla, M., & Proffitt, D.R. (1999). Visual-motor recalibration in geographical slant perception. Journal of Experimental Psychology. Human Perception and Performance, 25(4), 1076-1096. doi. https://psycnet.apa.org/doi/10.1037/0096-1523.25.4.1076
- Carranza, J.E. (2010). Product innovation and adoption in market equilibrium: The case of digital cameras, International Journal of Industrial Organization, 28(6), 604-618. doi. https://doi.org/10.1016/j.ijindorg.2010.02.003
- Coccia, M. (2005). Measuring intensity of technological change: The seismic approach. Technological Forecasting and Social Change, 72(2), 117-144. doi. https://doi.org/10.1016/j.techfore.2004.01.004
- Coccia, M. (2005a). Technometrics: Origins, historical evolution and new direction. Technological Forecasting & Social Change, 72(8), 944-979. doi. https://doi.org/10.1016/j.techfore.2005.05.011
- Coccia, M. (2017). Sources of disruptive technologies for industrial change. L’industria –rivista di economia e politica industriale, 38(1), 97-120.
- Coccia, M. (2017a). Sources of technological innovation: Radical and incremental innovation problem-driven to support competitive advantage of firms. Technology Analysis & Strategic Management, 29(9), 1048-1061. doi. https://doi.org/10.1080/09537325.2016.1268682
- Coccia M. 2017b. Fundamental Interactions as Sources of the Evolution of Technology (May 25, 2017). Working Paper CocciaLab, No.23. Available at: Electronic Library SSRN: https://ssrn.com/abstract=2974043
- Coccia, M. (2018). A Theory of classification and evolution of technologies within a Generalized Darwinism, Technology Analysis & Strategic Management, doi. http://dx.doi.org/10.1080/09537325.2018.1523385
- Coccia, M., & Wang, L. (2015). Path-breaking directions of nanotechnology-based chemotherapy and molecular cancer therapy, Technological Forecasting and Social Change, 94, 155-169. doi. https://doi.org/10.1016/j.techfore.2014.09.007
- Coccia, M., & Wang, L. (2016). Evolution and convergence of the patterns of international scientific collaboration, Proceedings of the National Academy of Sciences of the United States of America, 113(8), 2057-2061, www.pnas.org/cgi/doi/10.1073/pnas.1510820113
- Daim, T.U., Byung-Sun, Y., Lindenberg, J., Grizzi, R., Estep, J., & Oliver, T. (2018). Strategic roadmapping of robotics technologies for the power industry: A multicriteria technology assessment, Technological Forecasting and Social Change, 131, 49-66. doi. https://doi.org/10.1016/j.techfore.2017.06.006
- Erwin, D.H., & Krakauer, D.C. (2004). Evolution. Insights into innovation. Science, 304(5674), 1114-1119. doi. https://doi.org/10.1126/science.1099385
- Farmer, J.D., & Lafond, F. (2016). How predictable is technological progress? Research Policy, 45, 647-665. doi. https://doi.org/10.1016/j.respol.2015.11.001
- Farrell, C.J. (1993). A theory of technological progress, Technological Forecasting and Social Change, 44(2), 161-178. doi. https://doi.org/10.1016/0040-1625(93)90025-3
- Faust, K. (1990). Early identification of technological advances on the basis of patent data, Scientometrics, 19(5-6), 473-480. doi. https://doi.org/10.1007/BF02020708
- Gherardi, M., & Rotondo, P. (2016). Measuring logic complexity can guide pattern discovery in empirical systems, Complexity, 21(S2), 397-408. doi. https://doi.org/10.1002/cplx.21819
- Hall, B.H., & Jaffe, A.B. (2018). Measuring science, technology, and innovation: A review. Annals of Science and Technology Policy, 2(1), 1-74. doi. http://dx.doi.org/10.1561/110.00000005
- Iriki, A., Tanaka, M., & Iwamura, Y. (1996). Attention-induced neuronal activity in the monkey somatosensory cortex revealed by pupillometrics. Neuroscience Research, 25(2), 173-181. doi. https://doi.org/10.1016/S0168-0102(96)01043-7
- Koh, H., & Magee, C.L. (2006). A functional approach for studying technological progress: Application to information technology. Technological Forecasting and Social Change, 73(9), 1061-1083. doi. https://doi.org/10.1016/j.techfore.2006.06.001
- Koh, H., & Magee, C.L. (2008). A functional approach for studying technological progress: Extension to energy technology. Technological Forecasting and Social Change, 75(6), 735-758. doi. https://doi.org/10.1016/j.techfore.2007.05.007
- Lacohée, H., Wakeford, N., & Pearson, I. (2003). A social history of the mobile telephone with a view of its future, BT Technology Journal, 21(3), 203–211. doi. https://doi.org/10.1023/A:1025187821567
- Lee, H.P., & Lim, S.P. (2014). Comparative studies of perceived vibration strength for commercial mobile phones. Applied Ergonomics, 45(3), 807-810. doi. https://doi.org/10.1016/j.apergo.2013.07.006
- Leutgeb, S., Leutgeb, J.K., Barnes, C.A., Moser, E.I., McNaughton, B.L., & Moser, M. (2005). Independent codes for spatial and episodic memory in hippocampal neuronal ensembles. Science, 309(5734), 619-623. doi. https://doi.org/10.1126/science.1114037
- Linstone, H.A. (2004). From information age to molecular age, Technological Forecasting and Social Change, 71(2), 187-196. doi. https://doi.org/10.1016/j.techfore.2003.09.004
- Magee, C.L., Basnet, S., Funk, J.L., & Benson, C.L. (2016). Quantitative empirical trends in technical performance. Technological Forecasting & Social Change, http://doi.org/10.1016/j.techfore.2015.12.011
- Magee, C.L. (2012). Towards quantification of the role of materials innovation in overall technological development. Complexity, 18(1), 10-25. doi. https://doi.org/10.1002/cplx.20309
- McNerney, J., Farmer, J.D., Redner, S., & Trancik, J.E. (2011). Role of design complexity in technology improvement, Proceedings of the National Academy of Sciences, 108(22), 9008-9013. doi. https://doi.org/10.1073/pnas.1017298108
- Nagy, B., Farmer, J.D., Bui, Q.M. & Trancik, J.E. (2013). Statistical basis for predicting technological progress. PloS One, 8(2), e52669. doi. https://doi.org/10.1371/journal.pone.0052669
- Punto, C. (2018). Schede Tecniche Cellulari, https://puntocellulare.it/schede-cellulari/cellulari.html (accessed 18th June 2018).
- Sahal, D. (1981). Patterns of Technological Innovation. Addison-Wesley Publishing Company, Inc., Reading, Massachusetts.
- Sahal, D. (1985). Foundations of technometrics, Technological Forecasting & Social Change, 27(1), 1-37. doi. https://doi.org/10.1016/0040-1625(85)90002-2
- Saviotti, P. (1985). An approach to the measurement of technology based on the hedonic price method and related methods, Technological Forecasting & Social Change, 27(2-3), 309-334. doi. https://doi.org/10.1016/0040-1625(85)90064-2
- Simon, H.A. (1962). The architecture of complexity, Proceeding of the American Philosophical Society, 106(6), 476-482.
- Tran, T.A., & Daim, T.U. (2008). A taxonomic review of methods and tools applied in technology assessment, Technological Forecasting and Social Change, 75(9), 1396-1405. doi. https://doi.org/10.1016/j.techfore.2008.04.004
- Triplett, J.E. (1985). Measuring technological change with characteristics-space techniques, Technological Forecasting & Social Change, 27(2-3), 283-307. doi. https://doi.org/10.1016/0040-1625(85)90063-0
- Triplett, J.E. (2006). Handbook on Hedonic Indexes and Quality Adjustments in Price Indexes: Special Application to Information Technology Products, OECD Publishing, Paris, https://doi.org/10.1787/9789264028159-en
- Wang, C.C., Sung, H.Y., Huang, M.H. (2016). Technological evolution seen from the USPC reclassifications, Scientometrics, 107(2), 537-553. doi. https://doi.org/10.1007/s11192-016-1851-3
- Watanabe, C., Kanno, G., & Tou, Y. (2012). Inside the learning dynamism inducing the resonance between innovation and high-demand consumption: A case of Japan's high-functional mobile phones, Technological
Forecasting & Social Change, 79(7), 1292-1311. doi. https://doi.org/10.1016/j.techfore.2012.03.003
- Watanabe, C., Moriyama, K., & Shin, J. (2009). Functionality development dynamism in a diffusion trajectory: a case of Japan's mobile phones development, Technol. Technological Forecasting & Social Change, 76(6), 737-753. doi. https://doi.org/10.1016/j.techfore.2008.06.001
- Woods, B. (2018). Smartphone screens explained: display types, resolutions and more. https://www.androidpit.com/smartphone-displays-explained (accessed 18th June, 2018)
- Wright, G. (1997). Towards a more historical approach to technological change, The Economic Journal, 107, 1560-1566. doi. https://doi.org/10.1098/rsif.2013.1190
Akıllı Telefon Teknolojisinin Zaman İçinde İzlediği Gelişim Rotaları (2008-2018 Dönemi)
Year 2024,
, 369 - 395, 30.06.2024
Bilal Kargı
,
Mario Coccia
Abstract
Bu makalenin amacı, ürün yeniliğini teşvik eden ve hızla gelişen teknolojik yörüngelerin tahminini kolaylaştıran temel teknik özellikleri belirlemek ve incelemektir. Bu çalışma, 2008'den 2018'e kadar uzanan 738 modellik bir örneklemi kapsayan, akıllı telefon teknolojisi bağlamında kullanılan hedonik fiyatlandırma yöntemini ve diğer çeşitli yaklaşımları tanıtmaktadır. Bulgular, akıllı telefon teknolojisindeki ilerlemenin öncelikle teknik faktörler tarafından yönlendirildiğini göstermektedir. Toplam piksel cinsinden çözünürlük, megapiksel (Mpx) cinsinden birinci ve ikinci kamera ve depolama kapasitesi (gigabayt cinsinden RAM ve bellek, Gb) dahil olmak üzere kullanıcıların algısal deneyimiyle ilgili özellikler. İnovasyon ürün yönetimine yönelik çıkarımlar da tartışılmaktadır.
References
- Arthur, B.W. (2009). The Nature of Technology. What it is and How it Evolves, Penguin Books: London.
- Arthur, B.W., & Polak, W. (2006). The evolution of technology within a simple computer model, Complexity, 11(5), 23-31. doi. https://doi.org/10.1002/cplx.20130
- Bhalla, M., & Proffitt, D.R. (1999). Visual-motor recalibration in geographical slant perception. Journal of Experimental Psychology. Human Perception and Performance, 25(4), 1076-1096. doi. https://psycnet.apa.org/doi/10.1037/0096-1523.25.4.1076
- Carranza, J.E. (2010). Product innovation and adoption in market equilibrium: The case of digital cameras, International Journal of Industrial Organization, 28(6), 604-618. doi. https://doi.org/10.1016/j.ijindorg.2010.02.003
- Coccia, M. (2005). Measuring intensity of technological change: The seismic approach. Technological Forecasting and Social Change, 72(2), 117-144. doi. https://doi.org/10.1016/j.techfore.2004.01.004
- Coccia, M. (2005a). Technometrics: Origins, historical evolution and new direction. Technological Forecasting & Social Change, 72(8), 944-979. doi. https://doi.org/10.1016/j.techfore.2005.05.011
- Coccia, M. (2017). Sources of disruptive technologies for industrial change. L’industria –rivista di economia e politica industriale, 38(1), 97-120.
- Coccia, M. (2017a). Sources of technological innovation: Radical and incremental innovation problem-driven to support competitive advantage of firms. Technology Analysis & Strategic Management, 29(9), 1048-1061. doi. https://doi.org/10.1080/09537325.2016.1268682
- Coccia M. 2017b. Fundamental Interactions as Sources of the Evolution of Technology (May 25, 2017). Working Paper CocciaLab, No.23. Available at: Electronic Library SSRN: https://ssrn.com/abstract=2974043
- Coccia, M. (2018). A Theory of classification and evolution of technologies within a Generalized Darwinism, Technology Analysis & Strategic Management, doi. http://dx.doi.org/10.1080/09537325.2018.1523385
- Coccia, M., & Wang, L. (2015). Path-breaking directions of nanotechnology-based chemotherapy and molecular cancer therapy, Technological Forecasting and Social Change, 94, 155-169. doi. https://doi.org/10.1016/j.techfore.2014.09.007
- Coccia, M., & Wang, L. (2016). Evolution and convergence of the patterns of international scientific collaboration, Proceedings of the National Academy of Sciences of the United States of America, 113(8), 2057-2061, www.pnas.org/cgi/doi/10.1073/pnas.1510820113
- Daim, T.U., Byung-Sun, Y., Lindenberg, J., Grizzi, R., Estep, J., & Oliver, T. (2018). Strategic roadmapping of robotics technologies for the power industry: A multicriteria technology assessment, Technological Forecasting and Social Change, 131, 49-66. doi. https://doi.org/10.1016/j.techfore.2017.06.006
- Erwin, D.H., & Krakauer, D.C. (2004). Evolution. Insights into innovation. Science, 304(5674), 1114-1119. doi. https://doi.org/10.1126/science.1099385
- Farmer, J.D., & Lafond, F. (2016). How predictable is technological progress? Research Policy, 45, 647-665. doi. https://doi.org/10.1016/j.respol.2015.11.001
- Farrell, C.J. (1993). A theory of technological progress, Technological Forecasting and Social Change, 44(2), 161-178. doi. https://doi.org/10.1016/0040-1625(93)90025-3
- Faust, K. (1990). Early identification of technological advances on the basis of patent data, Scientometrics, 19(5-6), 473-480. doi. https://doi.org/10.1007/BF02020708
- Gherardi, M., & Rotondo, P. (2016). Measuring logic complexity can guide pattern discovery in empirical systems, Complexity, 21(S2), 397-408. doi. https://doi.org/10.1002/cplx.21819
- Hall, B.H., & Jaffe, A.B. (2018). Measuring science, technology, and innovation: A review. Annals of Science and Technology Policy, 2(1), 1-74. doi. http://dx.doi.org/10.1561/110.00000005
- Iriki, A., Tanaka, M., & Iwamura, Y. (1996). Attention-induced neuronal activity in the monkey somatosensory cortex revealed by pupillometrics. Neuroscience Research, 25(2), 173-181. doi. https://doi.org/10.1016/S0168-0102(96)01043-7
- Koh, H., & Magee, C.L. (2006). A functional approach for studying technological progress: Application to information technology. Technological Forecasting and Social Change, 73(9), 1061-1083. doi. https://doi.org/10.1016/j.techfore.2006.06.001
- Koh, H., & Magee, C.L. (2008). A functional approach for studying technological progress: Extension to energy technology. Technological Forecasting and Social Change, 75(6), 735-758. doi. https://doi.org/10.1016/j.techfore.2007.05.007
- Lacohée, H., Wakeford, N., & Pearson, I. (2003). A social history of the mobile telephone with a view of its future, BT Technology Journal, 21(3), 203–211. doi. https://doi.org/10.1023/A:1025187821567
- Lee, H.P., & Lim, S.P. (2014). Comparative studies of perceived vibration strength for commercial mobile phones. Applied Ergonomics, 45(3), 807-810. doi. https://doi.org/10.1016/j.apergo.2013.07.006
- Leutgeb, S., Leutgeb, J.K., Barnes, C.A., Moser, E.I., McNaughton, B.L., & Moser, M. (2005). Independent codes for spatial and episodic memory in hippocampal neuronal ensembles. Science, 309(5734), 619-623. doi. https://doi.org/10.1126/science.1114037
- Linstone, H.A. (2004). From information age to molecular age, Technological Forecasting and Social Change, 71(2), 187-196. doi. https://doi.org/10.1016/j.techfore.2003.09.004
- Magee, C.L., Basnet, S., Funk, J.L., & Benson, C.L. (2016). Quantitative empirical trends in technical performance. Technological Forecasting & Social Change, http://doi.org/10.1016/j.techfore.2015.12.011
- Magee, C.L. (2012). Towards quantification of the role of materials innovation in overall technological development. Complexity, 18(1), 10-25. doi. https://doi.org/10.1002/cplx.20309
- McNerney, J., Farmer, J.D., Redner, S., & Trancik, J.E. (2011). Role of design complexity in technology improvement, Proceedings of the National Academy of Sciences, 108(22), 9008-9013. doi. https://doi.org/10.1073/pnas.1017298108
- Nagy, B., Farmer, J.D., Bui, Q.M. & Trancik, J.E. (2013). Statistical basis for predicting technological progress. PloS One, 8(2), e52669. doi. https://doi.org/10.1371/journal.pone.0052669
- Punto, C. (2018). Schede Tecniche Cellulari, https://puntocellulare.it/schede-cellulari/cellulari.html (accessed 18th June 2018).
- Sahal, D. (1981). Patterns of Technological Innovation. Addison-Wesley Publishing Company, Inc., Reading, Massachusetts.
- Sahal, D. (1985). Foundations of technometrics, Technological Forecasting & Social Change, 27(1), 1-37. doi. https://doi.org/10.1016/0040-1625(85)90002-2
- Saviotti, P. (1985). An approach to the measurement of technology based on the hedonic price method and related methods, Technological Forecasting & Social Change, 27(2-3), 309-334. doi. https://doi.org/10.1016/0040-1625(85)90064-2
- Simon, H.A. (1962). The architecture of complexity, Proceeding of the American Philosophical Society, 106(6), 476-482.
- Tran, T.A., & Daim, T.U. (2008). A taxonomic review of methods and tools applied in technology assessment, Technological Forecasting and Social Change, 75(9), 1396-1405. doi. https://doi.org/10.1016/j.techfore.2008.04.004
- Triplett, J.E. (1985). Measuring technological change with characteristics-space techniques, Technological Forecasting & Social Change, 27(2-3), 283-307. doi. https://doi.org/10.1016/0040-1625(85)90063-0
- Triplett, J.E. (2006). Handbook on Hedonic Indexes and Quality Adjustments in Price Indexes: Special Application to Information Technology Products, OECD Publishing, Paris, https://doi.org/10.1787/9789264028159-en
- Wang, C.C., Sung, H.Y., Huang, M.H. (2016). Technological evolution seen from the USPC reclassifications, Scientometrics, 107(2), 537-553. doi. https://doi.org/10.1007/s11192-016-1851-3
- Watanabe, C., Kanno, G., & Tou, Y. (2012). Inside the learning dynamism inducing the resonance between innovation and high-demand consumption: A case of Japan's high-functional mobile phones, Technological
Forecasting & Social Change, 79(7), 1292-1311. doi. https://doi.org/10.1016/j.techfore.2012.03.003
- Watanabe, C., Moriyama, K., & Shin, J. (2009). Functionality development dynamism in a diffusion trajectory: a case of Japan's mobile phones development, Technol. Technological Forecasting & Social Change, 76(6), 737-753. doi. https://doi.org/10.1016/j.techfore.2008.06.001
- Woods, B. (2018). Smartphone screens explained: display types, resolutions and more. https://www.androidpit.com/smartphone-displays-explained (accessed 18th June, 2018)
- Wright, G. (1997). Towards a more historical approach to technological change, The Economic Journal, 107, 1560-1566. doi. https://doi.org/10.1098/rsif.2013.1190