Research on interaction of innovation spillovers in the AI, Fin-Tech, and IoT industries: considering structural changes accelerated by COVID-19
Tóm tắt
This paper aims to probe the influence of innovation spillovers in the artificial intelligence (AI) and financial technology (Fin-tech) industries on the value of the internet of things (IoT) companies. Python was utilized to download public information from Yahoo Finance, and then the GARCH model was used to extract the fluctuations of cross-industry innovation spillovers. Next, the Fama–French three-factor model was used to explore the interactive changes between variables. The panel data regression analysis indicates that the more firms accept innovation spillovers from other industries, the better the excess return; however, this effect differs because of industrial attributes and the environmental changes induced by COVID-19. Additionally, this study finds that investing in large-cap growth stocks of IoT firms is more likely to yield excess returns. Finally, the study yields lessons for policy leverage to accelerate the upgrading and transformation of innovation-interactive industries by referring to the practices of Singapore and South Korea.
Tài liệu tham khảo
Almeida H (2021) Liquidity management during the Covid-19 pandemic. Asia Pac J Financ Stud 50(1):7–24. https://doi.org/10.1111/ajfs.12322
Arrow KJ (1972) Economic welfare and the allocation of resources for invention. In: Rowley CK (ed) Readings in industrial economics. Palgrave, London
Aysun U, Yom Z (2021) R&D characteristics, innovation spillover, and technology-driven business cycles. J Ind Compet Trade 21:339–365. https://doi.org/10.1007/s10842-021-00358-4
Bali TG, Engle RF (2010) The intertemporal capital asset pricing model with dynamic conditional correlations. J Monetary Econ 57:377–390
Bareisis Z (2017) The internet of things and the opportunity for payments. J Paym Strategy Syst 11(3):236–247
Bernstein JI, Nadiri MI (1989) Research and development and intra-industry spillovers: an empirical application of dynamic duality. Rev Econ Stud 56(2):249–267. https://doi.org/10.2307/2297460
Bhayo J, Hameed S, Shah SA (2020) An efficient counter-based DDoS attack detection framework leveraging software defined Iot (SD-IoT). IEEE Access 8:221612–221631. https://doi.org/10.1109/ACCESS.2020.3043082
Black F (1972) Capital market equilibrium with restricted borrowing. J Bus 45:444–455
Blomstrom M, Persson H (1983) foreign investment and spillover efficiency in an underdeveloped economy: evidence from the Mexican manufacturing industry. World Dev 11:493–501. https://doi.org/10.1016/0305-750X(83)90016-5
Bloom N, Schankerman M, Van Reenen J (2013) Identifying technology spillovers and product market rivalry. Econometrica 81(4):1347–1393. https://doi.org/10.3982/ECTA9466
Bollerslev T (1986) General autoregressive conditional heteroscedasticity. J Econom 31:307–327. https://doi.org/10.1016/0304-4076(86)90063-1
Bollerslev T, Chou RY, Kroner K (1992) ARCH modeling in finance: a review of the theory and empirical evidence. J Econom 52:5–59. https://doi.org/10.1016/0304-4076(92)90064-X
Campbell JY, Vuolteenaho T (2004) Inflation illusion and stock prices. Am Econ Rev 94(2):19–23. https://doi.org/10.1257/0002828041301533
Chan SH, Martin JD, Kensinger JW (1990) Corporate research and development expenditures and share value. J Financ Econ 26(2):255–276
Chen SS, Chen YS, Liang WL, Wang Y (2013) R&D Spillover effects and firm performance following R&D increases. J Financ Quant Anal 48:1607–1634. https://doi.org/10.1017/S0022109013000574
Chen MA, Wu Q, Yang B (2019) How valuable is fintech innovation? Rev Financ Stud 32(5):2062–2106. https://doi.org/10.1093/rfs/hhy130
Chen SS, Chen YS, Liang WL, Wang Y (2020) Public R&D spending and cross-sectional stock returns. Res Policy 49(1):103887. https://doi.org/10.1016/j.respol.2019.103887
Cohen WM, Levinthal DA (1989) Innovation and learning: the two faces of R & D. Econ J 99(397):569–596. https://doi.org/10.2307/2233763
Crawford V, Sobel J (1982) Strategic information transmission. Econometrica 50:1431–1451. https://doi.org/10.2307/1913390
Dai P-F, Xiong X, Liu Z, Huynh TLD, Sun J (2021) Preventing crash in stock market: the role of economic policy uncertainty during COVID-19. Financ Innov 7(1):1–15. https://doi.org/10.1186/s40854-021-00248-y
Daniel K, Grinblatt M, Titman S, Wermers R (1997) Measuring mutual fund performance with characteristics-based benchmarks. J Financ 52:1035–1058. https://doi.org/10.1111/j.1540-6261.1997.tb02724.x
De Prisco R, Guarino A, Lettieri N, Malandrino D, Zaccagnino R (2021) Providing music service in Ambient Intelligence: experiments with gym users. Expert Syst Appl. https://doi.org/10.1016/j.eswa.2021.114951
Diebold FX, Yilmaz K (2012) Better to give than to receive: predictive directional measurement of volatility spillovers. Int J Forecast 28(1):57–66. https://doi.org/10.1016/j.ijforecast.2011.02.006
Dietzenbacher E (2000) Spillovers of innovation effects. J Policy Model 22(1):27–42. https://doi.org/10.1016/S0161-8938(97)00107-5
Eleswarapu VR, Tiwari A (1996) Business cycles and stock market returns: evidence using industry-based portfolios. J Financ Res 19(1):121–134. https://doi.org/10.1111/j.1475-6803.1996.tb00588.x
Eom C, Kaizoji T, Kang SH, Pichl L (2019) Bitcoin and investor sentiment: statistical characteristics and predictability. Physica A 514:511–521. https://doi.org/10.1016/j.physa.2018.09.063
Fama EF, French KR (1996) Multifactor explanations of asset pricing anomalies. J Finance LI 1:56–84. https://doi.org/10.1111/j.1540-6261.1996.tb05202.x
Feng G, Giglio S, Dacheng X (2020) Taming the factor zoo: a test of new factors. J Finance. https://doi.org/10.2139/ssrn.2934020
Ferreira CMS, Garrocho CTB, Oliveira RAR, Silva JS, Cavalcanti CFMD (2021) IoT registration and authentication in smart city applications with block chain. Sensors. https://doi.org/10.3390/s21041323
Fleisch E (2010) What is the internet of things? An economic perspective. Econ Manag Financ Mark 5(2):125–157
Globerman S (1979) Foreign direct investment and “Spillover” efficiency benefits in Canadian manufacturing industries. Can J Econom 12(1):42–56. https://doi.org/10.1002/tie.5060210203PDFPDF
Guo K (2018) An artificial intelligence-based collaboration approach in industrial iot manufacturing: key concepts. Arch Ext Potential Appl J Sens 18(5):1341. https://doi.org/10.3390/s20195480
Gupta N, Gupta S, Khosravy M, Dey N, Joshi N, Crespo RG, Patel N (2021) Economic IoT strategy: the future technology for health monitoring and diagnostic of agriculture vehicles. J Intell Manuf 32:1117–1128. https://doi.org/10.1007/s10845-020-01610-0
Hirshleifer D, Jiang D (2010) A financing-based misvaluation factor and the cross-section of expected returns. Rev Financ Stud 23:3401–3436. https://doi.org/10.2307/40865481
Ho CM (2020) Does virtual currency development harm financial stocks’ value? Comp Taiwan China Mark Econ Res Ekonomska Istraž 33(1):361–378. https://doi.org/10.1080/1331677X.2019.1702076
Hong H, Torous W, Valkanov R (2007) Do industries lead stock markets? J Financ Econ 83:367–396. https://doi.org/10.1016/j.jfineco.2005.09.010
Huckle S, Bhattacharya R, White M, Beloff N (2016) Internet of things, blockchain and shared economy applications. Procedia Comput Sci 98:461–466. https://doi.org/10.1016/j.procs.2016.09.074
Hughes A, Park A, Kietzmann J, Archer-Brown C (2019) Beyond bitcoin: what blockchain and distributed ledger technologies mean for firms. Bus Horiz 62(3):273–281. https://doi.org/10.1016/j.bushor.2019.01.002
Jaffe A (1986) Technological opportunity and spillovers of R&D: evidence from firms’ patents. Profits Market Value Am Econ Rev 76:984–1001
Jiang Y, Qian Y, Yao T (2015) R&D spillover and predictable returns. Rev Finance 20:1769–1797. https://doi.org/10.1093/rof/rfv050
Jiao Z, Shahid MS, Mirza N, Tan Z (2021) Should the fourth industrial revolution be widespread or confined geographically? A country-level analysis of fintech economies. Technol Forecast Soc Change. https://doi.org/10.1016/j.techfore.2020.120442
Kandasamy K, Srinivas S, Achuthan K, Rangan VP (2020) IoT cyber risk: a holistic analysis of cyber risk assessment frameworks, risk vectors, and risk ranking process. EURASIP J Inf Secur. https://doi.org/10.1186/s13635-020-00111-0
Kang W, De Gracia FP, Ratti RA (2017) Oil price shocks, policy uncertainty, and stock returns of oil and gas corporations. J Int Money Financ 70:344–359. https://doi.org/10.1016/j.jimonfin.2016.10.003
Li J, Li J, Zhu X, Yao Y, Casu B (2020) Risk spillovers between FinTech and traditional financial institutions: evidence from the US. Int Rev Financ Anal 71:101544. https://doi.org/10.1016/j.irfa.2020.101544
Lim SH, Kim DJ, Hur Y, Park K (2021) An empirical study of the impacts of perceived security and knowledge on continuous intention to use mobile fintech payment services. Int J Hum Comput Interact 35(10):886–898. https://doi.org/10.1080/10447318.2018.1507132
Lin AJ (2021) Volatility contagion among stock, currency, and bulk shipping market during the china’s stock market crash crisis. Singap Econ Rev 66(4):1–18. https://doi.org/10.1142/S021759082140004X
Lintner J (1965) The valuation of risk assets and the selection of risky investments in stock portfolios and capital budgets. Rev Econ Stat 47(1):13–37. https://doi.org/10.2307/1924119
Lu Y, Papagiannidis S, Alamanos E (2021) Adding “things” to the internet: exploring the spillover effect of technology acceptance. J Mark Manag 37(7–8):626–650. https://doi.org/10.1080/0267257X.2021.1886156
Marsal-Llacuna ML (2018) Future living framework: Is block chain the next enabling network? Technol Forecast Soc Chang 128:226–234. https://doi.org/10.1016/j.techfore.2017.12.005
Massa M, Zhang L (2021) The spillover effects of hurricane katrina on corporate bonds and the choice between bank and bond financing. J Financ Quant Anal 56(3):885–913. https://doi.org/10.1017/S0022109020000459
Matray A (2021) The local innovation spillovers of listed firms. J Financ Econ 141(2):395–412. https://doi.org/10.1016/j.jfineco.2021.04.009
Mohammad ZN, Farha F, Abuassba AOM, Yang S, Zhou F (2021) Access control and authorization in smart homes: a survey. Tsinghua Sci Technol 26(6):906–917. https://doi.org/10.26599/TST.2021.9010001
Nakashima T (2018) Creating credit by making use of mobility with FinTech and IoT. IATSS Research 42(2):61–66. https://doi.org/10.1016/j.iatssr.2018.06.001
Naveed K, Watanabe C, Neittaanmaki P (2017) Co-evolution between streaming and live music leads a way to the sustainable growth of music Industry-Lessons from the US experiences. Technol Soc 50:1–19. https://doi.org/10.1016/j.techsoc.2017.03.005
Ong SP, Richards WD, Jain A, Hautier G, Kocher M, Cholia S, Cedera G (2013) Python materials genomics (pymatgen): a robust, open-source python library for materials analysis. Comput Mater Sci 68:314–319. https://doi.org/10.1016/j.commatsci.2012.10.028
Qarni MO, Gulzar S (2021) Portfolio diversification benefits of alternative currency investment in Bitcoin and foreign exchange markets. Financ Innov 7(1):17. https://doi.org/10.1186/s40854-021-00233-5
Qi R, Ji S, Shen J, Vijayakumar P, Kumar N (2021) Security preservation in industrial medical CPS using Chebyshev map: an AI approach. Futur Gener Comput Syst 122:52–62. https://doi.org/10.1016/j.future.2021.03.008
Ramelli S, Wagner A (2020) Feverish Stock Price Reactions to COVID-19. Rev Corp Finance Stud 9(3):622–655
Rehman MU, Narayan S (2021) Analysis of dependence structure among investor sentiment, policy uncertainty and international oil prices. Int J Oil Gas Coal Technol 27(3):286–306. https://doi.org/10.1504/IJOGCT.2021.115799
Rogers EM (2002) Diffusion of preventive innovations. Addict Behav 27(6):989–993. https://doi.org/10.1016/S0306-4603(02)00300-3
Rogers, E. M., 1995, Diffusion of innovations (4th Ed.), New York, NY: The Free Press.
Schumpeter JA (2000) Entrepreneurship as innovation. In: Swedberg R (ed) Entrepreneurship: the social science view. Oxford University Press, Oxford, pp 51–75
Sharpe WF (1964) Capital asset prices: a theory of market equilibrium under conditions of risk. J Finance 19(3):425–442
Shiraishi M, Yano G (2021) Do ‘zombie firms’ emerge among private firms in China? A survival analysis approach that pays attention to the reception of trade credit. J Chin Econ Bus Stud 19(1):1–34. https://doi.org/10.1080/14765284.2021.1884796
Singha RP, Javaid M, Abid H, Suman R (2020) Internet of things (IoT) applications to fight against COVID-19 pandemic. Clin Res Rev 14(4):521–524. https://doi.org/10.1016/j.dsx.2020.04.041
Spanaki K, Karafili E, Despoudi S (2021) AI applications of data sharing in agriculture 4.0: a framework for role-based data access control. Int J Inf Manag 59:102350. https://doi.org/10.1016/j.ijinfomgt.2021.102350
Stambaugh R, Yuan Y (2017) Mispricing factors. Rev Financ Stud 30:1270–1315. https://doi.org/10.1093/rfs/hhw107
Sun J, Yan J, Zhang KZK (2016) Blockchain-based sharing services: What blockchain technology can contribute to smart cities. Financ Innov 2(1):26. https://doi.org/10.1186/s40854-016-0040-y
Zhang Y, Ding S (2021) Liquidity effects on price and return co-movements in commodity futures markets. Int Rev Financ Anal. https://doi.org/10.1016/j.irfa.2021.101796