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Study on early warnings of strategic risk during the process of firms’ sustainable innovation based on an optimized genetic BP neural networks model: Evidence from Chinese manufacturing firms

Author

Listed:
  • Duan, Yunlong
  • Mu, Chang
  • Yang, Meng
  • Deng, Zhiqing
  • Chin, Tachia
  • Zhou, Li
  • Fang, Qifeng

Abstract

Strategic risk is an inevitable question of reality, which leads to a significant impact that negatively affects firms’ overall development, even threatening their survival. Most of extant studies on early warning models merely take the financial factors into account, whereas strategic risk pertaining to firms involves a diverse group of non-financial factors. In addition, the growing attention attached to the sustainable development of ecological and social environment has raised specific concerns to manufacturing firms, which need especially manage the risks generated from the process of sustainable innovation. However, scholars have paid far less attention to early warning models that comprehensively address the above problems. It is crucial to facilitate manufacturing firms to timely detect strategic risk during the process of sustainable innovation, whereas the existing early warning models are not reliable enough to warn the potential risks. Therefore, this study sets out to introduce the sustainable risk into the early warning indicators system of strategic risk. Then, Chinese manufacturing firms are applied to construct an early warning model which based on the back-propagation (BP) neural network optimized by genetic algorithm (GA). The results provide evidence that the proposed model shows a better fitting effect, higher prediction precision and higher convergence speed when compared with conventional models. In addition, the weights of the early warning model obtained from the training are substituted into the forward propagation formula, which enables to determine the relative importance of risk factors. It is of great significance for the firms to prioritize risk management actions. Furthermore, the new model enables manufacturing firms to warn the strategic risk during the process of sustainable innovation while striking a balance among economic, environmental, and social performances.

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  • Duan, Yunlong & Mu, Chang & Yang, Meng & Deng, Zhiqing & Chin, Tachia & Zhou, Li & Fang, Qifeng, 2021. "Study on early warnings of strategic risk during the process of firms’ sustainable innovation based on an optimized genetic BP neural networks model: Evidence from Chinese manufacturing firms," International Journal of Production Economics, Elsevier, vol. 242(C).
    • Handle: RePEc:eee:proeco:v:242:y:2021:i:c:s0925527321002693
    DOI: 10.1016/j.ijpe.2021.108293
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    as
    1. Guimarães, Julio Cesar Ferro de & Severo, Eliana Andrea & Dorion, Eric Charles Henri & Coallier, François & Olea, Pelayo Munhoz, 2016. "The use of organisational resources for product innovation and organisational performance: A survey of the Brazilian furniture industry," International Journal of Production Economics, Elsevier, vol. 180(C), pages 135-147.
    2. Shih‐Fang Lo & Her‐Jiun Sheu, 2007. "Is Corporate Sustainability a Value‐Increasing Strategy for Business?," Corporate Governance: An International Review, Wiley Blackwell, vol. 15(2), pages 345-358, March.
    3. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2013. "Financial Risk Measurement for Financial Risk Management," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1127-1220, Elsevier.
    4. Latan, Hengky & Chiappetta Jabbour, Charbel Jose & Lopes de Sousa Jabbour, Ana Beatriz & de Camargo Fiorini, Paula & Foropon, Cyril, 2020. "Innovative efforts of ISO 9001-certified manufacturing firms: Evidence of links between determinants of innovation, continuous innovation and firm performance," International Journal of Production Economics, Elsevier, vol. 223(C).
    5. Baillie, Richard T. & Cho, Dooyeon, 2016. "Assessing Euro crises from a time varying international CAPM approach," Journal of Empirical Finance, Elsevier, vol. 39(PB), pages 197-208.
    6. Alam, Shahriar Tanvir & Ahmed, Sayem & Ali, Syed Mithun & Sarker, Sudipa & Kabir, Golam & ul-Islam, Asif, 2021. "Challenges to COVID-19 vaccine supply chain: Implications for sustainable development goals," International Journal of Production Economics, Elsevier, vol. 239(C).
    7. Chochola, Ondřej & Hušková, Marie & Prášková, Zuzana & Steinebach, Josef G., 2013. "Robust monitoring of CAPM portfolio betas," Journal of Multivariate Analysis, Elsevier, vol. 115(C), pages 374-395.
    8. Blum, M, 1974. "Failing Company Discriminant-Analysis," Journal of Accounting Research, Wiley Blackwell, vol. 12(1), pages 1-25.
    9. Christian Geisler Asmussen & Andrea Fosfuri, 2019. "Orchestrating corporate social responsibility in the multinational enterprise," Strategic Management Journal, Wiley Blackwell, vol. 40(6), pages 894-916, June.
    10. Korol, Tomasz, 2013. "Early warning models against bankruptcy risk for Central European and Latin American enterprises," Economic Modelling, Elsevier, vol. 31(C), pages 22-30.
    11. Shashi, & Centobelli, Piera & Cerchione, Roberto & Singh, Rajwinder, 2019. "The impact of leanness and innovativeness on environmental and financial performance: Insights from Indian SMEs," International Journal of Production Economics, Elsevier, vol. 212(C), pages 111-124.
    12. Afshari, Hamid & Searcy, Cory & Jaber, Mohamad Y., 2020. "The role of eco-innovation drivers in promoting additive manufacturing in supply chains," International Journal of Production Economics, Elsevier, vol. 223(C).
    13. Arısoy, Yakup Eser & Altay-Salih, Aslıhan & Akdeniz, Levent, 2015. "Aggregate volatility expectations and threshold CAPM," The North American Journal of Economics and Finance, Elsevier, vol. 34(C), pages 231-253.
    14. Lubom??r L??zal, 2002. "Determinants of Financial Distress: What Drives Bankruptcy in a Transition Economy? The Czech Republic Case," William Davidson Institute Working Papers Series 451, William Davidson Institute at the University of Michigan.
    15. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    16. Song, Yu & Akagi, Fumio, 2016. "Application of artificial neural network for the prediction of stock market returns: The case of the Japanese stock marketAuthor-Name: Qiu, Mingyue," Chaos, Solitons & Fractals, Elsevier, vol. 85(C), pages 1-7.
    17. Edward I. Altman, 1968. "The Prediction Of Corporate Bankruptcy: A Discriminant Analysis," Journal of Finance, American Finance Association, vol. 23(1), pages 193-194, March.
    18. Phebo D. Wibbens & Nicolaj Siggelkow, 2020. "Introducing LIVA to measure long‐term firm performance," Strategic Management Journal, Wiley Blackwell, vol. 41(5), pages 867-890, May.
    19. Lolli, F. & Gamberini, R. & Regattieri, A. & Balugani, E. & Gatos, T. & Gucci, S., 2017. "Single-hidden layer neural networks for forecasting intermittent demand," International Journal of Production Economics, Elsevier, vol. 183(PA), pages 116-128.
    20. Delen, Dursun & Cogdell, Douglas & Kasap, Nihat, 2012. "A comparative analysis of data mining methods in predicting NCAA bowl outcomes," International Journal of Forecasting, Elsevier, vol. 28(2), pages 543-552.
    21. Alexandro Kleine & Michael Hauff, 2009. "Sustainability-Driven Implementation of Corporate Social Responsibility: Application of the Integrative Sustainability Triangle," Journal of Business Ethics, Springer, vol. 85(3), pages 517-533, April.
    22. Duan, Yunlong & Liu, Shuling & Cheng, Hao & Chin, Tachia & Luo, Xuan, 2021. "The moderating effect of absorptive capacity on transnational knowledge spillover and the innovation quality of high-tech industries in host countries: Evidence from the Chinese manufacturing industry," International Journal of Production Economics, Elsevier, vol. 233(C).
    23. Bai, Chunguang & Dallasega, Patrick & Orzes, Guido & Sarkis, Joseph, 2020. "Industry 4.0 technologies assessment: A sustainability perspective," International Journal of Production Economics, Elsevier, vol. 229(C).
    24. Vasilios Plakandaras & Juncal Cunado & Rangan Gupta & Mark E. Wohar, 2017. "Do leading indicators forecast U.S. recessions? A nonlinear re†evaluation using historical data," International Finance, Wiley Blackwell, vol. 20(3), pages 289-316, December.
    25. Power, Michael, 2009. "The risk management of nothing," Accounting, Organizations and Society, Elsevier, vol. 34(6-7), pages 849-855, August.
    26. Robert G. Eccles & Ioannis Ioannou & George Serafeim, 2014. "The Impact of Corporate Sustainability on Organizational Processes and Performance," Management Science, INFORMS, vol. 60(11), pages 2835-2857, November.
    27. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 71-111.
    28. Stefan Schaltegger, 2011. "Sustainability as a driver for corporate economic success," Society and Economy, Akadémiai Kiadó, Hungary, vol. 33(1), pages 15-28, April.
    29. Kenneth Peasnell & Yuan Yin & Martien Lubberink, 2018. "Analysts’ stock recommendations, earnings growth and risk," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(1), pages 217-254, March.
    30. Chang, Xin & Chen, Yangyang & Zolotoy, Leon, 2017. "Stock Liquidity and Stock Price Crash Risk," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 52(4), pages 1605-1637, August.
    31. Constantin Belu & Cristiana Manescu, 2013. "Strategic corporate social responsibility and economic performance," Applied Economics, Taylor & Francis Journals, vol. 45(19), pages 2751-2764, July.
    32. Anne Marie Knott, 2003. "Persistent heterogeneity and sustainable innovation," Strategic Management Journal, Wiley Blackwell, vol. 24(8), pages 687-705, August.
    33. Giovanna Michelon & Giacomo Boesso & Kamalesh Kumar, 2013. "Examining the Link between Strategic Corporate Social Responsibility and Company Performance: An Analysis of the Best Corporate Citizens," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 20(2), pages 81-94, March.
    34. Gunday, Gurhan & Ulusoy, Gunduz & Kilic, Kemal & Alpkan, Lutfihak, 2011. "Effects of innovation types on firm performance," International Journal of Production Economics, Elsevier, vol. 133(2), pages 662-676, October.
    35. Ayodele Ariyo Adebiyi & Aderemi Oluyinka Adewumi & Charles Korede Ayo, 2014. "Comparison of ARIMA and Artificial Neural Networks Models for Stock Price Prediction," Journal of Applied Mathematics, Hindawi, vol. 2014, pages 1-7, March.
    36. Yi-Kai Chen & Chung-Hua Shen & Lanfeng Kao & Chuan-Yi Yeh, 2018. "Bank Liquidity Risk and Performance," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 21(01), pages 1-40, March.
    37. Paul C. Godfrey & Craig B. Merrill & Jared M. Hansen, 2009. "The relationship between corporate social responsibility and shareholder value: an empirical test of the risk management hypothesis," Strategic Management Journal, Wiley Blackwell, vol. 30(4), pages 425-445, April.
    38. Pratima Bansal, 2005. "Evolving sustainably: a longitudinal study of corporate sustainable development," Strategic Management Journal, Wiley Blackwell, vol. 26(3), pages 197-218, March.
    39. Fathi, Mahdi & Khakifirooz, Marzieh & Diabat, Ali & Chen, Huangen, 2021. "An integrated queuing-stochastic optimization hybrid Genetic Algorithm for a location-inventory supply chain network," International Journal of Production Economics, Elsevier, vol. 237(C).
    40. Kamble, Sachin S. & Gunasekaran, Angappa & Gawankar, Shradha A., 2020. "Achieving sustainable performance in a data-driven agriculture supply chain: A review for research and applications," International Journal of Production Economics, Elsevier, vol. 219(C), pages 179-194.
    41. Gerald Steiner, 2008. "Supporting sustainable innovation through stakeholder management: a systems view," International Journal of Innovation and Learning, Inderscience Enterprises Ltd, vol. 5(6), pages 595-616.
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    2. Pan, Xianyou & Shen, Zhiyang & Song, Malin & Shu, Yalin, 2023. "Enhancing green technology innovation through enterprise environmental governance: A life cycle perspective with moderator analysis of dynamic innovation capability," Energy Policy, Elsevier, vol. 182(C).
    3. Jiang, Rong & Kang, Yuanjie & Liu, Yongsong & Liang, Zhihong & Duan, Yunlong & Sun, Yani & Liu, Jialan, 2022. "A trust transitivity model of small and medium-sized manufacturing enterprises under blockchain-based supply chain finance," International Journal of Production Economics, Elsevier, vol. 247(C).

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