Search Advanced

Data Science in Finance and Economics

2024, Volume 4, Issue 2: 285-308. doi: 10.3934/DSFE.2024012
Previous Article Next Article
Research article

Market power, internal and external monitoring, and firm distress in the Chinese market

  • 1.
    Yamanashi Gakuin University, International College of Liberal Arts, 2-4-5 Sakaori, Kofu, Yamanashi, Japan
  • 2.
    International Christian University, Department of Business & Economics, International Christian University, 3-10-2, Osawa, Mitaka Shi, Tokyo, Japan
  • Received: 08 March 2024 Revised: 27 April 2024 Accepted: 10 May 2024 Published: 05 June 2024

  • JEL Codes: G32, G33, G34

  • This research revealed the factors that cause firm distress in the Chinese market. The stock exchange–listed firm samples are classified as moderate or severe distressed firms if they receive a special treatment warning from stock exchanges due to continuous negative net loss or are suffering from negative equities. By applying ordinary least square and logit regressions to the 2015–2022 data sample, the results showed that market power and internal and external monitoring significantly affect the likelihood of firm distress. Interestingly, debt only negatively affects a firm's earnings, has no impact on moderate firm distress, and reduces the likelihood of falling into severe distress. State-owned enterprises (SOEs) receive government support and are therefore less likely to be distressed, in contrast to family-owned firms. The recovery results confirmed that SOEs are easier to recover that family-owned firms. The ability to repay debt increases credibility and is a good signal of recovery. We differentiated from past discussions that focused on earning management and business failure. Our research contributes to the literature by analyzing firm distress and recovery from market power and monitoring, which are not well discussed with observable evidence. These findings could be helpful for both corporate and regulatory policy decision-making.

    Citation: Dachen Sheng, Opale Guyot. Market power, internal and external monitoring, and firm distress in the Chinese market[J]. Data Science in Finance and Economics, 2024, 4(2): 285-308. doi: 10.3934/DSFE.2024012

    Related Papers:

    [1] Yicang Zhou, Zhien Ma . Global stability of a class of discrete age-structured SIS models with immigration. Mathematical Biosciences and Engineering, 2009, 6(2): 409-425. doi: 10.3934/mbe.2009.6.409
    [2] Yanxia Dang, Zhipeng Qiu, Xuezhi Li . Competitive exclusion in an infection-age structured vector-host epidemic model. Mathematical Biosciences and Engineering, 2017, 14(4): 901-931. doi: 10.3934/mbe.2017048
    [3] Zhiping Liu, Zhen Jin, Junyuan Yang, Juan Zhang . The backward bifurcation of an age-structured cholera transmission model with saturation incidence. Mathematical Biosciences and Engineering, 2022, 19(12): 12427-12447. doi: 10.3934/mbe.2022580
    [4] Toshikazu Kuniya, Hisashi Inaba . Hopf bifurcation in a chronological age-structured SIR epidemic model with age-dependent infectivity. Mathematical Biosciences and Engineering, 2023, 20(7): 13036-13060. doi: 10.3934/mbe.2023581
    [5] Azmy S. Ackleh, Keng Deng, Yixiang Wu . Competitive exclusion and coexistence in a two-strain pathogen model with diffusion. Mathematical Biosciences and Engineering, 2016, 13(1): 1-18. doi: 10.3934/mbe.2016.13.1
    [6] Churni Gupta, Necibe Tuncer, Maia Martcheva . A network immuno-epidemiological model of HIV and opioid epidemics. Mathematical Biosciences and Engineering, 2023, 20(2): 4040-4068. doi: 10.3934/mbe.2023189
    [7] Tsuyoshi Kajiwara, Toru Sasaki, Yoji Otani . Global stability of an age-structured infection model in vivo with two compartments and two routes. Mathematical Biosciences and Engineering, 2022, 19(11): 11047-11070. doi: 10.3934/mbe.2022515
    [8] Xiaodan Sun, Yanni Xiao, Zhihang Peng . Modelling HIV superinfection among men who have sex with men. Mathematical Biosciences and Engineering, 2016, 13(1): 171-191. doi: 10.3934/mbe.2016.13.171
    [9] Abba B. Gumel, Baojun Song . Existence of multiple-stable equilibria for a multi-drug-resistant model of mycobacterium tuberculosis. Mathematical Biosciences and Engineering, 2008, 5(3): 437-455. doi: 10.3934/mbe.2008.5.437
    [10] Azizeh Jabbari, Carlos Castillo-Chavez, Fereshteh Nazari, Baojun Song, Hossein Kheiri . A two-strain TB model with multiplelatent stages. Mathematical Biosciences and Engineering, 2016, 13(4): 741-785. doi: 10.3934/mbe.2016017

  • This research revealed the factors that cause firm distress in the Chinese market. The stock exchange–listed firm samples are classified as moderate or severe distressed firms if they receive a special treatment warning from stock exchanges due to continuous negative net loss or are suffering from negative equities. By applying ordinary least square and logit regressions to the 2015–2022 data sample, the results showed that market power and internal and external monitoring significantly affect the likelihood of firm distress. Interestingly, debt only negatively affects a firm's earnings, has no impact on moderate firm distress, and reduces the likelihood of falling into severe distress. State-owned enterprises (SOEs) receive government support and are therefore less likely to be distressed, in contrast to family-owned firms. The recovery results confirmed that SOEs are easier to recover that family-owned firms. The ability to repay debt increases credibility and is a good signal of recovery. We differentiated from past discussions that focused on earning management and business failure. Our research contributes to the literature by analyzing firm distress and recovery from market power and monitoring, which are not well discussed with observable evidence. These findings could be helpful for both corporate and regulatory policy decision-making.




    [1] Ahn S, Choi W (2009) The role of bank monitoring in corporate governance: Evidence from borrowers' earnings management behavior. J bank Financ 33: 425–434. https://doi.org/10.1016/j.jbankfin.2008.08.013 doi: 10.1016/j.jbankfin.2008.08.013
    [2] Al‐Hadi A, Chatterjee B, Yaftian A, et al. (2019) Corporate social responsibility performance, financial distress and firm life cycle: evidence from Australia. Account Financ 59: 961–989. https://doi.org/10.1111/acfi.12277 doi: 10.1111/acfi.12277
    [3] Álvarez L, García-Posada M, Mayordomo S (2023) Distressed firms, zombie firms and zombie lending: a taxonomy. J Bank Financ 149: 106762. https://doi.org/10.1016/j.jbankfin.2023.106762 doi: 10.1016/j.jbankfin.2023.106762
    [4] Andreou CK, Andreou PC, Lambertides N (2021) Financial distress risk and stock price crashes. J Corp Financ 67: 101870. https://doi.org/10.1016/j.jcorpfin.2020.101870 doi: 10.1016/j.jcorpfin.2020.101870
    [5] Babenko I (2009) Share repurchases and pay‐performance sensitivity of employee compensation contracts. J Financ 64: 117–150. https://doi.org/10.1111/j.1540-6261.2008.01430.x doi: 10.1111/j.1540-6261.2008.01430.x
    [6] Bhattacharya A, Morgan NA, Rego LL (2022) Examining why and when market share drives firm profit. J Marketing 86: 73–94. https://doi.org/10.1177/00222429211031922 doi: 10.1177/00222429211031922
    [7] Boone JP, Khurana IK, Raman KK (2010) Do the Big 4 and the second-tier firms provide audits of similar quality? J Account Public Pol 29: 330–352. https://doi.org/10.1016/j.jaccpubpol.2010.06.007 doi: 10.1016/j.jaccpubpol.2010.06.007
    [8] Chang HY, Liang LH, Yu HF (2019) Market power, competition and earnings management: accrual-based activities. J Financ Econ Policy 11: 368–384. https://doi.org/10.1108/JFEP-08-2018-0108 doi: 10.1108/JFEP-08-2018-0108
    [9] Chang K, Kang E, Li Y (2016) Effect of institutional ownership on dividends: An agency-theory-based analysis. J Bus Res 69: 2551–2559. https://doi.org/10.1016/j.jbusres.2015.10.088 doi: 10.1016/j.jbusres.2015.10.088
    [10] Charitou A, Lambertides N, Trigeorgis L (2007) Managerial discretion in distressed firms. Brit Account Rev 39: 323–346. https://doi.org/10.1016/j.bar.2007.08.003 doi: 10.1016/j.bar.2007.08.003
    [11] Chen CJ, He W, Lu CJ, et al. (2022) Bank loan covenants, accrual quality and firms' information environment. Account Financ 62: 547–575. https://doi.org/10.1111/acfi.12798 doi: 10.1111/acfi.12798
    [12] Chen JZ, Lobo GJ, Wang Y, et al. (2013) Loan collateral and financial reporting conservatism: Chinese evidence. J Bank Financ 37: 4989–5006. https://doi.org/10.1016/j.jbankfin.2013.09.003 doi: 10.1016/j.jbankfin.2013.09.003
    [13] Chen L, Gao F, Guo T, et al. (2023) Mixed ownership reform and the short-term debt for long-term investment of non-state-owned enterprises: Evidence from China. Int Rev Financ Anal 90: 102861. https://doi.org/10.1016/j.irfa.2023.102861 doi: 10.1016/j.irfa.2023.102861
    [14] Chen Y, Huang Y, Wen M (2023) Accounts Receivable Reform and Financing Constraints: Evidence from China's A-Share Market. Emerg Mark Financ Trade 1–26. https://doi.org/10.1080/1540496X.2023.2298255 doi: 10.1080/1540496X.2023.2298255
    [15] Clinch G, Sidhu B, Sin S (2002) The usefulness of direct and indirect cash flow disclosures. Rev Account Stud 7: 383–404. https://doi.org/10.1023/A:1020759511460 doi: 10.1023/A:1020759511460
    [16] Cook DO, Zhang W (2022) CEO option incentives and corporate share repurchases. Int Rev Econ Financ 78: 355–376. https://doi.org/10.1016/j.iref.2021.12.002 doi: 10.1016/j.iref.2021.12.002
    [17] Córdoba‐Pachón JR, Garde‐Sánchez R, Rodríguez‐Bolívar MP (2014) A systemic view of corporate social responsibility (CSR) in state‐owned enterprises (SOEs). Knowl Process Manag 21: 206–219. https://doi.org/10.1002/kpm.1453 doi: 10.1002/kpm.1453
    [18] Demydyuk G, Shawky HA, Rest JVD, et al. (2015) Key operating indicators to lever financial performance of publicly traded restaurant companies: a market's perspective from 2007–2011. Int J Revenue Manag 8: 165–192. https://doi.org/10.1504/IJRM.2015.070006 doi: 10.1504/IJRM.2015.070006
    [19] Elyasiani E, Jia J (2010) Distribution of institutional ownership and corporate firm performance. J Bank Financ 34: 606–620. https://doi.org/10.1016/j.jbankfin.2009.08.018 doi: 10.1016/j.jbankfin.2009.08.018
    [20] Emery GW, Marques MA (2011) The effect of transaction costs, payment terms and power on the level of raw materials inventories. J Oper Manage 29: 236–249. https://doi.org/10.1016/j.jom.2010.11.003 doi: 10.1016/j.jom.2010.11.003
    [21] Fabbri D, Klapper LF (2016) Bargaining power and trade credit. J Corp Financ 41: 66–80. https://doi.org/10.1016/j.jcorpfin.2016.07.001 doi: 10.1016/j.jcorpfin.2016.07.001
    [22] Farooq U, Jibran Qamar MA, Haque A (2018) A three-stage dynamic model of financial distress. Manag Financ 44: 1101–1116. https://doi.org/10.1108/MF-07-2017-0244 doi: 10.1108/MF-07-2017-0244
    [23] García‐Teruel PJ, Martínez‐Solano P (2010) A dynamic approach to accounts receivable: a study of Spanish SMEs. Eur Financ Manag 16: 400–421. https://doi.org/10.1111/j.1468-036X.2008.00461.x doi: 10.1111/j.1468-036X.2008.00461.x
    [24] Grundy T (2006) Rethinking and reinventing Michael Porter's five forces model. Strateg Chang 15: 213–229. https://doi.org/10.1002/jsc.764 doi: 10.1002/jsc.764
    [25] Gustafson MT, Ivanov IT, Meisenzahl RR (2021) Bank monitoring: Evidence from syndicated loans. J Financ Econ 139: 452–477. https://doi.org/10.1016/0378-4266(95)00006-2 doi: 10.1016/0378-4266(95)00006-2
    [26] Han X, Epetia MCF, Cheng Y (2021) "Subsidies" or "taxes"? Corporate credit misallocation induced by the nexus of state-owned enterprises and state-owned banks. J Asian Econ 76: 101346. https://doi.org/10.1016/j.asieco.2021.101346 doi: 10.1016/j.asieco.2021.101346
    [27] Habib AM (2023) Do business strategies and environmental, social, and governance (ESG) performance mitigate the likelihood of financial distress? A multiple mediation model. Heliyon 9. https://doi.org/10.1016/j.heliyon.2023.e17847 doi: 10.1016/j.heliyon.2023.e17847
    [28] Habib AM, Kayani UN (2022) Does the efficiency of working capital management affect a firm's financial distress? Evidence from UAE. Corp Gov Int J Bus Soc 22: 1567–1586. https://doi.org/10.1108/CG-12-2021-0440 doi: 10.1108/CG-12-2021-0440
    [29] Hertzel MG, Li Z, Officer MS, et al. (2008) Inter-firm linkages and the wealth effects of financial distress along the supply chain. J Financ Econ 87: 374–387. https://doi.org/10.1016/j.jfineco.2007.01.005 doi: 10.1016/j.jfineco.2007.01.005
    [30] Huang Z, Li Z (2021) What reflects investor sentiment? Empirical evidence from China. Data Sci Financ Econ 1: 235–252. https://doi.org/10.3934/DSFE.2021013 doi: 10.3934/DSFE.2021013
    [31] Kahl M, Shivdasani A, Wang Y (2015) Short‐term debt as bridge financing: Evidence from the commercial paper market. J Financ 70: 211–255. https://doi.org/10.1111/jofi.12216 doi: 10.1111/jofi.12216
    [32] Lee KW, Sharpe IG (2009) Does a bank's loan screening and monitoring matter? J Financ Serv Res 35: 33–52. https://doi.org/10.1007/s10693-008-0041-8 doi: 10.1007/s10693-008-0041-8
    [33] Leverty JT, Grace MF (2012) Dupes or incompetents? An examination of management's impact on firm distress. J Risk Insur 79: 751–783. https://doi.org/10.1111/j.1539-6975.2011.01443.x doi: 10.1111/j.1539-6975.2011.01443.x
    [34] Li S, Wu Y (2022) Government subsidies, ownership structure and operating performance of state-owned enterprises: evidence from China. Appl Econ 54: 6480–6496. https://doi.org/10.1080/00036846.2022.2069671 doi: 10.1080/00036846.2022.2069671
    [35] Miarka T, Tröge M (2005) Do bank–firm relationships reduce bank debt? Evidence from Japan. Eur J Financ 11: 75–92. https://doi.org/10.1080/1351847032000168687 doi: 10.1080/1351847032000168687
    [36] Nam H, Uchida K (2019) Accounts payable and firm value: International evidence. J Bank Financ Financ 102: 116–137. https://doi.org/10.1016/j.jbankfin.2019.03.010 doi: 10.1016/j.jbankfin.2019.03.010
    [37] Navissi F, Naiker V (2006) Institutional ownership and corporate value. Manag Financ 32: 247–256. https://doi.org/10.1108/03074350610646753 doi: 10.1108/03074350610646753
    [38] Novy-Marx R (2011) Operating leverage. Rev Financ 15: 103–134. https://doi.org/10.1093/rof/rfq019 doi: 10.1093/rof/rfq019
    [39] Nuta AC, Habib AM, Neslihanoglu S, et al. (2024) Analyzing the market performance of Romanian firms: do the COVID-19 crisis and classification type matter? Int J Emerg Market. https://doi.org/10.1108/IJOEM-05-2023-0842 doi: 10.1108/IJOEM-05-2023-0842
    [40] Opler TC, Titman S (1994) Financial distress and corporate performance. J Financ 49: 1015–1040. https://doi.org/10.1111/j.1540-6261.1994.tb00086.x doi: 10.1111/j.1540-6261.1994.tb00086.x
    [41] Pianeselli D, Zaghini A (2014) The cost of firms' debt financing and the global financial crisis. Financ Res Lett 11: 74–83. https://doi.org/10.1016/j.frl.2013.12.002 doi: 10.1016/j.frl.2013.12.002
    [42] Poncet S, Steingress W, Vandenbussche H (2010) Financial constraints in China: Firm-level evidence. China Econ Rev 21: 411–422. https://doi.org/10.1016/j.chieco.2010.03.001 doi: 10.1016/j.chieco.2010.03.001
    [43] Rajan R, Winton A (1995) Covenants and collateral as incentives to monitor. J Financ 50: 1113–1146. https://doi.org/10.1111/j.1540-6261.1995.tb04052.x doi: 10.1111/j.1540-6261.1995.tb04052.x
    [44] Safdar R, Chaudhry NI, Mirza SS, et al. (2019) Principal–principal agency conflict and information quality in China: The governance role of audit quality and analyst following. J Financ Report Account 17: 42–59. https://doi.org/10.1108/JFRA-07-2017-0052 doi: 10.1108/JFRA-07-2017-0052
    [45] Saleemi J (2023) Political-obsessed environment and investor sentiments: pricing liquidity through the microblogging behavioral perspective. Data Sci Financ Econ 3: 196–207. https://doi.org/10.3934/DSFE.2023012 doi: 10.3934/DSFE.2023012
    [46] Sano K (2022) Intelligence and global bias in the stock market. Data Sci Financ Econ 3: 184–195. https://doi.org/10.3934/DSFE.2023011 doi: 10.3934/DSFE.2023011
    [47] Sevinç, D. (2022). Volatility spillovers among MIST stock markets. Data Sci Financ Econ 2: 80–95. https://doi.org/10.3934/DSFE.2022004 doi: 10.3934/DSFE.2022004
    [48] Shahwan TM, Habib AM (2020) Does the efficiency of corporate governance and intellectual capital affect a firm's financial distress? Evidence from Egypt. J Intellect Cap 21: 403–430. https://doi.org/10.1108/JIC-06-2019-0143 doi: 10.1108/JIC-06-2019-0143
    [49] Shaikh I, Randhawa K (2022) Managing the risks and motivations of technology managers in open innovation: Bringing stakeholder-centric corporate governance into focus. Technovation 114: 102437. https://doi.org/10.1016/j.technovation.2021.102437 doi: 10.1016/j.technovation.2021.102437
    [50] Sudarsanam S, Lai J (2001) Corporate financial distress and turnaround strategies: An empirical analysis. Brit J Manage 12: 183–199. https://doi.org/10.1111/1467-8551.00193 doi: 10.1111/1467-8551.00193
    [51] Tang Q, Chow CW, Lau A (1999) Auditing of state-owned enterprises in China: historic development, current practice and emerging issues. Int J Account 34: 173–187. https://doi.org/10.1016/S0020-7063(99)00008-4 doi: 10.1016/S0020-7063(99)00008-4
    [52] Turetsky HF, McEwen RA (2001) An empirical investigation of firm longevity: A model of the ex ante predictors of financial distress. Rev Quant Financ Account 16: 323–343. https://doi.org/10.1023/A:1011291425075 doi: 10.1023/A:1011291425075
    [53] Ukaegbu B (2014) The significance of working capital management in determining firm profitability: Evidence from developing economies in Africa. Res Int Bus Financ 31: 1–16. https://doi.org/10.1016/j.ribaf.2013.11.005 doi: 10.1016/j.ribaf.2013.11.005
    [54] Wang Y, Xia H (2014) Do lenders still monitor when they can securitize loans? Rev Financ Stud 27: 2354–2391. https://doi.org/10.1093/rfs/hhu006 doi: 10.1093/rfs/hhu006
    [55] Wang XY, Shan W (2013) Chairperson's government background, excess employment and government subsidies: evidence from Chinese local state-owned enterprises. China J Account Res 6: 51–74. https://doi.org/10.1016/j.cjar.2012.08.005 doi: 10.1016/j.cjar.2012.08.005
    [56] Yeung G (2009) How banks in China make lending decisions. J Contemp China 18: 285–302. https://doi.org/10.1080/10670560802576034 doi: 10.1080/10670560802576034
    [57] Zhang W (2015) R & D investment and distress risk. J Empir Financ 32: 94–114. https://doi.org/10.1016/j.jempfin.2015.03.009 doi: 10.1016/j.jempfin.2015.03.009
    [58] Zhu Q, Liu J, Lai KH (2016) Corporate social responsibility practices and performance improvement among Chinese national state-owned enterprises. Int J Prod Econ 171: 417–426. https://doi.org/10.1016/j.ijpe.2015.08.005 doi: 10.1016/j.ijpe.2015.08.005
    [59] Zou H, Adams MB (2008) Debt capacity, cost of debt, and corporate insurance. J Financ Quant Anal 43: 433–466. https://doi.org/10.1017/S0022109000003586 doi: 10.1017/S0022109000003586
    [60] Zulkhibri M (2015) Interest burden and external finance choices in emerging markets: Firm-level data evidence from Malaysia. Int Econ 141: 15–33. https://doi.org/10.1016/j.inteco.2014.11.002 doi: 10.1016/j.inteco.2014.11.002

  • This article has been cited by:

    1. E. Numfor, S. Bhattacharya, S. Lenhart, M. Martcheva, S. Anita, N. Hritonenko, G. Marinoschi, A. Swierniak, Optimal Control in Coupled Within-host and Between-host Models, 2014, 9, 0973-5348, 171, 10.1051/mmnp/20149411
    2. Lin Zhao, Zhi-Cheng Wang, Shigui Ruan, Traveling wave solutions in a two-group epidemic model with latent period, 2017, 30, 0951-7715, 1287, 10.1088/1361-6544/aa59ae
    3. Rony Izhar, Jarkko Routtu, Frida Ben-Ami, Host age modulates within-host parasite competition, 2015, 11, 1744-9561, 20150131, 10.1098/rsbl.2015.0131
    4. Tufail Malik, Abba Gumel, Elamin H. Elbasha, Qualitative analysis of an age- and sex-structured vaccination model for human papillomavirus, 2013, 18, 1553-524X, 2151, 10.3934/dcdsb.2013.18.2151
    5. Robert Rowthorn, Selma Walther, The optimal treatment of an infectious disease with two strains, 2017, 74, 0303-6812, 1753, 10.1007/s00285-016-1074-5
    6. Jemal Mohammed-Awel, Eric Numfor, Ruijun Zhao, Suzanne Lenhart, A new mathematical model studying imperfect vaccination: Optimal control analysis, 2021, 500, 0022247X, 125132, 10.1016/j.jmaa.2021.125132
    7. Mohammad A. Safi, Abba B. Gumel, Elamin H. Elbasha, Qualitative analysis of an age-structured SEIR epidemic model with treatment, 2013, 219, 00963003, 10627, 10.1016/j.amc.2013.03.126
    8. S.M. Garba, M.A. Safi, A.B. Gumel, Cross-immunity-induced backward bifurcation for a model of transmission dynamics of two strains of influenza, 2013, 14, 14681218, 1384, 10.1016/j.nonrwa.2012.10.003
    9. Toshikazu Kuniya, Jinliang Wang, Hisashi Inaba, A multi-group SIR epidemic model with age structure, 2016, 21, 1531-3492, 3515, 10.3934/dcdsb.2016109
    10. Roberto Cavoretto, Simona Collino, Bianca Giardino, Ezio Venturino, A two-strain ecoepidemic competition model, 2015, 8, 1874-1738, 37, 10.1007/s12080-014-0232-x
    11. Eminugroho Ratna Sari, Fajar Adi-Kusumo, Lina Aryati, Mathematical analysis of a SIPC age-structured model of cervical cancer, 2022, 19, 1551-0018, 6013, 10.3934/mbe.2022281
    12. Chin-Lung Li, Chang-Yuan Cheng, Chun-Hsien Li, Global dynamics of two-strain epidemic model with single-strain vaccination in complex networks, 2023, 69, 14681218, 103738, 10.1016/j.nonrwa.2022.103738
    13. S.Y. Tchoumi, H. Rwezaura, J.M. Tchuenche, Dynamic of a two-strain COVID-19 model with vaccination, 2022, 39, 22113797, 105777, 10.1016/j.rinp.2022.105777
    14. Ting Cui, Peijiang Liu, Fractional transmission analysis of two strains of influenza dynamics, 2022, 40, 22113797, 105843, 10.1016/j.rinp.2022.105843
    15. Shasha Gao, Mingwang Shen, Xueying Wang, Jin Wang, Maia Martcheva, Libin Rong, A multi-strain model with asymptomatic transmission: Application to COVID-19 in the US, 2023, 565, 00225193, 111468, 10.1016/j.jtbi.2023.111468
    16. Md. Mamun-Ur-Rashid Khan, Md. Rajib Arefin, Jun Tanimoto, Time delay of the appearance of a new strain can affect vaccination behavior and disease dynamics: An evolutionary explanation, 2023, 24680427, 10.1016/j.idm.2023.06.001
    17. Yucui Wu, Zhipeng Zhang, Limei Song, Chengyi Xia, Global stability analysis of two strains epidemic model with imperfect vaccination and immunity waning in a complex network, 2024, 179, 09600779, 114414, 10.1016/j.chaos.2023.114414
    18. 彦锦 吉, Studies with Vaccination and Asymptomatic Transmission Models, 2024, 14, 2160-7583, 424, 10.12677/pm.2024.145197
    19. Mohammadi Begum Jeelani, Rahim Ud Din, Ghaliah Alhamzi, Manel Hleili, Hussam Alrabaiah, Deterministic and Stochastic Nonlinear Model for Transmission Dynamics of COVID-19 with Vaccinations Following Bayesian-Type Procedure, 2024, 12, 2227-7390, 1662, 10.3390/math12111662
    20. Taqi A.M. Shatnawi, Stephane Y. Tchoumi, Herieth Rwezaura, Khalid Dib, Jean M. Tchuenche, Mo’tassem Al-arydah, A two-strain COVID-19 co-infection model with strain 1 vaccination, 2024, 26668181, 100945, 10.1016/j.padiff.2024.100945
    21. Riya Das, Dhiraj Kumar Das, T K Kar, Analysis of a chronological age-structured epidemic model with a pair of optimal treatment controls, 2024, 99, 0031-8949, 125240, 10.1088/1402-4896/ad8e0b
    22. Xi-Chao Duan, Chenyu Zhu, Xue-Zhi Li, Eric Numfor, Maia Martcheva, Dynamics and optimal control of an SIVR immuno-epidemiological model with standard incidence, 2025, 0022247X, 129449, 10.1016/j.jmaa.2025.129449
  • Reader Comments
  • © 2024 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索
Data Science in Finance and Economics
2.2

Metrics

Article views(1423) PDF downloads(52) Cited by(6)

Preview PDF
Download XML
Export Citation
Article outline
Abstract
References

Figures and Tables

Tables(13)

Other Articles By Authors

Related pages

Tools

Copyright © AIMS Press

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog