Advancing sustainable financial management in greening companies through big data technology innovation.

Publisher: Springer Country of Publication: Germany NLM ID: 9441769 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1614-7499 (Electronic) Linking ISSN: 09441344 NLM ISO Abbreviation: Environ Sci Pollut Res Int Subsets: MEDLINE

Publication: <2013->: Berlin : Springer
Original Publication: Landsberg, Germany : Ecomed

Big Data* ; Financial Management*; Ecosystem ; Technology ; Investments ; Commerce

Incorporating sustainability into financial management procedures has emerged as a critical component in the modern business landscape for organizations looking to strengthen their environmental stewardship while guaranteeing financial viability. The study "Advancing Sustainable Financial Management in Greening Companies through Big Data Technology Innovation" explains the crucial role that big data technologies play in empowering businesses to incorporate environmental sustainability into their financial management strategies. The research the strong link between big data analytics and the optimization of sustainable financial management in businesses from year 1990 to 2022. The study's findings show that big data analytics enables firms to make data-driven decisions, significantly increasing the effectiveness of their sustainability activities. With the enormous amounts of data that big data technologies can analyze, businesses can access actionable insights that make it easier to identify and reduce environmental impacts, use resources more efficiently, and streamline supply chains to support sustainability. To emphasizes the businesses can match their financial goals with sustainability objectives through big data technology without sacrificing profitability. Big data analytics may help businesses assess environmental risks and find possibilities for sustainable investment, enabling them to make well-informed financial decisions consistent with their commitment to environmental stewardship. The conclusion emphasizes the businesses to adopt big data technology focusing on long-term financial management strategically. The growing environmental problems that endanger the world's ecosystems underscore even more how crucial it is to include these advancements. Therefore, integrating sustainability into financial management using big data technology is not just a choice but a requirement for businesses to succeed in this century. The study demonstrated that the businesses, decision-makers, and other stakeholders to understand and use big data technologies' potential to advance sustainable financial management and build more resilient and sustainable corporate environments.
(© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Abbott BP, Abbott R, Abbott T, Abraham S, Acernese F, Ackley K et al (2019) GWTC-1: a gravitational-wave transient catalog of compact binary mergers observed by LIGO and Virgo during the first and second observing runs. Phys Rev X 9(3):031040.
Abbott R (2013) Big data and pharmacovigilance: using health information exchanges to revolutionize drug safety. Iowa L Rev 99:225.
Armitage J, Baigent C, Barnes E, Betteridge DJ, Blackwell L, Blazing M et al (2019) Efficacy and safety of statin therapy in older people: a meta-analysis of individual participant data from 28 randomised controlled trials. Lancet 393(10170):407–415. (PMID: 10.1016/S0140-6736(18)31942-1)
Bollier D, Firestone CM (2010) The promise and peril of big data. Aspen Institute, Communications and Society Program, Washington, DC, pp 1–66.
Breckenridge J, Farquharson J, Hendon R (2014) The role of business model analysis in the supervision of insurers. Bank of Engl Q Bull 54(1):49–57.
Chen H, Chiang RH, Storey VC (2012) Business intelligence and analytics: from big data to big impact. MIS Q:1165–1188.
Chunara R, Andrews JR, Brownstein JS (2012) Social and news media enable estimation of epidemiological patterns early in the 2010 Haitian cholera outbreak. Am J Trop Med Hygiene 86(1):39. (PMID: 10.4269/ajtmh.2012.11-0597)
Cigu E, Agheorghiesei DT, Gavriluță AF, Toader E (2018) Transport infrastructure development, public performance and long-run economic growth: a case study for the Eu-28 countries. Sustainability 11(1):67. (PMID: 10.3390/su11010067)
Clark KR, Vealé BL (2018) Strategies to enhance data collection and analysis in qualitative research. Radiol Technol 89(5):482CT–485CT.
Clarkson C, Jacobs Z, Marwick B, Fullagar R, Wallis L, Smith M et al (2017) Human occupation of northern Australia by 65,000 years ago. Nature 547(7663):306–310. (PMID: 10.1038/nature22968)
Crawford K, Schultz J (2014) Big data and due process: Toward a framework to redress predictive privacy harms. BCL Rev 55:93.
Dubey R, Gunasekaran A, Childe SJ, Wamba SF, Papadopoulos T (2016) The impact of big data on world-class sustainable manufacturing. Int J Adv Manuf Technol 84:631–645. (PMID: 10.1007/s00170-015-7674-1)
Duhigg C (2012) How companies learn your secrets. New York Times 16(2):1–16.
Epstein MJ, Buhovac AR (2014a) Making sustainability work 2nd edition: Best Practices in managing and measuring corporate social, environmental, and economic impacts. Berrett-Koehler Publishers, San Francisco (CA, US).
Epstein MJ, Buhovac AR (2014b) Making sustainability work: Best practices in managing and measuring corporate social, environmental, and economic impacts. Berrett-Koehler Publishers.
Fan W, Yang L, Bouguila N (2022) Unsupervised grouped axial data modeling via hierarchical Bayesian nonparametric models with Watson distributions. IEEE Trans Pattern Anal Mach Intell 44(12):9654–9668.  https://doi.org/10.1109/TPAMI.2021.3128271.
Friedman, M. (1937) The use of ranks to avoid the assumption of normality implicit in the analysis of variance. American Statistical Association 32:675–701. https://doi.org/10.1080/01621459.1937.10503522.
Gao H, Shi D, Zhao B (2021) Does good luck make people overconfident? Evidence from a natural experiment in the stock market. J Corp Finance (Amsterdam, Netherlands) 68:101933.  https://doi.org/10.1016/j.jcorpfin.2021.101933.
Gao H, Hsu P, Li K, Zhang J (2020) The real effect of smoking bans: evidence from corporate innovation. J Financ Quant Anal 55(2):387–427.  https://doi.org/10.1017/S0022109018001564.
Gupta M, George JF (2016) Toward the development of a big data analytics capability. Inf Manag 53(8):1049–1064.
Hamby S, Blount Z, Smith A, Jones L, Mitchell K, Taylor E (2018) Digital poly-victimization: The increasing importance of online crime and harassment to the burden of victimization. J Trauma Dissoc 19(3):382–398. (PMID: 10.1080/15299732.2018.1441357)
Hart SL, Dowell G (2011) Invited editorial: A natural-resource-based view of the firm: Fifteen years after. J Manag 37(5):1464–1479.
Hu F, Xi X, Zhang Y (2021) Influencing mechanism of reverse knowledge spillover on investment enterprises’ technological progress: an empirical examination of Chinese firms. Technol Forecast Soc Chang 169:120797.  https://doi.org/10.1016/j.techfore.2021.120797.
Huang X, Chau KY, Tang YM, Iqbal W (2022) Business ethics and irrationality in SME during COVID-19: does it impact on sustainable business resilience?. Front Environ Sci 10:870476.  https://doi.org/10.3389/fenvs.2022.870476.
Hughes L, Dwivedi YK, Misra SK, Rana NP, Raghavan V, Akella V (2019) Blockchain research, practice and policy: Applications, benefits, limitations, emerging research themes and research agenda. Int J Inf Manag 49:114–129. (PMID: 10.1016/j.ijinfomgt.2019.02.005)
Kang P (1998) Stalking and Domestic Violence: The Third Annual Report to Congress under the Violence Against Women Act, Washington DC: US Department of Justice. Office of Justice Programs, Violence Against Women Grants Office.
Karlsson S, Löthgren M (2000) On the power and interpretation of panel unit root tests. Economics Letters. 66(3):249–255.
Kshetri N (2014) Big data′ s impact on privacy, security and consumer welfare. Telecommun Policy 38(11):1134–1145. (PMID: 10.1016/j.telpol.2014.10.002)
Lane J, Stodden V, Bender S, Nissenbaum H (2014) Privacy, big data, and the public good: Frameworks for engagement. Cambridge University Press. (PMID: 10.1017/CBO9781107590205)
Lee KH, Wu Y (2014) Integrating sustainability performance measurement into logistics and supply networks: A multi-methodological approach. Br Account Rev 46(4):361–378. (PMID: 10.1016/j.bar.2014.10.005)
Li X, Sun Y (2020) Stock intelligent investment strategy based on support vector machine parameter optimization algorithm. Neural Comput & Applic 32(6):1765–1775.  https://doi.org/10.1007/s00521-019-04566-2.
Ling Guo L, Qu Y, Tseng ML (2017) The interaction effects of environmental regulation and technological innovation on regional green growth performance. J Clean Prod 162:894–902. (PMID: 10.1016/j.jclepro.2017.05.210)
Liu X, He J, Liu M, Yin Z, Yin L et al (2023a) A scenario-generic neural machine translation data augmentation method. Electronics 12(10):2320.  https://doi.org/10.3390/electronics12102320.
Liu X, Shi T, Zhou G, Liu M, Yin Z, Yin L et al (2023b) Emotion classification for short texts: an improved multi-label method. Humanit Soc Sci Commun 10(1):306.  https://doi.org/10.1057/s41599-023-01816-6.
Lu S, Liu M, Yin L, Yin Z, Liu X, Zheng W et al (2023) The multi-modal fusion in visual question answering: a review of attention mechanisms. PeerJ Comput Sci 9:e1400.  https://doi.org/10.7717/peerj-cs.1400.
Luo J, Zhuo W, Xu B (2023) The bigger, the better? Optimal NGO size of human resources and governance quality of entrepreneurship in circular economy. Manag Decis.  https://doi.org/10.1108/MD-03-2023-0325.
Mayer-Schönberger V, Cukier K (2013) Big data: A revolution that will transform how we live, work, and think. Houghton Mifflin Harcourt.
Meng F, Wang X, Chen H, Zhang J, Yang W, Wang J, Zheng Q (2016) The influence of organizational culture on talent management: A case study of a real estate company. J Chinese Hum Resour Manag 7(2):129–146. (PMID: 10.1108/JCHRM-07-2016-0010)
Mikalef, P., Pappas, I., Krogstie, J., & Pavlou, P. (2019) Big data and business analytics: A research agenda for realizing business value.
Orlitzky M, Schmidt FL, Rynes SL (2003) Corporate social and financial performance: A meta-analysis. Org Stud 24(3):403–441. (PMID: 10.1177/0170840603024003910)
Pesaran MH, Shin Y, Smith RJ (2000) Structural analysis of vector error correction models with exogenous I (1) variables. J Econ 97(2):293–343.
Qiu L, Yu R, Hu F, Zhou H, Hu H (2023) How can China's medical manufacturing listed firms improve their technological innovation efficiency? An analysis based on a three-stage DEA model and corporate governance configurations. Technol Forecast Soc Chang 194:122684.  https://doi.org/10.1016/j.techfore.2023.122684.
Ransbotham S, Kiron D, Prentice PK (2015) The talent dividend. MIT Sloan Manag Rev 56(4):1–12.
Sebi C, Nadel S, Schlomann B, Steinbach J (2019) Policy strategies for achieving large long-term savings from retrofitting existing buildings. Energy Effic 12:89–105.
Sebele-Mpofu FY, Mashiri E, Korera P (2021) Transfer pricing audit challenges and dispute resolution effectiveness in developing countries with specific focus on Zimbabwe. Account Econ Law Conviv 0:000010151520210026.
Sivarajah U, Kamal MM, Irani Z, Weerakkody V (2017) Critical analysis of Big Data challenges and analytical methods. J Bus Res 70:263–286. (PMID: 10.1016/j.jbusres.2016.08.001)
Stefana E, Cocca P, Marciano F, Rossi D, Tomasoni G (2019) A review of energy and environmental management practices in cast iron foundries to increase sustainability. Sustainability 11(24):7245. (PMID: 10.3390/su11247245)
Strahilevitz LJ (2013) Toward a positive theory of privacy law. Harvard Law Rev 126(7):2010–2042.
Sundarakani B, Ajaykumar A, Gunasekaran A (2021) Big data driven supply chain design and applications for blockchain: An action research using case study approach. Omega 102:102452. (PMID: 10.1016/j.omega.2021.102452)
Toda M, Williams SR, Berkow EL, Farley MM, Harrison LH, Bonner L et al (2019) Population-based active surveillance for culture-confirmed candidemia—four sites, United States, 2012–2016. MMWR Surveill Summ 68(8):1. (PMID: 10.15585/mmwr.ss6808a1)
Tu Y, Liu R, Li H (2022) The Development of Digital Economy and the Future of the Trade Union Law of the People's Republic of China. J Chinese Hum Resour Manag 13(2):76–85. https://doi.org/10.47297/wspchrmWSP2040-800507.20221302. (PMID: 10.47297/wspchrmWSP2040-800507.20221302)
Wang X, Li L, Zhao K, Lin Q, Li H, Xue X et al (2020) A novel LncRNA HITT forms a regulatory loop with HIF-1α to modulate angiogenesis and tumor growth. Cell Death Differ 27(4):1431–1446. (PMID: 10.1038/s41418-019-0449-8)
Wu B, Gu Q, Liu Z, Liu J (2023) Clustered institutional investors, shared ESG preferences and low-carbon innovation in family firm. Technol Forecast Soc Chang 194:122676.  https://doi.org/10.1016/j.techfore.2023.122676.
Xiang H, Chau KY, Iqbal W, Irfan M, Dagar V (2022) Determinants of social commerce usage and online impulse purchase: implications for business and digital revolution. Front Psychol 13:837042.
Yin J, Song H (2023) Does the perception of smart governance enhance commercial investments? Evidence from Beijing, Shanghai, Guangzhou, and Hangzhou. Heliyon 9(8):e19024.  https://doi.org/10.1016/j.heliyon.2023.e19024.
Yi H, Meng X, Linghu Y, Zhang Z (2023) Can financial capability improve entrepreneurial performance? Evidence from rural China. Econ Res-Ekon Istraž 36(1):1631–1650.  https://doi.org/10.1080/1331677X.2022.2091631.
Yu B, Zhou X (2023) Urban administrative hierarchy and urban land use efficiency: evidence from Chinese cities. Int Rev Econ Finance 88:178–195.  https://doi.org/10.1016/j.iref.2023.06.033.

Keywords: Cost effivency; Financial management; Government regulation (GRP); Investment green technologies

Date Created: 20231220 Date Completed: 20240122 Latest Revision: 20240202

20240202

10.1007/s11356-023-30950-6

38123775