Financial Distress Analysis as Strategy and Policy Determinants Mining Company

Zarah Puspitaningtyas(1*), Ika Sisbintari(2), Amalia Muyassaroh(3),

(1) Business Administration, Faculty of Social dan Political Sciences, University of Jember
(2) Business Administration, Faculty of Social dan Political Sciences, University of Jember
(3) Business Administration, Faculty of Social dan Political Sciences, University of Jember
(*) Corresponding Author




DOI: https://doi.org/10.26858/ja.v8i1.21872

Abstract


Financial distress is the initial condition of company bfore going bankrupt. Financial position is experiencing severe liquidity difficulties, so the company cannot carry out operational activities properly. This study aims to determine the results of assessment of financial distress in mining sector companies listed on BEI for 2015-2019 period as material for determining the company's strategy and policies. This research uses quantitative approach with descriptive analysis method. There are 15 companies as samples based on purposive sampling technique . The analysis technique using Altman Z-Score model. The results showed that there were seven companies experiencing financial distress, five companies experiencing gray area conditions and three companies are declared in non-distress condition . The results of this analysis will be taken into consideration for internal and external parties of the company for making future decisions so that both are profitable

Full Text:

PDF

References


Al-Manaseer, S., & Al-Oshaibat, S. (2018). Validity of Altman Z-Score Model to Predict Financial Failure: Evidence From Jordan. International Journal of Economics and Finance. https://doi.org/10.5539/ijef.v10n8p181

Analytica, O. (2015). Specialty commodities will not see global oversupply. Emerald Expert Briefings, oxan-db.

Cornot-Gandolphe, S. (2013). Global Coal Trade. From Tightness to Oversupply.

Financial Performance and Firm Value Lesson from Mining Sub-sector Companies on the Indonesia Stock Exchange. (2019). Jurnal Dinamika Akuntansi. https://doi.org/10.15294/jda.v11i1.17278

Folwarczny, M. (2020). Crisis management in mining companies in the event of an epidemic threat. Inzynieria Mineralna. https://doi.org/10.29227/IM-2020-02-39

Gorajek, A., & Rees, D. (2015). Lower bulk commodity prices and their effect on economic activity. RBA Bulletin, September, 31–38.

Hosseinzadeh, A., Smyth, R., Valadkhani, A., & Moradi, A. (2018). What determines the efficiency of Australian mining companies? Australian Journal of Agricultural and Resource Economics. https://doi.org/10.1111/1467-8489.12232

Kuranchie-Mensah, E. B., & Amponsah-Tawiah, K. (2016). Employee motivation and work performance: A comparative study of mining companies in Ghana. Journal of Industrial Engineering and Management. https://doi.org/10.3926/jiem.1530

Manyaeva, V. A., Piskunov, V. A., & Fomin, V. P. (2016). Strategic management accounting of company costs. International Review of Management and Marketing.

Nikolaev, M. G. (2018). Strategic company management in the digital business environment. European Journal of Management Issues. https://doi.org/10.15421/191809

Prasetiyani, E., & Sofyan, M. (2020). Bankruptcy Analysis Using Altman Z-Score Model and Springate Model In Retail Trading Company Listed In Indonesia Stock Exchange. Ilomata International Journal of Tax and Accounting. https://doi.org/10.52728/ijtc.v1i3.98

Sanzillo, T. (2014). No Need for New US Coal Ports: Data Shows Oversupply in Capacity. Institute for Energy Economics and Financial Analysis (IEEFA).

Schulte, J., & Hallstedt, S. I. (2018). Company risk management in light of the sustainability transition. Sustainability (Switzerland). https://doi.org/10.3390/su10114137

Slade, M. E. (1982). Trends in natural-resource commodity prices: an analysis of the time domain. Journal of Environmental Economics and Management, 9(2), 122–137.

Subramanyam, B., & Das, A. (2014). Linearised and non-linearised isotherm models optimization analysis by error functions and statistical means. Journal of Environmental Health Science and Engineering. https://doi.org/10.1186/2052-336X-12-92

Surahman, B., Khairani, E., Erna, E., & Erita, E. (2020). Do Financing and Investment Determine the Capital Market Reaction? Evidence from Listed Mining Companies in Indonesia. Journal of Accounting Research, Organization and Economics. https://doi.org/10.24815/jaroe.v3i1.16439

Sutomo, S., Wahyudi, S., Pangestuti, I. R. D., & Muharam, H. (2020). The determinants of capital structure in coal mining industry on the Indonesia Stock Exchange. Investment Management and Financial Innovations. https://doi.org/10.21511/imfi.17(1).2020.15

Thai, S. B., Goh, H. H., Teh, B. H., Wong, J. C., & Ong, T. S. (2014). A Revisited of Altman Z- Score Model for Companies Listed in Bursa Malaysia. International Journal of Business and Social Science.

Tung, D. T., & Phung, V. T. H. (2019). An application of Altman Z-score model to analyze the bankruptcy risk: Cases of multidisciplinary enterprises in Vietnam. In Investment Management and Financial Innovations. https://doi.org/10.21511/imfi.16(4).2019.16

Von Below, M. A. (1993). Sustainable mining development hampered by low mineral prices. Resources Policy, 19(3), 177–181.

Vrbka, J., & Rowland, Z. (2020). Using Artificial Intelligence in Company Management. In Lecture Notes in Networks and Systems. https://doi.org/10.1007/978-3-030-27015-5_51


Article Metrics

Abstract view : 200 times | PDF view : 45 times

Refbacks

  • There are currently no refbacks.


Copyright (c) 2021 Zarah Puspitaningtyas, Ika Sisbintari, Amalia Muyassaroh

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.