Do generic strategy and productivity help detect corporate retail bankruptcy risk?
Recently, there have been several retail companies experiencing bankruptcy. Many studies on bankruptcy risk are more seen from the financial performance perspective. Studies on the risk of financial performance are good but it seems too late to detect the risk. So far, no research investigates some antecedents on the risk directly. It is commonly ended in financial performance. This study detects earlier the risk from antecedents of financial performance as an indicator of the risk. The study aims to investigate the effect of generic strategy, as well as productivity, on bankruptcy. The study is causality research. The population is 25 retail companies. With certain criteria, there are 17 companies as a sample. By using SEM and smart-PLS, it can be concluded that cost leadership affects both on productivity and the risk. Then, the differentiation strategy does not affect productivity, but it affects the risk. Furthermore, productivity is eligible as an intervening variable on the risk. Moreover, the strategy and productivity are good but not enough to detect the risk. Therefore, for detecting the risk possibility, it is needed a further research improvement for detecting the risk from a macro and micro perspective comprehensively.
This work is licensed under a Creative Commons Attribution 4.0 International License.
Aghajani, V., & Jouzbarkand, M. (2012). The creation of bankruptcy prediction model using Springate and SAF Models. World Applied Sciences Journal, 17, 1–5.
Akbar, A., Akbar, M., Tang, W., & Qureshi, M. A. (2019). Is bankruptcy risk tied to corporate life-cycle? Evidence from Pakistan. Sustainability, 11(3), 678. https://doi.org/10.3390/su11030678
Ali, I., Rehman, K. U., Yilmaz, A. K., Khan, M. A., & Afzal, H. (2010). The causal relationship between macro-economic indicators and stock exchange prices in Pakistan. African Journal of Business Management, 4(3), 312–319.
Altman, E. I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. The Journal of Finance, 23(4), 589–609. https://doi.org/10.1111/j.1540-6261.1968.tb00843.x
Altman, E. I., Haldeman, R. G., & Narayanan, P. (1977). ZETATM analysis A new model to identify bankruptcy risk of corporations. Journal of Banking & Finance, 1(1), 29–54. https://doi.org/10.1016/0378-4266(77)90017-6
Asdemir, O., Fernando, G. D., & Tripathy, A. (2013). Market perception of firm strategy. Managerial Finance, 39(2), 90–115. https://doi.org/10.1108/03074351311293972
Balsam, S., Fernando, G. D., & Tripathy, A. (2011). The impact of firm strategy on performance measures used in executive compensation. Journal of Business Research, 64(2), 187–193. https://doi.org/10.1016/j.jbusres.2010.01.006
Barney, J. B., & Hesterly, W. S. (2019). Strategic management and competitive advantage: Concepts and cases. Pearson.
Banker, D. R., Mashruwala, R., & Tripathy, A. (2014). Does a differentiation strategy lead to more sustainable financial performance than a cost leadership strategy? Management Decision, 52(5), 872–896. https://doi.org/10.1108/MD-05-2013-0282
Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173. https://doi.org/10.1037/0022-35126.96.36.1993
Beaver, W. H. (1966). Financial ratios as predictors of failure. Journal of Accounting Research, 71–111. https://doi.org/10.2307/2490171
Beaver, W. H. (1968). Market prices, financial ratios, and the prediction of failure. Journal of Accounting Research, 179–192. https://doi.org/10.2307/2490233
Bhattarai, D. (2018). Generic strategies and sustainability of financial performance of Nepalese Enterprises. Pravaha, 24(1), 39–49. https://doi.org/10.3126/pravaha.v24i1.20224
Blocher, E. J., Stout, D. E., & Cokins, G. (2010). Cost management: A strategic emphasis. Includes index.
Bryan, D., Dinesh Fernando, G., & Tripathy, A. (2013). Bankruptcy risk, productivity, and firm strategy. Review of Accounting and Finance, 12(4), 309–326. https://doi.org/10.1108/RAF-06-2012-0052
Cenciarelli, V. G., Greco, G., & Allegrini, M. (2018). Does intellectual capital help predict bankruptcy? Journal of Intellectual Capital, 19(2), 321–337. https://doi.org/10.1108/JIC-03-2017-0047
Calandro Jr, J. (2007). Considering the utility of Altman–s Z-score as a strategic assessment and performance management tool. Strategy & Leadership, 35(5), 37–43. https://doi.org/10.1108/10878570710819206
Darrat, A. F., Gray, S., Park, J. C., & Wu, Y. (2016). Corporate governance and bankruptcy risk. Journal of Accounting, Auditing & Finance, 31(2), 163–202. https://doi.org/10.1177/0148558X14560898
García, V., Marqués, A. I., & Sánchez, J. S. (2019). Exploring the synergetic effects of sample types on the performance of ensembles for credit risk and corporate bankruptcy prediction. Information Fusion, 47, 88–101. https://doi.org/10.1016/j.inffus.2018.07.004
Gavurova, B., Packova, M., Misankova, M., & Smrcka, L. (2017). Predictive potential and risks of selected bankruptcy prediction models in the Slovak business environment. Journal of Business Economics and Management, 18(6), 1156–1173. https://doi.org/10.3846/16111699.2017.1400461
Götz, O., Liehr-Gobbers, K., & Krafft, M. (2010). Evaluation of structural equation models using the partial least squares (PLS) approach. In Handbook of partial least squares (pp. 691–711). Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-32827-8_30
Hasan, I., Kobeissi, N. L., & Wang, H. (2018). Corporate social responsibility and firm financial performance: The mediating role of productivity. Journal of Business Ethics, 149(3), 671–688. https://doi.org/10.1007/s10551-016-3066-1
Hayes, S. K., Hodge, K. A., & Hughes, L. W. (2010). A study of the efficacy of Altman’s Z to predict bankruptcy of specialty retail firms doing business in contemporary times. Economics & Business Journal: Inquiries & Perspectives, 3(1), 130–134.
Kaliappen, N., & Hilman, H. (2013). Enhancing organizational performance through strategic alignment of cost leadership strategy and competitor orientation. Middle-East Journal of Scientific Research, 18(10), 1411–1416.
Kasilingam, R., & Ramasundaram, G. (2012). Predicting the solvent of non-banking financial institutions in India using Fulmer and Springate. Journal of Services Research, 12(1).
Kim, S., Mun, B. M., & Bae, S. J. (2018). Data depth based support vector machines for predicting corporate bankruptcy. Applied Intelligence, 48(3), 791–804. https://doi.org/10.1007/s10489-017-1011-3
Kurt, A., & Zehir, C. (2016). The relationship between cost leadership strategy, total quality management applications and financial performance. Doğuş Üniversitesi Dergisi, 17(1), 97–110. https://doi.org/10.31671/dogus.2018.45
Movahed, L. R., & Shamszadeh, B. (2015). Studying bankruptcy risk, productivity and firm strategy in companies listed in Tehran stock exchange. International Research Journal of Applied and Basic Sciences, 9(5), 680–685.
Nyitrai, T. (2019). Dynamization of bankruptcy models via indicator variables. Benchmarking: An International Journal. https://doi.org/10.1108/BIJ-03-2017-0052
Ohlson, J. A. (1980). Financial ratios and the probabilistic prediction of bankruptcy. Journal of Accounting Research, 109–131. https://doi.org/10.2307/2490395
O’Hara, H. T., Lazdowski, C., Moldovean, C., & Samuelson, S. T. (2000). Financial indicators of stock price perfor-mance. American Business Review, 18(1), 90.
Orcullo, N. (2007). Fundamentals of strategic management (2007 Ed.). Rex Bookstore, Inc.
Sulub, S. A. (2014). Testing the predictive power of Altman’s revised Z’ model: the case of 10 multinational companies. Research Journal of Finance and Accounting, 5(21), 174–184.
Takahashi, M., Taques, F. H., & Basso, L. (2018). Altman’s bankruptcy prediction model: test on a wide out of business private companies sample. iBusiness, 10(01), 21. https://doi.org/10.4236/ib.2018.101002