How does total quality management influence the loan quality of the bank?

Innovative profiles of TQM in banking management. The relationship between employee training and risk mitigation

Purpose

This paper aims to investigate the relationship between employee training and bank risk to verify whether and to what extent an increase in employee training, as a soft component of total quality management (TQM), affects bank risk.

Design/methodology/approach

The research adopts a panel regression, based on a unique dataset of a sample of Italian banks over the period 2011–2018, to test whether employee training affects bank risk, measured alternatively in terms of Z-score, a proxy of bank stability and non-performing loans (NPLs)/gross loans ratio as a proxy of credit risk.

Findings

Research findings reveal that increasing employee training leads to growing bank stability. In contrast, credit risk is not affected by employee training. However, by investigating training heterogeneity, this study found that the increase in the number of managerial training hours, as a proxy for soft skills training, negatively impacts credit risk. Therefore, an increase in soft skills leads to a reduction in bank credit risk.

Research limitations/implications

This study provides empirical evidence in support of the relationship between employee training and bank risk, which seems novel in the literature. From a managerial point of view, this study highlights the need for banks to pay attention to the skills, particularly soft skills, that banks' employees must possess to effectively manage bank risk and, more specifically, the core bank risk.

Originality/value

Empirical evidence on the relationship between employee training, soft/hard skills and bank risk appears limited if not absent. Therefore, the findings provide insights for a more nuanced interpretation of variables that affect bank risk.

Determinants of Sino-ASEAN Banking Efficiency: How Do Countries Differ?

The purpose of this paper is to assess the importance of geographical location in the banking sector efficiency of the Sino-ASEAN (Association of Southeast Asian Nations) region, and how the location was affected before, during and after the financial crisis. Using a panel of data from 407 banks from China, Indonesia, Malaysia, the Philippines, Singapore, Thailand and Vietnam from 2000–2013, this study applies data envelopment analysis, Tobit regression, bootstrapping, and Simar and Wilson double bootstrapping regression. The empirical evidence suggests that the banking market has an important and significant role in the efficiency of the banking sector in the Sino-ASEAN region. The significant country’s coefficients suggest that during the pre-crisis period, banks belonging to China and Indonesia were more likely to be efficient due to the geographical location effect. The study finds the same tendency among Chinese banks in the crisis period as in the period before the crisis. Overall, the results suggest that Chinese banks outperform banks from the ASEAN countries in terms of efficiency. This study raises some significant policy implications for improving bank efficiency.

Fuzzy Systems in Business Valuation

This research aims to develop a model that is able to integrate and objectify information provided by the different business valuation methods, incorporating quality management in its formal approach, which to date has not been considered in the literature about business valuation or quality management. Firstly, the company is valued using the methods which best adapt to its specific characteristics. Because of the subjectivity inherent in any valuation process, the results will be expressed through Triangular Fuzzy Numbers (TFN). These Fuzzy Numbers will be aggregated and summarized by applying Basic Defuzzification Distribution Uncertain Probabilistic Ordered Weighted Averaging operator (BADD-UPOWA). The weighting factors will be: the degree of confidence in each of the business valuation methods applied, and the innovative use of the company’s position on Crosby’s Quality Administration Grid. The results from application of the model in a case study show a significant reduction in uncertainty in contrast to the initial valuations. Moreover, the proposed methodology is seen to increase the final value of the company as its advances in quality management.