Assessment of Financial Distress Risk of Logistics Companies in Malaysia Using the Zmijewski Model ^†

Abstract

The logistics industry plays a vital role in supporting economic growth by facilitating the efficient movement of goods and services and is a key component of Malaysia’s supply chain and trade activities. However, logistics companies are highly exposed to operational risks, economic fluctuations, and financial uncertainties, particularly during challenging periods such as the COVID-19 pandemic and its aftermath from 2020 to 2024. Without systematic financial evaluation, stakeholders such as investors, management, and policymakers may face difficulties in identifying financially healthy and distressed companies. The purpose of this study is to assess the financial performance of logistics companies listed on Bursa Malaysia from 2020 to 2024 using the Zmijewski model. A total of 28 logistics companies were evaluated in this study. The findings indicate that 24 companies remained financially healthy throughout the five-year period, representing 85.71% of the sampled firms. The results suggest that the majority of logistics companies maintained sound financial conditions despite economic challenges during the study period. On the contrary, the results of the study also revealed that a small number of companies are experiencing financial distress. The findings of this study are significant as they assist investors in making informed investment decisions, enable company management to identify potential signs of financial distress, and support policymakers in understanding the financial resilience of the logistics sector.

1. Introduction

The logistics industry is one of the key sectors that supports economic growth and development by facilitating the efficient movement, storage, and distribution of goods and services [1,2]. In Malaysia, the logistics sector plays a significant role in supporting domestic and international trade activities, contributing to supply chain efficiency and economic competitiveness. The increasing globalization of markets, growth of e-commerce, and expansion of international trade have further enhanced the importance of logistics companies in ensuring smooth business operations and customer satisfaction [3].

Evaluation of the company’s financial performance is important for identifying the signs of financial distress at an early stage and determining the financial health of the company. Early detection of financial problems can assist the company management to take corrective actions immediately, support policymakers to know the industry’s stability, and help investors to make better investment decisions. The Zmijewski model is broadly used to assess the likelihood of corporate financial distress [4,5,6,7,8,9,10].

Although numerous studies have examined financial distress prediction in different industries, limited attention has been given to the financial health of logistics companies in Malaysia, particularly during the post-pandemic period. Therefore, this study aims to evaluate the financial performance of logistics companies listed on Bursa Malaysia from 2020 to 2024 using the Zmijewski model. Specifically, the study seeks to identify financially healthy and financially distressed logistics companies and provide insights into the financial resilience of the logistics sector. The outcomes of this study are expected to be beneficial to various stakeholders, including company management, policymakers, and investors, by providing insights into the financial condition of logistics companies. Furthermore, the findings can support future decision-making processes and contribute to the development of appropriate strategies for improving financial performance and sustainability. The organization of this paper is as follows: Section 2 depicts the methods adopted in the study. Section 3 demonstrates the results and discussion. The final section of this paper is the conclusion of the study.

2. Methods

In this study, there are 28 logistics companies listed on Bursa Malaysia that are evaluated in terms of their financial performance. The Zmijewski model is utilized to assess the financial performance of the companies. The study period is between the years 2020 and 2024.

The companies’ financial performance is assessed using the Zmijewski model. The formulation of the Zmijewski model is presented below [11,12,13,14]:

$$X-score=-4.336-4.513X_1+5.679X_2+0.004X_3$$

where

$$\begin{array}{l}{X}_1={\displaystyle \frac{\mathrm{net}\mathrm{income}}{\mathrm{total}\mathrm{assets}}}\\ X_2={\displaystyle \frac{\mathrm{total}\mathrm{liabilities}}{\mathrm{total}\mathrm{assets}}}\\ X_3={\displaystyle \frac{\mathrm{current}\mathrm{assets}}{\mathrm{current}\mathrm{liabilities}}}\end{array}$$

The financial condition of each logistics company is determined based on the computed Zmijewski score. According to the original Zmijewski model, companies with a score less than zero are classified as financially healthy, whereas companies with a score greater than zero are classified as financially distressed [15]. The companies were subsequently categorized into financially healthy and financially distressed groups. The results were then summarized to evaluate the overall financial performance and resilience of the Malaysian logistics sector during the study period. The Zmijewski model is a Probit model. The estimated X-score represents the linear Probit index, which can be transformed into a predicted probability of bankruptcy as P = Φ(X). Since Φ(0) = 0.5, classifying firms with X ≥ 0 as distressed is equivalent to applying a predicted-probability threshold of 0.5. In this study, a zero cut-off is used as a simplified classification method to distinguish between financially distressed and financially healthy companies.

3. Results and Discussion

Table 1. X-scores for the years 2020, 2021, 2022, 2023 and 2024.

Company	2020	2021	2022	2023	2024
ANCOMLB	−2.20193	−1.91415	−1.92545	−2.40178	−1.09356
AVANGAAD	0.70469	2.40277	0.84438	0.44975	−3.55427
BHIC	0.86636	0.16029	0.85422	2.57224	−0.89860
BIPORT	−1.43379	−2.21432	−2.00433	−1.99014	−2.10571
CJCEN	−1.71070	−1.84231	−2.10127	−2.12179	−2.03273
GCAP	−3.96359	−3.05149	−1.63219	−1.56922	−1.22068
GDEX	−3.02528	−3.30863	−2.71445	−2.46182	−2.68657
HEXTECH	−4.16441	−3.04486	−3.81325	−3.18897	−2.00075
HUBLINE	−0.93085	−2.09223	−1.98072	−1.54631	−1.77755
KGW	−0.82285	−1.48312	−2.51688	−2.71390	−2.89979
M&G	2.10586	0.93976	1.45610	0.42718	−0.08918
MAYBULK	−0.88797	−4.31863	−3.61383	−4.49686	−2.91886
MISC	−2.22809	−2.21552	−2.25295	−2.26670	−2.33319
MMAG	−1.44449	−2.47555	−1.14033	0.60573	−0.18224
PDZ	−1.72885	−3.38834	−3.27308	−3.25570	−4.33522
POS	−0.25842	0.21099	0.10838	0.37119	0.93875
PRKCORP	2.65524	−1.06880	−1.51953	−1.51966	−1.36229
SEALINK	−1.95862	−1.40558	−2.05342	−2.48388	−2.72104
SEEHUP	−1.82046	−1.61525	−2.91490	−1.83048	−2.22994
SINKUNG	−0.99417	−1.94864	−1.90273	−1.33273	−1.24237
SURIA	−3.32065	−3.36282	−3.15324	−3.13836	−3.31658
SWIFT	−0.82900	−1.28130	−1.18931	−1.14266	−1.17339
SYGROUP	−1.86653	−2.54411	−3.15678	−3.60264	−3.54652
TAS	−1.69073	−2.02876	−1.29404	−1.37365	−1.19875
TNLOGIS	−0.68888	−0.82174	−0.84509	−0.68195	−0.57196
TRIMODE	−2.32674	−2.20475	−2.36566	−1.79921	−1.65730
WPRTS	−2.27464	−2.61785	−2.71586	−3.04677	−1.93969
XINHWA	−1.70357	−1.57726	−1.73715	−1.36186	−1.19977

demonstrates the X-scores of logistics companies for the years 2020, 2021, 2022, 2023 and 2024.

Based on Table 1, a total of 22 logistics companies were classified as financially healthy throughout the period from 2020 to 2024. The X-scores for these companies were below 0, indicating that they fell within the safe zone according to the Zmijewski model. This suggests that these companies maintained strong financial performance during the study period and may serve as references for other companies experiencing financial distress. The financially healthy companies are ANCOMLB, BIPORT, CJCEN, GCAP, GDEX, HEXTECH, HUBLINE, KGW, MAYBULK, MISC, PDZ, SEALINK, SEEHUP, SINKUNG, SURIA, SWIFT, SYGROUP, TAS, TNLOGIS, TRIMODE, WPRTS, and XINHWA. Among all companies, HEXTECH consistently recorded one of the lowest X-scores during the study period, ranging from −4.16441 in 2020 to −2.00075 in 2024. Moreover, MAYBULK, PDZ, SURIA, and SYGROUP also maintained highly negative X-scores. This demonstrates that these companies displayed excellent financial performance and a low chance of financial distress, as their X-scores are lower. The companies with stronger financial stability have lower X-scores. In contrast, MMAG experienced financial distress in 2023 but remained financially healthy in 2020, 2021, 2022, and 2024. Similarly, PRKCORP demonstrated strong financial performance throughout the study period, except in 2020. POS was financially healthy only in 2020 and experienced financial distress from 2021 to 2024. Furthermore, three companies, namely AVANGAAD, BHIC, and M&G, exhibited financial distress from 2020 to 2023 but improved their financial condition and became financially healthy in 2024. These companies should continue to implement appropriate financial improvement strategies to strengthen their financial position and enhance their competitiveness. Improved financial performance can increase the confidence of investors and policymakers while contributing to the long-term sustainability of the companies. Overall, the majority of companies show low bankruptcy risk scores when applying the Zmijewski model.

Table 2. Number and percentage of distressed companies over the five-year period.

Year	Number of Distressed Companies	Percentage of Distressed Companies (%)	Mean X-Score
2020	4	14.29	−1.35511
2021	4	14.29	−1.78972
2022	4	14.29	−1.80548
2023	5	17.86	−1.67503
2024	1	3.57	−1.83392

presents the number and percentage of distressed companies over the five-year period.

Based on

Table 3. Average X-score for the 5-year period.

Company	Average X-Score	Zone
ANCOMLB	−1.90737	Safe
AVANGAAD	0.16946	Distress
BHIC	0.71090	Distress
BIPORT	−1.94966	Safe
CJCEN	−1.96176	Safe
GCAP	−2.28743	Safe
GDEX	−2.83935	Safe
HEXTECH	−3.24245	Safe
HUBLINE	−1.66553	Safe
KGW	−2.08731	Safe
M&G	0.96794	Distress
MAYBULK	−3.24723	Safe
MISC	−2.25929	Safe
MMAG	−0.92737	Safe
PDZ	−3.19624	Safe
POS	0.27418	Distress
PRKCORP	−0.56301	Safe
SEALINK	−2.12451	Safe
SEEHUP	−2.08221	Safe
SINKUNG	−1.48413	Safe
SURIA	−3.25833	Safe
SWIFT	−1.12313	Safe
SYGROUP	−2.94332	Safe
TAS	−1.51719	Safe
TNLOGIS	−0.72192	Safe
TRIMODE	−2.07073	Safe
WPRTS	−2.51896	Safe
XINHWA	−1.51592	Safe

, the number of distressed companies remained relatively stable at four companies in 2020, 2021, and 2022. The percentage of distressed companies from 2020 to 2022 was 14.29%. Subsequently, the number increased slightly to five companies in 2023, accounting for 17.86%. In 2024, only one company was identified as financially distressed, accounting for 3.57%. Therefore, it can be observed that there was a substantial improvement in the financial condition of the companies from 2023 to 2024. According to the mean X-score, 2024 had the most negative mean X-score at −1.83392. This implies that the companies were, overall, financially healthier in 2024 compared with the other years. In 2020, the mean X-score was −1.35511. The mean X-scores in 2021 and 2022 were −1.78972 and −1.80548, respectively. Subsequently, the mean X-score increased to −1.67503 in 2023.

Table 3 depicts the average X-score of each company for the 5-year period.

According to Table 3, the logistics companies classified as being in the safe zone are ANCOMLB, BIPORT, CJCEN, GCAP, GDEX, HEXTECH, HUBLINE, KGW, MAYBULK, MISC, MMAG, PDZ, PRKCORP, SEALINK, SEEHUP, SINKUNG, SURIA, SWIFT, SYGROUP, TAS, TNLOGIS, TRIMODE, WPRTS, and XINHWA. A total of 24 companies were identified as financially healthy, as their Zmijewski scores were below 0. This represents 85.71% of the logistics companies and indicates that they remained financially stable throughout the five-year period from 2020 to 2024.

Among the financially healthy companies, SURIA obtained the lowest average X-score (−3.25833), followed closely by MAYBULK (−3.24723), HEXTECH (−3.24245), PDZ (−3.19624), SYGROUP (−2.94332), and GDEX (−2.83935). This demonstrates that these companies show strong financial performance with a very low probability of bankruptcy over the study period since their average X-scores are highly negative.

PRKCORP achieved an average X-score of −0.56301 despite facing financial distress in 2020, suggesting that its financial recovery in subsequent years outweighed its earlier financial difficulties. Although MMAG experienced temporary financial distress in 2023, its overall average X-score remained negative (−0.92737), implying that its financial condition over the five years was still considered financially healthy.

On the other hand, the financially distressed companies are AVANGAAD, BHIC, M&G, and POS. These companies exhibited weaker financial performance, with Zmijewski scores of at least 0. Therefore, these distressed companies should take remedial actions and use financially healthy companies as references to improve their financial performance in the future. Financially healthy companies such as HEXTECH, MAYBULK, PDZ, SYGROUP, and GDEX are recommended to serve as references for financially distressed companies. These companies can provide references for sound financial management practices, enabling distressed companies to improve their long-term financial sustainability.

4. Conclusions

This study evaluated the financial performance of 28 logistics companies listed on Bursa Malaysia from 2020 to 2024 using the Zmijewski model. The findings revealed that 24 companies, representing 85.71% of the sampled firms, remained financially healthy throughout the study period, indicating that the majority of logistics companies demonstrated strong financial resilience despite the economic uncertainties and operational challenges experienced during and after the COVID-19 pandemic. However, a small number of companies were identified as financially unhealthy, highlighting the need for continuous financial monitoring and improvement strategies. The findings of this study provide valuable insights for company management, investors, and policymakers. Company management can identify potential signs of financial distress and closely monitor the company’s financial condition over time. Furthermore, investors can utilize the findings to make more informed investment decisions. Policymakers may also use the outcomes of this study to better understand the financial condition of logistics companies and formulate policies that support the sustainable growth of the logistics sector. Future research may incorporate multiple financial distress prediction models and compare their predictive performance to provide a more comprehensive assessment of corporate financial health. Such studies would contribute to a deeper understanding of the financial resilience of logistics companies and offer valuable information for potential investors seeking more secure investment opportunities.