# A Sustainable Method for Evaluating the Activity of Logistics Service Providers (LSPs) in a Turbulent Environment—Case Study Analysis (2020–2021)

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## Abstract

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## 1. Introduction

#### Description of the Proposed Research Method

- It is based on known, and commonly used in other countries, measures of the economic evaluation of individual companies, as well as the measure of fleet assessment. These are the following measures:
- Profitability indicators (ROE, ROA, ROS, gross profit margin indicator, revenue dynamics indicator);
- Performance indicators (current assets turnover indicator, liabilities turnover indicator);
- Debt indicators (debt to equity ratio, total debt ratio);
- Liquidity indicators (quick ratio QR);
- Fleet emission index (the number of vehicles meeting the Euro 6 standard and higher in relation to the number of vehicles in the company’s fleet) [12].

- Economic measures are obtained in the same way in all countries, i.e., from published financial statements of companies or based on individual surveys.
- The evaluation measures have the same component parameters.
- The fractional measure (one of eleven) concerning the emissivity of the fleet is also a universal tool, because all LSP companies, regardless of the country of residence, must meet the requirements of the EU regulations on the emissivity of the fleet. Therefore, the evaluation of their resource potential based on the assessment of the emissivity of the fleet makes it possible to compare entities from different countries in a universal way.

- It includes a wide set of 10 economic evaluation indicators commonly used in the financial analysis of individual companies.
- Additionally, which is a novelty, it includes one fleet assessment measure, which is important in evaluating the resource potential of companies in the context of changes in the EU regulations in the field of emissions.
- It provides a better and more reliable evaluation than company rankings based, so far, on sets of 2–3 measures, eliminating the risk of randomness and selective assessments.
- It guarantees a balanced selection of assessment measures by prior checking the degree of correlation between them.
- Ensuring a variety of correlation coefficients in the set of 11 aggregate assessment measures ensures sufficient data comparability. The use of only highly correlated indicators leads to the duplication of information and excessive increase in its importance in the whole analysis, which is not taken into account by most of the authors of the rankings. Such errors occur in rankings, where the selection of the indicators is performed randomly, without examining the correlation between them.
- The compatibility of the segregating of companies was examined in the case of selecting indicators that were differently correlated (−0.2–1) and based on only highly correlated indicators (0.8–1). The results obtained allow us to conclude that limiting the number of indicators used to build a synthetic measure only to highly correlated indicators leads to the creation of a ranking of companies that shows a high randomness of their compilation in two consecutive years.
- The ranking based on a more diverse set of indicators in terms of the correlation showed a greater convergence in both years than the ranking based solely on indicators with a high correlation close to 1. This was particularly evident in the case of the top ten companies in the rankings and the use of indicators from the same group, i.e., profitability (ROE, ROA, ROS).

## 2. Emissivity of LSPs and the Method for Its Measurement

_{2}emissions. It is estimated that transport is responsible for approx. 15%, and in agglomeration areas, even for 30% of global CO

_{2}emissions [12]. LSPs become rather spectacularly involved in pro-ecological activities aimed at reducing greenhouse gas emissions and pollution, especially if it is to improve their image or activities for the benefit of so-called corporate social responsibility (CSR) [12]. Pro-ecological activities are part of the EU policy [12,13] for sustainable development, which sets itself ambitious targets for reducing CO

_{2}[14]. The main assumption is to reduce greenhouse gas emissions by 55% by 2030 and achieve climate neutrality by 2050. The European Green Deal shows that a 90% reduction in CO

_{2}emissions from the entire transport sector is necessary by 2050, which means that almost the entire LSP fleet should be zero-emission by then [13,14]. In reality, however, environmental strategies are relatively reluctantly being implemented by the carriers and logistics operators, due to the lack of sufficient economic incentives in Poland and the availability of an alternative fuel infrastructure. Diesel-powered trucks are standard in Poland, where they still account for over 97% of the entire fleet. According to the data of the Polish Automotive Industry Association, in March 2020 there were 2848 natural gas-powered trucks in Poland, including LNG. However, automotive manufacturers have declared large-scale investments in zero-emission transport in the next dozen or so years. The first step is to reduce CO

_{2}emissions by switching from diesel to LNG. Some LSPs, in cooperation with other entities from the supply chains, develop joint projects of using vehicles powered by electricity or fuel cells in everyday cargo traffic. The main challenge for the companies from the Polish LSP sector is currently a package of climate regulations entitled “Fit for 55”, tightening regulations in relation to the EU’s 2021 emission agreements. Some companies are already trying to make large investments to reduce fleet emissions and adapt to the new regulations in advance. The authors of this article, by evaluating the fleet emissivity index of the surveyed companies, decided to check to what extent the companies’ investment activities, aimed at reducing fleet emissivity, are correlated with the economic position they occupy in the LSP rankings. The results of these analyses are included in Section 4.2, Section 4.3, Section 4.4, Section 4.5 and Section 4.6. The main tools for the greening of LSPs are investments in a so-called low-emission fleet and energy-efficient autonomous solutions for warehouses and terminals. Moreover, the vast majority of MTI respondents, i.e., 39 out of 46 surveyed LSP entities, treat the modernization or replacement of vehicles as the basis for activities aimed at environmental protection. A study conducted by the MTI in 2022 shows, however, that pro-eco investments are not of much importance for LSP customers when choosing logistics and transport services. This opinion is shared by 64% of the surveyed service users. In order to widen the application of a low-emission fleet on the LSP market, it is necessary to introduce appropriate legislative and organizational changes, e.g., related to tax deductions, the simplification of investment procedures in the area of charging infrastructure or the provision of services with the use of this type of fleet based on co-sharing. The carriers will invest in a zero-emission fleet, as long as the system of financial incentives related to the purchase of this type of vehicle will balance the cost of a traditional vehicle with similar parameters. The equalization of prices for electric vehicles, compensated by government subsidies, will take place in Poland in 2025 [10,11,13,14]. Polish transport companies are expanding their fleets, but still have mostly older vehicles at their disposal. The dynamics of the changes in the field of rejuvenation of the fleet, however, are growing. In the first half of 2019, we registered 12% more vehicles meeting the highest emission standards than in the corresponding period of 2018. Although, in 2020, the number of such registrations decreased, it was dictated by the limitations resulting from the pandemic. The highest emission standards, i.e., Euro 6, were met in 2019 by almost 100,000 trucks from Polish transport companies, and another 80,000 met the Euro 5 standard. During this time, approx. 32,000 new trucks were registered annually and approx. 68,000 commercial vehicles [14]. In 2017–2020, the registration dynamics of light commercial vehicles significantly increased, which is in line with the observed trends in the development of the courier sector and groupage deliveries based on the e-commerce market; however, the youngest cars, up to four years old, amounted only to 14% of this vehicle fleet at the end of 2019 (Figure 3) [14].

## 3. Methods Used in the Evaluation of LSPs

#### 3.1. Multi-Criteria Analysis

#### 3.2. Fundamental Analysis

#### 3.3. Statistical Analysis of LSPs (Including Economic and Ecological Parameters)

## 4. An Example of Applying a Sustainable Method for Assessing LSPs

- A set of indicators for the comparative economic evaluation of LSP companies;
- Examining the degree of correlation of the economic indicators in order to ensure a reliable evaluation;
- Determining the fleet emission index and checking its correlation with the economic indicators;
- Changes in the rankings for 2020–2021 using different sets of indicators;
- Determining the method for the positioning of companies in the ranking;
- Determining the indicators for the aggregate evaluation of LSP sector companies based on the convergence of the rankings.

- The use of a set of partial indicators with diversified correlation results in a greater similarity of the rankings in successive years;
- The use of a set of indicators only from the same group (e.g., profitability) and with a high correlation (above 0.8) causes more randomness of the rankings in subsequent years;
- When selecting a set of partial indicators for the LSP ranking evaluation, care should be taken to select measures from various groups (profitability, operational efficiency, liquidity and debt) and to examine the correlation between them as well as selecting a set of indicators with a greater dispersion of the correlation coefficient value.

#### 4.1. The Scheme and Stages of the Study

- Review of LSP assessment methods;
- Choice of partial characteristics (indicators);
- Data collection and grouping up of companies, coding;
- Analysis of the variable correlation;
- Developing the variable correlation matrix;
- Evaluation of companies in the subgroups (leaders, tail, background);
- Development of 11 partial rankings and aggregated one based on the characteristics of the two-number signatures of LSPs.

#### 4.2. Characteristics Correlation

- Net profit and equity (0.9);
- Net profit and net revenues (0.8);
- Net profit and fixed assets (0.7–0.8).

_{2}emissions. However, in the whole group of indicators adopted for this study, their correlation varied (−0.2–0.9) and it was appropriate to achieve the set objective.

_{2}emissions was not confirmed.

#### 4.3. Grouping Up of the LSPs into Homogeneous Subsets

#### 4.4. Signaturization of Companies and Development of a Collective LSP Ranking Up of the LSPs into Homogeneous Subsets

#### 4.5. Conclusions Based on the Statistics

- Within each of the subgroups (profitability, efficiency, solvency, liquidity), the analyzed economic indicators were correlated with each other [41].
- Cases of correlating indicators belonging to different subgroups were less frequent.
- The thesis on the correlation between the financial condition indicators and the degree of application of pro-ecological solutions, in particular in the field of a low-emission fleet, has not been confirmed. Investments in this area are still characterized by a negligible nature, high randomness and the susceptibility of companies to short-term trends.
- Most of the variables were correlated at the level ≥ 0.6, slightly fewer at the level of 0.4, relatively few were correlated between 0.4–0.6. In both years, the relative positions (ranks) of the surveyed companies in the rankings, determined by the values of the adopted variables, did not change significantly. This allows to create only a simplified collective ranking based on two-number signatures obtained in a linear way, by counting the highest/lowest variables in the partial rankings
- The similarity of aggregated rankings for subsequent years was also confirmed by the Spearman’s rank correlation coefficient (r), assuming values in the range [−1.0–1.0]. The analysis prompted the conclusion that, in the analyzed years, the rankings of companies did not change significantly. However, if there was a need to develop an aggregated indicator based on partial indicators, then in the case of indicators characterized by a mutually high (above 0.85) correlation coefficient from the same group (e.g., regarding profitability, efficiency), it would be necessary to limit their number with the same simplified weighting factor. Another method that would not narrow down the set of partial indicators would be to assign weights lower than 1 (e.g., 0.5–0.8) for the indicators with mutually high correlation coefficients [17,39,41].

#### 4.6. Economic Evaluation of the Studied Group of LSPs, Taking into Account the Leaders

## 5. Conclusions from the Research

## 6. Summary

## Author Contributions

## Funding

## Data Availability Statement

## Conflicts of Interest

## References

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**Figure 1.**Declines in the traffic of international road carriers’ vehicles (by country) registered in Germany (April 2019–April 2020) [1].

**Figure 2.**Number of publications concerning methods of evaluating transport and logistics companies (1958–2020) [5].

**Figure 3.**Age structure of commercial vehicles in Poland (up to 3.5 PGW) updated in the last 6 years in CEP (2019) [14].

**Figure 4.**Age structure of heavy goods vehicles in Poland (over 3.5 PGW) updated in the last 6 years in CEP [14].

**Figure 7.**The histogram for rank correlation—2020 based on a statistical computing platform [32].

**Figure 8.**The histogram for rank correlation—2021 based on a statistical computing platform [32].

**Figure 10.**The degree of correlation of the greening index and financial indicators of LSPs in 2021.

**Scheme 2.**Characteristics of the subset of leaders based on 2021 variables. Based on own research according to CRAN [32].

**Scheme 3.**Aggregated ranking of top ten LSP companies based on signaturization. Based on own research.

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**MDPI and ACS Style**

Zysińska, M.; Żak, J.
A Sustainable Method for Evaluating the Activity of Logistics Service Providers (LSPs) in a Turbulent Environment—Case Study Analysis (2020–2021). *Energies* **2023**, *16*, 1984.
https://doi.org/10.3390/en16041984

**AMA Style**

Zysińska M, Żak J.
A Sustainable Method for Evaluating the Activity of Logistics Service Providers (LSPs) in a Turbulent Environment—Case Study Analysis (2020–2021). *Energies*. 2023; 16(4):1984.
https://doi.org/10.3390/en16041984

**Chicago/Turabian Style**

Zysińska, Małgorzata, and Jolanta Żak.
2023. "A Sustainable Method for Evaluating the Activity of Logistics Service Providers (LSPs) in a Turbulent Environment—Case Study Analysis (2020–2021)" *Energies* 16, no. 4: 1984.
https://doi.org/10.3390/en16041984