A Tone Analysis of the Non-Financial Disclosure in the Automotive Industry
Abstract
:1. Introduction
2. Literature Review
2.1. Tone Analysis in (Non-)Financial Corporate Reporting
2.2. Hypothesis Development
3. Global Automotive Industry
4. Materials and Methods
4.1. Sample Selection and Data Collection
4.2. Data Analysis
4.3. Content Analysis
4.4. Statistical Analysis
+ β3 TIME_BACKWARD + β4 TIME_FORWARD + β5 EUROPE + β6 SIZE + ε
+ β3 GOV_SCORE + β4 SOC_SCORE + β5 TIME_BACKWARD +
+ β6 TIME_FORWARD + β7 EUROPE + β8 SIZE + ε
5. Results
Robustness Tests
6. Discussion
7. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Firm | Continent | Year | |||
---|---|---|---|---|---|
Variable | N. of Obs | Variable | N. of Obs | Variable | N. of Obs |
BMW | 4 | Europe | 19 | 2016 | 11 |
Daimler | 4 | Asia | 41 | 2017 | 17 |
FCA Group | 4 | Americas | 8 | 2018 | 17 |
Ford | 4 | 2019 | 17 | ||
Geely Global | 4 | 2020 | 6 | ||
General Motors | 4 | ||||
Honda | 5 | ||||
Hyundai Motor Co | 5 | ||||
Kia Motors | 4 | ||||
Mazda | 4 | ||||
Nissan Motor | 5 | ||||
Groupe PSA | 4 | ||||
Subaru | 4 | ||||
Suzuki | 3 | ||||
Tata Group | 3 | ||||
Toyota | 4 | ||||
Volkswagen Group | 3 | ||||
Total | 68 | Total | 68 | Total | 68 |
NFD Tone [52] | Positive | A text unit including good news for the company. |
Negative | A text unit including bad news for the company. | |
Time orientation [52,55,56,57,58,59,60] | Forward-looking | A text unit referring to the firm’s future prospects, strategy and expectations. |
Backward-looking | A text unit referring to the past. | |
Combined [52,57] | FLI-Positive | A text unit referring to the firm’s future prospects, strategy and expectations presented with a positive tone. |
Variable Acronym | Variable Definition | Variable Measurement |
---|---|---|
Dependent Variable | ||
TONE_POSITIVE | Positive Disclosure Tone | (Positive text units − Negative text units)/ (Positive text units + Negative text units) |
Independent Variables | ||
DECL_FIN_PERF | Declining Financial Performance | Dummy variable equal to 1 if the firm’s ROE is decreasing, 0 otherwise. Source: Datastream |
ESG_SCORE | ESG Score | ESG Score Source: Thomson Reuters Asset4 |
ENV_SCORE | Environmental Pillar Score | Environmental Pillar Score Source: Thomson Reuters Asset4 |
GOV_SCORE | Governance Pillar Score | Governance Pillar Score Source: Thomson Reuters Asset4 |
SOC_SCORE | Social Pillar Score | Social Pillar Score Source: Thomson Reuters Asset4 |
Control Variables | ||
SIZE | Size | Balance Sheet Total Assets. Source: Datastream |
TIME_FORWARD | Forward-looking Disclosure | Forward-looking Text Units. |
TIME_BACKWARD | Backward-looking Disclosure | Backward-looking Uext Units. |
EUROPE | Continent | Dummy Variable Equal to 1 if the Firm is from Europe; 0, otherwise. |
Variable | N. Obs | Mean | Std. Dev. | Min | Max |
---|---|---|---|---|---|
TONE_POSITIVE | 68 | 0.173 | 0.119 | −0.086 | 0.450 |
DECL_FIN_PERF | 54 | 0.593 | 0.496 | 0.000 | 1 |
ESG_SCORE | 62 | 74.453 | 13.589 | 46.930 | 93.440 |
ENV_SCORE | 62 | 82.120 | 12.392 | 46.590 | 98.860 |
GOV_SCORE | 62 | 66.258 | 17.312 | 21.760 | 95.050 |
SOC_SCORE | 62 | 72.744 | 19.839 | 31.180 | 96.100 |
TIME_BACKWARD | 68 | 206.927 | 113.475 | 8.000 | 571.000 |
TIME_FORWARD | 68 | 1116.926 | 688.383 | 79.000 | 3519.000 |
EUROPE | 68 | 0.279 | 0.452 | 0.000 | 1.000 |
SIZE | 6 | 2.02 × 1010 | 4.45 × 1010 | 4.46 × 107 | 1.92 × 1011 |
TONE_POSITIVE | DECL_FIN_PERF | ESG_SCORE | ENV_SCORE | GOV_SCORE | SOC_SCORE | TIME_BACKWARD | TIME_FORWARD | EUROPE | SIZE | |
---|---|---|---|---|---|---|---|---|---|---|
TONE_POSITIVE | 1.0000 | |||||||||
DECL_FIN_PERF | −0.0304 | 1.0000 | ||||||||
0.8270 | ||||||||||
ESG_SCORE | 0.1095 | −0.0260 | 1.0000 | |||||||
0.3967 | 0.8548 | |||||||||
ENV_SCORE | −0.1856 | −0.0156 | 0.7830 | 1.0000 | ||||||
0.1486 | 0.9127 | 0.0000 *** | ||||||||
GOV_SCORE | 0.1277 | −0.1311 | 0.5897 | 0.2442 | 1.0000 | |||||
0.3226 | 0.3544 | 0.0000 *** | 0.0432 ** | |||||||
SOC_SCORE | 0.2129 | 0.0313 | 0.9263 | 0.6387 | 0.3399 | 1.0000 | ||||
0.0967 * | 0.8256 | 0.0000 *** | 0.0000 *** | 0.0043 *** | ||||||
TIME_BACKWARD | −0.2588 | 0.0236 | 0.2220 | 0.3734 | −0.1836 | 0.2636 | 1.0000 | |||
TIME_FORWARD | 0.0331 ** | 0.8653 | 0.0829 * | 0.0028 *** | 0.1531 | 0.0385 ** | ||||
EUROPE | ||||||||||
TIME_FORWARD | −0.3366 | 0.0350 | 0.2474 | 0.3975 | −0.1640 | 0.2828 | 0.9775 | 1.0000 | ||
0.0050 *** | 0.8016 | 0.0525 * | 0.0014 *** | 0.2029 | 0.0260 ** | 0.0000 *** | ||||
EUROPE | −0.2190 | −0.0634 | 0.6081 | 0.6438 | 0.1946 | 0.5593 | 0.4168 | 0.4518 | 1.0000 | |
0.0727 * | 0.6363 | 0.0000 *** | 0.0000 *** | 0.1091 | 0.0000 *** | 0.0004 *** | 0.0001 *** | |||
SIZE | 0.4991 | −0.0280 | −0.0943 | −0.3089 | 0.0571 | −0.0254 | −0.0829 | −0.1299 | −0.2723 | 1.0000 |
0.0000 *** | 0.8345 | 0.4407 | 0.0098 *** | 0.6413 | 0.8356 | 0.5116 | 0.3025 | 0.0181 ** |
Statistical Model Dependent Variable: TONE_POSITIVE | Model 1 | Model 2 |
---|---|---|
DECL_FIN_PERF | 0.0080 (0.0154) | 0.0042 (0.0155) |
ESG_SCORE | 0.0037 ** (0.0016) | |
ENV_SCORE | 0.0031 * (0.0018) | |
GOV_SCORE | −0.0005 (0.0009) | |
SOC_SCORE | 0.0020 * (0.0012) | |
TIME_BACKWARD | 0.0009 ** (0.0005) | 0.0010 * (0.0005) |
TIME_FORWARD | −0.0002 (0.000) | −0.0003 *** (0.0000) |
EUROPE | −0.0155 (0.0601) | −0.0381 (0.0614) |
SIZE | 1.18 × 10−12 ** (4.91 × 10−13) | 1.31 × 10−12 *** (5.07 × 10−13) |
cons | −0.0475 (0.1107) | −0.1252 (0.1346) |
N R2 within R2 between R2 overall | 51 32.64% 53.40% 48.16% | 51 40.33% 55.02% 50.43% |
Hypothesis 1 (H1):There is a relationship between the profitability of automotive firms and the positive tone of Non-Financial Disclosures. | Not supported |
Hypothesis 2a (H2a):There is a relationship between the ESG performance of automotive firms and the positive tone of Non-Financial Disclosures. | Supported |
Hypothesis 2b (H2b):There is a relationship between the environmental performance of automotive firms and the positive tone of Non-Financial Disclosures. | Supported |
Hypothesis 2c (H2c):There is a relationship between the social performance of automotive firms and the positive tone of Non-Financial Disclosures. | Supported |
Hypothesis 2d (H2d):There is a relationship between the governance performance of automotive firms and the positive tone of Non-Financial Disclosures. | Not Supported |
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Beretta, V.; Demartini, M.C.; Lico, L.; Trucco, S. A Tone Analysis of the Non-Financial Disclosure in the Automotive Industry. Sustainability 2021, 13, 2132. https://doi.org/10.3390/su13042132
Beretta V, Demartini MC, Lico L, Trucco S. A Tone Analysis of the Non-Financial Disclosure in the Automotive Industry. Sustainability. 2021; 13(4):2132. https://doi.org/10.3390/su13042132
Chicago/Turabian StyleBeretta, Valentina, Maria Chiara Demartini, Laura Lico, and Sara Trucco. 2021. "A Tone Analysis of the Non-Financial Disclosure in the Automotive Industry" Sustainability 13, no. 4: 2132. https://doi.org/10.3390/su13042132
APA StyleBeretta, V., Demartini, M. C., Lico, L., & Trucco, S. (2021). A Tone Analysis of the Non-Financial Disclosure in the Automotive Industry. Sustainability, 13(4), 2132. https://doi.org/10.3390/su13042132