Bibliographic record
Abstract
Purpose: The end of the first quarter of 2020 is the beginning of a new, difficult time in the functioning of transport companies, as well as the entire Polish and world economy. The appearance of Covid-19 (SARS-CoV-2) resulted in a number of market restrictions and a sharp decline in transport orders. Enterprises had to change the way they were managed and operated, had to adapt to a different economic reality in order to continue to prosper. The aim of the article is to define the essence of managing a transport company in the new market and economic conditions that appeared during the Covid-19 pandemic. Design/methodology/approach: The research procedure included review of polish and foreign literature, analysis of legal acts, questionnaire research, analysis of the content of internal documents of transport companies, method of analysis and synthesis, case study, methods of inductive and deductive reasoning. The article presents the results of scientific research on the impact of Covid-19 on the management and decisions made in a transport company. Findings: The high level of impact of the Covid-19 pandemic on the management of a transport company has been demonstrated. The factor that most influenced the management and decisions of transport companies is the decline or fear of a decline in contracts for transport services. Transport companies are afraid of the further negative effects of the pandemic, and therefore do not want to take out investment loans in order to develop the company. The article discusses the activities of transport companies and the management of a transport company in crisis conditions. Research limitations/implications: The article presents a survey carried out in Polish transport companies from the Podkarpackie and Lubelskie voivodships. Therefore, the research results concern the area of south-eastern Poland. Practical implications: The results of the research may be helpful for managers of transport companies (management decisions made) in order to limit the negative impact of the Covid-19 pandemic on their business activities. Originality/value: The presented research and conclusions provide practical guidance to managers about what decisions and actions can improve the economic condition of their transport companies in the difficult period of the Covid-19 pandemic, based on the example of the analyzed transport companies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".