Synergies between an Observed Port and a Logistic Company: Application of the Discounted Cash–Flow Model and the Monte Carlo Simulation
The paper addresses an analysis of potential synergies in collaboration between an observed Port in the Mediterranean Sea and Central-European logistic railway-services based company. Both companies have established a strategic partnership. The main motive was cooperation in rail transport, with a p...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Sciendo
2017-05-01
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| Series: | Logistics & Sustainable Transport |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/jlst-2017-0001 |
| _version_ | 1797962973328703488 |
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| author | Dragan Dejan Rosi Bojan Avžner Toni |
| author_facet | Dragan Dejan Rosi Bojan Avžner Toni |
| author_sort | Dragan Dejan |
| collection | DOAJ |
| description | The paper addresses an analysis of potential synergies in collaboration between an observed Port in the Mediterranean Sea and Central-European logistic railway-services based company. Both companies have established a strategic partnership. The main motive was cooperation in rail transport, with a particular emphasis on potential synergies that would a rail traffic have brought to a port’s business. For the purpose of synergies valuation under uncertain conditions, a Monte Carlo simulation-based framework with integrated discounted cash flow (DCF) model is applied. The possible values of future synergies are calculated via the DCF model by simultaneously changing values of different uncertain financial parameters at each repetition of a Monte Carlo scenario-playing mechanism. In this process, predicted forecasts of future synergetic throughputs are also used for various types of observed cargo. As it turned out, the generated synergies’ values follow the approximate normal distribution. Based on statistical inference and analysis of probability intervals it was discovered that there might indeed exist certain important synergies in the collaboration between both companies. This fact has convinced us into a belief in the correctness of companies′ decision to enter into such kind of strategic cooperation. |
| first_indexed | 2024-04-11T01:21:01Z |
| format | Article |
| id | doaj.art-d57474e7e6c34997827263edd3b93829 |
| institution | Directory Open Access Journal |
| issn | 2232-4968 |
| language | English |
| last_indexed | 2024-04-11T01:21:01Z |
| publishDate | 2017-05-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Logistics & Sustainable Transport |
| spelling | doaj.art-d57474e7e6c34997827263edd3b938292023-01-03T11:24:49ZengSciendoLogistics & Sustainable Transport2232-49682017-05-018111810.1515/jlst-2017-0001jlst-2017-0001Synergies between an Observed Port and a Logistic Company: Application of the Discounted Cash–Flow Model and the Monte Carlo SimulationDragan Dejan0Rosi Bojan1Avžner Toni2Associate Professor at the Faculty of Logistics, University of Maribor, Celje, SloveniaFull Professor and the Dean at the Faculty of Logistics, University of Maribor, Celje, SloveniaPresident of the ALUMNI CLUB at the Faculty of Logistics, University of Maribor, Celje, SloveniaThe paper addresses an analysis of potential synergies in collaboration between an observed Port in the Mediterranean Sea and Central-European logistic railway-services based company. Both companies have established a strategic partnership. The main motive was cooperation in rail transport, with a particular emphasis on potential synergies that would a rail traffic have brought to a port’s business. For the purpose of synergies valuation under uncertain conditions, a Monte Carlo simulation-based framework with integrated discounted cash flow (DCF) model is applied. The possible values of future synergies are calculated via the DCF model by simultaneously changing values of different uncertain financial parameters at each repetition of a Monte Carlo scenario-playing mechanism. In this process, predicted forecasts of future synergetic throughputs are also used for various types of observed cargo. As it turned out, the generated synergies’ values follow the approximate normal distribution. Based on statistical inference and analysis of probability intervals it was discovered that there might indeed exist certain important synergies in the collaboration between both companies. This fact has convinced us into a belief in the correctness of companies′ decision to enter into such kind of strategic cooperation.https://doi.org/10.1515/jlst-2017-0001port economicsfinancial management and valuationsynergieslogisticscompanies′ collaborationdiscounted cash-flow modelmonte carlo simulation |
| spellingShingle | Dragan Dejan Rosi Bojan Avžner Toni Synergies between an Observed Port and a Logistic Company: Application of the Discounted Cash–Flow Model and the Monte Carlo Simulation Logistics & Sustainable Transport port economics financial management and valuation synergies logistics companies′ collaboration discounted cash-flow model monte carlo simulation |
| title | Synergies between an Observed Port and a Logistic Company: Application of the Discounted Cash–Flow Model and the Monte Carlo Simulation |
| title_full | Synergies between an Observed Port and a Logistic Company: Application of the Discounted Cash–Flow Model and the Monte Carlo Simulation |
| title_fullStr | Synergies between an Observed Port and a Logistic Company: Application of the Discounted Cash–Flow Model and the Monte Carlo Simulation |
| title_full_unstemmed | Synergies between an Observed Port and a Logistic Company: Application of the Discounted Cash–Flow Model and the Monte Carlo Simulation |
| title_short | Synergies between an Observed Port and a Logistic Company: Application of the Discounted Cash–Flow Model and the Monte Carlo Simulation |
| title_sort | synergies between an observed port and a logistic company application of the discounted cash flow model and the monte carlo simulation |
| topic | port economics financial management and valuation synergies logistics companies′ collaboration discounted cash-flow model monte carlo simulation |
| url | https://doi.org/10.1515/jlst-2017-0001 |
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