Logistics decision-making based on the maturity assessment of imperfect knowledge
| Dec 18, 2019
About this article
Published Online: Dec 18, 2019
Page range: 65 - 79
Received: Jun 15, 2019
Accepted: Oct 15, 2019
DOI: https://doi.org/10.2478/emj-2019-0034
© 2019 Lech Bukowski, published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.
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Development steps of logistics in business practice
| STAGE | THE MAIN CHARACTERISTIC | THE DOMINANT APPROACH | THE MAIN GOAL |
|---|---|---|---|
| Logistics 1.0 | Delivery of goods in three steps: “transport — transshipment — storage” | functional, regulatory, reactive | effectiveness |
| Logistics 2.0 | Management of goods flow processes within a single enterprise | systemic, active | lean, flexibility |
| Logistics 3.0 | Comprehensive management of the goods flow in supply chains | integration across the borders of the organisation | efficiency, agility |
| Logistics 4.0 | Optimisation and virtualisation of logistics networks within the 3rd IT platform (SMAC) | dynamic, global perspective, realtime operation (RTE) | effectiveness efficiency, leagility, resilience |
Example of the Knowledge Maturity Level rating for the given example
| KNOWLEDGE MATURITY ATTRIBUTES Di | VL=1 | L=2 | M=3 | H=4 | VH=5 | RANK |
|---|---|---|---|---|---|---|
| D1 – DVV | x | 3 | ||||
| D2 – IUV | x | 4 | ||||
| D3 – KPQ | x | 3 | ||||
| Knowledge Maturity Level (KML) = | 36 - moderate |
Data Veracity Value appraisement for the given example
| DATA VERACITY ATTRIBUTES Ai | 0 | 1 | 2 | RANK |
|---|---|---|---|---|
| A1 –Accuracy (ACC) | x | 1 | ||
| A2 – Clarity (CLA) | x | 2 | ||
| A3 – Consistency (CON) | x | 1 | ||
| A4 – Plausibility (PLA) | x | 2 | ||
| A5 – Traceability (TRA) | x | 1 | ||
| Data Veracity Value (DVV) = | 4 - moderate |
Informati on Utility Value estimation for the given example
| INFORMATION UTILITY ATTRIBUTES Bi | 1 | 2 | 3 | RANK |
|---|---|---|---|---|
| B1 – Believability (BEL) | x | 2 | ||
| B2 – Completeness (COM) | x | 3 | ||
| B3 – Correctness (COR) | x | 2 | ||
| B4 – Relevancy (REL) | x | 3 | ||
| B5 – Timeliness (TIM) | x | 2 | ||
| Information Utility Value (IUV) = | 72 - high | |||
Example of the Knowledge Processing Quality evaluation for the given example
| KNOWLEDGE PROCESSING QUALITY ATTRIBUTES Ci | 1 | 2 | 3 | RANK |
|---|---|---|---|---|
| C1 – Model adequacy (MA) | x | 3 | ||
| C2 – Parameter accuracy (PA) | x | 2 | ||
| C3 – Decision correctness (DC) | x | 2 | ||
| C4 – Communication reliability (CR) | x | 3 | ||
| C5 – Realization compliance (RC) | x | 1 | ||
| Knowledge Processing Quality (KPQ) = | 36 - moderate | |||