Smart Port Sustainability: A Business Intelligence Framework for CO2 Reduction in Cargo Truck Operations

Marco Hegger; Adriana Saraceni

doi:10.1007/978-3-031-71622-5_21

Smart Port Sustainability: A Business Intelligence Framework for CO2 Reduction in Cargo Truck Operations

Marco Hegger
, Adriana Saraceni^*

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceeding › Academic › peer-review

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Abstract

This research aims at investigating how to assist European ports in the decision-making of business intelligence tools to reduce the CO2 emission of cargo trucks. Thus, several scientific papers are analyzed during this research, and BI tools are selected based on sequence and integration. Thereafter, this research conducted interviews with field experts to discuss the selected BI tools and broaden the knowledge for this research. Furthermore, it was possible to contact several European ports to acquire insights into the current port operations and the desire to introduce such tools. A performance dashboard prototype, created with simulated data through R, was demonstrated to the respondents during the structured interview. Finally, a BI framework has been developed to assist European ports in the decision-making of business intelligence tools to reduce the CO2 emission of cargo trucks.

Original language	English
Title of host publication	Advances In Production Management Systems-production Management Systems For Volatile, Uncertain, Complex, And Ambiguous Environments, Apms 2024, Pt I
Editors	Matthias Thürer, Ralph Riedel, Gregor von Cieminski, David Romero
Publisher	Springer Verlag
Pages	309-323
Number of pages	15
Volume	728
ISBN (Electronic)	978-3-031-71622-5
ISBN (Print)	9783031716218
DOIs	https://doi.org/10.1007/978-3-031-71622-5_21
Publication status	Published - 1 Jan 2024
Event	43rd IFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS 2024 - Chemnitz, Germany Duration: 8 Sept 2024 → 12 Sept 2024 https://www.apms-conference.org/

Publication series

Series	IFIP Advances in Information and Communication Technology
Number	728
ISSN	1868-4238

Conference

Conference	43rd IFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS 2024
Abbreviated title	APMS 2024
Country/Territory	Germany
City	Chemnitz
Period	8/09/24 → 12/09/24
Internet address	https://www.apms-conference.org/

Keywords

Blockchain
Business Intelligence Tools
CO2 emission
Machine Learning
OLAP
Smart ports
SQL Server. Dashboard
WSN Sensor

Access to Document

10.1007/978-3-031-71622-5_21

Full TextFinal published version, 829 KBLicence: Taverne

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Hegger, M., & Saraceni, A. (2024). Smart Port Sustainability: A Business Intelligence Framework for CO2 Reduction in Cargo Truck Operations. In M. Thürer, R. Riedel, G. von Cieminski, & D. Romero (Eds.), Advances In Production Management Systems-production Management Systems For Volatile, Uncertain, Complex, And Ambiguous Environments, Apms 2024, Pt I (Vol. 728, pp. 309-323). Springer Verlag. https://doi.org/10.1007/978-3-031-71622-5_21

Hegger, Marco ; Saraceni, Adriana. / Smart Port Sustainability : A Business Intelligence Framework for CO2 Reduction in Cargo Truck Operations. Advances In Production Management Systems-production Management Systems For Volatile, Uncertain, Complex, And Ambiguous Environments, Apms 2024, Pt I. editor / Matthias Thürer ; Ralph Riedel ; Gregor von Cieminski ; David Romero. Vol. 728 Springer Verlag, 2024. pp. 309-323 (IFIP Advances in Information and Communication Technology; No. 728).

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title = "Smart Port Sustainability: A Business Intelligence Framework for CO2 Reduction in Cargo Truck Operations",

abstract = "This research aims at investigating how to assist European ports in the decision-making of business intelligence tools to reduce the CO2 emission of cargo trucks. Thus, several scientific papers are analyzed during this research, and BI tools are selected based on sequence and integration. Thereafter, this research conducted interviews with field experts to discuss the selected BI tools and broaden the knowledge for this research. Furthermore, it was possible to contact several European ports to acquire insights into the current port operations and the desire to introduce such tools. A performance dashboard prototype, created with simulated data through R, was demonstrated to the respondents during the structured interview. Finally, a BI framework has been developed to assist European ports in the decision-making of business intelligence tools to reduce the CO2 emission of cargo trucks.",

keywords = "Blockchain, Business Intelligence Tools, CO2 emission, Machine Learning, OLAP, Smart ports, SQL Server. Dashboard, WSN Sensor",

author = "Marco Hegger and Adriana Saraceni",

note = "data source: Primary data has been collected through semi-structured interviews and structured interviews. Sections 4.1 and 4.3 describe the participants.; 43rd IFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS 2024, APMS 2024 ; Conference date: 08-09-2024 Through 12-09-2024",

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Hegger, M & Saraceni, A 2024, Smart Port Sustainability: A Business Intelligence Framework for CO2 Reduction in Cargo Truck Operations. in M Thürer, R Riedel, G von Cieminski & D Romero (eds), Advances In Production Management Systems-production Management Systems For Volatile, Uncertain, Complex, And Ambiguous Environments, Apms 2024, Pt I. vol. 728, Springer Verlag, IFIP Advances in Information and Communication Technology, no. 728, pp. 309-323, 43rd IFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS 2024, Chemnitz, Saxony, Germany, 8/09/24. https://doi.org/10.1007/978-3-031-71622-5_21

Smart Port Sustainability: A Business Intelligence Framework for CO2 Reduction in Cargo Truck Operations. / Hegger, Marco; Saraceni, Adriana.
Advances In Production Management Systems-production Management Systems For Volatile, Uncertain, Complex, And Ambiguous Environments, Apms 2024, Pt I. ed. / Matthias Thürer; Ralph Riedel; Gregor von Cieminski; David Romero. Vol. 728 Springer Verlag, 2024. p. 309-323 (IFIP Advances in Information and Communication Technology; No. 728).

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceeding › Academic › peer-review

TY - GEN

T1 - Smart Port Sustainability

T2 - 43rd IFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS 2024

AU - Hegger, Marco

AU - Saraceni, Adriana

N1 - data source: Primary data has been collected through semi-structured interviews and structured interviews. Sections 4.1 and 4.3 describe the participants.

PY - 2024/1/1

Y1 - 2024/1/1

N2 - This research aims at investigating how to assist European ports in the decision-making of business intelligence tools to reduce the CO2 emission of cargo trucks. Thus, several scientific papers are analyzed during this research, and BI tools are selected based on sequence and integration. Thereafter, this research conducted interviews with field experts to discuss the selected BI tools and broaden the knowledge for this research. Furthermore, it was possible to contact several European ports to acquire insights into the current port operations and the desire to introduce such tools. A performance dashboard prototype, created with simulated data through R, was demonstrated to the respondents during the structured interview. Finally, a BI framework has been developed to assist European ports in the decision-making of business intelligence tools to reduce the CO2 emission of cargo trucks.

AB - This research aims at investigating how to assist European ports in the decision-making of business intelligence tools to reduce the CO2 emission of cargo trucks. Thus, several scientific papers are analyzed during this research, and BI tools are selected based on sequence and integration. Thereafter, this research conducted interviews with field experts to discuss the selected BI tools and broaden the knowledge for this research. Furthermore, it was possible to contact several European ports to acquire insights into the current port operations and the desire to introduce such tools. A performance dashboard prototype, created with simulated data through R, was demonstrated to the respondents during the structured interview. Finally, a BI framework has been developed to assist European ports in the decision-making of business intelligence tools to reduce the CO2 emission of cargo trucks.

KW - Blockchain

KW - Business Intelligence Tools

KW - CO2 emission

KW - Machine Learning

KW - OLAP

KW - Smart ports

KW - SQL Server. Dashboard

KW - WSN Sensor

U2 - 10.1007/978-3-031-71622-5_21

DO - 10.1007/978-3-031-71622-5_21

M3 - Conference article in proceeding

SN - 9783031716218

VL - 728

T3 - IFIP Advances in Information and Communication Technology

SP - 309

EP - 323

BT - Advances In Production Management Systems-production Management Systems For Volatile, Uncertain, Complex, And Ambiguous Environments, Apms 2024, Pt I

A2 - Thürer, Matthias

A2 - Riedel, Ralph

A2 - von Cieminski, Gregor

A2 - Romero, David

PB - Springer Verlag

Y2 - 8 September 2024 through 12 September 2024

ER -

Hegger M, Saraceni A. Smart Port Sustainability: A Business Intelligence Framework for CO2 Reduction in Cargo Truck Operations. In Thürer M, Riedel R, von Cieminski G, Romero D, editors, Advances In Production Management Systems-production Management Systems For Volatile, Uncertain, Complex, And Ambiguous Environments, Apms 2024, Pt I. Vol. 728. Springer Verlag. 2024. p. 309-323. (IFIP Advances in Information and Communication Technology; No. 728). doi: 10.1007/978-3-031-71622-5_21

Smart Port Sustainability: A Business Intelligence Framework for CO2 Reduction in Cargo Truck Operations

Abstract

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