SELECTING SUSTAINABILITY KEY PERFORMANCE INDICATORS FOR SMART LOGISTICS ASSESSMENT
Research output: Contribution to journal › Article › Research › peer-review
Standard
In: Acta logistica, Vol. 9.2022, No. 4, 28.12.2022, p. 467-478.
Research output: Contribution to journal › Article › Research › peer-review
Harvard
APA
Vancouver
Author
Bibtex - Download
}
RIS (suitable for import to EndNote) - Download
TY - JOUR
T1 - SELECTING SUSTAINABILITY KEY PERFORMANCE INDICATORS FOR SMART LOGISTICS ASSESSMENT
AU - Lenort, Radim
AU - Wicher, Pavel
AU - Samolejova, Andrea
AU - Zsifkovits, Helmut
AU - Raith, Chiara
AU - Miklautsch, Philipp
AU - Pelikanova, Jana
PY - 2022/12/28
Y1 - 2022/12/28
N2 - The application of smart technologies and applications is becoming increasingly common in the logistics processes of companies and supply chains. However, standard logistics indicators are still used to evaluate their performance, which contradicts the sustainable development strategy of many industrial enterprises and their supply chains. Thus, the article aims to design a methodology for selecting sustainability key performance indicators (SKPIs) suitable for assessing smart logistics and its technologies and applications. The research relies on cluster analysis of the SKPIs recommended in the relevant literature, frequency analysis of indicators used in practice and their comparison. The cluster analysis showed that the primary attention in the references is given to sustainability’s economic andenvironmental dimensions. Most frequently, the authors highlighted the importance of the following indicators: production-related costs and investments, planning performance and quality, customer satisfaction, energy efficiency,waste intensity and treatment, emissions, and resource efficiency. On the contrary, the frequency analysis corroborated that leading industrial enterprises paid more-or-less balanced attention to all areas of sustainability, but at the companylevel. The article’s primary result constitutes a methodology comprising six steps, respecting the results of the analyses carried out: (1) Sustainability objectives definition; (2) Establishing SKPIs cluster pool; (3) Definition of criteria forselecting SKPIs clusters; (4) Selection of SKPIs clusters; (5) Definition of SKPIs and their parameters; and (6) Development of SKPIs hierarchical structure.
AB - The application of smart technologies and applications is becoming increasingly common in the logistics processes of companies and supply chains. However, standard logistics indicators are still used to evaluate their performance, which contradicts the sustainable development strategy of many industrial enterprises and their supply chains. Thus, the article aims to design a methodology for selecting sustainability key performance indicators (SKPIs) suitable for assessing smart logistics and its technologies and applications. The research relies on cluster analysis of the SKPIs recommended in the relevant literature, frequency analysis of indicators used in practice and their comparison. The cluster analysis showed that the primary attention in the references is given to sustainability’s economic andenvironmental dimensions. Most frequently, the authors highlighted the importance of the following indicators: production-related costs and investments, planning performance and quality, customer satisfaction, energy efficiency,waste intensity and treatment, emissions, and resource efficiency. On the contrary, the frequency analysis corroborated that leading industrial enterprises paid more-or-less balanced attention to all areas of sustainability, but at the companylevel. The article’s primary result constitutes a methodology comprising six steps, respecting the results of the analyses carried out: (1) Sustainability objectives definition; (2) Establishing SKPIs cluster pool; (3) Definition of criteria forselecting SKPIs clusters; (4) Selection of SKPIs clusters; (5) Definition of SKPIs and their parameters; and (6) Development of SKPIs hierarchical structure.
U2 - 10.22306/al.v9i4.350
DO - 10.22306/al.v9i4.350
M3 - Artikel
VL - 9.2022
SP - 467
EP - 478
JO - Acta logistica
JF - Acta logistica
SN - 1339-5629
IS - 4
ER -