Pāriet uz galveno navigāciju Pāriet uz meklēšanu Pāriet uz galveno saturu

Data-driven Analysis of Workforce Flow for Advancing Green and Circular Organizational Practices

  • ABC Software

Zinātniskās darbības rezultāts: Devums žurnālamKonferences zinātniskais rakstskoleģiāli recenzēts

Kopsavilkums

Organizations increasingly recognize the importance of workflow management in achieving resource efficiency and environmental goals. This study presents a data-driven approach to monitoring and analysing employee workflow as an integral part of green and circular organizational systems. By incorporating digital activity data such as software usage patterns, communication frequency, meeting durations, and the intensity of multitasking, organizations can identify inefficiencies, digital waste, and work practices that generate unnecessary energy consumption. The developed framework interprets workflow as a micro-level circularity mechanism, where the efficient circulation of time, attention, and digital resources reduces the overall environmental footprint of an organization's operations. Continuous monitoring of digital behaviour makes it possible to detect patterns of excessive cognitive load, redundant communication, or fragmented work, all of which frequently contribute to unnecessary time and energy consumption in the digital environment. Empirical analysis shows that optimized workflow models are closely linked to improved resource utilization, reduced emissions and increased employee well-being, thus creating synergies between human resource and technological process efficiency within the framework of a circular economy. The results indicate that digital monitoring systems can serve as an effective tool for sustainable management, promoting balanced workloads, energy-efficient work habits and data-driven decision-making. The study contributes to the emerging research field of “green digitalization” by interpreting workflow monitoring as a strategic tool for achieving both economic and environmental goals. It offers an analytical framework for organizations that want to integrate data analytics into their sustainability management systems, promoting the coordinated development of technological innovation and ecological responsibility.

OriģinālvalodaAngļu
Lapas (no-līdz)645-652
ŽurnālsInternational Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM
Sējums25
Izdevuma numurs4.2
DOIs
Publikācijas statussPublicēts - 2025
Pasākums25th International Multidisciplinary Scientific GeoConference: Energy and Clean Technologies, SGEM 2025 - Vienna, Austrija
Ilgums: 3 dec. 20256 dec. 2025

ANO IAM

Šis izpildes rezultāts palīdz sasniegt šādus ANO ilgtspējīgas attīstības mērķus (IAM)

  1. 7. IAM — Tīra Enerģija par Pieejamu Cenu
    7. IAM — Tīra Enerģija par Pieejamu Cenu
  2. 12. IAM — Atbildīgs Patēriņš un Ražošana
    12. IAM — Atbildīgs Patēriņš un Ražošana
  3. 17. IAM — Partnerības Mērķu Sasniegšanai
    17. IAM — Partnerības Mērķu Sasniegšanai

OECD Zinātnes nozare

  • 1.5 Zemes zinātnes, fiziskā ģeogrāfija un vides zinātnes
  • 5.2 Ekonomika un uzņēmējdarbība

Nospiedums

Uzziniet vairāk par pētniecības tēmām “Data-driven Analysis of Workforce Flow for Advancing Green and Circular Organizational Practices”. Kopā tie veido unikālu nospiedumu.

Citēt šo