| Title |
A process-oriented model to measure product carbon footprint: an exploratory study based on multiple cases |
| ID_Doc |
18830 |
| Authors |
Hu, JL; Shi, YJ; Cheng, Y; Liu, Z |
| Title |
A process-oriented model to measure product carbon footprint: an exploratory study based on multiple cases |
| Year |
2023 |
| Published |
|
| DOI |
10.1080/09537287.2023.2266410 |
| Abstract |
Climate change is global challenge and decarbonisation becomes top agenda for manufacturing firms. As it is generally recognized that only the measured get managed, an understanding and measuring of the Product Carbon Footprint (PCF) is now needed. International standards have provided the basic steps for carbon footprint measurement, yet, in practice, there is knowledge insufficiency and high cost. This paper aims to answer the research question: 'How can companies conduct PCF measurement projects effectively?'. This research adopts the qualitative method with multiple case studies. Data is collected through interviews with operation managers and the sustainability specialists of nine manufacturing companies, with a focus on the motivation and details of activities relating to their PCF measurement projects. Through within-case and cross-case analysis, a process model is proposed alongside the identification of three types of PCF, trial-oriented, process-oriented, and market-oriented PCF. A series of tailored measurement process models are further developed according to the PCF scenarios. The holistic process model contributes to the understanding of a PCF measurement that is based on empirical evidence. Practically, the process model can serve as a 'cookbook' to implement PCF measurement projects. |
| Author Keywords |
Product carbon footprint; carbon footprint measurement; PAS 2050; sustainability |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:001078549300001 |
| WoS Category |
Engineering, Industrial; Engineering, Manufacturing; Operations Research & Management Science |
| Research Area |
Engineering; Operations Research & Management Science |
| PDF |
https://www.tandfonline.com/doi/pdf/10.1080/09537287.2023.2266410?needAccess=true
|