Carbon Footprint: A study of key components of pro-environmental

Gravitiani, E.; Mulia, N. W.; Ratnadewati, A.; Cahyaningsih, D. T.

Carbon Footprint: A study of key components of pro-environmental

Articles in Press, Accepted Manuscript
Available Online from 19 May 2026

International Journal of Human Capital in Urban Management

Document Type : ORIGINAL RESEARCH ARTICLE

Authors

E. Gravitiani ¹

N. W. Mulia ¹

A. Ratnadewati ²

D. T. Cahyaningsih ³

¹ Economic Development, Faculty of Economic and Business, Universitas Sebelas Maret, Surakarta, Indonesia

² Magister of Economic and Study Development, Faculty of Economic and Business, Universitas Sebelas Maret, Surakarta, Indonesia

³ Faculty of Law, Universitas Sebelas Maret Surakarta, Indonesia

Abstract

BACKGROUND AND OBJECTIVES: Carbon emissions from the daily activities of urban populations are a primary contributor to climate change. The city of Surakarta, characterized by high mobility and significant emissions, necessitates an approach that emphasizes individual participation in efforts to reduce carbon footprints. This research aims to assess the community's willingness to reduce their carbon footprint based on five key indicators: housing, food, waste and water management, energy use, and transportation. Additionally, an analysis is conducted to identify the dominant factors influencing the community's preferences for environmentally friendly behavior.
METHODS: This study was conducted across five sub-districts in Surakarta City: Mojosongo, Sumber, Jayengan, Serengan, and Sondakan, selected for their high levels of urban activity and environmental relevance. The analytical method employed was Principal Component Analysis, a multivariate statistical technique used to reduce the dimensions of data and identify latent structures within a set of correlated variables. Principal Component Analysis enabled the researchers to extract principal components that represent key behavioral dimensions related to the willingness to decrease carbon footprint. The analysis was performed using STATA-13 and Minitab software for statistical computation and data visualization.
FINDINGS: The research findings indicate that the primary factors influencing WDC are community preferences regarding energy efficiency, waste management, and food consumption, which collectively account for 49.7% of the variability. The preference for sustainable living spaces and environmentally friendly transportation emerges as the second major factor, explaining 21.7% of the variability. The overall willingness of the community to reduce its carbon footprint is categorized as moderate. Among the five sub-districts, Jayengan exhibits the highest WDC index at 1.30, followed by Sumber (1.19), Semanggi (1.14), and both Sondakan and Mojosongo, which have the lowest indices of 1.10 each.
CONCLUSION: Research shows that residents in Surakarta City's five sub-districts have a moderate desire to lower their carbon footprint. Although awareness and concern, particularly about housing and transportation, are increasing, this has not yet translated into strong actions across all behaviors.

Keywords

Carbon footprint

Willingness to decrease

Principal Component Analysis (PCA)

Environmental behavior

Subjects

Urban ecology and related environmental concerns

Abdi, H.; Williams, L.J., (2010). Principal component analysis. WIREs Comp Stat., 2: 433–459 (27 pages).

Abdillah, A.; Buchari, R.A.; Widianingsih, I.; Nurasa, H., (2023). Climate change governance for urban resilience for Indonesia: A systematic literature review. Cogent Soc. Sci., 9(1): 2235170 (18 pages).

Arabiun, A., Tajpour, M.; Zahedi, M.R., (2024). The effect of digital leadership on the performance of

businesses: The mediating role of organizational entrepreneurship. International Journal of Human Capital in Urban Management, 9(1): 17–28 (12 pages).

Batalla-Bejerano, J.; Trujillo-Baute, E.; Villa-Arrieta, M., (2020). Smart meters and consumer behaviour: Insights from the empirical literature. Energy Policy, 144: 111610 (9 pages).

Bilsky, E.; Moreno, A.C.; Fernández Tortosa, A., (2021). Local governments and SDG localisation: Reshaping multilevel governance from the bottom. J. Hum. Dev. Capab., 22(4): 713–724 (12 pages).

Callahan, C.W.; Mankin, J.S., (2022). Globally unequal effect of extreme heat on economic growth. Science, 377: 43–45 (3 pages).

Ciambra, A.; Stamos, I., (2023). Localizing and monitoring climate neutrality through the Sustainable Development Goals (SDGs) framework: The case of Madrid. Sustainability, 15: 4819 (18 pages).

Fatati, I.; Puspitasari, D., (2015). Analisis faktor-faktor yang mempengaruhi pemilihan mal sebagai tempat berbelanja. Ind. Eng. Online J., 4(Page 4).

Huang, L.; Yoshida, Y.; Li, Y.; Cheng, N.; Xue, J.; Long, Y., (2024). Sustainable lifestyle: Quantification and determining factors analysis of household carbon footprints in Japan. Energy Policy, 186: 114016 (11 pages).

Institute for Essential Services Reform (IESR), (2023). Indonesia’s energy transformation to zero emission. IESR.

International Energy Agency (IEA), (2022). Indonesia: Emission. IEA.

IPCC, (2022). Climate change 2022 – Mitigation of climate change: Working Group III – Contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. IPCC Report.

Ivanova, D.; Barrett, J.; Wiedenhofer, D.; Macura, B.; Callaghan, M.; Creutzig, F., (2020). Quantifying the potential for climate change mitigation of consumption options. Environ. Res. Lett., 15(9): 094001 (16 pages).

Jia, K.; Sheng, Q.; Liu, Y.; Yang, Y.; Dong, G.; Qiao, Z., (2024). A framework for achieving urban sustainable development goals (SDGs): Evaluation and interaction. Sustain. Cities Soc., 114: 105780 (14 pages).

Khanam, T.; Rahman, A.; Xiaoqian, X.; Mola-Yudego, B.; Moula, M.M.E.; Pelkonen, P., (2022). Assessing the awareness and willingness of European experts to reduce their carbon footprint in everyday consumption. Environ. Impact Assess. Rev., 97: 106889 (13 pages).