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Modeling the Intention to Use Carbon Footprint Apps

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

Standard

Modeling the Intention to Use Carbon Footprint Apps. / Sagawe, Arno; Funk, Burkhardt; Niemeyer, Peter.

Information Technology in Environmental Engineering: Proceedings of the 7th International Conference on Information Technologies in Environmental Engineering (ITEE2015). ed. / Jorge Marx Gómez; Brenda Scholtz. Springer, 2016. p. 139-150 (Springer Proceedings in Business and Economics).

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

Harvard

Sagawe, A, Funk, B & Niemeyer, P 2016, Modeling the Intention to Use Carbon Footprint Apps. in JM Gómez & B Scholtz (eds), Information Technology in Environmental Engineering: Proceedings of the 7th International Conference on Information Technologies in Environmental Engineering (ITEE2015). Springer Proceedings in Business and Economics, Springer, pp. 139-150, 7th ITEE International Conference - 2015, Port Elizabeth, South Africa, 14.07.15. https://doi.org/10.1007/978-3-319-25153-0_12

APA

Sagawe, A., Funk, B., & Niemeyer, P. (2016). Modeling the Intention to Use Carbon Footprint Apps. In J. M. Gómez, & B. Scholtz (Eds.), Information Technology in Environmental Engineering: Proceedings of the 7th International Conference on Information Technologies in Environmental Engineering (ITEE2015) (pp. 139-150). (Springer Proceedings in Business and Economics). Springer. https://doi.org/10.1007/978-3-319-25153-0_12

Vancouver

Sagawe A, Funk B, Niemeyer P. Modeling the Intention to Use Carbon Footprint Apps. In Gómez JM, Scholtz B, editors, Information Technology in Environmental Engineering: Proceedings of the 7th International Conference on Information Technologies in Environmental Engineering (ITEE2015). Springer. 2016. p. 139-150. (Springer Proceedings in Business and Economics). doi: 10.1007/978-3-319-25153-0_12

Bibtex

@inbook{9525939ff820413f8ea503d6431265ea,
title = "Modeling the Intention to Use Carbon Footprint Apps",
abstract = "Today, there is an increasing number of smartphone apps which support users to understand their personal carbon footprint that is being developed by them. But until now there are not many users. In this paper, we discuss the relevant concepts that drive intention of smartphone users to use carbon footprint apps (CFA). To do so, we apply the Technology Acceptance Model (TAM) and adapt it to the context of carbon footprint apps. Furthermore, we present the design of an empirical study with more than 200 participants. We suggest, to measure and discuss positive and negative effects on the intention to use CFA. This should help in future development of CFA.",
keywords = "Business informatics, Environmental Concern, Carbon Footprint, Technology Acceptance Model, Perceive Behavioral Control, Perceive Usefulness",
author = "Arno Sagawe and Burkhardt Funk and Peter Niemeyer",
year = "2016",
month = feb,
day = "5",
doi = "10.1007/978-3-319-25153-0_12",
language = "English",
isbn = "978-3-319-25152-3",
series = "Springer Proceedings in Business and Economics",
publisher = "Springer",
pages = "139--150",
editor = "G{\'o}mez, {Jorge Marx} and Brenda Scholtz",
booktitle = "Information Technology in Environmental Engineering",
address = "Germany",
note = "7th ITEE International Conference - 2015 : Technologies for a sustainable future, ITEE Conference 2015 ; Conference date: 14-07-2015 Through 16-07-2015",
url = "http://www.itee2015.org/",

}

RIS

TY - CHAP

T1 - Modeling the Intention to Use Carbon Footprint Apps

AU - Sagawe, Arno

AU - Funk, Burkhardt

AU - Niemeyer, Peter

N1 - Conference code: 7

PY - 2016/2/5

Y1 - 2016/2/5

N2 - Today, there is an increasing number of smartphone apps which support users to understand their personal carbon footprint that is being developed by them. But until now there are not many users. In this paper, we discuss the relevant concepts that drive intention of smartphone users to use carbon footprint apps (CFA). To do so, we apply the Technology Acceptance Model (TAM) and adapt it to the context of carbon footprint apps. Furthermore, we present the design of an empirical study with more than 200 participants. We suggest, to measure and discuss positive and negative effects on the intention to use CFA. This should help in future development of CFA.

AB - Today, there is an increasing number of smartphone apps which support users to understand their personal carbon footprint that is being developed by them. But until now there are not many users. In this paper, we discuss the relevant concepts that drive intention of smartphone users to use carbon footprint apps (CFA). To do so, we apply the Technology Acceptance Model (TAM) and adapt it to the context of carbon footprint apps. Furthermore, we present the design of an empirical study with more than 200 participants. We suggest, to measure and discuss positive and negative effects on the intention to use CFA. This should help in future development of CFA.

KW - Business informatics

KW - Environmental Concern

KW - Carbon Footprint

KW - Technology Acceptance Model

KW - Perceive Behavioral Control

KW - Perceive Usefulness

UR - http://www.scopus.com/inward/record.url?scp=85125396416&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-25153-0_12

DO - 10.1007/978-3-319-25153-0_12

M3 - Article in conference proceedings

SN - 978-3-319-25152-3

T3 - Springer Proceedings in Business and Economics

SP - 139

EP - 150

BT - Information Technology in Environmental Engineering

A2 - Gómez, Jorge Marx

A2 - Scholtz, Brenda

PB - Springer

T2 - 7th ITEE International Conference - 2015

Y2 - 14 July 2015 through 16 July 2015

ER -

Other publications by the same author(s)

Automated Invoice Processing: Machine Learning-Based Information Extraction for Long Tail Suppliers

Krieger, F., Drews, P. & Funk, B., 01.11.2023, In: Intelligent Systems with Applications. 20, 14 p., 200285.

Research output: Journal contributions › Journal articles › Research › peer-review

Editorial: Quantitative modeling of psychopathology using passively collected data

Jacobson, N. C., Funk, B. & Abdullah, S., 24.01.2023, In: Frontiers in Psychology. 13, 2 p., 1126971.

Research output: Journal contributions › Other (editorial matter etc.) › Research

Extraction of information from invoices - challenges in the extraction pipeline

Thiée, L. W., Krieger, F. & Funk, B., 2023, INFORMATIK 2023: Designing Futures: Zukünfte gestalten, 26. – 29. September 2023, Berlin. Klein, M., Krupka, D., Winter, C. & Wohlgemuth, V. (eds.). Bonn: Gesellschaft für Informatik e.V., p. 1777-1792 16 p. (GI-Edition: Lecture Notes in Informatics (LNI), Proceedings; vol. P-337).

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

Finding the Best Match — a Case Study on the (Text‑) Feature and Model Choice in Digital Mental Health Interventions

Zantvoort, K., Scharfenberger, J., Boß, L., Lehr, D. & Funk, B., 12.2023, In: Journal of Healthcare Informatics Research. 7, 4, p. 447-479 33 p., 00148.

Research output: Journal contributions › Journal articles › Research › peer-review

Parsing Causal Models – An Instance Segmentation Approach

Scharfenberger, J. & Funk, B., 08.06.2023, Intelligent Information Systems - CAiSE Forum 2023, Proceedings. Cabanillas, C. & Pérez, F. (eds.). Springer Science and Business Media Deutschland GmbH, p. 43-51 9 p. (Lecture Notes in Business Information Processing; vol. 477 LNBIP).

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

DOI