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An Empirical Comparison of Discrete Choice Models for Mining Stakeholder Analysis

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Abstract

This research sought to facilitate improved stakeholder analysis in mining by providing further insights into the preferences of local community members using discrete choice theory. While recent research has demonstrated the usefulness of discrete choice theory in mining stakeholder analysis, no previous work has examined which discrete choice model (DCM) is most suitable. This paper provides a research note on a case study in a mining community that was performed to compare three DCMs. After a thorough examination of the benefits and deficiencies of all models, this study concludes that the conditional logit model stratified by questions is the most useful DCM for mining stakeholder analysis. The recommendation is based on the usefulness and accuracy (ability to match the survey data) of this model.

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Notes

  1. Percent concordant—the percent of pairs in which their corresponding prediction probability for the observation with the desirable event is higher than the non-event ones.

  2. Percent discordant—the percent of pairs in which their corresponding prediction probability for the observation with the desirable event is lower than the non-event ones.

  3. Percent tied—the percent of pairs in which their corresponding prediction probability for the observation with the desirable event is equal to the non-event ones.

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Funding

This work was financially supported by the Key Laboratory of Western Mine Exploitation and Hazard Prevention, Ministry of Education (grant no. SKLCRKF1916), Natural Science Foundation of Chongqing (cstc2020jcyj-msxmX1000), and Venture and Innovation Support Program for Chongqing Overseas Returnees (grant no.cx2018114).

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Authors and Affiliations

  1. Key Laboratory of Hydraulic and Waterway Engineering of the Ministry of Education, College of River and Ocean Engineering, Chongqing Jiaotong University, Chongqing, 400074, China

    Sisi Que, Yumin Wang & Shaochun Yuan

  2. State Key Laboratory of Coal Resources in Western China, Xi’an University of Science and Technology, Xi’an, 710054, China

    Sisi Que & Ziwei Ding

  3. Mining and Explosives Engineering, Missouri University of Science and Technology, Rolla, MO, 65409, USA

    Kwame Awuah-Offei

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  1. Sisi Que
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  2. Kwame Awuah-Offei
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  3. Yumin Wang
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  4. Ziwei Ding
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  5. Shaochun Yuan
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Correspondence to Yumin Wang.

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On behalf of all authors, the corresponding author declares no competing interests.

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Appendices

Appendix 1 Survey methodology

Table 4 Final list of four blocks of 16 mining projects attributes with three levels each
Full size table
Table 5 Demographic distribution of participants
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Appendix 2 Full survey

http://web.mst.edu/~kabp3/jem2015supplement.htm

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Que, S., Awuah-Offei, K., Wang, Y. et al. An Empirical Comparison of Discrete Choice Models for Mining Stakeholder Analysis. Mining, Metallurgy & Exploration 39, 2121–2132 (2022). https://doi.org/10.1007/s42461-021-00522-8

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