More recently, the Chinese Government had been making appreciable efforts to stimulate and encourage entrepreneurial emission reductions. These efforts could be boosted by availability of dual asymmetric information about the adopted technology for efficient reduction and enterprises’ investment strategies, possibly leading to adverse selection and moral hazard. This paper incorporates Stackelberg game model and incentive mechanism theory to find a feasible solution to dual asymmetric information problem. Hence firstly, through application of linear function of the total emission, an emission reduction contract would be formulated for regulating incentive payments from government to supervisory authorities followed by derivation of a two stage principal-agent monitoring model based on the enterprise’s private information and action respectively. Some findings have been obtained through analysis of the monitoring models along with their comparison with the results of no monitoring scenario which confirm the effectiveness of hiring the supervisory authorities for monitoring of enterprises’ emission reduction, which, ultimately, would facilitate increasing payoff and efficient emission reduction. In this perspective, the action-based monitoring mechanism depicts overall government dominance. Several, managerial insights have also been provided for various scenarios and propositions and all the findings are illustrated numerically. It could prove highly beneficial and significant to the government in encouraging entrepreneurial emission reductions.
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DOI : 10.1051/ro/2020095
Keywords: Overconfidence, effort-dependent demand, delegation, salesforce compensation
@article{RO_2021__55_S1_S2455_0,
author = {Kegui, Chen and Xinyu, Wang and Min, Huang and Liang, Ren},
title = {Monitoring strategies of enterprise{\textquoteright}s emission reduction with asymmetric information},
journal = {RAIRO. Operations Research},
pages = {S2455--S2470},
year = {2021},
publisher = {EDP-Sciences},
volume = {55},
doi = {10.1051/ro/2020095},
mrnumber = {4223192},
zbl = {1469.91036},
language = {en},
url = {https://www.numdam.org/articles/10.1051/ro/2020095/}
}
TY - JOUR AU - Kegui, Chen AU - Xinyu, Wang AU - Min, Huang AU - Liang, Ren TI - Monitoring strategies of enterprise’s emission reduction with asymmetric information JO - RAIRO. Operations Research PY - 2021 SP - S2455 EP - S2470 VL - 55 PB - EDP-Sciences UR - https://www.numdam.org/articles/10.1051/ro/2020095/ DO - 10.1051/ro/2020095 LA - en ID - RO_2021__55_S1_S2455_0 ER -
%0 Journal Article %A Kegui, Chen %A Xinyu, Wang %A Min, Huang %A Liang, Ren %T Monitoring strategies of enterprise’s emission reduction with asymmetric information %J RAIRO. Operations Research %D 2021 %P S2455-S2470 %V 55 %I EDP-Sciences %U https://www.numdam.org/articles/10.1051/ro/2020095/ %R 10.1051/ro/2020095 %G en %F RO_2021__55_S1_S2455_0
Kegui, Chen; Xinyu, Wang; Min, Huang; Liang, Ren. Monitoring strategies of enterprise’s emission reduction with asymmetric information. RAIRO. Operations Research, Tome 55 (2021), pp. S2455-S2470. doi: 10.1051/ro/2020095
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