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Operational Performance Evaluation of E-government Microblogs Under Emergencies Based on a DEA Method

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Abstract

Microblogging has become a crucial channel for e-governments to interact with the public and has been evolving as a powerful and promising tool to address emergency management. The operational performance of an e-government microblog under emergencies plays a key role in shaping the e-government’s overall performance. This study creatively proposes a novel multi-indicator system for evaluating this operational performance in the life cycles of emergencies and applies these multiple indicators in a data envelopment analysis method to establish an evaluation model. Twenty-four e-government microblogs concentrating on the bus crash emergency in the Wanzhou district of Chongqing city are evaluated by this model. The evaluation results indicate that the proposed multi-indicator system and evaluation model are feasible and effective. This study’s findings indicate that e-governments should be encouraged to attach great importance to microblogs, pay direct attention to emergencies during their life cycles, concentrate on multi-stage evaluations to discover their performance changes across the “turning points” of emergencies, and collaborate with superior or subordinate e-governments to improve their microblogs’ operational performances.

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Notes

  1. Government Affairs Index Microblog Impact Report published in 2018 People’s Daily, http://yuqing.people.com.cn/n1/2017/0119/c209043-29,036,185.html.

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Acknowledgements

This work was supported by the National Natural Science Foundation, China (No. 71771195, No. 71401153). Many thanks to the local municipal and district people’s governments, public security bureaus (PSBs) and transport agencies for their help during online mining and offline survey for data collection in the case study.

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Correspondence to Qingqi Long.

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Long, Q., Song, K. Operational Performance Evaluation of E-government Microblogs Under Emergencies Based on a DEA Method. Inf Syst Front 24, 1–18 (2022). https://doi.org/10.1007/s10796-021-10171-3

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