{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T17:27:39Z","timestamp":1754155659383,"version":"3.41.2"},"reference-count":29,"publisher":"Emerald","issue":"4","license":[{"start":{"date-parts":[[2020,7,2]],"date-time":"2020-07-02T00:00:00Z","timestamp":1593648000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IMDS"],"published-print":{"date-parts":[[2020,7,2]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title><jats:p>Banking is the key industry to guarantee the core leading role of finance in the process of economic development. It is important to study the bank efficiency and optimal allocation of bank\u2019s resources. The purpose of our paper is to study the optimal allocation of resources between the bank savings system and loan system under the premise of environmental heterogeneity.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title><jats:p>We use a two-stage meta-frontier Data Envelopment Analysis model to solve the relative efficiency of each city branch and use the multivariate statistical tools to analyze the empirical results.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Findings<\/jats:title><jats:p>This paper measures the relative efficiency of 16 Bank Branches of a state-owned bank in Anhui province considering regional heterogeneity. Based on the optimal resource allocation, we get the two-stage operation performance of all banks under group-frontier and meta-frontier and analyze the impact of the technical differences between the branches.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title><jats:p>This study has a positive guiding significance for the banking industry to improve its operational efficiency in various business practices in the new era of big data. It will also provide practical suggestions and support for the government and relevant departments in the process of formulating macro-policies to ensure the healthy and stable development of the banking industry.<\/jats:p><\/jats:sec>","DOI":"10.1108\/imds-10-2019-0541","type":"journal-article","created":{"date-parts":[[2020,7,2]],"date-time":"2020-07-02T05:35:45Z","timestamp":1593668145000},"page":"940-963","source":"Crossref","is-referenced-by-count":4,"title":["Bank supply chain efficiency analysis based on regional heterogeneity: a data-driven empirical 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