Késsia Thais Cavalcanti Nepomuceno

Browsing is a prevalent activity on the World Wide Web, and users usually demonstrate significant expectations for expeditious information retrieval and seamless transactions. This article presents a comprehensive performance evaluation of the most frequently accessed webpages in recent years using Data Envelopment Analysis (DEA) adapted to the context (inverse DEA), comparing their performance under two distinct communication protocols: TCP/IP and QUIC. To assess performance disparities, parametric and non-parametric hypothesis tests are employed to investigate the appropriateness of each website’s communication protocols. We provide data on the inputs, outputs, and efficiency scores for 82 out of the world’s top 100 most-accessed websites, describing how experiments and analyses were conducted. The evaluation yields quantitative metrics pertaining to the technical efficiency of the websites and efficient benchmarks for best practices. Nine websites are considered efficient from the point of view of at least one of the communication protocols. Considering TCP/IP, about 80.5% of all units (66 webpages) need to reduce more than 50% of their page load time to be competitive, while this number is 28.05% (23 webpages), considering QUIC communication protocol. In addition, results suggest that TCP/IP protocol has an unfavorable effect on the overall distribution of inefficiencies.

For strategic reasons, benchmarking best practices from efficient competitors is not usual in many data envelopment analysis (DEA) applications. Even for industries composed of multiple branches, providing information about efficient practices for their peers can jeopardize results for those branches if they compete for market, resources or recognition by the central administration. In this work, a time‐series adaptation for the DEA directional model is proposed as an alternative for coping with this problem. The methodological approach has three stages for this benchmarking to occur: Data, Information and Knowledge Extraction. In the first stage, we compare the same unit in different moments to identify efficient periods instead of efficient competitors. As a result, successful performance strategies are investigated using the bibliometric coupling of employees' relevant statements in the second and third stages. The application in a branch of the Brazilian Federal Savings Bank allowed an internal benchmarking of efficient periods when specific performance incentives, innovative processes, competitive strategies, and human resource changes were adopted for improving the unit's performance.

Data envelopment analysis (DEA) is a powerful nonparametric engineering tool for estimating technical efficiency and production capacity of service units. Assuming an equally proportional change in the output/input ratio, we can estimate how many additional medical resource health service units would be required if the number of hospitalizations was expected to increase during an epidemic outbreak. This assessment proposes a two-step methodology for hospital beds vacancy and reallocation during the COVID-19 pandemic. The framework determines the production capacity of hospitals through data envelopment analysis and incorporates the complexity of needs in two categories for the reallocation of beds throughout the medical specialties. As a result, we have a set of inefficient healthcare units presenting less complex bed slacks to be reduced, that is, to be allocated for patients presenting with more severe conditions. The first results in this work, in collaboration with state and municipal administrations in Brazil, report 3772 beds feasible to be evacuated by 64% of the analyzed health units, of which more than 82% are moderate complexity evacuations. The proposed assessment and methodology can provide a direction for governments and policymakers to develop strategies based on a robust quantitative production capacity measure.