Purpose/significance Technology competition is a powerful weapon for enterprises to maintain their advantages in the new market environment. The fundamental purpose of this paper is to construct a ...framework suitable for small and medium-sized enterprises to identify technological opportunities, so as to tap potential technological development opportunities for enterprises and make full use of Limited R&D resources to obtain technological breakthrough and innovation. Method/process Benchmarking analysis was used as the main method to select the competitor benchmarking of the target enterprise from the two dimensions of technical proximity and technical capability. Combined with the situation of benchmarking enterprises and the overall technical situation of the industry, potential technology categories were divided, and a three-dimensional patent technology/function matrix was constructed to identify technical opportunities, and the vacuum cleaner industry was taken as an example to verify. Result/conclus
Existing formats for Sparse MatrixaVector Multiplication (SpMV) on the GPU are outperforming their corresponding implementations on multi-core CPUs. In this paper, we present a new format called ...Sliced COO (SCOO) and an efficient CUDA implementation to perform SpMV on the GPU using atomic operations. We compare SCOO performance to existing formats of the NVIDIA Cusp library using large sparse matrices. Our results for single-precision floating-point matrices show that SCOO outperforms the COO and CSR format for all tested matrices and the HYB format for all tested unstructured matrices on a single GPU. Furthermore, our dual-GPU implementation achieves an efficiency of 94% on average. Due to the lower performance of existing CUDA-enabled GPUs for atomic operations on double-precision floating-point numbers the SCOO implementation for double-precision does not consistently outperform the other formats for every unstructured matrix. Overall, the average speedup of SCOO for the tested benchmark dataset is 3.33 (1.56) compared to CSR, 5.25 (2.42) compared to COO, 2.39 (1.37) compared to HYB for single (double) precision on a Tesla C2075. Furthermore, comparison to a Sandy-Bridge CPU shows that SCOO on a Fermi GPU outperforms the multi-threaded CSR implementation of the Intel MKL Library on an i7-2700 K by a factor between 5.5 (2.3) and 18 (12.7) for single (double) precision.
This work presents a study of relative efficiency of some ports using the Data Development Analysis (DEA). During the work, some ports chosen for the study are presented, as well as defined ...variables, inputs and outputs for modeling, and the mathematic model based on linear programming. Next, the relative efficiency obtained in each port is presented, and a comparison among the ports is carried out from the benchmarking, proposing changes in order to optimize port operations.
This book covers recent advances in efficiency evaluations, most notably Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) methods. It introduces the underlying theories, shows ...how to make the relevant calculations and discusses applications. The aim is to make the reader aware of the pros and cons of the different methods and to show how to use these methods in both standard and non-standard cases. Several software packages have been developed to solve some of the most common DEA and SFA models. This book relies on R, a free, open source software environment for statistical computing and graphics. This enables the reader to solve not only standard problems, but also many other problem variants. Using R, one can focus on understanding the context and developing a good model. One is not restricted to predefined model variants and to a one-size-fits-all approach. To facilitate the use of R, the authors have developed an R package called Benchmarking, which implements the main methods within both DEA and SFA. The book uses mathematical formulations of models and assumptions, but it de-emphasizes the formal proofs - in part by placing them in appendices -- or by referring to the original sources. Moreover, the book emphasizes the usage of the theories and the interpretations of the mathematical formulations. It includes a series of small examples, graphical illustrations, simple extensions and questions to think about. Also, it combines the formal models with less formal economic and organizational thinking. Last but not least it discusses some larger applications with significant practical impacts, including the design of benchmarking-based regulations of energy companies in different European countries, and the development of merger control programs for competition authorities.
WHAT IS BENCHMARKING? CEAUȘESCU IONUT
Analele Universităţii Constantin Brâncuşi din Târgu Jiu : Seria Economie,
04/2022
2
Journal Article
Peer reviewed
Open access
Benchmarking is an activity that consists of comparing the own practices of the organization with those of other organizations. Benchmarking is the process by which the best methods used in an ...economic activity are sought, these methods allowing the company to improve its performance..
Six years and more than seventy publications later this paper looks back and analyzes the development of prognostic algorithms using C-MAPSS datasets generated and disseminatedby the prognostic ...center of excellence at NASA Ames Research Center. Among those datasets are five run-to-failure CMAPSS datasets that have been popular due to various characteristicsapplicable to prognostics. The C-MAPSS datasets pose several challenges that are inherent to general prognostics applications. In particular, management of high variability due to sensor noise, effects of operating conditions, and presence of multiple simultaneous fault modes are some factors that have great impact on the generalization capabilities of prognostics algorithms. More than seventy publications have used the C-MAPSS datasets for developing datadriven prognostic algorithms. However, in the absence of performance benchmarking results and due to common misunderstandings in interpreting the relationships between these datasets, it has been difficult for the users to suitably compare their results. In addition to identifying differentiating characteristics in these datasets, this paper also provides performance results for the PHM’08 data challenge wining entries to serve as performance baseline. This paper summarizes various prognostic modeling efforts that used C-MAPSS datasets and provides guidelines and references to further usage of these datasets in a manner that allows clear and consistent comparison between different approaches.
Purpose
The purpose of this paper is to address the knowledge gap on the use of benchmarking techniques as utilized by facilities management (FM) professionals for the purpose of identifying means to ...improve industry benchmarking practices and guide the direction of future FM benchmarking research.
Design/methodology/approach
Data were collected through surveying 585 FM practitioners representing various countries, organization sizes, types, industries. The data were summarized and analyzed through creating frequency tables, charts, and cross-tabulations. The survey results were compared to a previously published study on benchmarking use to identify the similarities and differences between benchmarking for FM functions vs core business functions.
Findings
The findings indicate that while FM-oriented benchmarking has been adopted at similar levels as other industries, FM-oriented benchmarking tends to be simplistic, lacks a strategic position in the company, often relies upon self-report survey data, is often performed by an individual with no formal benchmarking team and does not utilize process benchmarking or benchmarking networks. These findings emphasize the need for benchmarking education, advocacy for FM as a strategic business partner, the development of verified data sources and networks specifically for the unique greater facilities management field functions.
Practical implications
These findings provide needed data on the state of FM practitioner use of benchmarking specifically for FM functions in North America. The results can be used as an assessment for the industry, to improve practitioner use and knowledge, and to identify further avenues for academic study.
Originality/value
The value of this study lies in filling in identified knowledge gaps on how FM practitioners are using benchmarking in practice. These data are absent from the research literature and offer the potential to help bridge the academic-practitioner divide to ensure that future research will focus on addressing practitioner needs for the industry.
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