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A product or service usually has multiple measurable characteristics, and its performance on different measures may vary and may change over time. Multi-criterion and multi-period performance benchmarking presents a challenge for management to determine performance gaps among comparable products or services. The purpose of this paper is to propose a new performance benchmarking method to address this challenge.

The author develop this method by formulating two benchmarking functions: a differentiation function based on Shewhart average and standard deviation charts to distinguish the performance of products or services on a single measure, and a categorization function to classify each product’s or service’s overall performance across all measures. By systematically removing the lowest-performing products or services from comparison, the author use these functions iteratively to detect performance gaps.

Using this method, the author find performance gaps in each of three benchmarking applications of airports, hotels, and minivans, although a number of performance gaps are not obvious from the raw data.

This benchmarking study focuses on the quantifiable outcome performance of products and services.

This benchmarking method is generic and applicable to most products and services. It is robust not only for discovering performance gaps, but also for providing useful insights for managers to prioritize improvement efforts on individual performance measures.

The novelty of this benchmarking method lies in that it can not only find the “best overall” products or services for all performance measures, but can also pinpoint the “best-in-class” products or services as well as performance gaps for each performance measure. In addition, this paper presents several original ideas for performance benchmarking, including: using the control limits of Shewhart control charts to categorize performance gaps, systematically removing the lowest-performing products or services from comparison for the purpose of detecting hidden performance gaps, and using symbolic expressions to integrate benchmarking results from all measures and to show all performance gaps intuitively.

Website benchmarking theory and the website analysis method (WAM) are benchmark tested across non-commercial tropical tourism websites. The paper aims to discuss this issue.

The abridged WAM benchmarks 280 tropical tourism websites from four continental areas (Africa, Asia, Oceania, and The Americas) and presence or absence of website components objectively rank-scores. Across locations significant website benchmark score differences are determined. In all, 20 of these websites are ranked by an eight expert focus group. These experts also seek-out the existence of allocated common website components.

The abridged WAM approach is suitable for benchmarking tropical tourism websites. Website benchmarking scores at-level are determined. At the website, domain, and function levels significant continental area differences exist. Experts cross-check the study. They find it easier to rank websites with fewer components, and show split decisions when determining the existence of common website components.

This study’s abridged version of WAM uses publicly viewable components to show significant differences across website scores, and identifies some missing components for possible future inclusion on the website, and it also supports the WAM benchmarking theory approach.

Website managers/owners can apply WAM (or an abridged WAM) to benchmark their websites. WAM is theoretically supported and it systematically allows comparison against the universal set of components and/or against competitor websites. A full or abridged WAM approach to website benchmarking is preferable to subjective or survey-based approaches.

This study successfully applies the Cassidy and Hamilton (2016) theory and approach to practical website benchmarking.

The purpose of this paper is to develop an effective approach to decide design details using benchmarking to capture the existing practice in sustainable design.

This paper reports a systematic method for sustainable product design. The method uses benchmarks as references searching for design details to achieve sustainable solutions. Quality function deployment is used to guide the search process for competitive products using benchmarking to meet quantitative targets of product and to increase knowledge for sustainable design.

The proposed method can meet both functional and sustainable requirements of product design. 18.55 percent reduction in carbon equivalent emissions is achieved compared to benchmarks in wheelchair design. The research reveals that when weight, material and number of components used in product decrease, environmental footprints and cost of the product improve.

The research improves the existing method of sustainable product design. Both sustainable requirements and functional demands of product are identified from qualitative criteria to quantitative metrics using benchmarking and the life cycle assessment.

Literature-identified website benchmarking (WB) approaches are generally time consuming, survey based, with little agreement on what and how to measure website components. The purpose of this paper is to establish a theoretical approach to WB. A comprehensive design science research methodology (DSRM) artifact facilitates the evaluation of the website against the universal set of benchmark components. This knowledge allows managers to gauge/reposition their websites.

DSRM establishes a website analysis method (WAM) artifact. Across six activities (problem identification, solution objective, artifact design/development, artifact demonstration, artifact evaluation, results communication), the WAM artifact solves the DSRM-identified WB problem.

The WAM artifact uses 230 differentiated components, allowing managers to understand in-depth and at-level WB. Typological website components deliver interpretable WB scores. Website comparisons are made at domain (aesthetic, marketing, technical) and/or functional levels.

New/emergent components (and occasionally new functions) are included (and redundant components removed) as upgrades to the DSRM WAM artifact’s three domains and 28 functions. Such modifications help keep latest benchmarking comparisons (and/or website upgrades) optimized.

This DSRM study employs a dichotomous present/absent component approach, allowing the WAM artifact’s measures to be software programmed, and merged at three different levels, delivering a useful WB tool for corporates.

DSRM identifies the benchmarking problem. Rough-cut set-theory and mutual-exclusivity of components allow the causal-summing of typological website components into an objective WAM artifact WB solution. This new, comprehensive, objective-measurement approach to WB thus offers comparative, competitive, and website behavioral implications for corporates.

To measure, classify and compare web site functions' development.

The objectives were achieved by developing a methodology to measure, classify and compare web site functions development. The measurement was based on the presence (or absence) of 91 web site components. The classification was achieved using an applied correspondence analysis. The comparison was performed with respect to 4,485 company web sites from two provinces in Canada. A formal procedure involving 50 assistants was developed to collect data over 5,000 sites within a month period and a conceptual model was developed to interpret results.

Findings show that web site functions development could be described on a three dimensional space, the three axes corresponding to directions of development. The development status of the whole sample appeared as a cone in which five classes (or categories) of web sites could be identified and described with respect to their development profile. The development of 18 web site functions was also benchmarked with respect to observations within a class and with respect to some other characteristics like the industrial sector and the province where the company was located.

Web site functions development was evaluated only with respect to components accessible to the general public. Development of intranet and extranet were not evaluated and hence taken into account for overall web sites development.

This research project of web site functions development was part of a more comprehensive project aimed at evaluating and documenting the impact of using a web site on business processes. So, combining the results of the two projects, allowed the authors to advance suggestions of how web sites should be developed to generate value for companies.

The approach to web site functions development evaluation is original. The methodology could be replicated anytime. The typology that emerged from the analysis is unique. Moreover, given the large sample of 4,485 web sites, results are statistically valid.

In this paper, the aim is to propose a framework for utilizing quality function deployment (QFD) and benchmarking in combination to chalk out an improvement plan that redesigns or modifies existing processes to a point where they consume the least amount of resources while imparting the maximum value (in the sense of customer satisfaction) to the output.

Using a real world case study, the paper demonstrates that the marriage of two tools – QFD and benchmarking – is synergistic in its import and vital to a company's strategic and financial superiority.

The product and process design was improved by using the combination of QFD and benchmarking techniques discussed in the paper. As a result, the company accomplished significant financial and strategic results.

The case study includes competitiveness analysis at the first house of quality (HOQ) but not at the subsequent HOQ due to lack of information from the competitors. However, the paper demonstrates the competitiveness analysis at the first HOQ which can be extended to all subsequent HOQ.

The research would be useful to academicians and practitioners in developing their own integrated versions of QFD and benchmarking methodologies to improve their products and processes and gain strategic advantage.

Despite the mutual dependence between a firm's strategic and financial performance and the consequent dependence on market share and profitability, which can both be maximized using QFD and benchmarking, the research that employs both techniques is virtually non‐existent.

In this paper, a newly proposed hybridization algorithm namely constriction coefficient-based particle swarm optimization and gravitational search algorithm (CPSOGSA) has been employed for training MLP to overcome sensitivity to initialization, premature convergence, and stagnation in local optima problems of MLP.

In this study, the exploration of the search space is carried out by gravitational search algorithm (GSA) and optimization of candidate solutions, i.e. exploitation is performed by particle swarm optimization (PSO). For training the multi-layer perceptron (MLP), CPSOGSA uses sigmoid fitness function for finding the proper combination of connection weights and neural biases to minimize the error. Secondly, a matrix encoding strategy is utilized for providing one to one correspondence between weights and biases of MLP and agents of CPSOGSA.

The experimental findings convey that CPSOGSA is a better MLP trainer as compared to other stochastic algorithms because it provides superior results in terms of resolving stagnation in local optima and convergence speed problems. Besides, it gives the best results for breast cancer, heart, sine function and sigmoid function datasets as compared to other participating algorithms. Moreover, CPSOGSA also provides very competitive results for other datasets.

The CPSOGSA performed effectively in overcoming stagnation in local optima problem and increasing the overall convergence speed of MLP. Basically, CPSOGSA is a hybrid optimization algorithm which has powerful characteristics of global exploration capability and high local exploitation power. In the research literature, a little work is available where CPSO and GSA have been utilized for training MLP. The only related research paper was given by Mirjalili et al., in 2012. They have used standard PSO and GSA for training simple FNNs. However, the work employed only three datasets and used the MSE performance metric for evaluating the efficiency of the algorithms. In this paper, eight different standard datasets and five performance metrics have been utilized for investigating the efficiency of CPSOGSA in training MLPs. In addition, a non-parametric pair-wise statistical test namely the Wilcoxon rank-sum test has been carried out at a 5% significance level to statistically validate the simulation results. Besides, eight state-of-the-art meta-heuristic algorithms were employed for comparative analysis of the experimental results to further raise the authenticity of the experimental setup.

Quality function deployment (QFD) has been used to translate customer requirements into engineering characteristics of a product, while benchmarking was developed to search for the best industry practices, which will lead to exceptional performance through the implementation of these best practices. However, no attempt has been made to integrate QFD with benchmarking to identify the best practices of QFD model. This paper aims to classify the QFD models and thereby applying benchmarking process to propose the best practices of QFD model.

The fundamental benchmarking model developed by Camp has been used to benchmark the existing QFD models available in the literature.

Benchmarking the QFD models revealed about 36 QFD steps in the first phase of the house of quality. The tools used in solving for each practice are also reported.

The proposed model is conceptual and it requires validation by implementing the same in an organization to understand its effectiveness.

Utilizing the benchmarking process to develop the best practices of QFD model is an original concept.

To use quality function deployment (QFD)/benchmarking for building an optimal activity‐based costing (ABC) model using baseline information from five different Spanish hospitals.

The customer satisfaction benchmarking process in QFD is discussed along with the benefits of hierarchical benchmarks in specifying areas of strategic competition and the logically ensuing product/service strategic decision‐making requirements. A case study is presented to illustrate the use of two methodological approaches: benchmarking and QFD to obtain the final product of the paper: an optimal ABC.

The resulting outcome from the QFD/benchmarking analysis is an ABC model, which has the customer expectations and the requirements that hospitals are looking for.

Future research can benefit from this research by expanding the scope from hospitals to other types of industries in order to comparatively analyze the applicability of the proposed tools, and applying the same methodology to other hospitals for developing a model for a standardized costing system in health care industry.

With the outcomes produced by the methodology applied in this paper, hospital strategic decision makers can now have specifics on which to base decisions regarding the most appropriate allocation of time, human and capital resources.

The paper presents a new approach for developing an optimal ABC for healthcare by applying two important methodologies: benchmarking and QFD. The use and modification of these methodologies in healthcare are new to research for achieving a final ABC model that will easily identify any performance improvements.

Ant Colony Optimization and Particle Swarm Optimization represent two widely used Swarm Intelligence (SI) optimization techniques. Information processing using Multiple-Valued Logic (MVL) is carried out using more than two discrete logic levels. In this paper, we compare two the SI-based algorithms in synthesizing MVL functions. A benchmark consisting of 50,000 randomly generated 2-variable 4-valued functions is used for assessing the performance of the algorithms using the benchmark. Simulation results show that the PSO outperforms the ACO technique in terms of the average number of product terms (PTs) needed. We also compare the results obtained using both ACO-MVL and PSO-MVL with those obtained using Espresso-MV logic minimizer. It is shown that on average, both of the SI-based techniques produced better results compared to those produced by Espresso-MV. We show that the SI-based techniques outperform the conventional direct-cover (DC) techniques in terms of the average number of product terms required.