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A review of benchmarking literature revealed that there are different types of benchmarking and a plethora of benchmarking process models. In some cases, a model has been uniquely developed for performing a particular type of benchmarking. This poses the following problems: it can create confusion among the users as to whether they should use only the unique benchmarking model that has been developed for particular type or they can use any model for any type of benchmarking; a user may find it difficult when it becomes necessary to choose a best model from the available models, as each model varies in terms of the number of phases involved, number of steps involved, application, etc. Hence, this paper aims to question the fundamental classification scheme of benchmarking and thereby the unique benchmarking models that are developed for each type of benchmarking. Further it aims to propose a universal benchmarking model, which can be applied for all types of benchmarking.

The fundamental benchmarking model developed by Camp has been used to benchmark the existing models, irrespective of the type of benchmarking, to identify the best practices in benchmarking.

Benchmarking the benchmarking models revealed about 71 steps in which around 13 steps have been addressed by many researchers. The remaining unique steps were considered to be the best practices in benchmarking.

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

Though some of the methodologies used in this paper are already available in the literature, their context of application in the field of benchmarking is new. For example, utilizing the benchmarking process itself to improve the existing benchmarking process is an original concept.

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.

This conceptual paper aims to propose the evidence-based benchmarking model that bridges standard benchmarking practices with evidence-based management (EBMgt) principles and lessens tensions between two opposite views of benchmarking as a useful management tool vs a management hype and fashion.

This conceptual paper is based on the critical reasoning, analysis and integration of so far largely separated research fields of benchmarking and EBMgt. The author employs a method of conceptual model building to identify connections between standard benchmarking model and EBMgt practices and to explain how a sequence of benchmarking events supplemented by EBMgt principles might lead to more reliable managerial decision-making.

The author argues that although there are no common benchmarking procedures, it is possible to identify a standard benchmarking model that resonates in most contemporary benchmarking procedures and consists of four main phases: plan, do, check and act (PDCA). The author integrated this standard model with EBMgt practices of searching for evidence in four sources of information and a six-step critical thinking process to put forward the model of evidence-based benchmarking.

The proposed model is a novel, comprehensive framework that puts together so far incompatible practices of benchmarking and EBMgt. The model clears up existing conceptual confusions around “casual” benchmarking and advances contemporary understanding of benchmarking practices. The model of evidence-based benchmarking might act as a practical, heuristic tool improving the quality of the managerial decisions and thus positively influencing the bottom line of business performance.

Gillette’s historically successful “razor and blade” business model (RBM) has been a promising benchmark for multiple businesses across diverse industries worldwide in the past several decades. The extant literature deals with very few nuances of this business model notwithstanding the fact that there are several variants of this business model being put to practical use by firms in diverse industries in grossly metaphorically equivalent situations.

This study adopts the 2 × 2 truth table framework from the domains of mathematical logic and combinatorics in fleshing out all possible (four logical possibilities) variants of the razor and blade business model for further analysis. This application presents four mutually exclusive yet collectively exhaustive possibilities on any chosen dimension. Two major dimensions (viz., provision of subsidy and intra- or extra-firm involvement in the making of razors or blades or both) form part of the discussion in this paper. In addition, this study synthesizes and streamlines entrepreneurial wisdom from multiple intra-industry and inter-industry benchmarks in terms of real-time firms explicitly or implicitly adopting several variants of the RBM that suit their unique context and idiosyncratic trajectory of evolution in situations that are grossly reflective of the metaphorically equivalent scenario of razor and recurrent blades. Inductive method of research is carried out with real-time cases from diverse industries with a pivotally common pattern of razor and blade model in some form or the other.

Several new variants of the razor and blade model (much beyond what the extant literature explicitly projects) have been discovered from the multiple metaphorically equivalent cases of RBM across industries. All of these expand the portfolio of options that relevant entrepreneurial firms can explore and exploit the best possible option chosen from them, given their unique context and idiosyncratic trajectory of growth.

This study has enriched the literature by presenting and analyzing a more inclusive or perhaps comprehensive palette of explicit choices in the form of several variants of the RBM for the relevant entrepreneurial firms to choose from. Future research can undertake the task of comparing these variants of RBM with those of upcoming servitization business models such as guaranteed availability, subscription and performance-based contracting and exploring the prospects of diverse combinations.

Smart entrepreneurial firms identify and adopt inspiring benchmarks (like razor and blade model whenever appropriate) duly tweaked and blended into a gestalt benchmark for optimal profits and attractive market shares. They target diverse market segments for tied-goods with different variants or combinations of the relevant benchmarks in the form of variegated customer value propositions (CVPs) that have unique and enticing appeal to the respective market segments.

Value-sensitive customers on the rise globally choose the option that best suits them from among multiple alternatives offered by competing firms in the market. As long as the ratio of utility to price of such an offer is among the highest, even a no-frills CVP may be most appealing to one market segment while a plush CVP may be tempting to yet another market segment simultaneously. While professional business firms embrace resource leverage practices consciously, amateur customers do so subconsciously. Each party subliminally desires to have the maximum bang-to-buck ratio as the optimal return on investment, given their priorities ceteris paribus.

Prior studies on the RBM have explicitly captured only a few variants of the razor and blade model. This study is perhaps the first of its kind that ferrets out many other variants (more than ten) of the razor and blade model with due simplification and exemplification, justification and demystification.

Building energy benchmarking is required for adopting an energy certification scheme, promoting energy efficiency and reducing energy consumption. It demonstrates the current level of energy consumption, the value of potential energy improvement and the prospects for additional savings. This paper aims to create a new data envelopment analysis (DEA) model that overcomes the limitations of existing models for building energy benchmarking.

Data preparation: the findings of the literature search and subject matter experts’ inputs are used to construct the DEA model. Particularly, it is ensured that the included variables would not violate the fundamental assumption of DEA modeling, DEA convexity axiom. New DEA formulation: controllable and non-controllable variables, e.g. weather conditions, are differentiated in the new formulation. A new approach is used to identify outliers to avoid skewing the efficiency scores for the rest of the buildings under consideration. Efficiency analysis: three distinct efficiencies are computed and analyzed in benchmarking building energy: overall, pure technical, and scale efficiency.

The proposed DEA approach is successfully applied to a data set provided by a utility management and energy services company that is active in the multifamily housing industry. Building characteristics and energy consumption of 124 multifamily properties in 15 different states in the USA are found in the data set. Buildings in this data set are benchmarked using the new DEA energy benchmarking formulation. Building energy benchmarking is also conducted in a time series manner showing how a particular building performs across the period of 12 months compared with its peers.

The proposed research contributes to the body of knowledge in building energy benchmarking through developing a new outlier detection method to mitigate the impact of super-efficient and super-inefficient buildings on skewing the efficiency scores of the other buildings; avoiding ratio variables in the DEA formulation to adhere to the convexity assumption that existing DEA methods do not follow; and distinguishing between controllable and non-controllable variables in the DEA formulation. This research contributes to the state of practice through providing a new energy benchmarking tool for facility managers and building owners that strive to relatively rank the energy-efficiency of their properties and identify low-performing properties as investment targets to enhance energy efficiency.

To provide a more requirements‐driven workload model for eXtensible Markup Language (XML) benchmark over the electronic data exchange and management in collaborative commerce.

A three‐component workload requirements model is formulated. They are the XML object model, the XML query operation model, and the control model. The object model extended from W3C data model gives a set of more generic data and document model. The query model enhanced from current and common benchmarks gives a more generalized set of standard and open queries against XML data and documents. The control model compiled from TPC and industry standards gives a set of more systematic experimental variables and performance metrics to set up and conduct an XML benchmark.

The long‐standing research issues of domain dependency and application irreproducibility of XML benchmarks are addressed, tackled and offered with a novel and computer‐aided alternative. Precision and cost‐effectiveness through a synthetic, standard, and scalable set of requirements‐driven workload model are presented.

XML constructs, constraints, and controls are investigated both in terms of data and documents. Workload formulation from the requirements analysis is explored. In‐depth schema, query, and control model to provide scalability and portability can be applied is developed.

Enterprise information integration over heterogeneous data sources has to be achieved through XML. Performance measurement and evaluation on XML is vital. With a more generic and generalized design, XML benchmark can become the key to the success of B2Bi interoperability and performance.

An origin of requirements‐driven benchmark modeling over collaborative commerce is presented. A novel extension on W3C XML model is created. A innovative enhancement from current XML benchmarks' query model is developed.

The purpose of this paper is to illustrate and evaluate the semantic process benchmarking concept.

The authors' approach includes the use of metamodels and ontologies, which make the process models syntactically and semantically comparable. Furthermore, a software prototype is presented to analyze and compare individual process models and their performance information. Thereafter, the technical, conceptual, and economic perspectives of the approach's evaluation are aligned with their respective outcomes.

The evaluation proves that this approach is generally suitable to generate novel and useful information on different process models and their performance within the same problem domain. However, the initial set‐up costs are high and will only pay off once process models are used regularly.

The proposed approach depends strongly on the availability of appropriate metrics and ontologies, as well as on the annotation of these ontologies to process models, which is a time‐consuming task. If large benchmarking clearing centers are established, the approach will be more cost‐effective. The developed SEMAT prototype, that demonstrates and proves the proposed approach's general viability, supports cost‐effective ontology engineering and annotation in the context of semantic process benchmarking initiatives.

To date, process benchmarking has primarily been a manual process. In this article, the authors suggest an approach that allows time‐consuming and costly process analysis to be partially automated, which makes the performance indicators, as well as qualitative differences between processes, apparent.

The purpose of this paper is to develop a quantitative methodology for benchmarking process which is simple, effective and efficient as a rejoinder to benchmarking detractors who debate benchmarking is just a catch‐up process.

The methodology developed for benchmarking here consists of three phases; define, analyze and results. Define phase concentrates on what to benchmark, whereas analyze and results concentrate on how to benchmark. Analyze phase is developed based on two popular mathematical programming techniques which are called technique for order preference by similarity to ideal solution (TOPSIS) and goal programming.

The developed benchmarking methodology is deployed in the case of business schools and results show its efficiency and effectiveness as well as its applicability to various business environments in implementation.

The main limitation here is necessity of collecting data about all the peers involved in benchmarking which indirectly restricts the number of peers in the benchmarking process.

Based on the TOPSIS that addresses the benchmark (what to benchmark) and the GP model that addresses the way to reach the benchmark, this methodology may be implemented as a solution procedure for business benchmarking process.

The novelty in this approach is that TOPSIS and GP are being used as a benchmarking techniques in a simple methodology which choose a non‐real benchmark that is more than all the peers involved. In that sense, this research work may be the first, where quantitative methodology for benchmarking is developed and rejoined to the benchmarking old criticize that debates benchmarking is just a catch‐up play.

In some contexts, this illiquidity of executive stock options is referred to as non-transferability. In others, the problem is cast in terms of the highly concentrated portfolios that managers hold, an implication of which is that managers could not trade the options to diversify. The notion of option liquidity usually conjures up images of trading pits at the Chicago Board Options Exchange or other exchanges. The existence of an active trading pit gives a powerful visual image of liquidity, but, as evidenced by the success of electronic options exchanges such as New York's International Securities Exchange and Frankfurt's EUREX, a trading pit is hardly a requirement for liquidity. The existence of a guaranteed market for standardized options as implied by options exchanges (whether pit-based or electronic) further gives a misleading appearance of high liquidity. There is also a very large market for customized over-the-counter options. It is a misconception to think that these options are not liquid when they are simply not standardized. If an investor can create a highly customized long position in an option, that investor should be able to create a highly customized short position in the same option at a later date before expiration. If both options are created through the same dealer, they will usually be treated as an offset, as they would if they were standardized options clearing through a clearinghouse. If the two transactions are not with the same dealer, they would both remain alive, but the market risks would offset. Only the credit risk, a factor we ignore in this paper, would remain. Hence, these seemingly illiquid options are, for all practical purposes, liquid.²

The purpose of this paper is to develop an improved management/performance model that yields superior business productivity by conjoining internal benchmarking, external benchmarking, and a strong employee performance/behavior paradigm.

Strengths and weaknesses of conventional benchmarking approaches to productivity maximization are examined through both literature surveys and experiments.

It is found that most benchmarking efforts are hampered by resistance of employees to change. It is therefore concluded that benchmarking efforts could be enhanced by integrating employee motivation/behavior programs with the benchmarking efforts.

The individual elements of the proposed model have been field‐validated; however the integrated model has not been field‐tested. This is planned as future research.

The conjoining of internal benchmarking, external benchmarking, and employee motivation/behavior programs should substantially enhance the results of productivity improvement programs based upon benchmarking.

This is the first effort that integrates internal benchmarking, external benchmarking, and employee motivation/behavior programs. This synergistic management model should be quite significant in enhancing corporate productivity.