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As the implementation and acceptance of utility analyses are afflicted by several problems, this paper sets out to describe how to circumvent these problems by implementing a new framework for utility analysis.

The HC BRidge™ model, developed by Boudreau and Ramstad, was implemented to determine the utility of assessment centers within a call center company.

The results demonstrate the utility of the assessment centers and the usefulness of the HC BRidge™ model.

Future research should clarify under which conditions human resource specialists can communicate effectively and reach an optimal decision within the HC BRidge™ model of utility analysis.

It is highlighted how human resource experts can assist in using utility analyses (as a component of HR strategy) for decision‐making processes concerning limited organizational resources.

To demonstrate the usefulness and value of the HC BRidge™ model for both researchers and practitioners.

To investigate the application of multi‐attribute utility theory (MAUT) to aid in the decision‐making process when performing benchmarking gap analysis.

MAUT is selected to identify the overall best‐in‐class (BIC) performer for performance metrics involving inventory record accuracy within a public sector warehouse. A traditional benchmarking analysis is conducted on 14 industry warehouse participants to determine industry best practices for the four critical warehouse metrics of picking and inventory accuracy, storage speed, and order cycle time. Inventory and picking tolerances are also investigated in the study. A gap analysis is performed on the critical metrics and the absolute BIC is used to measure performance gaps for each metric. The gap analysis results are then compared to the MAUT utility values, and a sensitivity analysis is performed to compare the two methods.

The results indicate that an approach based on MAUT is advantageous in its ability to consider all critical metrics in a benchmarking study. The MAUT approach allows the assignment of priorities and analyzes the subjectivity for these decisions, and provides a framework to identify one performer as best across all critical metrics.

This research study uses the additive utility theory (AUT) which is only one of multiple decision theory techniques.

A new approach to determine the best performer in a benchmarking study.

Traditional benchmarking studies use gap analysis to identify a BIC performer over a single critical metric. This research integrates a mathematically driven decision analysis technique to determine the overall best performer over multiple critical metrics.

This case study describes an application of utility analysis to guide decisions regarding retention and operation of various selection system components (i.e., tests and interviews). Selection processes for two “high throughput” selection systems (Meter Reader and Customer Service Representative) were examined to improve cost effectiveness and reduce cycle time (time to produce qualified candidates). Based on utility outcomes and client considerations, the interview was retained with modifications in one selection process, and deleted from the other. Insights gained from gathering data needed to conduct the utility analysis helped guide further refinements of the selection systems in which the tests and interviews were applied, drastically reducing the time needed to fill open positions.

This chapter explains how economic analysis can contribute to the delineation of the lone wolf’s opportunities and choices in a manner that allows operationally relevant advice to be contributed to the investigative process.

Using a risk-reward analytical framework we examine the lone wolf’s attack method opportunities and choices and identify those attack methods that would be chosen by lone wolves with different levels of risk aversion. We also use prospect theory as an alternative methodology for the determination of the lone wolf’s preference orderings over the available attack methods in a context where he references his actions against those of a predecessor whom he wishes to emulate.

We find that lone wolf terrorists with different levels of risk aversion can be expected to choose different attack methods or combinations of attack methods. More risk averse lone wolf terrorists will choose attack methods such as assassination. Less risk averse lone wolf terrorists will choose attack methods such as bombing, hostage-taking and unconventional attacks. Also, we find that lone wolf terrorists who reference their actions against ‘predecessor’ lone wolf terrorists will choose differently from among the available attack methods depending on which predecessor lone wolf is being referenced.

The analysis provides two different perspectives on terrorist choice but by no means exhausts the analytical alternatives. The analysis focuses on the fatalities and injuries inflicted whereas other perspectives might include different ‘payoffs’ series, including news or media coverage.

The chapter contributes an analysis of the order in which lone wolf terrorists with particular characteristics will choose from a set of available attack methods. During the course of our discussion we point out the consistency between the ‘rise’ of the lone wolf terrorist and the diseconomies to scale that are evident within the terrorism context. This presents the opportunity for new debates.

Traditional utility analysis only calculates the value of a given selection procedure over random selection. This assumption is not only an inaccurate representation of staffing policy but also leads to overestimates of a device's value. This paper presents a more accurate method for computing the validity of a selection battery for when there are multiple selection devices and multiple criteria. Application of the method is illustrated using previous utility analysis work and an actual case of administrative assistants with eight predictors and nine criteria. A final example also is provided that includes these advancements as well as other researchers' advances in a combined utility model. Results reveal that accounting for multiple criteria and outcomes dramatically reduces the utility estimates of implementing new selection devices.

The purpose of this paper is to benchmark the Indian mobile telecommunication service providers for relative efficiencies. In this paper, a method for benchmarking performance of mobile telecom utilities based on data envelopment analysis (DEA) is presented. The paper discusses some concepts between quality performance and benchmarking and the results include performance efficiency and sensitivity‐based classification of utilities. Also, peer‐to‐peer comparison of inefficient with efficient utilities is provided. Based on these results, inefficient utilities can develop strategic plans to improve performance.

The authors use DEA to measure comparative efficiencies of mobile telecom companies and two different DEA models, CCR and BCC, were applied to evaluate the relative efficiency of mobile telecom operators in India. Sensitivity‐based classification of utilities is carried out by removing one or more inputs or outputs from the base model to construct a new DEA model. Comparisons of DEA efficiencies from the base model with the structurally perturbed models show the impact on efficiency. Data include annual and quarterly reports showing various quality parameters.

DEA is used to derive the benchmarks based on the comparison of the 126 utilities which include public sector undertaking (PSU) operators (MTNL and BSNL) and private operators of the Indian mobile telecommunication sector. The result includes performance efficiency and peer‐to‐peer comparison of inefficient utilities with efficient utilities. Based on these results, inefficient utilities can develop strategic plans to improve their performance. Sensitivity analysis, based on removal of one or more variables from the base model to determine changes in DEA efficiencies is done for selecting the strength of parameters of utilities for performance improvement.

Benchmarking of service utilities in the telecom sector is virtually non‐existent at the national level in India. This research identifies the different variables and then a model is prepared for benchmarking of the service providers in India. Based on the efficiency analysis, benchmarks can be set, and utility efficiency scores can be obtained based on the set benchmarks. These scores can help develop a strategic plan for mitigating the factors that contribute to the system inefficiencies.

This paper is one of the few published studies that benchmark the performance of mobile telecom services in India. This research promises to be amongst the first of the works carried out taking specific parameters of mobile telecom utilities of India.

There has been a surge of interest in leader character and a push to bring character into mainstream management theory and practice. Research has shown that CEOs and board members have many questions about the construct of leader character. For example, they like to see hard data indicating to what extent character contributes to organizational performance. Human resource management professionals are often confronted with the need to discuss and demonstrate the value of training and development initiatives. The question as to whether such interventions have a dollars-and-cents return on the investment is an important one to consider for any organizational decision-maker, especially given the demand for increased accountability, the push for transparency and tightening budgets in organizations. The authors investigated the potential dollar impact associated with the placement of managers based on the assessment of leader character, and they used utility analysis to estimate the dollar value associated with the use of one instrument – the Leader Character Insight Assessment or LCIA – to measure leader character.

The authors used field data collected for purposes of succession planning in a large Canadian manufacturing organization. The focus was on identifying senior management candidates suitable for placement into the most senior levels of leadership in the organization. Peers completed the LCIA to obtain leader character ratings of the candidates. The LCIA is a behaviorally based and validated instrument to assess leader character. Performance assessments of the candidates were obtained through supervisor ratings.

The correlation between the leader character measure provided by peers and performance assessed by the supervisor was 0.30 (p < 0.01). Using the data required to calculate ΔU from the Brogden-Cronbach-Gleser model leads to an estimate of CAD $564,128 for the use of the LCIA over the expected tenure of 15 years, which is equivalent to CAD $37,609 yearly; and CAD $375,285 over an expected tenure of 10 years, which is equivalent to CAD $37,529 yearly. The results of the study also indicate that there is still a positive and sizeable return on investment or ROI associated with the LCIA in employee placement even with highly conservative adjustments to the basic utility analysis formula.

Utility analysis is a quantitative and robust method of evaluating human resource programs. The authors provide an illustration of the potential utility of the LCIA in a selection process for senior managers. They assert that selecting and promoting managers on leader character and developing their character-based leadership will not only leverage their own contributions to the organization but also contribute to a trickle-down effect on employees below them.

Multiattribute utility models link the relative attractiveness of a given project to the utility functions of the decision makers. Conjoint analysis is industry's most commonly used marketing research method for measuring consumers' multiattribute utility functions (Green 1984). In this article, conjoint analysis is proposed as a methodology for measuring managers' utility functions regarding innovative capital budgeting proposals.

Quality Function Deployment (QFD) proposes to take into account the “voice of the customer,” through a list of customer needs, which are (qualitatively) mapped to technical requirements in House One. But customers do not perceive products in this space, nor do they not make purchase decisions in this space. Marketing specialists use statistical models to map between a simpler space of customer perceptions and the long and detailed list of needs. For automobiles, for example, the main axes in perceptual space might be categories such as luxury, performance, sport, and utility. A product’s position on these few axes determines the detailed customer requirements consistent with the automobiles’ position such as interior volume, gauges and accessories, seating type, fuel economy, door height, horsepower, interior noise level, seating capacity, paint colors, trim, and so forth. Statistical models such as factor analysis and principal components analysis are used to describe the mapping between these spaces, which we call House Zero.

This paper focus on House One. Two important steps of the product development process using House One are: (1) setting technical targets; (2) identifying the inherent tradeoffs in a design including a position of merit. Utility functions are used to determine feature preferences for a product. Conjoint analysis is used to capture the product preference and potential market share. Linear interpolation and the slope point formula are used to determine other points of customer needs. This research draws from the formal mapping concepts developed by Nam Suh and the qualitative maps of quality function deployment, to present unified information and mapping paradigm for concurrent product/process design. This approach is the virtual integrated design method that is tested upon data from a business design problem.