Is performance measurement and management fit for the future?

Performance measurement and management (PMM) is a management and research paradox. On one hand, it provides management with many critical, useful, and needed functions. Yet, there is evidence that it can adversely affect performance. This paper attempts to resolve this paradox by focusing on the issue of "fit". That is, in today's dynamic and turbulent environment, changes in either the business environment or the business strategy can lead to the need for new or revised measures and metrics. Yet, if these measures and metrics are either not revised or incorrectly revised, then we can encounter situations where what the firm wants to achieve (as communicated by its strategy) and what the firm measures and rewards are not synchronised with each other (i.e., there is a lack of "fit"). This situation can adversely affect the ability of the firm to compete. The issue of fit is explored using a three phase Delphi approach. Initially intended to resolve this first paradox, the Delphi study identified another paradox - one in which the researchers found that in a dynamic environment, firms do revise their strategies, yet, often the PMM system is not changed. To resolve this second paradox, the paper proposes a new framework - one that shows that under certain conditions, the observed metrics "lag" is not only explainable but also desirable. The findings suggest a need to recast the accepted relationship between strategy and PMM system and the output included the Performance Alignment Matrix that had utility for managers. © 2013 .

Phone-level pronunciation scoring and assessment for interactive language learning

This paper investigates a method of automatic pronunciation scoring for use in computer-assisted language learning (CALL) systems. The method utilizes a likelihood-based `Goodness of Pronunciation' (GOP) measure which is extended to include individual thresholds for each phone based on both averaged native confidence scores and on rejection statistics provided by human judges. Further improvements are obtained by incorporating models of the subject's native language and by augmenting the recognition networks to include expected pronunciation errors. The various GOP measures are assessed using a specially recorded database of non-native speakers which has been annotated to mark phone-level pronunciation errors. Since pronunciation assessment is highly subjective, a set of four performance measures has been designed, each of them measuring different aspects of how well computer-derived phone-level scores agree with human scores. These performance measures are used to cross-validate the reference annotations and to assess the basic GOP algorithm and its refinements. The experimental results suggest that a likelihood-based pronunciation scoring metric can achieve usable performance, especially after applying the various enhancements.

A reason for unreason: returns-based beliefs in game theory

Players cooperate in experiments more than game theory would predict. We introduce the ‘returns-based beliefs’ approach: the expected returns of a particular strategy in proportion to total expected returns of all strategies. Using a decision analytic solution concept, Luce’s (1959) probabilistic choice model, and ‘hyperpriors’ for ambiguity in players’ cooperability, our approach explains empirical observations in various classes of games including the Prisoner’s and Traveler’s Dilemmas. Testing the closeness of fit of our model on Selten and Chmura (2008) data for completely mixed 2 × 2 games shows that with loss aversion, returns-based beliefs explain the data better than other equilibrium concepts.

A trapped field of 17.6 T in melt-processed, bulk Gd-Ba-Cu-O reinforced with shrink-fit steel

The ability of large-grain (RE)Ba2Cu3O7-δ ((RE)BCO; RE = rare earth) bulk superconductors to trap magnetic fields is determined by their critical current. With high trapped fields, however, bulk samples are subject to a relatively large Lorentz force, and their performance is limited primarily by their tensile strength. Consequently, sample reinforcement is the key to performance improvement in these technologically important materials. In this work, we report a trapped field of 17.6 T, the largest reported to date, in a stack of two silver-doped GdBCO superconducting bulk samples, each 25 mm in diameter, fabricated by top-seeded melt growth and reinforced with shrink-fit stainless steel. This sample preparation technique has the advantage of being relatively straightforward and inexpensive to implement, and offers the prospect of easy access to portable, high magnetic fields without any requirement for a sustaining current source. © 2014 IOP Publishing Ltd.