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The statement that evaluation works differently in different contexts might seem fairly obvious, but given how central it is to virtually all aspects of modern life, it is important to understand how these differences affect the objects of evaluation and the people doing the evaluation. Drawing on a mixed-methods study of evaluation in figure skating and classical music, the author addresses how evaluation practices affect judging and performance. In the early- to mid-2000s, the figure skating world transitioned from a judging system where judges used two overall marks to rank skaters to a much more rigid system where judges rate very specific aspects of performances without actively ranking them. These changes have impacted judges and skaters. In the classical music competitions the author focuses on, judges use deliberations to rank performances. The relative flexibility of these evaluation practices generally does not affect judges or performances as much. Building on research on the effects of measurement and evaluation systems, the author argues that formal, specific rules surrounding evaluation shape judging and performance more than informal, diffuse rules. Focusing on competition settings in skating and music, the author discusses how evaluation practices affect program and repertoire construction and the technical and artistic aspects of judging and performance in these fields. In addition to supplementing research suggesting that evaluation systems actively shape what they are designed to evaluate, this work highlights how different types of evaluation contribute to different responses in terms of the evaluation itself and the objects of evaluation.

This chapter examines the influence of outsourcing on airlines’ performance from countries of the Asia Pacific region. Performance in the context of this study is drawn from productivity growth and technical efficiency scores that are calculated using the standard data envelopment analysis (DEA) approach. We utilize data from airlines over the period 2003–2011 and estimate the impact of outsourcing on productivity and technical efficiency using generalized method of moments (GMM) estimators. The findings from DEA reveal an improvement in the technical efficiency score of airlines from Asia Pacific. Nonetheless, productivity estimates indicate fluctuations in the productivity growth trend of airlines, attributable to global economic recession in 2007/2008. GMM estimation results, however, suggest negative impacts of outsourcing on technical efficiency and productivity of the airlines from Asia Pacific countries. We offer several explanations for these outsourcing findings. Heavy outsourcing of airlines activities particularly maintenance of aircraft may negatively affect aircraft utilization and ultimately erode the service level of airlines. The erosion of the service level of airlines would affect the demand for air travel in a downward manner, thereby lowering the technical efficiency and productivity of airlines. Also, relatively low labor costs enjoyed by airlines in the Asia Pacific region would suggest that having many airline activities in-house would save operating expenses attributable to labor costs.

There has been much debate in the literature regarding whether political pressures are beneficial or detrimental to public agencies’ performance and outcomes. This chapter explores under what conditions, if any, do political pressures have any positive effects.

A survey methodology and multivariate regression models are applied to assess the relationship between political pressures and public agencies’ performance and outcomes, using data from South-America and Europe. The theoretical scope is developed drawing from the public sector, management control, and goal-setting literatures.

The effects of political pressures on public agencies’ performance and public officers’ job satisfaction are moderated by technical certainty. At low levels of technical certainty political pressures have negative effects while at high levels they have positive effects.

All limitations of survey research apply.

Governments, public officers, and politicians should take into account the dynamics described in this study so as to limit the negative effects of political pressures and take advantage of the positive ones.

This is the first study to suggest that the effects of political pressures on public agencies vary depending on the nature of the task public agencies perform. The results reported here bring a new perspective to the literature, helping to clarify prior conflicting results. In addition, the fact that results are consistent for South American and European public agencies suggests that these findings might be generalizable across cultural boundaries.

This study takes a novel approach to testing the efficacy of technical analysis. Rather than testing specific trading rules as is typically done in the literature, we rely on institutional portfolio managers’ statements about whether and how intensely they use technical analysis, irrespective of the form in which they implement it. In our sample of more than 10,000 portfolios, about one-third of actively managed equity and balanced funds use technical analysis. We compare the investment performance of funds that use technical analysis versus those that do not, using five metrics. Mean and median (3 and 4-factor) alpha values are generally slightly higher for a cross section of funds using technical analysis, but performance volatility is also higher. Benchmark-adjusted returns are also higher, particularly when market prices are declining. The most remarkable finding is that portfolios with greater reliance on technical analysis have elevated skewness and kurtosis levels relative to portfolios that do not use technical analysis. Funds using technical analysis appear to have provided a meaningful advantage to their investors, albeit in an unexpected way.

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.

The essential investments in new product development (NPD) made by industrial companies entail effective management of NPD activities. In this context, performance measurement is one of the means that can be employed in the pursuit of effectiveness.

Supply chains deliver goods and services between shippers and receivers, covering collection, transportation, distribution as well as their handling and storage in between. In particular, transportation services are carried out by different transport modes. In some modern supply chains, different categories of air cargo carriers – combinations, freighter-only, and/or integrators – provide critical transport services.

This chapter develops a methodology for estimating the performance of supply chains served by an air cargo carrier network. The methodology is based on indicators of infrastructure use, technical/technological level, operational factors, economic factors, and environmental performance. This proposed methodology is applied to estimate performance of supply chains served by an integrated air cargo carrier – FedEx Express – operating a single hub in the US domestic air network. Results indicate that the methodology may be useful for estimation of overall supply chain performance under the condition that relevant data are available.

This chapter provides a contemporary view of state-of-the science research and thinking done in the areas of selection and classification. It takes as a starting point the observation that the world of work is undergoing important changes that are likely to result in different occupational and organizational structures. In this context, we review recent research on criteria, especially models of job performance, followed by sections on predictors, including ability, personality, vocational interests, biodata, and situational judgment tests. The paper also discusses person-organization fit models, as alternatives or complements to the traditional person-job fit paradigm.

This chapter investigates the financial performance and technical efficiency of the 26 listed firms in the services sector of the Philippine Stock Exchange over the period 1998–2007, using the DuPont system and the super-efficiency data envelopment analysis (SE-DEA). Empirical findings revealed a negative return on equity for the sector and the presence of outliers in the sample. We also verified a robust significant association between the financial and technical performances of the sector.

The chapter offers new significant contributions to knowledge in terms of the multidimensional performance evaluation and the efficiency of the stock market, especially in developing economies, which has not been a well-researched area. Managerial implications are also identified for the improvement of the firms’ management and the usefulness of the SE-DEA model in performance management.

Although models have been published in the literature covering various aspects of the job performance domain (e.g., technical performance, contextual performance), researchers have recently recognized a void in these models and have called for their expansion to include adaptive performance components (Campbell, 1999; Hesketh & Neal, 1999; London & Mone, 1999; Murphy & Jackson, 1999). Toward this end, Pulakos, Arad, Donovan, and Plamondon (2000) developed a taxonomy of adaptive job performance similar to the model of job performance developed by Campbell, McCloy, Oppler, and Sager (1993). This model contained eight dimensions of adaptive job performance. Pulakos et al. began their research with a review of various literatures on adaptability and identified six different aspects of adaptive performance. These are shown in Table 1, along with the research references from which they were derived. The diversity of substantive areas that are represented in the research articles cited in Table 1 is a testament to the perceived importance of adaptability across a number of behavioral disciplines. Although the idea that adaptive performance is multi-dimensional was reasonable based on the wide range of behaviors “adaptability” has encompassed in the literature (for example, adapting to organizational change, different cultures, different people, new technology), no published research prior to Pulakos et al. had systematically defined or empirically examined specific dimensions of adaptive job performance. Pulakos et al. conducted two studies to refine the six-dimension model of individual adaptive job performance derived from the literature. In Study 1, over 1,000 critical incidents from 21 different jobs were content analyzed, yielding an eight-dimension taxonomy of adaptive performance. That is, the critical incident analysis produced two additional adaptive performance dimensions that are shown at the bottom of Table 1.