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Targets are an important part of our work life, whether we are setting them or meeting them. Target setting forms part of the budgeting process and the performance management of business units and individuals. Unfortunately the behavioral impacts of target setting on performance are not well understood, and this can lead to serious consequences such as game playing. Target setting is an under-researched area. This book will help you fill the gap in target setting for performance. The pivotal issue in target setting is that it is an art as well as a science. Perhaps more of an art, requiring a balance between the psychologies of the people taking initiatives, the science of estimating probabilities and aligning with strategies, coupled with the effects of incentives. Another feature of this book is how the authors drew on ideas and research across disciplines, which is rarely done in this field. Inside this book, you will be introduced to some of the important methods in target setting such as forecasting, sensitivity analysis, and probability analysis; all of which include practical examples to show how these techniques can be directly applied. In the end, you'll learn how interrelated the various parts of organizational activities are and how they impact on each other, which is important since target setting must include an understanding of the organizational context (e.g., people, competitive environment, structure, strategy) as well as the impact of incentive compensation and information flows.

We examine the extent to which firms use past performance as a basis for setting earnings targets in their bonus plans and assess the implications of such targets for managerial incentives. We find that high-profitability firms commonly decrease earnings targets when their managers fail to meet prior-year targets but rarely increase targets. Conversely, we find that low-profitability firms commonly increase earnings targets when their managers meet or exceed prior-year targets but rarely decrease targets. This target-revision process yields a serial correlation in target difficulty—targets remain relatively easy (or difficult) through time. We also find that firms are reluctant to revise earnings targets below zero, resulting in an unusually high frequency of zero earnings targets that are abnormally difficult to achieve. Collectively, our findings suggest that firms incorporate past performance information into targets, yet they do so only to a limited extent. This is consistent with theoretical arguments that highlight the benefits of contractual commitments.

In many situations, performance on several attributes is important. Moreover, a decision maker's utility may depend not on the absolute level of performance on each attribute, but rather on whether that level of performance meets a target, in which case the decision maker is said to be target oriented. For example, typical attributes in new product development include cost, quality, and features, and the corresponding targets might be the best performance on these attributes by competing products. Targets and performance levels typically are uncertain and often are dependent. We develop a model that allows for uncertain dependent targets and uncertain dependent performance levels, and we study implications for decision making in this general multiattribute target-oriented setting. We consider the impact on expected utility of modifying key characteristics of performance (or target) distributions: location, spread, and degree of dependence. In particular, we show that explicit consideration of dependence is important, and we establish when increasing or decreasing dependence is beneficial. We illustrate the results numerically with a normal model and discuss some extensions and implications.

This paper examines the performance of two position-velocity-measured (PVM) α - β - γ tracking filters. The first estimates the target acceleration using the measured velocity, and the second, which is proposed for the first time in this paper, estimates acceleration using the measured position. To quantify the performance of these PVM α - β - γ filters, we analytically derive steady-state errors that assume that the target is moving with constant acceleration or jerk. With these performance indices, the optimal gains of the PVM α - β - γ filters are determined using a minimum-variance filter criterion. The performance of each filter under these optimal gains is then analyzed and compared. Numerical analyses clarify the performance of the PVM α - β - γ filters and verify that their accuracy is better than that of the general position-only-measured α - β - γ filter, even when the variance in velocity measurement noise is comparatively large. We identify the conditions under which the proposed PVM α - β - γ filter outperforms the general α - β - γ filter for different ratios of noise variance in the velocity and position measurements. Finally, numerical simulations verify the effectiveness of the PVM α - β - γ filters for a realistic maneuvering target.

Since 2020, there is a new European Regulation (EU, 2020/741) on minimum requirements for water reuse, where routine and validation monitoring requirements (log reductions of indicator microorganisms and reference pathogens) have been established. Many reclamation facilities that are already in operation might have difficulties to comply with these performance targets. Existing disinfection systems must be expanded and upgraded. In the case of UV disinfection systems, fluence requirements must be determined to properly design with a focus on the safety and economic-environmental viability of reclaimed water. This study can be used as a reference to develop fluence-response curves for Clostridium perfringens spores, Escherichia coli, and total and F-specific coliphages, indicator microorganisms referred to in the new European Regulation. Eight UV-LED collimated beam tests were performed. Samples were obtained from filtered effluent of secondary treatment from two wastewater treatment plants (WWTPs) which ranged between 30 and 54%. Results showed UV sensitivity of 33.46 mJ/cm2 log I for C. perfringens spores and 2.86 mJ/cm2 log I for E. coli, both from environmental origin. Coliphages were inactivated below the limit of quantitation. The non-dominance of MS2 phages in environmental F-specific coliphages was observed.

To overcome the drawbacks of the traditional chaos control method (CC), such as non-convergence, inefficiency and repeated adjustment of control factor, a new method named adaptively active set-based CC (AASCC) is presented and further extended to the reliability-based design optimization (RBDO). First, the AASCC method builds a relationship between the iterative step size and search region of the minimum performance target point (MPTP) via gradient on the MPTP. This approach can adjust the iterative step size to respond dynamically to changes while automatically scaling the search domain of MPTP to eliminate unnecessary MPTP. As a result, it minimizes the demand for frequent debugging of control factors meanwhile accelerating computational efficiency. Second, the proposed strategy is combined with the reliability index to establish a dynamic dictate condition to optimize the performance of the RBDO-based double-loop method (DLM) in efficiency and accuracy. The dynamic dictate condition is executed to refresh the active determined constraint so that it effectively relieves the excessive redundant workloads. Finally, the proposed method is tested on several authoritative examples, involving both MPTP searching cases and RBDO problems to verify its characteristics, showing notable advantages.

In this study, we examine a setting where principals use past performance to annually revise performance targets, but do not fully incorporate the past performance information in their target revisions. We argue that this situation is driven by some principals and agents having an implicit agreement where the principal \"allows\" the agent to receive economic rents from positive performance-target deviations that are the result of superior effort or transitory gains by not revising targets upward, while the agent \"accepts\" target revisions by not restricting output when these revisions are the result of structural changes in the operation's true economic capacity. Although both the principal and the agent can benefit from an implicit agreement, we argue that for the implicit agreement to be maintainable, the principal either needs information on the cause of the performance-target deviation or there needs to be trust between the principal and the agent. Using archival data across multiple years and independent bank units, we find a pattern of ratchet attenuation and output restriction that is consistent with the existence of implicit agreements for those principal-agent dyads where information asymmetry is sufficiently reduced or mutual trust exists.

Kingdon's multiple streams approach has recently been applied to study implementation across sectors or levels of government. Building on these contributions, we suggest that two streams are especially important in shaping implementation: organisational problem constructions and political pressure from the centre. These variables produce a four-way typology of implementation modes. We test the model by analysing implementation of UK targets on asylum, defence and climate change, drawing on 54 semi-structured interviews with policy actors. The analysis shows how organisations can shift between modes of implementation over time, responding to changes in organisational problems and central political commitment to the policy.

A risk-based framework for targeting investment in prescribed burning in Western Australia is presented. Bushfire risk is determined through a risk assessment and prioritisation process. The framework provides principles and a rationale for programming fuel management with indicators to demonstrate that bushfire risk has been reduced to an acceptable level. Indicators provide targets for fuel management that are applicable throughout the state and can be customised to meet local circumstances. The framework identifies eight bushfire risk management zones having broad consistency of land use, fire environment and management approach, which combine to create a characteristic risk profile. Thirteen fuel types based primarily on structural attributes of the vegetation that influence fire behaviour are recognised and used to assign models for fuel accumulation and fire behaviour prediction. Each bushfire risk management zone is divided into fire management areas, based on the management intent. These are areas where fuels will be managed primarily to minimise the likelihood of fire causing adverse impacts on human settlements or critical infrastructure, to reduce the risk of bushfire at the landscape scale or to achieve other land management outcomes. Indicators of acceptable bushfire risk are defined for each fire management area and are modified according to the distribution of assets and potential fire behaviour in the landscape. Risk criteria established in the framework can be converted to spatially represented targets for fuel management in each zone and can be reported against to measure the effectiveness of the fuel management program. In areas where the primary intent is to reduce the risk of bushfire at the landscape scale, managers have flexibility to apply prescribed fire in ways that maintain and enhance ecosystem services, nature conservation and landscape values through variation in the seasonality, intensity and scale of planned burning.

Due to limited resources, development is associated with a process of transformation, including the performance of the transformation. In 2015, following the adoption of the Paris Agreement and the UN Sustainable Development Goals, the political agenda has shifted towards sustainable development for society, which includes environmental criteria. European Union Member States have strengthened the political agenda on sustainable development with the EU Green Deal initiative. Various development indexes could be employed for assessment, thus marking a decline in the role of the traditional measure of GDP. Some environmental criteria are included in the Social Progress Index (e.g. Water and sanitation; Environmental quality), while the Sustainable Development Index provides a more comprehensive picture. The research aims to assess sustainable development in European Union Member States in the context of achieving social progress and the Sustainable Development Goals. An analysis of the performance of EU Member States in terms of social progress, although their GDPs were not the highest, revealed that several environmental performance targets have been achieved, thereby indicating a change in the course of development. Almost all EU Member States have made progress towards the SDGs over the period 2019-2023, except France and the Netherlands, as their index scores were negative. Social progress has been fastest in Latvia, while at the same time making some progress towards the SDGs.