Editorial

n/

Ambiguity in public sector performance measurement: a systematic literature review

Purpose: This paper presents a systematic literature review aiming at analysing how research has addressed performance measurement systems’ (PMSs) ambiguities in the public sector. This paper embraces the ambiguity perspective that PMSs in public sector coexist with and cope with existing ambiguities. Design/methodology/approach: The authors conducted a literature review in Scopus and ScienceDirect, considering articles published since 1985, and the authors selected articles published in the journals included in the Association of Business Schools' Academic Journal Guide (Chartered ABS, 2018). Of the 1,278 abstracts that matched the study’s search criteria, the authors selected 131 articles for full reading and 37 articles for the final discussion. Findings: The study's key findings concern the elements of ambiguity in PMSs discussed in the literature. The study’s results suggest that ambiguity is still a relevant problem in performance measurement, as a problem that is impossible to be solved and therefore needs to be better understood by researchers and public managers. The analysis allows us to summarize the antecedents and consequences of ambiguity in the public sector. Research limitations/implications: The key findings of the study concern the main sources of ambiguity in PMSs discussed in the literature, their antecedents and their consequences. The study results suggest that ambiguity exists in performance measurement and that is an issue to be handled with various strategies that can be implemented by managers and employees. Practical implications: Managers and researchers may benefit from this research as it may represent a guideline to understand ambiguities in their organizations or in field research. Researchers may also benefit from a summary list of the key issues that have been analysed in the empirical cases provided by this research. Social implications: This research may provide insights to limit ambiguity and thus contribute to improve performance measurement in the public sector. Originality/value: This research presents a comprehensive review on the topic. It provides insight that suggests what future research should attend to in helping to interpret ambiguity, considering also what should be done to influence ambiguity

Heterogeneous Bayesian Decentralized Data Fusion: An Empirical Study

In multi-robot applications, inference over large state spaces can often be divided into smaller overlapping sub-problems that can then be collaboratively solved in parallel over `separate' subsets of states. To this end, the factor graph decentralized data fusion (FG-DDF) framework was developed to analyze and exploit conditional independence in heterogeneous Bayesian decentralized fusion problems, in which robots update and fuse pdfs over different locally overlapping random states. This allows robots to efficiently use smaller probabilistic models and sparse message passing to accurately and scalably fuse relevant local parts of a larger global joint state pdf, while accounting for data dependencies between robots. Whereas prior work required limiting assumptions about network connectivity and model linearity, this paper relaxes these to empirically explore the applicability and robustness of FG-DDF in more general settings. We develop a new heterogeneous fusion rule which generalizes the homogeneous covariance intersection algorithm, and test it in multi-robot tracking and localization scenarios with non-linear motion/observation models under communication dropout. Simulation and linear hardware experiments show that, in practice, the FG-DDF continues to provide consistent filtered estimates under these more practical operating conditions, while reducing computation and communication costs by more than 95%, thus enabling the design of scalable real-world multi-robot systems.Comment: 7 pages, 2 figures, submitted to IEEE Conference on Robotics and Automation (ICRA 2023

Management accounting change as a learning process: a longitudinal analysis

Purpose The purpose of this paper is to investigate how a substantial organization gradually builds a management accounting system from scratch, changing its accounting routines by learning processes. The paper uses the experiential learning theory and the concept of learning style to investigate the learning process during management accounting change. The study aims to expand the domain of management accounting change theory to emphasize the learning-related aspects that can constitute it. Design/methodology/approach The paper provides an interpretation of management accounting change based on the model of problem management proposed by Kolb (1983) and the theory of experiential learning (Kolb, 1976, 1984). The study is based on a 14-year longitudinal case study (1994-2007). The case examined can be considered a theory illustration case. Data were obtained from a broad variety of sources including interviews, document analysis and adopting an interventionist approach during the redesign of the costing system. Findings The paper contributes to two important aspects of management accounting change. First, it becomes apparent that the costing information change was not a discrete event but a process of experience and learning conducted through several iterations of trial-and-error loops that extended over the years. Second, the findings reveal that the learning process can alter management accounting system design in a radical or incremental way according to the learning style of the people involved in the process of change. Research limitations/implications Because of the adopted research approach, results could be extended only to other organizations presenting similar characteristics. Several further areas of research are suggested by the findings of this paper. In particular, it would be of interest to investigate the links between learning styles and communication and its effect on management accounting change. Practical implications The paper includes implications for the management of learning during management accounting change, to improve the efficiency and effectiveness of this process. Originality/value This paper is one response to the call for an interdisciplinary research approach to the management accounting change phenomena using a "method theory" taken from the discipline of management to provide an explanation of the change in management accounting. In respect of the previous literature, it provides two main contributions, namely, the proposal of a model useful both to interpret and manage learning processes; the effect of learning style on management accounting routines change

Existence theorems for lagrange control problems with unbounded time domain

Existence theorems are proved for usual Lagrange control systems, in which the time domain is unbounded. As usual in Lagrange problems, the cost functional is an improper integral, the state equation is a system of ordinary differential equations, with assigned boundary conditions, and constraints may be imposed on the values of the state and control variables. It is shown that the boundary conditions at infinity require a particular analysis. Problems of this form can be found in econometrics (e.g., infinite-horizon economic models) and operations research (e.g., search problems).Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45207/1/10957_2004_Article_BF00934054.pd

Canary in the Forest?—Tree mortality and canopy dieback of western redcedar linked to drier and warmer summers

Aim: Forest dieback is increasing from unfavourable climate conditions. Western redcedar (WRC)—a culturally, ecologically and economically important species—has recently experienced anomalously high mortality rates and partial canopy dieback. We investigated how WRC tree growth and dieback responded to climate variability and drought using tree-ring methods. Location: Pacific Northwest, USA. Taxon: Western redcedar (Thuja plicata). Methods: We collected tree cores from three tree health status groups (no canopy dieback, partial canopy dieback, and dead trees) at 11 sites in coastal (maritime climate) and interior (continental climate) WRC populations. From growth rates, we computed four growth indices that assessed the resilience to drought and estimated the year of death. Results: Warmer and drier climate conditions in May/June that extended the annual July-to- September dry season reduced radial growth in 9 of 11 sites (1975–2020). WRC trees recovered growth to pre-drought rates within 3 years when post-drought climate conditions were cooler/wetter than average. However, recovery from drought was slower or absent when warmer/drier conditions occurred during the post-drought recovery period, possibly leading to the recent and widespread mortality across the coastal population. WRC mortality was portended by 4–5 years of declining growth. Annually-resolved mortality in coastal populations predominately occurred in 2017–2018 (80% of sampled dead trees), a period that coincided with exceedingly hot temperatures and the longest regionally dry period from May to September (1970–2020). In interior populations, mortality was dispersed among years but associated with warmer and drier conditions from August to September. Main conclusions: Our findings forewarn that a warming climate and more frequent and severe summer droughts, especially in consecutive years, will likely increase the vulnerability of WRC to canopy dieback and mortality and possibly other drought-sensitive trees in one of the world\u27s largest forest carbon sinks