Reviewing performance: an analysis of the structure and functions of performance management reviews

This article proposes an analytical framework for conceptualising performance management reviews (PMRs). Drawing on multiple literatures, the article applies Pettigrew et al.'s (Pettigrew, A., Whipp R., and Rosenfield R., 1989. Competitiveness and the management of strategic change processes. In: A. Francis, and P.K.M. Tharakan, eds. The competitiveness of European industry: country policies and company strategies. London: Routledge) framework to develop our understanding of the context, process and content of PMR. The process elements of PMRs are the levers for managerial intervention as they determine the immediate outcome of PMR. They accomplish this task by acting on the content elements, transforming the subject of PMR into specific outcomes. The scope of the intervention, however, is constrained by factors in the organisation's context. This framework sheds light on various functions of PMRs, most notably strategy implementation.     

No going back: A review of the literature on sustaining organizational change

Why do some organizational changes persist, while others decay? The sustainability of change can be defined broadly as the process through which new working methods, performance goals and improvement trajectories are maintained for a period appropriate to a given context. However, sustainability has received limited attention, although the concept reflects Lewin's concern with ‘refreezing’ ( Lewin. K. 1951 . Field Theory in Social Science: Selected Theoretical Papers by Kurt Lewin, UK edition published 1952, ed. D. Cartwright, London: Tavistock). In an uncertain environment, working practices that fail to adapt are targets for change, and stability has been regarded not as a condition to be achieved, but as a symptom of inertia, a problem to be solved. This paper reviews the emerging literature, seeking to develop a provisional model of the processes influencing change sustainability and decay, as a platform for further research. This review suggests that sustainability is dependent on multiple factors, at different levels of analysis: substantial, individual, managerial, financial, leadership, organizational, cultural, political, processual, contextual and temporal. The relative significance of those factors cannot be determined a priori, raising questions concerning the properties of the sustainability process with regard to different types of change in different contexts.     

Managing from the Inside Out: Drawing on 'Receptivity' to Explain Variation in Strategy Implementation

With the rise of 'New Public Management' (NPM), government policy has encouraged public-sector organizations to downsize and outsource their services. There is, however, local variation in the use of outsourcing – this is 'managing from the inside out'. This paper draws on the notion of receptivity for organizational change to explain variation in strategy implementation. Four receptivity factors are identified which seem to explain the success of two contrasting English local government outsourcing strategies: ideological vision, leading change, institutional politics and implementation capacity. The organization level of change is interconnected with two other levels of change (the public service and environment levels) to illustrate the dynamic nature of change.     

Causation Analysis of Risk Coupling of Gas Explosion Accident in Chinese Underground Coal Mines

The coal mine production industry is a complex sociotechnical system with interactive relationships among several risk factors. Currently, causation analysis of gas explosion accidents is mainly focused on the aspects of human error and equipment fault, while neglecting the interactive relationships among risk factors. A new method is proposed through risk coupling. First, the meaning of risk coupling of a gas explosion is defined, and types of risk coupling are classified. Next, the coupled relationship and coupled effects among risk factors are explored through combining the interpretative structural modeling (ISM) and the NK model. Twenty‐eight representative risk factors and 16 coupled types of risk factors are obtained through analysis of 332 gas explosion accidents in coal mines in China. Through the application of the combined ISM–NK model, an eight‐level hierarchical model of risk coupling of a gas explosion accident is established, and the coupled degrees of different types of risk coupling are assessed. The hierarchical model reveals that two of the 28 risk factors, such as state policies, laws, and regulations, are the root risk factors for gas explosions; nine of the 28 risk factors, such as flame from blasting, electric spark, and local gas accumulation, are direct causes of gas explosions; whereas 17 of the risk factors, such as three‐violation actions, ventilation system, and safety management, are indirect ones. A quantitative analysis of the NK model shows that the probability of gas explosion increases with the increasing number of risk factors. Compared with subjective risk factors, objective risk factors have a higher probability of causing gas explosion because of risk coupling.     

Darwinism, probability and complexity: market-based organizational transformation and change explained through the theories of evolution

The study of transformation and change is one of the most important areas of social science research. This paper synthesizes and critically reviews the emerging traditions in the study of change dynamics. Three mainstream theories of evolution are introduced to explain change: the Darwinian concept of survival of the fittest, the Probability model and the Complexity approach. The literature review provides a basis for development of research questions that search for a more comprehensive understanding of organizational change. The paper concludes by arguing for the development of a complementary research tradition, which combines an evolutionary and organizational analysis of transformation and change.     

THE ANALYSIS OF OUTLYING DATA POINTS USING ROBUST REGRESSION: A MULTIVARIATE PROBLEM-BANK IDENTIFICATION MODEL*

Because the eight largest bank failures in United States history have occurred since 1973 [24], the development of early-warning problem-bank identification models is an important undertaking. It has been shown previously [3] [5] that M-estimator robust regression provides such a model. The present paper develops a similar model for the multivariate case using both a robustified Mahalanobis distance analysis [21] and principal components analysis [10]. In addition to providing a successful presumptive problem-bank identification model, combining the use of the M-estimator robust regression procedure and the robust Mahalanobis distance procedure with principal components analysis is also demonstrated to be a general method of outlier detection. The results from using these procedures are compared to some previously suggested procedures, and general conclusions are drawn.     

Team Receptivity to Newcomers: Five Decades of Evidence and Future Research Themes

Reviews of research on newcomers mostly address socialization processes, focusing on individual adjustment. This article takes a different approach by examining the ways in which teams adapt to newcomers, indicating team receptivity. We review the empirical research published over the last five decades (1960–June 2012) that examines the antecedents of three team receptivity components—team reflection, team knowledge utilization, and newcomer acceptance—across different research disciplines and team settings. Drawing on this literature, we propose that team receptivity to newcomers can have positive consequences for sustained team performance, provided that team reflection and team knowledge utilization coincide with newcomer acceptance. We challenge scholars to tackle these three components simultaneously and provide methodological recommendations for doing so. To facilitate such efforts, we present a conceptual multi-level model specifying team, oldtimer, and newcomer characteristics that contribute to team receptivity and are amenable to managerial intervention.     

Performance measurement with classification information: an enhanced additive DEA model

This paper presents an improved measurement tool for evaluating performance of branches within a major Canadian bank. While there have been numerous previous studies of performance in the banking industry, particularly at the branch level, this study is different in a very significant way: specifically two kinds of data are used to develop the model. The first type of data is that related to standard transactions, available from any bank; such have formed the basis of numerous previous studies. The second type of data, obtained from the site studied, is classification information, based on branch consultant/expert judgment as to good and poor performance of branches. The purpose herein is to present a modified version of an existing benchmarking model, data envelopment analysis (DEA), and to show how this tool is applied in the banking industry. The mechanism used herein to incorporate expert knowledge within the DEA framework is to first apply a discriminant or classification tool, to quantify the functional relation that best captures the expert's mental model for performance. The outcome of this first phase is an orientation of variables to aid in the definition of inputs and outputs. The resulting orientation then defines the DEA model that makes up the second phase of the model.     

Quantitative Uncertainty Analysis for a Weed Risk Assessment System

Weed risk assessments (WRA) are used to identify plant invaders before introduction. Unfortunately, very few incorporate uncertainty ratings or evaluate the effects of uncertainty, a fundamental risk component. We developed a probabilistic model to quantitatively evaluate the effects of uncertainty on the outcomes of a question‐based WRA tool for the United States. In our tool, the uncertainty of each response is rated as Negligible, Low, Moderate, or High. We developed the model by specifying the likelihood of a response changing for each uncertainty rating. The simulations determine if responses change, select new responses, and sum the scores to determine the risk rating. The simulated scores reveal potential variation in WRA risk ratings. In testing with 204 species assessments, the ranges of simulated risk scores increased with greater uncertainty, and analyses for most species produced simulated risk ratings that differed from the baseline WRA rating. Still, the most frequent simulated rating matched the baseline rating for every High Risk species, and for 87% of all tested species. The remaining 13% primarily involved ambiguous Low Risk results. Changing final ratings based on the uncertainty analysis results was not justified here because accuracy (match between WRA tool and known risk rating) did not improve. Detailed analyses of three species assessments indicate that assessment uncertainty may be best reduced by obtaining evidence for unanswered questions, rather than obtaining additional evidence for questions with responses. This analysis represents an advance in interpreting WRA results, and has enhanced our regulation and management of potential weed species.     

Recalibration of the Grunow–Finke Assessment Tool to Improve Performance in Detecting Unnatural Epidemics

Successful identification of unnatural epidemics relies on a sensitive risk assessment tool designed for the differentiation between unnatural and natural epidemics. The Grunow–Finke tool (GFT), which has been the most widely used, however, has low sensitivity in such differentiation. We aimed to recalibrate the GFT and improve the performance in detection of unnatural epidemics. The comparator was the original GFT and its application in 11 historical outbreaks, including eight confirmed unnatural outbreaks and three natural outbreaks. Three steps were involved: (i) removing criteria, (ii) changing weighting factors, and (iii) adding and refining criteria. We created a series of alternative models to examine the changes on the parameter likelihood of unnatural outbreaks until we found a model that correctly identified all the unnatural outbreaks and natural ones. Finally, the recalibrated GFT was tested and validated with data from an unnatural and natural outbreak, respectively. A total of 238 models were tested. Through the removal of criteria, increasing or decreasing weighting factors of other criteria, adding a new criterion titled “special insights,” and setting a new threshold for likelihood, we increased the sensitivity of the GFT from 38% to 100%, and retained the specificity at 100% in detecting unnatural epidemics. Using test data from an unnatural and a natural outbreak, the recalibrated GFT correctly classified their etiology. The recalibrated GFT could be integrated into routine outbreak investigation by public health institutions and agencies responsible for biosecurity.     

跨国公司在华子公司角色演化:理论及案例分析

本文根据影响子公司角色转变的因素,将子公司的角色根据每种因素的强弱不同分为八种类型,即起步者、淘汰者、办事员、支持者、小诸侯、贡献者、直辖领袖和自由领袖.根据该子公司角色划分方法和演化路径分析方法,本文深入研究了一家跨国公司在华子公司-BEC公司的角色演化情况,研究证实了本文得出的角色划分方法和演化路径分析框架的适用性,也得到了跨国公司在华子公司的一个具体演化路径.     

The Influence of Middle Managers in the Business Planning Process: A Case Study in the UK NHS

The paper takes a processual approach (Mintzberg and Waters, 1985; Pettigrew, Ferlie and McKee, 1992) in conjunction with a typology of middle-management influence upon strategic change (Floyd and Wooldridge, 1992) to investigate the role of middle managers in business planning in the National Health Service (NHS). Over time, as the business planning process becomes increasingly one which adopts a top-down approach, the main influence middle managers have is upon the implementation of deliberate strategic change. Middle managers modify the implementation of deliberate strategy by contesting the performance indicators that form the basis of the business planning framework. In particular they draw upon features of inner and outer context of the organization to question the legitimacy of business planning. However, the findings also show, albeit to a limited extent, that middle managers are purveyors as well as recipients of change. That middle managers can have upward influence has important implications for policy-makers since potentially, middle managers can enjoy an enhanced role and add value to organizations, in this case to patient care. Therefore recent attacks upon their numbers and role may be misplaced. In addition a high degree of central intervention in the NHS generally may be inappropriate, since it militates against an enhanced role for middle managers.     

Process research in strategy formation: Theory, methodology and relevance

This paper develops a view of the strategy formation process, drawing on a review of contributions that are based on a process approach, and more specifically the work of Henry Mintzberg, Andrew Pettigrew and Andrew Van de Ven. This view is meant to provide a way to bridge the content–process gap in strategic management by addressing the aspects of process theory and process methodology. Structuration is found to provide a useful theoretical basis for strategy formation research. Process methodology is found to be about discovering valid generative mechanisms that explain regular patterns in event sequences. Strategy formation research can then be made relevant for management practice by providing insight with regard to generative mechanisms and associated process trajectories of continuity and change, to allow for judgements on the favourability of the course of the process as well as the necessity to intervene or to let the process run its course.     

Creating receptivity in cross-cultural coordination: the role of civic virtue

This paper explores receptivity creation in cross-cultural coordination. Qualitative data from an inter-organizational relationship between culturally dissimilar and unequal groups are used to show that, while practices fostering defensiveness inhibit receptivity, those promoting civic virtue create partial receptivity. Partial receptivity falls short of cross-cultural synergy, but is a more achievable outcome.     

A Decision Support Tool to Compare Waterborne and Foodborne Infection and/or Illness Risks Associated with Climate Change

Climate change may impact waterborne and foodborne infectious disease, but to what extent is uncertain. Estimating climate‐change‐associated relative infection risks from exposure to viruses, bacteria, or parasites in water or food is critical for guiding adaptation measures. We present a computational tool for strategic decision making that describes the behavior of pathogens using location‐specific input data under current and projected climate conditions. Pathogen‐pathway combinations are available for exposure to norovirus, Campylobacter, Cryptosporidium, and noncholera Vibrio species via drinking water, bathing water, oysters, or chicken fillets. Infection risk outcomes generated by the tool under current climate conditions correspond with those published in the literature. The tool demonstrates that increasing temperatures lead to increasing risks for infection with Campylobacter from consuming raw/undercooked chicken fillet and for Vibrio from water exposure. Increasing frequencies of drought generally lead to an elevated infection risk of exposure to persistent pathogens such as norovirus and Cryptosporidium, but decreasing risk of exposure to rapidly inactivating pathogens, like Campylobacter. The opposite is the case with increasing annual precipitation; an upsurge of heavy rainfall events leads to more peaks in infection risks in all cases. The interdisciplinary tool presented here can be used to guide climate change adaptation strategies focused on infectious diseases.     

Enabling disruptive innovations through the use of customer analysis methods

The theory of disruptive innovation has had a profound effect on academic literature and management mindsets. Nevertheless, the processes that are required to develop disruptive innovations are not yet well understood. An essential part of creating disruptive innovations is gathering the right information on potential and current customers. The research questions that are addressed in this paper deal with the suitability of customer analysis methods for providing this information. The customer analysis model that is formulated in this paper summarizes the results of a literature review regarding the requirements of customer analysis for the success of disruptive innovations. With insights on context, customers, constraints and effects, the model reveals what information is needed to successfully shape the disruptive innovation process. Following the literature on disruptive and radical innovation, a group of eight customer analysis methods is selected and assessed. The analysis reveals that none of the existing methods can generate all of the required information. By combining and modifying the associated methods, the requirements of the proposed model and, by extension, the market can be met. Managers who follow the suggestions of this paper will develop a better understanding of current and potential customers and, therefore, unveil the potential of disruptive innovations.     

Shared Leadership in Commercial Organizations: A Systematic Review of Definitions,Theoretical Frameworks and Organizational Outcomes

The importance of context has been well established in studies of leadership (Bryman, A. and Stephens, M. (1996). The importance of context: qualitative research and the study of leadership. Leadership Quarterly, 7, pp. 353–371; Pettigrew, A. and Whipp, R. (1991). Managing Change for Competitive Success. Oxford: Blackwell). However, recent reviews of shared leadership have tended to merge findings across commercial and non‐commercial settings, disregarding contextual differences in these distinctive domains. Acknowledging that the challenges of leadership may vary in different organizational contexts, this paper argues that a focused review of shared leadership in commercial organizations (COs) is needed. The authors thus systematically review findings from over twenty years of empirical research on the practice of shared leadership in commercial organizations, critically reviewing definitions, theoretical dispositions and measurement approaches adopted in the field, before evaluating the impact of shared leadership on performance in this context. Findings from commercial and non‐ commercial organizations are then compared, highlighting significant differences in the conceptualization of shared leadership in these distinct settings. Contributing to theory in this field, a framework is developed, mapping the landscape of current research in commercial contexts, revealing critical gaps in our present understanding of shared leadership processes. Consequently, a model summarizing a proposed research agenda for future studies is provided, highlighting the need for such research to focus on the interactions of individuals as they share in the leadership of their team.     

The Accident Evolution and Barrier Function (AEB) Model Applied to Incident Analysis in the Processing Industries

This study develops a theoretical model for accident evolutions and how they can be arrested. The model describes the interaction between technical and human-organizational systems which may lead to an accident. The analytic tool provided by the model gives equal weight to both these types of systems and necessitates simultaneous and interactive accident analysis by engineers and human factors specialists. It can be used in predictive safety analyses as well as in post hoc incident analyses. To illustrate this, the AEB model is applied to an incident reported by the nuclear industry in Sweden. In general, application of the model will indicate where and how safety can be improved, and it also raises questions about issues such as the cost, feasibility, and effectiveness of different ways of increasing safety.