A contingency theory perspective on the risk management control system within Birmingham City Council

In recent years the topic of risk management has moved up the agenda of both government and industry, and private sector initiatives to improve risk and internal control systems have been mirrored by similar promptings for change in the public sector. Both regulators and practitioners now view risk management as an integral part of the process of corporate governance, and an aid to the achievement of strategic objectives.The paper uses case study material on the risk management control system at Birmingham City Council to extend existing theory by developing a contingency theory for the public sector. The case demonstrates that whilst the structure of the control system fits a generic model, the operational details indicate that controls are contingent upon three core variables—central government policies, information and communication technology and organisational size. All three contingent variables are suitable for testing the theory across the broader public sector arena.     

基于预算的考核、预算氛围和预算副效应

预算作为一种管理控制工具被广泛运用于实务,并有许多企业根据预算进行业绩考核。基于218个问卷样本,本文运用结构方程(SEM)研究了基于预算的考核执行、预算氛围和预算副作用之间的关系。结果表明,基于预算的考核执行与预算副作用正相关,预算氛围与预算副作用负相关。这表明严格的预算考核执行会带来副作用,而恰当的预算氛围可以降低副作用。该结论与权变理论的系统性适应相吻合,即在有较好预算氛围的公司,严格的预算考核执行更为适应,这类公司往往管理更规范。     

The enactment of management control systems: A critique of Simons

Simon proposes a contingency relationship between a firm's strategy and its management control systems. However, his model underspecifies the relationship between strategic uncertainties and management controls, underplays the recursive impact of management controls on strategy formulation, and ignores the potential influence of managerial characteristics on control system design.     

A contingency model of perceived effectiveness in accounting information systems: Organizational coordination and control effects

A contingency model is advanced that examines sources of requirements for organizational coordination and control as they affect the extent of integration in an accounting information system. Requirements that are contingent on the degree of organizational formalization, information interdependence among functional areas, and dependence in interorganizational information sharing and electronic data interchange links, are examined. The congruence or fit of system integration with those requirements is a key concept that influences beliefs about system effectiveness. Results of the empirical study indicated that, as hypothesized, the fit between the accounting system design and the contingency factors resulted in a more successful system. Specifically, system fit was a significant factor that explained variations in perceived AIS effectiveness, as measured by decision makers' perceived satisfaction with the accuracy and monitoring effectiveness of output information. The effect of system fit on a second factor of perceived AIS effectiveness, as measured by decision-makers' satisfaction with the perceived quality of information content in system outputs, was only marginally significant. The study addresses an important area in accounting systems research that directly relates to the decision facilitation and control objectives of accounting information.     

Firm size and cost system sophistication: The role of firm age

The costing literature has failed to conclusively explain why some companies implement sophisticated costing systems while others do not. Although some contingency variables were proposed, inconclusive results were reported which raised concerns about their underlying theory. Focusing on firm size, as the most examined and confusing variable in this contingency literature, we develop and test more complex relations than in prior studies to provide more insights into its role. More specifically, we test potential indirect positive relations between firm size and cost system sophistication (through product diversity and cost structure) and bring to light the role of firm age largely neglected in the cost accounting literature. Using two different statistical analyses (i.e. SEM and PLS) and data from manufacturing firms, our findings suggest, in contrast to the majority of prior studies, that not all larger firms should be expected to have sophisticated costing systems. The impact of firm size on cost system sophistication depends on firm age and is mediated by product diversity but not cost structure. We conclude by emphasizing the need for more complex models to further advance the theory on costing systems. Such models should go beyond explaining the potential impact of each contextual variable in isolation.     

Management control as a system or a package? Conceptual and empirical issues

Despite the trend in investigating combinations of MC practices that form packages or systems, there is ambiguity about what is meant by a “control package” or “control system”. In this paper, we address questions related to MC as a package and as a system, both from a conceptual and empirical perspective. The purpose of our study is to clarify a number of issues, so as to guide future research in this area. We do not claim to have all the answers. Rather we make a number of assumptions explicit to show when it is important to address multiple MC practices simultaneously, why this is the case, and what the empirical implications are. Our research directly relates to the systems approach to contingency theory and the literature’s struggle to clearly define its most fundamental concept, i.e., “internal consistency”. Our analysis provides a formal definition of “internal consistency” and shows how it can be used to conceptualize MC systems, thereby giving contingency theorists the necessary ingredient to move forward.     

Evaluating potential investments in new technologies: Balancing assessments of potential benefits with assessments of potential disbenefits, reliability and utilization

In recent years, the assessment of intangible benefits has become an explicit requirement of investment evaluation techniques. By contrast, assessments of three factors which can prevent the realization of any benefits have not become an explicit requirement. Those three factors are disbenefits, reliability and utilization. The importance of these factors may sometimes be identified prior to investment evaluation when exploratory methods such as contingency planning are used. However, evidence presented in this paper suggests that these three factors are often overlooked. Further, the evidence presented in this paper suggests that investment performance often suffers as a result. Accordingly, it is argued that investment evaluations need to be balanced by making assessments of disbenefits, reliability and utilization an explicit requirement. This argument is supported by reporting of experiences from action research. These experiences indicate that investment evaluations can be balanced by making assessments of disbenefits, reliability and utilization an explicit requirement.     

Aligning Performance Measurement Systems With Strategy: The Case of Environmental Strategy

Alignment of an organization's performance measurement system with its strategy is widely advocated as a guiding principle in management control system design. Despite its importance, it is far from clear what strategic alignment of performance measures entails, whether and how organizations achieve it. In this article we explore the alignment of performance measures focusing on firms' use of environmental performance indicators as the consequence of pursuing an environmental strategy. Based on the economic and contingency literatures on management control system design and performance measurement, we propose that the use of such performance measures is a consequence of changing the design of the performance measurement system to accommodate the strategy, and by increasing the informativeness of performance metrics. We test these propositions in a sample of financial managers in manufacturing firms in The Netherlands. We find that alignment to environmental strategy is mostly achieved through the increased quantification of environmental performance measures and via their increased sensitivity to managerial actions.     

An evaluation of volatility forecasting techniques

The existing literature contains conflicting evidence regarding the relative quality of stock market volatility forecasts. Evidence can be found supporting the superiority of relatively complex models (including ARCH class models), while there is also evidence supporting the superiority of more simple alternatives. These inconsistencies are of particular concern because of the use of, and reliance on, volatility forecasts in key economic decision-making and analysis, and in asset/option pricing. This paper employs daily Australian data to examine this issue. The results suggest that the ARCH class of models and a simple regression model provide superior forecasts of volatility. However, the various model rankings are shown to be sensitive to the error statistic used to assess the accuracy of the forecasts. Nevertheless, a clear message is that volatility forecasting is a notoriously difficult task.     

Dirichlet process mixture models for insurance loss data

In the recent insurance literature, a variety of finite-dimensional parametric models have been proposed for analyzing the hump-shaped, heavy-tailed, and highly skewed loss data often encountered in applications. These parametric models are relatively simple, but they lack flexibility in the sense that an actuary analyzing a new data-set cannot be sure that any one of these parametric models will be appropriate. As a consequence, the actuary must make a non-trivial choice among a collection of candidate models, putting him/herself at risk for various model misspecification biases. In this paper, we argue that, at least in cases where prediction of future insurance losses is the ultimate goal, there is reason to consider a single but more flexible nonparametric model. We focus here on Dirichlet process mixture models, and we reanalyze several of the standard insurance data-sets to support our claim that model misspecification biases can be avoided by taking a nonparametric approach, with little to no cost, compared to existing parametric approaches.     

交互预算:应对战略不确定性、契合管理控制的新机制——基于天津一汽丰田公司的案例研究

本文基于Simons的管理控制框架,在理论上梳理交互预算的控制特征、重构交互预算与其它管理控制方式间的协同关系,通过对天津一汽丰田公司预算控制的案例描述与理论分析,阐明了有别于传统的诊断预算控制,交互预算既能够克服传统预算方式的制度弊端,又能成为适应不确定性环境下的战略管理工具,还是促进企业上下级对话沟通、组织学习和管理创新的机制;另外,交互预算控制也是契合管理控制系统中信念控制、边界控制等其他控制方式的制度安排。     

Modeling Operational Risk With Bayesian Networks

Bayesian networks is an emerging tool for a wide range of risk management applications, one of which is the modeling of operational risk. This comes at a time when changes in the supervision of financial institutions have resulted in increased scrutiny on the risk management of banks and insurance companies, thus giving the industry an impetus to measure and manage operational risk. The more established methods for risk quantification are linear models such as time series models, econometric models, empirical actuarial models, and extreme value theory. Due to data limitations and complex interaction between operational risk variables, various nonlinear methods have been proposed, one of which is the focus of this article: Bayesian networks. Using an idealized example of a fictitious on line business, we construct a Bayesian network that models various risk factors and their combination into an overall loss distribution. Using this model, we show how established Bayesian network methodology can be applied to: (1) form posterior marginal distributions of variables based on evidence, (2) simulate scenarios, (3) update the parameters of the model using data, and (4) quantify in real‐time how well the model predictions compare to actual data. A specific example of Bayesian networks application to operational risk in an insurance setting is then suggested.     

Management accounting and the challenge of strategic focus

The paper presents a case study of management accounting in a company that had been a highly diversified conglomerate but was implementing a new strategy of product market focus combined with a more multinational scope. Formerly subject to a simple but rigorous form of financial control, the new organizational identity of becoming a high-growth, high-technology company posed fresh challenges for its control style and, in particular, for the role of management accounting. The paper draws on self-referential systems theory in order to analyse the paradox that while an organization can become more focused on particular markets and technologies, its management accounting seems to become more diffuse and differentiated. As the company sought to develop a different corporate epistemology through the reproduction of a fresh identity, it established new forms of corporate communication through its quality and performance management systems. Autopoietic theory would acknowledge that management accounting should provide some system guidance but would warn against the possible danger that some forms of performance control may damage company self-production.     

Management control of public and not-for-profit activities

Traditional approaches to management control usually fail for public and not-for-profit activities.¹ The type of control applicable to such activities depends on four criteria: are objectives unambiguous, outputs measurable, effects of interventions known, and is the activity repetitive? Depending on where activities stand with regard to these criteria, the control applicable corresponds to one of six different types: routine, expert, trial-and-error, intuitive, judgemental, or political control. The first three types can be represented by cybernetic models; the other three ask for more complex and less deterministic models. For these, a “political” and a “garbage-can” model are described. Key elements in the latter models are the values and the culture of the actors. As an example, the topology for management control is applied to the area of budgeting, covering regular budgeting as well as such techniques as PPBS, MBO, and ZBB and distinguishing between investment budgets, operations budgets for input centers, and operations budgets for input-output centers. Coming back to management control in general, the paper discusses the consequences of choosing the wrong model for a given management control situation: it distinguishes between “Type I” and “Type II” errors. It finally relates management control to organizational adaptation and suggests how to avoid control systems which prevent an organizational system from learning.     

A Conceptual Framework for Learning Management Accounting

This paper demonstrates how Schoenfeld's ( 1985 ) conceptual framework for mathematics can provide an alternate framework for learning and thereby teaching management accounting. The four‐part framework—heuristics, resources, beliefs, and controls—is a refinement to problem‐based learning with three attributes in regard to management accounting. First, all aspects for teaching management accounting are integrated into a single framework or theory. Consistency among all parts of management accounting clarifies student and instructor roles in the learning process. Second, the framework's problem‐solving focus with linkages to explanatory materials or resources allows students to be rigorously informed about the functionality of management accounting heuristics. Third, transition or extension of relatively simple, standard problems to more complex nonstandard problems or cases is facilitated by introducing appropriate beliefs and controls. In effect, this approach enables management accounting, and particularly case analysis, to be taught with more structure.     

Management control of complex,mission-critical processes

Because the failure of complex, mission-critical systems—such as certain process control and manufacturing operations—can be exceptionally costly to an organization, appropriate management control of these systems is imperative. This paper presents a theory of management control of complex systems that is the potential basis for an intelligent DSS, which would be capable of supporting human agents monitoring complex systems. The theory is derived from field studies of agent decision making under procedural guidance, and it focuses on the most crucial—and interesting—aspect of agent behavior, i.e. the decision to deviate from a procedure when the procedure is considered detrimental to the achievement of organizational goals. The theory is instantiated in a computer model of the agents' decision processes. The computer model in turn embeds a simulation of the agents' situation and goal assessment processes that produce procedural non-compliance. © 2000 John Wiley & Sons, Ltd.     

A conceptual Object-Oriented Bayesian Network (OOBN) for modeling aircraft carrier-based UAS safety risk

This paper illustrates the conceptual development of a demonstration Object-Oriented Bayesian Network (OOBN) to integrate the hazards associated with an experimental Unmanned Aircraft System (UAS) planned for deployment from an aircraft carrier. The final Air/Ship Integration (A/SI) demonstration model is characterized by a top-level Bayesian network model with nine sub-nets comprising 70 causal factors with 15 mitigations. With the creation of a probabilistic model, inferences about changes to the states of the causal factors given the presence or absence of controls or mitigations can be ascertained. These inferences build on qualitative reasoning and enable an analyst to identify the most prominent causal factor groupings leading to a prioritization of the most influential causal factors. Mitigation effects can be systematically studied and assessed. The A/SI OOBN demonstration model illustrates the construction of an integrative safety risk model that may be used to compute a higher-order system mishap probability for an experimental UAS that interacts with ship operations in a highly severe, dynamic sea environment. In addition to computing mishap probabilities, the Bayesian approach may also be used to support control contingency management for possible mitigation implementation.     

Monetary policy games,financial instability and incomplete information

In the aftermath of the recent global financial crisis, monetary authorities, while pursuing traditional objectives, such as the control of inflation, are also eager to promote financial stability. In this paper, we model the strategic interaction of the central bank and the financial sector and explore a simple monetary policy game with perceived substantial risks to financial stability, where the central bank can be of two types, one pursuing strict inflation-targeting and the other concerned with affecting the expectations formed by the financial sector participants; however, the financial sector is unsure which, due to incomplete information. The conclusion is that for small shocks to inflation there is a pooling equilibrium, whereas for larger shocks there is separation. In the latter case, the central bank that has an explicit financial stability concern is willing to exercise more muted control to inflation in order to reinforce the safety of the financial sector.     

Management control,culture and ethnicity in a Chinese Indonesian company

This study explores socio-cultural aspects of management control in a Chinese Indonesian manufacturing company. Ethnographic data collection methods were combined with grounded theory data analysis to explore how cultures, ethnic differences, history, politics, and commercial considerations shaped management controls. A combination of emic and etic methods were used to generate grounded comparisons with nomethetic research on culture and control in a cultural contingency tradition.