An exploratory study of management accounting and control systems in a developing country

This thesis reports on the results of case studies in four commercial banks in Nigeria. The study focuses how management accounting and control systems (MCS) operate in the four banks. The study is motivated by the dearth of literature on management accounting practices in the developing world in general and in Nigeria in specific. The case study approach adopted in conducting the research was useful in exploring the dynamics of the MCS in the organisations. Data was gathered from two sources. First, semi-structured interviews were conducted with managers at the head office, regional office and branches of each bank. The participants were selected from different backgrounds and managerial levels to provide broader understanding of the operations of the MCS. Second, various internal and external documents were reviewed to provide supporting evidence for the interview results. New institutional sociology (NIS) provided the theoretical framework to understand the results. NIS provided explanations for how the MCS in the four banks were shaped by diverse external and internal factors. The key factors identified as shaping the operations of the MCS were the need to comply with the regulatory environment (coercive isomorphism), the need to maintain social and cultural support (normative isomorphism) and the need to imitate successful organisations in order to appear legitimate (mimetic isomorphism). The study also examines the interplay between the institutional forces, market forces and infra-organisational power relations. This analysis is necessary to overcome the criticism of NIS that it downplays the role of market forces, agency and intra-organisational relations. The findings of the study have implications for understanding the operations of MCS in the developing world.

Strategy and control systems:a framework for analysis

This research explores the links between the strategies adopted by companies and the mechanisms used to control the organisation. This is not seen as a one way process with the control system following from the strategy but rather as an interactive process between the control systems, the environment and the business strategy. The main proposition of the research, derived from a review of the relevant literature, is that the dimensions of Business Pro-Activity and Environmental Change provide a plausible explanation of the reasons why companies need to adopt different strategies in order to be successful in different markets. A model is proposed which links these dimensions with the business strategy, organisational structure, strategic planning system and management control systems. The model is used as a framework for analysing four companies in order to further our understanding of these interactions and the mechanisms which act to both promote and resist change. Whilst it is not suggested that the model in its present form is a perfect instrument it has, during the course of this research, proved to be an appropriate framework for analysing the various mechanisms used by four companies to formulate and implement their strategies. The research reveals that these should not be viewed independently but as a balanced system.

Aspects of the design and operation of production control systems in manufacturing industry

Computerised production control developments have concentrated on Manufacturing Resources Planning (MRP II) systems. The literature suggests however, that despite the massive investment in hardware, software and management education, successful implementation of such systems in manufacturing industries has proved difficult. This thesis reviews the development of production planning and control systems, in particular, investigates the causes of failures in implementing MRP/MRP II systems in industrial environments and argues that the centralised and top-down planning structure, as well as the routine operational methodology of such systems, is inherently prone to failure. The thesis reviews the control benefits of cellular manufacturing systems but concludes that in more dynamic manufacturing environments, techniques such as Kanban are inappropriate. The basic shortcomings of MRP II systems are highlighted and a new enhanced operational methodology based on distributed planning and control principles is introduced. Distributed Manufacturing Resources Planning (DMRP), was developed as a capacity sensitive production planning and control solution for cellular manufacturing environments. The system utilises cell based, independently operated MRP II systems, integrated into a plant-wide control system through a Local Area Network. The potential benefits of adopting the system in industrial environments is discussed and the results of computer simulation experiments to compare the performance of the DMRP system against the conventional MRP II systems presented. DMRP methodology is shown to offer significant potential advantages which include ease of implementation, cost effectiveness, capacity sensitivity, shorter manufacturing lead times, lower working in progress levels and improved customer service.

Modelling manufacturing planning and control systems:the application of object-oriented principles and discrete-event simulation

Manufacturing planning and control systems are fundamental to the successful operations of a manufacturing organisation. 10 order to improve their business performance, significant investment is made by companies into planning and control systems; however, not all companies realise the benefits sought Many companies continue to suffer from high levels of inventory, shortages, obsolete parts, poor resource utilisation and poor delivery performance. This thesis argues that the fit between the planning and control system and the manufacturing organisation is a crucial element of success. The design of appropriate control systems is, therefore, important. The different approaches to the design of manufacturing planning and control systems are investigated. It is concluded that there is no provision within these design methodologies to properly assess the impact of a proposed design on the manufacturing facility. Consequently, an understanding of how a new (or modified) planning and control system will perform in the context of the complete manufacturing system is unlikely to be gained until after the system has been implemented and is running. There are many modelling techniques available, however discrete-event simulation is unique in its ability to model the complex dynamics inherent in manufacturing systems, of which the planning and control system is an integral component. The existing application of simulation to manufacturing control system issues is limited: although operational issues are addressed, application to the more fundamental design of control systems is rarely, if at all, considered. The lack of a suitable simulation-based modelling tool does not help matters. The requirements of a simulation tool capable of modelling a host of different planning and control systems is presented. It is argued that only through the application of object-oriented principles can these extensive requirements be achieved. This thesis reports on the development of an extensible class library called WBS/Control, which is based on object-oriented principles and discrete-event simulation. The functionality, both current and future, offered by WBS/Control means that different planning and control systems can be modelled: not only the more standard implementations but also hybrid systems and new designs. The flexibility implicit in the development of WBS/Control supports its application to design and operational issues. WBS/Control wholly integrates with an existing manufacturing simulator to provide a more complete modelling environment.

An investigation of management accounting control systems in the palm oil industry:a sociomaterial approach to practice change

The primary aim of this research is to understand what constitutes management accounting and control (MACs) practice and how these control processes are implicated in the day to day work practices and operations of the organisation. It also examines the changes that happen in MACs practices over time as multiple actors within organisational settings interact with each other. I adopt a distinctive practice theory approach (i.e. sociomateriality) and the concept of imbrication in this research to show that MACs practices emerge from the entanglement between human/social agency and material/technological agency within an organisation. Changes in the pattern of MACs practices happens in imbrication processes which are produced as the two agencies entangle. The theoretical approach employed in this research offers an interesting and valuable lens which seeks to reveal the depth of these interactions and uncover the way in which the social and material imbricate. The theoretical framework helps to reveal how these constructions impact on and produce modifications of MACs practices. The exploration of the control practices at different hierarchical levels (i.e. from the operational to middle management and senior level management) using the concept of imbrication process also maps the dynamic flow of controls from operational to top management and vice versa in the organisation. The empirical data which is the focus of this research has been gathered from a case study of an organisation involved in a large vertically integrated palm oil industry company in Malaysia specifically the refinery sector. The palm oil industry is a significant industry in Malaysia as it contributed an average of 4.5% of Malaysian Gross Domestic Product, over the period 1990 -2010. The Malaysian palm oil industry also has a significant presence in global food oil supply where it contributed 26% of the total oils and fats global trade in 2010. The case organisation is a significant contributor to the Malaysian palm oil industry. The research access has provided an interesting opportunity to explore the interactions between different groups of people and material/technology in a relatively heavy process food industry setting. My research examines how these interactions shape and are shaped by control practices in a dynamic cycle of imbrications over both short and medium time periods.

Fully probabilistic control for stochastic nonlinear control systems with input dependent noise

Robust controllers for nonlinear stochastic systems with functional uncertainties can be consistently designed using probabilistic control methods. In this paper a generalised probabilistic controller design for the minimisation of the Kullback-Leibler divergence between the actual joint probability density function (pdf) of the closed loop control system, and an ideal joint pdf is presented emphasising how the uncertainty can be systematically incorporated in the absence of reliable systems models. To achieve this objective all probabilistic models of the system are estimated from process data using mixture density networks (MDNs) where all the parameters of the estimated pdfs are taken to be state and control input dependent. Based on this dependency of the density parameters on the input values, explicit formulations to the construction of optimal generalised probabilistic controllers are obtained through the techniques of dynamic programming and adaptive critic methods. Using the proposed generalised probabilistic controller, the conditional joint pdfs can be made to follow the ideal ones. A simulation example is used to demonstrate the implementation of the algorithm and encouraging results are obtained.

Dynamic Ontologies in Information Security Systems

Different types of ontologies and knowledge or metaknowledge connected to them are considered and analyzed aiming at realization in contemporary information security systems (ISS) and especially the case of intrusion detection systems (IDS) or intrusion prevention systems (IPS). Human-centered methods INCONSISTENCY, FUNNEL, CALEIDOSCOPE and CROSSWORD are algorithmic or data-driven methods based on ontologies. All of them interact on a competitive principle ‘survival of the fittest’. They are controlled by a Synthetic MetaMethod SMM. It is shown that the data analysis frequently needs an act of creation especially if it is applied to knowledge-poor environments. It is shown that human-centered methods are very suitable for resolutions in case, and often they are based on the usage of dynamic ontologies

Probabilistic DHP adaptive critic for nonlinear stochastic control systems

Following the recently developed algorithms for fully probabilistic control design for general dynamic stochastic systems (Herzallah & Káarnáy, 2011; Kárný, 1996), this paper presents the solution to the probabilistic dual heuristic programming (DHP) adaptive critic method (Herzallah & Káarnáy, 2011) and randomized control algorithm for stochastic nonlinear dynamical systems. The purpose of the randomized control input design is to make the joint probability density function of the closed loop system as close as possible to a predetermined ideal joint probability density function. This paper completes the previous work (Herzallah & Kárnáy, 2011; Kárný, 1996) by formulating and solving the fully probabilistic control design problem on the more general case of nonlinear stochastic discrete time systems. A simulated example is used to demonstrate the use of the algorithm and encouraging results have been obtained.

Enhancing the performance of intelligent control systems in the face of higher levels of complexity and uncertainty

Modern advances in technology have led to more complex manufacturing processes whose success centres on the ability to control these processes with a very high level of accuracy. Plant complexity inevitably leads to poor models that exhibit a high degree of parametric or functional uncertainty. The situation becomes even more complex if the plant to be controlled is characterised by a multivalued function or even if it exhibits a number of modes of behaviour during its operation. Since an intelligent controller is expected to operate and guarantee the best performance where complexity and uncertainty coexist and interact, control engineers and theorists have recently developed new control techniques under the framework of intelligent control to enhance the performance of the controller for more complex and uncertain plants. These techniques are based on incorporating model uncertainty. The newly developed control algorithms for incorporating model uncertainty are proven to give more accurate control results under uncertain conditions. In this paper, we survey some approaches that appear to be promising for enhancing the performance of intelligent control systems in the face of higher levels of complexity and uncertainty.

Control Systems with Constraints and Uncertain Initial Conditions

AMS subject classification: 49N55, 93B52, 93C15, 93C10, 26E25.

Optimal control of affine connection control systems from the point of view of Lie algebroids

The purpose of this paper is to use the framework of Lie algebroids to study optimal control problems for affine connection control systems (ACCSs) on Lie groups. In this context, the equations for critical trajectories of the problem are geometrically characterized as a Hamiltonian vector field.