The two-way relationship between the Balanced Scorecard and Management Control Systems in organizations:Lessons from a Case Study

This paper reports a case study conducted in Quinta da Aveleda, one of
the three largest Portuguese wine companies. Our aim was to explore the
relationship established between a newly implemented Balanced Scorecard
(BSC) and the elements of the Management Control System (MCS) in the
organization. Thus, two specific objectives were pursued. Firstly, to identify
the influences (barriers, opportunities) of the existing MCS on the implementation
of the BSC. Secondly, to identify the impacts the BSC implementation
was able to exert on the configuration of the organization’s MCS.
We found that the budgeting process, the planning system, the information
infrastructure, and the organizational structure and culture were the elements
of the previous MCS that influenced the BSC implementation process.
Eventually, the BSC implementation led to important changes in the budgeting,
planning, reporting systems and processes. In order to explain these
findings, we briefly explored the main issues and factors accounting for the
scope and nature of the BSC’s impacts on Quinta da Aveleda. These issues
and factors were the mobilized organizational resources, the implementation
approach, the communication, and the organizational support.

PRECYSE: Cyber-attack Detection and Response for Industrial Control Systems

In this short paper, we present an integrated approach to detecting and mitigating cyber-attacks to modern interconnected industrial control systems. One of the primary goals of this approach is that it is cost effective, and thus whenever possible it builds on open-source security technologies and open standards, which are complemented with novel security solutions that address the specific challenges of securing critical infrastructures.

Investigation of organic xenobiotic transfers, partitioning and processing in air-soil-plant systems using a microcosm apparatus. Part I:Microcosm development

A microcosm system was developed to investigate transfers of organic xenobiotics in air-soil-plant systems. This was validated using ¹⁴C labelled 1,2-dichlorobenzene (DCB) as a model compound. Trapping efficiency was 106 ± 3% for volatile compounds and 93.0 ± 2.2% for carbon dioxide in a blank microcosm arrangement. Recovery of 1,2-dichlorobenzene spiked to grassed and unplanted soils was > 90% after 1 week. The predominant DCB loss process was volatilisation with no evidence for mineralisation over 1 week and 20-30% of the added spike remained in soil. Although there was no evidence for root uptake and translocation of added label, foliar uptake of soil volatilised compound was detected. The microcosm showed good potential for study of ¹⁴C labelled and unlabelled organic xenobiotic transfers in air-soil-plant systems with single plants and also intact planted cores.

Special section on intelligent control systems and signal processing

The IFAC International Conference on Intelligent Control Systems and Signal Processing (ICONS 2003) was organized under the auspices of the recently founded IFAC Technical Committee on Cognition and Control, and it was the first IFAC event specifically devoted to this theme. Recognizing the importance of soft-computing techniques for fields covered by other IFAC Technical Committees, ICONS 2003 was a multi-track Conference, co-sponsored by four additional Technical Committees: Computers for Control, Optimal Control, Control in Agriculture, and Modelling, Identification and Signal Processing. The Portuguese Society for Automatic Control (APCA) hosted ICONS 2003, which was held at the University of Algarve, Faro, Portugal.

Training multilayer perceptrons for control systems applications - a comparison of different approaches

Multilayer perceptrons (MLPs) (1) are the most common artificial neural networks employed in a large field of applications. In control and signal processing applications, MLPs are mainly used as nonlinear mapping approximators. The most common training algorithm used with MLPs is the error back-propagation (BP) alg. (1).

Learning control systems

Novel method of controller (PID) autotuning, involving neural networks and genetic algorithms: to employ neural networks to map the identification measures and controller parameters to objective functions, adapt these models on-line; to employ the genetic algorithm to perform on-line minimization.

Visualizing control systems performance: A fractional perspective

This article presents a novel method for visualizing the control systems behavior. The proposed scheme uses the tools of fractional calculus and computes the signals propagating within the system structure as a time/frequency-space wave. Linear and nonlinear closed-loop control systems are analyzed, for both the time and frequency responses, under the action of a reference step input signal. Several nonlinearities, namely, Coulomb friction and backlash, are also tested. The numerical experiments demonstrate the feasibility of the proposed methodology as a visualization tool and motivate its extension for other systems and classes of nonlinearities.

Smallholder group certification in Uganda - Analysis of internal control systems in two organic export companies

The organic agricultural sector of Uganda is among the most developed in Africa in terms of its professional institutional network and high growth rates of number of certified farmers and land area. Smallholder farmers are certified organic through contract production for export companies using a group certification scheme (internal control system - ICS). The ICS is a viable and well-accepted tool to certify small-scale producers in developing countries all over the world. Difficulties in certification are still stated to be among the main constraints for Uganda’s organic sector development. Therefore, this paper reports a qualitative case study comprising 34 expert interviews in two organic fresh-produce export companies in central Uganda, aiming to explore the challenges which underlie organic certification with ICS. The study shows that farmers cannot be labelled as ‘organic by default’ but deliberately engage in organic production as a marketing strategy. The small quantities purchased by the organic companies lead to a difficult marketing situation for the farmers, causing production and infiltration risks on the farm level. These risks require increased control that challenges the companies organizationally. The risks and control needs are a reason to involve farmers in ICS procedures and innovatively adapt the ICS by means of a bypass around formal perspective restrictions. The paper discusses different perspectives on risks, risk control and certification.

Moderating effects of management control systems and innovation on performance. Simple methods for correcting the effects of measurement error for interaction effects in small samples

In the accounting literature, interaction or moderating effects are usually assessed by means of OLS regression and summated rating scales are constructed to reduce measurement error bias. Structural equation models and two-stage least squares regression could be used to completely eliminate this bias, but large samples are needed. Partial Least Squares are appropriate for small samples but do not correct measurement error bias. In this article, disattenuated regression is discussed as a small sample alternative and is illustrated on data of Bisbe and Otley (in press) that examine the interaction effect of innovation and style of use of budgets on performance. Sizeable differences emerge between OLS and disattenuated regression

Effects of Air Pollution Control on Climate

Urban air pollution and climate are closely connected due to shared generating processes (e.g., combustion) for emissions of the driving gases and aerosols. They are also connected because the atmospheric lifecycles of common air pollutants such as CO, NOx and VOCs, and of the climatically important methane gas (CH4) and sulfate aerosols, both involve the fast photochemistry of the hydroxyl free radical (OH). Thus policies designed to address air pollution may impact climate and vice versa. We present calculations using a model coupling economics, atmospheric chemistry, climate and ecosystems to illustrate some effects of air pollution policy alone on global warming. We consider caps on emissions of NOx, CO, volatile organic carbon, and SOx both individually and combined in two ways. These caps can lower ozone causing less warming, lower sulfate aerosols yielding more warming, lower OH and thus increase CH4 giving more warming, and finally, allow more carbon uptake by ecosystems leading to less warming. Overall, these effects significantly offset each other suggesting that air pollution policy has a relatively small net effect on the global mean surface temperature and sea level rise. However, our study does not account for the effects of air pollution policies on overall demand for fossil fuels and on the choice of fuels (coal, oil, gas), nor have we considered the effects of caps on black carbon or organic carbon aerosols on climate. These effects, if included, could lead to more substantial impacts of capping pollutant emissions on global temperature and sea level than concluded here. Caps on aerosols in general could also yield impacts on other important aspects of climate beyond those addressed here, such as the regional patterns of cloudiness and precipitation.

Studies about the atomic capabilities concept for linear control systems in physical multi-agent environments

This paper shows the impact of the atomic capabilities concept to include control-oriented knowledge of linear control systems in the decisions making structure of physical agents. These agents operate in a real environment managing physical objects (e.g. their physical bodies) in coordinated tasks. This approach is presented using an introspective reasoning approach and control theory based on the specific tasks of passing a ball and executing the offside manoeuvre between physical agents in the robotic soccer testbed. Experimental results and conclusions are presented, emphasising the advantages of our approach that improve the multi-agent performance in cooperative systems