The politics of establishing catchment management agencies in South Africa: the case of the Breede-Overberg Catchment Management Agency

We reflect on the politics of establishing catchment management agencies in South Africa with a specific focus on the Breede-Overberg Catchment Management Agency (BOCMA), which was recently replaced by the Breede-Gouritz Catchment Management Agency (BGCMA). We do so by applying the framework of adaptive comanagement and its institutional prescriptions: collaboration, experimentation, and a bioregional approach. We start by introducing the history of this catchment management agency (CMA) and then describe the establishment of CMAs in South Africa in general and that of BOCMA in particular. We follow the framework for rule types and types of river basin organizations set out by the editors of this special feature with reference to adaptive comanagement where applicable. We then discuss the politics and strategies involved in the introduction of the CMA concept to the National Water Act and the latest developments around these institutions in South Africa. This is followed by reflections on what can be surmised about BOCMA’s democratic functioning and performance to date. We conclude by reflecting on the future of operations of the new BGCMA and CMAs in South Africa in general. While our research shows that BOCMA’s establishment process has featured several elements of adaptive comanagement and its institutional prescriptions, it remains to be seen to what extent it is possible to continue implementing this concept when further developing and operationalizing the BGCMA and the country’s other CMAs.

Talent Management : Utan Talent Management?

Syftet med denna studie är att kontrastera en utvald organisations strategier för att attrahera, behålla, utveckla och avveckla de viktigaste resurserna mot Talent Management och dess komponenter. Studien ämnar således mot att göra en kontrastering mellan traditionellt kompetensförsörjningsarbete mot det mer moderna konceptet Talent Management. Författarna har valt att undersöka detta genom att samla empiri från intervjuer med sex medarbetare kombinerat med analys av interna dokument. Resultatet visar att delar av myndighetens arbete med kompetensförsörjning kan likställas med Talent Management men att vissa komponenter är uteblivna. Baserat på resultatet framhålls i resultatdiskussionen att myndigheten möter stora utmaningar gällande enhetligt arbete med kompetensutveckling, kompetensförsörjning och ledarskap på grund utav det delegerade ansvaret från central nivå. I slutskedet av avsnittet för resultatdiskussion redovisas även en sammanfattande slutsats som grundar sig i ett framgångsrikt arbete inom blocken attrahera och avsluta samtidigt som arbete inom blocket behålla och utveckla varierar inom organisationen, dels på grund av delegerat ansvar. Slutligen presenteras förbättringsförslag inom organisationen och vidare forskning inom ämnet. 

Management and follow-up of a patient with Familial Atypical Multiple Mole-Melanoma (FAMMM) Syndrome

Introduction. Familial Atypical Multiple Mole-Melanoma Syndrome (FAMMM) is an autosomal dominant genodermatosis characterized by the presence of a high number of dysplastic nevi and family history of melanoma or pancreatic cancer. Melanomas in FAMMM patients tend to occur at a younger age, although they are clinically similar to sporadic melanomas in terms of overall survival. Case report. A 45 year-old woman with a family history of melanoma, a type II phototype and numerous (>100) nevi was admitted to our Department of Dermatology and Plastic Surgery. Over the past years, the patient underwent several surgical operations to remove pigmented lesions and two are dysplastic nevi. Since 1995, she underwent surgery to remove four melanomas. She is followed for skin examinations including dermoscopy. Conclusion. Identifying high-risk patients for melanoma represents a primary objective for the specialists that are involved in the management of this disease, especially in order to enact all the necessary surveillance and follow-up strategies.

Using Intelligent Agents to Understand Management Practices and Retail Productivity

Intelligent agents offer a new and exciting way of understanding the world of work. In this paper we apply agent-based modeling and simulation to investigate a set of problems in a retail context. Specifically, we are working to understand the relationship between human resource management practices and retail productivity. Despite the fact we are working within a relatively novel and complex domain, it is clear that intelligent agents could offer potential for fostering sustainable organizational capabilities in the future. The project is still at an early stage. So far we have conducted a case study in a UK department store to collect data and capture impressions about operations and actors within departments. Furthermore, based on our case study we have built and tested our first version of a retail branch simulator which we will present in this paper.

A Multi-Agent Simulation of Retail Management Practices

We apply Agent-Based Modeling and Simulation (ABMS) to investigate a set of problems in a retail context. Specifically, we are working to understand the relationship between human resource management practices and retail productivity. Despite the fact we are working within a relatively novel and complex domain, it is clear that intelligent agents do offer potential for developing organizational capabilities in the future. Our multi-disciplinary research team has worked with a UK department store to collect data and capture perceptions about operations from actors within departments. Based on this case study work, we have built a simulator that we present in this paper. We then use the simulator to gather empirical evidence regarding two specific management practices: empowerment and employee development.

Paths to peace: conflict management trajectories in militarized interstate disputes

When multiple third-parties (states, coalitions, and international organizations) intervene in the same conflict, do their efforts inform one another? Anecdotal evidence suggests such a possibility, but research to date has not attempted to model this interdependence directly. The current project breaks with that tradition. In particular, it proposes three competing explanations of how previous intervention efforts affect current intervention decisions: a cost model (and a variant on it, a limited commitments model), a learning model, and a random model. After using a series of Markov transition (regime-switching) models to evaluate conflict management behavior within militarized interstate disputes in the 1946-2001 period, this study concludes that third-party intervention efforts inform one another. More specifically, third-parties examine previous efforts and balance their desire to manage conflict with their need to minimize intervention costs (the cost and limited commitments models). As a result, third-parties intervene regularly using verbal pleas and mediation, but rely significantly less frequently on legal, administrative, or peace operations strategies. This empirical threshold to the intervention costs that third-parties are willing to bear has strong theoretical foundations and holds across different time periods and third-party actors. Furthermore, the analysis indicates that the first third-party to intervene in a conflict is most likely to use a strategy designed to help the disputants work toward a resolution of their dispute. After this initial intervention, the level of third-party involvement declines and often devolves into a series of verbal pleas for peace. Such findings cumulatively suggest that disputants hold the key to effective conflict management. If the disputants adopt and maintain an extreme bargaining position or fail to encourage third-parties to accept greater intervention costs, their dispute will receive little more than verbal pleas for negotiations and peace.

Coordinated pricing and inventory management

This dissertation mainly focuses on coordinated pricing and inventory management problems, where the related background is provided in Chapter 1. Several periodic-review models are then discussed in Chapters 2,3,4 and 5, respectively. Chapter 2 analyzes a deterministic single-product model, where a price adjustment cost incurs if the current selling price is changed from the previous period. We develop exact algorithms for the problem under different conditions and find out that computation complexity varies significantly associated with the cost structure. %Moreover, our numerical study indicates that dynamic pricing strategies may outperform static pricing strategies even when price adjustment cost accounts for a significant portion of the total profit. Chapter 3 develops a single-product model in which demand of a period depends not only on the current selling price but also on past prices through the so-called reference price. Strongly polynomial time algorithms are designed for the case without no fixed ordering cost, and a heuristic is proposed for the general case together with an error bound estimation. Moreover, our illustrates through numerical studies that incorporating reference price effect into coordinated pricing and inventory models can have a significant impact on firms' profits. Chapter 4 discusses the stochastic version of the model in Chapter 3 when customers are loss averse. It extends the associated results developed in literature and proves that the reference price dependent base-stock policy is proved to be optimal under a certain conditions. Instead of dealing with specific problems, Chapter 5 establishes the preservation of supermodularity in a class of optimization problems. This property and its extensions include several existing results in the literature as special cases, and provide powerful tools as we illustrate their applications to several operations problems: the stochastic two-product model with cross-price effects, the two-stage inventory control model, and the self-financing model.

Trajectory prediction uncertainty modelling for Air Traffic Management

The anticipated growth of air traffic worldwide requires enhanced Air Traffic Management (ATM) technologies and procedures to increase the system capacity, efficiency, and resilience, while reducing environmental impact and maintaining operational safety. To deal with these challenges, new automation and information exchange capabilities are being developed through different modernisation initiatives toward a new global operational concept called Trajectory Based Operations (TBO), in which aircraft trajectory information becomes the cornerstone of advanced ATM applications. This transformation will lead to higher levels of system complexity requiring enhanced Decision Support Tools (DST) to aid humans in the decision making processes. These will rely on accurate predicted aircraft trajectories, provided by advanced Trajectory Predictors (TP). The trajectory prediction process is subject to stochastic effects that introduce uncertainty into the predictions. Regardless of the assumptions that define the aircraft motion model underpinning the TP, deviations between predicted and actual trajectories are unavoidable. This thesis proposes an innovative method to characterise the uncertainty associated with a trajectory prediction based on the mathematical theory of Polynomial Chaos Expansions (PCE). Assuming univariate PCEs of the trajectory prediction inputs, the method describes how to generate multivariate PCEs of the prediction outputs that quantify their associated uncertainty. Arbitrary PCE (aPCE) was chosen because it allows a higher degree of flexibility to model input uncertainty. The obtained polynomial description can be used in subsequent prediction sensitivity analyses thanks to the relationship between polynomial coefficients and Sobol indices. The Sobol indices enable ranking the input parameters according to their influence on trajectory prediction uncertainty. The applicability of the aPCE-based uncertainty quantification detailed herein is analysed through a study case. This study case represents a typical aircraft trajectory prediction problem in ATM, in which uncertain parameters regarding aircraft performance, aircraft intent description, weather forecast, and initial conditions are considered simultaneously. Numerical results are compared to those obtained from a Monte Carlo simulation, demonstrating the advantages of the proposed method. The thesis includes two examples of DSTs (Demand and Capacity Balancing tool, and Arrival Manager) to illustrate the potential benefits of exploiting the proposed uncertainty quantification method.

A Performance Measurement System to Manage CEN Operations, Evolution and Innovation

Part 16: Performance Measurement Systems

A Performance Management Framework for Managing Sustainable Collaborative Enterprise Networks

Part 15: Performance Management Frameworks

Effects of dredging operations on sediment quality: contaminant mobilization in dredged sediments from the Port of Santos, SP, Brazil

Background, aim, and scope Contaminated sediments are a worldwide problem, and mobilization of contaminants is one of the most critical issues in environmental risk assessment insofar as dredging projects are concerned. The investigation of how toxic compounds are mobilized during dredging operations in the channel of the Port of Santos, Brazil, was conducted in an attempt to assess changes in the bioavailability and toxicity of these contaminants.Materials and methods Bulk sediment samples and their interstitial waters and elutriates were subjected to chemical evaluation and ecotoxicological assessment. Samples were collected from the channel before dredging, from the dredge's hopper, and from the disposal site and its surroundings.Results The results indicate that the bulk sediments from the dredging site are contaminated moderately with As, Pb, and Zn and severely with Hg, and that polycyclic aromatic hydrocarbon (PAH) concentrations are relatively high. Our results also show a 50% increase in PAH concentrations in suspended solids in the water collected from the hopper dredge. This finding is of great concern, since it refers to the dredge overflow water which is pumped back into the ecosystem. Acute toxicity tests on bulk sediment using the amphipod Tiburonella viscana showed no toxicity, while chronic tests with the sea urchin Lytechinus variegatus showed toxicity in the interstitial waters and elutriates. Results are compared with widely used sediment quality guidelines and with a sediment quality assessment scheme based on various lines of evidence.Conclusions The data presented here indicate that the sediments collected in this port show a certain degree of contamination, especially those from the inner part of the channel. The classification established in this study indicated that sediments from the dredged channel are impacted detrimentally and that sea disposal may disperse contaminants. According to this classification, the sediments are inappropriate for disposal at sea. It should be emphasized that the poor quality of fine sediments discharged from the hopper dredge in the overflow process can recontaminate the environment.Recommendations and perspectives These findings will help to underpin improved planning of management strategies for dredging operations and sediment disposal in Brazil and other countries.

Modelling and simulating retail management practices: a first approach

Multi-agent systems offer a new and exciting way of understanding the world of work. We apply agent-based modeling and simulation to investigate a set of problems in a retail context. Specifically, we are working to understand the relationship between people management practices on the shop-floor and retail performance. Despite the fact we are working within a relatively novel and complex domain, it is clear that using an agent-based approach offers great potential for improving organizational capabilities in the future. Our multi-disciplinary research team has worked closely with one of the UK’s top ten retailers to collect data and build an understanding of shop-floor operations and the key actors in a department (customers, staff, and managers). Based on this case study we have built and tested our first version of a retail branch agent-based simulation model where we have focused on how we can simulate the effects of people management practices on customer satisfaction and sales. In our experiments we have looked at employee development and cashier empowerment as two examples of shop floor management practices. In this paper we describe the underlying conceptual ideas and the features of our simulation model. We present a selection of experiments we have conducted in order to validate our simulation model and to show its potential for answering “what-if” questions in a retail context. We also introduce a novel performance measure which we have created to quantify customers’ satisfaction with service, based on their individual shopping experiences.

Virtual Enterprise Process Management: An Application to Industrial Maintenance

Part 2: Behaviour and Coordination

Improving Resource Management in Virtualized Data Centers using Application Performance Models

The rapid growth of virtualized data centers and cloud hosting services is making the management of physical resources such as CPU, memory, and I/O bandwidth in data center servers increasingly important. Server management now involves dealing with multiple dissimilar applications with varying Service-Level-Agreements (SLAs) and multiple resource dimensions. The multiplicity and diversity of resources and applications are rendering administrative tasks more complex and challenging. This thesis aimed to develop a framework and techniques that would help substantially reduce data center management complexity. We specifically addressed two crucial data center operations. First, we precisely estimated capacity requirements of client virtual machines (VMs) while renting server space in cloud environment. Second, we proposed a systematic process to efficiently allocate physical resources to hosted VMs in a data center. To realize these dual objectives, accurately capturing the effects of resource allocations on application performance is vital. The benefits of accurate application performance modeling are multifold. Cloud users can size their VMs appropriately and pay only for the resources that they need; service providers can also offer a new charging model based on the VMs performance instead of their configured sizes. As a result, clients will pay exactly for the performance they are actually experiencing; on the other hand, administrators will be able to maximize their total revenue by utilizing application performance models and SLAs. This thesis made the following contributions. First, we identified resource control parameters crucial for distributing physical resources and characterizing contention for virtualized applications in a shared hosting environment. Second, we explored several modeling techniques and confirmed the suitability of two machine learning tools, Artificial Neural Network and Support Vector Machine, to accurately model the performance of virtualized applications. Moreover, we suggested and evaluated modeling optimizations necessary to improve prediction accuracy when using these modeling tools. Third, we presented an approach to optimal VM sizing by employing the performance models we created. Finally, we proposed a revenue-driven resource allocation algorithm which maximizes the SLA-generated revenue for a data center.