Application of a Blockchain Enabled Model in Disaster Aids Supply Network Resilience

The disaster area is a dynamic environment. The bottleneck in distributing the supplies may be from the damaged infrastructure or the unavailability of accurate information about the required amounts. The success of the disaster response network is based on collaboration, coordination, sovereignty, and equality in relief distribution. Therefore, a reliable dynamic communication system is required to facilitate the interactions, enhance the knowledge for the relief operation, prioritize, and coordinate the goods distribution. One of the promising innovative technologies is blockchain technology which enables transparent, secure, and real-time information exchange and automation through smart contracts. This study analyzes the application of blockchain technology on disaster management resilience. The influences of this most promising application on the disaster aid supply network resilience combined with the Internet of Things (IoT) and Dynamic Voltage Frequency Scaling (DVFS) algorithm are explored employing a network-based simulation. The theoretical analysis reveals an advancement in disaster-aids supply network strategies using smart contracts for collaborations. The simulation study indicates an enhance in resilience by improvement in collaboration and communication due to more time-efficient processing for disaster supply management. From the investigations, insights have been derived for researchers in the field and the managers interested in practical implementation

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

Education for All? Complex solutions to complex problems in the Nigerian education sector

As Nigeria has grown to be the biggest economy on the continent, it has also earned the unfortunate distinction of having the highest number of out of school children in the world. Population growth disproportionate to investments in the education sector have stretched out resources to the detriment of quality. In the North, the majority of pupils are functionally illiterate. This is further compounded by a security (and humanitarian) crisis with girls in particular facing daunting odds. While the South has slightly better learning outcomes, there has been a steady decline in performance across the board. Unstable enrolment rates, high poverty levels, growing gender disparity and poor teaching quality have meant that even committed states face severe challenges in their efforts to improve the education system. Nonetheless, limited resources are still directed towards closing the education deficit. One of the notable efforts is the Education Sector Support Programme in Nigeria (ESSPIN). Using ESSPIN as a case-study, this thesis explores the potential of a new approach to development planning and implementation in the education sector; a complex adaptive systems approach. Structured in two parts, the research first makes the case for viewing the education sector as a complex system, and then moves out of the theoretical domain into development practice (a modelling exercise). Two of the most populated states (Kaduna and Lagos), representing the North and South are selected for analysis. To understand the dynamics of change processes, the research adopts investigative techniques (observations, interviews and interactive surveys) to collect primary data first-hand, and then simulates the social system using technical instruments (computing platforms and coding libraries). With secondary data from state records and projects reports, these elements come together in the development of one model architecture – the School Improvement Programme Model (SIPM). This research is a critical analysis of simulating social systems. It aims to shed light on the insights that can be gained from complex systems thinking, as well as its limitations. Results from the SIPM indicate that this approach can be utilised to recreate historical states within an acceptable range of accuracy. Thus, there is some potential for the SIPM as a tool to reasonably anticipate how changing conditions might affect the impact ESSPIN in the future. This research also provides a frank discussion on the challenges of this approach – the difficulty of ascertaining the precise effect of each element, over-elaborated processes, the degree to which assumptions about the system are inevitable, and the potential implications of any one of these considerations on the model. Overall, this approach demonstrates the multiple ways elements are connected in the education system. As with the famous metaphor of the butterfly effect, the SIPM operates under the same principles that allow small changes to produce a chain of events with large scale differences in a system. Processes of development (indeed change) are shown to be non-linear, and this thesis argues for a higher level of flexibility, while unpacking the problem of “measuring” project outcomes. By weaving together theory and practice, this research aims to contribute to development planning in Nigeria, and more generally to the design (and application) of models in an often “messy” and complex development space

Real-time foresight : preparedness for dynamic innovation networks

Collaborative innovation processes in unpredictable environments are a challenge for traditional management. But new demands in a global digital society push public and corporate leadership to collaborate ad hoc, without predictable goals and planned working rules. In this study, an actor-network approach (ANT) is combined with critical incident technique (CIT) to elaborate dynamic network principles for a new real-time foresight (RTF). Real-time foresight replaces traditional planning and strategic management in ad hoc multi-sector collaborations. Although ANT originates from science and technologies studies, it is here applied to a management problem due to ist ability to merge voluntaristic and evolutionary managerial components and micro- and macro perspectives. The investigation is placed in an exemplary management field of high dynamics: global disaster management. From process analysis and from comparison of three dynamic innovation networks that emerged around Indian coastal villages after Tsunami 2004, five dynamic network patterns are obtained which underly successful collaborative innovation processes. These dynamic structures build the agenda for a new real-time foresight, and for an instrument to evaluate in real-time the emergence of dynamic innovation networks (DINs).  Hella Langer StiftungAlgorithms and the Foundations of Software technolog

Australian water security and Asian food security: complexity and macroeconomics of sustainability

The thesis focuses on the macroeconomics of sustainable development and the extension to energy, water and food security, using a system dynamics approach, i.e. the methods of differential equations systems with initial values. The work is divided into three related parts that build a narrative concerning the interaction between economics, policy, natural resources and society. First, after reviewing the concepts of complexity in environmental security, a simple system comprising three coupled differential equations is used to explain the effects of macroeconomic business cycles on the exploitation of ecological resources, and from this is inferred an implied importance of averting business cycles. The concept of entropy production is used to represent the exploitation of ecological resources. The second part establishes a system methodology inspired by Post Keynesian economics to develop the Murray-Darling Basin Economy Simulation Model that links food production/water users and food consumers at the micro scale, to the macroeconomic system dynamics. The goal of this study is to integrate and analyze the ecological-economic system in the Murray-Darling basin. The concepts of entropy production, useful work and income distribution are used as a bridge between the micro and macro subsystems. The system parameters are estimated using an ecological-economic data set for the Murray-Darling basin and for Australia (where data of the Basin are unavailable) from 1978-2005, and the model is validated using data from 2006-2012. The results reveal important structural linkages between the two subsystems and are used to predict the consequences of business cycles and government intervention for the coordination of growth and sustainability. The third, and final, part presents the development of an ``Asian Food Security Risk Engine'' that predicts the threat of civil unrest from food insecurity in Asian developing countries. A basal characteristics index for each developing country in Asia is defined and evaluated. Based on these measures, and introducing the concept of flow of anger, we use a differential equation system to integrate the threat of food security, the trigger for food riots, and food policy. The system parameters are estimated using a data set tracking indexes for threat, trigger and policy for Asian developing countries from 2006-2008, and the model is validated using data from 2009-2012. The results show the possible alternative approaches to simulating threat severity from food insecurity and are used to predict the threat of social unrest due to food security for a given country one month ahead