CoPs-Centered Knowledge Management

Rajiv Khosla is an Associate Professor at School of Business, La Trobe University. He is the director of externally funded Business Intelligence Institute-Business Systems and Knowledge Modelling research laboratory. Rajiv has a multi-disciplinary background in management, engineering and computer science. He has published over 120 refereed journal and conference papers. He has also authored four books (research monographs) in the area of Emotional Intelligence, Human-Centred e-Business, Multimedia based Socio-technical Information systems, Intelligent Hybrid Multi-agent Systems. Rajiv is the Associate editor of the International Journal of Pattern Recognition, Regional editor of Journal of Intelligent Manufacturing (Springer-verlag), and Action Editor of Journal of Cognitive Systems Research. He has been a project leader of over a dozen industry projects and has commercialised four IT products in Australia. Associate Professor Rajiv Khosla Business Intelligence Institute and Business Systems Knowledge Modeling Laboratory (http://www.latrobe.edu.au/bskm) School of Business, La Trobe University, Melbourne, Victoria – 3086, Australia E-Mail: [email protected] of the primary reasons identified for the failure of existing knowledge management solutions has been that knowledge management tools and research have primarily been designed around technology push-models as against strategy pull-models. In an era where organizations are undergoing rapid and discontinuous change it is imperative that knowledge management systems and organizational entities like CoPs that facilitate knowledge management and organizational transformation are more closely aligned with business strategies and goals of an organization. This would enable organizations to respond more quickly to changing business environments and corresponding change in their knowledge management needs from time to time. This seminar presents a strategy-pull approach for Modeling and Design of CoPs-centered Knowledge Management Systems to facilitate organizational transformation. Among other aspects the seminar will focus on definition of dimensions and criteria for defining CoPs in an organization, application of fuzzy integral techniques to rank 16 criteria employed by CoPs to engage in knowledge management. From a knowledge management and organizational transformation perspective this approach will enable a more direct relationship between business strategy, CoPs and Knowledge Management solutions.published_or_final_versionCentre for Information Technology in Education, University of Hong Kon

Development and integration of environmental evaluation tools for the ecodesign of sustainable processes and products

Industry is recognized as one of the main sources of environmental pollution and resource depletion, both causing environmental degradation; nonetheless, its contribution to development and wealth creation is also acknowledged. Therefore, the identification of sustainable options in this area is a key factor. Nowadays, the attitude towards pollution prevention and control and cleaner production is not just a response to emerging environmental laws and regulations (Registration, Evaluation, Authorization and Restriction of Chemicals -REACH-, Integrated Pollution Prevention and Control –IPPC- Law, Integrated Product Policy –IPP-), but also a matter of corporate responsibility. Further, it has proved to be a way to increase profits. The sustainability definition has received certain criticism for its vagueness, ambiguity and difficulty to translate this concept at different levels. To overcome the difficulties of its implementation, a wide variety of indicators have been developed and applied over the years, providing metrics essential at the action level. This thesis poses a contribution to the development of environmental evaluation tools adapted to particular production sectors, aiming at providing metrics to guide decision making for the ecodesign of sustainable processes and products. Integrative frameworks that combine methodologies of different nature were proposed as the most suitable way to achieve comprehensive evaluations. At the same time, the simplicity of tools was pursued to make its application easier and more attractive for enterprises, avoiding the need of in depth training

Spatial multicriteria analysis for sustainability assessment : a new model for decision making

Policy makers have to consider the sustainability perspective in strategic planning decisions. Identifyand measure the level of sustainability, through its three dimensions, is a priority. Therefore, the aim of this work is to present a new model, called GeoUmbriaSUIT, integrating Multicriteria Analysis and Geographic Information Systems, specifically developed for helping Decision Makers to take policy decisions about sustainability in planning. The model provides outputs which are easy to be understood by not experts; the evaluation path is traceable and transparent, thanks to back analysis. To better explain the potentiality of GeoUmbriaSUIT and its functioning, a case study about Malta is described. Our results showed that in four regions of Malta the best dimension was the environmental one, while only for two regions (Northern Harbour and Southern Harbour) respectively the economic and social dimensions obtained the best scores. The integration of MCDA-GIS resulted to be a useful tool for sustainability assessment.peer-reviewe

An entrepreneurship model for assessing the investment attractiveness of regions

Аналіз результатів моделювання показав, що занадто багато показників усувають розбіжності в рівнях підприємницької моделі інвестиційної привабливості регіонів, тому при проведенні аналітичної роботи доцільно деталізувати напрям інвестицій. Отже, якщо врахувати рівень інвестиційної привабливості регіонів за факторами, ми можемо визначити чітких лідерів. Доведено, що при оцінці інвестиційної привабливості територіальних одиниць необхідно враховувати фактор "Захищеність інвестиційної діяльності" (криміногенний, екологічний, політичний). До останніх двох факторів слід віднести такі показники, як туристичний потенціал та національна самосвідомість населення регіону, які можна виразити в лінгвістичній формі та дослідити за допомогою нечіткої логічної апаратури.Analysis of the simulation results showed that too many indicators eliminate differences in an levels of entrepreneurship model the investment attractiveness of the regions, therefore, when conducting analytical work, it is advisable to detail the direction of investment. So, if we consider the level of investment attractiveness of the regions by factors, we can identify clear leaders. It is proved that in assessment the investment attractiveness of territorial units, it is necessary to take into account the factor "Security of investment activity" (criminogenic, environmental, political). The last two factors should be attributed to such indicators as tourism potential and national self-awareness of the population of the region, which can be expressed in linguistic form and investigated using fuzzy logic apparatus

Decision Support System Determination of Main Work Unit In WPP-711 Using Fuzzy TOPSIS

Decision-making to determine the working units for being prioritized to be developed in order to improve fishery monitoring in WPP-711 is imperative. The Ministry of Maritime Affairs and Fisheries should make no mismatch decision-making through long-term calculation and analysis. The problem of determining the priority of working units is a complex problem, thus it is required to find an appropriate method to avoid a missmatch decision. TOPSIS is a decision-making method capable of solving multi-criteria problems. TOPSIS working principle determines the alternative by considering the shortest distance from the positive ideal alternative and furthest from the ideal negative solution. To improve the performance of TOPSIS, this research is integrated with Fuzzy logic with the aim of giving the right numeric value preference. From the test of 11 alternatives of 6 criteria, the priority of development of fishery monitoring in FMA 711 is: Pontianak Working Unit= 0.917, Batam Working Unit = 0.791 Natuna Working Unit = 0.685 and Tanjung Pinang Working Unit = 0.607. Furthermore,  the ranking result will be used as the basis for determining the strategy in increasing the monitoring of WPP-711 to minimize State losses due to the illegal fishing within Indonesia’s WPP-711 Regions

Geoinformatic methodologies and quantitative tools for detecting hotspots and for multicriteria ranking and prioritization: application on biodiversity monitoring and conservation

Chi ha la responsabilità di gestire un’area protetta non solo deve essere consapevole dei problemi ambientali dell’area ma dovrebbe anche avere a disposizione dati aggiornati e appropriati strumenti metodologici per esaminare accuratamente ogni singolo problema. In effetti, il decisore ambientale deve organizzare in anticipo le fasi necessarie a fronteggiare le prevedibili variazioni che subirà la pressione antropica sulle aree protette. L’obiettivo principale della Tesi è di natura metodologica e riguarda il confronto tra differenti metodi statistici multivariati utili per l’individuazione di punti critici nello spazio e per l’ordinamento degli “oggetti ambientali” di studio e quindi per l’individuazione delle priorità di intervento ambientale. L’obiettivo ambientale generale è la conservazione del patrimonio di biodiversità. L’individuazione, tramite strumenti statistici multivariati, degli habitat aventi priorità ecologica è solamente il primo fondamentale passo per raggiungere tale obiettivo. L’informazione ecologica, integrata nel contesto antropico, è un successivo essenziale passo per effettuare valutazioni ambientali e per pianificare correttamente le azioni volte alla conservazione. Un’ampia serie di dati ed informazioni è stata necessaria per raggiungere questi obiettivi di gestione ambientale. I dati ecologici sono forniti dal Ministero dell’Ambiente Italiano e provengono al Progetto “Carta della Natura” del Paese. I dati demografici sono invece forniti dall’Istituto Italiano di Statistica (ISTAT). I dati si riferiscono a due aree geografiche italiane: la Val Baganza (Parma) e l’Oltrepò Pavese e Appennino Ligure-Emiliano. L’analisi è stata condotta a due differenti livelli spaziali: ecologico-naturalistico (l’habitat) e amministrativo (il Comune). Corrispondentemente, i risultati più significativi ottenuti sono: 1. Livello habitat: il confronto tra due metodi di ordinamento e determinazione delle priorità, il metodo del Vettore Ideale e quello della Preminenza, tramite l’utilizzo di importanti metriche ecologiche come il Valore Ecologico (E.V.) e la Sensibilità Ecologica (E.S.), fornisce dei risultati non direttamente comparabili. Il Vettore Ideale, non essendo un procedimento basato sulla ranghizzazione dei valori originali, sembra essere preferibile nel caso di paesaggi molto eterogenei in senso spaziale. Invece, il metodo della Preminenza probabilmente è da preferire in paesaggi ecologici aventi un basso grado di eterogeneità intesa nel senso di differenze non troppo grandi nel E.V. ed E.S. degli habitat. 2. Livello comunale: Al fine di prendere delle decisioni gestionali ed essendo gli habitat solo delle suddivisioni naturalistiche di un dato territorio, è necessario spostare l’attenzione sulle corrispondenti unità amministrative territoriali (i Comuni). Da questo punto di vista, l’introduzione della demografia risulta essere un elemento centrale oltre che di novità nelle analisi ecologico-ambientali. In effetti, l’analisi demografica rende il risultato di cui al punto 1 molto più realistico introducendo altre dimensioni (la pressione antropica attuale e le sue tendenze) che permettono l’individuazione di aree ecologicamente fragili. Inoltre, tale approccio individua chiaramente le responsabilità ambientali di ogni singolo ente territoriale nei riguardi della difesa della biodiversità. In effetti un ordinamento dei Comuni sulla base delle caratteristiche ambientali e demografiche, chiarisce le responsabilità gestionali di ognuno di essi. Un’applicazione concreta di questa necessaria quanto utile integrazione di dati ecologici e demografici viene discussa progettando una Rete Ecologica (E.N.). La Rete cosi ottenuta infatti presenta come elemento di novità il fatto di non essere “statica” bensì “dinamica” nel senso che la sua pianificazione tiene in considerazione il trend di pressione antropica al fine di individuare i probabili punti di futura fragilità e quindi di più critica gestione.Who has the responsibility to manage a conservation zone, not only must be aware of environmental problems but should have at his disposal updated databases and appropriate methodological instruments to examine carefully each individual case. In effect he has to arrange, in advance, the necessary steps to withstand the foreseeable variations in the trends of human pressure on conservation zones. The essential objective of this Thesis is methodological that is to compare different multivariate statistical methods useful for environmental hotspot detection and for environmental prioritization and ranking. The general environmental goal is the conservation of the biodiversity patrimony. The individuation, through multidimensional statistical tools, of habitats having top ecological priority, is only the first basic step to accomplish this aim. Ecological information integrated in the human context is an essential further step to make environmental evaluations and to plan correct conservation actions. A wide series of data and information has been necessary to accomplish environmental management tasks. Ecological data are provided by the Italian Ministry of the Environment and they refer to the Map of Italian Nature Project database. The demographic data derives from the Italian Institute of Statistics (ISTAT). The data utilized regards two Italian areas: Baganza Valley and Oltrepò Pavese and Ligurian-Emilian Apennine. The analysis has been carried out at two different spatial/scale levels: ecological-naturalistic (habitat level) and administrative (Commune level). Correspondingly, the main obtained results are: 1. Habitat level: comparing two ranking and prioritization methods, Ideal Vector and Salience, through important ecological metrics like Ecological Value (E.V.) and Ecological Sensitivity (E.S.), gives results not directly comparable. Being not based on a ranking process, Ideal Vector method seems to be used preferentially in landscapes characterized by high spatial heterogeneity. On the contrary, Salience method is probably to be preferred in ecological landscapes characterized by a low degree of heterogeneity in terms of not large differences concerning habitat E.V. and E.S.. 2. Commune level: Being habitat only a naturalistic partition of a given territory, it is necessary, for management decisions, to move towards the corresponding administrative units (Communes). From this point of view, the introduction of demography is an essential element of novelty in environmental analysis. In effect, demographic analysis makes the goal at point 1 more realistic introducing other dimensions (actual human pressure and its trend) which allows the individuation of environmentally fragile areas. Furthermore this approach individuates clearly the environmental responsibility of each administrative body for what concerns the biodiversity conservation. In effect communes’ ranking, according to environmental/demographic features, clarify the responsibilities of each administrative body. A concrete application of this necessary and useful integration of ecological and demographic data has been developed in designing an Ecological Network (E.N.).The obtained E.N. has the novelty to be not “static” but “dynamic” that is the network planning take into account the demographic pressure trends in the individuation of the probable future fragile points

Optimizing an Adaptive Neuro-Fuzzy Inference System for Spatial Prediction of Landslide Susceptibility Using Four State-of-the-art Metaheuristic Techniques.

Four state-of-the-art metaheuristic algorithms including the genetic algorithm (GA), particle swarm optimization (PSO), differential evolutionary (DE), and ant colony optimization (ACO) are applied to an adaptive neuro-fuzzy inference system (ANFIS) for spatial prediction of landslide susceptibility in Qazvin Province (Iran). To this end, the landslide inventory map, composed of 199 identified landslides, is divided into training and testing landslides with a 70:30 ratio. To create the spatial database, thirteen landslide conditioning factors are considered within the geographic information system (GIS). Notably, the spatial interaction between the landslides and mentioned conditioning factors is analyzed by means of frequency ratio (FR) theory. After the optimization process, it was shown that the DE-based model reaches the best response more quickly than other ensembles. The landslide susceptibility maps were developed, and the accuracy of the models was evaluated by a ranking system, based on the calculated area under the receiving operating characteristic curve (AUROC), mean absolute error, and mean square error (MSE) accuracy indices. According to the results, the GA-ANFIS with a total ranking score (TRS) = 24 presented the most accurate prediction, followed by PSO-ANFIS (TRS = 17), DE-ANFIS (TRS = 13), and ACO-ANFIS (TRS = 6). Due to the excellent results of this research, the developed landslide susceptibility maps can be applied for future planning and decision making of the related area

Sustainable cycle-tourism for society: Integrating multi-criteria decision-making and land use approaches for route selection

Cycle tourism is a sustainable active vacation, which is quickly growing in recent years. Although it has several benefits for society and users (e.g., social connections, amusement, and physical and mental health), cycle tourism requires an adequate route network to enjoy destinations with historical and landscape peculiarities. Past literature mainly investigated motivations and preferences for cycle tourists and proposed optimisation methods in planning routes. However, applying assessment methods for prioritising cycle-tourist routes is a seldom-explored topic. This study aims to address this gap by applying an integrated method for evaluating and prioritising cycle routes, searching for a compromise between route characteristics, service provided to users, and natural and building contexts crossed. It jointly includes Multi-Criteria Decision Methods (MCDMs) and a land use approach: AHP determines the weights of criteria and parameters describing cycle routes; GIS elaborates spatial analysis of parameters; ELECTRE I and VIKOR help find a compromise solution amongst different cycle routes. The integrated method involved a panel of experts to collect data, and it is applied to the wide-study area of Franciacorta (Italy). Some comparisons with other MCDMs are made to justify the results. The findings could support multi-institutions prioritising cycle route alternatives in deciding their building