Evaluation of team dynamic in Norwegian projects for IT students

The need for teaching realistic software development in project courses has increased in a global scale. It has always been challenges in cooperating fast-changing software technologies, development methodologies and teamwork. Moreover, such project courses need to be designed in the connection to existing theoretical courses. We performed a large-scale research on student performance in Software Engineering projects in Norwegian universities. This paper investigates four aspects of team dynamics, which are team reflection, leadership, decision making and task assignment in order to improve student learning. Data was collected from student projects in 4 years at two universities. We found that some leader's characteristics are perceived differently for female and male leaders, including the perception of leaders as skilful workers or visionaries. Leadership is still a challenging aspect to teach, and assigned leadership is probably not the best way to learn. Students is are performing well in task review, however, needs support while performing task assignment. The result also suggests that task management to be done in more fine-grained levels. It is also important to maintain an open and active discussion to facilitate effective group decision makings

Decision support for build-to-order supply chain management through multiobjective optimization

This is the post-print version of the final paper published in International Journal of Production Economics. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2010 Elsevier B.V.This paper aims to identify the gaps in decision-making support based on multiobjective optimization (MOO) for build-to-order supply chain management (BTO-SCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting MOO techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted. Future research directions to better exploit the decision support capabilities of MOO are proposed. These include: reformulation of the extant optimization models with a MOO perspective, development of decision supports for interfaces not involving manufacturers, development of scenarios around service-based objectives, development of efficient solution tools, considering the interests of each supply chain party as a separate objective to account for fair treatment of their requirements, and applying the existing methodologies on real-life data sets.Brunel Research Initiative and Enterprise Fund (BRIEF

Application of Computer Supported Multi–criteria Decision Models in Agriculture

Hierarchical multi criteria decision models (MCDM) are a general decision support methodology aimed at the classification or evaluation of options that occur in a decision-making processes. Decision models are typically developed through decomposition of complex decision problems into smaller and less complex sub-problems; the result of such decomposition is a hierarchical structure that consists of attributes and utility functions. Basic concepts of MCDM together with two multi criteria modeling methodologies (expert system DEX-i and analytical hierarchical process with application of Expert Choice decision support software) are presented and discussed. In order to show how the explained methods can be applied to agricultural decision problems, two applications of MCDM (DEX-i and AHP) for organic spelt processing planning problem are presented in detail

Towards the development of a simple tool to assist in agile methodology adoption decisions: agile adoption matrix

This paper describes the development of a decision support tool, an adoption assessment matrix based on critical adoption factors, that addresses a need in industry; namely, to improve the overall understanding of the constituent parts of agile systems development methodologies. It highlights the importance of critical adoption factors to the adoption of an agile method and illustrates the usefulness of a decision support process to determine the viability of an agile method for a specific software project. The paper describes the results of a series of workshops (two carried out in commercial software developement companies, and one with personnel from the British Minsitry of Defence) where the adoption assessment matrix was used to assess the suitability of agile methods in software development projects. A major benefit of the tool is that it guides discussion, concentrating the debate on the critical factors, applied to the individual project. These discussions proved to be as valuable as the output of the tool itself. The results of these workshops show that an argument can be made for the use of and benefit of such a decision support process in industry, in supporting the decision to adopt an agile methodology

Conceptual Framework for SDSS Development with an Application in the Retail Industry

Spatial information is becoming crucial for strategic decision making, but accessing and understanding this information is not easy. Dedicated tools can support the decision process in many ways, such as visualization interfaces or data analyses. Numerous Decision Support System (DSS) development methodologies exist along with dedicated Spatial Decision Support System (SDSS). Unfortunately, for multiple reasons, these tools andmethodologies are not easily adaptable for the development of another SDSS. This paper proposes a framework for the development of a flexible SDSS that is built on open source software, allowing for low cost implementation. To support the efficiency of our approach, the design of a specific SDSS that is currently in use will be presented. This SDSS was developed for a company that distributes products through various retail networks. The multiple capabilities of the resulting SDSS will be revealed through an explanation of the different development steps. The complete framework is applied to a real data set that will be detailed in a demonstration

An Integrated Decision Support Toolbox (DST) for the Management of Mountain Protected Areas

New tools and methodologies are required in systemic planning and management of mountain protected areas. Among others we propose here a decision support toolbox (DST) conceived as an integrated collection of both soft and hard system methodologies, consisting of participatory and computer-based modules to provide a set of integrated, self-contained tools and approaches to support decision-making processes in the management of mountain protected areas. The Sagarmatha National Park and Buffer Zone (SNPBZ) in Nepal was taken as a pilot case. A number of participatory exercises such as participatory 3-dimensional modeling, scenario planning, and qualitative modeling were carried out to understand social-ecological processes and generate a systemic view over space and time. The qualitative models were then converted into computer-based system dynamics models. The design and development of DST software were carried out with an incremental and modular approach. This process involved stakeholder analysis and decision-making processes through a series of consultations. The software was developed with the main modules including scenario analysis, spatial analysis, and knowledge base. The scenario analysis module runs system dynamics models built in Simile software and provides functions to link them with spatial data for model inputs and outputs. The spatial analysis module provides the basic geographic information system functions to explore, edit, analyze, and visualize spatial information. The knowledge base module was developed as a metadata management system for different categories of information such as spatial data, bibliography, research data, and models. The development of DST software, especially system dynamics modeling and its linkage with spatial components, provided an important methodological approach for spatial and temporal integration. Furthermore, training and interactions with park managers and concerned stakeholders showed that DST is a useful platform for integrating data and information and better understanding ecosystem behavior as a basis for management decisions

Integrated Modelling Frameworks for Environmental Assessment and Decision Support

As argued in Chapter 1, modern management of environmental resources defines problems from a holistic and integrated perspective, thereby imposing strong requirements on Environmental Decision Support Systems (EDSSs) and Integrated Assessment Tools (IATs). These systems and tools tend to be increasingly complex in terms of software architecture and computational power in order to cope with the type of problems they must solve. For instance, the discipline of Integrated Assessment (IA) needs tools that arc able to span a wide range of disciplines, from socio-economics to ecology to hydrology. Such tools must support a wide range of methodologies and techniques like agent-based modeling, Bayesian decision networks, optimization, multicriteria analyses and visualization tools, to name a few

Advances in Methodology and Applications of Decision Support Systems

These Proceedings are composed of a selection of papers of the Workshop on Advances in Methodology and Applications of Decision Support Systems, organized by the System and Decision Sciences (SDS) Program of IIASA and the Japan Institute of Systems Research (JISR). The workshop was held at IIASA on August 20-22, 1990. The Methodology of Decision Analysis (MDA) Project of the SDS Program focuses on a system-analytical approach to decision support and is devoted to developing methodology, software and applications of decision support systems concentrated primarily around interactive systems for data analysis, interpretation and multiobjective decisionmaking, including uncertainty analysis and group decision making situations in both their cooperative and noncooperative aspects. The objectives of the research on decision support systems (DSS) performed in cooperation with the MDA Project are to: compare various approaches to decision support systems; advance theory and methodology of decision support; convert existing theories and methodologies into usable (simple to use, user-friendly and robust) tools that could easily be used in solving real-life problems. A principal characteristic of decision support systems is that they must be tuned to specific decision situations, to complex real-life characteristics of every application. Even if the theory and methodology of decision support is quite advanced, every application might provide impulses for further theoretical and methodological advances. Therefore the principle underlying this project is that theoretical and methodological research should be strongly connected to the implementation and applications of its results to sufficiently complicated, real-life examples. This approach results in obtaining really applicable working tools for decision support. The papers for this Proceedings have been selected according to the above summarized framework of the research activities. Therefore, the papers deal both with theoretical and methodological problems and with real-life applications

On The Applicability of Data Envelopment Analysis for Multiple Attriliute Decision Making in the Context of Information Systems Appraisals

This article elaborates on the applicability of basic and extended data envelopment analysis (DEA) models for various information system (IS) decision use-cases including illustrative examples from an enterprise resource planning (ERP) software investment appraisal. The usage of data envelopment analysis models and their extensions for IS decisions remains limited. This omission seems critical in particular for two reasons. First, organizational studies have shown that in practice business management fails to appreciate the portfolio of investment appraisal techniques available. Second, DEA based methodologies, especially new extensions, promise valuable insights to support the complex IS decision problem. The results indicate DEA applicability in a number of use-cases, e.g. for structural analysis of system alternatives or validation of ranking outcomes