A problem-structuring model for analyzing transportation–environment relationships

This is the post-print version of the final paper published in European Journal of Operational Research. 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 @ 2009 Elsevier B.V.This study discusses a decision support framework that guides policy makers in their strategic transportation related decisions by using multi-methodology. For this purpose, a methodology for analyzing the effects of transportation policies on environment, society, economy, and energy is proposed. In the proposed methodology, a three-stage problem structuring model is developed. Initially, experts’ opinions are structured by using a cognitive map to determine the relationships between transportation and environmental concepts. Then a structural equation model (SEM) is constructed, based on the cognitive map, to quantify the relations among external transportation and environmental factors. Finally the results of the SEM model are used to evaluate the consequences of possible policies via scenario analysis. In this paper a pilot study that covers only one module of the whole framework, namely transportation–environment interaction module, is conducted to present the applicability and usefulness of the methodology. This pilot study also reveals the impacts of transportation policies on the environment. To achieve a sustainable transportation system, the extent of the relationships between transportation and the environment must be considered. The World Development Indicators developed by the World Bank are used for this purpose

Continuous Improvement Through Knowledge-Guided Analysis in Experience Feedback

Continuous improvement in industrial processes is increasingly a key element of competitiveness for industrial systems. The management of experience feedback in this framework is designed to build, analyze and facilitate the knowledge sharing among problem solving practitioners of an organization in order to improve processes and products achievement. During Problem Solving Processes, the intellectual investment of experts is often considerable and the opportunities for expert knowledge exploitation are numerous: decision making, problem solving under uncertainty, and expert configuration. In this paper, our contribution relates to the structuring of a cognitive experience feedback framework, which allows a flexible exploitation of expert knowledge during Problem Solving Processes and a reuse such collected experience. To that purpose, the proposed approach uses the general principles of root cause analysis for identifying the root causes of problems or events, the conceptual graphs formalism for the semantic conceptualization of the domain vocabulary and the Transferable Belief Model for the fusion of information from different sources. The underlying formal reasoning mechanisms (logic-based semantics) in conceptual graphs enable intelligent information retrieval for the effective exploitation of lessons learned from past projects. An example will illustrate the application of the proposed approach of experience feedback processes formalization in the transport industry sector

Information systems and healthcare XXIV: Factors affecting the EAI adoption in the healthcare sector

Recent developments in the field of integration technologies like Enterprise Application Integration (EAI) have emerged to support organizations towards improving the quality of services and reducing integration costs. Despite the importance of EAI, there is limited empirical research reported on its adoption in the healthcare sector. Khoumbati et al. [2006] developed a model for the evaluation of EAI in healthcare organizations. In doing so, the causal interrelationship of EAI adoption factors was identified by using fuzzy cognitive mapping. This paper is a progression of previous work in the area and seeks to contribute by validating the model through a different case environment. Thus, this paper contributes by deriving and proposing the MAESTRO model for EAI adoption. MAESTRO identifies a set of factors that influence EAI adoption and it is evaluated through a real-life case study. It provides an understanding of the EAI adoption process through its grounding on empirical data. In doing so, the MAESTRO model supports the management of healthcare organizations during the decision-making process for EAI adoption

Extending the IS-Impact model into the higher education sector

The study addresses known limitations of what may be the most important dependent variable in Information Systems (IS) research; IS-Success or IS-Impact. The study is expected to force a deeper understanding of the broad notions of IS success and impact. The aims of the research are to: (1) enhance the robustness and minimize limitations of the IS-Impact model, and (2) introduce and operationalise a more rigorously validated IS Impact measurement model to Universities, as a reliable model for evaluating different Administrative Systems. In extending and further generalizing the IS-Impact model, the study will address contemporary validation issues

Mapping domain characteristics influencing Analytics initiatives: The example of Supply Chain Analytics

Purpose: Analytics research is increasingly divided by the domains Analytics is applied to. Literature offers little understanding whether aspects such as success factors, barriers and management of Analytics must be investigated domain-specific, while the execution of Analytics initiatives is similar across domains and similar issues occur. This article investigates characteristics of the execution of Analytics initiatives that are distinct in domains and can guide future research collaboration and focus. The research was conducted on the example of Logistics and Supply Chain Management and the respective domain-specific Analytics subfield of Supply Chain Analytics. The field of Logistics and Supply Chain Management has been recognized as early adopter of Analytics but has retracted to a midfield position comparing different domains. Design/methodology/approach: This research uses Grounded Theory based on 12 semi-structured Interviews creating a map of domain characteristics based of the paradigm scheme of Strauss and Corbin. Findings: A total of 34 characteristics of Analytics initiatives that distinguish domains in the execution of initiatives were identified, which are mapped and explained. As a blueprint for further research, the domain-specifics of Logistics and Supply Chain Management are presented and discussed. Originality/value: The results of this research stimulates cross domain research on Analytics issues and prompt research on the identified characteristics with broader understanding of the impact on Analytics initiatives. The also describe the status-quo of Analytics. Further, results help managers control the environment of initiatives and design more successful initiatives.DFG, 414044773, Open Access Publizieren 2019 - 2020 / Technische Universität Berli

Dealing with propositional ambiguity in business process improvement

If it is true that people express their views about organisational issues in ambiguous terms then one needs to address this ambiguity instead of the ‘problems’ to find an appropriate methodological approach to resolving or dissolving problem situations in the organisation. This paper highlights and discusses those issues, which therefore relate to ambiguityin relation to decision making tasks within organisations, and the related Soft Systems Methodology / Systems Thinking school of thought, which traditionally constrains such ambiguities. A model of these issues is presented in terms of the Business Process Improvement (BPI) task to highlight these interdependencies

A scientometric analysis and review of fall from height research in construction

Fall from height (FFH) in the construction industry has earned much attention among researchers in recent years. The present review-based study introduced a science mapping approach to evaluate the FFH studies related to the construction industry. This study, through an extensive bibliometric and scientometric assessment, recognized the most active journals, keywords and the nations in the field of FFH studies since 2000. Analysis of the authors’ keywords revealed the emerging research topics in the FFH research community. Recent studies have been discovered to pay more attention to the application of Computer and Information Technology (CIT) tools, particularly building information modelling (BIM) in research related to FFH. Other emerging research areas in the domain of FFH include rule checking, and prevention through design. The findings summarized the mainstream research areas (e.g., safety management program), discussed existing research gaps in FFH domain (e.g., the adaptability of safety management system), and suggests future directions in FFH research. The recommended future directions could contribute to improving safety for the FFH research community by evaluating existing fall prevention programs in different contexts; integrating multiple CIT tools in the entire project lifecycle; designing fall safety courses to workers associated with temporary agents and prototype safety knowledge tool development. The current study was restricted to the FFH literature sample included the journal articles published only in English and in Scopus

Emerging Opportunities: Monitoring and Evaluation in a Tech-Enabled World

Various trends are impacting on the field of monitoring and evaluation in the area of international development. Resources have become ever more scarce while expectations for what development assistance should achieve are growing. The search for more efficient systems to measure impact is on. Country governments are also working to improve their own capacities for evaluation, and demand is rising from national and community-based organizations for meaningful participation in the evaluation process as well as for greater voice and more accountability from both aid and development agencies and government.These factors, in addition to greater competition for limited resources in the area of international development, are pushing donors, program participants and evaluators themselves to seek more rigorous – and at the same time flexible – systems to monitor and evaluate development and humanitarian interventions.However, many current approaches to M&E are unable to address the changing structure of development assistance and the increasingly complex environment in which it operates. Operational challenges (for example, limited time, insufficient resources and poor data quality) as well as methodological challenges that impact on the quality and timeliness of evaluation exercises have yet to be fully overcome

Towards a Holistic Approach to Designing Theory-based Mobile Health Interventions

Increasing evidence has shown that theory-based health behavior change interventions are more effective than non-theory-based ones. However, only a few segments of relevant studies were theory-based, especially the studies conducted by non-psychology researchers. On the other hand, many mobile health interventions, even those based on the behavioral theories, may still fail in the absence of a user-centered design process. The gap between behavioral theories and user-centered design increases the difficulty of designing and implementing mobile health interventions. To bridge this gap, we propose a holistic approach to designing theory-based mobile health interventions built on the existing theories and frameworks of three categories: (1) behavioral theories (e.g., the Social Cognitive Theory, the Theory of Planned Behavior, and the Health Action Process Approach), (2) the technological models and frameworks (e.g., the Behavior Change Techniques, the Persuasive System Design and Behavior Change Support System, and the Just-in-Time Adaptive Interventions), and (3) the user-centered systematic approaches (e.g., the CeHRes Roadmap, the Wendel's Approach, and the IDEAS Model). This holistic approach provides researchers a lens to see the whole picture for developing mobile health interventions