Application of context knowledge in supporting conceptual design decision making

Conceptual design is the most important phase of the product life cycle as the decisions taken at conceptual design stage affect the downstream phases (manufacture, assembly, use, maintenance, and disposal) in terms of cost, quality and function performed by the product. This research takes a holistic view by incorporating the knowledge related to the whole context (from the viewpoint of product, user, product's life cycle and environment in which the product operates) of a design problem for the consideration of the designer to make an informed decision making at the conceptual design stage. The design context knowledge comprising knowledge from these different viewpoints is formalised and a new model and corresponding computational framework is proposed to support conceptual design decision making using this formalised context knowledge. Using a case study, this paper shows the proof of the concept by selecting one concept among different design alternatives using design context knowledge thereby proactively supporting conceptual design decision making for an informed and effective decision making

A Conceptual Model of Client-driven Agile Requirements Prioritization: Results of a Case Study

ABSTRACT Requirements (re)prioritization is an essential mechanism of agile development approaches to maximize the value for the clients and to accommodate changing requirements. Yet, in the agile Requirements Engineering (RE) literature, very little is known about how agile (re)prioritization happens in practice. Conceptual models about this process are missing, which, in turn, makes it difficult for both practitioners and researchers to reason about requirements decision-making at inter-iteration time. We did a multiple case study on agile requirements prioritization methods to yield a conceptual model for understanding the inter-iteration prioritization process. The model is derived by using interview data from practitioners in 8 development organizations. Such a model makes explicit the concepts that are used tacitly in the agile requirements prioritization practice and can be used for structuring future empirical investigations about this topic, and for analyzing, supporting, and improving the process in real-life projects

Disruptive Business Model Innovation and Digital Transformation

Background: Innovating how organisations run their business is a strategic decision to create more value for customers using or consuming the product and/or service provided. In addition to the incentive of everybody embracing digital transformation, digital technologies, and digital innovation, which frame changes of operating business models today, disruptions, i.e., another incentive that occurs suddenly and impacts globally, all force businesses to adapt and change. Objectives: This research aims to provide a conceptual model that can be used for organisations to evaluate and propose feasible options for responding to disruptions that influence the businesses’ strategic innovation initiatives while assisting decision-makers in choosing the most appropriate option. Methods/Approach: Considering internal and external factors that influence digital transformation, the conceptual framework is designed to assess readiness and willingness to transform and create opportunities for future success digitally. Results: A conceptual framework was developed, tested, and demonstrated in a case study. The case study organisation rated positively the composition of steps to be perf readiness and willingness and choose the most feasible option to change. Conclusions: The digital environment and the influence of disruptions force organisations to change. The conceptual framework developed in this research helps the management choose the most feasible change option about the real as-is and the desired to-be state

Examining the strategy development process through the lens of complex adaptive systems theory

The development of strategy remains a debate for academics and a concern for practitioners. Published research has focused on producing models for strategy development and on studying how strategy is developed in organisations. The Operational Research literature has highlighted the importance of considering complexity within strategic decision making; but little has been done to link strategy development with complexity theories, despite organisations and organisational environments becoming increasingly more complex. We review the dominant streams of strategy development and complexity theories. Our theoretical investigation results in the first conceptual framework which links an established Strategic Operational Research model, the Strategy Development Process model, with complexity via Complex Adaptive Systems theory. We present preliminary findings from the use of this conceptual framework applied to a longitudinal, in-depth case study, to demonstrate the advantages of using this integrated conceptual model. Our research shows that the conceptual model proposed provides rich data and allows for a more holistic examination of the strategy development process. © 2012 Operational Research Society Ltd. All rights reserved

A conceptual spatio-temporal multidimensional model

Today, thanks to global positioning systems technologies and mobile devices equipped with tracking sensors, and a lot of data about moving objects can be collected, e.g., spatio-temporal data related to the movement followed by objects. On the other hand, data warehouses, usually modeled using a multidimensional view of data, are specialized databases to support the decision-making process. Unfortunately, conventional data warehouses are mainly oriented to manage alphanumeric data. In this article, we incorporate temporal elements to a conceptual spatial multidimensional model resulting in a spatio-temporal multidimensional model. We illustrate our proposal with a case study related to animal migration

A Sensitivity Analysis Framework for Health Economic Evaluation in Middle Income Countries: Appropriately Incorporating a Comprehensive Approach

When constructing a health economic decision model, it is critical to select a sensitivity analysis approach appropriate for the decision context. This point is particularly salient to Middle-Income Countries (MICs), where there is relatively heightened resource scarcity and increased opportunity-cost. MICs face acute shortages of accessible as well as highquality evidence, resulting in a frequent imputing of data from external jurisdictions. Conversely, there are also shortages in skills and research capacity, creating a strong complementary need to consider the contextual feasibility of applying more resource demanding sensitivity analysis methodologies. Given the above, it is therefore critical to establish whether and when the technical benefits of complex and resource demanding methods result in real-world value. We apply a comparative case study using a comprehensive approach to decision-modelling, implemented in the R and JAGS languages. Specifically, the case study replicates a deterministic model originally used to inform the cost-effectiveness of adding a bivalent Human Papilloma Virus (HPV) vaccine to South Africa's public health care cervical cancer screening programme. Crucially, the case study provides critical insight into the pros and cons of implementing more complex sensitivity analysis techniques within MIC climates. Our findings indicate that the benefits of more advanced sensitivity analysis methods are nuanced; are therefore contextually beneficial according to a case-by-case basis; and, moreover, choosing a sensitivity analysis method should be guided by a conceptual ‘fruitfulness' (i.e. a bang-for-buck), more than a mere desire to reduce model complexity. To aid analysts in this process, from our comparative case study we provide a framework with three core concept areas namely Decision-Maker Preferences (Decision Power, Investment, Risk Aversion), Analytical Considerations (Available resources, Indirect Evidence) and Policy Context (Knowledge of Topic, Technical Expertise). The framework intends to encourage more judicious selection of sensitivity analysis methods; help reduce the methodological variation apparent in MIC settings; and simultaneously provide decision-makers with greater methodological transparency in the selection of sensitivity analysis methods

Assessing the leanness of a supply chain using multi-grade fuzzy logic: a health-care case study

Purpose Numerous and diverse organizations have implemented lean principles and practices, which concentrate on improving the efficiency of business processes by reducing cost, waste, consumptions and effort. However, previous assessments have not focused on the leanness of the supply chain in a health-care setting. This paper aims to introduce a method for assessing the successful implementation of lean principles and tools in a supply chain. Furthermore, this paper validates the method in a health-care organization. Design/methodology/approach This paper starts with an extensive literature review on assessing leanness and using multi-grade fuzzy logic. Then, a conceptual model was developed to measure leanness. The conceptual model was validated by discussing the initial version with select academic experts, especially those who deal with leanness in health-care organizations. After responding to the experts’ valuable comments, the health-care organization that is the focus of this case study was chosen based on two criteria. The first criterion was the organization’s ability to participate in the study, and the second was the organization’s commitment to implementing lean principles. These criteria were important to ensure the organization had the necessary foundation for implementing change initiatives such as lean process improvements. Next, a multi-grade (multi-attributes) fuzzy logic was used for leanness measurement. A leanness index was calculated, and the results were validated using experts from the case study organization. Finally, the weaker areas of the organization’s processes were identified to point the way for further improvements. Findings The assessment indicated that the case study organization is not lean. The organization’s weaker attributes were identified, and improvements have been suggested. Research limitations/implications This study focused on a single health-care organization, which was selected from a limited pool of potential organizations, namely, organizations which are accredited by both the Saudi Central Board for Accreditation of Healthcare Institutions and the Joint Commission International. The scope of future research should be extended to multi-case studies to enhance the findings presented in this paper. This paper’s findings can be used to help decision-makers at health-care providers to implement lean thinking in supply chain processes. Practical implications This research may be interest to practicing supply chain managers, as it proposes what enablers, factors and attributes should be emphasized in lean implementation. The proposed model can work as an assessment tool to identify the gap between the present level of leanness and the desired leanness state so the health-care organization can identify what can be improved. This model enables decision-makers in hospital supply chain to take suitable actions for improving lean implementation level. Originality/value This study makes an original contribution to the body of research concerning lean principles; the study developed a conceptual model for leanness assessment that can be applied to the supply chain of health-care organizations. Indeed, the conceptual model is likely to be useful for assessing leanness outside of the health-care field, which suggests avenues for future research

The Use of Human Behaviour in Fire to Inform Canadian Wildland Urban Interface Evacuations

Wildland urban interface (WUI) communities are generally the most at risk of being impacted by wildfires. In order to assess the vulnerability of these communities, it is important to understand the impact that human behaviour in fire (HBiF) can have on wildfire evacuations, specifically in Canada where such data is lacking. To lay the groundwork for a comprehensive vulnerability assessment of a Canadian case study community, a conceptual model of protective action decision-making during WUI fires was created. This was used to develop a survey to understand the WUI fire awareness and experience as well as the anticipated protective actions of the case study community residents. The microsimulation software PTV VISSIM was used to model 10 evacuation scenarios to identify key evacuation modelling considerations and potential evacuation challenges faced by the community. In doing so, a framework for using HBiF to inform WUI vulnerability assessments and evacuations was developed