Narrow Results

For all of the many advantages and enormous benefits that information technology has brought to us, it has subjected to increasing risks that need enough attention. Bayesian network (BN) is an important probabilistic inference approach to support reasoning under uncertainty. This paper describes how BN is applied to quantify the occurrence probability of software process risk factors and the influence strength among the process risk factors in the context of Chinese trustworthy software. The information of 52 factors was obtained through a questionnaire survey of 93 project managers in five high Capability Maturity Model Integration (CMMI) level software companies. The focus of this paper is to present the key risk checklist and good timing for process risk control to improve software process risk management. Special effort has been put on the description of the experimental study, which provides the top 20 key risk factors in software process and critical software sub-processes for process risk management. The findings can provide the key risk checklist to software risk manager for risk identification and decision-making in process risk management. This is a general approach and, as such, it can be applied to a certain software project or some software enterprises with updated data.

Disruptive technology (DT) is an emerging technology whose arrival in the marketplace signifies the eventual displacement of the existing dominant technology. Identifying and assessing the risks associated with the various phases of a DT process is one of the key challenges a firm developing the technology might encounter. This paper identifies, classifies, and prioritizes a set of possible risks associated with different phases of a DT process. The paper presents ideas that differ from traditional risk assessment for new product development in that DT occurs at a different pace. These results can be used to develop a technology as well as a risk mitigation strategy.

Many large and highly complex engineering projects present enormous technical and financial risks to organizations. This is especially true in the defence industry where budgets can potentially run into billions and the project lifecycle may extend over many years. In frequent cases, such projects are too much for a single organization to undertake. One option that is becoming ubiquitous across contemporary defence projects is to spread the risk by forming an alliance between several organizations. Unfortunately, forming an alliance between potentially competing organizations brings its own set of challenges and risks. The operating conditions of the business environment are characterized by frequent changes in products, services, processes, organizations, markets, supply and distribution networks. The partners need to work together as an entity to achieve a goal but the relationships within the alliance are often disrupted by the established practices, culture and motivation of the individual companies. This paper starts by examining how risks can essentially multiply when an alliance is formed and what potential impacts these risks have on project success. A novel 3PE method for modeling the structure of an alliance with the three elements being product, people, process, and their interactions is proposed within an alliance environment. This methodology is then used to calculate the increase in interactions between the 3Ps with the introduction of more organizations to the alliance. By examining each of the elements and their interactions, risks are identified, and the key drivers are exposed. Finally, a case study is presented that illustrates how the architectural model can be used to estimate the probability of failure of the alliance.

A strategic capability of contemporary naval ships is the ability to launch and recover embarked aircraft such as helicopters in a maritime environment. Such operations are enormously challenging due to deck motion, limited landing space, visibility, ship’s superstructure, etc. This places extreme pressure on the pilot, ship’s crew and the platforms alike, making such shipboard operations the most dangerous of all helicopter flight missions. Therefore, the design and integration of equipment, systems and aids to ensure such operations are done as safely as is practicably possible presents ship builders, aircraft manufacturers, engineers and pilots with some extremely demanding and complex problems. Major naval ship design/build programmes that include an aviation capability will inevitably need to engage resources across multiple disciplines that include, but not limited to, engineering, design, logistics, administration, procurement, legal, alliance partners and the customer to manage project risks from the outset. This research highlights the need for a holistic/Systems Engineering approach that recognises risks across the wider ship programme, which can only be managed/resolved by cross-discipline collaboration. This paper presents a novel methodology to elicit risks qualitatively and models the relative risk profile of an aviation project throughout the ship programme life cycle. The use of an enterprise model based on the three “P” element methodology (3PE), product, process, people within an environment, has been developed. Furthermore, the research outlines a continuous management and visualisation approach that enables a process of dynamic analysis to both reduce and mitigate residual risks progressively throughout the project lifecycle to acceptable levels.

Given the characteristics of technology intensity, long cycle, and multiple supporting facilities in the performance of equipment procurement contracts, this paper uses the WBS method to sort out the main tasks of each link in the performance of contracts and constructs the performance risk index system of equipment procurement contracts. Aiming at the interaction of risks during the procurement contract performance, the Dematel-Aism method is used to build the identification model of key risk factors, and the risk confrontation hierarchy chart is obtained, which visually shows the influence path and interaction of different risks factors in the performance process. Finally, the paper puts forward relevant suggestions on risk control.