Knowledge acquisition in supply chain partnerships: The role of power

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 @ 2013 Elsevier B.V.Knowledge is recognised as an important source of competitive advantage and hence there has been increasing academic and practitioner interest in understanding and isolating the factors that contribute to effective knowledge transfer between supply chain actors. The literature identifies power as a salient contributor to the effective operation of a supply chain partnership. However, there is a paucity of empirical research examining how power among actors influences knowledge acquisition and in turn the performance of supply chain partners. The aim of this research is to address this gap by examining the relationship between power, knowledge acquisition and supply chain performance among the supply chain partners of a focal Chinese steel manufacturer. A structured survey was used to collect the necessary data. Two conceptually independent variables – ‘availability of alternatives’ and ‘restraint in the use of power’ – were used to assess actual and realised power, respectively. Controlling for contingencies, we found that the flow of knowledge increased when supply chain actors had limited alternatives and when the more powerful actor exercised restraint in the use of power. Moreover, we found a positive relationship between knowledge acquisition and supply chain performance. This paper enriches the literature by empirically extending our understanding of how power affects knowledge acquisition and performance

On Evidence-based Risk Management in Requirements Engineering

Background: The sensitivity of Requirements Engineering (RE) to the context makes it difficult to efficiently control problems therein, thus, hampering an effective risk management devoted to allow for early corrective or even preventive measures. Problem: There is still little empirical knowledge about context-specific RE phenomena which would be necessary for an effective context- sensitive risk management in RE. Goal: We propose and validate an evidence-based approach to assess risks in RE using cross-company data about problems, causes and effects. Research Method: We use survey data from 228 companies and build a probabilistic network that supports the forecast of context-specific RE phenomena. We implement this approach using spreadsheets to support a light-weight risk assessment. Results: Our results from an initial validation in 6 companies strengthen our confidence that the approach increases the awareness for individual risk factors in RE, and the feedback further allows for disseminating our approach into practice.Comment: 20 pages, submitted to 10th Software Quality Days conference, 201

GTTC Future of Ground Testing Meta-Analysis of 20 Documents

National research, development, test, and evaluation ground testing capabilities in the United States are at risk. There is a lack of vision and consensus on what is and will be needed, contributing to a significant threat that ground test capabilities may not be able to meet the national security and industrial needs of the future. To support future decisions, the AIAA Ground Testing Technical Committees (GTTC) Future of Ground Test (FoGT) Working Group selected and reviewed 20 seminal documents related to the application and direction of ground testing. Each document was reviewed, with the content main points collected and organized into sections in the form of a gap analysis current state, future state, major challenges/gaps, and recommendations. This paper includes key findings and selected commentary by an editing team

Continuous maintenance and the future – Foundations and technological challenges

High value and long life products require continuous maintenance throughout their life cycle to achieve required performance with optimum through-life cost. This paper presents foundations and technologies required to offer the maintenance service. Component and system level degradation science, assessment and modelling along with life cycle ‘big data’ analytics are the two most important knowledge and skill base required for the continuous maintenance. Advanced computing and visualisation technologies will improve efficiency of the maintenance and reduce through-life cost of the product. Future of continuous maintenance within the Industry 4.0 context also identifies the role of IoT, standards and cyber security