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The purpose of this paper is to explore the role knowledge plays in expert commercial valuer practice to unpack the way theoretical and experiential knowledge operates in order to improve practice and education.

Adopting a cognitivist perspective and identifying meta-reasoning, using a grounded theory methodology, through the study of 11 chartered valuation surveyors practicing in Birmingham, United Kingdom, the distinctive theoretical and experiential knowledge they used was elicited through their in-depth reflection on a valuation task followed by analytical interviews exploring meaning and reasons of actions described.

The results confirmed that multi-sourced and rich valuation knowledge was a key attribute of a valuation expert. However, the experiential knowledge was not used to undertake the task but to select the methods and knowledge appropriate for the task and context. This meta-reasoning is a key to the speed, accuracy and justification of their practices. Thus, the experience gained from many years of valuation provides expert valuers with meta-reasoning involving knowledge of what, how and when to deal with problems in different circumstances such as the knowledge of markets and handling of clients.

Making meta-reasoning a key aspect of valuation will identify its characteristics more clearly, thus assisting the development of practitioners and providing a new focus for education to advance professional goals.

Meta-reasoning and meta-cognitive knowledge have not been identified as a key to successful valuation practice. This meta-reasoning allows a subtle balance of theory and experience in valuation practice that is appropriate to the situation.

Wide area search munitions (WASMs) are a cross between an unmanned aerial vehicle and a munition. With an impressive array of onboard sensors and autonomous flight capabilities WASMs might play a variety of roles on the modern battle field including reconnaissance, search, battle damage assessment, or communications relay.

This study aims to investigate how participants have interacted during the execution of Online Public Access Catalogue (OPAC) searches, and whether they were satisfied or dissatisfied or confused.

This is based on a sample of 18 OPAC users of the British Council Library in Kolkata.

While implementing the verbal protocol method this study has developed a scheme of coding with the help of which the protocol data were analysed and proposed a generic model of online catalogue searching process flow. It is suggested that the method has a great potential in library and information science research.

The paper suggests that the method has a great potential in library and information science research.

This chapter focuses on the state-of-the-art modeling approaches used in Intelligent Tutoring Systems (ITSs) and the frameworks for researching and operationalizing individual and group models of performance, knowledge, and interaction. We adapt several ITS methodologies to model team performance as well as individuals’ performance of the team members. We briefly describe the point processes proposed by von Davier and Halpin (2013), and we also introduce the Competency Architecture for Learning in teaMs (CALM) framework, an extension of the Generalized Intelligent Framework for Tutoring (GIFT) (Sottilare, Brawner, Goldberg, & Holden, 2012) to be used for team settings.

In a complex semiconductor manufacturing system (SMS) environment, the implementation of dynamic production scheduling and dispatching strategies is critical for SMS distributed collaborative manufacturing events to make quick and correct decisions. The purpose of this paper is to assist manufacturers in achieving the real time dispatching and obtaining integrated optimization for shop floor production scheduling.

In this paper, an integrated model is designed under assemble to order environment and a framework of a real time dispatching (IRTD) system for production scheduling control is presented accordingly. Both of the scheduling and ordering performances are integrated into the days of inventory based dispatching algorithm, which can deal with the multiple indicators of dynamic scheduling and ordering in this system to generate the “optimal” dispatching policies. Subsequently, the platform of IRTD system is realized with four modules function embedded.

The proposed IRTD system is designed to compare the previous constant work in process method in the experiment, which shows the better performance achievement of the IRTD system for shop floor production dynamic scheduling and order control. The presented framework and algorithm can facilitate real time dispatching information integration to obtain performance metrics in terms of reliability, availability, and maintainability.

The presented system can be further developed to generic factory manufacturing with the presented logic and architecture proliferation.

The IRTD system can integrate the real time customer demand and work in process information, based on which manufacturers can make correct and timely decisions in solving dispatching strategies and ordering selection within an integrated information system.

Firm size is an important contingency variable in macro-organizational studies. Several questions arise in relation to knowledge management and organizational size that is critical to both public and private organizations. Unfortunately, despite its significance, all or most of the studies that examined the effects of organizational size’ on knowledge management have been in the private sector. This paper aims to empirically study the effects of organizational size on the key knowledge management processes and subsequent operational efficiency derived from its implementation in the public sector.

A structured country-wide survey of United Arab Emirates public sector organizations was conducted. The 383 completed responses obtained were then analysed to assess the hypothesized differences in the implementation of knowledge management processes (knowledge acquisition, knowledge creation, knowledge capture, knowledge storage and retrieval, knowledge sharing, knowledge utilization) and its impact on the operational efficiency across small and medium, large and very large public sector organizations.

The results revealed that the extent of implementation of all six knowledge management processes and operational efficiency followed an inverted “V” pattern, in which, both knowledge management processes and operational efficiency was found to increase while transitioning from small and medium entities to large entities, but was found to decrease while transitioning from large to very large entities. In terms of relationships, while all knowledge management processes had a significant positive impact on the operational efficiency of the public sector, the ability to derive operational efficiency from knowledge management processes was found to be the highest for very large public sector organizations.

The novel findings are useful for practitioners and policymakers, especially those overseeing a country’s knowledge management initiatives to devise strategies, policies and support mechanisms to ensure public sector organizations, regardless of their size, can implement efficient and effective knowledge management processes to improve their operational efficiency.

The study is arguably the first comprehensive attempt to understand the impact of organizational size on knowledge management in the public sector.