Subcontract and supply enquiries in the tender process of contractors

In the tender process, contractors often rely on subcontract and supply enquiries to calculate their bid prices. However, this integral part of the bidding process is not empirically articulated in the literature. Over 30 published materials on the tendering process of contractors that talk about enquiries were reviewed and found to be based mainly on experiential knowledge rather than systematic evidence. The empirical research here helps to describe the process of enquiries precisely, improve it in practice, and have some basis to support it in theory. Using a live participant observation case study approach, the whole tender process was shadowed in the offices of two of the top 20 UK civil engineering construction firms. This helped to investigate 15 research questions on how contractors enquire and obtain prices from subcontractors and suppliers. Forty-three subcontract enquiries and 18 supply enquiries were made across two different projects with average value of 7m. An average of 15 subcontract packages and seven supply packages was involved. Thus, two or three subcontractors or suppliers were invited to bid in each package. All enquiries were formulated by the estimator, with occasional involvement of three other personnel. Most subcontract prices were received in an average of 14 working days; and supply prices took five days. The findings show 10 main activities involved in processing enquiries and their durations, as well as wasteful practices associated with enquiries. Contractors should limit their enquiry invitations to a maximum of three per package, and optimize the waiting time for quotations in order to improve cost efficiency.

Knowledge communication and translation- A knowledge transfer model

Purpose – The purpose of this paper is to propose a process model for knowledge transfer in using theories relating knowledge communication and knowledge translation. Design/methodology/approach – Most of what is put forward in this paper is based on a research project titled “Procurement for innovation and knowledge transfer (ProFIK)”. The project is funded by a UK government research council – The Engineering and Physical Sciences Research Council (EPSRC). The discussions are mainly grounded on a thorough review of literature accomplished as part of the research project. Findings – The process model developed in this paper has built upon the theory of knowledge transfer and the theory of communication. Knowledge transfer, per se, is not a mere transfer of knowledge. It involves different stages of knowledge transformation. Depending on the context of knowledge transfer, it can also be influenced by many factors; some positive and some negative. The developed model of knowledge transfer attempts to encapsulate all these issues in order to create a holistic framework. Originality/value of paper – An attempt has been made in the paper to combine some of the significant theories or findings relating to knowledge transfer together, making the paper an original and valuable one.

The challenges of creating actionable knowledge: an action research perspective

Academia has a critical role in developing new knowledge which construction industry practitioners need to envision, undertake and sustain successful innovation. The new knowledge produced by academia, however, often does not satisfy the needs of practitioners. This unsatisfactory state of affairs is frequently taken to be the consequence of the cultural, motivational and operational differences between the two communities. Actionable knowledge is presented as a useful concept which can fuse the expectations, contributions and outputs of academia and practitioners. Within this context, action research is argued to be an appropriate methodology to develop successful actionable knowledge. Results from an action research project are given which provide researchers and practitioners greater understanding of the key factors that shape the degree to which action research produces actionable knowledge: change focus, collaboration capabilities and systematic process. The criteria intrinsic to Mode 2 research (Gibbons et al., 1994) are demonstrated to have utility in evidencing actionable knowledge. The implication for policy is that there is a need to develop and use appropriate actionable knowledge frameworks and measures to design funding calls, and to evaluate research proposals and outputs.

Does gym use impact upon nutritional knowledge?

Purpose - The purpose of this paper is to investigate gym and non-gym users' use and understanding of nutrition labels. Design/methodology/approach - A consumer survey in the form of a questionnaire conducted in the Greater London area in February/March 2005. Subject recruitment process took place in both a gym and university setting. Frequency tables and chi(2)-test are used to assess relationships between variables (p = 0.05). Findings - The resulting sample consisted of 187 subjects, with predominance of females and gym users. Of the subjects, 88 per cent reported to at least occasionally read nutrition labels, with higher reading rates amongst women, irrespective of gym user status. Total and saturated fats are the most often information viewed on labels, however the overall knowledge of the calorie content of fat is low, with 53 per cent of subjects responding saturated fat contains more calories per gram when compared with other types of fats. This paper does not find significant differences in the use and understanding of nutrition labels between gym and non-gym users, but highlights the publics' continued lack of understanding of nutrition labels. Originality/value - This paper is unique as it investigates whether there is any difference between gym/non-gym users' use and interpretation of use of nutrition labels. It finds gender impacted more on nutritional labels knowledge than gym user's status. This points to a gender issue and questions the quality of information available to the general public. This paper is valuable as it highlights and identifies an area that requires further research and assessment, and is therefore useful to key stakeholders responsible for public health nutrition.

Grey-box radial basis function modelling: the art of incorporating prior knowledge

A basic principle in data modelling is to incorporate available a priori information regarding the underlying data generating mechanism into the modelling process. We adopt this principle and consider grey-box radial basis function (RBF) modelling capable of incorporating prior knowledge. Specifically, we show how to explicitly incorporate the two types of prior knowledge: the underlying data generating mechanism exhibits known symmetric property and the underlying process obeys a set of given boundary value constraints. The class of orthogonal least squares regression algorithms can readily be applied to construct parsimonious grey-box RBF models with enhanced generalisation capability.

Semi-automatic knowledge extraction, representation and context-sensitive intelligent retrieval of video content using collateral context modelling with scalable ontological networks

Automatic indexing and retrieval of digital data poses major challenges. The main problem arises from the ever increasing mass of digital media and the lack of efficient methods for indexing and retrieval of such data based on the semantic content rather than keywords. To enable intelligent web interactions, or even web filtering, we need to be capable of interpreting the information base in an intelligent manner. For a number of years research has been ongoing in the field of ontological engineering with the aim of using ontologies to add such (meta) knowledge to information. In this paper, we describe the architecture of a system (Dynamic REtrieval Analysis and semantic metadata Management (DREAM)) designed to automatically and intelligently index huge repositories of special effects video clips, based on their semantic content, using a network of scalable ontologies to enable intelligent retrieval. The DREAM Demonstrator has been evaluated as deployed in the film post-production phase to support the process of storage, indexing and retrieval of large data sets of special effects video clips as an exemplar application domain. This paper provides its performance and usability results and highlights the scope for future enhancements of the DREAM architecture which has proven successful in its first and possibly most challenging proving ground, namely film production, where it is already in routine use within our test bed Partners' creative processes. (C) 2009 Published by Elsevier B.V.

Knowledge-elicitation and data-mining: fusing human and industrial plant information

Knowledge-elicitation is a common technique used to produce rules about the operation of a plant from the knowledge that is available from human expertise. Similarly, data-mining is becoming a popular technique to extract rules from the data available from the operation of a plant. In the work reported here knowledge was required to enable the supervisory control of an aluminium hot strip mill by the determination of mill set-points. A method was developed to fuse knowledge-elicitation and data-mining to incorporate the best aspects of each technique, whilst avoiding known problems. Utilisation of the knowledge was through an expert system, which determined schedules of set-points and provided information to human operators. The results show that the method proposed in this paper was effective in producing rules for the on-line control of a complex industrial process. (C) 2005 Elsevier Ltd. All rights reserved.

Fusing data-mining and knowledge elicitation for the supervisory control of an aluminium plate mill

Knowledge-elicitation is a common technique used to produce rules about the operation of a plant from the knowledge that is available from human expertise. Similarly, data-mining is becoming a popular technique to extract rules from the data available from the operation of a plant. In the work reported here knowledge was required to enable the supervisory control of an aluminium hot strip mill by the determination of mill set-points. A method was developed to fuse knowledge-elicitation and data-mining to incorporate the best aspects of each technique, whilst avoiding known problems. Utilisation of the knowledge was through an expert system, which determined schedules of set-points and provided information to human operators. The results show that the method proposed in this paper was effective in producing rules for the on-line control of a complex industrial process.

A Design for Generating Personalised Feedback in Knowledge Construction

As the learning paradigm shifts to a more personalised learning process, users need dynamic feedback from their knowledge path. Learning Management Systems (LMS) offer customised feedback dependent on questions and the answers given. However these LMSs are not designed to generate personalised feedback for an individual learner, tutor and instructional designer. This paper presents an approach for generating constructive feedback for all stakeholders during a personalised learning process. The dynamic personalised feedback model generates feedback based on the learning objectives for the Learning Object. Feedback can be generated at Learning Object level and the Information Object level for both the individual learner and the group. The group feedback is meant for the tutors and instructional designer to improve the learning process.

Articulation of information requirements for personalised knowledge and construction

The quality of information provision influences considerably knowledge construction driven by individual users’ needs. In the design of information systems for e-learning, personal information requirements should be incorporated to determine a selection of suitable learning content, instructive sequencing for learning content, and effective presentation of learning content. This is considered as an important part of instructional design for a personalised information package. The current research reveals that there is a lack of means by which individual users’ information requirements can be effectively incorporated to support personal knowledge construction. This paper presents a method which enables an articulation of users’ requirements based on the rooted learning theories and requirements engineering paradigms. The user’s information requirements can be systematically encapsulated in a user profile (i.e. user requirements space), and further transformed onto instructional design specifications (i.e. information space). These two spaces allow the discovering of information requirements patterns for self-maintaining and self-adapting personalisation that enhance experience in the knowledge construction process.

Design, implementation and testing of an intelligent knowledge-based system for the supervisory control of a hot rolling mill

This paper describes the design, implementation and testing of an intelligent knowledge-based supervisory control (IKBSC) system for a hot rolling mill process. A novel architecture is used to integrate an expert system with an existing supervisory control system and a new optimization methodology for scheduling the soaking pits in which the material is heated prior to rolling. The resulting IKBSC system was applied to an aluminium hot rolling mill process to improve the shape quality of low-gauge plate and to optimise the use of the soaking pits to reduce energy consumption. The results from the trials demonstrate the advantages to be gained from the IKBSC system that integrates knowledge contained within data, plant and human resources with existing model-based systems. (c) 2005 Elsevier Ltd. All rights reserved.

Risk accountability in the tender process of contractors in Ghana and UK

The process of how contractors take account of risk when calculating their bids for construction work is investigated based on preliminary investigations and case studies in Ghana and UK. Ghana and UK were chosen, more or less arbitrarily, for the purpose of case studies, and to test the idea that there are systematic differences between the approaches in different places. Clear differences were found in the risk pricing approaches of contractors in the two countries. The difference appeared to emanate from the professional knowledge and competence of the bid team members, company policy, corporate accountability and the business environments in which the contractors operate. Both groups of contractors take account of risk in estimates. However, risk accountability was found to be higher on the agenda in the tender process of UK contractors, documented more systematically, and assessed and managed more rigorously with input from the whole bid team. Risk accountability takes place at three levels of the tender process and is dictated strongly by market forces and company circumstances.

Knowledge transfer processes in PFI/PPP: critical success factors

Successful knowledge transfer is an important process which requires continuous improvement in today’s knowledge-intensive economy. However, improving knowledge transfer processes represents a challenge for construction practitioners due to the complexity of knowledge acquisition, codification and sharing. Although knowledge transfer is context based, understanding the critical success factors can lead to improvements in the transfer process. This paper seeks to identify and evaluate the most significant critical factors for improving knowledge transfer processes in Public Private Partnerships/Private Finance Initiatives (PPP/PFI) projects. Drawing upon a questionnaire survey of 52 construction firms located in the UK, data is analysed using Severity Index (SI) and Coefficient of Variation (COV), to examine and identify these factors in PPP/PFI schemes. The findings suggest that a supportive leadership, participation/commitment from the relevant parties, and good communication between the relevant parties are crucial to improving knowledge transfer processes in PFI schemes. Practitioners, managers and researchers can use the findings to efficiently design performance measures for analysing and improving knowledge transfer processes.

Dynamic knowledge representation in connectionist systems

One of the most pervading concepts underlying computational models of information processing in the brain is linear input integration of rate coded uni-variate information by neurons. After a suitable learning process this results in neuronal structures that statically represent knowledge as a vector of real valued synaptic weights. Although this general framework has contributed to the many successes of connectionism, in this paper we argue that for all but the most basic of cognitive processes, a more complex, multi-variate dynamic neural coding mechanism is required - knowledge should not be spacially bound to a particular neuron or group of neurons. We conclude the paper with discussion of a simple experiment that illustrates dynamic knowledge representation in a spiking neuron connectionist system.