Knowledge discovery for moderating collaborative projects

In today's global market environment, enterprises are increasingly turning towards collaboration in projects to leverage their resources, skills and expertise, and simultaneously address the challenges posed in diverse and competitive markets. Moderators, which are knowledge based systems have successfully been used to support collaborative teams by raising awareness of problems or conflicts. However, the functioning of a moderator is limited to the knowledge it has about the team members. Knowledge acquisition, learning and updating of knowledge are the major challenges for a Moderator's implementation. To address these challenges a Knowledge discOvery And daTa minINg inteGrated (KOATING) framework is presented for Moderators to enable them to continuously learn from the operational databases of the company and semi-automatically update the corresponding expert module. The architecture for the Universal Knowledge Moderator (UKM) shows how the existing moderators can be extended to support global manufacturing. A method for designing and developing the knowledge acquisition module of the Moderator for manual and semi-automatic update of knowledge is documented using the Unified Modelling Language (UML). UML has been used to explore the static structure and dynamic behaviour, and describe the system analysis, system design and system development aspects of the proposed KOATING framework. The proof of design has been presented using a case study for a collaborative project in the form of construction project supply chain. It has been shown that Moderators can "learn" by extracting various kinds of knowledge from Post Project Reports (PPRs) using different types of text mining techniques. Furthermore, it also proposed that the knowledge discovery integrated moderators can be used to support and enhance collaboration by identifying appropriate business opportunities and identifying corresponding partners for creation of a virtual organization. A case study is presented in the context of a UK based SME. Finally, this thesis concludes by summarizing the thesis, outlining its novelties and contributions, and recommending future research

What attracts vehicle consumers’ buying:A Saaty scale-based VIKOR (SSC-VIKOR) approach from after-sales textual perspective?

Purpose: The increasingly booming e-commerce development has stimulated vehicle consumers to express individual reviews through online forum. The purpose of this paper is to probe into the vehicle consumer consumption behavior and make recommendations for potential consumers from textual comments viewpoint. Design/methodology/approach: A big data analytic-based approach is designed to discover vehicle consumer consumption behavior from online perspective. To reduce subjectivity of expert-based approaches, a parallel Naïve Bayes approach is designed to analyze the sentiment analysis, and the Saaty scale-based (SSC) scoring rule is employed to obtain specific sentimental value of attribute class, contributing to the multi-grade sentiment classification. To achieve the intelligent recommendation for potential vehicle customers, a novel SSC-VIKOR approach is developed to prioritize vehicle brand candidates from a big data analytical viewpoint. Findings: The big data analytics argue that “cost-effectiveness” characteristic is the most important factor that vehicle consumers care, and the data mining results enable automakers to better understand consumer consumption behavior. Research limitations/implications: The case study illustrates the effectiveness of the integrated method, contributing to much more precise operations management on marketing strategy, quality improvement and intelligent recommendation. Originality/value: Researches of consumer consumption behavior are usually based on survey-based methods, and mostly previous studies about comments analysis focus on binary analysis. The hybrid SSC-VIKOR approach is developed to fill the gap from the big data perspective

A project management quality cost information system for the construction industry

A prototype Project Management Quality Cost System (PROMQACS) was developed to determine quality costs in construction projects. The structure and information requirements that are needed to provide a classification system of quality costs were identified and discussed. The developed system was tested and implemented in two case study construction projects to determine the information and management issues needed to develop PROMQACS into a software program. In addition, the system was used to determine the cost and causes of rework that occurred in the projects. It is suggested that project participants can use the information in PROMQACS to identify shortcomings in their project-related activities and therefore take the appropriate action to improve their management practices in future projects. The benefits and limitations of PROMQACS are identified

Nuclear Energy Complexes: Prospects for Development and Cooperation

1. 2005–2006 was a critical period in the development of the nuclear complexes of Russian Federation and the Republic of Kazakhstan. These years have ushered in a “nuclear renaissance”. Russia’s nuclear sector was subject to a total systemic review; the Federal Target Program (FTP) allocated to it funds totaling more than USD 55 billion. A decision was taken to consolidate all nuclear assets within one state corporation. Kazakhstan implemented the “15000 tons uranium by 2010” state development program. Its development programs for reactors and nuclear power plants are worked out jointly with Russia. Closer cooperation is also being pursued with other leaders in the field, primarily Japanese companies. Cooperation agreements between the two countries were adopted. The foundation of three joint ventures (JV) was the first tangible outcome of above agreements. 2. Meanwhile Kazakh uranium has become a focus of attention and fierce competition between the world’s largest consumers, including France, Canada, USA, Japan, China, South Korea, and Russia. Early this decade, Russia’s substantial production capacity and highly competitive uranium ore conversion technologies added to calls for the country to renew its economic links with Kazakhstan in the uranium mining and nuclear industries. Given Russia’s ambitious plans to develop nuclear energy, and the fact that its uranium stocks are practically depleted, the benefits of closer cooperation with Kazakhstan are clear. However, Russia will have to compete with well-established players on Kazakhstan’s uranium market. 3. Kazakhstan has aspirations to become a world leader in uranium mining and to focus production at the highly processed end of the nuclear fuel cycle. This was the backdrop for a recent transaction which will have a significant impact on the country’s nuclear industry. In the autumn of 2007, KazAtomProm purchased Toshiba’s 10% share in Westinghouse Electrics, a leading producer of nuclear reactors, for USD 540 million. This transaction has secured a permanent nuclear alliance between KazAtomProm, Toshiba and Westinghouse Electrics. For Kazakhstan, this creates new opportunities to develop a hi-tech nuclear industry and to market its output in the West. Supplying high-end nuclear products to Western markets is one of KazAtomProm’s development priorities, along with continued cooperation with Russia in supplying Soviettype reactors. 4. The need to integrate the nuclear power complexes of Kazakhstan and Russia along the entire production chain is a logical response to their urgent need to reduce their energy deficit, and to the synergies which exist between their production capacities and technologies at each stage of the nuclear fuel production chain: (1) uranium mining, (2) uranium enrichment, (3) production of fuel pellets and fuel elements, (4) reactor design and production, primarily 300 MW VBER-300 power reactors, (5) construction and operation of nuclear power plants, and (6) nuclear waste processing and disposal. 5. Kazakhstan has plans to develop its own nuclear power industry and is likely to base this on 300 MW Russian-Kazakh reactors and, in the longer-term, 1000 MW Westinghouse reactors. 6. The development of this capital-intensive sector will require extensive financing based on credit from a number of sources. International and national development banks are one promising potential source of such funding. The ability to secure this capital from international and national development banks rests entirely upon the nuclear energy industry’s potential for development, innovation, diversification and integration. The Eurasian Development Bank, VEB (Russian Development Bank) and the Development Bank of Kazakhstan have indicated their recognition of this. E.g., the EDB has extended credit to the Russian-Kazakh Zarechnoye JV.nuclear industry, economic cooperation, economic development, Russia, Kazakhstan, Eurasian Economic Community, CIS

Integrated use of technologies and techniques for construction knowledge management

The last two decades have witnessed a significant increase in discussions about the different dimensions of knowledge and knowledge management (KM). This is especially true in the construction context. Many factors have contributed to this growing interest including globalisation, increased competition, diffusion of new ICTs (information and communication technologies), and new procurement routes, among others. There are a range of techniques and technologies that can be used for knowledge management (KM) in construction organisations. The use of techniques for KM is not new, but many technologies for KM are fairly new and still evolving. This paper begins with a review of different KM techniques and technologies and then reports the findings of case studies of selected UK construction organisations, carried out with the aim of establishing what tools are currently being used in UK construction organisations to support knowledge processes. Case study findings indicate that most organisations do not adopt a structured approach for selecting KM technologies and techniques. The use of KM techniques is more evident compared to KM technologies. There is also reluctance among construction companies to invest in highly specialised KM technologies. The high costs of specialist KM technologies are viewed as the barrier to their adoption. In conclusion, the paper advocates integrated use of KM techniques and technologies in construction organisations

Components reuse in the building sector – A systematic review

© The Author(s) 2020. The final, definitive version of this paper has been published in Rakhshan, K., Morel, J.-C., Alaka, H., & Charef, R. (2020). Components reuse in the building sector – A systematic review. Waste Management & Research, 38(4), 347–370 by Sage Publications Ltd. All rights reserved. It is available at: https://doi.org/10.1177/0734242X20910463.Widespread reuse of building components can promote the circularity of materials in the building sector. However, the reuse ofbuilding components is not yet a mainstream practise. Although there have been several studies on the factors affecting the reuse ofbuilding components, there is no single study that has tried to harmonize the circumstances affecting this intervention. Through asystematic literature review targeting peer-reviewed journal articles, this study intends to identify and stratify factors affecting thereuse of components of the superstructure of a building and eventually delineate correlations between these factors. Factors identifiedthroughout this study are classified into six major categories and 23 sub-categories. Then the inter-dependencies between the barriersare studied by developing the correlation indices between the sub-categories. Results indicate that addressing the economic, socialand regulatory barriers should be prioritized. Although the impact of barriers under perception, risk, compliance and market subcategoriesare very pronounced, the highest inter-dependency among the sub-categories is found between perception and risk. Itsuggests that the perception of the stakeholders about building components reuse is affected by the potential risks associated with thisintervention.Peer reviewedFinal Accepted Versio

Critical analysis for big data studies in construction: significant gaps in knowledge

Purpose The purpose of this paper is to identify the gaps and potential future research avenues in the big data research specifically in the construction industry. Design/methodology/approach The paper adopts systematic literature review (SLR) approach to observe and understand trends and extant patterns/themes in the big data analytics (BDA) research area particularly in construction-specific literature. Findings A significant rise in construction big data research is identified with an increasing trend in number of yearly articles. The main themes discussed were big data as a concept, big data analytical methods/techniques, big data opportunities – challenges and big data application. The paper emphasises “the implication of big data in to overall sustainability” as a gap that needs to be addressed. These implications are categorised as social, economic and environmental aspects. Research limitations/implications The SLR is carried out for construction technology and management research for the time period of 2007–2017 in Scopus and emerald databases only. Practical implications The paper enables practitioners to explore the key themes discussed around big data research as well as the practical applicability of big data techniques. The advances in existing big data research inform practitioners the current social, economic and environmental implications of big data which would ultimately help them to incorporate into their strategies to pursue competitive advantage. Identification of knowledge gaps helps keep the academic research move forward for a continuously evolving body of knowledge. The suggested new research avenues will inform future researchers for potential trending and untouched areas for research. Social implications Identification of knowledge gaps helps keep the academic research move forward for continuous improvement while learning. The continuously evolving body of knowledge is an asset to the society in terms of revealing the truth about emerging technologies. Originality/value There is currently no comprehensive review that addresses social, economic and environmental implications of big data in construction literature. Through this paper, these gaps are identified and filled in an understandable way. This paper establishes these gaps as key issues to consider for the continuous future improvement of big data research in the context of the construction industry

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

Artificial Intelligence in the Construction Industry: A Systematic Review of the Entire Construction Value Chain Lifecycle

© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/In recent years, there has been a surge in the global digitization of corporate processes and concepts such as digital technology development which is growing at such a quick pace that the construction industry is struggling to catch up with latest developments. A formidable digital technology, artificial intelligence (AI), is recognized as an essential element within the paradigm of digital transformation, having been widely adopted across different industries. Also, AI is anticipated to open a slew of new possibilities for how construction projects are designed and built. To obtain a better knowledge of the trend and trajectory of research concerning AI technology application in the construction industry, this research presents an exhaustive systematic review of seventy articles toward AI applicability to the entire lifecycle of the construction value chain identified via the guidelines outlined by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The review’s findings show foremostly that AI technologies are mostly used in facility management, creating a huge opportunity for the industry to profit by allowing facility managers to take proactive action. Secondly, it shows the potential for design expansion as a key benefit according to most of the selected literature. Finally, it found data augmentation as one of the quickest prospects for technical improvement. This knowledge will assist construction companies across the world in recognizing the efficiency and productivity advantages that AI technologies can provide while helping them make smarter technology investment decisions.Peer reviewe