- My interest has always been in how people can and do (or do not) use models and systems to help them do things. At pr... moreMy interest has always been in how people can and do (or do not) use models and systems to help them do things. At present my principal research interests include how knowledge affects risk management, investigating knowledge management strategy and its implementationedit
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Research Interests: Engineering, Computer Science, HE, IEEE, expert System, and 5 moreQa, Ta, TS, Tk, and Decision Maker
Research Interests: Information Systems, Engineering, Computer Science, Expert Systems, Knowledge Management, and 14 moreInformation Management, Business Information Systems, Comparative Study, The Internet, Business and Management, Web Application, Web Based, expert System, World Wide Web, Knowledge Based Systems, Knowledge base, Added Value, Internet, and Information System
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Research Interests: Business, Information Systems, Cognitive Science, Computer Science, Distributed Computing, and 14 moreArtificial Intelligence, Expert Systems, Information Management, Transformative Learning, Machine Learning, Management Science, AI, Research Agenda, Library and Information Studies, Cognitive Computing, Engineering Ethics, Multidisciplinary Approach, Elsevier, and Pace
Research Interests: Information Systems, Sociology, Computer Science, Distributed Computing, Information Technology, and 10 moreKnowledge Management, Information Management, Library and Information Studies, Big Data, Digital Life, Pandemic, Digital World, Digital Transformation, CoVid, and Coronavirus Disease 2019 (COVID-19)
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Google, Inc. (search). ...
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Innovation is one of the key drivers for gaining competitive advantages in any firms. Understanding knowledge transfer through inter-firm networks and its effects on types of innovation in SMEs is very important in improving SMEs... more
Innovation is one of the key drivers for gaining competitive advantages in any firms. Understanding knowledge transfer through inter-firm networks and its effects on types of innovation in SMEs is very important in improving SMEs innovation. This study examines relationships between characteristics of inter-firm knowledge transfer networks and types of innovation in SMEs. To achieve this, social network perspective is adopted to understand inter-firm knowledge transfer networks and its impact on innovation by investigating how and to what extend ego network characteristics are affecting types of innovation. Therefore, managers can develop the firms'network according to their strategies and requirements. First, a conceptual model and research hypotheses are proposed to establish the possible relationship between network properties and types of innovation. Three aspects of ego network are identified and adopted for hypotheses development: 1) structural properties which address the potential for resources and the context for the flow of resources, 2) relational properties which reflect the quality of resource flows, and 3) nodal properties which are about quality and variety of resources and capabilities of the ego partners. A questionnaire has been designed based on the hypotheses. Second, semistructured interviews with managers of five SMEs have been carried out, and a thematic qualitative analysis of these interviews has been performed. The interviews helped to revise the questionnaire and provided preliminary evidence to support the hypotheses. Insights from the preliminary investigation also helped to develop research plan for the next stage of this research.
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This paper looks at expert systems in management, by using a business game as an experimental vehicle. An expert system called EXGAME was developed to play a business game, which is normally played by students, with minimal human... more
This paper looks at expert systems in management, by using a business game as an experimental vehicle. An expert system called EXGAME was developed to play a business game, which is normally played by students, with minimal human intervention. This paper concentrates on the effectiveness of EXGAME as compared with human players for tasks at different levels. EXGAME was able to replace human players in decision making at the operational level, and indeed outperform them. However, it proved to be impractical to replace human input at the strategic level. The paper also sheds some light on the problems of trying to build an expert system when there is no real expert. A combination of a modular knowledge-base structure and a process of ‘learning by experimentation’ was effective in this case; it is suggested that this may be an appropriate development strategy in other similar situations. © 1998 John Wiley & Sons, Ltd.
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Research Interests: Information Systems, Marketing, Computer Science, Information Technology, Hybrid Systems, and 14 moreStrategic Management, Strategic Planning, Marketing Strategy, Marketing Management, Process management, Judgement, Marketing Information Systems, Development Process, Strategic Information Systems, Support System, Hybrid System, Marketing Intelligence, Information System, and Hybrid intelligent system
Skip to content | main University navigation | local section navigation | search. Aston University: Site AZ; Contact us; Directions; Main University navigation links: Home; Study at Aston; About Aston; Departments; Birmingham; Research;... more
Skip to content | main University navigation | local section navigation | search. Aston University: Site AZ; Contact us; Directions; Main University navigation links: Home; Study at Aston; About Aston; Departments; Birmingham; Research; Business Services; News & Events. Login | Create Account, Knowledge elicitation supported by simulation. Edwards, JS; Alifantis, A; Hurrion, RD; Ladbrook, J; Robinson, S and Waller, T (2002). Knowledge elicitation supported by simulation. ...
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Transformative artificially intelligent tools, such as ChatGPT, designed to generate sophisticated text indistinguishable from that produced by a human, are applicable across a wide range of contexts. The technology presents opportunities... more
Transformative artificially intelligent tools, such as ChatGPT, designed to generate sophisticated text indistinguishable from that produced by a human, are applicable across a wide range of contexts. The technology presents opportunities as well as, often ethical and legal, challenges, and has the potential for both positive and negative impacts for organisations, society, and individuals. Offering multi-disciplinary insight into some of these, this article brings together 43 contributions from experts in fields such as computer science, marketing, information systems, education, policy, hospitality and tourism, management, publishing, and nursing. The contributors acknowledge ChatGPT’s capabilities to enhance productivity and suggest that it is likely to offer significant gains in the banking, hospitality and tourism, and information technology industries, and enhance business activities, such as management and marketing. Nevertheless, they also consider its limitations, disruptions to practices, threats to privacy and security, and consequences of biases, misuse, and misinformation. However, opinion is split on whether ChatGPT’s use should be restricted or legislated. Drawing on these contributions, the article identifies questions requiring further research across three thematic areas: knowledge, transparency, and ethics; digital transformation of organisations and societies; and teaching, learning, and scholarly research. The avenues for further research include: identifying skills, resources, and capabilities needed to handle generative AI; examining biases of generative AI attributable to training datasets and processes; exploring business and societal contexts best suited for generative AI implementation; determining optimal combinations of human and generative AI for various tasks; identifying ways to assess accuracy of text produced by generative AI; and uncovering the ethical and legal issues in using generative AI across different contexts.
Research Interests: Information Systems, Marketing, Distributed Computing, Artificial Intelligence, Information Management, and 13 moreTransformative Learning, Services Marketing and Management, Hospitality, Library and Information Studies, Engineering Ethics, Services Marketing, Generative grammar, Chatbot, Virtual conversational agents, Service Robots, Multidisciplinary Approach, ChatGPT, and Generative AI
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This chapter explains the role of knowledge management systems, whether technology-based or people-based, in service supply chain management. A systematic literature review was carried out to identify relevant examples of both successful... more
This chapter explains the role of knowledge management systems, whether technology-based or people-based, in service supply chain management. A systematic literature review was carried out to identify relevant examples of both successful and unsuccessful knowledge management systems. These are analyzed in terms of process, people and technology aspects, and the activities in the knowledge life-cycle (create, acquire, store, use, refine, transfer) that they support. These include systems used within a single organization, systems shared with supply chain partners, and systems shared with customers, the latter being the least common. Notable features are that more systems support knowledge exploitation than knowledge exploration, and that general-purpose software (e.g., internet search, database) is used more than software specific to knowledge management (e.g., data mining, “people finder”). The widespread use of mobile devices and social media offers both an opportunity and a challe...
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A hybrid approach for integrating group Delphi, fuzzy logic and expert systems for developing marketing strategies is proposed in this paper. Within this approach, the group Delphi method is employed to help groups of managers undertake... more
A hybrid approach for integrating group Delphi, fuzzy logic and expert systems for developing marketing strategies is proposed in this paper. Within this approach, the group Delphi method is employed to help groups of managers undertake SWOT analysis. Fuzzy logic is applied to fuzzify the results of SWOT analysis. Expert systems are utilised to formulate marketing strategies based upon the fuzzified strategic inputs. In addition, guidelines are also provided to help users link the hybrid approach with managerial judgement and intuition. The effectiveness of the hybrid approach has been validated with MBA and MA marketing students. It is concluded that the hybrid approach is more effective in terms of decision confidence, group consensus, helping to understand strategic factors, helping strategic thinking, and coupling analysis with judgement, etc.