5,044 research outputs found

    Developing a diagnostic heuristic for integrated sugarcane supply and processing systems.

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    Doctoral Degrees. University of KwaZulu-Natal, Pietermaritzburg.Innovation is a valuable asset that gives supply chains a competitive edge. Moreover, the adoption of innovative research recommendations in agricultural value chains and integrated sugarcane supply and processing systems (ISSPS) in particular has been relatively slow when compared with other industries such as electronics and automotive. The slow adoption is attributed to the complex, multidimensional nature of ISSPS and the perceived lack of a holistic approach when dealing with certain issues. Most of the interventions into ISSPS often view the system as characterised by tame problems hence, the widespread application of traditional operations research approaches. Integrated sugarcane supply and processing systems are, nonetheless, also characterised by wicked problems. Interventions into such contexts should therefore, embrace tame and/or wicked issues. Systemic approaches are important and have in the past identified several system-scale opportunities within ISSPS. Such interventions are multidisciplinary and employ a range of methodologies spanning across paradigms. The large number of methodologies available, however, makes choosing the right method or a combination thereof difficult. In this context, a novel overarching diagnostic heuristic for ISSPS was developed in this research. The heuristic will be used todiagnose relatively small, but pertinent ISSPS constraints and opportunities. The heuristic includes a causal model that determines and ranks linkages between the many domains that govern integrated agricultural supply and processing systems (IASPS) viz. biophysical, collaboration, culture, economics, environment, future strategy, information sharing, political forces, and structures. Furthermore, a diagnostic toolkit based on the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was developed. The toolkit comprises a diagnostic criteria and a suite of systemic tools. The toolkit, in addition, determines thesuitability of each tool to diagnose any of the IASPS domains. Overall, the diagnostic criteria include accessibility, interactiveness, transparency, iterativeness, feedback, cause-and-effect logic, and time delays. The tools considered for the toolkit were current reality trees, fuzzy cognitive maps (FCMs), network analysis approaches, rich pictures (RP), stock and flow diagrams, cause and effect diagrams (CEDs), and causal loop diagrams (CLDs). Results from the causal model indicate that collaboration, structure and information sharing had a high direct leverage over the other domains as these were associated with a larger number of linkages. Collaboration and structure further provided dynamic leverage as these were also part of feedback loops. Political forces and the culture domain in contrast, provided lowleverage as these domains were only directly linked to collaboration. It was further revealed that each tool provides a different facet to complexity hence, the need for methodological pluralism. All the tools except RP could be applied, to a certain extent, across both appreciation and analysis criteria. Rich pictures do not have causal analysis capabilities viz. cause-and-effect logic, time delays and feedback. Stock and flow diagrams and CLDs conversely, met all criteria. All the diagnostic tools in the toolkit could be used across all the system domains except for FCMs. Fuzzy cognitive maps are explicitly subjective and their contribution lies outside the objective world. Caution should therefore be practiced when FCMs areapplied within the biophysical domain. The heuristic is only an aid to decision making. The decision to select a tool or a combination thereof remains with the user(s). Even though the heuristic was demonstrated at Mhlume sugarcane milling area, it is recommended that other areas be considered for future research. The heuristic itself should continuously be updated with criteria, tools and other domain dimensions

    Analyzing the determinants of e-commerce in small and medium-sized enterprises: a cognition-driven framework

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    The increasing use of information technology in enterprises’ daily operations has led to multiple innovative ways to run a business, including electronic commerce (hereafter, e-commerce). However, firms with fewer resources, such as small and medium-sized enterprises (SMEs), are more reluctant to use electronic channels during transactions. This aversion to contemporary business models is a result of these companies’ lack of knowledge and capabilities regarding e-commerce. To improve their businesses, SMEs’ managers and decision makers could benefit from a methodological framework that fosters a deeper understanding of the determinants of e-commerce. This study sought to explore the use of fuzzy cognitive mapping to address this need. The results are grounded in the knowledge and experience of a panel of experts in e-commerce. The fuzzy cognitive map (FCM) developed shows that entrepreneur profile, market, operational management, marketing and promotions, website and digital platform, and products present the highest centrality indices as determinants of SME e-commerce. The findings offer a better understanding of the cause-and-effect relationships between these determinants. The advantages, limitations, and shortcomings of our constructivist proposal are also discussed.info:eu-repo/semantics/publishedVersio

    Repage: REPutation and ImAGE Among Limited Autonomous Partners

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    This paper introduces Repage, a computational system that adopts a cognitive theory of reputation. We propose a fundamental difference between image and reputation, which suggests a way out from the paradox of sociality, i.e. the trade-off between agents' autonomy and their need to adapt to social environment. On one hand, agents are autonomous if they select partners based on their social evaluations (images). On the other, they need to update evaluations by taking into account others'. Hence, social evaluations must circulate and be represented as "reported evaluations" (reputation), before and in order for agents to decide whether to accept them or not. To represent this level of cognitive detail in artificial agents' design, there is a need for a specialised subsystem, which we are in the course of developing for the public domain. In the paper, after a short presentation of the cognitive theory of reputation and its motivations, we describe the implementation of Repage.Reputation, Agent Systems, Cognitive Design, Fuzzy Evaluation

    Understanding Risk Perception Using Fuzzy Cognitive Maps

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    When making decision that can have far-researching effects, such as governmental policies or decisions on new technologies, decision-makers use their understanding of the risks that are associated with their choices to guide their decisions. Measuring how people perceive risks can be helpful for understanding and possibly improving the decision-making process. Building on a review of existing methods for investigating risk perceptions, this paper suggests Fuzzy Cognitive Maps (FCM) as a method for investigating differences in risk perception among stakeholders and stakeholder groups. The approach is illustrated with an example of wildfire risk perceptions. Results suggest that FCM can contribute to risk perception studies and provide means to improve Communications between different stakeholder groups and their involvement in the decision-making process. © 2016 Portland International Conference on Management of Engineering and Technology, Inc

    Big data and Sentiment Analysis considering reviews from e-commerce platforms to predict consumer behavior

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    Treballs Finals del MĂ ster de Recerca en Empresa, Facultat d'Economia i Empresa, Universitat de Barcelona, Curs: 2019-2020, Tutor: Javier Manuel RomanĂ­ FernĂĄndez ; Jaime Gil LafuenteNowadays and since the last two decades, digital data is generated on a massive scale, this phenomenon is known as Big Data (BD). This phenomenon supposes a change in the way of managing and drawing conclusions from data. Moreover, techniques and methods used in artificial intelligence shape new ways of analysis considering BD. Sentiment Analysis (SA) or Opinion Mining (OM) is a topic widely studied for the last few years due to its potential in extracting value from data. However, it is a topic that has been more explored in the fields of engineering or linguistics and not so much in business and marketing fields. For this reason, the aim of this study is to provide a reachable guide that includes the main BD concepts and technologies to those who do not come from a technical field such as Marketing directors. This essay is articulated in two parts. Firstly, it is described the BD ecosystem and the technologies involved. Secondly, it is conducted a systematic literature review in which articles related with the field of SA are analysed. The contribution of this study is a summarization and a brief description of the main technologies behind BD, as well as the techniques and procedures currently involved in SA

    KEMNAD: A Knowledge Engineering Methodology for Negotiating Agent Development

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    Automated negotiation is widely applied in various domains. However, the development of such systems is a complex knowledge and software engineering task. So, a methodology there will be helpful. Unfortunately, none of existing methodologies can offer sufficient, detailed support for such system development. To remove this limitation, this paper develops a new methodology made up of: (1) a generic framework (architectural pattern) for the main task, and (2) a library of modular and reusable design pattern (templates) of subtasks. Thus, it is much easier to build a negotiating agent by assembling these standardised components rather than reinventing the wheel each time. Moreover, since these patterns are identified from a wide variety of existing negotiating agents(especially high impact ones), they can also improve the quality of the final systems developed. In addition, our methodology reveals what types of domain knowledge need to be input into the negotiating agents. This in turn provides a basis for developing techniques to acquire the domain knowledge from human users. This is important because negotiation agents act faithfully on the behalf of their human users and thus the relevant domain knowledge must be acquired from the human users. Finally, our methodology is validated with one high impact system

    Applying FCM to Predict the Behaviour of Loyal Customers in the Mobile Telecommunications Industry

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    Using empirical data from the Kuwaiti mobile telecommunications sector, this study models a fuzzy cognitive map (FCM) to investigate the reciprocal effects of customer loyalty and its antecedents in an emerging market context. This study investigates the effect of perceived service quality, perceived service value and brand equity on customer loyalty and the simultaneous analysis of the reverse causality of these variables. Data pertaining to 350 subscribers were analysed. According to the results, the model reaches the equilibrium when brand equity and customer loyalty are increased and reach an optimal level. Based on these findings, the authors provide implications for managers in the mobile telecom industry

    Semantic discovery and reuse of business process patterns

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    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
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