Modeling enablers of knowledge management process using multi criteria decision making approach

Agrawal, Nishant

doi:10.1108/vjikms-08-2019-0122

Cited by 13 publications

(5 citation statements)

References 118 publications

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“…It can be further extended by assessing the SS against the sustainability context. In the future, researchers can also use other MCDM tools (Agrawal 2019a, b, 2020; Gedam et al , 2021) and techniques rather than PROMETHEE to find some more meaningful insights. In future researchers can use the PROMETHEE method and some other MCDM tools that may open new research areas in the field of SS.…”

Section: Discussionmentioning

confidence: 99%

Multi-criteria decision-making toward supplier selection: exploration of PROMETHEE II method

Agrawal

2021

BIJ

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PurposeSupplier Selection (SS) is one of the vital decisions frequently executed by numerous industries. In recent times, the number of suppliers has increased enormously depending on a wide range of criteria. A selection of suppliers is a sensitive process that may impact various supply chain activities. The purpose of this research is to explore an underutilized technique called PROMETHEE II method for SS.Design/methodology/approachVarious tools and techniques are available under multi-criteria decision-making tools, which sometimes creates confusion in researchers' minds regarding reliability. PROMETHEE II was the most prominent method for ranking all available alternatives that ultimately avoid decision-making errors. To execute this equal and unequal weights approach has been used with three case studies.FindingsIn this research, three case studies have been used and soved with the help of the PROMETHEE II approach. The study also provides fundamental insights into the supplier's ranking on different criteria using sensitivity analysis. Further, criteria were divided as per benefits and non-beneficial to get a robust result. The pros and cons of PROMETHEE II approaches are also highlighted compared to other MCDM tools in this study.Originality/valueMost of the SS research uses either AHP or TOPSIS as per existing literature. There are very few attempts highlighted in the literature that use PROMETHEE II for the SS problem with sensitivity analysis. The proposed method is probable to motivate decision-makers to consider using a more sophisticated method like PROMETHEE II in supplier evaluation processes. This study opens a new direction for the ranking of suppliers in the field of the supply chain. The study also bears significant practical as well as managerial implications.

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Section: Discussionmentioning

confidence: 99%

Multi-criteria decision-making toward supplier selection: exploration of PROMETHEE II method

Agrawal

2021

BIJ

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“…At the same time, the classification model is used to capture and create new explicit knowledge. This process is carried out because knowledge capture and knowledge creation are critical factors for decision-making (Agrawal, 2020). The fourth stage is the DSS design.…”

Section: Methodsmentioning

confidence: 99%

Decision support system for fish quarantine measures in Indonesia

Hidayat

Satuti

Sensuse

et al. 2022

VJIKMS

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Purpose Fish quarantine is a measure to prevent the entry and spread of quarantine fish pests and diseases abroad and from one area to another within Indonesia's territory. Based on these backgrounds, this study aims to identify the knowledge, knowledge management (KM) processes and knowledge management system (KMS) priority needs for quarantine fish and other fishery products measures (QMFFP) and then develop a classification model and web-based decision support system (DSS) for QMFFP decisions. Design/methodology/approach This research methodology uses combination approaches, namely, contingency factor analysis (CFA), the cross-industry standard process for data mining (CRISP-DM) and knowledge management system development life cycle (KMSDLC). The CFA for KM solution design is performed by identifying KM processes and KMS priorities. The CRISP-DM for decision classification model is done by using a decision tree algorithm. The KMSDLC is used to develop a web-based DSS. Findings The highest priority requirements of KM technology for QMFFP are data mining and DSS with predictive features. The main finding of this study is to show that web-based DSS (functions and outputs) can support and accelerate QMFFP decisions by regulations and field practice needs. The DSS was developed using the CTree algorithm model, which has six main attributes and eight rules. Originality/value This study proposes a novel comprehensive framework for developing DSS (combination of CFA, CRISP-DM and KMSDLC), a novel classification model resulting from comparing two decision tree algorithms and a novel web-based DSS for QMFFP.

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“…Rather managers involved in the front-end need to develop relationships, build trust, and participate in inter-organisational cooperation, joint sense-and 4 decision-making, goal compromise and an agreed project vision. Project stakeholders also need help to navigate the fuzzy phase (Agrawal, 2021). Verworn et al (2007) and Williams and Samset (2010) pointed to a lack of clarity, which others see as being caused by three fuzziness sources: complexity, uncertainty and equivocality (Zack, 2001;Stevens, 2014).…”

Section: Front-end Fuzzinessmentioning

confidence: 99%

Project fuzziness to project value: the role of social capital

Sharari

Paton

Smart

2022

VJIKMS

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Purpose Project management scholars and practitioners have long debated how best to harness social interactions to optimise knowledge exchange and enhance stakeholder alignment and value. This study aims to assist project managers to understand and manage fuzziness and create enduring front-end value. It views the project life cycle as a potential source of co-created value. The paper uses a social capital lens to provide a deeper understanding of the project front-end; it uses a three-dimensional view (structural, relational, cognitive) to explore how stakeholder social capital can overcome front-end fuzziness to enhance decision-making and, thus, value creation. Design/methodology/approach Semi-structured interviews were conducted with senior managers from teleconnections companies, which, when combined with secondary data, established the impact, nature and dimensions of social capital within a project management setting. Findings The research found that social capital can help to reduce complexity, uncertainty and equivocality in the early stages of projects, making them more clearly defined and thus helping to create greater stakeholder value in the later stages of the project. A surprising finding was that some project team members engaged in intentional equivocality to try to promote their own benefits rather than those of the organisation. Originality/value This paper reconceptualises the impact of social capital on stakeholder value creation in the front-end of projects. The paper contributes to a more holistic view of the front-end of project management, focusing social capital to reduce the sources of front-end fuzziness.

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Modeling enablers of knowledge management process using multi criteria decision making approach

Cited by 13 publications

References 118 publications

Multi-criteria decision-making toward supplier selection: exploration of PROMETHEE II method

Multi-criteria decision-making toward supplier selection: exploration of PROMETHEE II method

Decision support system for fish quarantine measures in Indonesia

Project fuzziness to project value: the role of social capital

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