A trustworthy network or a technologically disguised scam

Issac, Abraham Cyril; Baral, Rupashree

doi:10.1108/gkmc-06-2019-0072

Cited by 8 publications

(4 citation statements)

References 59 publications

(60 reference statements)

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“…Within organizations, knowledge hiding is generally observed in different forms such as playing dumb, evasive hiding, rationalized hiding, and counter-questioning (Connelly et al ., 2012; Jha and Varkkey, 2018). Academic researchers have established the existence of multiple strategic factors that engender knowledge hiding, including job insecurity (Ashford et al ., 1989; De Witte, 1999; Serenko and Bontis, 2016), workplace ostracism (Bogilović et al ., 2017; Černe et al ., 2017), territoriality (Peng, 2013; Singh, 2019), trust deficit (Ford and Staples, 2010; Issac and Baral, 2020a), complexity and uncertainty of task (Boz Semerci, 2019; Hernaus et al ., 2019; Kang, 2016), reciprocity (Ayub et al ., 2021; Zhao et al ., 2016), personality traits (Demirkasimoglu, 2015; Jain and Jain, 2014), emotional intelligence (Burmeister et al ., 2019; de Geofroy and Evans, 2017), and the non-availability of knowledge management systems (Issac and Baral, 2020b; Lanke, 2018). Research has also shown that knowledge hiding could be mitigated to a certain extent with the aid of ethical leadership (Koay and Lim, 2022), keeping a check on organizational politics (Al-Alawi et al ., 2007; Qureshi and Evans, 2015), avoiding externalities such as time pressures (Škerlavaj et al ., 2018) and dynamic cultural strength coupled with pro-social motivation (Demirkasimoglu, 2015; Issac et al ., 2020).…”

Section: Theoretical Backgroundmentioning

confidence: 99%

True knowledge vs empowering knowledge: conceptualizing a theory of mindfulness and knowledge transfer (TMKT)

Issac,

Dhir,

Christofi

2024

JMP

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PurposeMindfulness is the human ability to be fully present, aware of where we are and what we're doing. This study explores on the impact of mindfulness on different elements of knowledge management, knowledge creation, knowledge sharing and knowledge hiding.Design/methodology/approachThe authors undertake an inductive reasoning approach whereby they try to generate themes from specific observations and conceptualize the theory of mindfulness and knowledge transfer.FindingsThis study finds out that mindfulness critically facilitates an open environment and enhances the clarity of thought which aids in effective knowledge creation. Such a realistic understanding about the present scenario encourages employees to share knowledge and equips them to collaborate and effectively work in teams. Surprisingly, this study also finds that mindfulness increases the result orientation to the extent that employees tried to hide knowledge from their co-workers targeting certain self-desired outcomes. In other words, similar to knowledge creation and knowledge sharing, mindfulness increases agenda-based knowledge hiding.Originality/valueThe theory of mindfulness and knowledge transfer states that mindfulness increases knowledge creation, knowledge sharing and agenda-based knowledge hiding.

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Section: Theoretical Backgroundmentioning

confidence: 99%

True knowledge vs empowering knowledge: conceptualizing a theory of mindfulness and knowledge transfer (TMKT)

Issac,

Dhir,

Christofi

2024

JMP

Self Cite

View full text Add to dashboard Cite

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“…This study essentially identifies the same as an important external factor in engendering knowledge hiding and finally find its place in the conceptual framework. The characteristics of the job or task motivate the knowledge seeker and the hider to play their relevant roles during any dyadic exchange (Issac & Baral, 2020). The organizational environment is equally critical in facilitating knowledge sharing or making individuals disengaged from knowledge hiding (Issac & Thomas, 2019; Mowbray, Wilkinson, & Tse, 2015; Thomas & Issac, 2018; Vasconcelos, 2018).…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Why you hide what you know: Neuroscience behind knowledge hiding

Issac

Baral

et al. 2021

Knowl Process Manag

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Knowledge hiding is the deliberate concealment of knowledge when requested. This study underscores three divergent elements of the knowledge hiding process. First, it underlines both the distinct internal and external factors that trigger the knowledge hiding process. Second, it brings out the critical facilitators of knowledge hiding, which do have roots in both the internal and external factors but are inseparable and indistinguishable. Finally, this study brings out a conceptual framework that underscores the vital importance of neuroscience in establishing episodes of knowledge hiding. This final phase of the study categorically establishes the typical need for memory and the frontal lobe integrity in justifying any sequence of events or their combinations as an episode of knowledge hiding.

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“…It is the first cryptographic commodity that can be traded like cash. It has risen to become the world's most popular cryptocurrency in recent years, with an increasing number of businesses accepting it as payment, fostering a crypto‐driven society (Issac & Baral, 2020; Ostapowicz & Żbikowski, 2020).…”

Section: Introductionmentioning

confidence: 99%

EnLEFD‐DM: Ensemble Learning based Ethereum Fraud Detection using CRISP‐DM framework

Pahuja

Kamal

2023

Expert Systems

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Cryptocurrencies continue to captivate businesses and investors despite market fluctuations. The number of crypto users has risen rapidly in the last few years, and alarmingly, many appear to be unaware of the risks involved. These risks aren't confined to market hazards but include very sophisticated cybercrimes related to cryptocurrencies. As cryptocurrencies have become a breeding ground for a variety of cybercrimes, resulting in enormous financial losses, it hinders user adoption limiting the utility of blockchain technology. It has become crucial to spot such scams and devise intelligent techniques to make this technology safer for investors. This paper proposes a classification model based on the Cross Industry Standard Process for Data Mining (CRISP-DM) framework to identify fraudulent transactions over the Ethereum blockchain. Its contribution is multi-faceted; first, the available imbalanced Ethereum dataset has been balanced to enhance the accuracy of the classification model. Second, the correlation-based feature selection technique has been applied to retain the best discriminating features. Thirdly, an effective machine learning-based ensemble classification model has been adopted for the identification of fraudulent transactions over the Ethereum network. A comparative analysis of 10 machine learning techniques has been presented consisting of both individual and ensemble classifiers. Evaluated outcomes show that ensemble classifiers appear to yield better performance measures over individual classifiers, and among all, the LightGbm classifier outperformed with 99.2% accuracy. Further, extensive experiments indicate that the proposed method outperforms the state-of-the-art method when applied to a similar dataset.

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A trustworthy network or a technologically disguised scam

Cited by 8 publications

References 59 publications

True knowledge vs empowering knowledge: conceptualizing a theory of mindfulness and knowledge transfer (TMKT)

True knowledge vs empowering knowledge: conceptualizing a theory of mindfulness and knowledge transfer (TMKT)

Why you hide what you know: Neuroscience behind knowledge hiding

EnLEFD‐DM: Ensemble Learning based Ethereum Fraud Detection using CRISP‐DM framework

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