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All Journal International Journal of Supply Chain Management
Raju, Valliappan
International Journal of Supply Chain Management
Decision Sciences, Operations Research & Management Engineering Environmental Science Industrial & Manufacturing Engineering Transportation

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Meritorious Abilities of Supply Chain Management in Production Environment Raju, Valliappan; Phung, Siew Poh; Latiff, Norhaniza Abdul
International Journal of Supply Chain Management Vol 8, No 2 (2019): International Journal of Supply Chain Management (IJSCM)
Publisher : ExcelingTech

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59160/ijscm.v8i2.2861

Abstract

This paper is a hypothetical examination, opening with the presentation where the issue of the exploration, the question of the examination, the reason for the exploration and the exploration techniques are portrayed. The investigation uncovered that the market circumstance, association supply chains confront today, contrasts a ton from the circumstance years back. The job of dynamic abilities has consistently expanded with the impact that supply chains turned out to be longer and progressively mind-boggling. The opposition has more grounded because of the way that boundaries to the exchange have been step by step lessened. The fundamental question of this article is the dynamic abilities in production network the executives. The central motivation behind the article is systemization and exhaustive portrayal of the learning and data (found in an expansive number of sources) about the dynamic abilities, dynamic capacities idea, to show an intelligible outline on such parts of coordination as store network, production network the board.
Fundamentals of Green Supply Chain Management: Organizational Measures on Implementation Raju, Valliappan; Poh, Siew Phung; Kalimuthu, Ramanathan
International Journal of Supply Chain Management Vol 8, No 2 (2019): International Journal of Supply Chain Management (IJSCM)
Publisher : ExcelingTech

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59160/ijscm.v8i2.2864

Abstract

A coordinated effort among store network accomplices is fundamental to upgrade ecological execution amid the existence cycle of an item. Between hierarchical measures for green inventory network, management will in general show assorted examples in light of different prerequisites that develop in an unpredictable production network. In any case, this assorted variety hampers the extensive understanding and efficient selection of these measures. Consequently, this paper characterizes different between hierarchical measures for green production network the executives into a few coordinated effort designs and breaks down their auxiliary relations through an interpretive basic displaying. The outcomes uncover the joint effort designs that have higher driving force and reliance than different examples and, in this way, require further considerations.
Framework Assimilation in Supply Chain Management: Exploratory Study based on Investigation Poh, Siew Phung; Raju, Valliappan
International Journal of Supply Chain Management Vol 8, No 2 (2019): International Journal of Supply Chain Management (IJSCM)
Publisher : ExcelingTech

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59160/ijscm.v8i2.2867

Abstract

There has been a major leap in the field of inventory network for the executives. With every one of the procedures identified with production network are being completed carefully the Data has extended as far as possible where in it needs to took care of fastidiously. Dealing with and separating such a many-sided boundless data enormous Data investigation is the main safeguard to turn to. Enormous Data investigation keeps running on the Hadoop system so far which enables an association to store Big amount of Data on circle and furthermore process it. Because of increment sought after for Data examination, explicitly quicker Data investigation system Hadoop is viewed as not quick enough. This is the place Apache Spark came into picture year and a half back. Apache Spark is named to be multiple times quicker than Hadoop and this enables an association to process the equivalent Big Data in a shorter range of time in this manner, tending to the expanding request adequately. In this exploration paper we set forward the insights concerning the Apache Spark system while contrasting it and the current Hadoop structure close by, how utilizing Apache Spark system in Supply chain the board for Data examination would profit the association and organizations.
Co-Authors Kalimuthu, Ramanathan Latiff, Norhaniza Abdul Phung, Siew Poh Poh, Siew Phung