ORCID Profile
0000-0002-6717-8634
Current Organisations
Auckland University of Technology
,
Queensland University of Technology
,
Victoria University of Wellington
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
Publisher: American Geophysical Union (AGU)
Date: 29-04-2022
DOI: 10.1029/2021GL097687
Abstract: This paper reports that there has been a significant relationship between the quasi‐biennial oscillation (QBO) in zonal wind at 50 hPa in summer and precipitation in August in northern China since the late 1970s. The correlation coefficient between them reaches up to −0.61 during 1979–2018. Associated with the easterly (westerly) phase of the QBO, there is a meridional dipole pattern of zonal wind from the stratosphere to troposphere over the Northwest Pacific in August with the easterly (westerly) anomalies in 25–50°N and westerly (easterly) anomalies in 50–65°N. This meridional zonal‐wind dipole favors the strengthening (weakening) of the tropospheric Japan Sea high in the QBO easterly (westerly) phase, causing an increase (decrease) of the water vapor transportation from the Northwest Pacific to northern China and thus more (less) precipitation in these regions. The finding of this study has import implications for predicting the summer precipitation in northern China in the future.
Publisher: Springer Science and Business Media LLC
Date: 18-02-2023
DOI: 10.1007/S10796-023-10374-W
Abstract: Organizations are integrating big data technologies with Enterprise Resource Planning (ERP) systems with an aim to enhance ERP responsiveness (i.e., the ability of the ERP systems to react towards the large volumes of data). Yet, organizations are struggling to manage the integration between the ERP systems and big data technologies, leading to lack of ERP responsiveness. For ex le, it is difficult to manage large volumes of data collected through big data technologies and to identify and transform the collected data by filtering, aggregating and inferencing through the ERP systems. Building on this motivation, this research examined the factors leading to ERP responsiveness with a focus on big data technologies. The conceptual model which was developed through a systematic literature review was tested using Structural equation modelling (SEM) performed on the survey data collected from 110 industry experts. Our results suggested 12 factors (e.g., big data management and data contextualization) and their relationships which impact on ERP responsiveness. An understanding of the factors which impact on ERP responsiveness contributes to the literature on ERP and big data management as well as offers significant practical implications for ERP and big data management practice.
Publisher: Emerald
Date: 19-03-2020
Abstract: This paper aims to develop a conceptual taxonomy for building requisite knowledge capabilities for different supply chain network (SCN) types. Specifically, it examines knowledge capabilities required for three types of SCNs: efficient, collaborative and agile SCNs. This paper integrates two bodies of thought (i.e. knowledge management and organisational learning) and applies them to SCNs. An abductive research process is used to develop this conceptual taxonomy. The conceptual taxonomy details three archetypical knowledge capabilities – exploitation, exploration and ambidextrous. Those knowledge capabilities are required for efficient, collaborative and agile SCNs, respectively. This paper is conceptual and theory-based. The next stages of the research seek to further strengthen the explanatory value of the taxonomy through empirical validation. The taxonomy developed in this paper provides a valuable and pragmatic tool for managerial decision-making in the context of SCNs. Specifically, it provides a roadmap for practitioners since the study develops an understanding of the relationship between knowledge capabilities and types of SCNs. This is one of the earliest studies that attempt to unearth requisite knowledge capabilities for different types of SCNs.
Publisher: Association for Information Systems
Date: 2021
DOI: 10.17705/1CAIS.04907
Publisher: Association for Information Systems
Date: 2019
DOI: 10.17705/1CAIS.04629
Publisher: Emerald
Date: 04-02-2014
Publisher: IEEE
Date: 12-2010
DOI: 10.1109/VCON.2010.8
Publisher: Elsevier BV
Date: 2022
Publisher: Informa UK Limited
Date: 30-11-2020
Publisher: Springer Nature Switzerland
Date: 2023
No related grants have been discovered for Maduka Subasinghage.