Leveraging the capabilities of service-oriented decision support systems: Putting analytics and big data in cloud
By Haluk Demirkan, Dursun Delen. Decision Support Systems, 2013
613 citations recorded by the source corpus.
Subfields: Management Information Systems, Management Science and Operations Research
View Paper: https://www.semanticscholar.org/paper/84feeffcdaf5df2b172e5a321e6a1d1453a94dfa
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Management Information Systems
- Angappa Gunasekaran
- Rameshwar Dubey
- Stephen J. Childe
- Thanos Papadopoulos
- Goran Calic
- Maryam Ghasemaghaei
- David Roubaud
- Eric Wai Ting Ngai
In Management Science and Operations Research
- Goran Calic
- Angappa Gunasekaran
- Stephen J. Childe
- Rameshwar Dubey
- Samee Ullah Khan
- Maryam Ghasemaghaei
- Eric Wai Ting Ngai
- Thanos Papadopoulos
Citations in the corpus
- Business intelligence & analytics in management accounting research: Status and future focus (2018, background): “Research is also needed to see whether SMEs take advantage of cloud-based BI&A solutions, which are increasingly being “ ser-vitized ” (Delen and Demirkan, 2013).”
- A Big Data Analytics Method for Tourist Behaviour Analysis (2017, neutral): “In most cases, databases, rules, models and other traditionally relevant technologies and methods employed in decision support systems were not designed to work with social media data: instead, these work best with highly structured data [15; 67].”
- Assessing the impact of big data on firm innovation performance: Big data is not always better data (2020, background): “Based on the findings, although firms now have access to better storage solutions (e.g., Hadoop) and lower storage costs (Demirkan & Delen, 2013), there are still challenges in managing large volumes of data.”
- How ‘Big Data’ Can Make Big Impact: Findings from a Systematic Review and a Longitudinal Case Study (2015, neutral): “…2012), (Ann Keller, et al., 2012), (Boja, et al., 2012), (Beath, et al., 2012), (McAfee & Brynjolfsson, 2012), (Thomas H. Davenport, et al., 2012), (Demirkan & Delen, 2012), (Danyel Fisher, et al., 2012), (Gehrke, 2012), (R. Griffin, 2012), (J. Griffin & Danson, 2012), (Huwe, 2012), (J. E.…”
- The rise of "big data" on cloud computing: Review and open research issues (2015, background): “[54] “ Leveraging the capabilities of service-oriented decision support systems: putting analytics and big data in cloud ” To propose a framework for decision support systems in a cloud [32] “ Cloud Computing and Scientific Applications — Big Data, Scalable Analytics, and Beyond ” To review some of…”
- Big data analytics and artificial intelligence pathway to operational performance under the effects of entrepreneurial orientation and environmental dynamism: A study of manufacturing organisations (2020, background): “BDA-AI enabled dynamic capabilities are necessary components for gaining significant competitive advantage (Demirkan and Delen, 2013).”
- Investigating acceptance of telemedicine services through an extended technology acceptance model (TAM) (2020, background): “It is identified in the literature that perceived risk contributes to the expectations of destructive consequences, thus, imparting a negative effect on usage intention [35,67,68].”
- Big Data and cloud computing: innovation opportunities and challenges (2017, background): “The increasing dependence on computers and Internet over the past decades makes businesses and individuals vulnerable to data breach and abuse (Denning and Denning 1979; Abraham and Papr-zycki 2004; Redlich and Nemzow 2006).”
- Big data analytics in logistics and supply chain management: Certain investigations for research and applications (2016, positive): “…rather, we draw on the taxonomy of analytics under three main categories: descriptive, predictive and prescriptive analytics (Trkman et al., 2010; Delen and Demirkan, 2013; Souza, 2014): (a) Descriptive analytics takes place either at standardized periods or whenever needed using techniques such…”
- Mitigating Supply Chain Risk via Sustainability Using Big Data Analytics: Evidence from the Manufacturing Supply Chain (2017, background): “Researchers categorize big data analytics into descriptive, predictive, and prescriptive [5,11,36].”
- A comprehensive review of big data analytics throughout product lifecycle to support sustainable smart manufacturing: A framework, challenges and future research directions (2019, methodology): “Keywords: big data analytics; smart manufacturing; servitization; sustainable production; conceptual framework; product lifecycle Abbreviations ABC Artificial bee colony IoT Internet of things ABS Agent-based system IT Information technology ACO Ant colony optimization JIT Just-in-time AD Anomaly de”