Role of big data analytics capability in developing integrated hospital supply chains and operational flexibility: An organizational information processing theory perspective

2020 ◽  
pp. 120417
Author(s):  
Wantao Yu ◽  
Gen Zhao ◽  
Qi Liu ◽  
Yongtao Song
Keyword(s):  
Big Data ◽  
Information Processing ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Operational Flexibility ◽  
Information Processing Theory ◽  
Processing Theory ◽  
Organizational Information ◽  
Analytics Capability

scholarly journals Creating Sustainable Innovativeness through Big Data and Big Data Analytics Capability: From the Perspective of the Information Processing Theory

2020 ◽  
Vol 12 (5) ◽  
pp. 1984
Author(s):  
Michael Song ◽  
Haili Zhang ◽  
Jinjin Heng
Keyword(s):  
Big Data ◽  
Information Processing ◽  
Data Analytics ◽  
Big Data Analytics ◽  
The United States ◽  
Information Processing Theory ◽  
Processing Theory ◽  
Study Results ◽  
Analytics Capability ◽  
Cross National

Service innovativeness is a key sustainable competitive advantage that increases sustainability of enterprise development. Literature suggests that big data and big data analytics capability (BDAC) enhance sustainable performance. Yet, no studies have examined how big data and BDAC affect service innovativeness. To fill this research gap, based on the information processing theory (IPT), we examine how fits and misfits between big data and BDAC affect service innovativeness. To increase cross-national generalizability of the study results, we collected data from 1403 new service development (NSD) projects in the United States, China and Singapore. Dummy regression method was used to test the model. The results indicate that for all three countries, high big data and high BDAC has the greatest effect on sustainable innovativeness. In China, fits are always better than misfits for creating sustainable innovativeness. In the U.S., high big data is always better for increasing sustainable innovativeness than low big data is. In contrast, in Singapore, high BDAC is always better for enhancing sustainable innovativeness than low BDAC is. This study extends the IPT and enriches cross-national research of big data and BDAC. We conclude the article with suggestions of research limitations and future research directions.

How supply chain analytics enables operational supply chain transparency

2018 ◽  
Vol 48 (1) ◽  
pp. 47-68 ◽  
Author(s):  
Suning Zhu ◽  
Jiahe Song ◽  
Benjamin T. Hazen ◽  
Kang Lee ◽  
Casey Cegielski
Keyword(s):  
Supply Chain ◽  
Information Processing ◽  
Business Environment ◽  
Business Practices ◽  
Information Processing Theory ◽  
Content Type ◽  
Processing Theory ◽  
Organizational Information ◽  
Organizational Information Processing Theory ◽  
Analytics Capability

Purpose The global business environment combined with increasing societal expectations of sustainable business practices challenges firms with a host of emerging risk factors. As such, firms seek to increase supply chain transparency, enabling them to monitor operational activities and manage supply chain risks. Drawing on organizational information processing theory, the purpose of this paper is to examine how supply chain analytics (SCA) capabilities support operational supply chain transparency. Design/methodology/approach Using data from 477 survey participants, hypotheses are tested using seemingly unrelated regression. Findings The results reveal that: analytics capability in support of planning functions indirectly affects organizational supply chain transparency (OSCT) via SCA capabilities in source, make, and deliver functions; SCA capabilities in source, make, and deliver positively influence OSCT; and supply uncertainty moderates the relationship between SCA capabilities in make and OSCT. Research limitations/implications This research suffers from limitations inherent in all survey-based research. Nonetheless, the authors found convincing evidence that suggests firms can employ SCA capabilities to meet transparency requirements. Practical implications The findings inform design of SCA systems, noting the importance of linking planning tools with tools that support source, make, and deliver functions. The research also shows how transparency can be increased via employing SCA capabilities. Originality/value This is one of first studies to empirically demonstrate that SCA capabilities can be used to increase supply chain transparency. The research also advances organizational information processing theory by illustrating an analytics capability paradox, where increased levels of certain analytics capabilities can become counterproductive in the face of supplier uncertainty.

scholarly journals A systematic review of the role of Big Data Analytics in reducing the influence of cognitive errors on the audit judgement

2019 ◽  
Vol 22 (2) ◽  
pp. 187-202 ◽  
Author(s):  
Fawad Ahmad
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Information Processing ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Future Research ◽  
Cognitive Errors ◽  
Revisión Sistemática ◽  
Toma De Decisiones

This systematic literature review provides the association between memory processes, auditors judgement and decision-making process under the influence of cognitive errors. Due to limited cognitive resources, auditors are unable to analyze the population of accounting transactions, therefore, they use sampling and heuristics for information processing. In the context of Big Data (BD), auditors may face a similar problem of information overload and exhibit cognitive errors, resulting in the selection and analysis of irrelevant information cues. But Big Data analytics (BDA) can facilitate information processing and analysis of complex diverse Big Data by reducing the influence of auditor’s cognitive errors. The current study adapts Ding et al., (2017) framework in the auditing context that identify causes of cognitive errors influencing auditor’s information processing. This review identified 75 auditing related studies to elaborate the role of BD and BDA in improving audit judgement. In addition, role of memory, cognitive errors, and judgement and decision-making are highlighted by using 61 studies. The analysis provides useful insight in different open areas by proposing research propositions and research questions that can be explored by future research to gain extensive understanding on the association between memory and audit judgement in the context of BD and BDA. La revisión sistemática de la literatura proporciona la asociación entre los procesos de la memoria, el juicio de los auditores y el proceso de toma de decisiones bajo la influencia de errores cognitivos. Debido a los limitados recursos cognitivos, los auditores no pueden analizar la población de transacciones contables; por lo tanto, utilizan el muestreo y la heurística para el procesamiento de la información. En el contexto de Big Data (BD), los auditores pueden enfrentarse a un problema similar de sobrecarga de información y exhibir errores cognitivos, lo que resulta en la selección y análisis de indicios de información irrelevantes. No obstante, la analítica de Big Data (BDA) puede facilitar el procesamiento de información y el análisis de datos complejos y diversos al reducir la influencia de los errores cognitivos del auditor. El presente estudio adapta el marco de trabajo de Ding et al (2017) en el contexto de la auditoría que identifica las causas de los errores cognitivos que influyen en el procesamiento de la información del auditor. Esta revisión identificó 75 estudios relacionados con la auditoría para elaborar el papel de BD y BDA en la mejora del juicio de auditoría. Además, el papel de la memoria, los errores cognitivos y el juicio y la toma de decisiones se destacan mediante el uso de 61 estudios. El análisis proporciona una visión útil de los diferentes aspectos abiertos de la cuestión proponiendo propuestas y preguntas de estudio que puedan ser exploradas por la investigación futura para obtener una comprensión amplia de la asociación entre la memoria y el juicio de auditoría en el contexto de BD y BDA.

Big data analytics capability and decision-making: The role of data-driven insight on circular economy performance

2021 ◽  
Vol 168 ◽  
pp. 120766
Author(s):  
Usama Awan ◽  
Saqib Shamim ◽  
Zaheer Khan ◽  
Najam Ul Zia ◽  
Syed Muhammad Shariq ◽  
...  
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Circular Economy ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Data Driven ◽  
Analytics Capability

Impacts of big data analytics management capabilities and supply chain integration on global sourcing: a survey on firm performance

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shokouh Razaghi ◽  
Sajjad Shokouhyar
Keyword(s):  
Big Data ◽  
Firm Performance ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Global Sourcing ◽  
Content Type ◽  
Mediating Role ◽  
Management Capability ◽  
Analytics Capability

Purpose This study aims to show that management with big data analytics capability can achieve more advantages of the global sourcing process. Furthermore, this study using its conceptual attitude model aims to show that big data analytics management capability leads to an increase in firm performance by the mediating role of integration. Design/methodology/approach Using an online questionnaire, 158 managers from 13 Iranian companies taking advantage of the global sourcing process were surveyed. The validity of the hypotheses was evaluated using partial least squares based on structural equation modeling (PLS method). Findings The results of the study showed that big data analytics management capability has a positive impact on global sourcing and firm performance directly, and by the mediating role of integration. Originality/value Previous studies have carefully addressed the role of big data and big data analytics in firms. However, this is among a few studies addressing the role of big data analytics capability, especially management capability, in improving firms’ performance. The results of this study shed light on the fact that how global sourcing takes the best advantage of big data analytics management capability for better accomplishment of organizations’ duties. The results of this study also disclose how big data analytics management capability helps organizations with their performance and bring benefits to their units.

The Role of Data and Technology in Promoting Big Data Analytics Capability

2021 ◽  
Author(s):  
Chu-Le Chong ◽  
Siti Zaleha Abdul Rasid ◽  
Haliyana Binti Khalid
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Analytics Capability
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