Big data analytics capability and decision-making: The role of data-driven insight on circular economy performance
| Autor: | Syed Muhammad Shariq, Najam Ul Zia, Zaheer Khan, Usama Awan, Saqib Shamim, Muhammad Naveed Khan |
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| Přispěvatelé: | Lappeenrannan-Lahden teknillinen yliopisto LUT, Lappeenranta-Lahti University of Technology LUT, fi=School of Engineering Science|en=School of Engineering Science |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Knowledge management
Circular economy Computer science 020209 energy media_common.quotation_subject Big data 02 engineering and technology Manufacturing firms Big data analytics Structural equation modeling Data-driven Big data analytics capabilities Management of Technology and Innovation 0502 economics and business 0202 electrical engineering electronic engineering information engineering Quality (business) Business and International Management Applied Psychology media_common business.industry 05 social sciences HF5351 Data-driven insights Analytics Business intelligence business 050203 business & management Decision-making |
| ISSN: | 0040-1625 |
| Popis: | Big data analytics (BDA) is a revolutionary approach for sound decision-making in organizations that can lead to remarkable changes in transforming and supporting the circular economy (CE). However, extant literature on BDA capability has paid limited attention to understanding the enabling role of data-driven insights for supporting decision-making and, consequently, enhancing CE performance. We argue that firms drive decision-making quality through data-driven insights, business intelligence and analytics (BI&A), and BDA capability. In this study, we empirically investigated the association of BDA capability with CE performance and examined the mediating role of data-driven insights in the relationship between BDA capability and decision-making. Data were collected from 109 Czech manufacturing firms, and partial least squares structural equation modeling was applied to analyze the data. The results reveal that BDA capability and BI&A are positively associated with decision-making quality. This effect is stronger when the manufacturer utilizes data-driven insights. The results demonstrate that BDA capability drives decision-making quality in organizations, and data-driven insights do not mediate this relationship. BI&A is associated with decision-making quality through data-driven insights. These findings offer important insights to managers, as they can act as a reference point for developing data-driven insights with the CE paradigm in organizations. Post-print / Final draft |
| Databáze: | OpenAIRE |
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