Details

Autor(en) / Beteiligte

• Anjaningrum, Widiya Dewi
• Azizah, Nur
• Suryadi, Nanang

Titel

Spurring SMEs’ performance through business intelligence, organizational and network learning, customer value anticipation, and innovation - Empirical evidence of the creative economy sector in East Java, Indonesia

Ist Teil von

• Heliyon, 2024-04, Vol.10 (7), p.e27998-e27998, Article e27998

Ort / Verlag

England: Elsevier Ltd

Erscheinungsjahr

2024

Link zum Volltext

Quelle

EZB-FREE-00999 freely available EZB journals

Beschreibungen/Notizen

• Several studies have explored firm performance in the post-Covid-19 pandemic era. However, there is not much research to find reports divulging the complex relationship dynamics between business intelligence, organizational and network learning, customer value anticipation, and creative economy-based small-medium enterprises (SMEs) performance in developing countries. This study aims to uncover the complexity of those relationships. The quantitative data were collected from 313 creative economy-based SMEs in East Java, Indonesia. Using PLS-SEM, this study disclosed that business intelligence practices could not directly impact SMEs' performance. Business intelligence will be crucial to SMEs' performance with the support of organizational learning as a mediator. The finding also confirmed the presence of serial mediation of organizational learning and innovation in the relationship between business intelligence and SMEs' performance. However, the role of network learning and innovation is also important, considering their relatively large direct impact on SMEs’ performance. The theoretical implications of this research broke the boundaries of strategic management theory in resource-based view and knowledge-based view in the latest era, where creative economy-based SMEs have been able to mobilize resources to carry out business intelligence to realize innovation and high performance. Further research is suggested to explore the role of business intelligence in promoting specific performance areas, such as marketing performance, financial performance, and human resource management. In addition, it is advisable to choose more specific research subjects, including those in the culinary subsector, and pay attention to other areas, e.g., the demographics of respondents in the model as a control variable.