The Effect of Financial Management Quality, Product Innovation, and Digital Marketing on Micro Business Growth in the Jakarta Culinary Sector

Authors

  • Sidrotun Naim Sekolah Tinggi Manajemen IPMI Jakarta

DOI:

https://doi.org/10.58812/wsbm.v2i01.734

Keywords:

Micro Business Growth, Financial Management Quality, Product Innovation, Digital Marketing, Jakarta Culinary Sector

Abstract

This research investigates the dynamics of micro-business growth in the Jakarta Culinary Sector, focusing on the impact of Financial Management Quality (FMQ), Product Innovation (PI), and Digital Marketing (DM). A quantitative analysis involving a sample of 150 micro businesses reveals compelling insights. Results indicate significant positive relationships between FMQ, PI, and DM with Micro Business Growth (MBG). The study emphasizes the pivotal role of sound financial practices, innovation, and digital marketing in fostering growth within the competitive culinary landscape of Jakarta. Findings contribute to the understanding of success factors in micro-businesses, offering practical implications for entrepreneurs and policymakers.

References

M. A. C. Perdana, N. W. Sulistyowati, A. Ninasari, and S. Mokodenseho, “Analisis Pengaruh Pembiayaan, Skala Usaha, dan Ketersediaan Sumber Daya Manusia terhadap Profitabilitas UMKM,” Sanskara Ekon. dan Kewirausahaan, vol. 1, no. 03, pp. 135–148, 2023.

E. A. Lau, A. Y. Rukmana, S. Uhai, S. Mokodenseho, and W. I. D. A. Tapaningsih, “Mapping Research on the Influence of Social Media on Consumer Food Behavior a Bibliometric Approach,” Eastasouth J. Soc. Sci. Humanit., vol. 1, no. 02, pp. 84–94, 2024.

T. C. Wijayanti, S. Naim, N. Hendayani, A. Alfiana, and F. Hanum, “Identify the Use of Economics for Family Financial Management in Digital Days,” Indones. Interdiscip. J. Sharia Econ., vol. 7, no. 1, pp. 325–345, 2024.

S. Mokodenseho and T. L. Puspitaningrum, “Relasi sosial-ekonomi dan kekuasaan antara rentenir dan pedagang pasar tradisional di jawa tengah,” Polit. J. Ilmu Polit., vol. 13, no. 1, pp. 41–58, 2022.

K. Sivaraman, R. M. V. Krishnan, B. Sundarraj, and S. Sri Gowthem, “Network failure detection and diagnosis by analyzing syslog and SNS data: Applying big data analysis to network operations,” Int. J. Innov. Technol. Explor. Eng., vol. 8, no. 9 Special Issue 3, pp. 883–887, 2019, doi: 10.35940/ijitee.I3187.0789S319.

A. D. Dwivedi, G. Srivastava, S. Dhar, and R. Singh, “A decentralized privacy-preserving healthcare blockchain for IoT,” Sensors (Switzerland), vol. 19, no. 2, pp. 1–17, 2019, doi: 10.3390/s19020326.

F. Al-Turjman, H. Zahmatkesh, and L. Mostarda, “Quantifying uncertainty in internet of medical things and big-data services using intelligence and deep learning,” IEEE Access, vol. 7, pp. 115749–115759, 2019, doi: 10.1109/ACCESS.2019.2931637.

S. Kumar and M. Singh, “Big data analytics for healthcare industry: Impact, applications, and tools,” Big Data Min. Anal., vol. 2, no. 1, pp. 48–57, 2019, doi: 10.26599/BDMA.2018.9020031.

L. M. Ang, K. P. Seng, G. K. Ijemaru, and A. M. Zungeru, “Deployment of IoV for Smart Cities: Applications, Architecture, and Challenges,” IEEE Access, vol. 7, pp. 6473–6492, 2019, doi: 10.1109/ACCESS.2018.2887076.

B. P. L. Lau et al., “A survey of data fusion in smart city applications,” Inf. Fusion, vol. 52, no. January, pp. 357–374, 2019, doi: 10.1016/j.inffus.2019.05.004.

Y. Wu et al., “Large scale incremental learning,” Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit., vol. 2019-June, pp. 374–382, 2019, doi: 10.1109/CVPR.2019.00046.

A. Mosavi, S. Shamshirband, E. Salwana, K. wing Chau, and J. H. M. Tah, “Prediction of multi-inputs bubble column reactor using a novel hybrid model of computational fluid dynamics and machine learning,” Eng. Appl. Comput. Fluid Mech., vol. 13, no. 1, pp. 482–492, 2019, doi: 10.1080/19942060.2019.1613448.

V. Palanisamy and R. Thirunavukarasu, “Implications of big data analytics in developing healthcare frameworks – A review,” J. King Saud Univ. - Comput. Inf. Sci., vol. 31, no. 4, pp. 415–425, 2019, doi: 10.1016/j.jksuci.2017.12.007.

J. Sadowski, “When data is capital: Datafication, accumulation, and extraction,” Big Data Soc., vol. 6, no. 1, pp. 1–12, 2019, doi: 10.1177/2053951718820549.

J. R. Saura, B. R. Herraez, and A. Reyes-Menendez, “Comparing a traditional approach for financial brand communication analysis with a big data analytics technique,” IEEE Access, vol. 7, pp. 37100–37108, 2019, doi: 10.1109/ACCESS.2019.2905301.

D. Nallaperuma et al., “Online Incremental Machine Learning Platform for Big Data-Driven Smart Traffic Management,” IEEE Trans. Intell. Transp. Syst., vol. 20, no. 12, pp. 4679–4690, 2019, doi: 10.1109/TITS.2019.2924883.

S. Schulz, M. Becker, M. R. Groseclose, S. Schadt, and C. Hopf, “Advanced MALDI mass spectrometry imaging in pharmaceutical research and drug development,” Curr. Opin. Biotechnol., vol. 55, pp. 51–59, 2019, doi: 10.1016/j.copbio.2018.08.003.

C. Shang and F. You, “Data Analytics and Machine Learning for Smart Process Manufacturing: Recent Advances and Perspectives in the Big Data Era,” Engineering, vol. 5, no. 6, pp. 1010–1016, 2019, doi: 10.1016/j.eng.2019.01.019.

F. Zuhriyah, S. Naim, D. Rahmanudin, F. Widjayanto, and S. Mokodenseho, “The role of village government policies in improving the economy in sumbermulyo village,” J. Kewarganegaraan, vol. 6, no. 2, pp. 3975–3983, 2022.

T. B. Sembiring and S. Mokodenseho, “The Impact of Online Interactions on Mental Health among Adolescents in West Java,” Eastasouth J. Soc. Sci. Humanit., vol. 1, no. 01, pp. 1–9, 2023.

G. Xu, Y. Shi, X. Sun, and W. Shen, “Internet of things in marine environment monitoring: A review,” Sensors (Switzerland), vol. 19, no. 7, pp. 1–21, 2019, doi: 10.3390/s19071711.

M. Aqib, R. Mehmood, A. Alzahrani, I. Katib, A. Albeshri, and S. M. Altowaijri, Smarter traffic prediction using big data, in-memory computing, deep learning and gpus, vol. 19, no. 9. 2019.

S. Leonelli and N. Tempini, Data Journeys in the Sciences. 2020.

N. Stylos and J. Zwiegelaar, Big Data as a Game Changer: How Does It Shape Business Intelligence Within a Tourism and Hospitality Industry Context? 2019.

Q. Song, H. Ge, J. Caverlee, and X. Hu, “Tensor completion algorithms in big data analytics,” arXiv, vol. 13, no. 1, 2017.

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Published

2024-03-28

How to Cite

Naim, S. (2024). The Effect of Financial Management Quality, Product Innovation, and Digital Marketing on Micro Business Growth in the Jakarta Culinary Sector. West Science Business and Management, 2(01), 9–18. https://doi.org/10.58812/wsbm.v2i01.734