Evaluation of Data-Driven Sustainability Potential at SMEs Using an Altered Ecocanvas Model

被引:0
作者
Balint, Levente Peter [1 ,2 ]
Varallyai, Laszlo [2 ]
Botos, Szilvia [2 ]
机构
[1] Univ Debrecen, Doctoral Sch Management & Business, 138 Boszormeny ut, H-4032 Debrecen, Hungary
[2] Univ Debrecen, Inst Methodol & Business Digitalizat, Fac Econ & Business, 138 Boszormeny ut, H-4032 Debrecen, Hungary
关键词
sustainability; Ecocanvas; ESG; reporting; barriers; SMEs; data-driven; CIRCULAR ECONOMY; SUPPLY CHAIN; BIG; DIGITALIZATION; PERFORMANCE; MANAGEMENT; PRODUCT; DESIGN; ESG;
D O I
10.3390/economies13020049
中图分类号
F [经济];
学科分类号
02 ;
摘要
Incorporating sustainability into business operations is likely to become one of the most significant priorities and challenges for companies in the near future. SMEs operating within conventional frameworks often experience constraints when adjusting to evolving circumstances. They frequently lack resources, qualified experts, skills, and capabilities to enable the efficient implementation of DT within the organization. In this paper, Eurostat datasets were analyzed to uncover trends in SME digitalization and sustainability, focusing on patterns in data utilization, employee training, and environmental considerations. These insights were integrated into an altered Ecocanvas sustainability modeling tool to develop a framework supporting their strategic planning and decision-making. It has proven to be a useful tool for this purpose by mapping business processes against sustainability and strategic goals while indicating where digital or alternative solutions can be introduced. SMEs analyze data and consider environmental impacts at different levels based on their size categories. To determine whether these differences are statistically significant, we have performed one-way ANOVA tests. This paper aims to provide a data-driven situational analysis and tool, which outlines the benefits of data analytics from several aspects while offering practical recommendations for company leaders to consider and implement.
引用
收藏
页数:25
相关论文
共 119 条
  • [1] Ahmadi E., Maihami R., Ghalehkhondabi I., Big data analytics in supply chain management: A comprehensive overview, Journal of Cleaner Production, 213, pp. 904-932, (2020)
  • [2] Ali S., Poulova P., Yasmin F., Danish M., Akhtar W., Javed H.M.U., How big data analytics boosts organizational performance: The mediating role of the sustainable product development, Journal of Open Innovation: Technology, Market, and Complexity, 6, 4, (2020)
  • [3] Alshuaibi I.S.M., Alhebri A., Khan S.N., Sheikh A.A., Big data analytics, GHRM practices, and green digital learning paving the way towards green innovation and sustainable firm performance, Journal of Open Innovation: Technology, Market, and Complexity, 10, 4, (2024)
  • [4] Anshari M., Almunawar M.N., Lim S.A., Al-Mudimigh A., Customer relationship management and big data enabled: Personalization & customization of services, Applied Computing and Informatics, 15, 2, pp. 94-101, (2019)
  • [5] Antikainen M., Uusitalo T., Kivikyto-Reponen P., Digitalisation as an enabler of circular economy, Procedia CIRP, 73, pp. 45-49, (2018)
  • [6] Appiah-Kubi E., Management knowledge and sustainability reporting in SMEs: The role of perceived benefit and stakeholder pressure, Journal of Cleaner Production, 434, 1, (2024)
  • [7] Aslam A.M., Aseel A., Rithul R., Sunil P., Predictive big data analytics for drilling downhole problems: A review, Energy Reports, 9, pp. 5863-5876, (2022)
  • [8] Barbosa B., Bravo I., Oliveira C., Antunes L., Couto J.G., McFadden S., Hughes C., McClure P., Dias A.G., Digital skills of therapeutic radiographers/radiation therapists—Document analysis for a European educational curriculum, Radiography, 28, 4, pp. 955-963, (2022)
  • [9] Basit S.A., Gharleghi B., Batool K., Hassan S.S., Jahanshahi A.A., Kliem M.E., Review of enablers and barriers of sustainable business practices in SMEs, Journal of Economy and Technology, 2, pp. 79-94, (2024)
  • [10] Biemans W., The impact of digital tools on sales-marketing interactions and perceptions, Industrial Marketing Management, 115, pp. 395-407, (2023)