| Title |
Environmental and economical sustainability and stakeholder satisfaction in SMEs. Critical technological success factors of big data analytics |
| ID_Doc |
75767 |
| Authors |
Shaik, AS; Nazrul, A; Alshibani, SM; Agarwal, V; Papa, A |
| Title |
Environmental and economical sustainability and stakeholder satisfaction in SMEs. Critical technological success factors of big data analytics |
| Year |
2024 |
| Published |
|
| DOI |
10.1016/j.techfore.2024.123397 |
| Abstract |
In todays' world, utilising technology and adopting sustainability in small and medium business may benefit stakeholders while reducing adverse environmental effects. For SMEs to succeed, economic and environmental sustainability are crucial, particularly when using big data analytics to increase stakeholder satisfaction. This study intends to investigate the how the critical technological success factors of big data analytics help in achieving stakeholder satisfaction using environmental and economical sustainability. To analyse the data gathered from 324 SMEs, the study uses a quantitative research tool called structural equation modelling (SEM). A survey questionnaire created to examine the relevant factors was used to gather the sample data. According to the study's findings, stakeholder satisfaction is significantly impacted favourably by both environmental and economic sustainability. The results show that in order to increase stakeholder satisfaction, SMEs must implement sustainable practises and make use of technical advancements like big data analytics. For policymakers, business professionals, and academic researchers interested in how sustainability and big data analytics are used in SMEs, the study's findings are extremely insightful. The study underlines the significance of taking into account both environmental and economic sustainability in order to satisfy stakeholders and highlights the potential of big data analytics in doing so. |
| Author Keywords |
Environmental sustainability; Economical sustainability; Stakeholder satisfaction; Big data analytics; Small & medium enterprise; Structural equation modelling |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Social Science Citation Index (SSCI) |
| EID |
WOS:001234981700001 |
| WoS Category |
Business; Regional & Urban Planning |
| Research Area |
Business & Economics; Public Administration |
| PDF |
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