UPSKILLING STRATEGIES FOR SME EMPLOYEES IN THE DIGITAL AGE
Muhammad Ismail et al.
What the paper says
The domineering demand for upskilling employees in a Small Medium Enterprises (SMEs) for being competitive has brought to light by the growing demand for skilled workers in the digital age. The contemporary age’s growing demand for skilled workers shines through the human capital theory, thereby asserts that investment in staff training is imperative, developments of an organization. Insufficient research delays effective upskilling ingenuities in Pakistan. This study explores at how employees of Small and Medium Enterprises can advance their skills in the digital age, with a focus on technology tools, training techniques, financial and managerial skills. This study employed the qualitative methods for research by 5-point Likert-scale questionnaire survey to 411 employees from an event management company in Lahore, Pakistan. ‘Correlation’ (r) and ‘Regression’ (r2) analysis also shown positive values, which more supports our study hypothesis. Reliability shown that Cronbach’s alpha (ἀ) 0.81, it revealed that SME employees want to improve their skills in the digital transformation. The results show that respondents strongly agreed with the value of upskilling in improving their performance and the effectiveness of the Small and Medium Enterprises. The results indicate a noteworthy positive correlation between employee performance and upskilling, with 95.6% of respondents recognizing the value of upskilling and 71.5% strongly agreeing that it is necessary to improve their job serving work, which is proven by their understanding the benefits of technology and digital change. The findings of the study shed light on the advantages and maneuvers for upskilling SME employees in the digital age. JEL Classification Codes: M53, M12, O33, L26.
2 citations
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.22 × 0.4 = 0.09 |
| M · momentum | 0.55 × 0.15 = 0.08 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.