Predicting Workforce Engagement towards Digital Transformation through a Multi-Analytical Approach
Abstract
:1. Introduction
2. Literature Review
2.1. Social Exchange Theory (SET)
2.2. Knowledge Sharing
2.3. Employee Mobility
2.4. Training and Development
2.5. Psychological Empowerment
2.6. Research Framework
3. Methodology
4. Results
4.1. Demographic Results
4.2. Common Method Bias (CMB)
4.3. PLS-SEM
4.4. PLSpredict
4.5. Multigroup Analysis
4.6. IPMA
5. Discussion and Implications
6. Limitations and Recommendations
7. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A
- Questionnaire Items
Knowledge Sharing (KS) | |
KS1 | I often share new working skills with my colleagues. |
KS2 | Our colleagues often share the new working skills that they learn. |
KS3 | Sharing knowledge with colleagues is regarded as something normal. |
KS4 | Our colleagues often share their work experiences. |
KS5 | I often share my job experiences with colleagues when they ask. |
KS6 | Our organization’s staff often exchanges knowledge of working skills and information. |
KS7 | Our colleagues often share the new information that they acquire. |
Employee Mobility (EM) | |
EM1 | My organization prioritizes the movement of its potential employees. |
EM2 | My organization has a clearly articulated employee mobility process. |
EM3 | My organization allows for vertical moves (taking a higher-level role). |
EM4 | My organization allows for lateral moves (taking on a new role at the same level). |
EM5 | My organization has a relocation policy (moving to another geographical office). |
EM6 | My organization has enrichment activities (growing in place—e.g., taking on new assignments/tasks). |
Training and Development (TD) | |
TD1 | Our company spends enough money and time on related training programs. |
TD2 | Within my organization, I receive training to develop my problem-solving skills. |
TD3 | Within my organization, leadership skills development training is provided. |
TD4 | With training, I am skillful in understanding the organizational work policy. |
TD5 | Through training, I am able to make any group decision. |
Psychological Empowerment (PE) | |
PE1 | The work I do is very important to me. |
PE2 | My job activities are personally meaningful to me. |
PE3 | The work I do is meaningful to me. |
PE4 | I am confident about my ability to do my job. |
PE5 | I am self-assured about my capabilities to perform my work activities. |
PE6 | I have mastered the skills necessary for my job. |
PE7 | I have significant autonomy in determining how I do my job. |
PE8 | I can decide on my own how to go about doing my work. |
PE9 | I have considerable opportunities for independence and freedom in how I do my job. |
PE10 | My impact on what happens in my department is large. |
PE11 | I have a great deal of control over what happens in my department. |
PE12 | I have significant influence over what happens in my department. |
Employee Engagement (EE) | |
EE1 | At work, I am bursting with energy. |
EE2 | At my job, I feel strong and vigorous. |
EE3 | I am enthusiastic about my job. |
EE4 | My job inspires me. |
EE5 | When I get up in the morning, I feel like going to work. |
EE6 | I feel happy when I am working intensely. |
EE7 | I am proud of the work that I do. |
EE8 | I am immersed in my work. |
EE9 | I get carried away when I am working |
References
- Meske, C.; Junglas, I. Investigating the elicitation of employees’ support towards digital workplace transformation. Behav. Inf. Technol. 2020, 40, 1120–1136. [Google Scholar] [CrossRef]
- Ahmed, W.; Hizam, S.M.; Sentosa, I. Digital Dexterity: Employee as Consumer Approach towards Organizational Success. Hum. Resour. Dev. Int. 2020, 25, 631–641. [Google Scholar] [CrossRef]
- Singh, A.; Hess, T. How chief digital officers promote the digital transformation of their companies. MIS Q. Exec. 2017, 16, 1–17. [Google Scholar] [CrossRef]
- Gartner. Executive Guidance: Digital Dexterity at Work; Gartner: Stamford, CT, USA, 2018; pp. 1–29. Available online: https://www.gartner.com/en/executive-guidance/digital-dexterity (accessed on 9 February 2023).
- Saran, C. Study Reveals Employees’ Fears over Digital Change. 2017. Available online: https://www.computerweekly.com/news/450429100/Study-reveals-employees-fears-over-digital-change (accessed on 9 February 2023).
- Mittal, R.; Pankaj, P.; Aggarwal, S.; Kaul, A. Evaluation of Adoption of Blockchain Technology for Supply Chain Management: A Case of Indian MSME. In Soft Computing for Problem Solving; Springer: Singapore, 2021; pp. 621–633. [Google Scholar]
- Winasis, S.; Djumarno; Riyanto, S.; Ariyanto, E. Digital Transformation in the Indonesian Banking Industry: Impact on Employee Engagement. Int. J. Innov. Creat. Chang. 2020, 12, 528–543. [Google Scholar]
- Vardarlier, P.; Ozsahin, M. Digital Transformation of Human Resource Management: Social Media’s Performance Effect. Int. J. Innov. Technol. Manag. 2021, 18, 2150005. [Google Scholar] [CrossRef]
- Ulas, D. Digital Transformation Process and SMEs. Procedia Comput. Sci. 2019, 158, 662–671. [Google Scholar] [CrossRef]
- Katiliūtė, E.; Stankevičiūtė, Ž.; Daunorienė, A. The Role of Non-academic Staff in Designing the Green University Campus. In Handbook of Theory and Practice of Sustainable Development in Higher Education; Springer: Berlin/Heidelberg, Germany, 2017; pp. 49–61. [Google Scholar]
- Mugizi, W.; Odetha Katuramu, A.; Ogaga Dafiewhare, A.; Kanyesigye, J. Rewards and Work Engagement of Non-Academic Staff: A Case of a Public University in Uganda. East Afr. J. Educ. Soc. Sci. 2020, 1, 79–88. [Google Scholar] [CrossRef]
- Baltaru, R.-D. Do non-academic professionals enhance universities’ performance? Reputation vs. organisation. Stud. High. Educ. 2019, 44, 1183–1196. [Google Scholar] [CrossRef]
- Nkechi, P.A.J.; Dialoke, I. Effects of Career Growth on Employees Performance: A Study of Non-Academic Staff of Michael Okpara University of Agriculture Umudike Abia State, Nigeria. World J. Entrep. Dev. Stud. 2017, 5, 8–18. [Google Scholar] [CrossRef]
- Alias, N.E. Employee Satisfaction in Higher Education: A Malaysian Case Study among Non-Academic Staff. Acad. J. Bus. Soc. Sci. 2017, 1, 1–14. Available online: http://ir.uitm.edu.my/id/eprint/29964/ (accessed on 9 February 2023).
- Nasidi, Y.; Makera, A.U.; Kamaruddeen, A.M.; Jemaku, I.M. Assessing the Impact of Work Environment on Employee Engagement among Non-Academic Staff of the University. SEISENSE J. Manag. 2019, 2, 57–68. [Google Scholar] [CrossRef]
- Juan, S.H.; Yao, L.; Tamyez, P.F.B.M.; Ayodele, F.O. Review on Knowledge Management and Employee Engagement. In Proceedings of the National Conference for Postgraduate Research 2016, Pahang, Malaysia, 24–25 September 2016; pp. 127–134. [Google Scholar]
- Garfield, S. Employee Engagement in the Digital Workplace. In Proceedings of the Uropean SharePoint, Office 365 & Azure Conference, Prague, Czech Republic, 18 November 2016. [Google Scholar]
- Tran, K. Maximising Employee Training and Development in the Digital Workplace; TRG International: Ho Chi Minh City, Vietnam, 2018. [Google Scholar]
- Hamburg, I. Implementation of a Digital Workplace Strategy to Drive Behavior Change and Improve Competencies. In Strategy and Behaviors in the Digital Economy; Orlando, B., Ed.; IntechOpen: London, UK, 2019; pp. 1–16. [Google Scholar]
- Aldabbas, H.; Pinnington, A.; Lahrech, A. The mediating role of psychological empowerment in the relationship between knowledge sharing and innovative work behaviour. Int. J. Innov. Manag. 2020, 25, 21500146. [Google Scholar] [CrossRef]
- Chernyak-Hai, L.; Rabenu, E. The New Era Workplace Relationships: Is Social Exchange Theory Still Relevant? Ind. Organ. Psychol. 2018, 11, 456–481. [Google Scholar] [CrossRef]
- Olubunmi, F.; Samuel, O.; Babalola, O. Factors influencing knowledge sharing among information and communication technology artisans in Nigeria. J. Syst. Inf. Technol. 2016, 18, 148–169. [Google Scholar] [CrossRef]
- Rehman, W.U.; Ahmad, M.; Allen, M.M.C.; Raziq, M.M.; Riaz, A. High involvement HR systems and innovative work behaviour: The mediating role of psychological empowerment, and the moderating roles of manager and co-worker support. Eur. J. Work Organ. Psychol. 2019, 28, 525–535. [Google Scholar] [CrossRef]
- Attaran, M.; Attaran, S.; Kirkland, D. The need for digital workplace: Increasing workforce productivity in the information age. Int. J. Enterp. Inf. Syst. 2019, 15, 1–23. [Google Scholar] [CrossRef]
- Dery, K.; Sebastian, I.M.; Meulen, N. van der The digital workplace is key to digital innovation. MIS Q. Exec. 2017, 16, 135–152. [Google Scholar]
- Rahman, M.S.; Daud, N.M.; Hassan, H. Generation “X” and “Y” knowledge sharing behaviour: The influence of motivation and intention on non-academic staff of higher learning institutions. J. Appl. Res. High. Educ. 2017, 9, 325–342. [Google Scholar] [CrossRef]
- Eccarius, T.; Lu, C.C. Adoption intentions for micro-mobility—Insights from electric scooter sharing in Taiwan. Transp. Res. Part D Transp. Environ. 2020, 84, 102327. [Google Scholar] [CrossRef]
- Ahmed, W. Understanding self-directed learning behavior towards digital competence among business research students: SEM-neural analysis. Educ. Inf. Technol. 2022. [Google Scholar] [CrossRef]
- Saks, A.M. Antecedents and consequence of work engagement. J. Manag. Psychol. 2006, 21, 600–619. [Google Scholar] [CrossRef]
- Koon, V.Y.; Chong, K.N. Workplace flexibility and organisational citizenship behaviour: An investigation of the mediating role of engagement and moderating role of perceived fairness. Int. J. Work. Organ. Emot. 2018, 9, 45–62. [Google Scholar] [CrossRef]
- Lai, P.; Lee, J.; Lim, Y.; Yeoh, R.; Mohsin, F.H. The Linkage between Training and Development and Co-Worker Support towards Employee Engagement in Hotel Industry. Int. J. Sci. Res. Publ. 2015, 5, 1–8. [Google Scholar]
- Maan, A.T.; Abid, G.; Butt, T.H.; Ashfaq, F.; Ahmed, S. Perceived organizational support and job satisfaction: A moderated mediation model of proactive personality and psychological empowerment. Future Bus. J. 2020, 6, 21. [Google Scholar] [CrossRef]
- Cropanzano, R.; Anthony, E.L.; Daniels, S.R.; Hall, A.V. Social Exchange Theory: A Critical Review with Theoretical Remedies. Acad. Manag. Ann. 2017, 11, 479–516. [Google Scholar] [CrossRef]
- Wu, W.-L.; Lee, Y.-C. Empowering group leaders encourages knowledge sharing: Integrating the social exchange theory and positive organizational behavior perspective. J. Knowl. Manag. 2017, 21, 474–491. [Google Scholar] [CrossRef]
- Aktar, A.; Pangil, F. Mediating role of organizational commitment in the relationship between human resource management practices and employee engagement: Does black box stage exist? Int. J. Sociol. Soc. Policy 2018, 38, 606–636. [Google Scholar] [CrossRef]
- Göçer, Ö.; Göçer, K.; Karahan, E.E.; Oygür, I.İ. Exploring mobility & workplace choice in a flexible office through post-occupancy evaluation. Ergonomics 2018, 61, 226–242. [Google Scholar] [CrossRef]
- Arefin, M.S.; Alam, M.S.; Islam, M.R.; Rahaman, M. High-performance work systems and job engagement: The mediating role of psychological empowerment. Cogent Bus. Manag. 2019, 6, 1664204. [Google Scholar] [CrossRef]
- Meira, J.V.d.S.; Hancer, M. Using the social exchange theory to explore the employee- organization relationship in the hospitality industry. Int. J. Contemp. Hosp. Manag. 2021, 33, 670–692. [Google Scholar] [CrossRef]
- Ahmad, F. Knowledge sharing in a non-native language context: Challenges and strategies. J. Inf. Sci. 2018, 44, 248–264. [Google Scholar] [CrossRef]
- Li, J.; Herd, A.M. Shifting practices in digital workplace learning: An integrated approach to learning, knowledge management, and knowledge sharing. Hum. Resour. Dev. Int. 2017, 20, 185–193. [Google Scholar] [CrossRef]
- Juan, S.H.; Ting, I.W.K.; Kweh, Q.L.; Yao, L. How does knowledge sharing affect employee engagement? Inst. Econ. 2018, 10, 49–67. [Google Scholar]
- Al-Jabri, I.M. Investigating the mediating role of knowledge sharing on employee engagement: Evidence from a developing nation. Int. J. Hum. Cap. Inf. Technol. Prof. 2020, 11, 47–63. [Google Scholar] [CrossRef]
- Shah, M. Employee Mobility: Is It Beneficial for Your Business; TechFunnel: Frisco, TX, USA, 2018. [Google Scholar]
- Rajagopal, A. Relationship between Employee Mobility and Organizational Creativity to Improve Organizational Performance: A Strategic Analysis. In Business Governance and Society; Rajagopal, B.R., Ed.; Palgrave Macmillan: Cham, Switzerland, 2019; pp. 237–250. [Google Scholar]
- De Kok, A.; Lubbers, Y.; Helms, R.W. Mobility and security in the new way of working: Employee satisfaction in a Choose Your Own Device (CYOD) environment. In Proceedings of the Ninth Mediterranean Conference on Information Systems (MCIS), Samos, Greece, 2–5 October 2015; pp. 1–20. [Google Scholar]
- Edwards, R.G. How Mobile Technology is Transforming Workplace Performance How Mobile Technology is Transfoming Workplace Performance; Nudge Rewards Inc.: Toronto, ON, Canada, 2017. [Google Scholar]
- Azeem, M.F.; Rubina; Paracha, A.T. Connecting training and development with employee engagement: How does it matter? World Appl. Sci. J. 2013, 28, 696–703. [Google Scholar] [CrossRef]
- DeCenzo, D.A.; Robbins, S.P.; Verhulst, S.L. Human Resource Management, 11th ed.; International Student Version; John Wiley & Sons, Inc.: Hoboken, NJ, USA, 2013. [Google Scholar]
- ICTC. Digital Talent Road to 2020 and Beyond: A National Strategy to Develop Canada’s Talent in a Global Digital Economy; ICTC: Muskogee, OK, USA, 2016. [Google Scholar]
- Golubenko, S. How Digital Transformation Refashions Employee Training and Development. 2018. Available online: https://www.scnsoft.com/blog/digital-transformation-of-employee-training-development (accessed on 9 February 2023).
- Khan, A.J.; Iqbal, J. Training and Employee Commitment: The Social Exchange Perspective. J. Manag. Sci. 2020, 7, 88–100. [Google Scholar] [CrossRef]
- Spreitzer, G.M. Psychological empowerment in the workplace: Dimensions, measurement, and validation. Acad. Manag. J. 1995, 38, 1442–1465. [Google Scholar] [CrossRef]
- Meng, Q.; Sun, F. The impact of psychological empowerment on work engagement among university faculty members in China. Psychol. Res. Behav. Manag. 2019, 12, 983–990. [Google Scholar] [CrossRef]
- Owan, V.J.; Bassey, B.A.; Mbon, U.F.; Okon, A.E.; Egbula, E.O.; Ekaette, S.O.; Ojong, C.O.; Ekpe, M.B. Validation of an Instrument and Measurement of Employee Work-Life Policies, Psychological Empowerment, and Job Commitment of Academic Staff in Universities. Mediterr. J. Soc. Sci. 2020, 11, 86–100. [Google Scholar] [CrossRef]
- Helmy, I.; Adawiyah, W.R.; Banani, A. Linking Psychological Empowerment, Knowledge Sharing, and Employees’ Innovative Behavior in SMEs. J. Behav. Sci. 2019, 14, 66–79. [Google Scholar]
- Saunders, M.N.K.; Lewis, P.; Thornhill, A. Research Methods for Business Students, 8th ed.; Pearson: London, UK, 2019. [Google Scholar]
- Stratton, S.J. Population Research: Convenience Sampling Strategies. Prehosp. Disaster Med. 2021, 36, 373–374. [Google Scholar] [CrossRef] [PubMed]
- Sekaran, U.; Bougie, R. Research Methods for Business: A Skill Building Approach, 7th ed.; Wiley: New York, NY, USA, 2016. [Google Scholar]
- Kline, R.B. Principles and Practice of Structural Equation Modeling, 3rd ed.; The Guilford Press: New York, NY, USA, 2011. [Google Scholar]
- i4cp. 2015 Talent Mobility Survey; i4cp: Washington, DC, USA, 2015. [Google Scholar]
- Edgar, F.; Geare, A. HRM practice and employee attitudes: Different measures—Different results. Pers. Rev. 2005, 34, 534–549. [Google Scholar] [CrossRef]
- Siddiqui, D.A.; Noor-us-Sahar. The Impact of Training & Development and Communication on Employee Engagement—A Study of Banking Sector. Bus. Manag. Strateg. 2019, 10, 23–40. [Google Scholar] [CrossRef]
- Schaufeli, W.B.; Bakker, A.B.; Salanova, M. The Measurement of Work Engagement with a Short Questionnaire—A Cross-National Study. Educ. Psychol. Meas. 2006, 66, 701–716. [Google Scholar] [CrossRef]
- Sarstedt, M.; Ringle, C.M.; Hair, J.F. Partial Least Squares Structural Equation Modeling. In Handbook of Market Research; Springer International Publishing: Cham, Switzerland, 2021; pp. 1–47. [Google Scholar]
- Larasati, O.; Dirgahayani, P. Importance-Performance Matrix Analysis (IPMA) Of Transport Disadvantage Variables on Social Exclusion in a Rural Context. IOP Conf. Ser. Earth Environ. Sci. 2018, 158, 012015. [Google Scholar] [CrossRef]
- Albort-Morant, G.; Sanchís-Pedregosa, C.; Paredes Paredes, J.R. Online banking adoption in Spanish cities and towns. Finding differences through TAM application. Econ. Res. Istraz. 2022, 35, 854–872. [Google Scholar] [CrossRef]
- Hair, J.F.; Risher, J.J.; Sarstedt, M.; Ringle, C.M. When to use and how to report the results of PLS-SEM. Eur. Bus. Rev. 2019, 31, 2–24. [Google Scholar] [CrossRef]
- Roy, S.K.; Balaji, M.S.; Quazi, A.; Quaddus, M. Predictors of customer acceptance of and resistance to smart technologies in the retail sector. J. Retail. Consum. Serv. 2018, 42, 147–160. [Google Scholar] [CrossRef]
- Jarvis, C.B.; MacKenzie, S.B.; Podsakoff, P.M. A Critical Review of Construct Indicators and Measurement Model Misspecification in Marketing and Consumer Research. J. Consum. Res. 2003, 30, 199–218. [Google Scholar] [CrossRef]
- Podsakoff, P.M.; MacKenzie, S.B.; Lee, J.Y.; Podsakoff, N.P. Common Method Biases in Behavioral Research: A Critical Review of the Literature and Recommended Remedies. J. Appl. Psychol. 2003, 88, 879–903. [Google Scholar] [CrossRef]
- Soelton, M.; Noermijati, N.; Rohman, F.; Mugiono, M.; Aulia, I.N.; Siregar, R.E. Reawakening perceived person organization fit and perceived person job fit: Removing obstacles organizational commitment. Manag. Sci. Lett. 2020, 10, 2993–3002. [Google Scholar] [CrossRef]
- Henseler, J.; Ringle, C.M.; Sarstedt, M. A new criterion for assessing discriminant validity in variance-based structural equation modeling. J. Acad. Mark. Sci. 2015, 43, 115–135. [Google Scholar] [CrossRef]
- Henseler, J.; Hubona, G.; Ray, P.A. Using PLS path modeling in new technology research: Updated guidelines. Ind. Manag. Data Syst. 2016, 116, 2–20. [Google Scholar] [CrossRef]
- Ning, Y.; Yan, M.; Xu, S.X.; Li, Y.; Li, L. Shared parking acceptance under perceived network externality and risks: Theory and evidence. Transp. Res. Part A Policy Pract. 2021, 150, 1–15. [Google Scholar] [CrossRef]
- Hair, J.F.; Hult, G.T.M.; Ringle, C.M.; Sarstedt, M.; Danks, N.P.; Ray, S. Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R: A Workbook; Springer Nature: Cham, Switzerland, 2021. [Google Scholar]
- Shmueli, G.; Ray, S.; Velasquez Estrada, J.M.; Chatla, S.B. The elephant in the room: Predictive performance of PLS models. J. Bus. Res. 2016, 69, 4552–4564. [Google Scholar] [CrossRef]
- Shmueli, G.; Sarstedt, M.; Hair, J.F.; Cheah, J.H.; Ting, H.; Vaithilingam, S.; Ringle, C.M. Predictive model assessment in PLS-SEM: Guidelines for using PLSpredict. Eur. J. Mark. 2019, 53, 2322–2347. [Google Scholar] [CrossRef]
- Cheah, J.-H.; Thurasamy, R.; Memon, M.A.; Chuah, F.; Ting, H. Multigroup Analysis using SmartPLS: Step-by-Step Guidelines for Business Research. Asian J. Bus. Res. 2020, 10, I–XIX. [Google Scholar] [CrossRef]
- Sarstedt, M.; Henseler, J.; Ringle, C.M. Multigroup Analysis in Partial Least Squares (PLS) Path Modeling: Alternative Methods and Empirical Results. In Measurement and Research Methods in International Marketing; Emerald Group Publishing Limited: Bingley, UK, 2011; pp. 195–218. [Google Scholar]
- Jamal, T.; Zahid, M.; Martins, J.M.; Mata, M.N.; Rahman, H.U.; Mata, P.N. Perceived Green Human Resource Management Practices and Corporate Sustainability: Multigroup Analysis and Major Industries Perspectives. Sustainability 2021, 13, 3045. [Google Scholar] [CrossRef]
- Tensay, A.T.; Singh, M. The nexus between HRM, employee engagement and organizational performance of federal public service organizations in Ethiopia. Heliyon 2020, 6, e04094. [Google Scholar] [CrossRef]
- Jose, G.; Mampilly, S.R. Psychological Empowerment as a Predictor of Employee Engagement: An Empirical Attestation. Glob. Bus. Rev. 2014, 15, 93–104. [Google Scholar] [CrossRef]
- Attaran, M.; Attaran, S.; Kirkland, D. Technology and Organizational Change: Harnessing the Power of Digital Workplace. In Handbook of Research on Social and Organizational Dynamics in the Digital Era; Idemudia, E., Ed.; IGI Global: Hershey, PA, USA, 2020; pp. 383–408. [Google Scholar]
- Grosseck, G.; Malita, L.; Bunoiu, M. Higher Education Institutions Towards Digital Transformation—The WUT Case. In European Higher Education Area: Challenges for a New Decade; Curaj, A., Deca, L., Pricopie, R., Eds.; Springer: Cham, Switzerland, 2020; pp. 565–581. [Google Scholar]
- Lanzara, G.F. Shifting Practices: Reflections on Technology, Practice, and Innovation; MIT Press: Cambridge, MA, USA, 2016. [Google Scholar]
- Ilyasa; Madhakomala; Ramly, M. The Effect of Organization Culture, Knowledge Sharing and Employee Engagement on Employee Work Innovation. Int. J. Sci. Res. Manag. 2018, 6, 57–63. [Google Scholar] [CrossRef]
- Hughes, C.; Robert, L.; Frady, K.; Arroyos, A. Managing People and Technology in the Workplace. In Managing Technology and Middle- and Low-Skilled Employees; Emerald Publishing Limited: Bingley, UK, 2019; pp. 91–101. [Google Scholar]
- Benavides, L.M.C.; Arias, J.A.T.; Serna, M.D.A.; Bedoya, J.W.B.; Burgos, D. Digital transformation in higher education institutions: A systematic literature review. Sensors 2020, 20, 3291. [Google Scholar] [CrossRef] [PubMed]
- Kley, S. The Impact of Job-Related Mobility and Migration Intentions on Union Dissolution. In Spatial Mobility, Migration, and Living Arrangements; Aybek, C., Huinink, J., Muttarak, R., Eds.; Springer: Cham, Switzerland, 2015; pp. 139–158. [Google Scholar]
- Kynčlová, P.; Upadhyaya, S.; Nice, T. Composite index as a measure on achieving Sustainable Development Goal 9 (SDG-9) industry-related targets: The SDG-9 index. Appl. Energy 2020, 265, 114755. [Google Scholar] [CrossRef]
- Shamim, S.; Cang, S.; Yu, H. Impact of knowledge oriented leadership on knowledge management behaviour through employee work attitudes. Int. J. Hum. Resour. Manag. 2019, 30, 2387–2417. [Google Scholar] [CrossRef]
Respondents’ Profile | N | % | Respondents’ Profile | N | % |
---|---|---|---|---|---|
Gender: | Tenure: | ||||
Male | 118 | 58 | <1 year | 7 | 3 |
Female | 87 | 42 | 1–5 years | 67 | 33 |
Age: | 6–10 years | 110 | 54 | ||
20–25 | 12 | 6 | >10 years | 21 | 10 |
26–30 | 27 | 13 | Job level: | ||
31–35 | 96 | 47 | 49 | 24 | |
36–40 | 65 | 32 | Senior Officer | 71 | 35 |
>40 | 5 | 2 | Middle Manager | 52 | 25 |
Race: | Manager | 33 | 16 | ||
Malay | 107 | 52 | Department | ||
Chinese | 57 | 28 | Admission | 52 | 25 |
India | 26 | 13 | IT | 79 | 39 |
Others | 15 | 7 | Finance | 34 | 17 |
Education: | HR | 21 | 10 | ||
Diploma | 13 | 6 | Marketing | 19 | 9 |
Bachelor | 157 | 77 | |||
Master’s/Others | 35 | 17 |
Construct | Items | α | CR | AVE | Outer Loadings | VIF | HTMT Ratio | ||||
---|---|---|---|---|---|---|---|---|---|---|---|
EE | EM | KS | PE | TD | |||||||
Employee Engagement (EE) | EE1 | 0.908 | 0.925 | 0.579 | 0.761 | 2.031 | |||||
EE2 | 0.730 | 1.934 | |||||||||
EE3 | 0.781 | 2.356 | |||||||||
EE4 | 0.790 | 2.308 | |||||||||
EE5 | 0.811 | 2.409 | |||||||||
EE6 | 0.831 | 2.855 | |||||||||
EE7 | 0.701 | 1.715 | |||||||||
EE8 | 0.707 | 2.089 | |||||||||
EE9 | 0.723 | 1.945 | |||||||||
Employee Mobility (EM) | EM1 | 0.895 | 0.920 | 0.656 | 0.837 | 2.553 | 0.843 | ||||
EM2 | 0.827 | 2.364 | |||||||||
EM3 | 0.782 | 1.957 | |||||||||
EM4 | 0.803 | 2.079 | |||||||||
EM5 | 0.822 | 2.363 | |||||||||
EM6 | 0.787 | 1.953 | |||||||||
Knowledge Sharing (KS) | KS1 | 0.864 | 0.896 | 0.554 | 0.703 | 1.801 | 0.853 | 0.804 | |||
KS2 | 0.787 | 2.026 | |||||||||
KS3 | 0.805 | 2.253 | |||||||||
KS4 | 0.730 | 1.706 | |||||||||
KS5 | 0.785 | 1.998 | |||||||||
KS6 | 0.752 | 1.781 | |||||||||
KS7 | 0.633 | 1.375 | |||||||||
Psychological Empowerment (PE) | PE1 | 0.922 | 0.933 | 0.540 | 0.770 | 2.504 | 0.665 | 0.566 | 0.633 | ||
PE2 | 0.734 | 2.349 | |||||||||
PE3 | 0.766 | 2.340 | |||||||||
PE4 | 0.760 | 2.816 | |||||||||
PE5 | 0.686 | 2.007 | |||||||||
PE6 | 0.709 | 2.154 | |||||||||
PE7 | 0.762 | 2.446 | |||||||||
PE8 | 0.721 | 2.219 | |||||||||
PE9 | 0.747 | 2.294 | |||||||||
PE10 | 0.625 | 1.644 | |||||||||
PE11 | 0.750 | 2.354 | |||||||||
PE12 | 0.772 | 2.537 | |||||||||
Training and Development (TD) | TD1 | 0.881 | 0.913 | 0.677 | 0.793 | 1.864 | 0.648 | 0.583 | 0.596 | 0.461 | |
TD2 | 0.844 | 2.352 | |||||||||
TD3 | 0.827 | 2.177 | |||||||||
TD4 | 0.824 | 2.069 | |||||||||
TD5 | 0.827 | 2.238 |
Hypothesis | Path | f2 | β | T-Statistics | p-Value | Result |
---|---|---|---|---|---|---|
H1 | KS → EE | 0.118 | 0.260 | 3.705 | 0.000 | Accepted |
H2 | EM → EE | 0.424 | 0.475 | 6.312 | 0.000 | Accepted |
H3 | TD → EE | 0.047 | 0.131 | 2.827 | 0.005 | Accepted |
H4 | PE → EE | 0.070 | 0.164 | 2.723 | 0.007 | Accepted |
Endogenous Variable | R2 | R2 Adjusted | ||||
EE | 0.758 | 0.753 |
Items | PLS | LM | PLS-LM | ||||||
---|---|---|---|---|---|---|---|---|---|
RMSE | MAE | Q2_predict | RMSE | MAE | Q2_predict | RMSE | MAE | Q2_predict | |
EE1 | 0.551 | 0.445 | 0.391 | 0.6 | 0.477 | 0.278 | −0.049 | −0.032 | 0.113 |
EE2 | 0.579 | 0.44 | 0.387 | 0.617 | 0.481 | 0.304 | −0.038 | −0.041 | 0.083 |
EE3 | 0.555 | 0.446 | 0.431 | 0.599 | 0.479 | 0.337 | −0.044 | −0.033 | 0.094 |
EE4 | 0.565 | 0.46 | 0.437 | 0.604 | 0.479 | 0.355 | −0.039 | −0.019 | 0.082 |
EE5 | 0.583 | 0.462 | 0.421 | 0.635 | 0.507 | 0.314 | −0.052 | −0.045 | 0.107 |
EE6 | 0.561 | 0.458 | 0.483 | 0.604 | 0.481 | 0.401 | −0.043 | −0.023 | 0.082 |
EE7 | 0.627 | 0.504 | 0.411 | 0.691 | 0.534 | 0.284 | −0.064 | −0.03 | 0.127 |
EE8 | 0.611 | 0.514 | 0.398 | 0.677 | 0.556 | 0.261 | −0.066 | −0.042 | 0.137 |
EE9 | 0.603 | 0.498 | 0.443 | 0.648 | 0.524 | 0.358 | −0.045 | −0.026 | 0.085 |
IT–Admission | Path Coefficients-Diff (IT-Admission) | p-Value Original 1-Tailed (IT vs. Admission) | p-Value New (IT vs. Admission) | p-Value (Parametric Test) | p-Value (Welch-Satterthwait Test) |
EM → EE | 0.201 | 0.071 | 0.071 | 0.080 | 0.067 |
KS → EE | −0.311 | 0.995 | 0.005 | 0.008 | 0.005 |
PE → EE | −0.050 | 0.649 | 0.351 | 0.371 | 0.360 |
TD → EE | 0.052 | 0.327 | 0.327 | 0.331 | 0.329 |
IT–Finance | Path Coefficients-diff (IT-Finance) | p-Value Original 1-tailed (IT vs. Finance) | p-Value New (IT vs. Finance) | p-Value (Parametric Test) | p-Value (Welch-Satterthwait Test) |
EM → EE | 0.500 | 0.011 | 0.011 | 0.008 | 0.019 |
KS → EE | −0.263 | 0.905 | 0.095 | 0.070 | 0.085 |
PE → EE | −0.180 | 0.868 | 0.132 | 0.164 | 0.134 |
TD → EE | −0.189 | 0.947 | 0.053 | 0.075 | 0.057 |
IT–HR | Path Coefficients-diff (IT-HR) | p-Value Original 1-Tailed (IT vs. HR) | p-Value New (IT vs. HR) | p-Value (Parametric Test) | p-Value (Welch-Satterthwait Test) |
EM → EE | −0.001 | 0.502 | 0.498 | 0.499 | 0.498 |
KS → EE | −0.182 | 0.880 | 0.120 | 0.171 | 0.125 |
PE → EE | 0.024 | 0.420 | 0.420 | 0.457 | 0.444 |
TD → EE | 0.070 | 0.293 | 0.293 | 0.330 | 0.294 |
IT–Marketing | Path Coefficients-diff (IT-Marketing) | p-Value Original 1-Tailed (IT vs. Marketing) | p-Value New (IT vs. Marketing) | p-Value (Parametric Test) | p-Value (Welch-Satterthwait Test) |
EM → EE | 0.548 | 0.033 | 0.033 | 0.012 | 0.025 |
KS → EE | −0.388 | 0.839 | 0.161 | 0.072 | 0.167 |
PE → EE | −0.237 | 0.778 | 0.222 | 0.178 | 0.208 |
TD → EE | 0.023 | 0.440 | 0.440 | 0.449 | 0.452 |
Particulars | IPMA Factors | EM | KS | PE | TD | Average Values |
---|---|---|---|---|---|---|
All Departments | Importance | 0.4525 | 0.2450 | 0.1768 | 0.1159 | 0.2475 |
Performances | 70.082 | 67.924 | 75.837 | 69.827 | 70.9173 | |
Placement | Q2 | Q4 | Q3 | Q4 | ||
IT | Importance | 0.593 | 0.067 | 0.114 | 0.120 | 0.223 |
Performances | 68.731 | 67.079 | 76.146 | 67.811 | 69.942 | |
Placement | Q2 | Q4 | Q3 | Q4 | ||
Admission | Importance | 0.391 | 0.381 | 0.172 | 0.114 | 0.265 |
Performances | 73.954 | 69.142 | 78.799 | 72.311 | 73.552 | |
Placement | Q1 | Q2 | Q3 | Q4 | ||
Finance | Importance | 0.142 | 0.307 | 0.346 | 0.363 | 0.289 |
Performances | 70.685 | 68.377 | 75.991 | 74.229 | 72.320 | |
Placement | Q4 | Q2 | Q1 | Q1 | ||
HR | Importance | 0.610 | 0.239 | 0.083 | 0.079 | 0.253 |
Performances | 66.808 | 68.620 | 73.977 | 67.193 | 69.149 | |
Placement | Q2 | Q4 | Q3 | Q4 | ||
Marketing | Importance | 0.073 | 0.414 | 0.316 | 0.114 | 0.229 |
Performances | 67.308 | 64.901 | 68.591 | 68.373 | 67.293 | |
Placement | Q3 | Q2 | Q1 | Q4 |
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Hizam, S.M.; Akter, H.; Sentosa, I.; Ahmed, W.; Masrek, M.N.; Ali, J. Predicting Workforce Engagement towards Digital Transformation through a Multi-Analytical Approach. Sustainability 2023, 15, 6835. https://doi.org/10.3390/su15086835
Hizam SM, Akter H, Sentosa I, Ahmed W, Masrek MN, Ali J. Predicting Workforce Engagement towards Digital Transformation through a Multi-Analytical Approach. Sustainability. 2023; 15(8):6835. https://doi.org/10.3390/su15086835
Chicago/Turabian StyleHizam, Sheikh Muhamad, Habiba Akter, Ilham Sentosa, Waqas Ahmed, Mohamad Noorman Masrek, and Jawad Ali. 2023. "Predicting Workforce Engagement towards Digital Transformation through a Multi-Analytical Approach" Sustainability 15, no. 8: 6835. https://doi.org/10.3390/su15086835
APA StyleHizam, S. M., Akter, H., Sentosa, I., Ahmed, W., Masrek, M. N., & Ali, J. (2023). Predicting Workforce Engagement towards Digital Transformation through a Multi-Analytical Approach. Sustainability, 15(8), 6835. https://doi.org/10.3390/su15086835