Enablers of workforce agility in engineering educational institutions

Abstract

PurposeThe purpose of this paper is to explore and encapsulate the enablers that can facilitate agility in faculty members of engineering institutions. The paper also aims to conduct a prelim qualitative validation of the enablers and analyze the interplay between them using the total interpretive structural modeling (TISM) approach.Design/methodology/approachThe study adopted the TISM approach to comprehend the interactions and transitivity between the enablers. Cross-impact multiplication matrix (MICMAC) analysis was applied to rank the enablers and classify them on the basis of the driving and dependence power into dependent, autonomous, independent and linkage enablers.FindingsExtensive literature review and expert opinion helped identify 16 enablers that can promote workforce agility. The results indicate “management support” as the most crucial enabler. Rewards and recognition and employee empowerment were among the other enablers that have a high driving force. New capabilities, learning and innovation and the expanding role of faculty members were found to have high dependence power, which makes the enablers dependent on other enablers for activation.Practical implicationsThe results of this study would assist the management of engineering colleges and universities to design, adopt and implement policies and practices that would facilitate agility in faculty members. Faculty members shoulder the responsibility of molding the future generation, and hence, it is important that they are competent enough to impart quality education. The policymakers should focus on policies and practices that leverage human resource potential and support an innovative climate that nurtures entrepreneurial activities in engineering institutions.Originality/valueSo far research on workforce agility has predominantly focused on the manufacturing sector. Despite the workforce (refers to faculty members here) being crucial in contributing to the progress of universities and colleges, very little work is done on how faculty members can be made agile. Application of the TISM method in identifying the variables that can facilitate faculty members' agility in engineering institutions in India is a new and original contribution to the literature on workforce agility.

A study on the influential factors of the last mile delivery projects during Covid-19 era

“… Interpretation of relationship between factors: how factor-A influences factor-B (Patil and Suresh 2019 ). Developing the final reachability matrix (FRM): the FRM has been derived through transitivity check (Menon and Suresh 2021b ) as shown in Table 3 . Partition of the factors from FRM into levels (Suresh and Arun Ram Nathan 2020 ) Designing the interaction matrix: the significat transitive links are identified through expert opinions and direct links are depicted in Table 4 .…”

“…Developing the final reachability matrix (FRM): the FRM has been derived through transitivity check (Menon and Suresh 2021b ) as shown in Table 3 .…”

Factors influencing organizational agility in higher education

“…Some of the studies that applied TISM, particularly in the manufacturing sector, involved the understanding of the interplay between the enablers in flexible manufacturing (Jain and Soni, 2019), sustainable manufacturing (Agrawal and Vinodh, 2019; Dwivedi et al , 2019), lean performance (Solke and Singh, 2018), agile manufacturing (Sindhwani and Malhotra, 2017) and leagile manufacturing (Chaple et al , 2018). Lately, TISM application has found grounding in supply chain management (Soda et al , 2018; Lamba and Singh, 2018), healthcare (Vaishnavi et al , 2019; Ajmera and Jain, 2019; Mishra and Satapathy, 2019; Patri and Suresh, 2017), telecommunication (Jena et al , 2016), aviation (Singh and Sushil, 2013), pharmaceutical (Wasuja et al , 2012) and higher education (Menon and Suresh, 2020; Kashiramka et al , 2019; Yeravdekar and Behl, 2017; Sehgal and Nasim, 2018; Voolaid and Ehrlich, 2017).…”

A study on the factors that influence the agility of COVID-19 hospitals

“…(3) Deriving Final Reachability Matrix (FRM): The transitivity analysis has been done on all the entries with '0' in the IRM [26,27]. If transitivity is exists replace the original value '0' and enter 1* or 1** or 1*** in FRM; otherwise '0' is retained in Table 3.…”