Skip to main content
SpringerLink
Log in

Modelling the Enablers of Workforce Agility in IoT Projects: A TISM Approach

  • Original Research
  • Published:
Global Journal of Flexible Systems Management Aims and scope Submit manuscript

Abstract

IoT projects can be categorized as high technology with an extremely dynamic product development lifecycle. To be a leader under such conditions, organizations need to focus priorities on achieving shorter product development cycle along with organization agility and workforce agility. Many researchers have tried to identify the enablers that affect workforce agility in different segments, but none has really looked into the IoT project environment. In this paper, efforts are taken to model the enablers of workforce agility in IoT projects and to understand the interrelationship among enablers using total interpretive structural modelling. The current study makes an attempt to provide a hierarchical structure representing the driving enablers and the dependent enablers and to give the order of enablers with respect to influence on workforce agility. Results indicate that employee proactivity, innovativeness, resiliency skills and ownership or self-motivation bring agility in the workforce. These enablers help employees to act in all decision-making situations to achieve IoT organization goals faster.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  • Abrahamsson, P., Conboy, K., & Wang, X. (2009). ‘Lots done, more to do’: the current state of agile systems development research. European Journal of Information Systems, 18(4), 281–284.

    Article  Google Scholar 

  • Agrawal, U., Mangla, A., & Sagar, M. (2016). Company-cause-customer: Interaction architecture. Global Journal of Flexible Systems Management, 17(3), 307–319.

    Article  Google Scholar 

  • Bag, S. (2017). Identification of green procurement drivers and their interrelationship using total interpretive structural modelling. The Journal of Business Perspective, 17(2), 129–142.

    Article  Google Scholar 

  • Balaji, M., & Arshinder, K. (2016). Modeling the causes of food wastage in Indian perishable food supply chain. Resources, Conservation and Recycling, 114, 153–167.

    Article  Google Scholar 

  • Breu, K., Hemingway, C. J., Strathern, M., & Bridger, D. (2002). Workforce agility: The new employee strategy for the knowledge economy. Journal of Information Technology, 17(1), 21–31.

    Article  Google Scholar 

  • Dubey, R., & Ali, S. S. (2014). Identification of flexible manufacturing system dimensions and their interrelationship using total interpretive structural modelling and fuzzy MICMAC analysis. Global Journal of Flexible Systems Management, 15(2), 131–143.

    Article  Google Scholar 

  • Dubey, R., Gunasekaran, A., Papadopoulos, T., Childe, S. J., Shibin, K. T., & Wamba, S. F. (2017). Sustainable supply chain management: Framework and further research directions. Journal of Cleaner Production, 142, 1119–1130.

    Article  Google Scholar 

  • Dyer, L., & Ericksen, J. (2006). Dynamic organizations: Achieving marketplace agility through workforce scalability. CAHRS Working Paper Series, 06-12.

  • Dyer, L., & Shafer, R. A. (1998). From human resource strategy to organizational effectiveness: Lessons from research on organizational agility. CAHRS working paper series, 125.

  • Dyer, L., & Shafer, R. A. (2003). Dynamic organizations: Achieving marketplace and organizational agility with people. CAHRS working paper series, 27.

  • Griffin, B., & Hesketh, B. (2003). Adaptable behaviours for successful work and career adjustment. Australian Journal of Psychology, 55(2), 65–73.

    Article  Google Scholar 

  • Gubbi, J., Buyya, R., Marusic, S., & Palaniswami, M. (2013). Internet of Things (IoT): A vision, architectural elements, and future directions. Future Generation Computer Systems, 29(7), 1645–1660.

    Article  Google Scholar 

  • Gunasekaran, A. (1998). Agile manufacturing: Enablers and an implementation framework. International Journal of Production Research, 36(5), 1223–1247.

    Article  Google Scholar 

  • Gunasekaran, A. (1999). Agile manufacturing: A framework for research and development. International Journal of Production Economics, 62(1), 87–105.

    Article  Google Scholar 

  • Gupta, V., Kapur, P. K., & Kumar, D. (2016). Modelling and measuring code smells in enterprise applications using TISM and two-way assessment. International Journal of System Assurance Engineering and Management, 7(3), 332–340.

    Article  Google Scholar 

  • Hosein, Z. Z. (2012). The role of emotional intelligence on workforce agility in the workplace. International Journal of Psychological Studies, 4(3), 48.

    Article  Google Scholar 

  • Isenberg, M.-A., Werthmann, D., Morales-Kluge, E., & Scholz-Reiter, B. (2011). The role of the Internet of Things for increased autonomy and agility in collaborative production environments. In Uckelmann, D., Harrison, M., & Michahelles, F. (Eds.) Architecturing the internet of things (pp. 195–228). Berlin: Springer. ISBN: 9783642191572.

    Chapter  Google Scholar 

  • Jayalakshmi, B., & Pramod, V. R. (2015). Total interpretive structural modelling (TISM) of the enablers of a flexible control system for industry. Global Journal of Flexible Systems Management, 16(1), 63–85.

    Article  Google Scholar 

  • Khatwani, G., Singh, S. P., Trivedi, A., & Chauhan, A. (2015). Fuzzy-TISM: A fuzzy extension of TISM for group decision making. Global Journal of Flexible Systems Management, 16(1), 97–112.

    Article  Google Scholar 

  • Kisielnicki, J. (2014). Project management in research and development. Foundations of Management, 6(3), 57–70.

    Article  Google Scholar 

  • Lee, I., & Lee, K. (2015). The Internet of Things (IoT): Applications, investments, and challenges for enterprises. Business Horizons, 58(4), 431–440.

    Article  Google Scholar 

  • Luo, Z., Dubey, R., Papadopoulos, T., Hazen, B., & Roubaud, D. (2018). Explaining environmental sustainability in supply chains using graph theory. Computational Economics, 52(4), 1257–1275.

    Article  Google Scholar 

  • Mandal, A., & Deshmukh, S. G. (1994). Vendor selection using interpretive structural modelling (ISM). International Journal of Operations & Production Management, 14(6), 52–59.

    Article  Google Scholar 

  • Mangla, S. K., Kumar, P., & Barua, M. K. (2014). Flexible decision approach for analysing performance of sustainable supply chains under risks/uncertainty. Global Journal of Flexible Systems Management, 15(2), 113–130.

    Article  Google Scholar 

  • McCann, J., & Selsky, J. W. (2012). Mastering turbulence: The essential capabilities of agile and resilient individuals, teams and organizations. Hoboken: Wiley.

    Google Scholar 

  • Miragliotta, G., Perego, A., & Tumino, A. (2012). Internet of Things: Smart present or smart future. Politecnico di Milano, Italy: Department of Management, Economics and Industrial Engineering.

    Google Scholar 

  • Muduli, A. (2013). Workforce agility: A review of literature. IUP Journal of Management Research, 12(3), 55.

    Google Scholar 

  • Patri, R., & Suresh, M. (2017). Modelling the enablers of agile performance in healthcare organization: A TISM approach. Global Journal of Flexible Systems Management, 18(3), 251–272.

    Article  Google Scholar 

  • Plonka, F. E. (1997). Developing a lean and agile work force. Human Factors and Ergonomics in Manufacturing & Service Industries, 7(1), 11–20.

    Article  Google Scholar 

  • Prasad, U. C., & Suri, R. K. (2011). Modeling of continuity and change forces in private higher technical education using total interpretive structural modeling (TISM). Global Journal of Flexible Systems Management, 12(3–4), 31–39.

    Article  Google Scholar 

  • Qin, R., & Nembhard, D. A. (2015). Workforce agility in operations management. Surveys in Operations Research and Management Science, 20(2), 55–69.

    Article  Google Scholar 

  • Rajesh, R. (2017). Technological capabilities and supply chain resilience of firms: A relational analysis using Total Interpretive Structural Modelling (TISM). Technological Forecasting and Social Change, 118, 161–169.

    Article  Google Scholar 

  • Ren, J., Yusuf, Y. Y., & Burns, N. D. (2003). The effects of agile attributes on competitive priorities: A neural network approach. Integrated Manufacturing Systems, 14(6), 489–497.

    Article  Google Scholar 

  • Sagar, M., Bora, S., Gangwal, A., Gupta, P., Kumar, A., & Agarwal, A. (2013). Factors affecting customer loyalty in cloud computing: A customer defection-centric view to develop a void-in-customer loyalty amplification model. Global Journal of Flexible Systems Management, 14(3), 143–156.

    Article  Google Scholar 

  • Sandeepa, S., & Chand, M. (2018). Analysis of flexibility factors in sustainable supply chain using Total Interpretive Structural Modeling (T-ISM) technique. Uncertain Supply Chain Management, 6(1), 1–12.

    Article  Google Scholar 

  • Sehgal, V., Sagar, M., & Shankar, R. (2016). Modelling of key success factors for mobile virtual network operators in Indian telecommunication market. Global Business Review, 17(6), 1314–1338.

    Article  Google Scholar 

  • Shafer, R. A., Dyer, L., Kilty, J., Amos, J., & Ericksen, J. (2001). Crafting a human resource strategy to foster organizational agility: A case study. Human Resource Management, 40(3), 197–211.

    Article  Google Scholar 

  • Sheffield, J., & Lemétayer, J. (2013). Factors associated with the software development agility of successful projects. International Journal of Project Management, 31(3), 459–472.

    Article  Google Scholar 

  • Sherehiy, B., Karwowski, W., & Layer, J. K. (2007). A review of enterprise agility: Concepts, frameworks, and attributes. International Journal of Industrial Ergonomics, 37(5), 445–460.

    Article  Google Scholar 

  • Shibin, K. T., Gunasekaran, A., Papadopoulos, T., Dubey, R., Singh, M., & Wamba, S. F. (2016). Enablers and barriers of flexible green supply chain management: A total interpretive structural modelling approach. Global Journal of Flexible Systems Management, 17(2), 171–188.

    Article  Google Scholar 

  • Sindhwani, R., & Malhotra, V. (2017). A framework to enhance agile manufacturing system: A total interpretive structural modelling (TISM) approach. Benchmarking: An International Journal, 24(2), 467–487.

    Article  Google Scholar 

  • Singh, A. K., & Sushil, (2013). Modelling enablers of TQM to improve airline performance. International Journal of Productivity and Performance Management, 62(3), 250–275.

    Article  Google Scholar 

  • Srivastava, A. K., & Sushil, (2014). Modelling drivers of adapt for effective strategy execution. The Learning Organization, 21(6), 369–391.

    Article  Google Scholar 

  • Sushil, (2012). Interpreting the interpretive structural model. Global Journal of Flexible Systems Management, 13(2), 87–106.

    Article  Google Scholar 

  • Sushil, (2017a). Modified ISM/TISM process with simultaneous transitivity checks for reducing direct pair comparisons. Global Journal of Flexible Systems Management, 18(4), 331–351.

    Article  Google Scholar 

  • Sushil, (2017b). Multi-criteria valuation of flexibility initiatives using integrated TISM–IRP with a big data framework. Production Planning & Control, 28(11–12), 999–1010.

    Article  Google Scholar 

  • Sushil, (2018a). Incorporating polarity of relationships in ISM and TISM for theory building in information and organization management. International Journal of Information Management, 43(December), 38–51.

    Article  Google Scholar 

  • Sushil, (2018b). How to check correctness of total interpretive structural models? Annals of Operations Research, 270(1–2), 473–487.

    Google Scholar 

  • Warfield, J. N. (1974). Developing interconnection matrices in structural modelling. IEEE Transactions on Systems, Man, and Cybernetics, 1, 81–87.

    Article  Google Scholar 

  • Worldwide IoT forecast. (2015–2020). IDC # 256397, https://www.idc.com/infographics/IoT/ATTACHMENTS/IoT.pdf. Accessed 15 Sept 2017.

  • Yadav, N., & Sushil (2014). Total interpretive structural modelling (TISM) of strategic performance management for Indian telecom service providers. International Journal of Productivity and Performance Management, 63(4), 421–445.

    Article  Google Scholar 

  • Yadav, D. K., & Barve, A. (2016). Modeling post-disaster challenges of humanitarian supply chains: A TISM approach. Global Journal of Flexible Systems Management, 17(3), 321–340.

    Article  Google Scholar 

  • Yadav, M., Rangnekar, S., & Bamel, U. (2016). Workplace flexibility dimensions as enablers of organizational citizenship behavior. Global Journal of Flexible Systems Management, 17(1), 41–56.

    Article  Google Scholar 

  • Yeravdekar, S., & Behl, A. (2017). Benchmarking model for management education in India: A total interpretive structural modelling approach. Benchmarking: An International Journal, 24(3), 666–693.

    Article  Google Scholar 

  • Yusuf, Y. Y., Sarhadi, M., & Gunasekaran, A. (1999). Agile manufacturing: The drivers, concepts and attributes. International Journal of Production Economics, 62(1–2), 33–43.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Amrita School of Business, Amrita Vishwa Vidyapeetham, Coimbatore, 641 112, India

    Madhukar Patil & M. Suresh

Authors
  1. Madhukar Patil
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. M. Suresh
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to M. Suresh.

Ethics declarations

Conflict of interest

We declare we do not have any conflict of interest with respect to this manuscript.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix

Appendix

See Tables 8, 9, 10, 11, 12, 13, 14 and 15.

Table 8 Iteration 1 level partition matrix
Full size table
Table 9 Iteration 2 level partition matrix
Full size table
Table 10 Iteration 3 level partition matrix
Full size table
Table 11 Iteration 4 level partition matrix
Full size table
Table 12 Iteration 5 level partition matrix
Full size table
Table 13 Iteration 6 level partition matrix
Full size table
Table 14 Iteration 7 level partition matrix
Full size table
Table 15 Profile of respondents for TISM
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Patil, M., Suresh, M. Modelling the Enablers of Workforce Agility in IoT Projects: A TISM Approach. Glob J Flex Syst Manag 20, 157–175 (2019). https://doi.org/10.1007/s40171-019-00208-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40171-019-00208-7

Keywords

Search

Navigation