Skip to main content

Advertisement

Log in

Mediating role of cloud of things in improving performance of small and medium enterprises in the Indian context

  • S.I.: Information- Transparent Supply Chains
  • Published:
Annals of Operations Research Aims and scope Submit manuscript

Abstract

Integration of cloud computing and the Internet of things can influence large as well as small-scale organizations in transforming their business systems for high performance. However, in developing nations like India, cloud of things is relatively novel, and there is a need for its proper understanding specifically, in small and medium scaled enterprises. This study aims to investigate the mediating role of cloud of things on the performance of small and medium scaled enterprises and the influence of various key factors namely security and privacy, perceived ease of use, top management support, perceived security risk, big data analytics, trust, customer–supplier intention, manufacturing infrastructure, IT support, knowledge sharing, and external environment support on cloud of things was analyzed. A sample of 290 responses from 96 Indian small and medium scaled enterprises was collected and exploratory factor analysis, confirmatory factor analysis, structural equation modelling methodologies were employed for the analysis. Results suggest that big data analytics, top management support, trust, perceived security risk, etc. require the mediating support of cloud of things. This study is useful for managers, policymakers, practitioners, and regulatory authorities to understand the importance of information, and the cloud of things, and further to formulate strategies to improve firm’s performance by improving the information transparency across the value chain.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1

Source The Author

Fig. 2

Source The Author

Fig. 3

Source The Author

Similar content being viewed by others

References

  • Addo-Tenkorang, R., & Helo, P. T. (2016). Big data applications in operations/supply-chain management: A literature review. Computers & Industrial Engineering, 101, 528–543.

    Google Scholar 

  • Ahmadov, Y., & Helo, P. (2018). A cloud based job sequencing with sequence-dependent setup for sheet metal manufacturing. Annals of Operations Research, 270(1–2), 5–24.

    Google Scholar 

  • Alkhanak, E. N., Lee, S. P., & Khan, S. U. R. (2015). Cost-aware challenges for workflow scheduling approaches in cloud computing environments: Taxonomy and opportunities. Future Generation Computer Systems, 50, 3–21.

    Google Scholar 

  • Anderson, J. C., & Gerbing, D. W. (1984). The effect of sampling error on convergence, improper solutions, and goodness-of-fit indices for maximum likelihood confirmatory factor analysis. Psychometrika, 49(2), 155–173.

    Google Scholar 

  • Bagozzi, R. P. (1980). Causal models in marketing. Hoboken: Wiley.

    Google Scholar 

  • Barki, H., & Hartwick, J. (2001). Interpersonal conflict and its management in information system development. Mis Quarterly, 25, 195–228.

    Google Scholar 

  • Ben-Daya, M., Hassini, E., & Bahroun, Z. (2019). Internet of things and supply chain management: a literature review. International Journal of Production Research, 57(15–16), 4719–4742.

    Google Scholar 

  • Botta, A., De Donato, W., Persico, V., & Pescapé, A. (2016). Integration of cloud computing and internet of things: A survey. Future Generation Computer Systems, 56, 684–700.

    Google Scholar 

  • Conti, M., Dehghantanha, A., Franke, K., & Watson, S. (2018). Internet of Things security and forensics: Challenges and opportunities. Future Generation Computer Systems, 78, 544–546.

    Google Scholar 

  • Côrte-Real, N., Oliveira, T., & Ruivo, P. (2017). Assessing business value of big data analytics in European firms. Journal of Business Research, 70, 379–390.

    Google Scholar 

  • Da Xu, L., He, W., & Li, S. (2014). Internet of things in industries: A survey. IEEE Transactions on Industrial Informatics, 10(4), 2233–2243.

    Google Scholar 

  • Davenport, T. H., Barth, P., & Bean, R. (2012). How’big data’is different. MIT Sloan Management Review.

  • de Sousa Jabbour, A. B. L., Jabbour, C. J. C., Foropon, C., & Godinho Filho, M. (2018a). When titans meet–Can industry 4.0 revolutionise the environmentally-sustainable manufacturing wave? The role of critical success factors. Technological Forecasting and Social Change, 132, 18–25.

    Google Scholar 

  • de Sousa Jabbour, A. B. L., Jabbour, C. J. C., Godinho Filho, M., & Roubaud, D. (2018b). Industry 4 and the circular economy: A proposed research agenda and original roadmap for sustainable operations. Annals of Operations Research, 270(1–2), 273–286.

    Google Scholar 

  • Díaz, M., Martín, C., & Rubio, B. (2016). State-of-the-art, challenges, and open issues in the integration of Internet of things and cloud computing. Journal of Network and Computer Applications, 67, 99–117.

    Google Scholar 

  • Dimitrov, D. M. (2014). Statistical methods for validation of assessment scale data in counseling and related fields. Hoboken: Wiley.

    Google Scholar 

  • Dubey, R., Gunasekaran, A., Childe, S. J., Papadopoulos, T., Luo, Z., Wamba, S. F., et al. (2017). Can big data and predictive analytics improve social and environmental sustainability? Technological Forecasting and Social Change, 144, 534–545.

    Google Scholar 

  • Esmaeilian, B., Behdad, S., & Wang, B. (2016). The evolution and future of manufacturing: A review. Journal of Manufacturing Systems, 39, 79–100.

    Google Scholar 

  • Gangwar, H., Date, H., & Ramaswamy, R. (2015). Understanding determinants of cloud computing adoption using an integrated TAM-TOE model. Journal of Enterprise Information Management, 28(1), 107–130.

    Google Scholar 

  • Ghatak, S. (2010). Micro, small and medium enterprises (MSMEs) in India: An appraisal. Journal of Technology Management & Innovation, 6(1), 66–76.

    Google Scholar 

  • Gunasekaran, A., Yusuf, Y. Y., Adeleye, E. O., & Papadopoulos, T. (2017). Agile manufacturing practices: The role of big data and business analytics with multiple case studies. International Journal of Production Research, 56(1–2), 385–397.

    Google Scholar 

  • Hair, J. F., Anderson, R. I., Tatham, R. L., & Black, W. C. (1995). Multivariate data analysis (5th ed.). Engle wood cliffs: Prentice Hall International.

    Google Scholar 

  • Han, S., Huang, H., Luo, Z., & Foropon, C. (2018). Harnessing the power of crowdsourcing and Internet of Things in disaster response. Annals of Operations Research, 283, 1–16.

    Google Scholar 

  • Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55.

    Google Scholar 

  • IANS (2019). Indian government sector next big thing for Google Cloud, ET Prime. Retrieved September 9, 2019 from (https://cio.economictimes.indiatimes.com/news/cloud-computing/indian-government-sector-next-big-thing-for-google-cloud/70435456.

  • Jarvenpaa, S. L., Tractinsky, N., & Vitale, M. (2000). Consumer trust in an Internet store. Information Technology and Management, 1(1–2), 45–71.

    Google Scholar 

  • Jiang, P., Ding, K., & Leng, J. (2016). Towards a cyber-physical-social-connected and service-oriented manufacturing paradigm. Social Manufacturing Manufacturing Letters, 7, 15–21.

    Google Scholar 

  • Jin, X., Wah, B. W., Cheng, X., & Wang, Y. (2015). Significance and challenges of big data research. Big Data Research, 2(2), 59–64.

    Google Scholar 

  • Kang, H. S., Lee, J. Y., Choi, S., Kim, H., Park, J. H., Son, J. Y., et al. (2016). Smart manufacturing: Past research, present findings, and future directions. International Journal of Precision Engineering and Manufacturing-Green Technology, 3(1), 111–128.

    Google Scholar 

  • Li, G., Liu, W., Wang, Z., & Liu, M. (2017). An empirical examination of energy consumption, behavioral intention, and situational factors: Evidence from Beijing. Annals of Operations Research, 255(1–2), 507–524.

    Google Scholar 

  • Li, G., Zheng, H., Sethi, S. P., & Guan, X. (2018). Inducing downstream information sharing via manufacturer information acquisition and retailer subsidy. Decision Sciences, 1–29.

  • Liu, P., & Yi, S. P. (2018). A study on supply chain investment decision-making and coordination in the Big Data environment. Annals of Operations Research, 270(1–2), 235–253.

    Google Scholar 

  • Lounis, A., Hadjidj, A., Bouabdallah, A., & Challal, Y. (2016). Healing on the cloud: Secure cloud architecture for medical wireless sensor networks. Future Generation Computer Systems, 55, 266–277.

    Google Scholar 

  • Lu, Y. (2017). Industry 4.0: A survey on technologies, applications and open research issues. Journal of Industrial Information Integration, 6, 1–10.

    Google Scholar 

  • Luthra, S., Mangla, S. K., Chan, F. T., & Venkatesh, V. G. (2018a). Evaluating the drivers to information and communication technology for effective sustainability initiatives in supply chains. International Journal of Information Technology & Decision Making, 17(1), 311–338.

    Google Scholar 

  • Luthra, S., Mangla, S. K., Chan, F. T., & Venkatesh, V. G. (2018b). Evaluating the drivers to information and communication technology for effective sustainability initiatives in supply chains. International Journal of Information Technology & Decision Making, 17(01), 311–338.

    Google Scholar 

  • MacCallum, R. C., & Austin, J. T. (2000). Applications of structural equation modeling in psychological research. Annual Review of Psychology, 51(1), 201–226.

    Google Scholar 

  • Mai, V., & Khalil, I. (2017). Design and implementation of a secure cloud-based billing model for smart meters as an Internet of things using homomorphic cryptography. Future Generation Computer Systems, 72, 327–338.

    Google Scholar 

  • Manuel, P. (2015). A trust model of cloud computing based on quality of service. Annals of Operations Research, 233(1), 281–292.

    Google Scholar 

  • Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., & Byers, A. H. (2011). Big data: The next frontier for innovation, competition, and productivity. http://www.mckinsey.com/Insights/MGI/Research/Technology_and_Innovation/Big_data_The_next_frontier_for_innovation. Accessed 10 April 2019.

  • Martins, R., Oliveira, T., & Thomas, M. A. (2016). An empirical analysis to assess the determinants of SaaS diffusion in firms. Computers in Human Behavior, 62, 19–33.

    Google Scholar 

  • McAfee, A., Brynjolfsson, E., Davenport, T. H., Patil, D. J., & Barton, D. (2012). Big data: The management revolution. Harvard Business Review, 90(10), 60–68.

    Google Scholar 

  • Mishra, D., Gunasekaran, A., Childe, S. J., Papadopoulos, T., Dubey, R., & Wamba, S. (2016). Vision, applications and future challenges of Internet of Things: A bibliometric study of the recent literature. Industrial Management & Data Systems, 116(7), 1331–1355.

    Google Scholar 

  • Narwane, V., Narkhede, B., Raut, R., Gardas, B., Priyadarshinee, P., Kavre, M. (In press). To identify the determinants of the CloudIoT technologies adoption in the Indian MSMEs: structural equation modelling approach. International Journal of Business Information Systems.

  • Patel, P., & Cassou, D. (2015). Enabling high-level application development for the Internet of Things. Journal of Systems and Software, 103, 62–84.

    Google Scholar 

  • Pavlou, P. A., & Gefen, D. (2004). Building effective online marketplaces with institution-based trust. Information Systems Research, 15(1), 37–59.

    Google Scholar 

  • Perera, C., Zaslavsky, A., Christen, P., & Georgakopoulos, D. (2014). Context aware computing for the internet of things: A survey. IEEE Communications Surveys & Tutorials, 16(1), 414–454.

    Google Scholar 

  • Raut, R. D., Mangla, S. K., Narwane, V. S., Gardas, B. B., Priyadarshinee, P., & Narkhede, B. E. (2019). Linking big data analytics and operational sustainability practices for sustainable business management. Journal of Cleaner Production, 224, 10–24.

    Google Scholar 

  • Rekik, M., Boukadi, K., & Ben-Abdallah, H. (2015). A decision-making method for business process outsourcing to the cloud based on business motivation model and AHP. International Journal of Cloud Computing 2, 4(1), 47–62.

    Google Scholar 

  • Ren, S., Fosso Wamba, S., Akter, S., Dubey, R., & Childe, S. J. (2017). Modelling quality dynamics, business value and firm performance in a big data analytics environment. International Journal of Production Research, 55(17), 5011–5026.

    Google Scholar 

  • Reyna, A., Martín, C., Chen, J., Soler, E., & Díaz, M. (2018). On blockchain and its integration with IoT: Challenges and opportunities. Future Generation Computer Systems., 88(2018), 173–190.

    Google Scholar 

  • Srivastava, S. C., Mithas, S., & Jha, B. (2013). What is your global innovation strategy? IT Professional, 15(6), 2–6.

    Google Scholar 

  • Stergiou, C., Psannis, K. E., Kim, B. G., & Gupta, B. (2018). Secure integration of IoT and cloud computing. Future Generation Computer Systems, 78, 964–975.

    Google Scholar 

  • Tao, F., Qi, Q., Liu, A., & Kusiak, A. (2018). Data-driven smart manufacturing. Journal of Manufacturing Systems, 48, 157–169.

    Google Scholar 

  • Tao, F., Wang, Y., Zuo, Y., Yang, H., & Zhang, M. (2016). Internet of Things in product life-cycle energy management. Journal of Industrial Information Integration, 1, 26–39.

    Google Scholar 

  • Tao, F., Zuo, Y., Da Xu, L., & Zhang, L. (2014). IoT-based intelligent perception and access of manufacturing resource toward cloud manufacturing. IEEE Transactions on Industrial Informatics, 10(2), 1547–1557.

    Google Scholar 

  • Thompson, B. (2004). Exploratory and confirmatory factor analysis: Understanding concepts and applications. Washington: American Psychological Association.

    Google Scholar 

  • Varghese, B., & Buyya, R. (2018). Next generation cloud computing: New trends and research directions. Future Generation Computer Systems, 79, 849–861.

    Google Scholar 

  • Wamba, S. F., Gunasekaran, A., Akter, S., Ren, S. J. F., Dubey, R., & Childe, S. J. (2017). Big data analytics and firm performance: Effects of dynamic capabilities. Journal of Business Research, 70, 356–365.

    Google Scholar 

  • Wang, S., Wan, J., Li, D., & Zhang, C. (2016). Implementing smart factory of industrie 4.0: An outlook. International Journal of Distributed Sensor Networks, 12(1), 3159805.

    Google Scholar 

  • Wang, Z., & Wang, N. (2012). Knowledge sharing, innovation and firm performance. Expert Systems with Applications, 39(10), 8899–8908.

    Google Scholar 

  • Williams, B., Onsman, A., & Brown, T. (2010). Exploratory factor analysis: A five-step guide for novices. Australasian Journal of Paramedicine, 8(3), 1–13.

    Google Scholar 

  • Zeng, D., Gu, L., & Yao, H. (2018). Towards energy efficient service composition in green energy powered Cyber-Physical Fog Systems. Future Generation Computer Systems. https://doi.org/10.1016/j.future.2018.01.060.

    Article  Google Scholar 

  • Zhong, R. Y., Xu, X., Klotz, E., & Newman, S. T. (2017). Intelligent manufacturing in the context of industry 4.0: A review. Engineering, 3(5), 616–630.

    Google Scholar 

  • Zissis, D., & Lekkas, D. (2012). Addressing cloud computing security issues. Future Generation computer systems, 28(3), 583–592.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sachin Kumar Mangla.

Additional information

Publisher's Note

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

Appendices

Annexures-I

Table 4 Rotated Component Matrix

Annexures-II

Table 5 Estimates for CFA Model

Annexure-III

Table 6 Estimates for the structural model

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Narwane, V.S., Raut, R.D., Mangla, S.K. et al. Mediating role of cloud of things in improving performance of small and medium enterprises in the Indian context. Ann Oper Res 329, 69–98 (2023). https://doi.org/10.1007/s10479-019-03502-w

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10479-019-03502-w

Keywords

Navigation