IDEAS home Printed from https://ideas.repec.org/a/spr/ijsaem/vyid10.1007_s13198-020-01008-4.html
   My bibliography  Save this article

On interdisciplinarity between product adoption and vulnerability discovery modeling

Author

Listed:
  • Avinash K. Shrivastava

    (International Management Institute)

  • Armaan Singh Ahluwalia

    (Student Member of SREQOM)

  • P. K. Kapur

    (Amity University)

Abstract

In the last three decades, Interdisciplinary research has attracted researchers, academicians, and practitioners from the varied field to collaborate and come up with the solution to a problem. This increase in interdisciplinary research is due to its ability to solve complex problems with the help of tools from various disciplines. Interdisciplinary research is based on some of the most important methods that were built through interdisciplinary study to examine and solve a wide variety of business and engineering related problems. Six applications of interdisciplinary research work done in the area of marketing and software security engineering have been discussed in this paper. Specifically, we have discussed the similarity of the modeling framework developed for product adoption using innovation diffusion modeling and vulnerability discovery process. From this work, we aim to provide an understanding to the readers about the importance of interdisciplinary research and its contribution to solving real-life complex decision problems by utilizing the knowledge of various disciplines together.

Suggested Citation

  • Avinash K. Shrivastava & Armaan Singh Ahluwalia & P. K. Kapur, 0. "On interdisciplinarity between product adoption and vulnerability discovery modeling," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 0, pages 1-12.
  • Handle: RePEc:spr:ijsaem:v::y::i::d:10.1007_s13198-020-01008-4
    DOI: 10.1007/s13198-020-01008-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13198-020-01008-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s13198-020-01008-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. P.K. Kapur & Ompal Singh & A.K. Shrivastava, 2018. "A unified approach for optimal release, patching and testing time of a software," International Journal of Mathematics in Operational Research, Inderscience Enterprises Ltd, vol. 13(4), pages 471-491.
    2. Paul Shrivastava & Silvester Ivanaj & Vera Ivanaj, 2016. "Strategic Technological Innovation for Sustainable Development," Post-Print hal-01512866, HAL.
    3. Prabhanjan Mishra & A. K. Shrivastava & P. K. Kapur & Sunil K. Khatri, 2018. "Modeling Fault Detection Phenomenon in Multiple Sprints for Agile Software Environment," Springer Proceedings in Business and Economics, in: P.K. Kapur & Uday Kumar & Ajit Kumar Verma (ed.), Quality, IT and Business Operations, pages 251-263, Springer.
    4. Frank M. Bass & Trichy V. Krishnan & Dipak C. Jain, 1994. "Why the Bass Model Fits without Decision Variables," Marketing Science, INFORMS, vol. 13(3), pages 203-223.
    5. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    6. P.K. Kapur & Hoang Pham & A. Gupta & P.C. Jha, 2011. "Software Reliability Assessment with OR Applications," Springer Series in Reliability Engineering, Springer, number 978-0-85729-204-9, September.
    7. Adarsh Anand & Mohini Agarwal & Gunjan Bansal & A. H. S. Garmabaki, 2016. "Studying product diffusion based on market coverage," Journal of Marketing Analytics, Palgrave Macmillan, vol. 4(4), pages 135-146, December.
    8. Iqra Saraf & A.K. Shrivastava & Javaid Iqbal, 2020. "Generalised fault detection and correction modelling framework for multi-release of software," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 34(4), pages 464-493.
    9. Stummer, Christian & Kiesling, Elmar & Günther, Markus & Vetschera, Rudolf, 2015. "Innovation diffusion of repeat purchase products in a competitive market: An agent-based simulation approach," European Journal of Operational Research, Elsevier, vol. 245(1), pages 157-167.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Avinash K. Shrivastava & Armaan Singh Ahluwalia & P. K. Kapur, 2021. "On interdisciplinarity between product adoption and vulnerability discovery modeling," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(1), pages 176-187, February.
    2. Herbert Dawid & Reinhold Decker & Thomas Hermann & Hermann Jahnke & Wilhelm Klat & Rolf König & Christian Stummer, 2017. "Management science in the era of smart consumer products: challenges and research perspectives," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 25(1), pages 203-230, March.
    3. Singhal, Shakshi & Anand, Adarsh & Singh, Ompal, 2020. "Studying dynamic market size-based adoption modeling & product diffusion under stochastic environment," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    4. Chul-Yong Lee & Sung-Yoon Huh, 2017. "Technology Forecasting Using a Diffusion Model Incorporating Replacement Purchases," Sustainability, MDPI, vol. 9(6), pages 1-14, June.
    5. Chumnumpan, Pattarin & Shi, Xiaohui, 2019. "Understanding new products’ market performance using Google Trends," Australasian marketing journal, Elsevier, vol. 27(2), pages 91-103.
    6. Saurabh Panwar & P. K. Kapur & Ompal Singh, 2021. "Technology diffusion model with change in adoption rate and repeat purchases: a case of consumer balking," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(1), pages 29-36, February.
    7. Shi, Xiaohui & Chumnumpan, Pattarin, 2019. "Modelling market dynamics of multi-brand and multi-generational products," European Journal of Operational Research, Elsevier, vol. 279(1), pages 199-210.
    8. Zhang, Tianyu & Dong, Peiwu & Zeng, Yongchao & Ju, Yanbing, 2022. "Analyzing the diffusion of competitive smart wearable devices: An agent-based multi-dimensional relative agreement model," Journal of Business Research, Elsevier, vol. 139(C), pages 90-105.
    9. Frank M. Bass, 2004. "Comments on "A New Product Growth for Model Consumer Durables The Bass Model"," Management Science, INFORMS, vol. 50(12_supple), pages 1833-1840, December.
    10. Yuri Peers & Dennis Fok & Philip Hans Franses, 2012. "Modeling Seasonality in New Product Diffusion," Marketing Science, INFORMS, vol. 31(2), pages 351-364, March.
    11. Constanza Fosco, 2012. "Spatial Difusion and Commuting Flows," Documentos de Trabajo en Economia y Ciencia Regional 30, Universidad Catolica del Norte, Chile, Department of Economics, revised Sep 2012.
    12. Guseo, Renato, 2016. "Diffusion of innovations dynamics, biological growth and catenary function," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 464(C), pages 1-10.
    13. Toka, Agorasti & Iakovou, Eleftherios & Vlachos, Dimitrios & Tsolakis, Naoum & Grigoriadou, Anastasia-Loukia, 2014. "Managing the diffusion of biomass in the residential energy sector: An illustrative real-world case study," Applied Energy, Elsevier, vol. 129(C), pages 56-69.
    14. Krishnan, Trichy V. & Feng, Shanfei & Jain, Dipak C., 2023. "Peak sales time prediction in new product sales: Can a product manager rely on it?," Journal of Business Research, Elsevier, vol. 165(C).
    15. Brito, Thiago Luis Felipe & Islam, Towhidul & Stettler, Marc & Mouette, Dominique & Meade, Nigel & Moutinho dos Santos, Edmilson, 2019. "Transitions between technological generations of alternative fuel vehicles in Brazil," Energy Policy, Elsevier, vol. 134(C).
    16. Vakratsas, Demetrios & Kolsarici, Ceren, 2008. "A dual-market diffusion model for a new prescription pharmaceutical," International Journal of Research in Marketing, Elsevier, vol. 25(4), pages 282-293.
    17. Ruiz-Conde, Enar & Wieringa, Jaap E. & Leeflang, Peter S.H., 2014. "Competitive diffusion of new prescription drugs: The role of pharmaceutical marketing investment," Technological Forecasting and Social Change, Elsevier, vol. 88(C), pages 49-63.
    18. Al-Alawi, Baha M. & Bradley, Thomas H., 2013. "Review of hybrid, plug-in hybrid, and electric vehicle market modeling Studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 190-203.
    19. Hariharan, Vijay Ganesh & Talukdar, Debabrata & Kwon, Changhyun, 2015. "Optimal targeting of advertisement for new products with multiple consumer segments," International Journal of Research in Marketing, Elsevier, vol. 32(3), pages 263-271.
    20. Kurdgelashvili, Lado & Shih, Cheng-Hao & Yang, Fan & Garg, Mehul, 2019. "An empirical analysis of county-level residential PV adoption in California," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 321-333.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:ijsaem:v::y::i::d:10.1007_s13198-020-01008-4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.