Academic literature on the topic 'Total Interpretive Structural Modelling'
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Journal articles on the topic "Total Interpretive Structural Modelling"
Dhir, Sanjay, Rashi Taggar, Sunali Bindra, and Deepika Sharma. "Retailer responsiveness: a total interpretive structural modelling approach." J. for Global Business Advancement 13, no. 3 (2020): 336. http://dx.doi.org/10.1504/jgba.2020.10033253.
Full textSharma, Deepika, Rashi Taggar, Sunali Bindra, and Sanjay Dhir. "Retailer responsiveness: a total interpretive structural modelling approach." J. for Global Business Advancement 13, no. 3 (2020): 336. http://dx.doi.org/10.1504/jgba.2020.111014.
Full text., Ambikadevi Amma T. "TOTAL INTERPRETIVE STRUCTURAL MODELLING ON ENABLERS OF CLOUD COMPUTING." International Journal of Research in Engineering and Technology 03, no. 06 (June 25, 2014): 398–406. http://dx.doi.org/10.15623/ijret.2014.0306074.
Full textDubey, Rameshwar, Angappa Gunasekaran, and Tripti Singh. "Building theory of sustainable manufacturing using total interpretive structural modelling." International Journal of Systems Science: Operations & Logistics 2, no. 4 (March 31, 2015): 231–47. http://dx.doi.org/10.1080/23302674.2015.1025890.
Full textKaur, Irameet, and Charu Shri. "Total Interpretive Structural Modeling of Emotional Intelligence at Workplace." International Journal of Applied Management Sciences and Engineering 2, no. 2 (July 2015): 1–19. http://dx.doi.org/10.4018/ijamse.2015070101.
Full textMehra, Ritika, and Pooja Gupta. "Total Interpretive Structural Modelling of Machine learning Enablers in the Healthcare System." International Journal of Applied Decision Sciences 1, no. 1 (2022): 1. http://dx.doi.org/10.1504/ijads.2022.10038271.
Full textMahajan, Ritika, Rajat Agrawal, Vinay Sharma, and Vinay Nangia. "Analysis of challenges for management education in India using total interpretive structural modelling." Quality Assurance in Education 24, no. 1 (February 1, 2016): 95–122. http://dx.doi.org/10.1108/qae-07-2013-0030.
Full textTalib, Faisal, Zillur Rahman, and M. N. Qureshi. "An interpretive structural modelling approach for modelling the practices of total quality management in service sector." International Journal of Modelling in Operations Management 1, no. 3 (2011): 223. http://dx.doi.org/10.1504/ijmom.2011.039528.
Full textObi, Lovelin, Paul Hampton, and Bankole Awuzie. "Total Interpretive Structural Modelling of Graduate Employability Skills for the Built Environment Sector." Education Sciences 10, no. 12 (December 8, 2020): 369. http://dx.doi.org/10.3390/educsci10120369.
Full textKumar, Sanjay, Vasdev Malhotra, and Vikas Kumar. "A framework to enhance cellular manufacturing system: a total interpretive structural modelling approach." International Journal of Process Management and Benchmarking 8, no. 4 (2018): 393. http://dx.doi.org/10.1504/ijpmb.2018.095052.
Full textDissertations / Theses on the topic "Total Interpretive Structural Modelling"
Lawrie, Peter Richard. "Development of computer software support for interpretive structural modelling." Master's thesis, University of Cape Town, 1995. http://hdl.handle.net/11427/15980.
Full textInterpretive Structural Modelling is a computer-driven method for dealing with complexity, by allowing individuals or groups to interpret the inter-relationships between different aspects or elements of a problem. In doing this interpretation, the elements are structured, and from this structuring, a graphical model is produced, allowing the modeller(s) to better understand the problem. The main contribution of this thesis was to develop a computer package for Interpretive Structural Modelling (ISM), for use at the School of Engineering Management at the University of Cape Town. The package was developed for the IBM PC.
Al-Muftah, Hamad M. "Toward Formulation a Maturity Framework for E-diplomacy." Thesis, University of Bradford, 2018. http://hdl.handle.net/10454/17318.
Full textRamos, Edgar, Timothy J. Pettit, Mamun Habib, and Melissa Chavez. "A model ISM-MICMAC for managing risk in agri-food supply chain: An investigation from the Andean region of Peru." Inderscience Publishers, 2021. http://hdl.handle.net/10757/656006.
Full textAl-Kuwari, Wasmiya Dalhem M. D. "Information management within the Nursing Department at Hamad Medical Corporation (HMC), Qatar." Thesis, Loughborough University, 2005. https://dspace.lboro.ac.uk/2134/7811.
Full textMathivathanan, D., K. Mathiyazhagan, Nripendra P. Rana, S. Khorana, and Y. K. Dwivedi. "Barriers to the adoption of blockchain technology in business supply chains: a total interpretive structural modelling (TISM) approach." 2020. http://hdl.handle.net/10454/18202.
Full textBlockchain is an emerging technology with a wide array of potential applications. This technology, which underpins cryptocurrency, provides an immutable, decentralised, and transparent distributed database of digital assets for use by firms in supply chains. However, not all firms are appropriately suited to adopt blockchain in the existing supply chain primarily due to their lack of knowledge on the benefits of this technology. Using Total Interpretive Structural Modelling (TISM) and Cross-Impact Matrix Multiplication Applied to Classification (MICMAC), this paper identifies the adoption barriers, examines the interrelationships between them to the adoption of blockchain technology, which has the potential to revolutionise supply chains. The TISM technique supports developing a contextual relationship based structural model to identify the influential barriers. MICMAC classifies the barriers in blockchain adoption based on their strength and dependence. The results of this research indicate that the lack of business awareness and familiarity with blockchain technology on what it can deliver for future supply chains, are the most influential barriers that impede blockchain adoption. These barriers hinder and impact businesses decision to establish a blockchain-enabled supply chain and that other barriers act as secondary and linked variables in the adoption process.
The full-text of this article will be released for public view at the end of the publisher embargo on 13 Jan 2022.
Hughes, D. L., Nripendra P. Rana, and Y. K. Dwivedi. "Elucidation of IS project success factors: an interpretive structural modelling approach." 2019. http://hdl.handle.net/10454/18099.
Full textThis study extends the debate surrounding the components of IS project success by reviewing success factors from the perspective of their interdependency and influence on each other. This research utilises interpretive structural modelling as the methodology and framework to develop the relationships between the selected factors. This approach is presented as a mechanism that can provide greater insight to the underlying causal interrelationships associated with IS project success and the successful transition to operations. The findings identify a number of key outcomes that have significant driving influence on other interconnected factors in the final model. This study highlights the benefits of an interpretive approach where IS factor interrelationships can be modelled to demonstrate potential influence on other connected factors thereby, increasing the chances of project success.
Al-Muftah, H., Vishanth J. P. Weerakkody, Nripendra P. Rana, Uthayasankar Sivarajah, and Zahir Irani. "Factors influencing e-diplomacy implementation: Exploring causal relationships using interpretive structural modelling." 2018. http://hdl.handle.net/10454/15340.
Full textElectronic diplomacy (E-diplomacy) is the use of technology by nations to define and establish diplomatic goals and objectives and to efficiently carry out the functions of diplomats. These functions include representation and promotion of the home nation, establishing both bilateral and multilateral relations, consular services and social engagement. It encapsulates the adoption of multiple ICT tools over the Internet to support a nation’s interests in other countries while ensuring that foreign relations are improved between the countries. Given its embryonic nature, little scholarly research has been undertaken to study its influence on diplomatic functions and the various factors that influence its implementation. This paper applies the Interpretative Structural Modelling (ISM) methodological approach to identify factors that impact the implementation of e-diplomacy and to determine their causal relationship and rankings. This study applies the ISM methodology to the subject of e-diplomacy. The ISM-based model provides a framework for practitioners to aid decision-making and manage the implementation of e-diplomacy.
Hughes, D. L., Y. K. Dwivedi, Nripendra P. Rana, and A. C. Simintiras. "Information systems project failure – analysis of causal links using interpretive structural modelling." 2016. http://hdl.handle.net/10454/18079.
Full textThe analysis of the root causes of information systems project failure has been the subject of intense scrutiny for some time within industry and the academic community. Researchers have developed various models, notions of failure and categorisations to succinctly classify project failure into a set of key factors for organisations and project managers to focus on in their attempts to avoid failure. This study incorporates a technique titled: interpretive structural modelling as the methodology to formalise the relationships between the selected failure factors. This approach is positioned as a mechanism that can yield greater insights into the relationships between the factors surrounding project failure, thereby developing a better understanding of how these relationships can have a bearing on project outcomes. The findings identify key driving variables that are presented as having significant impact on the other factors within the model. A number of variables are also identified as being heavily dependent on other connected factors highlighting that a failure in one or more of these connected factors is likely to result in a failure in one or more of the dependent factors unless timely steps are taken to address these key issues. This research details a number of practical implications for senior management and project managers as well as the academic community. These considerations form an underlying thread within this study as specific practice-related implications are highlighted and discussed throughout the study.
Rajan, R., Nripendra P. Rana, N. Parameswar, S. Dhir, Sushil, and Y. K. Dwivedi. "Developing a modified total interpretive structural model (M-TISM) for organizational strategic cybersecurity management." 2021. http://hdl.handle.net/10454/18482.
Full textCybersecurity is a serious issue that many organizations face these days. Therefore, cybersecurity management is very important for any organization. Organizations should learn to deal with these cyber threats through effective management across all business functions. The main purpose of this study is to identify the factors that affect cybersecurity within an organization and analyze relationships among these factors. The modified total interpretive structural modeling (M-TISM) technique is used to build a hierarchical model and define the common interactions between the factors. This study presents the impact of collaboration, training, resources and capabilities, information flow, technology awareness, and technological infrastructure on effective cybersecurity management. In addition, the study also explains the interrelationships among the identified factors in the M-TISM model.
The full text will be available at the end of the publisher's embargo: 20th July 2022
Janssen, M., Nripendra P. Rana, E. L. Slade, and Y. K. Dwivedi. "Trustworthiness of digital government services: deriving a comprehensive theory through interpretive structural modelling." 2017. http://hdl.handle.net/10454/18091.
Full textHaving its origin in public administration, trustworthiness is a significant concept in digital government research, influencing the relationships between citizens and governments. However, the interrelationships between the facets of trustworthiness are given inadequate attention. Therefore, the aim of this research was to develop a theory detailing the factors affecting citizens’ perceptions of e-government trustworthiness. A comprehensive review of public administration and information systems literature highlighted 20 pertinent variables. The interrelationships of these variables were identified and categorized according to their driving and dependence power by employing interpretive structural modelling. The proposed model was then drawn based on the level partitioning of variables and interrelationships of the variables determined using the final reachability matrix. The findings reveal that current conceptualizations of digital government trustworthiness take a too narrow view. The findings can help government policy makers with understanding the interrelated factors associated with trustworthiness in the context of digital government services and implement them in effective strategic planning.
Book chapters on the topic "Total Interpretive Structural Modelling"
Menon, Shalini, and M. Suresh. "Total Interpretive Structural Modelling: Evolution and Applications." In Innovative Data Communication Technologies and Application, 257–65. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-38040-3_30.
Full textAkriti Jain, Ruchi Sharma, and P. Vigneswara Ilavarasan. "Total Interpretive Structural Modelling of Innovation Measurement for Indian Universities and Higher Academic Technical Institutions." In Flexible Systems Management, 29–53. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-4888-3_3.
Full textKhurana, Sonal, Bisma Mannan, and Abid Haleem. "Total Interpretive Structural Modelling of Critical Factors of Sustainable-Oriented Innovation for Indian Manufacturing MSMEs." In Lecture Notes in Mechanical Engineering, 95–106. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1071-7_9.
Full textThakkar, Jitesh J. "Interpretive Structural Modelling (ISM)." In Multi-Criteria Decision Making, 311–24. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4745-8_18.
Full textBai, Ming, and Xu Ren. "Interpretive Structural Modelling of Factors Influencing Enterprise Transformation." In IEIS2019, 745–57. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5660-9_56.
Full textRanaei Kordshouli, Habib Allah, Moslem Alimohammadlou, Ghasem Salimi, and Seyed Moslem Alavi. "Third-Generation University Governance Model Using Total Interpretive Structural Modeling." In Global Encyclopedia of Public Administration, Public Policy, and Governance, 1–12. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-319-31816-5_4221-1.
Full textSuresh, M., D. Sangeetha, and Sumathi Kumaraswamy. "Modelling of Factors Influencing Saving Behaviour of Women in India: An Interpretive Structural Modelling." In Springer Proceedings in Materials, 809–18. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-8319-3_81.
Full textKim, Ikno, and Junzo Watada. "Towards a New Medical Decision Support System with Bio-inspired Interpretive Structural Modelling." In Studies in Computational Intelligence, 459–66. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-00909-9_44.
Full textVinodh, S., and Rohit Agrawal. "Application of Interpretive Structural Modelling for analysis of factors influencing Sustainability in Higher Education." In Higher Education and Sustainability, 117–31. Boca Raton, FL : Taylor & Francis Group, 2020.: CRC Press, 2019. http://dx.doi.org/10.1201/b22452-6.
Full textBahari, Mahadi, Tiara Izrinda Jafni, Waidah Ismail, Haslina Hashim, and Hafez Hussain. "Analysis of the Readiness for Healthcare Personnel Adopting Telerehabilitation: An Interpretive Structural Modelling (ISM) Approach." In Information Systems, 353–68. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-11395-7_28.
Full textConference papers on the topic "Total Interpretive Structural Modelling"
Tyagi, Sanjay K., Sujeet K. Sharma, and Vinod Kumar Shukla. "Interpretive Structural Modelling Using Fuzzy Linguistic Information." In 2019 4th International Conference on Information Systems and Computer Networks (ISCON). IEEE, 2019. http://dx.doi.org/10.1109/iscon47742.2019.9036267.
Full textSingh, Rajbala, Deepak Kumar, and B. B. Sagar. "Interpretive structural modelling in assessment of agile methodology." In 2017 International Conference on Infocom Technologies and Unmanned Systems (Trends and Future Directions) (ICTUS). IEEE, 2017. http://dx.doi.org/10.1109/ictus.2017.8286055.
Full textBisht, Marut, Mohammed Shahid Irshad, Niyati Aggarwal, and Adarsh Anand. "Understanding Popularity Dynamics for YouTube Videos: An Interpretive Structural Modelling based Approach." In 2019 Amity International Conference on Artificial Intelligence (AICAI). IEEE, 2019. http://dx.doi.org/10.1109/aicai.2019.8701274.
Full textTuan, Nien-Tsu, Ian Jay, and Mark Massyn. "Modelling the Factors Impacting the Sustainability of South Africa's Construction Industry – An Interpretive Structural Modelling Approach." In International Conference on Engineering, Project, and Production Management. Association of Engineering, Project, and Production Management, 2014. http://dx.doi.org/10.32738/ceppm.201411.0031.
Full textPundir, Ashok Kumar, L. Ganapathy, Pratik Maheshwari, and Shashikant Thakur. "Interpretive Structural Modelling to assess the enablers of blockchain technology in supply chain." In 2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON). IEEE, 2020. http://dx.doi.org/10.1109/iemcon51383.2020.9284828.
Full textAbinaya, R., and M. Suresh. "Analyzing the drivers for lean practices of commercial banking using interpretive structural modelling." In 2016 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC). IEEE, 2016. http://dx.doi.org/10.1109/iccic.2016.7919632.
Full textGoel, Pawan, Jayakrishna Kandasamy, Logesh G., Vijayakumar Manupati, and Vimal Kek. "Modelling Sustainable Manufacturing practices for plastic part manufacturing organization using Interpretive Structural Modeling." In 2018 International Conference on Production and Operations Management Society (POMS). IEEE, 2018. http://dx.doi.org/10.1109/poms.2018.8629442.
Full textFeifei Wu and Lucheng Huang. "Approaches on evaluating industrialization potentiality of Olympic technology projects based on interpretive structural modelling." In Technology (ICMIT 2008). IEEE, 2008. http://dx.doi.org/10.1109/icmit.2008.4654342.
Full textSharma, Bhupendra Prakash, Akshat Jain, and Harshit Ahuja. "Modelling of agile manufacturing barriers in the Indian engineering industries: An interpretive structural modeling approach." In 2017 International Conference on Advances in Mechanical, Industrial, Automation and Management Systems (AMIAMS). IEEE, 2017. http://dx.doi.org/10.1109/amiams.2017.8069180.
Full textPrakash, Surya, Maheshwar Dwivedy, Sameer Sharma Poudel, and Dilesh Raj Shrestha. "Modelling the barriers for mass adoption of electric vehicles in Indian automotive sector: An Interpretive Structural Modeling (ISM) approach." In 2018 5th International Conference on Industrial Engineering and Applications (ICIEA). IEEE, 2018. http://dx.doi.org/10.1109/iea.2018.8387144.
Full textReports on the topic "Total Interpretive Structural Modelling"
de Kemp, E. A., and K. B. Sprague. New interpretive tools for three-dimensional structural geological modelling: Bézier-based curves, ribbons, and skeletons. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2001. http://dx.doi.org/10.4095/212176.
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