This paper contributes a conceptual framework to guide the strategic alignment of software selection criteria using a new method - Decision Resonance Method and an established method - ELECTRE III within the existing decision theory frameworks. The analysis contributes empirically tested software selection criteria that will improve the categorization of decision implications This study provides input for decision theory extensions related to information, the value of problem structuring, and its application to emerging research chasing implicit decisions. Managerial implications include enhancing awareness of implicit assumptions when replicating a previous strategic decision-context (culture), and when considering how a decision environment or set of alternatives has subtly drifted rendering uncertainty or missed dynamic opportunities. Industry will benefit from the associated modeling correctness by appreciating the role of less visible weighting error in overlooked alternatives. Applied to a 10-alternative, 10-criteria matrix of real-world constraints within Coimbatore’s manufacturing ecosystem, both approaches converge in the elimination of alternatives that are not suited, however, they differ in the top ranking recommendations. Mastercam is identified as the most appropriate decision for immediate implementation while Siemens NX is the most suitable long-term investment .The comparative analysis exposes the philosophical distinctions between the two approaches and provides insights that can be operationalized for the adoption of technology by SMEs.

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1. making methods for material selection. Materials Today: Proceedings, 3(6), 1894-1902.
2. Coimbatore District Small Industries Association. (2023). Annual Technology Adoption Survey Report. CODISSIA Publications.
3. Figueira, J., Greco, S., & Ehrgott, M. (2005). Multiple Criteria Decision Analysis: State of the Art Surveys. Springer.
4. Govindan, K., Rajendran, S., Sarkis, J., & Murugesan, P. (2015). Multi criteria decision making approaches for green supplier evaluation and selection: A literature review. Journal of Cleaner Production, 98, 66-83.
5. Greco, S., Figueira, J., & Ehrgott, M. (2016). Multiple Criteria Decision Analysis: State of the Art Surveys(Vol. 233). Springer.
6. Ishizaka, A., & Nemery, P. (2013). Multi-criteria Decision Analysis: Methods and Software. John Wiley & Sons.
7. Mardani, A., Jusoh, A., Nor, K., Khalifah, Z., Zakwan, N., & Valipour, A. (2015). Multiple criteria decision-making techniques and their applications–a review of the literature from 2000 to 2014. Economic Research-Ekonomska Istraživanja, 28(1), 516-571.
8. Roy, B. (1996). Multicriteria Methodology for Decision Aiding. Springer.
9. Sharma, M., & Rawani, A. M. (2016). Multi-criteria decision making approaches for supplier evaluation and selection: A review. International Journal of Engineering Research and Applications, 6(5), 55-61.
10. Tamil Nadu Industrial Development Corporation. (2023). Manufacturing Sector Development Report 2023. Government of Tamil Nadu.
11. Zavadskas, E. K., Turskis, Z., & Kildienė, S. (2014). State of art surveys of overviews on MCDM/MADM methods. Technological and Economic Development of Economy, 20(1), 165-179.

This paper contributes a conceptual framework to guide the strategic alignment of software selection criteria using a new method - Decision Resonance Method and an established method - ELECTRE III within the existing decision theory frameworks. The analysis contributes empirically tested software selection criteria that will improve the categorization of decision implications This study provides input for decision theory extensions related to information, the value of problem structuring, and its application to emerging research chasing implicit decisions. Managerial implications include enhancing awareness of implicit assumptions when replicating a previous strategic decision-context (culture), and when considering how a decision environment or set of alternatives has subtly drifted rendering uncertainty or missed dynamic opportunities. Industry will benefit from the associated modeling correctness by appreciating the role of less visible weighting error in overlooked alternatives. Applied to a 10-alternative, 10-criteria matrix of real-world constraints within Coimbatore’s manufacturing ecosystem, both approaches converge in the elimination of alternatives that are not suited, however, they differ in the top ranking recommendations. Mastercam is identified as the most appropriate decision for immediate implementation while Siemens NX is the most suitable long-term investment .The comparative analysis exposes the philosophical distinctions between the two approaches and provides insights that can be operationalized for the adoption of technology by SMEs.

🔒 This is a subscription article

Full text is available to subscribers and institutional members. Please choose an option below to access it.

1. making methods for material selection. Materials Today: Proceedings, 3(6), 1894-1902.
2. Coimbatore District Small Industries Association. (2023). Annual Technology Adoption Survey Report. CODISSIA Publications.
3. Figueira, J., Greco, S., & Ehrgott, M. (2005). Multiple Criteria Decision Analysis: State of the Art Surveys. Springer.
4. Govindan, K., Rajendran, S., Sarkis, J., & Murugesan, P. (2015). Multi criteria decision making approaches for green supplier evaluation and selection: A literature review. Journal of Cleaner Production, 98, 66-83.
5. Greco, S., Figueira, J., & Ehrgott, M. (2016). Multiple Criteria Decision Analysis: State of the Art Surveys(Vol. 233). Springer.
6. Ishizaka, A., & Nemery, P. (2013). Multi-criteria Decision Analysis: Methods and Software. John Wiley & Sons.
7. Mardani, A., Jusoh, A., Nor, K., Khalifah, Z., Zakwan, N., & Valipour, A. (2015). Multiple criteria decision-making techniques and their applications–a review of the literature from 2000 to 2014. Economic Research-Ekonomska Istraživanja, 28(1), 516-571.
8. Roy, B. (1996). Multicriteria Methodology for Decision Aiding. Springer.
9. Sharma, M., & Rawani, A. M. (2016). Multi-criteria decision making approaches for supplier evaluation and selection: A review. International Journal of Engineering Research and Applications, 6(5), 55-61.
10. Tamil Nadu Industrial Development Corporation. (2023). Manufacturing Sector Development Report 2023. Government of Tamil Nadu.
11. Zavadskas, E. K., Turskis, Z., & Kildienė, S. (2014). State of art surveys of overviews on MCDM/MADM methods. Technological and Economic Development of Economy, 20(1), 165-179.