Gestão & Produção
Gestão & Produção
Artigo Original

Design Science Research in practice: review of applications in Industrial Engineering

Lucas Schmidt Goecks; Michele de Souza; Tatiane Pereira Librelato; Luiz Reni Trento

Downloads: 0
Views: 72


Abstract: The present study analyzes aspects of the application of the Design Science Research (DSR), identifies the problem classes, as well as the contributions and limitations in the implementation of the method in the various areas and subareas of Industrial Engineering. The research uses the method of systematic literature review through a review of articles using the Atlas.ti 8 software, it performs network analysis for classification by area and grouping by similarities, analyzing the aspects proposed in the objective of the study. Through investigation, it offers theoretical and practical contributions. First, it provides a comprehensive view of how DSR has been applied in research, identifying problem classes, artifacts, and classification areas in Industrial Engineering. Similarly, it contributes to a research agenda to replicate the method in emerging areas.


Design Science Research, Research method, Industrial Engineering, Improving process, Problem classes, Emergent topics


Amrollahi, A., & Rowlands, B. (2018). OSPM: a design methodology for open strategic planning. Information & Management, 55(6), 667-685.

Anke, J. (2019). Design-integrated financial assessment of smart services. Electronic Markets, 29(1), 19-35.

Arli, D., Bauer, C., & Palmatier, R. W. (2018). Relational selling: Past, present and future. Industrial Marketing Management, 69(1), 169-184.

Baierle, I. C., Schaefer, J. L., Sellitto, M. A., Fava, L. P., Furtado, J. C., & Nara, E. O. B. (2020). MOONA software for survey classification and evaluation of criteria to support decision-making for properties portfolio. International Journal of Strategic Property Management, 24(4), 226-236.

Bardin, L. (2011). Content analysis. São Paulo: Edições 70.

Braglia, M., Marrazzini, L., Padellini, L., and Rinaldi, R. (2020). Managerial and Industry 4.0 solutions for fashion supply chains. Journal of Fashion Marketing and Management: An International Journal, 25(1), 184-201.

Campos, F. C., & Alves, A. G., Fo. (2020). Proposal for a framework for production strategy utilizing Big Data: illustrative case in public service. Gestão & Produção, 27(3), e4651.

Carstensen, A. K., & Bernhard, J. (2019). Design science research – a powerful tool for improving methods in engineering education research. European Journal of Engineering Education, 44(1–2), 85-102.

Castillo-Martinez, A., Medina-Merodio, J.-A., Gutierrez-Martinez, J.-M., & Fernández-Sanz, L. (2021). Proposal for a maintenance management system in industrial environments based on ISO 9001 and ISO 14001 standards. Computer Standards & Interfaces, 73, 103453.

Cavata, J. T., Massote, A. A., Maia, R. F., & Lima, F. (2020). Highlighting the benefits of industry 4.0 for production: an agent-based simulation approach. Gestão & Produção, 27(3), e5619.

Chiu, V., Liu, Q., Muehlmann, B., & Baldwin, A. A. (2019). A bibliometric analysis of accounting information systems journals and their emerging technologies contributions. International Journal of Accounting Information Systems, 32, 24-43.

Corbin, J., & Strauss, A. (1990). Grounded theory research: procedures, canons and evaluative criteria. Zeitschrift für Soziologie, 19(6), 418-427.

Costa, E., Soares, A. L., & Sousa, J. P. (2020). Industrial business associations improving the internationalisation of SMEs with digital platforms: a design science research approach. International Journal of Information Management, 53, 102070.

Doyle, C., Sammon, D., & Neville, K. (2016). A design science research (DSR) case study: building an evaluation framework for social media enabled collaborative learning environments (SMECLEs). Journal of Decision Systems, 25(1), 125-144.

Dresch, A., Lacerda, D. P., & Antunes, J. A. V. A., Jr. (2015). Design science research: a method for science and technology advancement. New York: Springer.

Dresch, A., Veit, D. R., Lima, P. N., Lacerda, D. P., & Collatto, D. C. (2019). Inducing brazilian manufacturing SMEs productivity with lean tools. International Journal of Productivity and Performance Management, 68(1), 69-87.

Falagas, M. E., Pitsouni, E. I., Malietzis, G. A., & Pappas, G. (2008). Comparison of PubMed, Scopus, Web of Science, and Google Scholar: strengths and weaknesses. The FASEB Journal, 22(2), 338-342. PMid:17884971.

Flórez, C. A. C., Rosário, J. M., & Hurtado, D. A. (2020). Application of Automation and Manufacture techniques oriented to a service-based business using the Internet of Things (IoT) and Industry 4.0 concepts. Case study: smart Hospital. Gestão & Produção, 27(3), e5416.

Goecks, L. S., Santos, A. A., & Korzenowski, A. L. (2020). Decision-making trends in quality management: a literature review about Industry 4.0. Production, 30, 20190086.

Guirro, D. N., Asato, O. L., Santos, G. A., & Nakamoto, F. Y. (2020). Manufacturing operational management modeling using interpreted Petri nets. Gestão & Produção, 27(2), e3920.

Hao, J., Yu, Y., Law, R., & Fong, D. K. C. (2015). A genetic algorithm-based learning approach to understand customer satisfaction with OTA websites. Tourism Management, 48, 231-241.

Heathcote, D., Savage, S., & Hosseinian-Far, A. (2020). Factors affecting university choice behaviour in the UK higher education. Education in Science, 10(8), 199.

Hevner, A., Vom Brocke, J., & Maedche, A. (2019). Roles of digital innovation in design science research. Business & Information Systems Engineering, 61(1), 3-8.

Kakhki, M., & Gargeya, V. B. (2019). Information systems for supply chain management: a systematic literature analysis. International Journal of Production Research, 57(15-16), 5318-5339.

Korzenowski, A. L., Simões, W. L., Goecks, L. S., Gerhard, M., Fogaça, P., & Noronha, R.S. (2020). Economic sustainability of the X̅ implementation in uncapable processes. International Journal of Qualitative Research, 14(3), 881-894.

Krawatzeck, R., Hofmann, M., Jacobi, F., & Dinter, B. (2013). Constructing software-intensive methods: A design science research process with early feedback cycles. In: International Conference on Design Science Research in Information Systems (pp. 486-493). Berlin, Heidelberg: Springer.

Kuechler, B., & Vaishnavi, V. (2008). On theory development in design science research: anatomy of a research project. European Journal of Information Systems, 17(5), 489-504.

Lacerda, D. P., Dresch, A., Proença, A., & Antunes, J. A. V. A., Jr. (2013). Design science research: método de pesquisa para a engenharia de produção. Gestão & Produção, 20(4), 741-761.

Lehnert, M., Linhart, A., & Röglinger, M. (2016). Value-based process project portfolio management: integrated planning of BPM capability development and process improvement. Business Research, 9(2), 377-419.

Lima, A. L. S., Duarte, F., Madeira, V., Afonso, H. C. A.G., Camara, M. K., & Peixoto, A. (2019). Curriculum analysis of Production Engineering courses in Brazil and their relations with the areas defined by ABEPRO. In 2019 IEEE World Conference on Engineering Education (EDUNINE) (pp. 1-6). Lima: IEEE Xplore.

Mamoghli, S., Cassivi, L., & Trudel, S. (2018). Supporting business processes through human and IT factors: a maturity model. Business Process Management Journal, 24(4), 985-1006.

Manfio, N. M., & Lacerda, D. P. (2016). Definition of scope in new product development projects for the food industry: a proposed method. Gestão & Produção, 23(1), 18-36.

Manson, N. (2006). Is operations research really research?. ORiON, 22(2), 155-180.

Matana, G., Simon, A., Godinho, M., Fo., & Helleno, A. (2020). Method to assess the adherence of internal logistics equipment to the concept of CPS for industry 4.0. International Journal of Production Economics, 228, 107845.

Nfuka, E. N., & Rusu, L. (2013). Critical success framework for implementing effective IT Governance in Tanzanian public sector organizations. Journal of Global Information Technology Management, 16(3), 53-77.

Ngai, E. W. T., Poon, J. K. L., Suk, F. F. C., & Ng, C. C. (2009). Design of an RFID-based Healthcare Management System using an Information System Design Theory. Information Systems Frontiers, 11(4), 405-417.

Öhman, M. (2019). Design science in operations management: Extracting knowledge from maturing designs (Doctoral dissertation). Aalto University, Department of Industrial Engineering and Management, Finland.

Peffers, K., Rothenberger, M., Tuunanen, T., & Vaezi, R. (2012). Design science research evaluation. In K. Peffers, M. Rothenberger & B. Kuechler (Eds.), Lecture notes in Computer Science (pp. 398-410). Berlin: Springer Berlin Heidelberg.

Peffers, K., Tuunanen, T., Rothenberger, M. A., & Chatterjee, S. (2007). A design science research methodology for information systems research. Journal of Management Information Systems, 24(3), 45-77.

Pereira, G., Tzempelikos, N., Trento, L. R., Trento, C. R., Borchardt, M., & Viegas, C. V. (2019). Top managers’ role in key account management. Journal of Business and Industrial Marketing, 34(5), 977-993.

Raj, A., Dwivedi, G., Sharma, A., Jabbour, A. B. L. S., & Rajak, S. (2020). Barriers to the adoption of industry 4.0 technologies in the manufacturing sector: an inter-country comparative perspective. International Journal of Production Economics, 224, 107546.

Sanches, C., Meireles, M., & Silva, O. R. (2015). Framework for the generic process of diagnosis in quality problem solving. Total Quality Management & Business Excellence, 26(11-12), 1173-1187.

Saraswat, S. P., Anderson, D. M., & Chircu, A. M. (2014). Teaching business process management with simulation in graduate business programs: an integrative approach. Journal of Information Systems Education, 25(3), 221-232.

Schneider, P. (2018). Managerial challenges of Industry 4.0: an empirically backed research agenda for a nascent field. Review of Managerial Science, 12(3), 803-848.

Simon, H. (1996). The sciences of the artificial (3rd ed.). Cambridge: The MIT Press.

Sousa, A. M. H., & Barros, J. D. P., No. (2020). Is it possible to implement ERP in the production function of civil construction? Gestão & Produção, 27(3), e4445.

Takeda, H., Veerkamp, P., & Yoshikawa, H. (1990). Modeling design process. AI Magazine, 11(4), 37.

Teece, D. J. (2018). Business models and dynamic capabilities. Long Range Planning, 51(1), 40-49.

Tuunanen, T., Peffers, K., & Hebler, S. (2010). A requirements engineering method designed for the blind. In R. Winter, J. L. Zhao & S. Aier (Eds.), Global perspectives on Design Science Research (pp. 475-489). Berlin: Springer Berlin Heidelberg.

Van Aken, J. E. (2004). Management research based on the paradigm of the design scien- ces: the quest for field-tested and grounded technological rules. Journal of Management Studies, 41(2), 219-246.

Van Aken, J. E., Chandrasekaran, A., & Halman, J. (2016). Conducting and publishing design science research. Journal of Operations Management, 47-48(1), 1-8.

Venable, J., Pries-Heje, J., & Baskerville, R. (2012). A comprehensive framework for evaluation in design science research. In K. Peffers, M. Rothenberger & B. Kuechler (Eds.), Lecture notes in Computer Science (pp. 423-438). Berlin: Springer Berlin Heidelberg.

Vial, G. (2019). Understanding digital transformation: a review and a research agenda. The Journal of Strategic Information Systems, 28(2), 118-144.

Vieira, E. S., & Gomes, J. A. N. F. (2009). A comparison of Scopus and Web of Science for a typical university. Scientometrics, 81(2), 587-600.

Vosooghidizaji, M., Taghipour, A., & Canel-Depitre, B. (2020). Supply chain coordination under information asymmetry: a review. International Journal of Production Research, 58(6), 1805-1834.

Wang, M., Vogel, D., & Ran, W. (2011). Creating a performance-oriented e-learning environment: a design science approach. Information & Management, 48(7), 260-269.

Wolfswinkel, J. F., Furtmueller, E., & Wilderom, C. P. M. (2013). Using grounded theory as a method for rigorously reviewing literature. European Journal of Information Systems, 22(1), 45-55.

Wu, J. H. (2009). A design methodology for form-based knowledge reuse and representation. Information & Management, 46(7), 365-375.

Wu, J., Kang, J. Y. M., Damminga, C., Kim, H. Y., & Johnson, K. K. P. (2015). MC 2.0: testing an apparel co-design experience model. Journal of Fashion Marketing and Management, 19(1), 69-86.

617c25c1a95395264f4366f2 gp Articles

Gest. Prod.

Share this page
Page Sections