English
Bibtex
Cite as text
@Select Types{,
Journal = "Band-2",
Title= "Designing Analytics-Based Services – Exploring Design Requirements for Methodological Tool Assistance in Service Design Teams",
Author= "Fabian Hunke, Florian Kiefer",
Doi= "https://doi.org/10.30844/wi_2020_t2-hunke",
Abstract= "Analytics-based services (ABS) apply analytical methods to data in order to enable customers to make better decisions and solve more complex problems. While it is widely acknowledged that ABS pave the way for new value creation opportunities, surprisingly little is known about their systematic design. Service design teams still struggle to create ABS solutions systematically, i.e. to define what is to be done, how this is going to be achieved and how decisions are taken during ABS design projects. In this research, we report on the first iteration of our design science research project which aims to build design knowledge on methodological tools that can support service design teams in this particular context. We derive and evaluate four meta-requirements and four design principles – thus contributing to a more profound design knowledge base that can support researchers in developing new methodological tools in the field of ABS in the future.
",
Keywords= "Analytics-Based Services, Service Design, Methodological Tool",
}
Fabian Hunke, Florian Kiefer: Designing Analytics-Based Services – Exploring Design Requirements for Methodological Tool Assistance in Service Design Teams. Online: https://doi.org/10.30844/wi_2020_t2-hunke (Abgerufen 23.11.24)
Open Access
Abstract
Abstract
Analytics-based services (ABS) apply analytical methods to data in order to enable customers to make better decisions and solve more complex problems. While it is widely acknowledged that ABS pave the way for new value creation opportunities, surprisingly little is known about their systematic design. Service design teams still struggle to create ABS solutions systematically, i.e. to define what is to be done, how this is going to be achieved and how decisions are taken during ABS design projects. In this research, we report on the first iteration of our design science research project which aims to build design knowledge on methodological tools that can support service design teams in this particular context. We derive and evaluate four meta-requirements and four design principles – thus contributing to a more profound design knowledge base that can support researchers in developing new methodological tools in the field of ABS in the future.
Keywords
Schlüsselwörter
Analytics-Based Services, Service Design, Methodological Tool
References
Referenzen
1. Legner, C., Eymann, T., Hess, T., Matt, C., Böhmann, T., Drews, P., Mädche, A., Urbach, N., Ahlemann, F.: Digitalization: Opportunity and Challenge for the Business and Information Systems Engineering Community. Bus. Inf. Syst. Eng. 59, 301–308 (2017).
2. Brynjolfsson, E., Mcafee, A.: The Business of Artificial Intelligence: What It Can – and Cannot – Do for Your Organization. Harv. Bus. Rev. 95, 3–11 (2017).
3. Huang, M.H., Rust, R.T.: Technology-driven service strategy. J. Acad. Mark. Sci. 45, 906– 924 (2017).
4. Troilo, G., De Luca, L.M., Guenzi, P.: Linking Data-Rich Environments with Service Innovation in Incumbent Firms: A Conceptual Framework and Research Propositions. J. Prod. Innov. Manag. 34, 617–639 (2017).
5. Davenport, T.H.: Analytics 3.0. Harv. Bus. Rev. 91, 64 (2013).
6. Hunke, F., Engel, C., Schüritz, R., Ebel, P.: Understanding the Anatomy of Analytics- Based Services – a Taxonomy to Conceptualize the Use of Data and Analytics in Services. ECIS 2019 Proc. 1–15 (2019).
7. Ostrom, A.L., Parasuraman, A., Bowen, D.E., Patrício, L., Voss, C.A.: Service Research Priorities in a Rapidly Changing Context. J. Serv. Res. 18, 127–159 (2015).
8. Demirkan, H., Bess, C., Spohrer, J., Rayes, A., Allen, D., Moghaddam, Y.: Innovations with smart service systems: Analytics, big data, cognitive assistance, and the internet of everything. Commun. Assoc. Inf. Syst. 37, 733–752 (2015).
9. Rust, R.T., Huang, M.-H.: The Service Revolution and the Transformation of Marketing Science. Mark. Sci. 33, 206–221 (2014).
10. Saarijärvi, H., Grönroos, C., Kuusela, H.: Reverse use of customer data: Implications for service-based business models. J. Serv. Mark. 28, 529–537 (2014).
11. Davenport, T.H., Lucker, J.: Running on data. Deloitte Rev. 5–15 (2015).
12. Rizzon, E., Kayande, U., Chaudhary, V., Young, C.: The Untapped Value of Analytics, https://www.atkearney.com/analytics/article?/a/the-untapped-value-of-analytics.
13. Patrício, L., Gustafsson, A., Fisk, R.: Upframing Service Design and Innovation for Research Impact. J. Serv. Res. 21, 3–16 (2018).
14. Lim, C.-H., Kim, M.-J., Kim, K.-H., Kim, K.-J., Maglio, P.P.: Using data to advance service: managerial issues and theoretical implications from action research. J. Serv. Theory Pract. 28, 99–128 (2018).
15. Günther, W., Hosein, M., Huysman, M., Feldberg, F.: Rushing for Gold : Tensions in Creating and Appropriating Value from Big Data. In: ICIS 2017 Proceedings. pp. 1–9 (2017).
16. Goldstein, S.M., Johnston, R., Duffy, J.A., Rao, J.: The Service Concept: The Missing Link in Service Design Research? J. Oper. Manag. 20, 121–134 (2002).
17. Edvardsson, B., Olsson, J.: Key concepts for new service development. Serv. Ind. J. 16, 140–164 (1996).
18. Figl, K., Recker, J.: Exploring cognitive style and task-specific preferences for process representations. Requir. Eng. 21, 63–85 (2016).
19. McAfee, A., Brynjolfsson, E.: Big Data : The Management Revolution. Harv. Bus. Rev. 90, 61–67 (2012).
20. Sharma, R., Mithas, S., Kankanhalli, A.: Transforming decision-making processes: A research agenda for understanding the impact of business analytics on organisations. Eur. J. Inf. Syst. 23, 433–441 (2014).
21. Watson, H.: Tutorial: Business Intelligence – Past, Present, and Future. Commun. Assoc. Inf. Syst. 25, 487–510 (2009).
22. Hunke, F., Seebacher, S., Schüritz, R., Satzger, G.: Pathways from Data to Value : Identifying Strategic Archetypes of Analytics-Based Services. Proc. 15th Int. Conf. Wirtschaftsinformatik (2020).
23. Huang, M.H., Rust, R.T.: IT-Related Service: A Multidisciplinary Perspective. J. Serv. Res. 16, 251–258 (2013).
24. Allmendinger, G., Lombreglia, R.: Four Strategies for the Age of Smart Services. Harv. Bus. Rev. 83, 131–145 (2005).
25. Beverungen, D., Müller, O., Matzner, M., Mendling, J., Vom Brocke, J.: Conceptualizing smart service systems. Electron. Mark. 29, 7–18 (2019).
26. Woerner, S.L., Wixom, B.H.: Big data: Extending the business strategy toolbox. J. Inf. Technol. 30, 60–62 (2015).
27. Patrício, L., Fisk, R.P., e Cunha, J.F., Constantine, L.: Multilevel service design: From customer value constellation to service experience blueprinting. J. Serv. Res. 14, 180–200 (2011).
28. Kim, K.-J., Meiren, T.: New Service Development Process. In: Salvendy, G. and Karwowski, W. (eds.) Introduction to Service Engineering. pp. 253–267. John Wiley & Sons, New Jersey (2010).
29. Bettencourt, L.: Service Innovation: How to go from customer needs to breakthrough services. McGraw-Hill Education, New York (2010).
30. Avdiji, H., Elikan, D., Missonier, S., Pigneur, Y.: Designing Tools for Collectively Solving Ill-Structured Problems. Proc. 51st Hawaii Int. Conf. Syst. Sci. 400–409 (2018).
31. Mastrogiacomo, S., Missonier, S., Bonazzi, R.: Talk Before It’s Too Late: Reconsidering the Role of Conversation in Information Systems Project Management. J. Manag. Inf. Syst. 31, 47–78 (2014).
32. Osterwalder, A., Pigneur, Y.: Business Model Generation. John Wiley & Sons, Hoboken (2010).
33. Eppler, M., Bresciani, S.: Visualization in management: From communication to collaboration. J. Vis. Lang. Comput. 24, 146–149 (2013).
34. Hevner, A.R., March, S.T., Park, J., Ram, S.: Design Science in Information Systems Research. MIS Q. 28, 75–105 (2004).
35. Kuechler, B., Vaishnavi, V.: On Theory Development in Design Science Research: Anatomy of a Research Project. Eur. J. Inf. Syst. 17, 489–504 (2008).
36. Hunke, F., Engel, C.: Utilizing Data and Analytics to Advance Service Towards Enabling Organizations to Successfully Ride the Next Wave of Servitization. In: Satzger, G., Patricio, L., Zaki, M., Kühl, N., and Hottum, P. (eds.) Exploring Service Science, 9th International Conference, IESS 2018. pp. 219–231. Springer, Cham (2018).
37. Porter, M., Heppelmann, J.: How Smart, Connected Products are Transforming Companies. Harvard Buisness Rev. 93, 97–114 (2015).
38. Bryman, A.: Social Research Methods. Oxford University Press, Oxford (2012).
39. Krippendorff, K.: Content Analysis: An Introduction to Its Methodology. Sage, Los Angeles (2013).
40. Charmaz, K.: Constructing grounded theory: a practical guide through qualitative analysis. Sage, London (2006).
41. Walls, J.G., Widmeyer, G.R., El Sawy, O.A.: Building an information system design theory for vigilant EIS. Inf. Syst. Res. 3, 36–59 (1992).
42. Baskerville, R., Pries-Heje, J.: Explanatory Design Theory. Bus. Inf. Syst. Eng. 2, 271–282 (2010).
43. Brenner, W., Uebernickel, F., Abrell, T.: Design Thinking as Mindset, Process, and Toolbox. In: Brenner, W. and Uebernickel, F. (eds.) Design Thinking for Innovation. pp. 3–21. Springer, Cham (2016).
44. Gregor, S.: The nature of theory in Information Systems. MIS Q. 30, 611–642 (2006).
45. Tremblay, M., Hevner, A., Berndt, D.: The Use of Focus Groups in Design Science Research. In: Hevner, A. and Chatterjee, S. (eds.) Design Research in Information Systems. pp. 121–143. Springer, Boston (2010).
46. Hevner, A.R.: A three cycle view of design science research. Scand. J. Inf. Syst. 19, 87–92 (2007).
47. Patton, M.Q.: Qualitative evaluation and research methods. Sage, Thousand Oaks (1990).
48. Hunke, F., Schüritz, R.: Smartere Produkte durch analysebasierte Dienstleistungen – Ein methodisches Werkzeug zur strukturierten Entwicklung. HMD Prax. der Wirtschaftsinformatik. 56, 514–529 (2019).
49. Cochlear: Hear your way, https://www.hearyourway.com/uk/n7/adults.
50. Gregor, S., Hevner, A.R.: Positioning and Presenting Design Science Research for Maximum Impact. MIS Q. 37, 337–355 (2013).