University of Oulu

P. Rodríguez, E. Mendes and B. Turhan, "Key Stakeholders’ Value Propositions for Feature Selection in Software-Intensive Products: An Industrial Case Study," in IEEE Transactions on Software Engineering, vol. 46, no. 12, pp. 1340-1363, 1 Dec. 2020, doi: 10.1109/TSE.2018.2878031

Key stakeholders’ value propositions for feature selection in software-intensive products : an industrial case study

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Author: Rodríguez, Pilar1; Mendes, Emilia1,2; Turhan, Burak3
Organizations: 1University of Oulu, Finland
2Blekinge Institute of Technology, Sweden
3Monash University, Australia
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 2 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2018
Publish Date: 2018-11-08


Numerous software companies are adopting value-based decision making. However, what does value mean for key stakeholders making decisions? How do different stakeholder groups understand value? Without an explicit understanding of what value means, decisions are subject to ambiguity and vagueness, which are likely to bias them. This case study provides an in-depth analysis of key stakeholders’ value propositions when selecting features for a large telecommunications company’s software-intensive product. Stakeholder’ value propositions were elicited via interviews, which were analyzed using Grounded Theory coding techniques (open and selective coding). Thirty-six value propositions were identified and classified into six dimensions: customer value, market competitiveness, economic value/profitability, cost efficiency, technology & architecture, and company strategy. Our results show that although propositions in the customer value dimension were those mentioned the most, the concept of value for feature selection encompasses a wide range of value propositions. Moreover, stakeholder groups focused on different and complementary value dimensions, calling to the importance of involving all key stakeholders in the decision making process. Although our results are particularly relevant to companies similar to the one described herein, they aim to generate a learning process on value-based feature selection for practitioners and researchers in general.

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Series: IEEE transactions on software engineering
ISSN: 0098-5589
ISSN-E: 1939-3520
ISSN-L: 0098-5589
Volume: 46
Issue: 12
Pages: 1340 - 1363
DOI: 10.1109/TSE.2018.2878031
Type of Publication: A1 Journal article – refereed
Field of Science: 113 Computer and information sciences
Funding: This research has been carried out within the FiDiPro VALUE project number 40150/14, which is funded by Tekes (the Finnish Funding Agency for Technology and Innovation).
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