[期刊]
The current state of software license renewals in the I.T. industry
作者:
Ghosh, Aindrila;Nashaat, Mona;Miller, James
发表时间:
2019
来源期刊:
Information and software technology
年/卷/期:
2019 / 108 / Apr.
Context: The software industry has changed significantly in the 21st century; no longer is it dominated by organizations seeking to sell products directly to customers, instead most multinational organizations nowadays provide services via licensing agreements. These licenses are for a fixed-duration; and hence, the question of their renewal becomes of paramount importance for the selling organization's revenue.Objective: Despite its financial impact, the topic of license renewal strategies, processes, tools, and support receives very limited attention in the research literature. Hence, it is believed that an interesting research question is: What is the state of current industrial practice in this essential field?Method: To initially explore the topic of license renewals, this paper implements the Grounded theory method. To implement the method, semi-structured, cross-sectional, anonymous, selfreported interviews are carried out with 20 professionals from multiple organizations, later the Constant Comparative Method is used to analyse the collected data.Results: This paper presents a synthesized picture of the current industrial practice of the end-to-end software license renewal process. Alongside, it also identifies a set of challenges and risk factors that impact on renewal decisions of customers, hence on the overall revenue of seller organizations. Finally, using structured brainstorming techniques, this paper identifies 11 future research directions, that can help organizations with the mitigation of the risks in the license renewal process.Conclusion: It is concluded that lack of effective communication among stakeholders, the absence of customer trust, and scarcity of value generated from purchased licenses are among the primary drivers that influence renewal decisions. Also, there is a need to invest in intelligent automation along with artificial intelligence enabled analytics in order to enhance customer satisfaction.