SUMMARY In software intensive products such as cars or telecom systems, software has traditionally been associated with cost, and there has been no real perception of its value in relation to the entire product offering. However, because software is becoming a larger part of the main competitive advantage, driving innovation and product differentiation, hardware is becoming more standardized, thus the valuation of software is becoming critical. In existing literature, several value constructs and corresponding valuation/measurement solutions needed for making decisions about software product development are presented. However, the contributions are often isolated with respect to a certain perspective such as focusing on product's internal or external quality aspects only. Consequently, a complete view of value constructs relevant from different perspectives required for making decisions about software product development is missing. This paper presents a consolidated view of the software value concept utilizing the major perspectives and introduces a software value map. The created value map was evaluated through an industry case study through the development of impact evaluation patterns, which were subsequently used by professionals in industry, and experiences gathered. During industry evaluation, practitioners found substantial benefits of having a consolidated, vastly improved, and extended value aspect's view of software. Copyright © 2012 John Wiley & Sons, Ltd.

Software supporting an enterprise’s business, also known as a business support system, needs to support the correlation of activities between actors as well as influence the activities based on knowledge about the value networks in which the enterprise acts. This requires the use of policies and rules to guide or enforce the execution of strategies or tactics within an enterprise as well as in collaborations between enterprises. With the help of policies and rules, an enterprise is able to capture an actor’s intent in its business support system, and act according to this intent on behalf of the actor. Since the value networks an enterprise is part of will change over time the business intents’ life cycle states might change. Achieving the changes in an effective and efficient way requires knowledge about the affected intents and the correlation between intents. The aim of the study is to identify how a business support system can support continuous changes to business intents. The first step is to find a theoretical model which serves as a foundation for intent-driven systems. We conducted a case study using a focus group approach with employees from Ericsson. This case study was influenced by the spiral case study process. The study resulted in a model supporting continuous definition and execution of an enterprise. The model is divided into three layers; Define, Execute, and a common governance view layer. This makes it possible to support continuous definition and execution of business intents and to identify the actors needed to support the business intents’ life cycles. This model is supported by a meta-model for capturing information into viewpoints. The research question is addressed by suggesting a solution supporting continuous definition and execution of an enterprise as a model of value architecture components and business functions. The results will affect how Ericsson will build the business studio for their next generation business support systems.

Continuously achieving and maintaining competitive advantage is the critical survival factor for software-intensive product development companies undergoing digitalization transformation. These companies remain uncertain if investments in business modeling is sufficient to cope with rapidly changing business models, technology, and customer demands. We conducted a Systematic Literature Review using the snowballing methodology to explore the effects of business modeling on business flexibility and variability in the realization. Our results confirm a research gap regarding translating desired strategic flexibility into business options that can efficiently and effectively be implemented using software-based variability in the realization. We conclude that more research is needed consolidating business model innovation, experimentation, and operationalization. Building on theories for learning and knowledge creation, we propose a framework for describing change and analyzing strategic, tactical and operational choices in business model experimentation.

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