Adaptive choice-based conjoint analysis; Requirements engineering; Cloud service design; Cloud computing; User preferences
Naous Dana and Legner Christine (2017), Leveraging Market Research Techniques in IS – A Review of Conjoint Analysis in IS Research, in International Conference on Information Systems
, Seoul, South KoreaInternational Conference on Information Systems, Seoul, South Korea.
Naous Dana Schwarz Johannes and Legner Christine (2017), Analytics as a Service: Cloud Computing and the Transformation of Business Analytics Business Models and Ecosystems, in European Conference on Information Systems
, Guimarães, Portugal.
Giessmann Andrea Naous Dana and Legner Christine (2016), User-Oriented Cloud Service Design based on Market Research Techniques, in European Conference on Information Systems
, Istanbul, TurkeyEuropean Conference on Information Systems, Istanbul, Turkey.
For the IT industry, the cloud paradigm changes has a disruptive effect by fundamentally changing the way how IT resources are produced, distributed, consumed, and priced. It elicits a need for more thoroughly defined IT services with clearly specified delivery and pricing models. At the same time, the emerging markets for cloud services are very dynamic and user requirements are often not well known. Although cloud services will only be successful if they fit customer needs in terms of their functional, non-functional and economic properties, we are still lacking appropriate requirements engineering methods and techniques for designing high-utility cloud services. The purpose of this project is to improve our understanding of user preferences for cloud services in order to support their user-oriented design. More precisely, this project aims to develop and validate a systematic approach for eliciting and analysing customer preferences for cloud services and simulating market reaction to variations in cloud service design. Our approach leverages conjoint analysis, which is a statistical technique used in marketing research to determine how people value different features that make up an individual product or service. In the context of cloud services, it allows to measure the trade-offs between the functional and non-functional properties as well as economic and vendor-related aspects. The results of our research will comprise (1) a validated method component for requirements engineering for cloud services; and (2) two empirical studies of consumer preferences for two distinct types of cloud services. Thereby our research will not only contribute to methodology development, but also provide empirical insights into user preferences for cloud services. The potential contribution of this research is three-fold: First, from a theoretical perspective, we address the lack of techniques and methods for analysing and prioritising user requirements for commercial cloud services. By designing and validating a method component which adapts proven marketing research techniques to cloud services design, we will contribute to enhancing the existing requirements engineering methods. Second, from a practical perspective, designing high-utility cloud services is challenging given the large number of design decisions and the uncertainty in user preferences in immature markets. Understanding the factors in designing cloud services that are most influential on users’ choice or decision making will help cloud service providers in designing high-utility cloud services. Third, from a societal and economic perspective, cloud infrastructures and services are expanding the scope of digital services to the individual users and allow improving their daily lives. This explains why cloud services in domains like healthcare, green energy or city services receive significant attention from governments and industry. Since the design of high-utility cloud services will be a key challenge in the upcoming years, our project results will be relevant to the society and industry at large.