Questionnaires using Likert-type rating scales are an important source of data in marketing research. Researchers use different rating scale formats with varying numbers of response categories and varying label formats (e.g., 7-point rating scales labeled at the endpoints, fully labeled 5-point scales, etc.) but have few guidelines when selecting a specific format. Drawing from the literature on response styles, we formulate hypotheses on the effect of the labeling of response categories and the number of response categories on the net acquiescence response style, extreme response style and misresponse to reversed items. We test the hypotheses in an online survey (N = 1207) with eight experimental conditions and a follow-up study with two experimental conditions (N = 226). We find evidence of strong effects of scale format on response distributions and misresponse to reversed items, and we formulate recommendations on the choice of a scale format.

This study provides an empirical perspective of the influence of online health information search on patient co-creation in healthcare service delivery at the micro level. The study primarily sheds light on the influence of information seeking on the clinical encounter process and how this cumulatively impacts on the expected service outcomes. The following research questions are addressed: 1. How do patients search for information and what motivates them to seek health related information? 2. What impact does online information seeking have on patients’ engagement in healthcare clinical encounters? 3. How is co-creation modeled in healthcare to ascertain the cumulative effects of ICT on the expected outcomes at the micro level?

While the smart city gains global attention as a popular umbrella term for digitally enabled sustainable city development, city administrations are faced with the managerial challenge that comes with a strategic digital transformation. Smart city projects form the frontline of smart city strategies. In these smart projects, cities find a way to implement the principles of the smart city. Many of these are high-visibility projects with substantial budget implications, and therefore require scrutiny by means of a formal selection and evaluation process. In this research-in-progress paper we propose the outline for a project-level smart value assessment instrument. The instrument should serve at the same time as a tool for smart city managers to assess and plan upfront how a project will contribute to reach the city's smart city ambition, as well as a post factum evaluation. The conceptual instrument has been developed in action-design research mode in collaboration with practitioners in the city of Brisbane, Australia and is demonstrated by mapping four smart city initiatives in different international contexts.

Formal Concept Analysis (FCA) is an unsupervised clustering technique and many scientific papers are devoted to applying FCA in Information Retrieval (IR) research. We collected 103 papers published between 2003-2009 which mention FCA and information retrieval in the abstract, title or keywords. Using a prototype of our FCA-based toolset CORDIET, we converted the pdf-files containing the papers to plain text, indexed them with Lucene using a thesaurus containing terms related to FCA research and then created the concept lattice shown in this paper. We visualized, analyzed and explored the literature with concept lattices and discovered multiple interesting research streams in IR of which we give an extensive overview. The core contributions of this paper are the innovative application of FCA to the text mining of scientific papers and the survey of the FCA-based IR research.

The purpose of this research project is to explore and demonstrate the dynamics behind the value creation process in the context of sustainability. As it currently stands, the service dominant logic as a theoretical proposition is not a sustainable one. In fact, it may serve to undermine the very progress being made for a sustainable future.

This paper discusses the relevant literature on collaboration in product development and proposes a framework for exploring collaboration proneness in development processes. The framework proposes valuable insight into managing collaboration in practice, as it provides an evaluation tool for managers to determine their internal team competences and gaps to be addressed. Furthermore, it enables companies to assess potential NPD partners outside company boundaries. A test on an industrial case demonstrates the applicability of the theoretically derived framework to practice.

In this paper we introduce a novel human-centered data mining software system which was designed to gain intelligence from unstructured textual data. The architecture takes its roots in several case studies which were a collaboration between the Amsterdam-Amstelland Police, GasthuisZusters Antwerpen (GZA) hospitals and KU Leuven. It is currently being implemented by bachelor and master students of Moscow Higher School of Economics. At the core of the system are concept lattices which can be used to interactively explore the data. They are combined with several other complementary statistical data analysis techniques such as Emergent Self Organizing Maps and Hidden Markov Models.