Measuring the promise of open data: Development of the Impact Monitoring Framework

It is a challenge to measure the impact of releasing data to the public since the effects may not be directly linked to particular open data activities or substantial impact may only occur several years after publishing the data. This paper proposes a framework to assess the impact of releasing open data by applying the Social Return on Investment (SROI) approach. SROI was developed for organizations intended to generate social and environmental benefits thus fitting the purpose of most open data initiatives. We link the four steps of SROI (input, output, outcome, impact) with the 14 high-value data categories of the G8 Open Data Charter to create a matrix of open data examples, activities, and impacts in each of the data categories. This Impact Monitoring Framework helps data providers to navigate the impact space of open data laying out the conceptual basis for further research.

Measuring citizens' implicit and explicit attitudes towards the European Union

Studies assessing citizens’ attitudes towards Europe have mostly used explicit concepts and measures. However, psychologists have shown that human behaviour is not only determined by explicit attitudes which can be assessed via self-report, but also by implicit attitudes which require indirect measurement. We combine a self-report questionnaire with an implicit Affective Misattribution Procedure for the first time in an online environment to estimate the reliability, validity and predictive power of this implicit measure for the explanation of European Union-skeptical behaviour. Based on a survey with a sample representative for Germany, we found evidence for good reliability and validity of the implicit measure. In addition, the implicit attitude had a significant incremental impact beyond explicit attitudes on citizens’ proneness to engage in EU-skeptical information and voting behaviour.

How comparable are parallel corpora? Measuring the distribution of general vocabulary and connectives

In this paper, we question the homogeneity of a large parallel corpus by measuring the similarity between various sub-parts. We compare results obtained using a general measure of lexical similarity based on χ2 and by counting the number of discourse connectives. We argue that discourse connectives provide a more sensitive measure, revealing differences that are not visible with the general measure. We also provide evidence for the existence of specific characteristics defining translated texts as opposed to non-translated ones, due to a universal tendency for explicitation.

Development of a questionnaire measuring Attitudes towards Psychological Online Interventions–the APOI

BACKGROUND: Only a minority of people suffering from depression receive adequate treatment. Psychological Online Interventions (POIs) could help bridge existing treatment gaps and augment the effectiveness of current treatments. Apart from effectiveness, user acceptance of POIs must be achieved if such interventions are to be broadly implemented in existing health-care. Valid measurement tools examining attitudes towards POIs are lacking. Therefore, we examined the dimensionality of attitudes towards POIs, developed a novel questionnaire, the Attitudes towards Psychological Online Interventions Questionnaire (APOI), and gathered data to examine its reliability. METHODS: We recruited a sample of 1004 adults with mild to moderate depressive symptoms from a range of sources. We constructed a set of 35 items based on literature review as well as expert and patient queries. The initial items were subjected to an exploratory factor analysis (EFA) in a randomly selected subsample. A final set of 16 items was subjected to a confirmatory factor analysis (CFA) to cross-validate the factor structure in a separate subsample. RESULTS: The EFA revealed four dimensions: "Scepticism and Perception of Risks", "Confidence in Effectiveness", "Technologization Threat" and "Anonymity Benefits". The model fit in the CFA was excellent relating to all applied indices (χ(2)=105.816, p=.651; SRMR=.042; RMSEA=.013; CFI=.994) and the APOI total scale showed acceptable to good internal consistency. CONCLUSIONS: Further research with the APOI might facilitate the development and dissemination of POIs and, ultimately, help improve the quality of care for people experiencing depressive symptoms.

Measuring Spatial Presence: Introducing and Validating the Pictorial Presence SAM

The aim of the present study was to develop a pictorial presence scale using selfassessment- manikins (SAM). The instrument assesses presence sub-dimensions (selflocation and possible actions) as well as presence determinants (attention allocation, spatial situation model, higher cognitive involvement, and suspension of disbelief). To qualitatively validate the scale, think-aloud protocols and interviews (n = 12) were conducted. The results reveal that the SAM items are quickly filled out as well as easily, intuitively, and unambiguously understood. Furthermore, the instrument’s validity and sensitivity was quantitatively examined in a two-factorial design (n = 317). Factors were medium (written story, audio book, video, and computer game) and distraction (non-distraction vs. distraction). Factor analyses reveal that the SAM presence dimensions and determinants closely correspond to those of the MEC Spatial Presence Questionnaire, which was used as a comparison measure. The findings of the qualitative and quantitative validation procedures show that the Pictorial Presence SAM successfully assesses spatial presence. In contrast to the verbal questionnaire data (MEC), the significant distraction effect suggests that the new scale is even more sensitive. This points out that the scale can be a useful alternative to existing verbal presence selfreport measures.

Measuring the Social Identity of Entrepreneurs: Scale Development and International Validation

Recent research indicates that social identity theory offers an important lens to improve our understanding of founders as enterprising individuals, the venture creation process, and its outcomes. Yet, further advances are hindered by the lack of a valid scale that could be used to measure founders' social identities - a problem that is particularly severe because social identity is a multidimensional construct that needs to be assessed properly so that organizational phenomena can be understood. Drawing on social identity theory and the systematic classification of founders' social identities (Darwinians, Communitarians, Missionaries) provided in Fauchart and Gruber (2011), this study develops and empirically validates a 12-item scale that allows scholars to capture the multidimensional nature of social identities of entrepreneurs. Our validation tests are unusually comprehensive and solid, as we not only validate the developed scale in the Alpine region (where it was originally conceived), but also in 12 additional countries and the Anglo-American region. Scholars can use the scale to identify founders' social identities and to relate these identities to micro-level processes and outcomes in new firm creation. Scholars may also link founders' social identities to other levels of analysis such as industries (e.g., industry evolution) or whole economies (e.g., economic growth).

Measuring the Social Identity of Entrepreneurs: Scale Development and International Validation

Social identity theory offers an important lens to improve understanding of founders as enterprising individuals, the venture creation process, and its outcomes. Yet, further advances are hindered by the lack of valid scales to measure founders’ social identities. Drawing on social identity theory and a systematic classification of founders’ social identities (Darwinians, Communitarians, and Missionaries), we develop and test a corresponding 15-item scale in the Alpine region and validate it in 13 additional countries and regions. The scale allows identifying founders’ social identities and relating them to processes and outcomes in entrepreneurship. The scale is available online in 15 languages.