DOI: 10.5061/dryad.x69p8cznr
title: Assessing the influence of organizational factors on knowledge sharing in inter-firm collaborations

description: Collaborations between media organisations are becoming an increasingly
 common practice in the field of journalism. Academic research, so far,
 mostly focused on large-scale investigations and communities of digital
 outlets, such as fact-checkers networks. However, new types of inter-firm
 partnerships are emerging, namely between legacy media and tech startups,
 towards media innovation and digital transformation. The paper to which
 this database is connected aims to advance the theoretical understanding
 of the relationship between collaborations and media innovation. We
 formulate an original analytical model to assess the influence of
 organisational factors of collaborations on knowledge sharing, a key
 condition for explorative innovation. Based on the experience of the
 Stars4Media programme, we present an empirical application of the
 analytical model (based on this data-set) to a case study of thirty
 collaborative projects involving seventy-six European media companies.
description: <strong>How was this dataset
 collected?</strong> The
 empirical analysis draws on a structured survey filled in by the 76 team
 leaders of the companies involved. Circa 50% of the companies represented
 in the survey were micro-size companies (&lt;10 employees), the
 remaining 50% was composed of a mix of small- (10–50 employees), medium- (50–250 employees) and
 large-sized companies (&gt;250 employees). This cross-sectional study,
 conducted through an online survey designed in Google Forms, was issued at
 the end of the implementation phase of the Second Edition of the
 Stars4Media programme, making this study a cross-sectional, correlational
 research (Field, 2018). The 76 team leaders were asked to provide answers
 on behalf of their team, after consulting with them. To avoid multiple
 interpretations of the main technical vocabulary and concepts, a glossary
 was provided to all respondents. Filling in the survey was part of the
 mandatory project deliverables for the companies involved, but the
 companies were made aware that their responses to the survey would be used
 exclusively for research purposes. <strong>How has it been
 processed?</strong> Once
 the responses to the survey were collected, the data were imported in SPSS
 Statistics. Ordinal independent and dependent variables were created and
 were given a label for each of the 3 organizational factors (independent
 variables) and the knowledge sharing (dependent variable).
 The first organizational factor is
 'centrality of multidisciplinarity of activities' and
 corresponds to question 18 (Independent variable
 1)<br> The
 second organizational factor is 'intensity of collaboration' and
 corresponds to question 17 (Independent variable
 2)<br> The
 third organizational factor is 'agency of innovation design' and
 corresponds to question 11a (Independent variable
 3)<br> The
 two dependent variables
 were knowledge sharing (Q22) and capacity to design innovations
 (Q23). Descriptive statistics, particularly
 cross-tabulation, were chosen as the method of data analysis (Momeni et
 al., 2018). The observed data were analysed to assess whether there was an
 association between two variables (an independent one and a dependent one)
 observed in each test of the four tests conducted, applying the Pearson
 Chi-Squared test, and to assess the strength of this association, looking
 at Cramer’s V (Field, 2018; Momeni et al, 2018). 
 Four distinct tests were conducted. The first
 three tests were designed to observe, separately, the association of each
 of the three structural/organisational factors (independent variables)
 with knowledge-sharing (the dependent variable) of the teams involved. A
 fourth test was conducted to observe if a certain level of
 knowledge-sharing (independent variable) would correspond to a certain
 level of innovation capacity (dependent variable) gained as a result of
 the collaboration.
description: Microsoft Excel, SPSS Statistics