How User‐centric Innovation is Affecting Stakeholder Marketing Strategies: Exploratory Findings from the Music Industry

This paper empirically explores how user‐centric innovation (UCI) in the music industry is affecting how key stakeholder groups are approaching and developing their marketing (and associated management) strategies. The three‐stage interview‐based research methodology consisted of 52 semi‐structured in‐depth interviews with UCI experts and artist managers, as well as representatives from major record labels. The findings make four substantial contributions to theory and practice in the interrelated fields of UCI, marketing and the music industry. First, they provide practical and pragmatic insights for industry practitioners on how different UCI marketing approaches are affecting their management strategies. Second, they take steps towards answering many of the identified gaps in research and knowledge relating to the concept of UCI. Third, they present theoretical models as a foundation for which new UCI marketing theory can be built upon. Last, they offer directions for future research to advance our empirical findings.</jats:p

Rock fall susceptibility assessment along a mountainous road: an evaluation of bivariate statistic, analytical hierarchy process and frequency ratio

Few studies have been conducted for susceptibility of rock falls in mountainous areas. In this study, we compare and evaluate rock fall susceptibility mapping using bivariate statistical [weight of evidence (WoE)], analytical hierarchy process (AHP) and frequency ratio (FR) methods along 11 km of a mountainous road in the Salavat Abad saddle in southwestern Kurdistan, Iran. A total of 34 rock fall locations were constructed from various sources. These rock fall locations were then partitioned into a training dataset (70% of the rock fall locations) and a testing dataset (30% of the rock fall locations). Eight conditioning factors affecting on the rock falls including slope angle, aspect, curvature, elevation, distance to road, distance to fault, lithology and land use were identified. The modeling process and rock fall susceptibility mapping has been constructed using three methods. The performance of rock fall susceptibility mapping was evaluated using the area under the curve of success rate curve for training and prediction rate curves (PRC) for testing datasets and also seed cell area index. The results show that the rock fall susceptibility mapping using the WOE method has better prediction accuracy than the AHP and FR methods. Ultimately, the weight-of-evidence method is a promising technique so that it is proposed to manage and mitigate the damages of rock falls in the prone areas