infonet-economy

Cet ouvrage réunit les communications présentées en 2016 à Neuchâtel lors de la 11e Journée de recherche en marketing horloger. Il présente également les exposés et tables rondes qui ont eu lieu à la 20e Journée internationale du marketing horloger à La Chaux-de-Fonds. Il fait suite aux autres ouvrages de la même collection qui ont pour but de faire rayonner le savoir-faire des entreprises horlogères et de leurs partenaires. Sans être un ouvrage de prospective, le présent volume aborde les visions des chercheurs comme des praticiens sur quelques perspectives d’avenir du secteur horloger: les montres (connectées ou non) devront être sans cesse innovantes et véhiculer encore plus d’émotion; il faudra débusquer et fidéliser les clients simultanément online et offline, notamment les jeunes générations; les détaillants auront à cœur d’offrir de nouveaux services; certains pays d’Afrique et d’Amérique du Sud pourront stimuler les exportations horlogères suisses. De nombreux enseignants-chercheurs et spécialistes de l’horlogerie ont contribué au contenu de cet ouvrage: Nathalie Veg-Sala, Elisabeth Robinot, Léo Trespeuch, Wendy Bendoni, Fabio Duma, Stephan Post, Maria Bashutkina, David Freléchox, Cédric Chèvre, Hugues Steiner, Said El Guennouni, Etienne Arrivé, Sylvia Morel, Monika Maire-Hefti, Stéphane Gachet, Jean-Daniel Dubois, Arni Kapschitzer, Bruno Moutarlier, Jean-François Ruchonnet, Luiggino Torrigiani, Marco Gabella, Aline Isoz, Jean-Jacques Merlet, Vincent Perriard, Davide Traxler, Charris Yadigaroglou, Joël Grandjean, François Engisch, Jacky Epitaux, David Sadigh, Laetitia Vifian Benoit, Kalust Zorik et François Courvoisier.

As organisational governance has evolved from hierarchical structures to relational networks, project-based alliances are increasingly employed by automakers as part of their innovation strategy. In this study, we explore characteristics of different types of project-based alliances in the automotive industry. Employing dyadic data drawn from 59 new product development project-based alliances undertaken by two firms, we are able to discern the relevant characteristics of product, process, and software development projects. Our results suggest very different characteristics for each project type, with products and software presenting contrary results across almost all characteristics. Characteristics of process-focused projects are unique from either product and software alliance-based projects.

Many bipartite and unipartite real-world networks display a nested structure. Examples pervade different disciplines: biological ecosystems (e.g. mutualistic networks), economic networks (e.g. manufactures and contractors networks) to financial networks (e.g. bank lending networks), etc. A nested network has a topology such that a vertex’s neighbourhood contains the neighbourhood of vertices of lower degree; thus – upon vertex reordering – the adjacency matrix is step-wise. Despite its strictmathematical definition and the interest triggered by their common occurrence, it is not easy to measure the extent of nested graphs unequivocally. Among others, there exist three methods for detection and quantification of nestedness that are widely used: BINMATNEST, NODF, and fitness-complexity metric (FCM). However, thesemethods fail in assessing the existence of nestedness for graphs of low (NODF) and high (NODF, BINMATNEST) network density. Another common shortcoming of these approaches is the underlying assumption that all vertices belong to a nested component. However, many real-world networks have solely a sub-component (i.e. a subset of its vertices) that is nested. Thus, unveiling which vertices pertain to the nested component is an important research question, unaddressed by the methods available so far. In this contribution, we study in detail the algorithm Nestedness detection based on Local Neighbourhood (NESTLON). This algorithm resorts solely on local information and detects nestedness on a broad range of nested graphs independently of their nature and density. Further, we introduce a benchmark model that allows us to tune the degree of nestedness in a controlled manner and study the performance of different algorithms. Our results show that NESTLON outperforms both BINMATNEST and NODF.

In this article, we demonstrate the relevance of eye-tracking experiments in social and environmental accounting (SEA) research. Up to now, this type of design has been used in some areas within accounting research, but SEA has been neglected. If one is to adopt a user perspective [Merkl-Davies, D. M., and N. M. Brennan. 2007. “Discretionary Disclosure Strategies in Corporate Narratives: Incremental Information or Impression Management?” Journal of Accounting Literature 27: 116–196; 2011. “A Conceptual Framework of Impression Management: New Insights from Psychology, Sociology and Critical Perspectives.” Accounting and Business Research 41 (5): 415–437], the investigation and the understanding of the way social and environmental information affects user perceptions and decisions requires, among other tools, the use of eye-tracking setups. We discuss the need for eye-tracking experiments in SEA research and provide some preliminary evidence on their usefulness by conducting an illustrative experiment.

This study examines how hospitality students perceive ethics, corporate social responsibility (CSR), and sustainability (ECSRS) with regard to their current academic program and future career. Previous literature has shown an evolution in higher education institutions to implement ECSRS topics into their curriculum. This quantitative study measured 202 first-year students’ levels of interest, perceived importance, and potential implementation of ECSRS in a hospitality management program. Based on student responses, there is a high expectation that courses on ECSRS will be taught during their academic program to better prepare them for their future ambitions and the future of the planet.

Risk-based investing is experiencing growing success among investors, although some critics contend that the implicit “no-views” characteristic of these solutions might trigger other forms of risk, such as valuation risk. In this article, the authors introduce an analytical framework that allows investors to add active views on top of a risk-based solution, bridging the gap between risk-based investing and mean-variance portfolio optimization. Starting from a Black-Litterman approach, the authors derive closed-form expressions for the active risk-based portfolio weights and discuss practical implementation aspects. The framework is illustrated with a multi-asset allocation exercise over the period 1974–2016. Using views generated from macroeconomic regime signals, the active risk-based strategy is shown to outperform empirically both passive risk-based strategies and popular methodologies such as Equal-weight or Maximum Sharpe ratio.