Sustainable Business Models of SMEs: Challenges in Yacht Tourism Sector

Despite the high number of active small and medium enterprises (SMEs) in all sectors, current studies have barely developed investigations on the sustainability of their business models so far. The aim of this study was thus to bridge the gap between sustainable business models of SMEs in the service industry, to uncover the challenges that SMEs face when seeking business model reconfiguration toward sustainability. More specifically, the empirical investigation adopted a case study research design in the context of yacht tourism, as one business form among many within the tourism industry and thus within the broader category of the service industry. Interviews were conducted with seven European SMEs, whose business models were analyzed through the lens of the triple bottom line and sustainability challenges in their business models. The results display a varied typology of case studies, where business model components reveal diverse expressions of facing sustainability challenges. The work discusses reported findings with a cross-case comparison among detected business models and outlines a list of propositions for sustainable business models of SMEs. The paper contributes in continuing the discourse on sustainable business models, adopting the perspective of the challenges for SMEs and offers food for thought for managers of SMEs in comparing their own business with the identified business model types

Un nuevo enfoque basado en perfiles con aprendizaje de representaciones

Los Enfoques Basados en Perfiles (EBP’s) han mostrado muy buen comportamiento específicamente en la tarea de atribución de autoría. Este trabajo tiene como finalidad extender al EBP empleando aprendizaje de representaciones. Para ello, se utilizará la gran flexibilidad de los mecanismos de coincidencia (matching) que proveen los embeddings. La similitud entre perfiles, en este caso, ya no considerará únicamente aquellas palabras que coinciden “exactamente”, sino aquellas que son lo “suficientemente similares”, de acuerdo a un umbral predeterminado. Este trabajo comprende un estudio exhaustivo comparativo empleando las colecciones Enron y CIAPPA, donde quedará probada la viabilidad y efectividad de nuestra propuesta en relación a enfoques de EBP clásicos como SPI y KRD empleando escenarios con diferentes métodos de embeddings, tales como Word2Vec, Fastext y Glove.XIX Workshop Base de Datos y Minería de Datos (WBDMD)Red de Universidades con Carreras en Informátic

Flower pollination algorithm: a novel approach for multiobjective optimization

Multiobjective design optimization problems require multiobjective optimization techniques to solve, and it is often very challenging to obtain high-quality Pareto fronts accurately. In this article, the recently developed flower pollination algorithm (FPA) is extended to solve multiobjective optimization problems. The proposed method is used to solve a set of multiobjective test functions and two bi-objective design benchmarks, and a comparison of the proposed algorithm with other algorithms has been made, which shows that the FPA is efficient with a good convergence rate. Finally, the importance for further parametric studies and theoretical analysis is highlighted and discussed

Silhouette + Attraction: A Simple and Effective Method for Text Clustering

[EN] This article presents silhouette attraction (Sil Att), a simple and effective method for text clustering, which is based on two main concepts: the silhouette coefficient and the idea of attraction. The combination of both principles allows us to obtain a general technique that can be used either as a boosting method, which improves results of other clustering algorithms, or as an independent clustering algorithm. The experimental work shows that Sil Att is able to obtain high-quality results on text corpora with very different characteristics. Furthermore, its stable performance on all the considered corpora is indicative that it is a very robust method. This is a very interesting positive aspect of Sil Att with respect to the other algorithms used in the experiments, whose performances heavily depend on specific characteristics of the corpora being considered.This research work has been partially funded by UNSL, CONICET (Argentina), DIANA-APPLICATIONS-Finding Hidden Knowledge in Texts: Applications (TIN2012-38603-C02-01) research project, and the WIQ-EI IRSES project (grant no. 269180) within the FP 7 Marie Curie People Framework on Web Information Quality Evaluation Initiative. The work of the third author was done also in the framework of the VLC/CAMPUS Microcluster on Multimodal Interaction in Intelligent Systems.Errecalde, M.; Cagnina, L.; Rosso, P. (2015). Silhouette + Attraction: A Simple and Effective Method for Text Clustering. Natural Language Engineering. 1-40. https://doi.org/10.1017/S1351324915000273S140Zhao, Y., & Karypis, G. (2004). 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GZMKhigh CD8+ T effector memory cells are associated with CD15high neutrophil abundance in non-metastatic colorectal tumors and predict poor clinical outcome.

CD8(+) T cells are a major prognostic determinant in solid tumors, including colorectal cancer (CRC). However, understanding how the interplay between different immune cells impacts on clinical outcome is still in its infancy. Here, we describe that the interaction of tumor infiltrating neutrophils expressing high levels of CD15 with CD8(+) T effector memory cells (T(EM)) correlates with tumor progression. Mechanistically, stromal cell-derived factor-1 (CXCL12/SDF-1) promotes the retention of neutrophils within tumors, increasing the crosstalk with CD8(+) T cells. As a consequence of the contact-mediated interaction with neutrophils, CD8(+) T cells are skewed to produce high levels of GZMK, which in turn decreases E-cadherin on the intestinal epithelium and favors tumor progression. Overall, our results highlight the emergence of GZMK(high) CD8(+) T(EM) in non-metastatic CRC tumors as a hallmark driven by the interaction with neutrophils, which could implement current patient stratification and be targeted by novel therapeutics

Means-end analysis of consumers’ perceptions of virtual world affordances for e-commerce

Virtual worlds are three-dimensional (3D) persistent multi-user online environments where users interact through avatars. The affordances of virtual worlds can be useful for business-to-consumer e-commerce. Moreover, affordances of virtual worlds can complement affordances of websites to provide consumers with an enhanced e-commerce experience. We investigated which affordances of virtual worlds can enhance consumers‟ experiences on e-commerce websites. We conducted laddering interviews with 30 virtual world consumers to understand their perceptions of virtual world affordances. A means-end analysis was then applied to the interview data. The results suggest co-presence, product discovery, 3D product experience, greater interactivity with products and sociability are some of the key virtual world affordances for consumers. We discuss theoretical implications of the research using dimensions from the Technology Acceptance Model. We also discuss practical implications, such as how virtual world affordances can be incorporated into the design of e-commerce websites