Extended framework for the analysis of innovative Smart City business models

Besides the promising forecasts for Smart City market, many projects haven't taken off due to financial restrictions, unsustainable business models or too technological visions instead of citizen orientation. The need for innovative business models in the context of Smart City motivates this study, that first reviews the Smart City business model literature, and then proposes a framework to study several companies within each sector of a broad definition of the Smart City. The results of the analysis show that there is a need to build a holistic framework to analyze all business models included in the Smart City. They also suggest that policy makers should extend their vision of the Smart City, and include a large group of innovative businesses that, using disruptive technologies, are creating deep impacts on citizens' lives

Choosing the delivery and return method in purchases: the effect of situational factors in omni-channel contexts

Even though retailers have engaged in many efforts to offer and integrate new alternatives for delivering and returning consumers’ purchases, it is not clear what motivates consumers to choose one option or another. Although most consumers are already familiar with options such as home delivery or pick-up locations, situational factors determine their choice among the different alternatives; no study has, however, addressed this topic before. To fill this gap, this study identifies 15 different situational factors to examine their influence on the selection of delivery and return options and the effect of consumers’ demographic characteristics. The empirical analysis is based on an online questionnaire distributed to 650 respondents (266 valid responses). In addition, this study uses MANOVA and ANOVA to determine the relationship between each situational factor and consumer characteristics. The results show that 13 situational factors have a significant impact on consumer decisions, and among them time pressure, the distance to the store and channel spill-over are the most influential factors. The results also show that situational factors significantly rely on individual characteristics. For instance, getting help from an employee is significantly more important for consumers who are under 25 years of age. The study reveals some valuable implications for retailer

Identifying consumer’s last-mile logistics beliefs in omni-channel environment

Over the past few years, retailers have offered new alternatives in last-mile logistics for consumers’ purchases; however, still, it is unclear why consumers select one option over another. A significant number of studies have tried to give some guidance, but very little research has considered the consumer’s point of view; specifically, in Omni-channel environment it has been undiscovered. To fulfil this gap, this study tends to identify some beliefs that may affect consumers’ behaviour in last-mile logistics. However, to validate these beliefs this study uses the Theory of Planned Behaviour (TPB) approach. Following the TPB, this study employs an online questionnaire to obtain 280 samples of Spanish students. The final results show that although some beliefs such as convenience, risk of time, and finances are consistent with previous studies, there are new salient beliefs in which have not been identified before: Accessibility & Comparability. As a conclusion, this study not only is an effective mechanism for predicting the intention of selecting a last-mile logistics by consumers, but also can be guidance and assistance for practitioners to develop proper strategies for facilitating consumer’s shopping journey, and ultimately, improving consumer’s satisfaction

Nueva economía 20+20

276 p : il.El fuerte avance de las Tecnologías de la Información y las Comunicaciones (TIC) ha provocado profundos cambios económicos, sociales y culturales en las últimas décadas (Cohen, De Long y Zysman, 2000). La gran velocidad con la que se ha producido este cambio ha quedado reflejada en cifras, como el avance de Internet que, desde 1969, fecha de su nacimiento, hasta la actualidad, se ha extendido a más del 25% de la población mundial, con más de 1.700 millones de usuarios en todo el mundo, siendo especialmente significativos los casos de Europa y Estados Unidos, con penetraciones del 52% y 74,2%, respectivamente (Internet World Stats, 2009). Es igualmente significativo el fuerte crecimiento experimentado por los ordenadores personales que, desde 1977, año en el que vio la luz el primero de ellos, se estima que alcanzaron los 1.000 millones en el 2008, y se hacen predicciones de que se doblará dicha cifra en torno al año 2014 (Gartner, 2008). El trabajo, el ocio, el transporte o, incluso, las relaciones personales se encuentran en un proceso de cambio permanente debido a la profunda influencia que estas tecnologías han tenido sobre la sociedad. Tanto es así que en la nueva realidad, a la que el conocimiento y la tecnología trasladan al ser humano, existen nuevas concepciones del tiempo o del espacio (Castells, 2005). Desde el punto de vista económico, se han producido cambios en la estructura mundial que han desembocado en una nueva economía. Por una parte, las nuevas tecnologías han transformado la economía tradicional, dando lugar a una compleja estructura interconectada de forma global, en la que el desarrollo de las comunicaciones ha jugado un papel fundamental. Adicionalmente, la incorporación de la tecnología en el proceso productivo ha transformado elementos tales como la localización, el tamaño, las estructuras o las relaciones entre las empresas (Brynjolfsson y Kahln, 2000). Por otra parte, las nuevas tecnologías dan lugar a un nuevo mercado de enormes dimensiones, formado por todos aquellos bienes y servicios que dependen de forma crítica de las tecnologías digitales o lo son en sí mismas, lo cual constituye la base de la economía digital (Kling y Lamb, 1999). Con todo ello, el presente informe se encarga, en primer lugar, de identificar en qué consiste la economía digital y cuáles son sus principales componentes. En el siguiente apartado se intenta medir la importancia de este sector, a través de los datos más significativos, que reflejan el crecimiento que dicho sector de la economía ha sufrido en los últimos años, y la importancia relativa del mismo respecto al resto de los sectores. A continuación se presenta una caracterización de los perfiles de empresa que constituyen la economía digital y se busca plantear, después, un modelo de variables significativas que nos permita medir de forma adecuada el sector.Esta publicación ha contado con la cofinancia- ción del Fondo Social Europeo a través del Pro- grama Operativo Plurirregional de Adaptabili- dad y Empleo 2007-2013.ÍNDICE Capítulo 0 EL PROYECTO SECTORES DE LA NUEVA ECONOMÍA 20+20 Capítulo 1 LA ECONOMÍA DIGITAL 1 Introducción 2 ¿Qué es la economía digital? 3 Importancia de la economía digital 4 Las empresas de la economía digital 5 ¿Cómo analizar la economía digital? 6 Conclusiones Capítulo 2 EXPERIENCIAS EMPRESARIALES 11870.COM AGNITIO ASPgems BARRABESBIZ BITDEFENDER BUONGIORNO BUYVIP COMEX GRUPO IBÉRICA DAEDALUS DEIMOS SPACE EPTISA TI ÍNCIPY ISDE ING KERAJET LA CIGÜEÑA DEL BEBÉ MICROGÉNESIS QAPACITY ÍNDICE TERRITORIO CREATIVO TOPRURAL TYVEN Capítulo 3 CONCLUSIONES Capítulo 4 BIBLIOGRAFÍ

SNOLA, creando una Red sobre Analíticas de Aprendizaje en España [SNOLA: creating a network about Learning Analytics in Spain]

Este artículo introduce de forma somera el Learning Analytics como disciplina y campo de investigación, incluyendo sus principales características, potenciales beneficios de cara a la sociedad, retos y tendencias actuales. A su vez, este manuscrito presenta la Red de Investigación SNOLA (Spanish Network of Learning Analytics, Red Española de Analítica de Aprendizaje), reconocida por el Ministerio de Economía y Competitividad del Gobierno de España. Sobre esta red, se comentan sus objetivos, retos, áreas de trabajo y actividades. En cuanto a SNOLA, se destaca su carácter participativo y abierto hacia la colaboración con distintos actores dentro del área LA, como son las instituciones, usuarios, educadores o los tecnólogos. [This article briefly introduces Learning Analytics as a discipline and field of research, including its main features, potential benefits for the Society, as well as the current challenges and trends. On the other hand, this manuscript presents the SNOLA Research Network (Spanish Network of Learning Analytics), recognized by the Ministry of Economy and Competitiveness of the Spanish Government. Regarding this research network, the paper discusses its goals, challenges, working areas and activities. Also, is featured the SNOLA participative and open culture towards collaboration with different actors within the LA area, such as institutions, users, educators or technologists.

Predicting Academic Performance: A Systematic Literature Review

The ability to predict student performance in a course or program creates opportunities to improve educational outcomes. With effective performance prediction approaches, instructors can allocate resources and instruction more accurately. Research in this area seeks to identify features that can be used to make predictions, to identify algorithms that can improve predictions, and to quantify aspects of student performance. Moreover, research in predicting student performance seeks to determine interrelated features and to identify the underlying reasons why certain features work better than others. This working group report presents a systematic literature review of work in the area of predicting student performance. Our analysis shows a clearly increasing amount of research in this area, as well as an increasing variety of techniques used. At the same time, the review uncovered a number of issues with research quality that drives a need for the community to provide more detailed reporting of methods and results and to increase efforts to validate and replicate work.Peer reviewe