Time patterns and perceptions of online learning success factors

Online learning provides the opportunity to work on academic tasks at any time at the same time as doing other activities, such as using in web 2.0 tools. This study identifies factors that contribute to success in online learning from the students¿ perspective and their relationship with time patterns. A survey of learning outputs was used to find relationships between students¿ satisfaction, knowledge acquisition and knowledge transfer with time for working on academic tasks. In this study, 199 students from a university in Mexico completed the survey. Findings suggest that knowledge transfer has a significant association with the number of hours online per day, hours spent on social networks and the use made of e-learning during working hours. Learner satisfaction has a strong relationship with the time in years a learner has been using the Internet and the number of hours devoted to the course per week. The findings of this research will be helpful for faculty and instructional designers for implementing learning strategies.

Forecasting tourism demand using consumer expectations

Abstract Purpose- There is a lack of studies on tourism demand forecasting that use non-linear models. The aim of this paper is to introduce consumer expectations in time-series models in order to analyse their usefulness to forecast tourism demand. Design/methodology/approach- The paper focuses on forecasting tourism demand in Catalonia for the four main visitor markets (France, the UK, Germany and Italy) combining qualitative information with quantitative models: autoregressive (AR), autoregressive integrated moving average (ARIMA), self-exciting threshold autoregressions (SETAR) and Markov switching regime (MKTAR) models. The forecasting performance of the different models is evaluated for different time horizons (one, two, three, six and 12 months). Findings- Although some differences are found between the results obtained for the different countries, when comparing the forecasting accuracy of the different techniques, ARIMA and Markov switching regime models outperform the rest of the models. In all cases, forecasts of arrivals show lower root mean square errors (RMSE) than forecasts of overnight stays. It is found that models with consumer expectations do not outperform benchmark models. These results are extensive to all time horizons analysed. Research limitations/implications- This study encourages the use of qualitative information and more advanced econometric techniques in order to improve tourism demand forecasting. Originality/value- This is the first study on tourism demand focusing specifically on Catalonia. To date, there have been no studies on tourism demand forecasting that use non-linear models such as self-exciting threshold autoregressions (SETAR) and Markov switching regime (MKTAR) models. This paper fills this gap and analyses forecasting performance at a regional level. Keywords Tourism, Forecasting, Consumers, Spain, Demand management Paper type Research paper

Considering tourist perceptions and network configuration in destination management

The competitiveness of tourism destinations is a relevant issue for tourism studies, moreso, is a key element on the daily basis of tourism destinations. In this sense, the management of tourism destinations is essential to maintain competitive advantages. In this article tourism destination is considered as a relational network, where interaction and cooperation is needed among tourist agents, to achieve major levels of competitive advantage and a more effective destination management system. In addition, the perceptions of tourists are obtained from two main sources. The first one is the social construction of a tourism destination previous to the visit and the second one is obtained from the interaction between tourists and tourism destination agents during the visit. In this sense, the management of tourism destination to emit a homogenous and collective image is a factor that can reduce the gap if dissatisfaction from the previous and real tourist perception. The discussion is centered on the relationship within a destination, between the supply network and the targeted demand, considering these two approaches jointly, to benefit destination management. The main result is a conceptual model that shows how tourism agents and tourists in the tourism destination interact to improve the destination competitiveness

The pedagogical value of games and songs : The perceptions of teachers

Aquest estudi intenta explorar i descobrir les actituds i creences d’alguns mestres de llengua anglesa de Catalunya sobre la naturalesa dels jocs i les cançons, així com el paper que juguen en les seves aules per ensenyar l’anglès als infants. Les opinions dels mestres de llengua anglesa van ser recollides mitjançant un qüestionari que contenia preguntes sobre els jocs i les cançons i els resultats s’analitzen i s’exposen en aquest estudi.

Platform pricing and consumer foresight: The case of airports

Airports have become platforms that derive revenues from both aeronautical and commercial activities. The demand for these services is characterized by a one-way complementarity in that only air travelers can purchase retail goods at the airport terminals. We analyze a model of optimal airport behavior in which this one-way complementarity is subject to consumer foresight, i.e., consumers may not anticipate in full the ex post retail surplus when purchasing a flight ticket. An airport sets landing fees, and, in addition, also chooses the retail market structure by selecting the number of retail concessions to be awarded. We find that, with perfectly myopic consumers, the airport chooses to attract more passengers via low landing fees, and also sets the minimum possible number of retailers in order to increase the concessions’ revenues, from which it obtains the largest share of profits. However, even a very small amount of anticipation of the consumer surplus from retail activities changes significantly the airport’s choices: the optimal airport policy is dependent on the degree of differentiation in the retail market. When consumers instead have perfect foresight, the airport establishes a very competitive retail market, where consumers enjoy a large surplus. This attracts passengers and it is exploited by the airport by charging higher landing fees, which then constitute the largest share of its profits. Overall, the airport’s profits are maximal when consumers have perfect foresight. Keywords: two-sided markets, platform pricing, one-way demand complementarity, consumer foresight. JEL classification: L1, L2, L93.

Playing cat and mouse : consumer empowerment and marketing interaction on the net

Peer-reviewed

An empirical study on faculty perceptions and teaching practices of Wikipedia

Peer-reviewed

Wikipedia in Higher Education: An Empirical Study on Faculty Perceptions and Practices

Peer-reviewed

The use of non-animal alternatives in the safety evaluations of cosmetics ingredients by the Scientific Committee on Consumer Safety (SCCS)

In Europe, the safety evaluation of cosmetics is based on the safety evaluation of each individual ingredient. Article 3 of the Cosmetics Regulation specifies that a cosmetic product made available on the market is to be safe for human health when used normally or under reasonably foreseeable conditions. For substances that cause some concern with respect to human health (e.g. colorants, preservatives, UV-filters), safety is evaluated at the Commission level by a scientific committee, presently called the Scientific Committee on Consumer Safety (SCCS). According to the Cosmetics Regulations, in the EU, the marketing of cosmetics products and their ingredients that have been tested on animals for most of their human health effects, including acute toxicity, is prohibited. Nevertheless, any study dating from before this prohibition took effect is accepted for the safety assessment of cosmetics ingredients. The in vitro methods reported in the dossiers summited to the SCCS are here evaluated from the published reports issued by the scientific committee of the Directorate General of Health and Consumers (DG SANCO); responsible for the safety of cosmetics ingredients. The number of studies submitted to the SCCS that do not involve animals is still low and in general the safety of cosmetics ingredients is based on in vivo studies performed before the prohibition.

Informed recommender: basing recommendations on consumer product reviews

Recommender systems attempt to predict items in which a user might be interested, given some information about the user's and items' profiles. Most existing recommender systems use content-based or collaborative filtering methods or hybrid methods that combine both techniques (see the sidebar for more details). We created Informed Recommender to address the problem of using consumer opinion about products, expressed online in free-form text, to generate product recommendations. Informed recommender uses prioritized consumer product reviews to make recommendations. Using text-mining techniques, it maps each piece of each review comment automatically into an ontology

Consumer valuation of energy-saving features of residential air conditioners with hedonic and choice models

The promotion of energy-efficient appliances is necessary to reduce the energetic and environmental burden of the household sector. However, many studies have reported that a typical consumer underestimates the benefits of energy-saving investment on the purchase of household electric appliances. To analyze this energy-efficiency gap problem, many scholars have estimated implicit discount rates that consumers use for energy-consuming durables. Although both hedonic and choice models have been used in previous studies, a comparison between two models has not yet been done. This study uses point of sale data about Japanese residential air conditioners and estimates implicit discounts rates with both hedonic and choice models. Both models demonstrate that a typical consumer underinvests in energy efficiency. Although choice models estimate a lower implicit discount rate than hedonic models, the latter models estimate the values of other product characteristics more consistently than choice models.