Understanding online customer repurchasing intention and the mediating role of trust - an empirical investigation in two developed countries

Although e-commerce adoption and customers initial purchasing behavior have been well studied in the literature, repeat purchase intention and its antecedents remain understudied. This study proposes a model to understand the extent to which trust mediates the effects of vendor-specific factors on customers intention to repurchase from an online vendor. The model was tested and validated in two different country settings. We found that trust fully mediates the relationships between perceived reputation, perceived capability of order fulfillment, and repurchasing intention, and partially mediates the relationship between perceived website quality and repurchasing intention in both countries. Moreover, multi-group analysis reveals no significant between-country differences of the model with regards to the antecedents and outcomes of trust, except the effect of reputation on trust. Academic and practical implications and future research are discussed. © 2009 Operational Research Society Ltd.

On-line Emotion Recognition in a 3-D Activation-Valence-Time Continuum using Acoustic and Linguistic Cues

For many applications of emotion recognition, such as virtual agents, the system must select responses while the user is speaking. This requires reliable on-line recognition of the user’s affect. However most emotion recognition systems are based on turnwise processing. We present a novel approach to on-line emotion recognition from speech using Long Short-Term Memory Recurrent Neural Networks. Emotion is recognised frame-wise in a two-dimensional valence-activation continuum. In contrast to current state-of-the-art approaches, recognition is performed on low-level signal frames, similar to those used for speech recognition. No statistical functionals are applied to low-level feature contours. Framing at a higher level is therefore unnecessary and regression outputs can be produced in real-time for every low-level input frame. We also investigate the benefits of including linguistic features on the signal frame level obtained by a keyword spotter.

Overcoming Customer Dependency - A Case Study of Small Consumer Food Producers in Northern Ireland

Dependency on a small number of customer puts intense pressure on suppliers' profit margin and, in slow growing markets, limits their ability to grow. using stragtegic benchmarking information, a group of Northern Ireland consumer food producer are shown, depsite slow market growth and higher than averge customer dependency, to have increased market share while maintaining aboe vergate proitability. examination of the business strategic and develoment activites of the consumer food firms,and comparble information for other small food prodcuers in Ireland, suggests and emphasiss on cost-reduction and new prodcut development. A comparision of the productivity and prodcut range of the consuer food firms provides evidence of the success of these strategic. This suggests that even a relatively weak market situations, charactrised by dependency on a small number of customers, can be over come by effective and appropriate business strategy.

Perception of emotion: towards a realistic understanding of the task

A decade ago, perceiving emotion was generally equated with taking a sample (a still photograph or a few seconds of speech) that unquestionably signified an archetypal emotional state, and attaching the appropriate label. Computational research has shifted that paradigm in multiple ways. Concern with realism is key. Emotion generally colours ongoing action and interaction: describing that colouring is a different problem from categorizing brief episodes of relatively pure emotion. Multiple challenges flow from that. Describing emotional colouring is a challenge in itself. One approach is to use everyday categories describing states that are partly emotional and partly cognitive. Another approach is to use dimensions. Both approaches need ways to deal with gradual changes over time and mixed emotions. Attaching target descriptions to a sample poses problems of both procedure and validation. Cues are likely to be distributed both in time and across modalities, and key decisions may depend heavily on context. The usefulness of acted data is limited because it tends not to reproduce these features. By engaging with these challenging issues, research is not only achieving impressive results, but also offering a much deeper understanding of the problem.