Exploring the use of a gap analysis approach for quantitative evaluation of teaching effectiveness

The article investigates the potential of an adaptation of the SERVQUAL approach for obtaining student feedback. The technique involves measuring the gaps between what students want in terms of teaching delivery and what they actually receive, thereby enabling areas for improvement to be identified. Improving the effectiveness of classroom teaching so as to enhance the students’ learning experience is frequently viewed as a key to raising retention rates. Student feedback, just one of many indicators of teaching quality, plays a crucial role in teaching enhancement. Whilst informal methods are also useful for teaching appraisal, this project investigates a formal approach for obtaining student feedback. If a SERVQUAL type approach can be adapted using a fairly short questionnaire then it may prove a useful alternative / supplement to traditional survey methods for evaluating teaching effectiveness. The project focuses on several undergraduate and postgraduate business Marketing modules and was conducted to see whether the technique offers any particular benefits which the Department of Business and Service Sector Management may use in the future

Multimodal Classification of Urban Micro-Events

In this paper we seek methods to effectively detect urban micro-events. Urban micro-events are events which occur in cities, have limited geographical coverage and typically affect only a small group of citizens. Because of their scale these are difficult to identify in most data sources. However, by using citizen sensing to gather data, detecting them becomes feasible. The data gathered by citizen sensing is often multimodal and, as a consequence, the information required to detect urban micro-events is distributed over multiple modalities. This makes it essential to have a classifier capable of combining them. In this paper we explore several methods of creating such a classifier, including early, late, hybrid fusion and representation learning using multimodal graphs. We evaluate performance on a real world dataset obtained from a live citizen reporting system. We show that a multimodal approach yields higher performance than unimodal alternatives. Furthermore, we demonstrate that our hybrid combination of early and late fusion with multimodal embeddings performs best in classification of urban micro-events

Opinion mining and sentiment analysis in marketing communications: a science mapping analysis in Web of Science (1998–2018)

Opinion mining and sentiment analysis has become ubiquitous in our society, with applications in online searching, computer vision, image understanding, artificial intelligence and marketing communications (MarCom). Within this context, opinion mining and sentiment analysis in marketing communications (OMSAMC) has a strong role in the development of the field by allowing us to understand whether people are satisfied or dissatisfied with our service or product in order to subsequently analyze the strengths and weaknesses of those consumer experiences. To the best of our knowledge, there is no science mapping analysis covering the research about opinion mining and sentiment analysis in the MarCom ecosystem. In this study, we perform a science mapping analysis on the OMSAMC research, in order to provide an overview of the scientific work during the last two decades in this interdisciplinary area and to show trends that could be the basis for future developments in the field. This study was carried out using VOSviewer, CitNetExplorer and InCites based on results from Web of Science (WoS). The results of this analysis show the evolution of the field, by highlighting the most notable authors, institutions, keywords, publications, countries, categories and journals.The research was funded by Programa Operativo FEDER Andalucía 2014‐2020, grant number “La reputación de las organizaciones en una sociedad digital. Elaboración de una Plataforma Inteligente para la Localización, Identificación y Clasificación de Influenciadores en los Medios Sociales Digitales (UMA18‐ FEDERJA‐148)” and The APC was funded by the same research gran

EMOTIONS THAT INFLUENCE PURCHASE DECISIONS AND THEIR ELECTRONIC PROCESSING

Recent studies have shown that most of our purchasing choices and decisions are theresult of a careful analysis of the advantages and disadvantages and of affective and emotionalaspects. Psychological literature recognizes that the emotional conditions are always present andinfluence every stage of decision-making in purchasing process. Consumers establish with companybrands an overall emotional relationship and express, also with web technologies, reviews andsuggestions on product/service. In our department we have developed an original algorithm ofsentiment analysis to extract emotions from online customer opinions. With this algorithm we haveobtained good results to polarize this opinions in order to reach strategic marketing goals.emotions, emotional marketing, emotional brand, emotions measurement, sentiment analysis.

Social media research: influencing the influencers

One of the central concepts in marketing theory is the idea that some individuals are more influential than others, and that these influencers play a central role in driving adoption of new products and services. From a customer service perspective, when these influencers are dissatisfied, they are able to drive disproportionally large numbers of customers, and potential customers, away. This report includes two pieces of research to help organisations engage with, and manage, online influencers. The first investigates the role of hyperinfluencers in online rate-and-review sites. Whilst existing research suggests that most individuals who post online are motivated by feelings of altruism or reciprocity this study found that the hyperinfluencers viewed reviewing products as a form of entertainment, creating ‘game’ elements out of the review process. The second piece of research examined the role of influence on social media sites, specifically Facebook, and questions whether it is possible to build effective brand communities on Facebook. The effectiveness of Facebook as a tool for building relationships with customers has been questioned, with some arguing that Facebook has only a limited value for marketers as a platform for promotions and offers. The research indicates that effective brand communities can be built on Facebook, but many brands are currently adopting social media community strategies that actually destroy brand value. For both pieces of research recommendations are provided for best practice in maximising the beneficial effect of online influencers, and minimising the potential for damaging brands online

Customer perception of switch-feel in luxury sports utility vehicles

Successful new product introduction requires that product characteristics relate to the customer on functional, emotional, aesthetic and cultural levels. As a part of research into automotive human machine interfaces (HMI), this paper describes holistic customer research carried out to investigate how the haptics of switches in luxury sports utility vehicles (SUVs) are perceived by customers. The application of these techniques, including an initial proposal for objective specifications, is addressed within the broader new product introduction context, and benefits described. One-hundred and one customers of SUVs assessed the feel of automotive push switches, completing the tasks both in, and out of vehicles to investigate the effect of context. Using the semantic differential technique, hedonic testing, and content analysis of customers’ verbatim comments, a holistic picture has been built up of what influences the haptic experience. It was found that customers were able to partially discriminate differences in switch-feel, alongside considerations of visual appearance, image, and usability. Three factors named ‘Affective’, ‘Robustness and Precision’, and ‘Silkiness’ explained 61% of the variance in a principle components analysis. Correlations of the factors with acceptance scores were 0.505, 0.371, and 0.168, respectively