Customer Review Provision Policies with Heterogeneous Cluster Preferences

Companies often post user-generated reviews online so that potential buyers in different clusters (age, geographic region, occupation, etc.) can learn from existing customers about the quality of an experience good and cluster preferences before purchasing. In this paper, we evaluate two common user-generated review provision policies for selling experience goods to customers in different clusters with heterogeneous preferences. The first policy is called the association-based policy (AP) under which a customer in a cluster can only observe the aggregate review (i.e., average rating) generated by users within the same cluster. The second policy is called the global-based policy (GP) under which each customer is presented with the aggregate review generated by all users across clusters. We find that, in general, the firm benefits from a policy that provides a larger number of “relevant reviews” to customers. When customers are more certain about the product quality and when clusters are more diverse, AP is more profitable than GP because it provides cluster-specific reviews to customers. Otherwise, GP is more profitable as it provides a larger number of less relevant reviews. Moreover, we propose a third provision policy that imparts the union of the information by AP and GP and show that it is more profitable for the firm. Although the third policy always renders a higher consumer welfare than GP, it may generate a lower consumer welfare than AP. This paper was accepted by Martínez-de-Albéniz Victor, operations management.

Examination of the Hexad User Types and their Relationships with Gender, Game Mode, and Gamification Experience in the Context of Open and Distance Learning

Gamification, which is defined as the use of game design elements in non-game contexts, is put forward as a solution to low motivation and is suggested for the creation of a sustainable learning ecology in open and distance learning (ODL). The overall purpose of the present study was to examine the distribution of the Hexad gamification user types and the correlations of gamification experience, game mode, and gender with the user types’ scores within the context of an ODL system. The researchers adapted quantitative cross-sectional survey design to seek answers in this study. The Hexad user types of distance learners were determined based on the online “Gamification User Types Hexad Scale.” Findings revealed that the most common user types in the ODL environment were Philanthropists, Achievers, and Free Spirits, followed by Socializers and Players with a lower mean, while the least common user type was Disruptors. Women tended to score higher than men on the Disruptor user type. Achievers, Socializers, Philanthropists, and Players preferred multiplayer game modes, while the game mode had little influence on Free Spirits and Disruptors. Regarding the gamification experience, Players and Free Spirits seemed to have more experience of gamified applications. This study provides insights to learning designers in developing gamified ODL systems to engage the different Hexad user types.

User encoding for clustering in very sparse recommender systems tasks

Recommender Systems are a very useful tool which let companies and service providers focus in the preferences of their customers, helping them to avoid an overwhelming variety of choices. In this context, clustering tools can play an important role to detect groups of customers with similar tastes. Thus, companies can make personalized marketing campaigns, offering to their users new products which have been consumed by other users with comparable preferences. In this paper we present a general framework to cluster users with respect to their tastes when the registers stored about the interactions between users and products are extremely scarce. Commonly, clustering methods employ the values of features describing the samples to be clustered (users in our case), but such features are not always available. We propose some alternative representations for users, in which their tastes are gathered to some extent, so that clustering algorithms can take advantage and make more homogeneous groups in this regard. To illustrate the performance of the whole framework, we tested it on six popular datasets commonly used as a benchmark for recommender systems, as well as on an extremely sparse real-world dataset that records the preferences of readers to click promoted links in digital publications. In the experimental section we compare our proposed representations to other common user encodings. We show that clustering users attending only to their feature values or to the items they have evaluated gives rise to the worst scores in terms of taste homogeneity.

Scrambling Keypad for Secure Pin Entry to Defeat Shoulder Surfing and Inference Attacks

Personal identification number (PIN) is a common user authentication method widely used especially for automated teller machines and point-of-sales devices. The user's PIN entry is susceptible to shoulder-surfing and inference attacks, where the attacker can obtain the PIN by looking over the user's shoulder. The conventional keypad with a fixed layout makes it easy for the attacker to infer the PIN entered by casual observation. This paper proposes a method of authentication to address these challenges. The paper develops a prototype numeric keypad with a layout akin to the conventional keypad, with the keys randomized for each PIN entry. The shuffle algorithm, Durstenfeld shuffle algorithm, is implemented in an application developed using JavaScript, which is a prototype-based object-oriented programming application that conforms to the ECMAScript specification. The prototype is implemented on three computing platforms for evaluation. The test proves the effectiveness of the system to mitigate shoulder-surfing and inference attacks.

4D BIM for Construction Logistics Management

This study presents an investigation into the extent to which emerging building information modelling (BIM) can be applied to construction logistics management (CLM). Given the specialist nature of the domains, the study employed an in-depth qualitative interview, whereby six experts were interrogated about their experiences of BIM for CLM. The study found the main applications of BIM on CLM to be the creation of three-dimensional (3D) site layout plans and four-dimensional (4D) coordination of site processes and common user plant, updating the 4D logistics plan as the project progressed and collaboration in BIM-based logistics coordination. Furthermore, there was a consensus amongst interviewees on improvement in site safety, comprehension of logistics information, efficiency on site, and effectiveness of layout planning as the main benefits. Lastly, the lack of training with implications on understanding was one of the main barriers to applying BIM to CLM. The findings from this study have the potential to stimulate the uptake of BIM by construction logistics practitioners. By so doing, the performance construction project delivery can be improved, and waste can be minimised or eliminated.

Comparing ten WCAG tools for accessibility evaluation of websites

BACKGROUND: Web accessibility is one of the most important aspects of building a website. It is important for web developers to ensure that their website is accessible according to WCAG standards for people with different range of abilities. There is plethora of tools for ensuring conformance to WCAG standards but not many studies compared performance of automatic WCAG tools. OBJECTIVE: This paper compares a set of ten WCAG tools and their results in terms of ease of comprehension and interpretation by web developers. We proposed a Common User Profile format to help personalize contents of website making it accessible to people with different range of abilities. METHODS: We selected ten WCAG tools from World Wide Web Consortium (W3C) to evaluate landing pages of two popular websites. For each webpage, we identified accessibility issues and recommended alternate suggestions to help developers improve accessibility. Further, we highlighted accessibility issues that cannot be captured only through conformance to WCAG tools; and proposed additional methods to evaluate accessibility through an Inclusive User Model. We then demonstrated how simulation of user interaction can capture usability and accessibility issues that are not detected through only syntactic analysis of websites’ content. Finally, we proposed a Common User Profile format that can be used to compare and contrast accessibility systems and services, and to simulate and personalize interaction for users with different range of abilities. RESULTS AND CONCLUSIONS: After careful evaluation of two websites using the ten tools, we noted that, both websites lacked color contrast between background and foreground; lack of sign language alternatives; opening of pop-ups without proper warnings and so on. Further, results from comparative analysis of selected web accessibility tools noted that, there is no single tool that can be found ideal in all aspects. However, from our study, Utilitia Validator by Utilitia SP. z O.O was considered the most feasible tool. By rectifying and incorporating issues and alternate suggestions by simulation study and Common User Profile format respectively, developers can improve both websites making it accessible to maximum audience.

Fiji plugins for qualitative image annotations: routine analysis and application to image classification

Quantitative measurements and qualitative description of scientific images are both important to describe the complexity of digital image data. While various software solutions for quantitative measurements in images exist, there is a lack of simple tools for the qualitative description of images in common user-oriented image analysis software. To address this issue, we developed a set of Fiji plugins that facilitate the systematic manual annotation of images or image-regions. From a list of user-defined keywords, these plugins generate an easy-to-use graphical interface with buttons or checkboxes for the assignment of single or multiple pre-defined categories to full images or individual regions of interest. In addition to qualitative annotations, any quantitative measurement from the standard Fiji options can also be automatically reported. Besides the interactive user interface, keyboard shortcuts are available to speed-up the annotation process for larger datasets. The annotations are reported in a Fiji result table that can be exported as a pre-formatted csv file, for further analysis with common spreadsheet software or custom automated pipelines. To illustrate possible use case of the annotations, and facilitate the analysis of the generated annotations, we provide examples of such pipelines, including data-visualization solutions in Fiji and KNIME, as well as a complete workflow for training and application of a deep learning model for image classification in KNIME. Ultimately, the plugins enable standardized routine sample evaluation, classification, or ground-truth category annotation of any digital image data compatible with Fiji.

Interacción de las instituciones de auditoría pública con los usuarios a través de los medios de comunicación social

The interaction of public audit institutions with users through social media is analyzed. In addition to determining explanatory factors for the adoption of these platforms by supreme and regional European public audit institutions, a comparative analysis of the most commonly used social media is carried out to answer the following research questions: How do European public audit institutions use social media? What is the level of follow-up and interaction of their users? This paper analyzes 92 European public audit institutions: 28 supreme audit institutions (SAIs), 63 regional audit institutions (RAIs), and the European Court of Auditors (ECA). The results of this study indicate that the level of social media use by these institutions is low, with higher levels of adoption by SAIs and in areas with larger populations and Anglo-Saxon, Nordic, and Eastern public administration styles. The results also show that social media are mainly used to disclose information on their activities and that publications seeking to improve the image of the institutions have the greatest impact on users. Publications aimed at starting a dialogue with users are the least frequent. Users interact more on Facebook than on Twitter, “likes” being the most common user reaction and comments the least frequent. Resumen Se analiza la interacción de las instituciones de auditoría pública con los usuarios a través de los medios de comunicación social. Además de determinar factores explicativos de la adopción de estos medios por parte de las instituciones de auditoría pública europeas centrales y regionales, se lleva a cabo un análisis comparativo de las redes sociales que más utilizan, para contestar las siguientes preguntas: ¿cómo utilizan las instituciones de auditoría pública europeas los medios de comunicación social? y ¿cuál es el nivel de seguimiento e interacción de sus usuarios? Este trabajo analiza 92 instituciones de auditoría pública europeas: 28 instituciones de auditoría centrales (supreme audit institutions, SAIs), 63 regionales (regional audit institutions, RAIs) y la European Court of Auditors (ECA). Los resultados indican que el nivel de uso de los medios de comunicación social por parte de estas instituciones es reducido, con mayores niveles de adopción en las SAIs, en los territorios con mayor número de habitantes y con estilos de administración pública anglosajón, nórdico y del Este de Europa. Los resultados también muestran que las redes sociales se utilizan principalmente para transmitir información sobre las actividades que realizan y que las publicaciones que buscan mejorar la imagen de las instituciones son las que generan una mayor repercusión en los usuarios. Las publicaciones dirigidas a comenzar un diálogo con los usuarios son las menos frecuentes. Los usuarios interaccionan más en Facebook que en Twitter, siendo los “me gusta” la reacción más común y los comentarios la menos frecuente.

MEGARA-GTC Stellar Spectral Library (II). MEGASTAR First Release

MEGARA is an optical integral field and multi-object fibre-based spectrograph for the 10.4m Gran Telescopio CANARIAS that offers medium to high spectral resolutions (FWHM) of R ≃ 6000, 12000, 20000. Commissioned at the telescope in 2017, it started operation as a common-user instrument in 2018. We are creating an instrument-oriented empirical spectral library from MEGARA-GTC stars observations, MEGASTAR, crucial for the correct interpretation of MEGARA data. This piece of work describes the content of the first release of MEGASTAR, formed by the spectra of 414 stars observed with R ≃ 20000 in the spectral intervals 6420 – 6790 Å and 8370 – 8885 Å, and obtained with a continuum average signal to noise ratio around 260. We describe the release sample, the observations, the data reduction procedure and the MEGASTAR database. Additionally, we include in Appendix A, an atlas with the complete set of 838 spectra of this first release of the MEGASTAR catalogue.

Embedded Versus Horizontal UX Research Teams: Which May Best Suit You?

This paper explores the two most common user experience research team structures found in industry. The first is a horizontal research team that operates like an internal consultancy to support research across the organization. This structure is great for researchers that are looking to work with a strong community of researchers, have exposure to multiple methodologies, and impact the broader organization. Alternatively, an embedded research team model consists of a researcher supporting a specific product or feature. This model is great for researchers looking to work across the product lifecycle and build closer relationships with cross-functional stakeholders.