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The field of website quality evaluation attracts the interest of a range of disciplines, each bringing its own particular perspective to bear. This study aims to identify the main characteristics – methods, techniques and tools – of the instruments of evaluation described in this literature, with a specific concern for the factors analysed, and based on these, a multipurpose model is proposed for the development of new comprehensive instruments.

Following a systematic bibliographic review, 305 publications on website quality are examined, the field's leading authors, their disciplines of origin and the sectors to which the websites being assessed belong are identified, and the methods they employ characterised.

Evaluations of website quality tend to be conducted with one of three primary focuses: strategic, functional or experiential. The technique of expert analysis predominates over user studies and most of the instruments examined classify the characteristics to be evaluated – for example, usability and content – into factors that operate at different levels, albeit that there is little agreement on the names used in referring to them.

Based on the factors detected in the 50 most cited works, a model is developed that classifies these factors into 13 dimensions and more than 120 general parameters. The resulting model provides a comprehensive evaluation framework and constitutes an initial step towards a shared conceptualization of the discipline of website quality.

Wall-modeled large eddy simulation (LES) is a practical tool for solving wall-bounded flows with less computational cost by avoiding the explicit resolution of the near-wall region. However, its use is limited in flows that have high non-equilibrium effects like separation or transition. This study aims to present a novel methodology of using high-fidelity data and machine learning (ML) techniques to capture these non-equilibrium effects.

A precursor to this methodology has already been tested in Radhakrishnan et al. (2021) for equilibrium flows using LES of channel flow data. In the current methodology, the high-fidelity data chosen for training includes direct numerical simulation of a double diffuser that has strong non-equilibrium flow regions, and LES of a channel flow. The ultimate purpose of the model is to distinguish between equilibrium and non-equilibrium regions, and to provide the appropriate wall shear stress. The ML system used for this study is gradient-boosted regression trees.

The authors show that the model can be trained to make accurate predictions for both equilibrium and non-equilibrium boundary layers. In example, the authors find that the model is very effective for corner flows and flows that involve relaminarization, while performing rather ineffectively at recirculation regions.

Data from relaminarization regions help the model to better understand such phenomenon and to provide an appropriate boundary condition based on that. This motivates the authors to continue the research in this direction by adding more non-equilibrium phenomena to the training data to capture recirculation as well.

This article aims to open the black box of the relationship between customer experience and customer satisfaction. The authors also take a fine-grained approach to the concept of customer experience analysis in terms of four dimensions: basic service experience (BSE), moments of truth (MT), focus on results (FR) and peace of mind (PM).

A total sample of 185 industrial customers in Spain was collected via an online platform from March to April 2020. The data were analysed using partial least squares-structural equation modelling (PLS-SEM).

The results indicated that the four dimensions of customer experience are the foundation of commercial success (i.e. customer satisfaction) for express parcel companies in the business-to-business (B2B) environment. Therefore, the most innovative express parcel companies should not only pay attention to providing services in accordance with the customer agreement but also go beyond that; hence, these companies must understand customer needs to be able to offer a unique experience. Therefore, these companies must design experiences that go beyond pure technical delivery services.

Although previous work has linked customer experience to customer satisfaction, there is little work that does so specifically in an industry as in vogue as express parcels and less so in the B2B environment. In addition, this work analyses fine-grained customer experience in terms of grain's four dimensions, and therefore, the authors analyse how each dimension (e.g. more rational or more subjective dimensions) impacts customer satisfaction. Few studies have focussed on this type of analysis for express parcel companies in the B2B environment.