Improving campus dining operations using capacity and queue management: A simulation-based case study

TL;DR: This article used Logistic regression, artificial neural network, gradient boosting, and the random forest algorithms to predict the length of stay of each animal at shelters considering key features such as animal type (dog, cat, etc.), age, gender, breed, animal size, and location.

TL;DR: The proliferation of telecommunication companies has contributed to nearly 7 percent of the US gross domestic product and while employing over five million people as mentioned in this paper. But despite offering new services and pro...

TL;DR: This study proposes managerial insights for these upcoming UAM services by analyzing online customer reviews and conducting an internal assessment of helicopter operations, and proposes managerial recommendations for air taxis.

TL;DR: This paper is the first to propose next-generation manufacturing insights for companies producing smart devices by determining the current strengths, weaknesses, opportunities, and threats (SWOT) of these gadgets using text analytics.

TL;DR: In this article, the authors identify the pedagogical principles underlying the teaching and learning activities that constitute effective e-learning and present an analysis and synthesis of the principles and ideas by the practicing e-Learning company employing the author in the perspective of deploying an effective Learning Management Systems (LMS).

TL;DR: In this article, the authors proposed a conceptual model to examine how customers' perceptions of the physical environment influenced disconfirmation, customer satisfaction, and customer loyalty for first-time and repeat customers in upscale restaurants.

TL;DR: In this paper, the relationship between consumers' knowledge of a restaurant's sustainable practices, environmental concern, and ecological behavior and their intention to patronize a “green” restaurant was discussed.

TL;DR: In this paper, the authors demonstrate a methodology to quantify the links between customer satisfaction, repeat-purchase intentions, and restaurant performance using data from a national restaurant chain, and construct a series of mathematical models that predict how the level of customer satisfaction with certain attributes of guests' dining experience affects the likelihood that they will come back.