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The overall goal of science is to build a valid and reliable body of knowledge about the functioning of the world and how applying that knowledge can change it. As personnel and human resources management researchers, we aim to contribute to the respective bodies of knowledge to provide both employers and employees with a workable foundation to help with those problems they are confronted with. However, what research on research has consistently demonstrated is that the scientific endeavor possesses existential issues including a substantial lack of (a) solid theory, (b) replicability, (c) reproducibility, (d) proper and generalizable samples, (e) sufficient quality control (i.e., peer review), (f) robust and trustworthy statistical results, (g) availability of research, and (h) sufficient practical implications. In this chapter, we first sing a song of sorrow regarding the current state of the social sciences in general and personnel and human resources management specifically. Then, we investigate potential grievances that might have led to it (i.e., questionable research practices, misplaced incentives), only to end with a verse of hope by outlining an avenue for betterment (i.e., open science and policy changes at multiple levels).

This paper aims to derive a reduced-order model for the heat transfer across the interface between a millimetric thermocapillary liquid bridge from silicone oil and the surrounding ambient gas.

Numerical solutions for the two-fluid model are computed covering a wide parametric space, making a total of 2,800 numerical flow simulations. Based on the computed data, a reduced single-fluid model for the liquid phase is devised, in which the heat transfer between the liquid and the gas is modeled by Newton’s heat transfer law, albeit with a space-dependent Biot function Bi(z), instead of a constant Biot number Bi.

An explicit robust fit of Bi(z) is obtained covering the whole range of parameters considered. The single-fluid model together with the Biot function derived yields very accurate results at much lesser computational cost than the corresponding two-phase fully-coupled simulation required for the two-fluid model.

Using this novel Biot function approach instead of a constant Biot number, the critical Reynolds number can be predicted much more accurately within single-phase linear stability solvers.

The Biot function for thermocapillary liquid bridges is derived from the full multiphase problem by a robust multi-stage fit procedure. The derived Biot function reproduces very well the theoretical boundary layer scalings.

The research aims at finding out the extent to which such urban transformation projects—in terms of their design components and aspects—contribute to providing big data (BD) with effective datasets, which are considered a key requirement in operating smart city solutions.

The present research investigates the predisposition level of these projects for supporting the BD through one of the urban initiatives for humanizing neighborhoods in Al Riyadh city (KSA). The selected case is analyzed by mapping the functional performance of its design features with certain characteristics of BD.

One of the core conclusions is: Despite the readiness of the design components of these projects to provide high levels of integration with IoT and smart transformation, the level of application is lower than expected on account of the dearth of initial targets and strategies, especially the lack of a supporting environment, street facilities and security and safety datasets.

The answer—arrived at through both descriptive and analytical approaches—is expected to guide those who query the further key concept of smart applications—is the answer characterized as technologically based, or is the same based on human aspects?

While the metaverse is promised to be the next big step for the Internet, this new technology may also bear negative impacts on individuals and society. Drawing on innovation resistance literature, this article explores the reasons for metaverse resistance.

The study is based on 66 semi-structured interviews, and the subsequent data were analysed thematically.

The findings revealed 11 reasons for metaverse resistance: lack of understanding, lack of regulation, addiction avoidance, claustrophobia, loss of social ties, disconnection from reality, privacy concerns, extreme consumer society, unseen benefits, infeasibility and nausea.

By understanding the various reasons for metaverse resistance managers and policymakers can make better decisions to overcome the challenges facing this innovation, rather than adopting a “one-size-fits-all” approach.

While the literature has mainly adopted a positive perspective on the metaverse, this research offers a more nuanced view by identifying the reasons why consumers may resist the metaverse. Furthermore, this study introduces for the first-time “addiction-driven-innovation-resistance (ADIR)” as a potential reason for metaverse resistance, which may also apply to other cases of innovation resistance, when new innovations are perceived as being “too good” and therefore potentially addictive.