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Municipalities commonly ask the public to give input by answering questions about their preferences. There is some belief that input enhances the public's confidence in government. The purpose of this paper is to examine whether different types of input activities (obtained by phone or online surveys, or via face‐to‐face engagements) differentially impact confidence.

Data were collected over two years from different input activities undertaken to inform a city's budgeting and performance measures' determinations.

Significant amounts of variance in the public's confidence in municipal governments are accounted for by independent predictors such as current satisfaction, perceived trustworthiness, legitimacy, and loyalty to the institution. Compared to online and phone surveys, face‐to‐face input methods seem to have a particularly strong, positive relationship with the public's perceptions of the trustworthiness (e.g. competence, integrity, benevolence) of municipal government officials. Persons who participate in face‐to‐face, online, or phone events differ both in extent of confidence and, to a small extent, in the bases of their confidence.

The study design is correlational rather than experimental and data were not originally gathered to test the identified hypotheses. In addition, it is not prudent to put too much stock in results from only one jurisdiction that relied primarily on convenience samples.

In instances in which enhancing confidence in the institution is a specific objective of public input, this work provides researchers and practitioners with guidance to better anticipate which input technique(s) works best and why.

Sustainable human resource management highlights the importance of the eighth sustainable development goal, “decent work and economic growth”. Thus, the purpose of this study is to align human resource practices and policies with Industry 4.0 is imperative.

The authors aimed to identify key challenges of sustainable human resource implementation in view of Industry 4.0 and to analyse these identified challenges by prioritising them for effective Industry 4.0 implementation in an emerging economy such as India. A mixed-methods approach was utilised to prioritise identified challenges. Semi-structured interviews were conducted with experts, academicians and industry mangers. Transcribed interviews were run in NVivo to emerge into broad themes/challenges, which were prioritised using fuzzy best–worst methodology.

The performance appraisal challenge holds maximum importance, followed by learning and development. This finding signifies the need for instilling job security and continuous learning opportunities for employees amidst all disruption caused by Industry 4.0.

This work enhances the link between sustainability, disruptive technologies and Industry 4.0 to transform economic outlooks, leading to improvement under economic aspects through the adoption of sustainable human resource practices into workplaces and society.

Sustainable human resource management has mostly focused on employee welfare. However, the major challenges of disruption caused by Industry 4.0 have not been addressed in the literature. The upskilling and reskilling requirements due to disruptions by Industry 4.0 range from recruitment to performance appraisal and every facet that relates to an employee's cycle in a company. Hence, there is a need to identify critical challenges for optimum adaptation to upcoming industry demands.

The purpose of this study is to provide the reader with a full study of the bat algorithm, including its limitations, the fields that the algorithm has been applied, versatile optimization problems in different domains and all the studies that assess its performance against other meta-heuristic algorithms.

Bat algorithm is given in-depth in terms of backgrounds, characteristics, limitations, it has also displayed the algorithms that hybridized with BA (K-Medoids, back-propagation neural network, harmony search algorithm, differential evaluation strategies, enhanced particle swarm optimization and Cuckoo search algorithm) and their theoretical results, as well as to the modifications that have been performed of the algorithm (modified bat algorithm, enhanced bat algorithm, bat algorithm with mutation (BAM), uninhabited combat aerial vehicle-BAM and non-linear optimization). It also provides a summary review that focuses on improved and new bat algorithm (directed artificial bat algorithm, complex-valued bat algorithm, principal component analyzes-BA, multiple strategies coupling bat algorithm and directional bat algorithm).

Shed light on the advantages and disadvantages of this algorithm through all the research studies that dealt with the algorithm in addition to the fields and applications it has addressed in the hope that it will help scientists understand and develop it.

As far as the research community knowledge, there is no comprehensive survey study conducted on this algorithm covering all its aspects.

Mathematical and numerical models are developed to study the melting of a Phase Change Material (PCM) inside a 2D cavity. The bottom of the cell is heated at constant and uniform temperature or heat flux, assuming that the rest of the cavity is completely adiabatic. The paper used suitable numerical methods to follow the interface temporal evolution with a good accuracy. The purpose of this paper is to show how the evolution of the latent energy absorbed to melt the PCM depends on the temperature imposed on the lower wall of the cavity.

The problem is written with non-homogeneous boundary conditions. Momentum and energy equations are numerically solved in space by a spectral collocation method especially oriented to this situation. A Crank-Nicolson scheme permits the resolution in time.

The results clearly show the evolution of multicellular regime during the process of fusion and the kinetics of phase change depends on the boundary condition imposed on the bottom cell wall. Thus the charge and discharge processes in energy storage cells can be controlled by varying the temperature in the cell PCM. Substantial modifications of the thermal convective heat and mass transfer are highlighted during the transient regime. This model is particularly suitable to follow with a good accuracy the evolution of the solid/liquid interface in the process of storage/release energy.

The time-dependent physical properties that induce non-linear coupled unsteady terms in Navier-Stokes and energy equations are not taken into account in the present model. The present model is actually extended to these coupled situations. This problem requires smoother geometries. One can try to palliate this disadvantage by constructing smoother approximations of non-smooth geometries. The augmentation of polynomials developments orders increases strongly the computing time. When the external heat flux or temperature imposed at the PCM is much greater than the temperature of the PCM fusion, one must choose carefully some data to assume the algorithms convergence.

Among the areas where this work can be used, are: buildings where the PCM are used in insulation and passive cooling; thermal energy storage, the PCM stores energy by changing phase, solid to liquid (fusion); cooling and transport of foodstuffs or pharmaceutical or medical sensitive products, the PCM is used in the food industry, pharmaceutical and medical, to minimize temperature variations of food, drug or sensitive materials; and the textile industry, PCM materials in the textile industry are used in microcapsules placed inside textile fibres. The PCM intervene to regulate heat transfer between the body and the outside.

The paper's originality is reflected in the precision of its results, due to the use of a high-accuracy numerical approximation based on collocation spectral methods, and the choice of Chebyshev polynomials basis in both axial and radial directions.

Multi-criteria decision-making (MCDM) techniques are decision support systems that provide systematic approaches to solve hospitality and tourism (H&T) problems while minimizing the risk of failure. However, less is known about the application of MCDM techniques in H&T research. This study aims to systematically assess the use of MCDM techniques in H&T research to classify its current application and determine its application potential for H&T research.

This study used bibliometric analysis to examine all published MCDM studies focused on H&T industries, since 1997. In addition, topic modelling was used to discover key concepts. Finally, top cited studies in terms of total citations per year and total citations were qualitatively reviewed for more insights.

The findings revealed an ongoing interest in applying MCDM techniques in H&T research. Specifically, the extension of fuzzy theory in MCDM techniques is burgeoning among H&T researchers. However, a certain number of MCDM techniques seem to be ignored in this field with a repetitive application of MCDM techniques in particular areas.

The data for the current research was solely retrieved from Scopus and other databases were not included. Therefore, future research is called for to re-examine the study by considering data from various databases.

This study contributes to extant H&T literature by identifying the most prolific and influential countries, journals, publications and trends by applying MCDM techniques in H&T research, and elucidating the implications and characteristics of MCDM techniques in H&T research.