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This research navigates the confluence of data analytics, machine learning, and artificial intelligence to revolutionize the management of urban services in smart cities. The study thoroughly investigated with advanced tools to scrutinize key performance indicators integral to the functioning of smart cities, thereby enhancing leadership and decision-making strategies. Our work involves the implementation of various machine learning models such as Logistic Regression, Support Vector Machine, Decision Tree, Naive Bayes, and Artificial Neural Networks (ANN), to the data. Notably, the Support Vector Machine and Bernoulli Naive Bayes models exhibit robust performance with an accuracy rate of 70% precision score. In particular, the study underscores the employment of an ANN model on our existing dataset, optimized using the Adam optimizer. Although the model yields an overall accuracy of 61% and a precision score of 58%, implying correct predictions for the positive class 58% of the time, a comprehensive performance assessment using the Area Under the Receiver Operating Characteristic Curve (AUC-ROC) metrics was necessary. This evaluation results in a score of 0.475 at a threshold of 0.5, indicating that there's room for model enhancement. These models and their performance metrics serve as a key cog in our data analytics pipeline, providing decision-makers and city leaders with actionable insights that can steer urban service management decisions. Through real-time data availability and intuitive visualization dashboards, these leaders can promptly comprehend the current state of their services, pinpoint areas requiring improvement, and make informed decisions to bolster these services. This research illuminates the potential for data analytics, machine learning, and AI to significantly upgrade urban service management in smart cities, fostering sustainable and livable communities. Moreover, our findings contribute valuable knowledge to other cities aiming to adopt similar strategies, thus aiding the continued development of smart cities globally.

The Covid-19 pandemic has profoundly affected urban communities, generating the need for an immediate response from local governance. The availability of urban data platforms in some smart cities helped the relevant actors to develop various solutions in an innovative and highly contextual way. The purpose of this paper is to explore the role of data platforms in smart cities in the context of the Covid-19 crisis.

A total of 85 studies were identified using the Clarivate Analytics Web of Science electronic library. After applying exclusion and inclusion criteria, 61 publications were considered appropriate and reasonable for the research, being read in-depth. Finally, only 52 studies presented relevant information for the topic and were synthesized following the defined research questions. During the research, the authors included in the paper other interesting references found in selected articles and important information regarding the role of data in the fight against Covid-19 in smart cities available on the Internet and social media, with the intention to capture both academic and practical perspectives.

The authors' main conclusion suggests that based on their previous expertise in collecting, processing and analyzing data from multiple sources, some smart cities quickly adapted their data platforms for an efficient response against Covid-19. The results highlight the importance of open data, data sharing, innovative thinking, the collaboration between public and private stakeholders, and the participation of citizens, especially in these difficult times.

The city managers and data operators can use the presented case studies and findings to identify relevant data-driven smart solutions in the fight against Covid-19 or another crisis.

The performance of smart cities is a social concern since the population of urban communities is continuously growing. By reviewing the adoption of information technologies-based solutions to improve the quality of citizens' life, the paper emphasizes their potential in societies in which information technology is embedded, especially during a major crisis.

This research re-emphasizes the importance of collecting data in smart cities, the role of the diversity of their sources and the necessity of citizens, companies and government synergetic involvement, especially in a pandemic context. The existence of smart solutions to process and extract information and knowledge from large data sets was essential for many actors involved in smart cities, helping them in the decision-making process. Based on previous expertise, some smart cities quickly adapted their data platforms for an efficient response against Covid-19. The paper analyzes also these success cases that can be considered models to be adopted by other municipalities in similar circumstances.

In recent years, instant messaging platforms like WhatsApp have gained substantial popularity in both academic and practical domains. However, despite this growth, there is a lack of a comprehensive overview of the literature in this field. The primary purpose of this study is to bridge this gap by analyzing a substantial dataset of 12,947 articles retrieved from the Dimensions.ai, database spanning from 2011 to March 2023.

To achieve the authors' objective, the authors employ bibliometric analysis techniques. The authors delve into various bibliometric networks, including citation networks, co-citation networks, collaboration networks, keywords and bibliographic couplings. These methods allow for the uncovering of the social and conceptual structures within the academic discourse surrounding WhatsApp.

The authors' analysis reveals several significant findings. Firstly, the authors observe a remarkable and continuous growth in the number of academic studies dedicated to WhatsApp over time. Notably, two prevalent themes emerge: the impact of coronavirus disease 2019 (COVID-19) and the role of WhatsApp in the realm of social media. Furthermore, the authors' study highlights diverse applications of WhatsApp, including its utilization in education and learning, as a communication tool, in medical education, cyberpsychology, security, psychology and behavioral learning.

This paper contributes to the field by offering a comprehensive overview of the scholarly research landscape related to WhatsApp. The findings not only illuminate the burgeoning interest in WhatsApp among researchers but also provide insights into the diverse domains where WhatsApp is making an impact. The analysis of bibliometric networks offers a unique perspective on the social and conceptual structures within this field, shedding light on emerging trends and influential research. This study thus serves as a valuable resource for scholars, practitioners and policymakers seeking to navigate the evolving landscape of WhatsApp research. The study will also be useful for researchers interested in conducting bibliometric analysis using Dimensions.ai, a free database.

The aim of this research is to underscore the pivotal role of warehouse management in the current turbulent global landscape exacerbated by the confluence of a health crisis and geopolitical instability in Europe. In today's interconnected global economy, the turbulence of the global supply chain causes a lack of its resilience among companies. Facing this critical crisis context, companies are refocusing on business processes and outsourcing support processes such as logistics. In this paper we have empirical and methodological objectives. Methodologically, we employ a qualitative research approach utilizing action research in a collaborative framework that involves academics and practitioners. The purpose of this methodology is to empirically investigate warehouse outsourcing as a solution for enhancing a company's performance and agility within the crisis context.

The authors’ action research based on case study approach is conducted through an immersion within the ALCL French multinational company located in Morocco. The authors mobilize the theory of constraints, which allows us to set up a process of identification and optimization of managerial constraints (Goldratt, 1990). The approach allows to set up a retroactive loop to increase the performance of the constraint.

The study shows that ALCL has a storage over-dimension constraint due to the decrease of physical flows caused by the global crisis. The results of action research protocol show that the optimization of warehousing constraint is achieved by the total outsourcing of the process.

The study provides new insights into how action research can improve management practices within companies and explore concrete solutions to the logistical challenges faced by businesses.

The purpose of the study is to analyze a sample of 528 published papers over the past 11 years by conducting a bibliometric analysis. The study also aims to provide a consolidated overview of the existing literature on “gaming addiction” and presents the status of research with future directions for researchers who wish to explore and contribute to this rapidly evolving field. The descriptive statistics have been conducted through citation and co-citation analysis.

For the bibliometric analysis, the documents were retrieved from the Scopus database with the help of the Scopus analyzer while the VOS viewer1.6.16 software was used to analyze citations, co-authorship, etc. The literature search strategy was applied across various databases and the articles published between 2010 and December 2021 giving a total of 1,219 articles across all disciplines. Finally, 528 articles were shortlisted through the query restricted to subject areas, namely, business management, psychology, social science and multidisciplinary areas.

IGA has also been recognized by the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, as one of the disorders; hence, this certainly calls for focussed efforts to understand the same and control further damage. The number of articles devoted to the study of “gaming addiction” has increased rapidly in recent years. Moreover, this study identifies some of the most influential articles in this area. Finally, this paper highlights the new trends and discusses the future research associated with gaming addiction.

This study focusses on gaming addiction and its trends, related to researchers and country-wise contributions. This is one of the few studies to review the literature on gaming addiction by using citation and co-citation analysis. The main findings of this paper will help academicians and practitioners to improve the body of knowledge on the topic and provide an overview of promising future research avenues.

Internet gaming is a newly emerging area and studies related to gaming addiction are very recent. To the best of the authors’ knowledge, this study is a unique and comprehensive overview of the leading works done in this area.

Social media fatigue (SMF) has been widely recognized; however, previous studies have included various concepts into a single fatigue construct. Fatigue has typically been explored from the stressor-strain-outcome (SSO) or stimulus-organism-response (SOR) perspectives. To further investigate SMF, the authors split it into the two constructs of exhaustion and disinterest. Furthermore, the authors introduced the concept of emotional labor and identified rules that may affect surface and deep acting strategies.

The authors designed and conducted a survey to collect data from social networking platform users.

Results from 364 users of social networking platforms supported most of the authors' hypotheses. First, most of the display rules affect the choice of deep or surface acting. Second, both types of acting lead to exhaustion, but only surface acting leads to disinterest. Third, discontinuance intention is affected by both types of fatigue.

This study contributes to SMF research by adding more antecedents (deep and surface acting) based on the emotional labor perspective and showing the impacts of communication rules on emotional labor. In addition, this study also distinguishes disinterest-style fatigue from exhaustion.

The purpose of this study is to explore the role skepticism plays among adolescents’ online information literacy skills.

The authors provide the conceptual grounding to operationalize and measure the notion of skepticism in an online information literacy context. Inspired by an existing measure known as the Skepticism Scale (Hurtt, 2010), the authors made substantial revisions to the scale to target middle school and high school students’ skepticism in six distinct, but related factors: questioning mind; search for knowledge; suspension of judgment; self-esteem; interpersonal understanding; and autonomy. The authors provide preliminary evidence of validity and reliability of the revised Skepticism Scale using Exploratory Factor Analysis and performed multiple linear regression using the Skepticism Scale measures to predict an adolescents’ online information literacy skills.

The Skepticism Scale was found to produce internally consistent constructs for all six measures. Three of the six measures were related to online information literacy skills, including the search for knowledge, interpersonal understanding and questioning mind.

This paper attempts to examine the potentially positive role of skepticism in information literacy skills among adolescents.

Despite the immense popularity of WhatsApp, there needs to be more reliable and valid scales for identifying and measuring users' motivation behind frequent WhatsApp status updates. This study explores the underlying motivations of users in updating their WhatsApp statuses and develops a scale to measure them.

Following a mixed-method research design, data were obtained from WhatsApp users in India. The current research furnishes results from five studies, involving both qualitative and quantitative approaches.

The results uncover seven unique motivations of users for keeping WhatsApp status, namely: social good, attention seeking, social relations, expressing views, life updates, inspiration and entertainment. Additionally, the empirical findings demonstrate the effects of the above dimensions on the positive and negative emotions of users.

This research is a pioneering effort in developing and validating a scale on WhatsApp status motivation construct. Key managerial and scholarly implications of the findings arising from this research are also discussed.

This study aims to focus on how smartphone addiction impacts young consumer behavior related to mobile technology (i.e. the compulsive app downloading tendency). After a thorough literature review and following the risk and protective factors framework, this study explores factors that could mitigate its effects (resilience, family harmony, perceived social support and social capital).

The study used the covariance-based structural equation modeling approach to analyze data collected from 275 Generation Z (Gen Z) smartphone users in Spain.

Results suggest that resilience is a critical factor in preventing smartphone addiction, and smartphone addiction boosts the compulsive app downloading tendency, a relevant downside for younger Gen Z consumers.

Through the lens of the risk and protective factors framework, this study focuses on protective factors to prevent smartphone addiction and its negative side effects on app consumption. It also offers evidence of younger consumers’ vulnerability to smartphone addiction, not because of the device itself but because of app-consumption-related behaviors.

This study aims to posit the extended version of the technology acceptance model to explain the psychological factors of Muslim university students’ smartphone addictive behaviour and neglect of studies. In particular, this research conceptualised addictive behaviour as smartphone dependency and proposed process usage, flow, habitual smartphone behaviour and preference for online social interaction (POSI) as the associated factors. Besides, this study investigated the effect of smartphone dependency on the neglect of studies.

Following the quantitative research design, this research tested the proposed model using data collected from Muslim students’ smartphone users in Malaysia. The analyses were based on the partial least squares–structural equation modelling technique.

The results revealed that flow has the most significant influence on smartphone dependency. Habitual behaviour and process usage were also significant predictors, but POSI was not significantly associated with smartphone dependency. Also, smartphone dependency was significantly related to the neglect of studies.

This study provides empirical support to guide university management in preventing Muslim students’ over-dependence on smartphones. The Muslim community is synonymous with time management, where overdependence would diminish students’ religious and academic responsibilities. Such overdependence can cause neglect of studies; thus, the research findings can assist the university in introducing policies and campaigns that can educate students on the negative consequences of this pervasive digital addiction and ways to overcome them. This study contributes to the body of knowledge in understanding Muslim students coping mechanisms through smartphone usage.

This study contributes to the literature by demonstrating the psychological factors of smartphone addiction and the resultant effect on the neglect of studies among Muslim university students.