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This study seeks to enhance productivity, motivation and well-being of workers by improving decision-making processes. Using inner knowledge management (IKM), this study aims to identify, manage and transform unconscious beliefs and negative emotions that limit decision-making processes.

The methodology used is empirical research, analyzing multiple cases qualitatively and using the T-test statistical model to analyze the hypotheses. The study tests the relation between different limiting beliefs and negative emotions that influence decision-making processes.

This study shows that IKM is positively related to the productivity, motivation and well-being of workers.

The study is limited to workers who are mentally healthy, who work in teams and who seek professional help to achieve their goals.

The results indicate that there is a lot of potential to be explored applying IKM in companies and organizations. Specifically, this study proves that there are several inner knowledge assets that constrain the workers’ potential and therefore affect the efficiency of businesses.

The results have strong implications for how companies and organizations can create great value for themselves and their workers.

To the best of the authors’ knowledge, this is the first data-based study using an IKM model. The importance of this study opens the door to further exploration of the effects on IKM on productivity, motivation and the general well-being of workers.

This study aims to investigate the impact of job loss on the mental health of individuals in Tunisia during the COVID-19 crisis.

In this research, the authors use the counterfactual decomposition technique and the potential outcome approach. In the first part, the authors calculated mental health indicators for all individuals included in the sample based on the World Health Organization-5 items. The individuals were then grouped into two subpopulations: the first group included those who had lost their jobs and the second group included individuals whose status in the labor market had remained unchanged. In the second part, the authors used the Blinder and Oaxaca decomposition to explain the mean difference in the mental health scores between the two groups and determine the factors contributing to this difference.

The empirical results identified symptoms of depressed mood, decreased energy and loss of interest in several individuals. Based on these three symptoms, the authors were able to classify individuals into three types of depression: mild, moderate and severe. In addition, it appeared that job loss had significantly contributed to the worsening mental health of the individuals.

Although the psychological impact of the COVID-19 outbreak among health-care professionals has been the subject of other studies in health literature on Tunisia, to the best of the authors’ knowledge, no research has addressed the impact of job loss on the mental health of Tunisian workers. Thus, this study fills this gap in the literature.

This paper aims to conduct a systematic literature review on prosocial rule-breaking (PSRB) and identify the underlying themes using content analysis.

The current review is based on a portfolio of 37 studies collected from different electronic databases. An extensive literature review is done following a four-step methodology to understand the field comprehensively.

The present article identified themes in the field of PSRB based on antecedents, consequences, moderators and mediators. Further, the identified themes are classified into individual, job and organizational levels. Through a conceptual framework, how antecedents impact PSRB is shown, which leads to diverse consequences.

Through this study, the authors attempt to help practitioners understand why PSRB behaviors occur in the workplace. Simultaneously, the authors' work helps managers identify potential strategies to evade the adverse effects of PSRB.

To the best of the authors' knowledge, this study is the first systematic review of PSRB. The review also highlighted the gaps and provided future research directions based on the theory, context, characteristics and methodology (TCCM) framework.

This study aims to examine the relationship between investor gambling preferences and stock returns, using data for all firms listed in Shanghai A-share market during 2016 and 2021.

This study employs price and trading volume data to capture the behavioral characteristics and gambling preferences of investors. Using the Fama-French three-factor and five-factor models to estimate benchmark returns, this study investigates whether investing in gambling stocks can yield positive excess returns.

The study reveals that stocks identified as gambling stocks generate high returns in the month they are identified as such but subsequently experience a significant drop in excess returns compared to non-gambling stocks over the following one to six months. These results are found to be consistent across different methods used to classify gambling stocks and across various industry sectors.

This research provides insights into the risk-return tradeoff of different stock types and the factors that fuel irrational investment behavior. This research underscores the importance of considering the behavioral elements of investment, particularly in emerging markets where individual investors have a significant impact.

This study advises investors to avoid adopting a gambler or speculative mindset and instead make well-informed and calculated investment decisions that are in line with investors financial objectives and risk appetite. This approach can help create a more stable and sustainable financial market.

This study provides new evidence on the relationship between gambling preferences and future stock returns in financial markets and sheds new light on the important role of irrational factors in investment decisions.

In order to estimate the value of semi-automated subject indexing in operative library catalogues, the study aimed to investigate five different automated implementations of an open source software package on a large set of Swedish union catalogue metadata records, with Dewey Decimal Classification (DDC) as the target classification system. It also aimed to contribute to the body of research on aboutness and related challenges in automated subject indexing and evaluation.

On a sample of over 230,000 records with close to 12,000 distinct DDC classes, an open source tool Annif, developed by the National Library of Finland, was applied in the following implementations: lexical algorithm, support vector classifier, fastText, Omikuji Bonsai and an ensemble approach combing the former four. A qualitative study involving two senior catalogue librarians and three students of library and information studies was also conducted to investigate the value and inter-rater agreement of automatically assigned classes, on a sample of 60 records.

The best results were achieved using the ensemble approach that achieved 66.82% accuracy on the three-digit DDC classification task. The qualitative study confirmed earlier studies reporting low inter-rater agreement but also pointed to the potential value of automatically assigned classes as additional access points in information retrieval.

The paper presents an extensive study of automated classification in an operative library catalogue, accompanied by a qualitative study of automated classes. It demonstrates the value of applying semi-automated indexing in operative information retrieval systems.

This study aims to examine the effect of faultline based on job responsibility and their interaction with the incentive scheme on knowledge-sharing behavior.

This research is an experimental study with a 2 × 2 factorial design between subjects. Faultline and incentive schemes are manipulated into two groups (strong faultline–weak faultline and group incentive–individual incentives). This study involved 89 undergraduate accounting students as participants.

This research shows that a strong faultline created a strong social identity effect. Hence, the knowledge-sharing behavior among group members tends to be lower than the weak faultline. Knowledge-sharing behavior tends to be higher in group incentive schemes than individual ones. However, there is no support for interactions between incentive schemes and faultline effects on knowledge-sharing behavior. The results indicate that forming a working subgroup based on informational characteristics attributes reduces cooperative behavior and knowledge sharing between groups.

This study adds a new addition to faultline literature by examining the effect of faultline and incentive schemes on knowledge-sharing behavior based on informational characteristics attributes. Previous research on faultline and knowledge sharing was limited and primarily focused on faultlines created by demographic attributes. This study also enriches faultline literature on knowledge-sharing behavior using an experimental design.

This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.

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 Covid-19 period has led to defining changes in the teaching process. Therefore, it is essential to explore how teachers have approached these changes, what experiences they have gained and what they have tried to change. This study aims to elucidate how innovative practices were applied in teaching – which was influenced by emergency remote teaching (ERT) – and better understand teachers' experiences related to these practices.

The phenomenology design, a qualitative research model, was executed in the current study. Phenomenological inquiry aims to interpret people's experiences about a specific concept designated as a phenomenon. Creswell (2020) classified two types of phenomenology: interpretive and descriptive. Interpretive phenomenology was employed in the current study as researchers collected data from individuals experiencing the phenomenon, collected and interpreted the data via excluding their own experiences.

As a result of the data interpretation, four themes related to experiences of innovative teaching practices during ERT were discovered: interpretation of innovative teaching, innovative teaching practices, needs related to innovative teaching and challenges to innovative teaching. The categories related to the interpretation of innovative teaching include positive and negative interpretation. The categories related to the second theme, innovative teaching practices, consist of characteristics of innovative teachers and innovative teaching practices employed. The categories related to the third theme, needs related to innovative teaching, are the need for guidance, training and technological infrastructure. The categories related to the fourth and final theme, challenges to innovative teaching, are barriers related to the teacher, barriers related to the learner and those related to the environment.

This study discovered that for teachers to practice innovative teaching, they must develop themselves, keep up-to-date and develop lifelong learning skills. Hung and Li (2017) reached a similar conclusion to the findings of this study: teachers' professional development is positively related to innovative teaching skills at a high level. The participating teachers stated that they had to rapidly improve their technological competency. It is thought that teachers developing their technological competencies will contribute to both ERT and face-to-face education at the end of the Pandemic.

The relationship between variation in time perspectives and collaborative performance is scarcely explored, and even less is known about the respective mechanisms that lead to varying task performance. Thus, we aim to further the literature on time perspectives and collaborative performance, shedding light on the underlying behavioral patterns.

We report a quasi-experiment analyzing the impact of past, present and future orientation variation in dyads (N = 76) on their quantitative and qualitative performance when confronted with a simple incentivized creative task with constraints. Subsequently, we offer a qualitative analysis of comments given by the participants after the task on the collaboration.

Results indicate that a dyad's elevation of past orientation and diversity in future orientation negatively affect collaborative performance. At the same time, there is a positive effect of elevation of future orientation. The positive effect is driven by clear communication and agreement during the task, while the negative effect arises from work sharing and complementation.

This study provides insights for organizations on composing individuals regarding their temporal focus for collaborative tasks that should be executed rapidly and require creative solutions.

Our study distinguishes by considering the composition of past, present and future time perspectives in dyads and focuses on a creative task setting. Moreover, we explore the mechanisms in the dyads with a substantial elevation of/diversity in future orientation, leading to their stronger/weaker performance.