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Debates regarding climate change risk perception (CCRP), particularly its scale and impact on social and environmental sustainability, have continued for decades. CCRP is experiencing a renaissance with an increased focus on environmentally relevant behaviors to mitigate the effects of climate change. However, CCRP lacks investigation from the employee perspective. Supported by the social exchange and value–belief–norm theories, this study aims to address the impact of employees’ CCRP on their proenvironmental behavior (PEB) via the moderating roles of environmental values and psychological contract breach.

The nonprobability convenience sampling technique was used to collect survey data from a sample of 299 employees across 138 manufacturing firms in Pakistan.

The results show that employees’ CCRP positively impacts their PEB and that this relationship is moderated by their environmental values and psychological contract breach. Specifically, environmental values strengthen the CCRP–PEB relationship, while psychological contract breach weakens it.

The findings of the study emphasize useful guidance for managers and practitioners as a future avenue to restructure the climate change framework by emphasizing the conditions (i.e. environmental values and psychological contract breach). In doing so, the study is beneficial for managers and practitioners in helping to increase employees’ PEB through the development of climate change action plans.

To the best of the authors’ knowledge, this study is one of the first investigations into CCRP–employees’ PEB nexus in the developing country context. The study incorporates social exchange and value–belief–norm theory, which serve as the CCRP’s theoretical underpinnings. The findings advance the new knowledge about a firm’s social responsibility to achieve the sustainable development goals outlined in the UN’s 2030 Agenda.

Ageism has deleteriously influenced individuals and society for nearly half a century. Despite receiving increased attention, it remains under-researched regarding how it might be reduced in the workplace. Even though its prevalence and allure, review studies on workplace ageism (WA) are also scarce, and thus a review is warranted.

To fill the preceding void, this study will systematically review the existing literature on WA using data from the past four decades.

This study identified the various antecedents and the intervention mechanism through which WA may be reduced. Additionally, through reviews, the authors advance the research by offering promising avenues for future research.

This review contributes to human resources managers and will inspire future scholars to delve deeper into combating age discrimination, stereotypes and bias toward employees in workplaces.

This research explored the storytelling (collection, curation and use) in the Cabrach, a remote Scottish glen. This study aims to capture the methodological process of storytelling and curation of heritage knowledge through the lens of the Cabrach's whisky distilling history, a central part of the area's cultural heritage, tangible and intangible. This research was conceptualised as “telling the story of telling the story of the Cabrach”. It was concerned with how the history, heritage, historiography and testimony associated with the parish could be harvested, made sense of and subsequently used.

The study was epistemological in nature and the research was concerned with how heritage knowledge is gathered, curated and understood. It was built around the collection of knowledge through expert testimony from Colin Mackenzie and Alan Winchester, who have extensively researched aspects of life in the Cabrach. This was done using a series of theme-based but free-flowing conversational workshop involving participants and research team. Issues of trust and authority in the research team were crucial. Data were recorded, transcribed and coded. A conceptual model for heritage storytelling in the Cabrach was developed together with a transferable version for other contexts.

The research was conceived around identifying the stories of the Cabrach and grouping them into cohesive narrative themes focused on the most important aspect of the glen's history (the development of malt whisky distilling). The research showed how all crucial narratives associated with the Cabrach were interconnected with that malt whisky story. It was concerned with identifying broad thematic narratives rather than the specific detailed stories themselves, but also from a methodological perspective how stories around those themes could be collected, curated and used. It presents the outcome of “expert testimony” oral history conversations and presents a conceptual model for the curation of heritage knowledge.

This paper reports on research which focuses on the confluence of those issues of heritage-led regeneration, intangible cultural heritage, as well as how stories of and from, about and for, a distinctive community in North-East Scotland can be collected, curated and displayed. It presents methodological conceptualisations as well as focused areas of results which can be used to create a strong and inclusive narrative to encapsulate the durable sense of place and support the revival of an economically viable and sustainable community.

This conceptual model offers a framework with universal elements (Place, People, Perception) alongside a strong core narrative of storytelling. That core element may vary but the outer elements remain the same, with people and place being omnipresent and the need to build an emotional or visceral connection with visitors being crucial, beyond “telling stories” which might be regarded as parochial or narrowly focused. The model informs how communities and heritage organisations tell their stories in an authentic and proportionate manner. This can help shape and explain cultures and identities and support visitors' understanding of, and connection with, places they visit and experience.

The originality lies in two principal areas, the exploration of the narratives of a singularly distinctive community – the Cabrach – which plays a disproportionately significant role in the development of malt whisky distilling in Scotland; and also in terms of the methodological approach to the collection and curation of heritage storytelling, drawing not on first-hand accounts as in conventional oral history approaches but through the expert testimony of two historical and ethnographic researchers. The value is demonstrating the creation of a conceptual model which can be transferred to other contexts.

The study is aimed to compare the prediction success of basic machine learning and ensemble machine learning models and accordingly create novel prediction models by combining machine learning models to increase the prediction success in construction labor productivity prediction models.

Categorical and numerical data used in prediction models in many studies in the literature for the prediction of construction labor productivity were made ready for analysis by preprocessing. The Python programming language was used to develop machine learning models. As a result of many variation trials, the models were combined and the proposed novel voting and stacking meta-ensemble machine learning models were constituted. Finally, the models were compared to Target and Taylor diagram.

Meta-ensemble models have been developed for labor productivity prediction by combining machine learning models. Voting ensemble by combining et, gbm, xgboost, lightgbm, catboost and mlp models and stacking ensemble by combining et, gbm, xgboost, catboost and mlp models were created and finally the Et model as meta-learner was selected. Considering the prediction success, it has been determined that the voting and stacking meta-ensemble algorithms have higher prediction success than other machine learning algorithms. Model evaluation metrics, namely MAE, MSE, RMSE and R², were selected to measure the prediction success. For the voting meta-ensemble algorithm, the values of the model evaluation metrics MAE, MSE, RMSE and R² are 0.0499, 0.0045, 0.0671 and 0.7886, respectively. For the stacking meta-ensemble algorithm, the values of the model evaluation metrics MAE, MSE, RMSE and R² are 0.0469, 0.0043, 0.0658 and 0.7967, respectively.

The study shows the comparison between machine learning algorithms and created novel meta-ensemble machine learning algorithms to predict the labor productivity of construction formwork activity. The practitioners and project planners can use this model as reliable and accurate tool for predicting the labor productivity of construction formwork activity prior to construction planning.

The study provides insight into the application of ensemble machine learning algorithms in predicting construction labor productivity. Additionally, novel meta-ensemble algorithms have been used and proposed. Therefore, it is hoped that predicting the labor productivity of construction formwork activity with high accuracy will make a great contribution to construction project management.

The direction of causality between job satisfaction and job performance (known as the holy grail of industrial psychologists) is undetermined and related research findings in different organizational contexts are mixed. Based on the ample literature, mainly from Western countries, on the relationship between job satisfaction and job performance, a non-recursive bow pattern model was utilized to investigate the direct relationship between these two variables in an Asia–Pacific higher education system.

This study is quantitative in approach and survey in design. Additionally, to meet the statistical requirements of non-recursive bow pattern analysis, the authors added welfare as a theory-driven instrumental variable to introduce exogenous variability. Using the efficient partial least squares (PLSe2) estimator, the authors fitted the model to the data collected from 2008 academics affiliated with Malaysian public universities and polytechnics.

The results showed that while job satisfaction is considerably influenced by welfare, it is not a significant predictor of job performance directly. In addition, a meaningful positive correlation between the disturbance terms of job satisfaction and job performance was observed, suggesting the existence of other factors that could increase both job satisfaction and job performance. The findings' theoretical and practical implications are discussed, and a list of theory-driven evidenced-based policies in this regard is provided.

This is the first study to test a non-recursive bow pattern model and examine the holy grail of industrial psychology based on the PLSe2 methodology, as a parametric approach to partial least squares (PLS), in a higher education context. This study also provides higher education researchers with the advantages of the PLSe2 method, especially in causal-predictive modeling, in the context of applied higher education research.

Student interest and learning success is an important component of teaching learning research. However, while the impact of emotions and psychological needs on students' achievements has been a focus of research, the impact of their physiological needs has been under studied. In this explorative study, I examine what impact the physiological and psychological needs of student teachers have on their feelings, motivation, and interest in different learning settings.

The research method used was the daily reconstruction method and included the Felix-App, a new digital research and feedback tool that allows the measurement of feelings, needs, motivation, and interest in real time.

The results suggest the importance of physiological needs for perceived emotions, motivation, and interest in the learning subject. The psychological needs, on the other hand, are of less importance.

The Felix-App is an innovative tool to learn more about learners' emotions and needs in real learning settings. The importance of physiological needs has been known since Maslow, but should be considered much more in the context of teaching and learning research in the future. There is a need for further research on the importance of physical aspects in learning.

The purpose of this study was to compare four different consumer pathway models based on identity theory, attitude/loyalty theory, lifestyle theory and hierarchy of effects theory, each with associated instruments measuring connection to the team.

The authors did a two-study analysis, first collecting data from people aware of an NFL team (N = 218) and then an MLS team (N = 209) to determine which connection item performed better.

The authors found that the Consumer Pathway for Sport Fandom based on the hierarchy of effects theory and its associated interest measurement item performed better than the other three frameworks and items. The Interest item shared the most variance with games attended, games intending to attend, games watched via media and games intending to watch via media.

The Consumer Pathway for Sport Fandom represents the entire consumer spectrum from non-aware consumers all the way up to die-hard sports fans. This pathway will allow sport marketers to track their consumers from initial awareness of the product or service all the way through the brand relationship to ultimate loyalty.

The purpose of this study is to investigate the psychological consequences of human trafficking and to reveal the importance of appropriate post-trafficking psychological interventions. Specifically, this study provides a detailed analysis of human trafficking categories, as well as the characteristics of victims and traffickers’ motives. More recent data in the literature show that trauma-coerced attachments and complex post-traumatic stress disorder are also observed among trafficking survivors.

Each of the mentioned mental disorders is presented separately, and results are discussed throughout this study. Consequently, psychological interventions are proposed in accordance with the human trafficking category, survivors’ characteristics and needs and with the relevant personal risk factors determined among victims.

Sex trafficking can have a severe effect on a victim’s mental health, and mental health disorders are substantially higher in human trafficking victims compared to non-trafficked victims or general psychiatric population. Limitations, implications and future recommendations are discussed.

A limited number of past studies evaluated the mental health consequences and identified that survivors have a higher prevalence of anxiety disorders, depression disorders and post-traumatic stress disorder.