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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.

The rapid pace of progress in academic institutions in developing economies has created stressful and relatively toxic workplaces, resulting in different negative organizational outcomes indicating the need to transform universities into healthier academic workplaces. However, a review of the higher education literature in both developed and developing countries shows that the antecedents and consequences of academics' affective states has been a relatively unexplored area. Hence, our study aims at testing basic tenets of Affective Events Theory (AET) in a higher education context to address this issue.

This is a quantitative study which applies CB-SEM methodology in analyzing the collected data from 2,324 academics in Malaysian higher education sector. We analyzed the data using EQS software package.

Our results provided substantial support for the applicability and relevancy of AET in higher education domain. Specifically, welfare and supervisory support were identified as the two work environment features which significantly and equally contribute to academics' job satisfaction. In addition, the results showed that positive affect, in comparison with negative affect, was three times stronger in influencing academics' job satisfaction.

Given the considerable role of positive affect in our study, higher education policy makers are urged to make relevant policies to transform universities into more emotionally safe workplaces. In addition, policies should be formulated in a way that encourages supervisory support and decreases workloads to ensure that the conflicts in general are reduced among academics.

This work is the first large-scale study testing the main tenets of AET in the higher education context. In addition, it addresses the problem of multivariate normality and solves this problem based on the robust methodology which corrects standard errors and fit indices, thereby providing more precise and unbiased results.

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.

Knowledge workers live and work in a technology-enabled, push-notification world full of interruptions that create information overload, often requiring these workers to utilize task switching as a mechanism to meet multiple competing tasks' demands. Previous research has examined both the positive and, more often, negative effects from interruptions and task switching on knowledge workers' performance. However, this paper aims to examine knowledge workers' agentic approach to managing interruption signals and consequent task switching to remain dedicated to the task at hand.

Using an inductive grounded theory approach, we analyzed data from semi-structured interviews with knowledge workers regarding their experiences with task management strategies in interruption-heavy environments.

The results indicate the emergence of a new construct that we define as “task adherence.” We identified behavioral and technological mechanisms that knowledge workers employ to adhere to tasks, and we also categorized a host of environmental, personal and task-related factors that influence a knowledge worker's task adherence level.

This study offers a novel conceptualization of key determinants of knowledge workers' task management. Through insights into how knowledge workers purposefully prepare for and address potential interruption signals, as well as manage task switching from subsequent interruptions, managers may be able to design new work processes to improve task performance.

In a world of interruptions, task adherence adds to and clarifies a missing element in the time and task management dilemma that can enhance future efforts in designing strategies that enable knowledge workers to be more productive.

The purpose of this paper is to examine the determinants of user satisfaction in the context of academic web digital library (DL). A model based on the re-specified information system success model was developed and tested using the structural equation modeling (SEM) technique.

The study employed survey research methodology with self-administered questionnaire as the research instrument. The questionnaire was developed based on the instruments used by previous researchers. The population of the study was students enrolled for the bachelor’s degree in the Faculty of Information Management, Universiti Teknologi MARA, Malaysia. These students were chosen because of researcher’s easy access to the sampling frame. Descriptive analysis and inferential analysis which include SEM were executed using IBM SPSS and AMOS statistical software.

The findings indicate that information quality, systems quality, service quality, perceived usefulness, perceived ease of use and cognitive absorption are significant predictor of users’ satisfaction with the web DL.

Instead of collecting data from students from various faculties, this study only covered students enrolled in one faculty. In the same light, as the respondents were from one faculty, they only report their experience of using one DL. Given these limitations, the results obtained are narrowed in terms of generalizability. The second limitation of the study is related to the predictor variables which only focussed on six variables only.

From the practical viewpoint, the instrument that has been developed can be used as a diagnostic tool for continuous improvements of the DL.

From the theoretical viewpoint, the study has developed an empirical based framework that depicts critical factors influencing DL satisfaction. Researchers specializing on the assessment of DL effectiveness can consider adopting the framework for future studies. Alternatively, the framework can be further extended by integrating other variables such as users’ characteristics or organizational characteristics.

Since the development of the COVID-19 vaccinations, questions surrounding race have been prominent in the literature on vaccine uptake. Early in the vaccine rollout, public health officials were concerned with the relatively lower rates of uptake among certain racial/ethnic minority groups. We suggest that this may also be patterned by racial/ethnic residential segregation, which previous work has demonstrated to be an important factor for both health and access to health care.

In this study, we examine county-level vaccination rates, racial/ethnic composition, and residential segregation across the U.S. We compile data from several sources, including the American Community Survey (ACS) and Centers for Disease Control (CDC) measured at the county level.

We find that just looking at the associations between racial/ethnic composition and vaccination rates, both percent Black and percent White are significant and negative, meaning that higher percentages of these groups in a county are associated with lower vaccination rates, whereas the opposite is the case for percent Latino. When we factor in segregation, as measured by the index of dissimilarity, the patterns change somewhat. Dissimilarity itself was not significant in the models across all groups, but when interacted with race/ethnic composition, it moderates the association. For both percent Black and percent White, the interaction with the Black-White dissimilarity index is significant and negative, meaning that it deepens the negative association between composition and the vaccination rate.

The analysis is only limited to county-level measures of racial/ethnic composition and vaccination rates, so we are unable to see at the individual-level who is getting vaccinated.

We find that segregation moderates the association between racial/ethnic composition and vaccination rates, suggesting that local race relations in a county helps contextualize the compositional effects of race/ethnicity.

Congruent with the world-wide call to combat global warming concerns within the context of advancements in smart technology, artificial intelligence, robotics, algorithms (STARA), and digitalisation, organisational leaders are being pressured to ensure that talented employees are effectively managed (nurtured and retained) to curb the potential risk of staff turnover. By managing such talent(s), organisations may be able to not only retain them, but consequently foster environmental sustainability too. Equally, recent debates encourage the need for teams to work digitally and interdependently on set tasks, and for leaders to cultivate competencies fundamental to STARA, as this may further help reduce staff turnover intention and catalyse green initiatives. However, it is unclear how such turnover intention may be impacted by these actions. This paper therefore, seeks to investigate the predictive roles of green hard and soft talent management (TM), leader STARA competence (LSC) and digital task interdependence (DTI) on turnover intention.

The authors used a cross-sectional data collection technique to obtain 372 useable samples from 49 manufacturing organisations in Nigeria.

Findings indicate that green hard and soft TM and LSC positively predict turnover intention. While LSC amplifies the negative influence of green soft TM on turnover intention, LSC and DTI dampen the positive influence of green hard TM on turnover intention.

Our study offers novel insights into how emerging concepts like LSC, DTI, and green hard and soft TM simultaneously act to predict turnover intention.

THIS number will appear at the beginning of the Leeds Conference. Although there is no evidence that the attendance will surpass the record attendance registered at the Birmingham Conference, there is every reason to believe that the attendance at Leeds will be very large. The year is one of importance in the history of the city, for it has marked the 300th anniversary of its charter. We hope that some of the festival spirit will survive into the week of the Conference. As a contributor has suggested on another page, we hope that all librarians who attend will do so with the determination to make the Conference one of the friendliest possible character. It has occasionally been pointed out that as the Association grows older it is liable to become more stilted and formal; that institutions and people become standardized and less dynamic. This, if it were true, would be a great pity.