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The study responds to the common concerns of authors, reviewers, and editors on writing and publishing high-quality literature review (LR) studies. First, we evolved the background and decision elements on the five parameters of a quality LR paper: Planning, Operationalizing, Writing, Embedding, and Reflecting (POWER), from the editorials and guiding literature. Statistical procedure and refinement of 256 responses from writers, reviewers, and editors revealed 37 decision elements. Finally, a multicriteria-decision-making approach was applied to the detailed responses from the lead editors of ABDC, Scopus, ABS, and WoS journals, and 31 decision elements were found strong enough to represent these five parameters on the quality of LR studies. All five parameters are found important to be considered. However, a high priority is suggested for embedding (the results coming out of the review) and operationalizing (the process of conducting the review), whereas reflection, writing, and planning of LR papers still remain important. The purpose of the POWER framework is to overcome the challenges and decision dilemmas faced by writers and decision-makers. The POWER framework acts as a guiding tool to conduct LR studies in general and business management scholars in specific ways. In addition, this study provides a checklist (Table 6) and template (Appendix A1) of a quality LR study to its stakeholders.

This study aims to explore the mediating role of employee work engagement in the relationship between training and creativity in the education sector in India.

The sample for this study consisted of 260 faculty members from 11 public universities in the Punjab region. Partial least squares-structural equation modeling (PLS-SEM) was utilized to test the hypotheses.

The results of the study revealed that training has a significant direct and indirect effect on employee creativity through employee work engagement. The findings suggest that training can stimulate work engagement, highlighting the importance of fostering employee engagement for enhancing creativity.

While the method used in this study may not facilitate direct generalizations, it offers valuable insights into prevalent discursive strategies found in numerous contemporary public organizations.

The findings offer insights for designing targeted training interventions to enhance work engagement and foster creativity among faculty members in the education sector.

This study contributes to the existing literature by addressing a gap in research on the interaction between training, work engagement and creativity. As there have been limited studies on this topic in the education sector in India, this research provides novel insights and extends the understanding of how these variables are related.

This paper aims to study the agent learning from expert demonstration data while incorporating reinforcement learning (RL), which enables the agent to break through the limitations of expert demonstration data and reduces the dimensionality of the agent’s exploration space to speed up the training convergence rate.

Firstly, the decay weight function is set in the objective function of the agent’s training to combine both types of methods, and both RL and imitation learning (IL) are considered to guide the agent's behavior when updating the policy. Second, this study designs a coupling utilization method between the demonstration trajectory and the training experience, so that samples from both aspects can be combined during the agent’s learning process, and the utilization rate of the data and the agent’s learning speed can be improved.

The method is superior to other algorithms in terms of convergence speed and decision stability, avoiding training from scratch for reward values, and breaking through the restrictions brought by demonstration data.

The agent can adapt to dynamic scenes through exploration and trial-and-error mechanisms based on the experience of demonstrating trajectories. The demonstration data set used in IL and the experience samples obtained in the process of RL are coupled and used to improve the data utilization efficiency and the generalization ability of the agent.

This paper aims to examine how organizational practices such as climate for conflict management (CCM) and high involvement work practices (HIWPs) reduce the negative consequences of workplace bullying (WPB) on work-related depression (WRD).

Data were collected from 468 full-time employees working in the financial sector in Türkiye by applying a student-recruited sampling strategy. The aforesaid relationships were assessed using SPSS AMOS 29.

The results indicated that WPB leads to WRD; however, this effect is alleviated by employee perceptions of strong CCM and the administration of HIWPs in workplace settings.

Collecting data from a single source poses the risks of self-report data bias; however, in the future, data may be collected from multiple sources to lessen this potential threat. The study was a cross-sectional study, which makes it hard to make casual inferences; longitudinal data would be more beneficial to establish casual associations.

Business owners and managers can draw from the study results to create a work environment perceived by employees to be fair when dealing with conflicts and the negative vices of bullying in workplaces. Also, organizations may administer practices that empower employees’ confidence and competence to deal with negative persecution in organizations.

Few studies, if any, have focused on examining the moderating effect of CCM and HIWPs in the association between WPB and WRD. Drawing upon conservation of resources theory, the study stands out as it tests the moderating effect of CCM and HIWPs in the connection between WPB and WRD. The findings contribute to the few available studies tackling organizational factors relevant to alleviating the negative consequences of WPB in organizations.

Images and caption descriptions serve as important visual stimuli that influence consumer preferences; therefore, the current study focuses on property images and captions illustrated on the home pages of accommodation-sharing platforms. Specifically, this study investigates the relative importance of hue, brightness and saturation of a property image and caption description styles on potential consumers’ preferences.

A mixed-method approach was used, and a total of 293 valid responses were collected through a discrete choice experiment approach. Interviews were conducted for additional analyses to explore the detailed explanations.

The utility model demonstrated that the image’s saturation was the most critical attribute perceived by the respondents, followed by caption description style, hue and brightness.

This is one of the first studies to investigate the display of attributes on a digital accommodation platform by exploring potential customers’ stated preferences. This study focuses explicitly on images and captions illustrated on the home page of an accommodation booking platform. Detailed image investigation is also a new research area in sharing economy-related research.

No study has investigated the effects of different parameters on publication bias in meta-analyses using a machine learning approach. Therefore, this study aims to evaluate the impact of various factors on publication bias in meta-analyses.

An electronic questionnaire was created according to some factors extracted from the Cochrane Handbook and AMSTAR-2 tool to identify factors affecting publication bias. Twelve experts were consulted to determine their opinion on the importance of each factor. Each component was evaluated based on its content validity ratio (CVR). In total, 616 meta-analyses comprising 1893 outcomes from PubMed that assessed the presence of publication bias in their reported outcomes were randomly selected to extract their data. The multilayer perceptron (MLP) technique was used in IBM SPSS Modeler 18.0 to construct a prediction model. 70, 15 and 15% of the data were used for the model's training, testing and validation partitions.

There was a publication bias in 968 (51.14%) outcomes. The established model had an accuracy rate of 86.1%, and all pre-selected nine variables were included in the model. The results showed that the number of databases searched was the most important predictive variable (0.26), followed by the number of searches in the grey literature (0.24), search in Medline (0.17) and advanced search with numerous operators (0.13).

The results of this study can help clinical researchers minimize publication bias in their studies, leading to improved evidence-based medicine.

To the best of the author’s knowledge, this is the first study to model publication bias using machine learning.

Prior research examining cultural effects on customer service expectations has primarily used more generic Western cultural theory on an aggregate scale or with only a single variable to draw conclusions on a customer’s underlying reasoning for buying a service. This study aims to focus on culturally distinct clusters within non-Western nations, specifically exploring within-cluster differences in service expectations within the Confucian Asia cluster.

This study developed a measurement model of Chinese cultural values and service expectations, consisting of a three and five-factor structure, respectively. Data from a sample of 351 diners were analysed using SmartPLS software. The data was compared with similar studies within the Confucian Asia cluster to understand the culture effect on service expectations and within-cluster variations.

The findings underscore the varying importance of cultural values in shaping customer service expectations, emphasizing their relative, rather than equal, significance. The study provides insights into potential within-group differences in customer service expectations within the same cultural cluster – without losing sight of the fundamental cultural heterogeneity of the Confucian culture.

Managers should leverage the distinct cultural values of their operating country to gain insights into diverse customer groups, predict their behaviours and meet their needs and expectations.

This study offers valuable insights to both service management scholars and practitioners by focusing on culturally distinct clusters of non-Western nations and exploring their effects on variation in service expectations within these clusters.

It is predicted that micromanagement may become a growing workplace concern post-Covid-19, with managers grappling for control in the current hybrid/remote working environment. This will be happening at a time when millennials represent half of the working population. This study contributes to existing literature and provides an overall appreciation of the complexities of micromanagement and how it impacts millennials' followership styles.

A quantitative study was undertaken and a series of hypotheses were tested. The target sample for this research was the millennial cohort aged between 24 and 41. Data were analysed using SPSS.

This paper confirmed that “unfavourable followership styles” consisted of various negative followership reactions such as anxiety, demotivation, dissatisfaction, disengagement, reduction in support for managers, limited upward feedback, team conflict, reduced productivity and innovation due to fear of making mistakes ultimately facilitating a toxic workplace. Essentially, this research validated the notion that in order to create a sustainable organisation post-Covid-19, HR professionals must take proactive measures to mitigate this form of harmful leadership.

Data weaknesses transpire where respondents have never interacted with a micromanager in reality. Therefore, perceived reactions to a hypothetical micromanager may differ from those respondents who were exposed to micromanagers.

A lack of research exists on the intersection of micromanagement and millennials' followership styles and as such this paper bridges that gap.

As young individuals transition from educational settings to embark on their career paths, their expectations for their future careers become of paramount importance. Ng et al. (2010) examined the expectations of young people in post-secondary education in 2007; those colloquially referred to as “Millennials” or “GenY”. The present study replicates Ng et al.'s (2010) study among a sample of post-secondary students in 2019 (referred to as Generation Z or GenZ) and compares the expectations of young adults in GenY and GenZ.

This study employs a time-lag comparison of GenY and GenZ young career entrants based on data collected in 2007 (n = 23,413) and 2019 (n = 16,146).

Today's youth seem to have realistic expectations for their first jobs and the analyses suggest that young people continue to seek positive, healthy work environments which make room for work–life balance. Further, young people today are prioritizing job security and are not necessarily mobile due to preference, restlessness or disloyalty, but rather leave employers that are not meeting their current needs or expectations.

Understanding the career expectations of young people allows educators, employers and policymakers to provide vocational guidance that aligns those expectations with the realities of the labor market and the contemporary career context.

While GenY was characterized as optimistic with great expectations, GenZ can be described as cautious and pragmatic. The results suggest a shift away from opportunity, towards security, stability, an employer that reflects one's values and a job that is satisfying in the present.

Manufacturing firms must embrace smart technologies and develop complex leadership approaches to achieve sustainability. Using the dynamic capability theory, this paper aims to examine the influence of the adoption of industry 4.0 technologies (AT) and paradoxical leadership (PL) on corporate sustainable performance (CSP) of manufacturing small-medium enterprises (SMEs) in Malaysia. Moreover, organisational ambidexterity (OA) is a mediator and strategic flexibility (SF) is a moderator in the study.

The study is a cross-sectional, quantitative study design that collected 395 usable responses through a simple random sampling technique and a close-ended structured questionnaire. Structural equation modelling (SEM) procedures were followed to analyse the data.

The statistical outcome implies that the AT significantly influence CSP and OA and mediate with CSP in the presence of OA. Moreover, PL shows a significant impact on OA, is insignificant on CSP and mediates with OA and CSP. The authors found a significant association between OA and CSP; however, SF did not provide evidence of a moderate effect.

The findings of this study clarify the role that organisational capabilities (OA, AT, PL and SF) play in fostering sustainability. The authors suggest incorporating SMEs from different geographies in other sectors by applying diverse methodologies and relevant constructs.

The result injects new perspectives into policy, managerial and individual levels. Installing OA, AT, PL and SF makes SMEs sustainable.

The empirical validation of the influence of OA and AT on CSP and the interaction of PL and SF enriches the organisational and entrepreneurial literature.