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This study investigates the impact of tax planning, both independently and in conjunction with earnings management, on the persistence of earnings and its various components.

In this study, tax planning refers to corporate strategies aimed at minimizing taxes, while earnings management involves manipulating reported earnings through accounting accruals. The analysis uses a dataset of US companies from 1989 to 2016 and includes a series of regression tests.

The study finds that firms implementing aggressive tax strategies exhibit lower persistence in cash flows from operations and earnings. Furthermore, companies using both aggressive tax planning and earnings management techniques show the lowest persistence in total accruals, cash flows from operations and reported earnings.

Our sample of US firms limits generalizability. Future research could explore the international impacts of tax planning and earnings management on earnings quality and include post-2016 data for insights on the 2018 tax cuts and COVID-19. Investigating other earnings quality measures and their influence on investors and analysts could enhance performance assessment.

This research identifies key factors influencing the interpretation of financial statements, offering valuable insights for regulators, auditors, tax authorities, financial analysts and other users with significant practical and social implications.

This study contributes to prior research by highlighting the need to investigate the real effects of tax avoidance and extends prior research by examining the impact of high levels of tax planning, along with aggressive earnings management, on earnings persistence.

This research conducts bibliometric analyses and network mapping on smart libraries worldwide. It examines publication profiles, identifies the most cited publications and preferred sources and considers the cooperation of the authors, organizations and countries worldwide. The research also highlights keyword trends and clusters and finds new developments and emerging trends from the co-cited references network.

A total of 264 records with 1,200 citations were extracted from the Web of Science database from 2003 to 2021. The trends in the smart library were analyzed and visualized using BibExcel, VOSviewer, Biblioshiny and CiteSpace.

The People’s Republic of China had the most publications (119), the most citations (374), the highest H-index (12) and the highest total link strength (TLS = 25). Wuhan University had the highest H-index (6). Chiu, Dickson K. W. (H-index = 4, TLS = 22) and Lo, Patrick (H-index = 4, TLS = 21) from the University of Hong Kong had the highest H-indices and were the most cooperative authors. Library Hi Tech was the most preferred journal. “Mobile library” was the most frequently used keyword. “Mobile context” was the largest cluster on the research front.

This study helps librarians, scientists and funders understand smart library trends.

There are several studies and solid background research on smart libraries. However, to the best of the author’s knowledge, this study is the first to conduct bibliometric analyses and network mapping on smart libraries around the globe.

This paper aims to study a neural network-based fault-tolerant controller to improve the tracking control performance of an unmanned autonomous helicopter with system uncertainty, external disturbances and sensor faults, using the prescribed performance method.

To ensure that the tracking error satisfies the prescribed performance, the authors adopt an error transformation function method. A control scheme based on the neural network and high-order disturbance observer is designed to guarantee the boundedness of the closed-loop system. A simulation is performed to prove the validity of the control scheme.

The developed adaptive fault-tolerant control method makes the system with sensor fault realize tracking control. The error transformation function method can effectively handle the prescribed performance requirements. Sensor fault can be regarded as a type of system uncertainty. The uncertainty can be approximated accurately using neural networks. A high-order disturbance observer can effectively suppress compound disturbances.

The tracking performance requirements of unmanned autonomous helicopter system are considered in the design of sensor fault-tolerant control. The inequality constraint that the output tracking error must satisfy is transformed into an unconstrained problem by introducing an error transformation function. The fault state of the velocity sensor is considered as the system uncertainty, and a neural network is used to approach the total uncertainty. Neural network estimation errors and external disturbances are treated as compound disturbances, and a high-order disturbance observer is constructed to compensate for them.

This study examines how green human resource management (GHRM), individually and collectively, affects green psychological climate (PGC), green in-role behavior (GIB), extra-role behavior (GEB) and green creativity (GC) in small, medium and large textile companies. The study also explores how green intellectual capital (GIC) moderates the relationship between GHRM and PGC and GC.

The study was conducted in two phases: in phase 1 (N = 41 records), a systematic literature review was performed to identify the gaps, and in phase 2 (N = 412 managers and supervisors), a quantitative survey method was employed. The structural equation model, with 1st-order and 2nd-order hierarchical models, was used to test the hypotheses.

The results showed that GHRM practices positively impacted PGC and GC. GHRM practices, including employee involvement (GEI), compensation and reward (GCR), training and development (GTD) and recruitment and selection (GRS), enhanced PGC. However, performance and management (GPM) do not significantly affect PGC. PGC significantly and positively affects GIB and GEB. GHRM also directly significantly influenced GC. Additionally, GIC significantly and positively moderated the relationship between GHRM and GC but not PGC, improving green creative behaviors in textile companies.

This study spurs textile enterprises, especially small, medium and large, to prioritize GHRM practices where employees with green climate (i.e. PGC), behaviors (i.e. GIB and GEB), knowledge, skills and abilities (i.e. GIC) strengthen their GC. Policymakers should encourage the adoption of GHRM to align GIC practices with environmental goals.

This study is unique in examining how GHRM practices, individually and collectively, enhance PGC employees’ GIB, GEB and GC. GIC strengthens employee green behaviors to develop innovative ideas (i.e. GC). It examines how GIC is crucial for GHRM to enhance creative activities toward environmental sustainability practices and goals.

Green intellectual capital is broadly acknowledged as an invaluable resource for attaining a strategic advantage for enterprises. This article develops a novel theoretical framework to assess the impact of green intellectual capital on firms’ performance through green innovation and environmental performance, considering the “natural resource-based view (NRBV)” theory.

This paper applied a “quantitative research design” with a sample of 405 managers and owners of “small and medium enterprises” (SMEs) from NCR (India). The data were analyzed through the “covariance-based structural equation modeling (PLS-SEM)” technique.

The outcomes showed that green human capital and green structural capital substantially impact green innovation and environmental performance. Nevertheless, green relational capital negatively affects green innovation and environmental performance. Additionally, green innovation and environmental performance significantly influence firm (market and financial) performance.

This article delivers fruitful and actionable insights for SME managers, owners, academicians and policymakers in measuring a firm’s capability to translate resources into green intellectual capital from the “Industrial Revolution 4.0” viewpoint to empower its innovation, environmental and firm performance.

The study pioneered the exploration of the different roles of green intellectual capital and green innovation in improving environmental and firm (“market and financial”) performance. Additionally, to the researchers’ best knowledge, no former research has earlier categorized the firm performance into “market and financial performance,” as outlined in this research, thereby contributing novel insights to the field of intellectual capital.

This study utilizes social exchange theory to investigate the relationship between green intellectual capital and employee environmental citizenship behavior through serial mediation of organizational agility and employee green creativity.

This study uses a multi-level and multi-wave dataset of 425 employees and 70 managers nested within 35 manufacturing firms. The authors followed a 2-2-1-1 research framework in which organizational green intellectual capital (a level 2 variable) influenced employee environmental citizenship behavior (a level 1 outcome variable), which was then mediated by organizational agility (a level 2 variable) and employee green creativity (a level 1 variable). This study used Jamovi for hypotheses testing.

The findings suggest a positive relationship between green intellectual capital and organizational agility, leading positively to employee environmental citizenship behavior and employee green creativity. It indicates that green intellectual capital positively relates to employee environmental citizenship behavior via serial mediation effects of organizational agility and employee green creativity.

This study provides valuable insights for manufacturing firms and policymakers. The study encourages environmental conservation and restoration efforts by individuals and organizations, supporting initiatives to protect the environment. Findings may help manufacturing firms and policymakers towards mitigating environmental harm to achieve their sustainability objectives.

This study enhances our understanding of the link between green intellectual capital and employee environmental citizenship behavior through indirect path of organizational agility and employee green creativity.

This paper presents a comprehensive study using bibliometric and social network analysis (SNA) to depict the academic community, research hotspots and the correlation between research performance and social network measurements within Library Hi Tech.

Publications from Library Hi Tech between 2010 and 2022 are reviewed and analysed through coauthorship analysis, co-occurrence analysis, SNA and the Spearman rank correlation test.

The annual number of publications in Library Hi Tech increased from 2016 to 2022, indicating that this research has gradually gained global attention. The USA and China are the most significant contributors to the relevant publications. Scholars in this field mainly engage in small-scale cooperation. Academic libraries, digital libraries, libraries, information technology and COVID-19 were hot topics during the study period. In light of the COVID-19 pandemic, there was a marked increase in research on healthcare. Academic interest in the internet of Things and social media has proliferated recently and may soon attract more attention. Spearman rank correlation analysis shows that research performance (i.e. publication count and citation count) is significantly and positively correlated with social network measurements (i.e. degree centrality, betweenness centrality, closeness centrality and eigenvector centrality) in studies of Library Hi Tech.

This paper reveals a systematic picture of the research landscape of Library Hi Tech and provides a potential guide for future research. The relationship between scientific research performance and social network measurements can be objectively identified based on statistical knowledge.

This study investigates the direct influence of ambidextrous leadership on employees’ innovation behaviour, the mediating role of innovative self-efficacy and harmonious work passion, and the moderating role of Zhong-Yong thinking.

The authors conducted a series of questionnaire surveys to collect data in three time periods and from multiple sources; 332 supervisor–subordinate matched samples were obtained. The hypothesised relationships were tested using structural equation modelling and ProClin.

Ambidextrous leadership is positively associated with employees’ innovation behaviour, while innovative self-efficacy and harmonious work passion play mediating roles. The analysis further confirms that innovative self-efficacy and harmonious work passion play a chained double-mediating role between ambidextrous leadership and employees’ innovation behaviour, while Zhong-Yong thinking plays moderating roles between ambidextrous leadership and innovative self-efficacy and between ambidextrous leadership and harmonious work passion.

This study demonstrates the influence of ambidextrous leadership on employees’ innovation behaviour, specifically the role of ambidextrous leadership, and extends the relationship’s theoretical foundation. It is also expected to provide inspiration and serve as a reference for local Chinese management.

Environmental concerns and the urgent issues of climate change have shifted the organization’s focus toward achieving sustainability. Therefore, this study aims to evaluate the complex relationships among green human resource management (GHRM), green innovation (GI), green human capital (GHC) and sustainable performance (SP).

To investigate the relationships, the study employed partial least square structural equation modeling to run an analysis on 384 managers working in the hotel sector in Egypt, selected through a simple random sampling technique.

The results demonstrate that GHRM positively influences both GI and GHC. Additionally, GI and GHC have a positive impact on SP. Furthermore, GHRM directly contributes to SP, with GI and GHC acting as significant mediators in the relationship between GHRM and SP.

This study advances theoretical understanding and offers practical insights by employing the resource-based view theory and the ability-motivation-opportunity theory.

This research introduces and empirically tests a novel conceptual framework that comprehensively assesses the impacts of GHRM, GI and GHC on SP.

Existing studies have paid less attention to the impact of knowledge accumulation on digital transformation and its boundary conditions. Hence, this study aims to investigate the effects of ambidextrous knowledge accumulation on manufacturing digital transformation under the moderation of dynamic capability.

This study divides knowledge accumulation into exploratory and exploitative knowledge accumulation and divides dynamic capability into alliance management capability and new product development capability. To clarify the relationship among ambidextrous knowledge accumulation, dynamic capability and manufacturing digital transformation, the authors collect data from 421 Chinese listed manufacturing enterprises from 2016 to 2020 and perform analysis by multiple hierarchical regression method, heterogeneity test and robustness analysis.

The empirical results show that both exploratory and exploitative knowledge accumulation can significantly promote manufacturing digital transformation. Keeping ambidextrous knowledge accumulation in parallel is more conducive than keeping single-dimensional knowledge accumulation. Besides, dynamic capability positively moderates the relationship between ambidextrous knowledge accumulation and manufacturing digital transformation. Moreover, the heterogeneity test shows that the impact of ambidextrous knowledge accumulation and dynamic capabilities on manufacturing digital transformation varies widely across different industry segments or different regions.

First, this paper shifts attention to the role of ambidextrous knowledge accumulation in manufacturing digital transformation and expands the connotation and extension of knowledge accumulation. Second, this study reveals that dynamic capability is a vital driver of digital transformation, which corroborates the previous findings of dynamic capability as an important driver and contributes to enriching the knowledge management literature. Third, this paper provides a comprehensive micro measurement of ambidextrous knowledge accumulation and digital transformation based on the development characteristics of the digital economy era, which provides a theoretical basis for subsequent research.