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The purpose of this study is to perform bibliometric analysis to systematically and comprehensively examine the current landscape of digital knowledge, integration and performance in the transformation of sustainability accounting, reporting and assurance.

This research uses a systematic literature review, following the Scientific Procedures and Rationales for Systematic Literature Review protocol and uses various bibliometric and performance analytical methods. These include annual scientific production analysis, journal analysis, keyword cooccurrence analysis, keyword clustering, knowledge gap analysis and future research direction identification to evaluate the existing literature thoroughly.

The analysis reveals significant insights into the transformative impact of digital technologies on sustainability practices. Annual scientific production and journal analyses highlight key contributors to the adoption of digital technologies in sustainability accounting, reporting and assurance. Keyword cooccurrence analyses have identified key themes in sustainability accounting, reporting and assurance, highlighting the transformative role of digital technologies such as artificial intelligence (AI), blockchain, Internet of Things (IoT) and big data. These technologies enhance corporate accountability, transparency and sustainability by automating processes and improving data accuracy. The integration of these technologies supports environmental, social and governance (ESG) reporting, circular economy initiatives and strategic decision-making, fostering economic, social and environmental sustainability. Cluster-by-coupling analyses delve into nine broader revealing that IoT improves ESG report accuracy, eXtensible Business Reporting Language structures ESG data and AI enhances life cycle assessments and reporting authenticity. In addition, digital transformation impacts environmental performance, big data optimizes resource use and edge computing improves eco-efficiency. Furthermore, this study identifies avenues for future research to advance the understanding and implementation of digital technology in sustainability accounting, reporting and assurance practices.

Academically, this research enriches the understanding of how digital technologies shape sustainability practices and identifies gaps in digital knowledge and integration. Practically, it provides actionable insights for organizations to improve sustainability reporting and performance by effectively leveraging these technologies. Policy-wise, the findings advocate for frameworks supporting the effective implementation of these technologies, ensuring alignment with global sustainability goals.

This study offers a detailed analysis of the performance and intellectual framework of research on implementing digital technology in sustainability accounting, reporting and assurance. It highlights the evolving research landscape and emphasizes the need for further investigation into how emerging technologies can be leveraged to achieve sustainability goals.

The purpose of this study is to evaluate the tea stem natural dye was extracted from tea stem waste and applied to dyeing silk fiber, after which the properties of dyed samples were tested and analyzed.

The dyeing process was optimized using the response surface methodology (RSM) approach. Dyeing temperature, pH and time were chosen as variables and the color difference value as a response. The properties of dyed samples were tested and analyzed.

The optimized dyeing process was as follows: dyeing temperature 70°C, pH 3.5 and time 110 min. The K/S and color difference value of silk fiber dyed with the optimal process dye enzymatic oxidation with laccase was 1.4 and 27.8, respectively. The silk fiber dyed has excellent color fastness, antioxidant and antibacterial property, which greatly increases the added value of the dyed products. Furthermore, the optimized dyeing process did not significantly affect the strength properties and handle of the silk fiber.

Researchers have not used statistical analysis to optimize the process of dyeing process of silk fiber by tea stem natural dye enzymatic oxidation with laccase using response surface methodology. Additionally, this dyeing process was a low-temperature dyeing process, which not only saves energy consumption and reduces silk fiber damage but also obtains superbly dyeing results and biological functional properties, achieve the effects of waste utilization and clean dyeing.

Green finance aims to promote sustainable financial activities, environmental conservation and ecological balance. This study examines how renewable energy consumption (REN), technological innovation (TEC) and green finance (GRF) influence CO2 emissions in Vietnam from 2000 to 2022.

We utilize a novel three-stage methodology including quantile-on-quantile regression, wavelet coherence and wavelet-quantile regression to explore the relationship in the structure of intercorrelation in terms of quantile, time and frequency.

The findings show that Vietnam will increase environmental quality for higher green development. Specifically, there is a negative influence of TEC, REN and GRF on CO2 emissions across different quantiles and timescales.

The study recommends policies that support green development and reduce carbon emissions, such as increasing the use of renewable energy and conducting well-planned research to achieve a carbon-free, sustainable environment.

This article looks into the effects of GRF, TEC and REN on CO2 emissions in Vietnam. Some studies argue that green development in underdeveloped nations is insufficient to reduce CO2 emissions, thereby limiting the sample to a few advanced economies. Adopting diverse methodologies demonstrates the varied and intricate nature of understanding CO2 drivers. Additionally, our work makes detailed policy implications for Vietnam to meet its net-zero emission target and achieve sustainable development by 2050.

Despite a growing number of manufacturing firms actively collaborating with ecosystem members aiming for advanced service solutions, it remains unclear how digital collaboration capability (DCC) affects incremental service innovation (ISI) and radical service innovation (RSI) in the context of ecosystems. Drawing on dynamic capabilities theory and resource orchestration theory, this study aims to investigate the impacts of DCC on ISI/RSI and examine the mediating role of organizational agility (OA).

In this empirical paper, the authors obtained questionnaire data from 238 Chinese manufacturing firms embedded in the ecosystems. Then, the authors examined all the hypotheses through hierarchical regression analyses.

The empirical evidence indicates that DCC has a distinct effect on ISI and RSI. DCC positively affects ISI, whereas DCC shows an inverted U-shaped effect on RSI. In addition, OA mediates the positive effect of DCC on ISI within a certain range, whereas OA always mediates the inverted U-shaped effect of DCC on RSI.

This study enriches and extends existing research on DCC and service innovation by elucidating the heterogeneous effects of DCC on ISI/RSI and the complicated mediating role of OA. This study also has practical implications for manufacturing firms to revisit their collaboration capability and agility to boost ISI/RSI in the context of ecosystems.

This study examines conditions under which taxes and subsidies designed to mitigate corporate environmental impact positively influence corporate pro-environmental behavior (CPEB) adoption, considering unique dynamics within different industries.

A systematic literature review was conducted on 171 articles. Articles were coded using an inductive grid for comprehensive examination.

Taxes generally positively influence CPEB adoption, but reduced positive or even negative effects can arise. Subsidies, while often facilitating the achievement of environmental goals, variously impact CPEB. Explanations for variations include the level of taxation or subsidy, economic agent affected, subsidy source, nature of subsidy, factors external to tax or subsidy characteristics and conflicting environmental objectives. We suggest research avenues for each aspect, to enhance literature on the influence of tax policies on promoting CPEB.

Beyond general tax-policy considerations, we provide policymakers with recommendations for tax policies designed to promote CPEB.

We examine the distinctive effects of taxes and subsidies on CPEB adoption within diverse industries ((re)manufacturing, agriculture, shipping, automobile, freight transport and power generation). We compare specific effects across industries, and advocate detailed exploration of recurrent elements identified, emphasizing their potential significance in designing taxes and subsidies that promote CPEB.

The emerging economies of Asia have made remarkable economic progress over the past few decades, primarily driven by rapid structural transformation towards industrialization and manufacturing in particular. The share of informal manufacturing sector value added to GDP and of employment in the informal sector in total employment has increased considerably in these countries. Although this shift from agricultural to industrial/manufacturing may be seen as positive for the goals of poverty reduction, increased standard of living, formation of human capital, etc., its impact on the environment is often not free from contention. The aim of the paper is to examine the impact of informal manufacturing sector growth on environmental degradation in emerging Asian economies. Here, we have used CO₂ emissions as an indicator of environmental degradation. The impact of other exogenous variables, such as population growth, energy consumption, trade openness and foreign direct investment, has also been studied. We have employed the fixed effect model and the random effect model on the data spanning from 2000 to 2022. We have also used the Hausman test to check the suitability of the models. The results of the analysis indicate the presence of a U-shaped relationship between CO₂ emissions and informal manufacturing growth, thus refuting the validity of the Environmental Kuznets Curve hypothesis.

This study aims to deepen our understanding of how conventional technologies and robust accounting education standards can impact the effectiveness of green accounting practices in enhancing firm performance. To achieve this, the paper explores the moderating effects of artificial intelligence (AI) and accounting education quality on the relationship between green accounting and firm performance.

Using generalized method of moments estimation, this research uses a comprehensive dataset comprising 32,680 firm-year observations of listed companies from ten prominent countries – Canada, the UK, the USA, China, France, Germany, India, Japan, South Korea and Italy – over the period from 2012 to 2022. These countries, selected based on their high gross domestic product rankings as reported by the International Monetary Fund, ensure a diverse representation of economic strengths and capture a wide range of green accounting practices.

The study shows that green accounting practices positively impact current firm performance. Country-level AI positively moderates this relationship, suggesting that advanced AI infrastructure enhances the benefits of green accounting through improved data accuracy and decision-making. However, country-level accountancy education quality negatively moderates the relationship, indicating that stringent implementation of green accounting standards in these regions may introduce complexities and costs that reduce firm performance.

Integrating AI enhances data processing, predictive analytics and decision-making, improving green accounting effectiveness. High-quality accounting education ensures accurate reporting and greater transparency. These insights, when applied, can empower businesses to optimize sustainability strategies, assist policymakers in developing targeted regulations and guide educators in preparing accountants for the evolving demands of green accounting.

To the best of the authors’ knowledge, this study is the first to explore the combined moderating effects of AI and accounting education quality on the relationship between green accounting and firm performance. By highlighting the synergistic role of digital innovation and robust educational standards, this research offers novel insights into how these factors can enhance the effectiveness of green accounting practices and improve financial outcomes.

The purpose of this study is to detect the bolt loosening under conditions of impact loading with a low-cost self-powered triboelectric nanogenerator sensor.

In this work, an Al/PTFE-based triboelectric nanogenerator (AP-TENG) is used as a sensor. A pendulum impact device and a force hammer were used to apply the impact loads. The bolt status and the applied torque can be monitored under impact loading conditions by using the output voltage results of the AP-TENGs.

The output voltage results of the current AP-TENG sensor under five different bolt torques, i.e. from 0.5 to 2.5 N m, were measured. The measurements revealed that a thicker buffer layer significantly contributed to the generation of higher voltages. Besides, the AP-TENG was also used to light ten commercial green LEDs in series, and the brightness of the LEDs was high enough even for the daytime, which showed that it can be used as the alarm device. In addition, a sudden loose test was also carried out, and the obvious voltage spikes can be seen without the external impact. The force hammer impact tests have expanded the application scope of the AP-TENG in the bolt loosening detection.

The bolt loosening monitoring is important and useful for the safe operation. The application of TENG technology for detecting bolt loosening remains relatively unexplored. In addition, ten commercial green LEDs can be driven by the AP-TENG sensor, which can be used for the early warning of the bolted loosening status.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-06-2024-0216/

This study aims to propose and empirically examine the simultaneous complementary mediating role of bank branch collective human capital and justice climate between implemented high-performance work system (HPWS) and bank branch performance in the banking sector.

Data were collected at three different intervals of time between March 2022 to July 2022 from a final sample of 323 branch managers and 1,369 employees of commercial banks operating in Pakistan. Partial least square structural equation modeling was used to test the theoretical model proposed by this study.

Study results revealed that collective human capital and justice climate simultaneously mediate the relationship between implemented HPWS and branch performance.

The study contributes to the strategic HRM theory by proposing the complementary mediating roles of human capital and organizational justice to reap the benefits of implementing HPWS for improving branch-level performance. The managers should focus on developing and exploiting the knowledge, skills and experiences (human capital) of branch employees and improve their collective perceptions of justice to reap the benefits of HPWS for enhancing branch-level performance.

Drawing upon the resource-based view of the firm and organizational justice theory, this novel study examines the simultaneous and complementary mediating effects of collective human capital and justice climate between implemented HPWS and branch performance relationships at the branch-level analysis.

This paper aims to study the problem of starvation lubrication of high-speed ball bearings due to temperature rise during operation and to avoid thermal failure of bearing lubrication.

Under the quasi-statics model of grease lubrication, both the oil film dragging force and the rolling friction between the balls and raceways collectively counteract the gyroscopic torque. Initially, the static model for grease lubrication is solved, followed by calculating the generated heat using the local heat generation method and ultimately the multinodal thermal network model is solved, and the solved results of the quasi-statics are updated by the temperatures of the grease nodes based on the relationship of the grease temperature and viscosity, as well as the relationship of the viscosity and the film thickness.

By comparing the numerical calculation results of bearings under different working conditions, the influence of starvation lubrication on the oil film thickness, oil film drag force and rolling friction of bearings is discussed, and it is found that the numerical calculation results of the outer ring temperature of bearings under the starvation lubrication due to the consideration of temperature rise are closer to the experimental values.

This study reveals the dynamic characteristics of bearings under starvation lubrication, which is more practical and engineering guiding significance for the design of bearings, and introduces a new method and basis for the calculation of temperature rise of rolling bearings.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-06-2024-0208/