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The literature on knowledge management in sustainable supply chain (KMSSC) has witnessed significant growth in the past two decades. However, a scientometric review that consolidates the primary trends and clusters within this topic has been notably absent. This paper aims to scrutinize recent advancements and identify the intellectual underpinnings of KMSSC research conducted between 2002 and 2022.

The present review employs a scientometric analysis approach via visualization maps of prolific contributions, co-citation, co-occurrence and thematic networks to examine a total of 114 articles and conference papers on KMSSC.

Emerging research frontiers and hotspots are revealed and a state-of-the-art framework of KMSSC research structure is developed.

The review provides significant implications that guide KMSSC research and better inform sustainability decisions in the supply chain context.

To the best of the authors' knowledge, this is the first review to thoroughly synthesize the intersected domain of KMSSC using scientometric analysis.

Gender disparity is a global phenomenon where females outnumber male participants. It has been observed that males are the early leaver from higher education, thus reflecting a severe concern about social instability. Malaysia is a prominent example where females outnumber males in higher education. In this context, this paper aims to examine the effect of individual, social and financial factors on the higher education self-efficacy of male and female students. It develops a comprehensive understanding of gender-based decision factors in pursuing higher education.

The hypothesis was formed based on a comprehensive literature review following the hypothetico-deductive positivist approach. These hypotheses were tested based on a sample of 250 respondents. A multiple regression analysis was deployed to test the relationship between the dependent variable and its predictors.

The results suggest that male and female students’ self-efficacy depends on five determinants, i.e. family influence, peer influence, career expectancy outcome, gender roles and institutional factors. Male students tend to be influenced more by these five determinants than females. Additionally, male students with better financial backgrounds are more likely to have higher self-efficacy, whereas gender roles negatively affect male and female students’ self-efficacy for higher education.

The breakout of COVID-19 resulted in the selection of limited students in Malaysia. Due to restricted movement orders, it was impossible to reach out to the students for data collection. Future research could include a broader area to include multiple other regions of Malaysia. For a broader aspect, the study could be conducted in other areas/countries where the problem of less male participation exists.

The relationship between higher education self-efficacy is assessed with social, financial and institutional factors for male and female students. It will enable the stakeholders and policymakers to make better decisions in increasing the self-efficacy of students to attain equity in higher education institutions.

The finding of this paper will assist in increasing male participation in higher education institutions to avoid any social instability.

This paper contributes to the literature in understanding the causes of gender gap reversal, focusing on Malaysian higher education institutions. It also provides empirical evidence to look at potential factors that affect the higher education self-efficacy of male and female students.

The agriculture sector is crucial for all economies, especially the developing ones. However, agricultural production is influenced by government intervention, which outshines the significant role of good governance indicators in agricultural productivity. In addition to this, the major climate changes also posed various challenges and led to water shortages and yield losses. Thus affecting agricultural production. In this paper, we address the issue by determining the association between state governance and agricultural productivity in N-11 countries.

Panel data have been collected from 2000 to 2021 through the Governance Indicator, World Development Indicator and World Bank databases. For data analysis, the researcher has utilized the autoregressive distributed lag (ARDL) estimations.

Through ARDL estimations, it is suggested that corruption (CC), employment in agriculture (EAG), political stability and violence absence (PS), rule of law (RL), regulatory equality (RQ) and water quality (WQ) significantly impact agricultural productivity (AGP) in the long run. In the short run, the impact of RL on AGP has been significant.

This study follows the method of data collection from secondary sources, which hinders the effectiveness of this study as, on the basis of the respective data, the potential of the researcher to get specific answers to research questions has been affected. Also, this study examines the context of N-11 countries from 2000 to 2021, which exerts a geographical limitation. While exploring the association between state governance and agricultural productivity, this study neglects the internal aspects of implementing state policies in firms.

On practical grounds, the significant association demonstrated by this study encourages agricultural firms to keenly consider state policies to gain sustainable agricultural development. Moreover, this study encourages agricultural firms to efficiently follow governance policies for efficient productivity. The outcomes of the study have shown that agricultural employment and governance infrastructure can efficiently enhance agricultural productivity. Besides, as per the results, water quality also positively impacts agricultural productivity; thus, relevant steps can be taken by the agricultural sector to improve the quality of water.

This study aims to identify factors affecting tax avoidance and tax evasion in Bangladesh and propose a future research agenda.

This paper reviewed 423 articles published between 2010 and 2023 using a systematic literature review (SLR) approach.

The review classified the factors into three categories, namely individual taxpayers, corporate taxpayers and tax administration. Income level, tax penalty, tax morale, inefficient tax return system and tax assessment process are associated with the individual’s tax avoidance and tax evasion activities. Profitability, corporate governance and financial restrictions are key factors influencing corporate taxpayers’ involvement in tax avoidance and tax evasion. Factors related to tax administration include lack of social interaction, distrust of national officials, complexities of policies, politicisation of tax authority, lack of political stability, incompetent auditing, insufficient recording, lack of administrative cooperation, lack of accountability, insufficient counselling and compromising in tax prosecution cases.

This paper provides tax regulators with insights to improve regulations and lessen tax avoidance and tax evasion activities.

This paper is the first attempt to provide guidance for academics when examining tax avoidance and tax evasion in Bangladesh.

Most research on tax evasion focused on microeconomic variables revolving around perceptions and decisions of individual taxpayers. However, a new wave of research is now investigating the role of macroeconomic variables in inducing tax evasion. This study adds to the limited studies in this new direction of research. Previous studies found that inflation, low gross domestic product (GDP) growth and gross fixed capital formation causes recession, increases unemployment, raise interest rates, hurts both domestic and foreign direct investments. This study examined the relationship between these variables and estimated tax evasion in Sub-Saharan Africa.

The study adopts a correlation research design with 2,300 data points collected from 23 countries in Sub-Saharan Africa. Specifically, tax to GDP ratio, gross fixed capital formation per GDP and the GDP annual growth report from each country for the period 2011–2020 was retrieved. Generalised least square regression technique was employed to analyse the data due to the presence of heteroskedasticity in the model and random effect was utilized based on the Hausman test. To avoid misspecification and biased result; therefore, all relevant test was conducted including the multicollinearity test.

The results indicate that GDP annual growth and gross fixed capital formation have a significant negative impact on estimated tax evasion in Sub-Saharan Africa. The findings further indicate a negative but insignificant relationship between inflation and estimated tax evasion in Sub-Saharan Africa. The study concludes that both GDP annual growth rate and gross fixed capital formation negatively influence estimated tax evasion and the policy implications in the African continent were discussed.

The new findings on the effects of GDP annual growth, growth fixed capital formation and inflation on estimated tax evasion provide novel knowledge that is currently lacking in the current literature, specifically Sub-Saharan African continent.

The substantial rise in tax evasion raises concerns about its adverse impact on the tax system’s integrity. This article aims to empirically investigate the factors affecting income tax evasion behavior among individuals in India’s National Capital Region (NCR).

A cross-sectional design was applied to gather primary data from (N = 548) taxpayers using a “self-administered survey questionnaire.” The hybrid “partial least squares structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA)” approach was applied to analyze the data.

This research presents a comprehensive model that explains 53.4% of the variance in behavioral intention and accounts for 51.4% in the actual behavior of individuals who participate in income tax evasion. The outcomes show that high tax burden, corruption and complexity of the tax system significantly influence behavioral intention. On the contrary, digitalization and tax morale insignificantly influence behavioral intention. Notably, behavioral intention is significantly associated with the actual behavior of individuals engaging in income tax evasion.

The outcomes offer valuable implications for practitioners, including policymakers, governments and tax authorities, to effectively curb income tax evasion behavior and help them make informed decisions.

The innovative research model enhances prevailing knowledge by providing empirical insights into the effect of income tax evasion behavior among individuals in India. This study also contributes methodologically by combining PLS (linear) and fsQCA (nonlinear) techniques, demonstrating that both methodologies offer a deeper comprehension of the factors affecting individual behavior to engage in income tax evasion.

This study examines the moderating role of female directors on the relationship between the firms’ characteristics and tax avoidance in an emerging economy.

This study employs the second-generation unit root test and the generalised method of moments (GMM) techniques. The Kao residual cointegration test corroborates a long-run cointegration among variables.

Female directors demonstrate mixed and unusual findings. No significant impact of female directors on tax avoidance is found. In addition, the presence of female directors does not show any negative or significant moderating impacts on the relationship between leverage, firm age, board size and tax avoidance. However, having more female directors can negatively and significantly moderate the relationship between more profitable firms, larger firms and tax avoidance. These findings show that the board of directors could use the presence of female directors to maximise their opportunistic behaviour, such as to avoid tax.

Research limitations – The study is limited by considering only 62 listed firms. The scope could be extended to include non-listed firms.

Research implications – There is increasing pressure for female directors on boards from diverse stakeholders, such as the European Commission, national governments, politicians, employer lobby groups, shareholders, and Fortune and Financial Times Stock Exchange (FTSE) rankings. This study provides input to decision-makers putting gender quota laws into practice. Our findings can help policy-makers adopt regulatory reforms to control tax avoidance practices and enhance organisational legitimacy. Policymakers can change their policy to include female directors up to the threshold suggested by the critical mass theory.

This is the first attempt in Bangladesh to explore the role of female directors in the relationship between the firms' characteristics and tax avoidance. The current study has significant ramifications for bringing gender diversity into practice as a component of good corporate governance.

Brief introduction on the importance and the need for plastic analysis methods were presented in the beginning section of this review. The plastic method for analysis was considered to be the more advanced method of analysis because of its ability to represent the true behaviour of the steel structures. Then in the following section, a literature analysis has been carried out on the previous investigations done on steel plates, steel beams and steel frames by other authors. The behaviour of them under different types of loading were presented and are under the investigation of innovative new analysis methods.

Structure member connections also have the potential for plastic failure. In this study, the authors have highlighted a few topics to be discussed. The three topics in this study are T-end plate connections to a square hollow section, semi-rigid connections and cold-formed steel storage racks with spine bracings using speed-lock connections. Connection is one of the important parts of a structure that ensures the integrity of the structure. Finally, in this technical paper, the authors introduce some topics related to seismic action. Application of the Theory of Plastic Mechanism Control in seismic design is studied in the beginning. At the end, its in-depth application for moment resisting frames-eccentrically braced frames dual systems is investigated.

When this study involves the design of a plastic structure, the design criteria must involve the ultimate load rather than the yield stress. As the steel behaves in the plastic range, it means the capacity of the steel has reached the ultimate load. Ultimate load design and load factor design are the methods in the range of plastic analysis. After the steel capacity has reached beyond the yield stress, it fulfills the requirement in this method. The plastic analysis method offers a consistent and logical approach to structural analysis. It provides an economical solution in terms of steel weight, as the sections designed using this method are smaller compared with elastic design methods.

The plastic method is the primary approach used in the analysis and design of statically indeterminate frame structures.

The pivotal aspect of aircraft assembly lies in precise measurement accuracy. While a solitary digital measuring tool suffices for analytical and small surfaces, it falls short for extensive synthetic surfaces like aircraft fuselage panels and wing spars. The purpose of this study is to develop a “combined measurement method” (CMM) that enhances measurement quality and expands the evaluative scope, addressing the limitations posed by singular digital devices in meeting measurement requirements across various aircraft components.

The study illustrated the utilization of the CMM by combining a laser tracker and a portable arm-measuring machine. This innovative approach is tailored to address the intricate nature and substantial dimensions of aircraft fuselage panels. The portable arm-measuring machine performs precise scans of panel components, while common points recorded by the laser tracker undergo coordinate conversion to reconstruct the fuselage panel’s shape. The research outlines the CMM’s measurement procedure and scrutinizes the data processing technique. Ultimately, the investigation yields a deviation vector matrix and chromatogram deviation distribution, pivotal in achieving enhanced measurement precision for the novel CMM device.

The use of CMM noticeably enhances fuselage panel assembly accuracy, concurrently reducing assembly time and enhancing efficiency compared to conventional measurement systems.

The research’s practical implication lies in revolutionizing aircraft assembly by mitigating accuracy issues through the innovative digital CMM for aircraft synthetic structure type product (aircraft fuselage panel). This ensures safer flights, reduces rework and enhances overall efficiency in the aerospace industry.

Introducing a new aircraft assembly accuracy compensation method through digital combined measurement, pioneering improved assembly precision. Also, it enhances aerospace assembly quality, safety and efficiency, offering innovative insights for optimized aviation manufacturing processes.

The purpose of this study is to evaluate and enhance sustainable manufacturing practices across various industries, focusing on environmental, economic and social dimensions, to promote a comprehensive understanding and implementation of sustainability, thereby improving overall industry performance and fostering long-term ecological and economic health.

The study uses multi-criteria decision-making-multivariate analysis technique to examine sustainable manufacturing practices (SMPs) in the Indian manufacturing sector. It identifies 11 SMP criteria through literature review and expert recommendations. Data are collected through questionnaires, expert committees and interviews. The study focuses on four key industries: automobile, steel, textile and plastic. Techniques like principal component analysis (PCA), technique for order preference by similarity to ideal solution (TOPSIS) and complex proportional assessment (COPRAS) are used to rank and assess performance.

The Indian automobile industry has shown the most effective SMPs compared to steel, textile and plastic sectors. The automobile sector is the benchmark for sustainable measures, emphasizing the importance of green practices for environmental, social and economic performance. Recommendations extend beyond the automobile sector to cement, electronics and construction.

The research emphasizes the importance of SMPs across various industries, focusing on economic, environmental and social considerations. It advocates for a holistic approach that enhances resource efficiency and minimizes ecological footprint.

The study uses ranking methods like PCA-integrated TOPSIS and COPRAS to evaluate performance in different industries, focusing on the benchmarked automobile sector. The research offers valuable insights and advocates for the widespread adoption of sustainable policies beyond the studied sectors.