Search results

In developing countries, rapid industrial growth frequently results in companies with high pollution levels, which in turn exhibit characteristics such as elevated emissions, increased energy consumption and overcapacity. In order to promote sustainable development among these heavily polluting firms, it is essential to implement a system of incentives and penalties that encourages environmentally responsible behaviour. China's environmental protection tax has replaced the previous pollution discharge fee (PDF) system. This tax aims to guide enterprises towards continuous adjustments and improvements in their production methods, increased investments in green technology, adoption of environmentally friendly production methods, reduced pollutant emissions and promotion of high-quality development. This chapter analyses how China's Environmental Protection Tax Law, enforced in 2018, affects the sustainable development capabilities of A-share listed companies in China. We utilise a difference-in-differences (DiD) model and measure total factor productivity (TFP) to quantify the impact of the tax law on these enterprises. TFP is a key indicator used to measure the effectiveness of resources utilised by enterprises in the production process. Our empirical analysis provides compelling evidence that the implementation of environmental protection taxes has significantly enhanced the TFP of heavily polluting enterprises. Importantly, the impact of these taxes is more pronounced for state-owned enterprises (SOEs) in comparison to their private counterparts in this sector. These findings offer valuable insights for policymakers in developing countries as they consider the design of environmental protection tax systems and supportive measures to promote sustainable development of companies with significant environmental impacts.

Recent studies have documented the significant influence of investment bank relationships on the forecast accuracy of affiliated analysts. However, the literature primarily focuses on investment bank-firm relationships, such as whether the investment bank has underwriter or lending relationships with firms. Little attention has been paid to the impact of investment bank-state relationships. To fill this gap in the literature, this paper investigates whether investment bank-state relationships create an information advantage for affiliated analysts.

We empirically test the information advantage of state-affiliated analysts using a large sample of analyst forecasts from China spanning the period 2008 to 2020. Specifically, we investigate whether state-affiliated analysts issue more accurate and timely forecasts around macro events. To address endogeneity concerns, we examine instances where analysts move between state-affiliated and non-affiliated banks, as well as changes in the controlling structure of investment banks.

We find that state-affiliated analysts demonstrate greater accuracy in forecasts driven by macro events, indicating their information advantage. This effect is more pronounced under conditions of heightened economic policy uncertainty and closer ties between investment banks and the state. After transitioning to a non-state-affiliated investment bank, analysts no longer maintain the ability to make superior macro-event-driven forecasts. Conversely, when the investment bank's affiliation changes from non-state to state, financial analysts gain an information advantage following the establishment of new state affiliation. Additionally, state-affiliated analysts tend to issue more assertive forecasts in response to macro events, which are subsequently echoed by their peers. Furthermore, this information advantage is recognized by investors, enhancing stock price informativeness.

Firstly, we contribute to the literature on the economic implications of state ownership in financial intermediaries. Secondly, we enrich the existing literature on financial analysts by acknowledging the pivotal role of investment bank relationships in shaping analysts' behaviors. Lastly, unlike existing literature that treats forecasts driven by macroeconomic events and those influenced by firm-specific events as a homogeneous category, this study contributes to the literature by innovatively categorizing analyst forecasts into two distinct types.

The purpose of this study is to learn what kinds of obstacles Indian businesses face when trying to make biodiversity protection a top priority as part of their corporate social responsibility (CSR) efforts. Interventions are proposed to elevate biodiversity protection to the ranks of CSR priorities among Indian businesses.

This study applies an interpretive phenomenological analysis strategy to glean information from in-depth interviews with leaders and professionals in CSR.

The findings of the study revealed that the main factors influencing Indian companies’ CSR area choices are existing processes and stakeholder pressures. Companies prioritise engaging with local communities and employees when selecting CSR activities. The major challenge is integrating biodiversity into business plans, with CSR heads struggling to secure investment due to long gestation periods and limited media coverage. Implementing agencies face issues with project deliverables, mainly due to land ownership and lack of local government support. Companies can also encourage employee involvement in pro-environmental behaviours. The study also provides practical solutions for Indian companies to enhance their CSR engagement in biodiversity conservation.

The research only focuses on the opinions of CSR specialists and leaders, so it may only consider part of the situation’s complexity inside the organisation. The results may only apply to the business climate in India; hence, extra care is warranted when extrapolating them to other countries. Nonetheless, the study provides valuable insights into the interplay between CSR and biodiversity protection that might inform future studies and policy initiatives.

This research fills a gap in the literature by investigating an uncharted territory: the role of CSR in protecting biodiversity in India. Examining obstacles and variables affecting CSR objectives illuminates business involvement in biodiversity conservation. The recommended treatments have real-world consequences for improving CSR involvement in this critical area.

We adopt an information risk view and argue that higher levels of pledge risk incurred by insiders incentivize opportunistic financial disclosure and impair the quality of information available to analysts to forecast firm performance.

We sample Chinese listed companies from 2010 to 2022. Following the literature, we apply established models to measure and test analysts’ forecasting accuracy/dispersion related to controlling shareholders pledging equity and the amount of margin call pressure. Analyst characteristics and nonfinancial disclosures proxied by CSR reports are also examined as factors likely to influence the relationship between pledge risk and analysts’ forecast quality.

We find that analysts’ earnings predictions are less accurate and more dispersed as the proportion of shares pledged (pledge ratio) increases and in combination with greater margin call pressure. Pledge ratios are significantly associated with several information risk proxies (i.e. earnings permanence, accruals quality, audit quality, financial restatements, related party transactions and internal control weaknesses), validating the channel through which equity pledges undermine analysts’ forecast quality. The results also demonstrate that forecast quality declines for a wide variety of analysts’ attributes, including high- and low-quality analysts and analysts from small and large brokerage firms. Importantly, nonfinancial disclosures, as proxied by CSR reporting, improve analysts’ forecasts.

We extend the literature by demonstrating that incremental pledge risk increases non-diversifiable information risk; all non-pledging shareholders pay a premium through more diverse and less accurate earnings forecasts. Our study provides important policy implications with economically significant costs to investors associated with insider equity pledges. Our results highlight the benefits of nonfinancial disclosures in China, which has implications for the current debate on the global convergence of CSR reporting.

Establishing and developing digital science and education evaluation platforms (DSEEPs) have several practical implications for the development of China's science, technology and education. Identifying and analyzing the key factors influencing DSEEP user experience (UX) can improve the users' willingness to use the platform and effectively promote its sustainable development.

First, a literature survey, a five-element model of UX and semi-structured interviews were used in this study to develop a DSEEP UX-influencing factor model, which included five dimensions and 22 influencing factors. Second, the model validity was verified using questionnaire data. Finally, the key influencing factors were identified and analyzed using a fuzzy decision-making trial and evaluation laboratory (fuzzy-DEMATEL) method.

Fourteen influencing factors, including diverse information forms and comprehensive information content, are crucial for the DSEEP UX. Its optimization path is “‘Function Services’ → ‘Information Resources’ → ‘Interaction Design’ → ‘Interface Design’ and ‘Visual Design’.” In this regard, platform managers can take the following measures to optimize UX: strengthening functional services, improving information resources, enhancing the interactive experience and considering interface effects.

This study uses a combination of qualitative and quantitative research methods to determine the key influencing factors and optimization path of DSEEP UX. Optimization suggestions for UX are proposed from the perspective of platform managers, who provide an effective theoretical reference for innovating and developing a DSEEP.

Energy poverty is a global phenomenon, but its prevalence is enormous in most African countries, with a potential impact on quality of life. This study aims to investigate the impact of energy poverty on the shadow economy.

The study uses panel data from 45 countries in Africa over a period of 1996–2018. Using panel cointegrating regression and panel vector auto-regression model in the generalized method of moments technique.

This study provides that energy poverty deepens the size of the shadow economy in Africa. It also documents that there is a bidirectional causality between shadow economy and energy poverty. Therefore, the two variables can predict each other.

The study suggests that lack of access to clean and modern energy services contributes to the depth of the shadow economy in Africa. African authorities are advised to strengthen rural and urban electrification initiatives by providing adequate energy infrastructure so as to reduce the level of energy poverty in the region. To ensure energy sustainability delivery, the study proposes that the creation of national and local capacities would be the most effective manner to guarantee energy accessibility and affordability. Also, priorities should be given to the local capital mobilization and energy subsidies for the energy poor. Energy literacy may also contribute to the sustainability and the usage of modern energy sources in Africa.

Previous studies reveal that income inequality contributes to the large size of shadow economy in developing economies. However, none of these studies analyzed the role of energy poverty and its implications for underground economic operations. Inadequate access to modern energy sources is likely to deepen the prevalence of informality in developing nations. Based on this, this study provides fresh evidence on the implications of energy deprivation on the shadow economy in Africa using a heterogeneous panel econometric framework. The study contributes to the literature by advocating that the provision of affordable modern energy sources for rural and urban settlements, and the creation of good energy infrastructure for the firms in the formal economy would not only improve the quality of life but also important to discourage underground economic operations in developing economies.

Nanotechnology (NT) advancements in personal protective textiles (PPT) or personal protective equipment (PPE) have alleviated spread and transmission of this highly contagious viral disease, and enabled enhancement of PPE, thereby fortifying antiviral behavior.

Review of a series of state of the art research papers on the subject matter.

This paper expounds on novel nanotechnological advancements in polymeric textile composites, emerging applications and fight against COVID-19 pandemic.

As a panacea to “public droplet prevention,” textiles have proven to be potentially effective as environmental droplet barriers (EDBs).

PPT in form of healthcare materials including surgical face masks (SFMs), gloves, goggles, respirators, gowns, uniforms, scrub-suits and other apparels play critical role in hindering the spreading of COVID-19 and other “oral-respiratory droplet contamination” both within and outside hospitals.

When used as double-layers, textiles display effectiveness as SFMs or surgical-fabrics, which reduces droplet transmission to <10 cm, within circumference of ∼0.3%.

NT advancements in textiles through nanoparticles, and sensor integration within textile materials have enhanced versatile sensory capabilities, robotics, flame retardancy, self-cleaning, electrical conductivity, flexibility and comfort, thereby availing it for health, medical, sporting, advanced engineering, pharmaceuticals, aerospace, military, automobile, food and agricultural applications, and more. Therefore, this paper expounds on recently emerging trends in nanotechnological influence in textiles for engineering and fight against COVID-19 pandemic.

Finite element (FE) analysis can be used for both design and verification of components. In the case of 3D-printed materials, a proper characterization of properties, accounting for anisotropy and raster angles, can help develop efficient material models. This study aims to use compression tests to characterize short carbon-reinforced PA12 made by fused filament fabrication (FFF) and to model its behaviour by the FE method.

In this work, the authors focus on compression tests, using post-processed specimens to overcome external defects introduced by the FFF process. The material’s elastoplastic mechanical behaviour is modelled by an elastic stiffness matrix, Hill’s anisotropic yield criterion and Voce’s isotropic hardening law, considering the stacking sequence of raster angles. A FE analysis is conducted to reproduce the material’s compressive behaviour through the LS-DYNA software.

The proposed model can capture stress values at different deformation levels and peculiar aspects of deformed shapes until the onset of damage mechanisms. Deformation and damage mechanisms are strictly correlated to orientation and raster angle.

The paper aims to contribute to the understanding of 3D-printed material’s behaviour through compression tests on bulk 3D-printed material. The methodology proposed, enriched with an anisotropic damage criterion, could be effectively used for design and verification purposes in the field of 3D-printed components through FE analysis.

The aim of this study was to investigate the role of immersive gaming on brand coolness and brand equity, with particular emphasis on fashion gaming collaborations. We used game theory as a theoretical framework to analyse immersive branding strategies and gain a deeper understanding of fashion consumers’ decision-making process in gaming environments. Gender, as a significant factor affecting gamers, has been studied as a moderator that impacts the overall proposed framework.

A quantitative method was used to assess the significance of relationships within the proposed model empirically. The partial least squares structural equation modelling technique was implemented to assess the relationships of the framework with a sample size of 160 active Malaysian gamers.

The findings indicate that brand equity is positively associated with perceived brand coolness. Furthermore, of the three core values of online games, perceived enjoyment is most strongly associated with perceived brand coolness, ahead of the values of self-expression and perceived emotional challenge. The results of the multigroup analysis further suggest that in the fashion industry, building brand equity through online games is strongly related to perceived brand coolness among female respondents, the role of perceived brand coolness being weaker among male respondents.

The study contributes to the existing literature by providing a deeper understanding of the impact of immersive gaming branding practices on the overall equity of the fashion brand. The results provide insight for fashion brand managers into the significant effect on consumer behaviour outcomes of fashion-gaming collaborations.

本研究擬探討身歷其境的遊戲體驗在品牌酷感和品牌資產上所扮演的角色; 研究特別強調裝扮遊戲的合作。研究人員以博弈論作為研究的理論框架,來分析沉浸品牌策略、和對時裝消費者在遊戲的環境中如何作出決策取得更深入的瞭解。研究人員探討了性別作為影響遊戲參與者的重要因素,這因素被視為為整個被提出的框架帶來調節的影響和作用。

研究人員採用定量方法進行研究,目的為於被提出的模型內之各種關聯的意義進行以經驗為依據的評估。研究人員採用了基於偏最小平方法的結構方程模型研究法,來對一個包含160名活躍的馬來西亞遊戲參與者的樣本進行框架的各個聯繫的評估研究。

研究結果顯示,品牌資產與品牌酷感成正相關; 而且,在網絡遊戲的三個核心價值中,感知享受與品牌酷感之間的聯繫最為強烈和密切,超過自我表現和感知情感挑戰兩者的價值; 多群組的分析結果更暗示了在時裝產業裡,透過網絡遊戲去建立品牌資產在女性回應者中是與品牌酷感有強烈密切的關係; 而在男性回應者中,品牌酷感所扮演的角色則較弱。

本研究使我們能更深入認識沉浸遊戲品牌的慣常做法如何影響時裝品牌的整體資產。研究結果為時裝品牌經理提供了啟示,使他們明瞭時裝遊戲的合作會給消費者行為產生重要的影響。

This paper draws on the dynamic capabilities (DC) view to develop a conceptual framework that explicates the mechanisms through which human intelligence (HI) and artificial intelligence (AI) substitute and complement each other for organizational knowledge management (KM) while considering the role of ethics.

This is a conceptual paper that draws on DC theory and integrates insights from the burgeoning literature on organizational AI adoption and application to develop a conceptual framework that explains the mechanisms through which HI and AI may substitute and complement each other for organizational KM to develop DC.

The conceptual framework demonstrates that substituting HI with AI is suitable for external environmental scanning to identify opportunities, while AI substitution for HI is ideal for internal scanning through data analytics. Additionally, HI complementing AI is effective for seizing opportunities by aligning internal competencies with external opportunities, whereas AI complementing HI is beneficial for reconfiguring assets by transforming tacit knowledge into explicit knowledge. This substitution and complementarity between HI and AI shape KM processes—acquisition, conversion, application, and retention—that influence organizational performance, depending on how internal and external ethical standards govern organizational AI use.

The paper presents key insights into how AI may substitute for HI for internal data analytics in KM but may be ineffective for external environmental scanning to sense opportunities. It further reveals that using AI to capture and convert tacit knowledge (HI) to explicit knowledge requires ethical considerations at the organizational level, but ethical considerations are necessary at the employee/manager level when HI relies on AI-generated insights for strategic decisions.

The study implies that in environments with defined regulations for AI and KM (e.g. privacy protection), responsibility for the consequences of AI-HI substitution and complementarity in developing DC can be assigned to specific steps in the KM process. However, in environments with undefined regulations, responsibility must be assigned to people, units or departments who manage the entire KM process to ensure accountability for ethical breaches.

This study proposes AI-HI substitution and complementarity in organizations to extend the understanding of the relationship between AI and HI to DC development.