The Impact of the Performance Gap on Corporate Biodiversity Disclosure

The Energy-conservation and Emission-reduction Paths of Industrial sectors: Evidence from Chinas 35 industrial sectors

The influence of disclosing product lifecycle carbon footprint information on consumer purchase intentions based on the APE model perspective: An ERP and questionnaire study

Examining the relationships between carbon emissions and land supply in China

Hydrogen direct reduction (H-DR) in steel industry—An overview of challenges and opportunities

PurposeOne of the key components to fraud prevention is strong internal controls. However, the greatest threat to an organization's information security is the manipulation of employees who are too often the victims of ploys and techniques used by slick con men known as social engineers. The purpose of this paper is to help prevent future incidents by increasing the awareness of social engineering attacks.Design/methodology/approachA review of the more common social engineering techniques is provided. Emphasis is placed on the fact that it is very easy for someone to become a victim of a social engineer.FindingsWhile many organizations recognize the importance and value of having strong internal controls, many fail to recognize the dangers associated with social engineering attacks.Practical implicationsIndividuals and organizations remain vulnerable to social engineering attacks. The focus on internal controls is simply not enough and is not likely to prevent these attacks. Raising awareness is a good first step to addressing this significant and potentially dangerous problem.Originality/valueThis paper provides a concise summary of the most common social engineering techniques. It provides additional evidence that individuals need to better understand their susceptibility to becoming a victim of a social engineer as victims may expose their organizations to very significant harm.

Employee benefit plans require strong internal controls to operate effectively and efficiently. The Internal Revenue Service and the U.S. Department of Labor have given companies clear indication that they take note of plans that are governed by strong internal controls, and companies will notice more efficient, more focused examinations as a result. A strong system of internal control incorporates both preventive and detective controls to assure the plan is administered in an orderly manner, to safeguard plan assets, to deter wrongdoing, to ensure accuracy and completeness of information and to produce reliable and timely information. A strong control environment would be designed to assure the plan is run in accordance with the plan document and that funds are flowing to the correct trust or individual and according to the timing intended. This gives plan administrators a clear understanding of how the goals of the plan are being met. Good controls would assure policies and procedures are clearly established and are followed to keep the plan in compliance both with the plan document and with all relevant regulatory requirements.

Resource reconfiguration enables firms to adapt in dynamic environments by supplementing, removing, recombining, or redeploying resources. Whereas prior research has underscored the merits of resource reconfiguration and the modes for implementing it, little is known about the antecedents of this practice. According to prior research, under given industry conditions, resource reconfiguration is prompted by a firm’s corporate strategy and by characteristics of its knowledge assets. We complement this research by identifying learning from performance feedback as a fundamental driver of resource reconfiguration. We claim that performance decline relative to aspiration motivates the firm’s investment in knowledge reconfiguration, and that this investment is reinforced by the munificence of complementary resources in its industry, although uncertainty about the availability of such resources limits that investment. Testing our conjectures with a sample of 248 electronics firms during the period 1993–2001, we reveal a clear distinction between exploitative reconfiguration, which combines existing knowledge elements, and exploratory reconfiguration, which incorporates new knowledge elements. We demonstrate that performance decline relative to aspiration motivates a shift from exploitative reconfiguration to exploratory reconfiguration. Moreover, munificence of complementary resources mitigates the tradeoff between exploratory and exploitative reconfigurations, whereas uncertainty weakens the motivation to engage in both types of reconfiguration, despite the performance gap. Nevertheless, codeployment, which extends the deployment of knowledge assets to additional domains, is more susceptible to uncertainty than redeployment, which withdraws those assets from their original domain and reallocates them to new domains. Our study contributes to emerging research on resource reconfiguration, extends the literature on learning from performance feedback, and advances research on balancing exploration and exploitation.

This study introduces a behavioral theory of capability development. It suggests that a firm’s efforts to develop its explorative and exploitative capabilities are driven by performance feedback, and subsequently enhance performance. This full feedback loop is tested with a sample of U.S. firms in the electronics industry during 1993-2001. The findings reveal reduced investment in exploitative capability when performance exceeds aspirations, yet investment in explorative capability increases following such performance gap. In addition, environmental munificence and uncertainty attenuate these effects. The firm’s exploitative capability enhances performance in the short term, while its explorative capability undermines it in the short-term but improves it in subsequent periods. Finally, availability of resources and business relatedness enhance these performance effects. Accordingly, this study integrates theories on learning from performance feedback with the resource-based view while informing research o...

Allocation of provincial carbon emission allowances under China's 2030 carbon peak target: A dynamic multi-criteria decision analysis method

Climate finance is first and foremost a risk‐management problem, which means three things for investors. First, prudent investors will seek to hedge climate change risk by reducing their exposure to this risk. Second, investors will demand compensation for holding this risk. Third, investors will engage with companies to urge them to reduce this risk if they are not adequately compensated for it.For companies, the main implication of climate‐risk management by investors is that the companies with greater carbon emissions will have to pay a higher financial cost of carbon (FCC). In their new study described in this article, the authors undertake a comprehensive analysis of the risk compensation implications of exposing investors to carbon transition risk. They explore how corporate GHG emissions have affected the price‐to‐earnings (P/E) ratios of listed companies in Europe and the U.S. over the period 2016 to 2020. Their main finding is that financial markets are beginning to broadly discount companies whose high carbon emissions are viewed as subjecting them to higher levels of political and regulatory risk, and providing them with what amounts to a higher cost of capital.Although price‐earnings ratios are generally lower for companies with higher emissions, the discount varies significantly by sector and across firm size, with larger companies experiencing the larger discounts. Although the carbon discount is similar in the U.S. and in Europe, the authors find significantly higher discounts in industries in Europe that are directly covered by carbon pricing through the EU ETS. They even find a small price discount on corporate debt for smaller issuers. Overall, what emerges is a clear pattern of investors' growing concern over climate risk, which translates into an increasingly material FCC for companies with high GHG emissions. This growing valuation discount for companies with high emissions should encourage them to progress further along their decarbonization path, which our results suggest have large financial as well as other social benefits.

Regional sustainability contrasts in Brazil as indicated by the Compass of Sustainability – CompasSus

The dramatic changes in land use caused by human economic activities have a profound impact on carbon emissions and ecosystem service value （ESV）. In order to explore the evolution characteristics of carbon emissions and ESV on the spatial and temporal scales， based on the land use data of the Yellow River Basin from 2000 to 2020， this study used spatial autocorrelation and multivariate Logit regression models to study the spatial and temporal characteristics and spatial correlation of total carbon emissions and ESV in counties of the Yellow River Basin， then to explore the influencing factors of spatial correlation. The research findings were as follows： ① In the past 20 years， the total amount of land use carbon emissions in the basin has shown an overall growth trend， and the increasing counties were concentrated in energy-rich areas such as Inner Mongolia， Ningxia， and northern Shaanxi. The total amount of ESV increased first and then decreased， and the high value counties were mainly distributed on the edge of the Yellow River Basin， among which Qumalai County in Qinghai Province had the most ESV. The low value counties of ESV were mainly located in the economically active urban agglomerations such as the Shandong Peninsula Region， Central Plains Region， Guanzhong Plains Region， and cities along the yellow river in Ningxia. The lowest value of ESV has always been located in Xi'an. ② There was a spatial negative correlation between total carbon emissions and total ESV. The number of counties with high carbon emissions and high ESV has been increasing， mainly distributed in southern Inner Mongolia， eastern Ningxia， and northern Shaanxi， which was related to the location near the Yellow River and energy development. The double low type was mainly located in the gully area of the Loess Plateau， which is connected to the strip from the east and west. The low-high class was contiguously distributed in Qinghai， Sichuan， and western Gansu， and some were island-like distributed around the double-low class. The number of high-low classes was increasing year by year， mainly located in the core city area. ③ In low ESV counties， regions with better economic development and higher population were more likely to increase their carbon emissions. Taking the low carbon emissions from land use as a reference， the per capita GDP， energy use efficiency， and rainfall were significantly negatively correlated with the high-high and high-low categories. This indicates that most counties with high carbon emissions had relatively dense populations and less rainfall， resulting in higher energy dependence. Additionally， there was a positive correlation between low-high class areas and total population. When located in areas with low land use carbon emissions， areas with higher ESV values tended to have more a concentrated population distribution. The increase in land reclamation rate may encroach on forests and grasslands that can provide higher ecosystem services， reducing the value of regional ecosystem services. The research findings have certain reference significance for ecological protection and high-quality development decision-making in the Yellow River Basin.

The identification of influential factors of carbon emissions is crucial for carbon reduction， and the carbon emission characteristics and influencing factors of regions with different economic levels may be inconsistent， leading to differences in emission reduction strategies. Therefore， this study investigated the influencing factors of China's carbon emissions within the context of regional economic differentiation at a national scale. First， cluster analysis was conducted， resulting in four clusters labeled as follows： high economy with high carbon emission， high economy with low carbon emission， low economy with high carbon emission， and low economy with low carbon emission. Then， the STIRPAT model was used to identify key influencing factors in different regions with different levels of economic development and characteristics of carbon dioxide emissions. Finally， differentiated carbon emission reduction strategies were developed and proposed. The findings revealed spatial variations in both the influencing factors and their degrees. Population growth， energy consumption， and the development of primary and secondary industries are no longer the predominant factors influencing the growth of China's carbon emissions. The migration of population from low economic zones to high economic zones has led to an increase in the resident population in high economic zones， thereby promoting carbon emissions in these areas while suppressing emissions in low economic zones. However， the increase in per capita household size in high economic zones mitigates carbon emissions to some extent. Population density and urbanization rate exhibit an inverted U-shaped relationship with CO2 emissions. GDP per capita， carbon emission per unit of energy consumption， and GDP per unit of energy consumption have significant positive effects across all regions， although their impact is lower in high economic zones than in low economic zones. The proportion of tertiary industry significantly impacts carbon emission within only high economic zones， with both positive effects on low-carbon emission areas and negative effects on high-carbon emission areas. In the context of energy conservation and emission reduction performance， local governments should formulate policies tailored to their respective characteristics.

The high carbon emissions of vehicles traveling on horizontal curve road sections cannot be ignored. Facing the difficulty of accurately quantifying the carbon emission of driving on horizontal curves and the unknown causes of high carbon emission, this study proposes to construct a carbon emission prediction model applicable to road sections with different planar geometries. The direct and indirect effects of horizontal curve alignment on vehicle carbon emissions are represented in the model in terms of travel stabilization and speed changes, respectively. A lateral force coefficient parameter was introduced into the model to integrate the carbon emission quantification problem for different planar geometry sections. Meanwhile, field tests were conducted to assess the reliability of the model and the research findings. The model reveals that the geometric parameters of horizontal curves that affect carbon emissions are the radius of the circular curve, the superelevation, and the length of the gentle curve. The root causes of high carbon emissions on horizontal curve road sections are curve driving resistance and speed fluctuations. Under the free-flow driving condition of the highway, the maximum curve radius affecting the carbon emissions of passenger cars and trucks is 400 m and 550 m, respectively. The research results can realize the carbon emission quantification of vehicles on the road sections with different plane geometries. Also, it is helpful to control the high carbon emission of vehicles traveling on horizontal curve road sections.

In today's complex business landscape, robust corporate governance and financial compliance are essential for maintaining organizational integrity, accountability, and transparency. This review examines the key components and strategies necessary to enhance these frameworks, ensuring sustainable success and stakeholder trust. Corporate governance encompasses regulatory compliance, risk management, ethical conduct, and stakeholder engagement. Adherence to laws and regulations, such as the Sarbanes-Oxley Act (SOX) and the General Data Protection Regulation (GDPR), is foundational in minimizing legal risks and safeguarding reputation. Effective risk management involves identifying, assessing, and mitigating potential threats to an organization’s financial health and operational integrity through strong internal controls and regular audits. Promoting ethical conduct within organizations is crucial for maintaining trust and reputation. Establishing codes of conduct, ethical guidelines, and whistleblower protections fosters a culture of integrity. Transparent communication and stakeholder engagement ensure that organizational activities align with stakeholder interests and expectations. Enhancing accountability and transparency involves several key strategies. Strong board oversight and independence, characterized by diverse and skilled board members, ensure balanced and objective decision-making. Regular internal and external audits verify financial accuracy and compliance, identifying areas for improvement. Leveraging technology and data analytics is pivotal in modern compliance efforts. Technologies like blockchain, artificial intelligence (AI), and machine learning automate processes, improve accuracy, and provide real-time insights into financial performance and risk management. Transparent regulatory reporting and disclosure practices, adhering to standards such as the International Financial Reporting Standards (IFRS), further enhance stakeholder trust. Continuous training and education for employees and board members on corporate governance principles, regulatory requirements, and ethical standards are vital for fostering a culture of compliance and accountability. Strengthening corporate governance and financial compliance is fundamental for enhancing accountability and transparency. By adopting comprehensive regulatory frameworks, leveraging technology, and promoting ethical conduct, organizations can build trust, mitigate risks, and ensure sustainable growth in a dynamic business environment. Keywords: Corporate Governance, Global Corporations, Harmonization.