This study investigates the impact of corporate carbon performance on financing costs, focusing on S&P 500 companies from 2015 to 2022. Utilizing a fixed-effects regression model, the research reveals a complex U-shaped nonlinear relationship between carbon intensity (CI) and cost of debt (COD). The sample comprises 2896 firm-year observations, with CI measured by the ratio of Scope 1 and 2 greenhouse gas (GHG) emissions to annual sales. The findings indicate that companies with higher CI initially face increased COD due to heightened regulatory and operational risks. However, as CI falls below a certain threshold, further reductions in emissions can paradoxically lead to increased COD, likely due to the substantial investments required for advanced technologies. Additionally, a positive relationship between CI and cost of equity (COE) is observed, suggesting that shareholders demand higher returns from companies with greater environmental risks. These results underscore the importance of balancing short-term and long-term environmental strategies. The study highlights the need for corporate managers to communicate the long-term benefits of environmental efforts effectively to creditors and investors. Policymakers should consider these dynamics when designing regulations that incentivize lower carbon emissions.

This study examines the factors influencing e-government adoption in the Tangerang city government from 2010 to 2022. We gathered statistics from multiple sources to reduce joint source prejudice, resulting in a preliminary illustration of 1670 annotations from 333 regions or cities. These regions included major urban centers such as Jakarta, Surabaya, Bandung, Medan, Makassar, and Denpasar, as well as other significant municipalities across Indonesia. After removing anomalous values, we retained a final illustration of 1656 annotations. Results indicate that higher-quality digital infrastructure significantly boosts e-government adoption, underscoring the necessity for resilient digital platforms. Contrary to expectations, increased budget allocation for digital initiatives negatively correlates with adoption levels, suggesting the need for efficient spending policies. IT training for staff showed mixed results, highlighting the importance of identifying optimal training environments. The study also finds that policy adaptability and organizational complexity moderate the relationships between digital infrastructure, budget, IT training, and e-government adoption. These findings emphasize the importance of a holistic approach integrating technological, organizational, and policy aspects to enhance e-government implementation. The insights provided are valuable for policymakers and practitioners aiming to improve digital governance and service delivery. This study reveals the unexpected negative correlation between budget allocation and e-government adoption and introduces policy adaptability and organizational complexity as critical moderating factors, offering new insights for optimizing digital governance.

This study investigated the utilization of Artificial Intelligence (AI) in the Recruitment and Selection Process and its effect on the Efficiency of Human Resource Management (HRM) and on the Effectiveness of Organizational Development (OD) in Jordanian commercial banks. The research aimed to provide solutions to reduce the cost, time, and effort spent in the process of HRM and to increase OD Effectiveness. The research model was developed based on comprehensive review of existing literature on the subject. The population of this study comprised HR Managers and Employees across all commercial banks in Jordan, and a census method was employed to gather 177 responses. Data analysis was conducted using Amos and SPSS software packages. The findings show a statistically significant positive impact of AI adoption in the Recruitment and Selection Process on HR Efficiency, which in turn positively impacted OD Effectiveness. Additionally, the study indicated that the ease-of-use of AI technologies played a positive moderating role in the relationship between the Recruitment and Selection Process through AI and HR Efficiency. This study concludes that implementing AI tools in Recruitment is vital through improving HR Efficiency and Organization Effectiveness.

This paper provides a unique empirical analysis of the effects of political factors on the adoption of PPP contracts in Brazil. As such, it innovates along two different lines: first, political factors behind the adoption of PPPs have been largely ignored in the vast body of empirical literature, and second, there is scant work done on the motives of any kind behind the adoption of PPPs in Brazil. Various economic and financial reasons have been evoked to justify the use of PPPs in general. These include the goal of promoting socio-economic development in a tight public budgetary framework or of improving the quality of public services through the use of economically efficient and cost-effective mechanisms. Any possible underlying political motives, however, have been overlooked in the PPP research. And yet, there is abundant literature suggesting a link between the adoption of PPPs and the ideology of the governing body or the political cycles associated with elections. This study examines the impact of ideological commitment and opportunistic political behavior on the process of PPP contracting in Brazil, including the stages of public consultation, the publication of tender, and the signature of the contract, using federative-level data for the period between 2005 and 2022. Consistent with the outstanding literature, the two hypotheses are tested: first, conservative parties tend to celebrate more PPP contracts than left-leaning parties, and second, the electoral calendar has a significant effect in the process, allowing for opportunistic behaviors. Empirical results suggest that there is little evidence for the relevance of ideological leanings in the process of adopting PPPs in Brazil. Additionally, regardless of ideology, parties significantly choose to enter PPPs at specific points in the electoral cycle, suggesting decisions are influenced by political considerations and electoral strategy rather than by purely financial or ideological considerations. This may pose severe constraints on the efficiency and cost-effectiveness of the contracts, negatively impacting public governance and leading to protracted costs for taxpayers.

Research in the field of online advertising has focused on the effect of in-stream ads on viewers’ attitudes and intentions to purchase. However, little is known regarding the crucial role of viewer’s control in terms of the ‘skip ad option’ towards the attitude to purchase. This research aims to investigate the effect of in-stream ads on viewers’ attitudes to purchasing with the moderating role of viewer control. Primary data was collected from respondents of Vehari district of Pakistan through a questionnaire based on 5 points Likert scale. 370 questionnaires were incorporated after excluding the questionnaires having missing values. Structural equation modelling was used through SmartPLS-3 software in testing the hypotheses. The findings reveal that, in-stream (emotional, informational, and entertaining) ads have positive impact on viewers’ attitudes, and viewers’ control moderates the relationship between in-stream ads and viewers’ attitudes towards the ads. Further, viewers’ attitude toward the ads has a significant positive impact on viewers’ intention to purchase. To the best of our knowledge this is one of the first studies that examines the effect of in-stream ads on viewers’ attitudes to purchasing with the moderating role of viewer control in the context of a developing country, like Pakistan.

With the continuous development of network has also greatly developed, exploring the role of social network relationships and attachment emotions on consumer intention helps community managers to promote community purchases for more consumer. As another core component of social e-commerce, social media influencer also has a significant influence on consumer intention. This study systematically analyzed the effects of social network relationships and social media influencer characteristics on consumer purchase intentions. Introduced consumer attachment and perceived value as mediating variables to construct the research framework of this study. This article adopts quantitative analysis methods to test the research hypotheses proposed. This article collected 600 first-hand data in the form of a survey questionnaire and analyzed the data using AMOS and SPSS statistical software. The empirical analysis in this article confirms that social network relationships has a significant impact on consumer purchase intentions; social media influencer characteristics has a significant impact on consumer purchase intentions; consumer attachment has a significant impact on perceived value;  consumer attachment plays a mediating role in the effect of social network relationships on consumers purchase intentions; perceived value plays no mediating role in the effect of social media influencer characteristics on consumer purchase intentions; perceived value plays a mediating role in the effect of consumer attachment on consumer purchase intentions; consumer attachment and perceived value have a chain mediating role between social network relationships and consumer purchase intentions.