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This study aims to examine the effect of foreign direct investment (FDI) inflows on tax revenue in 34 developed and developing countries from 2006 to 2020.

Feasible generalised least squares (FGLS), a dynamic panel of a two-step system generalised method of moments (GMM) system and a pool mean group (PMG) panel autoregressive distributed lag (ARDL) approach were used to compare the developed and developing countries. Basic estimators were used as pre-estimators and diagnostic tests were used to increase robustness.

The FGLS, a two-step system of GMM, PMG–ARDL estimator’s results showed that there was a significant negative long and positive short-term in most countries relationship between FDI inflows and tax revenue in developed countries. This study concluded that attracting investments can improve the quality of institutions despite high tax rates, leading to low tax revenue. Meanwhile, there was a significant positive long and negative short-term relationship between FDI inflows and tax revenue in the developing countries. The developing countries sought to attract FDI that could be used to create job opportunities and transfer technology to simultaneously develop infrastructure and impose a tax policy that would achieve high tax revenue.

The present study sheds light on the effect of FDI on tax revenue and compares developed and developing countries through the design and implementation of policies to create jobs, transfer technology and attain economic growth in order to assure foreign investors that they would gain continuous high profits from their investments.

This study examines the impact of university science parks’ (USPs) capabilities on revenue generation and introduces regional innovation as a moderating variable. This study aims to provide insights into enhancing revenue generation and fully leveraging the role of USPs in promoting revenue generation.

This study employs system generalized method of moments (GMM) estimation for 116 universities in China from 2008 to 2020, using hierarchical regression analysis to examine the relationships between variables.

The findings suggest that USPs play a beneficial role in fostering revenue generation. Specifically, the provision of incubation funding demonstrates a positive correlation, while USPs size exhibits an inverted U-shaped pattern, with a threshold at 3.037 and a mean value of 3.712, highlighting the prevalent issue of suboptimal personnel allocation in the majority of USPs. Moreover, the analysis underscores the critical moderating influence of regional innovation, affecting the intricate interplay between USPs size, incubation funding and revenue generation.

The single country (China) analysis relied solely on the use of secondary data. Future studies could expand the scope to include other countries and employ primary data collection. For instance, future research can further examine how regional development and USPs strategic plan impact revenue generation.

The study recommends that USPs managers and policymakers recognize the importance of incubation funding and determine the optimal quantity of USPs size to effectively foster revenue generation in USPs. Policymakers can use regional innovation as a moderating variable to reinforce the relationship between USPs size and incubation funding on revenue generation.

The study’s findings can contribute to the strategic industry growth and economic development of nations by promoting revenue generation. Leveraging the role of USPs and implementing the study’s recommendations can strengthen innovation and technology capabilities, driving strategic industry growth and economic development. This can enhance global competitiveness and promote sustainable economic growth.

This study introduces regional innovation as a moderating variable and provides empirical evidence of its influence on the relationship between USPs size and incubation funding on revenue generation. This adds value to research to the existing literature on USPs and revenue generation by showcasing the importance of examining the regional impact in research and innovation.

This study aims to investigate earnings management practice of classification shifting of revenues in Chinese-listed firms.

The study employs a dataset of 2,920 A-listed firms from Chinese stock exchanges of Shanghai and Shenzhen for the period of 2003–2019. We apply both univariate and panel regression analysis by using fixed effect estimation with robust standard errors.

Our findings reveal that firms misclassify revenues by taking advantage of the flexibility provided by applicable financial reporting standards. The empirical evidence obtained through regression analysis suggest that managers reclassify non-operating revenues as operating revenue to alter the economic reality while seeking the advantage of financial reports users’ vulnerability for valuing the upper half of income statement items more as compared to lower part. The results further indicate that international financial reporting standards adoption inhibits the earnings management practices using classification shifting of revenues. It is also concluded that firms, which are suffering losses or having low growth, are more persistently involved in misclassification of revenues.

The study is unique from the point of view that it investigates earnings management from the prospective of revenue’s classification in an emerging market characterized by various market imperfections such as lower investor protection and higher information asymmetry.

This paper examines the short- and long-run effects of foreign direct investment (FDI) on tax revenue in Ghana.

The paper adopts the autoregressive distributed lag approach to estimate FDI’s long-run and short-run effects on tax revenue. The study uses time-series data from 1983 to 2019 for Ghana, mainly obtained from The Bank of Ghana, the World Bank and the IMF.

The results show that, in the short-run, FDI has no significant effect on direct tax revenue and total tax revenue but significantly hurts indirect tax revenue. In the long run, however, the results show that FDI has significant positive effects on indirect tax revenue and total tax revenue but no significant effect on direct tax revenue.

Empirical studies often fail to analyse the short-run and long-run effects of FDI on tax revenue. This study contributes to the mixed literature by analysing the short-run and long-run effects of FDI on tax revenue in an emerging market context. Additionally, this study employs three tax revenue measures in analysing the nexus.

Inflation and federal monetary efforts to control it with interest rate hikes have very real and overwhelmingly negative consequences on US local governments following the onset of COVID-19. This study explores the post-pandemic inflationary environment of US local governments; examines the impacts of inflation and high interest rates on local government revenue, operating costs, capital costs, and debt service; reviews local government inflation management strategies, including the use of intergovernmental revenue; and assesses ongoing threats to local government financial health and financial resilience.

This study uses trend and literature analysis to comment on current issues local governments face.

The study finds that the growth of property values and resulting stability of property tax revenue has been important to local government revenues; that local governments bear very real burdens as operating and capital costs increase; and that the combination of high inflation and interest rates affects local government debt issuance by negatively affecting credit quality and interest costs, leading to municipal market contraction. Local governments have benefitted tremendously from intergovernmental revenue, but would be ill-advised to rely on it.

Vulnerabilities owing from revenue mismatch with the economy; inadequate affordable housing, inequality, and social issues; a changing workforce and tight labor market; climate change; and federal fiscal contraction—all of which are exacerbated by high inflation and interest rates—require local governments to act strategically, boldly and collaboratively to achieve fiscal health and financial resilience, and to realize positive returns of investments in people and capital.

This work is unique in addressing the post-pandemic impact of inflation and interest rates on local governments.

The environmental characteristics of international football can vary significantly from one country to another. As a result, the economic and market possibilities and the objectives of each national league are very heterogeneous. This article aims to examine the differences in revenue structures amongst European national football leagues (n = 50) and cluster them based on these structures. It also investigates which revenue structure would be more effective for similar leagues, considering the previously mentioned varying environmental characteristics of international football.

The study utilises a theoretical framework of business modelling, applied in a unique way to league organisers of national championships. Data on sports and business aspects were collected from sources such as the Union of European Football Associations (UEFA) Financial Benchmarking Reports, transfermarkt.de and related sources for the period 2015 to 2018. K-means cluster analysis, using the Euclidean distance approach, was employed to develop clusters based on revenue sources over a four-year average.

The paper presents the characteristics and year-to-year changes of nine developed clusters. Throughout the analysis, variables such as average overpayment and inequality between player values amongst leagues were prioritised. The study's practical implications can assist league organisers in enhancing the competitiveness of their leagues, supported by short case studies that provide illustrative examples.

The novelty of the current article lies in introducing innovative variables such as the variance of player value whilst focussing on meso-level analysis, providing a fresh contribution to the existing literature in the field for understanding revenue structures and performance in European national football leagues.

This case uses an array of carefully selected and excerpted revenue recognition related information contained in Salesforce.com's January 31, 2019, 10-K. Maria, the fictional protagonist, is seeking to understand those disclosures as part of her preparation for an upcoming job interview with the company. As such, she is relying on those disclosures to provide insights as to the company's main product/service lines, the events that signal when and how much revenue the company has earned (i.e., the essence of its business model), along with the related official generally accepted accounting principles (GAAP) criteria pertinent to the valuing and timing of recorded revenues.

To study these issues, the authors chose a GFSC with one producer and one material supplier as research object, the supplier will offer green material to the producer and the producer will make green food using green production technology. Then, the authors proposed that consumers' perceived value was determined by the trustworthiness levels of the related green and quality-safety information provided by the supplier and the producer. Then, considering the trustworthiness levels of the green and quality information provided by the supplier and the producer, the authors improved the demand function. Afterwards, we constructed four investment models and their income models are built and then a cost-sharing and revenue-sharing contract (hereafter, CSRS) was adopted to coordinate the GFSC.

With the growth of consumers environmental awareness and life level, consumers' requirements for green and high quality food are growing. In recently years, to increase consumers' perceived trustworthiness on the product greenness and quality levels, stakeholders in green food supply chain (hereafter, GFSC) start to adopt the blockchain-based traceability system (hereafter, BLTS). For investors, they need to know the investment conditions and how to coordinate the GFSC.

(1) When the revenue-sharing coefficient is less than three-fourths and higher then a certain vaule, the cost-sharing and revenue-sharing contract can make the GFSC coordinate. (2) The investment cost threshold of the BLTS has a positive relationship with the trustworthiness improvement levels of the green and quality information, the green degree of food products and the quality of food products. (3) In the proposed four investment situations, as the growth of consumers perceived credibility coefficient about the greenness information and the quality information, chain members' revenues will increase. In addition, comparing with co-investing the BLTS, benefits of chain members are lower than them in the sole investment model.

(1) The demand function we proposed can help chain members forecast market demand to support production or ordering decisions. (2) The investment decision policies can offer a theoretical reference for chain members to use the BLTS. (3) The CSRS will offer the theoretical reference for coordinating the supply chain after using the BLTS. Furthermore, our study method can be referenced by other scholars. (4) The study method can offer a method reference for researchers who do a similar discussion in a manufacturing supply chain. Although, our research cannot guide the industrial practices, it can serve as a reference of the similar research in industry.

The study aims at examining the relationship between the forms of misclassification practices, namely expense shifting and revenue shifting. In particular, the study aims at identifying the form of shifting that has been preferred by firms to meet the industry average profitability.

Core earnings and operating revenue expectation models are used to measure expense shifting and revenue shifting, respectively. The panel fixed-effects models are used to control for unobserved heterogeneity across industries and time.

Based on a sample of Bombay Stock Exchange-listed firms, the author finds that firms prefer expense shifting over revenue shifting to meet industry average profitability, implying that firms choose the shifting tool based on the relative advantage. Further, the findings deduced from the empirical results demonstrate that firm life cycle and mandatory adoption of International Financial Reporting Standards (IFRS) moderates the relationship between shifting forms and industry average profitability. However, the negative impact of IFRS on shifting practices is found to be less pronounced among BigN audit firms.

The study is among the pioneering attempt to document the substitution relationship between shifting forms. It is the first study that examines a form of classification shifting, where gross profit and core earnings both change as an effect of misclassification.

It is important to consider economic and political factors when designing the tax mix and setting the level of corporate taxation. Increasing corporate taxation can be seen as an inefficient way to raise revenue for the state, as it can have a negative impact on investment and the competitiveness of firms. However, lowering corporate taxation can encourage investment and job creation, but it can also be perceived as supporting large corporations. The aim of this chapter is to evaluate corporate taxation, its position in the tax mix and its potential impact on economic growth. The revenues of corporate income tax (CIT) have an increasing tendency even though the tax rate was reduced from 41% to 19%. Revenues are influenced by both legislative changes and economic cycles. The level of taxation is also influenced by deductions, which include asset depreciations, research and development expenses, or loss deductions. The Pearson Correlation Coefficient was used to examine the correlation between the selected factors. A moderately strong positive correlation was found between GDP growth and CIT as a percentage of total taxes, as well as between GDP growth and CIT as a percentage of GDP.