Tax evasion, psychological egoism, and revenue collection performance: Evidence from Amhara region, Ethiopia.

Tax evasion is the illegal withholding or underpayment of taxes, typically accomplished by intentionally providing false or no evidence to tax authorities. Tax evasion has had a severe detrimental influence on the economy of the Amhara National Regional State, Ethiopia. The Amhara Regional State lost tax revenue in recent years due to tax evasion. The objective of this study was to see how tax evasion, taxpayers' psychological egoism, and other relevant factors affect tax revenue collection performance in the Amhara Region, Ethiopia. Data were collected from 395 VAT-registered taxpayers through a structured questionnaire. The structural equation model and multiple regression analysis method were utilized for empirical test based on the softwares of SPSS and AMOS. This research revealed that tax evasion and psychological egoism negatively affect tax revenue collection performance. Tax education and technology significantly and positively affected tax revenue collection performance. Meanwhile, the relationships between the above factors (tax evasion, tax education, and technology) and the tax revenue collection performance are reliably mediated by taxpayers' psychological egoism. Those findings can give clues to researchers, tax experts, and policymakers for improving the tax revenue collection performance in Amhara Region. The government can enhance public education to reduce tax evasion and such misbehavior caused by taxpayers' psychological egoism. Meanwhile, the most up-to-date tax invoicing technologies, like artificial intelligence and machine learning technology should be adopted.

Industrial Coagglomeration, Green Innovation, and Manufacturing Carbon Emissions: Coagglomeration's Dynamic Evolution Perspective.

The achievement of China's low-carbon development and carbon neutrality depends heavily on the decrease of manufacturing carbon emissions. From coagglomeration's dynamic evolution perspective, by using panel-threshold-STIRPAT and mediation-STIRPAT models, this study examines the relationships among industrial coagglomeration, green innovation, and manufacturing carbon emissions and explores the direct and indirect function mechanisms. Panel data of China's 30 provinces from 2010 to 2019 are employed. The results imply that, first, the impact of industrial coagglomeration on manufacturing carbon emissions is nonlinear and has significant threshold effects. Industrial coagglomeration negatively affects manufacturing carbon emissions, and as the coagglomeration level deepens, the negative effect has a diminishing trend in marginal utility. Once the coagglomeration degree exceeds a certain threshold, the negative impact becomes insignificant. At present, for 90% of China's regions, an increase in industrial coagglomeration level can help reduce manufacturing carbon emissions. Second, green innovation is a vital intermediary between industrial coagglomeration and manufacturing carbon emissions. It is a partial intermediary when industrial coagglomeration is at a relatively lower-level stage and a complete intermediary when industrial coagglomeration is at a relatively higher-level stage. These findings reveal the significance of optimizing industrial coagglomeration and the level and efficiency of green innovation to decrease carbon emissions.

Digital economy, energy efficiency, and carbon emissions: Evidence from provincial panel data in China.

Improving energy efficiency and lowering carbon emissions are of great importance to realize the "dual carbon" goal of carbon peak and carbon neutrality. Digital economy is a new engine of economic development, but whether or how it affects energy efficiency and carbon emissions are unclear. Utilizing panel data of China's 30 provinces from 2012 to 2019, this study empirically explores the relationships among digital economy, energy efficiency, and carbon emissions. Meanwhile, from the perspective of energy efficiency, applying mediation models and panel threshold model, it analyzes the direct, indirect, and nonlinear influencing mechanisms of digital economy on carbon emissions. The results reflect that the development of digital economy in China intensifies carbon emissions. Energy efficiency serves as a vital partial mediator between the two. The enhancement of energy efficiency can lower carbon emissions. However, the development of digital economy is not conducive to improving energy efficiency, thereby, indirectly increasing carbon emissions. The mediating effect of energy efficiency accounts for 30.58 % of the total effect of digital economy on carbon emissions. Meanwhile, taking energy efficiency into account, the impact of digital economy on carbon emissions has a significant double-threshold effect and presents an N-shaped trend. [0.824, 0.912] is the optimal range of energy efficiency, within which the growth of the digital economy can empower carbon emission abatement to some extent. In addition, the expansion of population size, the coal-based energy consumption structure, and the industrial structure significantly increase carbon emissions. The improvements in living standards and environmental regulations can help to decrease carbon emissions, but the emission abatement effects are not significant. Those conclusions reveal the importance of optimizing the level and quality of digital economy and adopting differentiated digital economy development policies based on energy efficiency to achieve carbon emission reduction.

You Have Received More Help than I Did and I Envy You: A Social Comparison Perspective on Receiving Help in the Team.

In the current research, we developed and tested a model of how and when upward social comparison of received help influenced an employee's interpersonal citizenship behavior. Based on social comparison theory, we posited that upward social comparison of received help triggered an employee's feelings of envy, which in turn had a negative relationship with interpersonal citizenship behavior (ICB). Further, we argued that the effects of upward social comparison of received help on envy differed in the employee's social comparison orientation. Using data collected in three waves from 411 employees in China, we found that upward social comparison of received help was positively associated with the employee's feelings of envy while controlling for overall receiving help, which further negatively affected interpersonal citizenship behavior. Moreover, the relationship between the upward social comparison of received help and the employee's feelings of envy was stronger when employees had high levels of social comparison orientation and further strengthened the indirect relationship between the upward social comparison of received help and the employee's ICB via envy. Overall, these findings have the potential to extend our knowledge of the adverse effects of receiving help in a team by introducing a social comparison perspective.

Feeling Gratitude and Depletion: The Ambivalent Consequences of Receiving Help in the Workplace.

Drawing from social exchange theory, we developed a dual-path model of employees' reactions to episodic help received from colleagues. Through a diary study, using data collected from 127 full-time employees working in a large Chinese bank, we tested this model, revealing that receiving episodic help from colleagues is positively related to the help receivers' gratitude and ego depletion. Through these two ambivalent psychological states, help receivers were found to simultaneously engage in more organizational citizenship behaviors and deviance behaviors on a daily basis. These empirical findings contribute to research that adopts a target-centric perspective in examining the consequences of helping behavior in the workplace.