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Recently the use of biomass to provide energy in Zimbabwe is estimated at 66% of the total energy used in the country. There has been a strong movement to use biomass resources for energy purposes in the past decade. Zimbabwe's significant biomass resources are crops, animal excrement, refuse, and industrial waste materials. The study aims to determine the status and trends of biomass production in Zimbabwe between 2010 to 2019. The paper analyzes how biomass crops are grown and how they are utilized and how they present problems. This research was performed using a qualitative approach and is focused on secondary data obtained from various outlets, including journal papers, conference proceedings, government records, magazine articles searched through search engines. This study's findings disclose that a total of 711 biomass plants in the country by the end of 2017, such as local plants, institutional plants, and households plants 90%, 8%, 2%, respectively. In these plants, 1% used pig manure, 8% sewage, 1% cow dung, and other digested local sources, while 90% used cattle faeces. In meat production, 97% of the working biomass is used for cooking, while 1% is used in poultry. The study determines that bioenergy is not as common as other types of energy. Education and communication concerning the benefits of biomass technology promote its use.

The anti-corruption campaign and the Chinese dream -- Debating governance and the rule of law : China's narrative and images in Western countries -- Soft power and sharp power in the age of Noopolitik -- Methodology -- The framing of governance : the China model and the Chinese -- When "House of cards" meets "in the name of people" : framing China's anti-corruption campaign.

Good governance and anti-corruption efforts were expected to enhance soft power overseas. The party-state successfully governed China for decades relying on its controversial governance approaches. The country has visibly demonstrated economic and social development. However, China's growing influence has failed to be recognised as soft power, being viewed rather as sharp power most times. The monograph investigates whether China is mindful of exporting its political ideas and whether it considers its governance model to be the pillar of its soft power portfolio. Through framing analysis of media coverage and in-depth interviews with Australian public diplomacy experts, the monograph presents how Australia, a western country with close economic ties with China, interprets China's intended narrative regarding its governance model and development. Examining the congruity between China's projection and Australia's mediation sheds a new light on the relationship between domestic governance, soft power, and sharp power. By sketching out Beijing's ambitions and attempts, the monograph draws implications about China's public diplomacy and the future global order.

The recent research on citizen participation in the provision of public services represented by coproduction has become a hot topic in public management. Coproduction studies propose that citizens can directly or indirectly participate in the process of public services to help improve the quality and legitimacy of public services. Very little, however, has been written in the existing coproduction literature on the outcome of public services provision. Based on the "One-Hundred Villages" Survey in 2020, this article analyzes and evaluates the impact of coproduction on the perceived outcome of public service in rural China. A series of statistical analysis results show that both co-planning and co-delivery have significant and positive impacts on how one views the outcome of rural public service provision. This research provides new evidence in rural China that citizen participation plays a crucial role in the state-led "New Socialist Countryside" campaign.

This dissertation researchdesigned, implemented, and evaluated a Web-based Dynamic Voting Toolfor small group decision-making in a collaborative environment. In this dissertation, theliterature on voting tools in current GDSS research is presented. Variousvoting theories and methods are analyzed, and the advantages and weaknessesare compared, so as to gain a better understanding of how to apply thesedifferent voting methods to diverse decision-making situations. A briefoverview of scaling theories is also given, with an emphasis on Thurstone'sLaw. The basic features of someweb-based voting tool implementations are reviewed along with a discussionof the pros and cons of Intemet voting. A discussion of Human DynamicVoting (HDV) follows; HDV allows multiple voting and continuous feedbackin a group process. The Dynamic Voting Tool designed and developed bythe author (i.e., Zheng Li) integrated multiple scaling and voting methods,and supported dynamic voting. Its features, user feedback, and futureimprovements are further discussed. A controlled experiment wasconducted to evaluate the effects of the Dynamic Voting Tool (alongwith the List Gathering Tool by Yuanqiong Wang) interacting with smallgroup process. The design and procedures of the experiment, and thedata analysis results extracted from 187 student subjects from New JerseyInstitute of Technology are reported. While the System Survey yieldedvery positive feedback on the voting tool, the hypotheses tested bythe Post-Questionnaire and expert judgments showed no major positivesignificant results. This was probably due to the complexity of thetask and procedures, lack of motivation of the subjects, bad timing,insufficient training, and uneven distribution of subjects, etc. Several field studies usingthe Social Decision Support System (SDSS) Toolkit (List Gathering Tool+ Dynamic Voting Tool) are presented. The SDSS system worked well whenthe subjects were motivated. The field studies show that the toolkitcan be used in course evaluations, or other practical ...

In this paper, we introduce the causal forests method (Athey et al., 2019) and illustrate how to apply it in social sciences to addressing treatment effect heterogeneity. Compared with existing parametric methods such as the multiplicative interaction model and traditional semi-/non-parametric estimation, causal forests are more flexible for complex data generating processes. Specifically, causal forests allow for nonparametric estimation and inference on heterogeneous treatment effects in the presence of many moderators. To reveal its usefulness, we revisit existing studies in political science and economics. We uncover new information hidden by original estimation strategies while producing findings that are consistent with conventional methods. Through these replication efforts, we provide a step-by-step practice guide for applying causal forests in evaluating treatment effect heterogeneity.