Goodwill impairment, resulting from the impairment tests conducted on goodwill generated during business mergers, serves as an effective indicator of a company's true and reliable goodwill value, as well as its operational and financial conditions. This study investigates the impact of earnings management motivations on goodwill impairment from the perspective of corporate governance, focusing on Chinese manufacturing listed companies between 2016 and 2020. Utilizing regression analysis and panel data models, the study examines the internal governance mechanisms, including the combined shareholding ratio of the top ten shareholders, and the external governance mechanisms, such as the role of the four major auditing firms. The findings reveal that both "big bath" and earnings smoothing motives can influence companies' decisions to recognize goodwill impairment, while effective internal and external governance mechanisms can help mitigate earnings management motivations. Further analysis shows that non-state-owned manufacturing listed companies are more likely to exhibit goodwill impairment behaviors driven by earnings management motives. These findings provide valuable insights for listed companies seeking to improve their corporate governance structures and for Chinese capital market regulators aiming to enhance relevant regulatory policies and refine goodwill measurement standards.

The process of decision-making involves selecting the most suitable management action from a range of options, thereby guiding the system towards its management objectives. Within the complex decision-making environment, uncertainty prevails, giving rise to the domain of risk. Effective risk management entails various activities that are implemented during distinct phases of system management. To address this, a systemic approach to risk management is crucial, along with the adoption of software solutions for risk analysis. This study examines the systemic approach to risk management and proposes a potential solution for managing uncertainties and risks by employing software tools that are rooted in system quality. System quality encompasses the development of novel models, methods, tools, and procedures, whose consistent application ensures reliable outcomes based on the best available information. Consequently, this study explores the application of innovative software solutions that support the risk management process across all phases. Given that risk management relies on data, which may not offer a comprehensive view of the environment, decision-making can be regarded as a process of managing the conversion of data into information. The acquisition of new information regarding the system's state determines the approach to modify the system through the chosen decision. Information serves as the essence of the decision-making process, as quality information facilitates quality decisions. However, in an information space characterized by incomplete data, the quality of decisions diminishes. Software solutions capable of providing the necessary level of information quality, despite uncertainties and incompleteness, enable decision-making based on partial information while upholding a minimum standard of quality.

In recent years, a surge in studies concerning indigenous knowledge (IK) has been observed, yet a clear definition of IK remains elusive. Discrepancies in international studies lead to fluid interpretations of the concept. The present study seeks to delineate the key elements characterizing knowledge as either indigenous or foreign to a specific community. Through a meticulous exploration of definitions surrounding indigenous knowledge, it is posited that all knowledge forms can be considered indigenous within the communities of their origination. To elucidate this argument, the impact of community demographics on the adoption of knowledge perceived as indigenous within the Chief Albert Luthuli Municipality was investigated. Data were collected using structured interviews, involving a total of 398 respondents. Analyses were conducted employing a mixed-method approach, utilizing Microsoft Excel and the Statistical Package for Social Sciences (SPSS). Findings revealed a significant relationship between variables such as commonly spoken language, cultural attributes, age, and employment level with IK practices within communities. Furthermore, the economic factors, including employment status, education levels, and household income, were examined for their association with the adoption of IK practices. It was discerned that such variables were correlated with the adoption of IK practices, especially as alternative strategies in the absence of consistent household income. Key determinants like the language proficiency of the household head, employment status, educational attainment, family size, household income level, age, and gender of the household heads were analyzed. The influence of these determinants on household adoption of indigenous practices was assessed using inferential statistical methods, specifically probability and regression analysis.