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.

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.

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 advent of air travel, originally proposed by the Wright brothers, has led to a significant surge in aircraft usage for human transportation. In its nascent stages, this mode of transport was linked with a high frequency of accidents and consequent fatalities, placing it in the high-risk category. To counter these risks, the International Civil Aviation Organization (ICAO) was established in 1947 as a collaborative effort among numerous countries with the primary goal of enhancing aviation safety regulations. This study analyzed archival data from the Bureau of Aircraft Accidents Archives (B3A), covering a span of 72 years from 1918, the year of the first commercial airplane crash, until 2020. The objective was to understand the ICAO's impact on altering accident rates, fatalities, and underlying causes. Analytical methodologies encompassed both descriptive statistics—examining data distribution, central tendencies, and category frequencies—and exploratory data analysis (EDA) to identify variable relationships and outlier identification. The results indicated that ICAO's interventions have led to a notable decline in accident rates, with an annual average reduction of 70.9%, and a corresponding decrease in incidents attributed to technical factors. However, an unexpected trend was the increase in fatalities despite the drop in accident numbers, attributable to the introduction of larger aircraft designs carrying more passengers per flight. The findings underscore the ICAO's successful efforts in reducing aircraft accidents, but also suggest a need for further exploration into factors contributing to the rise in fatalities.

Existing legal and by-law regulations prescribe risk management methodologies for various domains, such as the transportation of hazardous materials, fire and explosion protection, environmental protection, and protection against chemical accidents. However, there is a lack of comprehensive methodological guidance that unifies the management of all risks associated with the transportation of explosive remnants of war (ERW), which pose significant threats to human life, cultural assets, and the environment. Furthermore, the transportation of ERW often occurs along traffic corridors with compromised infrastructure, increasing the range of potential risks affecting the safety of people, their property, and critical infrastructure. This study presents an integrated risk management model for ERW transportation in the Republic of Serbia, developed based on current legal and by-law regulations, as well as modern criteria and risk assessment methodologies. By applying this model, the various risks associated with ERW transportation can be effectively mitigated, ensuring the safety and protection of people, assets, and the environment.

The continuous evolution of consumer behavior in the modern era of consumption has prompted enterprises to explore the underlying behavioral factors of consumers and cater to their particular needs. Moreover, developing a rational operational behavior model and responding effectively to the dynamic market environment have become critical concerns for businesses. This study examines the impact of consumer reference price effects and enterprise short-sighted behavior on strategic selection and performance, employing differential game theory to construct a game model between manufacturers and retailers. Utilizing Behrman's continuous dynamic programming theory, analytical solutions for various models are derived, followed by comparative analyses and numerical examples. The research reveals that: (1) manufacturers' behavior patterns are found to be dominant, favoring far-sighted behavior, which not only enhances profits but also enables consumers to access higher quality and cost-effective products; retailers should opt for collaboration with far-sighted manufacturers and exhibit a preference for short-sighted behavior. (2) In terms of overall system profit, the FM model emerges as the optimal combination. (3) When the reference price effect has a small impact on market demand, enterprises can make use of the reference price effect to actively promote marketing and gain profit; as the influence increases, intensifying the degree of influence effectively augments profits.

This study aims to identify efficient Information Technology (IT) candidates for a specific position and highlight areas for improvement using Data Envelopment Analysis (DEA). By streamlining the selection process and reducing costs, the findings can assist companies in making better-informed hiring decisions. Additionally, the results provide candidates with valuable feedback on areas for development, increasing their chances of securing employment in their desired company. The DEA model offers a unique advantage in this context by generating reference units for each candidate, enabling precise determination of the necessary changes in inputs or outputs for achieving efficiency. The Charnes, Cooper, and Rhodes (CCR) model served as the baseline, with parallel comparisons drawn against the Banker, Charnes, and Cooper (BCC) and categorical models to identify the most effective approach. The findings reveal the efficient candidates based on the assessed criteria, demonstrating that less experienced candidates can be evaluated as efficient compared to their more experienced counterparts. The hypothesis that the BCC model, with its more flexible efficiency frontier, results in poorer candidate differentiation was confirmed. This study highlights the value of adopting the DEA method in evaluating the employment efficiency of IT candidates, offering practical implications for both hiring organizations and job-seekers.