This study aimed to review and analyze corporate entrepreneurship (CE) within family businesses and small and medium enterprises (SMEs), providing a review of the current state of research and suggesting a future research agenda. In a systematic literature review, 1040 articles indexed in Scopus were initially subjected to bibliometric and qualitative analysis. Finally, 53 papers published in various academic journals, focusing on corporate entrepreneurship, family businesses, and SMEs, were subjected to bibliometric analysis and qualitative research to identify the new potential state of the art in corporate entrepreneurship. CE in family businesses and SMEs is not a general research trend in the entrepreneurial area. This research shows that the literature on CE models and tools in family businesses and SMEs is still sparse. The review results correlate the actors of CE, behavior, and activities, including entrepreneurial orientation, entrepreneurial management, and entrepreneurial leadership and performance, as outcomes in family business and SMEs.

The purpose of this research was to apply exploratory data analysis techniques to building energy meters, such as electricity, cold, heat, and steam meters. A thorough understanding of energy usage patterns becomes increasingly vital in an era of growing awareness of energy management and sustainability. Trends, patterns, and anomalies can be identified in building energy meter data using meticulous data exploration approaches, which can give significant insights for increasing energy efficiency. Exploratory data analysis combined with machine learning approaches may be was used to reveal hidden patterns of energy usage and examine the links between relevant factors. The findings of this exploratory data analysis gave vital insights into building energy use trends. Some significant and hidden information that was crucial for understanding energy usage within a certain time frame in each building was discovered via the investigation of the data used in this study. Steam had the highest use, whereas electricity had the lowest. Utilities were more popular before 5 a.m., followed by healthcare, with daytime use hours beginning around 10 a.m., depending on the area. During the working day, the industry needs more energy. Places of worships use more energy on weekends. There was a significant relation between the number of floors and spaces per level of a building and the height meter reading between May and October. There is a significant association between the kind of buildings used for schools, workplaces and high energy use. This study significantly contributed to the management of the energy and sustainability domains. Using exploratory data analysis and machine learning approaches to building energy meters could optimize energy usage, minimize running costs, and enhance overall energy efficiency. This research is still very open to be continued using other methods, to obtain other hidden information.

Information about a product's shelf life is essential for the food industry to ensure the safety and quality of the product. Process development is needed if the product's shelf life is short-lived. This study aimed to increase the shelf life of ginger latte with sterilization at 121oC temperature using an autoclave for 10, 15, and 20 minutes then being hot filled at 90oC. Product sterilized in aluminum foil pouch then transferred to PET plastic bottles with hot fill method. Beforehand, the product characteristics were tested on the organoleptic test, pH, and total dissolved solids before being treated with sterilization and hot fill. The Arrhenius method was used to calculate product shelf life with sensory, pH, and total dissolved solids as parameters. The product shelf life before sterilization and hot filling were 18 days in storage at 10oC. Based on the calculation using the ASLT method Arrhenius model, the product shelf life was 35 days with sterilization at 121oC in 25oC storage temperature. The pH and total dissolved solids on day 28 after sterilization were recorded at 5.33 and 14.5 oBrix for 15 minutes, respectively, and 5.83 and 14.9oBrix for 10 minutes of sterilization, respectively. Keywords: accelerated shelf life study (ASLT), ginger latte, sterilization, shelf life

The Indonesia Government has implemented the mandatory B30 program or mixing 30% biodiesel with 70% diesel oil since January 2020, and it has become one of the priority programs to reduce emissions and dependency on fossil fuels. Researchers have reported that the use of biodiesel has an impact on engine filter clogging and fuel performance. This problem can be overcome by bio-additives addition. Several researchers also reported that essential oils can function as fuel bio-additives. This study aimed to identify B30 performance with and without the addition of bio-additives during engine durability and field tests. In this study, the bio-additives used were formulations of a mixture of essential oils (turpentine, rhodinol, and clove terpenes). B30 with a mixture of essential oil-based bio-additive formulas was applied directly to the diesel engine, and then analysis was carried out in the form of engine RPM, fuel consumption, filter pressure difference, and smoke emission before and after the durability test. The durability test results for up to 100 hours showed that the values for RPM and power of the engine, fuel consumption, filter pressure differences, and smoke emissions tended to be the same or identical to the values at the beginning phase of the measurement. Field test results showed that the addition of bio-additives can reduce particulate levels in the main tank by up to 60% after 4 days of use, and the same result was obtained in the measurement of water content. The fuel filter with the addition of bio-additives was cleaner than without the addition of bio-additives. The use of bio-additives improves the B30 and still comply with the technical specifications required by the Directorate General of Oil and Gas, Indonesia.

The nationwide implementation of B35 biodiesel in Indonesia is constrained by elevated water and particulate contents, which accelerate fuel degradation and promote filter clogging. Mitigating these issues is essential to ensure fuel quality, safe distribution, and stable engine operation. This study proposes a renewable essential-oil-derived bioadditive as an alternative to petroleum-based additives, with novelty arising from a fractionation-guided multi-essential-oil formulation and its comprehensive validation, encompassing molecular characterization, fuel-quality compliance, engine performance, and exhaust emissions. The objective of this study was to develop and validate an essential-oil bioadditive capable of (i) reducing water and particulate contents in B35 biodiesel in compliance with Indonesian fuel standards and (ii) evaluating its effects on engine performance and emissions. Turpentine, clove terpene, citronella, and rhodinol oils were characterized by GC–MS and fractionated to obtain α-pinene-, caryophyllene-, and rhodinol-rich fractions. Eight formulations were prepared by varying oil ratios and blended into B35 at 0.1% v/v. Water content was monitored over 7 days of storage, followed by flash point screening. The optimal formulation was further evaluated for particulate content, physicochemical properties, engine performance using a dynotest, and exhaust emissions on a Kubota D722 diesel engine. Among all formulations, D1 (turpentine:clove terpene:citronella = 1:8:1) exhibited the most balanced performance. D1 reduced water content to 320 mg/kg, meeting the ≤400 mg/kg limit, and increased the flash point to 75 °C (minimum requirement: 52 °C). Particulate levels across 4, 6, and 14 μm fractions were substantially reduced. The B35 + D1 blend satisfied key fuel specifications, including a cetane number of 54.7, viscosity of 3.171 mm²/s, and oxidation stability exceeding 35 h. Engine testing showed more stable torque and power at high speeds with D1 at 1% v/v compared with 0.1% v/v. Smoke emissions decreased markedly, while NOx emissions increased, indicating a combustion trade-off typical of oxygenated additives.