Human resource management is essential to the success of the organization based on the concept that an organization achieves a competitive edge by effectively and efficiently utilizing its people. However, HR professionals require organizational support to increase employee commitment and passion for their work. In this study, the goal of the study is to explore the moderating impact of government support in the relation between electronic human management (E-HRM), digital orientation, and performance of medium enterprises. To examine the relationships, the researcher collected data from 309 managers from Amman's medium-sized businesses via a survey questionnaire. Partial least squares-structural equation modelling (PLS-SEM) is used in statistical analysis to evaluate the data as well as test hypotheses. The data showed that E-HRM and digital orientation have a good and substantial impact on ME performance. Furthermore, government support has a positive and significantly moderating effect between digital orientation and ME performance. On the other hand, government support has insignificant moderating influence on E-HRM and ME performance. This research extends to the literature on digital services and electronic human resource management practices in the sector of local medium enterprises. This research also discusses the implications and the future directions. One of these is that the study framework gives guidelines to HR practitioners on what competences they should focus on to improve in digital and electronic human resource management. According to the results of this research, HR professionals in medium-sized businesses should be involved in digital services, strategy planning and implementation in their organizations.

The construction of smart villages has begun in many Indonesian villages, along with the advancement of technology and local economic growth. Villagers must participate in constructing the smart economy-smart village by becoming familiar with the characteristics of the village's inhabitants using the citizen science model. This study intends to categorize villagers so that researchers can assess and decide their level of readiness for a smart economy in an ecosystem based on a smart village. Clustering is required to find communities of residents who are ready based on their traits. Using fuzzy C-Means with a Davied Bouldin Index value of 0.129, the data were divided into 4 clusters. The most important variables were chosen using information from the test's 300 responders, and the Kaiser Mayer Olkin assumption of 0.975 was used to validate the results. Our paper provides new information on how smart village readiness is assessed by the citizen science cluster. It was decided to divide residents into four groups: those who are less prepared (24.33%), those who are somewhat prepared (29.33%), those who are ready ( 25.67%) %), those who are ready (level of participatory knowledge), and those who are very ready for the smart economy (20.67%) based on the cluster model.

Parabens are chemicals that are frequently used as preservatives in numerous cosmetic products. In recent years, the safety concern over these compounds has grown due to their endocrine-disrupting activity. In this research, a novel green magnetic molecularly imprinted polymer (GMMIP) was synthesised using propylparaben as a template and then applied as an adsorbent to selectively recognise and remove parabens from cosmetic samples. The green strategies were introduced by using Persicaria odorata or Kesum leaf extract as a reducing agent to synthesise green magnetic nanoparticles (MNP) as a magnetic core, and deep eutectic solvent (DES) has been designed as an environmentally friendly functional monomer that was used in the preparation of GMMIP. The GMMIP was characterised using Fourier transform infrared spectroscopy (FTIR), field emission scanning electron microscopy (FESEM), and Brunauer-Emmett-Teller (BET). The results of FESEM and BET indicated that the GMMIP exhibited an irregular spherical shape and mesoporous characteristics with a pore size of 17.74 nm. The adsorption pH, kinetics, isotherms, and thermodynamics parameters were performed to investigate the interactions that take place between GMMIP and propylparaben. The adsorption processes appeared to best fit the pseudo-second-order kinetic and Freundlich isotherm models at an optimum pH of 12. Findings from a thermodynamics study revealed the adsorption process was exothermic, spontaneous, and more favourable at 298 K. The optimised GMMIP was applied as an adsorbent to remove the parabens from cosmetic samples. When compared to methylparaben and ethylparaben, the GMMIP had the highest selectivity and effectively removed propylparaben, with recoveries ranging from 75.6% to 113.3%. It was found that the limits of detection (LOD) and quantification (LOQ) were between 0.03 and 0.05 mg/L and 0.11 and 0.16 mg/L, respectively. The synthesised GMMIP proved to be a convenient and effective adsorbent to remove parabens from cosmetic products.

Upstream textile companies in Indonesia are the most significant contributors to environmentally hazardous production waste. Green Transformational Leadership (GTL) is critical to achieving a Green Resilient Supply Chain (GRS) to address vulnerability to supply chain disruptions while maintaining environmentally friendly practices. In addition, the mediation of Green Ambidexterity (GAM) and Green Innovation (GIN) is believed to strengthen the achievement of GRS. In line with the Indonesian government's policy to protect the environment, this study examines the direct effect of green transformational leadership variables on a green resilient supply chain. It evaluates Green Ambidexterity and Green Innovation's mediating effect on the relationship between GTL and GRS. This study analyzes the data of 50 production managers of upstream textile companies from 87 respondents collected from the survey. The analysis uses PLS-SEM based on variance to verify the relationship between variables. The research results indicate that green transformational leadership significantly influences green resilient supply chains. It was found that both Green Ambidexterity and Green Innovation significantly influence the Green Resilient Supply Chain, both directly and through mediating effects. Therefore, managers should consider implementing a Green Resilient Supply Chain, Green Ambidexterity, and Green Innovation practices to improve organizational goals while maintaining a green environment.

In the present work, synthesis of phthalimide and naphthalimide derived Biginelli compounds was performed. Allylation of phthalic & naphthalic anhydride, followed by ozonolysis resulted in the formation of N-phathalimido/naphpthalimido acetaldehyde (2 and 7). These aldehydes were subjected to Biginelli reaction using urea/thiourea and divergent β-keto esters in the presence of sulfated tin oxide (5 mol%) as catalyst in ethanol reflux to produce the corresponding dihydropyrimidinone compounds (5a-j and 8a-h). Additionally, both their antioxidant and anti-inflammatory functions were carried out. Compounds 5e, 5f, 5i, and 5j have shown potent to moderate potent activity for both antioxidant and anti-inflamamtory activities when compared to standard. Compounds 8c and 8g have shown potent antioxidant and anti-inflamamtory activities when compared to other compounds.

Giving credit to debtors can pose a default risk. This risk arises because of an error in analyzing the credit risk rate of the debtor. Therefore, this study aims to design a framework for analyzing the credit risk rate of debtors so that the default risk can be reduced. This framework is created using the integration of factor analysis and Tsukamoto’s fuzzy logic method. This integration method can group many credit assessment variables into several decisive factors. In addition, the integration method can estimate credit risk rate firmly based on the α-predicate of each basic rule. This analytical framework is simulated on credit application data at a Rural Bank, in Indonesia. The simulation results show that there are three factors and one variable to measure the credit risk rate, namely: factor 1 represents repayment capacity, business length, working capital, and liquidity value; factor 2 represents the age and the difference between the granted and the proposed loan amount; factor 3 represents the stay length, character, and credit history; and one variable represents a dependent number. This research is expected to help credit institutions measure the credit risk rate in making credit decisions for prospective debtors.

The processes involved to extract chitosan biopolymers from natural resources often employ hazardous chemicals and long processing time. This work provides a sustainable direct extraction method of chitosan from snail shells. Previous attempts using acetogenin in graviola extracts succeeded in the extraction of chitosan from marine shells. However, the slow reaction has prompted the addition of hydrogen bond acceptor solution into the graviola extract. Choline chloride is an excellent hydrogen bond acceptor mixed with acetogenin as hydrogen bond donor to form natural deep eutectic solvent (NADES) for the direct extraction of chitosan. Chitosan obtained from this method has a degree of deacetylation of 91% and a molecular weight of 481 kDa with fiber-like morphology. The direct extraction of chitosan from NADES consisting of choline chloride and acetogenin has proven to extract chitosan with comparable properties to commercial chitosan.

Life insurance is designed to reduce the risk of financial loss due to unforeseen consequences related to the insured's death. In life insurance, the insurer provides death benefits as a claim when the insured suffers death. The claim is the compensation for a risk loss. Individual claim in one-period insurance is called aggregation claim, while aggregation claim is a collective risk. Collective risk is usually measured using a variance. However, the variance risk measure cannot often accommodate any event risk because there is a risk of claims beyond the amount of variance. Using the proposed method CVaR and confidence level are taken from α = 0.25% until 4%. This study found that the proposed method CVaR scored more fairly than Collective Risk. In conclusion, this study indicated that the collective risk model is just included using mean and variance without any confidence level. Therefore, only one result for the Collective Risk model, which automatically shows the model using mean, variance and standard deviation, could not accommodate all risk events.

Global business is getting more and more cutthroat. Digital technology plays a significant role in giving companies a competitive advantage and improving the effectiveness of corporate processes. The Malaysian government has advanced by implementing e-government to use digital technologies to improve operations. In line with the objective of Malaysia’s government, this study examines the impact of e-procurement adoption and e-procurement determinants on supply chain performance among Malaysian manufacturing companies. Using a quantitative research design with an online survey questionnaire, 99 responses from manufacturers listed in the Federation of Malaysian Manufacturers directory were obtained, representing 19.41% of the response rates. It fulfilled the minimum sample size of 92, and the data were examined using PLS-SEM. A total of 13 hypotheses are supported, accepted hypotheses one and two in which top management support and information communication technology infrastructure do not directly affect supply chain management. Besides, the findings prove this study's mediating effect on e-procurement adoption. It indicates that most Malaysian manufacturing companies have embraced e-procurement to support their supply chain operations.

The purpose of the study is to examine the mediating role of corporate image on the influence of retailers’ corporate social responsibility (CSR) practices of a fast-food chain brand and its corporate reputation. The study utilized the dimensions of the retailer’s CSR dimension. This study focused on the external stakeholders (customers) of X fast food brand in Klang Valley. Social exchange theory was employed to guide the study. Quantitative (survey) methods have been used in this study, whereby 150 valid online questionnaires were gathered among the customers in the Petaling Jaya and analyzed using Partial Least Square Structural Equation Modelling (Smart-PLS 4.0). The findings showed that Philanthropic activities, Respect for the Environment, and Respect for Consumers have positive and significant relationships with corporate image, and corporate image also has a positive and significant relationship with corporate reputation. Furthermore, there is a significant mediating effect of corporate image on the relationship between CSR practices (Respect for Consumers, Respect for the Environment, Philanthropic Activities) and corporate reputation. The conclusion, implications, and suggestions for future studies were also discussed.