Slow fashion is a new movement in the textile industry, where slow production mode and more ethical business processes are highly considered. This movement is an alternative to buying fast fashion productsto achieve a sustainable pattern. The theory of planned behavior also includes attitudes, subjective norms, and perceived behavior control, which are commonly used to analyze the patterns of green attitudinal variables through other additional principles, namelythe willingness to pay a premium, consumer effectiveness, and environmental knowledge. Therefore, this study analyzed factors influencing purchase intention of slow-fashion products. In this analysis, a randomized questionnaire was implemented and distributed to 140 Generation Z people in West Java Province, Indonesia. Structural equation modelingwas also used to test the fit model and path analysis of attitudes mediating green products knowledge on the intensity of buying slow-fashion products. The results showed that the three main variables of TPB and other influential/significant expanding principles were observed, except consumers' perceived effectiveness did not affect purchase intention. The limitations also prioritized the need for more experimental loci capable of being developed at different points. Moreover, the results obtained were beneficial for both academic and managerial purposes. This proved that green product purchasing behavior analysis needs to be academically improved, specifically for slow-fashion in developing countries. Managerial suggestions also increased green knowledge of fashion products through descriptive analysis. These suggestions enhanced consumers' understanding of the effective reduction of textile waste by purchasing fashion products.

Manufacturing companies constantly strive to build sustainable performance to survive fierce business competition. Besides, the company should be committed to protecting the environment by paying attention to the role of supply chain members. Companies should collaborate with external partners, enabling them to fulfill customers' needs for environmentally friendly products. This study explores the effect of green supply chain management on operational performance with the mediating role of information technology infrastructure, internal integration, and external integration. This study surveyed manufacturing companies in Indonesia using structured questionnaires designed with a five-point Likert scale. The questionnaire is designed using Google Forms, and the links are distributed to respondents through email, WhatsApp, and other social media. As many as 245 responses were obtained and valid for analysis. The data processing used SmartPLS software version 4.0. The hypothesis test results found that green supply chain management influences information technology infrastructure, internal integration, external integration, and operational performance. Information technology infrastructure impacts improving internal integration, external integration, and operational performance. Internal integration has an impact on external integration and operational performance. External integration has an impact on improving operational performance. The research contributes to managerial practice by adopting the ISO 14001 standard in green supply chain management. for companies to make improvements. These findings also enrich the current research in supply chain management theories.

The objective of the current study is to explore how certain attributes of chief executive officers (CEOs), such as their innovativeness, knowledge of information systems (IS), and trust in technology and technological factors (Compatibility, relative advantage, and complexity) on the utilization of accounting information systems (AIS) in companies across various industries in Jordan. The research gathered data through a structured questionnaire, which included a 7-point scale. The respondents were CEO/owner of small, medium, and large enterprises (SMEs) in Jordan. A total of 315 valid responses were analyzed using the Partial Least Squares Structural Equation Modeling (PLS-SEM) technique. The findings indicated a significant and positive correlation between complexity, compatibility, CEOs trust in technologies, CEOs information system (IS) knowledge, and the utilization of AIS. However, CEO innovativeness and relative advantage have an insignificant impact on AIS use. The present study is the first to examine CEO characteristics in the AIS context. The practical and theoretical implications derived from the empirical findings of this study offer valuable insights for managers and practitioners. These insights aim to enhance their understanding of the fundamental factors crucial for the successful implementation of AIS in companies, ultimately contributing to improved firm performance.

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.