Lack of knowledge, attitude, and behavior in managing leftover foods in households impacts the natural ecosystem and food chain, particularly in developing countries. This research aims to analyze appropriate methods for reducing and processing food waste produced in household areas. This research method uses qualitative research with operational research methods carried out for 6 months on 25 housewives in Pondok Labu Village in South Jakarta, Indonesia. The research was carried out in 3 stages, the first stage before the intervention, the second stage providing the intervention, and the third stage after the intervention. Results showed that before the intervention, on average each respondent produced 351 g of food waste each day. This amount decreased to 8.43 g/day after respondents participated in socialization to reduce food waste and training to manage food waste. The concluded that a combination of education and training improves knowledge, attitude, and behavior in household food waste management and helps moderate food waste generation.

This paper presents an effective method for performing audio steganography, which would help in improving the security of information transmission. Audio steganography is one of the techniques for hiding secret messages within an audio file to maintain communication secrecy from unwanted listeners. Most of these conventional methods have several drawbacks related to distortion, detectability, and inefficiency. To mitigate these issues, a new scheme is presented which combines the techniques of image interpolation with LSB encoding. It selects non-seed pixels to allow reversibility and diminish distortion in medical images. Our technique also embeds a fragile watermarking scheme to identify any breach during transmission to recover data securely and reliably. A magic rectangle has also been used for encryption to enhance data security. This paper proposes a robust, low-distortion audio steganography technique that provides high data integrity with undetectability and will have wide applications in sectors like e-healthcare, corporate data security, and forensic applications. In the future, this approach will be refined for broader audio formats and overall system robustness.

In the face of growing competition, industrial and commercial firms need more effective strategies to gain competitive advantages. This study investigates the role of enterprise risk management (ERM) as a mediator in highlighting the significance of innovation capability on profitability in industrial and commercial firms listed on the Amman Stock Exchange (ASE). Data were collected from 244 respondents using a standardized questionnaire and analyzed with SPSS software. The results indicate that the innovation capability has an impact on profitability in industrial and commercial firms, as well as their ERM practices. Additionally, ERM mediates the relationship between innovation capability and profitability. Firms that adopt distinctive innovation strategies tend to maintain formal ERM strategies, which in turn enhance market superiority and profitability. This research offers some significant managerial ramifications that may be essential for business owners, executives, and decision-makers involved in the development of firms.

This research analyses digital nomads’ relationship with tourism, their motivations for travelling and their expectations of the destinations they visit. In addition, it aims to understand the lifestyle of this public and their preference for sustainable destinations, as well as the implications for policies and the organisation of tourism infrastructure, in line with their specific needs. A questionnaire was administered to users of open-access social networks or members of online digital nomad communities (n = 34), between December 2022 and March 2023. Descriptive statistics, construct validations, reliability and internal consistency of the measures were carried out and Pearson’s linear correlation coefficient (r) was applied between items of the same scale and different scales. The results indicate that quality of life, life-work balance, living with other cultures, being in contact with nature, escaping from large urban centres, indulging in tourism all year round and travelling for long stays, are the main motivations of this public. The importance of quality Wi-Fi, flexible tourist services and support services is emphasised as the main attributes to be considered in tourist destinations.

We analyze Thailand’s projected 2023–2030 energy needs for power generation using a constructed linear programming model and scenario analysis in an attempt to find a formulation for sustainable electricity management. The objective function is modeled to minimize management costs; model constraints include the electricity production capacity of each energy source, imports of electricity and energy sources, storage choices, and customer demand. Future electricity demands are projected based on the trend most closely related to historical data. CO₂ emissions from electricity generation are also investigated. Results show that to keep up with future electricity demands and ensure the country’s energy security, energy from all sources, excluding the use of storage systems, will be necessary under all scenario constraints.

Objectives: This research aimed to empirically examine the transformative impacts of Artificial Intelligence (AI) adoption on financial reporting quality in Jordanian banking, with internal controls as a hypothesized mediation mechanism. Methodology: Quantitative survey data was collected from 130 bank personnel. Multi-item reflective measures assessed AI adoption, internal controls, and financial reporting quality—structural equation modelling analysis relationships between constructs. Findings: The research tested four hypotheses grounded in agency and contingency theories. Confirmatory factor analysis demonstrated sound measurement models. Structural equation modelling revealed that AI adoption significantly transformed financial reporting quality. The mediating effect of internal controls on the AI-quality relationship was supported. Specifically, the path from AI adoption to quality was significant, indicating a positive impact. Despite internal controls strongly predicting quality, its mediating effect significantly shaped the degree of transformation driven by AI adoption. The indirect effect of AI on quality through internal controls was also significant. Findings imply a growing diffusion of AI applications in core financial reporting systems. Practical implications: Increasing AI applications focus on holistically transforming systems, reflecting committing adoption. Jordanian banks selectively leverage controls to moderate AI-induced transformations. Originality/value: This study provides essential real-world insights into how AI is adopted and impacts the Jordanian banking sector, a key player in a fast-evolving developing economy. By examining the role of internal controls, it deepens our understanding of how AI works in practice and offers practical advice for integrating technology effectively and improving information quality. Its mixed methods, unique context, and focus on AI’s impact on organizations significantly enrich academic literature. Recommendations: Banks should invest in integrated AI architectures, strategically strengthen critical controls to steer transformations, and incrementally translate AI innovations into core processes.