Determining 2n values of fuzzy measure prior to applying Choquet integral normally turns into a complex undertaking, especially when the decision problem entails a large number of evaluation attributes, n. Many patterns of fuzzy measure have thus been suggested to deal with this complexity. λ0-measure is one such pattern. However, the original λ0-measure identification method was found to be unsuccessful in providing clear-cut indications on the relationships held by the attributes. A revised version of the method was then introduced to tackle this issue, but unfortunately it requires a large amount of initial data from the respondents compared to the original method. This paper therefore proposes an alternate version of λ0-measure identification method that synchronously compensates the shortcomings associated with each existing method. The proposed method uses interpretive structural modelling (ISM) to uncover the actual relationships held by the attributes. The outputs of ISM (i.e. digraph, driving power and dependence power) are then utilised to determine the inputs required to identify the complete set of λ0-measure values. A supplier selection problem was used to demonstrate the feasibility of the method. Also, the usability of the method was compared over the existing ones.

Over the last two decades, the global financial landscape has changed dramatically, including the corporate and political climates, the creation of more market-based economies, and rapid technological advancements. Micro, Small, and Medium Enterprises (MSMEs) is one form of market-based economies created with the most significant business opportunities and very important socially and economically in developing countries for many reasons. However, MSMEs face significant difficulty related to financial reporting standards to evaluate the achievement of business activities. Most MSMEs use a simple form for financial reporting, such as by calculating the difference between inflow and outflow from their business activities. Also, numerous previous studies that focus on Financial Accounting Standards in Indonesia are still limited. Thus, the present study investigates the factors that influence the implementation of Financial Accounting Standards (FAS) of Micro, Small, and Medium Enterprises (MSMEs) in Aceh Province, Indonesia. This quantitative study uses cross-sectional data collected by distributing 200 questionnaires to MSMEs actors that spread North Aceh Regency, namely Lhokseumawe city and Bireuen regency. The data are analyzed using descriptive statistics (e.g., frequency, percentage, mean, standard deviation) and inferential statistic (multiple linear regression) analyses. The study indicated that Perception, Education, Socialization and Incentive factors had significant positive effects on implementing Financial Accounting Standards of Micro, Small, and Medium Enterprises (MSMEs) in Aceh Province, Indonesia. In conclusion, this study has successfully investigated the factors that influence the implementation of Financial Accounting Standards of Micro, Small, and Medium Enterprises (MSMEs) in Aceh Province.

The purpose of this paper is to provide a method of process reference to supply chain relationships in a downstream sector. It serves as a tool to analyze collaboration between entities in the supply chain strategy. The study is categorized into the case study research in Malaysian oil palm refineries. The data collection is accomplished through semi-structured interview using snowball sampling and observation by visiting four oil palm refineries based on selecting non probability sampling technique through purposive personal judgment. Most of downstream industries select produced end products with the aim of getting greater margins. Nevertheless, a process reference analyzes that the downstream industry distributes semi-finished products to the international market than producing end products in the local market. There are the effects of supply chain relationships between upstream and downstream. Furthermore, entities that have the high dependencies tend to follow the strategy of the dominant entities consequently network of business process driven by the strong entities. The result gives implication to leverage SCOR model for analyzing the supply chain relationships between entities. It can be applied to any industry that decide the effective collaboration with their supplier, distributor and buyer.

As the workforce worldwide goes through a transformative shift towards remote work, this paper discusses the positive effects of this quite flexible work arrangement on team’s innovation performance (TIP) in multinational, non-governmental organizations (NGOs). Adopting cross-sectional, quantitative research design, empirical data were collected through a survey of 268 employees of multinational NGOs operating in Jordan. The collected data were, then, analyzed using structural equation modeling. The results of the analysis showed that remote work has significant, positive effects on TIP in NGOs. Of the various remote work features investigated, spatial flexibility has the highest effect. The study results contribute to the ongoing discourse on the future of the work styles and have implications for leaders, policymakers, and practitioners who seek promoting innovation in multinational NGOs.

While many small and medium enterprises (SMEs)recognize the benefits of Big Data Analytics (BDA) for digital transformation, they face challenges in implementing this technology, highlighting the need for more research on its adoption by SMEs. The objective of this study is to amalgamate the Technology Organization Environment (TOE) framework with the Diffusion of Innovation (DOI) theory, aiming to dissect the factors that sway BDA adoption in Jordanian SMEs. Additionally, the study delves into how perceived usefulness impacts this adoption process. Utilizing structural equation modeling, the study examined data from 388 managers in Jordan. The study validates all its hypotheses, revealing that variables like relative advantage, compatibility, complexity, top management support, competitive pressure, and security influence perceived usefulness, which subsequently has a positive impact on BDA adoption. This research presents a range of theoretical and practical insights.

This study on the moderating effect of electronic quality in mobile marketing aims to examine the factors that influence how Saudi commercial banks are viewed by their customers. A research framework that sheds light on the state of the research was developed after a comprehensive analysis of the accessible literature. The theoretical foundation of this study is the idea of perceived characteristics, which identifies five critical factors that influence adoption rates. The empirical results of this study are presented based on a sample of 300 respondents (n = 300). The research was conducted using the statistical technique of least squares structural equation modeling (PLS-SEM). The reporting format conforms to accepted PLS-SEM analysis standards. The results reveal a significant association between mobile marketing and customer perceptions in the context of Saudi commercial banks, especially when electronic quality is used as a mediating variable. Based on these findings, we suggest that Saudi commercial banks should strategically include e-quality in their digital marketing campaigns, paying special attention to mobile marketing.

Recently, there has been tremendous interest worldwide in the possibility of using chaos in communication systems. Many different chaos-based secure communication schemes have been proposed up until now. However, systems with strong chaoticity are more suitable for chaos-based secure communication. From the viewpoint of Lyapunov exponents, a chaotic system with a larger positive Lyapunov exponent is said to be more complex. This paper constructing a multistable chaotic system that can produce coexisting attractors is an attractive field of research due to its theoretical and practical usefulness. An innovative 3D dynamical system is presented in this research. It can display various coexisting attractors for the same values of parameters. The new system is more suitable for chaos-based applications than recently reported systems since it exhibits strong multistable chaotic behavior, as proved by its large positive Lyapunov exponent. Furthermore, the accuracy of the numerical calculation and the system's physical implementations are confirmed by analog circuit simulation. Finally, implementing the proposed voice encryption is done using a four-wing chaotic system based on the PRNG.

The potential for transforming the estate management industry through the resolution of common inefficiencies, lack of transparency, and security concerns is presented by the use of blockchain technology into estate governance. The purpose of this article is to clarify how incorporating blockchain technology would affect estate operations and governance. This study is based on quantitative information that was collected from 317 estate management professionals using a 5-point Likert scale questionnaire. SmartPLS4 analysis demonstrates that blockchain governance has a statistically significant and robust influence on estate governance in Jordan. The impact of Blockchain Governance on Jordanian Estate Management appears to be negligible and unimportant. Furthermore, there appears to be a negligible and insignificant correlation between Jordanian estate management and estate planning methods. In-depth analysis of these theories is done in this article, which also offers insights into how blockchain technology affects estate governance dynamics and how it can affect Jordan's estate management procedures. The consequences go beyond theoretical understandings; they promote the use of blockchain technology in estate governance frameworks as a game-changing means of ensuring the safe, transparent, and effective administration of frozen estates in Jordan and elsewhere.

In the real world of engineering problems, in order to reduce optimization costs in physical processes, running simulation experiments in the format of computer codes have been conducted. It is desired to improve the validity of simulation-optimization results by attending the source of variability in the model’s output(s). Uncertainty can increase complexity and computational costs in Designing and Analyzing of Computer Experiments (DACE). In this state of the art review paper, a systematic qualitative and quantitative review is implemented among Metamodel Based Robust Simulation Optimization (MBRSO) for black-box and expensive simulation models under uncertainty. This context is focused on the management of uncertainty, particularly based on the Taguchi worldview on robust design and robust optimization methods in the class of dual response methodology when simulation optimization can be handled by surrogates. At the end, while both trends and gaps in the research field are highlighted, some suggestions for future research are directed.

The proliferation of online violence has given rise to a spate of malignant incidents, necessitating a renewed focus on the identification of cyberbullying comments. Text classification lies at the heart of efforts to tackle this pernicious problem. The identification of cyberbullying comments presents unique challenges that call for innovative solutions. In contrast to traditional text classification tasks, cyberbullying comments are often accompanied by subtle and arbitrary expressions that can confound even the most sophisticated classification networks, resulting in low recognition accuracy and effectiveness. To address this challenge, a novel approach is proposed that leverages the BERT pre-training model for word embedding to retain the hidden semantic information in the text. Building on this foundation, the BiSRU++ model which combines attentional mechanisms is used to further extract contextual features of comments. A multi-task learning framework is employed for joint training of sentiment analysis and cyberbullying detection to improve the model's classification accuracy and generalization ability. The proposed model is no longer entirely reliant on a sensitive word dictionary, and experimental results demonstrate its ability to better understand semantic information compared to traditional models, facilitating the identification of potential online cyberbullying comments.