Search results

Since the performance of vehicular users and cellular users (CUE) in Vehicular networks is highly affected by the allocated resources to them. The purpose of this paper is to investigate the resource allocation for vehicular communications when multiple V2V links and a V2I link share spectrum with CUE in uplink communication under different Quality of Service (QoS).

An optimization model to maximize the V2I capacity is established based on slowly varying large-scale fading channel information. Multiple V2V links are clustered based on sparrow search algorithm (SSA) to reduce interference. Then, a weighted tripartite graph is constructed by jointly optimizing the power of CUE, V2I and V2V clusters. Finally, spectrum resources are allocated based on a weighted 3D matching algorithm.

The performance of the proposed algorithm is tested. Simulation results show that the proposed algorithm can maximize the channel capacity of V2I while ensuring the reliability of V2V and the quality of service of CUE.

There is a lack of research on resource allocation algorithms of CUE, V2I and multiple V2V in different QoS. To solve the problem, one new resource allocation algorithm is proposed in this paper. Firstly, multiple V2V links are clustered using SSA to reduce interference. Secondly, the power allocation of CUE, V2I and V2V is jointly optimized. Finally, the weighted 3D matching algorithm is used to allocate spectrum resources.

The authors examine the impact of CEO generalist experience on firm performance. Using 522 listed firms in Indonesia for the period 2010–2018, the authors find that the generalist CEO is negatively associated with firm performance. Generalist CEOs tend to experience ambiguity in adjustments in the new environment. In order to decrease the impact of a generalist CEO, our empirical evidence finds that CEO tenure does not significantly moderate the association between the two. This is because generalist CEOs with longer tenure tend to avoid changing strategies, and therefore the negative impact of CEO generalist is not altered. The results of this study provide suggestions for the firm in the developing country to appoint a CEO with generalist experience.

Women’s involvement in business is growing and positively impacting the national economy, especially in developing countries. Women entrepreneurs’ success has shown women’s abilities to empower and support national policies and agendas. Efforts and tenacity in a consecutive e-commerce business require innumerable tactics since the business ecosystem has become more challenging and complex. Therefore, this study aims to identify the multiple mediation influence of the need for achievement and locus of control towards the relationship between entrepreneurial knowledge and women entrepreneurs’ e-commerce ventures. The theory of planned behaviour provides excellent opportunities for understanding and envisaging entrepreneurial actions. The study pre-supposes that the interaction of these variables ultimately defines women entrepreneurs’ e-commerce ventures.

This study used a cross-sectional design, and the survey data were collected from 259 valid women entrepreneurs. The study population covers the Klang Valley area, composed of the Federal Territory of Kuala Lumpur and Selangor, Malaysia. The instrument used in this study was adapted from previous studies. Structural equation modelling was used to establish the measurement model and examine the direct and causal path models.

Firstly, results show a positive relationship between entrepreneurial knowledge and women entrepreneurs’ e-commerce ventures. Secondly, the results show that the need for achievement and locus of control plays an intermediate role in the relationship between entrepreneurial knowledge and women entrepreneurs’ e-commerce ventures.

There are some limitations to this study. Firstly, the main limitation is that it is impossible to generalise the study’s findings since it only examines the sample in the Klang Valley area. Therefore, it would be better for future research to conduct similar studies in other areas. Next, the data were collected cross-sectional, and considering the changes in time that might influence human behaviour, future studies might consider a longitudinal research technique. Thirdly, this study model is limited; hence, future studies can advance and develop the current research model by including more variables, such as moderating and mediating variables.

Education is one of the driving factors that help increase entrepreneurs’ knowledge and skills. Lifelong learning programs must be implemented for women entrepreneurs to increase their knowledge. The relevant parties, including the government, entrepreneurial bodies, training institutions and universities, must provide and develop a more affordable, flexible and inclusive short-course training program and activities for women entrepreneurs.

Empirical studies have proposed reconsidering the effect of entrepreneurial personalities for a better understanding of entrepreneurship engagement. These unique characteristics could act as an enabler for a capable entrepreneur. Many studies have examined the direct relationship between predictor and intention or between predictor and behaviour. Nevertheless, only a few studies have identified the influence of mediating variables in the theory-based framework. By adding the role of personality traits (i.e. need for achievement and locus of control), this study delivers fascinating insights into the current entrepreneurship research and literature. This study also makes a meaningful contribution to entrepreneurship literature, especially in Malaysia’s context of entrepreneurship ecosystems, considering there are still few studies on women entrepreneurship. This study also provides exposure and explanation of the function of the need for achievement and locus of control as the mediators for the relationship between entrepreneurial knowledge and women entrepreneurs’ e-commerce ventures.

This study aims to theoretically investigate the effect of activating corporate governance (CG) mechanisms on the association between adopting corporate social responsibility (CSR) and tax avoidance (TA). Based on the analyzing of the previous studies, the authors support the results of studies that found a positive effect for activating CG on the adoption of CSR. Also, they found that there is a negative impact of activating CG mechanisms on TA, as CG includes controls and procedures that contribute to limiting opportunistic behaviors of management and ensures making decisions that maximize value for shareholders. To the best of the authors' knowledge, it is the only chapter that examines the effect of activating CG mechanisms on the association between CSR and TA.

Despite extensive research on supply chain management (SCM), the literature lacks a perspective to empirically assess the importance of poverty alleviation in social business. Using resources dependence theory, the purpose of this study is to analyze to ascertain whether financial innovation has a powerful solution for business sustainability and, hence, poverty alleviation in developing countries. This study reviews the financial innovations offered by Dompet Dhuafa Republika in integrated supply chain management (ISCM) of smallholder livestock business through Tebar Hewan Kurban (Spreading Sacrificial Animals) program to overcome capital and marketing problems at the farmer level and distribute Qurban meat to the recipients.

This study was conducted using descriptive qualitative method. The data were obtained through a field survey, by interviewing two crowdfunding-based investment companies, 250 partner farmers, program managers and assistants, marketing partners, donors/consumers/person who sacrifice and Mustahik (recipients of Qurban meat) involved in program implementation, using purposive sampling method. Focus group discussion was conducted with selected panelists to validate the results of the field survey.

The results of this study showed that the Tebar Hewan Kurban program provides greater benefits to farmers, while increasing the distribution of Qurban meat to be more equitable. The role of moneylenders and middlemen can also be eliminated. Donors feel satisfied because their goals are fulfilled in the Qurban ritual. Program implementers and investors also got decent returns. ISCM is very feasible to be developed on a wider scale, to improve the welfare of farmers or fishermen.

This study used a set of samples of the assisted areas from only one institution, which may lead to institution-specific results. Although the sample is small, the results of this study are expected to provide new insights into the implementation of the Qurban, which will provide more profits and benefits for partner farmers. In broader practice, the program flow is worth considering compared to similar programs in other institutions, in Indonesia or abroad. Because of the COVID-19 pandemic situation, the field survey and focus group discussion were carried out online.

The results show that ISCM is able to increase the income of farmers. Practically, this program can be duplicated in similar institutions, as well as in government or non-government organizations, in Indonesia and abroad, that have the same context and activity.

This study offers several social contributions by exploring how and why ISCM can eliminate the role of moneylenders and middlemen, increasing the small farmers' income, providing reasonable profits to parties involved in marketing and satisfying donors and equitable distribution of Qurban meat.

This study contributes to the literature by confirming the higher impact of ISCM in social business on poverty alleviation. Therefore, this paper provides an alternative solution to increase the income of small farmers through the supply of animals for Qurban or other religious rituals through ISCM arrangements.

In past decades, artificial neural network (ANN) models have revolutionised various stock market operations due to their superior ability to deal with nonlinear data and garnered considerable attention from researchers worldwide. The present study aims to synthesize the research field concerning ANN applications in the stock market to a) systematically map the research trends, key contributors, scientific collaborations, and knowledge structure, and b) uncover the challenges and future research areas in the field.

To provide a comprehensive appraisal of the extant literature, the study adopted the mixed approach of quantitative (bibliometric analysis) and qualitative (intensive review of influential articles) assessment to analyse 1,483 articles published in the Scopus and Web of Science indexed journals during 1992–2022. The bibliographic data was processed and analysed using VOSviewer and R software.

The results revealed the proliferation of articles since 2018, with China as the dominant country, Wang J as the most prolific author, “Expert Systems with Applications” as the leading journal, “computer science” as the dominant subject area, and “stock price forecasting” as the predominantly explored research theme in the field. Furthermore, “portfolio optimization”, “sentiment analysis”, “algorithmic trading”, and “crisis prediction” are found as recently emerged research areas.

To the best of the authors’ knowledge, the current study is a novel attempt that holistically assesses the existing literature on ANN applications throughout the entire domain of stock market. The main contribution of the current study lies in discussing the challenges along with the viable methodological solutions and providing application area-wise knowledge gaps for future studies.

This paper aims to apply several data mining techniques for predicting the daily precision improvement of Jakarta Islamic Index (JKII) prices based on big data of symmetric volatility in Indonesia’s Islamic stock market.

This research uses big data mining techniques to predict daily precision improvement of JKII prices by applying the AdaBoost, K-nearest neighbor, random forest and artificial neural networks. This research uses big data with symmetric volatility as inputs in the predicting model, whereas the closing prices of JKII were used as the target outputs of daily precision improvement. For choosing the optimal prediction performance according to the criteria of the lowest prediction errors, this research uses four metrics of mean absolute error, mean squared error, root mean squared error and R-squared.

The experimental results determine that the optimal technique for predicting the daily precision improvement of the JKII prices in Indonesia’s Islamic stock market is the AdaBoost technique, which generates the optimal predicting performance with the lowest prediction errors, and provides the optimum knowledge from the big data of symmetric volatility in Indonesia’s Islamic stock market. In addition, the random forest technique is also considered another robust technique in predicting the daily precision improvement of the JKII prices as it delivers closer values to the optimal performance of the AdaBoost technique.

This research is filling the literature gap of the absence of using big data mining techniques in the prediction process of Islamic stock markets by delivering new operational techniques for predicting the daily stock precision improvement. Also, it helps investors to manage the optimal portfolios and to decrease the risk of trading in global Islamic stock markets based on using big data mining of symmetric volatility.

This research is a pioneer in using big data mining of symmetric volatility in the prediction of an Islamic stock market index.

Hoping to uncover the physical principles of the vibration of the functionally graded material (FGM) microplate, by which the authors can make contributions to the design and manufacturing process in factories like micro-electro-mechanical system (MEMS) and other industries.

The authors design a method by establishing a reasonable mathematical model of the physical microplate composed of a porous FGM.

The authors discover that the porosity, the distributions of porosity, the power law of the FGM and the length-to-thickness ratio all affect the natural frequency of the vibration of the microplate, but in different ways.

Originally proposed a model of the micro FGM plate considering the different distributions of the porosity and scale effect and analyzed the vibration frequency of it.

This study aims to investigate the association between corporate tax avoidance and environmental costs and disclosure in Indonesia and Australia for the research period 2015–2019. This study also analyzes corporate strategies for overcoming public concerns about tax avoidance activities, namely, the trade-off legitimacy and risk reduction strategies, through two mechanisms: the mediation and moderation roles of environmental disclosure on the relationship between environmental costs and tax avoidance activities.

The data consists of 675 and 235 observations for Australia and Indonesia, respectively, which were analyzed quantitatively using panel regression.

The results showed that the trade-off legitimacy or risk reduction strategies are not found to be implemented by companies in Indonesia, while in Australia, corporations use the trade-off legitimacy strategy to reduce risk and overcome the negative impact of tax avoidance activities. The results also provide empirical evidence on the impact of environmental costs on environmental disclosure in both countries.

This study contributes to the literature by providing the latest evidence on the role of environmental costs on environmental disclosure, which has rarely been investigated in previous studies.

This study aims to explore the relationship between fraud triangle theory (FTT) and the accounting fraud phenomenon in all listed companies in China.

The CSMAR database is used as the sample, including 16,063 data of all listed companies in Shanghai and Shenzhen markets for the 2010–2020 period. The authors also use quantitative methods, such as regression analysis, to investigate the relationship between five variables (cover three elements of FTT) and fraud occurrence.

Results show that leverage and liquidity ratios positively affect fraud detection, whereas return on net equity, audit size and independent director percentage negatively affect fraud detection.

This study enriches theoretical research on the causes of accounting fraud in China and is of great significance to the sound development of China’s capital market.