• Agribusiness and Information Management
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• v.13 no.1
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• pp.1-25
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• 2021

Technological propensity of agricultural entrepreneurs is becoming necessary to identify and explore new opportunities. Recent studies suggest that the adoption of new technologies is strictly coherent with wider approaches of Entrepreneurial Orientation (EO). Even if the relevance of agriculture is increasing, entrepreneurial research has largely overlooked this challenging sector. Moreover, there is a relative shortage of empirical studies in the literature and there is an enormous potential to be still explored. Stemming from the EO literature, the work proposes for the agricultural sector, the approach of Humane Entrepreneurial Orientation (HEO). The paper proposes an empirical analysis, to verify the effect of the different dimensions of HEO on the propensity of farmers to adopt new technologies. All the results highlight several implications for businesses, for the research system and for public policies.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.307-318
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• 2021

The objective of this study is to analyze the performance of Islamic banks with the Maqashid Shariah approach. The analysis technique used is the Simple Additive Weighting Method (SAW) to solve multi-attribute decision problems. The sampling technique used was purposive sampling while the data came from the annual report of each bank. The results showed that the BTPN Shariah (BTPNS) and Bank Muamalat Indonesia (BMI) are ranked first and second respectively on the Maqashid Shariah Index (MSI) with values of 0.265429 and 0.237110 respectively. Panin Dubai Shariah Bank (PDSB) ranked third with an MSI value of 0.180733, followed by BCA Shariah which ranked fourth with an MSI value of 0.151299. BRI Shariah ranked fifth with an MSI value of 0.128606, followed by BNI Shariah which ranked sixth with an MSI value of 0.124661. Bank Mega Shariah ranked last with an MSI value of 0.087068. Furthermore, there is a relationship (correlation) between ROE, ROA, and OEOI and MSI since each data has a value of 0.000, 0.000, 0.050, and 0.001 respectively, which is smaller than the significance value of 0.05. On the other hand, NPF, TPF, and Asset Growth Rates do not correlate with the MSI since each data has a value of 0.051, 0.252, and 0.215 respectively which is greater than the significance value of 0.05.

• Steel and Composite Structures
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• v.44 no.1
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• pp.65-79
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• 2022

The main goal of this paper is to study the vibration of damaged core laminated annular plates with FG face sheets based on a three-dimensional theory of elasticity. The structures are made of a damaged isotropic core and two external face sheets. These skins are strengthened at the nanoscale level by randomly oriented Carbon nanotubes (CNTs) and are reinforced at the microscale stage by oriented straight fibers. These reinforcing phases are included in a polymer matrix and a three-phase approach based on the Eshelby-Mori-Tanaka scheme and on the Halpin-Tsai approach, which is developed to compute the overall mechanical properties of the composite material. In this study the effect of microcracks on the vibrational characteristic of the sandwich plate is considered. In particular, the structures are made by an isotropic core that undergoes a progressive uniform damage, which is modeled as a decay of the mechanical properties expressed in terms of engineering constants. These defects are uniformly distributed and affect the central layer of the plates independently from the direction, this phenomenon is known as "isotropic damage" and it is fully described by a scalar parameter. Three complicated equations of motion for the sectorial plates under consideration are semi-analytically solved by using 2-D differential quadrature method. Using the 2-D differential quadrature method in the r- and z-directions, allows one to deal with sandwich annular plate with arbitrary thickness distribution of material properties and also to implement the effects of different boundary conditions of the structure efficiently and in an exact manner. The fast rate of convergence and accuracy of the method are investigated through the different solved examples. The sandwich annular plate is assumed to have any arbitrary boundary conditions at the circular edges including simply supported, clamped and, free. Several parametric analyses are carried out to investigate the mechanical behavior of these multi-layered structures depending on the damage features, through-the-thickness distribution, and boundary conditions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.5
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• pp.1273-1300
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• 2024

In the complex virtual environment of cyberspace, comprised of digital and communication networks, ensuring the security of information is being recognized as an ongoing challenge. The importance of 'Cyber Situation Awareness (CSA)' is being emphasized in response to this. CSA is understood as a vital capability to identify, understand, and respond to various cyber threats and is positioned at the heart of cyber security strategies from a defensive perspective. Critical industries such as finance, healthcare, manufacturing, telecommunications, transportation, and energy can be subjected to not just economic and societal losses from cyber threats but, in severe cases, national losses. Consequently, the importance of CSA is being accentuated and research activities are being vigorously undertaken. A systematic five-step approach to CSA is introduced against this backdrop, and a deep analysis of recent research trends, techniques, challenges, and future directions since 2019 is provided. The approach encompasses current situation and identification awareness, the impact of attacks and vulnerability assessment, the evolution of situations and tracking of actor behaviors, root cause and forensic analysis, and future scenarios and threat predictions. Through this survey, readers will be deepened in their understanding of the fundamental importance and practical applications of CSA, and their insights into research and applications in this field will be enhanced. This survey is expected to serve as a useful guide and reference for researchers and experts particularly interested in CSA research and applications.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.1281-1281
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• 2024

About 70% of the data generated on building construction sites consists of unstructured data, such as text, photos, videos, etc. However, the text data, which constitutes the largest proportion of unstructured data, has been restrictively utilized. When using standardized data to evaluate safety performance, there are a few difficulties in addressing issues such as lack of data, omissions, and errors. This copes with limitations on the practical evaluation of safety performance on building construction sites. Despite generating extensive text-centric documents, the previous researches on evaluating safety performance levels using unstructured data are still in its infancy. This study proposes a framework for evaluating the safety performance by preprocessing and refining text-based construction supervision documents. In this framework, relevant keywords related to safety performance are extracted from supervision documents, tokenized, and analyzed for association rules among keywords. Based on the results of the association rule analysis, keywords are selected, and the unsatisfactory or satisfactory level of safety performance is quantified using logistic regression analysis, considering the frequency of their occurrence. While the proposed framework focuses on quantifying the safety performance levels of construction sites, it can be expanded to implement integrated performance diagnostics on-site by linking with tools that evaluate diverse performance levels. This extension will allow for a comprehensive assessment of on-site performance. Furthermore, the framework can serve as a tool supporting practical and proactive inspections and responses of safety managers by utilizing unstructured data alongside the traditional approach focused on standardized data for safety performance assessment.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.711-720
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• 2020

This research aims to analyze the factors affecting the acceptance of social commerce, including performance expectancy, effort expectancy, social support, facilitating conditions, hedonic motivation, habitability, price saving orientation, and privacy concerns using the Unified Theory of Acceptance and Use of Technology (UTAUT2). UTAUT2 has been examined and modified in various contexts. The research model studies the acceptance and use of technology in the context of customers. This study adopts a quantitative method using the partial least squares regression (PLS) approach involving 244 respondents. The respondents are users of social commerce in Indonesia. The result of this research indicates that social influence, facilitating conditions, hedonic motivation, habit, price value orientation, and privacy concerns have a significant effect on behavioral intention. On the other hand, performance expectancy and effort expectancy does not affect behavioral intention. Furthermore, price value has a significant effect on social commerce user behavior. Lastly, facilitating conditions and habits does not affect social commerce user behavior. This research contributes to the development of theory by examining an additional variable, which is privacy concern. This study is significant since social media and social commerce have grown exponentially nowadays. Implications of the results for the development of the theory (UTAUT2) and practice are discussed in the article.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.43-52
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• 2020

This paper examines how macroeconomic variables, such as interest rate differences, inflation, exchange rates, economic growth and external debt growth, affect capital flight in the ASEAN-8 countries. We apply a panel data model with fixed effect estimation for the data for eight countries from the period 1994 to 2018. We use the residual approach used by the World Bank to measure the value of capital flight. The results show that the interest rate differences, exchange rates, economic growth and foreign debt growth had a positive and significant effect on outward capital flight. A further implication of this finding is that the interest rate differences, exchange rate, economic growth and foreign debt growth are factors that trigger an increase in capital outflow in the ASEAN-8 countries. Nonetheless, inflation rate is not considered to be the main factor influencing capital flight, as average inflation in the ASEAN-8 countries remains relatively stable. This paper will be beneficial for policymakers in the ASEAN-8 countries and encourage them to constantly pay attention to these four variables, as they significantly influence capital flight, whereas they can disregard the impact of the inflation variable that is not significant in influencing capital flight.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.481-490
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• 2020

Batik industry is a business activity oriented towards customer loyalty and is demanded to show an increasing diversity of products with various motives designed to prevent customers from moving to other companies. Therefore, the purpose of this study is to develop a theoretical approach in solving problems in the relationship between service quality and product diversity on satisfaction and word of mouth (WoM) and its impact on customer loyalty. Furthermore, this study also examined the mediating effects of satisfaction and WoM in the relationship between service quality and product diversity on customer loyalty. This research's object took the customers of Batik Semarangan Craftwork, Indonesia, with the phenomenon of always developing creative and innovative Batik motif designs that can be accepted by the market without leaving Semarang's uniqueness. The total sample was 98 customers. The results of the study showed that service quality and product diversity positively affected satisfaction and WoM and had a positive effect on customer loyalty. Besides, satisfaction and WoM had a mediating effect on the effect of service quality and product diversity on loyalty. Thus, it is essential for management to create and increase customer loyalty by paying attention to service quality, product diversity, satisfaction, and WoM.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.169-179
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• 2020

This study examines the drivers and implementation of intrapreneurship strategy in a property service company. Using a qualitative case study approach, the study interviewed four managers involved in related intrapreneurship initiatives. The data was validated by an expert and a practitioner from a different company. The implementation of the company's intrapreneurship strategy is limited to improving new ways of working and developing products and services. However, business development and the creation of new business models are still limited. From several intrapreneurship driving factors, it was observed that the company practices are considered adequate with regard to top management support, leadership, flexibility in carrying out work, as well as in fairly harmonious arrangements for ongoing business relationships with the intrapreneurship projects. On the other hand, human resources with entrepreneurial behavior are still minimal. Similarly, the driving factors in reward and training that promote entrepreneurial behavior are also considered to be insufficient. The application of intrapreneurship as a strategy requires understanding and commitment from all parties in the organization. This study provides insight into the Indonesian context and proposes that intrapreneurship initiatives are less likely to succeed if they are not supported by developing a more systematic entrepreneurial mindset, behavior, and culture.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.109-114
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• 2020

The aim of this study is to develop basic artificial neural network models in forecasting the in-sample gross domestic product (GDP) of Malaysia. GDP is one of the main indicators in presenting the macro economic condition of a country as set by the world authority bodies such as the World Bank. Hence, this study uses an artificial neural network-based approach to make predictions concerning the economic growth of Malaysia. This method has been proposed due to its ability to overcome multicollinearity among variables, as well as the ability to cope with non-linear problems in Malaysia's growth data. The selected inputs and outputs are based on the previous literatures as well as the economic growth theory. Therefore, the selected inputs are exports, imports, private consumption, government expenditure, consumer price index (CPI), inflation rate, foreign direct investment (FDI) and money supply, which includes M1 and M2. Whilst, the output is real gross domestic product growth rate. The results of this study showed that the neural network method gives the smallest value of mean error which is 0.81 percent with a total difference of 0.70 percent. This implies that the neural network model is appropriate and is a relevant method in forecasting the economic growth of Malaysia.