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The purpose of this paper is to propose a soft computing model based on multi-objective evolutionary algorithm (MOEA), namely, modified micro genetic algorithm (MmGA) coupled with a decision tree (DT)-based classifier, in classifying and optimising the students’ online interaction activities as classifier of student achievement. Subsequently, the results are transformed into useful information that may help educator in designing better learning instructions geared towards higher student achievement.

A soft computing model based on MOEA is proposed. It is tested on benchmark data pertaining to student activities and achievement obtained from the University of California at Irvine machine learning repository. Additional, a real-world case study in a distance learning institution, namely, Wawasan Open University in Malaysia has been conducted. The case study involves a total of 46 courses collected over 24 consecutive weeks with students across the entire regions in Malaysia and worldwide.

The proposed model obtains high classification accuracy rates at reduced number of features used. These results are transformed into useful information for the educational institution in our case study in an effort to improve student achievement. Whether benchmark or real-world case study, the proposed model successfully reduced the number features used by at least 48 per cent while achieving higher classification accuracy.

A soft computing model based on MOEA, namely, MmGA coupled with a DT-based classifier, in handling educational data is proposed.

In a changing trade landscape, global trade transaction relies on a global supply-chain network. Customs clearance to cross borders is critical to enhancing the competitiveness of both importers and exporters. As such, each country has adopted an authorized economic operator (AEO) program to promote the security of both imported and exported cargo as well as expedite freight movements. The purpose of this paper is to discover the factors which should be taken into account to utilize an AEO program, and to look at the causal relations between these factors.

This study conducted a survey on 201 AEO programs in Korea. With partial least squares, the structure model is tested using the coefficient value of the determination of the dependent variable, explained by the sign and scale of the path coefficient, statistical significance, and leading variable. Moreover, this study performed bootstrap re-sampling to verify all paths and significance.

It was found that AEO external pressure, training capacity, and sustainability are shown to have a significant impact on AEO performance. Furthermore, for the group with a high level of AEO application, training capacity and AEO sustainability are shown to have a greater effect on AEO performance. For the group with a low level of AEO application, internal regulation is shown to have a bigger impact on AEO performance.

This study sets itself apart from previous ones in that it examines AEO application for trade security and facilitation with regard to customs, which would affect global supply-chain management.

The purpose of this study is to elucidate the factors that underlie the differences in individual absorptive capacity (ACAP) within the context of joint project teams, following the individual-level perspective on potential ACAP.

The model was empirically validated through structural equation modeling conducted on a cross-sectional survey of 248 local team members of joint projects in the Nigerian upstream oil industry.

Prior experience and learning goal orientation are positively associated with the ability to assimilate knowledge, whereas performance approach goal orientation and need for cognition are positively associated with the ability to recognize the value of knowledge. Surprisingly, no significant relationship exists between prior experience and ability to recognize the value of knowledge. In addition, the positive relationship between ability to recognize the value of knowledge and ability to assimilate knowledge is supported.

This study contributes to the empirical justification of the role of individuals in acquiring and assimilating external knowledge, and extends classroom-based constructs (i.e. need for cognition and goal orientation) to the project domain.

This study aims to empirically examine the conditions for latecomers to successfully pursue path-creating catch-up strategies. In particular, the company is divided into two conditions: the external environment, which refers to the gap in the market share between the leaders and latecomers, and the internal capacities of the company, such as the company’s absorptive capacity, re-combinative capabilities and technological innovation leadership.

Because firms supported by the government tend to be conservative in their decision-making and technology development strategies, governmental assistance is likely to negatively affect path-creating catch-up strategies. This study surveyed small to medium enterprises in the Korea IT industry and analyzed the latecomers’ catch-up strategies from internal and external environment perspectives.

After ensuring its innovation capacity by developing of internal capacity, it turned out to lead to path-creative catch-up strategy and market disparity and government dependence moderates this relation. While market disparity has a positive moderation effect, government dependence showed a negative moderation effect.

The authors proposed and tested hypotheses of how a firm’s path-creative catch-up strategy is adopted and succeeds. Regarding the internal conditions, the authors statistically proved that absorptive capabilities, re-combinative capabilities and technology innovation leadership are important factors for a firm’s technology innovation capacity.

This study aims to investigate how artificial intelligence (AI)-powered smart home devices affect young consumers' requirements for convenience, support, security and monitoring, as well as their ability to advance environmental sustainability. This study also examines the variables that impact users' motivation to use AI-powered smart home devices, such as perceived value, ease of use, social presence, identity, technology security and the moderating impact of trust.

The responses from residents of Sarawak, Malaysia, were collected through online questionnaires. This study aimed to examine the perceptions of millennials and zillennials towards their trust and adoption of AI-powered devices. This study used a quantitative approach, and the relationships among the study constructs were analysed using partial least squares - structural equation modelling.

The present study found that perceived usefulness, ease of use and social presence were the main motivators among actual and potential users of smart home devices, especially in determining their intentions to use and actual usage. Additionally, there was a moderating effect of trust on the relationship between perceived ease of use, social presence, social identity and intention to use AI-powered devices in smart homes.

To the best of the authors’ knowledge, this is one of the first studies to examine the factors influencing smart technology adoption. This study provided meaningful insights on the development of strategies for the key stakeholders to enhance the adoption and usage of AI-powered smart home devices in Sarawak, one of the promising Borneo states. Additionally, this study contributed to the growing body of knowledge on the associations between technology acceptance model dimensions, intention and actual usage of smart technology, with the moderating impact of trust.

The purpose of this paper is to understand the factors that determine the knowledge exchange intention and behavioural nature of academics by the help of social media tools in the Indian higher education.

This study has used valance–instrumentality–expectancy (VIE) theory to determine the knowledge exchange behaviour of academics. The study has considered the effects of knowledge contributor (KC) and knowledge seeker (KS) as moderators. The model has been validated by using a survey with 320 usable respondents.

The results highlight that if the stakeholders of higher education institutions feel the deficits of knowledge exchange, they realize importance of knowledge sharing and use social media to increase effect of knowledge exchange. Besides, perceived usefulness impacts on the use of social media for knowledge exchange by the concerned stakeholders. Moreover, it is observed that experience of the use of social media impacts the use of this tool for knowledge exchange.

The use and application of VIE theory have successfully been able to interpret the factors affecting use of social media for knowledge exchange in higher educational institutes. The use of VIE theory has also been able to explain the proposed model better as the model could achieve a high explanative power (87%).

This study has provided meaningful insights to the practitioners and policymakers to realize how the stakeholders of the higher education institutions in India can be motivated to feel the need of sharing of knowledge and how they can use social media with ease for this purpose.

Not much research has been conducted with regard to the usage of social media as a tool for knowledge sharing in higher education sector in India. In that sense, this study is a novel attempt to undertake such research.