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This paper aims to develop flame-retardant (FR) polyamide 12 (PA12) nanocomposite from regenerated powder via selective laser sintering (SLS), an additive manufacturing technique.

First, the morphology, processibility, thermal and mechanical properties of PA12 regenerated powder, consisting of 50 wt% new and 50 wt% recycled powder, as well as corresponding printed specimens, were evaluated to characterize the effects of previous SLS processing. Second, flame-retardant PA12 was developed by incorporating both single and binary halogen-free flame retardants into the regenerated powder.

It was found that the printed specimens from regenerated powder had much higher tensile and impact properties compared to specimens made from new powder, which is attributed to better particulate fusion and coalescence realized in higher temperature SLS printing. The effect of FRs on thermal, mechanical and flame retardant properties of the PA12 composites/nanocomposites was investigated systematically. It was found that the nanoclay, as a synergist, improved both flame-retardant and mechanical properties of PA12. UL94 standard rating of V-0 was achieved for the printed nanocomposite by incorporating 1 wt% nanoclay into 15 wt% phosphinates FR. Moreover, on average, the tensile and impact strength of the nanocomposite were increased by 26.13% and 17.09%, respectively, in XY, YZ and Z printing orientations as compared to the equivalent flame retardant composite with 20 wt% of the phosphinates FR.

This paper fulfills the need to develop flame retardant parts via SLS technology with waste feedstock. It also addresses the challenge of developing flame retardant materials without obviously compromising the mechanical properties by making use of the synergistic effect of nanoclay and organic phosphinates.

The purpose of this paper is to develop a proof-of-concept (POC) Forward Collision Warning (FWC) system for the motorcyclist, which determines a potential clash based on time-to-collision and trajectory of both the detected and ego vehicle (motorcycle).

This comes in three approaches. First, time-to-collision value is to be calculated based on low-cost camera video input. Second, the trajectory of the detected vehicle is predicted based on video data in the 2 D pixel coordinate. Third, the trajectory of the ego vehicle is predicted via the lean direction of the motorcycle from a low-cost inertial measurement unit sensor.

This encompasses a comprehensive Advanced FWC system which is an amalgamation of the three approaches mentioned above. First, to predict time-to-collision, nested Kalman filter and vehicle detection is used to convert image pixel matrix to relative distance, velocity and time-to-collision data. Next, for trajectory prediction of detected vehicles, a few algorithms were compared, and it was found that long short-term memory performs the best on the data set. The last finding is that to determine the leaning direction of the ego vehicle, it is better to use lean angle measurement compared to riding pattern classification.

The value of this paper is that it provides a POC FWC system that considers time-to-collision and trajectory of both detected and ego vehicle (motorcycle).

This paper explores the reasons behind the slow uptake of mobile payment (m-payment) from a switching intention (SI) perspective. The antecedents of SI from cash to m-payment were explored using an integrated conceptual model of the push-pull-mooring (PPM) framework and the status quo bias (SQB) perspective.

A self-administered survey was used to collect data, which are empirically tested using SmartPLS 3.0.

The push factor was found to have an insignificant effect on SI to m-payment whereas the pull factor was significant. Furthermore, the results revealed that the two mooring variables have contrasting results as trust is not a significant determinant of SI to m-payment while perceived security and privacy (PSP) is. Additionally, all SQB-related relationships were found to be statistically significant

This study determined the factors that play vital roles in the consumers' decision-making to transition from cash to m-payment. This was done via a uniquely developed conceptual model that incorporated the PPM framework with the SQB perspective.

Ever since its emergence, the metaverse has presented opportunities and disruptions to every stakeholder, including individual users and organizations. This article aims to offer valuable perspectives on six identified critical areas that the metaverse could significantly impact: marketing ethics, marketing communication, relationship marketing, retail marketing, supply chain management and transportation management.

Through a multi-perspective approach, this paper gathers valuable perspectives from various invited contributors to each of the six identified key areas that the metaverse could significantly impact.

For each key area identified, the invited contributors first share their valuable perspectives by discussing the roles of the metaverse. Subsequently, the invited contributors discuss their views on vital opportunities, challenges and research agenda concerning the metaverse.

With the widespread metaverse, it is expected that each key area identified is likely to undergo significant levels of disruption. Against this backdrop, this paper contributes to the academic literature and industry by gathering different perspectives from invited contributors on the relevance of the metaverse in marketing and logistics domains.

This study aims to examine the effects of voice enthusiasm (enthusiastic voice vs calm voice) on social ratings of the speaker, cognitive load and transfer performance in multimedia learning.

Two laboratory experiments were conducted in which learners learned from a multimedia presentation about computer algorithm that was narrated by either an enthusiastic human voice or a calm human voice.

Results from Experiment 1 revealed that the enthusiastic voice narration led to higher social ratings of the speaker and transfer performance when compared to the calm voice narration. Experiment 2 demonstrated that the enthusiastic voice led to higher affective social ratings (human-like and engaging) and transfer performance as compared to the calm voice. Moreover, it was shown that a calm voice prompted a higher germane load than an enthusiastic voice, which conforms to the argument that prosodic cues in voice can influence processing in multimedia learning among non-native speakers.

This study extends from prior studies that examined voice effects related to mechanization, accent, dialect, and slang in multimedia learning to examining the effects of voice enthusiasm in multimedia learning.

This study aims to look into the role of gamification as an effective marketing tool to engage with consumers and influence purchase behaviours. As there are a plethora of gamified elements, it is crucial to determine which of them can significantly facilitate consumer purchase behaviour. Therefore, a unique stimulus–organism–response (SOR) framework which encompasses four popular gamified elements (i.e. fun, rewards, competition and badges) was employed to investigate consumers’ engagement.

An online survey was utilized to collect the data which yielded 307 responses. Subsequently, partial least squares-structural equation modeling (PLS-SEM) was used to analyse the data.

Among the gamification elements assessed in this study, fun was revealed to be the strongest facilitating antecedent of shopping engagement. However, reward was revealed to have an insignificant effect on shopping engagement. In addition, it was found that consumers undergo a processual development with regard to their impulse buying of retail food products. More precisely, shopping engagement is a significant facilitator of customer satisfaction which subsequently motivates impulse buying.

This is among the pioneering studies to provide detailed insights into the effect of different gamified elements on consumer engagement. Furthermore, a number of practical and theoretical implications for the relevant stakeholders were discussed.

The COVID-19 pandemic has brought about significant changes to the lives of many people. One of which is the accelerated digitalization in the commerce sector. Hence, this study looks to determine the antecedents that affect users' mobile shopping actual use during a pandemic.

The research model was founded on the integration of the Protection Motivation Theory and Transactional Theory of Stress. This is in addition to further extending the integrated research model with other constructs to develop a multi-dimensional framework that accounted for the health, personal, technological and social dimensions. The data was collected from users of mobile shopping through an online survey which was then analyzed via Partial Least Squares–Structural Equation Modeling.

This study provides empirical support to establish the major role of COVID-19 pandemic in affecting the actual usage of mobile shopping. Furthermore, the determinants of actual usage of mobile shopping were found to be multi-dimensional. In particular, the Importance-Performance Map Analysis revealed that emphasis should be place on perceived vulnerability.

As other studies focused on users' intentions, this study looked into the factors that influence the actual usage of mobile shopping. Furthermore, this study emphasizes on the contextualization of time and situation in addition to a multi-dimensional approach toward the subject matter. Overall, this study offers practical insights to stakeholders to better tailor their mobile shopping services in times of a pandemic and advances the literature on actual usage of mobile shopping.

The purpose of this paper is to develop an integrated approach for a green product cradle-to-cradle (C2C) fuzzy recycling production planning model.

This paper applies the failure mode and effects analysis technique and Taguchi experimental design method, develops a green product C2C performance evaluation system that considers the fuzzy impacts of environmental laws and regulations, green goodwill, and environmental efficiency of targeting countries, and decides both the optimal green production plan and estimated optimal life cycles.

This study compares the different degree of maturity in environmental regulations, and various recycling situations are simulated to demonstrate the successful applicability of the proposed model as well as the incentive policy for Taiwan, the USA and Bangladesh.

Previous studies failed both to develop a holistic recycling production plan which is able to consider both the optimal combination of recycled components used and final green products produced with the maximum total resultant sales profit and to consider the potential failure phenomenon of recycled components adopted in the final product. Furthermore, most prior studies ignored the influence of environmental law, goodwill of the product and the efficiency of recycling mechanism of the community.

This study develops an integrated zero waste discharge planning approach for improving resource efficiency in a pulp-and-paper manufacturing firm.

The objectives of this study are to (1) identify the environmental, technical and social metrics in resource efficiency; (2) utilize fuzzy multi-objective programming and the hybrid particle swarm optimization algorithm to solve the fuzzy problem; and (3) develop an assessment for resource efficiency improvement in an industrial case study.

The findings demonstrate the superiority of hybrid particle swarm optimization algorithm in generating optimal results for a pulp-and-paper manufacturing firm.

The findings demonstrate the superiority of hybrid particle swarm optimization algorithm in generating optimal results for a pulp-and-paper manufacturing firm.

Resource efficiency is a multi-objective problem in an uncertain environment. In particular, zero waste discharge planning involves minimizing the total cost and maximizing the waste material recovery rate, wastewater reuse, and waste heat recovery.