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This study aims to investigate how gamification, namely, WeChat’s cultural gifting function, improves emotional involvement among three generations (Y, X and silver) in mobile payments. It draws attention to the beneficial effects of cultural components and digital intimacy on gamified mobile payment systems.

The data were collected from Y, X and silver generation in Dalian, China. The users were well equipped with the WeChat pay features and had experience. The PLS-SEM software was used to assess the data.

The findings show that consumer word of mouth and loyalty are positively impacted by perceived utility, fun, and enjoyment. Besides, gamification components like fun and playfulness have a favourable effect on how useful mobile payments are judged to be. It demonstrates how delighted and ecstatic users are with WeChat Hongbao. In addition, the positive moderation effect of intimacy on the hypothesised connections shows that all three generations are likely to accept gamified money features. These results provide a substantial contribution to our comprehension of gamification in the context of mobile payment services for all three generations.

The study is distinctive because it focuses on how China’s three generations use WeChat Pay for routine transactions. The framework confirms that the gamification elements improve user performance and encourage continued usage of mobile payment systems.

Este estudio investiga cómo la gamificación, específicamente la función de regalos culturales de WeChat, mejora la participación emocional entre tres generaciones (Y, X y plata) en los pagos móviles. Se presta atención a los efectos beneficiosos de los componentes culturales y la intimidad digital en los sistemas de pago móvil gamificados.

Los datos fueron recopilados de las generaciones Y, X y plata en Dalian, China. Los usuarios estaban familiarizados con las características de pago de WeChat y tenían experiencia. Se utilizó el software PLS-SEM para evaluar los datos.

Los resultados muestran que la reputación y la lealtad del consumidor son positivamente influenciadas por la utilidad percibida, la diversión y el disfrute. Los componentes de gamificación, como la diversión y la jugabilidad, tienen un efecto favorable en cómo se juzga la utilidad de los pagos móviles. Se demuestra cuán encantados están los usuarios con WeChat Hongbao. Además, la moderación positiva de la intimidad en las relaciones supuestas muestra que las tres generaciones tienen probabilidades de aceptar las características de dinero gamificado. Estos resultados contribuyen sustancialmente a nuestra comprensión de la gamificación en el contexto de los servicios de pago móvil para las tres generaciones.

El estudio es novedoso ya que se centra en cómo las tres generaciones de China utilizan WeChat Pay para transacciones rutinarias. El marco confirma que los elementos de gamificación mejoran el rendimiento del usuario y fomentan el uso continuado de los sistemas de pago móvil.

本研究探讨了游戏化, 即微信的文化赠送功能, 如何提高三代人（Y、X和银发族）在移动支付中的情感投入。它引起了人们对文化成分和数字亲密关系对游戏化移动支付系统的有益影响的注意。

数据来自中国大连市的Y、X和银发族用户。用户对微信支付功能非常熟悉, 并具有使用经验。采用PLS-SEM软件对数据进行评估。

结果表明, 消费者的口碑和忠诚度受到了感知效用、乐趣和享受的积极影响。乐趣和趣味等游戏化组件对移动支付的有用性评估产生了积极影响, 展示了用户对微信红包的喜悦和兴奋程度。此外, 亲密关系对假设连接的正向调节效应表明, 三代人都可能接受游戏化货币功能。这些结果为我们理解移动支付服务背景下游戏化对三代人的贡献提供了实质性的帮助。

该研究独特之处在于它着眼于中国三代人如何将微信支付用于日常交易。该框架证实了游戏化元素如何提高用户绩效并鼓励继续使用移动支付系统。

Switching power converters for photovoltaic (PV) applications with high gain are rapidly expanding. To obtain better voltage gain, low switch stress, low ripple and cost-effective converters, researchers are developing several topologies.

It was decided to use the particle swarm optimization approach for this system in order to compute the precise PI controller gain parameters under steady state and dynamic changing circumstances. A high-gain q- ZS boost converter is used as an intermittent converter between a PV and brushless direct current (BLDC) motor to attain maximum power point tracking, which also reduces the torque ripples. A MATLAB/Simulink environment has been used to build and test the positive output quadratic boost high gain converters (PQBHGC)-1, PQBHGC-8, PQBHGC-4 and PQBHGC-3 topologies to analyse their effectiveness in PV-driven BLDC motor applications. The simulation results show that the PQBHGC-3 topology is effective in comparison with other HG cell DC–DC converters in terms of efficiency, reduced ripples, etc. which is most suitable for PV-driven BLDC applications.

The simulation results have showed that the PQBHGC-3 gives better performance with minimum voltage ripple of 2V and current ripple of 0.4A which eventually reduces the ripples in the torque in a BLDC motor. Also, the efficiency for the suggested PQBHGC-3 for PV-based BLDC applications is the best with 99%.

This study is the first of its kind comparing the different topologies of PQBHGC-1, PQBHGC-8, PQBHGC-4 and PQBHGC-3 topologies to analyse their effectiveness in PV-driven BLDC motor applications. This study suggests that the PQBHGC-3 topology is most suitable in PV-driven BLDC applications.

This study aims to determine the antecedents that influence attitudes towards the use of environmentally friendly household appliance products and consumers' green purchase intention among consumers in Harare, Zimbabwe.

Data were collected from 329 consumers in Harare, Zimbabwe's commercial capital who were served from five using a structured questionnaire via an online web-based cross-sectional survey. Hypothesised relationships were tested through structural equation modelling with the aid of Smart PLS software.

Green product awareness, social influence, perceived benefit and attitude towards green appliances were found to have a significant positive effect on green purchase intention.

The study's findings may not be generalised to other contexts as sample data was only collected in Zimbabwe. Complementary cross-sectional research studies can be done in other parts of the world to enable cross-cultural comparisons and methodological validations.

The green appliance and energy saving practices are vastly growing, with many multinational appliance companies introducing green products within their product lines and adopting the concept of sustainability through modifications in production, design and consumption of household appliance products that encompass fewer harmful consequences on the environment in response to their concerns about the scarcity of natural resources, environmental well-being and the potential detriment of future generations.

Notwithstanding the limitations of the current study, the results have the potential to contribute to an improved understanding of influence attitudes towards the use of environmentally friendly household appliance products.

This study aims to examine the impact of website design, reliability and perceived ease of use as an engagement motivational factors on customer e-trust and e-retention in online shopping.

By using deductive approach, quantitative methods and purposive sampling technique, this study has collected the data from 295 young online customers to enhance an understanding of website design, reliability and perceived ease of use in an online shopping context.

The findings revealed interesting insights where reliability is the most significant predictor of customer e-trust in online shopping, followed by perceived ease of use and website design. In addition, a significant mediating effect of e-trust is found between customer e-retention, website design, reliability and perceived ease of use.

Future research is recommended to predict the antecedents of online engagement motivational factors with value co-creation and co-creation experience in online shopping context.

This study offers fresh insights about driving elements and impediments of online customer retention. Customer engagement comprising of website design, reliability and perceived ease of use appear to influence the online customer retention through direct and indirect effect.

Building on the resource-based view (RBV) and the theory of other orientation, this study aims to examine the association between Islamic work ethics (IWEs) and organizational performance highlighting the role of employee relations climate as an underlying mechanism.

Data were collected from 239 employees working in diverse sectors in the state of Qatar. Structural equation modeling of partial least squares was used to analyze the data of the study.

The results suggest that IWEs positively impact organizational performance and employee relations climate. Furthermore, employee relations climate demonstrated to play a mediating role in the IWEs-organizational performance link.

The study can be used by administrators pertaining to the importance of IWE and employee relations climate to cultivate higher organizational outcomes such as organizational performance.

This research is distinctive as it examines the connection between IWEs and organizational performance in Qatar, a country where the influence of Islamic values and beliefs on work ethics is profound. In addition, the research sheds light on a topic that has received little attention in the literature: the significance of the workplace climate in determining how IWEs affect organizational performance. Finally, the research integrates two important theoretical frameworks, the RBV and the theory of other orientation, to create a comprehensive model that explains the complex relationship between IWEs, employee relations climate and organizational performance.

The main purpose of this research is to examine the impact of institutional quality and sectoral employment on environmental degradation in developing countries. This paper also re-examined the validity of the Environmental Kuznets Curve (EKC) hypothesis and estimated the long run impact of explanatory variables on CO₂ emissions.

In this paper, the balanced panel data for the period 2002–2016 was used based on data availability and applied two-step SYS-GMM estimators.

The results showed that institutional quality such as government effectiveness (GE) and the rule of law (RL) reduce CO₂ emissions and promote environmental quality in developing countries. Interestingly, the authors found new evidence that employment in agriculture and industry has a positive impact on pollution, while employment in the service sector was negatively associated with CO₂ emissions, and the validity of the EKC hypothesis was confirmed. In addition, the research suggests that strong institutional frameworks and their effective implementation are the most important panacea and should be treated as a top priority to counteract environmental degradation and achieve the UN Sustainable Development Goals.

This is the first study to examine the short run and long run effects of institutional quality and sectoral employment on environmental degradation using the balanced panel data for a large sample of developing countries. This paper also used a special technique of Driscoll and Kraay standard error approach to confirm the robustness results and showed the different roles of sectoral employment on environmental quality.

In time and accurate detection of cancer can save the life of the person affected. According to the World Health Organization (WHO), breast cancer occupies the most frequent incidence among all the cancers whereas breast cancer takes fifth place in the case of mortality numbers. Out of many image processing techniques, certain works have focused on convolutional neural networks (CNNs) for processing these images. However, deep learning models are to be explored well.

In this work, multivariate statistics-based kernel principal component analysis (KPCA) is used for essential features. KPCA is simultaneously helpful for denoising the data. These features are processed through a heterogeneous ensemble model that consists of three base models. The base models comprise recurrent neural network (RNN), long short-term memory (LSTM) and gated recurrent unit (GRU). The outcomes of these base learners are fed to fuzzy adaptive resonance theory mapping (ARTMAP) model for decision making as the nodes are added to the F_2ˆa layer if the winning criteria are fulfilled that makes the ARTMAP model more robust.

The proposed model is verified using breast histopathology image dataset publicly available at Kaggle. The model provides 99.36% training accuracy and 98.72% validation accuracy. The proposed model utilizes data processing in all aspects, i.e. image denoising to reduce the data redundancy, training by ensemble learning to provide higher results than that of single models. The final classification by a fuzzy ARTMAP model that controls the number of nodes depending upon the performance makes robust accurate classification.

Research in the field of medical applications is an ongoing method. More advanced algorithms are being developed for better classification. Still, the scope is there to design the models in terms of better performance, practicability and cost efficiency in the future. Also, the ensemble models may be chosen with different combinations and characteristics. Only signal instead of images may be verified for this proposed model. Experimental analysis shows the improved performance of the proposed model. This method needs to be verified using practical models. Also, the practical implementation will be carried out for its real-time performance and cost efficiency.

The proposed model is utilized for denoising and to reduce the data redundancy so that the feature selection is done using KPCA. Training and classification are performed using heterogeneous ensemble model designed using RNN, LSTM and GRU as base classifiers to provide higher results than that of single models. Use of adaptive fuzzy mapping model makes the final classification accurate. The effectiveness of combining these methods to a single model is analyzed in this work.