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The halal food market is a large and fast-growing market. To maintain and boost the growth of the halal food industry, scholars have attempted to understand the behaviour of Muslims and non-Muslims towards halal food. To advance understating of previous studies on behaviour towards halal food and shedding light on future studies, this study aims to systematically review the literature.

A sample of 985 peer-reviewed papers was extracted from Scopus and Web of Science databases. A total of 96 articles related to customers' behaviour towards halal food by reviewing the titles, abstracts and contents of the extracted articles were identified and reviewed.

This study illustrates: (i) various research designs and methodology used in halal food context, (ii) theories that researchers used to explain customer behaviour towards halal food, (iii) most tested behaviours and (iv) determinants of customer behaviour towards halal food.

The findings provide deep insights into the current state of halal food literature. This paper highlights many gaps in the literature and suggests directions for future studies to advance the understanding of customer behaviour towards halal food. This study will help researchers to identify the new dimensions of research and contribute to the literature.

Despite the fact that the success of e-government services is contingent on their continuous usage, the continuance intention to use e-government services has received extremely little scholarly attention. This study aims to investigate the determinants of the residents’ continuous intention to use e-government services.

The research model was developed based on the integration of technology continuance theory along with trust, transparency and habit constructs. The authors adopted a survey approach to collect the data. The data were collected using an online questionnaire from 260 residents of Penang in Malaysia.

Results revealed that transparency has a positive effect on both perceived usefulness and trust. Contrary to earlier studies on e-government, perceived ease of use was found to have no significant relationship with residents' perceived usefulness. Similarly, the results also demonstrated that habit was not significantly related to users’ continuous intention to use e-government services. This study also applied importance-performance analysis map analysis and discovered that perceived usefulness has the highest impact on continuous intention to use e-government services, whereas satisfaction was found to have the least effect.

This study used an integrative framework and presented an in-depth knowledge of the basic aspects that contribute to the post-adoption usage process and resident satisfaction, trust and attitude towards e-government services.

The purpose of this study is to unearth the factors that influence tourists’ revisit intention. The proposed model of the study is grounded on using the theory of planned behaviour (TPB) and extending it with additional variables, i.e. satisfaction, destination image, perceived risk, service quality and perceived value.

This study adopted a cross-sectional approach to collect data. The data were collected by conducting a field survey questionnaire on 330 respondents and were analysed using partial least squares version 3.2.9.

The results show that perceived behavioural control, perceived value, destination image and satisfaction significantly affect visitors’ revisit intention. The influence of perceived value, perceived service quality and destination image on satisfaction is also confirmed. On the other hand, satisfaction is found to be a significant mediator between perceived service quality, destination image and perceived value.

The extended TPB model that includes perceived service quality, perceived value, perceived risk and satisfaction provided a model with a theoretical basis to explain tourist revisit intentions to a tourist destination.

El objetivo principal del estudio es descubrir los factores que influyen en la intención de revisita de los turistas. El modelo propuesto para el estudio se basa en el uso de la teoría del comportamiento planificado y se amplía con variables como la satisfacción, la imagen del destino, el riesgo percibido, la calidad del servicio y el valor percibido.

Este estudio adoptó un enfoque transversal para la recogida de datos. Los datos se recopilaron mediante un cuestionario de campo en el que participaron 330 encuestados. Los datos se analizaron utilizando la versión 3.2.9 de PLS.

Los resultados muestran que el control conductual percibido, el valor percibido, la imagen del destino y la satisfacción afectan significativamente a la intención de revisita. También se confirma la influencia del valor percibido, la calidad de servicio percibida y la imagen del destino sobre la satisfacción. Por otra parte, la satisfacción resulta ser un mediador significativo entre la calidad de servicio percibida, la imagen del destino y el valor percibido.

El modelo TPB ampliado que incluye la calidad de servicio percibida, el valor percibido, el riesgo percibido y la satisfacción proporcionó un modelo con una base teórica para explicar las intenciones de revisita de los turistas a un destino turístico.

本研究的目的是揭示影响游客重访意向的因素。本研究提出的模型以计划行为理论（TPB）为基础, 并以额外的变量（即满意度、目的地形象、感知风险、服务质量和感知价值）进行扩展。

本研究采用了横断面的方法来收集数据。通过对330名受访者进行实地调查问卷来收集数据, 并使用偏最小二乘法3.2.9版进行分析。

结果显示, 感知行为控制、感知价值、目的地形象和满意度对游客的再访意向有显著影响。感知价值、感知服务质量和目的地形象对满意度的影响也被证实。另一方面, 满意度被发现是感知服务质量、目的地形象和感知价值之间的一个重要中介因素。

包括感知服务质量、感知价值、感知风险和满意度在内的扩展TPB模型为解释游客对旅游目的地的再访意向提供了理论基础。

关键词: 满意度; 旅游; 计划行为理论; PLS-SEM; 目的地形象

Machine learning (ML) techniques are increasingly important in enabling business-to-business (B2B) companies to offer personalized services to business customers. On the other hand, humans play a critical role in dealing with uncertain situations and the relationship-building aspects of a B2B business. Most existing studies advocating human-ML augmentation simply posit the concept without providing a detailed view of augmentation. Therefore, the purpose of this paper is to investigate how human involvement can practically augment ML capabilities to develop a personalized information system (PIS) for business customers.

The authors developed a research framework to create an integrated human-ML PIS for business customers. The PIS was then implemented in the energy sector. Next, the accuracy of the PIS was evaluated using customer feedback. To this end, precision, recall and F1 evaluation metrics were used.

The computed figures of precision, recall and F1 (respectively, 0.73, 0.72 and 0.72) were all above 0.5; thus, the accuracy of the model was confirmed. Finally, the study presents the research model that illustrates how human involvement can augment ML capabilities in different stages of creating the PIS including the business/market understanding, data understanding, data collection and preparation, model creation and deployment and model evaluation phases.

This paper offers novel insight into the less-known phenomenon of human-ML augmentation for marketing purposes. Furthermore, the study contributes to the B2B personalization literature by elaborating on how human experts can augment ML computing power to create a PIS for business customers.