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Prior studies have put much emphasis on using the uses and gratification (U&G) theory to find out why people use games, social media, the Internet, e-shopping, etc. Despite past research efforts, the root causes underlying this phenomenon still need to be discovered as to why people use interactive virtual rides (vrides) entertainment services, especially when incorporating the hedonic consumption perspective (i.e. playful-consumption experiences). Considering the knowledge gap in the vrides’ context, this study aims to use the UGT to find out why people use the vrides entertainment service from a hedonic consumption point of view.

With 217 usable responses, the research model was tested using partial least squares-based structural equation modeling (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA).

Findings reveal that only perceived enjoyment, arousal and sensory experience derive continuous intention behavior to consume vride entertainment service. Findings using the fsQCA revealed multiple causal configurations for the proposed outcome.

This study contributes to extending the assumption of UGT via incorporating the hedonic consumption perspective to explore the potential motives and intention to consume vrides entertainment services. Our study also discusses the important theoretical/practical implications of our findings. Besides, this study is unique because it shows both symmetrical and asymmetrical connections that help us understand why people keep using vrides entertainment service.

There has been a dramatic rise in the use of online food delivery apps (FDAs) services since the COVID-19 pandemic. Though online FDAs have contributed significantly to the rise in demand for products from the gourmet industry, little is known regarding the factors that inspire customers to order from online FDAs, subsequently influencing customers’ satisfaction. Considering the knowledge gap, this study utilizes the stimulus-organism-response (S-O-R) model to conceptualize the factors: stimuli (eWOM, online reviews and online deals as external stimuli, and late-night craving and convenience as internal stimuli) that determine the organism level (i.e. customers’ inspiration) to subsequently generate the response (i.e. customers’ satisfaction).

We collected the data from 388 users and analyzed it via partial least squares – structural equation modeling (PLS-SEM).

The results reveal that online reviews, deals, late-night food cravings and convenience positively determine customers’ inspiration and satisfaction. In contrast, eWOM fails to impact customers’ inspiration directly and indirectly, affecting customers’ satisfaction through inspiration. Besides, customers’ inspiration positively mediates the relationship between stimuli (e.g. online reviews, online deals, late-night cravings and convenience) and customers’ satisfaction.

This study is novel in that it explores the impact of internal (late-night craving and convenience) and external (eWOM, online reviews and online deals) stimuli on customer inspiration and subsequently predicts customer satisfaction. We also expand prior studies on food delivery apps by studying customer inspiration as a mediating mechanism between internal and external stimuli and customer satisfaction.

Students’ academic achievement is a multifaceted phenomenon. While depression can suppress academic performance, academic satisfaction can promote it. This study aims to investigate the relationship between depression and academic satisfaction among students studying at Shahroud University of Medical Sciences.

This cross-sectional study was carried out on 312 undergraduate students of Shahroud University of Medical Sciences. Data collection tools included demographic data form, University Student Depression Inventory and academic satisfaction scale. Data were collected by a simple random sampling method and self-reporting by the participants. Data were analyzed using descriptive and inferential statistics (multivariate multiple regression analysis and multivariate linear regression).

The participants’ mean depression and academic satisfaction scores were 71.92 ± 22.94 and 53.70 ± 9.69, respectively. In addition, the depression score was significantly and inversely correlated with students' academic satisfaction (r = −0.122, p-value = 0.031). Moreover, there was a significant correlation between students’ depression with marital status, level of the semester, interest in the field of study and study topic.

This study emphasizes improving education, spiritual and social support and strengthens strategies to deal with depression and medical science students’ related factors.

Students of medical sciences are exposed to depression during their college years, which is related to their academic satisfaction.

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

This paper aims to utilize an extended involvement-commitment and trust commitment model to examine post-consumption decisions related to food delivery app use.

A self-administered online survey was used to collect data from food delivery app users in the USA.

Findings validate a favorable role of perceived app security and menu description on trust in app recommendations. Trust was found to be positively related to involvement, commitment and willingness to provide feedback. The positive moderating role of perceived convenience and rewards and incentives was also confirmed in relation to consumers’ trust in app recommendations, and involvement and commitment

A key contribution of this study includes the development of a comprehensive model to understand postconsumption decisions related to the usage of food delivery apps. To the best of the authors’ knowledge, this study is also the first to unveil the antecedent and moderating factors related to food delivery app users’ willingness to provide feedback, share personal data and to pay more.

Customer differences and similarities play a crucial role in service operations, and service industries need to develop various strategies for different customer types. This study aims to understand the behavioral pattern of customers in the banking industry by proposing a hybrid data mining approach with rule extraction and service operation benchmarking.

The authors analyze customer data to identify the best customers using a modified recency, frequency and monetary (RFM) model and K-means clustering. The number of clusters is determined with a two-step K-means quality analysis based on the Silhouette, Davies–Bouldin and Calinski–Harabasz indices and the evaluation based on distance from average solution (EDAS). The best–worst method (BWM) and the total area based on orthogonal vectors (TAOV) are used next to sort the clusters. Finally, the associative rules and the Apriori algorithm are used to derive the customers' behavior patterns.

As a result of implementing the proposed approach in the financial service industry, customers were segmented and ranked into six clusters by analyzing 20,000 records. Furthermore, frequent customer financial behavior patterns were recognized based on demographic characteristics and financial transactions of customers. Thus, customer types were classified as highly loyal, loyal, high-interacting, low-interacting and missing customers. Eventually, appropriate strategies for interacting with each customer type were proposed.

The authors propose a novel hybrid multi-attribute data mining approach for rule extraction and the service operations benchmarking approach by combining data mining tools with a multilayer decision-making approach. The proposed hybrid approach has been implemented in a large-scale problem in the financial services industry.

This paper aims to investigate Supply Chain (SC) Performance Measurement Systems (PMSs) (SCPMSs) that are suitable and applicable to evaluate SC performance during unexpected events such as global pandemics. Furthermore, the contribution of Industry 4.0 Disruptive Technologies (IDTs) to implement SCPMSs during such Black Swan events is investigated in this study.

The research methodology is based upon a novel qualitative and quantitative mixed-method. A Systematic Literature Review (SLR) was initially employed to identify two complete lists of SCPMSs and IDTs. Then, a novel Interval-Valued Intuitionistic Hesitant-Fuzzy (IVIHF)-Delphi method was firstly developed in this paper to screen the extracted SCPMSs. Afterward, the Propriety, Economic, Acceptable, Resource, Legal (PEARL) indicator of the Hanlon method was innovatively applied to prioritize the identified IDTs for each finalized SCPMS.

Two high-score SCPMSs including the SC operations reference (SCOR) model and sustainable SCPMS were recommended to improve measuring the performance of the pharmaceutical SC of emerging economies such as Iran in which the societal, biological and economic issues were undeniable, particularly during unexpected events. Employing nine IDTs such as simulation, big data analytics, cloud technologies, etc., would facilitate implementing sustainable SCPMS from distinct perspectives.

This is one of the first papers to provide in-depth insights into determining the priority of contribution of IDTs in applying different SCPMSs during global pandemics. Proposing a novel multi-layer mixed-methodology involving SLR, IVIHF-Delphi, and the PEARL indicator of the Hanlon method is another originality offered by this paper.

This paper proposes a multi-layer hybrid decision-making approach to evaluate the capability alternatives for developing a collaborative network to operate in the international market.

The present study is contextualised in the Iranian pistachio export industry. An extensive review of the state-of-the-art literature on supplier collaboration was conducted to identify key capabilities that are essential to establish a collaborative network. The set of defined capabilities were then optimised through interviews with 14 experts from the relevant industry, academics and export authorities. A combination of the fuzzy Delphi method and the best–worst method (BWM) approach was, respectively, used to reduce the number of capability alternatives and assign priority weights to these alternatives. Subsequently, a weighted aggregated sum product assessment method (WASPAS) was employed to rank and evaluate the ability to creating a collaborative network for the export of pistachio.

From the extant literature review, 18 capabilities for the formation of coordination networks in the international markets were identified. Then, the prominent indicators in forming a global network were extracted. After ranking the top pistachio export countries/regions to formalise an efficient collaborative network, it was revealed that although Iran exports approximately 30% of the global market, it falls behind the USA and European Union. The competitors have scored higher in critical criteria, including “trust and commitment”, “strategy and management”, “managerial control and standardization” and “financial resources”.

The proposed hybrid approach encompassing fuzzy Delphi–BWM–WASPAS offers to solve the capability evaluation and selection as well as ranking the possible alternative to formalise a collaborative network in an integrated fashion. This combination of methods is capable to first identify the most important factors, then measuring their importance and eventually rank the possible alternatives. The suggested framework provides an approach to deal with the uncertainty of global collaborative network formation.