Search results

The purpose of this study is to make property price forecasts for the Chinese housing market that has grown rapidly in the last 10 years, which is an important concern for both government and investors.

This study examines Gaussian process regressions with different kernels and basis functions for monthly pre-owned housing price index estimates for ten major Chinese cities from March 2012 to May 2020. The authors do this by using Bayesian optimizations and cross-validation.

The ten price indices from June 2019 to May 2020 are accurately predicted out-of-sample by the established models, which have relative root mean square errors ranging from 0.0458% to 0.3035% and correlation coefficients ranging from 93.9160% to 99.9653%.

The results might be applied separately or in conjunction with other forecasts to develop hypotheses regarding the patterns in the pre-owned residential real estate price index and conduct further policy research.

Artificial intelligence (AI) in mobile apps is growing rapidly, with features such as image recognition, personalized notifications and prescriptive analytics becoming more common. One such app is the Equalizer AI-powered mobile app, which uses AI to process water invoices, advise customers on fair prices and consumption and allow for online payment and data submission. This study aims to develop a technology adoption model for AI-powered mobile apps in the water sector by extending the value-based adoption model (VAM) to include customer trust.

Primary data was collected from 385 smartphone-using water customers. A stratified sampling approach ensured a representative sample of Palestinian water customers in the West Bank region. The study used a validated tool to measure perceived customer value, trust and adoption intention. It also used structural equation modeling to develop a causal diagram using the AMOS software.

The results confirmed a positive relationship between perceived usefulness, perceived innovation and perceived value and a negative relationship between perceived technical difficulty and perceived value. Contrary to VAM theory, the study showed a positive relationship between perceived fees and perceived value, indicating that users view premium fees as a cue of quality, accuracy, innovation and trustworthiness.

The high adoption intention of these apps holds significant implications for both the government and the water sector. This is because it results in the accumulation of substantial data, which can be used by government authorities and water providers to monitor and sustain the sector effectively.

This research extends existing technology adoption models by integrating customer trust and applying them to the water sector in a developing country. It offers new insights into public service innovations, addressing the unique cultural and sectoral challenges in this context.

The advent of Industry 4.0 (I4.0), characterised by rapid technological advancement, presents a transformative opportunity for companies to adapt and innovate in all aspects of life. However, I4.0 also ushers in challenges related to resource scarcity, waste generation, pollution and sustainability concerns, particularly in operations and supply chain management (OSCM). Despite the growing importance of I4.0 for supply chain sustainability, more research must be conducted on the processes required to foster sustainable innovation through these technologies. This study aims to bridge this gap by exploring the role of multi-criteria decision-making (MCDM) methods in evaluating the factors that affect sustainable digitalisation within OSCM. The research analyses how MCDM methods can facilitate sustainable digitalisation in OSCM, the primary MCDM methods used for sustainable digitalisation in OSCM and the key indicators for measuring sustainable digitalisation in OSCM. Therefore, this study offers a unique contribution by exploring the uncharted territory of MCDM methods in the context of I4.0 and sustainability within OSCM, shedding light on essential indicators for this critical transformation, and equipping managers with the knowledge needed to steer their organisations towards a sustainable digital future.

The significance of event tourism in destination development underscores the importance of assessing the quality of events and their sustainability for competitiveness. This study investigates tourists’ perceptions of service quality and sustainability at the “Biggest São João in the World” event in 2023. Employing a quantitative approach, we conducted field research using questionnaires based on the Tourqual model, integrating sustainability indicators to address environmental impacts associated with such events. Data collection took place between June and July 2023, with a non-probabilistic convenience sample of 709 visitors. Descriptive statistics were applied to the 2022 survey data (397 respondents), on the 2023 data (709 respondents). Results reveal that the event’s diverse activities received the highest average rating at 4.03, while the use of sustainable transport during the event garnered the lowest rating at 1.93. This emphasizes the need for event organizers to implement continuous improvement plans, focusing particularly on areas with critical evaluations to enhance visitor satisfaction. This study’s originality and innovative approach contribute valuable insights for event managers and researchers and promote both local development and environmental awareness.

This chapter presents an international review of the experiences of children and parents regarding care during the COVID-19 pandemic. The pandemic profoundly impacted children and families, magnifying the influence of governmental policies, socio-economic disparities and cultural contexts on children's experiences and exacerbating global inequalities. Vulnerable families faced increased challenges affecting children's rights and well-being, while the transition to digital learning highlighted the critical need for equitable access to technology. Despite extensive documentation of these challenges, research focusing on the pandemic's impact on young children's development, well-being, socialization and learning opportunities, as well as the experiences of parents/carers, remains limited. This scarcity stems from the pandemic's constraints on research activities, requiring reliance on online methods and the increased burdens on parents/carers, making participation in research more challenging.

Employing the PRISMA 2020 method for a literature review, this chapter aggregates international research findings on the subject, examining the impacts of COVID-19 on health and well-being, knowledge of the pandemic, effects on learning, educational strategies, online activity engagement and collaboration with Early Childhood Education and Care (ECEC) services. It concludes with a synthesis of insights and recommendations drawn from the reviewed literature.

The chapter contributes to a comprehensive framework for understanding the pandemic's impact on young children and their families, emphasising the importance of targeted interventions, equitable resource distribution and ongoing support for the ECEC sector to address the challenges and opportunities presented by the COVID-19 pandemic and future crises.

This study aims to describe the effect of ironing process parameters on mixing efficiency and gradient generation in Y-micromixers and microfluidic gradient generators (MGGs), respectively.

Material extrusion (MEX) enables the production of miniaturized devices with the advantage of lower manufacturing costs and higher design freedom. However, surface finishing is the most important drawback when it comes to microfluidic applications where flow splitting is not required. First, the effect of ironing line spacing (LS) and speed (IS) on mixing efficiency in Y-micromixers was experimentally investigated. Then, the best ironing settings were chosen to further study the spatial stability of the normalized concentration gradient in MGGs.

Lower ironing LS and IS enhance the microchannel surface smoothness. The best combination of ironing parameters (lowest values of LS and IS) leads to an increase in mixing length of 191% at Q = 10 µL/min and 198% at Q = 20 µL/min, with respect to a similar Y-micromixer geometry where ironing was not performed. These findings were applied in the production of a MGG, showing that the normalized concentration gradient in the crosswise flow direction does not depend on the streamwise position when ironing is performed.

To the best of the authors’ knowledge, for the first time, the possibility of optimizing ironing parameters to enhance the surface roughness in MEX microfluidic devices has been investigated. Ironing of the channel bottom surface allows to reduce ridges-induced flow convection, thus delaying mixing in Y-micromixers and achieving stable concentration gradient in MGGs.

The study aims to present a systematic literature review (SLR) to understand the current status of research on social media usage among the bottom of the pyramid (BOP). The purpose of this study is to identify the research gaps in this domain and review future research agendas by using theory, context, characteristics and methods [TCCM] framework.

An SLR, keywords co-occurrence and TCCM analysis were used to analyse and synthesize insights from 44 studies gained from Web of Science and Scopus databases.

The findings suggest that the USA and India are popular contexts for studying BOP. The BOP population uses social media to gain utilitarian, hedonic and social values. Further, social media can help BOP explore “entrepreneurship” opportunities, value co-creation and bring innovations.

This study expands the intellectual boundaries of social media at BOP and suggests multidisciplinary research. Additionally, adopting novel theoretical lenses helped determine social media's impact on BOP.

Inspired by the concept of the moment of truth, this study aims to examine how service interactions between hotel front-desk staff and a first-time check-in guest affect the guest’s brand satisfaction and brand attitudes, considering the moderating effect of welcome hospitality.

This study employs a between-subjects 2 (check-in service with high-service interaction vs low-service interaction) × 2 (with welcome hospitality vs without welcome hospitality) experimental method to investigate the mechanism of building brand attitudes towards a hotel during the check-in process.

The results of Study 1 showed that participants in the high-service interaction group reported higher brand satisfaction and brand attitudes than the low-service interaction group. It also confirmed that brand satisfaction fully mediates the relationship between service interactions and brand attributes. The results of Study 2 demonstrated the moderating effect of welcome hospitality. When service interaction is low, welcome hospitality can effectively improve brand satisfaction, but when service interaction is high, the improvement in brand satisfaction is smaller.

This research contributes to the literature on service interactions by potentially first experimentally examining the impact of first-time employee-customer interactions within a hotel setting. Recommendations were provided to hotel operators on how hotel staff can improve their service interactions.