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To understand differences in visitors' travel motivations, this study investigates the relations between personal values and travel motivations as well as the moderating effects of visit experience, age and gender on values–motivations relations among Australian visitors visiting Indonesia.

The multigroup confirmatory factor analysis (MGCFA) was performed using Analysis of Moment Structures (AMOS) to assess the constructs' validity across groups (potential vs repeat visitors; younger vs older visitors; male vs female visitors). A group model comparison thus was run in the multigroup analysis to test whether any differences in values–motivations relationships were significant across the groups.

This study shows that travel motivations are associated with values in a systematic way, and values–motivations relations can vary by age, gender and visit experience. Specifically, self-enhancement values are associated with escape-seeking motivation and conservation values are associated with assurance-seeking motivations. Whilst, there is no associations found between openness to change values and novelty-seeking motivations and between self-transcendence values and interaction-seeking motivations. Further, values influence travel motivations for potential but not repeat visitors and for younger but not older visitors.

Tailoring marketing strategies to align with visitors' personal values and travel motivations is crucial. Further, acknowledging the moderating influences of visit experience, gender and age in values–motivations relations enables destination marketers to create more effective and targeted approaches for diverse demographic groups in marketing, promotions and destination development.

This study for the first time provides a better explanation on how the travel motivations are formed in relation to values, age, gender and visit experience.

Ball grid array (BGA) package is prone to failure issues in a thermal vibration-coupled environment, such as deformation and fracture of solder joints. To predict the minimum equivalent stress of solder joints more accurately and optimize the solder joint structure, this paper aims to compare the machine learning method with response surface methodology (RSM).

This paper introduced a machine learning algorithm using Grey Wolf Optimization (GWO) Support Vector Regression (SVR) to optimize solder joint parameters. The solder joint height, spacing, solder pad diameter and thickness were the design variables, and minimizing the equivalent stress of solder joint was the optimization objective. The three dimensional finite element model of the printed circuit board assembly was verified by a modal experiment, and simulations were conducted for 25 groups of models with different parameter combinations. The simulation results were employed to train GWO-SVR to build a mathematical model and were analyzed using RSM to obtain a regression equation. Finally, GWO optimized these two methods.

The results show that the optimization results of GWO-SVR are closer to the simulation results than those of RSM. The minimum equivalent stress is decreased by 8.528% that of the original solution.

This study demonstrates that GWO-SVR is more precise and effective than RSM in optimizing the design of solder joints.

Salt rock from salt lakes can serve as a cost-effective material for subgrade filling, as demonstrated in projects like the Qarhan Salt Lake section of the Qinghai-Tibet Railway and the Qarhan Salt Lake section of the G215 Highway. This state-of-the-art paper aims to summarize the engineering properties of salt rock filling and present the advances of its utilization.

This paper collects and analyzes laboratory and field data of salt rock filling from previous studies to present a comprehensive analysis of the engineering properties and utilization of salt rock fillings.

Salt rock primarily contains minerals such as halite and glauberite, which contribute to its unique phase-changing behavior under varying environmental conditions, impacting its mechanical properties. Salt rock filling shrinks when in contact with vapor or unsaturated brine and expands under cooling or evaporation. Its use is particularly recommended for arid regions, with specific restrictions depending on the structure type. This paper discusses suggested countermeasures to mitigate these issues, as well as key quality acceptance indices for salt rock filling compaction. Moisture content after air-drying is recommended as a crucial parameter for construction quality control.

This review aims to support future research and engineering practices in salt rock subgrade applications.

Investors and other stakeholders depend on financial reports prepared by accountants to make informed decisions. During the aftermaths of unprecedented events, such as COVID-19, the need investors have for high-quality financial information is greater than ever. The purpose of this study is to examine whether financial reporting judgments made in groups rather than as individuals result in a better reflection of the economic substance of a transaction.

To examine the benefits that decision-making in groups may have on the reporting judgments of accountants, we conducted an experiment in which experienced accountants, located in Australia, were asked to make a decision over a lease classification. Each of the 87 respondents were either assigned to make their decision individually or as part of a three-member group.

Our results indicate that accountants in groups of three make significantly more accurate judgments than accountants who make judgments individually. The results also support the presumption that accountants in groups are significantly more confident in their judgments than accountants who make judgments individually.

We contribute to the important discussion that decision-making in groups has the potential to improve the quality of financial reporting by better reflecting economic reality.

This study is one of the first to examine the merits of group judgments and decision-making when interpreting and applying the International Financial Reporting Standards.

The purpose of this study is to investigate the relationship between dietary total antioxidant capacity (DTAC) and the dietary inflammatory index (DII) with inflammatory status in children recently diagnosed with Acute Lymphoblastic Leukemia (ALL). As the relationship between diet quality scores and inflammation remains uncertain in this population, the authors carried out a hospital-based cross-sectional study.

The study used a cross-sectional design involving 54 children recently diagnosed with ALL. Dietary data was collected using a 147-item semi-quantitative food frequency questionnaire developed for the Tehran Lipid and Glucose Study. Inflammatory status was evaluated using various indicators like C-reactive protein (CRP), neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), Glasgow prognostic score (GPS) and Complete blood count-based inflammatory score.

The authors found no significant relationship between DII with inflammatory indices and length of hospitalization in patients. However, a significant inverse relationship was observed between the antioxidant indices ferric-reducing ability of plasma, total reactive antioxidant potential and Trolox equivalent antioxidant capacity with the inflammatory index MLR, respectively (ß: −0.19, p = 0.001), (ß: −0.42, p = 0.02), (ß: −0.53, p = 0.005). Also, a significant inverse relationship between FRAP and CRP was observed in the crude model (ß: −0.13, p = 0.05). FRAP was also inversely correlated with GPS and PLR, respectively (ß: −0.08, p = 0.02), (ß: −0.26, p = 0.03). No additional significant links were discovered between food scores and the outcomes studied.

This study found no link between DII with inflammatory markers or hospitalization duration in children with ALL. However, the authors did observe a noteworthy inverse relationship between DTAC and certain inflammatory markers like MLR. To achieve more dependable findings, further research in this area is necessary.

This study aims to investigate the relationship between patient satisfaction (PS) and the parameters in healthcare and supply chain management (HLSCM).

The structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) method have been employed to identify correlation and possible configuration of causal factors that influence PS, including lack of resilience (LS), lack of visibility (LV), cost management (CM) and integration and interoperability (II).

The results from SEM confirmed that PS is highly correlated with lack of visibility, CM and II as critical parameters. Moreover, fsQCA findings state that the configuration of high levels of both resilience and lack of visibility, as well as high levels of II, are crucial for PS.

The researchers also identified the configuration of factors that lead to low PS. The study’s results could assist healthcare providers in improving their supply chain operations, resulting in more effective and efficient healthcare service delivery and ultimately improving PS.

The fsQCA method used in the study provides a more nuanced understanding of the complex interplay between these factors. The inclusion of supply chain management characteristics as parameters in the evaluation of PS is a novel aspect of this research. Previous studies largely focused on more traditional factors such as physical care, waiting times and hospital amenities. By considering supply chain management factors, this study provides insights into an under-explored area of PS research, which has important implications for healthcare providers looking to improve their operations and PS.

Community health centres (CHCs) play a vital role in healthcare service delivery in rural India and act as a crucial link between the primary and tertiary healthcare systems. The rural population in the union territory of Jammu and Kashmir primarily depends on CHCs for healthcare services due to the scarcity of private healthcare infrastructure and the lack of access to tertiary hospitals. The purpose of this study is to analyse the impact of management capability, staff competence, waiting time and patient satisfaction on revisit intention among patients visiting CHCs for care needs. It further examines the mediational role of patient satisfaction between antecedents of patient satisfaction and revisit intention.

A survey by questionnaire was used to collect data from 318 inpatients and outpatients visiting CHCs. Partial least square-structural equation modelling was performed with the help of SmartPLS 3 software to evaluate the causal relationships between variables.

The findings of the study ascertain that staff competence and waiting time are strong predictors of patient satisfaction while management capability was reported as an insignificant factor. Patient satisfaction significantly affects revisit intention and successfully mediates the impact of management capability, staff competence and waiting time on revisit intention.

CHCs play a significant role in bridging the gap between primary healthcare and tertiary healthcare and in delivering healthcare services to the vast rural population in India. This study necessitates the active participation of management to ensure the smooth functioning of CHCs. There is a need to provide adequate staff and necessary infrastructural facilities to reduce the treatment waiting time.

As the new frontier in online healthcare innovation, mobile health consultation (MHC) is transforming how traditional healthcare is delivered. Despite being known on a large scale for its benefits, MHC still faces consumer resistance. MHC is a technology-enabled service, so an in-depth analysis of consumer resistance from the perspective of technology is crucial to enhance service adoption. This study sought to determine the mechanism by which two information technology (IT)-specific traits – IT affordance and IT identity – influence consumer resistance to MHC during consumer–platform interactions.

We used the Credamo platform to gather data from 786 users with medical consulting experience to validate the resulting relationships.

Based on partial least squares structural equation modeling, three of the six IT affordances (visibility, searching and guidance shopping) exerted a significant positive influence on IT identity, while trigger attending and association affordance had no significant effect on IT identity. Persistence affordance was negatively associated with IT identity, and IT identity negatively influenced consumer resistance to MHC.

Academically, this empirical paper primarily contributes to the MHC literature and the theory of IT affordance and IT identity. Practically, several valuable guidance for MHC platforms is provided.

Drawing on the technology affordance and affinity theories, this study proposes a framework explaining the antecedents and consequences of customers’ smart experiences (CSEs) in the artificial intelligence (AI) chatbot context.

The quantitative approach employing an online survey was adopted to obtain data from chatbot users (N = 761) and analyzed using structural equation modeling.

Results from a survey study show that chatbot affordances, including interactivity (two-way communication, active control and synchronicity), selectivity (customization and localization), information (argument quality and source credibility), association (connectivity and sense of safety) and navigation positively affect CSEs (hedonic and cognitive), leading to customer chatbot stickiness through affinity.

Our study provides evidence that supports and extends the affordances and affinity lens by highlighting the roles of specific chatbot affordances that contribute to a positive-smart experience and subsequently enhances customer chatbot stickiness through affinity.

The purpose of this study is to explore the factors influencing viewers’ engagement intention in travel live streaming (TLS) from a perceived value perspective.

This study used a mixed-methods approach. In Study 1, 48 semistructured interviews were analyzed based on grounded theory and perceived value theory, and a research framework was established to investigate the impact of viewers’ engagement intentions in TLS. In Study 2, partial least squares structural equation modeling (PLS-SEM) was used to empirically validate survey data from 255 TLS viewers.

Through an analysis of the interview content, it was found that the expertise and interaction of the live streamer in TLS as well as the immersion, aesthetics and novelty of the live streaming scene are key influencing factors that affect the engagement of TLS viewers. This finding was confirmed through empirical research.

This research provides practical suggestions for live streamers, TLS platforms and local government to increase viewer engagement. Specifically, it provides methods and directions for the individual improvement of live streamers, further promotes the development and construction of the platform and underscores the importance of government initiatives in policy support and regulatory framework development.

This study focuses on the less-researched field of TLS. Using a mixed-methods approach combining interviews and PLS-SEM, this study explores the key factors that affect the engagement of TLS viewers based on the characteristics of live streamers and live streaming scenes.