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This study investigates the relationship between feelings of loneliness in the workplace, life satisfaction, affect, hope and expressivity among hotel employees.

The research model was tested via structural equation modeling based on the empirical data collected from hotel employees in Antalya, Turkey.

The research findings suggest that emotional deprivation and social companionship have a significant impact on life satisfaction, that life satisfaction has a significant impact on positive and negative emotions, and that positive and negative emotions have the same impact on pathways and agencies.

The research findings should assist researchers and practitioners to understand the behaviors of hotel employees in continuous interaction and relationship with individuals to motivate them while providing more effective services.

A separate study of the different behavioral biases does not allow for a full understanding of the complexity and stability of the heterogeneity of beliefs. Therefore, through a more global view of these anomalies, the authors wish to show that they can converge on a single concept, which is the heterogeneity of beliefs.

It is therefore essential to stress that the importance of this study is mainly reflected in the methodological approach used in the construction and analysis of the map and not only in the results achieved. This contribution states that structural analysis, as a means of building the cognitive map, can facilitate the task of investors and other decision-makers, in the identification and analysis of the heterogeneity of beliefs that can therefore guide investors' strategy in decision-making.

The authors have studied the behavior of the investor and its way of interpreting the information and the authors have emphasized the value of studying the concept of heterogeneity of beliefs in its complexity. So that part of the work seems to be relevant and crucial to filling, if you will, that void. In this sense, the authors have shown that behavioral abnormalities are multidimensional concepts: “self-deception”, “cognitive bias”, “emotional bias” and “social bias”.

In particular, this article will aim to achieve the objective of proposing a model for measuring the heterogeneity of beliefs. Thus, the authors want to show that the heterogeneity of beliefs can be measured directly through the different behavioral anomalies.

The food industry is continuously developing its online services called food delivery applications (FDAs). This study aims to evaluate FDA's importance–performance and identify strategies to maximize its potential gains from a business partner's perspective.

Data are collected from 208 FDA partners in Indonesia. Importance–performance analysis (IPA) is applied to evaluate the FDA feature and extended the theory of potential gain in customer value (PGCV) to achieve potential gains from FDA business partners.

This study provides a clear and measurable direction for future research to develop FDA performance. Owning customer data, revenue sharing and competitive advantage are the most potential gains from joining the FDA from the business partner perspective.

The respondents are restaurants from the micro, small, and medium enterprises levels. Further research should involve middle to upper level restaurants to discover all business partners' perceptions. This will be very helpful for FDA providers interested in improving the best performance for all their partners.

FDA providers must focus on improving and maintaining the features of owning customer data, revenue sharing, competitive advantage, stable terms and conditions, customer interface, building customer loyalty, online presence, user credit rating, promotion and offers, delivery service and sales enhancement to increase consumer satisfaction and meet the expectations desired by business partners.

This research provides a meaningful theoretical foundation for future work. It extends the theory of PGCV using the value of a partner perspective as a substitute for customer value; hence, the authors call it a potential gain in partner value.

Background: The annual average daily traffic (AADT) data from road segments are critical for roadway projects, especially with the decision-making processes about operations, travel demand, safety-performance evaluation, and maintenance. Regular updates help to determine traffic patterns for decision-making. Unfortunately, the luxury of having permanent recorders on all road segments, especially low-volume roads, is virtually impossible. Consequently, insufficient AADT information is acquired for planning and new developments. A growing number of statistical, mathematical, and machine-learning algorithms have helped estimate AADT data values accurately, to some extent, at both sampled and unsampled locations on low-volume roadways. In some cases, roads with no representative AADT data are resolved with information from roadways with similar traffic patterns.

Methods: This study adopted an integrative approach with a combined systematic literature review (SLR) and meta-analysis (MA) to identify and to evaluate the performance, the sources of error, and possible advantages and disadvantages of the techniques utilized most for estimating AADT data. As a result, an SLR of various peer-reviewed articles and reports was completed to answer four research questions.

Results: The study showed that the most frequent techniques utilized to estimate AADT data on low-volume roadways were regression, artificial neural-network techniques, travel-demand models, the traditional factor approach, and spatial interpolation techniques. These AADT data-estimating methods' performance was subjected to meta-analysis. Three studies were completed: R squared, root means square error, and mean absolute percentage error. The meta-analysis results indicated a mixed summary effect: 1. all studies were equal; 2. all studies were not comparable. However, the integrated qualitative and quantitative approach indicated that spatial-interpolation (Kriging) methods outperformed the others.

Conclusions: Spatial-interpolation methods may be selected over others to generate accurate AADT data by practitioners at all levels for decision making. Besides, the resulting cross-validation statistics give statistics like the other methods' performance measures.

The user experience during the use of activities and services is a fundamental aspect for sports managers and can provide a competitive advantage. The purpose of this study was to identify the dimensions of experiential quality and the relationship of this construct with customer trust and customer satisfaction in achieving behavioral intention.

Using a convenience sampling technique, a total of 322 gym users in Turkey participated. A two-step approach was used to test both the model and the research hypotheses [confirmatory factor analysis (CFA) and structural equation modeling (SEM)].

The interaction quality, physical environmental quality, outcome quality and enjoyment quality were positively related to experiential quality. Similarly, the experimental quality was positively related to customer satisfaction and customer trust. Finally, customer satisfaction was related to behavioral intentions.

This study provides empirical evidence about the importance of experiential quality to gain a competitive advantage in the context of fitness centers.

Background: Geostatistics focuses on spatial or spatiotemporal datasets. Geostatistics was initially developed to generate probability distribution predictions of ore grade in the mining industry; however, it has been successfully applied in diverse scientific disciplines. This technique includes univariate, multivariate, and simulations. Kriging geostatistical methods, simple, ordinary, and universal Kriging, are not multivariate models in the usual statistical function. Notwithstanding, simple, ordinary, and universal kriging techniques utilize random function models that include unlimited random variables while modeling one attribute. The coKriging technique is a multivariate estimation method that simultaneously models two or more attributes defined with the same domains as coregionalization.

Objective: This study investigates the impact of populations on traffic volumes as a variable. The additional variable determines the strength or accuracy obtained when data integration is adopted. In addition, this is to help improve the estimation of annual average daily traffic (AADT).

Methods procedures, process: The investigation adopts the coKriging technique with AADT data from 2009 to 2016 from Montana, Minnesota, and Washington as primary attributes and population as a controlling factor (second variable). CK is implemented for this study after reviewing the literature and work completed by comparing it with other geostatistical methods.

Results, observations, and conclusions: The Investigation employed two variables. The data integration methods employed in CK yield more reliable models because their strength is drawn from multiple variables. The cross-validation results of the model types explored with the CK technique successfully evaluate the interpolation technique's performance and help select optimal models for each state. The results from Montana and Minnesota models accurately represent the states' traffic and population density. The Washington model had a few exceptions. However, the secondary attribute helped yield an accurate interpretation. Consequently, the impact of tourism, shopping, recreation centers, and possible transiting patterns throughout the state is worth exploring.

The development of green manufacturing has become essential to achieve sustainable development and modernize the nation’s manufacturing and production capacity without increasing nonrenewable resource consumption and pollution. This study investigates the effect of green industrial practices on technical efficiency for Thai manufacturers.

The study uses stochastic frontier analysis (SFA) to estimate the stochastic frontier production function (SFPF) and inefficiency effects model, as pioneered by Battese and Coelli (1995).

This study shows that, on average, Thai manufacturing firms have experienced declining returns-to-scale production and relatively low technical efficiency. However, it is estimated that Thai manufacturing firms with a green commitment obtained the highest technical efficiency, followed by those with green activity, green systems and green culture levels, compared to those without any commitment to green manufacturing practices. Finally, internationalization and skill development can significantly improve technical efficiency.

Green industry policy mixes will be vital for driving structural reforms toward a more environmentally friendly and sustainable economic system. Furthermore, circular economy processes can promote firms' production efficiency and resource use.

To the best of the authors' knowledge, this study is the first to investigate the effect of green industry practices on the technical efficiency of Thai manufacturing enterprises. This study also encompasses analyses of the roles of internationalization, innovation and skill development.

The purpose of this paper is to review cases of artificial reefs built through additive manufacturing (AM) technologies and analyse their ecological goals, fabrication process, materials, structural design features and implementation location to determine predominant parameters, environmental impacts, advantages, and limitations.

The review analysed 16 cases of artificial reefs from both temperate and tropical regions. These were categorised based on the AM process used, the mortar material used (crucial for biological applications), the structural design features and the location of implementation. These parameters are assessed to determine how effectively the designs meet the stipulated ecological goals, how AM technologies demonstrate their potential in comparison to conventional methods and the preference locations of these implementations.

The overview revealed that the dominant artificial reef implementation occurs in the Mediterranean and Atlantic Seas, both accounting for 24%. The remaining cases were in the Australian Sea (20%), the South Asia Sea (12%), the Persian Gulf and the Pacific Ocean, both with 8%, and the Indian Sea with 4% of all the cases studied. It was concluded that fused filament fabrication, binder jetting and material extrusion represent the main AM processes used to build artificial reefs. Cementitious materials, ceramics, polymers and geopolymer formulations were used, incorporating aggregates from mineral residues, biological wastes and pozzolan materials, to reduce environmental impacts, promote the circular economy and be more beneficial for marine ecosystems. The evaluation ranking assessed how well their design and materials align with their ecological goals, demonstrating that five cases were ranked with high effectiveness, ten projects with moderate effectiveness and one case with low effectiveness.

AM represents an innovative method for marine restoration and management. It offers a rapid prototyping technique for design validation and enables the creation of highly complex shapes for habitat diversification while incorporating a diverse range of materials to benefit environmental and marine species’ habitats.

The use of digital technologies in the financial service industry has brought new complexities to the corporate governance in banks. Relying on the agency perspective of the shareholder, debtholder and societal governance in banks, this research examines the impact of financial technology innovation (FinTech) on banks' performance by enlightening the monitoring role of female independent directors.

Relying on a sample of Italian banks observed during the period 2016–2020, the authors hand-collected data on the use of FinTech by considering (1) the in-house provisions of FinTech solutions, (2) the collaboration with external FinTech firms and (3) a combination of both measures. The authors run a panel data regression analysis with fixed effects, measuring bank performance through bank competitiveness and bank riskiness.

The authors find that FinTech increases bank competitiveness in gathering money from depositors and that independent women on board mitigate the negative relationship between FinTech and the riskiness of banks' assets, ameliorating the conflicting interests among shareholders, debtholder and societal governance.

This study emphasizes the complexities of bank governance when dealing with FinTech in the wider perspective of equity governance, debt governance and the societal governance spotlighting the importance of appointing female directors in independent positions to enhance the bright sides of financial innovation. The authors enrich the literature on FinTech with a finer understanding of the drivers and implications of in-house provisions of FinTech solutions versus the collaboration with external FinTech firms.