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Using passive techniques like twisted tapes and corrugated surface is an efficient method of heat transfer improvement, since the referred manners break the boundary layer and improve the heat exchange. This paper aims to present an improved dual-flow parabolic trough collector (PTC). For this purpose, the effect of an absorber roof, a type of turbulator and a grooved absorber tube in the presence of nanofluid is investigated separately and simultaneously.

The FLUENT was used for solution of governing equation using control volume scheme. The control volume scheme has been used for solving the governing equations using the finite volume method. The standard k–e turbulence model has been chosen.

Fluid flow and heat transfer features, as friction factor, performance evaluation criteria (PEC) and Nusselt number have been calculated and analyzed. It is showed that absorber roof intensifies the heat transfer ratio in PTCs. Also, the combination of inserting the turbulator, outer corrugated and inner grooved absorber tube surface can enhance the PEC of PTCs considerably.

Results of the current study show that the PTC with two heat transfer fluids, outer and inner surface corrugated absorber tube, inserting the twisted tape and absorber roof have the maximum Nusselt number ratio equal to 5, and PEC higher than 2.5 between all proposed arrangements for investigated Reynolds numbers (from 10,000 to 20,000) and nanoparticles [Boehmite alumina (“λ-AlOOH)”] volume fractions (from 0.005 to 0.03). Maximum Nusselt number and PEC correspond to nanoparticle volume fraction and Reynolds number equal to 0.03 and 20,000, respectively. Besides, it was found that the performance evaluation criteria index values continuously grow by an intensification of nanoparticle volume concentrations.

Present investigation conducts a study on the hydrothermal features of a double flow Parabolic Trough Solar Collector (PTSC) equipped with sinusoidal-wavy grooved absorber tube and twisted tape insert filled with nanofluid. This paper aims to present an effectual PTSC which is comprised by nanofluid numerically by means of finite volume method.

The beneficial results such as pressure drop inside the absorber tube, mean predicted friction factor, predicted average Nusselt number and hydrothermal Performance Evaluation Criteria (PEC) are evaluated and reported to present the influences of numerous factors on studied interest outcomes. Effects of different Reynolds numbers and environmental conditions are also determined in this investigation.

It is found that using the absorber roof (canopy) can enhance the heat transfer ratio of PTSCs significantly during all studied Reynolds numbers. Also, it is realized that the combination of inner grooved surface, outer corrugated surface and inserting turbulator can improve the thermal-hydraulic characteristics of PTSCs sharply.

Novel PTSC (N.PTSC) filling with two Heat Transfer Fluids (HTFs), inner and outer surface corrugated absorber tube, absorber roof and inserting twisted tape (N.PTSC.f) has the highest PEC values among all novel configurations along all investigated Reynolds numbers which is followed by configurations N.PTSC with two HTFs and inserting twisted tape (N.PTSC.e), N.PTSC with two HTFs and outer surface corrugated absorber tube (N.PTSC.b) and N.PTSC with two HTFs and inner surface corrugated absorber tube (N.PTSC.c), respectively. N.PTSC.f Nusselt number values can overcome the high values of friction factor, and therefore is introduced as the most efficient model in the current study.

Considering both the current opportunities of the Internet of things (IoT) and aviation, as well as the potential opportunities they may offer for the future, it is understood that they are among the important issues that need to be examined in the literature. This study aims to provide an idea by conducting bibliometric and visualization analyses of the current trends and development opportunities of IoT and aviation.

In this study, descriptive and bibliometric analyses within the framework of co-author, co-citation, bibliographic coupling, and keyword co-occurrence analysis were carried out for publications found to be published between 2007 and 2023 in the Web of Science (WoS) database related to IoT and aviation. VOSviewer (ver. 1.6.18) program and the Biblioshiny application were used to create bibliometric networks and provide visualization.

As a result of some descriptive and visualization analyses, the current trend of publications on IoT and aviation and future publication opportunities has been revealed. It has been understood that the subject of IoT and aviation is one of the subjects whose number of publications has increased in recent years and has not yet fully matured in terms of the number of publications and has the potential to make new publications.

In this study, bibliometric analysis of IoT and aviation, which could not be found examined before in the literature, and the creation of existing bibliometric networks by visualizing were carried out.

The purpose of this study is to discover the components of virtual leadership in universities and higher education institutions during Covid-19 pandemic.

This research uses the qualitative research design, and semi-structured interviews with senior leaders were conducted with non-random purposeful and snowball sampling methods. Also, grounded theory was used for analyzing, coding and classifying the data.

After analyzing data, five main components influencing virtual leadership including leader's personality traits, followers' characteristics, technological, environmental and organizational components were identified.

As leadership, particularly virtual leadership, highly depends on context such as the level of technology in that certain region, the results cannot be generalized to other sectors or countries.

The research advances leadership development theory by highlighting the main components of virtual leadership in educational sector as a comprehensive perspective and complement the other aspects of virtual leadership such as consequences and challenges investigated by other studies.

This exploratory paper examined consumers' use of information sources and intentions to book future travel in the early stages of the COVID-19 pandemic. Authors expected that general news and travel information accessed on the Internet would impact travel intentions.

Data were collected from 547 US online consumer panelists when all states were under “stay-at-home orders” in April 2020.

Differences existed in the impact of three stressors (health, personal and financial) on the use of information sources (general news and travel sources) and ultimately on booking intentions.

The lack of influence health stressors had on travel research activity raises a question for the travel industry as to critical choice of messages to be imparted during pandemic environments.

A three-factor model was used to assess the determinants of booking intentions during uncertain times. Authors applied the stimulus-organism-response (S-O-R) framework to explore information searching for travel during the pandemic.

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.

Current models of organizational excellence are appropriate for the private organizations. It is evident that if an appropriate model is not adopted, the process of excellence in the organizations fails and some dimensions of the organization get affected by unpredictable damages. This research aims to identify an appropriate excellence model for public organizations.

First, a comprehensive literature review was conducted to identify the excellence criteria and models. Second, the models were through an expert-oriented questionnaire, analyzed by the analytical hierarchy process (AHP) technique. Participants were experts in the two domains of excellence models and public sector management. A sample of 15 experts was selected using purposive sampling. In order to emphasize on reliability, 10 questionnaires were adopted for analysis.

The findings showed that the European Foundation for Quality Management (EFQM) model is the most appropriate model for excellence measurement in the public organizations based on the five selected indices.

The identification of a model for measuring organizational excellence for public sector can significantly contribute to existing literature on excellence measurement.

Information and communication technologies have been widely implemented and made radical changes for several decades in the hospitality and tourism industry. This rapid development also generates considerable data in social media. This trend opens the door to analyze unstructured data and gain increased attention of a qualitative research approach from hospitality and tourism researchers and industry professionals. Therefore, this paper aims to describe how a computer-assisted qualitative data analysis (CAQDA) approach can be used in the hospitality and tourism technology literature to uncover the trends and thematic concepts of hospitality and tourism technology research and their dynamics in Journal of Hospitality and Tourism Technology (JHTT)

To achieve the proposed research goals, the current study used CAQDA software, Leximancer, to analyze 218 articles published in JHTT between Volume 1(1) in 2010 and Volume 10(4) in 2019. Based on the rigorous CAQDA processes, the study performed the thematic analysis using all articles and subgroup analyses in the five-year periods.

Using CAQDA, the study reveals the critical research trends and insights on hospitality and tourism technology for 10 years in the JHTT. The findings of this study can provide strong evidence of what hospitality and tourism technology research topics have been examined and how these topics were connected and changed over time. More importantly, the current study illustrates how the CAQDA approach can be applied to uncover the hidden trends and thematic concepts from text data in the hospitality and tourism literature.

This study is the first attempt to apply CAQDA software to identify research trends and thematic concepts and gain insights from past JHTT’s articles. Moreover, this study applies this software to describe how hospitality and tourism researchers can use one of the modern computer-assisted qualitative techniques. Based on the findings of this study, theoretical and methodological implications for hospitality and tourism researchers are provided. More importantly, the current study presents the specific guidelines of how the CAQDA approach can be used for the literature review.

在酒店与旅游研究中, 信息和通讯技术被广泛应用了数十载, 也在发展中经历了巨大变革。如此迅速的发展在社交媒体中产生了大量数据。此项趋势为分析非结构化的数据以及为酒店旅游界增加定性研究打开了大门。因此, 以 Journal of Hospitality and Tourism Technology（JHTT） 发表的论文为例, 本研究旨在介绍在酒店旅游文献中如何运用计算机辅助的定性研究方法来发现研究趋势, 主题概念, 以及发展进程。

为达到研究目的, 本研究运用 CAQDA 软件, Leximancer, 来分析了 JHTT 从2010 年第1卷第1期截止到 2019 年第 10 卷第4期之间发表的 218 篇论文。基于 CAQDA 的严谨分析, 本研究对所有发表的论文进行了以5年为阶段的主题分析和分主题分析。

通过 CAQDA, 本研究发现了 10 年间在 JHTT 发表论文中凸显出来的酒店和旅游科技的研究趋势。研究结果为了解酒店旅游研究中出现的以科技为核心主题, 以及主题之间是如何关联以及发展提供了科研证据。更重要的是, 本论文为阐述 CAQDA 是如何可被应用到酒店旅游研究的文本分析中提供了例证。

本论文首次应用了 CAQDA 软件来发现科研趋势和研究主题, 从 JHTT 发表的论文中得到了深刻见解。此外, 通过应用此软件, 本研究也为酒店旅游学者展示了如何运用此项现代计算机辅助定性分析技术。本文结果对理论和方法论具有深远意义。更重要的是, 本研究提供了在文献综述中如何运用 CAQDA 提供了指导方针。

定性研究, 文献综述, 主题分析, 文本分析, 酒店和旅游科技, 计算机辅助定量分析, CAQDA, Journal of Hospitality and Tourism Technology, JHTT.

文章类型 研究论文

The findings of this study have lightened the focal research areas in maintenance planning and scheduling. These also served as effective guidelines for future studies in this area. This research, therefore, contributes in fulfilling the gap by carrying out an SLR of contemporary research studies in the area of models for maintenance planning and scheduling. At present, SLR rooted in BA has not been carried focusing on a survey over models for maintenance planning and scheduling. SLR uses advanced scientific methodologies from BA tools to unveil thematic structures.

We have systematically reviewed over 1,021 peer-reviewed journal articles. Advanced contemporary tools from Bibliometric Analysis (BA) are used to perform a Systematic Literature Review (SLR). First, exploratory analysis is presented, highlighting the influential authors, sources and region amongst other key indices. Second, the large bibliographical data is visualized using co-citation network analyses, and research clusters (themes) are identified. The co-citation network is extended into a dynamic co-citation network and unveils the evolution of the research clusters. Last, cluster-based content analysis and historiographical analysis is carried out to predict the prospect of future research studies.

BA tools first outlined an exploratory analysis that noted influential authors, production countries, top-cited papers and frequent keywords. Later, the bibliometric data of over 1,021 documents is visualized using co-citation network analyses. Later, a dynamic co-citation analysis identified the evolution of research clusters over time. A historiographical direct citation analysis also unveils potential research directions. We have clearly observed that there are two main streams of maintenance planning and scheduling applications. The first has focused on joint maintenance and operations on machines. The second focused on integrated production and maintenance models in an echelon setting for unrealizable production facilities.

There are many literature review-based research studies that have contributed to maintenance scheduling research surveys. However, most studies have adopted traditional approaches, which often fall short in handling large bibliometric data and therefore suffer from selection biases from the authors. As a result, in this area, the existing reviews could be non-comprehensive. This study bridges the research gap by conducting an SLR of maintenance models, which to the best of our knowledge, has not been carried out before this study.

The purpose of this study is to investigate the potential of using computer vision and deep learning (DL) techniques for improving safety on construction sites. It provides an overview of the current state of research in the field of construction site safety (CSS) management using these technologies. Specifically, the study focuses on identifying hazards and monitoring the usage of personal protective equipment (PPE) on construction sites. The findings highlight the potential of computer vision and DL to enhance safety management in the construction industry.

The study involves a scientometric analysis of the current direction for using computer vision and DL for CSS management. The analysis reviews relevant studies, their methods, results and limitations, providing insights into the state of research in this area.

The study finds that computer vision and DL techniques can be effective for enhancing safety management in the construction industry. The potential of these technologies is specifically highlighted for identifying hazards and monitoring PPE usage on construction sites. The findings suggest that the use of these technologies can significantly reduce accidents and injuries on construction sites.

This study provides valuable insights into the potential of computer vision and DL techniques for improving safety management in the construction industry. The findings can help construction companies adopt innovative technologies to reduce the number of accidents and injuries on construction sites. The study also identifies areas for future research in this field, highlighting the need for further investigation into the use of these technologies for CSS management.