Search results

This study focuses on (re-)introducing computer simulation as a part of the research paradigm. Simulation is a widely applied research method in supply chain and operations management. However, leading journals, such as the International Journal of Operations and Production Management, have often been reluctant to accept simulation studies. This study provides guidelines on how to conduct simulation research that advances theory, is relevant, and matters.

This study pooled the viewpoints of the editorial team of the International Journal of Operations and Production Management and authors of simulation studies. The authors debated their views and outlined why simulation is important and what a compelling simulation should look like.

There is an increasing importance of considering uncertainty, an increasing interest in dynamic phenomena, such as the transient response(s) to disruptions, and an increasing need to consider complementary outcomes, such as sustainability, which many researchers believe can be tackled by big data and modern analytical tools. But building, elaborating, and testing theory by purposeful experimentation is the strength of computer simulation. The authors therefore argue that simulation should play an important role in supply chain and operations management research, but for this, it also has to evolve away from simply generating and analyzing data. Four types of simulation research with much promise are outlined: empirical grounded simulation, simulation that establishes causality, simulation that supplements machine learning, artificial intelligence and analytics and simulation for sensitive environments.

This study identifies reasons why simulation is important for understanding and responding to today's business and societal challenges, it provides some guidance on how to design good simulation studies in this context and it links simulation to empirical research and theory going beyond multimethod studies.

This study aims to analyze the two-dimensional ferrofluid flow in porous media. The effects of changes in parameters such as permeability parameter, buoyancy parameter, Reynolds and Prandtl numbers, radiation parameter, velocity slip parameter, energy dissipation parameter and viscosity parameter on the velocity and temperature profile are displayed numerically and graphically.

By using simplification, nonlinear differential equations are converted into ordinary nonlinear equations. Modeling is done in the Cartesian coordinate system. The finite element method (FEM) and the Akbari-Ganji method (AGM) are used to solve the present problem. The finite element model determines each parameter’s effect on the fluid’s velocity and temperature.

The results show that if the viscosity parameter increases, the temperature of the fluid increases, but the velocity of the fluid decreases. As can be seen in the figures, by increasing the permeability parameter, a reduction in velocity and an enhancement in fluid temperature are observed. When the Reynolds number increases, an increase in fluid velocity and temperature is observed. If the speed slip parameter increases, the speed decreases, and as the energy dissipation parameter increases, the temperature also increases.

When considering factors like thermal conductivity and variable viscosity in this context, they can significantly impact velocity slippage conditions. The primary objective of the present study is to assess the influence of thermal conductivity parameters and variable viscosity within a porous medium on ferrofluid behavior. This particular flow configuration is chosen due to the essential role of ferrofluids and their extensive use in engineering, industry and medicine.

The consolidation process and morphology evolution in ceramics-based additive manufacturing (AM) are still not well-understood. As a way to better understand the ceramic selective laser sintering (SLS), a dynamic three-dimensional computational model was developed to forecast thermal behavior of hydroxyapatite (HA) bioceramic.

AM has revolutionized automotive, biomedical and aerospace industries, among many others. AM provides design and geometric freedom, rapid product customization and manufacturing flexibility through its layer-by-layer technique. However, a very limited number of materials are printable because of rapid melting and solidification hysteresis. Melting-solidification dynamics in powder bed fusion are usually correlated with welding, often ignoring the intrinsic properties of the laser irradiation; unsurprisingly, the printable materials are mostly the well-known weldable materials.

The consolidation mechanism of HA was identified during its processing in a ceramic SLS device, then the effect of the laser energy density was studied to see how it affects the processing window. Premature sintering and sintering regimes were revealed and elaborated in detail. The full consolidation beyond sintering was also revealed along with its interaction to baseplate.

These findings provide important insight into the consolidation mechanism of HA ceramics, which will be the cornerstone for extending the range of materials in laser powder bed fusion of ceramics.

When a large number of project proposals are evaluated to allocate available funds, grouping them based on their similarities is beneficial. Current approaches to group proposals are primarily based on manual matching of similar topics, discipline areas and keywords declared by project applicants. When the number of proposals increases, this task becomes complex and requires excessive time. This paper aims to demonstrate how to effectively use the rich information in the titles and abstracts of Turkish project proposals to group them automatically.

This study proposes a model that effectively groups Turkish project proposals by combining word embedding, clustering and classification techniques. The proposed model uses FastText, BERT and term frequency/inverse document frequency (TF/IDF) word-embedding techniques to extract terms from the titles and abstracts of project proposals in Turkish. The extracted terms were grouped using both the clustering and classification techniques. Natural groups contained within the corpus were discovered using k-means, k-means++, k-medoids and agglomerative clustering algorithms. Additionally, this study employs classification approaches to predict the target class for each document in the corpus. To classify project proposals, various classifiers, including k-nearest neighbors (KNN), support vector machines (SVM), artificial neural networks (ANN), classification and regression trees (CART) and random forest (RF), are used. Empirical experiments were conducted to validate the effectiveness of the proposed method by using real data from the Istanbul Development Agency.

The results show that the generated word embeddings can effectively represent proposal texts as vectors, and can be used as inputs for clustering or classification algorithms. Using clustering algorithms, the document corpus is divided into five groups. In addition, the results demonstrate that the proposals can easily be categorized into predefined categories using classification algorithms. SVM-Linear achieved the highest prediction accuracy (89.2%) with the FastText word embedding method. A comparison of manual grouping with automatic classification and clustering results revealed that both classification and clustering techniques have a high success rate.

The proposed model automatically benefits from the rich information in project proposals and significantly reduces numerous time-consuming tasks that managers must perform manually. Thus, it eliminates the drawbacks of the current manual methods and yields significantly more accurate results. In the future, additional experiments should be conducted to validate the proposed method using data from other funding organizations.

This study presents the application of word embedding methods to effectively use the rich information in the titles and abstracts of Turkish project proposals. Existing research studies focus on the automatic grouping of proposals; traditional frequency-based word embedding methods are used for feature extraction methods to represent project proposals. Unlike previous research, this study employs two outperforming neural network-based textual feature extraction techniques to obtain terms representing the proposals: BERT as a contextual word embedding method and FastText as a static word embedding method. Moreover, to the best of our knowledge, there has been no research conducted on the grouping of project proposals in Turkish.

This study aims to conduct a bibliometric analysis of sustainable tourism research published in Scopus-indexed journals covering the period from 1997 to 2021. Articles published during these 25 years were subjected to science mapping and performance analysis to propose potential areas for future research.

A bibliometric analysis using performance analysis and science mapping was conducted on 1,754 research papers retrieved from the Scopus database using the keyword “sustainable tourism.” Biblioshiny and VOSviewer are commonly used bibliometric tools. Science mapping techniques use coauthorship, keyword co-occurrence and co-citation analyses.

This study revealed the sustainable tourism publications’ spatial and temporal patterns, indicating a yearly growth rate of 19.9% during a 25-year period. The study identified Stefan Gossling as the most influential author, the “Journal of Sustainable Tourism” as the leading journal and Australia as the most productive country in sustainable tourism literature. The study used co-citation analysis to identify five thematic clusters, namely, reconceptualization and criticism, the role of residents, eco-labeling and the role of stakeholders, community-based tourism and the shift toward establishing sustainability indicators and effective governance and policymaking. The coauthorship analysis identifies the most influential author in collaborative efforts, and the most common pattern of collaboration is between researchers from different institutions in the same country, such as China and the Philippines, followed by collaborations between authors from other countries. The keyword co-occurrence analysis uncovered keywords that aligned with theme clusters generated from the co-citation analysis.

This study comprehensively uncovers five thematic clusters that have never been extracted so far in the literature. Also, it attempts to fill the gaps related to sustainable tourism by suggesting directions for future research.

There is limited research examining the relationship between social media and green food purchasing behaviour. In the current study, we examine the factors that affect consumers’ green food purchasing behaviour in Türkiye.

Data collected from the participants by survey method were analysed using Smart PLS 4.0 with IBM SPSS 26 and PLS to run SEM.

Our findings have revealed that from all the structural elements in the theory of planned behaviour (TPB), only attitude and perceived behavioural control contribute to consumers’ green food purchasing behaviour, while subjective norms do not contribute to consumers’ green food purchasing behaviour. Additionally, it was found that social media usage (SMU) and digital marketing interactions (DMI) have a positive and significant effect on green food purchasing behaviour. More information, experiences, opinions and recommendations on green foods in social media channels can encourage consumers to buy more green food.

This study first evaluates the applicability of the TPB model in explaining green food purchasing behaviour. This study is extended with two new factors included in the original framework of the TPB model, namely, SMU and DMI.

Food waste in the hospitality sector has emerged as a global concern. Various technology-driven online food services such as the food delivery apps (FDA) contribute to hospitality food waste. FDA users might behave irresponsibly by ordering more foods than required which may lead to food waste generation. To date, limited studies have been attempted to understand how consumers’ over-ordering behavior through FDA result in hospitality food waste.

The authors used partial least squares structural equation modeling (PLS-SEM) to analyze survey data from 248 FDA users.

The results indicated that perceived convenience and trust positively influence consumers' attitude toward FDA, which in turn promotes over-ordering behavior. Interestingly, the anticipated positive relationship between price advantage and attitude toward FDA was not supported by the data. Furthermore, the authors confirmed that over-ordering behavior contributes to food waste, an outcome that has crucial implications for both the hospitality sector and sustainability efforts.

The current study employs the stimulus-organism-behavior-consequence (SOBC) theory to investigate the catalysts and consequences of over-ordering behavior via FDA. This study thus highlights the importance of the SOBC model in understanding consumer behavior.

One of the existing and commonly used solar energy harvesting devices is the parabolic trough solar collector (PTSC). Because of their ability to operate in low and medium temperatures, parabolic trough concentrators are widely used in power generation plants and industrial process heating applications. Therefore, the investigation of how different operating conditions affect these devices’ overall efficiency has received a great deal of attention in the recent decade. This study aims to enhance the thermal performance of the PTSC and reduce the system cost.

In the novel configuration, a noncirculated nanofluid absorbs solar radiation through a glass wall. The base fluid was synthetic oil (5W30), and the nanoparticles used were copper oxide. The heat captured is immediately absorbed by the water circulating inside the copper tube immersed in the nanofluid. ANSYS FLUENT 15.0 was used for carrying out computational fluid dynamics simulations for two models of single and triple copper tubes. The experimental results obtained from a test rig constructed for this purpose were compared with the numerical outcomes of the single copper tube model.

The findings of the simulation demonstrated that performance was superior for the single copper tube model over the triple copper tube model. The numerical findings of the single copper tube model were compared with the experimental results. The numerical and experimental results differed from 3.17% to 5.6%. Investigations were carried out to study the effects of varying the volumetric flow rate of (20, 40, 60 and 80 L/h) and water inlet temperatures of (300, 315 and 330 K) on the effectiveness and performance of the newly developed model. Additionally, two nanofluid volume fractions of 0.05% and 0.075% were used for investigating their effect on the performance of the novel configuration. According to the findings, the highest thermal efficiency of 55.31% was recorded at 0.075% concentration and 80 L/h volume flow rate.

In this study, a novel direct absorption solar collector configuration using a noncirculated nanofluid was designed to enhance the thermal efficiency of PTSC. This new approach makes it possible to boost the thermal performance of the PTSC and lower the system’s cost.

This paper aims to review norms and their relationship with consumer behavior in the tourism sector. The review aims to identify gaps in relation to various norms and their impact on the literature to provide future research recommendations.

A systematic literature review method was used to analyze norms in consumer behavior research within the context of tourism and hospitality. The review focused on the research context, conceptualizations, roles, measurements, theoretical backgrounds and the major findings.

The review reveals that the conceptualizations and dimensionality of norms in the existing studies are inconsistent, and most research in the tourism context only adopted the concept partially without capturing the totality of the concept. The theoretical gaps and measurement of norms were also identified for future research.

This study contributes to a better understanding of the role of norms in shaping tourist behavior and can guide practitioners in developing effective marketing strategies. The findings suggest the need for a more comprehensive understanding of the concept of norms in tourism in relation to theoretical underpinnings, measurement and application. The recommendations provided in this study can guide future research on norms and tourist behavior.

Norms have been extensively discussed in the literature. This paper is the first to systematically review norms and their influence on consumer behavior in the tourism sector.

本文审视规范及其与旅游业消费者行为的关系。此审查旨在确定关于各种规范及其对文献的影响的差距, 并提供未来研究建议。

采用系统文献综述方法, 分析了旅游和酒店消费者行为研究中的规范。审查侧重于研究背景、概念化、角色、测量方法、理论背景和主要发现。

审查发现现有研究中规范的概念化和维度存在不一致性, 而大多数旅游环境下的研究只部分采用了该概念, 未能完整捕捉概念的整体。还确定了未来研究中规范的理论差距和测量问题。

本研究有助于更好地理解规范在塑造游客行为中的作用, 并可以指导从业者制定有效的营销策略。研究结果表明, 需要更全面地理解规范概念在旅游中的理论基础、测量和应用。本研究提供的建议可以指导未来关于规范和游客行为的研究。

规范在文献中已经广泛讨论。本文是第一个系统地审查规范及其对旅游业消费者行为的影响。

Este artículo examina las normas y su relación con el comportamiento del consumidor en el sector turístico. El objetivo de la revisión es identificar brechas con relación a diversas normas y su impacto en la literatura, para proporcionar recomendaciones en futuras investigaciones.

Se empleó un método de revisión sistemática de la literatura para analizar las normas en la investigación del comportamiento del consumidor en el contexto del turismo y hostelería. La revisión se centró en el contexto de investigación, conceptualizaciones, roles, medidas, fundamentos teóricos y los principales hallazgos.

La revisión revela que las conceptualizaciones y la dimensionalidad de las normas en los estudios previos son inconsistentes, y la mayoría de las investigaciones en el contexto del turismo solo adoptaron parcialmente el concepto sin capturar la totalidad de este. También se identificaron lagunas teóricas y medición de las normas para futuras investigaciones.

Este estudio contribuye a una mejor comprensión del papel de las normas en la formación del comportamiento turístico y puede orientar a los profesionales en el desarrollo de estrategias de marketing efectivas. Los resultados sugieren la necesidad de una comprensión más holística del concepto de normas en el turismo en relación con los fundamentos teóricos, la medición y la aplicación. Las recomendaciones proporcionadas en este estudio pueden guiar futuras investigaciones sobre normas y comportamiento turístico.

Las normas han sido ampliamente discutidas en la literatura. Este artículo es el primero en revisar sistemáticamente las normas y su influencia en el comportamiento del consumidor en el sector turístico.

The main purpose of this research paper is to generate a holistic bibliometric study of the tourism industry and COVID-19 fields, to further investigate the current interests and trends emerging from scientific collaboration and thematic analysis and to identify research gaps that indicate future research directions.

This study conducts several analyses, which include the co-authorship and social network analysis, co-citation and keyword co-occurrence knowledge structures. The authors generate a knowledge map of the leading articles and link them with previous literature to elucidate the debates and consensus in research on COVID-19 and tourism.

Research interests concentrate in the USA, China, Europe and the Oceania areas, so more cross-continental collaborations are expected among them and with other regions. Popular topics are tourism sustainable transformation, crisis management and multidisciplinary fields like tourism, hospitality, information technology and environmental sciences. This paper also identifies underexplored topics for future investigation on the social, environmental, cultural and governance dimensions of sustainable tourism.

This paper contributes to guiding tourism researchers in identifying and finding publication references and future collaborations. Moreover, the investigation of knowledge structures could be beneficial for scholars hoping to broaden the current understanding of this field and discover potential for future tourism research, especially in the global pandemic and other severe health crises.

This study enriches the existing literature in the fields of tourism and the pandemic and highlights current interests and research trends exploring scientific collaboration, thematic analysis and knowledge mapping.