Search results

Online food delivery has been prevalent in recent years worldwide, especially during the COVID-19 pandemic, and people's consumption behaviors have changed significantly. This study aims to investigate the consumption behavior of young adults using online food delivery platforms during the COVID-19 pandemic and focuses on the dominant factors influencing their decision to use online food delivery platforms.

Semi-structured interviews including 14 young adults aged 18–25 living in Hong Kong were conducted to collect data about their perspectives on online food delivery platforms in five areas. This research adopted the stimulus-organism-response model (S-O-R model) to analyze how the factors influence young adult users' loyalty and satisfaction with online food delivery platforms.

Thematic analyses revealed that young adults were attracted to online food delivery platforms for their numerous benefits. They had a high frequency of usage and significant spending. Usability, usefulness, satisfaction and loyalty influenced young adults' behaviors on online food delivery platforms. Participants were overall satisfied with their experiences, but platforms still had room for improvement.

Few prior studies investigated the factors affecting the consumer experience and behavioral intention of online food delivery for young adults in Asia. This study contributes to understanding young adults' experiences and problems with online food delivery platforms. It provides practical insights for system engineers and designers to improve the current services and for the governments to enhance the existing regulatory loopholes.

Political factors play a crucial role in China's initial public offering (IPO) market due to its distinctive institutional context (i.e. “economic decentralization” and “political centralization”). Given the significant level of IPO underpricing in China, we examine the impact of local political uncertainty (measured by prefecture-level city official turnover rate) on IPO underpricing.

Using 2,259 IPOs of A-share listed companies from 2001 to 2019, we employ a structural equation model (SEM) to examine the channel (voluntarily lower the issuance price vs aftermarket trading) through which political uncertainty affects IPO underpricing. We check the robustness of the results using bootstrap tests, adopting alternative proxies for political uncertainty and IPO underpricing and employing subsample analysis.

Local official turnover-induced political uncertainty increases IPO underpricing by IPO firms voluntarily reducing the issuance price rather than by affecting investor sentiment in aftermarket trading. These relations are stronger in firms with pre-IPO political connections. The effect of political uncertainty on IPO underpricing is also contingent upon the industry and the growth phase of an IPO firm, more pronounced in politically sensitive industries and firms listed on the growth enterprise market board.

Local government officials in China usually have a short tenure and Chinese firms witness significantly severe IPO underpricing. By introducing the SEM model in studying China IPO underpricing, this study identifies the channel through which local government official turnover to political uncertainty on IPO underpricing.

Accurate and rapid tracking and counting of building materials are crucial in managing on-site construction processes and evaluating their progress. Such processes are typically conducted by visual inspection, making them time-consuming and error prone. This paper aims to propose a video-based deep-learning approach to the automated detection and counting of building materials.

A framework for accurately counting building materials at indoor construction sites with low light levels was developed using state-of-the-art deep learning methods. An existing object-detection model, the You Only Look Once version 4 (YOLO v4) algorithm, was adapted to achieve rapid convergence and accurate detection of materials and site operatives. Then, DenseNet was deployed to recognise these objects. Finally, a material-counting module based on morphology operations and the Hough transform was applied to automatically count stacks of building materials.

The proposed approach was tested by counting site operatives and stacks of elevated floor tiles in video footage from a real indoor construction site. The proposed YOLO v4 object-detection system provided higher average accuracy within a shorter time than the traditional YOLO v4 approach.

The proposed framework makes it feasible to separately monitor stockpiled, installed and waste materials in low-light construction environments. The improved YOLO v4 detection method is superior to the current YOLO v4 approach and advances the existing object detection algorithm. This framework can potentially reduce the time required to track construction progress and count materials, thereby increasing the efficiency of work-in-progress evaluation. It also exhibits great potential for developing a more reliable system for monitoring construction materials and activities.

This paper aims to investigate the motivational drivers for knowledge sharing (KS) through the application of mobile social networking (MSN) and their influence on employee productivity in the Malaysian construction industry.

The data was collected by distributing a self-administered questionnaire among employees working in the construction industry. A total of 250 questionnaires were collected and analysed using partial least squares structural equation modeling. This study used a variety of analysis methodologies including correlation analysis, reliability and validity testing, as well as a structural model in evaluating the relationships between KS, motivational factors and influence on productivity.

The empirical results of this study reveal that utilitarian motivation is positively related to internal and external KS. Similarly, internal and external KS have a positive influence on productivity, while internal and external hedonic motivation does not show any significant relationship with productivity.

Considering the paucity of evidence regarding the determinants of KS motivational drives on employee productivity in the Malaysian construction industry, this study enriches the social cognitive theory-based literature on KS.

This study provides some insights to the players in the construction industry in implementing the most appropriate KS promotion strategies that could potentially influence employee productivity. Organisations in the construction industry that place great emphasis on utilitarian motivation including competency, reward and incentives are more likely to have a better influence on KS and, in turn, positively impact employee productivity.

This study meaningfully contributes to enhancing the understanding of the motivational drivers for sharing knowledge on MSN and its influence on productivity. The findings of this study potentially assist construction practitioners in developing a holistic blueprint for managing their KS towards improving the overall productivity of their employees.

Blockchain technology, renowned for its decentralization, security, reliability, and data integrity, has the potential to revolutionize businesses globally. However, its full potential remains unrealized due to adoption barriers, necessitating further studies to address these challenges. Identifying these barriers is crucial for businesses and practitioners to effectively tackle them. This systematic review analyzed 70 eligible studies out of 1944 gathered from various databases to understand and identify common blockchain adoption barriers. The Technology–Organization–Environment (TOE) framework was the most popular theory used in these studies. Despite differences in variable definitions, financial constraints, lack of stakeholder collaboration and coordination, and social influences like resistance to change and negative perceptions emerged as the top three barriers. The supply chain domain had the highest number of studies on blockchain adoption. Notably, there was a significant increase in studies addressing blockchain adoption in 2023, comprising 34.2% of the total reviewed studies. This review provides a comprehensive overview of identified barriers, serving as a valuable foundation for future research. Understanding these challenges allows researchers to design targeted studies aimed at developing solutions, strategies, and innovations to overcome obstacles hindering blockchain adoption.

This paper aims to investigate the impact of perceived usefulness of online reviews and crowd cues on restaurant selection. In addition, the authors also examine the moderating role of perceived crowding and gender in this process.

The proposed hypotheses were tested with survey data (N = 200) collected from customers visiting full-service restaurants in Malaysia. The data were analyzed using SEM through Smart PLS.

The findings supported that the perceived usefulness of online reviews and perceived crowding have a positive effect on a consumer's purchase intentions, i.e. their decision of restaurant selection. Besides, a higher level of perceived crowding strengthens the relationship between the perceived usefulness of online reviews and their purchase intentions. This finding delineates that consumers prefer to dine in a crowded place with useful online reviews in an unfamiliar place. Finally, the results show that the effect of the usefulness of online reviews on purchase intentions does not vary with respect to gender (no significant contingent effect). However, the effect of perceived crowding varies with respect to gender – male customers have higher intentions to join crowded restaurants as compared to females.

Limitation of this study is its cross-sectional research design; data were collected in a single time frame. Longitudinal research design can be used to get in-depth knowledge of this phenomenon. Secondly, a non-probability sampling technique was used in this study, future research can used probability sampling technique to enhance generalizability of the study. Moreover, this study focused on the human crowding aspect, future studies can cover both aspects of crowding (human crowding and spatial crowding) in retailing or other service sectors (Blut and Iyer, 2020).

This study has multiple practical implications.

This study extends the current research on usefulness of online reviews and perceived crowding by investigating its direct and conditional effects. Specifically, the authors contribute in extant research by explaining its differential effects for male and female customers, when they select which restaurants to dine.

The process of conveyance of solid–liquid mixtures poses a significant challenge due to the considerable wear and tear experienced by critical components. This issue not only affects the lifespan of the system but also jeopardizes its safe operation. The purpose of this study is to numerically and experimentally investigate the erosion wear behavior of impeller steels (SS-410 and S-317) using Computational Fluid Dynamics (CFD) and Design of Experiments (DOE) techniques, aiming to address the significant challenges posed by wear in slurry transportation systems.

In this study, a robust two-phase solid-liquid model combining CFD with Discrete Phase Modeling (DPM) was applied to simulate the effects of coal-ash slurries on impeller steel. Additionally, an experimental evaluation was conducted using the DOE approach to analyze the impact of various parameters on impeller steel. This integrated methodology enabled a comprehensive analysis of erosion wear behavior and the influence of multiple factors on impeller durability by leveraging CFD for fluid flow dynamics and DPM to model particle interactions with the steel surface.

Simulation results highlight a strong link between particle size and the wear life of impeller steel. Through simulations and experiments on SS-410 and SS-317 under varied conditions, it’s evident that SS-410 outperforms SS-317 due to its higher hardness and density. This is supported by Taguchi’s method, with SS-410 showing a higher Signal-to-Noise ratio. Notably, particle size emerges as the most influential parameter compared to others.

Current research primarily focuses on either CFD or experimentation to predict pump impeller steel erosion wear, lacking relevant erosion mechanism insights and experimental data. This study bridges this gap by employing both CFD and DPM methods to comprehensively investigate particle effects on pump impeller steel and elucidate erosion mechanisms.

With respect to severe working conditions such as heavy load and impact, this paper aims to investigate the friction reduction and anti-wear performance of kaolin and molybdenum dialkyl dithiophosphate (MoDDP) composite lubricant additives to improve the lubrication effect of a single additive.

A four-ball friction test was carried out to determine the optimal concentration of kaolin and organic molybdenum additives and the tribological properties of the kaolin/MoDDP composite lubricant additives. A ring block test of composite lubricant additives was designed to investigate its lubrication performance under the severe working conditions of low speed, heavy load and impact.

The results showed that the optimal addition mass fractions of kaolin and MoDDP were 4.0 and 1.5 Wt.%, respectively, when kaolin and MoDDP were used as single lubricant additives. Compared with the single additive, the 4.0 Wt.% kaolin/1.5 Wt.% MoDDP composite lubricant additive showed excellent friction reduction and anti-wear effects under heavy load and impact conditions. Physicochemical analysis of the wear surface revealed that the lamellar kaolin additive and MoDDP had excellent synergistic effects, and the friction process promoted the generation of lubricant films containing a chemically reactive layer of MoS₂, MoO₂, FeS₂ and Fe₂O₃ and a physically adsorbent layer containing SiO₂ and Al₂O₃, which play important roles in anti-wear and friction reduction.

The excellent friction reduction and anti-wear effects of lamellar silicate minerals and the excellent antioxidant properties and good synergistic effects of molybdenum were comprehensively used to develop the composite additives with great lubricating properties.

This study aims to explore the transformative potential of digital twins (DTs) in the construction industry by addressing challenges and bridging the technology adoption gap. Focusing on construction offices, on-site environments and their interface, the research identifies key success factors for DT implementation. Emphasizing practical applications, the study foresees a substantial impact on project management, highlighting the pivotal role of DTs in reshaping the construction sector.

We reviewed 30 variables within the DT literature, classifying investigations into three main domains: on-site environments, office environments and site-office interface in construction projects. We employed a questionnaire to examine variables, with collected data analyzed using SmartPLS version 4 software. Confirmatory analysis and structural equation modeling rigorously assessed the model’s reliability, validity and predictive utility.

The study identifies 11 critical factors crucial for successfully implementing DTs in construction projects, emphasizing contributions from office-related (ORF), site-related (SRF) and office-site-related factors (OSRF). Notably, impactful contributions from ORF affirm its pivotal role. The research sheds light on specific aspects within construction offices, on-site environments and their interface, providing valuable insights for industry stakeholders, policymakers and researchers.

Despite discussions on DT’s potential, a research gap exists in addressing essential factors for its effective application in monitoring and optimizing construction projects throughout their lifecycle. This study fills this gap by identifying and categorizing these factors, enhancing the knowledge base for successful DT assimilation and emphasizing the need for practitioners to understand key factors crucial for its integration into construction processes.

The review paper aims to understand the development of workplace ostracism as a field in organizational studies from 2000 to the present. The study provides a comprehensive synthesis of the current state of the domain by exploring its antecedents, consequences, underlying mechanisms and buffering mechanisms.

The present study analyses 134 published peer-reviewed empirical and non-empirical articles retrieved from the Scopus database. A systematic literature review and bibliometric analyses (using VOS viewer) have been used to gain insights into the development and trends within the field. Bibliometric analyses involved science mapping techniques such as co-citation analysis, co-occurrence of keywords and bibliographic coupling. Combining these three techniques, the study aimed to provide a comprehensive overview of the workplace ostracism research domain's historical, current and future landscape.

In the present study, through descriptive analyses, the authors uncovered publishing trends, productive journals, countries and industries that contribute to this research field. The systematic review enabled the showcasing of the current landscape of workplace ostracism. The bibliometric analyses shed light on major authors, influential articles, prominent journals and significant keywords in workplace ostracism.

This study enriches the existing literature by offering a comprehensive research framework for workplace ostracism. It goes beyond that by presenting significant bibliographic insights by applying bibliometric analyses. Furthermore, this study identifies and emphasizes future research directions using the theory, characteristics, construct and methodologies framework, aiming to expand the knowledge base and understanding of this topic.