Billy T.W. Yu and Stella T.X. Liu
This analysis examines the evolving role of deep learning in engagement marketing research. It tries to address a critical knowledge gap despite the rapid growth of artificial…
Abstract
Purpose
This analysis examines the evolving role of deep learning in engagement marketing research. It tries to address a critical knowledge gap despite the rapid growth of artificial intelligence (AI) applications in this field.
Design/methodology/approach
Using bibliometric techniques, this study analyzes Scopus data to investigate the evolution of engagement marketing research influenced by technology. Overlapping maps, evolution maps and strategic diagrams reveal key trends and intellectual structures within this dynamic field.
Findings
Our analysis reveals key trends in deep learning applications, like focuses on language-interaction, interactivity-privacy and human-focus satisfaction. While results show the contribution in foundational works like linguistics, algorithms and interactive marketing, they also raise concerns about the algorithmic bias, privacy violations and etc.
Research limitations/implications
While Scopus data offers valuable insights, our analysis acknowledges its limitations on publication language. Future research should treasure foundational works and historical context for comprehensive understandings. Additionally, addressing emerging challenges such as negative customer experiences and fairness is crucial for future studies.
Originality/value
This review provides a comprehensive perspective on deep learning applications on engagement marketing research in the context of interactive marketing. We present trends and thematic structures with practical implications for scholars and practitioners. It presents a fuller intellectual landscape and suggests that future research directions shall prioritize a human-centered approach to AI implementation, ultimately fostering genuine customer connections.
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Xiang Li, Ming Yang, Hongguang Ma and Kaitao (Stella) Yu
Travel time at inter-stops is a set of important parameters in bus timetabling, which is usually assumed to be normal (log-normal) random variable in literature. With the…
Abstract
Purpose
Travel time at inter-stops is a set of important parameters in bus timetabling, which is usually assumed to be normal (log-normal) random variable in literature. With the development of digital technology and big data analytics ability in the bus industry, practitioners prefer to generate deterministic travel time based on the on-board GPS data under maximum probability rule and mean value rule, which simplifies the optimization procedure, but performs poorly in the timetabling practice due to the loss of uncertain nature on travel time. The purpose of this study is to propose a GPS-data-driven bus timetabling approach with consideration of the spatial-temporal characteristic of travel time.
Design/methodology/approach
The authors illustrate that the real-life on-board GPS data does not support the hypothesis of normal (log-normal) distribution on travel time at inter-stops, thereby formulating the travel time as a scenario-based spatial-temporal matrix, where K-means clustering approach is utilized to identify the scenarios of spatial-temporal travel time from daily observation data. A scenario-based robust timetabling model is finally proposed to maximize the expected profit of the bus carrier. The authors introduce a set of binary variables to transform the robust model into an integer linear programming model, and speed up the solving process by solution space compression, such that the optimal timetable can be well solved by CPLEX.
Findings
Case studies based on the Beijing bus line 628 are given to demonstrate the efficiency of the proposed methodology. The results illustrate that: (1) the scenario-based robust model could increase the expected profits by 15.8% compared with the maximum probability model; (2) the scenario-based robust model could increase the expected profit by 30.74% compared with the mean value model; (3) the solution space compression approach could effectively shorten the computing time by 97%.
Originality/value
This study proposes a scenario-based robust bus timetabling approach driven by GPS data, which significantly improves the practicality and optimality of timetable, and proves the importance of big data analytics in improving public transport operations management.
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Xing (Stella) Liu, Lisa C. Wan and Anna S. Mattila
This study aims to explore how the extensive implementation of virtual influencers (VIs) in the hospitality and tourism industry shapes tourists’ trust perceptions. Specifically…
Abstract
Purpose
This study aims to explore how the extensive implementation of virtual influencers (VIs) in the hospitality and tourism industry shapes tourists’ trust perceptions. Specifically, it compares the differences between human influencers (HIs) and VIs based on mind perception theory and outlines the strategies for hospitality and tourism marketers to efficiently adopt influencers to enhance customers’ trust in diversified consumption contexts.
Design/methodology/approach
Three experiments were conducted with online panels (n = 799). Study 1 outlines the anticipated focal effect and the mediating role of perceived experience. Study 2 replicates the effect and investigates its downstream consequences. Study 3 examines the moderating effect of product type.
Findings
The results reveal that customers are more likely to distrust VIs than their human counterparts because the former is thought to possess a lower degree of perceived experience. This effect is more prominent in the endorsement of experiential (versus functional) products and services.
Originality/value
This research advances the understanding of how tourists perceive HIs andVIs differently in social media endorsement, enriching the growing literature on VIs. Hospitality marketers can also gain insights into the advantages and limitations of VIs, providing valuable information to optimize their marketing effectiveness.
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Amol Vasant Bhide and Milind M. Akarte
This paper aims to assess the feasibility of a hybrid manufacturing and remanufacturing system (HMRS) for essential commodities in the context of COVID-19. Specifically, it…
Abstract
Purpose
This paper aims to assess the feasibility of a hybrid manufacturing and remanufacturing system (HMRS) for essential commodities in the context of COVID-19. Specifically, it emphasises using HMRS based on costs associated with various manufacturing activities.
Design/methodology/approach
The combination of mathematical model and system dynamics is used to model the HMRS system. The model was tried on sanitiser bottle manufacturing to generalise the result.
Findings
The remanufacturing cost is higher because of reverse logistics, inspection and holding costs. Ultimately remanufacturing costs turn out to be lesser than the original manufacturing the moment system attains stability.
Practical implications
The study put forth the reason to encourage remanufacturing towards sustainability through government incentives.
Originality/value
The study put forth the feasibility of the HMRS system for an essential commodity in the context of a covid pandemic. The research implemented system dynamics for modelling and validation.
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Junbo Liu, Yaping Huang, Shengchun Wang, Xinxin Zhao, Qi Zou and Xingyuan Zhang
This research aims to improve the performance of rail fastener defect inspection method for multi railways, to effectively ensure the safety of railway operation.
Abstract
Purpose
This research aims to improve the performance of rail fastener defect inspection method for multi railways, to effectively ensure the safety of railway operation.
Design/methodology/approach
Firstly, a fastener region location method based on online learning strategy was proposed, which can locate fastener regions according to the prior knowledge of track image and template matching method. Online learning strategy is used to update the template library dynamically, so that the method not only can locate fastener regions in the track images of multi railways, but also can automatically collect and annotate fastener samples. Secondly, a fastener defect recognition method based on deep convolutional neural network was proposed. The structure of recognition network was designed according to the smaller size and the relatively single content of the fastener region. The data augmentation method based on the sample random sorting strategy is adopted to reduce the impact of the imbalance of sample size on recognition performance.
Findings
Test verification of the proposed method is conducted based on the rail fastener datasets of multi railways. Specifically, fastener location module has achieved an average detection rate of 99.36%, and fastener defect recognition module has achieved an average precision of 96.82%.
Originality/value
The proposed method can accurately locate fastener regions and identify fastener defect in the track images of different railways, which has high reliability and strong adaptability to multi railways.
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A. Huerta and F. Casadei
The arbitrary Lagrangian—Eulerian (ALE)formulation, which is already well established in the hydrodynamics andfluid‐structure interaction fields, is extended to materials…
Abstract
The arbitrary Lagrangian—Eulerian (ALE) formulation, which is already well established in the hydrodynamics and fluid‐structure interaction fields, is extended to materials with memory, namely, non‐ linear path‐dependent materials. Previous attempts to treat non‐ linear solid mechanics with the ALE description have, in common, the implicit interpolation technique employed. Obviously, this implies a numerical burden which may be uneconomical and may induce to give up this formulation, particularly in fast‐transient dynamics where explicit algorithms are usually employed. Here, several applications are presented to show that if adequate stress updating techniques are implemented, the ALE formulation could be much more competitive than classical Lagrangian computations when large deformations are present. Moreover, if the ALE technique is interpreted as a simple interpolation enrichment, adequate—in opposition to distorted or locally coarse—meshes are employed. Notice also that impossible computations (or at least very involved numerically) with a Lagrangian code are easily implementable in an ALE analysis. Finally, it is important to observe that the numerical examples shown range from a purely academic test to real engineering simulations. They show the effective applicability of this formulation to non‐linear solid mechanics and, in particular, to impact, coining or forming analysis.
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Micaela Jaramillo-Arévalo, Aldo Alvarez-Risco, Myreya De-La-Cruz-Diaz, Maria de las Mercedes Anderson-Seminario and Shyla Del-Aguila-Arcentales
Science, Technology, Engineering, and Mathematics (STEM) education, its importance, and its difficulties have been defined. This chapter seeks to present the digital tools that…
Abstract
Science, Technology, Engineering, and Mathematics (STEM) education, its importance, and its difficulties have been defined. This chapter seeks to present the digital tools that have been used during the pandemic period and that have been focused on promoting STEM education at different levels. The efforts made by educational organizations worldwide are mentioned. Different regions are shown presenting the best experiences of digital tools that enhance the elements of STEM and can be extended to different levels of education from elementary school to university. On the other hand, successful experiences of the use of technological tools from the teachers' point of view are shown, depicting the tools that have worked the most during the process of adapting to online classes to devise a much better educational plan that continues to take advantage of digital tools for STEM education.
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Mirjana Pejic Bach, Emil Tustanovski, Andrew W.H. Ip, Kai-Leung Yung and Vasja Roblek
System dynamics is a whole-system modelling and learning approach, useful for tackling non-linear problems, such as sustainable urban development. The purpose of this paper is to…
Abstract
Purpose
System dynamics is a whole-system modelling and learning approach, useful for tackling non-linear problems, such as sustainable urban development. The purpose of this paper is to review system dynamics applications in the simulation of sustainable urban development over a period from 2005 to 2017.
Design/methodology/approach
The analysis reveals that the number of applications of system dynamics modelling in the area of urban sustainable development increased in the analysed period. Research has changed its focus from the modelling of environmental problems to more complex models, portraying the multidimensional socio-economic processes that have an impact on the sustainability of urban development. Analysed case studies most often use the behaviour reproduction test for model validation, but without a unified approach. In most cases, modelling has been done in China, Germany and the USA, while urban development in the Eastern European countries, Africa and Latin America has not often been investigated. This paper indicates the knowledge gaps and suggests future research directions.
Findings
Papers that report the use of system dynamics modelling reveal a wide range of applications in urban sustainability. The analysis shows significant emphasis on environmental problems, while the interest for modelling social problems has been increasing during the last several years. Most of the modelled problems examine the sustainability of resources (land, water) and waste management, which are used for insights into the reasons for the system behaviour, forecasting future behaviour and policy testing.
Originality/value
The presented models were developed in most cases for the purpose of understanding the phenomena examined, as well as the future use of the models in policy planning. This brings us back to the need for greater stakeholder involvement, not only in the initial phase, but also during the whole modelling process, which could increase understanding, use and ownership of the models in the future, and thus increase their practical application.