Fusheng Xie, Ling Gao and Peiyu Xie
This paper examines the different features of China's economic development in different stages of economic globalization. The study finds that the investment- and export-based…
Abstract
Purpose
This paper examines the different features of China's economic development in different stages of economic globalization. The study finds that the investment- and export-based growth model drove China's high-speed economic growth between 2000 and 2007, which came into existence around 2000 when China plugged into the global production network.
Design/methodology/approach
This paper also finds that China slowed down to the New Normal because of the disruption to the socio-economic underpinnings of this growth model. As China adapts to and steers the New Normal, supply-side structural reforms can channel excess capacity to the construction of underground pipe networks in rural areas of central China and fix capital while advance rural revitalization.
Findings
At the same time, enterprises must strive to build a key component development platform for key component innovation and the standard-setting power in global manufacturing.
Originality/value
The establishment of a domestic production network integrating the integrated innovation-driven core enterprises and modular producers at different levels can satisfy the dynamic demand structure of China in which standardized demands and personalized demands coexist.
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This chapter provides first insights into identities and communities of educational staff in one of the largest, multi-campus universities in Italy. This group of managers refers…
Abstract
This chapter provides first insights into identities and communities of educational staff in one of the largest, multi-campus universities in Italy. This group of managers refers to those supporting teaching and learning in the light of emerging demands from the European strategy for universities which is positioning education at the frontline in today’s higher education institutions (HEIs).
These insights are compared with common issues surveyed among research managers and administrators (RMAs) working in the same as well as in other international HEIs using Evans’ ‘restricted’ and ‘extended’ models of professionalism.
Among findings, educational managers (EM) show awareness of their identity only as ‘professionals’ while RMAs may feel like ‘hybrid’ profiles. Unlike RMAs, EM report not having a strong sense of belonging to one community but feeling like they belong to a plethora of groups. In conclusion, there are no dominant ‘extended’ or ‘restricted’ traits for any of the two groups and they have both these attitudes to a certain extent as the results of this chapter will further explain.
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Luís Jacques de Sousa, João Poças Martins, Luís Sanhudo and João Santos Baptista
This study aims to review recent advances towards the implementation of ANN and NLP applications during the budgeting phase of the construction process. During this phase…
Abstract
Purpose
This study aims to review recent advances towards the implementation of ANN and NLP applications during the budgeting phase of the construction process. During this phase, construction companies must assess the scope of each task and map the client’s expectations to an internal database of tasks, resources and costs. Quantity surveyors carry out this assessment manually with little to no computer aid, within very austere time constraints, even though these results determine the company’s bid quality and are contractually binding.
Design/methodology/approach
This paper seeks to compile applications of machine learning (ML) and natural language processing in the architectural engineering and construction sector to find which methodologies can assist this assessment. The paper carries out a systematic literature review, following the preferred reporting items for systematic reviews and meta-analyses guidelines, to survey the main scientific contributions within the topic of text classification (TC) for budgeting in construction.
Findings
This work concludes that it is necessary to develop data sets that represent the variety of tasks in construction, achieve higher accuracy algorithms, widen the scope of their application and reduce the need for expert validation of the results. Although full automation is not within reach in the short term, TC algorithms can provide helpful support tools.
Originality/value
Given the increasing interest in ML for construction and recent developments, the findings disclosed in this paper contribute to the body of knowledge, provide a more automated perspective on budgeting in construction and break ground for further implementation of text-based ML in budgeting for construction.
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Rossella C. Gambetti and Robert V. Kozinets
This study aims to expand understanding of the diversity of virtual influencer forms by investigating their nonhuman-like, animal and graphic or cartoon variations.
Abstract
Purpose
This study aims to expand understanding of the diversity of virtual influencer forms by investigating their nonhuman-like, animal and graphic or cartoon variations.
Design/methodology/approach
A three-year multisite longitudinal netnography studied 174 virtual influencers and spanned ten social media platforms. Typological categories were constructed from the data set, focusing on 14 influencers located across quadrants. In-depth findings were then developed for eight illustrative cases.
Findings
Findings deepen the knowledge of the virtual influencer sphere by highlighting diversity in human-like, nonhuman-like, imaginative and realistic forms. The authors postulate four types of virtual influencers: hyper-human, antihuman, pan-human and alter-human. These forms are linked to specific personalities and communication styles, addressing various consumer needs. Imaginatively represented virtual influencers may prompt audiences to reevaluate beliefs, values and behaviors. These findings challenge prior work’s focus on attractive, hyperreal and human-like virtual influencers, encouraging consideration of divergent types engaged in novel meaning-shaping activities and targeting different segments.
Research limitations/implications
This research paves the way for consumer and marketing researchers and practitioners to broaden their representations of virtual influencers beyond the human-like, beyond the commercial and into new worlds of fantasy, imagination and posthuman possibility.
Practical implications
Different types of virtual influencers speak to diverse audiences and convey marketing messages in subtly different ways. Some forms of virtual influencers fit into roles like defiant voices, oppositional characters, activists, educators, entertainers and change leaders. As the universe of virtual influencers diversifies, this research opens new avenues of marketing for brands.
Originality/value
This study pioneers comprehensive qualitative research across the universe of virtual influencers and their communities, exploring links to popular culture. It offers connections between virtual influencer forms and communication strategies for marketers.
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Jiemin Zhong, Haoran Xie and Fu Lee Wang
A recommendation algorithm is typically applied to speculate on users’ preferences based on their behavioral characteristics. The purpose of this paper is to provide a systematic…
Abstract
Purpose
A recommendation algorithm is typically applied to speculate on users’ preferences based on their behavioral characteristics. The purpose of this paper is to provide a systematic review of recommendation systems by collecting related journal articles from the last five years (i.e. from 2014 to 2018). This paper aims to study the correlations between recommendation technologies and e-learning systems.
Design/methodology/approach
The paper reviews the relevant articles using five assessment aspects. A coding scheme was put forward that includes the following: the metrics for the e-learning system, the evaluation metrics for the recommendation algorithms, the recommendation filtering technology, the phases of the recommendation process and the learning outcomes of the system.
Findings
The research indicates that most e-learning systems will adopt the adaptive mechanism as a primary metric, and accuracy is a vital evaluation indicator for recommendation algorithms. In existing e-learning recommender systems, the most common recommendation filtering technology is hybrid filtering. The information collection phase is an important process recognized by most studies. Finally, the learning outcomes of the recommender system can be achieved through two key indicators: affections and correlations.
Originality/value
The recommendation technology works effectively in closing the gap between the information producer and the information consumer. This technology could help learners find the information they are interested in as well as send them a valuable message. The opportunities and challenges of the current study are discussed; the results of this study could provide a guideline for future research.
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Lianghui Xie, Zhenji Zhang, Robin Qiu and Daqing Gong
The paper aims to identify and analyze passengers’ riding paths for providing better operational support for digital transformation in megacity metro systems.
Abstract
Purpose
The paper aims to identify and analyze passengers’ riding paths for providing better operational support for digital transformation in megacity metro systems.
Design/methodology/approach
The authors develop a method to leverage certain passengers’ deterministic riding paths to corroborate other passengers’ uncertain paths. Using Automatic Fare Collection data and train schedules, a witness model is built to recover the actual riding paths for passengers whose paths are unknown otherwise. The identification and analysis of passenger riding paths between three different types of origin–destination) pairs reveal the complexity of passenger path choice.
Findings
The results show that passenger path choice modeling is usually characterized by complexity, experience and partial blindness. Some passengers choose paths that are not optimal due to their experience and limited access to overall metro system information. These passengers could be the subject of improved path guidance in light of riding efficiency improved through digital transformation.
Originality/value
This research contributes to the improvement of metro management and operations by leveraging ongoing digital transformation in megacity metro systems. Based on the riding paths and trip chains of a large number of individual passengers identified by the proposed method, metro operation management could prevent risks in areas with concentrated passenger flow in advance, optimally adjust train schedules on a daily basis and deliver real-time riding guidance station by station, which would greatly improve megacity metro systems’ service safety, quality and operational efficacy over time.
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Lianhua Liu, Aili Xie and Shiqi Lyu
This paper aims to clarify the spatial connection characteristics and organization mode of logistics economy of 21 cities in Guangdong Province under the background of the…
Abstract
Purpose
This paper aims to clarify the spatial connection characteristics and organization mode of logistics economy of 21 cities in Guangdong Province under the background of the integrated development of Guangdong, Hong Kong and Macao Bay area, and explore the spatial development characteristics and influencing factors of logistics economy in Guangdong Province.
Design/methodology/approach
This paper constructs the development level model of urban logistics economy in Guangdong Province from three aspects: demand level, supply level and support level, and uses the entropy weight method to measure the development level index of urban logistics economy in Guangdong Province. Then, the traffic accessibility index model is used to measure the traffic accessibility index between cities in Guangdong Province. Finally, using the social network analysis method, combined with the development level index of urban logistics economy in Guangdong Province and the urban traffic access index in Guangdong Province, this paper analyzes the spatial connection characteristics and influencing factors of logistics economy network in Guangdong Province.
Findings
There are regional differences in the development level of logistics economy in Guangdong Province; The overall network density of its logistics economic connection is large, but there is an imbalance in the network structure, and the core edge phenomenon is obvious; Logistics economic space presents the characteristics of double core development.
Research limitations/implications
Because the research object is the spatial connection characteristics of logistics economy in Guangdong Province, the research results may lack universality. Therefore, researchers are encouraged to put forward further tests.
Practical implications
By studying the spatial connection mode of logistics economy in 21 cities in Guangdong Province, China, this paper promotes the original methods and empirical contributions, and constructs the research framework of spatial relationship of logistics economy. This research framework is universal to a certain extent.
Social implications
This paper is conducive to promoting the integrated development of logistics economy in Guangdong Province and improving the balance of regional development of logistics economy.
Originality/value
Firstly, this study provides a new perspective to understand the spatial relationship and spatial spillover of logistics economy from relational data rather than attribute data. Secondly, This study enriched and broadened the research topic of spatial correlation of logistics economy. Thirdly, this research aims to promote the original methods and empirical contributions. Specifically, this study establishes a comprehensive research framework on the spatial network structure of logistics economy.
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Chun Sing Maxwell Ho, Ori Eyal and Thomas Wing Yan Man
Literature on teacher leadership highlights a significant gap in understanding the role of teacher leaders (TLs) as entrepreneurs. This research aims to bridge this gap by…
Abstract
Purpose
Literature on teacher leadership highlights a significant gap in understanding the role of teacher leaders (TLs) as entrepreneurs. This research aims to bridge this gap by examining the multifaceted entrepreneurial dimension of teacher leadership. It specifically focuses on providing a comprehensive profile of these leaders and assessing their perceived influence on teachers’ outcome, which are important for improving school performance.
Design/methodology/approach
A two-step clustering procedure was utilized to discern profiles of teacher leaders’ entrepreneurial behaviours, sampling 586 participants in a teacher leader training program. To assess mean differences in relation to perceived influence on teacher outcomes (i.e. job satisfaction, intrateam trust and innovative teaching practices) among these clusters, two-way contingency table analysis and MANOVA were conducted.
Findings
We identified three teacher-leader profiles: congenial facilitators, champion-leaders and executors. Our findings reveal the unique strengths and weaknesses of each profile and their contributions to job satisfaction, intrateam trust and innovative teaching practices.
Originality/value
This study is innovative in its detailed examination of teacher leadership through the lens of Teacher Entrepreneurial Behaviour (TEB), providing new perspectives on the intricate relationships between teacher leaders' TEB and their perceived influences. This deeper insight emphasizes the important role of entrepreneurial behaviours within teacher leadership, suggesting new directions for further research and development in educational leadership practices.
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Bin Yao, Richard T.R. Qiu, Daisy X.F. Fan, Anyu Liu and Dimitrios Buhalis
Due to product diversity, traditional quality signals in the hotel industry such as star ratings and brand affiliation do not work well in the accommodation booking process on the…
Abstract
Purpose
Due to product diversity, traditional quality signals in the hotel industry such as star ratings and brand affiliation do not work well in the accommodation booking process on the sharing economy platform. From a suppliers’ perspective, this study aims to apply the signaling theory to the booking of Airbnb listings and explore the influence of quality signals on the odds of an Airbnb listing being booked.
Design/methodology/approach
A binomial logistic model is used to describe the influences of different attributes on the market demand. Because of the large sample size, sequential Bayesian updating method is utilized in hospitality and tourism field for the first attempt.
Findings
Results show that, in addition to host-specific information such as “Superhost” and identity verification, attributes including price, extra charges, region competitiveness and house rules are all effective signals in Airbnb. The signaling impact is more effective for the listings without any review comments.
Originality/value
This study contributes to the literature by incorporating the signaling theory in the analysis of booking probability of Airbnb accommodation. The research findings are valuable to hosts in improving their booking rates and revenue. In addition, government and industrial management organizations can have more efficient strategy and policy planning.