Faguo Liu, Qian Zhang, Tao Yan, Bin Wang, Ying Gao, Jiaqi Hou and Feiniu Yuan
Light field images (LFIs) have gained popularity as a technology to increase the field of view (FoV) of plenoptic cameras since they can capture information about light rays with…
Abstract
Purpose
Light field images (LFIs) have gained popularity as a technology to increase the field of view (FoV) of plenoptic cameras since they can capture information about light rays with a large FoV. Wide FoV causes light field (LF) data to increase rapidly, which restricts the use of LF imaging in image processing, visual analysis and user interface. Effective LFI coding methods become of paramount importance. This paper aims to eliminate more redundancy by exploring sparsity and correlation in the angular domain of LFIs, as well as mitigate the loss of perceptual quality of LFIs caused by encoding.
Design/methodology/approach
This work proposes a new efficient LF coding framework. On the coding side, a new sampling scheme and a hierarchical prediction structure are used to eliminate redundancy in the LFI's angular and spatial domains. At the decoding side, high-quality dense LF is reconstructed using a view synthesis method based on the residual channel attention network (RCAN).
Findings
In three different LF datasets, our proposed coding framework not only reduces the transmitted bit rate but also maintains a higher view quality than the current more advanced methods.
Originality/value
(1) A new sampling scheme is designed to synthesize high-quality LFIs while better ensuring LF angular domain sparsity. (2) To further eliminate redundancy in the spatial domain, new ranking schemes and hierarchical prediction structures are designed. (3) A synthetic network based on RCAN and a novel loss function is designed to mitigate the perceptual quality loss due to the coding process.
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Xixian Peng, Jiaqi Ren and Yutong Guo
E-commerce live streaming (ELS) has become a new and important shopping channel. Although previous studies have provided insightful findings on how to engage consumers in ELS…
Abstract
Purpose
E-commerce live streaming (ELS) has become a new and important shopping channel. Although previous studies have provided insightful findings on how to engage consumers in ELS, limited effort has been made to explore the role of factors of live streaming rooms. Based on the literature on space perception and the retail environment, this study aims to develop a theoretical model to examine how perceived distance and perceived depth affect consumers' affective and cognitive perceptions and then further impact product attitude in ELS.
Design/methodology/approach
This study collected 414 valid survey responses to test the proposed research model. Survey data were analyzed using partial least squares (PLS)-structural equation modeling. The PLS Multi-Group analysis (PLS-MGA) was used to test the consistency of the research model across different product types and watching durations.
Findings
The results suggest that environmental factors of a live streaming room (i.e. perceived distance and perceived depth) can impact consumers' attitudes toward the product in the live streaming via both cognitive and affective routes. These effects keep consistent across different product types and watching durations.
Originality/value
The paper focuses on the environmental perspective, which is unexplored in previous literature on ELS. It highlights the importance of the space design of live streaming rooms.
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Xiaofen Jiang, Gao Guangkuo and Yang Xuezheng
This paper considers the brand awareness and anchor influence on consumers' live-streaming purchases, and explores the existence of “free-riding” behavior, the comparison of brand…
Abstract
Purpose
This paper considers the brand awareness and anchor influence on consumers' live-streaming purchases, and explores the existence of “free-riding” behavior, the comparison of brand promotion effect and active live-streaming effect and the optimal strategic combination between the brand and the anchor. The authors investigate the evolutionary stabilization strategies of the bounded rational brand and anchor, and explore the conditions for the realization of the optimal strategy. Management suggestions for the development of live streaming commerce can be provided in this paper.
Design/methodology/approach
Two significant models are used in this paper. The Stackelberg model is used to study the “free-riding” behavior, the comparison of brand promotion effect and active live-streaming effect and the optimal strategic combination between the brand and the anchor. Using evolutionary game theory to get the evolutionary stable equilibrium strategies and analyze the binary equilibrium strategy of the bounded rational brand and anchor. In addition, relevant simulation analysis is conducted using realistic data to verify the conclusions and for further analysis, making the conclusions of the paper have realistic significance.
Findings
The study shows that “free-riding” behavior exists and the positive effect of brand promotion is greater than that of active live-streaming. The brand and the anchor take active actions as the optimal strategy. As the sensitivity coefficient of consumers to live-streaming effort and the sensitivity coefficient of consumers to brand promotion change, various evolutionary stabilization strategies will appear. When the two sensitivity coefficients are below a certain threshold, the game sides will reach the optimal strategic combination to obtain the maximum benefits. When they rise above this threshold, it is counterproductive instead. The system achieves the optimal strategic combination when the difference factor between effort cost and promotion cost must be higher than a certain value, but when it takes the smallest possible value, the game sides tend to take active actions. This study can provide management suggestions for the sustainable development of the live-streaming model.
Research limitations/implications
This paper shows that under certain conditions, the brand and the anchor can evolve into the optimal strategy to maximize the profits of both parties, which has certain practical significance for the prosperous development of live streaming commerce. In future research, the authors will consider the regulatory role of the government and construct a more realistic game model to provide constructive suggestions for the sustainable prosperity of live streaming commerce. Meanwhile, there are also games between multiple brands and multiple anchors, as well as games among brands-anchors-the live streaming platforms, and the authors will conduct more in-depth research in the future.
Originality/value
So far, the co-impact of anchor influence and brand awareness has not been considered simultaneously in published articles. This paper provides theoretical guidance for the behavioral choices of the brand and the anchor under the live streaming commerce, which is conducive to the prosperous development of live streaming commerce.
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Abstract
Purpose
Emotions, understood as evolving mental states, are pivotal in shaping individuals“' decision-making, especially in ambiguous information evaluation, probability estimation of events, and causality analysis. Public–private partnership (PPP) projects represent a confluence of “economic–environmental–social” dimensions, wherein stakeholder behavior follows the sequential progression of “cognition–emotion–action.” Consequently, comprehending the effects of emotional shifts on stakeholder's decision-making processes is vital to fostering the sustainability of PPP projects.
Design/methodology/approach
The paper utilizes rank-dependent expected utility and evolutionary game theory to systematically examine the influence of emotional factors on stakeholders' behavior and decision-making processes within PPP projects. The paper integrates three emotional state functions—optimism, pessimism and rationality—into the PPP framework, highlighting the intricate interactions among the government, private sector, surrounding public and the media. Furthermore, the paper amalgamates the evolutionary pathways of environmental rights incidents with the media's role. Through equilibrium analysis and numerical simulation, the paper delves into the diverse interplay of emotions across different phases of the environmental rights incident, assessing the impact of these emotions on the evolutionary game's equilibrium results.
Findings
Emotions significantly influence the microlevel decisions of PPP stakeholders, adapting continually based on event dynamics and media influences. When the private sector demonstrates optimism and the surrounding public leans toward rationality or pessimism, the likelihood of the private sector engaging in speculative behavior escalates, while the surrounding public refrains from adopting a supervisory strategy. Conversely, when the private sector is pessimistic and the public is optimistic, the system fails to evolve a stable strategy. However, when government regulation intensifies, the private sector opts for a nonspeculative strategy, and the surrounding public adopts a supervisory strategy. Under these conditions, the system attains a relatively optimal state of equilibrium.
Originality/value
The paper develops a game model to examine the evolutionary dynamics between the surrounding public and private sectors concerning environmental rights protection in waste incineration PPP projects. It illuminates the nature of the conflicting interests among project participants, delves into the impact of emotional factors on their decision-making processes and offers crucial perspectives for the governance of such partnerships. Furthermore, this paper provides substantive recommendations for emotional oversight to enhance governance efficacy.
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Kausar Yasmeen, Mustafa Malik, Kashifa Yasmeen, Muhammad Adnan and Naema Mohammed Al Bimani
Tourism, Technology and Climate Change: The tourism industry is indispensable both for its socio-cultural offerings and its profound economic implications. The economic multiplier…
Abstract
Tourism, Technology and Climate Change: The tourism industry is indispensable both for its socio-cultural offerings and its profound economic implications. The economic multiplier effects inherent in the drivers of tourism can stimulate the regional economy even before these areas emerge as tourism meccas. While vast amounts of research have detailed tourism's overarching significance, there is an evident void in understanding its multifaceted impacts, particularly where technological advances, environmental performance (EP) and economic benefits converge. A thorough examination of 907 research records led to this chapter, which identifies these gaps by referencing nine observational and 11 intervention studies. Achieving a Cohen's kappa value of 0.75, the authors note a strong consensus among reviewers, adhering to Cohen's (1940) standards. The findings from the first quarter highlight several areas within the tourism industry that have been under-researched. Particularly, the integration of technology, from ATM infrastructures enhancing tourist financial experiences to digital platforms elevating traveller education and awareness, and tech-driven solutions addressing demographic and ethical considerations in tourism, remains insufficiently explored. Additionally, the authors recognise an existing gap in knowledge regarding the nexus between tourism development and its climatic repercussions, especially before tourism ventures are fully realized. This chapter aims to channel future research into these lesser-trodden areas, fostering a comprehensive grasp of tourism's evolution in the face of rapid technological advancements and its interplay with environmental shifts.
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Ming Gao, Anhui Pan, Yi Huang, Jiaqi Wang, Yan Zhang, Xiao Xie, Huanre Han and Yinghua Jia
The type 120 emergency valve is an essential braking component of railway freight trains, but corresponding diaphragms consisting of natural rubber (NR) and chloroprene rubber…
Abstract
Purpose
The type 120 emergency valve is an essential braking component of railway freight trains, but corresponding diaphragms consisting of natural rubber (NR) and chloroprene rubber (CR) exhibit insufficient aging resistance and low-temperature resistance, respectively. In order to develop type 120 emergency valve rubber diaphragms with long-life and high-performance, low-temperatureresistant CR and NR were processed.
Design/methodology/approach
The physical properties of the low-temperature-resistant CR and NR were tested by low-temperature stretching, dynamic mechanical analysis, differential scanning calorimetry and thermogravimetric analysis. Single-valve and single-vehicle tests of type 120 emergency valves were carried out for emergency diaphragms consisting of NR and CR.
Findings
The low-temperature-resistant CR and NR exhibited excellent physical properties. The elasticity and low-temperature resistance of NR were superior to those of CR, whereas the mechanical properties of the two rubbers were similar in the temperature range of 0 °C–150 °C. The NR and CR emergency diaphragms met the requirements of the single-valve test. In the low-temperature single-vehicle test, only the low-temperature sensitivity test of the NR emergency diaphragm met the requirements.
Originality/value
The innovation of this study is that it provides valuable data and experience for future development of type 120 valve rubber diaphragms.
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Libiao Bai, Xinru Zhang, Chaopeng Song and Jiaqi Wei
Effectively predicting research and development project portfolio benefit (R&D PPB) could assist organizations in monitoring the execution of research and development project…
Abstract
Purpose
Effectively predicting research and development project portfolio benefit (R&D PPB) could assist organizations in monitoring the execution of research and development project portfolio (R&D PP). However, due to the uncertainty and complexity of R&D PPB, current research remains lacking a valid R&D PPB prediction tool. Therefore, an R&D PPB prediction model is proposed via a backpropagation neural network (BPNN).
Design/methodology/approach
The R&D PPB prediction model is constructed via a refined immune genetic algorithm coupling backpropagation neural network (RIGA-BPNN). Firstly, considering the characteristics of R&D PP, benefit evaluation criteria are identified. Secondly, the benefit criteria values are derived as input variables to the model via trapezoidal fuzzy numbers, and then the R&D PPB value is determined as the output variable through the CRITIC method. Thirdly, a refined immune genetic algorithm (RIGA) is designed to optimize BPNN by enhancing polyfitness, crossover and mutation probabilities. Lastly, the R&D PPB prediction model is constructed via the RIGA-BPNN, followed by training and testing.
Findings
The accuracy of the R&D PPB prediction model stands at 99.26%. In addition, the comparative experiment results indicate that the proposed model surpasses BPNN and the immune genetic algorithm coupling backpropagation neural network (IGA-BPNN) in both convergence speed and accuracy, showcasing superior performance in R&D PPB prediction. This study enriches the R&D PPB predicting methodology by providing managers with an effective benefits management tool.
Research limitations/implications
The research implications of this study encompass three aspects. First, this study provides a profound insight into R&D PPB prediction and enriches the research in PP fields. Secondly, during the construction of the R&D PPB prediction model, the utilization of the composite system synergy model for quantifying synergy contributes to a comprehensive understanding of intricate interactions among benefits. Lastly, in this research, a RIGA is proposed for optimizing the BPNN to efficiently predict R&D PPB.
Practical implications
This study carries threefold implications for the practice of R&D PPM. To begin with, the approach proposed serves as an effective tool for managers to predict R&D PPB. Then, the model excels in efficiency and flexibility. Furthermore, the proposed model could be used to tackle additional challenges in R&D PPM, such as gauging the potential risk level of R&D PP.
Social implications
Effective predicting of R&D PPB enables organizations to allocate their limited resources more strategically, ensuring optimal use of capital, manpower and time. By accurately predicting benefit, an organization can prioritize high-potential initiatives, thereby improving innovation efficiency and reducing the risk of failed investments. This approach not only strengthens market competitiveness but also positions organizations to adapt more effectively to changing market conditions, fostering long-term growth and sustainability in a competitive business environment.
Originality/value
Incorporating the characteristics of R&D PP and quantifying the synergy between benefits, this study facilitates a more insightful R&D PPB prediction. Additionally, improvements to the polyfitness, crossover and mutation probabilities of IGA are made, and the aforementioned RIGA is applied to optimize the BPNN. It significantly enhances the prediction accuracy and convergence speed of the neural network, improving the effectiveness of the R&D PPB prediction model.
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Mingzhi Hu, Jiaqi Liu and Xue Wang
Individuals who spend a large percentage of their incomes on consumption are perceived to prefer risks. Since entrepreneurs are well recognized as risk-takers, this chapter…
Abstract
Individuals who spend a large percentage of their incomes on consumption are perceived to prefer risks. Since entrepreneurs are well recognized as risk-takers, this chapter investigates whether consumption propensity is associated with entrepreneurship. Using micro-level data from Chinese Household Income Project, we find that households with a higher income–consumption ratio on average have a higher preference for risk-seeking, while they have a lower probability to be entrepreneurs. However, households who have higher consumption–income ratio and are in the top 10% of the wealth distribution are more likely to embark on entrepreneurship. In addition, we find that in-system connection (relationship with government-related units) decreases the likelihood of starting new business, while out-system connection (relationship with market units) increases it. These findings suggest that in an imperfect financial market, start-up finance and connections play important roles for entrepreneurship.
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In order to resolve the problems of water shortage in China, oneshould consider the integration of irrigation projects, waterconservation and economical utilisation of water…
Abstract
In order to resolve the problems of water shortage in China, one should consider the integration of irrigation projects, water conservation and economical utilisation of water. Irrigation projects mean exploiting water resources. To transport water from rivers beyond their own flowing reaches, it is necessary to prove its applicability before undertaking construction work. Sinking wells can be done only in areas with a plentiful amount of groundwater. Reservoirs also should be constructed only in areas with sufficient water resources and where less arable land has to be irrigated. Water conservation is connected closely with afforestation or protection of forests as well as protection from industrial pollution. Economic utilisation of water resources includes using water wisely to grow crops, and economising on its use in industry and for domestic purposes.
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Kaimeng Zhang, Zhongxin Ni and Zhouyan Lu
This research paper aims to investigate the critical factors influencing the live commerce industry and their implications for Key Opinion Leaders (KOLs) and brands.
Abstract
Purpose
This research paper aims to investigate the critical factors influencing the live commerce industry and their implications for Key Opinion Leaders (KOLs) and brands.
Design/methodology/approach
The study comprehensively reviews previous research, develops relevant hypotheses and utilizes personal information from 66 anchors, along with data from 23,000 product links obtained from the backends of live commerce platforms.
Findings
The study emphasizes that KOLs with higher traffic significantly influence Gross Merchandise Volume (GMV). Intriguingly, KOLs with lower traffic levels exhibit a more pronounced effect on Return on Investment (ROI), highlighting their significance in driving profitability. Furthermore, the study explores the correlation between KOL hashtags and GMV/ROI and the intricate relationship between product types and KOL hashtags.
Practical implications
The findings significantly enhance the understanding of live shopping behavior and provide valuable insights for business management strategies. Practitioners can leverage this empirical evidence to make informed decisions, utilizing extensive data samples of KOLs and brands.
Originality/value
This research contributes unique insights into the live-streaming commerce industry using backend data from Live Streaming E-commerce platforms. The findings are more accurate based on market data than previous studies that relied on platform reviews or questionnaires. Additionally, this paper investigates the impact of KOLs on the performance of live e-commerce from three perspectives: GMV, ROI and hot-selling products.