Yue Suo, Jingyu Li, Yuanchun Shi and Peifeng Xiang
Smart spaces are open complex computing systems, consisting of a large variety of cooperative smart things. Central to building smart spaces is the support for sophisticated…
Abstract
Purpose
Smart spaces are open complex computing systems, consisting of a large variety of cooperative smart things. Central to building smart spaces is the support for sophisticated coordination among diverse smart things collaborating to accomplish specified tasks. Multi‐agent systems are often used as the software infrastructures to address the coordination issue in smart spaces. However, since agents in smart spaces are dynamic, resource‐bounded and have complicated service dependencies, current approaches to coordination in multi‐agent systems encounter new challenges when applied in smart spaces. The purpose of this paper is to address these issues.
Design/methodology/approach
The paper presents Baton, a service management system to explicitly resolve the particular issues stemming from smart spaces when coordinating agents. Baton is designed as a complement to coordination approaches in multi‐agent systems with a focus on mechanisms for service discovery, composition, request arbitration and dependency maintenance. Baton is now deployed in our own smart spaces to achieve better agent coordination.
Findings
The effectiveness and efficiency of Baton is validated by its practical use in the designed scenario and some evaluation experiments.
Research limitations/implications
An attempt at performing dynamic service composition in Baton is made by using semantic information in future work.
Originality/value
Baton, a service management system to explicitly resolve the particular issues stemming from smart spaces when coordinating agents is presented.
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Abubakar Sadiq Muhammad, Ibrahim Adeshola and Labaran Isiaku
Generation Z (Gen-Z), sometimes known as “digital natives”, represents the first generation to become immersed in digital communication. In a multicultural environment, this study…
Abstract
Purpose
Generation Z (Gen-Z), sometimes known as “digital natives”, represents the first generation to become immersed in digital communication. In a multicultural environment, this study aims to explore which types of factors are most beneficial in connection with Gen-Z’s impulsive purchase behaviour.
Design/methodology/approach
This study adopts an exploratory sequential mixed-method design, incorporating both qualitative and quantitative approaches. In Study 1, focus group discussions are conducted to address “why” and “how” questions, whereas Study 2 uses a quantitative method to test the hypothetical model. The model is assessed using structural equation modelling. This study used the stimulus–organism–response (SOR) framework in the context of Instagram.
Findings
Building on Mehrabian and Russell’s (1974) concept and focus group discussions, Study 1 introduces a novel SOR model tailored to Instagram. In Study 2, the model is tested, and results confirm most hypotheses, except for three. Factors such as aesthetic appeal, scarcity promotions and discounted prices stimulate impulse buying behaviour in Gen-Z. Positive emotional responses evoked by these factors also influence impulse buying, whereas the impact of negative emotional responses is found to be insignificant.
Originality/value
This mixed-methods study enhances the theoretical understanding of Gen-Zers’ impulse buying behaviour by highlighting the influence of diverse independent variables. By using the SOR framework, it reveals the intricate emotional aspects impacting impulsive purchase decisions. The research provides new insights into online impulsive buying behaviour, particularly relevant to consumer psychology and behavioural economics among young collectivist consumers.
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Xiao-qiang Jiao, Gang He, Zhen-ling Cui, Jian-bo Shen and Fu-suo Zhang
The purpose of this paper is to analyze the historical pattern of environmental cost due to grain production in China and to provide further implications of technologies and…
Abstract
Purpose
The purpose of this paper is to analyze the historical pattern of environmental cost due to grain production in China and to provide further implications of technologies and policies for the transformation of China’s agricultural development toward sustainable intensification.
Design/methodology/approach
The data sets about grain production, arable land and chemical fertilizer use in China were collected from FAO, NBSC, and IFA. Greenhouse gas emissions were estimated using life cycle assessments. The policies concerning grain production and the environment were collected from the Ministry of Agriculture, and the State Council of China.
Findings
China has produced enough food to feed its growing population, but has neglected the resource-environmental costs of grain production since 1978. Consequently, China’s grain production is always accompanied with a high cost of resource and environment sustainability. However, from 2006 to 2015, the growth rate of grain production has surpassed that of chemical fertilizer consumption, resulting in improvement in nutrient use efficiency and decreasing trends of environmental cost for grain production. This could be partially attributed to technology innovations, such as Soil-Testing and Fertilizer-Recommendations (STFR), soil quality and crop management improvement, and so on, and policy supports (policies of STFR, soil quality improvement, and high-yield construction). This indicated that China’s grain production is starting to transform from high-input and high-output model to “less for more.”
Originality/value
This study is the first to determine the detailed, historical role of technological innovation and agri-environmental policy on the sustainability of grain production in China. The findings should have significant implications for technology and policy for the transformation of China’s agriculture development to sustainable intensification.
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Studies of Tianhou-Mazu cult have been focused on three themes: studies in Taiwan emphasize hegemonic order; studies in Hong Kong reveal a relationship of “sisterhood” alliances;…
Abstract
Purpose
Studies of Tianhou-Mazu cult have been focused on three themes: studies in Taiwan emphasize hegemonic order; studies in Hong Kong reveal a relationship of “sisterhood” alliances; and studies in Singapore highlight the important role of ethnic groups. The rebuilding of the goddess’s ancestral temple in early 1980s and her acquiring a world intangible cultural heritage status in the early twenty-first century facilitate the redefinition of overseas Chinese’s religious affiliation. The purpose of this paper is to discuss this global development of the cult from the 1980s and its ritual implication in overseas Chinese communities.
Design/methodology/approach
This paper, by comparing the Tianhou-Mazu cult in Taiwan, Hong Kong and Southeast Asian Chinese settlements, argues that from sisters to descended replicas, or from local alliances to global hegemony, the cult of Tianhou-Mazu since the 1980s has not only replaced local culture with an emphasis on “high culture,” but also represents a religious strategy regarding local people’s interpretation of correctness and authority.
Findings
This paper argues that despite the imposition of hegemonic power from various authorities, popular religion is a matter of choice. This reflects how local religious practice is construed according to the interpretation of global cultural languages by the elite Chinese; their decision of when and how to reconnect with the goddess’s ancestral temple or the “imperial state,” or to form alliances with other local communities; and the implementation of the local government’s cultural policy.
Originality/value
This paper is one of the few attempts comparing development of a folk cult in various communities.
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Zhentao Li, Xiaoli Yin, Jixiang Yue, Fuyu Liu, Muming Hao and Baojie Ren
The purpose of this paper is to study the effects of operating conditions including process coefficient, lubricant viscosity and cavitation pressure on the cavitation of spiral…
Abstract
Purpose
The purpose of this paper is to study the effects of operating conditions including process coefficient, lubricant viscosity and cavitation pressure on the cavitation of spiral groove liquid-film seal (SG-LFS).
Design/methodology/approach
A mathematical model of SG-LFS is established based on the JFO boundary and a relative density is introduced. The universal governing equation after a coordinate transformation is discretized by the FVM method and solved by the Gauss-Seidel relaxation scheme.
Findings
The results indicate that the two-dimensional size of cavitation and cavitation degree are affected significantly by the process coefficient and lubricant viscosity but the effect of cavitation pressure can be ignored.
Originality/value
The effect mechanisms of operating conditions on the cavitation of SG-LFS are studied by the JFO boundary and cavitation degree characterized by a relative density. The results presented are helpful to perfect and deeply understand the cavitation mechanism of liquid-film seal.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-03-2020-0083/
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Yue Li, Xiaoquan Chu, Zetian Fu, Jianying Feng and Weisong Mu
The purpose of this paper is to develop a common remaining shelf life prediction model that is generally applicable for postharvest table grape using an optimized radial basis…
Abstract
Purpose
The purpose of this paper is to develop a common remaining shelf life prediction model that is generally applicable for postharvest table grape using an optimized radial basis function (RBF) neural network to achieve more accurate prediction than the current shelf life (SL) prediction methods.
Design/methodology/approach
First, the final indicators (storage temperature, relative humidity, sensory average score, peel hardness, soluble solids content, weight loss rate, rotting rate, fragmentation rate and color difference) affecting SL were determined by the correlation and significance analysis. Then using the analytic hierarchy process (AHP) to calculate the weight of each indicator and determine the end of SL under different storage conditions. Subsequently, the structure of the RBF network redesigned was 9-11-1. Ultimately, the membership degree of Fuzzy clustering (fuzzy c-means) was adopted to optimize the center and width of the RBF network by using the training data.
Findings
The results show that this method has the highest prediction accuracy compared to the current the kinetic–Arrhenius model, back propagation (BP) network and RBF network. The maximum absolute error is 1.877, the maximum relative error (RE) is 0.184, and the adjusted R2 is 0.911. The prediction accuracy of the kinetic–Arrhenius model is the worst. The RBF network has a better prediction accuracy than the BP network. For robustness, the adjusted R2 are 0.853 and 0.886 of Italian grape and Red Globe grape, respectively, and the fitting degree are the highest among all methods, which proves that the optimized method is applicable for accurate SL prediction of different table grape varieties.
Originality/value
This study not only provides a new way for the prediction of SL of different grape varieties, but also provides a reference for the quality and safety management of table grape during storage. Maybe it has a further research significance for the application of RBF neural network in the SL prediction of other fresh foods.
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Zhixun Wen, Fei Li and Ming Li
The purpose of this paper is to apply the concept of equivalent initial flaw size (EIFS) to the anisotropic nickel-based single crystal (SX) material, and to predict the fatigue…
Abstract
Purpose
The purpose of this paper is to apply the concept of equivalent initial flaw size (EIFS) to the anisotropic nickel-based single crystal (SX) material, and to predict the fatigue life on this basis. The crack propagation law of SX material at different temperatures and the weak correlation of EIFS values verification under different loading conditions are also investigated.
Design/methodology/approach
A three-parameter time to crack initial (TTCI) method with multiple reference crack lengths under different loading conditions is established, which include the TTCI backstepping method and EIFS fitting method. Subsequently, the optimized EIFS distribution is obtained based on the random crack propagation rate and maximum likelihood estimation of median fatigue life. Then, an effective driving force based on anisotropic and mixed crack propagation mode is proposed to describe the crack propagation rate in the small crack stage. Finally, the fatigue life of three different temperature ESE(T) standard specimens is predicted based on the EIFS values under different survival rates.
Findings
The optimized EIFS distribution based on EIFS fitting - maximum likelihood estimation (MLE) method has the highest accuracy in predicting the total fatigue life, with the range of EIFS values being about [0.0028, 0.0875] (mm), and the mean value of EIFS being 0.0506 mm. The error between the predicted fatigue life based on the crack propagation rate and EIFS distribution for survival rates ranges from 5% to 95% and the experimental life is within two times dispersion band.
Originality/value
This paper systematically proposes a new anisotropic material EIFS prediction method, establishing a framework for predicting the fatigue life of SX material at different temperatures using fracture mechanics to avoid inaccurate anisotropic constitutive models and fatigue damage accumulation theory.
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Siyuan Huang, Limin Liu, Xiongjun Fu, Jian Dong, Fuyu Huang and Ping Lang
The purpose of this paper is to summarize the existing point cloud target detection algorithms based on deep learning, and provide reference for researchers in related fields. In…
Abstract
Purpose
The purpose of this paper is to summarize the existing point cloud target detection algorithms based on deep learning, and provide reference for researchers in related fields. In recent years, with its outstanding performance in target detection of 2D images, deep learning technology has been applied in light detection and ranging (LiDAR) point cloud data to improve the automation and intelligence level of target detection. However, there are still some difficulties and room for improvement in target detection from the 3D point cloud. In this paper, the vehicle LiDAR target detection method is chosen as the research subject.
Design/methodology/approach
Firstly, the challenges of applying deep learning to point cloud target detection are described; secondly, solutions in relevant research are combed in response to the above challenges. The currently popular target detection methods are classified, among which some are compared with illustrate advantages and disadvantages. Moreover, approaches to improve the accuracy of network target detection are introduced.
Findings
Finally, this paper also summarizes the shortcomings of existing methods and signals the prospective development trend.
Originality/value
This paper introduces some existing point cloud target detection methods based on deep learning, which can be applied to a driverless, digital map, traffic monitoring and other fields, and provides a reference for researchers in related fields.
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René Heiberg Jørgensen, Jan Møller Jensen and Yingkui Yang
The purpose of this paper is to examine the influence of environmental concern, perceived consumer effectiveness (PCE), green self-identity and social influence on Danish…
Abstract
Purpose
The purpose of this paper is to examine the influence of environmental concern, perceived consumer effectiveness (PCE), green self-identity and social influence on Danish Generation Z consumers’ green purchase intention across three product categories: food, clothing and mobile phones.
Design/methodology/approach
Data were collected through convenience sampling, asking undergraduate students in a quantitative data analysis class at the University of Southern Denmark to share a link to the online survey via mail and through their social media platforms. This study includes 287 usable cases. Structural equation modeling (AMOS) was used to test the suggested relationships.
Findings
The results show that environmental concern, PCE, green self-identity and social influence positively relate to Danish Generation Z consumers’ green purchase intentions. However, results also suggest that the influence of the different factors varies across product categories.
Practical implications
The results show that marketers must refine their understanding of what guides green consumption, as the factors leading to green purchase intention vary across product categories. Therefore, practitioners need a deeper understanding of their specific category. The results offer insight into food, clothing and mobile phones.
Originality/value
To the best of the authors’ knowledge, this is one of the first studies investigating the antecedents to green purchase intentions across product categories.
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Maria Giuffrida, Riccardo Mangiaracina, Alessandro Perego and Angela Tumino
The purpose of this paper is to support companies’ risk-informed selection of a logistics solution to operate in China via cross-border e-commerce (CBEC).
Abstract
Purpose
The purpose of this paper is to support companies’ risk-informed selection of a logistics solution to operate in China via cross-border e-commerce (CBEC).
Design/methodology/approach
Decision theory is applied to the recent field of CBEC. This theoretic setup involves a decision maker who must choose among a set of alternatives, whose consequences depend on uncertain factors (Savage, 1954). The study develops an activity-based model to calculate logistics costs in a deterministic setting. Simulations and probabilistic sensitivity analyses are later performed to evaluate the impact of uncertainty.
Findings
There are four main solutions to enter China, determined by the adopted international transport mean and the presence of a local warehouse. The most important risk factors affecting the choice of the logistics solution are change of CBEC regulation, product value, expected service level and demand level.
Originality/value
From a theoretical perspective, this study improves CBEC literature, so far characterised by descriptive papers, often lacking industry focus or empirical exploration. It also provides new application opportunities for decision theory, whereas previous contributions have proposed different theoretical approaches, such as transaction cost or institutional theory. From a practical viewpoint, the paper is the first to compare the costs of the main logistics solutions to sell online to China, by taking uncertainty into account. The results can be used to better understand the differences among solutions and identify the most critical parameters. Finally, this research provides some observations for policy implementation.