Intelligent decision-making of online shopping behavior based on internet of things

Fu, Hanliang; Manogaran, Gunasekaran; Wu, Kuang; Cao, Ming; Jiang, Song; Yang, Aimin

doi:10.1016/j.ijinfomgt.2019.03.010

Cited by 163 publications

(117 citation statements)

References 31 publications

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“…The results of the discriminant validity test are shown in Table 5. The effective method of the discriminant validity test was used to determine whether the square root of the AVE value relative to potential variables was greater than all other potential variables and other correlation coefficients, which could be proved by the research results of Fornell and Larcker [23,24]. Therefore, it was not difficult to see that the data in Table 5 indicates that the potential variables in our questionnaire had good discriminant validity.…”

Section: Assessment Model Establishmentmentioning

confidence: 91%

“…Considering the frequency and possible adverse effects of risks, it also classified them according to the principle of average. After quantifying the level of policy risk, this paper classified three levels, namely, low level (<20), medium level (21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33)(34)(35)(36)(37)(38)(39)(40), and high level (>40), so as to understand the meaning of policy risk index more intuitively.…”

Section: Risk Assessmentmentioning

confidence: 99%

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Exploring Critical Variables That Affect the Policy Risk Level of Industrial Heritage Projects in China

Guo

Zhang

et al. 2019

Sustainability

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With the rapid development of the transformation and urbanization of Chinese social structures, more and more industrial heritage renewal projects are emerging. However, there are significant policy risks associated with Chinese industrial heritage renewal projects. Through a literature review, a total of 20 policy risk factors were determined, and a total of 10 industrial heritage renewal project managers in six regions nationwide conducted a pilot study. A questionnaire survey was conducted to collect 398 evaluations of these 20 risk factors from relevant professionals. Secondly, through confirmatory factor analysis, a six-part policy risk assessment model was established. The results indicated that the critical variables that affect the policy risk level were: (1) industry maturity, (2) tax policy, (3) financial freedom, (4) the rule of law, (5) local market size, and (6) local market experience. Moreover, there are significant opportunities and policy risks in Chinese industrial heritage renewal projects, and appropriate strategies can capture these opportunities and mitigate risks. As there are few pieces of research on the policy risks of industrial heritage renewal projects in China, this study has a certain reference significance for the policy risk management of industrial heritage renewal projects in China.

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Section: Assessment Model Establishmentmentioning

confidence: 91%

Section: Risk Assessmentmentioning

confidence: 99%

Exploring Critical Variables That Affect the Policy Risk Level of Industrial Heritage Projects in China

Guo

Zhang

et al. 2019

Sustainability

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show abstract

“…The definition of "Internet of Things Technology" is [16] a network technology through the RFID, infrared sensors, the global positioning system (GPS), laser scanners, and other information-sensing equipment. In order to achieve intelligent identification, positioning, tracking, monitoring, and management, any items connected with the Internet for information exchange and communication can [17] according to the agreement. Its core and foundation is still "Internet technology"; it is a kind of network technology that extends and expands on the basis of Internet technology.…”

Section: Iot Technologymentioning

confidence: 99%

Research on Intelligent Guidance Optimal Path of Shared Car Charging in the IOT Environment

Sun

Jin

Guo

et al. 2020

Wireless Communications and Mobile Computing

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In recent years, with the improvement of Internet of Things (IOT) technology, a “shared” service concept has appeared in people’s life. In the limited available resources, it is of great value to study the optimal path of charging pile selection for shared cars. With the help of Internet of Things technology and through analyzing the collected data, this paper introduces three path optimization methods, the Dijkstra algorithm, heuristic algorithm A∗, and improved particle swarm optimization (PSO) algorithm; establishes relevant convergence conditions; and takes the actual path cost as the criterion to judge the optimal path. In addition, this paper studies the optimal path from the shared car to the charging pile. Through the simulation experiment, the results show that compared with the traditional optimal path algorithm, the improved particle swarm optimization algorithm has strong parallelism and better search effect for optimal path selection in the case of large number of traffic path nodes and complex paths, which fully reflects the performance advantage of the algorithm.

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“…According to the studies of Smith and Lewis [8], the following observation variables were set to measure paradox cognition ( Table 1). In recent years, increasing numbers of scholars have noticed the theory of paradox, and applied this theory to their own studies [26][27][28][29][30].…”

Section: Questionnaire Designmentioning

confidence: 99%

A Study on the Relationship between Paradox Cognition, Green Industrial Production, and Corporate Performance

Gao

Khan

2019

Sustainability

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Based on the theory of paradox cognition, a relationship model among paradox cognition, industrial green production, and enterprise performance has been constructed, which mainly focuses on a study on whether the paradox cognition can have positive influences on the green production behavior of industrial enterprises, and then further promote the improvement of enterprises' economic benefits. The author wrote this thesis on the basis of results obtained from 305 sample surveys and verified the direct and indirect influence relationships among variables in the model with structural equation path coefficient and mediation effect. The empirical results show that: firstly, paradox cognition has a positive and significant impact on the industrial green production behavior. The higher the level of paradox cognition, the more likely the enterprises are to implement the industrial green production behavior. Secondly, paradox cognition can improve the potential performance of enterprises by affecting "green product provision", "green production management", and "green production technology", and then indirectly improve the financial performance of enterprises.

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Intelligent decision-making of online shopping behavior based on internet of things

Cited by 163 publications

References 31 publications

Exploring Critical Variables That Affect the Policy Risk Level of Industrial Heritage Projects in China

Exploring Critical Variables That Affect the Policy Risk Level of Industrial Heritage Projects in China

Research on Intelligent Guidance Optimal Path of Shared Car Charging in the IOT Environment

A Study on the Relationship between Paradox Cognition, Green Industrial Production, and Corporate Performance

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