China
Africa
Explore chapters and articles related to this topic
Employee Acceptance of ERP Information Solutions in Service Organizations: A Tam-Based Research
Published in Arvind K. Birdie, Employees and Employers in Service Organizations, 2017
Simona Sternad-Zabukovšek, Samo Bobek
The problem of TAM researches are that most researchers investigate small numbers of external factors that have influence on user acceptance and usage. In context of ERP systems, there are more external factors that can have influence on users’ acceptance and extended usage. Because of that, conceptualization of higher order factors (in our case second-order factors), in which more external factors jointly have to be included, have been researched because we wanted to extent the understanding of user behavior in ERP settings. On that presumption, we also hypothesized: H4: There is group of external factors which have influence through conceptual factor personal characteristics and information literacy on use of ERP system.H5: There is group of external factors which have influence through conceptual factor system and technological characteristics on use of ERP system.H6: There is group of external factors which have influence through conceptual factor organizational-process characteristics on use of ERP system.
Feedback Equivalence of Nonlinear Control Systems: A Survey on Formal Approach
Published in Wilfrid Perruquetti, Jean-Pierre Barbot, Chaos in Automatic Control, 2018
We have an analogous result for feedback equivalence to the strict feedforward form, where the role of strong infinitesimal symmetries is replaced by that of infinitesimal symmetries. To state this, we need the following considerations. We will write Σ(f, g), to denote the system Σ defined by the pair of vector fields (f, g). Assume that v is an infinitesimal symmetry of Σ(f, g), nonstationary at p ∈ X, that is, such that v(p) ≠ 0. Then the second item of Proposition 16 implies that there exists a feedback pair (α, β) such that v is a strong infinitesimal symmetry of the system Σ˜(f˜,g˜), where f˜=f+gα and g˜=gβ. Thus there exists a neighborhood Xp of p in which the factor system Σ˜/∼v is well defined, where the equivalence relation ∼v is induced by the local action of the 1-parameter local group defined by v. Notice that given a system Σ, there are many systems Σ˜(f˜,g˜), feedback equivalent to Σ, and such that v is a strong infinitesimal symmetry of Σ˜. We will denote by Σ˜ any of those systems. Actually, any two such systems are equivalent by a feedback pair (α˜,β˜), where the functions α˜ and β˜ are constant on the trajectories of v.
A networked risk perspective for analysing debris flow losses factors considering mitigation measures
Published in Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards, 2023
Yu-xin Wu, Shi-yu Hu, Gang Fan, Jia-wen Zhou, Hui-ge Xing
The research steps below were used to analyse the complex relationships among the influencing factors of debris flow disaster losses and identify the most critical factors. Identification of factors. The factor system of debris flow losses was preliminarily summarised based on a literature review and field research. Then, professors, researchers, and staff of relevant institutions engaged in geohazard research were invited to a focus group meeting (Table 1) to assess the comprehensiveness and accuracy of the factors. All participants must have theoretical knowledge and fieldwork experience to make the discussion results representative.Establishment of the adjacency matrix. Each factor is first regarded as “risk” so that the connection between factors is unified as “risk transmission”. For example, “mitigation measures” are considered “lack of mitigation measures or inadequate implementation”. Group members were invited to complete a questionnaire to quantify the relationships between the factors. For each pair, participants need to consider “Does factor A transfer risk to factor B? If so, to what extent?” and then fill the corresponding position in the matrix with the degree of impact. A Likert scale was used to quantify the extent of influence, where 1 and 5 indicate the lowest and highest impact values, respectively (with 0 indicating no relationship). Finally, all questionnaires would be checked and averaged for subsequent network analysis. The questionnaire usually includes research background, factor description, filling examples, adjacency matrix, and basic information. For more information and the results of the questionnaire, please check the documents posted on OSF (https://osf.io/UYJ2H/).Network analysis. The adjacency matrix was imported into the SNA software NetMiner 4 to visualise the network of factors influencing debris flow losses. By calculating network indicators, it analyses the nature of the network and factors. Then it identifies key factors in the formation process of debris flow losses. Finally, the research results and interview experiences were combined to discuss the implications for disaster loss reduction.