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Open access

Michael Pace

Abstract

This non-experimental correlational study extends previous research investigating the relationship between project management methodology and reported project success, as well as the moderating variables of industry and project manager experience. The sample included North American project managers with five years’ experience, 25 years of age or older, and experience with multiple project management methodologies. The survey instrument consisted of 58 questions, utilizing a 5-point Likert scale to record responses. The survey contained three sections, including demographic information, questions related to a successful project, and questions related to a less-than successful (failed / challenged) project. 367 usable responses were received. The examination of the constructs included Pearson’s correlation coefficient as well as linear regression to determine the impact of moderating variables. Results indicated that project management methodology has a weak correlation with reported project success, and this correlation is not moderated by industry nor project manager experience. The results did not align with previously conducted studies, illustrating a need to continue the study of methods impacting success including investigating additional moderating variables.

Open access

Chuanming Yu, Xingyu Zhu, Bolin Feng, Lin Cai and Lu An

Abstract

Purpose

Online reviews on tourism attractions provide important references for potential tourists to choose tourism spots. The main goal of this study is conducting sentiment analysis to facilitate users comprehending the large scale of the reviews, based on the comments about Chinese attractions from Japanese tourism website 4Travel.

Design/methodology/approach

Different statistics- and rule-based methods are used to analyze the sentiment of the reviews. Three groups of novel statistics-based methods combining feature selection functions and the traditional term frequency-inverse document frequency (TF-IDF) method are proposed. We also make seven groups of different rules-based methods. The macro-average and micro-average values for the best classification results of the methods are calculated respectively and the performance of the methods are shown.

Findings

We compare the statistics-based and rule-based methods separately and compare the overall performance of the two method. According to the results, it is concluded that the combination of feature selection functions and weightings can strongly improve the overall performance. The emotional vocabulary in the field of tourism (EVT), kaomojis, negative and transitional words can notably improve the performance in all of three categories. The rule-based methods outperform the statistics-based ones with a narrow advantage.

Research limitation

Two limitations can be addressed: 1) the empirical studies to verify the validity of the proposed methods are only conducted on Japanese languages; and 2) the deep learning technology is not been incorporated in the methods.

Practical implications

The results help to elucidate the intrinsic characteristics of the Japanese language and the influence on sentiment analysis. These findings also provide practical usage guidelines within the field of sentiment analysis of Japanese online tourism reviews.

Originality/value

Our research is of practicability. Currently, there are no studies that focus on the sentiment analysis of Japanese reviews about Chinese attractions.

Open access

Yaoyao Song, Torben Schubert, Huihui Liu and Guoliang Yang

Abstract

Purpose

This paper aims to investigate the scientific productivity of China’s science system.

Design/methodology/approach

This paper employs the Malmquist productivity index (MPI) based on Data Envelopment Analysis (DEA).

Findings

The results reveal that the overall efficiency of Chinese universities increased significantly from 2009 to 2016, which is mainly driven by technological progress. From the perspective of the functions of higher education, research and transfer activities perform better than the teaching activities.

Research limitations

As an implication, the indicator selection mechanism, investigation period and the MPI model can be further extended in the future research.

Practical implications

The results indicate that Chinese education administrative departments should take actions to guide and promote the teaching activities and formulate reasonable resource allocation regulations to reach the balanced development in Chinese universities.

Originality/value

This paper selects 58 Chinese universities and conducts a quantified measurement during the period 2009–2016. Three main functional activities of universities (i.e. teaching, researching, and application) are innovatively categorized into different schemes, and we calculate their performance, respectively.

Open access

Haiyun Xu, Chao Wang, Kun Dong and Zenghui Yue

Abstract

Purpose

Formal concept analysis (FCA) and concept lattice theory (CLT) are introduced for constructing a network of IDR topics and for evaluating their effectiveness for knowledge structure exploration.

Design/methodology/approach

We introduced the theory and applications of FCA and CLT, and then proposed a method for interdisciplinary knowledge discovery based on CLT. As an example of empirical analysis, interdisciplinary research (IDR) topics in Information & Library Science (LIS) and Medical Informatics, and in LIS and Geography-Physical, were utilized as empirical fields. Subsequently, we carried out a comparative analysis with two other IDR topic recognition methods.

Findings

The CLT approach is suitable for IDR topic identification and predictions.

Research limitations

IDR topic recognition based on the CLT is not sensitive to the interdisciplinarity of topic terms, since the data can only reflect whether there is a relationship between the discipline and the topic terms. Moreover, the CLT cannot clearly represent a large amounts of concepts.

Practical implications

A deeper understanding of the IDR topics was obtained as the structural and hierarchical relationships between them were identified, which can help to get more precise identification and prediction to IDR topics.

Originality/value

IDR topics identification based on CLT have performed well and this theory has several advantages for identifying and predicting IDR topics. First, in a concept lattice, there is a partial order relation between interconnected nodes, and consequently, a complete concept lattice can present hierarchical properties. Second, clustering analysis of IDR topics based on concept lattices can yield clusters that highlight the essential knowledge features and help display the semantic relationship between different IDR topics. Furthermore, the Hasse diagram automatically displays all the IDR topics associated with the different disciplines, thus forming clusters of specific concepts and visually retaining and presenting the associations of IDR topics through multiple inheritance relationships between the concepts.

Open access

Leo Egghe, Yves Fassin and Ronald Rousseau

Abstract

Purpose

To show for which publication-citation arrays h-type indices are equal and to reconsider rational h-type indices. Results for these research questions fill some gaps in existing basic knowledge about h-type indices.

Design/methodology/approach

The results and introduction of new indicators are based on well-known definitions.

Findings

The research purpose has been reached: answers to the first questions are obtained and new indicators are defined.

Research limitations

h-type indices do not meet the Bouyssou-Marchant independence requirement.

Practical implications

On the one hand, more insight has been obtained for well-known indices such as the h- and the g-index and on the other hand, simple extensions of existing indicators have been added to the bibliometric toolbox. Relative rational h-type indices are more useful for individuals than the existing absolute ones.

Originality/value

Answers to basic questions such as “when are the values of two h-type indices equal” are provided. A new rational h-index is introduced.

Open access

Dag W. Aksnes and Gunnar Sivertsen

Abstract

Purpose

The purpose of this study is to assess the coverage of the scientific literature in Scopus and Web of Science from the perspective of research evaluation.

Design/methodology/approach

The academic communities of Norway have agreed on certain criteria for what should be included as original research publications in research evaluation and funding contexts. These criteria have been applied since 2004 in a comprehensive bibliographic database called the Norwegian Science Index (NSI). The relative coverages of Scopus and Web of Science are compared with regard to publication type, field of research and language.

Findings

Our results show that Scopus covers 72 percent of the total Norwegian scientific and scholarly publication output in 2015 and 2016, while the corresponding figure for Web of Science Core Collection is 69 percent. The coverages are most comprehensive in medicine and health (89 and 87 percent) and in the natural sciences and technology (85 and 84 percent). The social sciences (48 percent in Scopus and 40 percent in Web of Science Core Collection) and particularly the humanities (27 and 23 percent) are much less covered in the two international data sources.

Research limitation

Comparing with data from only one country is a limitation of the study, but the criteria used to define a country’s scientific output as well as the identification of patterns of field-dependent partial representations in Scopus and Web of Science should be recognizable and useful also for other countries.

Originality/value

The novelty of this study is the criteria-based approach to studying coverage problems in the two data sources.

Open access

M. Abdullah Eissa

Abstract

This paper proposes a newly adaptive single-neuron proportional integral derivative (SNPID) controller that uses fuzzy logic as an adaptive system. The main problem of the classical controller is lacking the required robustness against disturbers, measurement noise in industrial applications. The new formula of the proposed controller helps in fixing this problem based on the fuzzy logic technique. In addition, the genetic algorithm (GA) is used to optimize parameters of the SNPID controller. Because of the high demands on the availability and efficiency of electrical power production, the design of robust load-frequency controller is becoming increasingly important due to its potential in increasing the reliability, maintainability and safety of power systems. So, the proposed controller has been applied for load-frequency control (LFC) of a single-area power system. The effectiveness of the proposed SNPID controller has been compared with the conventional controllers. The simulation results show that the proposed controller approach provides better damping of oscillations with a smaller settling time. This confirms its superiority against its counterparts. In addition, the results show the robustness of the proposed controller against the parametric variation of the system.

Open access

Leszek Jarzebowicz

Abstract

Pulse width modulation (PWM) of inverter output voltage causes the waveforms of motor phase currents to consist of distinctive ripples. In order to provide suitable feedback for the motor current controllers, the mean value must be extracted from the currents’ waveforms in every PWM cycle. A common solution to derive the mean phase currents is to sample their value at the midpoint of a symmetrical PWM cycle. Using an assumption of linear current changes in steady PWM subintervals, this midpoint sample corresponds to the mean current in the PWM cycle. This way no hardware filtering or high-rate current sampling is required. Nevertheless, the assumption of linear current changes has been recently reported as over simplistic in permanent magnet synchronous motor (PMSM) drives operating with low switching-to-fundamental frequency ratio (SFFR). This, in turn, causes substantial errors in the representation of the mean phase currents by the midpoint sample. This paper proposes a solution for deriving mean phase currents in low SFFR PMSM drives, which does not rely on the linear current change assumption. The method is based on sampling the currents at the start point of a PWM cycle and correcting the sampled value using a model-based formula that reproduces the current waveforms. Effectiveness of the method is verified by simulation for an exemplary setup of high-speed PMSM drive. The results show that the proposed method decreases the error of determining the mean phase currents approximately 10 times when compared to the classical midpoint sampling technique.

Open access

Lu An, Xingyue Yi, Yuxin Han and Gang Li

Abstract

This study aims at constructing a microblog influence prediction model and revealing how the user, time, and content features of microblog entries about public health emergencies affect the influence of microblog entries. Microblog entries about the Ebola outbreak are selected as data sets. The BM25 latent Dirichlet allocation model (LDA-BM25) is used to extract topics from the microblog entries. A microblog influence prediction model is proposed by using the random forest method. Results reveal that the proposed model can predict the influence of microblog entries about public health emergencies with a precision rate reaching 88.8%. The individual features that play a role in the influence of microblog entries, as well as their influence tendencies are also analyzed. The proposed microblog influence prediction model consists of user, time, and content features. It makes up the deficiency that content features are often ignored by other microblog influence prediction models. The roles of the three features in the influence of microblog entries are also discussed.