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The purpose of this paper is to perform the computational fluid dynamics (CFD) simulation with experimental validation to investigate the particle segregation effect in abrupt and smooth shapes circulating fluidized bed (CFB) risers.

The experimental investigations were carried out in lab-scale CFB systems and the CFD simulations were performed by using commercial software BARRACUDA. Special attention was paid to investigate the gas-particle flow behavior at the top of the riser with three different superficial velocities, namely, 4, 6 and 7.7 m/s. Here, a CFD-based noble simulation approach called multi-phase particle in cell (MP-PIC) was used to investigate the effect of traditional drag models (Wen-Yu, Ergun, Wen-Yu-Ergun and Richardson-Davidson-Harrison) on particle flow characteristics in CFB riser.

Findings from the experimentations revealed that the increase in gas velocity leads to decrease the mixing index inside the riser. Moreover, the solid holdup found more in abrupt riser than smooth riser at the constant gas velocity. Despite the more experimental investigations, the findings with CFD simulations revealed that the MP-PIC approach, which was combined with different drag models could be more effective for the practical (industrial) design of CFB riser. Well agreement was found between the simulation and experimental outputs. The simulation work was compared with experimental data, which shows the good agreement (<4%).

The experimental and simulation study performed in this research study constitutes an easy-to-use with different drag coefficient. The proposed MP-PIC model is more effective for large particles fluidized bed, which can be helpful for further research on industrial gas-particle fluidized bed reactors. This study is expected to give throughout the analysis of CFB hydrodynamics with further exploration of overall fluidization.

The purpose of this paper is to present the knowledge structure based on the articles published in Library Hi Tech. The research hotspots are expected to be revealed through the keyword co-occurrence and social network analysis.

Data sets based on publications from Library Hi Tech covering the time period from 2006 to 2017 were extracted from Web of Science and developed as testbeds for evaluation of the CiteSpace system. Highly cited keywords were analyzed by CiteSpace which supports visual exploration with knowledge discovery in bibliographic databases.

The findings suggested that the percentage of publications in the USA, Germany, China, and Canada are high. Further, the most popular keywords identified in Library Hi Tech were: “service,” “technology,” “digital library,” “university library,” and “academic library.” Finally, four research issues were identified based on the most-cited articles in Library Hi Tech.

While keyword plays an important role in scientific research, limited studies paid attention to the keyword analysis in librarian research. The contribution of this study is to systematically explore the knowledge structure constructed by the keywords in Library Hi Tech.

The purpose of this paper is to examine the evolution of collaboration among researchers in Library Hi Tech based on the co-authorship network analysis.

The Library Hi Tech publications were retrieved from Web of Science database between 2006 and 2017. Social network analysis based on co-authorship was analyzed by using BibExcel software and a visual knowledge map was generated by Pajek. Three important social capital indicators: degree centrality, closeness centrality and betweenness centrality were calculated to indicate the co-authorship. Cohesive subgroup analysis which includes components and k-core was then applied to show the connectivity of co-authorship network of Library Hi Tech.

The results indicated that around 42 percent of the articles were written by single author, while an increasing trend of multi-authored articles suggesting the collaboration among researchers in librarian research field becomes popular. Furthermore, the social network analysis identified authorship network with three core authors – Markey, K., Fourie, I. and Li, X. Finally, six core subgroups each included six or seven tightly connected researchers were also identified.

This study contributed to the existing literature by revealing the co-authorship network in librarian research field. Key researchers in the major subgroup were identified. This is one of the limited studies that describe the collaboration network among authors from different perspectives showing a more comprehensive co-authorship network.

This study extends the commitment-trust theory from the perspective of relationship marketing and explores its effect on purchase intention under the moderation of trust by investigating vloggers' relationship marketing in the context of social media.

The study employs a survey investigation with online questionnaires in China, and the hypotheses were tested using multiple regression analyses, with 319 valid consumer responses.

The findings reveal that the extended commitment-trust theory is applicable in the context of social media. Perceived relationship commitment, expertise, physical attractiveness, social attractiveness and self-disclosure play a significant role in predicting purchase intention. Relationship commitment proves to be a mediator between the antecedents and purchase intention. Trust shows a moderating effect on the antecedents and relationship commitment.

The study provides evidence of the importance of the above-mentioned antecedents in influencing viewers' relationship commitment to vloggers in the context of social media. The results contribute to the development of the commitment-trust theory and an understanding of the theory's underlying mechanisms. The result also provides further evidence of the effect of trust on relationship commitment.

The position/force control of the robot needs the parameters of the impedance model and generates the desired position from the contact force in the environment. When the environment is unknown, learning algorithms are needed to estimate both the desired force and the parameters of the impedance model.

In this paper, the authors use reinforcement learning to learn only the desired force, then they use proportional-integral-derivative admittance control to generate the desired position. The results of the experiment are presented to verify their approach.

The position error is minimized without knowing the environment or the impedance parameters. Another advantage of this simplified position/force control is that the transformation of the Cartesian space to the joint space by inverse kinematics is avoided by the feedback control mechanism. The stability of the closed-loop system is proven.

The position error is minimized without knowing the environment or the impedance parameters. The stability of the closed-loop system is proven.

Many reviews on the internet are contributed their time to evaluate which are largely transparent generally; however, How are these information valuable and useful to visitors before making a purchasing decision? As the reason, there is a need to understand the distal path of visitors concern. The purpose of this paper is to evaluate the effects of both perceived useful and valuable motivations on visitors’ willingness to buy in the distal paths.

Web questionnaire survey.

Visitors’ confirmation was the beginning to impact the intention to buy through only one distal path, perceived value (PV) and satisfaction.

Even though the author tried his best to design and implement thoughtfully for this research, there are still some limitations. First, the results could be influenced by self-selection bias. The sample of respondents surveyed in this study consisted of young adults (58.90 percent were between the ages 21 and 25 years old), the majority of whom (54.79 percent) were students. Therefore, in the context of this study, the visitors surveyed were young and able to easily access information online. The phenomenon has been, proved by Hsu (2013), found, it still needs to explore further. Second, perceived usefulness did not have a significant impact on satisfaction which consistent with Tao et al. (2009) result. The data represent the response’ feeling for now; it needs to be explored further. Third, it would also be worthwhile to investigate any obstacles, such as believable (Cheung et al., 2012) that might reduce the intentions to buy of visitors. Finally, recommendations and promotions have also been found to influence visitors’ further purchasing behavior, such as extra buy (Tsao, 2013). These phenomena are worth investigating in future research.

To inspire visitors, information of reviews can be posted by offering positive or negative suggestions (e.g. good or bad experience); managers should improve their products or services from the suggestions of reviews and need to consider the distinctive influences of various aspects of reviews when promoting products and devising e-marketing strategies. Marketers should recruit and filter reviews to write positive suggestions of their own products or service. IS practitioners should post the reviews might need to provide more detailed information (e.g. the reasons of like or dislike). The posted information from reviews should be accurate, particularly aiming at visitors who are motivated by reviews’ suggestions. All proposed measures are particularly important for visitors with sufficient reviews effects. Greater transparency of reviews might be achieved by more explicit reviews information (e.g. via like or dislike statements).

The result provides a basis to generate concrete advice for owners about reviews concern to enhance visitors’ PV. It seems sensible to pursue two strategies: first, enhance the visitors’ PV to trigger motivation forward, and second, inspire the visitors to progress smoothly in the visiting stage.

The results of the expectation-confirmation theory applied to reviews recommendations how important to employ for enterprises. These reviews were either directly given by experienced users or at least validated with their help to visitors. Therefore, the value is building the distal bridge between visitors and customers through online general reviews.

The aim of this article is to construct a performance evaluation framework that can be employed in companies to enhance their business operations and strengthen their financial advantage in the current environment. To validate the approach, a case example has been included to assess the practicality and validity of this approach when applied in a real environment.

This study focuses on an important part of the strategic planning process: internal scrutiny and environmental (external) scanning, in which an evaluation of company performance is divided into two stages by using network DEA and the cross-efficiency approach. In addition, this article employs Miles and Snow's typology for classifying the strategies used by companies.

The analytical results show that the proposed framework can be useful for companies seeking to evaluate which strategies may be the most appropriate, based on Miles and Snow's typology, to effectively reallocate limited resources.

The evaluation in this study only uses financial data and does not take other nonfinancial indicators into consideration.

This research provides value by classifying each company included in the study in terms of its capability and financial efficiency according to Miles and Snow's system of strategy classification. Second, an internal and external performance measuring framework is constructed. Finally, some propositions for top management are provided by analyzing the financial advantages of using a performance evaluation framework that can help top management make decisions more objectively.

The purpose of this study is to provide a nuanced understanding of the marketing placebo effect (MPE) of products with reduced sugar labeling and how it forms certain perceptual underpins (perceived healthiness (PH) and perceived tastiness (PT)), with the potential effect of product category and social class in consideration.

The proposed model is tested using a sample of 822 participants by employing partial least squares structural equation modeling (PLS-SEM). Hypothetical relationships among MPE, PH, PT, purchase intention (PI) and social class are examined for both hedonic and utilitarian products.

The results highlight the positive role of MPE in leveraging consumer PI through the parallel mediation of PH and PT. The positive effect of MPE on PH and PT was more pronounced for the utilitarian product. In addition, social class negatively moderated the relationship between PH and PI only in the case of the utilitarian product.

This paper contributed to the MPE literature in the food industry by challenging the conventional intuition of “Unhealthy = Tasty” and highlighting the potential of perceived food healthiness to positively influence perceived food tastiness under the effect of MPE. An upper social class would attenuate the positive effect of perceived food healthiness on PI.

The purpose of this paper is to investigate the effects of anthropomorphism and identify factors related to adopting voice shopping on smart speakers.

Progress in partial least squares structural equation modeling (PLS-SEM) approach is used to test the proposed research framework regarding anthropomorphism and user perceptions on voice shopping via smart speakers. Individuals' responses to questions about attitude and intention to use voice shopping via smart speakers were collected and analyzed.

The results showed that anthropomorphism had a positive influence on satisfaction, which, in turn, had a positive impact on intention to adopt voice shopping, and customers had positive opinions regarding smart speakers.

This study only reflects a younger perspective on smart speaker voice shopping. This study identified the characteristics of smart speakers that increase customers' intention to purchase, which can be used to formulate sales strategies and management guidelines.

This research provided a new perspective to enable practitioners to promote smart speakers for voice shopping. Smart speaker manufacturers can utilize the findings of this research to improve the system design of smart speakers to further facilitate voice shopping.

Unlike previous studies, which focused on product attributes of smart speakers or voice shopping experiences, this study provided a clear picture of how the anthropomorphic feature of smart speakers affects customers' intention to adopt voice shopping.

In the contemporary business environment, companies must constantly consider methods to enhance their competitive advantage and create value for their customers. The purpose of this paper is to develop a research model based on a business ecosystem view. Within a business ecosystem, the authors identified the key factors of co-development and the manner in which these factors affect a company’s innovation performance.

The theoretical hypotheses are confirmed by partial least squares analysis of survey responses collected from information and communication technology (ICT) and hotel industries in Taiwan.

In both industries, the results suggest that a firm’s co-development within its own ecosystem has positive effects on innovation performance. For companies in the ICT industry, collaborative networks and partner selection have significant impacts on the firms’ co-development, but their information technology (IT) capability does not; in contrast, in the hotel industry, partner selection and IT capability have significant impacts on firm co-development, but their collaborative network does not.

This study contributes to the literature of business ecosystem and co-development by offering a co-development model. As both conceptual and empirical research on this topic is still underdeveloped, this study provides fresh insights into collaboration management and offers significant theoretical and managerial implications from a business ecosystem perspective.