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The student-managed investment fund (SMIF) program at California State University, Long Beach (CSULB), was launched in 1995 with one portfolio worth $50,000. In the two decades since then, the program has grown to include three portfolios with a combined value of more than $700,000, managed on behalf of three different clients. The purpose of this paper is to describe the creation, evolution and growth of the program including the development of the new quantitative approach and its subsequent implementation. The paper also discusses the ongoing organizational, educational and investment-management challenges associated with the program.

The paper includes a description of the development and evolution of the program along with a discussion of the investment results for one of its three portfolios.

The paper finds: the new quantitative approach implemented in the program is effective as insurance against “black swan” events; and SMIF-type programs can provide learning experiences both for students and faculty members.

The paper explains the practical application of the new quantitative approach as well as the educational benefits of a SMIF-type program.

The paper provides insight into the structure of CSULB’s SMIF program and discusses a unique quantitative approach to asset allocation and security selection.

This research measured and compared the brand identity of Kentucky Fried Chicken (KFC) in China and the United States. Brand identity was defined as the customer impressions of four different KFC identity elements – properties, products, presentations, and publications. A survey of young consumers in the two countries (n = 795), showed that the Chinese respondents were more apt to eat within KFC restaurants, and spend more time doing so, than the Americans. The Chinese also had much more positive impressions of KFC than their US counterparts. Brand identity impressions were correlated with overall customer satisfaction and with future patronage intentions for both groups, but much more so for the Americans. These findings support a model where differences in cultural frames of reference lead consumers to actively localize the brand identity of this nominally globalized product.

This paper gathers tourism digital footprint from online travel platforms, choosing social network analysis method to learn the structure of destination networks and to probe into the features of tourist flow network structure and flow characteristics in Guilin of China.

The digital footprint of tourists can be applied to study the behaviors and laws of digital footprint. This research contributes to improving the understanding of demand-driven network relationships among tourist attractions in a destination.

(1) Yulong River, Yangshuo West Street, Longji Terraced Fields, Silver Rock and Four Lakes are the divergent and agglomerative centers of tourist flow, which are the top tourist attractions for transiting tourists. (2) The core-periphery structure of the network is clearly stratified. More specifically, the core nodes in the network are prominent and the core area of the network has weak interaction with the peripheral area. (3) There are eight cohesive subgroups in the network structure, which contains certain differences in the radiation effects.

This research aims at exploring the spatial network structure characteristics of tourism flows in Guilin by analyzing the online footprints of tourists. It takes a good try to analyze the application of network footprint with the research of tourism flow characteristics, and also provides a theoretical reference for the design of tourist routes and the cooperative marketing among various attractions.

To address the shortcomings of existing academic user information needs identification methods, such as low efficiency and high subjectivity, this study aims to propose an automated method of identifying online academic user information needs.

This study’s method consists of two main parts: the first is the automatic classification of academic user information needs based on the bidirectional encoder representations from transformers (BERT) model. The second is the key content extraction of academic user information needs based on the improved MDERank key phrase extraction (KPE) algorithm. Finally, the applicability and effectiveness of the method are verified by an example of identifying the information needs of academic users in the field of materials science.

Experimental results show that the BERT-based information needs classification model achieved the highest weighted average F1 score of 91.61%. The improved MDERank KPE algorithm achieves the highest F1 score of 61%. The empirical analysis results reveal that the information needs of the categories “methods,” “experimental phenomena” and “experimental materials” are relatively high in the materials science field.

This study provides a solution for automated identification of academic user information needs. It helps online academic resource platforms to better understand their users’ information needs, which in turn facilitates the platform’s academic resource organization and services.

Exploratory search activities are ubiquitous in various information systems. Much potentially useful or even serendipitous information is discovered during the exploratory search process. Given its irreplaceable role in information systems, exploratory search has attracted growing attention from the information system community. Since few studies have methodically reviewed current publications, researchers and practitioners are unable to take full advantage of existing achievements, which, in turn, limits their progress in this field. Through a literature review, this study aims to recapitulate important research topics of exploratory search in information systems, providing a research landscape of exploratory search.

Automatic and manual searches were performed on seven reputable databases to collect relevant literature published between January 2005 and July 2023. The literature pool contains 146 primary studies on exploratory search in information system research.

This study recapitulated five important topics of exploratory search, namely, conceptual frameworks, theoretical frameworks, influencing factors, design features and evaluation metrics. Moreover, this review revealed research gaps in current studies and proposed a knowledge framework and a research agenda for future studies.

This study has important implications for beginners to quickly get a snapshot of exploratory search studies, for researchers to re-align current research or discover new interesting issues, and for practitioners to design information systems that support exploratory search.

This study aims to investigate the thermohydrodynamic (THD) and thermoelastohydrodynamic (TEHD) performance of an air-lubricated thrust bearing under different slip conditions, especially the slip length effect.

In this study, a new modified boundary slip model was established to investigate thrust bearing performance. The THD and TEHD bearing characteristic distribution was analyzed with fluid–thermal–structure interaction approach. The effect of the slip length on the bearing performance was studied using various bearing structure parameters.

The increased slip length changed the classical feature distribution of the film pressure and temperature. The sacrifice of the bearing load capacity effectively compensated for the aerodynamic thermal effect and friction torque under the slip condition. The TEHD model has a lower film pressure and load capacity than the THD model. However, it also has lower film temperature, lower friction torque and smaller Knudsen number (Kn).

The bearing THD and TEHD performances of the modified boundary slip model were compared with those of a traditional no-slip bearing. The results help to guide the selection of the bearing surface materials and processing technology of rotor and foil, so as to fully control the degree of slip and make use of it.

Currently, there is a dearth of research studies regarding macro analysis of the workforce productivity of the US construction industry. The purpose of this paper is to calculate the workforce productivity changes of the US construction industry from 2006 to 2016, with the number of laborers as input and value of construction industry as output.

The present study introduced the data envelopment analysis (DEA) based Malmquist productivity index model to measure the workforce productivity of the US construction industry from 2006 to 2016.

The results indicated that the workforce productivity of the US construction industry experienced a continuous decline, except for the increases from 2011 to 2013 and from 2014 to 2015. It was also shown that there were gaps in the workforce productivity development level among all states and nine regions in the US construction industry. Besides, the relationship between workforce productivity and four aspects, including real estate price, workforce, climate distribution and economic factors, was analyzed.

The calculation of the productivity of the US construction industry is based on the premise that the external environment is fixed and unchanged from 2006 to 2016, but the multi-level DEA model for further calculation is required for obtaining more effective conclusions.

This paper measures the workforce productivity of the US construction industry over the past 11 years, which added latest analysis and knowledge into the construction industry, providing decision-makers with advice and data support to formulate policies to improve workforce productivity.

This study provided both government decision-makers and industrial practitioners with important macro background environment information, which will facilitate the improvement of workforce productivity in the construction industry in different regions of the US.

The rise of the mobile Internet has accumulated much text information in various online financial forums. Such information often contains the emotional attitudes of investors toward financial technology (fintech) platforms, so extracting the sentimental tendency information has great practical value for the development of fintech platforms. Based on the investor sentiment theory, the paper aims to analyze the relevant social media data and test the influence path of online news evaluation on the stock price fluctuation of fintech platforms.

Taking Oriental Fortune as the research object, this paper selects multiple variables such as stock bar popularity, snowball popularity, news popularity and news sentiment scores collected by UQER and combines the sentiment scores of single daily news into a daily sentiment score. Based on the period from November 1, 2019 to March 31, 2020, during the emergence of the coronavirus disease 2019 (COVID-19) pandemic as the background, the authors conduct the Granger causality test based on the vector autoregressive (VAR) model and analyze the relevant evaluation of Oriental Fortune through the empirical model.

The authors' results show that different online evaluations impact the rise and fall of stock prices differently, while news popularity has the most significant impact. Besides, news sentiment scores on share price fluctuation have a relatively substantial influence. These findings indicate that the authoritative news evaluation can strongly guide investors to make relevant investment behavior operations in the information dissemination process, significantly affecting stock prices.

The research findings of this paper have good inspiration and reference values for investors and financial regulators.

Bismaleimide (BMI) is a kind of thermosetting resin and its application is usually limited by low toughness. In this paper, two kinds of reinforcement intercalator amino-terminated polyoxypropylene (POP) and octadecyl trimethyl ammonium chloride (OTAC) were designed and synthesized to toughen BMI resin and the toughening effect was compared and analyzed. The purpose of this paper is to toughen BMI resin and analyze the toughening effect of two reinforcements intercalator amino-terminated polyoxypropylene (POP) and octadecyl trimethyl ammonium chloride (OTAC).

Sodium-based montmorillonite (Na-MMT) was modified by POP and OTAC, and the ion-exchange reaction obtained organic montmorillonite (POP-MMT and OTAC-MMT). The polymer matrix (MBAE) was synthesized, in which 4,4’-diamino diphenyl methane BMI was used as the monomer and 3,3’-diallyl bisphenol A and bisphenol A diallyl ether were used as active diluents. And then, POP-MMT/MBAE and OTAC-MMT/MBAE composites were prepared using MBAE as matrix and POP-MMT or OTAC-MMT as reinforcement. The Fourier-transform infrared, X-ray diffraction and scanning electron microscope (SEM) of the filler and microstructure and mechanical properties of the composite were characterized to the better reinforcement.

POP-MMT and OTAC-MMT enhanced BMI-cured products’ toughness by generating microcracks in the polymer to absorb more fracture energy. Meanwhile, POP-MMT and OTAC-MMT were the main stress components and the enhancement of the interface interaction was beneficial to transfer the external force from the matrix to the reinforcement and improved the mechanical properties of the composite. Furthermore, with the intercalation rate increasing, the compatibility of the two phases was increased and the performance of MBAE was also elevated.

BMI is generally used as aerospace structural materials, functional materials, impregnating paint and other fields. However, high crosslinking density leads to moulding material’s brittleness and limits a wider range of applications. Therefore, it has become an urgent priority to explore and improve the mechanical properties of BMI resin.

POP and OTAC have successfully intercalated Na-MMT layers to get POP-MMT and OTAC-MMT, and the interplanar crystal spacing and the intercalation rate were calculated, respectively. The results were corresponding with the SEM images of POP-MMT and OTAC-MMT. After that, the morphology of composites illustrated the compatibility was related to the intercalation rate. According to the mechanism of modified MMT toughening epoxy resin, when they were dispersed uniformly in the matrix, the composite’s mechanical properties had been significantly improved. Additionally, OTAC-MMT with a higher intercalation rate had better compatibility and interfacial force with the matrix, so that the mechanical properties of OTAC-MMT/MBAE were the best.