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This article examines why Korean academic libraries embarked on restructuring their organization and identifies possible solutions to some problems that these libraries face. The conclusion is drawn from the results of a case study on Sejong University Library that Korean academic librarians should become user‐centered professionals. After restructuring, the user service librarian’s job content has changed to concentrate on servicing users on specific subjects. The subject librarian will take care of reference services, SDI, DB instruction and book selection on the same subject.

The purpose of this paper is to conduct a big data analysis of public library operations and services of two cities in two countries by using the Chernoff face method.

The study is designed to evaluate library services by analyzing the Chernoff face. Big data on public libraries in London and Seoul were collected, respectively, from Chartered Institute of Public Finance and Accountancy and the Korean government’s website for drawing a Chernoff face. The association of variables and human facial features was decided by survey. Although limited in its capacity to handle a large number of variables (eight were analyzed in this study) the Chernoff face method does readily allow for the comparison of a large number of instances of analysis. A total of 58 Chernoff faces were drawn from the formatted data by using the R programming language.

The study reveals that most of the local governments in London perform better than those of Seoul. This consequence is due to the fact that local governments in London operate more libraries, invest more budgets, allocate more staff and hold more collections than local governments in Seoul. This administration resulted in more use of libraries in London than Seoul. The study validates the benefit of using the Chernoff face method for big data analysis of library services.

The Chernoff face method for big data analysis offers a new evaluation technique for library services and provides insights that may not be as readily apparent and discernible using more traditional analytical methods.

This study is the first to use the Chernoff face method for big data analysis of library services in library and information research.

In the era of information overload, the density of tourism information and the increasingly sophisticated information needs of consumers have created information confusion for tourists and scenic-area managers. The study aims to help scenic-area managers determine the strengths and weaknesses in the development process of scenic areas and to solve the practical problem of tourists' difficulty in quickly and accurately obtaining the destination image of a scenic area and finding a scenic area that meets their needs.

The study uses a variety of machine learning methods, namely, the latent Dirichlet allocation (LDA) theme extraction model, term frequency-inverse document frequency (TF-IDF) weighting method and sentiment analysis. This work also incorporates probabilistic hesitant fuzzy algorithm (PHFA) in multi-attribute decision-making to form an enhanced tourism destination image mining and analysis model based on visitor expression information. The model is intended to help managers and visitors identify the strengths and weaknesses in the development of scenic areas. Jiuzhaigou is used as an example for empirical analysis.

In the study, a complete model for the mining analysis of tourism destination image was constructed, and 24,222 online reviews on Jiuzhaigou, China were analyzed in text. The results revealed a total of 10 attributes and 100 attribute elements. From the identified attributes, three negative attributes were identified, namely, crowdedness, tourism cost and accommodation environment. The study provides suggestions for tourists to select attractions and offers recommendations and improvement measures for Jiuzhaigou in terms of crowd control and post-disaster reconstruction.

Previous research in this area has used small sample data for qualitative analysis. Thus, the current study fills this gap in the literature by proposing a machine learning method that incorporates PHFA through the combination of the ideas of management and multi-attribute decision theory. In addition, the study considers visitors' emotions and thematic preferences from the perspective of their expressed information, based on which the tourism destination image is analyzed. Optimization strategies are provided to help managers of scenic spots in their decision-making.

This study aims to investigate how the inter-organizational learning (inter-OL) of small and medium enterprises (SMEs) promote intra-organizational learnings (intra-OL) and how inter- and intra-OL jointly promote organizational innovation in the Korean electronics industry. This study also examines the moderating effect of organizational dynamism.

A unique theoretical model shows how inter-OL promotes organizational innovation through intra-OL, knowledge flows and stocks. Data was collected from 201 SMEs in the Korean electronics industry and analyzed by structural equation modeling.

The findings show that inter-OL directly and indirectly influences innovation. Inter-OL promotes both knowledge flows and stocks, but the only feedforward flows influence innovation through knowledge stocks while feedback flows directly influence innovation. Additionally, the study finds an indirect effect of inter-OL on knowledge stocks and a strong direct effect on innovation when dynamism is high. Intra-OL activities fully mediate between inter-OL and innovation when dynamism is low.

This study uses single informants to measure all constructs. Future studies should use multiple informants.

This study shows that OL in SMEs is shaped by internal processes and external collaborations. Maintaining a connection with various external knowledge sources and creating collaborative opportunities to share learning experiences is critical to innovation.

This study is the first to empirically examine the relationship between inter- and intra-OL activities within a conceptual framework. The study provides a strategic view of how to facilitate OL activities considering the degree of organizational dynamism.

The purpose of this paper is to identify how organizational learning processes influence perceived organizational performance and examine the moderating roles of organizational justice and trust in managers therein.

This study develops a theoretical model to exhibit how knowledge acquisition and transfer activities influence perceived organizational performance. Data were collected from 515 respondents and analyzed by PROCESS macro for SPSS.

This study found that feedback learning flows are strongly mediated between learning stocks and organizational performance. It also found that organizational justice moderates the effect of learning stocks on organizational performance through feed-forward learning flows, while trust in manager moderates the effect of learning stocks on organizational performance through feedback learning flows.

This study has a limitation in which it uses self-report data to measure all constructs. The objective measure may be necessary for future study.

The implications of this study are twofold. First, it finds that the higher organizational justice, the better the transfer of knowledge from the bottom up. When firms need to explore new knowledge, fairness in procedure and the distribution system is critical. Second, the higher the trust in management, the better the transfer of knowledge from the top down. The role of managers is instrumental in persuading employees and disseminating knowledge.

Combining functionalist and critical perspectives and developing a theoretical model, this study contributes to the understanding of how trust and justice facilitate learning activities within organizations.

The purpose of this paper is to identify how three types of socialization tactics – content, context and social tactics – influence fit perceptions, and then how three types of fit perceptions – person–organization (P–O) fit, person–job (P–J) fit and person–group (P–G) fit – mediate the relationship between socialization tactics and positive socialization outcomes: organizational commitment, job satisfaction and intent to quit.

Responses from participants – 207 Korean youth workers – were subjected to ordinary least squares path analyses with bootstrapping to test the hypotheses.

First, this study found that socialization tactics promote youth workers’ perceived fit with organization, job, and people. Then, the mediation model showed that content socialization tactics do not influence dependent variables (socialization outcomes) through mediators (fits), while context tactics influence through perceived P–O fit and P–G fit for organizational commitment only, and social tactics through perceived P–O, P–J and P–G fit for organizational commitment, job satisfaction and intent to quit.

The results of this study suggest that institutionalized social tactics can serve as a key socialization method for new employees. In addition, youth organizations need to implement jointly formal and collective training programs with follow-up social workplace learning (e.g. mentoring and study circle) to help newcomers share the values of the organization and integrate well into it.

This study contributes for understanding the socialization process of new employees working in educational and social work fields and role of fit perception between socialization tactics and their career successes.

The purpose of this study is to identify how young South Korean self-initiated expatriates (SIEs) have adjusted to their work and to verify the role of workplace learning activities as work adjustment processes in the relationship between work adjustment resources and outcomes.

The study adopted a mixed-method approach, beginning with a qualitative study, followed by a quantitative study.

The main findings of the qualitative study indicated two types of SIE personal characteristics (ability to embrace cultural differences and entrepreneurship), their participation in training programs and that a supportive work environment which facilitates their work adjustment. Workplace learning, which led to role clarification within their organizations, is also critical for adjustment. Based on these findings, the quantitative research study examined the effects of personal and contextual factors on workplace learning and adjustment (n = 120). The quantitative part of the study found cultural intelligence (CQ), entrepreneurship, training programs and supportive environments were positively related to sociocultural adjustment through the work adjustment process.

As work adjustment is an important predictor of increased sociocultural adjustment among SIEs, organizations should build learning-supportive climates to promote workplace learning and seek people with appropriate characteristics for expatriation. Further studies should expand participant sample sizes to represent a wider population of SIEs.

Extant literature on SIEs mainly explored their performance and management. This study explores their adjustment processes through the perspective of workplace learning.

The purpose of this paper is to investigate the relationships between three quality management (QM) practices, leadership, people focus, and process management practices and organizational learning (OL) activities and business performance in Korean manufacturing businesses.

The study draws on 204 responses to a survey of Korean manufacturing companies listed on the Korea Composite Stock Price Index to test nine hypotheses with structural equation modeling (SEM).

The results from SEM show that leadership practices have a significant effect on people focus and process management practices, and that the three QM practices jointly influence OL. However, leadership, people focus, and process management practices do not have direct associations with business performance, but rather show statistically influence only via OL activities. The findings verify that OL has a mediating role in QM practices and business performance as a crucial resource that determines a firm’s competitive advantage.

An important implication of this study’s findings for managers or QM professionals is that learning takes place at multiple levels and is a crucial resource that determines a firm’s competitive advantage, bridging quality and business outcomes.

This study aims to identify the relationship between protean career attitude (PCA) and organisational commitment (OC) in a learning organisation (LO) climate. The study also identified whether negative relationships exist between the structure dimension of LO (SDLO) and PCA, and between PCA and OC, and whether such relationships can be moderated by the people dimension of LO (PDLO).

Data collected from 305 employees of 26 firms were analysed using the PROCESS macro for SPSS.

This study found that SDLO had a negative relationship with PCA, whereas PCA was negatively associated with OC. Furthermore, this study found that PDLO moderated these relationships, in that the negative relationships were absent when PDLO activities were stronger, in contrast to when they were weaker.

The study is among the first to identify the negative relationships that exist between SDLO and PCA and between PCA and OC in Korean firms. An important implication for managers or OD professionals is that PDLO plays an important role in not only reducing the negative mediation effects of PCA in the relationships but also making the relationships positive.

The purpose of this paper is to improve the hydraulic efficiency without changing the overall dimension. The blade profile optimization design of the aero-centrifugal pump based on the biharmonic equation surrogate model has been studied.

First of all, Bezier curves and linear function are used to control the annular angle distribution and the stacking angle of blade profile under the MATLAB platform. Grid independence analysis has been studied to find the finest mesh scheme. After the precision comparison of test data and computation fluid dynamics 15 sets of design parameters are carried out as the boundary condition of the biharmonic equation. The efficiency surrogate model of the biharmonic equation is constructed via iteratively solving of a discrete difference equation. The other two surrogate models of response surface model (RSM) and radial basis function neural network surrogate model (RBFNNSM) are compared with the biharmonic equation surrogate model by the standard of modified complex correlation coefficient R² and root mean square deviation (RSME). Finally, the artificial fish swarm algorithm has been used to find the global optimal design parameters with the objective function of highest efficiency.

The results show that the design parameters code conversion method can reduce the number of optimization parameters from five to three, makes the design space become a cube, and compared with RSM and RBFNNSM, the biharmonic equation surrogate model has higher precision with R² is 0.8958, RSME is 0.1382. The final optimum result of AFSA is at the point of [1 −1 −1]. The internal flow field analysis shows that after optimization the outlet relative velocity becomes more uniform and the wake effect has been significantly decreased. The hydraulic efficiency of the optimized pump is about 59.45 per cent increasing 5.4 per cent compared with a prototype pump.

This study developed a new method to optimize the design parameters of aero-centrifugal pump impeller based on biharmonic equation surrogate model, which had a good agreement with experimental values within just 15 sets of the original design. The optimization results shows that the method can improve the hydraulic efficiency significantly.