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While prior research has emphasized the importance of diversity management for the betterment of future workforce, the role of managerial actors in leading the diversity management movement has not been substantiated. The purpose of this paper is to examine the role of managers in practicing diversity management and the extent to which inclusive leadership affects employee performance.

The study draws on a large survey data (n=415,696) with a representative sample of employees in federal government in the USA.

The quantitative results show that diversity policy alone predicts performance less strongly for employees of racial minority than for whites. In contrast, the study finds that inclusive leadership predicts performance more strongly for nonwhites.

The embodied approach to diversity management proposed in this paper expands the understanding of diversity management research by exploring the interaction effect between diversity policy and diversity leadership.

The paper is unique in proposing an interaction effect between diversity policy and diversity leadership in managing diversity.

Previous studies in the literature surprisingly neglected to take into account the role of leader behavior in managing diversity. As the study shows the significant moderating role of diversity leadership in diversity management, organizational leaders are encouraged to critically assess and provide training for those team leaders and middle level managers to promote diversity in the workplace.

This is the first empirical study to distinguish and examine the relative impact of diversity policy and inclusive leadership on employee performance in the public sector.

The purpose of this paper is to explicate the role of followership behavior on employee job satisfaction as well as the conditions that may moderate its impact.

This study uses a large n survey data from federal agencies and investigates an additive moderation model in which two situational factors, perceived supervisor support (PSS) and performance-oriented culture (POC), interact with followership behavior.

Employees high on active followership perceived greater job satisfaction when PSS was high, rather than low. On the other hand, employees high on active followership perceived greater job satisfaction when POC was low, rather than high.

This is, to the knowledge, the first empirical study based on a cross-sectional survey that tests how the effects of active followership on employee job satisfaction may vary depending on the different types of situational factors. As such, more studies are needed to validate the causal directions of the findings.

The present findings show that active engagement had greater association with job satisfaction when leader involvement was high and performance orientation was low. For highly engaged employees, leaders are encouraged to show higher degree of involvement in their work but with less emphasis on the performance orientation of the organization.

This study contributes to the broader literature in public sector leadership in two ways. First, research on the relationship between followership and job satisfaction has been sparse. Second, and most importantly, this study is the first empirical study that tests the moderating roles of situational (organizational) factors on the relationship between followership and employee attitude (job satisfaction).

Sitting in a chair is a typical act of modern people. Prolonged sitting and sitting with improper postures can lead to musculoskeletal disorders. Thus, there is a need for a sitting posture classification monitoring system that can predict a sitting posture. The purpose of this paper is to develop a system for classifying children’s sitting postures for the formation of correct postural habits.

For the data analysis, a pressure sensor of film type was installed on the seat of the chair, and image data of the postu.re were collected. A total of 26 children participated in the experiment and collected image data for a total of seven postures. The authors used convolutional neural networks (CNN) algorithm consisting of seven layers. In addition, to compare the accuracy of classification, artificial neural networks (ANN) technique, one of the machine learning techniques, was used.

The CNN algorithm was used for the sitting position classification and the average accuracy obtained by tenfold cross validation was 97.5 percent. The authors confirmed that classification accuracy through CNN algorithm is superior to conventional machine learning algorithms such as ANN and DNN. Through this study, we confirmed the applicability of the CNN-based algorithm that can be applied to the smart chair to support the correct posture in children.

This study successfully performed the posture classification of children using CNN technique, which has not been used in related studies. In addition, by focusing on children, we have expanded the scope of the related research area and expected to contribute to the early postural habits of children.

The purpose of this study was to investigate the differences in night eating status according to adolescents’ body mass index (BMI).

This was a cross-sectional study that included a total of 688 middle-school students. The subjects were categorized as underweight, normal weight and overweight according to their BMI, and their night eating intake patterns, night eating menu preference and intake frequency were compared and analyzed.

With regard to their night eating frequency, 39.8 per cent replied almost never, while 24.3 per cent replied once a week and less and 22.5 per cent replied two to three times a week. Among 11 night eating menus, the preference for fast foods, confectioneries, street foods and noodles was significantly higher in the underweight group than in the overweight group. The intake frequency of night eating menus such as fast foods, confectioneries and breads increased in the following order: overweight, normal and underweight group. The underweight group had a higher frequency of night eating, and they preferred to eat snacks more frequently from their night eating menu.

In conclusion, it is necessary to form positive dietary habits including nighttime eating for proper dietary management of adolescents.

The purpose of this paper is to apply the real option method with fuzzy logic to value the government‐sponsored projects of advanced technology development for strategic selection in an uncertain competitive environment.

For strategic selection of government‐sponsored industrial R&D projects, in this paper, Carlsson and Fúller's model was adopted which employs fuzzy logic to estimate the benefits and costs calculated from various scenarios and utilizes Black‐Scholes‐Merton model. The model of strategic selection is suggested for government R&D with fuzzy real option valuation (FROV) and the portfolio planning model from GE‐Mckinsey matrix as well.

FROV was found to be more appropriate to measure the strategic value than the traditional financial method (net present value, NPV, etc.). When the NPV is ambiguous in deciding whether to go or not to go, for instance, just below zero NPV and high volatility of expected benefit, FROV can offer the additive value of the project reflecting volatility of benefit due to the volatility.

Based on insufficient practical data, this methodology should be verified with various projects and measuring volatility of pay‐off requires precise analysis. In addition, research opportunities are in the stepwise R&D project with fuzzy compound real option.

Many papers on economic analysis of R&D project are focused on NPV or cost‐benefit analysis in the public sector. Several attempts with real option have been conducted in the pharmaceutical field or the aerospace (NASA) industry but are not concerned with the fuzziness of expected benefit. Hence, in this paper, fuzzy logic is added to handle imprecise information on the Black‐Scholes‐Merton model with dividend paying.

The Hanbo (meaning Korean treasure) scandal or “Hanbogate” occurred on January 23, 1997, with the bankruptcy of Hanbo Iron and Steel Company, the second largest steel company and 14th largest conglomerate in South Korea, as its debt had accumulated to US$5.6 billion. Hanbo's bankruptcy triggered an investigation by the Public Prosecutor's Office that resulted in the imprisonment for 15 years of Hanbo's founder, Chung Tae-Soo, for bribing politicians and bankers to pressure banks to extend hugh bank loans to Hanbo. Nine other persons were also convicted including Chung's son, who was jailed for three years for bribery and embezzlement, and Kim Hyun-Chol, the second son of President Kim Young-Sam, who was sentenced to three years jail and fined US$1.5 million (New York Times, 1997).