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Article
Publication date: 24 May 2021

Soo Jung Kim, Youjin Jang, Myunghyun Yoo and Ji Hoon Song

The purpose of this study is to empirically examine the mediating effect of organizational communication in the relationships among transformational leadership, organizational…

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Abstract

Purpose

The purpose of this study is to empirically examine the mediating effect of organizational communication in the relationships among transformational leadership, organizational justice and knowledge sharing within the higher education setting in South Korea.

Design/methodology/approach

A sample of 321 university employees, including 151 faculty members and 170 administrative staff members, from a representative private university, participated in the survey as part of a consulting project for university innovation. Structural equation modeling (SEM) was mainly used for data analysis to identify the structural relationship among the research variables.

Findings

The results of this study confirmed that transformational leadership positively influences organizational justice and knowledge sharing. However, the influence of organizational justice on knowledge sharing was not statistically significant. The mediating effect of organizational communication among those relationships to increase the members’ knowledge sharing behavior was statistically significant.

Originality/value

In this study, holistic aspects of the organization, including leadership, organizational culture and organizational strategy, were examined for encouraging employees’ knowledge sharing behavior while an organization undergoes innovational changes. More practically, this study suggested that organizational communication could be used as one of the critical strategies in the process of university innovation.

Details

Industrial and Commercial Training, vol. 53 no. 3
Type: Research Article
ISSN: 0019-7858

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Article
Publication date: 8 January 2021

Youjin Jang, Inbae Jeong and Yong K. Cho

The study seeks to identify the impact of variables in a deep learning-based bankruptcy prediction model, which has achieved superior performance to other prediction models but…

668

Abstract

Purpose

The study seeks to identify the impact of variables in a deep learning-based bankruptcy prediction model, which has achieved superior performance to other prediction models but cannot easily interpret hidden processes.

Design/methodology/approach

This study developed three LSTM-RNN–based models that predicted the probability of bankruptcy before 1, 2 and 3 years using financial, the construction market and macroeconomic variables as input variables. Then, the impacts of the input variables that affected prediction accuracy in each model were identified by using Shapley value and compared among the three models. This study also investigated the prediction accuracy using variants of input variables grouped sequentially by high-impact ranking.

Findings

The results showed that the prediction accuracies were largely impacted by “housing starts” in all models. As the prediction period increased, the effects of macroeconomic variables on prediction accuracy increased, whereas the impact of “return on assets” on prediction accuracy decreased. It also found that the “current ratio” and “debt ratio” significantly influenced the prediction accuracies in all models. Also, the results revealed that similar prediction accuracies could be achieved using only 8, 10, and 10 variables out of a total of 18 variables for the 1-, 2-, and 3-year prediction models, respectively.

Originality/value

This study provides a Shapley value-based approach to identify how each input variable in a deep-learning bankruptcy prediction model. The findings of this study can not only assist in obtaining better insights into the underlying concept of bankruptcy but also use to select variables by removing those identified as less significant.

Details

Engineering, Construction and Architectural Management, vol. 28 no. 10
Type: Research Article
ISSN: 0969-9988

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Article
Publication date: 3 August 2021

Youjin Jang, Monique Mitchell Turner, Ruth Jinhee Heo and Rachel Barry

This study aims to use the anger activism model as an audience segmentation tool in the context of the anti-vaccination movement.

547

Abstract

Purpose

This study aims to use the anger activism model as an audience segmentation tool in the context of the anti-vaccination movement.

Design/methodology/approach

A cross-sectional survey was conducted with a national purposive sample (N = 438).

Findings

The group with high anger, strong efficacy (i.e. “activists”) was found to be more likely to engage in information seeking and was more accurate and defense-motivated when examining information about anti-vaxxers compared to other groups. Importantly, activists were more likely to engage in both low and high commitment behaviors to change vaccine policy.

Originality/value

As anti-vaxxers have proven to be difficult to change attitudinally, future campaigns are more likely to succeed if they leverage pro-vaccine audiences to fight for change. However, the understanding of the various segments within the pro-vaccination audience is limited. The data are discussed regarding leveraging high anger, strong efficacy audiences as change agents in future persuasive campaigns.

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Article
Publication date: 7 March 2024

Shu-Mei Tseng and Shervina Octavyaputri

Developing green innovative services is critical to the restaurant industry to achieve significant benefits as well as environmental sustainability. This study aims to explore…

226

Abstract

Purpose

Developing green innovative services is critical to the restaurant industry to achieve significant benefits as well as environmental sustainability. This study aims to explore the mechanisms through which employees’ green involvement can foster green service innovation behavior.

Design/methodology/approach

The data set garnered from employees who worked in restaurants was used to test these mechanisms. A partial least square technique was conducted on this data set.

Findings

The results revealed the employees’ green involvement significantly influences their green service innovation intention, which subsequently influences their green service innovation behavior. Furthermore, information technology (IT) adoption was found to fortify the linkage of employee green involvement with green service innovation intention.

Practical implications

The results suggest to the restaurant industry that awareness of green service innovation and IT adoption practices can help restaurants to develop effective sustainability work practices and meet societal expectations.

Originality/value

This study extends the restaurant management literature by linking the green involvement of restaurant employees to green service innovation intention as well as identifying the moderating role of IT adoption underlying this link.

Details

Aslib Journal of Information Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2050-3806

Keywords

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