Search results

1 – 8 of 8
To view the access options for this content please click here
Article
Publication date: 27 August 2019

Junyeong Lee, Jinyoung Min, Chanhee Kwak, L.G. Pee and Heeseok Lee

An organization can be understood as a knowledge network in which teams send and receive knowledge. Many studies have explored knowledge sharing across teams but did not…

Abstract

Purpose

An organization can be understood as a knowledge network in which teams send and receive knowledge. Many studies have explored knowledge sharing across teams but did not consider the direction of knowledge flows (KF), specifically how the knowledge inflow (KIF) and knowledge outflow (KOF) can be induced and influence team activities differently. To fill this gap, this paper distinguishes between KIF and KOF, examines their antecedents and consequences and considers how KIF and KOF within a team moderate the relationship between antecedents and KF of a team.

Design/methodology/approach

This study used structural equation model analysis of a sample of 341 individuals within 73 teams from four companies.

Findings

The results suggest that IT support is essential because it influences both KIF and KOF. However, only KOF has a significant effect on team performance suggesting that ambidexterity is not always necessary. In promoting KOF, increasing task interdependency is also effective. The effect of IT support varies with the level of KIF diversity.

Originality/value

The findings emphasize the importance of distinguishing KOF from KIF in a team’s knowledge network under the theoretical lens of ambidexterity. Identifying how IT support influences KF and how these flows separately affect team performance can provide useful insights into managing and facilitating KF in an organization.

Details

Journal of Knowledge Management, vol. 23 no. 8
Type: Research Article
ISSN: 1367-3270

Keywords

To view the access options for this content please click here
Article
Publication date: 3 April 2017

Junyeong Lee, Jinyoung Min and Heeseok Lee

As teams are built around specialized and different knowledge, they need to regulate their knowledge boundaries to exchange their specialized knowledge with other teams…

Downloads
1291

Abstract

Purpose

As teams are built around specialized and different knowledge, they need to regulate their knowledge boundaries to exchange their specialized knowledge with other teams and to protect the value of such specialized knowledge. However, prior studies focus primarily on boundary spanning and imply that boundaries are obstacles to sharing knowledge. To fill this research gap, this study aims to indicate the importance of knowledge protection regulation, an activity that sets an adequate boundary for protecting knowledge, and investigate the factors that facilitate knowledge protection regulation and its consequences.

Design/methodology/approach

This study collected empirical data from 196 teams in seven organizations. Through a validation of the measurement model, data from 138 teams are used for further analysis. The hypotheses effects are assessed using a structural equation model.

Findings

The analysis results indicate that both task uncertainty and task interdependency enhance knowledge protection regulation in teams, and that information technology support moderates the relationship between task uncertainty and knowledge protection regulation. The results also indicate that knowledge protection regulation improves inter-team coordination and team performance.

Originality/value

This study focuses on knowledge protection regulation by adopting communication privacy management theory at the team level. The findings imply that boundary management is the process of communication and depends on the role the teams play in accomplishing their tasks. The findings also provide a new way to understand knowledge flow of the teams as well as the entire organization.

Details

Journal of Knowledge Management, vol. 21 no. 2
Type: Research Article
ISSN: 1367-3270

Keywords

To view the access options for this content please click here
Article
Publication date: 3 April 2017

L.G. Pee and Jinyoung Min

Various individual and environmental factors influencing employees’ online knowledge sharing have been identified, but the understanding regarding these has been mostly…

Downloads
1466

Abstract

Purpose

Various individual and environmental factors influencing employees’ online knowledge sharing have been identified, but the understanding regarding these has been mostly limited because of their independent and direct effects our understanding has been mostly limited to their independent and direct effects. This study aims to propose that the fit between employees and their environments (PE fit) matters. A model explaining how PE fit and misfit affect employees’ knowledge sharing behavior through influencing their affective commitment is developed and assessed.

Design/methodology/approach

The proposed model was assessed with data collected in a survey of 218 employees.

Findings

Results indicate that PE fit in the norm of collaboration, innovativeness and skill variety leads to the development of stronger affective commitment and, therefore, more knowledge sharing behavior than when they are in shortfall or excess in the environment (i.e. PE misfit).

Originality/value

The findings indicate a new direction for knowledge sharing research that focuses on PE fit and suggest that knowledge sharing can be improved more proactively in practice by assessing PE fit during recruitment.

Details

Journal of Knowledge Management, vol. 21 no. 2
Type: Research Article
ISSN: 1367-3270

Keywords

To view the access options for this content please click here
Article
Publication date: 3 July 2020

Jinyoung Min, Youngjin Yoo, Hyeyoung Hah and Heeseok Lee

Rather than viewing social network technology (SNT) as a mere tool to access a networked audience, we emphasize its role as both a means and a social actor to help verify…

Abstract

Purpose

Rather than viewing social network technology (SNT) as a mere tool to access a networked audience, we emphasize its role as both a means and a social actor to help verify people’s self-images in an online social context.

Design/methodology/approach

Drawing upon self-verification theory, this study investigates a mechanism of how users are willing to use SNTs continuously through the cognitive and affective reactions on two different SNTs. Structural equation modeling was used via data collected from 320 Facebook and 313 Twitter users.

Findings

Our results demonstrated that Facebook users regard it only as a useful tool for presenting self-images, while Twitter users are likely to feel an emotional attachment to technology as a social actor when ideal self-verification is gained, and that different types of SNTs create differential contexts for self-verification.

Research limitations/implications

This study suggests a new lens to understand SNT’s role as a social actor in the self-verification process, further identifying the SNT context in which SNT takes different roles.

Practical implications

In a certain SNT usage context, users are attached to SNTs, suggesting SNT providers consider features that enable SNT users to fulfill their own self-verification motives.

Originality/value

This study explores the roles of SNTs from a self-verification perspective. Our conceptualization of technology as a self-verifying social actor can further extend existing discussions on the role of SNT in response to self-verifying needs, while also promoting the continued use of SNTs in the future.

To view the access options for this content please click here
Article
Publication date: 2 February 2015

Byoungsoo Kim and Jinyoung Min

The purpose of this paper is to investigate the effects of dedication- and constraint-based mechanisms on users’ post-adoption behavior in the social networking site (SNS…

Abstract

Purpose

The purpose of this paper is to investigate the effects of dedication- and constraint-based mechanisms on users’ post-adoption behavior in the social networking site (SNS) context.

Design/methodology/approach

The proposed framework uses user satisfaction and trust belief to capture the dedication-based mechanism and perceived switching costs and social norms to capture the constraint-based mechanism. Hypotheses were tested by applying partial least squares to data from 250 experienced Facebook users. A structural equation modeling was used to test the validity of the proposed research models.

Findings

The analysis results show that SNS users’ continuance intention is jointly affected by two distinctive mechanisms: a dedication-based one and a constraint-based one, the former playing a more critical role. The findings indicate that both perceived relative benefits and perceived enjoyment significantly influence user satisfaction. Learning and network size were found to be the key predictors of perceived switching costs.

Research limitations/implications

This study applies the dedication- and constraint-based models by incorporating numerous sets of antecedents. The framework provides a theoretical lens of how two distinctive mechanisms influence SNS users’ post-adoption behaviors.

Practical implications

The analysis results provide several insights that can aid SNS providers understand SNS users post-adoption behaviors. Moreover, the findings will help SNS providers effectively facilitate dedication- and constraint-based mechanisms by enhancing the key antecedents of two distinctive mechanisms.

Originality/value

SNSs have become an important component of individuals lives. However, few systematic works investigate the fundamental mechanisms leading to SNS users’ continued usage. In an attempt to extend the horizons of SNS research, this study incorporates a set of antecedents to dedication- and constraint-based models.

Details

Internet Research, vol. 25 no. 1
Type: Research Article
ISSN: 1066-2243

Keywords

To view the access options for this content please click here
Article
Publication date: 2 April 2021

Jina Kim, Yeonju Jang, Kunwoo Bae, Soyoung Oh, Nam Jeong Jeong, Eunil Park, Jinyoung Han and Angel P. del Pobil

Understanding customers' revisiting behavior is highlighted in the field of service industry and the emergence of online communities has enabled customers to express their…

Abstract

Purpose

Understanding customers' revisiting behavior is highlighted in the field of service industry and the emergence of online communities has enabled customers to express their prior experience. Thus, purpose of this study is to investigate customers' reviews on an online hotel reservation platform, and explores their postbehaviors from their reviews.

Design/methodology/approach

The authors employ two different approaches and compare the accuracy of predicting customers' post behavior: (1) using several machine learning classifiers based on sentimental dimensions of customers' reviews and (2) conducting the experiment consisted of two subsections. In the experiment, the first subsection is designed for participants to predict whether customers who wrote reviews would visit the hotel again (referred to as Prediction), while the second subsection examines whether participants want to visit one of the particular hotels when they read other customers' reviews (dubbed as Decision).

Findings

The accuracy of the machine learning approaches (73.23%) is higher than that of the experimental approach (Prediction: 58.96% and Decision: 64.79%). The key reasons of users' predictions and decisions are identified through qualitative analyses.

Originality/value

The findings reveal that using machine learning approaches show the higher accuracy of predicting customers' repeat visits only based on employed sentimental features. With the novel approach of integrating customers' decision processes and machine learning classifiers, the authors provide valuable insights for researchers and providers of hospitality services.

Details

Data Technologies and Applications, vol. 55 no. 4
Type: Research Article
ISSN: 2514-9288

Keywords

To view the access options for this content please click here
Article
Publication date: 5 June 2019

Eunil Park, Sang Jib Kwon and Jinyoung Han

Although the notable and significant role of building information modeling (BIM) technologies in construction industries has gained user attention, only few studies have…

Abstract

Purpose

Although the notable and significant role of building information modeling (BIM) technologies in construction industries has gained user attention, only few studies have been examined on the user adoption of the technologies. The purpose of this paper is to introduce an acceptance model for BIM technologies and investigate how external factors which were extracted by in-depth interviews promote the adoption of such technologies.

Design/methodology/approach

An on-line survey was conducted by two South Korean survey agencies to test the acceptance model for BIM technologies. Then, the structural equation modeling (SEM) and confirmatory factor analysis (CFA) methods were used.

Findings

The results of the SEM and CFA methods from on-site construction employees (n=818) in Korea collected by the online survey indicate that compatibility and organizational support play a core role in positively and significantly affecting both perceived ease of use and usefulness, and that the connections introduced by the origin technology acceptance model are mainly confirmed.

Originality/value

Using the findings of the results, both implications and notable limitations are presented. Moreover, practical developers, as well as academic researchers can employ the results when they attempt to conduct future research.

To view the access options for this content please click here
Article
Publication date: 8 December 2017

Ying Guo, Qinghe Han, Jinxin Wang and Xu Yu

Localization is one of the critical issues in Ocean Internet of Things (OITs). The existing research results of localization in OITs are very limited. It poses many…

Abstract

Purpose

Localization is one of the critical issues in Ocean Internet of Things (OITs). The existing research results of localization in OITs are very limited. It poses many challenges due to the difficulty of deploy beacon accurately, the difficulty of transmission distance estimation in harsh ocean environment and the underwater node mobility. This paper aims to provide a novel localization algorithm to solve these problems.

Design/methodology/approach

This paper takes the ship with accurate position as a beacon, analyzes the relationship between underwater energy attenuation and node distance and takes them into OITs localization algorithm design. Then, it studies the movement regulation of underwater nodes in the action of ocean current, and designs an Energy-aware Localization Algorithm (ELA) for OITs.

Findings

Proposing an ELA. ELA takes the ship with accurate position information as a beacon to solve the problem of beacon deployment. ELA does not need to calculate the information transmission distance which solves the problem of distance estimation. It takes underwater node movement regulation into computation to solve the problem of node mobility.

Originality value

This paper provides an ELA based on the relationship between propagation energy attenuation and node distance for OITs. It solves the problem of localization in dynamic underwater networks.

Details

Sensor Review, vol. 38 no. 2
Type: Research Article
ISSN: 0260-2288

Keywords

1 – 8 of 8