• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.3
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• pp.201-214
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• 2022

This study theoretically and empirically examined whether organizational communication mediates the effect of organizational learning culture perceived by members in the organization on task performance and contextual performance. Organizational learning culture is defined as a culture that is good at creating, acquiring, transferring, and modifying behavior to reflect new knowledge and insights. The hypothesis of this study is that the perceived organizational learning culture can increase performance through organizational communication between members. In particular, we measured communication within the organization into three types: upward, horizontal, and downward. These communications were set as mediating variables. In empirical studies, independent variables were perceived organizational learning culture, mediation variables were upward, horizontal and downward communication, and dependent variables were task performance and contextual performance. Hypothesis 1 is that the organizational learning culture will have a positive effect on employees' tasks and contextual performance. Hypothesis 2 is about the mediating effect of communication on the relationship between Hypothesis 1. In the empirical study, after verifying the validity and reliability of the research variables, correlation analysis and hypothesis verification were conducted. Hypothesis 1 was verified through regression analysis, and all detailed hypotheses were supported. To verify Hypothesis 2, we conducted a bootstrap test using process macro to separate the total, direct, and indirect effects and examine the significance of the indirect effects. As a result, Hypothesis 2 was partially supported. Downward communication mediated organizational learning culture and task and contextual performance, and horizontal communication mediated organizational learning culture and contextual performance. The mediating effect of upward communication was not significant. The results of this study contributed to the suggestion of implications, research limitations, and research directions. Organizational learning culture is the direction and intention of the organization to achieve its goals through the learning and growth of its members. By strengthening internal motivation, organizational members can take voluntary desirable actions that help groups and organizations as well as essential tasks given. since this relationship appears as a medium of downward communication, organizations can strengthen the relationship between organizational learning culture and performance through leadership education.

• The Journal of Society for e-Business Studies
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• v.26 no.3
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• pp.1-20
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• 2021

As the Great Reset is discussed at the World Economic Forum due to the COVID-19 pandemic, artificial intelligence, the driving force of the 4th industrial revolution, is also in the spotlight. However, corporate research in the field of artificial intelligence is still scarce. Since 2000, related research has focused on how to create value by applying artificial intelligence to existing companies, and research on how startups seize opportunities and enter among existing businesses to create new value can hardly be found. Therefore, this study analyzed the cases of startups using the comprehensive framework of the multi-level perspective with the research question of how artificial intelligence based startups, a sub-industry of software, have different innovation patterns from the existing software industry. The target firms are gazelle firms that have been certified as venture firms in South Korea, as start-ups within 7 years of age, specializing in machine learning modeling purposively sampled in the medical, finance, marketing/advertising, e-commerce, and manufacturing fields. As a result of the analysis, existing software companies have achieved process innovation from an enterprise-wide integration perspective, in contrast machine learning technology based startups identified unit processes that were difficult to automate or create value by dismantling existing processes, and automate and optimize those processes based on data. The contribution of this study is to analyse the birth of artificial intelligence-based startups and their innovation patterns while validating the framework of an integrated multi-level perspective. In addition, since innovation is driven based on data, the ability to respond to data-related regulations is emphasized even for start-ups, and the government needs to eliminate the uncertainty in related systems to create a predictable and flexible business environment.