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Digital live streaming applications, combined with the broadcasting of cross-modal, video-mediated communication in the social networking community, have grown in popularity in recent years. A theoretical gap exists regarding a comprehensive framework that explains hardcore viewer engagement through the social exchanges in digital live streaming communities. Traditional viewers engaged with a single-dimensional focal object, but nowadays, viewers interact with multidimensional and multiobjects through the social exchanges (e.g. virtual gifts, emotional supports) in live streaming digital communities. This study aims to address this void in the marketing literature of hardcore viewer engagement under dynamic social exchanges in digital live streaming communities.

This research used a qualitative approach. The data collections were from October 2018 to January 2020. Data were collected in semistructured interviews with 17 Media 21 hardcore viewers.

The outcomes of hardcore viewer engagement and social exchange include three main stages: introduction, immersion and enthusiasm. It indicates that loyalty and active hardcore viewer–streamer relationships were fostered through the process of hardcore viewer engagement and social exchange with multiple objects and dimensions.

There are three main implications to the literature in this study. First, this empirical study extends the concept of consumer engagement to hardcore viewer engagement, and social exchange is found to trigger social behavior and relations in a digital live streaming community. Second, it contributes to the social media community literature. Hardcore viewer engagement provides a broad dimensional scope to examine digital live streaming community participation by integrating the cognitive, affective and behavioral aspects. Finally, it contributes to the literature of social exchange theory. It indicates that the extension of hardcore viewer–streamer social relationships is not restricted to traditional mass media but can be fostered in digital live streaming communities.

It contributes to the consumer engagement literature by exploring in depth viewer engagement dimensionality in a rich digital live streaming context. This study proposed a framework for understanding the stages and outcomes of viewer engagement and parasocial interactions according to three dimensions and multiple objects, which lacked empirical validation in previous studies.

This study also contributes to the social media community literature. In capturing the functions of such groups, the variables of interest were “participation,” “involvement” and “membership.” These variables were determined through behavioral actions or intentions. In contrast, viewer engagement provided a broad dimensional scope to examine digital live streaming community participation by integrating the cognitive, affective and behavioral aspects.

The findings of this study indicate that the extension of parasocial relationships is not restricted to traditional mass media but can be fostered in digital live streaming communities that are designed to bring the viewer close to streamer(s), community members and system functions and activities. Although digital live streaming applications differ from traditional parasocial interaction environments because they offer direct, instantaneous, multiple communication among streamer(s), system functions and community members, the findings of the present study indicate that viewer–streamer–viewer parasocial relationships established both online and offline are often interwoven.

Social media influencers (SMIs) have become vital components of interactive marketing to promote beauty-endorsed products. However, there are three major research gaps in the literature on influencer marketing. This research aimed to fill these gaps by integrating the stimulus-organism-response (SOR) model with theories of source credibility and parasocial interaction (PSI).

A qualitative method was used to gain a deep understanding of the Korean beauty field in YouTube influencer marketing.

The data showed that YouTube influencer marketing is an ongoing PSI process that conforms to the extended SOR model. This model was based on four concepts: stimulus, which was the SMIs’ source credibility; organism, which was the followers’ perceptions of homophily/relevance to the SMIs in PSIs; response, which was the desire to imitate and engage in impulse buying behavior, and management, which was the parasocial trust friendship and/or relationship.

This study expands the new concept into the existing SOR model and releases an insight into ongoing PSIs in YouTube influencer marketing.

The information needs of the users of literature database systems often come from the task at hand, which is short term and can be represented as a small number of articles. Previous works on recommending articles to satisfy users’ short-term interests have utilized article content, usage logs, and more recently, coauthorship networks. The usefulness of coauthorship has been demonstrated by some research works, which, however, tend to adopt a simple coauthorship network that records only the strength of coauthorships. The purpose of this paper is to enhance the effectiveness of coauthorship-based recommendation by incorporating scholars’ collaboration topics into the coauthorship network.

The authors propose a latent Dirichlet allocation (LDA)-coauthorship-network-based method that integrates topic information into the links of the coauthorship networks using LDA, and a task-focused technique is developed for recommending literature articles.

The experimental results using information systems journal articles show that the proposed method is more effective than the previous coauthorship network-based method over all scenarios examined. The authors further develop a hybrid method that combines the results of content-based and LDA-coauthorship-network-based recommendations. The resulting hybrid method achieves greater or comparable recommendation effectiveness under all scenarios when compared to the content-based method.

This paper makes two contributions. The authors first show that topic model is indeed useful and can be incorporated into the construction of coaurthoship-network to improve literature recommendation. The authors subsequently demonstrate that coauthorship-network-based and content-based recommendations are complementary in their hit article rank distributions, and then devise a hybrid recommendation method to further improve the effectiveness of literature recommendation.

In his autobiography, Chen Shui-bian (1999, p. 40) condemned the Koumintang's (KMT's) corruption and praised the Democratic Progressive Party (DPP) for being free from money politics and corruption. The DPP fought the 1992 Legislative Yuan election campaign effectively on an anticorruption platform and used the same strategy in subsequent elections. If Chen Shui-bian had criticized the KMT for its involvement with “black gold” politics and had won the 2000 presidential election on his anticorruption platform, why was he and his family found guilty of corruption after his second term of office? The short answer is that even though he had promised to curb corruption, President Chen himself had succumbed to corruption after assuming office. In June 2002, Keesing's Contemporary Archives cited a poll in Taiwan that indicated that more respondents had perceived the DPP to be more corrupt than the KMT (Copper, 2006, p. 14).

This paper aims to link academic classifications of service innovation with practical activities by firms to detail the essence of service innovation.

This research employs both qualitative and quantitative analyses. The qualitative study features interviews with senior managers from 590 companies, covering nine industries in Taiwan, to gather practitioners ' perspectives on service innovation. A content analysis details specific forms of service innovation. The quantitative study provides a homogeneity test and two-sample proportions test to examine differences in service innovation perspectives/activities across organizational characteristics.

The interview data link three types of service innovations to 11 associated elements and 25 labels, derived from 659 potential service innovation incidents (550 new service concepts, 82 new service processes, and 27 new service business models). This study also shows that elements of service innovations vary by company size, service innovation experience, and industry life cycle.

The three types of service innovations enable businesses to benchmark and modify their current service innovation activities. Service managers can use the results of this study to develop their own service innovation strategies and concrete action plans.

This pioneering study links the viewpoints of academics with practical service innovation activities and empirically shows that service innovation is dissimilar, depending on various organization characteristics.

This study aims to investigate the spectral illumination characteristics and geometric features of bicycle parts and proposes an image stitching method for their automatic visual inspection.

The unrealistic color casts of feature inspection is removed using white balance for global adjustment. The scale-invariant feature transforms (SIFT) is used to extract and detect the image features of image stitching. The Hough transform is used to detect the parameters of a circle for roundness of bicycle parts.

Results showed that maximum errors of 0°, 10°, 20°, 30°, 40° and 50° for the spectral illumination of white light light-emitting diode arrays with differential shift displacements are 4.4, 4.2, 7.8, 6.8, 8.1 and 3.5 per cent, respectively. The deviation error of image stitching for the stem accessory in x and y coordinates are 2 pixels. The SIFT and RANSAC enable to transform the stem image into local feature coordinates that are invariant to the illumination change.

This study can be applied to many fields of modern industrial manufacturing and provide useful information for automatic inspection and image stitching.

The current work studies the cause, process, and effects of financial reform in 10 countries in Eastern Asia for the period of 1993–2002, especially focusing upon comparisons between pre- and post-Asia financial crisis. This study utilizes Mann–Whitney U test and Intervention Analysis to explore the different effects of the changes of GDP, stock index, exchange rate, CPI index, and the changes of the unemployment rate before and after the Asia financial crisis. It shows the consistent relationship between stock index, exchange rate, CPI index, and the changes of unemployment rate.

Based on organizational capabilities and information technology implementation literature, this study seeks to propose a research model to examine the influence of organizational capabilities on e‐business implementation success.

Data collected from 202 information systems executives in large Taiwanese organizations were employed to test the relationships between the research model constructs. The results from the structural equation modeling approach provide quite a strong support for the hypothesized relations.

The results showed that certain factors related to organizational learning and knowledge management capabilities are important antecedents of e‐business value.

This study did not test all organizational factors, and focused particularly on learning capacity and knowledge capability factors. A knowledge asset must be rare and inimitable to become a source of competitive advantage. Without secure processes, knowledge loses the key qualities of being rare and inimitable. Future research could assess the influence of knowledge protection processes on e‐business implementation success.

Knowledge management means recognizing and managing all of an organization's intellectual and social capital to meet its e‐business objectives. An organization needs a well‐designed knowledge management infrastructure to create and maintain the e‐business knowledge required to improve back‐office efficiency, customer intimacy and efficiency of coordination with business partners.

This study is significant for at least two reasons: it determines the key antecedents to successful e‐business implementation based on organizational learning and knowledge management perspectives and it helps to understand the effects of organizational capabilities and e‐business contribution on a firm's performance.

The purpose of this paper is to apply social network analysis (SNA) to study faculty research productivity, to identify key leaders, to study publication keywords and research areas and to visualize international collaboration patterns and analyze collaboration research fields from all Management Information System (MIS) departments in Taiwan from 1982 to 2015.

The authors first retrieved results encompassing about 1,766 MIS professors and their publication records between 1982 and 2015 from the Ministry of Science and Technology of Taiwan (MOST) website. Next, the authors merged these publication records with the records obtained from the Web of Science, Google Scholar, IEEE Xplore, ScienceDirect, Airiti Library and Springer Link databases. The authors further applied six network centrality equations, leadership index, exponential weighted moving average (EWMA), contribution value and k-means clustering algorithms to analyze the collaboration patterns, research productivity and publication patterns. Finally, the authors applied D3.js to visualize the faculty members' international collaborations from all MIS departments in Taiwan.

The authors have first identified important scholars or leaders in the network. The authors also see that most MIS scholars in Taiwan tend to publish their papers in the journals such as Decision Support Systems and Information and Management. The authors have further figured out the significant scholars who have actively collaborated with academics in other countries. Furthermore, the authors have recognized the universities that have frequent collaboration with other international universities. The United States, China, Canada and the United Kingdom are the countries that have the highest numbers of collaborations with Taiwanese academics. Lastly, the keywords model, system and algorithm were the most common terms used in recent years.

This study applied SNA to visualize international research collaboration patterns and has revealed some salient characteristics of international cooperation trends and patterns, leadership networks and influences and research productivity for faculty in Information Management departments in Taiwan from 1982 to 2015. In addition, the authors have discovered the most common keywords used in recent years.