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PurposeThe purpose of this study is to clarify theory and identify factors that could explain the level of fintech continuance intentions with an expectation confirmation model that integrates self-efficacy theory.Design/methodology/approachWith data collected from 753 fintech users, this study applies partial least square structural equation modeling to compare and select the research model with the most predictive power.FindingsThe results show that financial self-efficacy, technological self-efficacy and confirmation positively affect perceived usefulness. Among these factors, financial self-efficacy and technological self-efficacy have both direct and indirect effects through confirmation on perceived usefulness. Perceived usefulness and confirmation are positively related to satisfaction. Finally, perceived usefulness and satisfaction positively influence fintech continuance intentions.Originality/valueTo the best of our knowledge, this is one of the earliest studies that investigates the effect of domain-specific self-efficacy on fintech continuance intentions, which enriches the existing research on fintech and deepens our understanding of users' fintech continuance intentions. We distinguish between financial self-efficacy and technological self-efficacy and specify the relationship between self-efficacy and continuance intentions. Moreover, this study highlights the importance of assessing a model's predictive power using the PLSpredict technique and provides a reference for model selection.

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Purpose The purpose of this paper is to explore the knowledge infrastructure of methodological research on partial least squares structural equation modeling (PLS-SEM) from a network point of view. The analysis involves the structures of authors, institutions, countries and co-citation networks, and discloses trending developments in the field. Design/methodology/approach Based on bibliometric data downloaded from the Web of Science, the authors apply various social network analysis (SNA) and visualization tools to examine the structure of knowledge networks of the PLS-SEM domain. Specifically, the authors investigate the PLS-SEM knowledge network by analyzing 84 methodological studies published in 39 journals by 145 authors from 106 institutions. Findings The analysis reveals that specific authors dominate the network, whereas most authors work in isolated groups, loosely connected to the network’s focal authors. Besides presenting the results of a country level analysis, the research also identifies journals that play a key role in disseminating knowledge in the network. Finally, a burst detection analysis indicates that method comparisons and extensions, for example, to estimate common factor model data or to leverage PLS-SEM’s predictive capabilities, feature prominently in recent research. Originality/value Addressing the limitations of prior systematic literature reviews on the PLS-SEM method, this is the first study to apply SNA to reveal the interrelated structures and properties of PLS-SEM’s research domain.

Internet research using partial least squares structural equation modeling (PLS-SEM) Innovation and diffusion of PLS-SEM Since Wold (1974) developed the PLS algorithm more than 40 years ago, the method has evolved considerably, particularly in recent years. Indeed, numerous researchers have contributed to expanding awareness and applications of what is now known as PLS-SEM. Today, PLS-SEM belongs to the common portfolio of multivariate analysis methods (Hair, Black, Babin and Anderson, 2018). But the road to its widespread adoption among researchers and practitioners was not always straightforward and sometimes bumpy. Figure 1 visualizes some key publications that contributed to the development and diffusion of PLS-SEM.PLS-SEM was standing in the shadows of the more popular covariance-based SEM (CB-SEM) method for many years. A likely reason was Jöreskog's development of the LISREL software, which led to the early widespread adoption of CB-SEM. In contrast, without software, PLS-SEM remained relatively unknownnotwithstanding early research comparing the methods and offering guidance for their choice ( Jöreskog and Wold, 1982;Dijkstra, 1983). This pattern continued for almost 20 years despite several fundamental advantages of PLS-SEM. The primary advantages of PLS-SEM include the relaxation of "hard" distributional assumptions required by the maximum likelihood method used to estimate models using CB-SEM, and PLS-SEM's ability to easily estimate much more complex models with smaller sample sizes ( Jöreskog and Wold, 1982). Lohmöller (1984) introduced the LVPLS software to estimate causal models and later published the comprehensive PLS-SEM textbook Latent Variable Path Modeling with Partial Least Squares (Lohmöller, 1989). Then in the early 1990s, Falk and Miller (1992) published their Primer on Soft Modeling. Despite these developments, little interest was shown in the method until Chin (1998) introduced the method to business research in his seminal article in Marcoulides's (1998) edited volume Modern Methods for Business Research, followed by his release of PLS-Graph ( 2003)the first software package with a graphical user interface for PLS-SEM analyses. While the availability of PLS-Graph (Chin, 2003) accelerated the use of PLS-SEM, particularly in management information systems (Ringle et al., 2012;Hair, Hollingsworth, Randolph and Chong, 2017), applications grew exponentially following the release of the free SmartPLS 2 software (Ringle et al., 2005) that included many analysis options and quickly became the most popular PLS-SEM software (e.g. Ali et al., 2018;Nitzl, 2016;. About the same time, Tenenhaus et al.'s (2005) seminal article was released, which summarized PLS-SEM's statistical properties and introduced it to a broader audience of methodological researchers. Also, international conferences such as the International Symposium on PLS and Related Methods started gaining momentum. In this regard, the 2005 PLS conference in Barcelona (Spain) certainly shaped the field by forming a strong and collaborat...

The purpose of this study is to understand factors that affect continuance intention of a popular hedonic information system, blogs. The expectation-confirmation theory (ECT) is adapted with perceived enjoyment, habit and user involvement. Data was collected via an online survey. A total of 430 valid responses were collected. The research model was assessed by structural equation modelling (SEM). The results show that continuance intention of blog use was predicted collectively by user involvement, satisfaction and perceived enjoyment. Habit, however, exhibited no strong relationship with satisfaction and use intention. Users' satisfaction with blog use was predicted primarily by perceived enjoyment, followed by users' confirmation of expectation and user involvement. Perceived enjoyment was predicted by users' involvement and users' confirmation of expectation. Blogging time significantly moderates the effect of habit on perceived enjoyment, but not on satisfaction and continuance intention. The integrated model explains 65% of the satisfaction and 57% of continuance intention. The results suggest that integrating perceived enjoyment and user involvement into the ECT provides better insights into continuous use in the blog context.

PurposeThe purpose of this paper is to contribute to the development of measures to assess the ERP adoption of small and medium‐sized enterprises.Design/methodology/approachThe paper follows Churchill's guideline for developing measures that have desirable reliability and validity. The pilot data are used to develop a proper measurement. The survey data, based on the 126 valid responses of 328 companies, are analysed by structural equation modelling (SEM) statistical methods.FindingsThe paper finds that the dimensions affecting ERP adoption show that characteristics of the CEO and perceived benefits possess positive effects on ERP adoption, while cost and technology have negative effects on ERP adoption. However, only “perceived benefits” is a significant dimension. It is surprising that the cost of the ERP system does not significantly affect ERP adoption.Research limitations/implicationsThe paper shows that the sample size should be taken into consideration when generalising the findings, and extended data and measures are required for further in‐depth investigation in specific areas.Practical implicationsThe paper points out that the managers of SMEs with limited resources can find many ways to get more resources from governments. Government managers should be more realistically set the goal of helping firms in a healthy condition to adopt e‐business instead of setting the goal of improving the e‐business readiness of all SMEs. To help all CEOs of SMEs to realise the potential benefits, governments can work with academic research groups to set up forums and workshops to broadcast knowledge.Originality/valueThe paper develops measurements to assess the ERP adoption of small and medium‐sized enterprises. The results offer practical help for government managers to better understand ERP adoption with institutional help in Taiwan. Meanwhile, researchers interested in IT/IS can use the information provided here to guide their future enquiries.

Over one billion people are currently using social media such as social websites (Facebook Newsroom 2015); consequently, numerous academic scholars have developed interest in studying the use of social media and social networks. However, few studies have focused on examining the core factors of social networks. In this study, we collected studies on social-network-related topics that were published between January 1996 and December 2014, assembling a total of 2,565 articles and 81,316 citations. Co-citation analysis and cluster analysis were applied to verify seven main factors regarding social networks: (a) the measure of complex social networks; (b) community structure; (c) strong and weak ties; (d) the evolution of social networks; (e) network structure and relationship; (f) value concept and measurement strategies; and (g) social capital. Finally, the results of this study were further discussed to elucidate the core topics relevant to social networks.