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PurposeThe outbreak of the Coronavirus (COVID-19) pandemic and its preventative social distancing measures have led to a dramatic increase in subscriptions to paid streaming services. Online users are increasingly accessing live broadcasts, as well as recorded video content and digital music services through internet and mobile devices. In this context, this study aims to explore the individuals’ uses and gratifications from online streaming technologies during COVID-19.Design/methodology/approachThis research has adapted key measures from the “technology acceptance model” (TAM) and from the “uses and gratifications theory” (UGT) to better understand the individuals’ intentions to use online streaming technologies. A structural equations partial least squares’ confirmatory composite approach was used to analyze the gathered data.FindingsThe individuals’ perceived usefulness and ease of use of online streaming services were significant antecedents of their intentions to use the mentioned technologies. Moreover, this study suggests that the research participants sought emotional gratifications from online streaming technologies, as they allowed them to distract themselves into a better mood and to relax in their leisure time. Evidently, they were using them to satisfy their needs for information and entertainment.Research limitations/implicationsThis study contributes to the academic literature by generating new knowledge about the individuals’ perceptions, motivations and intentions to use online streaming technologies to watch recorded movies, series and live broadcasts.Practical implicationsThe findings imply that there is scope for the providers of online streaming services to improve their customer-centric marketing by refining the quality and content of their recorded programs and through regular interactions with subscribers and personalized recommender systems.Originality/valueThis study integrates the TAM and UGT frameworks to better understand the effects of the users’ perceptions, ritualized and instrumental motivations on their intentions to continue watching movies, series and broadcasts through online streaming technologies, during COVID-19.

The paper determines Machine Learning (ML) applications of both supervised and unsupervised types in computerised accounting information systems (CAIS) to improve data consistency. The Partial Least Squares Structural Equation Modelling (SEM-PLS) approach was used for the processing of data, which comprised 163 building companies in China that were using Building Information Modelling (BIM). This paper examines the financial data in view of ML algorithms and looks into the way ML improves financial data accuracy, consistency, reliability, and consistency. The results revealed that the integration of ML algorithms could increase data integrity (DI) by as much as 27% and detection of error by as much as 35% compared with manual methods. These results emphasise artificial intelligence (AI) solutions' leading role in improving CAIS-focused financial decision-making and operational control systems, demonstrating how AI can be applied to the field efficiently. By investigating the impact of ML on data integrity, which is measured through advanced SEM-PLS technique, this research is among the first studies on AI finance to deepen the knowledge.

During the outbreak of the Coronavirus (COVID-19) pandemic, higher education institutions (HEIs) have shifted from traditional and blended learning approaches to a fully virtual course delivery. This research investigates the students’ perceptions on remote learning through asynchronous learning management systems (LMS) and via synchronous video conferencing technologies like Google Meet, Microsoft Teams or Zoom, among others. The data was gathered from a sample of 501 higher education students in a Southern European context. A survey questionnaire included measures that investigated the participants’ acceptance of interactive technology to better understand their utilitarian motivations to use them. The findings suggest that the research participants accessed asynchronous content and interacted with online users, including with their course instructor, in real time. While there are a number of theoretical or opinion papers on the impact of COVID-19 on higher education services, currently, there are still a few empirical papers that shed light on the factors that are having an effect on the students’ attitudes and intentions to utilize remote learning technologies. This contribution underlines the importance of maintaining ongoing, interactive engagement with students, and of providing them with appropriate facilitating conditions, to continue improving their learning journey.

PurposeGlobal economies are involved with enormous activities of internationalization that provide pure and untapped opportunities for entrepreneurs and businesses to place and promote their products.Design/methodology/approachThe authors applied structural equation modeling (SEM) analysis with the partial least squares (PLS), conducting an empirical analysis of data from 28 European countries.FindingsThe results reveal that the higher level of education/knowledge in a country enhances the foresight competencies of entrepreneurs and that they both have a positive influence on the effective business creation. The findings of this paper also stress on the positive relationship between the effect of business creation and international intensity in economy level.Research limitations/implicationsThe limitation of this study lies in the impossibility of obtaining a larger and more complete data. Consequently, this study uses national-level data from 28 European countries, which makes the sample too small. In addition, although innovation is one of the driving factors in both internationalization and entrepreneurship, because of the limitation, it has not been considered in this study.Practical implicationsThe authors assert that countries, specifically European nations studied in this research, can improve their employment rate and value creation (through their products in international markets) by giving a special attention to the entrepreneurial-oriented human capitals.Social implicationsThis research warns policymakers that they can have a serious contribution in promoting (international) entrepreneurship. They should draw a rigorous plan for formal and informal educational systems that effectively develops essential knowledge for launching new businesses and fosters the innovation and entrepreneurship.Originality/valueThis study set out to improve the understanding of the role of level of education/knowledge and foresight competencies, as the elements of human capitals, on international entrepreneurship.

Innovative behavior refers to the deliberate engagement in activities to generate and embrace novel ideas, concepts, or approaches to execute and accomplish tasks effectively. This study aims to investigate the impact of transformational leadership and emotional intelligence on innovative work behavior through knowledge sharing. The research population was employees in several public hospitals in Medan, North Sumatra, Indonesia. This quantitative study used survey methodology by sending questionnaires to administrative employees of public hospitals. The samples for this study consisted of 129 administrative employees with a minimum of one year of service at various public hospitals. The investigation employed a Likert scale questionnaire to gather data, which were subsequently analyzed utilizing SEM-PLS in conjunction with SmartPLS 4.0 software. The findings of this study indicate the influence between transformational leadership and emotional intelligence on knowledge sharing (p < 0.05) and innovative work behavior (p < 0.05). In addition, knowledge sharing affects innovative work behavior (p < 0.05). Knowledge sharing mediates the influence of transformational leadership on innovative work behavior (p < 0.05), and knowledge sharing mediates the influence of emotional intelligence on innovative work behavior (p < 0.05). AcknowledgmentThe funding for this study was provided by the budget allocated to Universitas Muhammadiyah Sumatera Utara for the fiscal year 2023. Hence, we express our profound appreciation to the Rectorate of Universitas Muhammadiyah Sumatera Utara and the Institute for Research and Community Service (LPPM) of Universitas Muhammadiyah Sumatera Utara.

Data-driven innovation (DDI) is a primary source of competitive advantage for firms and is a contemporary research priority. However, what facilitates the development of DDI has largely been understudied in literature. Through a systematic literature review, this study finds technological, organizational, and environmental variables under the TOE framework, which would drive effective DDI development. We thus develop a research model, which is tested using survey data from 264 Australian firms engaged in DDI development. The data have been analysed using both symmetric (partial least squares based structural equation modelling (PLS-SEM)) and asymmetric (fuzzy-set qualitative comparative analysis (fsQCA)) methods. The mixed method enhances the confidence in our empirical analyses of the antecedent variables of DDI development. PLS-SEM has revealed that technological readiness (i.e., data quality and metadata quality), and organizational absorptive capacity and readiness (i.e., technology-oriented leadership and availability of IT skilled professionals) affect DDI development. Our fsQCA results complement and extend the findings of PSL-SEM analysis. It reveals that quality of data and metadata, technology-oriented leadership, and exploitation capacity individually are necessary—but are not sufficient—conditions for high DDI development. Further, it identifies three different solutions each for small, medium, and large firms by combining the TOE factors. Additionally, this study suggests that the TOE framework is more applicable to small firms, on DDI context. Findings of our study have been related with theoretical and practical implications.

The researchers use the SEM-based multivariate approach to analyze the data in different fields, including management sciences and economics. Partial least square structural equation modeling (PLS-SEM) and covariance-based structural equation modeling (CB-SEM) are powerful data analysis techniques. This paper aims to compare both models, their efficiencies and deficiencies, methodologies, procedures, and how to employ the models. The outcomes of this paper exhibited that the PLS-SEM is a technique that combines the strengths of structural equation modeling and partial least squares. It is imperative to know that the PLS-SEM is a powerful technique that can handle measurement error at the highest levels, trim and unbalanced datasets, and latent variables. It is beneficial for analyzing relationships among latent constructs that may not be candidly witnessed and might not be applied in situations where traditional SEM would be infeasible. However, the CB-SEM approach is a procedure that pools the strengths of both structural equation modeling and confirmatory factor analysis. The CB-SEM is a dominant multivariate technique that can grip multiple groups and indicators; it is beneficial for analyzing relationships among latent variables and multiple manifest variables, which can be directly observed. The paper concluded that the PLS-SEM is a more suitable technique for analyzing relations among latent constructs, generally for a small dataset, and the measurement error is high. However, the CB-SEM is suitable for analyzing compound latent and manifest constructs, mainly when the goal is to generalize results to specific population subgroups. The PLS-SEM and CB-SEM have specific efficiencies and deficiencies that determine which technique to use depending on resource availability, the research question, the dataset, and the available time.

Financial Management Behavior refers to the systematic activities involved in predicting, gathering, allocating, investing, and strategizing the cash flow required for a company’s or individual’s efficient functioning. This study aims to examine the role of locus of control in moderating the relationship between financial socialization, financial knowledge, financial experience, and financial management behavior among Paylater users in Medan, North Sumatra, Indonesia. The population of this research is the people of Medan, North Sumatra, Indonesia, who use Paylater. The sampling methodologies utilized were purposive sampling and snowball sampling. A total of 221 individuals participated in data collection for this study. The questionnaires were disseminated using social media chat functions or messaging applications (e.g., WhatsApp, Line, Telegram) in which the Google Forms link is shared. The study employs the data analysis technique of SEM-PLS with the assistance of PLS 4.00 software. The research results show that financial socialization, knowledge, and experience influence financial management behavior (p < 0.05). Furthermore, financial socialization, financial knowledge, and financial experience influence financial management behavior, moderated by locus of control (p < 0.05). The research implications are expected to improve the Financial Management behavior of the Paylater users by providing literacy about managing their finances. AcknowledgmentThis study was funded by the Revenue and Expenditure Budget of the Universitas Muhammadiyah Sumatera Utara following the assignment agreement letter in the context of implementing the Basic Research Program of the Revenue and Expenditure Budget of the Universitas Muhammadiyah Sumatera Utara for the 2023 Fiscal Year, Number: 73/II.3- AU /UMSU-LP2M/C/2023.

Objective: This study aimed to analyze the influence of regulations on green marketing through consumer behavior in shrimp exporting companies in East Java.   Theoretical Framework: In this topic, regulations refer to how policies and rules set by the government or regulatory bodies influence the way consumers act, behave, or make decisions in consumption activities. These regulations can apply in various economic fields and sectors, such as health, environment, finance, consumer products, and others.   Method: A quantitative method was used, while data were collected through a survey of shrimp exporting companies in East Java. The samples comprised 42 shrimp companies and data were analyzed using SEM-PLS.   Results and Discussion: The results showed that government regulations have a significant effect on consumer behavior in shrimp exporting companies. Regulations that effectively guide consumers towards selecting environmentally friendly products can motivate companies to further improve green marketing.   Research Implications: The results provide practical guidance for shrimp exporting companies in the quest to achieve sustainable growth through environmentally responsible business strategies.   Originality/Value: This research highlights the role of regulations in encouraging companies to adopt environmentally friendly marketing practices and is specifically carried out in shrimp exporting companies in East Java, Indonesia.

Type of the article: Research Article AbstractAn individual’s intention to invest reflects their inclination to explore diverse investment instruments, allocate time to understand investment mechanisms through activities such as seminars or workshops, and actively participate in investment practices. This issue is particularly relevant, given the relatively low levels of financial literacy and investment participation among the public, especially Generation Z. The present study aims to examine the influence of financial literacy, prior behavioral experience, and subjective norms on investment intention among Generation Z in North Sumatra, Indonesia, both directly and indirectly through perceived behavioral control. Respondents comprised students and employees identified as Generation Z, selected using purposive and snowball sampling techniques, with data collected via online questionnaires. A quantitative approach was employed, and data were analyzed using Structural Equation Modeling with Partial Least Squares (PLS) version 4.0. The results demonstrate that financial literacy has a significant positive impact on both investment intention (p < 0.05) and perceived behavioral control (p < 0.05). Furthermore, perceived behavioral control, previous experience, and subjective norms significantly influence investment intention (p < 0.05). Mediation analysis reveals that perceived behavioral control plays a notable mediating role in the relationship between financial literacy and investment intention (p < 0.05). These findings emphasize the need to enhance financial literacy, strengthen investment communities, and deliver targeted training to build Generation Z’s confidence in investing, thereby fostering their investment intentions strategically and sustainably.