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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.

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.

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.

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.

Leveraging social action theory, social network theory and the notion of network externality, the purpose of this paper is to model two different return on investment (ROI) measures: the networked ROI which captures the network effect originating from a social media investment, and the discrete ROI which focuses social media discrete returns from individual users.

A field experiment was set up over a period of three months to test the effects of two variants of an advertisement campaign (a social vs a discrete ad) on the modeled networked and discrete ROIs.

The authors find that emphasizing discrete user actions leads to lower network gains, but higher monetary returns while the social action emphasis produces higher network gains, but lower monetary returns. The study further suggests that social action focus is preferable for brand promotion and engagement, whereas the discrete action focus is suitable for boosting sales and website traffic.

Several potential implications for social media researchers and marketers are also discussed.

The authors for the first time showed that that the social media returns are derived not only from individual actions taken by the user (e.g. likes and shares) but also from users’ social interdependencies and the additional exposure that results from network effects.

The primary objective of this paper is to determine the factors that affect the entrepreneurship propensity of students undergoing compulsory entrepreneurship education courses at various universities.

A research instrument was developed and implemented on a sample of 380 students who were offered compulsory entrepreneurship education courses at six major universities in the Jammu and Kashmir region of India. The study employed multiple cross-sectional designs with a simple random sampling technique to gather data. The collected data was subjected to descriptive statistics and structural equation modeling using SMART-PLS (Version 4).

The findings reveal that conceptualization, opportunity identification and implementation are the three antecedents of entrepreneurship propensity. The results indicate that the conceptualization factor is one of the most important predictors of entrepreneurship propensity, followed by opportunity identification, whereas implementation through education has the weakest influence on students' entrepreneurship propensity.

This research provides important insights to universities for designing and developing entrepreneurship courses that can foster the start-up culture. The results will be helpful for policymakers to devise various programs to boost entrepreneurship.

The study integrated the theories of planned behavior and human capital to evaluate the effectiveness of entrepreneurship courses at the university level. The three factors, namely, conceptual factors, actualization factors and implementation factors of entrepreneurship propensity are under-researched.

This study aims to explore Twitter use by Korea's central government by classifying the government's Twitter-based networking strategies into government-to-citizen (G2C) and government-to-government (G2G) strategies.

The study investigates the nature of social media interactions and networking strategies in the Korean government by extracting tweets, follower/following relationships, and hyperlinks for 32 ministries. Network patterns and networking strategies are reviewed through descriptive statistical analysis and social network analysis to map the government's Twitter activity.

The results indicate that the government's direct networking strategy targeting citizens does not necessarily motivate their participation in the government's social media activities but that it plays an instrumental role in reinforcing G2G relationships.

This study investigates the social media use patterns (e.g. network properties and co-link analyses) and strategies (e.g. the reciprocity of relationships and content-push strategies) in the context of G2C and G2G relationships in Korea's public sector.

The purpose of this paper is to seek reasons for some videos going viral over YouTube (a type of social media platform).

Using YouTube APIs (Application Programming Interface) and Webometrics analyst tool, the authors collected data on about 100 all-time-most-viewed YouTube videos and information about the users associated with the videos. The authors constructed and tested an empirical model to understand the relationship among users’ social and non-social capital (e.g. User Age, Gender, View Count, Subscriber, Join Date, Total Videos Posted), video characteristics (Post Date, Duration, and Video Category), external network capital (in-links and hit counts), and Virality (Likes, Dislikes, Favorite Count, View Count, and Comment Count). Partial least square and Webometric analysis was used to explore the association among the constructs.

Among other findings, the results showed that popularity of the videos was not only the function of YouTube system per se, but that network dynamics (e.g. in-links and hits counts) and offline social capital (e.g. fan base and fame) play crucial roles in the viral phenomenon, particularly view count.

The authors for the first time constructed and tested an empirical model to find out the determinants of viral phenomenon over YouTube.

The purpose of this paper is to: empirically validate a modified unified theory of acceptance and use of technology (UTAUT) model by adding an “e‐learning motivation” construct in the South American context; try to determine the role of e‐learning motivation in the use and adoption of e‐learning systems and conversely the effect of technology on students' e‐learning motivation; and to test region and gender as moderators in the model.

A survey method was used to collect data from 47 schools located at different regions: the coast, Andes, and jungle of Peru. The partial least square technique was used for data analysis.

It was found that “e‐learning motivation” and “social influence” had a positive influence on behavioural intention, while “facilitating condition” had no effect on e‐learning portal use. Furthermore, use behaviour had a positive influence on e‐learning motivation. Also found was the moderating role of “region”.

The analysis is carried out in a single country, thus, caution should be taken in generalisation of the results.

The findings will help policy makers and practitioners in developing countries to better understand students' e‐learning motivation.

By adopting the UTAUT model, a new construct of “e‐learning motivation” is added, and applied to the South American context.

This paper aims to explore the flow of nanofluid over bi-directional stretching sheet in the presence of magnetic field and linear thermal radiation.

In this study, water is taken as a base fluid, and copper is diluted in the base fluid. Further, four different shapes of nanoparticles are considered for the analysis. The governing nonlinear partial differential equations are transformed into the system of ordinary differential equations after using the feasible similarity transformations. Solution of the model is then performed by means of Runge–Kutta scheme.

Influence of the emerging dimensionless parameters on velocity, temperature, skin friction coefficient and local rate of heat transfer are studied with the help of graphs.

The study is presented in this paper is original and has not been submitted to any other journal for the publication purpose. The contents are original, and proper references have been provided wherever applicable.

Employee’s innovative behavior as a team allows the organization to achieve its goals; however, team green creativity requires transformational and entrepreneurial leader support. Therefore, the study explores the impact of green transformational and entrepreneurial leadership on team innovative behavior and green new product development with the mediating role of team green creativity.

A survey was conducted to collect data from 455 employees working in the hospitality industry via a self-administered questionnaire, and hypotheses were analyzed using the partial least squares structural equation modeling PLS-SEM technique using Smart-PLS 4.0.

The results indicate that green transformational and entrepreneurial leadership styles positively and significantly affect team innovative behavior and new green product development performance. Furthermore, findings show that team green creativity partially mediates the relationship between green transformational and entrepreneurial leadership on team innovative behavior, and new green product development performance.

The results of this study provide insights to hospitality professionals pursuing the improvement of team innovative behavior and new green product development performance through team green creativity and leadership styles.

This study is useful for organizations that target new green product development performance and establish higher green innovative behavior cohesively among its team members through these robust leadership styles.

This study is the first attempt to provide a valuable contribution to the growing field of green leadership styles on team innovative behavior and new green product development performance through team green creativity.

The Pashtun Jirga is a “tribal” conflict resolution method that has survived for centuries, with the Pashtuns, both in Afghanistan and Pakistan, still practicing it in rural communities. The chapter argues how the introduction and persistence of the Frontier Crimes Regulations, 1901, a colonial-era regulation, has undermined not only the traditional authority of the tribal elders but also diminished the importance of the Jirga. However, the tribal Pashtuns, through Jirga and Jirga-based Lashkars (tribal militias), have also occasionally supported the Pakistani military's actions against various militant groups operating in the Pashtun tribal areas, formerly known as the Federally Administered Tribal Areas. The chapter argues why, even with its positives, the Jirga still possess various loopholes that result in various gender rights violations in the Pashtun society. Finally, the chapter also discusses how recent developments in the Pashtun tribal areas, leading to their merger with the Khyber Pakhtunkhwa Province, along with the introduction of the country's judiciary present a challenge for the survival of the Jirga as a conflict resolution tool in the tribal areas. Moreover, the chapter also argues why the young Pashtuns from the tribal region are against the male-dominated nature of Jirga and want it to be replaced with modern judicial structures, presenting a challenge to the survival of Jirga in Pakistan.

This study aims to offer a hybrid stand-alone system for electric vehicle (EV) charging stations (CS), an emerging power scheme due to the availability of renewable and environment-friendly energy sources. This paper presents the analysis of a photovoltaic (PV) with an adaptive neuro-fuzzy inference system (ANFIS) algorithm, solid oxide fuel cell (SOFC) and a battery storage scheme incorporated for EV CS in a stand-alone mode. In previous studies, either the hydrogen fuel of SOFC or the irradiance is controlled using artificial neural network. These parameters are not controlled simultaneously using an ANFIS-based approach. The ANFIS-based stand-alone hybrid system controlling both the fuel flow of SOFC and the irradiance of PV is discussed in this paper.

The ANFIS algorithm provides an efficient estimation of maximum power (MP) to the nonlinear voltage–current characteristics of a PV, integrated with a direct current–direct current (DC–DC) converter to boost output voltage up to 400 V. The issue of fuel starvation in SOFC due to load transients is also mitigated using an ANFIS-based fuel flow regulator, which robustly provides fuel, i.e. hydrogen per necessity. Furthermore, to ensure uninterrupted power to the CS, PV is integrated with a SOFC array, and a battery storage bank is used as a backup in the current scenario. A power management system efficiently shares power among the aforesaid sources.

A comprehensive simulation test bed for a stand-alone power system (PV cells and SOFC) is developed in MATLAB/Simulink. The adaptability and robustness of the proposed control paradigm are investigated through simulation results in a stand-alone hybrid power system test bed.

The simulation results confirm the effectiveness of the ANFIS algorithm in a stand-alone hybrid power system scheme.