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Predicting the impact of social entrepreneurship is crucial as it can help social entrepreneurs to determine the achievement of their social mission and performance. However, there is a lack of existing social entrepreneurship models to predict social enterprises' social impacts. This paper aims to propose the social impact prediction model for social entrepreneurs using a data analytic approach.

This study implemented an experimental method using three different algorithms: naive Bayes, k-nearest neighbor and J48 decision tree algorithms to develop and test the social impact prediction model.

The accurate result of the developed social impact prediction model is based on the list of identified social impact prediction variables that have been evaluated by social entrepreneurship experts. Based on the three algorithms' implementation of the model, the results showed that naive Bayes is the best performance classifier for social impact prediction accuracy.

Although there are three categories of social entrepreneurship impact, this research only focuses on social impact. There will be a bright future of social entrepreneurship if the research can focus on all three social entrepreneurship categories. Future research in this area could look beyond these three categories of social entrepreneurship, so the prediction of social impact will be broader. The prospective researcher also can look beyond the difference and similarities of economic, social impacts and environmental impacts and study the overall perspective on those impacts.

This paper fulfills the need for the Malaysian social entrepreneurship blueprint to design the social impact in social entrepreneurship. There are none of the prediction models that can be used in predicting social impact in Malaysia. This study also contributes to social entrepreneur researchers, as the new social impact prediction variables found can be used in predicting social impact in social entrepreneurship in the future, which may lead to the significance of the prediction performance.

Although the financial shared service (FSS) mode has become a well-established organizational arrangement, current information system (IS) research remains limited and mixed. The purpose of this study is to narrow research gaps in the literature on shared services from an FSS practice perspective. The following research questions guide this study: (1) what are the important antecedents of FSS implementation? (2) what is the impact of FSS implementation on firm performance?

Drawing on the technology–organization–environment (TOE) framework and previous innovation studies, this study explores the impact of FSS implementation on firm performance. A questionnaire survey was conducted on Chinese firms using partial least squares (PLS) for data analysis.

The authors find technological, organizational and environmental factors affect the extent and depth of FSS implementation. The empirical results show that relative advantage, compatibility, top management support, managerial obstacles and competitive pressure significantly affect FSS implementation, but bandwagon pressure does not have a direct impact on it. Top management support is the most important factor, and managerial obstacles and compatibility are controllable and manageable factors for firms. The study confirms that FSS improves the financial and non-financial performance of firms significantly, and the degree of improvement in non-financial is greater than that in financial performance.

A comprehension of the key factors influencing FSS implementation will help companies predict weaknesses in their implementation plan and design suitable strategies to handle deployment to achieve these benefits. Managers can make a comprehensive decision regarding the long-term development of combining FSS and the suitability of companies.

The findings contribute to the shared services implementation theory by identifying a set of theoretical factors that shape a firm's shared service implementation. This study provides empirical support to gauge the impact of FSS implementation on firm performance and provides new evidence for a shared-service payoff study. Moreover, the study extends the applicability of the TOE framework and the balanced scorecard (BSC) viewpoint to the FSS implementation field.

This study aims to identify the negotiation parameters of needs for Halal talents in Malaysia and proffer solutions on the sustainability of halal talents in Malaysia.

A focus group discussion was performed among seven Halal talents from the industries of various schemes. Using the theory of inventive problem solving (TRIZ) analysis approach, a functional model, as well as causes and effect analysis, is generated by the participants. The model is translated into a contradiction matrix to obtain the necessary solutions in developing a sustainable framework for Halal Talents in Malaysia.

The cause-and-effect analysis reveals that poor career path, lack of training and poor salary structure are experienced by the participants.

Having had vast categories of halal industries, this research focuses on nine schemes under halal certification JAKIM which excludes banking and tourism.

It is suggested that the implementation of mutual benefits should be in place to enhance positivism among Halal talents in the near future.

Unlike the social science approach, the use of TRIZ analysis provides a substantial framework of sustainability among halal talents in Malaysia.

The purpose of this study is to investigate the addition of 0.05 Wt.% carbon nanotube (CNT) into the Sn-1.0Ag-0.5Cu (SAC) solder on the intermetallic (IMC) growth. Lead-based solders play an important role in a variety of applications in electronic industries. Due to the toxicity of the lead in the solder, lead-free solders were proposed to replace the lead-based solders. Sn-Ag-Cu solder family is one of the lead-free solders, which are proposed and considered as a potential replacement. Unfortunately, the Sn-Ag-Cu solder faces some reliability problems because of the formation of the thick intermetallic compounds. So the retardation of intermetallic growth is prime important.

The solder joint was aged under liquid state aging with soldering time from 1 to 60 min.

Two types of intermetallics, which are Cu₆Sn₅ and Cu₃Sn were observed under a scanning electron microscope. The morphology of Cu₆Sn₅ intermetallic transformed from scallop to planar type as the soldering time increases. The addition of carbon nanotube into the SAC solder has retarded the Cu₆Sn₅ intermetallic growth rate by increasing its activation energy from 97.86 to 101.45 kJ/mol. Furthermore, the activation energy for the Cu₃Sn growth has increased from 102.10 to 104.23 kJ/mol.

The increase in the activation energy indicates that the growth of the intermetallics was slower. This implies that the addition of carbon nanotube increases the reliability of the solder joint and are suitable for microelectronics applications.

Factors influencing the use of mobile phone technologies for agricultural market information access remain a mixed debate, and there are contradictive views among studies. This study examined factors influencing the use of mobile phone technologies for agricultural marketing information access. The study is anchored on the technological acceptance model (TAM).

A descriptive cross-sectional research design was adopted with a sample size of 400 grape smallholder farmers. A structured questionnaire and focus group discussions (FGDs) were used to gather data. Descriptive, ordinal logistic regression and thematic approaches were used in data analysis.

The study confirmed grape smallholder farmers generally considered mobile phone technologies as an appropriate communication channel to stay informed about agricultural marketing information. It was found that reliable electricity supply, relevance, timeliness, perceived ease of use (PEOU) and perceived usefulness (PU) of mobile phone technologies influenced the level of agricultural marketing information access.

This research is limited to a selected number of grape smallholder farmers in Dodoma, Tanzania, and leaves out those without mobile phones. Also, the study was cross-sectional in nature, so it may not be necessarily capable of consistently providing critical and consistent information about the same population over a series of times.

This study contributes to the body of knowledge by integrating the use of mobile phone technologies to access marketing information in informing policy and decision-making processes to promote grape marketing.

The direction of causality between job satisfaction and job performance (known as the holy grail of industrial psychologists) is undetermined and related research findings in different organizational contexts are mixed. Based on the ample literature, mainly from Western countries, on the relationship between job satisfaction and job performance, a non-recursive bow pattern model was utilized to investigate the direct relationship between these two variables in an Asia–Pacific higher education system.

This study is quantitative in approach and survey in design. Additionally, to meet the statistical requirements of non-recursive bow pattern analysis, the authors added welfare as a theory-driven instrumental variable to introduce exogenous variability. Using the efficient partial least squares (PLSe2) estimator, the authors fitted the model to the data collected from 2008 academics affiliated with Malaysian public universities and polytechnics.

The results showed that while job satisfaction is considerably influenced by welfare, it is not a significant predictor of job performance directly. In addition, a meaningful positive correlation between the disturbance terms of job satisfaction and job performance was observed, suggesting the existence of other factors that could increase both job satisfaction and job performance. The findings' theoretical and practical implications are discussed, and a list of theory-driven evidenced-based policies in this regard is provided.

This is the first study to test a non-recursive bow pattern model and examine the holy grail of industrial psychology based on the PLSe2 methodology, as a parametric approach to partial least squares (PLS), in a higher education context. This study also provides higher education researchers with the advantages of the PLSe2 method, especially in causal-predictive modeling, in the context of applied higher education research.

The need for seeking alternate materials with increased performance in the field of composites revived this research, to prepare and evaluate the mechanical properties of e-glass and aloe vera fiber-reinforced with polyester and epoxy resin matrices.

The composites are prepared by hand layup method using E-glass and aloe vera fibers with length 5-6 mm. The resin used in the preparation of composites was epoxy and polyester. Fiber-reinforced composites were synthesized at 18:82 fiber–resin weight percentages. Samples prepared were tested to evaluate its mechanical and physical properties, such as tensile strength, flexural strength, impact strength, hardness and scanning electron microscope (SEM).

SEM analysis revealed the morphological features. E-glass fiber-reinforced epoxy composite exhibited better mechanical properties than other composite samples. The cross-linking density of monomers of the epoxy resin and addition of the short chopped E-glass fibers enhanced the properties of E-glass epoxy fiber-reinforced composite.

This research work enlists the properties of e-glass and aloe vera fiber-reinforced with polyester and epoxy resin matrices which has not been attempted so far.

Electronic learning (e‐learning) has gradually become an important part of university education. There is a trend among universities in Taiwan to offer more and more e‐learning courses. The effectiveness of teaching or learning in an e‐learning system can be quantified by multi‐criteria measures. The purpose of this study was to evaluate the effectiveness of teaching or learning in an e‐learning system measures in linguistic preferences.

A generalized quantitative evaluation model that considers both the interdependence among measures and the fuzziness of subjective perception is currently lacking in the literature. The results indicated that the fuzzy analytical network process is a simple, suitable, and effective method of identifying the primary measures that influence the effectiveness of e‐learning, specifically in the context of interdependent measures and varying linguistic preferences.

The most significant measures of e‐learning effectiveness were the quality of the e‐learning system and learner attractiveness. Enhanced usage of multimedia features can attract learner attention and may eventually increase learner attractiveness. Reducing the waiting time for learning materials to load may improve the quality of the system. Furthermore, the management should actively maintain and improve the responsiveness of instructors to learner inquiries.

The main contributions of this study are twofold. First, the evaluation can be considered as a complex‐dependence, hierarchical decision‐making problem. This study contains a review of the literature and identifies 21 criteria and five aspects to measure e‐learning system effectiveness. Second, this study integrates fuzzy set theory and the ANP to develop an evaluation model that prioritizes the relative weights of the proposed measures. The proposed method can be used to handle dependence within a set of measures and to construct a hierarchical structure.

The purpose of this study is to introduce new tools to develop a more precise and focused bibliometric analysis on the field of digitalization in healthcare management. Furthermore, this study aims to provide an overview of the existing resources in healthcare management and education and other developing interdisciplinary fields.

This work uses bibliometric analysis to conduct a comprehensive review to map the use of the unified theory of acceptance and use of technology (UTAUT) and the unified theory of acceptance and use of technology 2 (UTAUT2) research models in healthcare academic studies. Bibliometric studies are considered an important tool to evaluate research studies and to gain a comprehensive view of the state of the art.

Although UTAUT dates to 2003, our bibliometric analysis reveals that only since 2016 has the model, together with UTAUT2 (2012), had relevant application in the literature. Nonetheless, studies have shown that UTAUT and UTAUT2 are particularly suitable for understanding the reasons that underlie the adoption and non-adoption choices of eHealth services. Further, this study highlights the lack of a multidisciplinary approach in the implementation of eHealth services. Equally significant is the fact that many studies have focused on the acceptance and the adoption of eHealth services by end users, whereas very few have focused on the level of acceptance of healthcare professionals.

To the best of the authors’ knowledge, this is the first study to conduct a bibliometric analysis of technology acceptance and adoption by using advanced tools that were conceived specifically for this purpose. In addition, the examination was not limited to a certain era and aimed to give a worldwide overview of eHealth service acceptance and adoption.