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Social media has emerged as a pivotal marketing instrument and a platform that facilitates connections between consumers and businesses. In the intense market competition among peer airlines and high-speed rail services, the effective and efficient use of social media can provide a competitive edge for airlines in China. This paper constructs a partial least squares structural equation modelling (PLS-SEM) and examines the impact of the perceived ease of use of the social media platform, perceived usefulness of information, and marketing strategies on customer perceived value and purchase intention for Chinese airlines using multigroup analysis. The results suggest that social media marketing can positively influence on customers’ purchase intention, and perceived value plays a mediating role between social media marketing and customers’ purchase intention. Perceived usefulness of information is the most important factor contributing to the perceived value of airline products while marketing strategy is the most significant factor that can increase purchase intention. The research indicates a clear need to tailor marketing strategies for passengers based on factors such as gender, income, social media usage, and travel frequency.

The metaverse, an immersive virtual environment enabling users to engage with digital experiences, has the potential to revolutionize education. However, research pertaining to this area is still in its early stages. This study investigates the variables that influence the acceptance of educational metaverses and the intention to use them. It also presents an expanded model called the Unified Theory of Acceptance and Use of Metaverse Technology (UTAUMT) to provide guidance to educators and decision-makers. The study involved 253 Vietnamese teachers and students who had experience with metaverse, selected through purposive sampling. The UTAUMT provides a comprehensive framework that encompasses various factors, including metaverse performance expectancy (MPE), metaverse effort expectancy (MEE), metaverse social influence (MSI), metaverse hedonic motivation (MHM), metaverse price value (MPC), metaverse self-efficacy (MSE), and metaverse facilitating conditions (MFC). These factors were assessed using a self-administered questionnaire. The findings indicate that MEE, MSI, MFC, MSE, and MBI have a considerable impact on the educational metaverse MUB. The extended UTAUMT model makes a theoretical contribution by including metaverse-specific elements into the technology acceptance framework. The managerial implications focus on the integration of the metaverse, training of users, and providing support to enhance the adoption rate. This study explores the elements that contribute to the adoption of metaverse technology in education and contributes to the existing literature on the acceptance of metaverse technology.

In complementing our existing knowledge of blockchain technology adoption in the construction industry, this research investigated how the Technology Acceptance Model (TAM) applies to adopting blockchain technology among Saudi Arabian Construction companies. This study utilized cross-sectional data collection, causal research design, a quantitative research approach, and a simple random sampling technique to collect data from 248 Saudi Arabian construction companies. Partial least squares structural equation modelling (PLS-SEM) was utilized to analyze the data. The results showed that attitude toward adopting Blockchain (ATT) and perceived ease of use (PEU) are good predictors of behavioural intention to adopt Blockchain. The findings showed that when construction companies perceive the ease of use of Blockchain, they intend to adopt the technology. Attitude toward adopting Blockchain, directly and indirectly, influences behavioural intention to adopt the Technology. However, top management support only directly leads to intention once the companies perceive the usefulness of blockchain technology. This paper complements the existing literature on adopting Blockchain in the Saudi Arabian construction industry. The study provides insight into the influence of top management support, attitude toward adoption, and perceived ease of use in the blockchain adoption process.

Human activity has transformed natural land use patterns and exerted a significant impact on the mechanisms underlying ecosystem service (ES) provisioning. This has disrupted the equilibrium between human development and ecological protection and hasled to further degradation of desert ecosystems endemic to arid regions. In this study, we employed the three SSP-RCP scenarios provided by CMIP6 to represent varying rates of development within the Tarim River Basin (TRB) and modeled land use in 2050 based on the coupled system dynamics (SD) + patch-generating land use simulation (PLUS) + InVEST model. A dynamic simulation of the trade-off/synergy between key land use types and ESs in the ecologically vulnerable areas of the TRB was performed to identify the impacts of the individual effects of single factors and the scale effects of multiple factors on ESs. The results showed that (1) in the SSP126, SSP245, andSSP585 scenarios, the ratio of outflows to inflows of converted unused land gradually increased in the following periods:79.28 %, 79.42 %, 79.54 %in 2020–2030; 96.19 %, 91.62 %, 66.07 %in 2030–2040; and 93.76 %, 91.65 %, 60.96 %in 2040–2050, respectively.(2) A high water yield (WY) was observed in the highland mountains; high habitat quality (HQ) was observed in the highland mountains, along the Tarim River, and around cities; high carbon storage (CS) was observed in the highland mountains, along the Tarim River, and in urban areas. (3) Under the three scenarios, WY, HQ, and CS were mainly affected by environmental factors, with the highest single-factor tests represented by temperature (0.594; 0.595; 0.596), precipitation(0.582; 0.589; 0.590); NDVI(0.312; 0.295; 0.299), soil erosion(0.227; 0.221; 0.219); and NDVI(0.298; 0.282; 0.310), soil erosion(0.122; 0.125; 0.132), respectively. Additionally, the interaction factors with the highest explanatory power for WY, HQ, and CS were precipitation ∪ NDVI (0.73); elevation ∪ NDVI (0.37); and soil ∪ NDVI (0.31), respectively. Moreover, the human aggregation level exerted positive (0.117), negative (−0.173), and negative (−0.286) impacts on WY, HQ, and CS, respectively. The results show that the combination of GeoDetector and the partial least squares structural equation modeling (PLS-SEM) provides a complementary and creative framework for investigating the driving mechanisms of ecosystems.

The data presented in this article is based on a questionnaire survey regarding e-commerce and business digitalization of SMEs in Mexico answered by the CEOs of the companies. A valid sample of 4121 Mexican SMEs was collected covering many industries, such as primary sector, extractive industries, manufacturing industries, energy, water, recycling, construction, trade, services, and others. The data includes information about the implementation of e-commerce, business digitalization, operational efficiency, corporate performance, and other demographic indicators of the sampling firms. The link between e-commerce and corporate performance is still underexplored in SMEs, even more so between companies from Latin America, being Mexico a perfect example to explore how different SMEs adapt and thrive due to the rapid growth of their e-commerce and the diversity of their business sectors (Santos-Jaén et al., 2023 [2]). Data analysis was conducted using SPSS and Smart PLS. The data are useful as the data can be reproduced, reused and reanalyzed paying special attention to group-specific effects. This data article also opens up better research opportunities going forward through collaboration with other researchers.

Many educators across U.S. high schools face information quality and system quality challenges when using learning management systems (LMS). These challenges impact both the individual and organizational levels, affecting overall success. The purpose of this study aims to evaluate the effectiveness of e-learning tools using the IS-Impact model. This quantitative research assesses the importance and performance factors of educators' use of LMS tools. Using PLS-SEM and IPMA in SmartPLS 4, the effects of Information Quality, System Quality, Individual Impact, and Organizational Impact on the Overall Impact were analyzed based on data from 237 respondents through an online survey across U.S. high schools. Two conceptual models were developed and assessed based on the original IS-Impact Model. One model examined information quality and system quality as having direct effects on overall impact, while the other considered these variables to have indirect effects. Comparing Model-A and Model-B, path analysis, total effects, importance, and performance of latent variables were analyzed in detail against the Overall Impact dependent variable. Findings emphasize Information Quality and Organizational Impact as critical factors influencing the Overall Impact of successful LMS implementation. The IPMA results from this study offer actionable insights by identifying performance areas needing improvement based on importance. This study reveals a complex interplay of direct and indirect effects, highlighting the need for a holistic approach to enhance the impact of e-learning tools within educational institutions. This study further fosters a culture of innovation and competitive advantage by leveraging information systems to improve organizational processes and outcomes.

This study investigates customers' trust and behavioural intentions regarding the use of cybernetic payment network services in an emerging country, focusing on perceived quality, system quality, and perceived image. Data from 324 respondents in Bangladesh were collected via a self-administered Google survey form distributed through email, WhatsApp, and Messenger using purposive sampling. The SmartPLS-4 software was used to assess construct validity and hypothesized path coefficients. Results indicate that perceived quality, system quality, and image significantly influence perceived trust in cybernetic payment network services. Additionally, perceived trust and system quality positively impact behavioural intention to use these services. Furthermore, perceived trust mediates the relationship between behavioural intention and system quality, perceived quality, and image. The study underscores the importance for cybernetic payment network service providers to enhance perceived quality, system quality, and perceived image to foster trust and promote adoption. It highlights the pivotal role of trust in driving customers' intention to adopt these services, urging providers to prioritize efforts in building trust among users. This study contributes to the limited literature on the impact of perceived quality, system quality, and perceived image on customers' inclination to use cybernetic payment network services, offering valuable insights for bank managers and policymakers to formulate effective strategies for sustaining innovation and enhancing adoption rates.

The study aims to understand the antecedents of customer satisfaction that lead to high purchase intention, encompassing moderating role of system quality to achieve purchase intention. Theoretically, this research employs the technology acceptance model to examine the proposed relationship and complexity theory to employ fuzzy-set qualitative comparative analysis (fsQCA) as a robust complementary method to the partial least squares-structural equation model (PLS-SEM). The proposed conceptual model is measured using data gathered from online customers in Bangladesh's electronic market. A survey of 311 e-commerce customers, using PLS-SEM and fsQCA models, reveals that factors influencing customer satisfaction are strongly linked to achieving purchase intention. The findings from PLS-SEM show that perceived ease of use and perceived enjoyment are highly supported by purchase intention. Similarly, system quality influences purchase intention and acts as a moderator. In the fsQCA analysis, hedonic motivation and perceived enjoyment are necessary conditions to achieve a high purchase intention. The hybrid models add the methodological contribution by combining both symmetric and asymmetric relationships, thereby providing a holistic understanding of system quality as a moderating factor to achieve high purchase intention, especially in the context of the e-commerce market in Bangladesh. This research outlines implications for the theoretical and managerial perspectives to build a better relationship between factors of satisfaction and purchase intention and enable policymakers to contribute better managerial decisions.

The integration of Artificial Intelligence (AI) into education is a recent development, with chatbots emerging as a noteworthy addition to this transformative landscape. As online learning platforms rapidly advance, students need to adapt swiftly to excel in this dynamic environment. Consequently, understanding the acceptance of chatbots, particularly those employing Large Language Models (LLM) such as Chat Generative Pretrained Transformer (ChatGPT), Google Bard, and other interactive AI technologies, is of paramount importance. Investigating how students accept and view chatbots is essential to directing their incorporation into Industry 4.0 and enabling a smooth transition to Industry 5.0's customized and human-centered methodology. However, existing research on chatbots in education has overlooked key behavior-related aspects, such as Optimism, Innovativeness, Discomfort, Insecurity, Transparency, Ethics, Interaction, Engagement, and Accuracy, creating a significant literature gap. To address this gap, this study employs Partial Least Squares Structural Equation Modeling (PLS-SEM) to investigate the determinant of chatbots adoption in education among students, considering the Technology Readiness Index and Technology Acceptance Model. Utilizing a five-point Likert scale for data collection, we gathered a total of 185 responses, which were analyzed using R-Studio software. We established 12 hypotheses to achieve its objectives. The results showed that Optimism and Innovativeness are positively associated with Perceived Ease of Use and Perceived Usefulness. Conversely, Discomfort and Insecurity negatively impact Perceived Ease of Use, with only Insecurity negatively affecting Perceived Usefulness. Furthermore, Perceived Ease of Use, Perceived Usefulness, Interaction and Engagement, Accuracy, and Responsiveness all significantly contribute to the Intention to Use, whereas Transparency and Ethics have a negative impact on Intention to Use. Finally, Intention to Use mediates the relationships between Interaction, Engagement, Accuracy, Responsiveness, Transparency, Ethics, and Perception of Decision Making. These findings provide insights for future technology designers, elucidating critical user behavior factors influencing chatbots adoption and utilization in educational contexts.

The ability of Geographic Information System (GIS) to organize, analyze, visualize and integrate spatial data has been at the top of its primary uses among professional industries. However, considering the extensive adoption of Information System (IS) throughout history for government organizations’ or citizens' disaster response, the implementation of geographical elements is still minimal. Previous GIS models and framework studies, particularly in developing countries, were affected by pandemic pressure, competitiveness pressure, change management, and security factors. Thus, this study aims to develop a model for the successful adoption of GIS using the Technology Acceptance Model (TAM), and De Lone and Mc Lean Information Success Model and analyze the applicability of the existing factors to enhance the performance of Public Sector Organizations (PSOs). From the study, a new conceptual framework was proposed to examine the effects of factors on GIS adoption that impact performance among PSOs from the perspective of Saudi Arabia. Quantitative methods were used to collect data through a questionnaire distributed to 350 respondents from PSO, and only 272 were found to be valid. Partial Least Square Structural Equation Modeling (PLS-SEM) validated the GIS model. The finding revealed that system quality, service quality, change management, competitiveness pressure, perceived ease of use, perceived usefulness, and security factors significantly and positively affected GIS adoption. The study also showed that GIS adoption substantially affected PSO performance. The proposed model provides insight into how GIS adoption can eventually enhance performance among PSOs. In essence, the study contributes to the running of PSO and the decisions taken by policymakers.

The group product-harm crisis has much greater and longer negative impact, and its governance has become an important issue. To address this issue, this study proposed a new construct: industry governance. On the basis of clarifying the dimensions and measurements of industry governance, this study constructed a reflective–formative hierarchical model and collected data through a questionnaire. Utilizing convenience sampling, 329 valid samples at the University in Wuhan, China collected by survey were used to verify the hypotheses. With the help of Smart PLS 3.0, this study finds that the industry governance has a significant and positive impact on consumer's trust (enterprise trust, industry trust and government trust) after the group product-harm crisis. Industry governance plays an important role in the governance of group product-harm crisis. This study is the first time to explore the structure and measurement of industry governance, and verifies the impact of industry governance on group product-harm crisis, which enriches governance theory, and perfects product-harm crisis theory, providing a new direction and guidance for managers to better manage product-harm crisis.

The demand for Industrial Engineers across the globe is significantly increasing and professional certifications give advantage in the job marketplace. The Philippine Institute of Industrial Engineers (PIIE) – Industrial Engineering Certification Board facilitates the conferment of the Certified Industrial Engineer (CIE) in the Philippines. The goal of this study was to determine the factors affecting the intention IEs in the Philippines to take the CIE examination using an integration of the Perceived Value Theory and the Extended Theory of Planned Behavior. The research data were collected through an online distributed survey questionnaire to 690 graduating students and graduates from private and public universities across the Philippines. Employing a variance-based partial least squares structural equation modeling, the different significant variables and factors were assessed holistically. It was seen that attitude, perceived behavioral control, subjective norms, and understanding of the CIE examination have significant positive effects to intent to take the CIE examination and becoming a CIE. The perceived benefits and positive emotions brought by becoming a CIE significantly affects the attitude and behavior. This study also confirmed that the higher the perceived return on investment, the more the IEs will take the CIE examination. Moreover, demographic characteristics were identified to correlate and are significant among different variables. As a reflection, the findings and the integrated framework can be utilized in future studies related to development, career pathing, lifelong learning, and other related professional education.

Effectively incorporating technology into teaching and learning can be accomplished through the application of information and communication technology (ICT). Nonetheless, the extent to which ICT is employed in educational environments is heavily impacted by numerous factors. Teachers' ICT integration in China was investigated with the aim of identifying the specific factors that influence it. The research sample consists of 680 educators, and it highlights three primary elements that affect their adoption of ICT: attitudes, self-efficacy, and digital competence. Employing a partial least squares structural equation modeling (PLS-SEM) method, the results indicate that all three elements play a significant role in the effective integration of ICT by educators. The study also indicated the mediating effect of attitudes and digital competence. Furthermore, the research identified no substantial disparities in the factors based on sex or age, except for the correlation between self-efficacy and attitudes. By providing useful insights for the development of successful instructional designs that integrate ICT, this study contributed to the advancement and impact of educational technology.

Aim: Prior research has indicated a connection between CD4+ T cells and the development of anxiety, but the specific CD4+ T cell subsets linked to anxiety disorders remain uncertain. Our study seeks to investigate the relationship between distinct CD4+ T cell subsets and anxiety, as well as to explore whether CD4+ T cell subsets mediate the effect of chronic psychological stress on anxiety. Methods: 56 eligible matched participants were recruited in Peking Union Medical College Hospital. The diagnosis was made based on DSM-5 diagnostic criteria. The severity of anxiety and depression symptoms was assessed using the Hamilton Anxiety Rating Scale and Hamilton Depression Rating Scale, respectively. The Life Events Scale (LES) evaluated the chronic stress level. CD4+ T cell subsets were characterized using multiparametric flow cytometry. To assess the impact of CD4+ T cells on the effect of chronic psychological stress on anxiety, Partial Least Squares Structural Equation Modeling (PLS-SEM) analysis was employed. Results: We discovered fifteen notably distinct CD4+ T-cell subsets in anxiety disorder patients compared to healthy controls. Multiple linear regression analysis unveiled an association between anxiety severity and CD27+CD45RA− Th cells, CD27+CD28+ Tregs, and the total Life Events Scale (LES) score. The PLS-SEM analysis demonstrated that CD4+ T cell subsets and LES could explain 80.2% of the variance in anxiety. Furthermore, it was observed that CD27+CD28+ Th/Treg cells acted as inverse mediators of the effects of LES on anxiety (P = 0.031). Conclusions: Drug naïve anxiety disorder patients exhibited significant alterations in numerous CD4+ T-cell subsets. Specifically, the memory subset of CD27+CD45RA− Th cells and the naïve subset of CD27+CD28+ Treg cells were found to be independent factors associated with the severity of anxiety. Additionally, the CD27+CD28+ Th and Treg cell subsets played a significant mediating role in the influence of long-term psychological stress on anxiety.

Enforcement of rules to increase farmers' involvement in participatory irrigation management (PIM) has been ineffective given the non-exclusivity nature of surface irrigation. In this study, we investigated the interrelationship of the social capital's role in higher participation in PIM and the effects towards farmers' efficiency using the case of rice farmers in Northern Thailand. We found that higher intention to participate in PIM collective activities is largely driven by the water user's social capital endowments. Farmers' efficiency level is positively associated with PIM participation and the condition of the collective irrigation management. Our findings suggest the importance of complementing current government efforts with policy interventions focusing on strengthening water user groups' social capital, such as improving group cohesion and their capacity for networking in compensating for various impediments faced by farmers.

Consumer attitudes toward novel fresh herb cultivation methods, including urban farming, hydroponics, and robotic cultivation, were explored among 148 participants in the UK. Urban farming emerged as the preferred method, followed by hydroponics, while robotic cultivation was least favoured. The study tested two hypotheses regarding the influence of environmental concern on acceptance of parsley from the different methods, and the impact of food technology neophobia on acceptance of parsley from hydroponics and robotic cultivation. Consumer levels of environmental concern positively influenced their acceptance of parsley from urban farming, while food technology neophobia negatively impacted the consumer acceptance of hydroponic and robotic cultivation methods. The study underscores the perceived natural elements inherent in these methods. Urban farming seems to align well with consumers’ values of nature and sustainability. Tailored messaging highlighting the natural aspects of all these methods, and addressing concerns about the use of technology, may help to bridge the gap between innovation and consumer acceptance, contributing to the delicate balance between tradition and innovation in agricultural strategies. At the same time, however, the study's exploratory nature may limit the generalizability of the results. Future research could broaden the participant sample and explore additional psychological factors shaping attitudes toward novel agricultural techniques.

In the era of Industry 4.0 (I4.0), automation and data analysis have undergone significant advancements, greatly impacting production management and operations management. Technologies such as the Internet of Things (IoT), robotics, cloud computing (CC), and big data, have played a crucial role in shaping Logistics 4.0 (L4.0) and improving the efficiency of the manufacturing supply chain (SC), ultimately contributing to sustainability goals. The present research investigates the role of I4.0 technologies within the framework of the extended theory of planned behavior (ETPB). The research explores various variables including subjective norms, attitude, perceived behavior control, leading to word-of-mouth, and purchase intention. By modeling these variables, the study aims to understand the influence of I4.0 technologies on L4.0 to establish a sustainable manufacturing SC. A questionnaire was administered to gather input from small and medium-sized firms (SMEs) in the manufacturing industry. An empirical study along with partial least squares structural equation modeling (SEM), was conducted to analyze the data. The findings indicate that the use of I4.0 technology in L4.0 influences subjective norms, which subsequently influence attitudes and personal behavior control. This, in turn, leads to word-of-mouth and purchase intention. The results provide valuable insights for shippers and logistics service providers empowering them to enhance their performance and contribute to achieving sustainability objectives. Consequently, this study contributes to promoting sustainability in the manufacturing SC by stimulating the adoption of I4.0 technologies in L4.0.

Social media's significance in higher education has increased due to its capacity to enhance participation, communication, teamwork, and information sharing. Important notifications, updates, and reminders can be promptly received by all members of the university community, assuring that information is shared with everyone. The objective of this study is to develop a model for a Customer Relationship Management (CRM) system in higher education that is based on social media and intends to increase student satisfaction, loyalty, and profitability. It blends the idea of trust with Delone Mclean success model. Partial Least Squares-Structural Equation Modeling (PLS-SEM) was used to evaluate the data that was gathered from 606 Jordanian private university students via an online survey. The findings demonstrated that user satisfaction affects social media usage and that system quality, information quality, service quality, and trust must all be considered to attain user satisfaction. This study examines how to create a CRM system based on social media in Jordanian universities. The study makes significant contribution to the development criteria for evaluating social media-based CRM systems in higher education institutions, and its broad conceptual model cloud be expanded and tested in future studies. This study is the first to investigate the use of social media to develop a CRM system for Jordanian universities. This is a novel study, and the work significantly create a set of criteria for evaluating social media-driven CRM systems in higher education. The study's expansive the model may serve as the base for more research in this field.

Aside from statutory requirements, Small and Medium-Sized Enterprises (SMEs) hardly take into consideration reliable accounting systems. Therefore, poor and ineffective bookkeeping has contributed to the collapse of some SMEs. This paper examines the intervening role of owners' accounting skills in the relationship between bookkeeping practices and the performance of SMEs in the Ho Municipal Assembly of Ghana using a sample of 296 SMEs. In a structural equation modelling (SEM) framework, the Smart Partial Least Squares (Smart-PLS) software is employed to analyse the relationships between owners' accounting skills, bookkeeping practices, and the performance of SMEs. We find that bookkeeping practices and owners' accounting skills have significant positive effects on the performance of SMEs. Most importantly, we show the existence of a significant indirect relationship between bookkeeping practices and SME performance such that owners' accounting skills positively intervenes the relationship between bookkeeping practices and SME performance. Thus, in the presence of higher owners’ accounting skills, the relationship between bookkeeping and the performance of SMEs is strengthened further. In a typical emerging economy context, while appropriate regulatory bodies, such as the National Board for Small Scale Industries (NBSSI), in the Ghanaian context, and local revenue collection authorities could put forth measures like periodic compliance audits to ensure that registered SMEs are managed by skilled personnel, fostering them to meet basic requirements for keeping records and managing their accounts to improve their performance, it is worth acknowledging that the onus lies on SME managers to recognise the relevance of good recordkeeping and account management practices to ensure sustained business performance.

China has entered a period of synchronous development between digitalization and aging. Based on the data from the China Household Finance Survey (CHFS), the partial least squares structural equation model (PLS-SEM) and multi-group analysis were used to analyze the impact mechanism of digital capabilities and digital finance on the wealth of elderly households. The results indicate that digital capabilities and digital finance can improve the wealth level of households headed by the elderly through direct and indirect paths. The indirect effects of digital capabilities and digital finance on elderly household wealth are all exerted through the node of business and property income, and entrepreneurship/investment are mediating variables. Moreover, digital capabilities have a greater impact on the wealth of elderly households in the central and western China regions, while digital finance has a greater impact in the eastern China regions. In addition, there is no significant difference in the effect of digital capabilities on business and property income across regions, while digital finance has a larger effect in the eastern region. The above conclusions can provide theoretical and practical support for realizing active aging and common prosperity in different countries and regions.

The COVID-19 pandemic has resulted in behavioural changes in the way people consume food in Indonesia, because people tend to use online food delivery (OFD) services to order food after the pandemic. In line with this, application-based OFD service providers in Indonesia such as GoFood, GrabFood, ShopeeFood, and others are growing year after year, creating competition among OFD service providers. On the other hand, now that the COVID-19 pandemic condition has begun to improve, people may return to ordering food in the traditional manner, namely by visiting restaurants directly without using the OFD service application. As a result, it may jeopardize the stability of the OFD service business. As a result, the purpose of this study is to investigate the factors that influence the satisfaction and intent of OFD service users in Indonesia to continue using OFD services in the future. The Unified Theory of Acceptance and Use of Technology (UTAUT2), Expectancy Confirmation Model (ECM), online review, online rating, and online tracking were all combined to do structural equation modeling (SEM) using the PLS-SEM approach. Data were gathered using an online poll of 325 respondents who have used OFD services. According to the findings of the structural model analysis, effort expectancy, hedonic motivation, price-saving orientation, and confirmation all have a direct impact on the level of satisfaction of OFD service users. Meanwhile, performance expectancy, habit, online review, and satisfaction all influence the intention to continue using OFD services. The findings of this study can be used as a reference for OFD service providers as a service improvement strategy, as well as to expand the literature on consumer behaviour regarding OFD services and provide a foundation for future research.

Industrial symbiosis is being increasingly recognized as a valuable tool for promoting a more sustainable production process in agriculture. However, the primary motivation for implementing industrial symbiosis is economic viability. In the context of industrial symbiosis, by linking agriculture and food together, the study examines the impact of the use of vermicompost, derived from agricultural by-products, on spinach yield as well as on nutritional and biochemical soil aspects. Moreover, the economic feasibility for spinach farmers is also investigated. A field experiment with five treatments i) solarization ii) solarization and vermicompost iii) green manure and solarization iv) green manure, solarization, and vermicompost, and v) vermicompost has been realized in “Piana del Sele”, a rural area in Southern Italy. Collected data have been analysed through a Partial Least Square Structural Equation Modeling approach to assess the overall impact (direct and indirect effects) of vermicompost on both spinach yield and soil characteristics. Lastly, the economic profitability of using vermicompost is pointed out for spinach growers. The study findings show that the highest positive impact on yield occurs when vermicompost is combined with solarization (+15 %). Moreover, with regard to soil characteristics, the combination of vermicompost and solarization has a positive impact on nutrients, fungal biodiversity, and the biochemical quality of the soil. The economic profitability of using vermicompost in conjunction with solarization is guaranteed when the price of vermicompost is below € 0.84/kg. In light of these findings, some policy interventions can be implemented to enable industrial symbiosis as a viable tool for a circular economy in the agri-food sector. These include promoting the diffusion of biogas plants to valorize agricultural by-products and promoting the use of vermicompost in farms, by encouraging its purchase by farmers.

Science popularization is not only a prerequisite for national development, but also an effective means of enhancing citizens' personal quality. All sectors of society, represented by colleges and universities, bear the responsibility of promoting popular science. The integration of popular science and tourism in popular science tourism serves to advance both the field of popular science and the tourism industry simultaneously. The Guangzhou Higher Education Mega Center (HEMC) possesses abundant resources for science popularization and has the potential to develop popular science tourism, yet its current development in this area remains insufficient. This study utilizes Guangzhou HEMC as a case study and modifies the American Customer Satisfaction Index model by incorporating relevant questions pertaining to popular science tourism. A total of 280 valid questionnaires were collected through surveying, which were then analyzed to measure tourist satisfaction using the Tourist Satisfaction Index. The partial least squares structural equation model was employed for analysis, and on the basis of calculation results, the IPA map was constructed. The research revealed that tourists' satisfaction with popular science tourism at Guangzhou HEMC was suboptimal. Among the factors correlating to satisfaction, expectations, quality, and price are all important factors to consider when making a purchase decision; however, prioritizing expectations and quality can lead to greater satisfaction in the long run. Therefore, there is still ample room for improvement in the popular science tourism of HEMC Guangzhou. This can be achieved by intensifying publicity efforts, enhancing infrastructure, improving the quality and safety of catering services, strengthening the introduction and construction of popular science content, as well as appropriately reducing the price of popular science products and services.

The process of blue water used in crop cultivation has both natural and economic properties due to the intervention of irrigation facilities. This study revealed crop water use (CWU) from 1999 to 2018 in each province of China based on water footprint theory, and then established the blue water dependence index (BDI) to evaluate the dependence of agricultural cultivation on irrigation water from the perspective of water withdraw, and conducted a spatial and temporal pattern analysis.The influencing factors and structural pathways of BDI were explored using least squares structural equation modeling (PLS-SEM) at national and regional scales. Results indicated that the annual amount of water used for crop production in China exceeded 900.0 Gm³. The growth in CWU from 1999 to 2018 for cash crops and grain crops was 145.4 Gm³ and 74.4 Gm³, respectively.BDI of all crops was 0.281 over the study period in China, with grain crops being 2.6 times more dependent on blue water resources than cash crops. Xinjiang, with annual average BDI of 0.716, 0.805, and 0.620 for all, grain and cash crops, respectively, has the highest irrigation demand. The PLS-SEM results showed a significant causal relationship between the economy and BDI, with obvious regional differences in structural path analysis. Based on the analysis of agricultural water use, the regions can adjust the structure of crop cultivation, optimize the allocation of water and soil resources, expand the cultivation of fodder grains and promote steady economic growth, to achieve a ''win-win'' situation of ensuring food security and sustainable use of agricultural water resources.

This study aims to identify key determinants impacting technology innovation and organizational performance, investigating how technological complexity and co-creation can enhance technology innovation and organizational performance. It also examines the role of government influence in stimulating technology innovation. The article extends the technology-organization-environment (TOE) framework to build a research model that supports hypothesis development. A survey design method collected data from 323 members of management teams in the manufacturing industry in Vietnam. A structural equation modeling approach enabled estimating the forecasted multidynamic relationships. The findings indicate that technological complexity, government influence, and co-creation significantly enhance technology innovation. Moreover, technological complexity, technology innovation, and co-creation stimulate organizational performance. Specifically, the results show government influence and organizational performance indirectly affecting organizational performance. The findings provide valuable insights for both academia and practitioners, offering a deeper understanding of the complex dynamics between determinants. A manufacturing industry could effectively utilize this study to implement innovative practices in its specific context.

Emergency ecological water replenishment(EEWR) has become a major strategy for recovering degraded wetland ecosystems worldwide. However, the actual replenishment process mainly depended on the tradeoff and experience between the managers of Taoer River and Xianghai Wetland, which is very random and lacks theoretical guidance. Thus, there is urge to assessing water replenishment effect on wetland and help to optimize the process. With contrasting results as different ecosystem elements respond differently, the optimization of water replenishment process should be based on the improvement of the ecosystem as whole rather than its separate elements. However, the dynamic monitoring of biotic and abiotic factors to reveal the complex relationships underlying their response can be challenging. Based on 6 years’ series data of migratory birds and environmental factors of Xianghai Wetland, which started emergency ecological water replenishment since 2004 and occurred frequently since 2011, the broader ecosystem response to water replenishment was analyzed using a multiple paths regression model and proposed an optimized scheme. The results showed that bird diversity was positively influenced by the increase in water area and vegetation was induced by ecological water replenishment. While the response of bird abundance to water replenishment varied with time, adequate open water in March was found to have a positive relationship with abundance by promoting vegetation germination and the reproduction of benthic organisms. High flow levels in the wet season (June–August) can negatively affect waterbird abundance by rapidly increasing water levels and inhibiting plant respiration, which leads to the reduction in feeding efficiency of waterbirds and biomass accumulation. Therefore, the existing ecological water replenishment time (May–September) is not suitable for bird abundance and should be advanced to spring (March–April). Given the antagonistic effect of flow on diversity and abundance, the total replenished water should be approximately 100 million m3. To avoid the negative influence of high water in the wet season, the allocation of water could be 0.3, 0.3, 0.2, and 0.2 million m3 in April, May, September, and October, respectively. These results scientifically support wetland protection and management.

One manifestation of efforts to preserve culture and practice is the traditional fabrics. In Indonesia, the textile industry for conventional fabrics and garments is quite productive and varies in entire archipelagos. Meanwhile, Indonesian people, especially Generation Y and Z, think that traditional Indonesian fabrics only need to be worn for special occasions. It is necessary to increase their level of interest and accordingly analyze the influence factors, so that the policymaker can create a strategy to increase the level of interest in using and purchasing Indonesian traditional fabrics. This study aims to formulate plans to optimize the level of use and consumption of Indonesian traditional fabrics by Indonesian people in their daily lives, especially by Gen Y and Z, by developing a conceptual model using instruments from the theory of planned behaviour (TPB) and partial least squares (PLS) are used to analyze both models. Furthermore, the Ansoff matrix method is used for strategy formulation and development, and the analytical hierarchy process method is used for strategy validation and selection. Based on the analysis of the model of Gen Y, six hypotheses were accepted and two hypotheses were rejected. Meanwhile, in the study of the model of Gen Z, five hypotheses were accepted and three hypotheses were rejected. Based on the formulation and development of strategies using Ansoff matrix, six strategic recommendations for each model are proposed, and then three strategies for each model are selected as priorities or main focus based on the data processing results using the analytical hierarchy process.

Despite strong evidence of the critical role of mobile money technology in deepening financial inclusion, the impact of taxing mobile money transactions on digital and financial inclusion remains an unexplored area of research. By drawing on the Unified Theory of Acceptance and Use of Technology model, this research presents a rich insight into the determinants of mobile money adoption and the moderating effect of taxation (e-levy) on mobile money adoption. The purposive data sampling technique was employed to collect data from 287 mobile money users. The structural equation modeling – partial least square method was applied to test the hypotheses of this study. The findings show that performance expectancy, effort expectancy, social influence, and facilitating conditions significantly influence behavioral intention. Consequently, behavioral intention shows a significant relationship with the actual use of mobile money. Furthermore, regarding the moderating effect of taxation, the findings show that taxation negatively and significantly influences the actual use of mobile money. Finally, the implications of the results to tax policymakers (government) and mobile money operators have been discussed.

This study proposed a new model for understanding the relationship between social capital investment (SCI) and academic stress (AS). The effect of SCI over the psychological symptoms of AS (PsyS) through multiple and sequential mediation of bonding social capital (BSC), socio-emotional support (SES) and self-efficacy was analyzed through partial least squares structural equations modeling (PLS-SEM). Based on data from 150 university students, findings suggest that as students increase their level of SCI, their perception of greater SES and BSC grows; in turn, this raises the probability to perceive higher levels of self-efficacy; and higher levels of SES and self-efficacy decrease PsyS levels. New identified effects in the analyzed relationship provide the basis for future intervention and research.

The main objective of this research is to investigate the impact of three different information system (IS) quality constructs, namely system quality, service quality, and information quality, as well as internal control quality, on both IS use and user satisfaction. The ultimate goal is to enhance the success of the information system. To achieve this goal, a quantitative approach using a survey questionnaire was employed to collect data from 111 respondents who are familiar with AIS use. The study utilized the Smart PLS-SEM to analyze the collected data and test the hypotheses. Additionally, the study proposed a theoretical model based on Delone and McLean's Information System (D&M IS) Success Model to support the findings. The results of the PLS-SEM analysis revealed that the paths leading from system quality to AIS utilization and information quality to AIS user satisfaction were not significant through direct correlations. However, all other links involving the IS success model were found to be significant according to the study outcomes. This research fills the gap in the limited theoretical understanding of AIS use and impact in Jordan and provides valuable contributions to existing IS literature, particularly in terms of identifying the determinants shaping the net benefits derived from AIS. The proposed model was validated in Jordanian companies implementing AIS, and the study can serve as a guide to underscore the importance of AIS. Finally, the study highlights some implications, acknowledges limitations, and presents prospects for subsequent research endeavors.

This study explores the role of the preventive quality of innovations on their adoption intention. The preventive quality of innovations is a distinctive feature of innovations that is directed towards avoiding a future, possibly harmful event. Empirically grounded in third-party ownership of photovoltaic systems in Finland, this study examines data collected from an online survey measuring respondent intention to adopt. A series of hypotheses theoretically grounded in the Diffusion of Innovations theory and the preventive quality of innovations were tested through Partial Least Squares Structural Equation Modeling with SmartPLS4. Findings for the overall sample reveal that the preventive quality and the relative advantage of innovations influenced adoption intention positively. Findings highlight the preventive quality of innovations as a construct that acts as the greatest contributor to the dependent variable.

This study aims to investigate the factors influencing the usage intentions of metaverse technology in digital library services within higher learning institutions, using the unified system information theory. To achieve this, an online survey was conducted among university staff and students, utilizing a link-scale measurement. Various factors affecting the usage intention of metaverse technology in library services were computed through transformation models such as UTAUT, DM, ISS, and TTF. Subsequently, the model parameters were empirically tested using partial least squares structural equation modeling (PLS-SEM) to identify the significant factors influencing the usage intention of metaverse technology. The results of the study reveal that users' intentions to use metaverse technology in digital library systems are influenced by perceptions of system use, perceived interaction, perceived usefulness, and perceived ease of use. Notably, these influences vary depending on the user's intended task. These findings provide valuable insights into the factors that affect the adoption and usage intentions of metaverse technology in the context of digital library services in higher learning institutions. This research contributes to enhancing understanding and guiding future strategies for leveraging metaverse technology effectively in educational environments.

Businesses operate in an increasingly dynamic environment requiring that they strike a delicate, healthy, and equitable balance among the interests of their numerous stakeholders. This study examined how employee orientation and shareholder orientation influence supply chain orientation and how employee orientation, shareholder orientation, and supply chain orientation influence firm performance. The study used a sample of 265 respondents and applied both linear and triangular data analysis techniques in Partial-Least Squares Structural Equation Modelling (PLS-SEM) and Necessary Condition Analysis (NCA) to examine how employee orientation, shareholder orientation, and supply chain orientation influence the performance of oil marketing companies (OMCs) in Ghana. The PLS-SEM results revealed that employee orientation and shareholder orientation are significant predictors of supply chain orientation. The NCA results revealed that employee orientation is the most important for supply chain orientation. Also, from the PLS-SEM results, employee orientation and supply chain orientation predict firm performance, but shareholder orientation does not. However, the NCA results suggest that all three orientations are necessary for firm performance and highlight supply chain orientation as the most important for firm performance. This study is the first to examine how employee orientation and shareholder orientation influence supply chain orientation, besides how the three orientations influence firm performance from both sufficiency and necessity theory perspectives. The study also uncovers supply chain orientation as an underlying process through which employee and shareholder orientation enhances firm performance.

After the COVID-19 pandemic, the use of virtual platforms, social networks and online applications has been totally modified by returning to face-to-face systems. The mandatory use of these tools in the period of social distancing has led to their extensive development. This paper analyzes the effects of the use of ICTs in a purely face-to-face environment. Therefore, it analyzes the factors that affect student satisfaction and effectiveness in marketing learning through the use of digital tools and online applications in face-to-face classes, and this analysis is from a dual perspective of user and learning dissatisfaction. Using a learner-centered approach in university classes, the use of the digital platform Blackboard, the digital tool YouTube and the social network TikTok in university marketing teaching is analyzed. The study is carried out on a sample of 327 university students of different levels. The analysis is performed through a mixed methodology using a symmetric (PLS-SEM) and non-symmetric (fsQCA) approach, allowing a better generalization of the results. In the measurement of effectiveness, both user assessment and student learning assessment are significative, the two being affected in a similar way. However, they are not related to each other, acting independently. Attitude is the construct that has the greatest impact on both types of satisfaction. Perceived enjoyment also exerts a notable influence, especially on learning satisfaction. The study presents one of the first post-pandemic approaches to the analysis of the effectiveness of technological tools (ICT tools) in the face-to-face setting of university marketing classes.

This data article focuses on a complex path model to explain and predict the relationships between dimensions of corporate reputation, relational trust as well as customer satisfaction and loyalty. The sample was collected in Germany in 2020 with German bank customers above the age of 18 via an official market research institute located in Cologne, Germany (Respondi). The German bank customer data were collected using an online survey that was programmed using the software SurveyMonkey. The subsample described in this data article comprises 675 valid responses and the data analysis was performed applying the SmartPLS 3 software.

This data article is based on the International Social Survey Programme (ISSP) Environment III Dataset and linked to a publication in Ecological Economics, in which we developed a model for explaining and predicting sustainable consumption behavior of Europeans using data of nine participating countries. In our study, we find that sustainable consumption behavior can be associated with environmental concern, which is influenced by increased levels of environmental knowledge and environmental risk perception. In this companion data article, we describe the usefulness, value, and relevance of the open ISSP dataset and take our linked article as an example. The data are publicly available via the GESIS-website (gesis.org). The dataset consists of individual-based interviews on the respondents’ perceptions regarding a variety of social matters, such as the environment, which we argue is especially suitable for PLS-SEM applications (for example, to conduct cross-sectional analyses).

This perspective article on using partial least squares structural equation modelling (PLS-SEM) is intended as a guide for authors who wish to publish datasets that can be analysed with this method as stand-alone data articles. Stand-alone data articles are different from supporting data articles in that they are not linked to a full research article published in another journal. Nevertheless, authors of stand-alone data articles will be required to clearly demonstrate and justify the usefulness of their dataset. This perspective article offers actionable recommendations regarding the conceptualisation phase, the types of data suitable for PLS-SEM and quality criteria to report, which are generally applicable to studies using PLS-SEM. We also present adjusted versions of the HTMT metric for discriminant validity testing that broaden its applicability. Further, we highlight the benefit of linking data articles to already published research papers that employ the PLS-SEM method.

Corporate reputation is crucial for maintaining and enhancing a company's competitiveness in the marketplace. To actively manage this important intangible asset, which significantly contributes to a company's value, managers need to understand the relationship between reputation and its antecedents and consequences. The dataset presented in this article stems from a conceptual replication of a seminal model of corporate reputation, its antecedents and effects on customer satisfaction and loyalty. Potential mediators and moderators in these relationships allow us to extend the original model in order to clarify the mechanism through which corporate reputation impacts satisfaction and loyalty. We document some of the model's main effects using partial least squares structural equation modeling (PLS-SEM).

A conceptual model on predicting consumers’ likelihood of buying plant-based drinkable snacks through food choice motives and consumers’ perceived health-related value of drinkable snacks was developed and tested with a total of 3078 consumers from the Netherlands, Germany, and France through partial least squares structural equation modeling (PLS-SEM). In addition, the mediating role of perceived health-related value between the food choice motives and the likelihood of buying was evaluated. The results show that perceived health-related value positively predicts the likelihood of buying plant-based drinkable snacks. In turn, perceived health-related value in drinkable snacks is positively associated with the food choice motives of healthiness, naturalness, and 'free from', while such association does not hold with the motives to choose environmentally sustainable or traditional foods. Due to the identified mediating effects of perceived health-related value with certain food choice motives, it is noted that the evaluation of the product's health-related value might be an essential step between the corresponding general motives and intentions to buy plant-based drinkable snacks. Implications of the results are discussed in light of research and the food industry.

Although extant literature has thoroughly investigated the incorporation of cloud computing services, examining their influence on sustainable performance, particularly at the organizational level, is insufficient. Consequently, the present research aims to assess the factors that impact the integration of cloud computing within small and medium-sized enterprises (SMEs) and its subsequent effects on environmental, financial, and social performance. The data were collected from 415 SMEs and were analyzed using a hybrid SEM-ANN approach. PLS-SEM results indicate that relative advantage, complexity, compatibility, top management support, cost reduction, and government support significantly affect cloud computing integration. This study also empirically demonstrated that SMEs could improve their financial, environmental, and social performance by integrating cloud computing services. ANN results show that complexity, with a normalized importance (NI) of 89.14%, is ranked the first among other factors affecting cloud computing integration in SMEs. This is followed by cost reduction (NI = 82.67%), government support (NI = 73.37%), compatibility (NI = 70.02%), top management support (NI = 52.43%), and relative advantage (NI = 48.72%). Theoretically, this study goes beyond examining the determinants affecting cloud computing integration by examining their impact on SMEs’ environmental, financial, and social performance in a comprehensive manner. The study also provides several practical implications for policymakers, SME managers, and cloud computing service providers.

Structural equation modelling (SEM) is a statistical technique used in the field of Information Systems amongst others. The technique has been paid attention thanks to its flexibility and predictive power. However, there is a paucity of guidelines in the application of the technique in the field of Behavioural Information Security. Hence, this paper aims to provide a comprehensive guide of using PLS-SEM in disclosure and privacy studies on Social Network Sites (SNSs). Data has been gathered using papers (n=21) published between 2006 and 2022 from scholarly databases such as Google Scholar, Association for Information Systems eLibrary (AISeL), IEEE Xplore and Science Direct. The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA 2020) was used to analyse and synthesize the status of the field. Our systematic review covers data characteristics, reasons for using PLS-SEM, the evaluation of measurement models, the evaluation of the structural model and reporting best practices. The review proposed guidelines for the use of PLS-SEM in the discipline of Behavioural Information Security with a focus on disclosure and privacy on SNSs studies and other fields as well.

Background: This work aims to study the levels of stress among students using e-learning platforms during the COVID-19 pandemic in higher education institutions. The major factors of higher-level stress among the student community focused on this study are: Changes in academic environment, family, social, personal, health and cognitive. Objective: the objective of this research the Partial Least Squares Structural Equation Modelling (PLS-SEM) procedure was used to explore the relationship and its impact on various levels of stress. Results: Data were collected by using a total of 1,000 email IDs of students that were made available by teachers from 12 Indian higher education institutions where they were enrolled and by using a random number method. With this procedure, a total of 800 email IDs were selected. The results drawn from this research are that students experienced more stress due to sudden changes in the academic environment, family, and personal factors. The stress levels of cognitive and social were found to be equally distributed among higher education students, but less than academic environment, family and personal. This research intends to fill the gap of short-term individual psychological changes that occur after the outbreak. Conclusion: Policy-makers can take note of the current study’s observations in continuing their fight against COVID-19 pandemic by improving the stability for student risk groups.

Brand loyalty is one of the main objectives of marketing, due to its impact on the sustainability of organisations; however, the explanation of how this type of loyalty is built in the sports industry is complex, due to the way it is organised. Traditionally, brand loyalty in this industry has been explained by satisfaction, service quality, commitment and trust, thus other variables that have been analysed from the marketing field have not been included in the models developed for the sports industry. The aim of this article was to explore the relationship between symbolic consumption as a non-traditional predictor of brand loyalty in the sports industry, more specifically in the football club segment. For this purpose, a quantitative cross-sectional study was defined, with a non-probabilistic sampling. To test the proposed relationship, modelling by means of partial least squares structural equations was chosen. The results showed that symbolic consumption is positively related to brand loyalty in the sports industry in the football club segment, with a large effect size. This study becomes a starting point for scholars who wish to further explore the relationship between symbolic consumption and brand loyalty in the context of sport. Likewise, for marketing professionals in the sports industry, it suggests the importance of symbolic consumption for the design of strategies that enable the creation of brand loyalty in consumers in the case of football clubs. In this sense, marketing professionals should seek to create advertising and promotional campaigns that appeal to strengthen the relationship of the sports consumer with their social groups based on the actual and ideal self-concept, as lifestyle.

The purpose of this research is to empirically analyze how regional specialization influence innovation in enterprises, as well as the mediation effect of absorptive capacity and cognitive social capital, as knowledge diffusion mechanisms. A questionnaire was developed and distributed, obtaining a sample of 197 energy firms in Spain. For the assessment of this data, the PLS-SEM technique, a multivariate analytical approach, has been used. The results show a positive and significant direct effect between the degree of regional specialization and the innovative performance of firms. In addition, the cognitive social capital and absorptive capacity variables show a positive and significant mediation effect in the relationship proposed, as well as between them, thus constructing a double mediation and proving to be relevant mechanisms for knowledge diffusion. Then, it is concluded that cognitive and geographical proximity matters, since enable firms to obtain resources for knowledge upgrading and innovation. Thus, it is crucial for firms to develop their capacity to absorb new external knowledge, as has been evidenced as a key factor to leverage the opportunities of the context in which firms are located. This paper has important implications for the long-standing complex debates about whether regions should develop, primarily whether they should do so through specialization or diversification.

This paper examines the determinants that drive ChatGPT use in learning among Indonesian Higher Education Institutions (HEIs) students. A proposed model based on the unified theory of acceptance and use of technology model-2 (UTAUT2) was used in the context of the study. A pilot study was done prior to the main data collection to examine the reliability of the instrument. For the structural model assessment, 1117 responses were analyzed through Partial Least Square Structural Equation Modeling (PLS-SEM) and Importance-Performance Analysis (IPMA). Most hypotheses are confirmed by the significant results reported through the PLS-SEM. The strongest determinant of Behavioral Intention (BI) to use ChatGPT in learning was Facilitating Conditions (FC). ChatGPT use (GPTU) was most significantly predicted by BI. However, one hypothesis was not supported; the insignificant role of Effort Expectancy (EE) on BI was revealed. Through IPMA, FC had the most significant importance for BI, while BI was the most important determinant for GPTU. Besides, BI obtains the highest performance in the IPMA procedure. This study addresses a UTAUT model by evaluating ChatGPT acceptance and use among HEIs students in Indonesia. Findings could facilitate policymakers with insights into the determinants and initiate effective and efficient policies to improve artificial intelligence use in education, specifically ChatGPT.

The utilisation of Artificial Intelligence (AI) in higher education has been a contemporary issue attracting varied perspectives. However, the nuances among the antecedents of AI usage among postgraduate students and the acquisition of 21st-century employability skills are under-researched. This study sought to fill the chasm by adopting a concurrent integrated mixed method to collect data using a questionnaire with closed-ended and open-ended items from 294 postgraduate students in Ghana. Descriptive statistics and partial least squares structural equation modelling (PLS-SEM) techniques were employed for the quantitative data analyses while thematic pattern matching was used to analyse the qualitative data gathered. Results from the descriptive analysis revealed that the most prevalent AI platforms used by postgraduate students were ChartGPT and Quillbot. The two most important uses of such AI tools were just used for learning in general; and searching for literature. The PLS-SEM paths modelling showed that antecedents of postgraduate students' AI usage were benefits, challenges and platform availability. Finally, both AI usage and AI challenges were significant predictors of postgraduate students’ acquisition of 21stcentury employability skills. However, the relationship between AI challenges and the acquisition of 21st-century employability skills was fully mediated by AI usage. Based on the results, recommendations were made for policy and practice of AI usage in higher education.

While the healthcare facilities for the people is questionable in Bangladesh, Rohingya refugees is a burning issue for both Bangladesh and global community. Integrating Rohingya refugees into the framework of mHealth could be beneficial for both Bangladesh and Rohingya refugees in general, and in specific situation like COVID-19 outbreak. However, no research has been found on what motivates Rohingya refugees to accept mHealth in Bangladesh. Drawing on the UTAUT2 model, this study investigates the predictors of acceptance of mHealth services technologies among Rohingya refugees. The study also seeks to clarify the roles of mHealth developers, the Bangladesh government, and non-governmental organizations working with the 1.1 million Rohingya refugees in Bangladesh. Quantitative data were collected from refugee camps with the permission of the Refugee Relief and Repatriation Commissioner (RRRC). The data were analyzed in two stages using a mixed approach that combines PLS-SEM and Artificial Neural Network (ANN). This study revealed that Effort expectancy (EE, with t = 5.629, β = 0.313) and facilitating conditions (FC with t = 4.442, β = 0.269) in PLS-SEM, and FC (with 100 percent importance) and Health consciousness (HC, with 94.88 percent importance) in ANN analysis were found to be the most substantial predictors of mHealth adoption. The study also revealed that EE and FC are more important for low education group, while PE and Situational Constraint (SC) are more important for the high education group of refugees. In addition to providing insights for mHealth developers, this study particularly focuses on the role of government institutions and non-governmental social workers in working with the subjects to increase FC and HC among Rohingya refugees and bring them under mHealth services.

The COVID-19 pandemic has significantly impacted on the working system, shifting working from office (WFO) into working from home (WFH) practice that requires employees to be skillful in using technology to support their work activities. However, this condition can affect job performance. This study aims to analyze the impact of ICT anxiety and smartphone addiction on job performance of all lecturers at NIPA School of Administration (Jakarta, Bandung, and Makassar). This study applied a quantitative method with a total sampling technique and conducted a survey on 135 respondents using an online questionnaire. Furthermore, this study employed job demands and resources theory as well as PLS-SEM to analyze five variables (ICT anxiety, smartphone addiction, interruption, job efficacy, and job performance) and to test seven hypotheses. The findings show that there is a positive relationship between ICT anxiety and interruption while interruption has negative influences on job efficacy and job performance. Therefore, this study recommends the facilitation of knowledge sharing related to ICT competence or literacy. In addition, NIPA should improve the security guarantees of the intellectual rights of the lecturers in relation to the choice of technology and integrate the demands of ICT needs with administrative-technical procedures.