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This study posits that the use of artificial intelligence (AI) enables supply chains (SCs) to dynamically react to volatile environments, and alleviate potentially costly decision-makings for small-medium enterprises (SMEs). Building on a resource-based view, this work examines the impact of AI on SC risk management for SMEs. A structural model comprising of AI-risk management capabilities, SC re-engineering capabilities and supply chain agility (SCA) was developed and tested based on data collected from executives, managers and senior managers of SMEs The main methodological approach used in this study is partial least squares-based structural equation modelling (PLS-SEM) and artificial neural network (ANN). The results identified the use of AI for risk management influences SC re-engineering capabilities and agility. Re-engineering capabilities further affect and mediate agility. PLS-SEM and ANN were compared and the results revealed consistency for models A and B. Current levels of demand uncertainties in the SC challenges managers in making complex trade-off decisions that require huge management resources in very limited time. With AI, it is possible to model various scenarios to answer crucial questions that archaic infrastructures are not able to. This study combines a multi-construct agility concept and identified non-linear relationships in the model. [ABSTRACT FROM AUTHOR]

Negative birth experiences are common. It is yet unclear which women may be most at risk already before pregnancy. Childhood trauma and non-autonoumous/unresolved attachment state of mind may affect how women experience giving birth. This study used longitudinal data to test childhood trauma and attachment state of mind as predictors of birth experience in at-risk sample of primipara women (N = 193). The Adverse Childhood Experiences questionnaire and the Adult Attachment interview were administered during pregnancy, and women reported about their birth experience three months postpartum. Partial Least Square Structural Equation Modelling was applied to answer the research questions. Childhood physical neglect and parental substance abuse were predictive of a more negative birth experience, while attachment state of mind was not associated with how women experienced giving birth. Cross-validation suggests that these findings may be considered externally valid. Further research using validated measures on birth experience are needed. [ABSTRACT FROM AUTHOR]

Our natural environment is suffering the consequences of the current highly dynamic and competitive social and economic conditions that force people and firms to mainly focus on economic outputs rather than in reducing their impact on the environment. In this context, environmentally aware leaders can play a key role in driving the development and implementation of sustainable practices within organizations, as well as the development an adequate organizational culture that promotes the engagement of its members. The objective of this research is to empirically evidence the influence of green transformational leadership on green performance, as well as the mediating role of green organizational culture and green engagement in this relationship. The results provide empirical evidence on the positive influence of green transformational leadership on green performance, as well as about the mediating variables raised, which has interesting practical, political and theoretical implications, related to the strategic management of firms, the promotion of environmental sustainability in corporate governance and industry standards, and the broader understanding of sustainable leadership in the academic sphere. Thus, this study provides a roadmap to embrace a leadership model that prioritizes environmental sustainability, advocating for a collective journey toward a sustainable future where leadership, culture, and commitment coalesce into a formidable force for environmental sustainability. It is concluded that there is a need for a paradigm shift where leadership integrates sustainability into the ethos of organizational culture. [ABSTRACT FROM AUTHOR]

This study investigates the factors influencing intentions to adopt circular business models (CBMs) among businesses in Vietnam, a manufacturing hub in the region. To conduct the investigation, we developed a conceptual framework based on the behavioral theory of the firm and the resource‐based view, categorizing factors into two dimensions: financial and non‐financial. Through empirical analysis involving a survey of 291 businesses and employing partial least squares structural equation modeling (PLS‐SEM), we found that financial factors, including capital availability, expected economic benefits, and cost management competence, exert a stronger influence on the adoption of CBMs compared to non‐financial factors, such as stakeholder pressure, technology competence, and innovation competence. Furthermore, while several businesses are actively engaging in activities related to CBMs, managerial commitment towards full CBM adoption remains a prospective goal rather than an immediately actionable present reality. This study contributes in both theoretical and practical terms by addressing a critical research gap and quantifying the impact of financial and non‐financial factors on CBM adoption. Our findings offer valuable insights for businesses and policymakers, facilitating the promotion of circular economy and sustainable development. [ABSTRACT FROM AUTHOR]

In economically vulnerable situations such as the pandemic, private‐label products generate bigger appeal. The behavior of online private‐label consumers has remained understudied thus far, despite several studies suggesting that different channels lead to different consumer behaviors. This study aims to develop and test a theoretical model that elucidates the factors influencing the online purchase intention of private‐label products in a post‐pandemic scenario. We assess the role of attitude in the relationship between value consciousness, convenience, perceived quality, awareness, price consciousness, private‐label image, retailer reputation, and functional risk, in relation to purchase intention. The study is based on a sample of 318 respondents and employs variance‐based partial least squares structural equation modeling (PLS‐SEM) for data analysis using Smart PLS 3. This study is one of the first to delve into post‐pandemic research on online private‐label products during an economic downturn. This study explores the purchase intention toward online private‐label products by drawing on the theory of planned behavior, attribution theory, and cue utilization theory. Our results reveal that retailer reputation influences private‐label image, which affects purchase intention. Additionally, perceived quality, private‐label image, and attitude positively influence the purchase intention of private‐label products. Retailer reputation also affects private‐label image and value consciousness. Furthermore, convenience has a positive effect on attitudes toward the online purchase of private labels. Interestingly, price consciousness did not affect the purchase intention of online private labels. These findings have significant implications for private‐label online retailers and policymakers. This article extends the current private‐label theory and holds promise for future application in an omnichannel private‐label context. [ABSTRACT FROM AUTHOR]

This study explores the mechanism that contributes to travel intention in the field of virtual tourism. The overall research method is based on the "Stimulus-Organism-Response" theory. In the research model, the effects of content quality, system quality, and interaction quality in virtual tourism on tourism experience and travel intention are explored, as well as the role of virtual attachment and travel intention. A total of 390 respondents were invited to participate in a virtual tourism experience, and provide feedback through a questionnaire. SmartPLS 3.3.2 was used to validate the causal model, and most of the study hypotheses were supported. The findings show that virtual tourism significantly promotes travel intention. Specifically, content quality, system quality, and interaction quality positively affect tourists' travel intention through the complementary mediations of tourism experience and virtual attachment; and system quality even directly promotes travel intention. However, tourism experience does not affect virtual attachment. The present study extends prior studies on virtual tourism with SOR as a general model for field tourism experience research, while demonstrating the effectiveness of virtual tourism in promoting tourists' travel intention. The results are useful in assisting governments with developing relevant policies and services, as well as helping tourism companies understand virtual tourism as an enhancement for tourist travel intention, thus contributing to the recovery of the tourism industry in the post-COVID-19 era. [ABSTRACT FROM AUTHOR]

Purpose: The prime purpose of the study is to analyse the effect of fintech adoption on the financial well-being of persons with disabilities (PWDs), considering the intervening role of financial behaviour, financial access and financial knowledge. Design/methodology/approach: A self-administered survey schedule collected primary data on fintech adoption and financial well-being among 205 PWD, through snowball sampling from January to May 2023. Researchers used exploratory factor analysis to identify reliable factors and PLS-SEM for testing mediation and research hypotheses. Findings: The study's outcome found that fintech adoption does not directly impact the financial well-being of PWDs. Instead, the impact on financial well-being is explained by mediating factors like financial access, financial knowledge and financial behaviour. Financial access is the most significant among these mediating factors. Research limitations/implications: The study demonstrates the significance of mediating factors in comprehending the influence of fintech adoption on financial well-being. These results underpin existing literature on determinants of financial well-being. Practical implications: Findings evidenced that developing disabled-friendly fintech tools can enhance financial access, reduce inequality and improve the financial well-being of PWDs, which would be helpful for public policymakers. Originality/value: There has been no comprehensive study conducted on this topic, particularly among PWDs. In the current study, an effort is being made to examine the relative effects of fintech adoption on financial well-being directly and indirectly through mediating variables. Peer review: The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-08-2023-0596 [ABSTRACT FROM AUTHOR]

Factors influencing Chinese graduate students’ adoption of AI-generated content (AIGC) tools are examined through partial least squares structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA). The developed AIGCT-SI model incorporates key elements such as information accuracy, trust, and privacy concerns. PLS-SEM results indicate that performance expectancy, effort expectancy, facilitating conditions, and habit significantly impact students’ intentions, with trust acting as a key mediator, particularly for privacy concerns and social influence. FsQCA reveals seven configurations, demonstrating how combinations of performance expectancy, effort expectancy, and facilitating conditions drive adoption. A bidirectional relationship between privacy concerns and trust is observed, with trust mitigating privacy risks in several configurations. This integrative approach highlights the complex dynamics of AIGC tool adoption and provides strategic insights for their effective use in Chinese graduate education. As the findings are based on the Chinese context, further exploration in other educational settings is encouraged to validate their broader applicability. [ABSTRACT FROM AUTHOR]

This study investigates the adoption of indoor air quality (IAQ) management technologies in Germany and Portugal, focusing on the common and differentiating factors influencing individuals' motivations and the perceived health impacts of these technologies. Utilizing a model based on the protection motivation theory, we surveyed 800 participants (400 from each country) to understand how their perceptions of the risks associated with poor IAQ and their evaluations of the effectiveness and costs of technologies like air purifiers and sensors drive the adoption intention of these technologies and well‐being of individuals. To estimate the complex relationships in our model, we employed partial least squares structural equation modeling (PLS‐SEM). Our model explains nearly 50% of the variance in well‐being for both countries. The results revealed significant differences in the factors driving technology adoption: Germans are primarily motivated by individual efficacy and personal responsibility with the people close to them. Regarding the similarities, participants from both countries value the technology's effectiveness in improving IAQ and do not see being vulnerable to health issues derived from poor IAQ as a motivator. These insights highlight the need for strategies that are tailored to specific cultural and national contexts to promote the adoption of IAQ management technologies, aiming to enhance IAQ and public health outcomes. [ABSTRACT FROM AUTHOR]

Despite student burnout has attracted the attention of researchers and practitioners in education and psychology, little is known about the factors that contribute to it in blended contexts. This research aims to formulate and verify a predictive model elucidating how social support and self-regulated learning predict student burnout within blended learning contexts. Utilizing data collected from a sample of 303 students, a complementary method that combines partial least squares structural equation modeling (PLS-SEM) with machine learning (ML) algorithms was implemented. The favorable impact of perceived social support and self-regulated learning in mitigating burnout was demonstrated by the PLS results. Additionally, it was discovered that self-regulated learning fully mediates the correlation between offline social support students received and learning burnout. Furthermore, the employed ML algorithms achieved a prediction accuracy rate exceeding 70% in the majority of cases. Employing a complementary analytical method is believed to offer a substantial contribution to the current body of research on learning burnout generally and blended learning in particular. [ABSTRACT FROM AUTHOR]

Arctic city mayors influence municipal sustainability outcomes, navigating decisions on waste management, social service funding, and economic development. How do mayors make these decisions and to what extent do they integrate sustainability indicator data? Interviews with the mayors of Fairbanks, Alaska, Yellowknife, Canada, and Luleå, Sweden, revealed indicators are used on a case-by-case basis to track trends but lack systematic integration into decision-making. Constituent concerns drive agendas rather than indicator trends. Based on International Organization for Standardization (ISO) guidelines, 128 indicators grouped into 19 sustainability themes were compiled from 2000 to 2019 for the study cities. Partial Least Squares Structural Equation Modeling (PLS-SEM) was applied to examine the utility of ISO indicators as a guiding factor for sustainability trend tracking, identifying key themes for each city. Results show that indicator trends are too inconsistent and interconnected to be useful as an independent form of guidance for mayors. For Arctic municipalities, sustainability indicator datasets are useful in specific circumstances, but they do not provide the same kind of decision-making heuristic that mayors receive from direct constituent interaction. Findings emphasize the importance of more robust data collection and the development of management frameworks that support sustainability decision-making in Arctic cities. [ABSTRACT FROM AUTHOR]

In recent times, the usage of cryptocurrencies has become remarkably widespread in e-commerce applications. This study aims to explain the factors affecting cryptocurrencies by proposing an extended technology acceptance model (TAM) consisting of perceived ease of use, perceived usefulness, trust, social influence, social support, religious belief, and intention to use. A web-based survey was conducted to collect data from individuals who had never previously used cryptocurrencies and data were analyzed via employing partial least square structural equation modelling (PLS-SEM) with SmartPLS software. According to the results, the relationships based on early TAM were validated. Additionally, trust, social influence, and social support have direct effects on the intention to use. Contrary to expectations, religious belief has no influence on trust and intention to use. This study could draw the attention of researchers, developers, and marketers in cryptocurrency to understand the dynamics of potential customers. Findings of this study highlight the pressing need for policymakers in Turkiye to prioritize ease of use, perceived usefulness, and, most importantly, trust within the evolving landscape of cryptocurrency systems. [ABSTRACT FROM AUTHOR]

This research, utilizing the technology-organization--environment (TOE) framework, aimed to examine the roles of technological competence, top management support, coercive pressures, normative pressures, and mimetic pressures in the adoption of enterprise social media (ESM) for marketing purposes by organizations, and ultimately, in facilitating their relationship marketing practices. From 452 responses collected via an online survey across five organizations using ESM for marketing in Iran, 400 valid data points were analyzed using partial least squares structural equation modeling (PLS-SEM). The findings revealed that technological competence, top management support, and mimetic pressures positively influence ESM implementation for marketing purposes. However, coercive and normative pressures were found to have no significant impact on ESM adoption for this purpose. Additionally, the study demonstrated that ESM implementation for marketing significantly impacts all components of relationship marketing practices. To the best of our knowledge, this is among the few studies addressing ESM adoption by organizations for marketing and external communications. Moreover, this study is the first to extend the advanced TOE framework to the domain of ESM implementation for marketing purposes. [ABSTRACT FROM AUTHOR]

Although Blockchain technology has shown its usefulness, there exist limited studies and industrial applications. Presented research investigates factors influencing blockchain adoption. It reflects on how the perceived benefit of blockchain may influence the adoption and how organisational size may affect this process. This study integrates the framework of the Technology Acceptance Model (TAM) with the Theory of Planned Behaviour (TPB) and extends it with the perceived benefits of blockchain adoption while including firm size as moderator. Data collected were analysed with a PLS-SEM. Our results showed that a significant predictor of intention to use blockchain is perceived behavioural control. Moreover, it was found that perceived benefit significantly influenced perceived usefulness. Finally, the study demonstrated that SMEs are more efficient in adopting blockchain compared to Large firms. [ABSTRACT FROM AUTHOR]

Food trucks represent a unique dining option that encompasses elements such as culinary innovation, small business entrepreneurship, and cultural diversity. Grounded in the self-determination theory, this research aimed to examine a framework of ethnic food truck visitors' satisfaction using symmetric and asymmetric approaches. Drawing from a sample of 416 online respondents, the symmetric analysis revealed that brand image mediated the relationship between the quality concepts (food quality and delivery quality) and satisfaction. In addition, destination image mediated the relationship between authenticity concepts (food authenticity and atmosphere authenticity) and satisfaction. Cuisine type partially moderated the structural model consisting of quality, image, and satisfaction. Through an asymmetric approach, the study identified configurations predicting high and low satisfaction, highlighting the combined effects of multiple ingredients. These insights provide valuable theoretical and managerial implications for understanding customer satisfaction within the food truck industry. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Engineering Management / Gongcheng Guanli Xuebao is the property of Journal of Engineering Management Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the face of globalisation's homogenising wave, this study serves as a beacon, illuminating the intricate web of factors that safeguard culinary heritage in India. The study hypothesised that a myriad of elements interweaves to form the fabric of food traditions, which in turn fortify collective identity. To validate this, the study engaged 696 individuals via an online survey, employing advanced statistical tools such as path analysis and partial least squares structural equation modelling (PLS-SEM) to unearth the core determinants of gastronomic lineage. Moreover, multiple regression analysis was utilised to measure the impact of these culinary practices on personal and cultural identity. The study's revelations are profound, demonstrating that each of the 18 determinants meticulously chosen for this research significantly contributes to the crafting of Indian food heritage, thereby seasoning the identity of the future with the flavours of the past. [ABSTRACT FROM AUTHOR]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose: This study aims to evaluate the usage of partial least squares structural equation modeling (PLS-SEM) in journals related to logistics and supply chain management (LSCM). Design/methodology/approach: Based on a structured literature review approach, the authors reviewed 401 articles in the field of LSCM applying PLS-SEM published in 15 major journals between 2014 and 2022. The analysis focused on reasons for using PLS-SEM, measurement model and structural model evaluation criteria, advanced analysis techniques and reporting practices. Findings: LSCM researchers sometimes did not clarify the reasons for using PLS-SEM, such as sample size, complex models and non-normal distributions. Additionally, most articles exhibit limited use of measurement models and structural model evaluation techniques, leading to inappropriate use of assessment criteria. Furthermore, progress in the practical implementation of advanced analysis techniques is slow, and there is a need for improved transparency in reporting analysis algorithms. Originality/value: This study contributes to the field of LSCM by providing clear criteria and steps for using PLS-SEM, enriching the understanding and advancement of research methodologies in this field. [ABSTRACT FROM AUTHOR]

Many countries have committed to carbon reductions and carbon neutrality targets in response to the Paris Agreement and Sustainable Development Goals (SDGs). With economic development, the transportation sector has become a major source of carbon emissions. In China, transport infrastructure—as an important carrier of the transportation sector—is important for controlling carbon emissions from this sector and achieving carbon neutrality and the targets of the SDGs. However, most studies have focused on transport vehicles and neglected transport infrastructure. Furthermore, the influences of collusive behavior and digital control technologies on the carbon reduction process have not yet been examined. This study aimed to analyze the influencing factors in the carbon reduction process in transport infrastructure. This study uses partial least squares structural equation modeling (PLS-SEM) to analyze the factors influencing carbon reductions in transport infrastructure and the mediating roles of collusive behavior and digital control technologies in the carbon reduction process. Low-carbon technologies, digital control technologies, and collusive behavior have positive direct and indirect effects on the carbon reduction effect. Digital control technologies have a positive effect on low-carbon regimes. Low-carbon technologies influence carbon reduction effects. Collusive behavior plays a mediating role in low-carbon regimes. Finally, the industrial structure influences carbon reduction effects. This study extends China's carbon emission research in the transportation sector by focusing on infrastructure rather than vehicles. Additionally, this is the first study to incorporate collusive behavior and digital control technologies into the framework to analyze the impact of carbon reductions. The study also employs PLS-SEM to explore effective carbon reduction paths. The findings provide decision-making support for controlling carbon reductions in transport infrastructure. [ABSTRACT FROM AUTHOR]

The goal of this study was to examine the predictors of sustainable tourism development during the post-COVID-19 pandemic period in the context of Bangladesh. Quantitative-type research was applied, and this study used a descriptive research design. A standardized questionnaire was used to collect 302 data points from actual indigenous tourists using an online purposive sampling method. A partial least squares structural equation modeling (PLS-SEM) approach was used to evaluate the data and test the hypotheses. The results of the PLS-SEM analysis method demonstrate that environmental integrity, social equity, economic prosperity, and technological adaption had a positive relationship with sustainable tourism development during the post-COVID-19 pandemic period in Bangladesh. This research article provides practical guidelines for tourism authorities (BTB, BPC, and so on) and stakeholders on how to effectively impact environmental integrity, social equity, economic prosperity, and technological adaption on sustainable tourism development during the post-COVID-19 pandemic period in the context of Bangladesh. This study recommends that influential strategic factors be utilized to develop a sustainable tourism business in Bangladesh, positioning it as an emerging tourism destination. [ABSTRACT FROM AUTHOR]

Higher education institutions are increasingly implementing hybrid flexible (HyFlex) learning mode due to its accessibility and flexibility. However, little is known about students' engagement and potential predictors in this learning approach. This study's objective was to look into strategies for enhancing learner engagement in HyFlex learning environments. In this study, the relationships between specific predictors (learner control, self-efficacy, and learning motivation), learners' perceived community of inquiry (CoI) presences, and learner engagement in HyFlex learning environments were investigated using partial least squares structural equation modeling (PLS-SEM). In order to collect data on the study's variables, an online survey was completed by 367 students who were enrolled in the HyFlex learning environments at a Chinese college. The results indicated a direct and positive relationship between learner engagement and factors such as self-efficacy, learner motivation, and learners' perceived CoI presences. However, learner control did not have a direct and positive impact on learner engagement. Instead, it indirectly influenced learner engagement by affecting learners' perceived CoI presences. In addition, the relationships between learner motivation and engagement, as well as self-efficacy and learner engagement, were significantly mediated by the learners' perceived CoI presences. The findings offer fresh perspectives on the roles of learner control, self-efficacy, learner motivation, and learners' perceived CoI presences in HyFlex learning, with implications for learning processes and learner engagement. [ABSTRACT FROM AUTHOR]

In the wake of the digital revolution transforming the landscape of higher education, e-learning has emerged as a pivotal model for knowledge dissemination, reshaping traditional pedagogical methodologies and fostering an unprecedented transition to virtual learning environments. This transformative shift, necessitated by global crises and the rapid evolution of technology, has spotlighted the urgency to evaluate and enhance the effectiveness and user satisfaction of online learning platforms. Particularly in the context of Indian higher education, where the demographic expanse and diverse educational needs present unique challenges and opportunities, understanding the drivers of student satisfaction in e-learning is paramount. This empirical investigation explores the factors influencing students' satisfaction with online education in Indian universities and higher education institutions. Data were collected from 460 postgraduates and undergraduates across 30 institutions offering programs in management, engineering, and commerce. Utilizing Structural Equation Modeling, the study identified key variables impacting learner satisfaction: learner inspiration and motivation, potential obstacles to e-learning, group and professor interaction, and the use of technology (including AI and other tools) in e-learning. Results indicate that potential obstacles to e-learning and the integration of technology had the most significant impact on student satisfaction, emphasizing the importance of overcoming barriers and leveraging technology effectively in e-learning environments. This study offers insights for higher education institutions seeking to enhance virtual learning experiences and underscores the imperative of addressing technological challenges to ensure sustained student satisfaction. [ABSTRACT FROM AUTHOR]

Purpose: Internationalisation is a complex and uncertain process for small and medium-sized enterprises (SMEs), characterised by challenges such as limited resources, lack of international experience and uncertainty in foreign markets. This study aims to explore the impact of entrepreneurial effectuation on the diversification of products and market expansion. Additionally, it examines the mediating role of alliance capabilities in this relationship. Design/methodology/approach: This study developed five hypotheses based on an extensive and relevant literature review. Data were collected using nonprobability judgemental and snowball sampling techniques from 202 software exporting firms in Bangladesh to measure the relationship. Data collected from the survey were then analysed using partial least squares-structural equation modelling. Findings: The results of this study show that all five hypotheses developed in this study are supported. This study found a positive impact of entrepreneurial effectuation on product and market diversification. Study results also show that alliance capabilities mediate the relationship between entrepreneurial effectuation and product and market diversification. Research limitations/implications: In the face of internationalisation uncertainties, SMEs use effectual decision-making logic and form strategic alliances to enhance their competitive positions. This research contributes to understanding how SMEs use effectuation in navigating international markets and expanding their product portfolios and market reach. Originality/value: This study pioneers a mediation approach to explore the relationship between entrepreneurial effectuation, alliance capabilities and diversification in SME internationalisation. Examining the interplay of decision-making logic and collaborative ventures, this study offers insights into the complexities of SME internationalisation in uncertain environments. [ABSTRACT FROM AUTHOR]

Economic development belongs to the group of the most important categories not only in economic, but also social and political theory. Even though this category has been the subject of research since the beginning of the formation of economics as a science, it seems that to this day it has not been possible to explain exactly why economies, despite similar resources, develop at a significantly varied pace. The quality of institutions becomes a factor of development, enabling the analysis of the economy from a much broader perspective. The question of whether institutions are relevant for economic development seems rhetorical. The group of norms of the greatest importance for development are informal ones. One of the most important of their elements is social trust. This paper aims to identify the relationship between social trust and economic development and to quantify these latent variables in selected European countries in 2017–2020. This article applies partial least squares structural equation modeling (PLS-SEM). The PLS-SEM model covered 35 European economies in 2017–2020. The analyses carried out in this paper indicate that social trust has a strong, positive and statistically significant influence on economic development dynamics. Differences in the level of trust seem to be a valid reason for notable developmental disproportions among European countries. Moreover, trust towards other people is more important than confidence in organizations in shaping social trust, and consequently accelerating economic development. Social trust can be categorized as a "deep" determinant of growth, due to its impacts on the growth itself and its other determinants. Therefore, it is crucial to make trust a strategic priority by policy makers. Not only does the article provide a novel method for measuring social trust and development, but also for identifying the relationship between these latent categories. [ABSTRACT FROM AUTHOR]

Infrastructure development's contribution to community wellbeing in sub-Saharan Africa (SSA) is largely unknown. Existing scholarship over-represents externally funded projects, sidelining micro-level initiatives. Empirical studies hardly apply Structural Equation Modeling (SEM) approaches that estimate wellbeing as a composite function of infrastructure development. We review the topical literature on infrastructure development and community wellbeing in SSA. We find positive effects of infrastructure development on community wellbeing in SSA. SEM was not applied in any reviewed case study. We then use the Partial Least Square Structural Equation Model (PLS – SEM) to assess the impacts of multiple micro-level infrastructure projects on community wellbeing in Cameroon. All four examined micro-projects had positive effects on community wellbeing. However, only the effects of two projects (hospitals and schools) were statistically significant. The study recommends more SEM-based studies as prerequisite to disentangling composite wellbeing benefits of infrastructure development in SSA, with cost efficiency and outcome-optimizing implications. [ABSTRACT FROM AUTHOR]

This article aims to investigate the effect of customer empowerment on their engagement on sharing platform in the retailing sector via the mediating role of service innovation and customer trust. This study utilized a quantitative design emphasizing mature theory research. The research sample consisted of 457 customers of sharing platform for the retailing sector, using a partial least square-structural equation model (PLS-SEM) for hypothesis testing. The result reveals that customer empowerment positively and significantly affects customer engagement directly and via service innovation as a mediating mechanism on the sharing platform. However, trust in the platform does not mediate this relationship. It is advisable to retailers on sharing platform to create a leading position in this market by enhancing customer engagement and promoting service innovation via customer empowerment. This paper develops a conceptual framework for customer engagement on sharing platform in the sharing economy via service innovation based on giving empowerment to customers. [ABSTRACT FROM AUTHOR]

In the university context, the self-regulated learning processes play an instrumental role as a strategy that allows students to achieve a greater academic self-concept due to their awareness of their academic development and their active participation in this process. This study involved 276 students of the Primary Education Degree of the University of Jaén, (Spain), participated, of which 213 (77.2%) were female and 63 (22.8%) were male, with the average age of 19.97 years (± 2.834). The Inventory of Self-Regulation of Learning Processes (IPAA) and the Academic Self-Concept Scale (EAA) were applied. The objective was to provide enough evidence on the complementarity of self-regulation learning processes with academic self-concept. This study introduces the combined used of structural equation modeling (PLS-SEM) and necessary conditions analysis (NCA) to investigate the proposed hypotheses. The results of the model found high coefficients of determination Execution [(Q2 = 0.261); (R² =0.547)]; Assessment [(Q2 = 0.249); (R² =0.393)]; and Academic self-concept [(Q2 = 0.074); (R²=0.329)]. The results have corroborated the composite use of PLS-SEM and NCA allow to identify some of the essential factors of academic self-concept according to the rationale of need. The combination of both perspectives supports the theoretical underpinning of this topic. [ABSTRACT FROM AUTHOR]

AbstractThis study aims to explore how travel serves as a tool for trauma recovery, aiding individuals in coping with psychological trauma and promoting mental health. We adopted a pragmatic mixed-methods approach, conducting two complementary studies: qualitative interviews with individuals who have experienced trauma and a quantitative survey. The qualitative interviews reveal the mechanisms and key factors of travel in the trauma recovery process. Based on the interview data, we constructed a conceptual model that includes latent variables such as travel experience, emotional regulation, self-reflection, social support, and trauma recovery. This model was subsequently validated through a quantitative survey study using Partial Least Squares Structural Equation Modeling. The results indicate that travel significantly promotes trauma recovery by providing a restorative environment, facilitating emotional regulation, and enhancing social interaction. This study provides new insights into the role of travel in trauma recovery and offers practical guidance for mental health interventions. [ABSTRACT FROM AUTHOR]

AbstractAlthough an increasing number of studies explore the factors influencing users’ privacy concerns regarding social robots, the existing understanding of this issue remains largely fragmented. Previous studies have mainly focused on the "net effect" between variables, leaving the complexity of causal configurations, and the holistic impact of design characteristics of social robots on user privacy concerns remains unclear. Based on the Stimuli-Organism-Response (S-O-R) framework and Communication Privacy Management Theory (CPMT), this study integrates social robot design characteristics such as Anthropomorphism, Warmth, Competence, and Transparency into causal configurations, and uses Perceived Privacy Risk and Perceived Privacy Control as mediating variables to propose a Comprehensive conceptual model. Based on valid data from a sample of 198 Chinese social robot users, this study conducted empirical analyses of the conceptual model using Partial Least Squares Structural Equation Modeling (PLS-SEM) and Fuzzy-set Qualitative Comparative Analysis (FsQCA). PLS-SEM results show that anthropomorphism, warmth, competence, and transparency are key factors influencing privacy concerns, and perceived privacy risk mediates the relationship between warmth, information transparency, and privacy concerns. The FsQCA results further validated the findings of PLS-SEM and identified five configurations of factor combinations that led to higher levels of user privacy concerns. Among them, the combination of high anthropomorphism design, high competence, and low warmth of social robots is the core configuration that leads to users’ privacy concerns. Overall, this study broadens our understanding of social robot users’ privacy concerns and reveals the causal complexity behind social robot users’ privacy concerns. It provides some theoretical and practical insights for subsequent scholars and designers. [ABSTRACT FROM AUTHOR]

The Indian automobile industry is witnessing a paradigm shift from fossil fuel to green energy. The current study employs an extended version of the theory of planned behaviour (TPB) to investigate the impact of attitudes, green nudges and perceived behavioural control on the behavioural intention (BI) for adoption of electric vehicles (EVs) by Indian consumers. Environmental concern is also added to the model to find its impact on actual buying behaviour (AB). Conclusive research is carried out, and data is collected through a structured questionnaire. 342 respondents were analysed using a two-step investigation approach: Partial least square-structural equation modelling (PLS-SEM), followed by an artificial neural network (ANN). Subsequently, two models are formed to determine the predictors of BI and AB. The findings suggest that all three factors positively impact BI and AB. Attitude plays the most significant role in BI (the most important predictor of AB). The study's findings also suggest that the extended TPB model is effective for forecasting customers' adoption intentions towards EVs. Moreover, this research adds to the existing literature on the intention and reluctance of consumers to embrace green technology. The results of this study will have significant implications not only for a greater understanding of customer behaviour regarding the adoption of EVs, but also for exploring their market expansion, product offerings, consumer BI and framing policies. [Display omitted] Problem Definition. • Need to understand the factors that influence consumer behavior for the adoption of Electric Vehicles (EVs). Concept. • Complexities surrounding consumer's intention and reluctance to embrace EVs implementation of carbon neutrality in organizations. Theoretical Underpinning. • An extended TPB model that includes Green Nudge & Environmental concerns. Methodology. • A hybrid PLS-SEM ANN has been used. Results. • The study validates the extended TPB model for forecasting consumer intentions towards EV adoption. Implications. • The results have significant implications for understanding consumer behavior, market expansion, product offerings, buying intentions, and policy frameworks for EV adoption. [ABSTRACT FROM AUTHOR]

In recent years, artificial intelligence (AI) has been developing rapidly and has had a broad impact on the food industry, with food produced from AI-generated recipes already appearing to actually go on sale. However, people's trust and willingness to purchase AI food are still unclear. This study builds an integrated theoretical model based on cognitive trust and affective trust, taking into account consumers' quality value orientations, social norms, and perceived risks of AI food, with the aim of predicting and exploring consumers' trust and acceptance of AI food. This study utilized the questionnaire method and 315 questionnaires were collected. The results of structural equation modeling (PLS-SEM) indicated that food quality orientation, subjective norms, perceived trust, and affective trust all had a significant positive effect on consumers' purchase intentions. Perceived risk had a negative effect on affective trust and consequently on consumers' purchase intention, but the effect on cognitive trust was not significant. The results also suggest that cognitive trust is the basis of affective trust and that consumer trust and acceptance of AI food can be enhanced by augmenting two antecedents of cognitive trust (food quality orientation and subjective norms). Possible practical implications and insights from the current findings are discussed. [ABSTRACT FROM AUTHOR]

Although there has been a growing interest in understanding the influence of corporate social responsibility (CSR) on business outcomes, the specific mechanisms through which CSR impacts financial performance (FP) and competitive advantage (CA) remain underexplored, particularly in the context of the food industry. This study contributes to the literature by looking into the mediating effect of innovation and the moderating role of CA in the relationship between CSR and FP in Saudi Arabian food industry companies. Employing Partial Least Squares Structural Equation Modeling (PLS-SEM), data were collected from executive managers of these companies to assess how CSR practices foster innovation and, consequently, enhance financial outcomes and competitive positioning. The results reveal that CSR significantly improves FP and CA, primarily when focused on innovation. Moreover, CA does not influence the strength or direction of the relationship between CSR and FP. This research offers essential guidance for food industry managers to integrate CSR into core business strategies, foster innovation, and strengthen stakeholder relationships, thereby achieving sustainable growth and profitability. [ABSTRACT FROM AUTHOR]