Partial Least Squares Structural Equation Modeling Research Articles

Using PLS-SEM and XAI for casual-predictive services marketing research

Purpose This study aims to redefine approaches to metrics in service marketing by examining the utility of partial least squares – structural equation modeling (PLS-SEM) and eXplainable Artificial Intelligence (XAI) for assessing service quality, with a focus on the airline industry. Design/methodology/approach Using the Airline Passenger Satisfaction data set from Kaggle platform, this study applies PLS-SEM, facilitated by ADANCO software and XAI techniques, specifically using the SHapley Additive exPlanations TreeExplainer model. This study tests several hypotheses to validate the effectiveness of these methodological tools in identifying key determinants of service quality. Findings PLS-SEM analysis categorizes key variables into Delay, Airport Service and In-flight Service, whereas XAI techniques rank these variables based on their impact on service quality. This dual-framework provides businesses a detailed analytical approach customized to specific research needs. Research limitations/implications This study is constrained by the use of a single data set focused on the airline industry, which may limit generalizability. Future research should apply these methodologies across various sectors to enhance a broader applicability. Practical implications The analytical framework offered here equips businesses with the robust tools for a more rigorous and nuanced evaluation of service quality metrics, supporting informed strategic decision-making. Social implications By applying advanced analytics to refine service metrics, businesses can better meet and exceed customer expectations, ultimately elevating the societal standard of service delivery. Originality/value This study contributes to the ongoing discourse on artificial intelligence interpretability in business analytics, presenting an innovative methodological guide for applying PLS-SEM and/or XAI in service marketing research. This approach delivers actionable insights, not only in the airline sector but also across diverse business domains seeking to optimize service quality.

Input-output-outcome innovation model: an analysis of the Brazilian manufacturing companies

PurposeThe objectives of this study are to identify which inputs are most relevant for development and successful introduction of product and process innovations and identify the impacts of these two types of innovation on the performance of Brazilian manufacturing companies.Design/methodology/approachThis study analyzes the relationships between input, output and outcome for a sample of 5,586 Brazilian manufacturing companies by using partial least squares structural equation modeling (PLS-SEM).FindingsThe results indicate that (1) product innovations are favored by internal resources, (2) process innovations are favored by external resources, (3) product innovations mainly affect a range of products offered by companies and (4) process innovations mainly affect performance in manufacturing capacity, flexibility and costs.Practical implicationsBy identifying the main efforts to improve the innovation performance and input-output-outcome relationships, the results can contribute to a better decision-making process for innovation investments and management in companies as well as for policymakers. The results are particularly relevant given that the Brazilian case can serve as a reference for other emerging countries.Originality/valueAnalyses of the innovation in input-output-outcome relationships were performed in a comprehensive way by using a set of variables for defining each construct. This allowed each construct to be better measured, which improved the understanding of the relationships between inputs and outcomes mediated by product and process innovations.

Identifying group metacognition associated with medical students’ teamwork satisfaction in an online small group tutorial context

BackgroundCollaborative learning is an essential pedagogy in medical education, within which small group learning constitutes an integral component. Online small group teaching has been widely applied and blended with in-person sessions in the aftermath of the Covid-19 pandemic. This study examined whether group metacognition was associated with teamwork satisfaction in an online small group teaching curriculum for medical students.MethodsWe enrolled medical students of the 2nd and 4th years during the 2021 fall semester after they participated in 3 consecutive sessions of online small group tutorials (SGTs), which have been implemented in our medical school for more than 20 years. The students completed a group metacognitive scale (GMS) and a teamwork satisfaction scale (TSS) after the sessions. We analyzed whether group metacognition in 4 dimensions (knowledge of cognition, planning, evaluating, and monitoring) could be connected with medical students’ teamwork satisfaction using partial least squares-structural equation modeling (PLS-SEM).ResultsA total of 263 medical students participated in this study. Both GMS and TSS exhibited good reliability and validity. Three of the 4 dimensions of group metacognition (cognition, planning, and evaluating) positively correlated with teamwork satisfaction (path coefficients 0.311, 0.279, and 0.21; p = 0.002, 0.002, and 0.043, respectively) following the online SGT curriculum, whereas the monitoring dimension did not (path coefficient 0.087; p = 0.357). The model achieved an adjusted R square of 0.683.ConclusionWe discovered that group metacognition correlated positively with better teamwork satisfaction, supporting the importance of group metacognitive competency for online collaborative learning.

The development of intrinsic capacity measures for longitudinal research: The Longitudinal Aging Study Amsterdam

BackgroundThe World Health Organization has introduced the construct of intrinsic capacity (IC) as an important component of healthy ageing and overall well-being in older adults The present study aimed to develop domain-specific and composite IC scores and to validate these scores by examining their longitudinal relation with functioning. MethodsWe used prospective data on participants aged 57 to over 90 years, with a 10-year follow-up, from the Longitudinal Aging Study Amsterdam, an ongoing cohort study of older Dutch men and women Using a formative, stepwise approach, we identified indicators across the different domains of IC, i.e. vitality, sensory, cognition, psychology, and locomotion, using a combination of unidimensional factor analyses and Partial Least Squares Structural Equation Modelling (PLS-SEM). Next, domain-specific and composite IC scores were generated, and the construct validity (score across age groups) and criterion validity (relationship with change in functional limitations) were assessed. ResultsThe multiple unidimensional factor analyses and PLS-SEM identified a total of 18 indicators, covering the five domains of IC. The mean composite IC score was 70.9 (SD = 0.9) in men and 69.7 (0.8) in women. The domain-specific and composite IC scores all showed good construct validity, with known-group validation results indicating age-related declines. A higher composite IC score was associated with less functional limitations over time (B = 0.20, 95%CI [0.19, 0.22]). ConclusionThe developed domain-specific IC scores and the composite IC score effectively discriminated age-related declines in IC. Additionally, the composite IC score was longitudinally associated with functional limitations. By creating this comprehensive and reliable tool for tracking IC, we aim to provide valuable insights into the dynamics of ageing and support more effective strategies for promoting health and well-being throughout later life. These scores establish a foundation for future research to track longitudinal changes across various IC domains and relate these changes to key age-related outcomes.

Family burden and psychological distress among Chinese caregivers of elderly people with dementia: a moderated mediation model

BackgroundAlthough the Stress-Coping Model (SCM) has been widely used to explain the coping process of individuals facing stressful situations, its applicability to caregivers of elderly people with dementia (PwD) in China needs to be further investigated. Furthermore, the role of external resources in caregivers stress coping is not yet clear. Therefore, our study aimed to investigated the mediating and moderating mechanisms between family burden and psychological distress in PwD caregivers based on the SCM.MethodsA cross-sectional study, with 193 pairs of PwD and caregivers completed the self-designed questionnaire, Family Burden Scale of Disease, Kessler Psychological Distress Scale, General Self-Efficacy Scale, Simplified Coping Style Question, The Family Adaptation and Cohesion Evaluation Scales II-CV and Social Support Rating Scale. Partial least squares-structural equation modeling (PLS-SEM) analyzed the mediating and moderating effects.ResultsFamily burden positively correlated with psychological distress; the chain mediation effects of self-efficacy and positive coping between family burden and psychological distress was significant; the interaction term (family function_positive coping) did not but (social support_positive coping) had a significant positive impact on psychological distress.ConclusionsThe findings provides a practical basis for the use of SCM in informal caregivers of elderly PwD, assists understanding the mechanism of the relationship between family burden and psychological distress. And it supplies new perspectives for reducing the negative psychological health status and a theoretical basis for designing interventions for caregivers.

The impact of intellectual capital and market capitalization on corporate investment decisions: exploring the mediating and moderating effect of knowledge sharing and the COVID-19 pandemic

PurposeThis paper examines the effect of intellectual capital (IC) and market capitalization (MC) on corporate investment decisions (ID) through the mediating and moderating effects of knowledge/information sharing (KS) and the Covid-19 pandemic.Design/methodology/approachWith the use of SPSS 26 and SmartPLS version 3.0, the partial least square structural equation modelling (PLS-SEM) technique is employed with 1,036 observations to examine the effects.FindingsOur findings show that IC and social interactions (SI) have a positive effect on KS. KS affects positively both MC and ID. KS has the mediating and moderating effects while the Covid-19 has the moderating impact on ID.Practical implicationsThis research suggests that company leaders should understand the important role of IC and MC in enhancing ID through KS. They should pay attention to MC to enhance their investment and SI among employees, partners, consumers and authorities should be encouraged.Originality/valueThis research contributes to the existing literature by employing the perceptual scale to examine the effect of IC and MC, the mediating and moderating effects of KS, and analyze the moderating role of the Covid-19 on ID. It also expands the current models by including the Covid-19 and MC to clarify the ID determinants. New measurements of MC and the Covid-19 constructed are also another contribution.

Assessing the Impact of Women Discrimination in HRM Practices on Three-component Model (TCM) of Organizational Commitment: A Study on the Indian Banking Sector

Notably, social-psychological approaches such as relative deprivation theory (personal and collective) and social exchange theory posit that there exists a negative association between women discrimination in HRM practices and organizational commitment. It is pertinent to note that the study of organizational commitment is significant across behavioral and attitudinal perspectives as well as differing conceptualizations. Considering this, the present study aims to investigate the causal linkages between women discrimination in HRM practices and the three-component model (TCM) of organizational commitment in the Indian banking sector. To test the hypothesized relationships, partial least squares structural equation modeling (PLS-SEM) was used on a sample of 394 women employees from the following banks in Northern India—State Bank of India, Punjab National Bank, Housing and Development Finance Corporation Bank, and Jammu and Kashmir Bank. The results obtained revealed that women discrimination in HRM practices has a significant negative impact on all three components of the TCM approach of organizational commitment—affective commitment, continuance commitment, and normative commitment. Specifically, the negative effect was found more on affective commitment and normative commitment, unlike continuance commitment. Consequently, the current study has thrown light on theoretical and managerial implications along with directions for future research.

Consumer Perception of Environmental Protection to Promote Mindful Consumption Behaviour through Mindfulness and Ascription of Responsibility

The fast fashion business under fire for its detrimental effects on the environment, and the economy. A lot of companies are taking ethical marketing tactics to urge consumers to be more responsible and conscious while making purchases. Study measure the impact of consumer ethical marketing perception environmental protection on mindful consumption through mindfulness and ascription of responsibility. Quantitative cross-sectional survey approach used. Test model used 321 final responses. Variance-based partial least squares structural equation modeling (PLS-SEM) was employed to examine the survey data. The outcomes indicated that fostering a mindful consumption behavior marketing tactics can play significant role. Consumer perception of environmental protection strategies can enhance the consumer responsibilities and their mindful mindset. Which ultimately influence their behavior. The research offers insightful information on ethical marketing tactics that local markets may use to promote mindful behavior and to support sustainable policies and practices in the fashion industry.

UNLOCKING ACADEMIC SUCCESS IN THE DIGITAL AGE: HOW SOCIAL MEDIA USE, SOCIAL ENGAGEMENT, AND SELF-REGULATION SHAPE UNIVERSITY STUDENTS' PERFORMANCE

In the digital age, social media has become an integral part of university life, influencing students' academic performance and social engagement. This study investigates the relationships between social networking site (SNS) usage, social engagement, self-regulation, and academic performance among Chinese university students. Utilizing a sample of 438 students from a public university, data were collected through a structured questionnaire administered via WeChat and Ding Talk. The analysis employed Partial Least Squares Structural Equation Modeling (PLS-SEM) using SmartPLS version 4.1 to test the proposed hypotheses. The results indicate that SNS usage significantly and positively influences students' academic performance and social engagement. Furthermore, social engagement was found to mediate the relationship between SNS usage and academic performance, suggesting that the benefits of social media extend beyond mere academic collaboration. Additionally, self-regulation was identified as a moderating factor, strengthening the positive impact of SNS usage on academic performance. These findings highlight the importance of leveraging social media as a tool for enhancing academic success while emphasizing the need for self-regulatory skills in navigating digital environments. This study provides valuable insights for educators and policymakers aiming to optimize the academic potential of social media in higher education settings. KEYWORDS: Social networking site usage, Social Engagement, Academic Performance, Self-Regulation

PENGARUH CUSTOMER RELATIONSHIP, STRATEGIC SUPPLIER, INFORMATION SHARING & POSTPONEMENT TERHADAP ORGANIZATIONAL PERFORMANCE YANG DIMEDIASI INBOUND DAN OUTBOUND INNOVATION

Technological advancements and the growth of e-commerce have increased the complexity of supply chain management, making it more vulnerable to disruptions. The COVID-19 pandemic has highlighted this vulnerability, leading organizations to reassess traditional risk management approaches and emphasize collaborative partnerships to enhance supply chain value. This study aims to evaluate the impact of Customer Relationship (CR), Quality of Information Sharing (QIS), Strategic Supplier Partnership (SSP), Postponement (P), Top Management Knowledge Value (TMKV), and Knowledge Sharing Practice (KSP) on Organizational Performance (OP), with Inbound and Outbound Open Innovation (IOI and OOI) as mediating variables. Data was collected from 164 professionals in Jakarta using the Purposive Sampling method through online questionnaires on Google Forms. Data analysis was conducted using the Partial Least Squares Structural Equation Modeling (PLS-SEM) method. The results of the study show that all independent variables positively affect organizational performance, although not all of these effects are significant. This indicates that effective integration between Supply Chain Management strategies and Open Innovation can improve organizational performance. TMKV has a significant positive impact on KSP, KSP also has a significant positive impact on IOI, IOI has a significant positive impact on OP, and KSP mediated by IOI is proven to have a significant positive effect in supporting OP, while OOI mediation is not proven. This study is not intended to generalize a theory due to the limitations in sample size, industry, and geographical area.

A dynamic capability perspective on the impact of big data analytics and enterprise architecture on innovation: an empirical study

PurposeThe prevailing conceptualization of information system (IS) capabilities, rooted in the resource-based view (RBV) framework, tends to focus on unique firm resources. In the digital age, as emphasized by dynamic capabilities (DC), resource reconfiguration is critical in maintaining strategic advantage. This paper focuses on big data analytics capabilities (BDAC) from a DC perspective to present a novel conceptualization of BDAC–DC. We examine its effects on product, business model and business process innovation, including the effects of enterprise architecture (EA) on the BDAC business model innovation relationship.Design/methodology/approachThis research presents a novel DC-based BDAC conceptualization, operationalized as a hierarchical construct. A survey-based approach is used for data collection and data analysis is done using partial least squares structural equation modeling (PLS-SEM).FindingsThe novel conceptualization and the effects of BDAC DC on BDA sensing-seizing and reconfiguration capacities support BDAC’s functional and evolutionary roleplay. Empirical results confirm the positive effects of BDAC–DC on first-order value targets (innovation) and the moderating effects of EA.Research limitations/implicationsThe novel BDAC–DC conceptualization has several implications for BDAC, DC, EA and business value research. Practicing managers must adopt a multifaceted approach to BDAC development by considering non-technical and organizational factors, collaborate with their business counterparts to explore unique big data ideas, initiate proof-of-concept projects to secure support and allocate resources synchronously, considering a multidimensional view of the process, product and business model innovation.Practical implicationsPracticing managers must adopt a multifaceted approach to BDAC development by considering non-technical and organizational factors, collaborate with their business counterparts to explore unique big data ideas, initiate proof-of-concept projects to secure support and allocate resources synchronously, considering a multidimensional view of the process, product and business model innovation for synergistic outcomes.Originality/valueTo the best of our knowledge, this research is the first attempt toward DC-based BDAC conceptualization, empirical validation of first-order effects on various forms of innovation and the often-overlooked role of critical EA capability.

The influence of tangibility, reliability and responsibility on the financial performance of banks with mediating role of customer satisfaction

The study explores the relationship between customer satisfaction and the financial performance of banks, focusing on mediating factors. This study aims to investigate in detail the impact of responsibility, tangibility, and reliability on banks’ financial performance, with a particular emphasis on the mediating function of customer satisfaction. The primary objectives are to analyze how these service quality dimensions influence customer satisfaction and, subsequently, financial outcomes. The research is grounded in the theory that higher levels of customer satisfaction lead to improved financial performance through increased loyalty. Using Employing Partial Least Squares Structural Equation Modelling (PLS-SEM), the study analyzes data collected from commercial bank clients in Kazakhstan over a four-month period, from November 2023 to February 2024. The dataset includes responses from approximately 200 participants, ensuring demographic representation through a stratified random sampling method. Hypotheses regarding customer satisfaction, reliability, responsibility, and tangibility were tested. Findings reveal a significant positive relationship between customer satisfaction and financial performance, indicating that higher satisfaction levels contribute to improved financial outcomes for banks. These findings highlight the multidimensional nature of customer satisfaction and underscore the importance of addressing various factors to enhance financial performance in the banking sector. This study contributes theoretical insights and practical implications for banks aiming to optimize their financial performance through customer-centric strategies.

Revealing the Secrets of Metaverse Technology Adoption for Sustainable Performance via Dual-Stage SEM-ANN Analysis

The growing ubiquity of the metaverse among small and medium-sized enterprises (SMEs) offers a game-changing chance for creative business plans and improved communication. This adoption reduces the consumption of physical resources and promotes an environmentally responsible business model in besides increasing operational efficiency. In accordance with the Sustainable Development Goals (SDGs) of the UNDP, our study attempts to clarify how the metaverse might improve the sustainable performance of SMEs. We developed a comprehensive study model based on the diffusion of innovation (DOI) and technical organizational and environmental (TOE) paradigms. For data analysis a hybrid approach merging partial least squares-structural equation modeling (PLS-SEM) and artificial neural network (ANN) was implemented. The study highlights the crucial roles of relative advantage, value alignment, compatibility, and top management after analyzing data from 369 respondents across Chinese SMEs that was collected both physically and online. The understanding of decision-makers becomes evident as a crucial element impacting the adoption of metaverse and ensuing sustainable (social, economic, and environmental) outcomes. This study offers valuable insights on metaverse adoption and sustainable performance for Chinese SMEs. Additionally, it offers appropriate suggestions for managers of SMEs, policy makers, and metaverse developers.

Service quality and repurchase intentions in the airline industry: a multiple mediation analysis through customer citizenship behaviour

ABSTRACT Building on expectation confirmation theory (ECT), this study examines the nexus between service quality and consumer repurchase intention in the airline industry, with a particular emphasis on the mediating role of customer citizenship behaviour (CCB). Utilising data from 260 respondents in the United Kingdom, the research employs partial least squares structural equation modelling (PLS-SEM) for the analysis. The findings indicate that service quality has a direct positive effect on CCB and repurchase intention. The study indicates that CCB, manifested through advocacy and tolerance, exerts a significant positive impact on consumer repurchase intention. The study uncovers that advocacy and tolerance behaviours serve as mediators in the relationship between service quality and repurchase intention, while feedback and helping do not play this role. The findings of the study contribute to the literature in the field of CCB and service quality in the airline industry.

Exploring the Impact of Positive Levers of Control on Organisational Resilience: The Mediating Role of Open Innovation

This study explores how positive control levers (belief systems and interactive control systems) affect organisational resilience, focusing on the role of open innovation as a mediator. Data were collected through a questionnaire administered to business managers and analysed using the partial least squares structural equation modelling (PLS-SEM) approach. The sample comprised 349 Moroccan industrial companies. The results demonstrate that positive control levers significantly impact open innovation and organisational resilience. Additionally, open innovation acts as a mediator, indirectly influencing the relationship between positive control levers and organisational resilience. This study contributes to the limited empirical research on management control systems by highlighting the importance of positive control tools and open innovation in developing sustainable organisational resilience.

Distribution Personalization and Content Decentralization on Brand Recall

Structural equation modeling examines the impact of distribution personalization and content decentralization on brand recall among Gen-Z consumers to analyze the causal relationship between these factors. The research used Covariance Based–Structural Equation Modeling (CB-SEM) and Partial Least Squares–Structural Equation Modeling (PLS-SEM) based on review of related literature. The 385 samples were Gen Z (age 12 to 27 as of year 2024 randomly from Region III, Philippines, comprising the provinces of Aurora, Bataan, Bulacan, Nueva Ecija, Pampanga, and Tarlac. Questionnaires with rating scales were used as research tools. Confirmatory factor analysis was used to analyze model fit, reliability, and validity. A structural model and path analysis were used to examine the links. Causal relationships were analyzed using PLS-SEM. The findings indicated that the model had a reasonable fit with empirical data and exhibited acceptable reliability and validity. The results demonstrate that distribution personalization has a direct positive effect on Gen Z’s ability to recall a brand. In addition, content decentralization acted as a partial mediator or indirect effect on the relationship between distribution personalization and Gen Z brand recall. Based on these results, sellers of clothing brands reliant on short-form video ads may consider employing advanced data analytics technologies to acquire insights into the preferences, behavior, and demographics of the audience and personalize video content to specific audience segments like Gen Z. Furthermore, it is advisable to optimize distribution channels, incorporate user-generated content into distribution strategies, and emphasize usercentric storytelling to create favorable associations with the brand. Future research should be qualitative or mixed methods to obtain a richer qualitative interpretation, and cohort or longitudinal research should be conducted to study these effects eventually.

Evaluating the Sabah Pay Mobile Application (e-Wallet) using the Technology Acceptance Model

The Sabah Pay e-wallet has been introduced as a digital payment solution in the state of Sabah, Malaysia, as part of a digital transformation initiative. However, there is a lack of comprehensive understanding regarding its user acceptance and the factors influencing it. Specifically, there is a need to investigate whether users perceive Sabah Pay as useful and easy to use. This research problem arises due to the importance of user acceptance in the success and sustainability of the e-wallet. Hence, we used the technology acceptance model (TAM) to analyse the perceived usefulness (PU) and customer satisfaction in using the Sabah Pay mobile application and the relationship between perceived ease of use (PEOU) and customer satisfaction using the Sabah Pay mobile application. The Cronbach's Alpha and composite reliability values are higher than 0.7, and the average variance extracted (AVE) is higher than 0.5, which supports the TAM constructs' convergence validity. The square root of AVE for each construct is higher than the corresponding correlations between constructs, which suggests the discriminant validity of the constructs. We used the Partial least squares structural equation modelling (PLS-SEM) to assess the data from the 173 respondents who reported using the Sabah Pay mobile application. We found that PU did not significantly affect customer satisfaction (CS), with a p-value of 0.207, although the path coefficient is 0.109, thus disproving the null hypothesis (H1). However, we supported the second hypothesis (H2) by observing that PEOU substantially impacted CS, with a p-value of 0.000 and a path coefficient of 0.614. The correlation indices demonstrated a satisfactory relationship between the data and the model. This research adds to the body of knowledge on mobile payment platforms by shedding light on perceived usefulness and ease of use factors that most affect users' happiness with Sabah Pay. The study suggests and identifies extensive research into potential customer satisfaction aspects like safety, trust, and value. This study's findings have real-world applications for practitioners and regulators looking to improve the mobile payment platform user experience and, by extension, boost customer happiness and adoption rates.

Pengaruh Kepercayaan, Religiusitas dan Pendapatan Terhadap Minat Membayar Zakat Masyarakat Muslim Kota Pekanbaru

This study investigates the influence of trust, religiosity, and income on the interest in paying zakat among the Muslim community in Pekanbaru City. Trust in zakat institutions is defined as the belief that these institutions are professional, honest, and transparent in managing zakat funds. Religiosity is measured as the level of adherence to religious teachings, while income reflects the economic status of the respondents. The research adopts a quantitative approach using a questionnaire as the data collection instrument from 114 respondents. Data analysis is conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM), and the results indicate that trust, religiosity, and income significantly influence the community's interest in paying zakat. These findings contribute to understanding the motivating factors or barriers among the Muslim community in Pekanbaru City in fulfilling their zakat obligations. The study provides practical implications for zakat institutions to enhance their transparency and professionalism to build trust among the public. It also offers deeper insights into the factors influencing community interest in zakat within a specific socio-economic context.

Investigating how consumption values and place identity shape long-haul truck drivers’ intention to visit roadside rest areas

Transportation business organisations, policymakers, and government entities attempt to enhance the welfare of long-haul truck drivers (LHTDs) by promoting safe driving practices. LHTDs spend long hours on goods delivery journeys, and that causes various health and in-route safety issues for drivers. For improved LHTD health and safety, many developed nations introduced the concept of roadside rest areas (RRAs) for regulated, safe, and enhanced driving experience for LHTDs, whereas developing nations’ research on RRAs development is nascent. The RRAs offer a chance to reduce negative truck driving impacts and promote wellbeing among LHTDs, but why drivers will visit RRAs during their tracking journey is a question for policymakers. Hence, the present study tries to comprehend the significance of drivers’ visit consumption values in terms of functional, social, emotional, epistemic, conditional value, and place identity concerning visit intentions towards RRAs. In addition, the present work examines the influence of consumption values on word of mouth (WoM) for RRAs by LHTDs. The research problem is examined via the lens of the theory of consumption values. The study utilised 247 valid responses for model analysis, using the partial least squares-structural equation modelling (PLS-SEM) technique. The findings establish that consumption value is a formative construct that further positively influences place identity, intentions to visit RRAs, and WoM for RRAs by LHTDs. This implies that the intentions of LHTDs to visit relaxation sites are mostly influenced by the values they perceive from such places. This perception of consumption values also helps LHTDs develop place identity with RRAs and influences them to spread positive WoM about it. However, the results of the present study did not find the mediation role of place identity. This implies that Indian LHTDs will develop the intention to visit RRAs because of the consumption values rather than any attachment to the place. The findings of this paper will help transport policymakers develop adequate measures for developing rest areas on major transport routes to improve road safety and drivers’ wellbeing.

Impacts of knowledge and trust on consumer perceptions and purchase intentions towards genetically modified foods.

Genetically Modified Foods (GMF) have emerged as a significant topic within the global food industry, provoking extensive debates over their safety and impact on consumer choices. This research aims to explore the impact of knowledge and trust in GMF on Vietnamese consumers' perceptions and their subsequent purchase intentions. By employing a quantitative methodology, this study gathered data from 424 valid respondents. The research model focuses on five constructs: knowledge, trust, perceived benefits, perceived risks, and purchase intentions. The data was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to test hypotheses and examine the interrelationships among these constructs. The results showed that increased knowledge of GMF is linked to heightened perceptions of benefits and reduced perceptions of risks, thereby elevating purchase intentions. Trust in GMF significantly enhances perceived benefits but does not significantly affect risk evaluation, although it is positively correlated with purchase intentions. Moreover, perceptions of greater benefits are positively associated with higher purchase intentions, whereas increased risk perceptions negatively influence them. These results underscore the complex relationship among knowledge, trust, perceived benefits, and perceived risks in shaping consumer purchase intentions toward GMF. The study proposes a comprehensive model delineating how knowledge and trust impact Vietnamese consumers' perceptions and purchase intentions regarding GMF. These findings provide implications for policymakers, business managers, and marketers, emphasizing the importance of disseminating transparent information, prioritizing trust-building, and adopting nuanced communication strategies. By effectively enhancing perceived benefits and addressing perceived risks, these strategies aim to foster positive consumer intentions and behaviors toward GMF.