The research, published in Discover Education, was led by Godswill Agu of Abia State University together with colleagues in Nigeria, Poland, and Spain. The team surveyed 213 final-year undergraduate marketing students drawn from Nigerian higher education institutions, focusing deliberately on students in their final year for three reasons: they have experienced the full breadth of their curriculum, they face cognitively demanding tasks such as dissertations and strategic campaign design where the temptation and utility of generative AI are greatest, and they are on the verge of entering a labor market where AI literacy is increasingly tied to employability. Data were collected over two weeks in October 2024 through a structured online questionnaire, and the researchers excluded eleven respondents who reported no prior awareness of ChatGPT, since awareness was a prerequisite for meaningfully reporting adoption intentions.

At the heart of the study lies a classic psychological framework: the Technology Acceptance Model, or TAM, first formulated by Fred Davis in the 1980s. TAM holds that two beliefs govern whether people embrace a new technology: perceived usefulness, the sense that the tool will improve performance, and perceived ease of use, the belief that operating it will require minimal effort. These beliefs shape attitudes, and attitudes in turn shape behavioral intention, the strongest proximal predictor of actual use. The model has endured for nearly four decades, but its authors and successors have long argued that its explanatory power can be enhanced by adding context-specific variables. Generative AI, the Nigerian team reasoned, is precisely the kind of technology that demands such an extension.

Unlike the relatively stable information systems of the pre-internet era, ChatGPT is interactive, adaptive, and demands active engagement. Users must craft effective prompts, critically evaluate AI-generated output for errors and bias, and integrate that output into academic work. The researchers therefore folded two additional constructs into the model. The first was awareness, drawn from Everett Rogers’s diffusion of innovations theory, which treats awareness as the opening stage of the innovation decision process: without knowing what a technology is and what it can do, people cannot form sensible judgments about its value. The second was perceived self-efficacy, rooted in Albert Bandura’s Self-Efficacy Theory, which captures a person’s confidence in their own ability to perform the tasks a technology requires. Crucially, self-efficacy is conceptually distinct from ease of use: the former is a judgment about the person, the latter about the system.

The analysis employed partial least squares structural equation modelling, a statistical technique well suited to exploratory models in emerging technology contexts, run in SmartPLS with bootstrapping on 10,000 subsamples. The sample skewed young and female: 57.28 percent of participants were women, and 88.26 percent were under 25 years old. The measurement scales, adapted from previously validated instruments and each measured with four items on five-point Likert scales, passed standard tests of reliability and validity, including factor loadings above the required threshold, satisfactory Cronbach’s alpha and composite reliability values, and convergent validity confirmed by average variance extracted figures exceeding the accepted minimum. Checks for common method bias, including Harman’s single-factor test and a full collinearity assessment, came back clean.

The results were dramatic. The extended model explained 81.6 percent of the variance in students’ attitudes toward ChatGPT and 80.1 percent of the variance in their intention to adopt it, figures the authors note are consistent with or higher than those reported in comparable studies elsewhere. Awareness emerged as the foundational driver, significantly boosting perceived usefulness, perceived ease of use, perceived self-efficacy, attitude, and intention alike. Its strongest single effect was on perceived ease of use, followed closely by self-efficacy and usefulness. Perceived usefulness significantly predicted both attitude and intention, and self-efficacy did the same, confirming that students who believed in their own capability to use ChatGPT effectively were markedly more positive about the tool and more determined to integrate it into their studies.

The surprise came with perceived ease of use. Although its path coefficients were positive, they failed to reach statistical significance for either attitude or intention. In other words, how easy students found ChatGPT to operate had no reliable bearing on whether they planned to use it. The authors offer a compelling explanation: for a generation of digitally fluent students, ease of use has become a baseline expectation rather than a differentiator. Moreover, the real challenge posed by ChatGPT is not technical but cognitive. The interface is simple; the harder skills involve formulating prompts, judging the reliability of outputs, and weaving AI content into rigorous academic work. Students, the study suggests, perceive the challenge of ChatGPT as skill-based rather than usability-based, which is precisely why self-efficacy, not ease of use, emerged as the significant determinant of adoption.

The study’s strongest single pathway ran from attitude to intention, with a path coefficient of 0.895. The authors caution that this very high value should be interpreted carefully, but they demonstrate that discriminant validity between the attitude and intention constructs held, with a heterotrait-monotrait ratio well within accepted bounds, meaning the effect is not an artifact of construct overlap. Notably, the finding challenges Davis’s original assertion that attitude is a weak predictor of intention, suggesting that for generative AI among technology-oriented students, attitudes function as a robust engine of adoption. It also aligns with prior work showing that as users grow familiar with AI and perceive its benefits, their attitudes shift from negative or merely instrumental to genuinely positive.

For educators and policymakers, the practical implications are pointed. Simply giving students access to generative AI tools may accomplish little if they lack the cognitive preparation to use them well. The authors argue that institutions should embed ChatGPT in structured learning activities that demonstrate its relevance to concrete marketing tasks, such as campaign development, while offering guided practice, prompt-design training, and explicit evaluation criteria to build student confidence. Clear ethical guidelines could reduce uncertainty and misuse. The authors also highlight that marketing students, as future shapers of consumer perceptions, may carry their attitudes toward AI well beyond the classroom, making mentoring and training in ethical and strategic AI use particularly consequential for this discipline.

The study has limits, as the authors acknowledge. It examined only final-year marketing students in a single country, limiting generalizability to other fields, levels, and national contexts, and its exclusively quantitative design cannot capture the texture of students’ lived experiences with the technology. Future work could test alternative frameworks such as the Unified Theory of Acceptance and Use of Technology, explore moderators like prior AI experience, digital literacy, or task complexity, and include the perspectives of administrators and policymakers. Still, the core message lands with force: in the age of generative AI, the decisive question is no longer whether a tool is easy to use, but whether people understand it and believe in their own ability to master it.

Subject of Research: Determinants of ChatGPT adoption among Nigerian undergraduate marketing students using an extended Technology Acceptance Model

Article Title: Extending the technology acceptance model with awareness and self-efficacy in predicting ChatGPT adoption among Nigerian marketing students

Article References: Agu, G., Obinna, E.-U. C., Okereafor, G. E., Omotosho, T. D., Chiana, C. A., Onyeokoro, S. C., Njoku, P. O., Okpara, G. S., & Margaça, C. (2026). Extending the technology acceptance model with awareness and self-efficacy in predicting ChatGPT adoption among Nigerian marketing students. Discover Education, 5(1), Article 1006. https://doi.org/10.1007/s44217-026-02152-y

Image Credits: AI Generated

DOI: 10.1007/s44217-026-02152-y

Keywords: ChatGPT, generative AI, technology acceptance model, self-efficacy, awareness, higher education, Nigeria, marketing students, PLS-SEM, AI adoption, perceived usefulness, educational technology

The study is built on the norm activation model, a well-established framework in environmental psychology that explains how prosocial and pro-environmental behavior emerges from a chain of psychological events. In its classic form, the model proposes that when individuals become aware of the negative consequences of not acting, and when they ascribe responsibility for those consequences to themselves, a personal moral norm is activated. This activated personal norm then drives behavioral intention. The model has been applied successfully to energy conservation, recycling, and green purchasing in many contexts, but it has rarely been tested in developing regions, where waste management infrastructure and cultural norms differ markedly from the wealthy countries where most of this research has historically been conducted.

Hidalgo-Crespo extends the model in a significant way. Beyond the core chain of awareness of consequences, ascription of responsibility, and personal norms, the study incorporates environmental consciousness as an upstream driver and adds subjective norms, the perceived social expectations of important others, drawn from the theory of reasoned action tradition. The extended model then predicts two distinct outcome variables: intentions to recycle and intentions toward green consumerism, meaning the willingness to purchase environmentally friendly products. By treating these two behaviors separately rather than lumping them together as a single pro-environmental intention, the study acknowledges that recycling a bottle and choosing a green product are psychologically different acts, shaped by different contextual pressures and different kinds of motivation.

The empirical foundation of the work is a cross-sectional survey of 1,198 respondents in Guayas Province, a coastal region of Ecuador that includes the country’s largest city, Guayaquil. Participants completed instruments measuring the Big Five personality traits, which are openness, conscientiousness, extraversion, agreeableness, and neuroticism, along with the constructs of the extended norm activation model and the two intention measures. The data were analyzed using partial least squares structural equation modeling, or PLS-SEM, a technique well suited to complex models with multiple constructs and pathways. To explore personality-based differences, the researcher applied cluster analysis, a statistical method that groups individuals according to their profiles across the five traits, and then used multigroup analysis to test whether the structural relationships in the model differed significantly between the resulting personality clusters.

The headline result is that personal norms and subjective norms emerge as significant predictors of both recycling intentions and green consumerism intentions. In other words, people intend to reduce waste when they feel a moral obligation to do so and when they perceive that the people around them expect such behavior. This dual pathway is important because it suggests that internal moral activation and external social expectation operate in parallel, each contributing independently to the intention to act. Environmental consciousness, meanwhile, was found to feed positively into awareness of consequences and ascription of responsibility, confirming its role as an upstream factor that primes the moral chain of the norm activation model. People who are more consciously attuned to environmental issues are more likely to recognize the harms of waste and to accept personal responsibility for preventing them.

Yet the most novel contribution of the study lies in what the multigroup analysis revealed. The strength and coherence of these normative pathways varied across the personality clusters identified in the sample. This means that the psychological mechanism linking, say, awareness of consequences to a personal norm, or a personal norm to a recycling intention, does not operate with the same force in everyone. For some personality profiles, the moral chain of the norm activation model appears tightly coupled, so that recognizing a problem reliably produces a sense of duty and then an intention to act. For others, the links are weaker or structured differently, revealing heterogeneous psychological mechanisms underlying what looks, from the outside, like the same pro-environmental attitude. Personality, in this framing, is not merely another predictor to add to a regression equation but a lens that refracts the entire motivational process.

The study also uncovered an asymmetry between the two behavioral outcomes. Recycling intentions appeared more strongly associated with contextual and situational factors than green consumerism intentions did. This makes intuitive sense once one considers the mechanics of the two behaviors. Recycling depends heavily on infrastructure: whether collection points exist, whether sorting systems are convenient, and whether the immediate environment makes the behavior easy or difficult. Green consumerism, by contrast, is a market-based choice that may be driven more by internal values and norms, since purchasing decisions are made within stores and online spaces where social and situational pressures differ. For waste policy in developing regions, this distinction matters, because investments in recycling infrastructure may yield returns that no amount of moral persuasion can match for that specific behavior.

The setting of the research gives these findings particular weight. Developing regions remain underrepresented in environmental psychology research, even as they confront rapidly growing waste streams and face some of the sharpest consequences of unsustainable consumption. Ecuador, like many Latin American countries, has been expanding recycling programs and environmental education initiatives, but the effectiveness of such programs depends on understanding what actually motivates citizens. By grounding the analysis in a large sample from Guayas Province, the study offers evidence that the theoretical machinery developed largely in Europe and North America can be meaningfully applied elsewhere, but only with careful attention to how personality and context reshape the motivational pathways in local populations.

The practical implications reach directly into the design of environmental communication campaigns. If personality clusters moderate the normative pathways to intention, then interventions could be tailored rather than universalized. A campaign emphasizing personal responsibility for consequences might resonate strongly with one cluster, while a campaign highlighting the expectations of family and community, thereby activating subjective norms, might work better for another. Personality-informed segmentation, long a staple of commercial marketing, could become a tool of environmental policy, allowing governments and NGOs to allocate their communication budgets more efficiently and to avoid the frustration of campaigns that consistently fail to move particular segments of the public. The study suggests that such differentiated strategies may support more effective waste reduction overall.

The research, which received no external funding and was conducted in accordance with internationally accepted ethical standards including written informed consent from all participants, ultimately delivers a message that extends well beyond waste management. Human behavior is the decisive variable in nearly every environmental challenge, from plastic pollution to climate change, and the models used to predict that behavior are increasingly sophisticated. This study pushes that sophistication one step further by insisting that the predictors themselves, the moral norms and social expectations that drive action, are filtered through stable individual differences in personality. Sustainability science, the findings imply, must come to terms with psychological heterogeneity, not as noise in the data, but as a fundamental feature of the human systems it seeks to change. In the effort to build greener societies, knowing who people are may be just as important as knowing what they believe.

Subject of Research: Psychosocial determinants of waste reduction intentions, including the norm activation model and Big Five personality effects, in Ecuador

Article Title: An extended norm activation model of waste reduction intentions with personality cluster effects

Article References: An extended norm activation model of waste reduction intentions with personality cluster effects. (n.d.). https://doi.org/10.1007/s43621-026-04624-5

Image Credits: AI Generated

DOI: 10.1007/s43621-026-04624-5

Keywords: waste reduction, norm activation model, recycling intentions, green consumerism, Big Five personality traits, cluster analysis, PLS-SEM, environmental psychology, Ecuador, subjective norms, personal norms, sustainable behavior

The research team, led by Tizita Derib Damtew of the Commercial Bank of Ethiopia and Girma Tadesse Gorfie of Wollo University, adopted a quantitative, explanatory design. They distributed standardized questionnaires measuring four constructs: perceived organizational support (POS), employee engagement (EE), organizational citizenship behaviour (OCB), and turnover intention. Each construct was rated on a five-point Likert scale, with items adapted from established instruments in the organizational psychology literature. From a target population of 301 employees across six purposively selected branches, a systematic random sampling procedure yielded 172 eligible respondents, of whom 157 returned fully completed questionnaires — a response rate of 91.3 percent.

To test the relationships among these variables, the researchers used partial least squares structural equation modelling (PLS-SEM), a statistical technique well suited to small samples and complex chains of mediation. Before running the structural analysis, the team verified that the measurement model was sound. All indicator loadings exceeded the recommended threshold of 0.708, and composite reliability scores for every construct — engagement, citizenship behavior, support, and turnover intention — were well above the 0.70 benchmark, confirming that the questionnaire items consistently measured what they were intended to measure. Discriminant validity checks using the Fornell-Larcker criterion and the heterotrait-monotrait ratio showed that the four constructs were statistically distinct rather than blurred together.

The structural results were dramatic. Perceived organizational support alone explained 50.4 percent of the variance in employee engagement and 30.5 percent of the variance in citizenship behavior. Together, the three predictors accounted for 64.5 percent of the variance in turnover intention — a remarkably high figure for behavioral research, where models explaining even half of an outcome are considered strong. The path from support to engagement was especially robust, with a standardized coefficient of 0.710, while the link between support and citizenship behavior reached 0.553. Both relationships were highly significant, with p-values below 0.001.

But the study’s most provocative finding concerns what did not work. The direct path from perceived organizational support to turnover intention was statistically insignificant, with a p-value of 0.983. In other words, simply feeling supported did not, by itself, reduce the urge to quit. Instead, the effect traveled entirely through the two mediators. When support raised engagement, turnover intention fell sharply (β = −0.383, t = 5.878); when support raised citizenship behavior, turnover intention also declined (β = −0.177, t = 3.800). This pattern constitutes what methodologists call full mediation: the indirect routes carry all of the explanatory power, and the direct route carries none.

The authors interpret this through two classic theoretical lenses. Social exchange theory holds that employees who receive favorable treatment feel an implicit obligation to reciprocate — and that reciprocity manifests as dedication and discretionary effort rather than as a simple decision to stay. The Job Demands-Resources model adds a complementary mechanism: in high-pressure environments like banking, organizational support functions as a job resource that buffers the psychological costs of heavy workloads, preventing the burnout that typically precedes resignation. The Ethiopian data suggest that these reciprocal and buffering processes must be activated — converted into engagement and citizenship — before they suppress withdrawal attitudes.

Why did the direct effect vanish in this context when many Western studies have found one? The researchers point to the economic realities of Ethiopian banking. Employees frequently cite dissatisfaction with compensation in the face of high living costs, limited opportunities for rapid career advancement, and poor work-life balance. A banker may feel that supervisors and the institution care about their well-being yet still intend to leave if baseline financial and professional needs go unmet. In such an environment, socio-emotional support alone is insufficient; it must be converted into engaged, invested performance before it changes retention outcomes. The finding underscores that models developed in high-income economies may not transfer cleanly to emerging-market settings.

The practical implications are concrete. The authors recommend that bank leadership formalize robust support systems: competitive compensation, transparent merit-based career tracks, structured reward programs, open feedback loops, and regular career development conversations that go beyond annual reviews. To cultivate citizenship behavior, they suggest shifting from purely competitive cultures toward cooperative ones — peer-recognition programs, cross-functional projects, team-building activities, and work-life balance initiatives that embed mutual assistance into institutional policy. Because commercial banking depends on customer service, teamwork, and proactive problem-solving, these investments in supportive human resource practices directly build the voluntary, extra-role behaviors that keep branches running efficiently.

The study also carries limitations that temper its conclusions. Its cross-sectional design captures a single moment in time and cannot establish strict causality; self-reported data may inflate or deflate responses; and the sample is drawn from one bank in one Ethiopian city, limiting generalizability to other industries or countries. The authors call for longitudinal and time-lagged studies, multi-source data combining employee surveys with objective records such as attendance logs and exit interviews, and comparative designs spanning healthcare, manufacturing, and technology sectors.

Even with those caveats, the message for managers is unusually clear and quantified. Feeling valued does not keep bankers in their seats by magic — it keeps them by first making them engaged and by drawing them into the social fabric of the organization through voluntary helping. Organizations that systematically build perceived support, the study concludes, effectively convert organizational backing into sustainable staff loyalty, lower attrition, and reduced hiring costs, advancing the broader goal of decent work in one of Africa’s most competitive banking markets.

Subject of Research: The mediating roles of employee engagement and organizational citizenship behaviour in the relationship between perceived organizational support and turnover intention among Ethiopian bank employees

Article Title: The nexus between perceived organizational support, employee engagement, organizational citizenship behaviours, and turnover intention in selected branches of the commercial bank of Ethiopia

Article References: Damtew, T. D., & Gorfie, G. T. (2026). The nexus between perceived organizational support, employee engagement, organizational citizenship behaviours, and turnover intention in selected branches of the commercial bank of Ethiopia. Discover Global Society, 4(1), Article 245. https://doi.org/10.1007/s44282-026-00589-y

Image Credits: AI Generated

DOI: 10.1007/s44282-026-00589-y

Keywords: perceived organizational support, employee engagement, organizational citizenship behaviour, turnover intention, Commercial Bank of Ethiopia, PLS-SEM, social exchange theory, job demands-resources model, employee retention, banking sector, Ethiopia, organizational psychology

The research team, led by Drini Imami of the Agricultural University of Tirana together with colleagues from the University of Prishtina, Rhine-Waal University of Applied Sciences, Weihenstephan-Triesdorf University of Applied Sciences and Corvinus University of Budapest, surveyed 183 farmers engaged in medicinal and aromatic plant production across Albania. Rather than simply cataloguing who had adopted which practice, the researchers applied a statistical technique known as partial least squares structural equation modeling, or PLS-SEM. This approach allows scientists to test an entire chain of hypothesized relationships simultaneously, linking farm characteristics to climate awareness, and climate awareness in turn to concrete adaptation behavior. It is a method well suited to questions where the underlying drivers, such as awareness or perceived risk, cannot be observed directly but must be inferred from multiple survey responses.

The results reveal a clear and consequential pathway. Farmers with higher levels of education and those who had acquired medicinal and aromatic plant-specific skills or training were significantly more likely to be aware of climate change and its potential consequences for their operations. That awareness, in turn, emerged as a strong predictor of adaptation. Farmers who recognized the climate threat were markedly more likely to adopt measures such as diversifying their crop portfolio, switching to certified seeds and seedlings, and adjusting the mix of plant varieties they cultivate. In statistical terms, awareness functions as a mediating variable: it translates external pressures and personal capabilities into deliberate on-farm change.

Farm size also mattered. Larger operations were more likely to implement adaptation measures, a pattern consistent with a well-documented dynamic in agricultural economics. Bigger farms typically command more land, labor and capital, and they can absorb the short-term costs and risks of trying something new, whether that means investing in certified planting material or experimenting with alternative species. Smaller holders, by contrast, often face resource constraints that make even low-cost adjustments difficult. The study’s authors point to this asymmetry as a warning sign: if adaptation is concentrated among better-endowed farms, climate change may widen existing inequalities within rural communities rather than simply imposing uniform losses.

Perceived climate impacts played a distinct role in the causal chain. Farmers who reported experiencing or observing climate-related damage, such as reduced yields or stressed plants, showed elevated awareness, and that awareness indirectly encouraged adaptation. This finding aligns with a growing body of international evidence suggesting that direct experience with climate extremes is one of the most powerful motivators of farmer response. Yet the Albanian data also imply that waiting for experience to accumulate is a risky strategy. By the time impacts are severe enough to register universally, the options for graceful adaptation may have narrowed considerably, particularly for perennial and wild-harvested species that cannot be replanted or relocated easily.

Perhaps the most striking number in the study is thirteen. Only 13 percent of the surveyed farmers reported receiving regular training related to their crop systems. For a sector that is export-oriented and ecologically delicate, this represents a substantial information and capacity gap. Medicinal and aromatic plants are not commodity grains; their market value depends heavily on quality standards, phytochemical profiles and compliance with certification requirements in destination markets. Climate change can alter essential oil content and terpene composition in these plants, meaning that both the agronomic and the commercial dimensions of production are climate-sensitive. Without structured extension services and training programs, most farmers are left to interpret a shifting environment on their own, relying on tradition and trial rather than science.

The export dimension sharpens the stakes considerably. Albania’s medicinal and aromatic plant sector supplies international buyers who demand consistent quality and traceable production. A climate-driven failure in this chain would not remain a local problem; it would ripple through value chains and into the livelihoods of the mountain households that depend on harvesting and cultivation. The study’s authors argue that strengthening extension services, improving access to farmer training, and easing resource constraints are essential for supporting adaptive land-use decisions. They call for targeted policy interventions that integrate advisory services, climate risk management, and improved access to land and finance, a package designed to enhance the resilience of both production systems and the rural livelihoods they sustain.

The Albanian case also resonates with a broader scientific conversation about medicinal plants and climate change. Researchers have documented climate-induced shifts in essential oil production and chemical composition in alpine aromatic species, and global assessments have warned that many medicinal plant species face range contractions and population declines as temperatures rise. In mountain regions from the Himalaya to the Balkans, these plants often occupy narrow ecological niches, which makes them particularly sensitive indicators of environmental change. When the farmers who cultivate or gather them lack access to climate information and adaptive resources, the risk is not only economic but also a quiet erosion of botanical knowledge and biodiversity that has accumulated over generations.

What makes the study methodologically notable is its use of structural equation modeling on a relatively modest sample, an approach that requires careful validation of the measurement instruments but yields insights that simple cross-tabulations cannot provide. By confirming that awareness mediates the relationship between education, training and adaptation, the analysis gives policymakers a concrete lever to pull. Investments in education and targeted training do not merely inform farmers; they measurably increase the likelihood of adaptive behavior. Conversely, policies that focus solely on subsidizing inputs or technologies, without building the underlying awareness and capacity, may fail to achieve durable change.

For Albania’s medicinal and aromatic plant farmers, the message of the research is ultimately one of conditional optimism. The adaptive pathway exists: awareness leads to action, and awareness can be built. But the current infrastructure supporting that pathway is thin, reaching roughly one farmer in eight with regular training. Closing that gap, the authors conclude, is not a luxury but a necessity for a sector whose products, markets and communities all sit on the front line of a changing climate. As climate pressures intensify across the Mediterranean and Balkan regions, the Albanian experience offers a replicable lesson: resilience in specialized agricultural systems begins not in the field, but in the flow of knowledge to the people who work it.

Subject of Research: Climate change awareness and adaptation strategies among medicinal and aromatic plant farmers in Albania

Article Title: Cultivating resilience: climate awareness and adaptation among Albanian medicinal and aromatic plant farmers

Article References: Imami, D., Miftari, I., Zhllima, E., van Bruggen-Wichern, J., & Darr, D. (2026). Cultivating resilience: climate awareness and adaptation among Albanian medicinal and aromatic plant farmers. Regional Environmental Change, 26(4), Article 202. https://doi.org/10.1007/s10113-026-02683-y

Image Credits: AI Generated

DOI: 10.1007/s10113-026-02683-y

Keywords: climate change adaptation, medicinal and aromatic plants, Albania, smallholder farmers, PLS-SEM, climate awareness, agricultural extension, rural livelihoods, crop diversification, export agriculture, mountain farming, farm training

The research, published in the open-access journal Heliyon, was conducted by JiSu Jang and Jihea Choi, who set out to understand how environmental, behavioral, and cognitive factors interact to shape parenting behavior in a generation redefining family roles. Drawing on Bandura’s social cognitive theory, the team modeled marital intimacy and household labor division as environmental and behavioral factors, parental efficacy as the cognitive factor, and parenting engagement as the behavioral outcome. The framework allowed them to test whether confidence acts as the psychological bridge between a supportive family environment and active participation in childcare.

The context is a society in rapid transition. Historically, Korean parenting was organized around rigid gender divisions, with fathers serving as economic providers and mothers as primary caregivers. That structure is eroding quickly. According to Statistics Korea, 72.8 percent of 20,000 surveyed adults rejected the idea that men should work while women stay home. The Ministry of Gender Equality and Family reported that agreement with the belief that mothers should primarily handle child-rearing fell from 53.8 percent in 2016 to 17.4 percent in 2021, while paternity leave utilization climbed from 1.9 percent in 2005 to 24.5 percent in 2020. Similar shifts toward egalitarian caregiving are visible across many OECD countries, making the Korean case part of a broader global reorganization of family life.

To capture these dynamics empirically, the researchers surveyed 210 parents in Wonju City—105 fathers and 105 mothers—aged 20 to 40, each raising a single child between 1 and 36 months old. Data were collected between March and May 2024 following approval from the Yonsei University Wonju Severance Christian Hospital Institutional Review Board. Participants completed validated questionnaires measuring marital intimacy, household labor division, parental efficacy, and parenting engagement, with all instruments showing strong internal consistency. The sample was highly educated—81 percent held bachelor’s degrees—and predominantly employed in office work, reflecting the profile of contemporary urban Korean parents.

Analysis relied on partial least squares structural equation modeling, a statistical technique well suited to estimating complex mediation and moderation pathways with minimal distributional assumptions. The measurement model passed rigorous validity checks, including indicator reliability, convergent validity via average variance extracted, and discriminant validity through heterotrait–monotrait ratios. The final structural model performed well, explaining 22.6 percent of the variance in parental efficacy and 41.4 percent of the variance in parenting engagement, with fit indices such as a standardized root mean square residual of 0.089 falling within acceptable bounds.

The path coefficients told a clear story. Marital intimacy strongly predicted parental efficacy (β = 0.407, p < 0.001), and household labor division also contributed positively (β = 0.194, p = 0.038). Yet the direct effect of marital intimacy on parenting engagement was not statistically significant, while household labor division showed only a modest direct effect. Parental efficacy, by contrast, was a powerful predictor of engagement (β = 0.545, p < 0.001) with a large effect size. Mediation analysis revealed that parental efficacy fully mediated the link between marital intimacy and engagement, accounting for 78.9 percent of the total effect, and partially mediated the link between household labor division and engagement, accounting for 36.1 percent.

The most provocative finding concerned gender. Parental role significantly moderated the relationship between household labor division and parental efficacy (β = −0.457, p = 0.001), and the direction of the association flipped between fathers and mothers. As the perceived fairness of household task division increased, parental efficacy rose among fathers—from a predicted 110.9 to 112.2 on the efficacy scale—but fell among mothers, from 105.4 to 103.7. In other words, the same behavioral condition carried opposite psychological meanings depending on which parent experienced it.

The authors interpret this divergence through the lens of persistent gendered expectations. For fathers, participating in household labor may represent an expansion of their caregiving role, reinforcing paternal identity, role satisfaction, and confidence. For mothers, an equitable division of labor may not confer the same psychological benefit; instead, it may be entangled with greater parenting-related burden and role stress, mechanisms the study did not directly measure but which previous research has linked to lower efficacy. The result suggests that behavioral equality can coexist with unequal cognitive and emotional experiences, echoing the concept of invisible labor—the unacknowledged mental and emotional workload that often continues to fall on mothers even in egalitarian households.

These dynamics may be especially pronounced among Millennial and Generation Z parents, whom the study treats as a single cohort shaped by a shared contemporary context rather than comparing them as separate generations. This group tends to construct parenting roles through negotiation and individual readiness rather than obligation, and their constant exposure to digital parenting information and social comparison environments amplifies the role of perceived competence. For some parents, abundant online resources build confidence; for others, they breed uncertainty and self-doubt. Either way, psychological readiness appears to outweigh structural equality in determining whether favorable conditions translate into engaged parenting.

The practical implications are significant. The findings suggest that interventions should prioritize building parental efficacy through mastery experiences, skill-based training, and supportive feedback, while couple-based programs that strengthen marital intimacy may indirectly boost engagement by reinforcing each partner’s confidence. Policy measures such as paternal leave and flexible work arrangements could support fathers’ involvement, but the authors caution that such policies must also address the visible and invisible burdens mothers carry, including emotional and cognitive labor. The study’s limitations—a cross-sectional design that precludes causal inference, self-reported measures vulnerable to social desirability bias, a single-city Korean sample, and a household labor measure based on only four items—warrant careful interpretation. Still, the core message resonates well beyond Korea: in the transition to egalitarian parenting, fairness in chores is only the beginning, and how parents feel about their own competence may ultimately decide how fully they show up for their children.

Subject of Research: Mediation and moderation effects of parental efficacy, marital intimacy, and household labor division on parenting engagement among Millennial and Generation Z parents

Article Title: Parenting engagement of Millennial and Generation Z parents in infant and toddler care: mediation and moderation effects

Article References: Jang, J., & Choi, J. (2026). Parenting engagement of Millennial and Generation Z parents in infant and toddler care: mediation and moderation effects. Heliyon, 12(15), Article e45443. https://doi.org/10.1016/j.heliyon.2026.e45443

Image Credits: AI Generated

DOI: 10.1016/j.heliyon.2026.e45443

Keywords: parenting engagement, parental efficacy, Millennial parents, Generation Z, household labor division, marital intimacy, South Korea, social cognitive theory, gender roles, infant care, PLS-SEM, invisible labor

The research, published in the journal Discover Sustainability, was conducted by Harimukti Wandebori, Anak Agung Ngurah Tata Pinandhika, and Bernadetta Nadya Amarani Sitompul of the School of Business and Management at Bandung Institute of Technology. Their starting point was a long-standing unresolved question in the sustainability literature: do the very capabilities that keep small firms viable in volatile markets also move them toward greener practices? Most previous studies could not answer this because they collapsed economic, social, and environmental performance into a single composite score, obscuring exactly the differences that matter most for policy and practice.

The team focused on strategic agility, a dynamic capability that combines two distinct components: market responsiveness, meaning the speed with which a firm detects and reacts to changes in customer needs, competitor moves, and emerging threats; and resource fluidity, meaning the ease with which money, people, and equipment can be redeployed across activities. They also modelled three separate channels through which agility might indirectly influence sustainability: managerial ties with buyers, ties with suppliers, and ties with government officials. Crucially, each channel was specified separately, and each of the three sustainability pillars was treated as a distinct outcome rather than blended into an index.

The survey gathered responses from 179 strategic decision makers in Indonesian micro and small enterprises. The measurement design showed unusual care for a survey study of this kind. Predictor and outcome blocks used deliberately differentiated response anchors so that, for example, economic performance was rated relative to competitors while environmental practices were rated on frequency of use. Two attention check items with prescribed answers were embedded at separate points, completion times were recorded automatically, and a marker variable built from questions about attitudes toward the colour blue allowed the researchers to test statistically whether common method bias was inflating their estimates. Analysis proceeded with partial least squares structural equation modelling, a technique suited to complex path models with modest samples.

The headline result was a clear asymmetry. Strategic agility predicted economic performance with a path coefficient of 0.409 and social performance with 0.365, both medium effect sizes, but environmental performance at only 0.218, roughly half the strength of the other two. Because the outcome scales used different anchors, the team checked the gap on scale-free metrics. On latent correlations, the environmental pillar separated from the economic pillar by 0.229 and from the social pillar by 0.196, with bootstrap intervals that excluded zero in both cases. On the metric of partial coefficients, only the separation from the economic pillar was statistically distinguishable, and the authors are explicit that their title claims only that contrast. The gap also passed a battery of robustness checks: the environmental block showed the lowest ceiling rate and the most symmetric response distribution of the three, which is the opposite of what a ceiling effect or social desirability bias would produce, and correcting for unequal reliability across blocks widened rather than narrowed the difference.

Perhaps the most sobering finding concerned prediction. The model achieved out-of-sample predictive relevance for the economic and social pillars, meaning the estimated structure genuinely anticipated new observations, but it achieved none for the environmental pillar. In other words, the capability-and-ties framework that works for explaining how small firms prosper and serve their communities simply does not contain enough signal to forecast their environmental behaviour. The indirect effect of agility on environmental performance through managerial ties was statistically equivalent to zero against a triviality bound of 0.10, tested with two one-sided tests on the bootstrap distribution.

The tie-based channels themselves fared almost entirely empty. Of the nine paths running from the three tie types to the three pillars, only one, buyer ties to social performance, reached significance at a coefficient of 0.193. The authors handle this carefully: one significant result out of nine tests is a count compatible with chance, and it does not survive correction for multiplicity. They report it as a pattern to be tested in future work rather than as an established mechanism, a level of statistical honesty that stands out in a literature where such a result might otherwise be presented as a discovery.

The study also probes what the gap means mechanistically, and here an item-level analysis delivers a subtle twist. One plausible explanation for weak environmental performance would be simple economics: environmental practices cost money without returning it, so agile firms invest where returns register. If pricing were the boundary, the one environmental practice that pays for itself, reducing waste and resource inefficiency, should attract agility’s influence more strongly than the two that do not. The item-level estimates ordered the three environmental items exactly as that reward-boundary argument predicts, but no within-block difference was statistically distinguishable. Pricing alone, therefore, is not the whole story; the boundary appears to lie in whether a firm’s existing routines register any return at all, and environmental returns rarely do for a small enterprise.

There is an important design caveat the authors state plainly: because a cross-sectional sample contains only surviving firms, the strong economic association is consistent with two competing accounts. Under a capability account, agility genuinely produces better economic outcomes; under a selection account, agile firms simply survive longer and therefore appear in the sample more often. The design cannot separate the two, and the researchers do not pretend otherwise. Nor could the study resolve whether the agility gap differs between resource-rich and resource-poor firms: multigroup comparisons across six operationalisations of resource endowment produced signs that flipped between splits and no significant differences, and a power analysis showed the observed differences all fell below the minimum the sample could detect.

The policy implication, the authors argue, follows directly from the pattern of results. If capability building alone does not reach the environmental pillar, because the returns from environmental practices are invisible to the routines that small firms already have, then progress will depend on instruments that make those returns visible and required: regulations that set minimum standards, incentives that convert environmental savings into financial ones, and market mechanisms that reward green practices through the buyers small firms already depend on. For the vast population of micro and small enterprises in emerging economies, the path to environmental sustainability is not a matter of becoming more agile. It is a matter of changing the payoffs the environment of business, rather than the natural one, currently provides.

Subject of Research: The relationship between strategic agility, managerial ties, and the three pillars of sustainability in Indonesian micro and small enterprises

Article Title: Strategic agility reaches the environmental pillar of small firm sustainability more weakly than the economic pillar: disaggregated evidence from Indonesian micro and small enterprises

Article References: Wandebori, H., Pinandhika, A. A. N. T., & Sitompul, B. N. A. (2026). Strategic agility reaches the environmental pillar of small firm sustainability more weakly than the economic pillar: disaggregated evidence from Indonesian micro and small enterprises. Discover Sustainability. https://doi.org/10.1007/s43621-026-04788-0

Image Credits: AI Generated

DOI: 10.1007/s43621-026-04788-0

Keywords: strategic agility, small and medium enterprises, sustainability, triple bottom line, environmental performance, managerial ties, Indonesia, PLS-SEM, dynamic capabilities, emerging economy, green practices, business strategy

The research, led by Hung-Che Wu of Universitas Brawijaya together with Waseem Ul Hameed, Yi-Chang Chen, Raditha Hapsari, and Ananda Sabil Hussein, set out to solve a persistent measurement problem. As artificial intelligence has spread across retail, hotels, banks, and customer service, researchers have struggled to define and quantify what customers actually experience when they move seamlessly between digital and physical channels powered by AI, a setup known as omnichannel service. Without a validated scale, businesses have been essentially flying blind, unable to tell which elements of their AI systems build loyalty and which merely add friction.

To build their measurement instrument, the team followed the rigorous scale-development paradigm first established by marketing researcher Gilbert Churchill in 1979, a multi-stage process that involves generating candidate items from theory and prior literature, purifying them through successive statistical tests, and validating the final structure on independent samples. The researchers collected data from a convenience sample of 496 consumers at an intelligent unmanned store in Beijing, a setting chosen because it compresses the entire omnichannel journey, from app-based entry to computer-vision checkout, into a single visit. The project received ethics approval from the Ethics Committee of Universitas Brawijaya, and the authors report no conflicts of interest and no external funding.

The analytical backbone of the study was partial least squares structural equation modeling, or PLS-SEM, a statistical technique widely used when researchers need to test networks of relationships among abstract psychological constructs that cannot be observed directly. The team assessed the reliability and validity of their measurement scales using established benchmarks, including the Fornell-Larcker criterion and the heterotrait-monotrait ratio developed by Henseler and colleagues, and they checked for common method bias using the full collinearity assessment approach. Confirmatory composite analysis, a newer model-quality test championed by Hair and colleagues in 2020, was also part of the validation toolkit.

What emerged from this statistical machinery was a multidimensional picture of the omnichannel AI experience. The findings contribute to services marketing theory by clarifying the dimensional structure of four interlocking constructs: omnichannel AI experiences themselves, AI experiential relationship quality, AI experiential evaluation cost, and AI experiential engagement intentions. In plain language, the researchers argue that when customers interact with AI across channels, they form a quality judgment about their relationship with the technology, weigh the mental effort required to evaluate it, and only then decide how deeply they want to engage with it in the future.

The chain of relationships the data revealed is as elegant as it is practical. Omnichannel AI experiences were positively associated with AI experiential relationship quality, meaning that smoother, richer, more consistent AI-powered interactions make customers feel a stronger bond with the service. That relationship quality, in turn, positively influenced both AI experiential evaluation cost and AI experiential engagement intentions. The link between relationship quality and evaluation cost may seem counterintuitive at first glance, but it echoes a classic finding from social psychology: Aronson and Mills showed as far back as 1959 that people who invest effort in a relationship tend to value it more. When customers feel connected to an AI service, they appear willing to expend more cognitive effort evaluating and exploring it, treating that effort as an investment rather than a burden.

This effort-based interpretation draws on a long line of consumer research into switching costs and evaluation costs. Building on Hauser and Wernerfelt’s influential evaluation cost model of consideration sets from 1990, the study treats the mental energy customers spend comparing and judging AI services as a real psychological currency. The practical implication is striking: a customer who has built a strong experiential relationship with an AI system is more tolerant of the effort required to use it, and that tolerance feeds directly into stronger engagement intentions, the willingness to keep using, exploring, and advocating for the service.

For the booming unmanned retail industry, the study arrives at a critical moment. Market analysts project substantial global growth for fully automated and semi-automated stores over the coming decade, particularly in Asia where the format is most mature. Yet the sector’s biggest challenge is not technology but psychology: customers who feel frustrated, confused, or impersonally processed by machines simply do not return. The researchers’ results suggest that enhancing omnichannel AI experiences, strengthening AI experiential relationship quality, and effectively managing AI experiential evaluation cost are promising strategies for fostering stronger engagement in unmanned retail environments. In other words, the path to loyalty runs through making the AI feel like a reliable partner rather than a cold interface.

The study also connects to a broader scientific conversation about how humans relate to intelligent machines. Prior research has shown that anthropomorphism, empathy responses, and interaction quality shape trust in AI, and that AI service quality feeds into customer experience and brand relationships. By formalizing the omnichannel AI experience as a validated multidimensional construct and mapping its downstream consequences, the new work gives researchers a standardized tool for comparing findings across industries and cultures. It also extends the experiential relationship quality framework that Wu and collaborators have previously applied to smart hotels, driverless buses, and pet-friendly medical tourism, demonstrating its versatility in contexts where human staff are absent entirely.

Limitations remain, as they do in any single-sample study. The data came from consumers at one intelligent unmanned store in Beijing using a convenience sampling approach, so generalizing to other markets, store formats, or cultural settings will require further testing. The cross-sectional design captures intentions rather than observed long-term behavior. Still, the contribution is substantial: the scale offers retailers, technologists, and psychologists a shared language for measuring the invisible glue between shoppers and the machines that serve them. As unmanned stores multiply worldwide, the study’s central message is likely to resonate far beyond Beijing, that the future of retail loyalty will be decided not by the sophistication of artificial intelligence alone, but by the quality of the relationship customers feel they have built with it.

Subject of Research: Validation of a multidimensional scale measuring how omnichannel AI experiences influence customer relationship quality and engagement intentions in unmanned retail

Article Title: Omnichannel AI experience and engagement intentions: validation of a multidimensional scale

Article References: Wu, H.-C., Hameed, W. U., Chen, Y.-C., Hapsari, R., & Hussein, A. S. (2026). Omnichannel AI experience and engagement intentions: validation of a multidimensional scale. Current Psychology, 45(18), Article 1531. https://doi.org/10.1007/s12144-026-10069-w

Image Credits: AI Generated

DOI: 10.1007/s12144-026-10069-w

Keywords: omnichannel AI, artificial intelligence, unmanned stores, consumer behavior, customer engagement, relationship quality, retail technology, scale validation, services marketing, PLS-SEM, evaluation cost, Beijing

At the center of the study is a proposed theoretical model the authors call EHBTAUT, which fuses three established pillars of behavioral science into a single architecture. The first is the eHealth context itself, encompassing how people orient themselves toward health information online. The second is the Health Belief Model, a classic framework that explains health behavior through perceptions of susceptibility, severity, benefits, and barriers. The third is the Unified Theory of Acceptance and Use of Technology 2, or UTAUT2, which captures how performance expectations, effort expectations, social influence, hedonic motivation, and habit shape whether people adopt a given technology. By weaving these together, the model allows the researchers to test, in a single integrated structure, how health beliefs and technology acceptance forces interact to produce actual behavioral intention and real utilization of eHealth services.

The empirical backbone of the work is substantial. The team collected two rounds of primary questionnaire data from young adults between the ages of 18 and 30, ultimately yielding 1,432 valid responses. Participants were assessed on a battery of constructs including health information orientation, online health behavior, eHealth literacy, social interaction needs, internet self-efficacy, and patterns of internet and social media use. The choice of age group was deliberate: young adults are the most digitally fluent generation, and if eHealth platforms are failing to capture them, the problem lies not in access to technology but in how these platforms are designed and communicated. Previous work by some of the same authors had already suggested that social media serves as a key gateway to health information for 18-to-30-year-old college students, making this cohort an ideal proving ground for testing a model of digital health engagement.

Methodologically, the study goes beyond the standard partial least squares structural equation modeling that dominates information systems research. The authors combined PLS-SEM with a probabilistic neural network, a hybrid approach the team labels PLS-PNN. Structural equation modeling identifies the strength and significance of the pathways connecting constructs, while the probabilistic neural network, a technique first formalized by Donald Specht in 1990, captures nonlinear classification patterns in the data that linear path models can miss. This combination reflects a growing movement in business research toward pairing interpretable statistical models with machine learning algorithms to boost predictive accuracy without sacrificing theoretical insight. To guard against fragile findings, the researchers supplemented their analysis with Monte Carlo simulation, repeatedly resampling and perturbing the data to confirm that the estimated relationships remained stable under uncertainty rather than emerging as artifacts of a single dataset.

The findings converge on a clear message: the desire for social interaction and the orientation toward health information are not peripheral factors but central engines of eHealth adoption. Health information-seeking motivations and internet-based information exchange, the study concludes, significantly shape healthcare information design. In practical terms, this means that a platform’s functionality must align with what its target audience actually expects and needs. A young adult who turns to Instagram or TikTok for health content does so partly for information and partly for the social texture surrounding it: comments, shares, peer validation, and community. An eHealth application that ignores this social dimension, offering only a sterile transactional interface, is fighting against the very motivations that bring people online in the first place. Conversely, platforms that weave in interaction opportunities can convert passive browsers into active users.

The study also gives weight to constructs that many commercial health apps undervalue. Internet self-efficacy, the confidence a person feels in their ability to navigate online environments, emerged as a meaningful contributor to acceptance, echoing earlier findings from online education research where interaction and self-efficacy predicted satisfaction. eHealth literacy, the capacity to find, appraise, and apply health information from electronic sources, similarly conditions whether digital health content translates into health action. These findings carry a pointed implication for health equity: populations with lower digital confidence or lower eHealth literacy may be systematically excluded from the benefits of digital health unless platforms are deliberately designed to lower those barriers, through simpler interfaces, clearer guidance, and built-in support.

What distinguishes this research from most survey-based studies is its final phase: an application-oriented demonstration. Rather than leaving the empirically supported mechanisms on paper, the team translated them into an iOS-based eHealth application and evaluated its practical relevance with 90 young adult participants. This design-to-validation loop is rare in information systems scholarship and gives the findings a concrete product dimension. It demonstrates that constructs measured in a questionnaire can be operationalized as design features, such as social interaction affordances and information architecture calibrated to user information needs, and that the resulting application resonates with the intended audience. For healthcare providers and technology firms, this offers a template for evidence-based product development in the digital health space.

The broader stakes are considerable. The eHealth market, spanning telemedicine, health information systems, mobile health, and e-pharmacy, has been projected to grow dramatically through 2030, and healthcare systems worldwide face chronic pressure on resources. The study’s framing of eHealth communication as a lever for the efficient utilization of healthcare resources highlights the practical payoff: when patients use digital tools effectively, they can make better-informed decisions, reduce unnecessary visits, and engage in preventive behavior, easing strain on overloaded systems. At the same time, the research implicitly acknowledges the darker currents of the online health ecosystem, including the infodemic of health misinformation that surged during the COVID-19 pandemic and the privacy concerns that shape acceptance of smart health technologies. Building platforms around verified information needs and genuine social interaction may be one of the most effective counters to misinformation, since trusted, well-designed channels can crowd out less reliable sources.

For the designers of the next generation of health applications, the study’s recipe is deceptively simple: start with the user’s information orientation and social needs, build confidence through ease of use and literacy support, and let health beliefs and technology acceptance theory guide the messaging. The researchers, whose work was approved by an Institutional Review Board and who report no competing financial interests, have made their data and materials available from the corresponding author upon request. As healthcare continues its migration to screens of every size, this research offers both a diagnostic of why adoption has lagged among the most connected generation and a validated blueprint for closing the gap between the digital health systems institutions build and the digital health behaviors people actually practice.

Subject of Research: Factors driving eHealth adoption and communication effectiveness among young adults

Article Title: Toward Effective eHealth Communication for Efficient Utilization of Healthcare Resources: A Social Interaction and Information Needs Perspective

Article References: Wang, Y., Prybutok, G., Gulzari, A., Peng, X., Prybutok, V., Lu, Y., & Cheng, F. (2026). Toward Effective eHealth Communication for Efficient Utilization of Healthcare Resources: A Social Interaction and Information Needs Perspective. Information Systems Frontiers. https://doi.org/10.1007/s10796-026-10819-y

Image Credits: AI Generated

DOI: 10.1007/s10796-026-10819-y

Keywords: eHealth, health communication, UTAUT2, Health Belief Model, eHealth literacy, social interaction, internet self-efficacy, PLS-SEM, probabilistic neural network, Monte Carlo simulation, healthcare platforms, young adults

The OCOP program, inspired by Japan’s One Village One Product and Thailand’s One Tambon One Product movements, has become a cornerstone of Vietnam’s rural development policy, designed to restructure the agricultural sector and strengthen the competitiveness of small and medium-sized enterprises in the countryside. Yet the program has a documented weakness: product lines are frequently undifferentiated, innovation rates remain low, and firms struggle to sustain a competitive presence beyond their local markets. That gap between institutional ambition and firm-level performance is precisely what motivated Huynh Nguyen Tuong An, Nguyen Quoc Cuong, and Nguyen Ngoc Thuc of the Industrial University of Ho Chi Minh City to investigate what actually drives product innovation among these enterprises.

The theoretical scaffolding of the study draws on three established frameworks. Entrepreneurial Orientation Theory, developed by Lumpkin and Dess and rooted in earlier work by Danny Miller, describes a firm’s strategic posture through three dimensions: innovativeness, the tendency to generate and pursue new ideas; proactiveness, the drive to anticipate and seize market opportunities before competitors; and risk-taking, the willingness to commit resources to ventures with uncertain outcomes. Dynamic Capabilities Theory, proposed by Teece and colleagues, explains how firms sense opportunities and reconfigure internal resources to adapt to rapid environmental change. Institutional Theory, meanwhile, emphasizes that formal structures such as government programs, regulations, and policy incentives shape organizational behavior, particularly in transition economies where firms operate under constraints that differ fundamentally from those in developed markets.

What makes the study methodologically distinctive is its unified model. Rather than treating business model innovation and technology capability as separate curiosities, the researchers positioned them as co-mediators, two parallel conduits through which entrepreneurial orientation flows into product outcomes. Business model innovation, defined by Foss and Saebi as a designed, novel change to the key elements of how a firm creates, delivers, and captures value, operates at the level of business logic. Technology capability, the ability to acquire, assimilate, and deploy technology, operates at the level of technical execution. On top of this dual mediation, the researchers layered a moderator: perceived institutional support, the degree to which firms believe government assistance, policy incentives, and program support are genuinely available to them.

To test this architecture, the team applied partial least squares structural equation modeling using SmartPLS software on survey data collected between May and October 2025. Respondents were owners, managers, and senior staff of OCOP enterprises across major provinces of Vietnam’s Southeast region, selected through purposive sampling because no comprehensive public registry of these firms exists. Of 500 initial responses, 480 survived data screening after incomplete or uniform questionnaires were removed, a sample size that comfortably exceeds both the ten-times rule minimum of 258 and the 138 participants required by an a priori power analysis conducted in G*Power. All constructs were measured on five-point Likert scales adapted from validated instruments, including Covin and Slevin’s entrepreneurial orientation scale, Clauss’s business model innovation measure, and Frishammar and Hörte’s new product development performance items.

The statistical rigor extended well beyond the basics. The measurement model showed all outer loadings above 0.70, composite reliability values surpassing 0.70, and average variance extracted above 0.50, while heterotrait-monotrait ratios confirmed that the constructs were empirically distinct. Common method bias, a chronic concern in self-reported cross-sectional surveys, was addressed both procedurally, through respondent anonymity, separated questionnaire sections, and pilot testing with 40 respondents, and statistically, through Harman’s single-factor test, which found the first factor accounted for only 33.028 percent of variance, and full collinearity assessment, in which all variance inflation factors fell below the 3.3 threshold. The model explained 52.2 percent of the variance in new product development performance, with Stone-Geisser Q-squared values confirming medium-to-strong predictive relevance.

The headline result is a striking asymmetry among the three entrepreneurial traits. Proactiveness and risk-taking each exerted a direct, statistically significant positive effect on new product development performance, while innovativeness failed to reach significance in the direct path. Yet innovativeness was far from irrelevant: all six indirect pathways through business model innovation and technology capability were significant at the 0.1 percent level, indicating that creativity works only when it is embedded in reconfigured value architectures and strengthened technical foundations. For proactiveness and risk-taking, both direct and indirect effects were significant, marking business model innovation and technology capability as partial mediators. Business model innovation emerged as the single most influential driver of product performance, with a medium effect size, while the effect sizes of innovativeness and institutional support on the outcome were negligible in the direct paths.

The moderating analysis added a further nuance. Perceived institutional support significantly amplified the effects of both innovativeness and proactiveness on product performance, with 95 percent bootstrapped confidence intervals excluding zero, and simple slope analysis showed the innovativeness-performance slope turning from negligible to strongly positive as institutional support rose. But the same amplification did not hold for risk-taking: although the interaction coefficient was positive, its confidence interval included zero, meaning the moderation was not supported at the conventional level. The authors interpret this as evidence that star-rating promotion standards and market access support do not sufficiently reduce the uncertainty firms face when committing resources to genuinely uncertain product development bets. In other words, government support helps firms be creative and seize opportunities, but it does not yet insure them against the downside of bold bets.

The practical implications ripple outward from the rice paddies and workshops of Dong Nai, Tay Ninh, and Binh Phuoc to the broader debate on innovation in emerging economies. Successful OCOP firms, the study shows, tend to restructure their business models through multi-platform sales channels, e-commerce applications, livestream commerce, and agricultural experience tourism, while investing in preservation technology, deep processing, and automation to improve quality, extend product life cycles, and shorten commercialization timelines. For managers, the message is that entrepreneurial orientation alone is a necessary but insufficient condition; it must be paired with deliberate business model reconfiguration and technology investment. For policymakers, the findings argue for transparent, accessible support systems, financial incentives, innovation management training, and digital transformation assistance that convert perceived support into real innovation capacity. The authors caution that the cross-sectional design precludes causal inference, the single-region sample limits generalizability, and self-reported measures introduce potential bias, calling for longitudinal and multi-source replication. Still, in a program meant to lift rural livelihoods toward the United Nations Sustainable Development Goals, the lesson is clear: in Vietnam’s countryside, boldness and foresight pay, but only when creativity is given the organizational machinery to become a product.

Subject of Research: How entrepreneurial orientation dimensions affect new product development performance among OCOP enterprises in Vietnam, with business model innovation and technology capability as mediators and perceived institutional support as a moderator.

Article Title: Investigating the relationship between entrepreneurial orientation and new product development performance

Article References: An, H. N. T., Cuong, N. Q., & Thuc, N. N. (2026). Investigating the relationship between entrepreneurial orientation and new product development performance. Discover Global Society, 4(1), Article 247. https://doi.org/10.1007/s44282-026-00605-1

Image Credits: AI Generated

DOI: 10.1007/s44282-026-00605-1

Keywords: entrepreneurial orientation, new product development performance, business model innovation, technology capability, perceived institutional support, OCOP enterprises, Vietnam, SMEs, PLS-SEM, dynamic capabilities, institutional theory, rural development

The research, conducted by Salem Handhal Al Marri of the Applied College at King Faisal University in Hofuf, Alahsa, examines how perceived entrepreneurial support influences entrepreneurial readiness among university students in Saudi Arabia. The study was supported by the Deanship of Scientific Research at King Faisal University and received approval from the university’s ethical committee, with informed consent obtained from all participants. Drawing on institutional theory, the work positions universities and policy frameworks not merely as background conditions but as active institutional forces that shape how students think about their professional futures.

Entrepreneurial readiness is a concept distinct from the entrepreneurial intention that has dominated prior scholarship. While intention captures whether someone wants to start a business, readiness describes whether that person is prepared to translate that desire into potential action. The distinction matters practically: a student may sincerely intend to become an entrepreneur yet lack the confidence, preparedness, and orientation needed to act on that intention. Existing research has focused predominantly on intention, leaving comparatively limited attention to the institutional and psychological mechanisms that shape readiness, a gap that is particularly evident in the Saudi context, where entrepreneurship has taken on heightened importance within the country’s economic transformation agenda.

To probe these mechanisms, the study surveyed 200 university students and applied Partial Least Squares Structural Equation Modeling, a statistical technique widely used in management and entrepreneurship research to test relationships among latent constructs and to examine mediating pathways simultaneously. This methodological choice allowed the researcher to evaluate not only whether perceived entrepreneurial support strengthens readiness directly, but also whether two proposed psychological mediators, entrepreneurial career attractiveness and preference for self-employment, carry that influence forward.

The findings are nuanced. On the direct side, perceived entrepreneurial support proved powerful across the board: it strengthened entrepreneurial career attractiveness, strengthened preference for self-employment, and strengthened entrepreneurial readiness. In other words, when students perceive that their environment offers meaningful entrepreneurial support, through university programs, institutional backing, and policy signals, they report feeling more ready to pursue entrepreneurship, view entrepreneurial careers more favorably, and lean more strongly toward working for themselves.

But the mediated pathways revealed an important asymmetry. Preference for self-employment significantly contributed to entrepreneurial readiness and significantly mediated the relationship between perceived support and readiness. Entrepreneurial career attractiveness, by contrast, did not significantly predict readiness and did not provide a significant mediating pathway. Making entrepreneurship look attractive, in other words, is not enough to make students feel ready to pursue it. The translation of institutional support into psychological preparedness appears to depend on something deeper: whether students genuinely prefer self-employment as a mode of working, a preference that entails confidence in one’s own capacity and an orientation toward independence rather than conventional employment.

This asymmetry carries real theoretical weight. The study extends institutional theory by demonstrating that institutional support is translated into entrepreneurial readiness not simply by making entrepreneurship appear attractive, but more importantly by strengthening students’ preference for self-employment. Institutional signals, according to this account, do their deepest work when they reshape what students want for themselves, not merely how appealing a career option looks from the outside. That reframing challenges a common assumption in entrepreneurship education, where promotional campaigns often emphasize the glamour and opportunity of startup life without cultivating the underlying disposition toward self-directed work.

The practical implications follow directly from the findings. Policymakers and universities, the study suggests, should move beyond promoting entrepreneurship as an appealing career and place greater emphasis on institutional mechanisms that develop students’ confidence, preparedness, and orientation toward self-employment. Concretely, that points toward interventions that build self-efficacy, provide hands-on preparation for the realities of running a venture, and normalize self-employment as a legitimate and attainable professional identity. Such interventions, the research argues, can strengthen university-based entrepreneurial ecosystems, which in turn contribute to youth employment, economic diversification, and sustainable development in Saudi Arabia, all priorities embedded in the kingdom’s broader transformation agenda.

The study also sits at the intersection of several research streams, including career counseling, industrial psychology, entrepreneurial finance, and professional and vocational education, and it engages questions of self-efficacy that have long been central to entrepreneurship scholarship. By simultaneously examining entrepreneurial career attractiveness and preference for self-employment as potential pathways, it fills a specific empirical gap: limited prior research had treated these two constructs as parallel mediators, and the results show that doing so yields a more discriminating picture of how support actually operates. A construct that looks superficially similar to self-employment preference, the appeal of an entrepreneurial career, turns out to behave very differently in the statistical model.

For Saudi Arabia, where a young population and an ambitious diversification agenda converge, the findings arrive at a consequential moment. Universities are expanding entrepreneurship offerings, and government initiatives have elevated self-employment as a national priority. This research suggests that the effectiveness of those investments will hinge less on how entrepreneurship is marketed and more on how deeply institutional support reshapes students’ working preferences. If the goal is a generation of students who are genuinely ready to act on entrepreneurial aspirations, the study’s message is clear: build the preference first, and readiness will follow.

Subject of Research: How perceived entrepreneurial support enhances entrepreneurial readiness among Saudi university students through career attractiveness and self-employment preference

Article Title: The roles of perceived support, career attractiveness, and self-employment preference in enhancing entrepreneurial readiness

Article References: Al Marri, S. H. (2026). The roles of perceived support, career attractiveness, and self-employment preference in enhancing entrepreneurial readiness. Discover Sustainability. https://doi.org/10.1007/s43621-026-04660-1

Image Credits: AI Generated

DOI: 10.1007/s43621-026-04660-1

Keywords: entrepreneurial readiness, perceived entrepreneurial support, self-employment preference, career attractiveness, Saudi Arabia, university students, institutional theory, PLS-SEM, entrepreneurship education, youth employment, economic diversification, King Faisal University