The researchers set out to fill a conspicuous gap. Big data analytics capability, often abbreviated as BDAC in the management literature, has been studied extensively in business contexts, where firms that can harness analytics are repeatedly shown to outperform rivals in innovation, marketing agility and risk management. Yet the political sphere, especially in African democracies, has remained largely unexamined territory. The authors note that while data-driven campaigning is well established in advanced democracies, its dynamics in developing democracies have gone largely unexplored, despite the fact that political parties in countries such as Ghana face many of the same pressures to modernize that transformed corporate marketing a decade earlier.

To build their theoretical scaffolding, the team drew on Institutional Theory, a framework that explains how organizations adopt structures and practices in response to pressures from their environment, whether coercive rules, normative expectations or the mimetic pull of copying successful peers. Applied to politics, the theory suggests that parties do not adopt analytics in a vacuum; they respond to institutional pressures, including the visible successes of digitally sophisticated competitors and the growing expectation that campaigns will be professional, responsive and technologically current. This framing allowed the researchers to treat analytics capability not merely as a technical resource but as an organizational adaptation shaped by the political ecosystem in which a party operates.

The study employed an explanatory research design, gathering data from 331 political campaign actors in Ghana through a structured questionnaire. Ghana makes a compelling laboratory for this kind of inquiry. The country’s Fourth Republic has held successive competitive elections, its parties operate within a vibrant media environment, and its recent campaigns have increasingly migrated onto social media platforms where digital engagement and data collection intersect. The researchers then analysed the survey data using Partial Least Squares Structural Equation Modelling, or PLS-SEM, a statistical technique well suited to testing networks of hypothesized relationships among latent constructs that cannot be directly observed, such as analytical capability or voter engagement. The method estimates both the measurement model, which checks that survey items reliably capture the underlying concepts, and the structural model, which tests the paths connecting them.

The headline findings are straightforward. Big data analytics capability showed a significant positive association with both voter engagement and political campaign performance. In other words, campaign organizations with stronger analytical capacity tended to report more engaged voters and better campaign outcomes. Voter engagement itself was also positively associated with campaign performance, confirming the intuitive chain in which analytics helps a campaign connect with citizens, and that connection in turn supports electoral success. For the authors, these results extend Institutional Theory into the political arena and provide empirical evidence from a developing democracy, a context where the mechanisms linking technology to political effectiveness have rarely been quantified.

But the study’s most interesting results lie in what did not hold. The researchers hypothesized that voter engagement would mediate the relationship between analytics capability and campaign performance, meaning that analytics would improve performance primarily by energizing voters. The data did not support this. Voter engagement did not significantly mediate the BDAC-performance relationship, suggesting that analytics capability may improve campaign performance through channels other than voter enthusiasm, such as better resource allocation, sharper targeting of messages, or more efficient ground operations. This null result is a useful corrective to the popular narrative that data-driven politics works mainly by micro-targeting persuasive content at individual voters. The Ghanaian evidence hints that the operational advantages of analytics may matter at least as much as its persuasive ones.

The second moderating variable, digital opportunism, produced a similarly nuanced picture. Digital opportunism refers to an organization’s propensity to sense and seize emerging opportunities in digital environments, whether new platforms, viral moments or shifting online conversations. The study found that digital opportunism strengthens the relationship between big data analytics capability and voter engagement. A campaign that can both analyze data and act quickly on digital openings appears to convert its analytical capability into genuine voter connection more effectively than one that merely crunches numbers. However, digital opportunism did not moderate the other paths in the model, including the link between analytics and campaign performance itself. The opportunity-sensing mindset, in other words, amplifies the engagement side of the equation but does not change how analytics translates directly into performance.

These findings carry practical weight for political strategists, particularly in emerging democracies where campaign budgets are constrained and every investment must be justified. The results suggest that building analytics capability, encompassing the technology, the skilled personnel and the management processes needed to turn raw data into decisions, is associated with better campaign outcomes. But they also suggest that analytics alone is not a silver bullet. Campaigns that want to deepen voter engagement should pair their analytical investments with a culture of digital opportunism, staying alert to the fast-moving rhythms of online political conversation. And campaigns expecting engagement to be the sole bridge between data and victory may need to look elsewhere, since the study found no significant mediating role for engagement in that relationship.

The research also speaks to a broader scholarly conversation about the digital transformation of democratic politics. Scholars have documented how social media reshape political participation, how platform affordances alter the ways citizens engage with campaigns, and how data-driven campaigning has evolved into a systematic field of study in Western democracies. By testing these ideas in Ghana, the study joins a growing body of work examining how digital tools function in contexts with different institutional arrangements, media ecosystems and levels of connectivity. The authors argue that extending Institutional Theory into the political sphere in this way advances theoretical understanding while offering actionable insights for practitioners, a dual contribution that reflects the study’s position at the intersection of information systems research and political science.

The study was reviewed and approved by the Ghana Communication Technology University Research Ethics Committee, with voluntary participation and written informed consent from all respondents, and the authors declare no funding or conflicts of interest. Like all survey-based research, it has limits that readers should keep in mind: the data capture the perceptions of campaign actors at a single point in time, and associations identified through structural equation modelling do not by themselves prove causation. Even so, the message is timely. As elections across Africa and the wider developing world become increasingly digital contests, the question is no longer whether campaigns will adopt big data analytics but how they will do so effectively. This study suggests that the answer lies not in technology alone, but in the combination of analytical capability, an opportunistic digital culture and a clear-eyed understanding of which pathways actually lead from data to votes.

Subject of Research: The association between big data analytics capability and political campaign performance in Ghana

Article Title: Unveiling the association between big data analytics capability and political campaign performance: the role of voter engagement and digital opportunism

Article References: Kissi, P. S., Brako, I., & Gyabaah, O. (2026). Unveiling the association between big data analytics capability and political campaign performance: the role of voter engagement and digital opportunism. SN Social Sciences, 6(9), Article 433. https://doi.org/10.1007/s43545-026-01734-9

Image Credits: AI Generated

DOI: 10.1007/s43545-026-01734-9

Keywords: big data analytics, political campaigns, voter engagement, digital opportunism, Ghana, PLS-SEM, Institutional Theory, political communication, developing democracies, campaign performance, social media, political marketing

The study, conducted in 2025 using purposive sampling, was led by Saad Faraj Alenzi and Ahmad Tawalbeh of Gulf University in Bahrain, together with Ferhat Yilmaz and colleagues at St. Petersburg State University. Rather than treating AI adoption as a single event—a switch flipped at one moment—the team proposed what they call a Barrier–Enabler Ecosystem Model. The framework integrates three established theories: the Technology Acceptance Model, which explains how perceived usefulness and ease of use shape individual decisions; Digital Divide Theory, which describes how access to motivation, material resources, skills, and usage opportunities is unevenly distributed; and Institutional Theory, which captures the coercive, mimetic, and normative pressures that organizations and their members feel from regulation, peer behavior, and professional norms. The model treats barriers and enablers not as two separate lists but as opposing valences of the same underlying dimensions—cost is a barrier when tools are expensive and a facilitator when they are affordable, for example.

Saudi Arabia makes an unusually revealing setting for this kind of analysis. Under Vision 2030, the Kingdom has pursued an explicit, state-directed program of digital transformation and national AI capability building, complete with dedicated institutions such as the Saudi Data and AI Authority. Media organizations therefore operate under unusually visible technological expectation from the top. At the same time, the sector faces constraints that are anything but generic: compliance obligations under the Personal Data Protection Law, well-documented performance gaps in Arabic-language processing relative to English, subscription costs benchmarked against international rather than local purchasing power, and uneven distribution of training capacity across regions and employment types. Strong institutional encouragement and substantive structural constraint operate simultaneously—precisely the configuration a multi-level framework is needed to explain.

Among the small group of non-users, privacy and security concerns topped the list of barriers, reported by 12 of the 17 respondents, followed closely by high subscription costs, reported by 11. The researchers are careful to note that with only 17 responses, this ranking is descriptive and exploratory rather than generalizable to the national sector. Still, the prominence of privacy is theoretically telling. Unlike cost or skill deficits, privacy is not resolved by acquiring resources; it persists even for well-resourced practitioners. The authors draw on the privacy calculus tradition to explain why: audio-visual professionals handle disproportionately confidential material—unpublished footage, pre-release assets, client information, and in journalism, source identities. Cloud-based AI tools typically require that material to leave organizational control for processing, and the Personal Data Protection Law makes the consequences of misjudgment concrete rather than hypothetical. A practitioner may judge a tool both useful and easy to use and still decline it because the conditions of its use are deemed impermissible.

Across the full sample of 400, the most frequently endorsed facilitating condition was training programs and specialized workshops, followed by easy-to-use tools at affordable prices, and then high-quality training data and open-source resources. Technical support services, collaboration with technology companies, clear standards and ethics frameworks, and industry case studies completed the ranking. The researchers emphasize that these conditions span three distinct levels—individual capability, organizational and market provision, and sector-level normative infrastructure—suggesting that no single category of intervention will be sufficient on its own. In a sample where nearly everyone already uses AI, the appetite for training likely reflects an awareness that current use is shallower than it could be, not an absence of access.

The demographic findings add another layer of nuance. AI readiness varied significantly by age, occupational sector, geographic region, and monthly income, but not by gender or education. The occupational association was the largest in the study: government-sector respondents reported the highest readiness, while retired professionals reported the lowest, though that latter group comprised only ten people. The authors offer a theoretically motivated institutional reading: state and public media organizations operate under explicit Vision 2030 digitalization expectations, and where organizations respond by providing tools, training, and time, practitioners experience institutional pressure as tangible support. They stress, however, that institutional pressure and organizational policy were not directly measured, and alternative explanations such as selection into public-sector employment cannot be excluded.

Perhaps the most intriguing result is regional. The Central region, home to Riyadh and the bulk of the Kingdom’s media infrastructure, reported the lowest mean readiness, while the Southern region reported the highest. Rather than invoking vague cultural explanations, the researchers propose a socio-technical reading: practitioners in the densest media market have the most cumulative exposure to AI tools in real production conditions, and therefore the most direct experience of where those tools fail—particularly in Arabic contextual processing, which ranked as the second-highest technical challenge in the survey. Readiness measured as attitude may be depressed by informed appraisal rather than inexperience. Conversely, elevated readiness in the South may reflect expansion-driven demand, as Vision 2030 tourism and gigaproject development generate urgent need for promotional content that automated tooling can help meet under capacity pressure. Both readings remain hypotheses, the authors caution, since neither market maturity nor demand pressure was measured.

The Arabic-language finding deserves particular emphasis because it is specific to the linguistic context and cannot be reduced to the generic constraints documented in Anglophone research. Difficulty understanding contextual meaning in Arabic content ranked second among technical challenges, behind only the need for large volumes of high-quality training data. Arabic presents specific processing difficulties—morphological richness, diglossia between Modern Standard Arabic and regional dialects, and orthographic underspecification of vowels—that general-purpose models trained predominantly on English corpora handle unevenly. The implication is significant for policy: no amount of practitioner upskilling can compensate for a model that misreads dialectal register or fails to disambiguate meaning. The researchers recommend that national AI bodies fund the development of Arabic-language models and resources tuned to media production, including dialectal variation, transcription and subtitling accuracy, and contextual disambiguation, alongside high-quality Arabic audio-visual training corpora with clear rights provenance.

On the question of job displacement, the study offers a striking contrast with Western findings. Concern about job impact was the least frequently reported barrier among non-users, cited by just two respondents, whereas displacement anxiety is prominent among Western journalists in prior research. The authors note this divergence rests on only two responses and should be treated as indicative, but suggest that sectoral expansion under Vision 2030 may reduce the perceived plausibility of displacement, or that differences in labor market structure may alter its perceived consequences. Respondents’ expectations about AI’s future impact were oriented toward efficiency first and creative augmentation second, indicating a complementarity rather than substitution view of the technology.

The study’s limitations are stated with unusual candor. The cross-sectional design precludes causal inference; the purposive sample is not statistically representative of the national workforce; the barrier profile rests on just 17 responses; and the attitudinal readiness composite was assessed for internal consistency only, without confirmatory factor analysis or test–retest validation. The proposed ecosystem model was not statistically estimated and awaits empirical validation through methods such as structural equation modeling with measured institutional and organizational variables. Within those bounds, the conclusions are clear: in near-saturated markets, advancing AI integration depends less on persuading professionals to adopt—most already have—than on resolving the data governance, cost, capability, and Arabic-language conditions that determine how well they are able to do so. The productive question, the authors argue, is no longer incidence of adoption but the depth, quality, and equity of integration.

Subject of Research: AI adoption readiness, barriers, and facilitating conditions among audio-visual media professionals in Saudi Arabia

Article Title: Artificial intelligence readiness among audiovisual media professionals in Saudi Arabia and its barriers and facilitating conditions

Article References: Alenzi, S. F., Tawalbeh, A., Yilmaz, F., Akhmatshina, E. K., & Nikonov, S. B. (2026). Artificial intelligence readiness among audiovisual media professionals in Saudi Arabia and its barriers and facilitating conditions. Discover Artificial Intelligence, 6(1), Article 1378. https://doi.org/10.1007/s44163-026-02231-x

Image Credits: AI Generated

DOI: 10.1007/s44163-026-02231-x

Keywords: artificial intelligence, Saudi Arabia, audio-visual media, technology acceptance, digital divide, institutional theory, Vision 2030, privacy, Arabic-language AI, media production, training, adoption barriers

The study, published in Discover Education by Mohammad Qasim Farooqi and Najibullah Habibi of Badghis University, explored how English as a Foreign Language (EFL) teachers at three Afghan public universities experience the implementation of OBE. The researchers conducted semi-structured interviews with nine male EFL teachers who were purposively selected because they had served both as OBE trainers and as university lecturers. Female teachers could not be recruited because, following the regime change, they were no longer teaching in Afghan higher education. Interviews were held online via WhatsApp audio calls in October and November 2023, lasted roughly fifty minutes each, and were conducted in English or Persian depending on the participant’s preference. The researchers stopped recruiting after the ninth interview because no new themes emerged, a sign that data saturation had been reached.

The interviews were analyzed using Braun and Clarke’s six-phase reflexive thematic analysis, interpreted through the lens of institutional theory. That theoretical framework, developed by organizational sociologist W. Richard Scott, describes institutional environments in terms of three pillars: regulative structures such as laws and policies, normative structures such as professional values, and cultural-cognitive structures such as shared assumptions about what is feasible. When a new reform clashes with these pillars, organizations often engage in what scholars call decoupling, formally adopting a policy to gain legitimacy while quietly continuing established routines. That concept proved strikingly apt for the Afghan case.

The most salient barrier the teachers described was resource inadequacy. Classrooms lacked projectors, libraries and basic technological infrastructure, forcing instructors back into traditional, content-delivery modes of teaching regardless of their enthusiasm for outcome-based principles. One participant, identified as T2, asked how a system can be implemented when there is no library, no LCD display and no working projector. The shortage was reported to be even more severe in remote provinces such as Badghis, Ghor and Farah, which the teachers described as an institutional inequity: OBE appeared to be designed, implicitly, for well-equipped universities in central provinces while being imposed everywhere.

Training emerged as a second, deeply ironic obstacle. The OBE workshops teachers attended were described as largely theoretical, lecture-based and compliance-oriented, lasting about ten days with long daily sessions running from early morning to late afternoon. Participants said the sessions raised awareness without building capacity, offering no guided practice, classroom simulations, model lessons or follow-up observation. One teacher noted that trainees were given certificates and then everything was finished, even though most did not understand what OBE actually required of them. The researchers highlight the performative contradiction here: a reform meant to promote active, student-centered learning was transmitted through passive, teacher-centered instruction, effectively socializing teachers into the very pedagogy OBE seeks to replace.

Curricular constraints compounded the problem. The national syllabus produced by the Ministry of Higher Education was perceived as misaligned with OBE principles, and the teachers who periodically revised it were seen as subject-matter experts rather than specialists in outcome-based design. Teachers reported having only about thirty percent freedom to adapt the syllabus to their departments’ needs, a ceiling the study interprets as a symbolic limit on professional autonomy. In OBE theory, curriculum content and learning experiences should be selected only after outcomes have been clearly defined, following frameworks such as Spady’s original formulation and the SMART criteria for writing specific, measurable, actionable, relevant and time-bound outcomes. In practice, Afghan teachers faced the reverse: a fixed content list to which outcomes had to be retrofitted.

Policy misalignment tied these barriers together. Institutional regulations mandated the number of pages to be covered per session, and teachers who fell behind were questioned by their department heads. Assessment rules heavily favored summative examinations, reportedly accounting for the overwhelming majority of evaluation, while OBE calls for rich formative assessment aligned with intended outcomes. Examination regulations requiring a fixed number of written questions were described as incompatible with skill-based courses, since speaking and writing competencies demand performance-based and extended tasks rather than knowledge-recall papers. The result, the authors argue, is a double bind: teachers are officially encouraged to pursue outcome-oriented pedagogy while the incentive structure punishes exactly the practices it requires.

A shortage of human resources ran through all of these accounts. Only a handful of OBE master trainers served the entire country, traveling to eight or ten provinces for ten-day workshops, and some trainers sent abroad for training came from disciplines such as computer science and biology with little background in pedagogy. Many teachers in remote universities had never received any OBE training at all. The participants argued that future trainers should be selected from educators holding master’s or doctoral degrees in education, whose expertise in teaching methodology would allow them to grasp and transmit OBE principles more effectively.

From these diagnoses, the teachers built a tripartite solution framework that the authors present as the study’s central practical contribution. First, deep professionalization: expanding the pool of master trainers, selecting them from education specialists, and replacing one-off workshops with sustained, practice-based development that builds assessment literacy and curriculum-design skill. Second, dedicated resource allocation: training a curriculum team in each department to design OBE-aligned syllabi, and investing in technological infrastructure, libraries and modern equipment. Third, institutional realignment: reforming teaching and assessment policies so that they reward rather than penalize outcome-based practices, or at minimum granting teachers the professional space to follow OBE rules where existing policy conflicts with them.

Crucially, the participants insisted that these three components are interdependent. Trained teachers without resources cannot enact the reform; resources without professional competence sit unused; and professionalism plus resources without supportive policy still leaves teachers unable to implement OBE. The authors conclude that reform failure in such contexts is rarely a matter of poor technique but of incompatible systemic logics, and that the Afghan pattern, resource scarcity, prescriptive curricula, ineffective training and contradictory assessment policy reinforcing one another, offers a diagnostic lens for stalled outcome-based reforms in other under-resourced, centrally governed systems. The study’s limitations are acknowledged: a small, purposive, all-male sample from three universities, potential trainer bias among participants, and the sensitivity of the political context, all of which call for larger and more diverse follow-up research before the proposed framework is scaled up.

Subject of Research: Implementation challenges and solutions for outcome-based education among EFL teachers in Afghan public universities

Article Title: Perceived challenges and potential solutions of outcome-based education in an under-resourced context

Article References: Farooqi, M. Q., & Habibi, N. (2026). Perceived challenges and potential solutions of outcome-based education in an under-resourced context. Discover Education, 5(1), Article 1110. https://doi.org/10.1007/s44217-026-02202-5

Image Credits: AI Generated

DOI: 10.1007/s44217-026-02202-5

Keywords: outcome-based education, Afghanistan, higher education, EFL teachers, qualitative research, thematic analysis, teacher training, curriculum alignment, assessment policy, institutional theory, educational reform, under-resourced contexts

In a perspective article published in Discover Education, Vita Hamaniuk, Yana Pristupa and Serhiy Semerikov of Kryvyi Rih State Pedagogical University propose a palimpsest model of educational change. Like a manuscript on which earlier writing has been imperfectly erased and remains visible beneath later text, education systems, they contend, accumulate successive reform layers without fully displacing what came before. Soviet-era structures persist beneath post-independence nationalizing reforms, which persist beneath European competency frameworks, which persist beneath the latest digital transformation initiatives. Each layer modifies the layers beneath it without wholly replacing them.

The argument builds on David Tyack and Larry Cuban’s influential concept of the grammar of schooling, the deep structural features of educational institutions such as age-grading, subject departmentalization, and teacher-centered instruction that have persisted for over a century despite repeated reform efforts. The authors extend this framework through institutional theory, drawing on DiMaggio and Powell’s notion of institutional isomorphism, the tendency of organizations to converge toward common structural forms regardless of their formal goals. The grammar of Soviet schooling, imposed systematically across a vast territory over decades, constitutes a particularly powerful institutional template that has proven remarkably durable even after the political system that created it collapsed.

The empirical basis is a documentary corpus of 393 catalogued items spanning seven decades of Ukrainian natural science education, of which 101 are primary legislative, archival and curricular documents. The primary record was drawn from two state repositories: the Central State Archive of Supreme Bodies of Power and Government of Ukraine in Kyiv, covering Soviet-era curricula and ministerial deliberations, and the State Archive of Dnipropetrovsk Oblast, covering regional education department records and materials from the Kryvyi Rih Pedagogical Institute. Each primary document was coded for persistent structural elements, genuinely new layers, and inter-layer friction, passages in which the requirements of different periods stand in tension. The authors are candid that the coding frame was applied deductively from the palimpsest model rather than induced from the material, and that a documentary corpus establishes what was required and authorized, not what happened in classrooms.

The Soviet foundation layer, established during the stabilization period of the 1950s through the 1980s, rests on the deepest documentary base, with 60 of the 101 primary documents. Five features constitute its grammar: strict disciplinary organization of physics, chemistry, biology, geography and astronomy as separate subjects; encyclopedic curriculum logic aiming at comprehensive coverage; knowledge-transmission pedagogy in which the teacher delivered pre-structured content; centralized textbook control with a single state-approved text per subject per grade; and a systematic urban-rural quality gradient in laboratories, teacher qualifications and resources. The staffing dimension of that gradient is visible in the record of the early 1960s, when Zhytomyr oblast was short of 300 teachers and the shortfall was met by drafting in senior students of the local pedagogical institute.

Yet the Soviet system itself recognized the limits of this model. Late-Soviet assessments found that schoolchildren assimilated factual material without sufficient awareness of the internal content of natural phenomena, and the 1988 All-Union Teacher Congress explicitly called for diverse approaches to educational content and an end to the uniformity that had constrained pedagogical creativity. Reformers argued that science education must move beyond the accumulation of facts to develop scientific thinking and inquiry skills. But the institutional grammar absorbed this reform rhetoric without structural alteration, and the authors identify a characteristic form of friction in the period: permission to depart from the prescribed method arrived together with the disappearance of the material means to act on it, a conjunction of authorization without capacity.

Ukrainian independence in 1991 initiated the second layer. The 1991 Education Law and the 1993 State National Program established new conceptual foundations of national identity, democratization, humanization and environmental awareness, the last catalyzed by the Chornobyl disaster of 1986. Science curricula were rewritten to include Ukrainian scientific achievements and local environmental contexts, and ideological content was removed. These changes were real, but the analysis reveals a critical pattern: the nationalizing layer changed the content of natural science education while largely preserving its structure. New content was, in effect, poured into old containers. The Chornobyl case is especially instructive, because understanding nuclear contamination demands exactly the cross-disciplinary thinking that the Soviet subject structure inhibits. Yet even this powerful impetus was formalized within existing structures, with radiation physics added to physics, biological effects to biology, and radionuclide chemistry to chemistry, and no instrument requiring these treatments to be brought into relation with one another.

The third layer arrived with Ukraine’s European orientation, formalized in the 2002 National Doctrine and elaborated through the 2004 State Standard’s key competencies, the 2011 STEM-referencing state program, the 2016 New Ukrainian School concept with its ten key competencies and integrated primary course I Explore the World, and the 2017 Law on Education. Again the palimpsest pattern continued. The external independent testing introduced in 2008 rewarded factual recall and algorithmic problem-solving far more than inquiry or investigation, precisely the outcomes the Soviet grammar was designed to produce, creating an incentive structure that ran counter to the competency language of the newer policy layer. International assessment data complicate the picture rather than confirming a simple story: in TIMSS 2007, Ukrainian eighth-graders scored 485 in science, below the scale average of 500, and their weakest cognitive domain was knowing, the opposite of what a straightforward transmission-grammar account would predict. The authors withdraw their earlier claim of a palimpsest signature in the assessment data and rest their case instead on the documentary and incentive evidence.

Russia’s full-scale invasion in February 2022 provides what the authors carefully call a critical case rather than a natural experiment, a historical disruption that renders ordinarily tacit institutional structures visible without permitting controlled comparison. By January 2023, 1259 schools had been damaged and 223 destroyed, and as of December 2022, 36 percent of schools were teaching entirely remotely while a further 36 percent alternated between remote and in-person instruction. Notably, the division of school science into separate subjects was not questioned in any emergency adaptation the authors identified: emergency guidance reduced teaching hours and compressed content but operated within the existing subject structure, and the All-Ukrainian Online School reproduced that subject-based structure in digital form. Systemic stress, they conclude, reveals which practices a system treats as dispensable, though resilience under stress confounds institutional depth with the resource intensity of the practices concerned.

The model also has a human dimension the authors advance as interpretation rather than finding. From the system’s point of view accumulation is additive, but from the teacher’s point of view the same process is subtractive: a teacher required to describe two decades of demonstration-based laboratory expertise as outdated transmission pedagogy has not acquired a layer but been told that what they were good at no longer counts. Drawing on Peter Marris’s account of loss and change, and on research showing that what reformers read as resistance is frequently mourning, they suggest that friction is not only structural but biographical, and that its intensity is greatest where reform rhetoric is most emphatically discontinuous, as Ukrainian reform discourse has been in defining itself against the Soviet inheritance. The implications reach beyond Ukraine: if new policy settles onto durable inherited structures rather than replacing them, the resulting friction is better treated as a cost of reform than as an anomaly, a consideration relevant to the assumptions embedded in Sustainable Development Goal 4. The authors propose that reforms attuned to layering, working with rather than against existing structures and asking which features of the grammar are genuinely constitutive and which are contingent, should fare better than strategies premised on replacement, while acknowledging that testing this proposition requires the classroom-level evidence their documentary study cannot supply.

Subject of Research: Accumulation versus replacement of educational reforms in Ukrainian natural science education from 1950 to 2022

Article Title: Why educational change accumulates rather than replaces in Ukrainian natural science education from 1950 to 2022

Article References: Why educational change accumulates rather than replaces in Ukrainian natural science education from 1950 to 2022. (n.d.). https://doi.org/10.1007/s44217-026-02247-6

Image Credits: AI Generated

DOI: 10.1007/s44217-026-02247-6

Keywords: palimpsest model, grammar of schooling, Ukraine, post-Soviet education, educational change, science curriculum, implementation gap, Soviet legacy, competency-based education, TIMSS, wartime disruption, institutional theory

The circular economy has become the dominant framework for reforming the fashion and textile industry, which produces an estimated 92 million tonnes of textile waste annually and recycles less than 1 percent of clothing into new fibres, according to the Ellen MacArthur Foundation’s landmark New Textiles Economy report. Policy instruments such as the European Union’s Ecodesign for Sustainable Products Regulation and India’s own Business Responsibility and Sustainability Reporting framework promise longer product life cycles, local material systems, and community-anchored production. But the dominant narrative centres on industrial transformation in the Global North: recycling infrastructure, take-back programmes, and fibre-to-fibre loops operated by formal, traceable, ESG-reportable firms. That assumption, the new paper contends, simply does not hold in India, where the craft textile sector employs an estimated 113 lakh workers, nearly 72 percent of them women, overwhelmingly in informal household production.

To measure the problem, the researchers built two original composite indices grounded entirely in verified, publicly available official data. The first, the GI-CE Institutional Alignment Score, measures how far the statutory provisions of India’s Geographical Indications Act of 1999 mandate circular-economy-compatible supply chains across 25 GI-registered textile products, from Kanchipuram silk to Banarasi brocades. The second, the Circular Informality Exposure Index, measures how vulnerable the artisans in those clusters are to the social risks of circular transition. The data sources are legally anchored and temporally consistent: the GI registry maintained by the Controller General of Patents, Designs and Trade Marks, the Fourth All India Handloom Census 2019-20, the Periodic Labour Force Survey Annual Report 2023-24, and the Securities and Exchange Board of India’s BRSR framework documents.

The results reveal a striking paradox. The GI-tagged craft textile clusters score consistently high on institutional circular alignment, with a mean score of 4.36 out of 5. This is no accident: the GI Act legally requires geographic input localisation, community-based producer organisation, and natural or traditional input specification, properties that structurally replicate every definitional criterion of a circular supply chain. Yet the workers inside these institutionally circular systems are among the most socially vulnerable in India’s manufacturing economy. Average daily earnings across the five-state handloom and handicraft economy surveyed by the Institute for Human Development and Crafts Council of India stand at just 270 rupees, well below minimum wage in every Indian state. Only 8.8 percent of weaver households access markets through cooperatives, and nine out of ten women in Indian manufacturing work in informal enterprises without contracts or social security.

Cross-referencing the two indices produces the study’s central empirical finding: nine of the 25 clusters, or 36 percent of the sample, fall squarely into the circular informalization trap, combining high institutional circular alignment with high informality exposure. These trapped clusters cluster geographically in two contexts: the North Indian plains, including Uttar Pradesh, Punjab, and Rajasthan, where cooperative market channel use falls below the national median and female part-time weaver concentration exceeds the average of 60.6 percent; and recently registered tribal textiles from the Northeast, such as Garo and Tangsa weaves, where the authorised user mechanism that should guarantee producer traceability has not yet been operationalised. No product fell into the low-alignment quadrants, reflecting how thoroughly the statute itself embeds circular design.

The deepest structural gap lies in environmental, social, and governance disclosure. SEBI’s BRSR framework, mandatory since the 2022-23 financial year for India’s top 1,000 listed companies by market capitalisation, requires comprehensive reporting across 140 questions, including human rights, labour practices, and supply chain conduct, with the BRSR Core adding 49 measurable key performance indicators and third-party assurance for the largest firms. But because the framework’s scope is defined by market capitalisation, no handloom cooperative, tribal craft association, or GI-registered producer group falls within it. All 25 clusters scored maximally on the ESG disclosure exclusion dimension of the informality index. The firms whose supply chains depend on artisan labour must disclose their ethics; the artisans who perform that labour remain entirely outside the disclosure perimeter, a disjunction the authors call the relative ESG discourse-labour asymmetry.

The gendered dimensions of this trap are particularly consequential. India’s female labour force participation rate has risen sharply, from 23.3 percent in 2017-18 to 41.7 percent in 2023-24, but the increase has been driven predominantly by rural self-employed women, more than 80 percent of them in agriculture or household-based production. The handloom sector, with its 72 percent female majority, part-time household structure, and chronic underemployment of 208 person-days per year, exemplifies this expansion of informal self-employment rather than gender-equalising formal job growth. The circular transition could carry a genuine gender dividend, since it raises the value of precisely the provenance, natural inputs, and durable craftsmanship that women artisans produce. But if circular premiums are captured by intermediaries and formal firms instead, women would bear the informality costs while the formal economy appropriates the circular value.

The trap also operates globally. European regulations, including Digital Product Passports under the Ecodesign regulation, corporate sustainability due diligence directives, and a proposed Forced Labour Regulation, are creating new traceability demands for textile imports. GI-registered Indian craft textiles are, by institutional design, exceptionally well positioned to meet them: authorised user registration provides producer identity, statutory collective applicant requirements provide community organisation, and Form GI-1 specifications document natural inputs. The authors argue that recognising GI registration as equivalent to Digital Product Passport compliance could satisfy EU requirements at a fraction of the cost industrial firms face, yet this compatibility remains invisible to European policymakers, Indian trade negotiators, and the corporations involved. Similar structural conditions, an origin-certification framework, a feminised informal workforce, and ESG rules scoped to formal entities, exist in Indonesia’s batik clusters, Peru’s Andean textile geographical indications, and among West African kente producers, suggesting the trap may be a global regularity rather than an Indian anomaly.

Crucially, the study insists that closing the gap requires no new legislation, infrastructure, or institutions, only the political will to connect systems that already exist. The authors advance four targeted recommendations. SEBI could amend BRSR Core leadership indicators by circular, making disclosure of GI-registered and informal artisan supply chain tiers mandatory rather than voluntary for large listed textile firms. The Department for Promotion of Industry and Internal Trade and the Ministry of Textiles could jointly issue a GI-CE Equivalence Framework, mapping statutory GI requirements onto circular procurement criteria and green finance access. The National Cooperative Development Corporation could extend cooperative market channel access from 8.8 percent to 25 percent of weaver households within five years, prioritising the trapped clusters and using existing artisan identity data for outreach. And in European Union-India free trade negotiations, GI-Digital Product Passport equivalence could be tabled as a technical annex, directly rewarding the institutional architecture India’s craft sector already possesses.

The broader lesson extends far beyond textiles. The circular economy is routinely framed as a redesign challenge, a matter of recycling plants and business models, but this research demonstrates that governance architecture, not technology, determines who benefits from sustainability transitions. India’s Geographical Indication system has already designed a circular supply chain; the Handloom Census has already documented the cooperative forms that could channel circular premiums to producers; and the BRSR framework has already built the disclosure infrastructure that could make artisan labour visible. What is missing is the linkage between them. Without it, the world’s most circular textiles will continue to be made by some of its most precarious workers, and the sustainability revolution will reproduce the very inequalities it claims to solve. The authors call for extending their dual-index framework to other developing economies and for primary cluster-level research to test whether cooperative organisation mediates between institutional alignment and artisan income, questions that the forthcoming Fifth All India Handloom Census will help answer.

Subject of Research: Circular economy governance and feminized informal labour in India's GI-registered textile clusters

Article Title: Institutional pressures link circular economy governance and feminized informality in India’s geographical indication registered textile clusters

Article References: Institutional pressures link circular economy governance and feminized informality in India’s geographical indication registered textile clusters. (n.d.). https://doi.org/10.1007/s44282-026-00619-9

Image Credits: AI Generated

DOI: 10.1007/s44282-026-00619-9

Keywords: circular economy, geographical indications, handloom, feminized informality, ESG disclosure, BRSR, textile clusters, India, social sustainability, global value chains, artisan welfare, institutional theory

The study integrates two established theoretical frameworks to make sense of the divergence. The first is Fountain’s technology enactment framework, which holds that information technologies are not simply adopted by organizations but are actively shaped, or enacted, by the institutional structures that surround them. The second is Horowitz’s adoption-capacity theory, which argues that a state’s ability to absorb transformative military technology depends on the financial and organizational capital it can marshal. By combining these lenses, Parisini argues that money alone cannot explain why the United States and the European Union have followed such different trajectories, because organizational capital, the accumulated capacity of institutions to absorb and deploy new technology, is the critical determinant of effective AI implementation.

The comparison reveals two distinct governance models. The United States exhibits what the study calls competitive institutional appropriation, a capability-first approach characterized by concentrated investment and a race to translate AI research into operational military advantage. This model is anchored in a dense ecosystem of institutions, from the Department of Defense’s Data, Analytics, and Artificial Intelligence Adoption Strategy, published in 2023 under the banner of accelerating decision advantage, to executive orders from the White House on safe and trustworthy AI development and, later, on removing barriers to American leadership in artificial intelligence. The National Artificial Intelligence Initiative Act of 2020 further institutionalized federal AI spending, and analyses of US government AI budgets show sustained growth in defense-related investment.

The European Union, by contrast, demonstrates fragmented institutional absorption. Rather than a single centralized push, AI adoption in European defence is distributed across member states and a lattice of EU frameworks, including Permanent Structured Cooperation, or PESCO, established by Council Decision in 2017, the European Defence Fund, and the Artificial Intelligence Act of 2024. The study finds that strategic choices within these frameworks have tended to reinforce member state autonomy rather than pool it, meaning that national capitals such as Paris and Berlin continue to chart their own courses. France, for example, has pursued defence AI through a dedicated defence innovation agency and one of Europe’s fastest classified supercomputers for defence applications, while Germany’s approach has been shaped by its own strategic reorientation. The result is a patchwork rather than a unified program.

The financial asymmetry between these two models is stark and consequential. The study highlights significant disparities in financial intensity between US and European defence AI efforts, a gap rooted in decades of divergent defence expenditure across EU countries. That spending gap, the analysis argues, creates technological dependencies, with European armed forces and defence industries relying on American platforms, standards, and infrastructure for critical AI capabilities. This dependency relationship poses profound implications for European strategic autonomy, the long-standing ambition that Europe should be able to act in security matters without critical reliance on external powers. In a domain as sensitive as military AI, where data pipelines, model architectures, and decision-support systems can determine battlefield outcomes, dependence on another bloc’s technology is a strategic vulnerability.

European policymakers are not blind to the problem. The study points to emerging strategic initiatives, most notably the European Commission’s White Paper for European Defence, known as Readiness 2030, published in 2025, as an attempt to close the gap and rearm Europe’s technological base. The White Paper sits alongside continued financing decisions for the European Defence Fund, which channels research and development money into collaborative defence technology projects. Yet the study’s central caution is that these initiatives will not succeed on funding alone. Because organizational capital, the trained personnel, institutional routines, data infrastructure, and decision-making structures that allow organizations to actually use AI, develops slowly, a surge of money without institutional reform risks reproducing the fragmentation that currently limits European absorption capacity.

The theoretical stakes of the finding extend beyond Europe. By showing that divergent implementation pathways reflect institutional logics rather than technological imperatives, the study challenges a common assumption that AI will naturally converge toward similar governance forms everywhere. Institutional theory has long held that organizations in the same field tend to grow alike through isomorphic pressures, yet the EU and US cases show that where those pressures come from, whether competitive markets, regulatory frameworks, or strategic traditions, shapes fundamentally different outcomes. In the American case, governance has been framed around competitive advantage and national security leadership; in the European case, around regulation, ethical safeguards, and the preservation of national sovereignty within a collective framework. Both are responses to the same technology, but they enact it in incompatible ways.

These divergences carry direct consequences for defence cooperation between the allies. The study suggests that successful transatlantic collaboration on military AI requires attention to both technical and institutional compatibility, while actively mitigating dependency risks. Interoperability between an American capability-first ecosystem and a fragmented European one is not merely a question of common data standards or shared interfaces; it requires aligning institutional logics that currently pull in different directions. The research also situates the issue in a broader geopolitical context, noting that the United States’ dominance of global arms exports has grown while Russian exports have fallen, and that Ukraine has become the world’s biggest arms importer, trends that raise the stakes of who controls the next generation of defence technology.

The methodological approach is a comparative case study, a design suited to tracing how institutional structures and organizational factors shape technology adoption in complex political settings. By examining documentary evidence ranging from the US Department of Defense’s AI adoption strategy and White House executive orders to the European AI Act, the Readiness 2030 White Paper, and national defence AI strategies from France and Germany, the study builds a picture of two governance systems operating at different speeds and with different centers of gravity. The author reports no competing interests, and the article appears in Volume 5 of Global Public Policy and Governance, pages 114 to 138.

For readers tracking the future of military technology, the study’s message is clear: the AI race in defence will not be won by algorithms alone. Governance structures mediate which technologies get adopted, how quickly, and under whose control, and the gulf between American competitive appropriation and European fragmented absorption is widening into a structural dependency that money alone cannot close. Whether initiatives like Readiness 2030 can build the organizational capital Europe needs, and whether transatlantic institutions can find enough common ground to cooperate on the most consequential technology of the era, are questions that will define European strategic autonomy for decades to come.

Subject of Research: Comparative governance of artificial intelligence adoption in the EU and US defence sectors

Article Title: Governing artificial intelligence in the defence sector: a comparative analysis of EU and US institutions

Article References: Parisini, E. (2025). Governing artificial intelligence in the defence sector: a comparative analysis of EU and US institutions. Global Public Policy and Governance, 5(2), 114-138. https://doi.org/10.1007/s43508-025-00115-x

Image Credits: AI Generated

DOI: 10.1007/s43508-025-00115-x

Keywords: artificial intelligence, defence policy, European Union, United States, AI governance, military technology, strategic autonomy, institutional theory, European Defence Fund, AI Act, defence innovation, transatlantic cooperation

The research, conducted by Detcharat Sumrit and Rodsak Kongsakul, focuses on Thailand’s SME logistics sector, a setting the authors argue is emblematic of challenges facing emerging economies worldwide. Thai policymakers have embraced a Bio-Circular-Green economy model and carbon neutrality commitments, but the small firms that dominate the sector still wrestle with outdated technology, manual reporting systems, fragmented data governance, and subcontractors with limited sustainability capabilities. The study treats these firms not as laggards but as organizations caught between internal resource limits and powerful external pressures, and it builds its entire analytical framework around that tension.

Theoretically, the work weaves together three complementary lenses. The resource-based view explains how internal assets, from financial capital to digital infrastructure, shape what the authors call endogenous barriers. Institutional theory captures the exogenous pressures that compel action: coercive forces such as the European Union’s Corporate Sustainability Reporting Directive, mimetic imitation of sustainability leaders like DHL and Maersk, and normative expectations from customers demanding low-carbon logistics. The technology-organization-environment framework then provides the structure for organizing potential responses. No prior study, the authors contend, has integrated all three perspectives while simultaneously linking barrier identification to strategy prioritization under uncertainty.

The methodological machinery is where the study becomes technically distinctive. The researchers deployed a hybrid multi-criteria decision-making pipeline combining the Full Consistency Method, the Decision-Making Trial and Evaluation Laboratory, and Quality Function Deployment, all operating within an interval-valued spherical fuzzy environment. Spherical fuzzy sets extend classical fuzzy logic by adding an explicit hesitancy parameter alongside membership and non-membership degrees, subject to the constraint that the squared components sum to at most one. This gives experts a larger, more flexible decision space than intuitionistic or Pythagorean fuzzy sets, and the interval-valued variant captures the variability inherent when twelve experts must reconcile subjective, linguistically expressed judgments.

An expert panel of twelve, drawn from government, industry, and academia through a purposive sampling process with a 60 percent response rate, validated seventeen candidate obstacles using Lawshe’s content validity ratio. Eleven survived, and the fuzzy FUCOM analysis then weighted them with striking clarity. The single most influential barrier, at 0.123, was fragmented collaboration among supply chain actors, followed almost immediately by capital constraints on sustainability investment at 0.122. Regulatory misalignment and inadequate governmental incentives rounded out the top four. The message is unambiguous: ESG failure in small logistics firms is less about unwillingness and more about an ecosystem in which no single actor can move alone.

That diagnosis directly shaped the remedy. Eleven mitigation strategies, organized within the technology-organization-environment structure, were mapped against the validated barriers in a House of Quality, with DEMATEL analysis revealing the causal web of interdependencies among them. When the dust settled, one strategy towered above the rest: collaborating with green suppliers and clients, earning a normalized priority of 0.148. Partnering with industry groups and embedding ESG into core corporate strategy followed closely. Notably, carbon footprint accounting software ranked last, suggesting that digital tools alone, however fashionable, cannot substitute for the relational and strategic work of building collaborative capacity.

The robustness testing is unusually thorough for this genre. The researchers varied every barrier weight across a range of minus thirty to plus thirty percent, generating sixty-six alternative scenarios, and the strategy ranking held steady in every one. A comparative assessment against crisp, triangular fuzzy, intuitionistic fuzzy, and spherical fuzzy versions of QFD showed the proposed approach correlating very strongly with spherical fuzzy QFD at a Spearman coefficient of 0.850, while traditional crisp methods managed only a weak 0.373. In other words, the sophistication of the fuzzy machinery is not decorative; it materially changes which conclusions survive scrutiny.

For managers, the practical implications are refreshingly concrete. Rather than attempting every ESG practice at once, the authors recommend phased investment in measures with rapid payback, such as energy-efficient equipment, route optimization, and digital documentation, financed through government grants, green financing, equipment leasing, and cost-sharing with supply chain partners. Joining industry associations and adopting affordable cloud platforms for shared sustainability data can attack the collaboration deficit at low cost. Designating staff to track evolving regulations and folding ESG indicators into existing performance reviews, rather than building separate reporting bureaucracies, addresses regulatory uncertainty without new overhead.

The study also sketches a phased policy roadmap. In the short term, governments should harmonize ESG standards, simplify reporting, and offer incentive-based compliance schemes, an approach the authors note resembles Singapore’s combination of structured reporting guidance with targeted financial support. Medium-term efforts should build standardized certification and capacity-building programs, drawing on Germany’s sector-wide logistics coordination. Long term, the goal is an adaptive regulatory ecosystem that embeds sustainability into national logistics strategy, exemplified by the Netherlands’ low-emission logistics zones. For a sector that keeps global commerce moving, the study’s central finding may prove its most viral idea: the greenest thing a small logistics firm can do is stop trying to go green alone.

Subject of Research: ESG mitigation strategies for sustainable transition in small and medium-sized third-party logistics providers

Article Title: Mitigation strategies for addressing environmental, social, and governance challenges in third-party logistics: A sustainable transition perspective

Article References: Sumrit, D., & Kongsakul, R. (2026). Mitigation strategies for addressing environmental, social, and governance challenges in third-party logistics: A sustainable transition perspective. Cleaner Engineering and Technology, 34, Article 101317. https://doi.org/10.1016/j.clet.2026.101317

Image Credits: AI Generated

DOI: 10.1016/j.clet.2026.101317

Keywords: ESG, third-party logistics, sustainability transition, SME logistics, fuzzy MCDM, FUCOM, DEMATEL, Quality Function Deployment, institutional theory, resource-based view, TOE framework, green supply chain collaboration

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

The research, conducted by Hani Abdelhadi of Meiji University’s School of Commerce, analyzed the institutional responses of 29 major Japanese universities to the two conflicts. The results reveal a profound asymmetry. Twenty-eight of the 29 institutions—96.6 percent—issued public statements supporting Ukraine, and 27 of those backed their words with concrete aid measures such as emergency scholarships and streamlined admissions for Ukrainian students. By contrast, only three of the 29 universities—10.3 percent—addressed the Palestine-Israel situation at all, and none of those offered any material support. Both crises, the study notes, involved civilian deaths exceeding 10,000, destruction of educational infrastructure, mass displacement of students and academics, determinations by international legal bodies, and extensive global media coverage, making differential responses difficult to explain as a matter of capacity or awareness.

To interpret this pattern, Abdelhadi draws on two established theoretical frameworks. The first is Oliver’s 1991 theory of strategic responses to institutional processes, which describes how organizations choose among tactics ranging from acquiescence to manipulation when facing external pressures. The second is Brunsson’s 2006 concept of organized hypocrisy, which captures the gap between what organizations say, what they decide, and what they actually do. Combining these lenses, the study proposes a new concept—strategic neutrality—to describe institutional behavior in which claims of political neutrality mask a politically calculated selectivity. In other words, Japanese universities were not neutral across the board; they were vocal on one crisis and silent on the other, and that asymmetry itself constitutes a strategic choice.

The timing and content of the responses matter as much as their frequency. Ukraine statements typically appeared within days of the invasion and were framed in the language of international solidarity, democracy, and academic freedom. The three universities that did address Gaza moved at strikingly different speeds: Ryukoku University issued a statement just five days after the October 2023 outbreak of hostilities, Nagasaki University responded after 33 days, and Sophia University took 234 days, releasing its statement in late May 2024. Notably, the rapid responses by Ryukoku and Nagasaki matched the speed typical of Ukraine statements, suggesting that institutional capacity was never the limiting factor. Nagasaki University, which had also accepted 40 Ukrainian students, demonstrated that peace-oriented institutions can sustain engagement on crises regardless of whether their stance aligns with Japan’s national diplomatic posture.

What distinguished these three institutions from their peers? The study identifies a common thread: explicit value foundations. Ryukoku is a Buddhist university, Sophia is Catholic, and Nagasaki carries a peace-oriented institutional identity rooted in its history as a survivor of atomic bombing. These normative anchors, the research suggests, gave their leaders a principled basis for action that transcended diplomatic calculation. By contrast, other religiously affiliated universities—including Rikkyo (Anglican), Doshisha (Congregational), Kwansei Gakuin (Methodist), and Aoyama Gakuin (Methodist)—did not issue Palestine statements, indicating that religious heritage alone was insufficient without a clearly articulated contemporary value commitment.

Perhaps the most striking finding concerns Japan’s flagship internationalization program. Universities designated as Super Global Universities (SGU) receive substantial government funding precisely because of their mandates to internationalize and engage with the world. Yet the study found that SGU institutions demonstrated complete silence on Palestine while unanimously supporting Ukraine. This, Abdelhadi argues, exposes a fundamental contradiction between performative and substantive internationalization. Internationalization, in this reading, has been reduced to market-driven activities—recruiting international students, climbing global rankings, and building partnerships with strategically convenient countries—rather than a genuine commitment to global engagement and universal academic values. When geopolitical pressures made engagement with one crisis costly, the market-oriented model of internationalization offered no resources for principled action.

The structural context of Japanese higher education helps explain why. The study describes a governance regime characterized by managed autonomy, in which universities are formally independent but operate under subtle and pervasive pressures from the Ministry of Education, Culture, Sports, Science and Technology (MEXT). One mechanism is amakudari—the circulation of former ministry officials into university presidencies and senior administrative posts—which creates information asymmetries favoring compliant institutions and exerts quiet pressure toward conformity. Japan’s official diplomatic position, which aligned strongly with Western support for Ukraine while maintaining a more cautious stance on the Middle East, thus filtered through the governance system into institutional communication. Universities reading the political winds found that supporting Ukraine carried reputational benefits and no risks, while addressing Gaza risked friction with government funders and key international partners.

Cultural factors add a further layer. The study invokes the Japanese concepts of tatemae—the publicly expressed principles that maintain social harmony—and honne—the actual intentions held privately. Abdelhadi is careful to note that this is not hypocrisy in the Western moralizing sense but a culturally legitimate way of managing contradictions. Applied institutionally, however, the tatemae of humanitarian solidarity was deployed selectively, voiced where it aligned with national interests and withheld where it did not. The result is what the study terms strategic silence: an organizational practice in which saying nothing is itself a communicative act, one that protects institutional relationships while allowing the appearance of principled neutrality to stand unexamined.

The theoretical contributions extend beyond Japan. The study demonstrates how managed autonomy in non-Western contexts produces distinctive patterns of organizational response that differ from the institutional neutrality debates playing out in the United States and Europe, where universities have faced their own controversies over statements on Gaza and Ukraine. It also extends organized hypocrisy theory through the concept of strategic silence, showing that silence can function as a deliberate organizational resource rather than a mere absence of communication. The findings carry implications for evaluating university social responsibility amid geopolitical pressures, and for assessing whether internationalization policies in different governance regimes produce institutions capable of principled action or only of strategically calibrated performance.

For the global higher education community, the study poses a pointed question: if universities claim universal values of human dignity and academic solidarity, what does it mean when those values are applied to one humanitarian catastrophe but not another of similar magnitude? The exceptional cases—Ryukoku, Nagasaki, and Sophia—suggest that institutional responses require clear normative anchors beyond market-driven internationalization. Without such anchors, the study implies, universities will continue to speak when speaking is safe and stay silent when silence is strategic, leaving the ideal of the globally engaged university hollow at precisely the moments it matters most.

Subject of Research: The asymmetric institutional responses of Japanese universities to the Ukraine and Gaza humanitarian crises

Article Title: The politics of institutional silence: Japanese universities’ asymmetric responses to international humanitarian crises

Article References: Abdelhadi, H. (2026). The politics of institutional silence: Japanese universities’ asymmetric responses to international humanitarian crises. Higher Education. https://doi.org/10.1007/s10734-026-01761-8

Image Credits: AI Generated

DOI: 10.1007/s10734-026-01761-8

Keywords: Japanese higher education, strategic neutrality, organized hypocrisy, university internationalization, Super Global Universities, institutional theory, humanitarian crises, Ukraine, Gaza, academic freedom, university governance, crisis communication