Electronic Human Resource Management (e-HRM) has become a strategic approach to support the digital transformation of human resource practices in organizations. This study analyzes the implementation of Waktoo, an internally developed e-HRM system at PT Kazee Digital Indonesia, through a qualitative case study. Data were collected using semi-structured interviews, observations, and documentation, and analyzed using Miles and Huberman’s interactive model, supported by manual coding and triangulation to ensure credibility. The SWOT analysis revealed several strengths, including face-detection–based attendance integrated with payroll and a user-friendly interface, while weaknesses included technical bugs, limited use of non-core features, and the absence of training modules. Opportunities include AI integration, HRIS market expansion, and the rising demand for digital HR solutions, whereas threats arise from established commercial HRIS providers, diverse user requirements, and system reliability issues. Based on these findings, strategic recommendations are formulated to optimize Waktoo’s development and competitiveness, such as adding HR development features, enhancing system stability, and strengthening customization capabilities. The study contributes theoretically by integrating SWOT with qualitative insights in evaluating e-HRM adoption and practically by providing strategies for improving the relevance and sustainability of in-house HR digitalization initiatives.

Handling dispersion of casein powders in water is widely encountered in the milk industry. However, in silico prediction of the apparent viscosity of these colloidal dispersions is not an easy task, especially when these micellar casein suspensions are highly concentrated, as in hyper-protein milk beverages, which are experiencing exponential market growth. In this work, Coarse-Grained (CG) models using Lennard-Jones potentials to model interactions were built for simulating rheological properties of colloidal micellar casein dispersions (native and demineralized). In a first approach, a polydisperse explicit CG model was developed. For this polydisperse CG model, the representation chain was composed of four large smooth spheres of different sizes mimicking the real distribution of casein colloids. The CG simulation results were validated by comparison with experimental rheological data for native colloidal casein dispersions. Both in-house experimental results and available data found in the literature were used for this purpose, covering a wide range of casein concentrations ([10 g/L–200 g/L], [8–20%] corresponding to casein concentration, colloid volume fraction and solid/liquid volume fraction, respectively). In a second approach, a simplified model using a monodisperse CG model was developed. This simplified model only included one type of soft sphere and was found to preserve the accuracy of the rheological prediction. Finally, a monodisperse CG model was set up to predict the behavior of demineralized micellar casein dispersions, for which a decrease in the average size of the micelle size distribution is observed when demineralization occurs. For all models, the comparison between the predicted and experimental rheological behavior is fully satisfactory, proving that the CG models proposed for casein-based micellar dispersions are physically well founded and that the proposed simplified representation chain, based on micelle size observation, makes sense.

Over the last decade, Nigeria has been persistently described as the world’s capital of poverty, with approximately half of its population reported to live below the poverty line according to the World Bank. This is a striking paradox given the nation’s status as the largest economy in Africa and one of the fastest-growing economies globally in recent years. The overwhelming evidence suggests that Nigeria’s economic growth has not been inclusive. This study therefore examined the moderating role of institutional quality in the relationship between financial inclusion and inclusive growth, employing time series data from 1990 to 2023. Estimated results from both the Autoregressive Distributed Lag (ARDL) model and the Quantile Generalized Method of Moments (QGMM)—used for robust inference—reveal that financial inclusion has a statistically significant positive impact on both aggregated inclusive growth (measured via principal component analysis) and disaggregated inclusive growth (including standards of living, life expectancy at birth, and GDP growth). The study also finds that institutional quality exerts a direct cautionary effect on inclusive growth and distorts the positive impact of financial inclusion. While this appears counterintuitive, the study attributes these cautionary effects to short-term disruptions that produce long-term ripple effects. It is recommended that institutional reforms be tailored to the peculiarities of the Nigerian economy and closely monitored to mitigate potential short-run disruptions that could undermine the long-term benefits of strong institutional quality.

This study investigates how inflation and monetary policy, as reflected in the policy interest rate (BI Rate), affect Indonesia's economic growth, as indicated by the GDP. Multiple linear regression analysis was employed to discover connections between independent and dependent variables in an economic setting. The analysis's findings indicate that neither the BI Rate nor inflation significantly affects GDP growth. Although not sufficiently strong to be regarded as statistically significant, the positive coefficients derived from both variables show a propensity for increases in inflation and policy interest rates to enhance economic growth. The significance of the interaction between the two variables in monetary policy is confirmed by simultaneous analysis, which reveals that both inflation and the BI Rate significantly contribute to GDP variance when examined together. These results suggest that monetary policy must work in tandem with fiscal policy and the real sector, as well as be adaptively managed to respond to changes in the global economy to effectively stimulate economic growth in Indonesia [2]. This study is anticipated to significantly aid policymakers in developing more potent plans to accomplish sustainable growth and national economic stability.

This study investigates the effect of inflation on economic growth in Nigeria using time series data spanning from 2010 to 2020. By examining the inflation rate alongside GDP growth rates, the research adopts a descriptive and comparative approach supported by graphical visualizations. The study further incorporates comparative insights from South Africa and Ghana to highlight regional patterns and deviations. Findings reveal that high inflation rates in Nigeria, especially post-2015, have adversely impacted GDP growth, supporting existing economic theories. The study concludes with actionable recommendations for inflation-targeting strategies and macroeconomic stabilization.

The rise of the digital economy has redefined competitiveness for MSMEs, positioning digital empowerment as a critical pathway for business resilience and long-term sustainability. This study aims to formulate a strategic framework that explains how local entrepreneurs can progress toward becoming digital champions through structured transformation stages. Adopting a descriptive qualitative approach, the research analyses interdisciplinary literature and documentary datasets, supported by empirical evidence from national MSME empowerment programs. Data were collected from policy briefs, government reports, academic studies, and case documentation, and examined using content interpretation, framework mapping, and theoretical empirical synthesis. Findings reveal that MSME transformation is driven by the interplay of mindset, capability development, and ecosystem collaboration, which are further operationalized through the CHAMP model Customer Value, Human-Centered Innovation, Alliance and Co-Creation, Market Expansion, and Purpose-Driven Growth. Four sequential transformation phases Go Modern, Go Digital, Go Online, and Go Global demonstrate clear pathways for business reinforcement, market expansion, and global competitiveness. The study concludes that scalable MSME empowerment requires integrated interventions that simultaneously strengthen entrepreneurial identity, digital skills, and ecosystem accessibility. Future initiatives are recommended to implement longitudinal evaluation and incorporate emerging technologies to maintain adaptability in increasingly dynamic markets.

In the era of globalization marked by a global growth projection of 2.8% in 2025 amid geopolitical tensions and supply chain disruptions, Indonesia and South Korea face economic shocks affecting GDP, inflation, and unemployment, prompting this qualitative descriptive study to analyze and compare their resilience strategies using secondary documents from BPS, Bank Indonesia, Bank of Korea, and IMF (2023-2025) as population with purposive sampling, analyzed via thematic reduction, comparative tables, and triangulation. Results show Indonesia sustained GDP growth above 5%, unemployment at 4.76%, and inflation at 0.76% in January 2025 through domestic market strengthening, downstreaming, and subsidies, while South Korea addressed 0.1% GDP contraction and high youth unemployment via flexible monetary policies, technological innovation, and vocational training. In conclusion, both nations' adaptive fiscal-monetary synergies proved effective, recommending export diversification for Indonesia and demographic incentives for South Korea to bolster future resilience.

Why do some developing countries sustain coherent institutional trajectories over long periods, while others cycle between reform, crisis, and incomplete recovery? Conventional measures of institutional quality emphasize levels of democracy, governance, or rule of law, yet they struggle to explain why countries with similar scores exhibit sharply different patterns of institutional persistence and rupture. This article advances a structural perspective on institutional stability, conceptualizing institutions as interdependent subsystems whose coherence, or misalignment, shapes long-run developmental trajectories.To operationalize this framework, the article introduces the Institutional Regime Stability Index (IRSI), a dynamic measure that captures the persistence of coherent institutional configurations rather than static institutional levels. Using comparative data for nine Latin American countries between 1900 and 2024, the analysis identifies three recurrent patterns of institutional development: resilient coherence, adaptive stability, and recurrent misalignment. Higher IRSI values are systematically associated with lower GDP growth volatility and greater capacity to attract foreign direct investment, linking institutional coherence to economic risk and policy credibility. By reframing institutional stability as a property of systemic coherence, the IRSI offers a new comparative lens for analysing development and institutional change.© The Author(s) 2026. Published by RITHA Publishing. This article is distributed under the terms of the license CC-BY 4.0., which permits any further distribution in any medium, provided the original work is properly cited maintaining attribution to the author(s) and the title of the work, journal citation and URL DOI.Article’s history: Received 10th of January, 2026; Revised 27th of January, 2026; Accepted for publication 2nd of February, 2026; Available online: 6th of February, 2026; Published as article in Volume II, Issue 1(3), 2026.

Mitigating electricity supply risks through flexible quota reallocation under cross-sectoral carbon market expansion

Lithium import demand and electric vehicle market growth in Europe: Perspectives on economic policy uncertainty and geopolitical turbulence

The demand for halal products has increased over the past few decades alongside the growing Muslim population worldwide. The halal market is expanding every year, not only in Islamic countries but also in non-Islamic countries. In most Muslim nations, people consume halal products because of halal certification, which guarantees that products are safe to eat and meet standards of quality, taste, and health. This study investigates the development of the halal industry in Brunei Darussalam using a PEST-embedded SWOT approach. Primary data were collected through 3 in-depth interviews with halal industry players, supported by 50 survey respondents, literature review and observation. Key findings reveal Brunei’s strengths in stringent halal certification procedures, strong government support, and public awareness. At the same time, weaknesses include insufficient enforcement manpower, low global ranking in the Global Islamic Economy Indicator, and overreliance on imports. Opportunities lie in leveraging ASEAN Free Trade, sustainable development goals, and halal product innovation, whereas threats include trade barriers, high technology costs, and a shortage of skilled manpower. The study highlights that political stability and institutional support provide Brunei with strong foundations, but economic diversification and technological upgrading remain urgent. Recommendations include targeted capacity-building, smart halal logistics, and regional market expansion to position Brunei as a credible halal hub.

This study examines the relationship between artificial intelligence (AI) and economic growth, focusing specifically on the channels through which AI-driven innovation may affect GDP growth. AI innovation is proxies by the number of granted AI-related patents, which also reveals the strength and robustness of patent activity in this field. The econometric approach, OLS, FE, Difference and System GMM, is used to investigate the significant macroeconomic determinants, including inflation, population growth, unemployment, government expenditure, and gross fixed capital formation (GFCF). The study findings show that AI patents are negatively associated with GDP growth in this model. It suggests that, at the national level, AI-related innovations are yet to be transformed into measurable economic gains. A plausible explanation is that AI technologies remain in an initial stage of adoption and diffusion, and their implementation requires skilled labor, complementary infrastructure, and substantial upfront costs, factors that delay their productivity-enhancing effects. Besides, GFCF, government expenditure, and population growth show a significant positive effect on GDP growth across the countries. It shows the continued importance of old drivers of economic expansion, mainly inflation, demographic dynamics, public spending, and physical investment. However, mergers are a barrier to economic growth. Therefore, unemployment does not appear to exert a statistically significant impact on the model employed. The results suggest that AI's future growth is unclear and needs more study, particularly regarding how AI advances can lead to wider economic gains. For now, the data confirms that economic progress hinges on macroeconomic stability and investment; AI's potential for growth will probably emerge over time with institutional readiness and supportive economic contexts.

Digitalization is increasingly central to economic growth strategies, yet robust macro-level evidence on the role of SME-led e-commerce remains limited. Drawing on the Resource-Based View, this study examines how SME digitalization, internet finance, and platform-based activities influence regional economic growth in China, and how these effects depend on digital infrastructure readiness (DIR). We construct an annual panel of 30 provincial-level regions in China over 2015–2024 and estimate dynamic relationships using two-step system GMM to address endogeneity and growth persistence. The results show that SME digitalization, supply-chain efficiency, mobile payment penetration, tech-driven employment growth, platform-economy contribution, and DIR all exert statistically significant positive effects on GDP growth. Quantitatively, a 10-percentage-point increase in SME digitalization is associated with approximately 0.3-percentage-point higher regional GDP growth, while a 10-point increase in DIR corresponds to about 0.4-percentage-point higher growth. Moderation analyses reveal that DIR significantly amplifies the growth effects of e-commerce expansion, mobile payments, and digital marketing, whereas its moderating role is weaker or insignificant for cross-border payments and supply-chain efficiency. These findings reconceptualize digitalization as a coordinated bundle of complementary resources and position DIR as a critical enabling capability for translating SME digital transformation into macroeconomic growth. The study offers policy-relevant evidence for targeting infrastructure investment and digital-economy strategies in emerging platform economies.

This study examines the long-term effects of economic and social factors affecting entrepreneurial activities across Türkiye’s NUTS1 regions between 2009 and 2022. Using the Fully Modified Ordinary Least Squares (FMOLS) methodology, the relationships among regional GDP growth, income inequality, unemployment rates, public education expenditures and early school leaving rates are analyzed. The results show that GDP growth and income inequality have a positive impact on entrepreneurial activities, whereas unemployment rate and public education expenditures have negative effects. Early school leaving rate is found to have a limited but positive effect on entrepreneurship. It explicitly links entrepreneurship to broader socio-economic dimensions, highlighting how factors such as income inequality, education, and unemployment shape entrepreneurial dynamics across regions. The findings reveal that economic and social factors play a multidimensional role in shaping entrepreneurship dynamics. By incorporating regional disparities and linking entrepreneurship with broader socio-economic dimensions, the study aligns with international literature on entrepreneurship and economic development. It also provides practical recommendations for policymakers, such as developing strategies to promote income equality, strengthening regional financial support mechanisms, and integrating entrepreneurship education into the national curriculum to foster sustainable development. This comprehensive analysis offers both insight into Turkey’s regional entrepreneurship landscape and a framework for policymakers aiming to balance economic growth with social equity.

The study investigates the relationship between bank profitability and a comprehensive list of bank-specific, industry-specific and macroeconomic variables using unique panel data from 23 Bangladeshi banks with large market shares from 2005 to 2019 employing the Pooled Ordinary Least Square (POLS) Method for regression estimation. The random Effect model has been used to check for robustness. Three variables, namely, Return on Asset (ROA), Return on Equity (ROE), and Net Interest Margin (NIM), have been used as profitability proxies. Non-interest income, capital ratio, and GDP growth have been found to have a significant relationship with ROA. In addition to non-interest income, market share, bank size, and real exchange rates are significant explaining variables if profitability is measured as NIM. The only significant determinant of profitability measured by ROE is market share. The primary contribution of this study to the existing knowledge base is an extensive empirical analysis by covering the entire gamut of independent variables (bank-specific, industry-related, and macroeconomic) to explain the profitability of the banks in Bangladesh. It also covers an extensive and recent data set. Banking sector stakeholders may find great value from the outputs of this paper: Regulators and policymakers may find this useful in undertaking analyses in setting policy rates, banking industry stability, and impact assessment of critical policy measures before and after the enactment, etc. Investors and the bank management are to use the findings of this paper in analyzing the real drivers of profitability of the banks they’re contemplating to invest and managing on a day-to-day basis. Journal of Business Studies, Vol. XLIV, No. 1, 2025 Page 139-164

Abstract This study examines the determinants of export sophistication across BRICS countries (Brazil, Russia, India, China, and South Africa) from 2000 to 2022. It focuses on the heterogeneous effects of macroeconomic variables economic growth (GDP), foreign direct investment (FDI), human capital, and research and development (R&D) as well as the impact of the COVID-19 pandemic on export sophistication. The study employs the cross-sectionally augmented autoregressive distributed lag (CS-ARDL) approach, which effectively captures cross-sectional dependence and slope heterogeneity, improving upon traditional panel estimation techniques. The empirical findings indicate that GDP growth, FDI inflows, human capital, and R&D expenditures positively influence export sophistication in BRICS economies, while the COVID-19 pandemic exerts a negative effect. These insights offer important policy implications for enhancing export quality and economic resilience in emerging markets.

This research experimentally investigates the association between multidimensional risk factors and economic growth, quantified by GDP as a partial indicator of advancement towards economically relevant Sustainable Development Goals (SDGs). This research experimentally investigates the correlation between multidimensional risk variables and economic growth, quantified by GDP as a partial indicator of advancement towards economically relevant Sustainable Development Goals (SDGs) in Saudi Arabia, particularly in alignment with the objectives of Saudi Vision 2030. This study utilizes annual data from 1990 to 2024 and employs the Autoregressive Distributed Lag (ARDL) bounds testing approach to examine the short-run and long-run relationships between economic growth, as measured by GDP, and five key risk dimensions: governance effectiveness, financial development, environmental pressure, human capital, and oil price volatility, which act as proxies for risk dimensions. The main contribution of this study is the integration of these governance, financial, environmental, human capital, and oil price risk factors into a single ARDL framework for Saudi Arabia from 1990 to 2024, using GDP growth as a proxy for progress toward SDGs within the Saudi Vision 2030 context, addressing gaps in prior studies that focus on individual determinants. The empirical evidence indicates a long-term cointegration relationship among the variables. Our findings indicate that government effectiveness and investment in human capital are important positive factors associated with long-term economic growth, thereby validating the importance of institutional improvements and educational expenditures. In contrast, fluctuations in oil prices and environmental pressures are linked to adverse association, highlighting issues related to resource dependency and ecological degradation. Financial development exhibits a negative long-run association, indicating potential inefficiencies or diminishing returns in loan distribution. The study offers essential policy recommendations, such as expediting digital governance reforms, allocating financial resources to non-oil SMEs (SDG 8), aligning educational curricula with labor market demands, and implementing stricter environmental regulations to separate economic growth from emissions.

Micro, Small, and Medium Enterprises (MSMEs) are the backbone of the Indonesian economy, but are faced with various obstacles such as access to capital, marketing, and innovation. This study aims to analyze the forms of collaboration between the village government and the private sector, identify inhibiting factors, and evaluate the contribution of such collaboration to the growth of MSMEs in Abiansemal Village, Badung Regency, Bali. Using a descriptive qualitative approach with in-depth interviews, observations, and documentation studies, this study found that collaboration manifests in program-based partnerships (training, market facilitation), structured financial and non-financial support (access to capital, shared facilities), Corporate Social Responsibility (CSR) programs, and informal networks. The main inhibiting factors include communication and data coordination gaps, different priorities and expectations, limited internal capacity of MSMEs (managerial and digital skills, quality standards), licensing bureaucracy, and lack of initial trust. Nonetheless, this collaboration significantly contributed to increased turnover (25-40%), employment (15-20% of MSMEs recruited workers), market expansion (regional and digital), improved product/service quality, increased access to capital (30% increase in microloans), and improved managerial/technical skills of MSME actors. The research recommends strengthening MSME data systems, improving proactive coordination and communication, more efficient licensing facilitation, inclusive partnership approaches, sustainable mentoring programs, and improving internal MSME readiness. The findings provide insights for stakeholders in designing more effective and sustainable collaboration strategies for local economic development.

ABSTRACT: The increasing use of social media platforms has transformed traditional marketing approaches, leading to the rapid growth of social media influencer marketing. Influencer marketing leverages the credibility, authenticity, and engagement of social media personalities to influence consumer attitudes and purchasing decisions. This study examines the impact of social media influencer marketing on consumer buying behavior in the Indian context, with specific focus on influencer trustworthiness, expertise, authenticity, and brand influencer alignment. The research adopts a descriptive and quantitative research design. Primary data were collected through a structured questionnaire administered to a sample of 30 - 50 active social media users within the young age group. Secondary data were obtained from academic journals, industry reports, and relevant digital marketing literature. The study is supported by theoretical frameworks such as Source Credibility Theory and the Elaboration Likelihood Model (ELM), which explain the persuasive role of influencers in shaping consumer behavior. The findings reveal a significant positive relationship between influencer marketing and consumer purchase intention. Respondents showed higher trust and buying inclination toward products promoted by influencers perceived as honest, relatable, and knowledgeable. The study also highlights that micro and nano influencers generate stronger engagement and credibility among consumers. The research concludes that social media influencer marketing is an effective strategic tool for building consumer trust, enhancing brand awareness, and influencing purchase decisions in the digital marketplace. The research offers practical insights for marketers in selecting suitable influencers, designing ethical campaigns, and optimizing digital marketing strategies. It also contributes academically by bridging traditional consumer behavior theories with emerging influencer- driven marketing practices in India’s evolving digital ecosystem. Keywords: Social Media Influencer Marketing, Consumer Buying Behavior, Influencer Credibility, Purchase Intention, Consumer Trust, Digital Marketing, Brand Engagement.

China’s rapid transition into a super-aged society is accelerating demand for advanced wearable healthcare sensors tailored for long-term, low-burden monitoring. While numerous reviews discuss demographic and policy contexts, fewer highlight the latest wearable sensor research emerging from Chinese laboratories and companies. This Mini Review summarizes representative advances published in the last five years across three major application areas—chronic metabolic disease management, neurodegenerative disease monitoring, and cardiovascular risk mitigation—focusing on sensor design, sampling media, data integration, and clinical relevance. Rather than examining demographic trends or general market growth, we emphasize technological breakthroughs such as non-invasive glucose-sensing microneedle patches, CKD-oriented urine/breath analyzers, multimodal gait–EEG neurodegenerative platforms, and bioresorbable cardiovascular implants that reflect China's emphasis on long-term, low-burden, and telemedicine-ready care. By concentrating on these China-originated devices and research prototypes, this review aims to provide a concise update on emerging concepts and highlight how these technologies reflect localized priorities—such as non-invasive sampling and family-assisted tele-care—while shaping future global trends.