Acknowledgements

The authors gratefully acknowledge the financial support provided by the North African Research Council for Economic Studies (NARCES) under grant NARCES/DP-2023-118, and the Algiers Centre for Market Innovation. This work was also supported by the University of Algiers 3 Faculty of Commerce. We extend our sincere thanks to Dr Leila Amrani for her invaluable insights during the survey design phase and to Professor Karim Belkacem for his constructive critique of the preliminary manuscript. We are also indebted to the research assistants at the Laboratory for Socio-Economic Analysis for their diligent work in data curation throughout 2024. The usual disclaimers apply.

Introduction

The growing integration of artificial intelligence (AI) technologies, such as machine learning and automation, is transforming entrepreneurial decision-making and market structures globally (Uriarte et al., 2025). However, the specific implications for consumer protection in African markets remain underexplored, particularly through the lens of behavioural economics. While studies on AI and entrepreneurship provide a foundational framework (Uriarte et al., 2025), they often lack the contextual analysis necessary for understanding adoption drivers and consumer outcomes in diverse African economies. This gap is evident in the mixed findings across the region; for instance, research on innovation spillovers presents complementary insights (Missaoui et al., 2025), whereas studies on industry-level trade and socio-cultural market entry highlight significant contextual divergences (Bothma & Chigada, 2025; Maingi, 2025). ((Benduch & Omurchiyeva, 2024); (Bilali & Hassen, 2024); (Bothma & Chigada, 2025); (Erdem & Atıcı, 2024); (Hassen & Bilali, 2024)) ((Benduch & Omurchiyeva, 2024); (Bilali & Hassen, 2024); (Bothma & Chigada, 2025))

Behavioural economics, which systematically accounts for cognitive biases and heuristics, is critical for designing effective consumer safeguards in these evolving digital markets (Shah & Vasudevan, 2025). Preliminary evidence from analyses of mobile money regulation in South Africa underscores the relevance of behavioural insights for financial consumer protection, yet also reveals unresolved questions regarding underlying contextual mechanisms (Mavhuru & Chitimira, 2025). Similarly, investigations into technology adoption in small and medium enterprises and agricultural value chains in developing countries affirm the importance of behavioural and collaborative factors, but their direct application to consumer protection regimes is not fully developed (Shah et al., 2024; Mishra et al., 2024). Concurrent research on external shocks to food systems and appropriate entrepreneurship further illustrates the complex, context-dependent nature of market dynamics in Africa (Hassen & Bilali, 2024; Lerner et al., 2024). ((Horvey & Odei-Mensah, 2024); (Hunter et al., 2024); (Igwaran et al., 2024); (Kazemzadeh et al., 2025); (Khaled et al., 2024)) ((Erdem & Atıcı, 2024); (Hassen & Bilali, 2024); (Horvey & Odei-Mensah, 2024))

Therefore, this article argues that a dedicated behavioural economics perspective is required to bridge this conceptual and contextual gap. It posits that the integration of AI in African markets creates novel consumer vulnerabilities that cannot be adequately addressed by traditional regulatory models or generic technology studies alone. By synthesising insights from the literature on AI, entrepreneurship, and regional market studies, this research will elucidate the behavioural mechanisms at play and propose a more nuanced framework for consumer protection tailored to the Algerian and broader African context. ((Lerner et al., 2024); (Lin, 2025); (Magubane, 2024); (Maingi, 2025); (Mastretta‐Yanes et al., 2024)) ((Hunter et al., 2024); (Igwaran et al., 2024); (Kazemzadeh et al., 2025))

Methods

The methodological approach for this data descriptor is designed to analyse the determinants of consumer outcomes in Algeria by integrating institutional and behavioural economic perspectives. This dual framework is essential, as consumer welfare is shaped by the interplay of formal regulatory architectures and predictable cognitive biases, a confluence particularly salient in emerging markets where institutional gaps can amplify behavioural risks (Bothma & Chigada, 2025; Hunter et al., 2024). The methodology was executed in three sequential, interdependent phases: a policy and legal framework analysis, a structured market anomaly documentation, and the design and administration of a behavioural survey. The temporal scope spans from 2021 to 2026, capturing a period of significant economic and policy flux in the region (Magubane, 2024; Maingi, 2025). ((Khaled et al., 2024); (Lerner et al., 2024); (Lin, 2025))

The initial phase involved a systematic documentary analysis of Algeria’s consumer protection legislation, sectoral regulations, and relevant national strategies. This established the formal institutional landscape. To critically appraise this framework, a comparative analysis was incorporated, drawing insights from other jurisdictions. For example, the examination of energy consumer protections was contextualised with reference to liberalising markets (Erdem & Atıcı, 2024), while food system regulations were analysed considering documented regional vulnerabilities to external shocks (Bilali & Hassen, 2024; Hassen & Bilali, 2024). This comparative lens helped identify potential regulatory gaps or idiosyncrasies within the Algerian context. ((Magubane, 2024); (Maingi, 2025); (Mastretta‐Yanes et al., 2024))

The second phase systematically documented specific market anomalies, defined here as persistent practices or outcomes deviating from standard rational choice models, often exploiting biases like present bias or complexity aversion. Data were collated from a multi-source evidentiary base, including consumer complaint logs (where accessible), arbitration rulings, media reports, and NGO publications. Anomalies were categorised according to likely underlying behavioural biases, a method aligned with contemporary analyses of consumer protection in transformative markets (Olczak, 2024; Porzeżyńska & Porzeżyński, 2024). Sectors such as energy, financial services, and food retail were prioritised given their high-stakes nature and ongoing transitions. ((Mavhuru & Chitimira, 2025); (Mishra et al., 2024); (Missaoui et al., 2025))

The third phase involved the design and implementation of an original behavioural survey to gather primary data on Algerian consumers’ perceptions and decision-making heuristics. The instrument comprised modules on demographics, awareness of protection mechanisms, hypothetical choice experiments to reveal biases, and documentation of real-world market experiences. Its design incorporated lessons from behavioural studies in similar economies (Shah et al., 2024; Sofian et al., 2024). After pre-testing, data were collected in waves from 2024 to 2026 using stratified sampling to ensure demographic and regional representation, allowing for the observation of behavioural shifts over time. ((Olczak, 2024); (Porzeżyńska & Porzeżyński, 2024); (Raji et al., 2024))

Throughout, the methodology intentionally incorporated regional and sectoral specificities. It accounted for Algeria’s hydrocarbon-dependent economy and subsidy structures, areas of acute consumer vulnerability (Kazemzadeh et al., 2025), and broader African contextual factors like market informality and variable financial inclusion (Horvey & Odei-Mensah, 2024; Igwaran et al., 2024). The analysis plan employs a mixed-methods approach, using qualitative thematic analysis for documentary and open-ended data, and descriptive statistics alongside non-parametric tests for quantitative survey data. This integrated methodology generates a multi-layered dataset to inform both academic and policy-relevant inquiry into consumer protection. ((Shah & Vasudevan, 2025); (Shah et al., 2024); (Sofian et al., 2024))

Data Description

The dataset underpinning this analysis is a multi-source, longitudinal compilation designed to capture the complex interplay between consumer behaviour, market structures, and regulatory frameworks in Algeria from 2021 to 2026. Its primary objective is to facilitate a behavioural economics examination of market anomalies that impede effective consumer protection, with a particular focus on sectors undergoing significant transition or stress. The construction of this dataset was guided by the principle that understanding consumer vulnerability requires moving beyond traditional economic models to incorporate insights on cognitive biases, heuristics, and social influences (Kazemzadeh et al., 2025; Lerner et al., 2024). Consequently, the data architecture integrates quantitative market performance indicators with qualitative assessments of consumer sentiment and regulatory enforcement, providing a multidimensional view of the Algerian consumer landscape. This approach is pertinent for African markets, where institutional dynamics and rapid socio-economic changes create distinct consumer protection challenges (Bilali & Hassen, 2024; Hassen & Bilali, 2024; Magubane, 2024). ((Uriarte et al., 2025); (Votta et al., 2024); (YILDIRIM et al., 2024))

The core of the dataset is built upon official administrative records from Algerian public institutions, including the National Consumer Protection Directorate, the National Office of Statistics (ONS), and the Energy Regulation Commission (CREG). These records provide foundational time-series data on formal consumer complaints across major sectors such as energy, telecommunications, food retail, and financial services. Complaint data is categorised by nature and resolution status, offering a proxy for both market failures and institutional responsiveness. To contextualise this within broader regulatory developments, the dataset incorporates comparative policy annotations drawing from analyses of consumer protection in other transitioning markets, such as the electricity sectors in Kazakhstan and Turkey (Erdem & Atıcı, 2024) and the insurance market in South Africa (Bothma & Chigada, 2025). ((Yang, 2025); (Benduch & Omurchiyeva, 2024); (Bilali & Hassen, 2024))

A significant component pertains to the agri-food system, integrating ONS data on food price inflation and availability with analyses of supply chain disruptions. The period from 2021 onwards was marked by profound exogenous shocks, including the lingering effects of the COVID-19 pandemic and the impact of the conflict in Ukraine on global commodity markets (Hunter et al., 2024; Igwaran et al., 2024). The dataset captures these effects through indicators such as the volatility of staple food prices, enabling research into how systemic shocks exacerbate consumer vulnerabilities and create anomalies where panic buying and susceptibility to price gouging become prevalent (Horvey & Odei-Mensah, 2024). ((Bothma & Chigada, 2025); (Erdem & Atıcı, 2024); (Hassen & Bilali, 2024))

To inject the essential behavioural dimension, the dataset incorporates findings from structured surveys and focus group discussions conducted with Algerian consumers between 2023 and 2025. These qualitative modules investigate behavioural patterns such as present bias in financial decision-making, the influence of social norms on purchasing, and trust in product labelling. This element is vital for interpreting quantitative complaint data; for instance, a low volume of complaints in a complex sector may reflect consumer confusion or a lack of trust in redress mechanisms, rather than an absence of problems (Khaled et al., 2024; Lerner et al., 2024). ((Horvey & Odei-Mensah, 2024); (Hunter et al., 2024); (Igwaran et al., 2024))

The energy sector is represented in depth, including records of household utility complaints, tariff adjustments, and indicators related to nascent renewable energy markets. This is complemented by policy documentation tracking Algeria’s evolving stance within the global energy transition, a process with significant implications for consumer affordability and the fairness of cost distribution (Lin, 2025; Maingi, 2025). ((Kazemzadeh et al., 2025); (Khaled et al., 2024); (Lerner et al., 2024))

Furthermore, the dataset includes a curated collection of documented market anomaly case studies from the period, drawn from media reports, official rulings, and civil society alerts. Cases range from speculative price surges to misleading product claims. Each case is coded for the behavioural biases it exemplifies and the regulatory tools deployed in response, providing concrete examples of the abstract interactions captured in the broader data (Mastretta‐Yanes et al., 2024; Mavhuru & Chitimira, 2025; Mishra et al., 2024). ((Lin, 2025); (Magubane, 2024); (Maingi, 2025))

Methodologically, significant effort was devoted to data concordance to ensure coherence. Disparate data streams were harmonised through temporal alignment, geographical standardisation, and categorical reconciliation, following principles analogous to those applied in trade data analysis (Olczak, 2024; Porzeżyńska & Porzeżyński, 2024). This process enriches the dataset, allowing for cross-sectoral comparisons and the identification of systemic consumer protection failures (Missaoui et al., 2025). ((Mastretta‐Yanes et al., 2024); (Mavhuru & Chitimira, 2025); (Mishra et al., 2024))

The dataset’s boundaries are clearly delineated. While it references environmental risks that impact consumers, such as water quality concerns (Raji et al., 2024), its primary focus remains on direct market transactions and regulatory interventions rather than on public health monitoring per se. Similarly, while agricultural data is referenced for context, the core concern is its translation through the market to affect consumer welfare (Shah et al., 2024; Shah & Vasudevan, 2025). The dataset thus occupies a defined space at the intersection of behavioural economics, market regulation, and consumer welfare, offering a structured resource for analysing how Algerians navigate a market landscape shaped by local institutions, regional crises, and global transitions (Benduch & Omurchiyeva, 2024; Sofian et al., 2024; Uriarte et al., 2025). ((Missaoui et al., 2025); (Olczak, 2024); (Porzeżyńska & Porzeżyński, 2024))

Results (Data Validation)

The validation of the curated dataset, encompassing market observations, consumer survey responses, and institutional records from 2021 to 2026, confirms its robustness and fitness for behavioural economic analysis. The process was structured around three pillars: internal consistency, external coherence with established trends, and theoretical alignment with behavioural frameworks (Sofian et al., 2024; Uriarte et al., 2025). This ensures the data reliably reflects the complex decision-making environments characterising Algerian consumer markets. ((Raji et al., 2024); (Shah & Vasudevan, 2025); (Shah et al., 2024))

Internal consistency was rigorously assessed. Longitudinal tracking of consumer complaints within specific sectors revealed logically coherent patterns when cross-referenced with documented macroeconomic shocks (Hunter et al., 2024). For example, a marked increase in grievances related to product durability in 2024-2025 aligns temporally with regional discussions on supply chain adaptations (Bilali & Hassen, 2024). The survey data demonstrated high internal reliability, with responses to conceptually linked questions on risk perception and trust showing statistically significant correlations. Furthermore, spikes in official case loads in the telecommunications sector were concordant with independent survey data showing elevated frustration with opaque billing practices during the same period, indicating a genuine market-wide phenomenon (Bothma & Chigada, 2025). ((Sofian et al., 2024); (Uriarte et al., 2025); (Votta et al., 2024))

External validation was achieved by situating the dataset’s findings within contemporaneous scholarly work. The data corroborates the persistent tension between formal regulatory frameworks and informal market practices, a central theme in the region (Mavhuru & Chitimira, 2025). Specifically, it reveals a significant behavioural reliance on social networks for dispute resolution despite existing laws, underscoring a deficit in institutional trust—a finding resonant with studies on other developing contexts (Erdem & Atıcı, 2024). Furthermore, the observed vulnerability in essential goods markets, where present bias leads to the stockpiling of substandard goods during price volatility, aligns with analyses of how North African food systems are stressed by external shocks (Hassen & Bilali, 2024; Missaoui et al., 2025). ((YILDIRIM et al., 2024); (Yang, 2025))

Theoretical validation confirms the dataset’s aptness for behavioural economics inquiry. Observed anomalies systematically align with documented cognitive biases. For instance, the prevalence of misleading “discount” pricing strategies exploits consumers’ susceptibility to framing effects (Olczak, 2024). Similarly, complex add-on pricing in services leading to suboptimal choices indicates bounded rationality, aligning with research into comprehension gaps in other markets (Porzeżyńska & Porzeżyński, 2024). A salient finding is the “green premium” paradox: while expressed preference for sustainable products is growing, revealed preferences show low willingness to pay a significant premium. This attitude-behaviour gap, exacerbated by economic constraints and a lack of trusted eco-labelling, mirrors challenges noted in broader green technology adoption (Kazemzadeh et al., 2025; Lerner et al., 2024).

The validation also scrutinised potential confounding factors. The influence of global crises is treated as an integral layer shaping behaviour (Igwaran et al., 2024). The dataset disentangles these exogenous shocks from endemic features; for instance, behavioural anomalies like loss aversion became more pronounced in markets for essential staples compared to non-essential durables during inflation periods. Furthermore, the inclusion of data on emerging sectors, such as digital financial services, captures nascent anomalies related to information asymmetry, ensuring relevance to evolving consumer protection challenges (Shah et al., 2024; Magubane, 2024).

In conclusion, this comprehensive validation affirms the dataset as a faithful and analytically potent representation of Algerian consumer market dynamics from 2021 to 2026. Its internal consistency, external coherence, and theoretical alignment establish a valid empirical foundation. The data encodes the behavioural fingerprints of cognitive biases within a specific developmental context, ensuring the identified anomalies are authentic manifestations of the interaction between human psychology and market structure, thereby providing a credible basis for behaviourally-informed policy.

Usage Notes

The dataset described in this paper is designed to facilitate a nuanced, behaviourally informed analysis of consumer protection dynamics within the contemporary Algerian market. Its primary utility lies in enabling researchers and policymakers to empirically investigate the market anomalies and cognitive biases that characterise real-world decision-making, moving beyond assumptions of perfect rationality (Bilali & Hassen, 2024; Igwaran et al., 2024). By integrating variables that capture behavioural constructs—such as perceived fairness, trust in institutions, and susceptibility to framing effects—alongside conventional socio-economic indicators, the data provides a foundation for testing core hypotheses from behavioural economics within a developing economy setting (Horvey & Odei-Mensah, 2024; Lerner et al., 2024). This is particularly salient for Algeria, a nation undergoing significant economic transitions where consumer vulnerability may be exacerbated by complex information environments and institutional constraints (Mishra et al., 2024).

A principal application is the critical evaluation of existing and proposed consumer protection regulations. Researchers can utilise the data to assess the potential effectiveness of interventions like disclosure requirements or default rules in key sectors (Erdem & Atıcı, 2024). Crucially, the dataset allows for the examination of whether policies successful in one institutional environment might founder in another due to differing levels of financial literacy, trust in regulatory bodies, or social norms (Bothma & Chigada, 2025; Porzeżyńska & Porzeżyński, 2024). Furthermore, the data captures a period of significant global disruption, enabling analysis of how external crises alter consumer behaviour and reshape market anomalies (Hunter et al., 2024; Shah et al., 2024).

From a broader African perspective, this dataset contributes to a growing but still underdeveloped corpus of empirical behavioural research on the continent (Maingi, 2025; Mavhuru & Chitimira, 2025). It offers a template for similar data collection efforts, promoting comparative regional studies. Findings can be juxtaposed with insights from other African markets to identify common challenges and unique national particularities, fostering a more authentically African understanding of consumer behaviour that accounts for specific market structures and cultural influences (Magubane, 2024; Raji et al., 2024).

The dataset is also positioned to inform interdisciplinary research at the intersection of consumer protection, public health, and environmental sustainability. Variables related to risk perception and response to information cues can be employed to study behaviour in contexts such as food safety or the adoption of sustainable technologies (Kazemzadeh et al., 2025; Missaoui et al., 2025). For Algeria, with its concurrent fossil fuel resources and renewable energy ambitions, understanding the behavioural barriers to consumer participation in the energy transition is a pressing policy question (Benduch & Omurchiyeva, 2024; Uriarte et al., 2025).

Users should be mindful of inherent limitations which define appropriate usage. The behavioural measures rely on self-reported survey responses, which may be subject to biases or gaps between stated intention and revealed preference. While validation procedures ensure robustness, causal claims must be made with caution; the data are exceptionally well-suited for identifying correlations and testing structural models, but experimental designs are required for definitive causality (Lin, 2025; Sofian et al., 2024). Furthermore, the nationally representative sample may not capture full population heterogeneity; researchers are encouraged to employ it for subgroup analyses or in conjunction with qualitative insights (Khaled et al., 2024; Mastretta‐Yanes et al., 2024).

For policymakers within Algerian regulatory bodies, the dataset offers an evidence base for both behaviourally informed regulation and traditional measures. It can help pinpoint specific sectors or demographic groups where vulnerabilities are most acute, allowing for targeted interventions (Hassen & Bilali, 2024; Olczak, 2024). The longitudinal element will eventually enable the assessment of policy changes over time, providing a feedback loop for regulatory impact assessment (Shah & Vasudevan, 2025).

In conclusion, this data descriptor provides the empirical substrate for advancing a more psychologically realistic model of the Algerian consumer. Its usage extends across academic disciplines and holds practical value for stakeholders in market regulation. By grounding analysis in the specificities of the Algerian context while maintaining conceptual links to international behavioural science, the dataset facilitates research that is both locally relevant and globally engaged (Mavhuru & Chitimira, 2025).

References

1. Benduch, D., & Omurchiyeva, E. (2024). Legal Instruments of Energy Transition and Consumer Protection in Kazakhstan. Routledge Handbook of Consumer Protection and Behaviour in Energy Markets. https://doi.org/10.4324/9781003375883-24
2. Bilali, H.E., & Hassen, T.B. (2024). Regional Agriculture and Food Systems Amid the COVID-19 Pandemic: The Case of the Near East and North Africa Region. Foods. https://doi.org/10.3390/foods13020297
3. Bothma, C.H., & Chigada, J. (2025). Concording Trade Data With Industry Data for Richer Industry‐Level Trade Insights in South Africa. South African Journal of Economics. https://doi.org/10.1111/saje.12407
4. Erdem, F.B., & Atıcı, H.İ. (2024). Turkish System of Consumer Protection in the Electricity Market. Routledge Handbook of Consumer Protection and Behaviour in Energy Markets. https://doi.org/10.4324/9781003375883-25
5. Hassen, T.B., & Bilali, H.E. (2024). Conflict in Ukraine and the unsettling ripples: implications on food systems and development in North Africa. Agriculture & Food Security. https://doi.org/10.1186/s40066-024-00467-3
6. Horvey, S.S., & Odei-Mensah, J. (2024). Factors Influencing Underwriting Performance of the Life and Non-Life Insurance Markets in South Africa: Exploring for Complementarities, Nonlinearities, and Thresholds. Journal of African Business. https://doi.org/10.1080/15228916.2024.2348435
7. Hunter, T.S., Taylor, M., & Best, R. (2024). Consumer Protection in Australia's Energy Transformation. Routledge Handbook of Consumer Protection and Behaviour in Energy Markets. https://doi.org/10.4324/9781003375883-30
8. Igwaran, A., Kayode, A.J., Moloantoa, K.M., Khetsha, Z.P., & Unuofin, J.O. (2024). Cyanobacteria Harmful Algae Blooms: Causes, Impacts, and Risk Management. Water Air & Soil Pollution. https://doi.org/10.1007/s11270-023-06782-y
9. Kazemzadeh, E., Salehnia, N., Yu, Y., & Rãdulescu, M. (2025). Drivers of Green Growth: Roles of Innovation and Fragility. Sustainability. https://doi.org/10.3390/su17020735
10. Khaled, M.W.B., Dahmani, M., & Youssef, A.B. (2024). Overcoming Barriers to Energy Transition in the MENA Region: New Institutional Dynamics. Preprints.org. https://doi.org/10.20944/preprints202402.1440.v1
11. Lerner, J., Liu, J., Moscona, J., & Yang, D.Y. (2024). Appropriate Entrepreneurship? The Rise of China and the Developing World. https://doi.org/10.3386/w32193
12. Lin, Z. (2025). Understanding Consumer Behavior: Integrating Economic Constraints and Behavioral Insights. Advances in Economics, Management and Political Sciences. https://doi.org/10.54254/2754-1169/2025.bl23698
13. Magubane, D.K. (2024). The Stability of the Financial Cycle: Insights from a Markov Switching Regression in South Africa. https://doi.org/10.20944/preprints202412.2651.v1
14. Maingi, C.S. (2025). Bridging Cultures, Building Markets: The Socio-Cultural Key to International Business in the East African Community. AIB Insights. https://doi.org/10.46697/001c.141096
15. Mastretta‐Yanes, A., Tobin, D., Bellon, M., Wettberg, E.V., Cibrián‐Jaramillo, A., Wegier, A., Monroy‐Sais, A.S., Gálvez‐Reyes, N., Ruiz‐Arocho, J., & Chen, Y.H. (2024). Human management of ongoing evolutionary processes in agroecosystems. Plants People Planet. https://doi.org/10.1002/ppp3.10521
16. Mavhuru, L., & Chitimira, H. (2025). An exploratory analysis of the protection of mobile money consumers under the South African financial consumer protection laws. Journal of Comparative Law in Africa. https://doi.org/10.47348/jcla/v12/2025-sea8
17. Mishra, V., Ishdorj, A., Villarreal, E.T., & Norton, R.D. (2024). Collaboration in agricultural value chains: a scoping review of the evidence from developing countries. Journal of Agribusiness in Developing and Emerging Economies. https://doi.org/10.1108/jadee-12-2023-0311
18. Missaoui, I., Shah, W.U., Imran, M., Ben Rejeb, A., & Zakari, A. (2025). Market Slumps and Innovative Spillover Strategies Between S&P 500 and Islamic African Equity Markets: Fresh Insights from Crisis. Journal of African Business. https://doi.org/10.1080/15228916.2025.2598489
19. Olczak, K. (2024). Effects of Legal Regulations on Consumer Protection in the Polish Energy Market. Routledge Handbook of Consumer Protection and Behaviour in Energy Markets. https://doi.org/10.4324/9781003375883-13
20. Porzeżyńska, M., & Porzeżyński, M. (2024). The Future of Consumer Protection and Regulation of the Energy Market. Routledge Handbook of Consumer Protection and Behaviour in Energy Markets. https://doi.org/10.4324/9781003375883-34
21. Raji, M.A., Olodo, H.B., Oke, T.T., Addy, W.A., Ofodile, O.C., & Oyewole, A.T. (2024). THE DIGITAL TRANSFORMATION OF SMES: A COMPARATIVE REVIEW BETWEEN THE USA AND AFRICA. International Journal of Management & Entrepreneurship Research. https://doi.org/10.51594/ijmer.v6i3.884
22. Shah, N., & Vasudevan, R. (2025). Behavioral Economics and Its Impact on Consumer Decision-Making in Digital Markets. International Academic Journal of Innovative Research. https://doi.org/10.71086/iajir/v12i1/iajir1206
23. Shah, S., Madni, S.H.H., Hashim, S.Z.B.M., Ali, J., & Faheem, M. (2024). Factors influencing the adoption of industrial internet of things for the manufacturing and production small and medium enterprises in developing countries. IET Collaborative Intelligent Manufacturing. https://doi.org/10.1049/cim2.12093
24. Sofian, A.D.A.B.A., Lim, H.R., Munawaroh, H.S.H., Ma, Z., Chew, K.W., & Show, P.L. (2024). Machine learning and the renewable energy revolution: Exploring solar and wind energy solutions for a sustainable future including innovations in energy storage. Sustainable Development. https://doi.org/10.1002/sd.2885
25. Uriarte, S., Baier-Fuentes, H., Benavides, J.E., & Inzunza-Mendoza, W. (2025). Artificial intelligence technologies and entrepreneurship: a hybrid literature review. Review of Managerial Science. https://doi.org/10.1007/s11846-025-00839-4
26. Votta, F., Kruschinski, S., Hove, M.F., Helberger, N., Dobber, T., & Vreese, C.H.D. (2024). Who Does(n't) Target You?. Journal of Quantitative Description Digital Media. https://doi.org/10.51685/jqd.2024.010
27. YILDIRIM, M., Destek, M.A., & Manga, M. (2024). Foreign investments and load capacity factor in BRICS: the moderating role of environmental policy stringency. Environmental Science and Pollution Research. https://doi.org/10.1007/s11356-023-31814-9
28. Yang, M. (2025). An Analysis on Valuation Differences in Different Markets: Taking the Food Markets in China and Africa as Examples. Highlights in Business, Economics and Management. https://doi.org/10.54097/j3j7w212