Asian Journal of Economics, Business and Accounting

Greenwashing in ESG Practices of Business Entities: Concept Evolution, Detection Patterns, and Research Agenda

2026-07-11T12:39:08+00:00

This study presents a systematic literature review of greenwashing within Environmental, Social, and Governance (ESG) practices of business entities. The aim is to map the conceptual evolution of greenwashing in the ESG context, identify detection patterns used in empirical research, analyse the impact of ESG greenwashing on investor trust, firm value, and regulatory effectiveness, and formulate a future research agenda relevant to emerging-market contexts, particularly Indonesia. Following the PRISMA protocol, 35 articles published between 2020 and 2025 were retrieved from Scopus, Web of Science, and Google Scholar and analysed using a multi-paradigm analytical framework that integrates functionalist and critical perspectives. The synthesis identifies six thematic clusters: detection and measurement of ESG greenwashing, divergence among ESG raters, governance and managerial behaviour, anti-greenwashing regulation, greenwashing in developing-country contexts, and financial and capital-market impacts. The review further maps six detection methods, identifies six research gaps, and proposes a four-cluster research agenda prioritised by urgency and contextual relevance to Indonesia. The findings indicate that ESG greenwashing is not merely an individual managerial deviation but a systemic consequence of structural vulnerabilities embedded in the ESG institutional architecture, including rating fragmentation, process-based measurement bias, and the absence of independent assurance mechanisms. Theoretical, methodological, and practical contributions are discussed, along with an integrative framework intended to guide future empirical research on corporate sustainability governance in emerging markets.

Corporate Governance, Innovation Incentives and Firm Performance: A Critical Synthesis of Empirical Research

2026-07-03T12:16:55+00:00

The relationship between corporate governance mechanisms, research and development (R&D) investment, and firm performance occupies a central but contested position in contemporary financial economics, accounting, and management research. This article provides a comprehensive narrative review of the empirical evidence, drawing primarily on peer-reviewed studies published between January 2015 and February 2026, supplemented by foundational earlier contributions that remain essential for contextualising current debates. Synthesising findings from more than sixty published studies, the review addresses five principal domains: board structure and composition; ownership and institutional investment patterns; executive compensation and chief executive officer characteristics; antitakeover provisions and the market for corporate control; and the performance implications of R&D investment. Consistent, if nuanced, evidence emerges that board independence, long-horizon institutional ownership, and equity-based managerial incentives generally support R&D investment and innovation output, whilst short-term-oriented ownership and weak intellectual property regimes tend to suppress innovative activity. R&D investment is broadly positively associated with market valuation and long-run performance, though this relationship is moderated by financing constraints, institutional context, and investor composition. The article identifies persistent gaps relating to governance and innovation in emerging economies, digital sectors, and causal identification, and offers directions for future research.

Artificial Intelligence and Machine Learning for Payroll Fraud Detection in the United States Public Sector Payroll Systems: A Scoping Review

2026-07-08T12:05:37+00:00

Payroll fraud remains a significant concern in United States public sector payroll systems because it may lead to financial loss, weaken accountability, and reduce public trust in public financial management. This scoping review maps available evidence on the application of artificial intelligence and machine learning to payroll fraud detection in United States public sector and related financial oversight contexts. The review was guided by the Joanna Briggs Institute framework and reported in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews. English-language studies published between 2016 and 2026 were searched across Scopus, Google Scholar, EBSCOhost, SpringerLink, and the Social Science Research Network. After screening and full-text assessment, 21 studies were included in the review. Thematic synthesis identified five main themes: the shift from manual and rule-based fraud detection to proactive AI- and machine learning-enabled monitoring; the importance of data quality, data integration, and system interoperability; the use of anomaly detection, risk scoring, alerts, and case prioritisation; the need for explainability, human oversight, privacy protection, fairness, and responsible AI governance; and institutional readiness, technical capacity, and the limited payroll-specific evidence base. The findings indicate that AI and machine learning can support earlier identification of payroll irregularities, including ghost employees, overtime abuse, duplicate payments, unauthorised salary changes, and suspicious disbursement patterns. However, the available evidence remains stronger in related areas such as banking, tax fraud, audit analytics, financial fraud detection, and payment integrity than in public sector payroll systems specifically. Effective implementation requires reliable data, interoperable systems, explainable models, skilled personnel, privacy safeguards, and human-in-the-loop decision-making.

Foreign Capital Flows and Economic Growth: Evidence from Sub-Saharan Africa

2026-07-02T09:17:12+00:00

This study examines the relationship between foreign capital flows and economic growth in Sub-Saharan Africa using panel data covering 32 countries over the period 2000–2023, yielding 766 country-year observations. The analysis focuses on four key external financial flows: foreign direct investment, official development aid, remittances, and sovereign debt, while controlling for population, trade openness, and human capital. A fixed-effects regression model is employed following diagnostic testing, including the Hausman specification test, which supports the model’s suitability. The empirical findings indicate that foreign direct investment, human capital, population, and sovereign debt exert a statistically significant positive effect on economic growth in Sub-Saharan Africa. These results suggest that capital inflows and demographic expansion can contribute to economic performance when supported by adequate absorptive capacity and productive utilisation mechanisms. Conversely, official development aid, remittances, and trade openness are found to have a statistically significant negative association with economic growth. These outcomes imply that external inflows do not automatically translate into productive economic gains and may depend on institutional quality, financial intermediation, and the structure of domestic economies. The results further highlight the heterogeneous nature of foreign capital flows, indicating that their effectiveness varies depending on how resources are allocated and managed within recipient economies. The study concludes that improving human capital formation and strengthening policy frameworks for managing external resources are essential for enhancing the growth impact of foreign capital inflows in Sub-Saharan Africa.

Examining Explorative and Exploitative Approaches of International Entrepreneurship in the Sustainability Performance of Food and Beverage: Evidence from Multinational Companies in Nigeria

2026-07-06T09:41:34+00:00

Sustainability performance has become a key concern for multinational enterprises operating in emerging economies, where firms face economic constraints, social expectations and environmental risks. This study examines how explorative and exploitative entrepreneurship influence the sustainability performance of multinational food and beverage companies in Nigeria. Using a cross-sectional survey design, data were collected from 226 managers across selected multinational enterprises and analysed through multiple regression. The results show that both explorative and exploitative entrepreneurship have statistically significant positive effects on economic, social and environmental sustainability performance. Exploitative entrepreneurship shows stronger effects on economic and social sustainability, reflecting the role of efficiency, refinement, resource optimisation and the effective use of existing capabilities. Explorative entrepreneurship shows a stronger contribution to environmental sustainability, indicating the relevance of experimentation, innovation and novel solutions in addressing ecological concerns. The findings suggest that entrepreneurial ambidexterity is important for multinational food and beverage firms seeking to integrate sustainability into international operations. Firms that balance exploration and exploitation may be better positioned to support economic resilience, stakeholder-oriented social practices and environmental responsiveness. The study contributes to the international entrepreneurship and sustainability literature by linking dual entrepreneurial orientations to distinct dimensions of sustainability performance in an emerging-market context.

Exploring the Role of Storytelling in Expanding Market Reach of Digital MSMEs: A Bibliometric Analysis of Marketing Communication Research

2026-07-06T12:58:32+00:00

This study aims to map the development of research on storytelling in marketing communications related to the expansion of market reach for digital MSMEs. This study uses a bibliometric analysis approach to identify research trends, thematic structures, and relationships between topics in the relevant literature. Research data were obtained through data mining using Publish or Perish software from the Crossref database with three main keywords: "Storytelling Marketing", "Digital MSMEs", and "Market Reach", with each search yielding many publications and resulting in approximately 3,000 documents for analysis. The obtained bibliographic data were then analysed using VOSviewer software and a keyword co-occurrence approach to produce research network visualisations, trend analysis, and topic density analysis. The results show that the literature on storytelling in digital marketing forms three main research clusters: storytelling and brand communication, digital marketing and community activities, and the digital transformation of MSMEs. The trend analysis indicates that storytelling research is evolving from a focus on narrative communication and consumer experience to integration with digital marketing and the digital transformation of MSMEs. Topic density analysis shows that keywords such as marketing, storytelling, micro, digital transformation, and performance are the most dominant research themes in the analysed literature. This study provides an overview of the knowledge structure and development of storytelling research in the context of digital marketing and demonstrates the relationship between storytelling, digital marketing, and the digital transformation of MSMEs in the academic literature.

Socioeconomic Determinants of Poverty Levels in Kenya: Evidence from the Structural Drivers of Development and Inequality

2026-07-09T05:41:01+00:00

This study examined the socioeconomic determinants of poverty levels in Kenya using annual time-series data for 1990-2024. Poverty was measured using the poverty headcount ratio at the international poverty line of $2.15 a day in 2017 purchasing power parity. The analysis focused on financial access, secondary school enrolment, public health expenditure and income inequality as structural explanatory variables. An explanatory research design was adopted and an autoregressive distributed lag model was estimated after descriptive and diagnostic analyses. The selected specification used 33 observations after lag adjustment and followed an ARDL(2,1,1,1,1) structure. The findings showed that financial access had a negative and statistically significant association with poverty, suggesting that wider access to formal finance can support poverty reduction where financial services are inclusive and productive. Public health expenditure also had a negative and significant association with poverty, indicating that health investment can protect households from illness-related deprivation and improve human capital productivity. Income inequality had a positive and significant association with poverty, confirming the importance of distributional conditions in poverty outcomes. Secondary school enrolment had a positive and significant coefficient, suggesting that enrolment expansion alone may not reduce poverty where education quality, labour-market relevance and employment absorption remain weak. The study concludes that poverty reduction in Kenya requires coordinated policies that combine inclusive finance, effective health investment, education quality improvement and inequality reduction. The results are interpreted as econometric associations rather than definitive proof of causality.

Supply Chain Management Practices, Innovation and Sustainability Performance Among Manufacturing Firms in North Rift Region

2026-07-10T04:05:39+00:00

This study examined the moderating role of innovation in the relationship between supply chain management practices and sustainability performance among manufacturing firms in the North Rift Region of Kenya. The study focused on lean, resilient and green supply chain management practices. An explanatory cross-sectional research design was adopted. The target population comprised 500 senior, middle and lower-level managers from manufacturing firms operating in the region. A sample of 222 respondents was selected through stratified random sampling, and 207 completed questionnaires were returned, representing a response rate of 93.2%. Primary data were collected using structured questionnaires based on a five-point Likert scale. Data were analysed using descriptive statistics, reliability and validity tests, correlation analysis, multiple regression and hierarchical moderation analysis. The findings showed that firm sustainability performance had a mean score of 3.9855, while lean, resilient and green supply chain management practices and innovation had mean scores of 4.0491, 3.7005, 3.8068 and 3.4839, respectively. Reliability coefficients ranged from 0.751 to 0.898, indicating acceptable internal consistency. Regression results showed that lean, resilient and green supply chain management practices had positive and significant effects on sustainability performance. Innovation also had a positive and significant direct effect and strengthened each practice-performance relationship. The final model explained 90.8% of the variance in sustainability performance. The study concludes that manufacturing firms may achieve stronger sustainability outcomes when supply chain practices are supported by innovation capabilities.

The Influence of Social Media Marketing on Consumer Purchase Intention and Brand Loyalty in the Indian Banking Sector

2026-07-11T12:25:34+00:00

Background: Social media has become an important communication and relationship-management channel for banks, particularly in-service contexts where trust, responsiveness and customer engagement influence behavioural outcomes. In India, however, limited empirical evidence explains how specific social media marketing dimensions shape customers’ purchase intention and subsequent brand loyalty in the banking sector.

Aims: This study examined the influence of social media marketing on banking customers’ purchase intention and brand loyalty, with purchase intention tested as a mediating variable.

Methods: A quantitative cross-sectional design was adopted. Data were collected from 101 banking customers through a structured questionnaire using convenience sampling. Social media marketing was measured through five dimensions: entertainment, interaction, trendiness, customisation and electronic word-of-mouth (eWOM). The measurement and structural models were assessed using partial least squares structural equation modelling (PLS-SEM).

Findings: The results showed that all five social media marketing dimensions had statistically significant positive effects on purchase intention. eWOM and interaction emerged as the strongest predictors, indicating the importance of peer-generated content, customer reviews, responsiveness and two-way communication in banking-related social media engagement. Purchase intention also had a strong positive association with brand loyalty and mediated the relationships between social media marketing dimensions and brand loyalty.

Conclusion: The findings suggest that social media marketing can contribute to loyalty formation in the Indian banking sector by strengthening customers’ intention to use or continue using banking services. Banks should therefore prioritise credible, responsive and customer-oriented social media communication across digital banking platforms.

Factors Determining Labour Productivity Across Indian States: Evidence from the Industrial Sector

2026-07-17T12:24:55+00:00

Regional industrial growth depends partly on the efficiency with which labour and capital are used in the production process. This study examines the factors associated with labour productivity in the industrial sector across 21 Indian states. Using secondary data from published sources, including the Annual Survey of Industries, Statistical Abstracts of various states and state-level Human Development Index estimates, the study applies correlation analysis, simple linear regression and multiple regression. Five-year averages for 2019–20 to 2023–24 are used for the selected indicators, except for the Human Development Index because of its irregular availability. Labour productivity is measured as net value added per person engaged, while the explanatory variables include the Human Development Index, capital intensity, average industrial wage and per capita public development expenditure. The results show that capital intensity and average industrial wages have positive and statistically significant relationships with industrial labour productivity. In contrast, the Human Development Index and per capita public development expenditure do not show statistically significant direct effects in the present cross-sectional model. The multiple regression results indicate that capital intensity and average wages together explain 64.59% of the variation in labour productivity. The findings suggest that policies supporting technological upgrading, productive capital access and fair wage structures may contribute to industrial productivity improvement.

Behavioral Biases and Investment Decisions: Analyzing the Influence of Heuristics, Prospects and Planned Behavior on Retail Investors

2026-07-18T11:10:06+00:00

Background: Behavioural finance challenges the assumption of fully rational investment decisions by showing that cognitive biases can shape how retail investors evaluate risk, information and market opportunities. In this context, integrating behavioural biases with the Theory of Planned Behaviour provides a useful framework for examining the investment intentions of retail investors.

Aims: This study examines the influence of behavioral biases and TPB components such as attitude, subjective norms, and perceived behavioral control on investment intentions of retail investors based in Delhi-NCR region, where behavioral biases are treated as second order construct, consisting of anchoring, availability, loss aversion, mental accounting, overconfidence, representativeness, and regret aversion.

Method: A structured questionnaire was administered to 379 retail investors using purposive and snowball sampling techniques. The data were analysed using PLS-SEM (SmartPLS 4.0) with bootstrapping based on 10,000 resamples.

Findings: Behavioral biases emerged as the strongest predictor of intention to invest (β = 0.441, p < 0.001) followed by perceived behavioral control (β = 0.199, p < 0.001), attitude (β = 0.159, p = 0.001), while subjective norms were insignificant (β = 0.088, p = 0.113). It was further noted that attitude mediated the link between behavioral biases and the intention to invest (β = 0.149, p < 0.001). The model accounted for 58.6% of variance (R² = 0.586).

Conclusion: This study provides a validated second-order model of behavioral biases and demonstrates that biases outperform TPB constructs, thus broadening TPB to behavioral finance theory. This mediation by attitude also suggests that there are two parallel decision routes for investment, one involves evaluation of attitudes, while the other route goes directly to making the decisions based on affects. This study advises on design of intervention strategies to mitigate bias and boost self-efficacy among advisors, fintech, regulators and educators.