Journal of Economics, Management and Trade

Industry Specific Framework for Artificial Intelligence Adoption in Project Risk, Cost and Schedule Management

Richard Bill Owusu Darko — 2026-07-10

Artificial intelligence (AI) is increasingly influencing project management practice, particularly in relation to project risk, cost and schedule management. However, the reviewed literature indicates that existing applications and adoption approaches remain fragmented across sectors and project functions. This study examines the use of AI in project risk, cost and schedule management and develops an industry-sensitive conceptual framework for structured AI adoption. A scoping review approach was used to map relevant literature published between 2015 and 2026 across construction, infrastructure, engineering, information technology, energy, insurance and public sector project contexts. The review identifies key AI functionalities, including predictive analytics, machine learning-based forecasting, natural language processing, optimisation algorithms, explainable AI and intelligent decision-support systems. These functionalities are aligned with project management tasks such as risk identification and mitigation, cost estimation and control, financial forecasting, schedule planning, delay prediction and resource allocation. The findings suggest that AI can support improved forecasting, earlier risk detection, enhanced cost control and more adaptive schedule management. However, successful implementation depends on data quality, digital infrastructure, organisational readiness, workforce capability, governance arrangements, transparency, cybersecurity and human oversight. The proposed framework integrates these factors across readiness, data and technology infrastructure, AI functional modules, governance and outcomes. The study contributes to project management scholarship by linking AI capabilities with core project management functions while recognising the need for sector-specific adaptation.

Does Corporate Governance Drive Financial Performance? Empirical Evidence from Palestinian Non-Financial Listed Firms

Monther Eldaia — 2026-07-03

This study examines the effect of selected corporate governance mechanisms on the financial performance of non-financial companies listed on the Palestine Exchange during 2017-2024. The analysis focuses on board independence, gender diversity, foreign board membership, firm size and leverage, while financial performance is measured by return on assets and return on equity. Panel data were collected from 33 listed non-financial companies. After accounting for lagged performance in the regression models, the empirical estimations are based on 231 balanced observations. Panel estimated generalised least squares with random effects and panel-corrected standard errors was employed to account for firm-level differences and potential heteroscedasticity. The findings indicate that past profitability has a positive and statistically significant effect on current return on assets and return on equity, suggesting persistence in firm performance. Firm size also shows a positive and significant relationship with both performance measures, whereas leverage has a negative and statistically significant effect on return on assets and return on equity. Foreign board membership is negatively associated with return on assets but is not statistically significant in the return on equity model. Board independence and gender diversity do not show statistically significant effects. The results suggest that financial structure and firm scale are more strongly associated with performance than formal board-composition characteristics in the Palestinian non-financial listed sector.

An Empirical Analysis of Factors Affecting Gross Domestic Savings in India (1991 to 2023)

Ruchika Pandey — 2026-07-07

This study examines the factors associated with gross domestic savings in India during 1991–2023. Gross domestic savings provide an important source of domestic resources for investment, capital formation and economic growth, especially in a developing economy where reliance on external finance may increase vulnerability. The study uses secondary annual data from the RBI Handbook of Statistics on Indian Economy and the World Bank. Gross domestic savings is treated as the dependent variable, while gross domestic product, broad money, inflation, tax revenue and bank credit to the private sector are used as explanatory variables. The analysis applies unit root testing through the Augmented Dickey-Fuller and Phillips-Perron procedures, followed by the ARDL bounds testing approach to examine long-run and short-run relationships. The results indicate the existence of a long-run relationship among the selected variables. Gross domestic product and bank credit to the private sector show positive and significant associations with gross domestic savings. In contrast, broad money and tax revenue show negative effects, while inflation is not statistically significant in the Indian case. The error correction term is negative and significant, indicating adjustment towards long-run equilibrium. The findings suggest that strengthening income growth, improving productive credit availability and encouraging household financial savings may support the mobilisation of domestic savings in India.

Investigating the Role of Economic Elements in Shaping the Trade Balance, and Reviewing the Twin-deficit Model and the Marshall-Lerner Condition: An Econometric Study on Bangladesh

Md. Aminul Islam — 2026-07-07

This study investigates the role of selected macroeconomic variables in shaping the trade balance of Bangladesh over the period 1980-2024. The analysis considers the exchange rate, budget deficit, terms of trade, inflation and economic growth as explanatory variables, with the trade balance as the dependent variable. The study applies time-series econometric techniques, including the Augmented Dickey-Fuller test, Johansen cointegration test and Granger causality test, to examine stationarity, long-run relationships and causal linkages among the variables. The ADF results indicate that all variables are stationary at first difference. The Johansen cointegration results show the presence of a long-run relationship among the selected macroeconomic variables. The estimated long-run coefficients indicate that exchange-rate depreciation and economic growth are positively associated with the trade balance, whereas the budget deficit, inflation and terms of trade are negatively associated with it. The positive relationship between exchange-rate depreciation and the trade balance supports the Marshall-Lerner condition in the context of Bangladesh. The negative relationship between the budget deficit and the trade balance also provides evidence consistent with the Twin-Deficit hypothesis. The Granger causality results indicate both unidirectional and bidirectional causal relationships among the variables. The findings suggest that improving Bangladesh's trade balance requires prudent fiscal management, export diversification, import management, trade facilitation and a stable macroeconomic environment.

FMCG Distributors Perspectives on Marketing Constraints and Operational Inefficiencies in Rural FMCG Networks

S. Jothipriya — 2026-07-08

Rural FMCG distribution networks in India operate under structurally constrained market conditions where distributors function as the principal executional link between manufacturers and fragmented retail systems. The study aims to investigate the relationship between marketing constraints and operational inefficiencies of FMCG distributors operating in the rural area. The study is specifically centered on FMCG networks in rural areas involving the dimensions of inventory inefficiency, delivery and logistics inefficiency, financial operational inefficiency and sustainability of the distributor. This study was based on empirical design and primary data was collected from 163 FMCG distributors operating in rural market in Salem district. The sampling method used was judgement sampling to ensure that the distributors have consistent operational exposure in rural areas and decision making authority. The primary data were collected by using a structured questionnaire with a 5 point Likert Scale of ‘strongly disagree’ to ‘strongly agree'. The measure of the reliability was ensured using Cronbach's Alpha values that were higher than the acceptable limit for all constructs and the validity of the instrument was supported by Kaiser–Meyer–Olkin and Bartlett's Test measures. The multi-variate analysis of variance, canonical discriminant analysis, exploratory factor analysis and multidimensional scaling were used for analysing the relationships of marketing constraints and operational inefficiency dimensions. The results showed highly statistically significant relationships between marketing constraints and delivering the two indicators of inventory inefficiency, delivery disruptions and financial stress and operational sustainability in rural distribution systems. The study adds to the existing rural FMCG literature by proposing an operational framework for the rural FMCG industry centered on the distributor who brings together elements of marketing rigidity and executional inefficiency. The results also offer managerial implications for creating sustainable and responsive marketing structures that can be adapted to rural marketing to enhance the sustainability of the marketing system.