The mining industry faces increasing challenges in enhancing productivity within complex operational environments characterized by the interaction of technical, organizational, human, and external factors. Nevertheless, existing studies frequently examine these determinants independently, thereby limiting a comprehensive understanding of their relative importance and combined influence on operational performance. This study develops a decision framework to identify and prioritize the factors affecting productivity in medium-scale mining in the Coquimbo Region, Chile, through the application of the Analytic Hierarchy Process (AHP) based on expert judgment obtained from active mining operations. The AHP model was structured using two criteria, seven subcriteria, and twenty-three decision factors, whose consistency and reliability were assessed through the consistency ratio (CR) and Cronbach’s alpha coefficient. The results revealed a marked predominance of Internal factors (75.0%) over External factors (25.0%), indicating that productivity is influenced primarily by variables that can be managed at the organizational level. Among the evaluated subcriteria, Work planning achieved the highest priority (32.0%), whereas Scheduling and control (10.2%), Human factors (6.4%), and Working conditions (5.2%) emerged as the most influential decision factors. Furthermore, sensitivity analysis confirmed the robustness and stability of the model. Beyond establishing a prioritization of productivity determinants, this study provides a decision-support framework that can assist mining companies in strengthening productivity management and improving operational performance in medium-scale mining.
This study examines how experts in traditional manufacturing prioritize environmental, social, and governance (ESG) factors, and what these perceived priorities imply for sustainable-development strategy. Rather than measuring competitiveness outcomes directly, it captures the relative importance that experienced managers assign to ESG criteria. Drawing on a systematic literature review and two rounds of focus group discussions (FGD) with ten industry and academic experts, a hierarchical framework of three criteria and nineteen sub-criteria was constructed and evaluated through an analytic hierarchy process (AHP) survey of 26 experienced managers in the textile, machine-tool, and hardware-component industries. Aggregating pairwise judgments by the geometric mean, the environmental dimension received the highest weight (0.5657), followed by the social (0.2600) and corporate governance (0.1742) dimensions, with all comparison matrices satisfying the consistency criterion (C.R. ≤ 0.10). At the sub-criterion level, effective energy management (global weight 0.1607), pollution prevention (0.1252), toxic-waste management (0.0860), resource recycling and reuse (0.0840), and employee rights and well-being (0.0741) ranked highest, indicating that experts prioritize energy efficiency, pollution control, regulatory compliance, and workforce stability. A sensitivity analysis confirms that environmental primacy is robust to moderate re-weighting of the three dimensions. A notable divergence between the qualitative emphasis on governance during the FGD and its comparatively low AHP weight is interpreted as a sequencing of managerial attentionfrom urgent environmental compliance and cost efficiency, through workforce resilience, toward longer-term governance optimization rather than as evidence of a causal effect on competitiveness. Grounded in the resource-based and stakeholder perspectives, the study contributes an empirically based, theory-informed prioritization framework for an under-researched sector and offers managers, policymakers, and investors a reference for staged ESG implementation and resource allocation.
Ching-hsing Chang, Cheng-Fu Wang, Wen-Tsung Wu et al.· Business and Economic Resear...· 0 citations
A multi-criteria decision-making framework for evaluating six AI tools against eight sustainability-oriented criteria indicates that improving individual productivity and enhancing employee engagement and motivation are the most influential evaluation criteria.
A. Puška, Jurica Bosna, Darko Božanić· Journal of Operations Intell...· 0 citations
Decision-making is one of the most fundamental activities within various organizations, and human resources are consistently involved in it, either individually or collectively. Decisions are always made in alignment with achieving organizational objectives; therefore, their quality directly or indirectly affects the entire organization and its human capital. Consequently, identifying and ranking the factors influencing decision-making plays a crucial role in enhancing organizational performance. In this regard, the present study aims to identify and rank the sub-criteria affecting the decision-making process using the Fuzzy Analytic Hierarchy Process (FAHP) technique. The findings indicate that the individual criterion exerts the highest influence, while the external organizational criterion is the least influential in the decision-making process. Among the sub-criteria, emotions and the alignment between competencies and job content rank the highest. This underscores their significance in performance evaluations and competency assessments during recruitment, selection, appointment, or strategic decision-making processes within organizations. Therefore, it is imperative for organizations to invest in these criteria to strengthen their decision-making processes.
Unknown authors· Management, Education and De...· 0 citations
This paper investigates the impact of internal factors, such as information technology readiness and owner/manager commitment, and external factors, such as regulatory support and competitive pressure, on the use of accounting information systems (AIS) levels among Iraqi small and medium-sized enterprises (SMEs). A quantitative approach via self-administered questionnaires; 190 self-administered questionnaires were distributed to the managers and owners of SMEs in Basra using a purposive sampling technique and analyzed using the partial least squares structural equation modeling (PLS-SEM) approach. The findings of this study demonstrated that internal factors, including information technology readiness and owner/manager commitment, and external factors, including regulatory support and competitive pressure, significantly and positively influenced SMEs’ AIS usage levels. The study provides meaningful contributions by expanding understanding of the use of AIS in controlling processes, operational efficiency, planning processes, and financial reporting, which assist SME managers and owners in sound decision-making and in creating short- and long-term strategies to survive in a competitive market, with a focus on both internal and external factors. The study recommended that the managers and owners could focus on multiple levels of AIS use when developing system processes.
H. Kareem, Mohammed Dauwed, A. Aldujaili· Humanities and Social Scienc...· 0 citations
Purpose. To develop and empirically verify a model-based approach to assessing the impact of a hybrid project management methodology on the performance of software development enterprises, taking into account the level of managerial maturity and the moderating role of artificial intelligence tools.
Methodology. The study is based on an original survey of 93 Ukrainian IT enterprises (2026) and combines cluster analysis (the k‑means algorithm with the silhouette quality criterion), multiple regression modelling (OLS), the Analytic Hierarchy Process (AHP) with verification of the consistency of expert judgements (CR < 0.1), and three-level scenario modelling. The enterprise typology is constructed by level of managerial maturity through the aggregation of managerial, engineering and business indicators.
Findings. A typology comprising three enterprise types is empirically confirmed: start-up, established Agile practices, and mature enterprise level. The regression model (R2 = 0.957) revealed a statistically significant effect of the presence of a project management office, CI/CD maturity and AI readiness on the composite project performance index (PPI). The transformation of the management system is substantiated through three scenarios: baseline, formalisation of the hybrid methodology, and integration of artificial intelligence tools. An adaptive PPI structure with differentiated subindex weights and assessment time horizons is proposed; the projected performance gain falls within the range of 10–40 %, peaking at highly mature enterprises.
Originality. A multi-level model for assessing the impact of a hybrid project management methodology has been developed and empirically verified which, unlike descriptive maturity models, combines an enterprise typology based on managerial maturity, an adaptive composite PPI indicator and a four-stage scheme for transforming management practices. The model operationalises the non-linearity of the transition between maturity levels while accounting for the moderating role of AI tools and the resource constraints of the enterprise.
Practical value. The proposed model is intended to serve as an analytical instrument for substantiating managerial decisions concerning the adoption of a hybrid methodology and the integration of artificial intelligence at software development enterprises. Its application delivers a predictably positive economic effect through the reduction of losses, revenue growth and an increase in the intangible value of assets, and provides a quantitative rationale for investment decisions by demonstrating positive NPV and IRR.
M. Bosovska, A. Piliukov· Naukovyi Visnyk Natsionalnoh...· 0 citations
The development of professional accounting service firms results from the interaction of a set of human, organizational, institutional, technological, and professional factors. This study aimed to identify the factors shaping the development of these firms in Iran and simultaneously examine their relative priorities and their influence–dependence positions. The study employed a sequential exploratory mixed-methods design. The statistical population consisted of 24 experts in accounting and finance during the 2025–2026 period who met the required criteria in terms of academic expertise, professional experience, and familiarity with the activities of accounting firms. These individuals were selected through purposive sampling using the snowball technique. In the qualitative phase, data were collected through semi-structured interviews, and the process continued until theoretical saturation was achieved. Data analysis was based on the grounded theory approach of Strauss and Corbin (1990) and was conducted using MAXQDA software. In the quantitative phase, to prioritize and examine the strength of relationships among the extracted criteria and subcriteria, data were collected through a questionnaire and were prioritized using the fuzzy analytic hierarchy process (FAHP); they were also examined using fuzzy DEMATEL in terms of network prominence and net influence. The qualitative findings led to the identification of five main categories: human capital and professional knowledge development; structure and governance of accounting firms; the institutional environment and professional structure; technology and transformation of the accounting profession; and professional quality and ethics. Together, these categories comprised 16 subcriteria. The FAHP results showed that, among the main criteria, human capital and professional knowledge development had the greatest weight and importance in the development of professional accounting service firms, followed by the structure and governance of accounting firms. At the subcriterion level, digital transformation in the accounting profession, professional human capital and development, and technology received the highest priorities. The fuzzy DEMATEL results further showed that human capital and professional knowledge development and the structure and governance of accounting firms were among the causal and influential factors in the model, whereas the other criteria primarily played the role of affected factors. The findings can provide an analytical framework for policymaking and decision-making aimed at developing professional accounting service firms in Iran.
Unknown authors· Business, Marketing, and Fin...· 0 citations
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