The process of selecting the optimal option among multiple conflicting criteria is a fundamental task across various disciplines and is known as multi-criteria decision-making (MCDM). This study seeks to enhance the Objective Pairwise Adjusted Ratio Analysis (OPARA) method, which is limited by its inability to rank alternatives when any criterion within the decision matrix assumes a zero value. To address this limitation, an additional transformation step is introduced, resulting in the development of the M-OPARA method. The effectiveness of the M-OPARA method has been rigorously assessed through diverse case studies, incorporating different sets of criterion weights derived from 20 scenarios, and by comparing its performance against several MCDM techniques, including OPARA, PIV, ROV, SAW, WASPAS, MARCOS, and FUCA. The findings indicate that the M-OPARA method achieves high accuracy in ranking alternatives and successfully mitigates the constraints of the OPARA method. The methodological advancements introduced by M-OPARA constitute a substantial improvement in the rank ability of alternatives within decision-making frameworks. This novel approach facilitates more precise and dependable decision-making in practice, equipping decision-makers with a more flexible and robust analytical tool
In the contemporary, highly competitive restaurant sector, securing high-quality food raw materials is pivotal to achieving sustained business success. An organised and systematic supplier selection process is fundamental for ensuring operational efficiency, cost control, and consistent service standards. The present study introduces a structured framework designed to assess and rank restaurant raw material suppliers by integrating subjective evaluations across multiple criteria. The proposed methodology follows a two-phase process. The first phase entails the identification of essential supplier evaluation criteria, utilising rank-based weighting methods to determine their relative significance from the perspective of restaurateurs in Thailand. In the second phase, the fuzzy technique for order preference by similarity to the ideal solution (fuzzy TOPSIS) is applied to assess and rank potential suppliers based on their aggregate performance. A practical case study is presented involving an independent full-service restaurant in Thailand that was required to select from four candidate suppliers. This case is used to demonstrate the effectiveness of the framework. Furthermore, a sensitivity analysis is conducted to examine the impact of different weighting approaches on the final supplier rankings. The results highlight eight key evaluation criteria: quality level, product cost, responsiveness speed, communication systems, delivery performance, lead time, fill rate, and process flexibility. Findings from the sensitivity analysis indicate that supplier rankings vary according to the weighting methodology applied, underscoring the necessity for adaptable decision-making models. Such flexibility is crucial as the relative importance of these criteria can shift in response to market dynamics or specific operational priorities. For restaurant operators, adopting a systematic approach is vital to address the inherent complexity and uncertainty of supplier assessments. Incorporating multiple weighting techniques can strengthen the robustness of selection processes. This study offers practical guidance for enhancing procurement strategies and competitive advantage, while also providing suppliers with valuable insights into industry requirements and expectations.
Inventory management is integral to ensure that products are available at the right time which enhance the company's operational efficiency. To optimize this, the study objective was to test the impact of IT infrastructure, demand forecasting, technology integration, and supply chain resilience on inventory management with the mediating effect of decision-making effectiveness of manufacturing companies. Cross-sectional quantitative data were collected from 260 employees of manufacturing companies using a convenient sampling technique. Hypothesis results show that IT infrastructure, demand forecasting, technology integration, and supply chain resilience have a positive and significant impact on inventory management. Decision-making effectiveness also significantly increases inventory management. Decision-making effectiveness also mediates among IT infrastructure, demand forecasting, technology integration, supply chain resilience, and inventory management of manufacturing companies. The study results indicated that increasing technological awareness and supply chain resilience could significantly improve inventory management in manufacturing companies. Furthermore, strengthening the effectiveness of decision-making also strengthens these impacts through serving as a key mediating mechanism. This study uniquely integrates multiple technological and strategic factors into one model, highlighting the mediating role of decision-making effectiveness in improving inventory management.
Research on the determinants of wages remains relatively limited, particularly within Central and Eastern Europe. This study addresses this gap by examining the personal factors that influence both salary levels and overall remuneration of project managers. The investigation employed two perspectives, one centred on corporate positions and the other on the project management discipline. Data were collected from Hungarian project managers using the 11th edition of the Project Management Institute’s Salary Survey questionnaire. A total of 257 valid responses were analysed through descriptive statistics and multivariate methods. The results revealed several variables with a significant effect on salary and total compensation. In relation to salary, eight factors were identified: possession of a PMP® certification (13%), length of professional experience (2% per year), years of project management experience (1–2% per year), along with five specific job positions (21–33%). For total compensation, six key determinants were found: PMP® certification (15–16%), work experience (2% per year), project management experience (2% per year), weekly working hours (0.6% per hour), portfolio management competence (12%), non-predictive approaches such as agile, iterative or incremental methods (10–13%), and risk management competence (13–14%). These insights are valuable for project management practitioners when negotiating remuneration and also provide a basis for researchers and human resource specialists to enhance salary and benefits estimation models.
This study investigates the influence of executives’ artificial intelligence (AI) capability on firm-level Environmental, So-cial, and Governance (ESG) outcomes within developing economies, recognising that such dynamics may diverge from those observed in advanced markets. Focusing on China as a representative context, the analysis explores the underlying pathways linking executives’ AI capability with ESG per-formance, while also examining the contingent effects of political dependence dimensions, including resource redun-dancy and ownership structure. Grounded in a strategic deci-sion-making perspective, the study posits that executives’ AI capability primarily informs ESG-oriented managerial judgements and investment allocations, rather than directly determining ESG outcomes. Utilising panel data spanning 2011 to 2023, the findings reveal three key insights. First, executives’ AI capability exerts a positive effect on ESG performance. Second, the presence of redundant resources weakens this relationship, whereas private ownership en-hances it. Third, additional examination shows that execu-tives’ AI capability is positively associated with symbolic environmental performance, but demonstrates no statistically significant linkage with substantive environmental perfor-mance, thereby indicating a strategic trade-off between sym-bolic and substantive ESG engagement. Collectively, these findings contribute to a more nuanced understanding of how managerial competencies at the individual level shape ESG outcomes in developing-country settings, while also offering practical implications for both corporate leaders and policy-makers.
