Multi - criteria decision making

The theory of psychology focuses on the explanation and prediction of individuals by examining specific behavior rather than the expression of an organization or society and on non-objective phenomena rather than an objective, and its importance for the management of the contingency arises from the fact that the function of the individual at any given time must be evaluated based on his conditions and working situations and due to its complex and diverse dimensions, decision making confronts with several choices and criteria which can be examined by multi-criteria analysis. This applied research aims to rank the psychological theories with an accounting approach based on the management of contingencies using the AHP method. The method of this study was a descriptive survey conducted by distributing the questionnaire. The statistical population of the study consisted of elites and accounting experts with over 20 years of job experience in Tehran. Sixty-eight individuals were selected randomly, and the questionnaires were distributed among them. After collecting the research for data analysis using expert choice software, the research, and ranking of the data were done using the AHP technique. The findings of the study indicate that the motivation theory and social psychology theory, and finally, cognitive psychology theory are based on priority order. In other words, in the accounting-based approach to contingency management, most motivational theories are presented and show a higher impact, one of the most important reasons for which can be attributed to the reliance of accounting on individual management

Objective : Reducing waste and improving productivity are crucial challenges in today’s competitive manufacturing landscape. Lean production tackles these issues by eliminating activities that do not add value, cutting costs, and enhancing quality. However, the success of lean implementation relies on selecting strategies that align with an organization’s operational context. This study evaluates four fundamental lean strategies under various production conditions: Work-in-Progress (WIP) Inventory Reduction, Batch Size Reduction, Setup Time Reduction, and Multi-skilled Workforces. Methods : A hybrid methodology was utilized, integrating discrete-event simulation (DES) with multi-criteria decision-making (MCDM). Six scenarios were modeled, varying production capacity (low, medium, and high) and work shift schedules (one or two shifts). The Best-Worst Method (BWM) was employed to determine the weights of the evaluation criteria: total cost, available inventory, waiting time, and lead time. The VIKOR method was then used to rank the strategies for each scenario. Results : The results indicate that total cost (weight = 0.54) is the most critical evaluation criterion, followed by available inventory (0.27), waiting time (0.11), and lead time (0.08). Both simulation and VIKOR analyses demonstrated a contextual pattern: reducing setup time was more effective than other strategies in low-capacity environments. In contrast, reducing batch size consistently ranked highest in medium and high-capacity environments, regardless of the shift schedule. Conclusion : The findings highlight that lean strategies' effectiveness depends on the context. Reducing setup time is most beneficial for resource-limited systems, while reducing batch size offers greater advantages in high-output environments. The hybrid simulation-MCDM framework created in this study is a structured and objective tool for managers, allowing them to choose lean strategies aligned with their specific operational conditions. This, in turn, enhances supply chain performance and fosters long-term competitiveness.

Objective : In the competitive global retail industry, achieving sustainable competitive advantage is a key factor for long-term success. This advantage arises when companies effectively utilize their unique resources and capabilities to outperform competitors. Operational efficiency and financial performance are critical for evaluating competitiveness and investment attractiveness. Data Envelopment Analysis (DEA) is a standard method for measuring efficiency, but classical DEA cannot fully rank efficient units. Integrating DEA with multi-criteria decision-making (MCDM) methods addresses this limitation, considering investor-relevant financial ratios. This study proposes a two-stage approach to evaluate and rank retail companies comprehensively.  Methodology: In the first stage, an input-oriented CCR model of DEA is applied, with assets, operating expenses, and the number of employees as inputs, and total revenue and net profit as outputs, to assess relative efficiency. In the second stage, financial indicators—asset turnover, dividend yield, return on equity (ROE), return on assets (ROA), and return on investment (ROI)—alongside DEA efficiency scores are evaluated using the PROMETHEE II method to generate a complete preference-based ranking of retailers. Results : DEA in the first stage provides relative efficiency insights but cannot rank efficient units. Employing PROMETHEE II in the second stage, and considering financial ratios, overcomes this limitation and produces a comprehensive ranking. Validation against DEA, hybrid DEA–PROMETHEE II, and hybrid DEA–AHP rankings demonstrates a strong alignment of the results with the actual market positions of retailers. Conclusion : The proposed method enables investors to identify high-performing companies and provides retailers with a strategic tool to monitor competitiveness, identify strengths and weaknesses, optimize resource allocation, and achieve a sustainable competitive advantage.