درخت حوزه‌های تخصصی

Allocating fixed costs with undesirable data has recently been one of the most important issues for managers to discuss. Lack of attention to undesirable data may lead to incorrect cost allocation. Considering and determining undesirable inputs and outputs, data envelopment analysis (DEA) technique can be significantly helpful in determining the cost allocation strategy. In-puts and outputs are divided into two desirable and undesirable groups. Obviously, desirable inputs and undesirable outputs must be reduced and undesirable inputs and desirable outputs must be increased to improve performance. This manuscript presents two strategies for allocating fixed costs with undesirable data. In the first strategy, each decision making unit (DMU) first determines the minimum and maximum shares that it can receive from the fixed resources while the efficiency of that DMU and other DMUs re-mains the same after receiving the fixed resources. Finally, the decision maker chooses the fixed cost for each DMU between the minimum and maxi-mum cost values proposed. In the second strategy, the allocation of fixed costs is done using the CCR multiplicative model with undesirable data. The effectiveness of both methods is examined by an applied study on the commercial banks.

This study was an endeavor to develop a model of identity among Iranian EFL learners. To achieve this end, a multiphase design was implemented. Initially, it attempted to investigate different factors of identity to propose and validate a model. Thus, 120 EFL learners studying in different English language institutes in Iran were randomly selected, and 36 learners were interviewed about their views of their identity in the qualitative phase. After extracting six factors of identity, including: second language acquisition and social status, cultural attachment, Persian language adhesion, pronunciation posture, technology involvement, and language identity, and second language knowledge, a questionnaire was constructed which reflected these factors. Then, in the quantitative phase, the questionnaire went through an exploratory factor analysis for the sake of validity. After its validity and reliability were corroborated through a pilot study with 20 learners, it was distributed among 120 EFL learners. Besides, Structural Equation Modeling (SEM) analysis was run to confirm that the final proposed model enjoyed validity for future research. To do so, the confirmatory factor analysis was run, and the model of identity was developed. Eventually, the possible relationship between 120 EFL learners’ identity and their English language achievement scores were examined, and the results of this phase indicated that there was a significant and positive relationship between learners’ identity and their English language achievement scores. The findings of this study can enhance awareness among English teachers, materials developers, and syllabus designers to equip themselves with the updated techniques to handle the possible challenges that may occur in EFL learning contexts.