فرهاد حسین زاده لطفی

Background: Unlike banking development in country, banks have not been able to satisfy customers yet. Therefore, the present study aimed at investigating banks ethical responsibility to compensate for services failure and reviving it. Method: This study is applied in purpose, exploratory in approach and mixed (qualitative-quantitative) in data analysis. In qualitative phase and in order to design a model based on grounded theory, a group of experts in banking management and services marketing (including university professors, bank CEOs and banking industry marketing counselors) selected as society and 11 have been selected through snowball sampling and until reaching theoretical saturation. In-depth-interview was research instrument in this phase and data analyzed through coding. In quantitative phase, banking industry customers in Tehran considered as statistical society and 400 of them selected through cluster sampling with equal volume as statistical sample. In quantitative phase also the research instrument was researcher-made and closed questionnaire and path analysis and SPSS and Lisrel used to analyze data. Results: 134 primary concepts extracted in this study that 51 ultimate concepts classified in 31 main categories. This results lead to designing failure procedural pattern and reviving services in Iran’s banking industry (based on paradigmatic model structure) and model hypothetical relationships tested and approved in a wide society. Conclusion: Customer satisfaction and loyalty depends on organization adherence to professional ethics and responsibility that the most important sign of an organization responsibility is organized activity to compensate for services failure and reviving it.

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.