Interdisciplinary Journal of Management Studies
Year:2018 | Volume:11 | Issue:1 |Papers Count:8

Nonlinear MUSA is an extension of MUSA, which employs a derived approach to analyze customer satisfaction and its determinants. It is a preference disaggregation approach, widely welcomed by scholars since 2002, following the principles of ordinal regression analysis. N-MUSA as a goal programing model, evaluates the level of satisfaction among some groups including customers, employees, etcetera according to their values and expressed preferences. Using simple satisfaction survey data, N-MUSA aggregates the different preferences in a unique satisfaction function. The main advantage of this approach is to consider and convert the qualitative form of customer judgments and preferences in an ordinal scale based on a simple questionnaire to an interval scale, in the first place, and to develop various fruitful analytical indices in order to get more knowledge of customers in the second place. In spite of the abovementioned strengths, this paper tackles some computational shortcomings within MUSA and leads to the development of nonlinear form (N-MUSA), which is more effective and efficient in practice. This paper takes MUSA and its drawbacks into account, to introduce N-MUSA as a more efficient alternative, then, deploys it in numerical examples and a real case for more insights.

It is generally accepted that Data Envelopment Analysis (DEA) is a method for indicating efficiency. The DEA method has many applications in the field of calculating the relative efficiency of Decision Making Units (DMU) in explicit input-output environments. Regarding imprecise data, several definitions of efficiency can be found. The aim of our work is showing an equivalence relation between one of the models of DEA with imprecise data and Multiple Objective Linear Programming (MOLP). The relation between DEA and MOLP was studied to use interactive multiple objective models for solving the DEA problem in exact situation and find the most preferred solution. The aim of this study is to analyze an equivalent relation between imprecise DEA (IDEA) and MOLP models. In this context, we tried to solve IDEA models with interactive project procedure. The Project method is the responsible method, because it can estimate any efficient solution, and it indicates Most Preferred Solution (MPS). In addition, we will use the Data Envelopment Scenario Analysis (DESA) model. The main characteristic of DESA model is to decrease all inputs and increase all outputs and estimate one problem instead of n problems.

The purpose of this study is to integrate the findings of the studies related to the relationship between CEO compensation and firm performance in Asian countries.The second concern of the paper is to explore the moderating role of countryspecific characteristics on the pay-performance relationship in Asian markets. In order to achieve the study’s objective, meta-analysis technique is utilized through CMA. Basically, the results are analyzed with both the fixed effect and random effect models. however, the assumption of the fixed effect model regarding same true effect size was not fulfilled. Moreover, a higher level of heterogeneity was detected. Therefore, this study ignores the results denoted by the fixed effect model and follows the results prescribed by the random effect model. After eliminating outliers, the findings from 22 studies revealed that CEO compensation in Asian markets is aligned with firm performance but with the small magnitude.Furthermore, the results from the method of moments suggested that there is a positive effect of country’s development and literacy on the pay-performance link, however, the negative effect of gender inequality and Islamic practices are evaluated. Conversely, no significant effect of corruption on the pay-performance relationship is purported in the study. As the authors find the influence of countryspecific characteristics on the pay-performance relationship in Asian markets, this study confirms the need for enhancing pay-performance sensitivity in Asian markets to mitigate potential agency conflicts.

This article examines a new approach which solves Linear Programming (LP) problems with stochastic parameters as a generalized model of the fuzzy mathematical model analyzed by Verdegay. An expectation model is provided for solving the problem. A multi-parametric programming is applied to access to a solution with different desired degrees as well as problem constraints. Additionally, we present a numerical example to demonstrate the state and method efficiency.

The Basel II Accord pointed out benefits of credit risk management through internal models to estimate Probability of Default (PD). Banks use default predictions to estimate the loan applicants’ PD. However, in practice, PD is not useful and banks applied credit scorecards for their decision making process. Also the competitive pressures in lending industry forced banks to use profit scorecards, which show the profitability of customers. Applying these scorecards together makes the loan decision making process for banks more confusing. This paper has an obvious and clean solution for facilitating the confusion of loan decision making process by combining the credit and profit scorecards through introducing a matrix sequential hybrid credit scorecard. The applicability of the introduced matrix sequential hybrid scorecard results are shown using data from an Iranian bank.

Optimization of the complete manufacturing and supply process has become a critical ingredient for gaining a competitive advantage. This article provides a unified mathematical framework for modeling manufacturing cell configuration and raw material supplier selection in a two-level supply chain network. The commonly used manufacturing design parameters along with supplier selection and a subcontracting approach are incorporated into our mathematical model. To the authors’ knowledge, there is no single model which integrates all of these attributes simultaneously. A sensitivity analysis is also performed to study the effects of this integration. An efficient meta-heuristic based on Genetic Algorithm (GA) search procedure is employed to effectively solve the model in medium and large scales.We improve the GA search mechanism by proper combination of linear programming optimization technique and GA in a cooperative framework.Computational results show that our hybrid solution technique can find satisfactory solutions in a timely manner.

This paper studies the moderating effect of Transformational Leadership (TL) on the relationship between Deviant Workplace Behavior (DWB) and Job Performance (JP). Data were collected using a self-administered questionnaire from 288 (n=288) respondents using quota sampling approach. The analysis shows that employees’ DWB negates JP and there is a moderating effect of TL behavior on the relationships of DWB and JP. TL can moderate the behavior of deviant employees which, in turn, contributes to accelerating JP. This study brings forth implications both for academics and professionals. It encourages more researches from academics on it and robust application of these findings for professionals for the effective utilization of their talents. It also proposes that the punitive approach of dealing with deviant employees requires replacement with appropriate leadership styles.

The aim of this research was to determine the impact of voluntary information disclosure on informational content of share price. In this regard, future earnings response coefficient was used to determine the informational content of the share price about the future income information. Furthermore, share price synchronicity was used to evaluate the informational content of the share price about firm-specific information. To this end, it was attempted to select 98 firms listed in Tehran Stock Exchange (from 2005 to 2016). The analyses indicated that the voluntary information disclosure improved the informational content of share prices in terms of the future earnings. However, it was indicated that the voluntary information disclosure did not affect the informational content of share price in terms of firmspecific information. So, voluntary information disclosure increases the capability of the investors to predict the future income and, consequently, future income information will be reflected in the share price.