مجله مدیریت تولید و عملیات
سال دوم شماره 1 (پیاپی 2، بهار و تابستان 1390)

In the world of today, most of countries attempt to improve their productivity and economic status by concentrating on innovation. Organizations have considered factors affecting innovation and have achieved enormous competitive advantages. The aim of this research is to investigate the influence of organizational climate in terms of seven dimensions of cohesiveness, autonomy, challenge, resources, openness to innovation, encouragement and supervision on process innovativeness. Data has been collected by random sampling in Khodrocar Lizing company as a subdivision of Iran Khodro Industrial Group. The validity of the conceptual models of each dimension of climate and process innovativeness has been assessed by confirmatory factor analysis (CFA). Results imply the validity of causal relationship between components and the latent variable except for the cohesiveness dimension. Finally, the hypotheses of research have been examined by structural equation modeling (SEM). Findings imply that challenge, resources, openness to innovation, and supervision influence process innovativeness. Supervision has the highest influence and openness to innovation has negative influence on innovativeness, while in prioritizing the factors by the Vikor technique, openness to innovation has the first rank.

Data envelopment analysis (DEA) is known as one of the most common approaches for efficiency evaluation. Network models are new subjects in which, a DMU with all its subunits and links is considered as a network structure. One of the most widely used DEA methods for network data is the suggested approach of Lewis and Sexton. In this approach, performance of each DMU is measured compared to a similar DMU by moving on the effective paths and then computing the final outputs and classic primary inputs. In reality, many cases can be found that an original input or an intermediate product allocates to several subunits or forms a tour in a network. In such networks, the approach of Lewis and Sexton is not able to calculate efficiency. Therefore, in this paper, an approach has been proposed for solving such problems and computing the efficiency of such networks.

Due to continuous changes in organizational environment, there is no warranty for long term survival in the market. Currently, those organizations can succeed that are agile and able to rapidly respond to environmental requirements. In this research a model has been proposed for applying proper strategies for achieving long term organizational success. The proposed model is an integration of Balanced Score Card (BSC) approach, Fuzzy Quality Function Development (FQFD) and Zero-One Goal Programming (ZOGP). In fact by BSC, appropriate strategic plans can be designed and prioritized by FQFD. Then, based on multiple objectives and existing problem constraints, feasible strategic plans are identified by ZOGP. Findings imply that decision making techniques can be well utilized in designing BSC through a structured methodology; make improvement in all aspects; and have a positive influence on organization's performance in long term.

The main purpose of this research is to address how robust design of service quality dimensions can be obtained. Service Quality Robust Design has been conducted by the integration of Taguchi Design of Experiments and SERVQUAL approach in Iran Travel Agency. Five basic dimensions of service quality, i.e. reliability, responsiveness, assurance, empathy, tangibles and price have been assumed as control factors. Response factor has been defined as two alternatives i) the sum of customer expectations, and ii) the sum of service quality gaps. In this investigation assumed that noise factor is not existed. The advantage of this paper is to improve the average and standard deviation simultaneously. Signal to noise ratio has been computed and the desired mix of the levels of service quality dimensions has been addressed. The main findings of this research includes the desired mix of the levels of service quality dimensions based on the sum of customer expectations and the desired mix of the levels of service quality dimensions based on the sum of service quality gaps. Comparing the two sets of findings helps the agency to analyze the cost of attracting new customers or retaining regular customers.

In today’s organizations, performance measurement comes more to the foreground with the advancement in the high technology. Supplier selection is an important issue in supply chain management. In recent years, determining the best supplier in the supply chain has become a key strategic consideration. However, these decisions usually involve several objectives or criteria, and it is often necessary to compromise among possibly conflicting factors. Thus, the multiple criteria decision making (MCDM) becomes a useful approach to solve this kind of problem. In order to use the conceptual framework for measuring performance supplier, a methodology that takes into account both quantitative and qualitative factors and the interrelations between them should be utilized. for leveling an integrated approach of analytic hierarchy process AHP and fuzzy TOPSIS method is proposed to obtain final ranking. The interactions among the criteria are also analyzed before arriving at a decision for the selection of supplier from among six alternatives. Linguistic values are used to assess the ratings and weights for criterion. These linguistic ratings can be expressed in triangular fuzzy numbers. Then, a hierarchy multiple criteria decision-making (MCDM) model based on fuzzy-sets theory including FAHP and FTOPSIS are applied. There are two approaches for aggregating values including relative importance of evaluation criteria with respect to the overall objective and rating of alternatives with respect to each criterion in fuzzy group TOPSIS: First aggregation and Last aggregation. In first aggregation approach weight of each criterion and rating of alternatives with respect to each criterion gained from decision makers are aggregated at first and TOPSIS method then apply to these aggregate values. In last aggregation approach weight of each criterion and rating of alternatives with respect to each criterion gained from decision makers are used in TOPSIS method directly. In this paper use the first method and gained weight of each criterion from AHP. This research has been conducted on manufacturing industry. However the results can also be used for other types of organizations managers that are located in a competitive environment.

The aim of this paper is estimation of Binary logistic regression parameters for maximizing the log-likelihood function with improved association indicators. In this paper the parameter estimation steps have been explained and then measures of association have been introduced and their calculations have been analyzed. Moreover a new related indicators based on membership degree level have been expressed. Indeed association measures demonstrate the number of success responses occurred in front of failure in certain number of Bernoulli independent experiments. In parameter estimation, existing indicators values is not sensitive to the parameter values, whereas the proposed indicators are sensitive to the estimated parameters during the iterative procedure. Therefore, proposing a new association indicator of binary logistic regression with more sensitivity to the estimated parameters in maximizing the log- likelihood in iterative procedure is innovation of this study.