Correction to: Why perceived organizational and supervisory family support is important for organizations? Evidence from the field

Review of Managerial Science - Under Table 1, the explanation regarding the dummy variables that represent gender is reverse coded.     

Particle swarm optimization based Liu-type estimator

In this study, a new method for the estimation of the shrinkage and biasing parameters of Liu-type estimator is proposed. Because k is kept constant and d is optimized in Liu’s method, a (k, d) pair is not guaranteed to be the optimal point in terms of the mean square error of the parameters. The optimum (k, d) pair that minimizes the mean square error, which is a function of the parameters k and d, should be estimated through a simultaneous optimization process rather than through a two-stage process. In this study, by utilizing a different objective function, the parameters k and d are optimized simultaneously with the particle swarm optimization technique.     

A new per-field classification method using mixture discriminant analysis

In this study, a new per-field classification method is proposed for supervised classification of remotely sensed multispectral image data of an agricultural area using Gaussian mixture discriminant analysis (MDA). For the proposed per-field classification method, multivariate Gaussian mixture models constructed for control and test fields can have fixed or different number of components and each component can have different or common covariance matrix structure. The discrimination function and the decision rule of this method are established according to the average Bhattacharyya distance and the minimum values of the average Bhattacharyya distances, respectively. The proposed per-field classification method is analyzed for different structures of a covariance matrix with fixed and different number of components. Also, we classify the remotely sensed multispectral image data using the per-pixel classification method based on Gaussian MDA.     

Time-series forecasting with a novel fuzzy time-series approach: an example for Istanbul stock market

Artificial intelligence procedures such as artificial neural networks (ANNs), genetic algorithms and particle swarm optimization and other procedures such as fuzzy clustering have been successfully used in the various stages of different fuzzy time-series forecasting approaches. Fuzzy clustering, genetic algorithm and particle swarm optimization are generally used in the fuzzification stage, and this simplifies the applicability of this stage and makes the fuzzy time-series approach more systematic. ANNs have also been applied successfully in the fuzzy relationship determination stage. In this study, we propose a new hybrid fuzzy time-series approach in which fuzzy c-means clustering procedure is employed in the fuzzification stage and feed-forward neural networks are used in the fuzzy relationship determination stage. This study also includes an empirical analysis pertaining to the forecasting of Index 100 for the stocks and bonds exchange market of Istanbul.     

Why perceived organizational and supervisory family support is important for organizations? Evidence from the field

Review of Managerial Science - The relationship between perceived organizational support and its work-outcomes were usually based on social exchange theories. By keeping the social exchange...     

Factors Affecting Choice and Satisfaction: Social Work in Turkey

ABSTRACT

The study examines the relationship between professional choices and employment expectations of social worker trainees in the country of Turkey. Professional choices are examined according to gender and the relationship between employment expectations and satisfaction. This study examined responses with a comparative relational scanning model with a sample of 692 social service (social worker) trainees studying at four different universities in Turkey. Students were surveyed and answered 25 open- and closed-ended questions identifying aspects related to their career choice. Study findings reveal that gender, university entrance scores, and employability were high among the career selection factors. Additional factors identified included family-related factors, personality traits, and compatibility. Examination of the findings is discussed, and recommendations for further research are made.     

A New Robust Regression Method Based on Particle Swarm Optimization

Regression analysis is one of methods widely used in prediction problems. Although there are many methods used for parameter estimation in regression analysis, ordinary least squares (OLS) technique is the most commonly used one among them. However, this technique is highly sensitive to outlier observation. Therefore, in literature, robust techniques are suggested when data set includes outlier observation. Besides, in prediction a problem, using the techniques that reduce the effectiveness of outlier and using the median as a target function rather than an error mean will be more successful in modeling these kinds of data. In this study, a new parameter estimation method using the median of absolute rate obtained by division of the difference between observation values and predicted values by the observation value and based on particle swarm optimization was proposed. The performance of the proposed method was evaluated with a simulation study by comparing it with OLS and some other robust methods in the literature.     

Beyond cheap labour: trade unions and development in the Turkish metal industry

The ability of developing countries to export to more developed parts of the world is often associated with cheap labour. But such very obvious economic advantage is not always the end of the story. A fuller account needs to consider the wider institutional context. In some instances trade unionism can be an important part of this. This paper addresses trade unionism with specific reference to workers employed in large firms in Turkey that are significant exporters of consumer goods to the European market. The union examined is the largest union in the metal industry, an industry that is a driving force in the Turkish economy, and a major centre of trade unionism with over half a million of Turkey's three million trade unionists. The particular ‐ autocratic ‐ character of this union is critically examined and located with reference to wider forces of political economy and the specific constraints and difficulties to which its members are subject. Finally, the significance of this sort of trade unionism for economic ‐ and socio‐political ‐ development is discussed.     

Social Workers in Turkey: Identifying and Addressing Professional Problems and Concerns

The purpose of this study is to explore the perceptions of social workers in terms of the occupational problems they experience in the country of Turkey. Using a mixed-methods approach, a survey of 98 social workers was followed by individual interviews with 10 social workers. Utilizing this combined approach, social workers reported several problem areas with the most common concerns being: work execution and working conditions that can impair the delivery of efficient and effective service delivery; limited community awareness of the profession leading to occupational identity concerns; employment setting and expectations that limit the capability of what can be done to assist those in need; and, employment setting difficulties such as long hours, limited wages, and strict requirements that limit creative problem-solving. Suggestions and future practice improvement suggestions are provided.