Why Do We Care About Having More than Others? Socioeconomic Determinants of Positional Concerns in Different Domains

This paper uses survey data to provide empirical evidence regarding the importance of positional concerns in different domains and their determinants. In the survey, respondents are asked to choose between a world in which they have more of a good than others and a world in which their endowment along with everyone else is greatly improved, but they have less than others. Our results lend support to the claim that positional concerns play a crucial role in the decision-making process of individuals, though they appear to be more influential in some domains than others. Moreover, empirical results point out relationships between the age, gender, education, and income level of the respondents and their positional concerns in different domains.     

Entry Deterrence of Capacitated Competition Using Price and Non‐Price Strategies

We analyze the role of pricing and branding in an incumbent firm's decision when facing competition from an entrant firm with limited capacity. We do so by studying two price competition models (Stackelberg and Nash), where we consider the incumbent's entry‐deterrence pricing strategy based on a potential entrant's capacity size. In an extension, we also study a branding model, where the incumbent firm, in addition to pricing, can also invest in influencing market preference for its product. With these models, we study conditions under which the incumbent firm may block the entrant (i.e., prevent entry without any market actions), deter the entrant (i.e., stop entry with suitable market actions) or accommodate the entrant (i.e., allow entry and compete), and how the entrant will allocate its limited capacity across its own and the new market, if entry occurs. We also study the timing difference between the two different dynamics of the price competition models and find that the incumbent's first‐mover advantage benefits both the incumbent and the entrant. Interestingly, the entrant firm's profits are not monotonically increasing in its capacity even when it is costless to build capacity. In the branding model, we show that in some cases, the incumbent may even increase its price and successfully deter entry by investing in consumer's preference for its product. Finally, we incorporate demand uncertainty into our model and show that the incumbent benefits from demand uncertainty while the entrant may be worse off depending on the magnitude of demand uncertainty and its capacity.     

Neighborhoods in Development: Human Development Index and Self-organizing Maps

The Human Development Index (HDI) has been instrumental in broadening the discussion of economic development beyond money-metric progress, in particular, by ranking a country against other countries in terms of the well being of their citizens. We propose self-organizing maps to explore similarities among countries using the components of the HDI rather than rankings. The similarities approach using the HDI components reveals information which is not available from ranking or bilateral comparisons. By illustrating clusters of countries, which we call “neighborhoods in development”, self-organizing maps draw out the potential for mutual policy learning among countries and shift the focus to discovering what kind of policies might have led countries change their position in the rankings.     

Inference in multivariate linear regression models with elliptically distributed errors

In this study we investigate the problem of estimation and testing of hypotheses in multivariate linear regression models when the errors involved are assumed to be non-normally distributed. We consider the class of heavy-tailed distributions for this purpose. Although our method is applicable for any distribution in this class, we take the multivariate t-distribution for illustration. This distribution has applications in many fields of applied research such as Economics, Business, and Finance. For estimation purpose, we use the modified maximum likelihood method in order to get the so-called modified maximum likelihood estimates that are obtained in a closed form. We show that these estimates are substantially more efficient than least-square estimates. They are also found to be robust to reasonable deviations from the assumed distribution and also many data anomalies such as the presence of outliers in the sample, etc. We further provide test statistics for testing the relevant hypothesis regarding the regression coefficients.     

Reliability and Some Characteristics of Circular Consecutive-k-Within-m-Out-of-n:F System

A system can be classified with respect to the physical arrangement of its components and the functioning principle. A circular consecutive k-within-m-out-of-n:F system consists of n circularly ordered components and fails if and only if there are m consecutive components that include among them at least k failed components. A circular consecutive k-within-m-out-of-n:F system turns into circular consecutive k-out-of-n:F for m = k and k-out-of-n:F system for m = n. In this study, signature-based analysis of circular consecutive k-within-m-out-of-n:F system is performed. A new approximation to this system is provided based on maximum number of failed components and an illustrative example is given for different values of n, m, k to compare the approximate results with simulated and exact results.     

Spatial Patterns of Marriage Migration in Turkey

Even though recent societal phenomena such as a heightened sense of individualism, economic well-being, and institutionalization have caused a shift in people's life course and made their lives less standard in developed societies, marriage still remains an important life course event in Turkey. Between the years 1995 and 2000 marriage migration comprised 7.4% of the interprovincial migration in Turkey, and of these marriage migrants 94% were woman. Young Turkish women tend toward marriage migration to escape the patriarchal family structure and gain more autonomy, economic security, and well-being. Focusing on the spatial patterns of marriage migration relationships in Turkey, this study seeks to reveal the economic and sociocultural background of male and female marriage migration and to visualize, explore, and model spatial data by using spatial data analysis (SDA) techniques. The results showed that marriage migration in different regions of Turkey varied by gender. Even though SDA techniques have previously been used in other social sciences studies, no other marriage migration study in the literature uses these techniques, thus enabling the article to contribute to the literature.     

Evaluation of the relationship between compliance with the follow-up and treatment protocol and health literacy in bladder tumor patients

Abstract

Objective: To investigate the relationship between the compliance of bladder cancer patients with cystoscopic follow-up and the treatment protocol, and their health literacy.

Methods: Patients who underwent transurethral resection surgery for bladder tumor were found to have non-muscular invasive bladder carcinoma on pathology examination and then underwent cystoscopic follow-up for 1?year or more were included in the study. Cystoscopic follow-up was recommended to the low- and high-risk groups in terms of progression and recurrence. The patients were evaluated with the Health Literacy Survey-European Union scale.

Results: The mean age of the patients was 67.13?±?10.77 years. The treatment continuity rate was 80.50% (n?=?33) in the adequate health literacy group (n?=?41) and significantly higher than the 56.50% (n?=?48) rate in the inadequate health literacy group (n?=?85) (p?=?.008). The health literacy results revealed that the health promotion and general index score was higher in the group of patients under the age of 65.

Conclusions: Adequate health literacy in bladder cancer patients is associated with better compliance with the treatment protocol. Young patients show better compliance with the follow-up protocol recommended by the physician. Increasing the follow-up protocol compliance of elderly patients with inadequate health literacy is necessary.     

Managing High‐Tech Capacity Expansion via Reservation Contracts

We study capacity reservation contracts between a high‐tech manufacturer (supplier) and her OEM customer (buyer). The supplier and the buyer are partners who enter a ‘design‐win” agreement to develop the product, and who share the stochastic demand information. To encourage the supplier for more aggressive capacity expansion, the buyer reserves capacity upfront by paying a deductible fee. As capacity expansion demonstrates diseconomy of scale in this context, we assume convex capacity costs. We show that as the buyer's revenue margin decreases, the supplier faces a sequence of four profit scenarios with decreasing desirability. We examine the effects of market size and demand variability to the contract conditions. We propose two channel coordination contracts, and discuss how such contracts can be tailored for situations where the supplier has the option of not complying with the contract, and when the buyer's demand information is only partially updated during the supplier's capacity lead‐time.     

Subset selection in quantile regression analysis via alternative Bayesian information criteria and heuristic optimization

Subset selection is an extensively studied problem in statistical learning. Especially it becomes popular for regression analysis. This problem has considerable attention for generalized linear models as well as other types of regression methods. Quantile regression is one of the most used types of regression method. In this article, we consider subset selection problem for quantile regression analysis with adopting some recent Bayesian information criteria. We also utilized heuristic optimization during selection process. Simulation and real data application results demonstrate the capability of the mentioned information criteria. According to results, these information criteria can determine the true models effectively in quantile regression models.     

Developing a restricted two-parameter Liu-type estimator: A comparison of restricted estimators in the binary logistic regression model

In the context of estimating regression coefficients of an ill-conditioned binary logistic regression model, we develop a new biased estimator having two parameters for estimating the regression vector parameter β when it is subjected to lie in the linear subspace restriction Hβ = h. The matrix mean squared error and mean squared error (MSE) functions of these newly defined estimators are derived. Moreover, a method to choose the two parameters is proposed. Then, the performance of the proposed estimator is compared to that of the restricted maximum likelihood estimator and some other existing estimators in the sense of MSE via a Monte Carlo simulation study. According to the simulation results, the performance of the estimators depends on the sample size, number of explanatory variables, and degree of correlation. The superiority region of our proposed estimator is identified based on the biasing parameters, numerically. It is concluded that the new estimator is superior to the others in most of the situations considered and it is recommended to the researchers.