Factors influencing food-choice behavior of African-American college students: implications for the foodservice industry

College students, particularly ethnic minorities in the US, are at a high risk for obesity and health complications. This study determines the type of foods that African-American college students are choosing to eat, and what factors influence those choices. Findings show that fresh fruits, whole grain bread, grilled chicken, and salad top the list of food choices. Knowledge of nutrition labels, gender, weight management, and eating facilities are among the factors found to influence these choices. Managerial implication of findings for the foodservice industry, and other interest groups are discussed. Directions for future research are given.     

Religiosity and social trust: evidence from Canada

Using the latest wave of the Canadian Ethnic Diversity Survey, I investigate whether religious identity and religious intensity associate with the degree to which people trust others, controlling for a wide range of characteristics. The analysis shows that Canadian Roman Catholics are appreciably less trusting than mainline Protestants, and religious nones are situated in between these two groups. With regard to religious intensity, I find that higher commitment negatively correlates with trust in unknown others for Roman Catholics. The reverse is true for Protestants. Results also show stark cross-denominational variations within Protestantism, as two highly committed denominations of Mennonite and Pentecostal are found to be the most and the least trusting religious groups in Canada. No non-Christian religious minority is found statistically significantly less trusting than Canadian Roman Catholics. Considering particularized trust in one’s neighbours and co-workers yields comparable conclusions.     

D‐optimal designs for a continuous predictor in longitudinal trials with discrete‐time survival endpoints

In designing an experiment with one single, continuous predictor, the questions are composed of what is the optimal number of the predictor's values, what are these values, and how many subjects should be assigned to each of these values. In this study, locally D‐optimal designs for such experiments with discrete‐time event occurrence data are studied by using a sequential construction algorithm. Using the Weibull survival function for modeling the underlying time to event function, it is shown that the optimal designs for a linear effect of the predictor have two points that coincide with the design region's boundaries, but the design weights highly depend on the predictor effect size and its direction, the survival pattern, and the number of time points. For a quadratic effect of the predictor, three or four design points are needed.     

INTERACTIONS AMONG DIFFERENT DIMENSIONS OF A RESPONSIVE PUBLIC SPACE: CASE STUDY IN IRAN

A place is generally identified by its varying physical, activity, social and meaning (connotative) characteristics. In this paper, the "Model of Responsive Public Space" is defined by these four aspects and each of them has its own special indicators as shown in previous studies on this subject. To examine this model and evaluate the interactions between these dimensions, experimental studies were carried out in two stages. In the first stage, open-ended structured interviews were carried out with 70 participants to adjust the model with personal opinions about public spaces in Qazvin city, Iran. In the second stage a questionnaire was used to explore the effect of the four dimensions on each other. 598 users of a selected public space participated in this study. The results were analyzed by SPSS software applying a Pearson correlation test and Excel software. These results indicate that not only in theory but also in practice, public spaces have four distinct aspects that must be taken into consideration when creating a responsive public space. The most significance correlation is that between the meaning and the social dimension of public spaces.     

Sodium content in fast foods: assessment of menu items in selected countries

This study was designed considering the ubiquitous presence of sodium in restaurant menus, the rapid growth of U.S. fast food operations globally, the impact of fast food on human health, and recent legislative steps to label sodium content. A strong correlation was found between calories and protein content versus sodium contents. Similar brand named menu items had different nutrient and sodium content in selected countries. When portion sizes of meat and cheese are controlled sodium can be reduced without sacrificing the flavor of the foods and in addition reducing the calories provided by selected menu items.     

Mixed-methods research proficiency for applied linguists: a PLS-path modelling approach

Quality & Quantity - Since the 2010s, the appeal for utilizing mixed methods research in applied linguistics and its related strands has been expanding. However, recent text-based studies...     

Reputation and adverse selection: theory and evidence from eBay

How can a marketplace introduce mechanisms to overcome inefficiencies caused by adverse selection? In this article, I use a unique data set that follows eBay sellers to show that reputation is a major determinant of price variations. I develop a model of sellers' dynamic behavior where sellers have heterogeneous qualities unobservable by buyers. Using reputation as a signal of quality, I structurally estimate the model to uncover buyers' utility and sellers' costs and underlying qualities. I show that removing the reputation mechanism increases low‐quality sellers' market share, lowers prices, and consequently reduces sellers' profit by 66% and consumer surplus by 35%.     

Market Moods and Network Dynamics of Stock Returns: The Bipolar Behavior

The authors show that a simple mood-separable preference in a network study of stock returns captures a variety of stylized facts regarding stocks’ provisional (ab)normal behavior. These behaviors are articulated in a multistate complete Euclidean network model that specifies the existence, direction, and magnitude of a self-organized dynamics for each individual stock during abnormal market moods. In the empirical setting, the authors apply suggested model along with 2 established visual approaches (multidimensional scaling and agglomerative hierarchical clustering) for benchmark purposes. Results reveal different levels of erratic return dynamics for each stock and the entire market in different abnormal market moods. The authors model and interpret these self-organized dynamics as evidence of stocks’ and market’s bipolar behavior.