Innovation by Teams in Shanghai,China: Cooperative Goals for Group Confidence and Persistence*

Organizations increasingly ask teams to stimulate innovation but research is needed to identify the conditions when teams have the confidence and persistence to innovate successfully. Using the concepts of cooperation, competition, group potency and initiative, this study proposes that relationships where team members believe that their goals are cooperative in that one person's goal attainment helps others reach their goals lay the foundation for innovation. Specifically, cooperative goals convince team members that they have the group potency to complete a range of tasks and the initiative to persist to overcome obstacles and innovate. In contrast, competitive, negatively related goals and independent, unrelated goals are hypothesized to undermine confidence, persistence and innovation. Group members from 101 teams from various organizations in Shanghai, China, completed a survey with measures of cooperative, competitive and independent goals, group potency, and initiative; their project leader completed the measure of innovation. Structural equation analysis supports the theoretical framework that cooperative goals help group members develop the confidence of group potency and the initiative to persist to accomplish tasks and innovate. These results suggest that cooperative goals and group potency and initiative are important conditions that help teams innovate for organizations and thereby specify conditions that can help groups realize their potential to achieve innovation for organizations.     

The 20-Year Trajectory of Marital Quality in Enduring Marriages: Does Equity Matter?

I examine the trajectory of marital quality as a function of relationship equity with data from a six-wave panel study of 704 married respondents between 1980 and 2000. Reporting that one "gives more" to the marriage (subjective underbenefit) is more likely for women than men at any given marital duration. Respondent's relative contribution to income, paid labor, housework, and health (objective underbenefit) raises this probability for women of average religiosity. For the more religious, objective underbenefit has no effect on women's sense of underbenefit, but reduces men's sense of underbenefit. Objective underbenefit lowers women's, but raises men's, marital quality, at any marital duration. The relevance of equity was not diluted by the passage of time in marriage.     

Population Trends in Metropolitan and Nonmetropolitan America: Selective Deconcentration and the Rural Rebound

This study uses revised annual population estimates that incorporate adjustments from the 2000 Census to backcast demographic change for U.S. counties during the 1990s. These data are supplemented with new post-censal population estimates for 2001–2003. We use these data to examine demographic trends in the late 1990s and first years of the new century. Our findings are consistent with a model suggesting that a selective deconcentration of the U.S. population is underway. Our findings also confirm the occurrence of the rural rebound in the first half of the 1990s and a waning of this rebound in the late 1990s. Post-censal data also suggest a modest upturn in nonmetropolitan population growth rates in 2001–2003.     

Factorial ecology: A critique and some suggestions

Studies in factorial ecology have typically used the principal factor procedure coupled with varimax rotation. Since it can be shown that the results one obtains vary according to the factor and rotation models he employs, and since there is no one “best” way of obtaining initial and derived factor solutions, it is proposed that future research in the area adopt an approach involving the simultaneous use of several different computing algorithms for obtaining initial solutions and both orthogonal and oblique rotation procedures to avoid the possibility that the results one obtains are not method-dependent. Ideally, the factor models employed should differ maximally with respect to the principles upon which they are based. If one finds a given factor regardless of the method he uses, only then can he assert with any confidencethat it is not an artifact of his method. Factorial ecologists are often interested in computing “factor scores”, but “true” factor scores are not uniquely computable; they can only be estimated. Since the proposed research strategy involves using either a component or an image model, in which the corresponding scores are exact and uniquely computable, the factor score problem is, in a sense, solved. Next it is suggested that, by using orthogonal solutions, factorial ecologists may be overlooking a very important piece of information—the correlation between the factors. There is some reason to believe that this varies from city to city, and may account for the fact that some factors which emerge in studies of Western cities are sometimes not found in cities elsewhere. Some comments are also made on the value of using census tract data, and on the availability of computer programs for different initial and derived factor solutions.