Transition to self‐directed work teams: implications of transition time and self‐monitoring for managers' use of influence tactics

In the face of heightened competitive pressures, elevated quality expectations, and calls for worker empowerment, more and more organizations have turned to self‐directed work teams (SDWTs). A review of the literature devoted to SDWTs suggests that managers often struggle with the transition to SDWTs because of the required shift in control to SDWT members. To promote the development of work teams, managers must modify their use of influence tactics in direct response to the control shift. In this study, we explore changes in managers' usage of influence tactics during the transition to SDWTs within a large aluminum manufacturing plant. Analyses of longitudinal data show that despite the new team environment, managers' use of influence tactics was focused at the individual level. We also found that transition time accounts for variance in managers' choices of influence tactics. Finally, an exploratory analysis suggests that high as opposed to low self‐monitoring managers may be more prone to increase their usage of soft influence tactics and decrease their usage of hard influence tactics over the course of the transition; the influence behavior of low self‐monitoring managers remained unchanged. Implications for future research are discussed. Copyright © 2004 John Wiley & Sons, Ltd.     

A framework for multi-level stakeholder studies in response to global change

Global change, as a process of large-scale environmental effects, and globalisation, as a change in peoples' livelihoods and consumption patterns, will impact communities increasingly in the years to come. Given these pressures, stakeholder consultations and broader stakeholder-centred activities that look at how people are affected by and able to adapt to change become crucial. Stakeholder consultations have been advanced, for instance, in Integrated Assessment activities which include several disciplines and stakeholder participation. Yet, thus far, such consultations have typically taken the form of direct group discussions, in which the differences in the way scientists and other stakeholders communicate are often underestimated. This paper suggests that there is a need to go beyond stakeholder dialogue to focus on the complex institutional factors that shape stakeholders' understandings and actions on multiple levels. Stakeholder studies would thus include not only direct consultation but also a social analysis of the vulnerabilities and adaptive capacities of regional and local institutions and livelihoods.     

Environmental Ethics Beyond Principle? The Case for a Pragmatic Contextualism

Many nonanthropocentric environmental ethicists subscribe to a ``principle-ist' approach to moral argument, whereby specific natural resource and environmental policy judgments are deduced from the prior articulation of a general moral principle. More often than not, this principle is one requiring the promotion of the intrinsic value of nonhuman nature. Yet there are several problems with this method of moral reasoning, including the short-circuiting of reflective inquiry and the disregard of the complex nature of specific environmental problems and policy arguments. In the present paper, we advance an alternative, pragmatic contextualist approach to environmental ethics, one grounded in the moral theory of John Dewey. We present the results of an empirical study of public environmental ethics and natural resource management attitudes to support our position, and we conclude with a few recommendations for future inquiry in the field of environmental ethics.     

Effect of selected and non-selected urban waste compost on the initial growth of corn

Brazil produces approximately 242,000 t of waste per day, 76% of it being dumped outdoors and only 0.9% recycled, including composting, which is an alternative still little known in Brazil. In search of a better destination for residues produced by domestic activities, composting stands as a feasible alternative. Organic compost from waste may be used for various purposes, among which are soil recovery, commercial production, pastures, lawns and reforestry and agriculture. However, the quality of the compost determines the growth and the development of plants. The effect of compost made from urban waste on corn plant (Zea mays L.) growth was investigated. Two types of compost were used: the selected compost (SC), produced from organic waste selectively collected; and the non-selected compost (NSC), taken from a 15-year-old cell from the Canabrava land-fill, located in Salvador, Bahia, Brazil (altitude 51 m, 12°22′–13°08′S, 38°08′–38°47′W). Corn was seeded in polyethylene pots, with soil-compost mixing substrate in the proportion of 0, 15, 30, 45 and 60 t ha⁻¹ equivalent doses. Chemical analyses of the compost and growth properties of the plant like chlorophyll content; height and stem diameter; aerial and radicular dry biomasses, were used to evaluate compost quality. Plants cultivated with SC presented a superior gain, being of 52.5% in stem diameter, 71.1 and 81.2% in root and stem biomasses, respectively. Chlorophyl content alterations were observed in plants from treatments using 30 t compost ha⁻¹ dose onwards. Conventional and multivariate statistical methods were used to evaluate these results. The beneficial action of organic compost in plant growth was confirmed with this research.     

EFFECTIVENESS OF POLYACRYLAMIDE (PAM) IN IMPROVING RUNOFF WATER QUALITY FROM CONSTRUCTION SITES1

ABSTRACT: Erosion from construction sites significantly affects water quality in receiving streams. A rainfall simulator was used to evaluate the effectiveness of different methods for controlling erosion from construction sites. Erosion control methods investigated included dry and liquid applications of polyacrylamide (PAM), hydroseed, and straw mulch. Fertilizer was also applied to each plot to examine the effectiveness of the methods in reducing nutrient losses in runoff. Runoff samples were analyzed for total suspended solids (TSS), nitrate, total Kjeldahl nitrogen (TKN), ammonium, total phosphorus (TP), and orthophosphate. Among all treatments investigated, straw mulch was the most effective treatment for controlling TSS and nutrient losses during short term and long term simulations. The low liquid PAM (half the recommended PAM) treatment resulted in the highest reduction in runoff, TSS bound nitrogen, and total nitrogen (TN) concentrations and loadings. The study results indicate that a high application rate (twice the recommended rate) of PAM could actually increase runoff and TSS losses. At a low application rate, both liquid and dry PAM were effective in reducing TSS and nutrient losses in runoff. However, application of the liquid form of PAM to construction sites is more practical and perhaps more economical than applying the PAM in the dry form.     

EFFECTS OF WATERSHED REPRESENTATION ON RUNOFF AND SEDIMENT YIELD MODELING1

ABSTRACT: This paper evaluates the effects of watershed geometric representation (i.e., plane and channel representation) on runoff and sediment yield simulations in a semiarid rangeland watershed. A process based, spatially distributed runoff erosion model (KINEROS2) was used to explore four spatial representations of a 4.4 ha experimental watershed. The most complex representation included all 96 channel elements identifiable in the field. The least complex representation contained only five channel elements. It was concluded that oversimplified watershed representations greatly influence runoff and sediment yield simulations by inducing excessive infiltration on hillslopes and distorting runoff patterns and sediment fluxes. Runoff and sediment yield decrease systematically with decreasing complexity in watershed representation. However, less complex representations had less impact on runoff and sediment‐yield simulations for small rainfall events. This study concludes that the selection of the appropriate level of watershed representation can have important theoretical and practical implications on runoff and sediment yield modeling in semiarid environments.     

TEMPORAL CHANGES IN THE YADKIN RIVER FLOW VERSUS SUSPENDED SEDIMENT CONCENTRATION RELATIONSHIP1

ABSTRACT: Dynamic linear models (DLM) and seasonal trend decomposition (STL) using local regression, or LOESS, were used to analyze the 50‐year time series of suspended sediment concentrations for the Yadkin River, measured at the U.S. Geological Survey station at Yadkin College, North Carolina. A DLM with constant trend, seasonality, and a log₁₀ streamflow regressor provided the best model to predict monthly mean log₁₀ suspended sediment concentrations, based on the forecast log likelihood. Using DLM, there was evidence (odds approximately 69:1) that the log₁₀ streamflow versus log₁₀ suspended sediment concentration relationship has changed, with an approximate 20 percent increase in the log₁₀ streamflow coefficient over the period 1981 to 1996. However, sediment concentrations in the Yadkin River have decreased during the decade of the 1990s, which has been accompanied by a concomitant increase in streamflow variability. Although STL has been shown to be a versatile trend analysis technique, DLM is shown to be more suitable for discovery and inference of structural changes (trends) in the model coefficient describing the relationship between flow and sediment concentration.     

ENHANCING FECAL COLIFORM TOTAL MAXIMUM DAILY LOAD MODELS THROUGH BACTERIAL SOURCE TRACKING1

ABSTRACT: Surface water impairment by fecal coliform bacteria is a water quality issue of national scope and importance. In Virginia, more than 400 stream and river segments are on the Commonwealth's 2002 303(d) list because of fecal coliform impairment. Total maximum daily loads (TMDLs) will be developed for most of these listed streams and rivers. Information regarding the major fecal coliform sources that impair surface water quality would enhance the development of effective watershed models and improve TMDLs. Bacterial source tracking (BST) is a recently developed technology for identifying the sources of fecal coliform bacteria and it may be helpful in generating improved TMDLs. Bacterial source tracking was performed, watershed models were developed, and TMDLs were prepared for three streams (Accotink Creek, Christians Creek, and Blacks Run) on Virginia's 303(d) list of impaired waters. Quality assurance of the BST work suggests that these data adequately describe the bacteria sources that are impairing these streams. Initial comparison of simulated bacterial sources with the observed BST data indicated that the fecal coliform sources were represented inaccurately in the initial model simulation. Revised model simulations (based on BST data) appeared to provide a better representation of the sources of fecal coliform bacteria in these three streams. The coupled approach of incorporating BST data into the fecal coliform transport model appears to reduce model uncertainty and should result in an improved TMDL.     

AN EVALUATION OF THE AVAILABLE TECHNIQUES FOR ESTIMATING MISSING FECAL COLIFORM DATA1

ABSTRACT: This paper presents the findings of a study aimed at evaluating the available techniques for estimating missing fecal coliform (FC) data on a temporal basis. The techniques investigated include: linear and nonlinear regression analysis and interpolation functions, and the use of artificial neural networks (ANNs). In all, seven interpolation, two regression, and one ANN model structures were investigated. This paper also investigates the validity of a hypothesis that estimating missing FC data by developing different models using different data corresponding to different dynamics associated with different trends in the FC data may result in a better model performance. The FC data (counts/100 ml) derived from the North Fork of the Kentucky River in Kentucky were employed to calibrate and validate various models. The performance of various models was evaluated using a wide variety of standard statistical measures. The results obtained in this study are able to demonstrate that the ANNs can be preferred over the conventional techniques in estimating missing FC data in a watershed. The regression technique was not found suitable in estimating missing FC data on a temporal basis. Further, it has been found that it is possible to achieve a better model performance by first decomposing the whole data set into different categories corresponding to different dynamics and then developing separate models for separate categories rather than developing a single model for the composite data set.