Participative Budgeting and Participant Motivation: A Review of the Literature

In their discussion - Participative Budgeting and Participant Motivation: A Review of the Literature - by Frederick J. Demicco, Assistant Professor, School of Hotel, Restaurant and Institutional Management, The Pennsylvania State University and Steven J. Dempsey, Fulton F. Galer, Martin Baker, Graduate Assistants, College of Business at Virginia Polytechnic Institute and State University, the authors initially observe: “In recent years behavioral literature has stressed the importance of participation In goal-setting by those most directly affected by those goals. The common postulate is that greater participation by employees in the various management functions, especially the planning function, will lead to improved motivation, performance, coordination, and functional behavior. The authors analyze this postulate as it relates to the budgeting process and discuss whether or not participative budgeting has a significant positive impact on the motivations of budget participants.” In defining the concept of budgeting, the authors offer: “Budgeting is usually viewed as encompassing the preparation and adoption of a detailed financial operating plan…” In furthering that statement they also furnish that budgeting’s focus is to influence, in a positive way, how managers plan and coordinate the activities of a property in a way that will enhance their own performance. In essence, framing an organization within its described boundaries, and realizing its established goals. The authors will have you know, to control budget is to control operations. What kind of parallels can be drawn between the technical methods and procedures of budgeting, and managerial behavior? “In an effort to answer this question, Ronen and Livingstone have suggested that a fourth objective of budgeting exists, that of motivation,” say the authors with attribution. “The managerial function of motivation is manipulative in nature.” Demicco, Dempsey, Galer, and Baker attempt to quantify motivation as a psychological premise using the expectancy theory, which encompasses empirical support, intuitive appeal, and ease of application to the budgetary process. They also present you with House's Path-Goal model; essentially a mathematics type formula designed to gauge motivation. You really need to see this. The views of Argyris are also explored in particular detail. Although, the Argyris study was primarily aimed at manufacturing firms, and the effects on line-supervisors of the manufacturing budgets which were used to control and evaluate their performance, its application is relevant to the hospitality industry. As the title suggests, other notables in the field of behavioral motivation theory, and participation are also referenced. “Behavioral theory has been moving away from models of purported general applicability toward contingency models that are suited for particular situations,” say the authors in closing. “It is conceivable that some time in the future, contingency models will make possible the tailoring of budget strategies to individual budget holder personalities.”

Off-line and on-line affective recognition of a computer user through a biosignal processing approach

Physiological signals, which are controlled by the autonomic nervous system (ANS), could be used to detect the affective state of computer users and therefore find applications in medicine and engineering. The Pupil Diameter (PD) seems to provide a strong indication of the affective state, as found by previous research, but it has not been investigated fully yet. ^ In this study, new approaches based on monitoring and processing the PD signal for off-line and on-line affective assessment ("relaxation" vs. "stress") are proposed. Wavelet denoising and Kalman filtering methods are first used to remove abrupt changes in the raw Pupil Diameter (PD) signal. Then three features (PDmean, PDmax and PDWalsh) are extracted from the preprocessed PD signal for the affective state classification. In order to select more relevant and reliable physiological data for further analysis, two types of data selection methods are applied, which are based on the paired t-test and subject self-evaluation, respectively. In addition, five different kinds of the classifiers are implemented on the selected data, which achieve average accuracies up to 86.43% and 87.20%, respectively. Finally, the receiver operating characteristic (ROC) curve is utilized to investigate the discriminating potential of each individual feature by evaluation of the area under the ROC curve, which reaches values above 0.90. ^ For the on-line affective assessment, a hard threshold is implemented first in order to remove the eye blinks from the PD signal and then a moving average window is utilized to obtain the representative value PDr for every one-second time interval of PD. There are three main steps for the on-line affective assessment algorithm, which are preparation, feature-based decision voting and affective determination. The final results show that the accuracies are 72.30% and 73.55% for the data subsets, which were respectively chosen using two types of data selection methods (paired t-test and subject self-evaluation). ^ In order to further analyze the efficiency of affective recognition through the PD signal, the Galvanic Skin Response (GSR) was also monitored and processed. The highest affective assessment classification rate obtained from GSR processing is only 63.57% (based on the off-line processing algorithm). The overall results confirm that the PD signal should be considered as one of the most powerful physiological signals to involve in future automated real-time affective recognition systems, especially for detecting the "relaxation" vs. "stress" states.^

Self -management factors, influences, and conditions for type 2 diabetes among Black ethnic groups in Miami, Florida and Abidjan, Cote d'Ivoire

The Dahlgren and Whitehead ecological theory provides the framework for a cross-sectional design to compare socio-demographic characteristics, living and working conditions, and lifestyle daily habits as well as cultural and ecological factors among six diabetic multiethnic Black groups in Miami and Abidjan. Approximately 180 Black Americans (African-, Caribbean-, and Haitian-) and 180 Black Africans (Akan, Malinke, and Krou) aged 20 years and older were surveyed. During the preliminary of this study participants' attitudes and behaviors were qualitatively assessed (N=60) and a tool was developed to describe, in the main study (N=360), differences in participants' strength of commitment to diabetes lifestyle self-management. Despite similarities found in terms of age and gender, statistically significant differences were also found within and among groups in terms of living and working conditions, education level, and religion. African American groups were more likely to participate in more diabetes classes than Haitian Americans and Caribbean Americans. However, African Americans were less likely to adhere to daily dietary and weight control regimens. Although, Black African groups reported limited access to equipment, facilities, and financial support they were more likely to follow dietary and weight control recommendations than Black American groups. Overall, African American participants showed the poorest attitudes towards recommended foods, Caribbean American respondents reported the best attitudes and behaviors towards weight control regimens, and the Malinke group had significantly more strength of commitment to successful weight control. Furthermore, Black African groups had significantly more strength of commitment to successful dietary adherence and significantly less support for weight control than Black American groups. ^ Significant differences found within Black groups suggest that understanding each patient's conditions may help healthcare professionals in initiating individualized appropriate counseling before goal setting, and in developing culturally relevant type 2 diabetes management programs. Moreover, significant differences exist in strength of commitment to lifestyle adherence among Black groups in Miami and Abidjan. Cultural, socio-demographic factors and self-management habits may explain differences in participants' outcomes. At the policy level, Black groups should not be approached as a homogenous group and assessment of the vulnerability of each ethnic group may be necessary in the decision-making process.^

Intelligent retrieval system for conditions of contract documents in construction

The outcome of this research is an Intelligent Retrieval System for Conditions of Contract Documents. The objective of the research is to improve the method of retrieving data from a computer version of a construction Conditions of Contract document. SmartDoc, a prototype computer system has been developed for this purpose. The system provides recommendations to aid the user in the process of retrieving clauses from the construction Conditions of Contract document. The prototype system integrates two computer technologies: hypermedia and expert systems. Hypermedia is utilized to provide a dynamic way for retrieving data from the document. Expert systems technology is utilized to build a set of rules that activate the recommendations to aid the user during the process of retrieval of clauses. The rules are based on experts knowledge. The prototype system helps the user retrieve related clauses that are not explicitly cross-referenced but, according to expert experience, are relevant to the topic that the user is interested in.

Off-line and On-line Affective Recognition of a Computer User through A Biosignal Processing Approach

Physiological signals, which are controlled by the autonomic nervous system (ANS), could be used to detect the affective state of computer users and therefore find applications in medicine and engineering. The Pupil Diameter (PD) seems to provide a strong indication of the affective state, as found by previous research, but it has not been investigated fully yet. In this study, new approaches based on monitoring and processing the PD signal for off-line and on-line affective assessment (“relaxation” vs. “stress”) are proposed. Wavelet denoising and Kalman filtering methods are first used to remove abrupt changes in the raw Pupil Diameter (PD) signal. Then three features (PDmean, PDmax and PDWalsh) are extracted from the preprocessed PD signal for the affective state classification. In order to select more relevant and reliable physiological data for further analysis, two types of data selection methods are applied, which are based on the paired t-test and subject self-evaluation, respectively. In addition, five different kinds of the classifiers are implemented on the selected data, which achieve average accuracies up to 86.43% and 87.20%, respectively. Finally, the receiver operating characteristic (ROC) curve is utilized to investigate the discriminating potential of each individual feature by evaluation of the area under the ROC curve, which reaches values above 0.90. For the on-line affective assessment, a hard threshold is implemented first in order to remove the eye blinks from the PD signal and then a moving average window is utilized to obtain the representative value PDr for every one-second time interval of PD. There are three main steps for the on-line affective assessment algorithm, which are preparation, feature-based decision voting and affective determination. The final results show that the accuracies are 72.30% and 73.55% for the data subsets, which were respectively chosen using two types of data selection methods (paired t-test and subject self-evaluation). In order to further analyze the efficiency of affective recognition through the PD signal, the Galvanic Skin Response (GSR) was also monitored and processed. The highest affective assessment classification rate obtained from GSR processing is only 63.57% (based on the off-line processing algorithm). The overall results confirm that the PD signal should be considered as one of the most powerful physiological signals to involve in future automated real-time affective recognition systems, especially for detecting the “relaxation” vs. “stress” states.