Achieving zero accidents—A strategic framework for continuous safety improvement in the construction industry

In the U.S., construction accidents remain a significant economic and social problem. Despite recent improvement, the Construction industry, generally, has lagged behind other industries in implementing safety as a total management process for achieving zero accidents and developing a high-performance safety culture. One aspect of this total approach to safety that has frustrated the construction industry the most has been “measurement”, which involves identifying and quantifying the factors that critically influence safe work behaviors. The basic problem attributed is the difficulty in assessing what to measure and how to measure it—particularly the intangible aspects of safety. Without measurement, the notion of continuous improvement is hard to follow. This research was undertaken to develop a strategic framework for the measurement and continuous improvement of total safety in order to achieve and sustain the goal of zero accidents, while improving the quality, productivity and the competitiveness of the construction industry as it moves forward. The research based itself on an integral model of total safety that allowed decomposition of safety into interior and exterior characteristics using a multiattribute analysis technique. Statistical relationships between total safety dimensions and safety performance (measured by safe work behavior) were revealed through a series of latent variables (factors) that describe the total safety environment of a construction organization. A structural equation model (SEM) was estimated for the latent variables to quantify relationships among them and between these total safety determinants and safety performance of a construction organization. The developed SEM constituted a strategic framework for identifying, measuring, and continuously improving safety as a total concern for achieving and sustaining the goal of zero accidents.

An integrated multi-agent framework for optimizing time, cost and environmental impact of construction processes

Environmentally conscious construction has received a significant amount of research attention during the last decades. Even though construction literature is rich in studies that emphasize the importance of environmental impact during the construction phase, most of the previous studies failed to combine environmental analysis with other project performance criteria in construction. This is mainly because most of the studies have overlooked the multi-objective nature of construction projects. In order to achieve environmentally conscious construction, multi-objectives and their relationships need to be successfully analyzed in the complex construction environment. The complex construction system is composed of changing project conditions that have an impact on the relationship between time, cost and environmental impact (TCEI) of construction operations. Yet, this impact is still unknown by construction professionals. Studying this impact is vital to fulfill multiple project objectives and achieve environmentally conscious construction. This research proposes an analytical framework to analyze the impact of changing project conditions on the relationship of TCEI. This study includes green house gas (GHG) emissions as an environmental impact category. The methodology utilizes multi-agent systems, multi-objective optimization, analytical network process, and system dynamics tools to study the relationships of TCEI and support decision-making under the influence of project conditions. Life cycle assessment (LCA) is applied to the evaluation of environmental impact in terms of GHG. The mixed method approach allowed for the collection and analysis of qualitative and quantitative data. Structured interviews of professionals in the highway construction field were conducted to gain their perspectives in decision-making under the influence of certain project conditions, while the quantitative data were collected from the Florida Department of Transportation (FDOT) for highway resurfacing projects. The data collected were used to test the framework. The framework yielded statistically significant results in simulating project conditions and optimizing TCEI. The results showed that the change in project conditions had a significant impact on the TCEI optimal solutions. The correlation between TCEI suggested that they affected each other positively, but in different strengths. The findings of the study will assist contractors to visualize the impact of their decision on the relationship of TCEI.

Financial Ratios: Perceptions of Lodging Industry General Managers, and Financial Executtves

Financial ratios are the most meaningful information in financial statements to executives and managers. The author analyzes the results of two surveys designed to rank the degree of importance and usefulness of these ratios to several user groups.

Strategic Directions of Hotel Industry Expectations

A factor analysis is presented which indicates that among 20 potential strategic issues reated by hotl industry executives three fundamental strategic directions exist. The author summarizes an empiracle study that queried these individuals' beliefs regarding strategic issues they rated at most important.

Ethical Challenges of the Industry: Are Graduates Prepared?

Hospitality graduates often enter their first jobs unaware of the difficult ethical dilemmas they will face. By having ethics teaching in a curriculum, the authors of this article believe that the perceptions of ethics of senior hospitality students at Northern Arizona University were comparable to those of operating industry managers.

The impact of *experience, industry characteristics, and individual differences on audit risk and the extent of testing decisions: An empirical investigation

The first part of the study examined the effect of industry risk changes on perceived audit risk at the financial statement level and whether these changes depended on individual differences such as experience and tolerance for ambiguity. ^ Forty-eight auditors from two offices of one of the “Big 5” CPA firms participated in this study. The ANOVA results supported the effect of industry risk in the assessment of audit risk at the financial statement level. Higher industry risk was associated with higher perceived audit risk. Tolerance for ambiguity was also significant in explaining the changes in the assessment of audit risk. Auditors with a high tolerance for ambiguity perceived lower audit risk than auditors with a low tolerance for ambiguity. Although ANOVA results did not find experience to be significant, a t-test for experience showed it to be marginally significant and inversely related to audit risk. ^ The second part of this study examined whether differences in perceived audit risk at the financial statement level altered the extent, nature or timing of the planned auditing procedures. The results of the MANOVA suggested an overall audit risk effect at the financial statement level. Perceived audit risk was significant in explaining the variation in the number of hours planned for the total cycle and the number of hours p1anned for the tests of balances and details. Perceived audit risk was not significant in determining the analytical review procedures planned, but assessed inherent risk at the cycle level was significant. The higher the inherent risk the more analytical procedures were planned. Perceived audit risk was not significant in explaining the timing of the procedures, but individual differences were significant. The results showed that experienced auditors and those with a high tolerance for ambiguity were less likely to postpone the performance of the interim procedures or the time at which the majority of audit work would be done. ^