4 resultados para Operating environment indicator

em Digital Commons at Florida International University


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In their dialogue entitled - The Food Service Industry Environment: Market Volatility Analysis - by Alex F. De Noble, Assistant Professor of Management, San Diego State University and Michael D. Olsen, Associate Professor and Director, Division of Hotel, Restaurant & Institutional Management at Virginia Polytechnic Institute and State University, De Noble and Olson preface the discussion by saying: “Hospitality executives, as a whole, do not believe they exist in a volatile environment and spend little time or effort in assessing how current and future activity in the environment will affect their success or failure. The authors highlight potential differences that may exist between executives' perceptions and objective indicators of environmental volatility within the hospitality industry and suggest that executives change these perceptions by incorporating the assumption of a much more dynamic environment into their future strategic planning efforts. Objective, empirical evidence of the dynamic nature of the hospitality environment is presented and compared to several studies pertaining to environmental perceptions of the industry.” That weighty thesis statement presumes that hospitality executives/managers do not fully comprehend the environment in which they operate. The authors provide a contrast, which conventional wisdom would seem to support and satisfy. “Broadly speaking, the operating environment of an organization is represented by its task domain,” say the authors. “This task domain consists of such elements as a firm's customers, suppliers, competitors, and regulatory groups.” These are dynamic actors and the underpinnings of change, say the authors by way of citation. “The most difficult aspect for management in this regard tends to be the development of a proper definition of the environment of their particular firm. Being able to precisely define who the customers, competitors, suppliers, and regulatory groups are within the environment of the firm is no easy task, yet is imperative if proper planning is to occur,” De Noble and Olson further contribute to support their thesis statement. The article is bloated, and that’s not necessarily a bad thing, with tables both survey and empirically driven, to illustrate market volatility. One such table is the Bates and Eldredge outline; Table-6 in the article. “This comprehensive outline…should prove to be useful to most executives in expanding their perception of the environment of their firm,” say De Noble and Olson. “It is, however, only a suggested outline,” they advise. “…risk should be incorporated into every investment decision, especially in a volatile environment,” say the authors. De Noble and Olson close with an intriguing formula to gauge volatility in an environment.

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It may soon be the norm for many airline passengers arriving at the check-in desk of any international airline with both stow- away and carry-on luggage to be asked to step onto the weighing scale as the airlines attempt to compete and remain operationally viable in what has become for most a cut-throat and highly litigious operating environment. The author's commentary seeks to highlight a number of the issues surrounding the current impasse. It is also intended to catalyze a more healthy and informed debate aimed at finding an acceptable resolution to this crisis prior to one being imposed which fails to satisfy the needs of either camp.

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Globally, human populations are increasing and coastal ecosystems are becoming increasingly impacted by anthropogenic stressors. As eutrophication and exploitation of coastal resources increases, primary producer response to these drivers becomes a key indicator of ecosystem stability. Despite the importance of monitoring primary producers such as seagrasses and macroalgae, detailed studies on the response of these benthic habitat components to drivers remain relatively sparse. Utilizing a multi-faceted examination of turtle-seagrass and sea urchin-macroalgae consumer and nutrient dynamics, I elucidate the impact of these drivers in Akumal, Quintana Roo, Mexico. In Yal Ku Lagoon, macroalgae bioindicators signified high nutrient availability, which is important for further studies, but did not consistently follow published trends reflecting decreased δ 15N content with distance from suspected source. In Akumal Bay, eutrophication and grazing by turtles and fishes combine to structure patches within the seagrass beds. Grazed seagrass patches had higher structural complexity and productivity than patches continually grazed by turtles and fishes. Results from this study indicate that patch abandonment may follow giving-up density theory, the first to be recorded in the marine environment. As Diadema antillarum populations recover after their massive mortality thirty years ago, the role these echinoids will have in reducing macroalgae cover and altering ecosystem state remains to be clear. Although Diadema antillarum densities within the coral reef ecosystem were comparable to other regions within the Caribbean, the echinoid population in Akumal Bay was an insufficient driver to prevent dominance of a turf-algal-sediment (TAS) state. After a four year study, declining coral cover coupled with increased algal cover suggests that the TAS-dominated state is likely to persist over time despite echinoid recovery. Studies on macroalgal diversity and nutrients within this same region of echinoids indicated diversity and nutrient content of macroalgae increased, which may further increase the persistence of the algal-dominated state. This study provides valuable insight into the variable effects of herbivores and nutrients on primary producers within a tropical coastal ecosystem. Results from this work challenge many of the currently accepted theories on primary producer response to nutrients and herbivory while providing a framework for further studies into these dynamics.

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Increased pressure to control costs and increased competition has prompted health care managers to look for tools to effectively operate their institutions. This research sought a framework for the development of a Simulation-Based Decision Support System (SB-DSS) to evaluate operating policies. A prototype of this SB-DSS was developed. It incorporates a simulation model that uses real or simulated data. ER decisions have been categorized and, for each one, an implementation plan has been devised. Several issues of integrating heterogeneous tools have been addressed. The prototype revealed that simulation can truly be used in this environment in a timely fashion because the simulation model has been complemented with a series of decision-making routines. These routines use a hierarchical approach to organize the various scenarios under which the model may run and to partially reconfigure the ARENA model at run time. Hence, the SB-DSS tailors its responses to each node in the hierarchy.