Suspending disbelief: Influencing engagement in scenarios of forest futures

Scenario analysis is an approach to long-term planning that informs decision-making in contexts of highly uncertain future conditions. Scenario-based studies are rapidly growing in popularity, yet many aspects of the method are not fully understood. Participants' willingness to suspend disbelief in possible futures is an integral component of scenario-based studies, essential for considering alternative future scenarios, yet little is known about the factors that affect it. Participation in a scenario project does not necessarily imply willingness or ability to suspend disbelief; participants may not suspend disbelief simply upon request. However, the scenario literature says little about the aspects of scenario-based studies that influence suspension of disbelief.This article explores the factors that influenced the suspension of disbelief in one scenario exercise about the future of Canada's forests. Participants differed in their abilities to suspend disbelief in the scenarios in part because of their past experiences and expertise in particular areas, and their assessments of probable and desired future outcomes. Elements of the project design and implementation influenced participants' abilities to engage the scenarios. The results have implications for those interested in using scenarios for helping people and communities envision possible - and sustainable - futures.     

Managing TFT-LCDs under uncertainty: When crystal cycles meet business cycles

Understanding the correlation between the crystal cycle and the business cycle is important, because it can help managers to anticipate change, reduce environmental uncertainty, and formulate operational objectives. To this end, we focused on China and the U.S. in our analysis. We found that the economic indicators that were the most relevant in the characterization of China's huge and burgeoning TFT-LCD market are gross domestic production and industrial production. We complemented this finding by conducting similar analyses in the U.S. market using a more comprehensive list of economic indicators.     

The state of research on technological uncertainties, social uncertainties and emerging markets: A multidisciplinary literature review

The objective of this research work is to study the progress of research on technological uncertainties, social uncertainties and emerging markets and outline and identify the key disciplines, journals, articles and authors. For this the author studied the existing literature from the various fields in which technological uncertainties, social uncertainties and emerging markets research work have been published using ISI Web of Knowledge database. The paper finds that there is increasing research work on technological uncertainties, social uncertainties and emerging markets and the bibliographical search resulted in ninety-one documents written by one-hundred-sixty-one authors in eighty-four journals in seventy-two disciplines. The five major disciplines and their underlying journals are business and economics, agriculture, psychology, public administration, and environmental sciences and ecology accounting for majority of publications. In journals the most prolific, measured by number of articles published are Harvard Business Review, Social Science and Medicine, World Development, and Higher Education; and most influential, measured by the global citation received, are Harvard Business Review, Social Science and Medicine and Sociological Review. The top 10% of the journals are responsible for 23% of all publications but 85% of all global citations received. This highlights that despite the high, diverse and increasing number of journals; only few are dominating and shaping the research arena of technological uncertainties, social uncertainties and emerging markets. Further, in the ten most cited articles, no author appears more than once.     

Forecasting of electricity costs based on an enhanced gray-based learning model: A case study of renewable energy in Taiwan

This work presents a novel gray-based cost efficiency (GCE) model that integrates the gray forecasting model into a two-factor cost efficiency curve model for renewable energy (RE) technologies and identifies the optimal forecasting model for power generation cost of RE technologies. The analytical framework of proposed GCE model improves short-term prediction of power generation cost, and can be applied during the early developmental stages for RE technologies. Empirical analysis is based on wind power data for Taiwan. Time lag of knowledge stock was simulated to represent the actual relationship between R&D expenditures and cost reductions in power generation by knowledge stock. Analytical results demonstrate the GCE model is a useful tool to quantify the influences of cost reductions in power generation. The implications of analytical results are that institutional policy instruments play an important role in RE technologies achieving cost reductions and market adoption. The proposed GCE model can be applied to all high-technology cases, and particularly to RE technologies. The study concludes by outlining the limitations of the proposed GCE model and directions for further research.     

A grey decision and prediction model for investment in the core competitiveness of product development

Because enterprises do not disclose their internal specific cost information to the public and, moreover, every firm has its own product character and financial constitutions, it is difficult to offer fixed guidelines for investment decisions. Thus, an enterprise may be uncertain when required to choose the most promising set of possible investments.The goal of this research is to use a grey relation analysis and analytic hierarchy process (AHP) to probe the core product development and competitiveness of an enterprise from limited data and, furthermore, by constructing the grey model, GM(1,1), to validate the feasibility of this assessment of the core competitiveness and investment strategy. In this study, a precision mechanical manufacturer is taken as an example, and the forecast estimate from this method is compared to those of a linear regression and the actual values to demonstrate the feasibility of applying this methodology to investment decision making, hence, demonstrating the value of this research.     

Contribution of low-level flammable vapor concentrations to dust explosion output

As a result of extensive dust explosion research, additional areas of hazards have arisen. The potential of combining small percentages of flammable vapors (below the lower explosion limit) introduces additional dust explosion hazards.     

Economic modeling for the US of the cost-efficiency and associated expanded treatment access of conversion to biosimilar pegfilgrastim-bmez from reference pegfilgrastim

Abstract

Aims: For this economic analysis, we aimed to model: (1) the cost-efficiency of prophylaxis with biosimilar pegfilgrastim-bmez for chemotherapy-induced (febrile) neutropenia (CIN/FN) compared to reference pegfilgrastim, and (2) the expanded access to CIN/FN prophylaxis and anti-neoplastic treatment that could be achieved with biosimilar cost-savings on a budget-neutral basis.

Methods: In a hypothetical panel of 20,000 cancer patients receiving CIN/FN prophylaxis and using the average sales price (ASP) for the second quarter of 2019 for reference pegfilgrastim, we: conducted an ex ante simulation from the payer perspective of the cost-savings of 10–100% conversion from reference to biosimilar pegfilgrastim-bmez using drug price discounting ranging from 10–35%; estimated the budget-neutral expanded access to biosimilar pegfilgrastim-bmez enabled by these cost-savings; and estimated the budget-neutral expanded access to anti-neoplastic treatment with pembrolizumab. The simulations were replicated using fourth quarter 2019 wholesale acquisition cost (WAC) for reference pegfilgrastim and biosimilar pegfilgrastim-bmez in a post facto analysis.

Results: In ASP simulations, cost-savings of using pegfilgrastim-bmez over reference pegfilgrastim in a 20,000 patient panel range from $1.3?M (at 15% price discount) to $3?M (35%) at 10% conversion rate and from $6.4?M to $14.9?M, respectively, at 50% conversion. These savings could provide prophylaxis with pegfilgrastim-bmez to an additional 352 (15% discount) to 1,076 patients (35%) at 10% conversion or 1,764–5,384, respectively, at 50% conversion. Alternatively, savings could be reallocated for anti-neoplastic treatment with pembrolizumab to 3 (15% discount) to 9 (35%) patients at 10% conversion or 19–45, respectively, at 50% conversion. When utilizing WAC, cost-savings range from $4.6?M (10% conversion) to $23.1?M (50%) which could provide pegfilgrastim-bmez to an additional 1,174 (10% conversion) to 5,873 patients (50%).

Conclusions: Prophylaxis with biosimilar pegfilgrastim-bmez increases the value of cancer care by generating significant cost-savings that could be reallocated to provide expanded access to CIN/FN prevention and anti-neoplastic therapy on a budget-neutral basis.     

Examining the efficacy of self-classification approach in segmenting special-interest tourists: food tourism case

Self-classification is used as an a priori approach to tourist typology and market segmentation. However, skepticism still surrounds its ability to incorporate the multidimensionality of tourist behavior. This study seeks to empirically verify the efficacy of a single-item self-classification approach. The robustness of this self-classification measure is examined by comparing it to a data-driven multidimensional psychographic approach in terms of its ability to predict the behaviors of tourists toward food-related destination consumption. Results suggest that the single-item self-classification approach performs equally well as the psychographic approach in segmenting food-related consumption behaviors. The implications and limitations of this study are also discussed.     

A Segmentation of Volunteers at the 2013 Austin City Limits Music Festival: Insights and Future Directions

Volunteers at music festivals play a critical role in festival operation and success. As the music festival industry continues to grow, the ability for these large productions to effectively execute a large volunteer program is augmented. Volunteers from the 2013 Austin City Limits Music Festival were surveyed in regards to their self-image congruency, motivation, satisfaction, and intent to return as a volunteer at the festival. Analysis resulted in three distinct segments which has significant practical implications for festival management. Academic implications exist with the addition of self-image congruency and further discovery of volunteers in the festival and event industry.     

Visitor centre staffing: Involving volunteers

Volunteer involvement in visitor centres has received little attention by tourism researchers despite the critical role staff play in welcoming tourists to a destination and promoting tourism activities. The community function of visitor centres - of which volunteering is part - has also been underplayed in previous research. Using data from a survey and interviews with visitor centre managers in Australia, this paper investigates the rationales for staffing visitor centres with volunteers and/or paid employees and, related to motivations for volunteering, the factors influencing the attractiveness of visitor centre volunteer programmes. The dominant rationales for involving volunteers are need, community involvement, visitor experience, and the personal qualities and motivations of volunteers. Visitor centre volunteering is attractive because of location and local pride, interactions with tourists and social relationships with other volunteers, and the reputation of the visitor centre and its volunteer programme.