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Thanks to the advancement of digital image technology, digital single-lens reflex cameras (DSLRs) have replaced film single-lens reflex cameras. This advancement is reflected in some core technologies of DSLRs such as digital image sensors and electronic shutter mechanisms, which have allowed taking photographs even under tough conditions. In a similar vein, mirrorless interchangeable-lens cameras (MILCs) are now threatening to disrupt the DSLR market. Disruptive technologies represent a major challenge in forecasting. This paper uses specifications of over a 100 DSLRs and MILCs from the six leading dominant brands: Canon, Nikon, Sony, Pentax, Panasonic, and Olympus, for the analysis.

This chapter illustrates the Technology Forecasting using Data Envelopment Analysis (TFDEA) process on Liquid Crystal Display (LCD) performance characteristics from 1997 to 2012. The objective of this study is to forecast future state-of-the-arts (SOAs) specifications as well as to diagnose past technological advancement of the LCD industry. Appropriate characteristics were determined from a group of LCD technologists. Data was gathered from public databases and outlying data points were cross-referenced as a validity check. The TFDEA process is defined and its application to the dataset is described in detail. The results not only provide information on how LCD industry has evolved but also provide an insight on future NPD targets.

Airplane technology is undergoing several exciting developments, particularly in avionics, material composites, and design tool capabilities, and, though there are many studies conducted on subsets of airplane technology, market, and economic parameters, few exist in forecasting new commercial aircraft model introduction. In fact, existing research indicates the difficulty in quantitatively forecasting commercial airplanes due in part to the complexity and quantity of exogenous factors which feed into commercial airplane introduction decisions. This paper seeks to address this gap.

The analysis is based on a literature review, supplemented by a collection of secondary data. The study then focuses on applying three technology forecasting techniques: multiple regression; linear regression; and the Pearl growth curve.

The results provide a valid model for multiple regression and linear regression on range and composite material percentage for use in commercial airplane forecasting. However, growth curve analysis, comparatively, appears to provide the most intriguing and flexible forecast outlook in alignment with industry dynamics.

Research implications include a caution for forecasters in support of the difficulty of commercial aircraft forecasting due in part to the quantity of exogenous factors, particularly compared with a related industry, military aircraft. Future work could include: utilizing other forecasting techniques that allow for greater numbers of forecast factors, additional future models, additional range aircraft and/or analyzing the impact that competing transportation modes in mid‐range aircraft could have on long‐range aircraft introduction.

The study provides value in extending a previous descriptive paper on airplane parameters. Additionally, it appears to be one of the first quantitative examples supporting previous research indicating the complexity of forecasting airplane new product introduction, but it overcomes some of this complexity by providing a valid model for forecasting with range and composite material percentage as inputs.

This research provides accounting-ethics authors and administrators with a benchmark for accounting-ethics research. While Bernardi and Bean (2010) considered publications in business-ethics and accounting’s top-40 journals this study considers research in eight accounting-ethics and public-interest journals, as well as, 34 business-ethics journals. We analyzed the contents of our 42 journals for the 25-year period between 1991 through 2015. This research documents the continued growth (Bernardi & Bean, 2007) of accounting-ethics research in both accounting-ethics and business-ethics journals. We provide data on the top-10 ethics authors in each doctoral year group, the top-50 ethics authors over the most recent 10, 20, and 25 years, and a distribution among ethics scholars for these periods. For the 25-year timeframe, our data indicate that only 665 (274) of the 5,125 accounting PhDs/DBAs (13.0% and 5.4% respectively) in Canada and the United States had authored or co-authored one (more than one) ethics article.

Forecasting techniques improve supply chain resilience by ensuring that the correct parts are available when required. In addition, accurate forecasts conserve precious resources and money by avoiding new start contracts to produce unforeseen part requests, reducing labor intensive cannibalization actions and ensuring consistent transportation modality streams where changes incur cost. This study explores the effectiveness of the United States Air Force’s current flying hour-based demand forecast by comparing it with a sortie-based demand forecast to predict future spare part needs.

This study employs a correlation analysis to show that demand for reparable parts on certain aircraft has a stronger correlation to the number of sorties flown than the number of flying hours. The effect of using the number of sorties flown instead of flying hours is analyzed by employing sorties in the United States Air Force (USAF)’s current reparable parts forecasting model. A comparative analysis on D200 forecasting error is conducted across F-16 and B-52 fleets.

This study finds that the USAF could improve its reparable parts forecast, and subsequently part availability, by employing a sortie-based demand rate for particular aircraft such as the F-16. Additionally, our findings indicate that forecasts for reparable parts on aircraft with low sortie count flying profiles, such as the B-52 fleet, perform better modeling demand as a function of flying hours. Thus, evidence is provided that the Air Force should employ multiple forecasting techniques across its possessed, organically supported aircraft fleets. The improvement of the forecast and subsequent decrease in forecast error will be presented in the Results and Discussion section.

This study is limited by the data-collection environment, which is only reported on an annual basis and is limited to 14 years of historical data. Furthermore, some observations were not included because significant data entry errors resulted in unusable observations.

There are few studies addressing the time measure of USAF reparable component failures. To the best of the authors’ knowledge, there are no studies that analyze spare component demand as a function of sortie numbers and compare the results of forecasts made on a sortie-based demand signal to the current flying hour-based approach to spare parts forecasting. The sortie-based forecast is a novel methodology and is shown to outperform the current flying hour-based method for some aircraft fleets.