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Leadership assessment programs are intended to ensure that the organization retains or hires high-quality leadership. Among the many skills that must be included, executive communication is a cornerstone of effective leadership. However, there are many techniques to assessing executive communication that impose numerous advantages and disadvantages. The purpose of this study is to explore several techniques for evaluating executive communication skills in leadership assessment programs.

Building upon case studies from novel commanding officer selection efforts in the military, the current study outlines three possible areas of executive communication for leadership assessment programs: panel-based interviews, guided discussion and executive writing.

Although each technique offers some advantages, the best technique depends upon the context. Panel-based interviews can provide excellent depth in evaluating candidates, whereas executive writing focuses more upon crafting a deliberate and clear message without the ability to clarify or use nonverbal cues. Selecting an appropriate technique depends greatly upon the workload imposed on the leadership assessment team and the number of candidates available.

Leadership selection programs are often done piecemeal or based on local experience. By building upon novel efforts in military commanding officer selection, the goal is to promulgate effective executive communication techniques that will enhance leadership selection through more effective communication across all levels of leadership positions.

Evaluating warfighter lethality is a critical aspect of military performance. Raw metrics such as marksmanship speed and accuracy can provide some insight, yet interpreting subtle differences can be challenging. For example, is a speed difference of 300 milliseconds more important than a 10% accuracy difference on the same drill? Marksmanship evaluations must have objective methods to differentiate between critical factors while maintaining a holistic view of human performance.

Monte Carlo simulations are one method to circumvent speed/accuracy trade-offs within marksmanship evaluations. They can accommodate both speed and accuracy implications simultaneously without needing to hold one constant for the sake of the other. Moreover, Monte Carlo simulations can incorporate variability as a key element of performance. This approach thus allows analysts to determine consistency of performance expectations when projecting future outcomes.

The review divides outcomes into both theoretical overview and practical implication sections. Each aspect of the Monte Carlo simulation can be addressed separately, reviewed and then incorporated as a potential component of small arms combat modeling. This application allows for new human performance practitioners to more quickly adopt the method for different applications.

Performance implications are often presented as inferential statistics. By using the Monte Carlo simulations, practitioners can present outcomes in terms of lethality. This method should help convey the impact of any marksmanship evaluation to senior leadership better than current inferential statistics, such as effect size measures.

Marksmanship data is a staple of military and law enforcement evaluations. This ubiquitous nature creates a critical need to use all relevant information and to convey outcomes in a meaningful way for the end users. The purpose of this study is to demonstrate how simple simulation techniques can improve interpretations of marksmanship data.

This study uses three simulations to demonstrate the advantages of small arms combat modeling, including (1) the benefits of incorporating a Markov Chain into Monte Carlo shooting simulations; (2) how small arms combat modeling is superior to point-based evaluations; and (3) why continuous-time chains better capture performance than discrete-time chains.

The proposed method reduces ambiguity in low-accuracy scenarios while also incorporating a more holistic view of performance as outcomes simultaneously incorporate speed and accuracy rather than holding one constant.

This process determines the probability of winning an engagement against a given opponent while circumventing arbitrary discussions of speed and accuracy trade-offs. Someone wins 70% of combat engagements against a given opponent rather than scoring 15 more points. Moreover, risk exposure is quantified by determining the likely casualties suffered to achieve victory. This combination makes the practical consequences of human performance differences tangible to the end users. Taken together, this approach advances the operations research analyses of squad-level combat engagements.

For more than a century, marksmanship evaluations have used point-based systems to classify shooters. However, these scoring methods were developed for competitive integrity rather than lethality as points do not adequately capture combat capabilities. The proposed method thus represents a major shift in the marksmanship scoring paradigm.

The purpose of this article is twofold. First, the article examines how managers can make more effective use of sales forecasts for strategic resource allocation decisions. Second, the article identifies those research issues in forecasting that must be addressed to better understand the managerial side of forecasting. Managers can improve resource planning by understanding the limitations of forecasts. These limitations are exemplified through several strategic forecasting paradoxes that managers must recognize. The paradoxes suggested here are: first, the most important managerial decisions a company can make are based on the least accurate forecasts; second, the most useful forecast information for resource planning is the least accurate; and, third, the organizations that need the most accurate forecast have the largest forecast error. By recognizing these paradoxes managers can devote their attention to improving the use and implementation of the forecast for better resource decisions. At the same time, future research should focus on broadening the understanding of the role of forecasts in strategic decision making.

Values have long guided special education services and supports for students with extensive support needs; over the past four decades, those values have been backed by research evidence demonstrating the critical nature of values related to inclusive education, self-determination, and seeking strengths and assets. In this chapter, we investigate these values and their supporting research, documenting strengths and needs in extant research. We emphasize the need to continue to embrace and maintain these values while pursuing research that addresses research gaps while centering the priorities, perspectives, and preferences of people with extensive support needs.

Applies time‐series forecasting, a traditional operations analysis methodology, to develop a forecasting procedure and ordering policy for a natural‐gas customer of Columbia Gas of Ohio, USA. Evaluates six time‐series methods and four operating policies against four commonly used measures of error and the cost consequences of error to the customer. Demonstrates that time‐series forecasting and decision theory developed by operations and applied in an actual industrial situation can become a powerful marketing technique. Provides further insights into evaluating forecasting models and ordering policies, demonstrating that introducing optimal planned bias is a robust decision‐making/forecasting approach within services. There are three parts to the study. The first is a straightforward testing of forecasting methods, using the forecasts as the natural‐gas ordering policy. Results vary depending upon how well forecasts are fitted to the data. For example, one inaccurate forecast with a poor fit incurs a penalty cost of $179,270, while the best forecast results in a penalty cost of $27,081. The second part evaluates two additional complex ordering rules with the same forecasting methods, further reducing the lowest cost to $17,709. The third part is a technical analysis reflecting a redesign of the study, demonstrating the difficulty of generalizing when characteristics of the underlying demand change. Concludes that the best forecasting model/operating policy is to use the very basic forecasting model of simple moving average (or the equivalent, first‐order exponential smoothing) combined with an optimal planned bias ordering policy, i.e. with the planned introduction of bias.

The aim of this paper is to examine a model that combines barriers, drivers, government responses, recovery expectations, expected future changes in performance and the extent of digitalisation as a moderator in SMEs.

This study uses exploratory causal methodologies. The study employs a quantitative methodology based on utilising an electronic questionnaire to gather the opinions of home workers and entrepreneurs in Jordan. The cross-sectional data collection approach was conducted in a single time frame, and a total of 1,179 valid questionnaires were analysed using Smart PLS along with SPSS.

The findings demonstrate that the barriers lower the expectations of recovering performance, whilst the drivers and government responses raise the expectations of both performance recovery and change in performance. Concerning digitalisation, this study discovered that firms going digital had a significant positive direct impact on expectations of performance change. This paper also found that expectations of performance change are significantly positively impacted by the interaction between drivers and digitalisation. However, the moderating influence of digitalisation on the positive impact of government responses on expectations of performance change was not verified.

The study's conclusions led to the formulation of several policy recommendations aimed at easing the burden on SMEs.

This study adds something new to the body of knowledge on SMEs by investigating the effects of barriers, drivers and government responses on expectations of performance recovery and the expected future change in performance moderated by digitalisation.

This paper examines William Stanley Jevons’s approach to human “improvement” in comparison with that of Carl Menger. In Jevons’s view, people are relatively static when left to their own devices. Thus, to “attack” the “citadel of poverty” they must be improved by those who know what is “best” for them. Menger’s view of people as planners, by contrast, is one in which people are capable of improving themselves. Jevons was a social reformer who placed great faith in education, and painful training and instruction, broadly defined, as key mechanisms of reform. Less frequently acknowledged but no less important, Menger also foresaw “the improvement of mankind” from within, as consumers came to better understand how best to attain their wants and needs over time.

This paper was written for practitioners in higher education, including academics and instructional designers who are engaged in curriculum revision. It aims to examine the notion of outcomes-based education, survey the literature and provide a critical review of the outcomes-based approach to quality assessment and curriculum improvement in higher education. The outcomes-based approach is completely student-centred, which focuses on what students know and can actually do. Sharpening the focus onto student learning outcomes goes beyond mere tinkering with traditional structures and methods; it really constitutes a paradigm shift in educational philosophy and practice.

This paper begins with a summary of developments in institutional quality assessment and curriculum improvement in higher education in recent decades. Then, it identifies the underlying concepts and principles that characterize the outcomes-based approach for the design and improvement of curriculum and instruction in higher education. Finally, the outcomes-based approach is critically reviewed for its value from the perspectives of both practical and philosophical considerations.

In so doing, it is directed to the heightening of sensitivity as to the manner and situations in which the outcomes-based approach may be employed.

A final note is that while learning outcomes approaches are useful, care is needed to take into account the different views and perceptions of those involved in defining learning outcomes and to keep the ultimate goal of improving student learning clearly in mind. Care must also be taken to avoid rigidity and conceptual reification during implementation in curriculum and instructional design.