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In recent years, practitioners have identified a number of problems with traditional performance management (PM) systems, arguing that PM is broken and needs to be fixed. In this chapter, we review criticisms of traditional PM practices that have been mentioned by journalists and practitioners and we consider the solutions that they have presented for addressing these concerns. We then consider these problems and solutions within the context of extant scholarly research and identify (a) what organizations should do going forward to improve PM practices (i.e., focus on feedback processes, ensure accountability throughout the PM system, and align the PM system with organizational strategy) and (b) what scholars should focus research attention on (i.e., technology, strategic alignment, and peer-to-peer accountability) in order to reduce the science-practice gap in this domain.

Increasing constraints on personnel and resources have led to a focus on alternative methods of transmitting knowledge to novices, whether university students or newly hired staff. This chapter focuses on one such alternative through the use of a technology-based educational delivery system (TBEDS). Prior research has addressed individual components of technology-supported systems or performed experiments of limited time and direct external relevance to the participants, but has not addressed the effect of a holistic approach to technology-based learning on users. This study capitalizes on a unique, holistically designed TBEDS to longitudinally examine the impact of systems on novices' procedural knowledge acquisition under conditions of actual usage. The longitudinal data also illustrates the role of user-determined experiential practice on achievement as moderated by comfort with technology. The findings indicate a strong relationship between the use of a TBEDS for repeated experiential practice and procedural knowledge acquisition. Individual components of effort (quantity of problems attempted, frequency of practice sessions, and quality of practice) are examined, with quantity being significantly positively related to performance, as is quality when the user is accountable to an external authority for that quality.

Activity-based costing (ABC) is presented in accounting textbooks as a costing system that can be used to make valuable managerial decisions. Little experimental or empirical evidence, however, has demonstrated the benefits of ABC under controlled conditions. Similarly, although case studies and business surveys often comment on business environments that appear to favor ABC methods, experimental studies of actual behavioral issues affecting ABCs usage are limited.

This study used an interactive computer simulation, under controlled, laboratory conditions, to test the decision usefulness of ABC information. The effects of presentation format (theory of cognitive fit and decision framing), decision commitment (cognitive dissonance), and their interactions were also examined. ABC information yielded better profitability decisions, requiring no additional decision time. Graphic presentations required less decision time, however, presentation formats did not significantly affect decision quality (simulation profits). Decision commitment beneficially affected profitability decisions, requiring no additional time. Decision commitment was especially influential (helpful) in non-ABC decision environments.

The credit migration process contains important information about the dynamics of a firm's credit quality, therefore, it has a significant impact on its relevant credit derivatives. We present a jump diffusion approach to model the credit rating transitions which leads to a partial integro-differential equation (PIDE) formulation, with defaults and rating changes characterized by barrier crossings. Efficient and reliable numerical solutions are developed for the variable coefficient equation that result in good agreement with historical and market data, across all credit ratings. A simple adjustment in the credit index drift converts the model to be used in the risk-neutral setting, which makes it a valuable tool in credit derivative pricing.

In this chapter we approach the estimation of dynamic stochastic general equilibrium models through a moments-based estimator, the empirical likelihood. We attempt to show that this inference process can be a valid alternative to maximum likelihood, which has been one of the preferred choices of the related literature to estimate these models. The empirical likelihood estimator is characterized by a simple setup and only requires knowledge about the moments of the data generating process of the model. In this context, we exploit the fact that these economies can be formulated as a set of moment conditions to infer on their parameters through this technique. For illustrational purposes, we consider a standard real business cycle model with a constant relative risk averse utility function and indivisible labor, driven by a normal technology shock.

Process-oriented guided-inquiry learning (POGIL) is a student-centered instructional strategy to actively engage students in the classroom in promoting content mastery, critical thinking, and process skills. The students organize into groups of three to four, and each group member works collaboratively to construct their understanding as they proceed through the embedded learning cycle in the POGIL activity. Each group member has a specific role and actively engages in the learning process. The roles rotate periodically, and each student has the opportunity to develop essential process skills, such as leadership skills, oral and written communication skills, team-building skills, and information-processing skills. The student groups are self-managed, and the instructor serves as a facilitator of student learning. A POGIL activity typically contains a model that the students deconstruct using a series of guided, exploratory questions. The students develop concepts (concept invention) as the group members reach a valid, consensus conclusion. The students apply their concepts to new problems completing the learning cycle. The authors implemented POGIL instruction in several chemistry courses at Jackson State University and Tuskegee University. They share their initial findings, experiences, and insights gained using a new instructional strategy.

Introduction: The internet of things (IoT) is the emerging technology of interconnected objects that can be termed as ‘things’ used to exchange data, connecting with different devices on the internet. It is the future where connected devices are controlled remotely. The insurance sector is one of the leading industries providing financial protection services to their customers to recover losses. Like others, the insurance industry uses the services very efficiently to solve their customer-centric problems and provide the best services to them. IoT in insurance is enhancing customer services.

Purpose: To determine how the insurance industry utilises the different IoT technologies to provide the best services and solutions to their users. The insurance sector is working on other areas of expertise to offer outstanding facilities to their clientele.

Methodology: We reviewed published material covering five years on IoT and insurance and customer services in the media, newspapers, journal publications, and the web. We determined how the insurance sector adapted the new terminology to contribute its best services to the users.

Findings: We observed that IoT services and technologies benefit the insurance industry and the clientele. This shows excellent results in the growth of the sector and heightened facilities for the consumers.

While deficits for students with learning disabilities (LD) are prevalent in almost all aspects of mathematics, difficulty in the application and understanding of problem-solving tasks are much more challenging to remediate than computational and procedural skills. Given the complexities involved in authentic problem-solving activities emphasized in current mathematics standards and the inherent challenges presented to students with LD, the importance of using strategies and techniques guided by evidence-based practices is paramount. Yet, ineffective instructional strategies for problem solving are still widespread in both mathematics curricula and available teacher resources. In this chapter, we provide a description of a commonly used ineffective problem-solving strategy (i.e., the keyword strategy), an overview of the keyword research, and an explanation for its ineffectiveness. We conclude with a description of three evidenced-based problem-solving approaches and practices that significantly improve the mathematical performance of students with LD.