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The conceptualization of the Base of Pyramid (BOP) proposes that low-income markets can lead to profitable opportunities for businesses. The purpose of this study is to identify key success factors of a BOP business strategy based on a case study of the discount retailer, Dollar General, in the USA.

The research design used in this research is an in-depth case study of Dollar General in the USA. Qualitative methods are applied in both the primary and secondary data collection and during the follow-on data analysis of Dollar General.

Dollar General’s strategic profile is achieved through the combination of the following four actions which are tailored to compete effectively at the BOP in the USA: creating the neighborhood discounter, raising aspirational appeal, reducing service and eliminating internationalization.

The case is specific to Dollar General in a US cultural context.

The case of Dollar General demonstrates how a discounter retailer should not only follow a low-cost strategy to compete at the BOP. Its ability to craft a distinctive strategy is coherent with meeting the logistical, rational and emotional needs of the low-income consumer in the USA.

Many businesses have neglected rural areas of the USA as being unprofitable. The ability for businesses such as Dollar General to serve the BOP segment can foster the socio-economic well-being of communities.

The overwhelming body of the BOP literature is based on emerging markets. To the best of the authors’ knowledge, this is one of the few studies to investigate BOP business strategy in the USA.

This case examines the opportunity for the Quaker-Tropicana-Gatorade (QTG) division of PepsiCo to invest in either or both of two small but fast-growing retail channels: the Dollar Channel and the Natural Foods Channel. The case gives an overview of PepsiCo's business strategy, focusing on health, wellness, and diversity and also provides a wide range of information. Students are challenged to take a broad, general management view in developing their recommendations.

The circular economy is a system that aims to conserve resources at every level for as long as possible with a minimization of waste. The core concept of the circular economy is to improve resource efficiency and prevent valuable materials from leaking out of the system. Better use of increasingly scarce resources can provide both economic and environmental benefits. When excess inventory, returned products, and end-of-life products are disposed of improperly, unnecessary waste is created, often with a detrimental impact to the environment. An effective system must exist to facilitate the proper handling of these products, and secondary markets are a crucial component in this system. In this chapter, we discuss the secondary markets’ role as an important mechanism for achieving a circular economy.

This case explores the decision of a fast-growing company to expand its distribution network. Financial information is provided in it so students can understand the basic distribution network design covering inbound transportation, outbound transportation, distribution-center operations, and inventory.

Secondary markets provide a place for unwanted items to be bought and sold, which diverts them from landfills, reducing the products' ecological impact and creating economic value. The purpose of this paper is study the secondary markets to understand the size of this important portion of the US economy.

The data were collected from financial reports, news articles, and interviews with subject experts. From all of these sources, the scope and size of secondary markets can be estimated.

Secondary markets are effective in diverting a large number of products from landfills, creating numerous jobs, resulting in substantial economic value in the process. Although not reflected in current government metrics, a conservative estimate is that the secondary market represents 2.28 percent of the 2008 US gross domestic product.

Several of the secondary markets have many small players, with no strong trade associations or other authorities to estimate their size. The paper's estimates based on known sources are very conservative, perhaps underestimating the size of these sectors.

As society increasingly pays attention to the ecological impact of its products, secondary markets will play an important role in supply chains. Understanding the magnitude, structure and reach of these markets can help firms develop better product stewardship and lifecycle management.

Individuals will not directly change their behavior from this research, but the findings should help companies behave differently, which in the end will offer products with lower ecological impact.

Secondary markets are an integral part of the US economy, and have not been adequately studied.

Selecting appropriate variables for analytical studies is critical for the validity of analysis. It is the same with data envelopment analysis (DEA) studies. In this study, for benchmarking using DEA, the paper seeks to suggest a novel framework based on return on assets (ROA), which is popular and user‐friendly to managers, and demonstrate it by use of an example.

The paper demonstrates the selection of variables using the elements of ROA and applies DEA for measuring and benchmarking the comparative efficiency of companies in the same industry.

It is frequently impossible to obtain internal data for benchmarking from competitors in the same industry. In this case, annual reports may be the only source of data for publicly traded companies. The framework demonstrated with an example is a practical approach for benchmarking with limited data.

This study employs financial data and is subject to the limitations of accounting practices.

The approach is applicable to various studies for performance measurement and benchmarking with minor modifications. Contributions of the study are twofold: first, a framework for selecting variables for DEA studies is suggested; second, the applicability of the framework with a real‐world example is demonstrated.

The purpose of this paper is to explore retail format choice among male shoppers, using desired store attributes and shopping orientations as predictors of format choice.

Male shoppers in the USA (n=560) were surveyed via the internet. Multiple regression was used to evaluate the data.

The findings identify distinctive predictors of male patronage across several retail formats including department stores, discounters, category killers, dollar stores and internet only stores.

The findings identify desired store attributes and shopping orientations of frequent male patrons of several retail formats. The information provided is useful for advancing the retail format choice literature as well as for retailers to better understand male patrons. Future research could examine patronage of newly developed retail formats and include situational variables that could provide additional predictive power for retail format choice among males.

This research provides retailers with specific knowledge to identify males who are likely to frequent specific retail formats based on desired store attributes and shopping orientations.

This exploratory study uses desired store attributes and shopping orientations to profile male shoppers of several retail formats in the USA. The research is unique because the investigation of retail format choice among males has been very limited.

In the age of “big data,” one of the most important capabilities that differentiates the winners from the losers in the intensely competitive grocery market is how successfully a firm can harness its vast amounts of shopper data to become more shopper-centric. Grocery retailers struggle with how to manage the tremendous amount of data available to them and best leverage their frequent shopper data to derive insights. These data also present an opportunity for academic research on decision-making and evaluation of strategic initiatives. This chapter discusses three case studies that illustrate the various capabilities of frequent shopper data in generating shopper insights. Specifically, using frequent shopper data for millions of shoppers, the three case studies demonstrate how frequent shopper data can be used as an important information asset for understanding differences and similarities among different shopper groups (Case Study 1), as a means to assess the effectiveness of store redesigns/environment changes (Case Study 2), and as a key tool for evaluating program success (Case Study 3). The chapter concludes with a discussion of how successful collaboration between practitioners and academics can be a boon to both business success and academic research.

This chapter describes three active learning activities developed for use in the introductory financial accounting class: an interview with a financial statement user, an internal control paper, and a financial statement project where students analyze two competing businesses. We gathered student surveys and direct assessment data to see if these activities add value to the introductory accounting course.

The learning activities were originally developed using Fink’s (2003) Taxonomy of Significant Learning, aligning the activities with Fink’s learning dimensions, which also support the higher order learning skills in Bloom’s revised taxonomy. Students completed surveys by comparing how well traditional class activities (i.e., homework and tests) and the new activities support the core competencies of the American Institute for Certified Public Accountants (AICPA). We also asked students open-ended questions on how they felt about these new activities. Researchers then compared pre- and postadoption assessment data to investigate the impact of the new learning activities on class completion rates and grades.

Based on faculty comments and student survey results, the three active learning assignments appear to be more effective in developing many of the AICPA’s core competencies and real world skill sets valued by professionals, providing more value than traditional teaching methods. In addition, the passing rates in the course at the Youngstown State University increased by 12% after adopting the learning innovations.