Dynamics of fertility and labour force participation of Canadian women in 1971 and 1981: a cohort approach

The authors analyze the relationship between labor force participation and fertility in Canada using data from the Public Use Sample Tapes from the 1971 and 1981 censuses. Factors considered include age, religion, educational status, and marital status. The authors conclude that "labour force participation of women seems to have less influence on fertility compared to [the] fertility effect on labour force participation."     

Micro-level product-market dynamics: Shared knowledge and its relationship to market development

This work draws on consumer and psychology research to explain sociocognitive aspects of product-market dynamics at a higher level of specificity than prior research. The authors extend the field’s understanding of market-shaping shared knowledge through a theory-informed discussion of how shared product knowledge comes to exist and how it changes as product markets develop. They define shared knowledge as the aspects of product representations that are common across the minds of market actors, making it possible for them to understand one another. The authors also discuss ways to track shared knowledge content that is expressed in market narratives. As the characteristics of shared knowledge are explained and linked to stages of product-market development, the authors develop a set of researchable propositions to guide future research. The theoretical arguments and propositions in this article complement extant marketing strategy research by integrating individual-level consumer theory with market evolution models. José Antonio Rosa (jose.rosa@case.edu; Ph.D., University of Michigan) is an assistant professor of marketing at Case Western Reserve University. His research interests include product markets as sociocognitive phenomena, embodied knowledge in consumer and managerial sensemaking, consumer illiteracy and coping, commitment and motivation among members of network marketing organizations, and buying group satisfaction. His research has been published in marketing and management publications, including theJournal of Marketing and theAcademy of Management Journal. Before entering academia, he worked in the automotive and information systems industries. Jelena Spanjol (jspanjol@tamu.edu; Ph.D., University of Illinois) is an assistant professor of marketing at Texas A&M University. Her research interests include product market dynamics, product portfolio management, innovation, sensemaking, and organizational and managerial cognition in marketing strategy. Her research has been published in marketing and management publications, including theJournal of Marketing and several book chapters. Before academia, she worked in the scientific software industry.     

Using a customer-Level marketing strategy to enhance firm performance: A review of theoretical and empirical evidence

It is becoming increasingly apparent from the literature that marketers need to consider customer-level information when they generate a marketing strategy for the firm. In this article, the authors develop a customer-focused framework that uses a marketing strategy with an overall objective of maximized financial performance. This strategy is driven by seven customer-level marketing tactics and shows how actual customer data can be used to generate an actionable marketing strategy leading to optimal levels of profitability, customer equity, and shareholder value. In addition, the authors discuss a successful implementation of this strategy for several business-to-business and business-to-consumer firms and offer insights as to how to customize an implementation strategy for any firm, along with presenting potential challenges a firm may encounter during the implementation process. Several suggestions for future research are offered to explore and harness this newly available evidence. V. Kumar (VK) (vk@business.uconn.edu) is the ING Chair Professor of Marketing and the executive director of the ING Center for Financial Services at the University of Connecticut. He spends his time by transferring his knowledge (however little it may be) to his two daughters about customer lifetime value, diffusion models, forecasting sales and market share, retailing, and marketing strategy. J. Andrew Petersen (apetersen@business.uconn.edu) is a doctoral candidate in marketing at the University of Connecticut. His research interests include customer lifetime value, word-of-mouth effects, and customer-level marketing strategy. His research has been published inMarketing Research Magazine and theJournal of the Academy of Marketing Science.     

Forecasting recovery rates on non-performing loans with machine learning

We compare the performance of a wide set of regression techniques and machine-learning algorithms for predicting recovery rates on non-performing loans, using a private database from a European debt collection agency. We find that rule-based algorithms such as Cubist, boosted trees, and random forests perform significantly better than other approaches. In addition to loan contract specificities, predictors that refer to the bank recovery process — prior to the portfolio’s sale to a debt collector — are also shown to enhance forecasting performance. These variables, derived from the time series of contacts to defaulted clients and client reimbursements to the bank, help all algorithms better identify debtors with different repayment ability and/or commitment, and in general those with different recovery potential.     

Characteristics of agricultural input package users in communal clubs serviced by Acat in KwaZulu: A note

Characteristics of communal club members who use input packages are studied using a survey of communal clubs serviced by Africa Co‐operative Action Trust (Acat) in KwaZulu during 1989. Discriminant analysis shows that full input package adopters tend to belong to older clubs, have less formal savings and receive more visits each year from KwaZulu Department of Agriculture (KDA) extension officers. They also have a greater proportion of land under sugar‐cane, larger farm sizes and a higher rand monetary value of livestock.

Members of older clubs benefit from greater club experience in ordering inputs and liquidity for securing discounts on bulk orders. Clubs also enable scarce KDA extension manpower resources to be used more effectively by focusing extension efforts on groups rather than individual farmers. Sugar‐cane production probably indicates member willingness to innovate and the availability of funds to buy complete input packages for other crops. Increased access to land promotes input package adoption which can raise agricultural productivity. Development of institutional arrangements for a land rental market in KwaZulu should be considered. Higher monetary values of livestock reflect Increased ability to bear risk associated with technology adoption and that adopters have the means to purchase input packages     

There is relevance in the classroom: Analysis of present methods of teaching business ethics

In 1988 the Journal of Business Ethics published a paper by David Mathison entitled Business Ethics Cases and Decision Models: A Call for Relevancy in the Classroom. Mathison argued that the present methods of teaching business ethics may be inappropriate for MBA students. He believes that faculty are teaching at one decision-making level and that students are and will be functioning on another (lower) level. The purpose of this paper is to respond to Mathison's arguments and offer support for the present methods and materials used to teach Master level ethics classes. The support includes suggested class discussion ideas and assignments.Victoria K. Strong is a graduate student at Bentley College. She returned to school to pursue a Master of Science in Accountancy after working in the engineering profession for 12 years. She received her B.S. in Mechanical Engineering in 1984. Her business experience includes positions as Mechanical Design Engineer and Unit Supervisor of an engineering development laboratory. Alan N. Hoffman is an Associate Professor of Management at Bentley College. He received his DBA from Indiana University. Dr. Hoffman's writing has been published in the Academy of Management Journal and Human Relations.The authors would like to thank Carolyn Colt and the entire spring 1988 MG520-class for their valuable contributions.     

Regional, national, and spatially explicit scenarios of demographic and economic change based on SRES

We report here spatially explicit scenario interpretations for population and economic activity (GDP) for the time period 1990 to 2100 based on three scenarios (A2, B1, and B2) from the IPCC Special Report on Emissions Scenarios (SRES). At the highest degree of spatial detail, the scenario indicators are calculated at a 0.5 by 0.5 degree resolution. All three scenarios follow the qualitative scenario characteristics, as outlined in the original SRES scenarios. Two scenarios (B1 and B2) also follow (with minor adjustments due to scenario improvements) the original SRES quantifications at the level of 4 and 11 world regions respectively. The quantification of the original SRES A2 scenario has been revised to reflect recent changing perceptions on the demographic outlook of world population growth. In this revised “high population growth” scenario, A2r world population reaches some 12 billion by 2100 (as opposed to some 15 billion in the original SRES A2 scenario) and is characterized by a “delayed fertility transition” that is also mirrored in a delayed (economic) development catch-up, resulting in an initially stagnating and subsequently only very slow reduction in income disparities. The spatially explicit scenario interpretation proceeds via two steps. Through a combination of decomposition and optimization methods, world regional scenario results are first disaggregated to the level of 185 countries. In a subsequent second step, national results are further disaggregated to a grid cell level, taking urbanization and regional (rural–urban) income disparities explicitly into account. A distinguishing feature of the spatially explicit scenario results reported here is that both methodologies, as well as numerical assumptions underlying the “downscaling” exercise, are scenario-dependent, leading to distinctly different spatial patterns of population and economic activities across the three scenarios examined.