Scientific status and knowledge use: Two perspectives

Summary In summary, it is important, from time to time, to step back and consider the publication process, as it exists in marketing and as it operates forJAMS. As part of this consideration, the issue of journal quality is paramount. As mentioned above, there are many ways to assess journal quality, and each method has its advantages and its limitations. In the field of marketing, we have a long history of relying on perceptual data, and this tradition is reflected in methods that rely on expert ratings and rankings of journals. In our field, we also have a history of trying to collect “objective” or quantitative data, and methods that rely on citation counts fit into this tradition. Here, using contrasting but related methods, we report encouraging evidence about the growing status and reputation ofJAMS as an influential publication outlet for marketing scholarship.     

An empirical test of trust-building processes and outcomes in sales manager-salesperson relationships

This study examines three trust-building processes and outcomes in sales manager-salesperson relationships. This study, based on a sample of more than 400 business-to-business salespeoples from a variety of industries, shows two trust-building processes (predictive and identification) to be significantly related to salesperson trust in the sales manager. Interpersonal trust was found to be most strongly related to shared values and respect. Trust was directly related to job satisfaction and relationalism, and indirectly related to organizational commitment and turnover intention. Thomas G. Brashear (brashear@mktg.umass.edu) (Ph.D., Georgia State University) is an assistant professor of marketing in the Isenberg School of Management at the University of Massachusetts-Amherst. James S. Boles (jboles@gsu.edu) (Ph.D., Louisiana State University) is an associate professor of marketing in the Robinson College of Business at Georgia State University. His research has appeared in a variety of journals, including theJournal of Marketing, theJournal of Business Research, theJournal of the Academy of Marketing Science, theJournal of Retailing, theJournal of Personal Selling and Sales Management, and theJournal of Applied Psychology. His areas of research interest include personal selling, sales management, key and strategic account management, and business relationships. Danny N. Bellenger (mktdnb@langate.gsu.edu) (Ph.D., University of Alabama) is currently chairman of the Marketing Department in the Robinson College of Business at Georgia State University. His research has appeared in a number of academic journals including theJournal of Marketing Research, theJournal of Marketing, theJournal of Advertising Research, theCalifornia Management Review, theJournal of Retailing, theJournal of Personal Selling and Sales Management, Industrial Marketing Management, and theJournal of Business Research. He has authored four monographs and four textbooks on marketing research, sales, and retailing. Charles M. Brooks (brooks@quinnipiac.edu) (Ph.D., Georgia State University) is an associate professor and chair of the Department of Marketing and Advertising at Quinnipiac University. His research has appeared in theJournal of Business Research, theJournal of Retailing, Marketing Theory, and theJournal of Marketing Theory and Practice.     

Playing the synthesizer with Canadian data: Adding polls to a structural forecasting model

Election forecasting has become a fixture of election campaigns in a number of democracies. Structural modeling, the major approach to forecasting election results, relies on ‘fundamental’ economic and political variables to predict the incumbent’s vote share usually a few months in advance. Some political scientists contend that adding vote intention polls to these models—i.e., synthesizing ‘fundamental’ variables and polling information—can lead to important accuracy gains. In this paper, we look at the efficiency of different model specifications in predicting the Canadian federal elections from 1953 to 2015. We find that vote intention polls only allow modest accuracy gains late in the campaign. With this backdrop in mind, we then use different model specifications to make ex ante forecasts of the 2019 federal election. Our findings have a number of important implications for the forecasting discipline in Canada as they address the benefits of combining polls and ‘fundamental’ variables to predict election results; the efficiency of varying lag structures; and the issue of translating votes into seats.     

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.     

General equilibrium impact of an energy-saving policy in the public sector

We analyse a disregarded environmental policy instrument: a switch in government expenditure away from energy (or other natural resources) and toward a composite good which includes energy-saving expenditure. We first develop two variants of an analytical general equilibrium model. A composite good is produced with constant returns to scale, and energy is imported or produced domestically with diminishing returns, yielding a differential rent to its owners. The government purchases energy and composite goods from private firms. Such a policy unambiguously increases employment. It also raises private consumption and welfare under two conditions: (i) it is not too costly and (ii) the initial share of the resource is smaller in public spending than in private consumption, or the difference is small enough. We then run numerically a model featuring both importation and domestic production of energy (oil, gas and electricity), for the OECD as a whole. Simulations show that employment, welfare and private consumption rise. We provide magnitudes for different parameter values. Earlier versions of this paper have benefited from conference participants at the European Council for an Energy-Efficient Economy, International Society for Ecological Economics World Congress, CIRED seminar and EUREQua environmental economics seminar. We especially thank Michèle Sadoun and two anonymous referees. The usual disclaimer applies.     

A Global Ex-vessel Fish Price Database: Construction and Applications

Synopsis We describe the first effort at creating a global ex-vessel fish price database, which is required for understanding the economic behavior of participants in the world’s fisheries. We demonstrate potential applications of the database by linking it to a spatially defined catch database, which makes it possible to attach landed values to species in both time and space. This is the first database available publicly where interested members of the public, researchers and managers can easily find and access ex-vessel prices of the world’s major commercial fish species. Preliminary results indicate that the average real price of a number of species have declined between 1950 and 2002. The estimated landed value of fish globally, in year 2000 dollars, was about US$24 billion in 1950. It increased steadily to about US$90 billion in the early 1970s, reached a peak of US$100 billion at the end of the 1980s, and declined to about US$80 billion in 2000. The top 15 fishing countries cumulatively account for 79% of total real landed value, with Japan leading, even though the value of its landings has been declining.      

Do we really care about Biodiversity?

This paper addresses from an economic perspective the issue of global biodiversity conservation. It challenges the perception that the world really cares a great deal about biodiversity and is prepared to pay the full cost of maintaining this stock of natural capital. Despite the existence of a plethora of international agreements there still seems to be a global ‘deficit of care’ surrounding efforts to combat challenges such as those posed by global warming and biodiversity conservation. More light can be thrown on the degree of care by measuring both the actual expenditures and the stated willingness to pay for biodiversity conservation. However, actual expenditures are much lower than willingness to pay estimates recorded in the published literature. Using the criteria that the ‘right’ amount of conservation effort is one where the marginal economic benefits from conservation just equal the marginal costs of conservation, the paper explores the biodiversity conservation conundrum and concluded that, on the available evidence, the world does not care too much about this natural capital stock and bequests to future generations. An erratum to this article can be found at     

Distributional assumptions and a test of the dual labor market hypothesis

Recent application of the switching regression model to allocate workers into the primary and secondary labor markets is considered to be the best solution to the classification problem of the empirical testing of the dual labor market theory. In such models, normality of the error terms is assumed. This paper adopts the switching regression model to test the dual labor market theory by assuming different distributions of the error terms. The test results strongly support the dual labor market theory regardless of the assumption one makes about the error terms. However, the results indicate that different distribution can lead to different percentage distributions of workers in the two segments. In particular, the normal distribution generates more workers in the primary segment than the non-normal distributions. Therefore, care must be taken not to generalize the type of industries or occupations that fall under the primary and secondary segments. First version received: October 2000/Final version received: March 2002 RID="*" ID="*"  I would like to thank Kevin Lang, Robert Marshall, and two anonymous referees for their helpful comments. I am grateful for comments received from the session participants of the Western Economic Association International Conference, San Francisco, CA, June 28–July 2, 1996, and the Midwest Economic Association Conference, Kansas City, 1997. I thank George Bonney, the Chief Statistician of Fox Chase Cancer Center, Philadelphia for his comments. Any remaining errors are my responsibility. I gratefully acknowledge financial support from Penn State Research and Development Grant, 1995.     

Applied Welfare Economics with Bounded Rationality: Public Policies Toward Remote Sensing

Earlier experimental evidence indicates that some decision makers under-invest in information when it is costly. This insight is applied to the cost–benefit analysis of the provision of data obtained by satellites. In fields like agriculture, remotely sensed information of great precision can be provided to additional farmers at minimal extra costs if a service for farmers with similar information needs is set up. Here, the tendency to under-invest in information asks for creative solutions by the private sector: bankers may work together with rational producers in setting up the information service and promoting it. However, if producers financial resources are insufficient, public intervention, in the form of a free information service may be necessary.The author would like to thank an anonymous referee, Stephan von Cramon-Taubadel, Sean Flynn, Daniel Heller, and Carlos Lenz and participants of the Lisbon Conference of the International Atlantic Economic Society, particularly Asatoshi Maeshiro, for helpful comments.