Business models and their relationship with marketing: A systematic literature review

The purpose of this paper is to identify the degree to which the marketing discipline has hitherto engaged with business model literature. The results of a systematic review of business model literature are presented and utilise both the citation counts and the h-index to objectively demonstrate the limited engagement that the marketing discipline has had with business model literature, and the limited degree that the discipline has influenced that literature. The key findings reveal a growing, but formative body of literature that, hitherto, has been dominated by non-marketing disciplines and which has only just begun to be addressed by present day marketing scholars. Using the most influential articles identified in the analysis, the paper concludes with a case for the empirical development of the business model concept with industrial marketing scholarship. Such development is argued to be grounded in the potential of open business models, co-created with multiple stakeholders in a supply chain and the end users of a value proposition.     

The Foreclosure–House Price Nexus: A Panel VAR Model for U.S. States, 1981–2009

Despite housing's economic importance, little has been written on how foreclosures and home prices interact in a framework that includes macroeconomic and housing variables such as employment, permits or sales. Panel VAR results for quarterly state‐level data indicate that price–foreclosure linkages run both ways. Foreclosures negatively impact home prices. The negative impact of prices on foreclosures, however, is much larger. These results suggest the low‐frequency association observed between foreclosures and prices is mostly driven by the endogenous adjustment of foreclosures to prices via the strategic choices of homeowners and lenders, rather than through the effects of foreclosures on home prices.     

The Impact of Second Loans on Subprime Mortgage Defaults

An estimated 12.6% of primary mortgage loans were simultaneously originated with a second loan from 2004 until 2008, although relatively little is known about how the presence of such subordinate loans affects the default decisions of borrowers. We use a novel data series of loan servicing records from 2002 until 2010 to identify such borrowers and find evidence that the default behavior of these borrowers significantly differs from borrowers without second loans. Estimating a discrete‐time proportional odds hazard model, we find borrowers with a second loan were 62.7% more likely to default each month on their primary loan when conditioning alone on the attributes of the primary loan. However, borrowers of second loans were 58.3% less likely to default on their primary loan as compared to single‐loan borrowers with equivalent current combined attributes (i.e., loan‐to‐value, balance and interest rate). We hypothesize and provide empirical evidence that this occurs because borrowers with second loans have the option to sequentially default on each loan since subordinate lenders will not pursue foreclosure if borrowers have insufficient equity. Lenders of defaulted subordinate debt may revisit their decision to foreclose in the future after housing markets start to recover, thus prompting a new round of foreclosures.     

Optimal Farm-to-Market Transportation and Storage of Certain Agriculture Commodities: Bogota,Colombia ∗

Decision rules for the make-buy decision most often assume the form of single-item, incremental cost rules which, for application, require decisions to be made for each item in isolation from all others. While it has been recognized that such decision rules may be non-optimal in situations where equipment capacity limits exist, the literature has not considered other cases where non-optimality arises. The purpose of this paper is to use linear programming as a framework for evaluating the optimality of single-item, incremental cost rules. The major conclusion of this paper is that the presence of any type of binding constraint in the planning problem, regardless of its origin, renders a single-item decision rule potentially non-optimal. A set of optimal screening decision rules is developed to be used in conjunction with a linear programming model for make-buy decisions in cases where such binding constraints exist.     

Private equity leveraged buyouts in European telecoms: The case of Eircom

Highly leveraged buyouts (LBOs) of former state owned telecoms operators by private equity groups have occurred in a number of countries in recent years. This paper examines the case of Eircom in Ireland which has experienced five changes in ownership since full privatisation in 1999, two of which were LBOs. Enormous increases in Eircom’s debt levels as a result of the LBOs resulted in the company’s bankruptcy in 2012. This paper argues that this outcome was largely attributable to the short-termist strategies adopted by the private equity groups that assumed ownership of the enterprise. These strategies included high leverage, cash extraction and underinvestment in the fixed-line network which contributed to the demise of the enterprise and had wider economic and social effects. The Eircom case demonstrates the risks attendant to ownership of important network infrastructure by private equity groups and the need for regulatory safeguards to protect the public interest.     

Reaffirming the CEO effect is significant and much larger than chance: A comment on Fitza (2014)

A recent study by Fitza argued that the prior estimates of the Chief Executive Officer (CEO) effect are conflated with events outside the CEO's control, are largely the result of random chance, and that the true CEO effect is smaller than has been previously estimated. We suggest that the empirical methodology employed by Fitza to support these claims substantially overstates the “random chance” element of the CEO effect. We replicate Fitza's findings, highlight methodological issues, offer alternative conclusions, and using multilevel modeling (MLM), suggest that his analyses mischaracterize the CEO effect. Copyright © 2016 John Wiley & Sons, Ltd.     

Higher Highs and Lower Lows: The Role of Corporate Social Responsibility in CEO Dismissal

Research summary: Investing a firm's resources in corporate social responsibility (CSR) initiatives remains a contentious issue. While research suggests firm financial performance is the primary driver of CEO dismissal, we propose that CSR will provide important additional context when interpreting a firm's financial performance. Consistent with this prediction, our results suggest that past CSR decisions amplify the negative relationship between financial performance and CEO dismissal. Specifically, we find that greater prior investments in CSR appear to expose CEOs of firms with poor financial performance to a greater risk of dismissal. In contrast, greater past investments in CSR appear to help shield CEOs of firms with good financial performance from dismissal. These findings provide novel insight into how CEOs' career outcomes may be affected by earlier CSR decisions. Managerial summary: In this study, we examined a potential personal consequence for CEOs related to corporate social responsibility (CSR). We explored the role prior investments in CSR play when a board evaluates the firm's financial performance and considers whether or not to fire the CEO. Our results suggest that while financial performance sets the overall tone of a CEO's evaluation, CSR amplifies that baseline evaluation. Specifically, our results suggest that greater past investments in CSR appear to (a) greatly increase the likelihood of CEO dismissal when financial performance is poor, and (b) somewhat reduce the likelihood of CEO dismissal when financial performance is good. Thus, striving to deliver profits in a socially responsible manner may have both positive and negative personal consequences. Copyright © 2017 John Wiley & Sons, Ltd.     

Spatial Heterogeneity in Mortgage Terminations by Refinance, Sale and Default

This article investigates the impact of spatially correlated unobservable variables on the refinancing, selling and default decisions of mortgage borrowers. Virtually the entire mortgage literature acknowledges that borrower-specific characteristics, such as culture, education or access to information, play an important role in mortgage termination decisions. While we do not observe these variables directly, we note that borrowers of similar background tend to cluster together in neighborhoods. We estimate a competing risks hazard model with random effects using a three-stage maximum likelihood estimation approach. We utilize the space-varying coefficient method to modify the covariance structure according to the spatial distribution of the observations. Beyond a significant improvement of the model performance, this yields a number of insightful implications for mortgage termination behavior. For instance, borrowers of the affluent "West Side" of Los Angeles County both refinance and move at a higher rate than predicted by the standard maximum likelihood estimation method. At the same time, borrowers from some lower-valued neighborhoods tend to stay longer than expected with their mortgages and properties.     

Technology improves sales performance—doesn't it?: An introduction to the special issue on selling and sales technology

Firms around the globe are rushing to invest in sales force technology or sales force automation (SFA). SFA appears to mean different things to different people. For example, management and sales personnel view the need for, application of, and advantages of SFA quite distinctly. As a result of technology, this special issue examines many areas of sales force automation to provide both practicing managers and sales force academicians with a clearer perspective of new technology in the B2B marketplace. This article introduces the special issue topic, individual contributors, and acknowledges support proffered by myriad individuals.     

The effect of uncertainty and asset co‐specialization on governance in biotechnology alliances

We explore transaction cost economics (TCE) and real option (RO) rationales for alliance governance and find the predictive power of each depends upon the type of uncertainty confronted. Our review of alliance activity from 1995 through 2000 for 642 alliances confirms that governance is influenced directly by partner, task, and technological uncertainty and by interactions among asset co‐specialization, partner uncertainty, and task uncertainty. Consistent with TCE, co‐specialized assets increased the likelihood of hierarchical governance. Partner and task uncertainty increased this effect. Consistent with RO, we find technological uncertainty decreased the likelihood of hierarchical governance. Copyright © 2005 John Wiley & Sons, Ltd.