A model of advertising with application to the German automobile industry

This paper develops a dynamic duopolistic model of advertising and price competition. Advertising accumulates a stock of goodwill which enters directly into the demand functions and both the cooperative and predatory effects of advertising are considered. It is shown that firms invest more in advertising the higher the degree of cooperativeness of advertising and some comparative static results are provided. In the second, empirical part of the article, estimations of the demand equations are presented using data from the German automobile industry. The main conclusion drawn is that advertising plays an important role in this market and has a predatory nature.     

The Effects of Bailouts and Soft Budget Constraints on the Environment

This paper investigates the effects of financial relief programs, commonly referred to as ‘bailouts’, on pollution. A partial equilibrium soft budget constraint model of the firm is developed to identify the effect of bailouts on the emission decisions of firms. The results from the model indicate that the expectation of bailouts increases ex ante emissions. A more stringent emissions tax is required to achieve the same level of emissions if bailouts are available than if bailouts are not available; however, a tradable permit system will maintain the same emissions level if bailouts are available as when bailouts are not available.     

Literature-related discovery (LRD): Lessons learned, and future research directions

Literature-related discovery (LRD) is the linking of two or more literature concepts that have heretofore not been linked (i.e., disjoint), in order to produce novel, interesting, plausible, and intelligible knowledge (i.e., potential discovery). The open discovery systems (ODS) component of LRD starts with a problem to be solved, and generates solutions to that problem through potential discovery. We have been using ODS LRD to identify potential treatments or preventative actions for challenging medical problems, among myriad other applications. The five immediately preceding papers in this Special Issue describe the application of ODS LRD to Raynaud's Phenomenon (RP), cataracts, Parkinson's Disease (PD), Multiple Sclerosis (MS), and Water Purification (WP). We describe the lessons learned from each application, and how the techniques can be improved further.Generation of much potential discovery using ODS LRD is possible when the conceptual roadblocks to discovery are removed. Some of these roadblocks include use of numerical filters that are unrelated to generating discovery, and excessive reliance on literatures directly related to the problem literature of interest. The issue of how to handle large amounts of potential discovery has not been addressed in the literature, since most ODS LRD researchers have tried to find a relatively few potential discovery items. We present a development strategy that capitalizes on the large amounts of potential discovery we have identified.     

Does the use of imported intermediates increase productivity? Plant-level evidence

This paper examines whether importing intermediate goods improves plant performance. While addressing the issue of simultaneous productivity shocks and decisions to import intermediates, we estimate the impact foreign intermediates have on plants' productivity using plant-level Chilean manufacturing panel data. Across different estimators, we find evidence that becoming an importer of foreign intermediates improves productivity.     

Implications of the COVID-19 pandemic on market orientation in retail banking

Journal of Financial Services Marketing - This qualitative study examines the implications of the COVID-19 pandemic on the implementation of market orientation (MO) in the context of retail...     

Crowdsourcing without profit: the role of the seeker in open social innovation

Crowdsourcing has increasingly been studied as an open innovation (OI) mechanism by which organizations (seekers) engage with an external crowd of potential solvers. Previous crowdsourcing research has focused on solvers and their individual motivations, providing few insights as to why and how seekers use crowdsourcing, and how these choices affect the value that might be realized from these efforts. Prior research has also emphasized profit‐seeking firms, despite the use of OI practices by public sector organizations to achieve societal benefits. This paper examines the organizational and project‐level choices of government agencies that crowdsource from citizens to drive open social innovation, and thus develop new ways to address societal problems, a process sometimes termed ‘citizensourcing.’ Using rich data from 18 local government seekers that use the same intermediary, we develop a model of seeker crowdsourcing implementation that links a previously unstudied variance in seeker intent and engagement strategies to differences in project team motivation and capabilities, in turn leading to varying online engagement behaviors and ultimately project outcomes. Our study compares and contrasts governmental and corporate crowdsourcing to reveal that the non‐pecuniary orientation of both seekers and solvers means that the motives of government crowdsourcing are fundamentally different from corporate crowdsourcing, but the process in our sample more closely resembles that of a firm‐sponsored community rather than government sponsored contests. More generally, we show how seeker organizational factors and choices shape project‐level implementation and success of crowdsourcing efforts, as well as provide insights for OI activities of other smaller, geographically bound organizations.     

The relationship of industry structure to open innovation: cooperative value creation in pharmaceutical consortia

With its focus on value creation and value capture, open innovation research explicitly or implicitly examines the competitive impacts of collaboration. However, to date such research has not considered the effects of a blockbuster industry structure upon open innovation. Here, we examine a particular form of multilateral collaboration, the open R&D consortium, in which the results from collaboration are allowed to spill over to members and nonmembers alike. We do so in the context of the pharmaceutical industry, a stable but fragmented industry defined by the ongoing search for blockbuster hits protected by strong appropriability. Using a novel data set, we identify 141 such consortia that involve two or more of the 30 largest pharma firms. We show that firms financially support such consortia, in part, because their value creation activities benefit members without disrupting the value capture or other aspects of the incumbent industry structure. We discuss the implications of these findings for research on multilateral collaboration in blockbuster industries, and open innovation more generally.