Incumbent Responses to an Entrant with a New Business Model: Resource Co-Deployment and Resource Re-Deployment Strategies

The constructs of re-deployment and co-deployment have been central to discussions of scope economies in diversified firms. We argue however that these constructs are also significant in the context of single business firms. Increasingly, changes in technology and demand preferences have provided opportunities for entrants to attack incumbents with a different business model, one that may neutralize the incumbent’s advantage for at least some set of customers (e.g. Netflix versus Blockbuster). In such a context incumbents often respond by modifying their business model. We note that several of the business model-altering responses of the incumbent can be characterized in terms of co-deployment and re-deployment benefits and costs, where co-deployment benefits/cost apply to the scope economies/diseconomies in running multiple business-models within the same firm and re-deployment benefits/costs apply to the implications of moving assets from one business model to another. We then examine the set of strategic choices faced by the incumbent in competing with an entrant with a different business model. We identify five set of factors that are likely to influence the decision to choose between these alternatives – uncertainty spawned by the new business model, market segment targeted by the new model, the within-business-across-business-model co-deployment and re-deployment benefits and costs, the across-business co-deployment and re-deployment benefits and costs, and the incumbent’s prior performance history. Although some of these choices have seen some work, most remain relatively underexplored in the strategy literature. We highlight the potential for research in this area with a set of propositions that identify key conditions that should hold true for a particular strategic choice to be picked by an incumbent

Strength of Protection for Geographical Indications: Promotion Incentives and Welfare Effects

We address the question of how the strength of protection for geographical indications (GIs) affects the GI industry\u27s promotion incentives, equilibrium market outcomes, and the distribution of welfare. Geographical indication producers engage in informative advertising by associating their true quality premium (relative to a substitute product) with a specific label emphasizing the GI\u27s geographic origin. The extent to which the names/words of the GI label can be used and/or imitated by competing products—which depends on the strength of GI protection—determines how informative the GI promotion messages can be. Consumers’ heterogeneous preferences (vis-à-vis the GI quality premium) are modeled in a vertically differentiated framework. Both the GI industry and the substitute product industry are assumed to be competitive (with free entry). The model is calibrated and solved for alternative parameter values. Results show that producers of the GI and of the lower-quality substitute good have divergent interests: GI producers are better off with full protection, whereas the substitute good\u27s producers prefer intermediate levels of protection (but they never prefer zero protection because they benefit indirectly if the GI producers’ incentives to promote are preserved). For consumers and aggregate welfare, the preferred level of protection depends on the model\u27s parameters, with an intermediate level of protection being optimal in many circumstances

Non-parametric Bayesian drift estimation for stochastic differential equations

We consider non-parametric Bayesian estimation of the drift coefficient of a one-dimensional stochastic differential equation from discrete-time observations on the solution of this equation. Under suitable regularity conditions that are weaker than those previosly suggested in the literature, we establish posterior consistency in this context. Furthermore, we show that posterior consistency extends to the multidimensional setting as well, which, to the best of our knowledge, is a new result in this setting.Comment: 27 page

Is complexity leadership theory complex enough? A critical appraisal, some modifications and suggestions for further research

Scholars are increasingly seeking to develop theories that explain the underlying processes whereby leadership is enacted. This shifts attention away from the actions of ‘heroic’ individuals and towards the social contexts in which people with greater or lesser power influence each other. A number of researchers have embraced complexity theory, with its emphasis on non-linearity and unpredictability. However, some complexity scholars still depict the theory and practice of leadership in relatively non-complex terms. They continue to assume that leaders can exercise rational, extensive and purposeful influence on other actors to a greater extent than is possible. In effect, they offer a theory of complex organizations led by non-complex leaders who establish themselves by relatively non-complex means. This testifies to the enduring power of ‘heroic’ images of leader agency. Without greater care, the terminology offered by complexity leadership theory could become little more than a new mask for old theories that legitimize imbalanced power relationships in the workplace. This paper explores how these problems are evident in complexity leadership theory, suggests that communication and process perspectives help to overcome them, and outlines an agenda for further research on these issues

What Explains Personality Covariation? A Test of the Socioecological Complexity Hypothesis

Correlations among distinct behaviors are foundational to personality science, but the field remains far from a consensus regarding the causes of such covariation. We advance a novel explanation for personality covariation, which views trait covariance as being shaped within a particular socioecology. We hypothesize that the degree of personality covariation observed within a society will be inversely related to the society’s socioecological complexity, that is, its diversity of social and occupational niches. Using personality survey data from participant samples in 55 nations (N ¼ 17,637), we demonstrate that the Big Five dimensions are more strongly intercorrelated in less complex societies, where the complexity is indexed by nation-level measures of economic development, urbanization, and sectoral diversity. This inverse relationship is robust to control variables accounting for a number of methodological and response biases. Our findings support the socioecological complexity hypothesis and more generally bolster functionalist accounts of trait covariation

Integrated Surveys of Neglected Tropical Diseases in Southern Sudan: How Much Do They Cost and Can They Be Refined?

Control of neglected tropical diseases (NTDs) is suggested to be more cost-effective when drugs are co-administered through a single integrated delivery system rather than separate systems. An essential prerequisite for such efficiency gains is sufficient geographical overlap of the targeted diseases – lymphatic filariasis (LF), onchocerciasis, schistosomiasis, soil-transmitted helminth infection and trachoma. Lack of data on geographical NTD distribution currently hampers the implementation of integrated control in many African countries. To generate the required data quickly and efficiently, integrated surveys of several NTDs simultaneously have been recommended. However, experience with integrated surveys is limited and requires additional research on cost and effectiveness to inform improvements in methodology and to guide scale-up. Here we analyse costs of the first integrated NTD survey round in Southern Sudan, generating average costs per implementation unit surveyed. Cost estimates are presented for use of the existing survey method and for modified versions. Key cost drivers were survey consumables and personnel, both of which are recurrent costs. These inputs could be reduced or put to more efficient use by modifying sampling for LF. To generate comparable cost estimates and identify key cost drivers in other settings we provide detailed cost data and guidance on how to replicate this work