Innovating for Good in Opportunistic Contexts: The Case for Firms’ Environmental Divergence

Journal of Business Ethics - Opportunistic behaviors are considered ethically and strategically troublesome since they disrupt otherwise mutually beneficial relationships. Previous literature has...     

Effects of broadband availability on total factor productivity in service sector firms: Evidence from Ireland

While broadband is widely believed to augment productivity, there is little firm-level evidence of a generalised causal effect. In this paper we examine whether the introduction of digital subscriber line (DSL) broadband services increased firms' productivity in nine sub-sectors within the services and distribution sector in Ireland from 2006 to 2012. Firm-level panel data on firms' characteristics are linked to spatial information on the rollout of DSL. While we do not find significant productivity effects in the services sectors taken together, we do find positive and significant effects on firm's total factor productivity in Information & Communication and Administrative & Support Services.     

Estimating Differential Dynamic Merger Effects on Market Structure and Entry in Related Markets

The U.S. and EU merger guidelines emphasize “ease of entry” arguments but little is known about the dynamic impact of realized mergers on market structure. This study provides insights on this topic with the use of detailed firm-level data on the memory chip market. Our estimation results provide evidence for differential merger effects on market structure. These effects depend on whether the mergers are dominated by market-power or efficiency gains. While efficiency-dominated mergers cause exit, market-power-dominated mergers attract entrants, and these effects are increasing over time. We also find that market-power mergers have a larger effect on entry than efficiency mergers have on exit. Our results show that mergers can reduce the number of potential entrants into related product markets and serve as an instrument to “reduce the likelihood of entry”.

     

The American Inventors Protection Act: A Natural Experiment on Innovation Disclosure and the Cost of Debt

We examine the impact of innovation disclosure through patenting on firms' cost of debt, focusing on the American Inventors Protection Act (AIPA) as an exogenous shock in innovation disclosure regulation. Post‐AIPA, firms have an incentive to apply for patents only if commercial success is likely. Accordingly, we expect post‐AIPA patents to be a better proxy for successful innovation activity, and thus to have a stronger effect on reducing the cost of debt than pre‐AIPA patents. Indeed, we find that pre‐AIPA patents reduce the cost of debt only for the most innovative firms, while post‐AIPA, this effect holds for all firms.     

Analytical approximations of local‐Heston volatility model and error analysis

This paper studies the expansion of an option price (with bounded Lipschitz payoff) in a stochastic volatility model including a local volatility component. The stochastic volatility is a square root process, which is widely used for modeling the behavior of the variance process (Heston model). The local volatility part is of general form, requiring only appropriate growth and boundedness assumptions. We rigorously establish tight error estimates of our expansions, using Malliavin calculus. The error analysis, which requires a careful treatment because of the lack of weak differentiability of the model, is interesting on its own. Moreover, in the particular case of call–put options, we also provide expansions of the Black–Scholes implied volatility that allow to obtain very simple formulas that are fast to compute compared to the Monte Carlo approach and maintain a very competitive accuracy.     

Business model innovation in a knowledge revolution: An evolutionary theory perspective

For knowledge‐intensive industries, a need remains to increase clarity on the dynamics through which business model innovation occurs. Progress has been limited owing to complexities in these industries and to the underlying ontology of the business model concept itself. Through a conceptual methodology, our findings expose impediments to current business model theory and propose economic evolutionary theory as a useful alternative lens through which to address these limitations. This research contributes to the literature by broadening the traditional scope of the economic evolutionary view as relevant for business model innovation research and by offering a corresponding framework for future research.     

The process of entrepreneurial action at the base of the pyramid in developing countries: a case of vegetable farmers in Benin

The assumption that entrepreneurship is a critical factor in expanding employment, creating wealth and contributing to poverty alleviation at the base of the pyramid (BoP) in developing countries has led to the development of many initiatives to strengthen the entrepreneurial activities of poor people. Despite the fact that entrepreneurship is seen as a strategy in combatting poverty, the process that leads to entrepreneurial action in a BoP context is still unclear. In this paper, we illustrate the possibilities a multi-layered perspective offers to understand the complexity of entrepreneurship in poverty settings. Based on five focus group discussions and 36 in-depth interviews with vegetable farmers in Benin, we examined the entrepreneurship of poor people. We learned that entrepreneurial action is the nexus of individual and exogenous factors in complex relationships. Based on this, we elaborate on the characteristics of the process model of entrepreneurial action. We provide a process-based view of entrepreneurship at the BoP, suggesting a need for consistency between individual, behavioural strategies and contextual elements. We discuss the implications of our findings for BoP practice and provide a framing perspective that we hope will encourage a greater focus on the complexity of entrepreneurship phenomenon.     

Human resource management practices and voluntary turnover: a study of internal workforce and external labor market contingencies

We tested relationships between employee quit rates and two bundles of human resource (HR) practices that reflect the different interests of the two parties involved in the employment relationship. To understand the boundary conditions for these effects, we examined an external contingency proposed to influence the exchange-based effects of HR practices on subsequent quit rates – the local industry-specific unemployment rate – and an internal contingency proposed to shape employees’ conceptualization of their exchange relationship – their employment status (i.e. full-time, part-time and temporary employment). Analyses of lagged data from over 200 Canadian establishments show that inducement HR practices (e.g. extensive benefits) and performance expectation HR practices (e.g. performance-based bonuses) had different effects on quit rates, and the former effect was moderated by unemployment rate. The effects of HR practices on quit rates did not differ between FT and PT employees, but a different pattern of main and interactive effects was found among temporary workers. These findings suggest that employees’ exchange-based decisions to leave may be less affected by the number of hours they expect to work each week, and more by the number of weeks they expect to work.     

Determinants of process innovation introductions: Evidence from 115 developing countries

This paper examines determinants of process innovation introductions across 115 (mostly) developing countries. Empirical research on process innovations lags behind product innovations. Accounting for firm characteristics, R&D, regulations and taxes, and corruption, results show that sole proprietors and R&D‐performing firms were more likely to introduce innovations, whereas greater prosperity made them less likely to do so. Corruption had a greasing effect, whereas firms in island nations were less likely to introduce, ceteris paribus. Effects of regulations and taxes and other firm characteristics were largely insignificant. Finally, some differences existed across manufacturing and service industries and across prevalence of innovation introductions.     

Bayesian Inference in Spatial Sample Selection Models

In this study, we consider Bayesian methods for the estimation of a sample selection model with spatially correlated disturbance terms. We design a set of Markov chain Monte Carlo algorithms based on the method of data augmentation. The natural parameterization for the covariance structure of our model involves an unidentified parameter that complicates posterior analysis. The unidentified parameter – the variance of the disturbance term in the selection equation – is handled in different ways in these algorithms to achieve identification for other parameters. The Bayesian estimator based on these algorithms can account for the selection bias and the full covariance structure implied by the spatial correlation. We illustrate the implementation of these algorithms through a simulation study and an empirical application.