Measuring to Improve Versus Measuring to Prove: Understanding the Adoption of Social Performance Measurement Practices in Nascent Social Enterprises

Social enterprises are described as organizations with dual objectives—social and commercial. While the measurement of commercial performance is relatively straightforward and well understood, our understanding of the factors related to measuring social performance is more ambiguous. Is the adoption of social performance measurement (SPM) practices more related to external pressures, such as the need to demonstrate legitimacy to funders and peers, or is it more closely related to the growing rationalization within the social sector? We examine the relationship between external and internal factors and the adoption of SPM using a novel dataset of 1864 nascent social enterprises from around the world. Our findings suggest support for the argument that the adoption of SPM in social enterprise is related to the growing rationalization of the social sector, which challenges some of the past research on this topic, and provides a more nuanced perspective of SPM in social enterprise.     

FROM MAIZE TO HAZE: AGRICULTURAL SHOCKS AND THE GROWTH OF THE MEXICAN DRUG SECTOR

Understanding how economic incentives affect illegal drug production is essential for crafting policies in response to the international drug trade. Policymakers typically face a choice between two strategies: targeting criminal groups via law enforcement, and offering producers incentives to engage in alternate activities. Yet, little is known about how the returns to alternate legal activities affect drug supply. We contribute to this literature by examining how shocks to legal commodity prices affect the drug trade in Mexico. Our analysis exploits exogenous movements in the Mexican maize price stemming from weather conditions in US maize‐growing regions, as well as exports of other major maize producers. Using data on over 2200 municipios spanning 1990–2010, we show that lower prices differentially increased the cultivation of both marijuana and opium poppies in municipios more climatically suited to growing maize. We also find impacts on downstream drug‐trade outcomes, including drug cartel operations and killings perpetrated by these groups. Our findings demonstrate that maize price changes contributed to the burgeoning drug trade in Mexico, and point to the violent consequences of an expanding drug sector.     

Managing Demand Uncertainty through Core Acquisition in Remanufacturing

We discuss the optimal raw material acquisition strategy for a third party remanufacturer (3PR). We specifically investigate whether a 3PR should acquire used products or cores in bulk with uncertain quality levels, or in sorted grades with known quality levels; and whether to acquire and remanufacture cores before the demand is realized (planned acquisition), or after the demand is realized (reactive acquisition), or on both occasions (sequential acquisition). When only sorted cores are acquired, we find that, (i) it is optimal to acquire cores in multiple grades to balance acquisition and remanufacturing costs; (ii) if reactive acquisition is possible, it reduces the assortment size (number of grades in which cores are acquired) and the total inventory acquired in the planned acquisition; and (iii) the optimal portfolio of grades to acquire and the optimal acquisition and remanufacturing quantities of these grades can be determined analytically. When bulk cores are acquired in addition to sorted cores, the property of reduction in assortment size of the planned acquisition is preserved. We also show that the 3PR should acquire only a fraction of the demand in planned acquisition, and leave the rest for reactive acquisition. This fraction changes during the lifecycle of a remanufactured product. Using a combination of empirical and realistic data from a smartphone remanufacturer we show that sequential acquisition increases expected profit by up to 8% and 27% over only planned and only reactive acquisitions respectively, and reduces the inventory acquired by up to 21% over only planned acquisition.     

FPT algorithms for Connected Feedback Vertex Set

We study the recently introduced Connected Feedback Vertex Set (CFVS) problem from the view-point of parameterized algorithms. CFVS is the connected variant of the classical Feedback Vertex Set problem and is defined as follows: given a graph G=(V,E) and an integer k, decide whether there exists F?V, |F|??k, such that G[V?F] is a forest and G[F] is connected. We show that Connected Feedback Vertex Set can be solved in time O(2 ^O(k) n ^O(1)) on general graphs and in time $O(2^{O(\sqrt{k}\log k)}n^{O(1)})$ on graphs excluding a fixed graph H as a minor. Our result on general undirected graphs uses, as a subroutine, a parameterized algorithm for Group Steiner Tree, a well studied variant of Steiner Tree. We find the algorithm for Group Steiner Tree of independent interest and believe that it could be useful for obtaining parameterized algorithms for other connectivity problems.     

Dynamic Pricing in e‐Services under Demand Uncertainty

High volatility of the e‐services market, due to increasing competition, low life cycle of products, and easy availability of information about competing service offerings to customers, makes the demand for service offerings quite uncertain. Revenue management in such markets calls for real‐time techniques to learn the demand and its dependence on both the price and the service level associated with the service offering. We assume firms reply on exploratory approaches for demand estimation, in which firms experiment with different service offerings in order to simultaneously learn the demand while doing business. Such exploration and learning process can be costly without supervision. As reported by Rothschild (Journal of Economic Theory, 9 185‐202, 1974), traditional Bayesian dynamic control approaches may conclude with suboptimal offerings. We propose a novel demand learning approach that is guaranteed to converge to the optimal offering. The approach combines simulated annealing algorithm with Bayesian learning. We further present intelligent techniques that adaptively reduce the effort of exploration on suboptimal service offerings so as to improve the long‐run average profit.     

Can Institutional Support Improve Volunteer Quality? An Analysis of Online Volunteer Mentors

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - Volunteer management practices have been shown to have positive effects on employees in terms of skill development, job...     

Managing Supply Risk for Vertically Differentiated Co‐Products

The manufacturing complexity of many high‐tech products results in a substantial variation in the quality of the units produced. After manufacturing, the units are classified into vertically differentiated products. These products are typically obtained in uncontrollable fractions, leading to mismatches between their demand and supply. We focus on product stockouts due to the supply–demand mismatches. Existing literature suggests that when faced with product stockouts, firms should satisfy all unmet demand of a low‐end product by downgrading excess units of a high‐end product (downward substitution). However, this policy may be suboptimal if it is likely that low‐end customers will substitute with a higher quality product and pay the higher price (upward substitution). In this study, we investigate whether and how much downward substitution firms should perform. We also investigate whether and how much low‐end inventory firms should withhold to strategically divert some low‐end demand to the high‐end product. We first establish the existence of regions of co‐production technology and willingness of customers to substitute upward where firms adopt different substitution/withholding strategies. Then, we develop a managerial framework to determine the optimal selling strategy during the life cycle of technology products as profit margins shrink, manufacturing technology improves, and more capacity becomes available. Consistent trends exist for exogenous and endogenous prices.