3. Producción
Browse
16 results
Search Results
- Some of the metrics are blocked by yourconsent settings
Item type:Publication, Quantifying productivity at landscape scale using remotely-sensed foliar traits and canopy structure(Research Square, 2020-11-02)Abstract Forests are integral to global carbon cycling but are threatened by anthropogenic degradation and climate change. Assessing this global threat has been hindered by a lack of clear, flexible, and easy-to-use productivity models along with a lack of functional trait and productivity data for parameterizing and testing those models. Current productivity models are either extremely complex requiring up to hundreds of parameters, many sub-models, and considerable computational expense or rely on statistical trait-growth relationships that can be hard to extrapolate to new systems or climates. Here we provide a simple alternative: a remote sensing canopy functional model (RS-CFM) that uses remotely-sensed foliar traits and canopy structure data to efficiently map productivity at high-resolution and large spatial scales. We test this model by quantifying net primary productivity (NPP) at 0.01-ha resolution in 30,040 hectares of Peruvian tropical rainforest along a 3,322-m Amazon-to-Andes elevation gradient. Our model predicts local NPP and elevational shifts in NPP much more accurately and in greater detail than a prominent alternative method—NASA’s MODIS NPP product. Furthermore, we show how NPP estimates depend on light competition and identify the appropriate spatial resolution for remote productivity estimation. Our framework opens up possibilities to fully harness remote sensing data and reliably scale up from traits to map regional or global productivity in a more direct, efficient, and cost-effective manner. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Sustainable development challenges in a war-torn country: Perceived danger and psychological well-being(John Wiley and Sons Ltd, 2020-08-01)The laborer's physical and mental health, well-being, and happiness are among the major indicators for measuring each nation's sustainable development. A conflictive and hostile external environment (war zone) poses considerable difficulty and psychological distress to workers and nonworkers. Therefore, working in such a physically dangerous business environment may hurt worker's well-being and happiness that in turn may reduce the workers' productivity at the workplace. A high level of laborers' productivity in public and private sectors is essential for achieving sustainable development in the long term. Therefore, this paper examines the effects of perceived danger on employees' psychological well-being in war-torn Afghanistan, an issue being addressed for the first time. We tested the moderating role of social support from coworkers on this effect in order to have a broader vision of which individuals are healthier and happier in a physically dangerous working environment. Two survey data sets were collected from 190 employees working in various small private and public businesses in Herat, Afghanistan. Our results reveal the negative impact of perceived danger on employees' psychological well-being and that employees who receive little or no social support from their peers feel the negative effects of a physically dangerous working condition even more acutely. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Assessing the effects of human capital composition, innovation portfolio and size on manufacturing firm performance(Emerald, 2020-09-04)Purpose This paper aims to focus on the effects of human capital composition, innovation portfolio and size on manufacturing firms’ performance. Moreover, it seeks to empirically identify the levels of education that are significant in labour productivity. Design/methodology/approach The resource-based view (RBV) theory is applied using data gathered from the National Innovation Survey in the Manufacturing Industries of Peru. Using the ordinary least squares method on a sample of 584 Peruvian manufacturing firms, the effects on firm performance of two subsamples according to innovation portfolio and firm size are determined. Findings The direct effects of human capital composition on productivity show that the higher the workers’ educational level, the higher the productivity. However, if this relationship is analysed in terms of the innovation portfolio, the authors find that labour productivity in companies with product–service innovation is greater (i.e. more significant) than in traditional manufacturing firms with only product innovations. Similarly, if this relationship is compared in terms of company, the authors find that large companies are more significant than small and medium-sized enterprises. Practical implications The study furthers the understanding of how the relationship between human capital composition, innovation portfolio and size of manufacturing firms positively affects labour productivity. Hence, it can help managers to craft their innovation portfolio according to the educational level of their human capital. This could require that not only human resource management innovates, but also that strategic partnerships be developed with educational establishments to boost training towards product–service innovation. Originality/value This study’s results provide confirmation that the configuration of human resources, innovation portfolio and size plays a significant role on manufacturing firms’ performance, particularly in the context of developing countries. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Effects of obstacles to innovation: are they complementary?(Centre international de psychosomatique, 2021-03-08)This paper investigates whether the effects of obstacles to firms’ propensity for and intensity of innovation were complementary in Peru, a middle-income developing country, during the period 2009-2011. The tests of complementarity are based on the estimation of two adjusted Crépon–Duguet–Mairesse (CDM) models that relate a firm’s decision to invest in science, technology and innovation activities (STI), the innovation process, and labor productivity. The estimations and tests yield four main results. First, there is evidence that the effects of obstacles to innovation are related and some are complementary. Second, firms’ size (particularly the largest ones) affects their decision to invest in STI. Third, under the assumption that obstacles are related, the intensity of investment in STI determines firms’ innovation outcomes. Lastly, robustness results suggest that human and physical capital and size are the most important factors that affect firms’ productivity.JEL Codes: O31, O3 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Exploring the effects of innovation strategies and size on manufacturing firms’ productivity and environmental impact(MDPI AG, 2021-03-02)In economies that are based on natural resources, efforts to achieve sustainability still seem unclear, especially in manufacturing companies. As a result, from a business perspective, many manufacturers have adopted various strategies to maintain their competitiveness in line with environmental regulations. In addition to product and process innovation, we have analyzed innovation based on product–service innovation (PSI), or servitization, which is seen as key to promoting more resource-efficient economies. This study examines the effects of innovation strategies on productivity and environmental impact. Based on data extracted from the National Innovation Survey of the manufacturing industries of Peru, a sample of 791 companies were analyzed. Our findings indicate that, although only a few companies carry out product and process innovation and especially product–service innovation, when they do, they have a positive effect on both productivity and environmental impact. However, this relationship is affected by the size of the company. Thus, the innovation strategies have a greater positive effect on environmental impact in large companies than companies with fewer than 50 employees. Finally, despite the importance of product–service innovation, it seems that this strategy is not yet established in Peruvian manufacturing companies. Given the positive effect on productivity and environmental impact, we conclude by emphasizing the importance of establishing public policies aimed at disseminating and promoting this type of innovation, with specific support for companies with fewer than 50 employees. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, An introduction to data envelopment analysis(Springer Science+Business Media, 2021-12-11)Following the seminal work of Farrell (1957), Charnes et al. (1978) introduced DEA as a deterministic and nonparametric efficiency evaluation tool. DEA is a linear programming-based technique that has been widely accepted as a competing methodology to evaluate the relative efficiency of entities or decision-making units, DMUs (Charles et al., 2016, 2018; Tsolas et al., 2020). DEA is a data-oriented technique (Zhu, 2020) that is used to construct an empirical production frontier to measure efficiency. Note that the original DEA program of Charnes et al. (1978) is based on the CRS specification of technology and is used to measure the technical and scale efficiency of DMUs. However, Banker et al. (1984) extended this program to the case of VRS to estimate purely technical efficiency. Over the past three decades, DEA has been widely used to evaluate the relative efficiency of production firms, the nature of the returns-to-scale, and the productivity changes. The DEA literature has seen a wide variety of applications across a plethora of domains, having become a powerful management science tool (Charles et al., 2018). In this chapter, we briefly review the fundamental concepts in DEA, along with the basic technologies and programs. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A robust capacity expansion integrating the perspectives of marginal productivity and capacity regret(Elsevier, 2021-04-16)This study addresses a capacity expansion problem (CEP). A typical CEP model usually focuses on addressing demand fluctuation for cost minimization and assumes a constant marginal productivity, which may overestimate the capacity level, thus leading to an infeasible capacity plan. However, the marginal productivity theory has some merits which can complement the CEP; for example, a production function estimates the production possibility set limiting the production behavior and characterizes the law of diminishing marginal returns (DMR). To integrate the perspective of marginal productivity factors in the CEP model, we propose a two-stage model to solve the CEP. The first stage estimates the production possibility set and finds the directional marginal productivity (DMP) towards marginal profit maximization. The second stage, which addresses demand fluctuation, develops the minimax regret model, balancing capacity shortage and capacity surplus to build a robust capacity plan. The results of a numerical illustration validate the robust decision generated by the proposed model and correct a typical CEP model without considering marginal productivity, where the major factor affecting capacity decisions is the ability to raise/leverage resource for marginal productivity rather than demand variation and cost structure. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, The Global Ecosystems Monitoring network: monitoring ecosystem productivity and carbon cycling across the tropics(Elsevier, 2021-01-01)A rich understanding of the productivity, carbon and nutrient cycling of terrestrial ecosystems is essential in the context of understanding, modelling and managing the future response of the biosphere to global change. This need is particularly acute in tropical ecosystems, home to over 60% of global terrestrial productivity, over half of planetary biodiversity, and hotspots of anthropogenic pressure. In recent years there has been a surge of activity in collecting data on the carbon cycle, productivity, and plant functional traits of tropical ecosystems, most intensively through the Global Ecosystems Monitoring network (GEM). The GEM approach provides valuable insights by linking field-based ecosystem ecology with the needs of Earth system science. In this paper, we review and synthesize the context, history and recent scientific output from the GEM network. Key insights have emerged on the spatial and temporal variability of ecosystem productivity and on the role of temperature and drought stress on ecosystem function and resilience. New work across the network is now linking carbon cycling to nutrient cycling and plant functional traits, and subsequently to airborne remote sensing. We discuss some of the novel emerging patterns and practical and methodological challenges of this approach, and examine current and possible future directions, both within this network and as lessons for a more general terrestrial ecosystem observation scheme. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Effects of the use of digital technologies on the performance of firms in a developing country: Are there differences between creative and manufacturing industries?(SciKA, 2022-01-01)This paper aims to analyse the effects of the use of digital technologies on firms’ net sales and productivity. The technology adoption approach is applied in empirical research using data from the National Enterprise Survey in Peru. Using the OLS method on a sample of 2,970 firms from creative and manufacturing industries in Peru, the effects of digital technologies on net sales and productivity are determined. Findings indicate that there is a positive relationship. However, these relationships can be different depending on the type of digital technology, the size of the firm and the manager’s gender proportion. We found that most of these technologies are more commonly related to creative industries than manufacturing firms. These relationships have greater statistical significance to net sales in large companies within both types of industry. However, SMEs have greater statistical significance with respect to productivity in both types of industries. Lastly, given the positive effect on these relationships, we conclude by highlighting the importance of managers crafting their technology portfolio and digital capabilities properly and the need for further research to determine the performance of companies in the context of developing countries. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Index of technical efficiency of Peruvian companies(Universidad de los Andes, Facultad de Economia, 2022-01-01)In a decade of low TFP —factorial total productivity— in Latin America, the paper shows evidence of the low level of TFP due to the degree of technical inefficiency of companies in the Peruvian productive sector case. For this, the technical efficiency indices of 116 875 companies (83 271 formal and 33 604 informal) distributed in 25 regions and ten productive sectors (agriculture, livestock, agriculture, mining, fishing, manufacturing, construction, commerce, hotels and restaurants, and the rest are non-governmental services). The estimates yielded a general average efficiency index for the regions and sectors of Peru of 37.94 —in other words, the total product of the companies would multiply by 2.6 without requiring additional productive factors—. This figure suggests that government or company interventions that induce technically efficient behaviors in production can contribute to increasing the TFP of the economy, probably at lower cost and time.