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La crisis de legitimidad que afecta a Chile provoca que todas las instituciones, tanto públicas como privadas, se replanteen su rol en la sociedad. En este artículo se analiza a los participantes del Seguro Social contra Riesgos de Accidentes del Trabajo y Enfermedades Profesionales, centrándose en los procesos de interrelación entre los organismos administradores del seguro laboral y los participantes de la salud común. Si bien existe un problema de legitimidad del sistema debido al rol de ‘juez y parte’ de los organismos administradores del seguro laboral, en este artículo se profundizan otros inconvenientes relacionados con las posibles ineficiencias existentes en la relación entre los participantes, los cuales pueden acentuar el malestar social hacia el seguro. Los problemas se relacionan con la eficiencia de los prestadores de salud, la burocracia excesiva, el proceso de rendición de cuenta de las instituciones, la incidencia indirecta en la salud de los pacientes y los sesgos en la elección del sistema de salud de primera atención. Como solución se propone retomar una política pública olvidada: la creación de una Comisión Calificadora Autónoma que externalice la determinación de la calificación de la enfermedad del trabajador. Para solucionar las ineficiencias descritas con anterioridad, se proponen otras funciones de esta institución que permitan, entre otras tareas, una interacción expedita entre los sistemas de salud y la continuidad de tratamiento a través de los organismos administradores del seguro laboral, lo cual no se permite en la actualidad.

Background: The COVID-19 pandemic hit Chile in March 2020, in the midst of the worst political and social crisis it had suffered in the last 40 years. The causes of the crisis, related to weak social cohesion, were in part the cause of Chile's poor performance in terms of deaths from the pandemic. Unlike the rest of the country, in the case of Chilean nursing homes, three levels of cohesion were achieved: the state, businesses and civil society. We explained in detail how each of these groups provided strategic capabilities that achieved a much higher than expected performance.Methods: Based on information from 18 developed countries and 60 regions (states of the USA, countries of the UK and regions of Spain), we postulated a number of statistical models, quadratic and exponential, to explain deaths in nursing homes as a function of deaths in their geographical area.Results: Knowing that by September 2020, 1,258 elderly people had died, with 95% confidence we deduce that slightly more than 400 were saved. Compared to the 78 countries and regions considered, this makes Chile's nursing homes the fourth best performers.Conclusions: This study demonstrates the importance of social cohesion in facing major challenges such as the battle against COVID-19 in Chile's care homes.

While the impact of formal incentives on individuals is well understood, their impact on teams is less clear. A handful of field experiments document a small or null impact of incentives on teams. However, these studies do not contrast their results with the impact of incentives on individuals, and thus, cannot rule out the possibility that the null/small results on teams are due to incentives being ineffective on individuals to begin with (for example, due to organizational culture). In this paper we perform a full comparison: we estimate the impact of incentives both on individuals and on teams, within the same setting. Concurring with the extant literature, we observe that incentives on individuals generate approximately a 20% productivity increase, but that such a gain disappears in teams. Exploiting the details of our setting, and guided by a formal model, we show that this is not because incentives do not work in teams, but because teams in our setting do not need them. This is because: i) effort complementarities strongly counteract free-riding in teams (so incentives do work), and ii) teams without incentives display larger social incentives than teams with them (and this asymmetry is large enough so that teams without incentives catch-up with those with incentives). We conclude that, under plausible conditions, having only an estimate of the impact of incentives on teams, without having an estimate for individuals, one cannot say much about the presence and magnitude of the generic mechanisms of free-riding, effort complementarity and social incentives.

Greater vertical pay disparity is associated with compensation schemes that reward relative performance. Considering tournament theory as a leading framework for those schemes, along with boosting productivity, they are likely to increase workers’ willingness to exert effort at the risk of injuries or occupational sickness. We find evidence of such pervasive effect on a novel database that includes more than 110,000 Chileans firms. For workers in the bottom half of the wage distribution, an increment of one standard deviation in within-firm vertical pay disparity is associated with an increase of around 10% in the number of injuries and almost 19% in the number of days lost. These results are negatively moderated by the proportion of female employees and state ownership.

Heinrich’s pyramid, which postulates that the severity distribution of occupational accidents is relatively constant, is one of the main tools for management of occupational safety. However, existing evidence suggests that decreases in minor accidents have not always been followed by similar decreases in serious and fatal accidents. To test the statistical validity of the pyramid, we propose a Bayesian two-part model: the first part estimates accident rates using a Poisson-gamma distribution, and the second part estimates the proportion of minor, serious and fatal accidents using a Multinomial-Dirichlet distribution. If this proportion does not change when the accident rate is reduced, then the statistical validity of the pyramid is confirmed, but if it changes, then its validity is refuted. Our data cover more than 50,000 companies observed over 28 months in Chile. Heinrich’s pyramid is confirmed to be statistically invalid for different economic activity sectors and geographic regions, but the discrepancy is so small that, for practical purposes, the pyramid is valid. We thus conclude that the occurrence of minor accidents is a useful signal for assessing and forecasting the overall safety performance of a firm.

Based on a detailed database of a beverages producer‐distributor that expanded its product variety by leveraging its logistic network, we show that product diversification generates economies of scope and also higher operational costs. The result is an inverted‐U relationship between variety and productivity: When the firm offers few additional categories, productivity grows, but as the number of categories rises, the costs of executing the operational routines increase rapidly and productivity falls. The negative effect on productivity increases if the added product category is more dissimilar to previous ones, and decreases with learning from operational experience. Our results highlight how frictions at the operational level can limit the benefits of diversification, even in the absence of other sources of diseconomies, such as increased coordination needs.

To reach a certain production level, firms sometimes allow overtime and/or adjust the number of their personnel. Under some circumstances, workers can decide to work overtime to gain additional compensation, even though the firm might not need that time. This type of overtime exists because of an information asymmetry that favors workers: they know better than management the everyday routines, the temporary bottlenecks, and the malfunctions in the workplace. This study models this situation as an infinitely repeated game. In each stage-game the workers decide whether to work overtime, and the firm decides whether to adjust the amount of personnel. The game characterizes the conditions of the Nash equilibriums, some of which might lead to collaborative communication between the workers and the firm. The study empirically tests two propositions with data from a Chilean smelting plant. The results identify under which circumstances the firm should “listen” to the workers (i.e., take into account how much overtime they incur) when making personnel decisions.

Scientific literature reports scarce evidence of whether Internetbased procurement systems improve the efficiency of State purchases. We propose a methodology to estimate savings in: (i) the centralization of administrative tasks, and (ii) price differentials due to a larger number of contractors and suppliers bidding on contracts. We test our methods with ChileCompra, the Chilean e-procurement agency. During 2007, 885 Chilean State agencies used this system to purchase US$4.5 billion in products and services. Our preliminary results show price reductions of 2.65% and administrative cost savings of 0.28%-0.38% between 2006 and 2007.

The hockey-stick pattern faced by suppliers consists of sales spikes at the end of each period. One of its causes is the information asymmetry that favors the retailer, who has better knowledge about the stochastic consumer demand. Because of delayed purchases, the supplier is induced to offer promotions, allowing the retailer to forward-buy at low prices. We model this situation as an infinitely repeated game, where each stage-game is subject to imperfect information. Drawing from the Nash equilibrium, we express sales and inventories in terms of demand, cost and the strategies players may adopt, and derive the conditions for a cooperative equilibrium.

Whenever a company implements a group-based incentive plan for the first time, free-riding may destroy trust among employees and harm performance. We propose a static model to describe how employees make the decision of whether to cooperate or not, which considers material rewards and social preferences. Given the deep uncertainty involved, we conjecture that workers apply the Arrow–Hurwicz criterion, which considers a combination of the best- and the worst-case scenarios. We derive a set of hypothesis from this model that we validate using a dataset of 107 effectively implemented incentive plans.

We describe an ambulance service in terms of its main operation parameters and strategic decision variables. Assisted by queuing theory, we calculate the key performance indicators (KPI) that concern the manager and the KPI that concern the patient. We use them to improve the operation of a private ambulance service in Chile. First, we evaluate whether the historical performance is consistent with the resources deployed. Then, we estimate the impact of some operational enhancements, such as reducing the cycle time or enlarging the fleet. Finally, we optimize the geographical coverage of the bases. We conclude that simple mathematical expressions are very useful to evaluate and improve the operation.

Companies in the natural resources industry (e.g., mining, timber, farming and fishery) face the dilemma of whether to focus upstream or downstream in the value chain. The literature provides arguments and empirical evidence for either position. This paper presents an analytical framework based on the neoclassical theory of the firm, for which the best competitive advantage is the one that maximizes production efficiency. It serves to formulate an optimization model for the sawmill industry, and draws the data from the largest sawmilling company in the southern hemisphere. Although one conclusion is that the company should concentrate on the upstream activities, such conclusion is not applicable to other firms, since the analysis of the upstream–downstream dilemma must focus on the individual capabilities of each firm.

We present an optimization model for steel manufacturing, whose objective function depends on activity-based costing (ABC). The constraints describe the capacity and the material balance, the product-dependent yield and the electrical balance, for all the activities of the plant. For the model to be reliable, one should validate that it accurately expresses the objective function of the user, and that it defines with precision the constraints that determine the feasible solutions. We validate the cost estimation by empirically testing how accurately it can predict future expenditures. We validate the constraints by comparing the polyhedron they generate with the production possibility set obtained with data envelopment analysis (DEA). We show the model implemented and validated in a Chilean steel manufacturer. The tests prove the model reliable enough for defining the product mix, and for evaluating investments and sourcing alternatives.

Queuing theory studies the behavior of systems subject to different working conditions, which sometimes force clients to wait for service. It has a vast applicability, since it quantifies the dilemma of many companies and institutions between efficacy (provide a good service) and efficiency (reduce the cost). However, the models do not always have a direct interpretation, reducing their helpfulness. In order to link queuing theory with management, we first explain the relevance of waiting time to the quality of service. Then we identify a number of key performance indicators, related to efficacy, efficiency and the design of the system. For different configurations, we present models that relate these indicators and show examples and applications in factories, service, logistics and health organizations.

PurposeThe existing business paradigm in the sawmill industry is that improvements are achieved by enhancements at each individual sawmilling plant. The authors investigate a collaborative approach, and propose a model for optimizing production and inventory planning decisions within a system of plants.Design/methodology/approachThe methodology models the sawmill production process in terms of two transformation stages and two inventory stages. The authors then extend the model to account for supply chain decisions consisting of timber transfers among plants. They apply the model at 11 Chilean sawmills to evaluate whether they can benefit from operating in a more integrated manner.FindingsThe authors find an opportunity to increase profits by more than 15 percent through a higher utilization of the capacity and a better assignment of production orders.Research limitations/implicationsThe study neglects the possibility of exchanging raw material among plants. Also, the findings are derived from a computational simulation, so are estimates, not actual observations.Practical implicationsThe study challenged the business paradigm of the company the authors performed the study for. Now, it is implementing the suggested improvements.Originality/valueAn investigation into how a number of sawmilling companies working together can profit from their distinctive competitive advantages, and which proved successful in challenging one company's business paradigms.

We develop an agency model subject to moral hazard to evaluate whether delivery prices reward carriers for their performance, or arbitrarily benefit some carriers and harm others. From the model, we derive several propositions that we test on a panel data of 58 carriers that work for a shipper in Santiago, over 93 weeks. We verify that the shipper rewards the experience, fleet size and service quality provided by the carrier, but not the quality of the trucks. The carrier has incentives to visit many clients, but not to travel longer distances. We also confirm that prices are sensitive to the alternatives to the agreement between the shipper and the carrier. However, a number of carriers are over or under compensated for no apparent reason.

Las prestaciones preventivas son fundamentales para prevenir accidentes laborales. Sin embargo, hasta ahora la Mutual (ACHS) en que se realiza el estudio no contaba con una metodología sistemática para su evaluación. Este trabajo presenta una metodología desarrollada por la organización (mutual) para evaluar las intervenciones preventivas, la cual está basada en Brodersen, K. H., Gallusser, F., Koehler, J., Remy, N., & Scott, S. L.1 Para cada empresa-sucursal se estiman los accidentes que habrían ocurrido de no haberse realizado intervenciones preventivas. Esta serie se compara con la serie real, y se calcula si son diferentes al 95 por ciento de confianza. De ser efectiva, se utiliza en un modelo de regresión lineal que estima el efecto marginal por tipo de intervención. Los supuestos de Brodersen et al.¹ se cumplen en la Mutual, justificando su utilización. Los resultados señalan que la "Capacitación sin propuesta Push", "Plan de acción del modelo preventivo" y "Primeros auxilios psicológicos" tienen efectos significativos en la reducción de accidentes. La "Capacitación con propuesta Push" y "Fuerza de tarea" no muestran efectos significativos. Estos resultados varían según el sector económico. Nuestra recomendación es adoptar esta metodología. También sugerimos implementar metodologías complementarias, para validar su idoneidad.

We show how a linear programming model can assist strategic decision-making, understanding it either within the neoclassical theory of the firm, the industrial organization theory, the resource-based view, or other approaches of strategic management. The model relays on Activity Based Costing (ABC) for calculating unit product cost, and on dynamic Activity Based Management (ABM) for assessing the feasibility of prospective production plans. It was implemented 4 years ago in a Chilean integrated steel manufacturer, and it is currently being used to optimize its business plan.

This paper studies a dynamic production system where multiple products must visit stations where inventories are constrained by maximum and minimum sojourn times with neither negative flow nor backlog being allowed. A resource availability constraint limits the aggregate throughput of the stations. The objective is to minimize the sum of flow and inventory cost. The problem is broken down into several single-product serial systems that serve as subroutines of a Lagrangian relaxation routine. This model is implemented in a spreadsheet so that it can be used by the officials of a Chilean institution for planning the operations and defining the optimal allocation of resources.

One of the main causes of the unemployment in low-qualification socioeconomic sectors is the problem of asymmetry of information: firms ignore the true predisposition of the candidates to commit with the job, and facing such uncertainty, they deter from contracting personnel. Using an optimization model, based on the revelation principle for games of incomplete information, we deduce that the public system should offer to those candidates willing to commit salaries too high in order to distinguish them from other candidates. That is why the public system only offers low-commitment transitory jobs, leaving out of the intermediation system the unemployed people with the highest potential. As an alternative, we propose to implement a mixed public-private system, in which the public agencies would specialize on transitory jobs, and the private agencies on higher commitment jobs. In such a case, the salaries for the latter jobs would be realistic, so people with a high potential would participate in the intermediation system.

Empowerment (giving others, within operative levels, a certain degree of decision-making power) is one of the requirements to execute quality management programs. The autonomy afforded by empowering others could be detrimental to systems where complexity and variability is high, as local decisions may have undesired consequences in the system as a whole. To resolve the conflict between empowerment and strategic issues, we propose a method based on the Open Systems Theory: sections of a certain firm are seen as a system that must reach imposed objectives. The head of each section has the freedom to decide how to reach the given objective, by defining and delegating goals for the subsystems. This technique was implemented in a chemical plant as a pilot. From this analysis we derived a set of proposals to improve monitoring and management capacity. The results of the first eight months after the implementation are promising.

Ambulances services, taxis, pizza delivery and vehicle tows have in common a sub-process of gathering the requests, usually by call-centers, and a sub-process of execution, consisting on dispatching a vehicle to the site. In this article we model those services in an integrated way, identifying key performance indicators for the manager and the client, and the tradeoffs among those indices. We analyze the performance of Unidad Coronaria Móvil, the firm that pioneered the private ambulance services in Chile. We evaluate the main opportunities for improvement, including the reduction of lead-times, fleet enlargements and the optimization of the bases coverage.

The purpose of this article is to analyze the main operational causes of conflict between shippers and carriers, and to evaluate the opportunity of improvement. We classify these problems according to whether they are related to the operations at the distribution centers, the configuration of routes, the contract clauses and the size of the fleet. Based on a transportation cost model, we present expressions for estimating the potential savings upon resolving those problems. We simulate several improvements for four different types of companies: a grocery delivery service that operates throughout the city of Santiago, a soft-drink deliverer that uses electric vans for the downtown area, a tanker service that operates between two distant facilities, and a hauling operation with very large trucks in an open-pit mine. We derive a number of managerial guidelines that could be more effective than any other capital-intensive approach method.

This paper studies a single-product distribution channel where a supplier manufactures items of a given type, some of which are defective, that are sold by a retailer who only detects a subset of the defective items, passing the rest along to customers. We conjecture the structure of the demand and cost functions, assuming customers to have a decreasing marginal aversion to bad quality while both the supplier and the retailer make marginally increasing efforts to avoid bad quality. This allows us to deduce several implicit parameters of a cost model based on observable data, such as the share of the channel margin. Once the parameters of the model are available, we analyze the result of vertical integration. Although we confirm the well-known fact that vertical integration improves the quality perceived by the customer, we characterize the supplier's decision of whether or not to provide a better quality in terms of the individual channel margins. As an alternative, we derive the conditions under which the supplier and the retailer may devise a mutually beneficial transfer contract that simultaneously increases their profit and improves quality.

We study the problem of configuring a fleet, in which vehicles receive information on-line about the demand that they should fulfil while they are on the road. In each district it must be decided the number of vehicles and their capacity. The objective function is to minimise the operational cost subject to constraints for the minimum delivery capacity, the maximum vehicle size and the average waiting time for customers. The last constraint is modelled as a queuing system that is adjusted according to the simulation of the delivery process of a Chilean company that distributes liquefied petroleum gas in portable cylinders. We provide the analytical form of all the components of the model, so it can be solved using a standard non-linear programming package. We show that the fleet may increase its sales by 3% and reduce the waiting time of customers 10% by allowing a set of vehicles to share the buffer of orders rather than having vehicles to exclusively serve smaller sectors.

The Chilean General Treasury is the governmental institution that, among other functions, is in charge of collecting debts from taxes, credits, and fees. Until now the central office in Santiago has performed the planning, which has caused inefficiencies due to the lack of knowledge of the local realities of 35 offices across the country. In order to allow for more independence, and yet not lose control, we develop a system in a spreadsheet that allows each office to perform its own planning. The system consists of a multi-period linear program that considers a combination of parameters that depend on each region. The primal optimal variables provide the production goals for each period that allow an objective performance appraisal, while the dual variables allow comparing the marginal benefit of allocating additional resources to the different offices.

While auctions gain relevance as a trading mechanism, different events show how unskilled many firms and governments are when using them. The objective of this article is to familiarize the reader with the auction theory, either to improve the auction design, if he is the auctioneer, or to orient the bidding strategy, if he is the bidder. First, we present the simplest auctions, using intuitive mathematical tools. Then, we consider more realistic setups, such as the existence of risk aversion, and the use of reservation prices. We also study the case where the goods auctioned can be later traded on the market, and those auctions where bidders can benefit from economies of complementarities if they are granted with specific bundles of goods. In both cases, the auctioneer must recognize the risks and opportunities, in order to maximize the economic value of the allocation of goods.

A rolling horizon heuristic is presented for large job shops, in which the total weighted tardiness must be minimized. The method divides a given instance into a number of subproblems, each having to correspond to a time window of the overall schedule, which are solved using a shifting bottleneck heuristic. A number of rules for defining each time window are derived. The method is tested by using instances up to 10 machines and 100 operations per machine, outperforming a shifting bottleneck heuristic that has been shown to generate close to optimal results. Scope and purpose There has been a significant amount of research focused on the scheduling of a job shop, either minimizing the makespan or the tardiness. Although the results for small-size problems are satisfactory, there has been no approach as for yet middle- and large-size problems. This paper presents a heuristic that decomposes the problems on a time window basis, solving each subproblem using a shifting bottleneck heuristic. Its results for a due-date-related objective function are promising.

INTRODUCTION: The recent events in Chile involving 33 miners who were trapped and rescued in the San Jose mine led the government to strongly promote occupational safety and health (OSH) training. However, there is an ongoing debate regarding which type of training is the most effective in reducing accidents. METHOD: The "engagement hypothesis" claims that traditional classrooms are rather ineffective and that only a strong student involvement may generate meaningful results, but the empirical evidence is inconclusive. To contribute to this debate, we claim that the selection of the training method may be contingent on the firm's OSH capabilities and commitment. Firms with fewer (greater) capabilities may optimally self-select less (more) engaging training methods. RESULTS: Accordingly, based on panel data from 2003 to 2009 for a representative sample of 2,787 Chilean firms, the engagement hypothesis initially appears to be supported; however, after correcting for self-selection bias, it loses most of its significance. IMPACT ON INDUSTRY: Chilean policymakers are strongly advised to expand OSH training. Language: en

This work studies the problem of scheduling a production plant subject to uncertain processing times that may arise, e.g. from the variability of human labour or the possibility of machine breakdowns. The problem is modelled as a job shop with random processing times, where the expected total weighted tardiness must be minimized. A heuristic is proposed that amplifies the expected processing times by a selected factor, which are used as input for a deterministic scheduling algorithm. The quality of a particular solution is measured using a risk averse penalty function combining the expected deviation and the worst case deviation from the optimal schedule. Computational tests show that the technique improves the performance of the deterministic algorithm by 25% when compared with using the unscaled expected processing times as inputs.

This work analyses the problem of defining when to diploid a new distribution center. The decision model considers the usual logistic cost drivers such as shipping, inventory, infrastructure and administration, focusing in the first one. The shipping cost driver is determined by the client coverage of the centers, which is calculated using a first order condition heuristic that takes into account the facilies' internal congestion. The model is applied to a company that operating in Santiago de Chile which faces a highly seasonal demand. We show that by defining the coverage in a dynamic fashion that depends on the demand, it is possible to postpone the deployment of a new center so the company can save an estimate of 2 percent of the delivery cost.

A decision support system (DSS) is discussed here. It was developed to analyze the interpersonal behavior of members of a work team; they are tested while interacting in a set of situations simulating a daily working session. By comparing the reactions of each member, it is possible to assess the members' working style compatibility. The system can, therefore, be configured to test specific features of interpersonal behavior, such as potential conflict factors; these can then be used to assess the effect of adding a member to a team during personnel selection. Field tests have showed that the system can satisfactorily predict potential conflicts within a group.

We present a shifting bottleneck heuristic for minimizing the total weighted tardi- ness in a job shop. The method decomposes the job shop into a number of single-machine subproblems that are solved one after another. Each machine is scheduled according to the solution of its corresponding subproblem. The order in which the single machine subproblems are solved has a significant impact on the quality of the overall solution and on the time required to obtain this solution. We therefore test a number of different orders for solving the subprob- lems. Computational results on 66 instances with ten jobs and ten machines show that our heuristic yields solutions that are close to optimal, and it clearly outperforms a well-known dispatching rule enhanced with backtracking mechanisms. © 1999 John Wiley & Sons, Inc. Naval

In the search for better optimisation techniques, new methods that mix artificial intelligence and operations research have emerged. Search heuristics are integrated with optimisation algorithms. Approximation methods, like Hill Climbing, Simulated Annealing, and Tabu Search, that have been used with success in combinatorial optimisation problems, are one of such research lines. This paper presents the key elements of approximation methods and combines them in a tool appropriate for solving sequencing and resource allocation problems. The system permits a clear division between problem specification and problem solving, allowing a declarative representation and therefore minimising developing costs. The key issues discussed in this work are a model for representing this class of problems in a standard form, a set of strategies for applying the approximation methodology, and an expert system that dynamically manipulates the strategies' parameters.