Showing papers in "Annals of Operations Research in 2015"
TL;DR: A game-theoretical analytical model is proposed and the unique Nash equilibrium is derived and several valuable managerial insights on bargaining power affected by external factors (such as environmental policies, market risks, etc).
Abstract: The paper focuses on the impact of emission ‘cap-and-trade’ mechanism in a so-called emission-dependent supply chain with the emission permit supplier and the emission-dependent firm. In the cap-and-trade system, emission permit becomes one of key factors of production for emission-dependent firms. Two major sources of emission permits are considered—emission cap/quota imposed by the government, and permits purchased via emission trading. If the quota is insufficient to satisfy the target production, extra permits should be purchased via trading. In this case, the traditional non-profit green organizations may be endowed with the role of emission permit suppliers. Thus, the introduction of market mechanism injects new life into environment protection. In the context of newsvendor, the paper investigates the behavior and decision-making of each member in the emission-dependent supply chain. A game-theoretical analytical model is proposed and the unique Nash equilibrium is derived. In their own self-interest, the emission permit supplier and the emission-dependent firm make their optimal decisions on permits pricing and production quantity respectively. Players’ bargaining power in the game is affected by several exogenous factors, such as the governmental environment policy, the market risk, etc. Several valuable managerial insights on bargaining power affected by external factors (such as environmental policies, market risks, etc.) are further concluded.
216 citations
TL;DR: The paper describes how a service level agreement is prepared combining quality of service requirements of user and capabilities of cloud resource provider and demonstrates that the proposed model performs better than the first in first out model and similar trust models.
Abstract: Trust plays an important role in commercial cloud environments. It is one of the biggest challenges of cloud technology. Trust enables users to select the best resources in a heterogeneous cloud infrastructure. We introduce a novel trust model based on past credentials and present capabilities of a cloud resource provider. Trust value is calculated using four parameters such as availability, reliability, turnaround efficiency, and data integrity. A trust management system is proposed implementing this trust model. The paper describes how a service level agreement is prepared combining quality of service requirements of user and capabilities of cloud resource provider. We also demonstrate that our proposed model performs better than the first in first out model and similar trust models.
184 citations
TL;DR: The findings indicate that SSCM models predominantly focus on deterministic approaches and the integration of environmental aspects of sustainability while neglecting stochastic modeling techniques and the consideration of social factors.
Abstract: Nowadays, the integration of sustainability into supply chain management (SCM) is a key issue for ensuring corporate competitiveness in face of dynamic ecological and social environments. This paper reviews 185 journal publications of the last 20 years that formalize issues related to sustainable supply chain management (SSCM) in quantitative models. In a content analysis, modeling and SCM characteristics as well as sustainability and SSCM constructs are elaborated. The models are assessed numerically by counting frequencies of occurrence and by clustering the paper sample according to selected characteristics. The findings indicate that SSCM models predominantly focus on deterministic approaches and the integration of environmental aspects of sustainability while neglecting stochastic modeling techniques and the consideration of social factors. By now, comprehensive modeling approaches are most often employed on intra-organizational levels whereas broader application areas are assessed by less complex models. The integration of pressures and incentives of external stakeholders or the formalization of sustainable supplier management and sustainability risks are identified as future research perspectives. Furthermore, the interrelationships between the triple bottom line dimensions are to be scrutinized in greater detail in order to avoid focused optimization of selected sustainability criteria. Seven modeling guidelines are derived from the reviewed literature to facilitate future model-based SSCM research.
167 citations
TL;DR: A model to extend Mahata’s 2012 model with time varying deterioration where Mahata wrote exponential deterioration but actually he considered constant deterioration is extended.
Abstract: The purpose of this study is two-fold. The first is to consider supplier’s and retailer’s trade-credit policy for fixed lifetime products and the second is to extend Mahata’s 2012 model with time varying deterioration where Mahata (Expert Syst Appl 39(3):3537–3550, 2012) wrote exponential deterioration but actually he considered constant deterioration. We assume that the suppliers offer full trade-credit to retailers but retailers offer partial trade-credit to their customers. Some numerical examples along with graphical representations are given to illustrate the model.
128 citations
TL;DR: An inventory model for perishable foods, in which the demand depends on the price and quality that decays continuously, is formulated to determine a joint dynamic pricing and preservation technology investment strategy while maximizing the total profit from selling a given initial inventory of foods.
Abstract: The food quality has always played an important role in the retail process since it has been considered as a direct factor to influence a consumer’s purchase decision. In this paper, we formulate an inventory model for perishable foods, in which the demand depends on the price and quality that decays continuously. The objective is to determine a joint dynamic pricing and preservation technology investment strategy while maximizing the total profit from selling a given initial inventory of foods. We first prove the existence of an optimal solution based on Filippov–Cesari theorem. Then, we obtain all the candidates and provide the conditions that make a certain candidate be an optimal solution according to Pontryagin’s maximum principle. Next, we present an effective algorithm to search for the optimal strategy. Finally, two numerical examples are employed to illustrate the solution procedure and the results, followed by sensitivity analysis and managerial insights.
122 citations
TL;DR: This paper presents a review of research papers published between 1982 and 2014 concerning MCDM for the design and operation of urban passenger transport systems and highlights the importance of taking into account the multiplicity of actors and their own decision criteria, as well as the resolution technique.
Abstract: Megacities around the world are highly concerned about the impacts of urban transportation. The rapid urbanization and motorization in megacities have a direct impact on sustainable development. Hence, it is very frequently to find the multiple actors from both private and public sectors involved in the design and operation of urban passenger transportation systems to make decisions that seek at optimizing their own particular objectives. However, urban passenger transport system is a very complex task involving multiple criteria related to economic, environmental and socio-political issues. Multi-criteria decision-making (MCDM) techniques actually aid the decision making process by assessing such problems. This paper presents a review of research papers published between 1982 and 2014 (up to May) concerning MCDM for the design and operation of urban passenger transport systems. From the analysis over more than 30 years, the current paper highlights the importance of taking into account the multiplicity of actors and their own decision criteria, as well as the resolution technique. Finally, some suggestions for future research are discussed.
115 citations
TL;DR: In this article, the authors consider the problem of planning preventive maintenance and overhaul for modules that are used in a fleet of assets such as trains or airplanes, and prove that this planning problem is strongly NP-hard, but also provide computational evidence that the mixed integer programming formulation can be solved within reasonable time for real-life instances.
Abstract: We consider the problem of planning preventive maintenance and overhaul for modules that are used in a fleet of assets such as trains or airplanes. Each type of module, or rotable, has its own maintenance program in which a maximum amount of time/usage between overhauls of a module is stipulated. Overhauls are performed in an overhaul workshop with limited capacity. The problem we study is to determine aggregate workforce levels, turn-around stock levels of modules, and overhaul and replacement quantities per period so as to minimize the sum of labor costs, material costs of overhaul, and turn-around stock investments over the entire life-cycle of the maintained asset. We prove that this planning problem is strongly $\mathcal{NP}$
-hard, but we also provide computational evidence that the mixed integer programming formulation can be solved within reasonable time for real-life instances. Furthermore, we show that the linear programming relaxation can be used to aid decision making. We apply the model in a case study and provide computational results for randomly generated instances.
108 citations
TL;DR: The current status of research on the application of OR methods to forestry and a number of research challenges or open questions that will be of interest to both researchers and practitioners are described.
Abstract: Forestry has contributed many problems to the Operations Research (OR) community. At the same time, OR has developed many models and solution methods for use in forestry. In this article, we describe the current status of research on the application of OR methods to forestry and a number of research challenges or open questions that we believe will be of interest to both researchers and practitioners. The areas covered include strategic, tactical and operational planning, fire management, conservation and the use of OR to address environmental concerns. The paper also considers more general methodological areas that are important to forestry including uncertainty, multiple objectives and hierarchical planning.
105 citations
TL;DR: The determination of membership is made to replace the general sense of ‘threshold’ value by using fuzzy theory and the concept of the ‘comprehensive threshold’ of economic development and environmental protection is proposed.
Abstract: Over the years, foreign direct investment (FDI) has not only promoted rapid economic growth in China, but also affected the country’s environmental quality through technology spillover. This paper tests the variables that may affect the ability of green innovation by using the Granger causality test. It extracts the variables passed the test as input variables, selects the number of patents as output variable, and evaluates the efficiency of various provinces in mainland China by examining their yearly technological progress variables. At the same time, technological progress is defined and divided into capital and environmental factors, and then panel data using the variable coefficients model was used to fit influencing factors to obtain impact coefficients of capital and environment. On this basis, this paper makes the determination of membership to replace the general sense of ‘threshold’ value by using fuzzy theory and proposes the concept of the ‘comprehensive threshold’ of economic development and environmental protection. The results show that less than a quarter of China’s provinces have crossed the comprehensive threshold. Finally, based on the conclusions of quantitative analysis, some suggestions are proposed that the Chinese government ought to enact different strategies for the introduction of FDI according to different development situations of different provinces.
104 citations
TL;DR: In this paper, an iterative algorithm is proposed to solve the problem of spare parts stocking in the context of the level of repair analysis (lora), where the lora does not consider the availability of the installed base, leading to suboptimal solutions.
Abstract: For the spare parts stocking problem, generally metric type methods are used in the context of capital goods. Implicitly, a decision is assumed on which components to discard and which to repair upon failure, and where to perform repairs. In the military world, this decision is taken explicitly using the level of repair analysis (lora). Since the lora does not consider the availability of the installed base, solving the lora and spare parts stocking problems sequentially may lead to suboptimal solutions. We propose an iterative algorithm to solve the two problems. We compare its performance with that of the sequential approach and a recently proposed, so-called integrated algorithm. The latter finds optimal solutions for two-echelon, single-indenture problems. In our experiment, we use a set of such problems, and a set of multi-echelon, multi-indenture problems, for which we achieve a cost reduction of 3% on average (35% at maximum) compared with the sequential approach. Compared with the integrated algorithm, the gap is only 0.6% on average (5% at maximum), while the maximum computation time falls from 3 hours to 2.5 minutes. In a case study, we achieve a cost reduction of 10% compared with the sequential approach.
94 citations
TL;DR: A new two-stage data envelopment analysis approach for measuring the slacks-based efficiency of Chinese commercial banks during years 2008-2012, where the banking operation process of each bank is divided into a deposit-generation stage (division) and a Deposit-utilization stage ( division).
Abstract: Bank industry plays a critical role in the economic development of China In this paper, we develop a new two-stage data envelopment analysis approach for measuring the slacks-based efficiency of Chinese commercial banks during years 2008–2012, where the banking operation process of each bank is divided into a deposit-generation stage (division) and a deposit-utilization stage (division) In the approach, the increase of desirable outputs and the decrease of undesirable outputs are simultaneously considered in order to identify the inefficiency of a bank Three efficiency statuses are first defined for such a system to investigate its input-output performance and divisional performances, and a full efficiency status is then defined based on these statuses The empirical results show that the improvement of the banks’ performances during this period was mainly contributed by the improvement of deposit-utilization stage Besides, the results also show that our approach can provide a benchmark for the intermediate measures of the two stages of an inefficient bank
TL;DR: A conceptual model to assess cities’ livability is proposed, that extends the concept of urban livability to include a component related to environmental sustainability and a new composite indicator was constructed based on a data envelopment analysis model specified using a directional distance function.
Abstract: This study develops a tool to assess livability in European cities covering two components of livability: human wellbeing and environmental impact. First, we propose a conceptual model to assess cities’ livability, that extends the concept of urban livability to include a component related to environmental sustainability. Second, we address the measurement of cities’ livability. For this purpose, a new composite indicator was constructed based on a data envelopment analysis model specified using a directional distance function. In addition to assigning a summary measure of performance for each city, the composite indicator can be used to guide improvements concerning different livability objectives. One of the innovative features of the model proposed is to enable, by the specification of different directional vectors, focusing separately on each component of livability (e.g., human wellbeing and environmental impact) or alternatively considering cities’ potential for improvement in all indicators simultaneously. In addition, it is possible to incorporate a new type of weight restrictions, specified as assurance regions type I, that reflect the relative importance of both desirable and undesirable outputs in percentage terms. Finally, this paper approached the assessment of the evolution of cities’ performance over time using the Luenberger productivity indicator.
TL;DR: It is shown that dedicated stocks have significant added value: the approach results in clear savings compared to a strategy of providing all customers with uniform service and the savings found are close to those with critical level policies, with dedicated stocks usually being much easier to implement in practice.
Abstract: We investigate the option of keeping dedicated stocks at customer sites in addition to stock kept at some central location as a tool for applying service differentiation in spare parts supply. We study the resulting two-echelon system in a multi-item setting, both under backordering and under the use of emergency shipments (equivalent to lost sales for the inventory system). In an extensive computational experiment, we show that dedicated stocks have significant added value: the approach results in clear savings compared to a strategy of providing all customers with uniform service. Furthermore, the savings found with dedicated stocks are close to those with critical level policies, with dedicated stocks usually being much easier to implement in practice
TL;DR: An intuitionistic fuzzy economic order quantity (EOQ) inventory model with backlogging is investigated using the score functions for the member and non-membership functions, showing that the score function can maintain the ranking rule also.
Abstract: An intuitionistic fuzzy economic order quantity (EOQ) inventory model with backlogging is investigated using the score functions for the member and non-membership functions. The demand rate is varying with selling price and promotional effort (PE). A crisp model is formulated first. Then, intuitionistic fuzzy set and score function (or net membership function) are applied in the proposed model, considering selling price and PE as fuzzy numbers. To obtain the best inventory policy, ranking index method has been adopted, showing that the score function can maintain the ranking rule also. Moreover, optimization is made under the general fuzzy optimal (GFO) and intuitionistic fuzzy optimal (IFO) policy. Finally, a graphical illustration, numerical examples with sensitivity analysis and conclusion is made to justify the model.
TL;DR: A slacks-based environmental efficiency index based on data envelopment analysis (DEA) is proposed to achieve this goal, and the west region of China has been developing quickly in recently years and performs well both in economy and environmental control.
Abstract: The industry activities produce massive bad by-products, in the form of waste water, waste gas or solid waste, which are the source of environmental issues. The growing concerns over environmental problems make China reconsider the current developing pattern, and partially necessitate the reformation of economic structure. If the environmental consequences from economic structure reformation are subject to empirical testing, it is of vital importance to make some actual measurement for environmental performance. To achieve this goal, this paper proposes a slacks-based environmental efficiency index based on data envelopment analysis (DEA). An empirical application to industry sector of China presents the following findings: (1) approximately two-thirds of the nation’s provinces are inefficient due to excessive resource utilization, insufficient products or considerable quantities of wastes; (2) Spearman test shows that SO2 and solid waste intensity have more impacts on industrial aggregated efficiency than those of electricity and COD intensity do, which implies that waste gas and solid waste should be paid more attention in pollution abatement; (3) the environmental protection activities have yielded the expected benefits, as the aggregated efficiency of regional industry has been on a rising trend during the past decade; (4) the west region of China has been developing quickly in recently years and performs well both in economy and environmental control.
TL;DR: This paper develops an economic ordering policy model for non-instantaneous deteriorating items with selling price- and inflation-induced demand under the effect of inflation, permissible delay in payments and customer returns.
Abstract: This paper develops an economic ordering policy model for non-instantaneous deteriorating items with selling price- and inflation-induced demand under the effect of inflation, permissible delay in payments and customer returns. Shortages are allowed and partially backlogged. The customer returns are assumed to increase with both the quantity sold and the product price. The main objective is to determine the optimal selling price, the optimal length of time in which there is no inventory shortage, and the optimal replenishment cycle simultaneously, to minimize the present value of the total profit. An efficient algorithm is presented to find the optimal solution of the developed model. Finally, a numerical example is extracted to solve the presented inventory model using the proposed algorithm.
TL;DR: A queueing-inventory system, with the item given with probability γ to a customer at his service completion epoch, is considered and numerically an expression for per unit time cost as a function of γ is investigated.
Abstract: A queueing-inventory system, with the item given with probability γ to a customer at his service completion epoch, is considered in this paper. Two control policies, (s,Q) and (s,S) are discussed. In both cases we obtain the joint distribution of the number of customers and the number of items in the inventory as the product of their marginals under the assumption that customers do not join when inventory level is zero. Optimization problems associated with both models are investigated and the optimal pairs (s,S) and (s,Q) and the corresponding expected minimum costs are obtained. Further we investigate numerically an expression for per unit time cost as a function of γ. This function exhibit convexity property. A comparison with Schwarz et al. (Queueing Syst. 54:55–78, 2006) is provided. The case of arbitrarily distributed service time is briefly indicated.
TL;DR: The development of a new method called TIME_GELS that uses the gravitational emulation local search algorithm (GELS) for solving the multi-objective flexible dynamic job-shop scheduling problem and supported the efficiency of the proposed method particularly in improving SME’s productivity.
Abstract: Scheduling problems are naturally dynamic. Increasing flexibility will help solve bottleneck issues, increase production, and improve performance and competitive advantage of Small Medium Enterprises (SMEs). Maximum make span, as well as the average work- flow time and latency time of parts are considered the objectives of scheduling, which are compatible with the philosophy of on-time production and supply chain management goals. In this study, these objectives were selected to optimize the resource utilization, minimize inventory turnover, and improve commitment to customers; simultaneously controlling these objectives improved system performance. In the job-shop scheduling problem considered in this paper, the three objectives were to find the best total weight of the objectives, maximize the number of reserved jobs and improve job-shop performance. To realize these targets, a multi-parametric objective function was introduced with dynamic and flexible parameters. The other key accomplishment is the development of a new method called TIME_GELS that uses the gravitational emulation local search algorithm (GELS) for solving the multi- objective flexible dynamic job-shop scheduling problem. The proposed algorithm used two
TL;DR: An optimization model for patient delivery and medical resource allocation with capacity restrictions and a mixed integer programming model to select the location and network flow of an on-site clinic for supporting first-aid treatment near disaster areas are proposed.
Abstract: We propose an optimization model for patient delivery and medical resource allocation with capacity restrictions. Our model considers the severity of the victims’ injuries in the initial search and rescue period and their survival probabilities, which decrease proportionally with the elapsed time. We develop a mixed integer programming model to select the location and network flow of an on-site clinic for supporting first-aid treatment near disaster areas. We also build a model of a general hospital as an objective function to maximize the number of patients whose survival probability exceeds the marginal level. Our model also considers patients waiting at the on-site clinic and hospital. We apply our optimization approach in a case study with data from a department store collapse in South Korea. Our computational results will facilitate future studies of logistics to support wounded victims of disasters.
TL;DR: The key idea of this approach is to determine the most trustable MCDM method by calculating the weights of several M CDM methods using the Spearman’s ranking correlation coefficients.
Abstract: The vulnerability assessment is important for earthquake prevention and mitigation. Since many criteria need to be considered during the evaluation process, it can be modeled as a multiple criteria decision making (MCDM) problem. This paper proposes an approach which integrates the results of different MCDM methods to provide regional earthquake vulnerability assessment. The key idea of this approach is to determine the most trustable MCDM method by calculating the weights of several MCDM methods using the Spearman’s ranking correlation coefficients. The most trustable MCDM method is the one with the highest weight, which indicates that it has the strongest agreements with other MCDM methods, and is used to provide a final assessment using the combination of other MCDM methods. The proposed approach is applied to evaluate the earthquake vulnerability of 31 Chinese regions using six MCDM methods and eleven vulnerability evaluation indices. The results indicate that the proposed approach can integrate the inconsistent evaluation results of different MCDM methods and produce a comprehensive assessment of regional earthquake vulnerability.
TL;DR: This paper built an empirical model to estimate the sensitivity of each type of online purchasers to three mainstream promotion strategies (discount, advertising and word-of-mouth), and found that economical purchasers are the most sensitive to discount promotion; direct purchaser are themost sensitive to advertising promotion; and active-star purchaser are theMost sensitive to word- of-mouth promotion.
Abstract: Online customer segmentation is a significant research topic of customer relationship management. Previous literatures mainly studied the differences between non-purchasers and purchasers, lacking further segmentation of online purchasers. There is still existing significant heterogeneity within purchaser-groups. This paper focuses on Chinese online purchaser segmentation based on large volume of real transaction data on Taobao.com, we firstly extracted and investigated Chinese online purchaser behavior indicators and classified them into six types by cluster analysis, these six categories are: economical purchasers, active-star purchasers, direct purchasers, high-loyalty purchasers, risk-averse purchasers and credibility-first purchasers; then we built an empirical model to estimate the sensitivity of each type of online purchasers to three mainstream promotion strategies (discount, advertising and word-of-mouth), and found that economical purchasers are the most sensitive to discount promotion; direct purchasers are the most sensitive to advertising promotion; active-star purchasers are the most sensitive to word-of-mouth promotion; finally, the implications of online purchaser classification for marketing strategies were discussed.
TL;DR: A mathematical programming based rolling horizon heuristic is introduced that is able to find near optimal solutions for networks of up to 80 hospitals very fast and is drawn from numerical studies regarding the benefits of pre-positioning medical supplies at the distribution centers.
Abstract: The practice of emergency operations often involves the travelling of medical teams and the distribution of medical supplies In an emergency, such as an earthquake, a medical team often has to visit various hospitals (the customers) one after another in a predetermined sequence in order to perform on-site operations that require certain amounts of medical supplies Because of their perishable nature, the medical supplies are typically shipped in batches from upstream suppliers and kept at multiple distribution centers during the disaster relief process The scheduling of the medical teams and the provisioning of the medical supplies give rise to a scheduling problem that involves the timely dispatching of supplies from distribution centers to hospitals in coordination with the scheduling of medical teams so as to minimize the total tardiness of the completions of the operations to be performed We introduce a mathematical programming based rolling horizon heuristic that is
TL;DR: The expected average cost function is formulated for both continuous and discrete distributions of demand function by trading off holding costs and stock out penalty.
Abstract: This paper deals with an economic order quantity (EOQ) model for uncertain demand when capacity of own warehouse (OW) is limited and the rented warehouse (RW) is considered, if needed. The expected average cost function is formulated for both continuous and discrete distributions of demand function by trading off holding costs and stock out penalty. The model is justified by suitable illustrations for various types of distributions.
TL;DR: The numerical results demonstrate that the novel mode-characteristic-based decomposition ensemble model significantly outperforms all considered benchmarks indicates that it is a very promising tool for forecasting complex and irregular data such as nuclear energy consumption.
Abstract: We propose a novel mode-characteristic-based decomposition ensemble model for nuclear energy consumption forecasting. Our method is based on the principles of “data-characteristic-based modeling” and “decomposition and ensemble”. The model improves on existing decomposition ensemble learning techniques (with “decomposition and ensemble”) by using “data-characteristic-based modeling” to forecast the decomposed modes. Ensemble empirical mode decomposition is first used to decompose the original nuclear energy consumption data into a series of comparatively simple modes, reducing the complexity of the data. Then, the extracted modes are thoroughly analyzed to capture hidden data characteristics. These characteristics are used to determine appropriate forecasting models for each mode. Final forecasts are obtained by combining these predicted components using an effective ensemble tool, such as least squares support vector regression. For illustration and verification purposes, we have implemented the proposed model to forecast nuclear energy consumption in China. Our numerical results demonstrate that the novel method significantly outperforms all considered benchmarks. This indicates that it is a very promising tool for forecasting complex and irregular data such as nuclear energy consumption.
TL;DR: A new way of constructing the global framework of the Malmquist index which applies the minimum extrapolation principle on the aggregation of the experienced contemporaneous technologies is proposed, which preserves the role of each contemporaneous technology in the determination of the newly-proposed best practice technology.
Abstract: This paper deals with a special case of the non-homogeneity problem related to the determination of the global benchmark technology when measuring productivity changes over time. The authors propose a new way of constructing the global framework of the Malmquist index which applies the minimum extrapolation principle on the aggregation of the experienced contemporaneous technologies. The proposed index, called overall Malmquist index, preserves the role of each contemporaneous technology in the determination of the newly-proposed best practice technology, whereby an acceptable level of discrimination between non-homogeneous observations is provided. With respect to both computational and test properties, the proposed index possesses the circularity property, generates a single measure of productivity change and is immune to infeasibility under variable returns to scale. Furthermore, unlike in the global form, previously computed results by the overall Malmquist index are more stable and less sensitive to changes in the shape of the best practice technology when a new time period is incorporated. Similar to traditional indices, it can be decomposed into various components such as efficiency change, scale efficiency change, and best practice change. The suggested index will be illustrated by means of a real-world example from banking. In particular, it will be compared to the contemporaneous and global forms of the Malmquist index introduced into the literature by Fare et al. (J Product Anal 3:85–101, 1992) and Pastor and Lovell (Econ Lett 88:266–271, 2005) , respectively.
TL;DR: This study developed a model for analyzing the criteria and sub-criteria involved in the implementation of GSCM using an Interpretive Structural Modeling (ISM) framework and the proposed model is validated based on a case study involving textile manufacturing industry in southern part of India.
Abstract: Due to the revolution in green manufacturing for the global market, Green Supply Chain Management (GSCM) concepts have become an important issue that can play a pivotal role in a company’s competitive advantage and help strategic decision making. GSCM is a concept, by which companies assess their suppliers to improve the environmental performance of their products or production processes of the suppliers. The tide of globalization has also resulted in pressure on multinational firms to improve environmental performance. Due to the increasing realization of the importance of integrating environmental factors into assessing suppliers’ performance, this study developed a model for analyzing the criteria and sub-criteria involved in the implementation of GSCM using an Interpretive Structural Modeling (ISM) framework. Finally, the proposed model is validated based on a case study involving textile manufacturing industry in southern part of India.
TL;DR: The Malmquist estimation results suggest there is a dropping change trend of energy productivity growth and Tobit regression results find that industrial structure, energy consumption structure and institutional factor have different influences on energy efficiency.
Abstract: China becomes the largest energy consumer in 2010 but its energy productivity is well below the world average. To meet China’s fast growing energy using, energy efficiency should be especially emphasized under China’s energy policy. This paper focuses on the regional level of energy efficiency change in China. And we analyze total factor energy efficiency for 30 Chinese provinces over the period 1998–2009 using Malmquist index method and Tobit analysis. The Malmquist estimation results suggest there is a dropping change trend of energy productivity growth. Chinese energy efficiency still faces with huge regional disparity, but the energy technical efficiency reflects convergence in the nationwide and west region. As a result of Tobit regression, we find that industrial structure, energy consumption structure and institutional factor have different influences on energy efficiency.
TL;DR: A system-of-equations two-stage approach to explain the simultaneous effect of a number of contextual variables on technical efficiency and capacity utilization in Greece shows that hospital size and location have a positive effect on hospital capacity utilization while the average length of stay a negative one.
Abstract: In this paper we develop a system-of-equations two-stage approach to explain the simultaneous effect of a number of contextual variables on technical efficiency and capacity utilization, which were derived using Johansen measure of capacity utilization and DEA. The model is applied to a sample of public hospitals in Greece and provides estimates of capacity utilization and optimal input usage. Our results indicate that the sample hospitals operated with excess capacity and by underutilizing doctors and nursing personnel. We also found some variation in capacity and variable input utilization across urban and non-urban hospitals. The results from the second stage SUR system of equations show that hospital size and location have a positive effect on hospital capacity utilization while the average length of stay a negative one.
TL;DR: This research sheds light on the behavioral and decision making aspects of a donor while developing analytical models of how that behavior can be influenced by soliciting a minimum amount of cash donation, which in turn mitigates the negative impact of unsolicited items.
Abstract: Whether in-kind or cash, coordinated help organizations such as the American Red Cross, count on donations to help those in need when and after disasters happen. Yet, it has been observed that the type (in-kind versus cash) and the quality of donations largely impact the success of meeting urgent demand in humanitarian operations. In particular, unsolicited items hamper the synchronization of logistical operations and hence may create more problems than solutions. This research sheds light on the behavioral and decision making aspects of a donor while developing analytical models of how that behavior can be influenced by soliciting a minimum amount of cash donation, which in turn mitigates the negative impact of unsolicited items. We investigate the literature on donor psychology and feed those extant findings to the analytical model. We provide explicit expressions for the optimal solicitation amount and the impact of that amount on maximizing the donor’s likelihood to donate cash, as opposed to in-kind items. Also provided are some execution insights through extensive sensitivity analysis.
TL;DR: This work proposes a nonlinear programming model that reduces inconsistency to zero or near zero, without needing to redo all judgments, and shows that the proposed model performed better, since the original judgments were changed in a minimum way.
Abstract: Analytic Hierarchy Process is one of the most known multicriteria decision aid methods. Nevertheless, as it relies on decision makers (DM) pairwise comparisons, a problem may occur if some comparisons are not well done. This issue, known as inconsistency, appears when an inconsistency threshold is violated. One way to deal with inconsistency is to redo all judgments, as many times as needed, in order to reach acceptable levels. This work proposes a nonlinear programming model that reduces inconsistency to zero or near zero, without needing to redo all judgments. The reduction is achieved by adjusting the original judgments in a minimum way, keeping the DM’s decisions within a tolerable range. Only discrete values are generated, so the solution respects the limits of the Saaty scale (1–9). To illustrate the efficiency of the nonlinear model, a comparison between the proposed model and other models taken from recent literature was made. The results show that the proposed model performed better, since the original judgments were changed in a minimum way, also the inconsistency was completely removed. Alternatively, if some inconsistency is allowed more original judgments can be preserved.