Evaluating sustainability of supply chains by two-stage range directional measure in the presence of negative data

Assessing sustainability of supply chains is a critical and increasingly complex problem. In recent years sustainability has received more attention in supply chain management (SCM) literature with triple bottom lines including social, environmental, and economic factors. Conventional data envelopment analysis (DEA) models consider decision making units (DMUs) as black boxes that consume a set of inputs to produce a set of outputs and do not take into consideration internal interactions of DMUs. Two-stage DEA models deal with such DMUs. However, existing two-stage DEA models are applicable only in technologies characterized by positive inputs/outputs. This paper aims to build and present a new two-stage DEA model considering negative input-intermediate-output data. Some numerical examples along with some theorems and properties are given to show capability of proposed method. The proposed ideas are used in a case study where 29 Iranian supply chains producing equipment of expendable medical devices are evaluated in terms of sustainability.     

A carbon footprint-based closed-loop supply chain model under uncertainty with risk analysis: A case study

The management of products’ end-of-life and the recovery of used products has gained significant importance in recent years. In this paper, we address the carbon footprint-based problem that arises in a closed-loop supply chain where returned products are collected from customers. These returned products can either be disposed of or be remanufactured to be resold as new ones. Given this environment, an optimization model for a closed-loop supply chain (CLSC) in which carbon emission is expressed in terms of environmental constraints, i.e., carbon emission constraints, is developed. These constraints aim to limit the carbon emission per unit of product supplied with different transportation modes. Here, we design a closed-loop network where capacity limits, single-item management and uncertainty on product demands and returns are considered. First, fuzzy mathematical programming is introduced for uncertain modeling. Then, the statistical approach to the possibility to synthesize fuzzy information is utilized. Therefore, using a defined possibilistic mean and variance, we transform the proposed fuzzy mathematical model into a crisp form to facilitate efficient computation and analysis. Finally, the risk caused by violating the estimated resource constraints is analyzed so that decision makers (DMs) can trade off between the expected cost savings and the expected risk. We utilize data from a company located in Iran.     

Reducing CO2 emissions in temperature-controlled road transportation using the LDVRP model

Temperature-controlled transport is needed to maintain the quality of products such as fresh and frozen foods and pharmaceuticals. Road transportation is responsible for a considerable part of global emissions. Temperature-controlled transportation exhausts even more emissions than ambient temperature transport because of the extra fuel requirements for cooling and because of leakage of refrigerant. The transportation sector is under pressure to improve both its environmental and economic performance. To explore opportunities to reach this goal, the Load-Dependent Vehicle Routing Problem (LDVRP) model has been developed to optimize routing decisions taking into account fuel consumption and emissions related to the load of the vehicle. However, this model does not take refrigeration related emissions into account. We therefore propose an extension of the LDVRP model to optimize routing decisions and to account for refrigeration emissions in temperature-controlled transportation systems. This extended LDVRP model is applied in a case study in the Dutch frozen food industry. We show that taking the emissions caused by refrigeration in road transportation can result in different optimal routes and speeds compared with the LDVRP model and the standard Vehicle Routing Problem model. Moreover, taking the emissions caused by refrigeration into account improves the estimation of emissions related to temperature-controlled transportation. This model can help to reduce emissions of temperature-controlled road transportation.     

递进式连锁经营管理专业实践教学改革研究——基于加盟创业项目视角

连锁经营管理专业人才培养目标大多定位在一线服务员或基层管理者，所培养的学生必须具备较强的连锁专业能力和创业能力，而大多数高职院校培养出来的学生在这些方面所表现出来的能力却差强人意，尤其是创业能力方面。本文提出将加盟创业项目贯穿于连锁经营管理实践教学全过程，按照“仿真训练-校内孵化-校内模拟-市场全真”四个阶段，形成一个递进式的实践教学流程，从而促使学生的专业能力和创业能力实现递进式提升。     

Situation analysis forecasting: the case of European maritime clusters

Within the literature concerned with aspects of competitiveness, innovation and strategic management of industrial clusters, the body regarding forecasting of strategic management is still nascent. This work aspires to render a contribution within the domain of strategic management forecasting, through the indicative case of European maritime clusters. For this end, a two-tier model is formulated. A quantitative strengths, weaknesses, opportunities, and threats (SWOT) methodology that derives from the fusion of a quondam situation analysis and crosstabs’ theory is generated. This leads to the utilization of the crosstab’s conditional probabilities as transition probabilities; the latter are called to compile the transition matrix of a Markov chain. Through this methodology, and the successive Markov chain’s transition matrices, strategic forecasts are extracted for a devised European maritime cluster case. This work relinquishes a novel application with respect to strategic management forecasting, that provides a dichotomy of practical interpretations and scenarios for quantitative situation analysis. Thus, it may enable effective real-time decision-making for strategic management and/or policy drafting. The situation analysis forecasting model may find applicability in a plethora of practical and theoretical cases, wherein forecasting may be desirable. It may as well pertain to an intrinsic methodology for situation analysis forecasting of maritime clusters.     

二灰冷再生沥青路面基层路用性能研究

通过对原路材料进行材料组成分析,并且通过对几种不同配合比的冷再生材料的无侧限抗压强度、劈裂强度、冲刷性能的初步研究,对二灰冷再生材料的性能做出了初步评价.二灰冷再生材料基本可以满足规范对沥青路面的半刚性基层的要求.     

As2O3诱导人卵巢癌细胞株HO8910凋亡和端粒酶活性的关系

目的探讨As2O3诱导HO8910细胞凋亡和端粒酶活性变化的关系。方法用不同浓度的As2O3溶液作用卵巢癌细胞株HO8910,于不同时间点收集细胞,MTT法检测细胞生长抑制率;FCM检测细胞凋亡率;TRAP-银染法观察端粒酶活性的变化。结果As2O3溶液对HO8910有生长抑制和诱导凋亡的作用,与药物浓度和作用时间相关。不同浓度As2O3作用HO8910细胞,其端粒酶活性在24h无明显改变,随着作用时间的延长,端粒酶活性逐渐下降,随着药物浓度的升高端粒酶活性也呈不断下降趋势,以致消失。结论As2O3可以诱导卵巢癌细胞株HO8910发生凋亡,其机制可能不是通过端粒酶活性下降直接调控的,但端粒酶调控与凋亡调控有一定相关性。     

Critical success factors of supply chain integration in container shipping: an application of resource-based view theory

ABSTRACT

The container shipping industry is receiving growing attention in driving the performance of global supply chains. This phenomenon has accelerated supply chain integration (SCI) within the industry. Although SCI could offer numerous benefits, it is often quoted to be implemented easier in theory than in practice. The high failure rate that is associated with SCI is often not addressed in the literature. Grounded on resource-based view (RBV) theory, this paper is aimed at identifying the critical success factors (CSFs) and examining their influence on SCI and supply chain performance (SCP). Survey questionnaires were administered on 164 container shipping firms. The constructs were validated empirically using confirmatory factor analysis and were subsequently analysed using structural equation modelling. The proposed CSFs in this study are found to be positively corelated with SCI, which, in turn, is positively correlated with SCP. This paper has contributed to both theory and practice by applying RBV theory to identify the key resources and capabilities that are necessary for SCI in the container shipping industry.     

Understanding members' carsharing (activity) persistency by using econometric model

Carsharing is an innovative travel alternative that has recently experienced considerable growth and become part of sustainable transportation initiatives. Although carsharing is becoming increasingly a popular alternative transportation mode in North America, it is still an under‐researched area. Current research is aimed at better understanding of the behavior of carsharing users. For every member, a two‐stage approach microsimulates the probability of being active in any month using a binary probit model and given that a particular member is active during a month, the probability of that member using the service multiple times using a random utility‐based model. The model is estimated using empirical data from one of the largest carsharing companies in North America. The model estimates reveal that the activity persistency of members is positively linked to previous behaviors for up to 4 months, and that the influence of previous months weakens over time. It also shows that some attributes of the traveler (gender, age, and language spoken at home) impact his or her behaviors. Copyright © 2010 John Wiley & Sons, Ltd.     

汽车行业供应链中成员协作信任与冲突研究

我国汽车行业正处于创建自主品牌,从传统的供应链向电子化、信息化、同步化转型 过程中,信任与冲突是汽车供应链协同整合的关键因素.针对汽车行业供应链特性及发展趋 势,构建了基于契约信任、知识信任、信誉信任的跨组织信任协调机制,并构建了汽车行业 供应链成员协作信任机制与关系、流程、任务3种冲突的关系模型,研究了不同协作类型供 应链的信任与冲突,指出信息与知识共享是我国汽车行业供应链转型建立信任、解决冲突的 必要措施.