Supplier selection for sustainable operations: A triple-bottom-line approach using a Bayesian framework
Supplier selection for sustainable operations: A triple-bottom-line approach using a Bayesian framework
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DOI：
10.1016/j.ijpe.2014.11.007
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发表时间：
2015-08
影响因子：
12
通讯作者：
Joseph Sarkis;D. Dhavale
中科院分区：
文献类型：
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作者：
Joseph Sarkis;D. Dhavale
在评估和选择可持续发展的供应商时，我们采用三重底线（利润、人员和地球）的方法，并考虑供应商的业务运营、环境影响和社会责任。引入了不同的度量来度量这三个领域的性能。为了检查不同组织和供应链运营理念的影响，选择供应商的目标被设计成其中一些有利于利润或业务运营，另一些有利于地球或环境，其余的侧重于人或社会责任。一种基于贝叶斯框架和蒙特卡罗马尔可夫链（MCMC）模拟的新方法被开发出来，使用特定的选择目标对供应商进行排名和选择。当存在较小或缺失的数据集时，这种技术也很有效，这是更新和复杂措施的一个特别普遍的特征，例如在可持续性决策环境中。从MCMC模拟中获得的结果提供了关于供应商绩效的丰富信息，这些信息构成了额外统计分析的基础。该模型允许决策者通过更改附加到三重底线区域的重要性权重来执行各种场景。我们提出了其中一些具有管理和研究意义的情景的结果，并确定了未来的研究方向。
In evaluating and selecting sustainable suppliers, we take a triple-bottom-line (profit, people and planet) approach and consider business operations as well as environmental impacts and social responsibilities of the suppliers. Different metrics are introduced to measure performance in these three areas. To examine the influences of different organizational and supply chain operating philosophies, the objectives in selection of suppliers are designed so that some of them favor profit or the business operations, others the planet or the environment and the remaining focusing on people or social responsibility. A novel methodological approach based on a Bayesian framework and Monte Carlo Markov Chain (MCMC) simulation is developed to rank and select suppliers using specific selection objectives. This technique is also effective when smaller or missing data sets exist, which is an especially prevalent characteristic for newer and complex measures such as in a sustainability decision environment. Results obtained from the MCMC simulation provide a wealth of information about supplier performance, which form the basis for additional statistical analyses. The model allows the decision maker to execute various scenarios by changing importance weights attached to the triple-bottom-line areas. We present results for some of those scenarios with managerial and research implications and future research directions identified.