基于免疫的组织健康捍卫机制建构:一个案例

本文借鉴医学免疫和健康的新视角,试图建构基于组织免疫行为的组织健康捍卫机制分析框架,探讨组织健康状态的理论维度和组织免疫行为如何捍卫组织健康状态并发挥作用的机制,同时,选取广东粤电集团沙角C电厂进行了案例研究。本文的研究揭示出,组织监视、组织防御和组织记忆是组织免疫过程的主要行为维度,而组织健康的理论维度,包括组织结构均衡性、功能活跃性、社会和谐性和环境适应性,组织免疫行为对组织健康有捍卫作用,任何一个要素和环节的缺失或失灵都会破坏组织健康状态,组织免疫系统的建立对于避免复杂系统的运行失败是非常关键的。     

Recursive Behavior of Safety Stock Reduction: The Effect of Lead‐Time Uncertainty

Motivated by a recent paper on the effect of lead‐time variability reduction on safety stocks, we provide evidence of the recursive nature of safety stock changes. When lead times follow a gamma distribution we demonstrate that, for cycle service levels between .60 and .70, the reduction of lead‐time variability will first increase safety stock and then either recursively decrease safety stock or make it remain constant. We also numerically show the existence of the recursive effect. A two‐by‐two matrix is introduced to assist managers in making decisions regarding safety stock policy.     

Some graph optimization problems with weights satisfying linear constraints

In this paper, we study several graph optimization problems in which the weights of vertices or edges are variables determined by several linear constraints, including maximum matching problem under linear constraints (max-MLC), minimum perfect matching problem under linear constraints (min-PMLC), shortest path problem under linear constraints (SPLC) and vertex cover problem under linear constraints (VCLC). The objective of these problems is to decide the weights that are feasible to the linear constraints, and find the optimal solutions of corresponding graph optimization problems among all feasible choices of weights. We find that these problems are NP-hard and are hard to be approximated in general. These findings suggest us to explore various special cases of them. In particular, we show that when the number of constraints is a fixed constant, all these problems are polynomially solvable. Moreover, if the total number of distinct weights is a fixed constant, then max-MLC, min-PMLC and SPLC are polynomially solvable, and VCLC has a 2-approximation algorithm. In addition, we propose approximation algorithms for various cases of max-MLC.

     

Approximation algorithms for two variants of correlation clustering problem

Correlation clustering problem is a clustering problem which has many applications such as protein interaction networks, cross-lingual link detection, communication networks, and social computing. In this paper, we introduce two variants of correlation clustering problem: correlation clustering problem on uncertain graphs and correlation clustering problem with non-uniform hard constrained cluster sizes. Both problems overcome part of the limitations of the existing variants of correlation clustering problem and have practical applications in the real world. We provide a constant approximation algorithm and two approximation algorithms for the former and the latter problem, respectively.

     

Designing optimal food safety monitoring schemes using Bayesian network and integer programming: The case of monitoring dioxins and DL-PCBs

Efficient food safety monitoring should achieve optimal resource allocation. In this article, a methodology is presented to optimize the use of resources for food safety monitoring aimed at identifying noncompliant samples and estimating background level of hazards in food products. A Bayesian network (BN) model and an optimization model were combined in a single framework. The framework was applied to monitoring dioxins and dioxin-like polychlorinated biphenyls (DL-PCBs) in primary animal-derived food products in the Netherlands. The BN model was built using a national dataset with monitoring results of dioxins and DL-PCBs in animal-derived food products over a 10-year period (2008–2017). These data were used to estimate the probability of detecting suspect samples with dioxins and DL-PCBs levels above preset thresholds, given certain sample conditions. The results of the BN model were then inserted into the optimization model to compute an optimal monitoring scheme. Model estimates showed that the probability of dioxins and DL-PCBs exceeding threshold limits was higher in laying hen eggs and sheep meat than in other animal-derived food (except deer meat). Compared with the monitoring scheme used in the Netherlands in 2018, the optimal monitoring scheme would save around 10,000 EUR per year. This could be obtained by reallocating monitoring resources from products with lower probability of dioxin and DL-PCBs exceeding threshold limits (e.g., pig meat) to products with higher probability (e.g., bovine animal meat), and by shifting sample collection from the last quarter of the year toward the first three quarters of the year.     

Employee green behaviour: A review and recommendations for future research

Despite the increasing awareness of impacts of organizational activities on the natural environment and the urgent need for sustainable management of ecosystems, emerging research on employee green behaviour in the field of management and organizational science is largely fragmented, requiring an integrative review. Seeking to better understand research opportunities and advance theoretical and empirical development, this paper evaluates available research on the topic by first reviewing conceptualizations and corresponding theoretical approaches. It then develops an overarching framework to evaluate the findings of empirical studies at different levels of analysis for different approaches. It concludes with recommendations for future research on employee green behaviour and provides important implications for environmental sustainability in organizations.