ویژگی‌های منحصربه‌فرد تدارکات بشردوستانه پس از بلای طبیعی

Logistic activity can be thought of as a socio-technical process whereby a social network of individuals orchestrates a series of technical activities using supporting systems such as transportation and communications. To understand the functioning of the entire system requires proper consideration of all its components. We identify seven key components: the objectives being pursued, the origin of the commodity flows to be transported, knowledge of demand, the decision-making structure, periodicity and volume of logistic activities, and the state of the social networks and supporting systems. Based on our analysis of the differences between commercial and humanitarian logistics, we pinpoint research gaps that need to be filled to enhance both the efficiency of humanitarian logistics and the realism of the mathematical models designed to support it. We argue that humanitarian logistics is too broad a field to fit neatly into a single definition of operational conditions. At one end of the spectrum we find humanitarian logistic efforts of the kind conducted in long-term disaster recovery and humanitarian assistance, where operational efficiency – akin to commercial logistics – is a prime consideration. At the other, post-disaster humanitarian logistic operations involved in disaster response and short-term recovery activities represent a vastly different operational environment, often in chaotic settings where urgent needs, life-or-death decisions and scarce resources are the norm. The huge contrast between these operational environments requires that they be treated separately.

Improving the state of the art and practice of humanitarian logistics (HL) has huge economic and social implications as there is ample evidence that the human and economic impacts of natural disasters are increasing (Centre of Research for the Epidemiology of Disasters, 2009). According to the Office of U.S. Foreign Disaster Assistance and the Center for Research on the Epidemiology of Disasters, in 2010 more than 297,000 people were killed and over 217 million were affected by natural disasters, and the economic damage has been estimated at over US$123.9 billion (Guha-Sapir et al., 2011). However, research on HL is simply not commensurate with its crucial role, particularly those aspects concerning characterization. The number of empirical studies of real life HL efforts is pitifully small. Part of the problem is that the HL practitioner community is very small – no more than a few thousand individuals in the entire world could claim HL as their full-time occupation. Given the minuscule size of the community, as well as its reluctance to produce publicly available accounts of actual HL efforts, only those individuals directly involved are familiar with the intricate details of the operations. In our view this represents a major obstacle to the development of relevant analytical models, since it is not possible to develop accurate models of a system that is poorly understood. In contrast, the functioning, features and dynamics of commercial logistics are well known, hence researchers have been able to develop highly sophisticated analytical models to optimize the various components of modern supply chains. Together with the development of advanced distribution systems, this has dramatically enhanced performance. To give one illustration of this, transportation's share of total production costs fell by 52.3% between 1970 and 2002 (Chopra and Meindl, 2007). The disparity between commercial and humanitarian logistics has prompted attempts to adapt analytical formulations originally developed for the commercial sector to the humanitarian context. While undoubtedly pragmatic, such adaptations have major limitations since commercial and humanitarian logistics are recognized as being radically different (Beamon, 2004, Beamon and Kotleba, 2006, Van Wassenhove, 2006 and Holguín-Veras et al., 2007) and most analytical formulations fail to fully capture the complexity of HL. This paper identifies differences between commercial logistics and the key variants of HL. The term ‘humanitarian logistics’ encompasses a wide range of operations including the distribution of medical supplies for routine disease prevention, food supplies to fight hunger, and critical supplies in the aftermath of a disaster. While these share humanitarian goals, they are profoundly different on account of the level of urgency of the operations, the state of the social networks that orchestrate the effort, the state of the supporting systems, and the dynamic nature of the needs, among others. Treating HL as a homogeneous block glosses over the complexity and distinctness of the various operational environments, making it difficult for outsiders to understand the unique features of the different types of HL and to develop suitable analytical formulations. While previous comparisons between commercial logistics and HL have been made (Beamon, 2004 and Holguín-Veras et al., 2007), the role of social networks and the differences between the various modalities of HL have been largely overlooked. In analyzing the key forms of HL, our main emphasis is on post-disaster operations, where the contrast with commercial logistics is most extreme. For this reason we discuss cases from the literature and from our fieldwork on post-disaster humanitarian logistics (PD-HL). The remainder of the paper is organized as follows. Section 2 focuses on the analysis of the differences between disasters and catastrophes from the standpoint of their respective impacts on the HL response. Section 3 discusses the differences between commercial and HL based on the disaster research literature, fieldwork by the authors, direct observation of prominent cases (e.g., World Trade Center, Hurricane Katrina, Haiti, Japan), and comprehensive analyses of the HL process. Section 4 presents an outline of research needs aimed at addressing the most pressing knowledge gaps related to PD-HL. We conclude with a summary of our key findings.

This paper compares and contrasts commercial and humanitarian logistics in order to determine the most salient differences and commonalities. In doing so, it makes the point that the field of humanitarian logistics is too broad to be neatly characterized by a single definition of operational conditions. At one end of the spectrum one finds regular humanitarian logistic efforts (R-HL) of the kind conducted in long-term disaster recovery and humanitarian assistance where operational efficiency – akin to the commercial logistics setting – is a primary consideration. At the other end, post-disaster humanitarian logistic (PD-HL) operations – part of disaster response and short-term recovery activities – take place in chaotic situations where urgent needs, life-or-death decisions, and scarce resources are the norm. The vast differences in these operational environments require that we treat them separately. We distinguish between disasters and catastrophes. Following a disaster the social networks which orchestrate the technical activities in logistics may remain largely functional, significant amounts of local supplies held by households and businesses may survive, private sector supply chains may remain largely operational (though impacted), hence local responders and the private sector can provide a first wave of resources and a more permanent source of supplies once the private sector recovers. After a catastrophe it can be anticipated that local social networks that manage logistics will be severely disrupted or destroyed, local supplies will be destroyed, private sector supply chains severely disrupted (taking them weeks to fully recover), and the demand for supplies will increase dramatically. In essence, after a catastrophe, most of the supplies have to come from the outside. Complicating the matter, “precautionary/opportunistic buying” by individuals and businesses, both before and after the disaster, contribute to the depletion of inventory. Rather than assuming that local responders will provide a first wave of resources during the first 24–48 h of the response, it should be acknowledged that the bulk of the help, including during the first hours of the response, must come from the outside, not from the local private sector. We argue that logistics is a socio-technical process that uses a number of supporting systems: a social network of individuals involved in the effort manages, orchestrates, and conducts technical activities, relying on supporting systems such as transportation. Hence problems in any of these components will impact the performance of the entire process. This insight has impelled us to define seven dimensions along which to describe and compare logistical operations: the objectives pursued, origin of the commodity flows, knowledge of demand, decision making structure, periodicity and volume of logistic activities, state of the social networks, and state of supporting systems. We argue that there is a need for significant advances in humanitarian logistics modeling to ensure that analytical formulations adequately take into account the full complexity of the operations. This need is most acute in PD-HL. Here, relief organizations strive to alleviate human suffering at the impacted site, operating in an environment characterized by: an impacted social system and networks; a massive influx of goods due to material convergence; dynamic, fragmented and at times competing supply chains; severe damage to the physical and virtual infrastructure; and short timeframes to respond and prevent loss of lives and property. The situation is aggravated by uncertainty about demand and supply. The paper identifies seven areas – the definition of suitable objective functions, material convergence, the decision-making structure, knowledge of demand and supply, decision support tools, social aspects, and public sector policy – where additional research should be conducted to improve both basic knowledge of the underpinnings of PD-HL, the level of realism of the analytical models and decision support tools, and the overall efficiency of the HL response. In the opinion of the authors, the various stakeholders in the disaster response community should proactively support such research as they have complementary views of this complex subject. One of the key insights reported here is that humanitarian logistics encompass a wide range of operational conditions that span different forms of humanitarian assistance – from those set in a stable environment for relatively long periods of time (referred to here as regular humanitarian logistics) to the chaotic, dynamic and ephemeral post-disaster environment (PD-HL). While regular humanitarian logistics operations are relatively similar to the commercial case (although the supply chain context may be very different, as well as the objective function and the constraints imposed by the donors), in PD-HL the situation is very different. We need to develop analytical models that capture the complexity of such operations as current models simply do not take into account the key aspects of PD-HL, and thus risk producing sub-optimal results. This paper calls for a concerted effort to develop a new paradigm of PD-HL models. This is best thought of as a long-term goal since despite commendable work by the research community, the underlying dynamics of PD-HL are still poorly understood and more field and case research is necessary.