Meaning of Post-disaster development

Post-disaster development has various approaches and different priorities in different countries. It is not surprising that there are widely divergent views and interpretations in various countries, with marked differences between countries that have a developed market economies, those with transition economies and in developing countries. Not all countries with one of theses three development levels, understand post-disaster development in the same way and so have different strategies.

Successful strategies for post-disaster development should be more-or-less compatible with disaster level, economic, social, cultural, institutional, technological, technical, cultural, environmental and legal/regulatory situations in the country under consideration. A varied spectrum of strategies can be launched, while keeping in mind that the mix of influencing factors and the relative emphasis is on one or other of the factors and overall will depend on local conditions.

Therefore, the best post-disaster development strategy of another country cannot just be copied. Strategies may only be adapted into a real disaster situation, economic, social, cultural, institutional, technological, technical, cultural, environmental and legal/regulatory circumstances of the existing state. There is no such thing as a single post-disaster development strategy that could be applied to all countries.

The trends of post-disaster development and modeling were investigated by researchers from various countries. For example,

  • Ruangrassamee and Saelem (2009) described effect of Tsunamis generated in the Manila Trench on the Gulf of Thailand.
  • Scheffers et al. (2008) analysed Late Holocene tsunami traces on the Western and Southern coastlines of the Peloponnesus (Greece).
  • Barbier (2008) presented lessons learned from the household decision to replant mangroves in Thailand.
  • Cochard et al. (2008) reviewed the 2004 tsunami in Aceh and Southern Thailand with special emphasis on coastal ecosystems, wave hazards and vulnerability.
  • Alongi (2008) studied mangrove forests with special emphasis on resilience, protection from tsunamis, and responses to global climate change.
  • Morton et al. (2007) presented physical criteria for distinguishing sandy tsunami and storm deposits using modern examples. Prez-Maqueo et al. (2007) examined coastal disasters from the perspective of ecological economics.
  • Rose (2007) analysed economic resilience to natural and man-made disasters.
  • Altay and Green (2006) applied OR/MS research in disaster operations management.
  • Benson and Clay (2006) analysed disasters, vulnerability and the global economy with special emphasis on implications for less-developed countries and poor populations.
  • Galbraith and Stiles (2006) reviewed disasters and entrepreneurship.
  • Hassan (2005) performed simplified two-dimensional numerical modelling of coastal flooding. Bates et al. (2004) analysed mitigating impacts on tourism.
  • Alcntara-Ayala (2002) studied geomorphology, natural hazards, vulnerability and prevention of natural disasters in developing countries.
  • Jayaraman et al. (1997) analysed management of the natural disasters from space technology inputs.

It can be noticed that above researchers engaged in the analysis of a post-disaster development and modeling but did not consider the research’s object as was analyzed by the authors of the present investigation. A life cycle of a post-disaster development may be described as follows: post-disaster development life cycle, the stakeholders involved in a post-disaster development as well as the micro and macro environments, having a particular impact on it and making an integral whole.

Ways of assessing post disaster development

There are two essential branches of knowledge development;

  • explicit and
  • Tacit


Explicit knowledge is widely used in information technologies. Explicit knowledge is comprised of the documents and data (for example, estimate for building costs) that are stored within the memory of computers. This information must be easily accessible, so that stakeholders could get all the necessary knowledge without disturbances.



Tacit knowledge is knowledge housed in the human brain, such as: expertise, understanding, skills, professional intuition, competence, experience, organizational culture, informal organizational communication networks, intellectual capital of an organization, ideals, traditions, values, emotions, etc.

The research’s aim was to develop a Knowledge Model for assessing Post-disaster development by undertaking a complex analysis of micro and macro environment factors affecting post-disaster life cycle and to present recommendations on efficient eliminating disaster’s subsequences. The research was performed by studying the most advanced expertise in the field. A simulation was undertaken to provide insight into creating an effective micro and macro environment.

The level of efficiency of the post-disaster development depends on the many micro and macro-level variable factors and all these variable factors can be optimized. The main objective of this Model is to analyze the best experiences in the field, to compare it and consequently to present particular recommendations.

The word ‘model’ implies ‘a system of game rules’, which the post-disaster development could use to its best advantage. The stakeholders of the post-disaster management cannot correct or alter the micro and macro level variables, but they can go into the essence of their effect and take them into consideration in their activities. Stakeholders, by knowing the environment affecting their activities, can organize their present and future actions more successfully.

Six stages of assessing post disaster development

1. Comparative description of the post-disaster development

  • A system of criteria characterizing the efficiency of post-disaster development was determined by means of using relevant literature and experts methods;
  • Based on a system of criteria, a description of the present state of post-disaster development is given in conceptual (textual, graphical, numerical, etc.) and quantitative forms.

2. A comparison and contrast of post disaster development

  • Identifying the global development trends (general regularities) of the post-disaster development;
  • Identifying post-disaster development differences between countries under analysis;
  • Determining pluses and minuses of these differences for countries under analysis;
  • Determining the best practice of post disaster development for countries under analysis as based on the actual conditions.
  • Estimating the deviation between post-disaster developers’ knowledge of worldwide best practice and their practice-in-use

3. A development of some of the general recommendations as how to improve the efficiency levels for post-disaster development

4. Submission of particular recommendations for post-disaster development

Each of the general recommendations proposed in the fifth stage carry several particular alternatives

5. A multiple criteria analysis of post-disaster development’s components and a selection of the most efficient version of post-disaster’s development life cycle were determined at this stage. After this stage, the received compatible and rational components of a post-disaster development are joined into the full post-disaster development process.

6. Performance of transformational learning and redesigning the mental and practical behaviour of post-disaster development

  • Post-disaster developers (stakeholders) becoming aware and conceptualize of their practice-in-use;
  • Post-disaster developers’ (firms’) becoming aware and conceptualize of their knowledge of worldwide best practice;
  • Post-disaster managers (stakeholders) estimating the deviation between knowledge of worldwide best practice and their practice-in-use;
  • Performance of best practice learning;
  • Fulfilling of best practice actions (understanding what the recurring motives caused developer’ initial behaviour are; redesigning managers’ core patterns of thought and behaviour);
  • Performance of transformational learning (acquiring new manners of technological, social, ethical, etc. behaviour, get better understanding of how to interact with micro and macro environment) and redesigning the behaviour.

In order to throw more light on the Knowledge Model for Post-disaster development, further follow more detailed description of the some above mentioned stages of analysis (determining the best practice for post-disaster development as based on the actual conditions and performance of transformational learning and redesigning the developer’ mental and practical behaviour).

Impact of post disaster development

Humanitarian aid agencies have a long-standing interest in evaluating the effectiveness of their assistance and interventions. The Development Assistance Committee adapted their core set of principles or criteria for the evaluation of development initiatives specifically for complex emergency settings. These criteria, reviewed in detail in a guide, include:

  • Relevance/appropriateness
  • Connectedness
  • Coherence
  • Coverage
  • Efficiency
  • Effectiveness
  • Impact

In this context, “impact” is defined as the broader, longer-term effect of a project, and is distinguished from “effectiveness”, which considers more short-term, intermediate objectives and outcomes.

The guide argues that impact of post disaster development may not be relevant in all contexts, “particularly those carried out during or immediate after an intervention”  and advocates undertaking impact evaluation only when impact evaluation specialists are involved, a longitudinal analysis is possible, and adequate data are available. The attribution challenge is discussed briefly—how is it possible to attribute observed change to specific interventions as time progresses? The discussion assumes that quasi-experimental designs are rarely feasible in this context, and encourages the use of “informal” control groups where possible. Impact evaluation is identified as the “most challenging” aspect of humanitarian action evaluation. This understandable note of caution has typified discussions of impact evaluation throughout the humanitarian community.

Interest however, Humanitarian Action, a full third of the report was devoted to the theory and practice of impact assessment (which I here consider to be synonymous with impact evaluation) in the humanitarian context. The report traces the evolution of a more evidence-based, outcomes-oriented approach to the provision of humanitarian relief over the past two decades, and cites the many initiatives around impact evaluation currently underway across the sector and through the wide aid and development communities, including a randomized study of a community-driven reconstruction program in Liberia; a participatory impact assessment in drought -affected communities in Niger; impact assessment of FAO’s emergency programs in DRC; and the Tsunami Recovery Impact Assessment and Monitoring

The report includes an eye-opening list of constraints to impact assessment in the humanitarian sector, including;

1) The complexity of terminology surrounding impact assessment;

2) lack of skills and capacity for impact assessment within most humanitarian agencies;

3) The unique timing of project and budget cycles; and

4) An absence of an impact orientation at the institutional level.

Also cite cultural biases against impact evaluation in humanitarian agencies, including the tendency to value action over analysis and risk aversion in the light of severely constrained resources. These constraints and biases have slowed progress towards establishing shared definitions of and methodologies for impact assessment.

The report is careful to draw an important distinction between approaches to impact evaluations (“comparative vs. “theory -based”) and data collection and analysis methods (quantitative vs. qualitative). Comparative approaches are described as quantitative, counterfactual methods while theory-based approaches are look at underlying causal models or program theories to identify the links from program activities through outcomes.

While the humanitarian community has often conflated these different aspects of evaluation

(e.g., assuming that all counterfactual analyses must be quantitative, or that all case study or theory of change models must be qualitative), this report and other recent discussions should help clarify the distinction.

A third important message on the report is the importance of choosing evaluation methods to suit the evaluation task at hand, a common theme in discussions of evaluation in the humanitarian sector. A notable backlash against experimental methods (or at least against anointing experimental approaches as the “gold standard” in evaluation) has prompted several different algorithms or frameworks for matching evaluation methods to intervention characteristics or evaluation goals:

  • Standardized interventions in identical settings with common beneficiaries are best suited to experimental designs.
  • Standardized interventions in diverse settings, possibly with diverse beneficiaries, are better suited to quasi-experiments and comparative approaches.
  • Customized interventions in diverse settings with diverse beneficiaries are better suited to case studies, narratives, and qualitative approaches.

Another important recent study from the humanitarian community examines motivations and opportunities and options for joint humanitarian impact evaluation commissioned. The study outlines in detail the many questions and issues that would have to agree upon before undertaking successful joint evaluation of humanitarian interventions. These include the purpose and use of joint evaluation, the conceptual framework to be used, the evaluation focus and scale (institutional vs. population), and methods. A set of pilot studies may emerge from the study, further evidence of the humanitarian community’s growing interest in impact evaluation.

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