Performance Measurement Systems for Humanitarian Logistics

Abstract

Purpose
The aim of this paper is to describe a performance measurement system (PMS) including adequate key performance indicators (KPI) for humanitarian logistics respecting the specific requirements of logistics processes of relief organizations.
Design/methodology/approach
The approach followed is based on a comprehensive literature study of existing logistic PMS in order to investigate their transferability to humanitarian logistics. Based on a differentiation between commercial and humanitarian logistics, a promising PMS concept for the application area of humanitarian logistics was designed.
Findings
The identification of a supply chain balanced scorecard (BSC) as a PMS seems to be beneficial for humanitarian logistics. It respects the diversity of humanitarian organizations considering different logistics strategies and allows for the integration of short- and long-term logistical targets.
Research limitations/implications
The findings are conceptual at this stage. Its application is necessary in order to evaluate the developed BSC and the ability of humanitarian organizations for the required data collection. Additionally, the acceptance and willingness of the PMS application by humanitarian organizations has to be determined.
Practical implications
The results put humanitarian organizations in a position to easily collect and analyze relevant data on logistics processes respecting their organization-specific logistics strategy. Thus, the improvement of logistics performance and reduction of logistics related costs is enabled.
Original/value
For the first time, a supply chain BSC framework and adequate KPI-set for humanitarian logistics were identified. They appear promising to fulfil the specific requirements within the application area.

Full text




The 23
rd
Annual NOFOMA Conference
9–10 June 2011, Harstad, Norway

Logistics and Supply Chain Management in a
High North perspective

Conference proceedings
Trond Hammervoll (Editor)

Performance Measurement Systems for
Humanitarian Logistics
Adam Widera
*
Bernd Hellingrath
**
*) University of Münster, Department of Information Systems, Chair for Information Systems
and Supply Chain Management, D-48149, Münster, Germany
E-mail: adam.widera@wi.uni-muenster.de, Tel: +49 (251) 83-3 80 11
**) University of Münster, Department of Information Systems, Chair for Information Systems
and Supply Chain Management, D-48149, Münster, Germany
E-mail: bernd.hellingrath@wi.uni-muenster.de, Tel: +49 (251) 83-3 80 00
ABSTRACT
Purpose
The aim of this paper is to describe a performance measurement system (PMS) including
adequate key performance indicators (KPI) for humanitarian logistics respecting the
specific requirements of logistics processes of relief organizations.
Design/methodology/approach
The approach followed is based on a comprehensive literature study of existing logistic
PMS in order to investigate their transferability to humanitarian logistics. Based on a
differentiation between commercial and humanitarian logistics, a promising PMS concept
for the application area of humanitarian logistics was designed.
Findings
The identification of a supply chain balanced scorecard (BSC) as a PMS seems to be
beneficial for humanitarian logistics. It respects the diversity of humanitarian organizations
considering different logistics strategies and allows for the integration of short- and long-
term logistical targets.
Research limitations/implications
The findings are conceptual at this stage. Its application is necessary in order to evaluate
the developed BSC and the ability of humanitarian organizations for the required data
collection. Additionally, the acceptance and willingness of the PMS application by
humanitarian organizations has to be determined.
Practical implications
The results put humanitarian organizations in a position to easily collect and analyze
relevant data on logistics processes respecting their organization-specific logistics strategy.
Thus, the improvement of logistics performance and reduction of logistics related costs is
enabled.
Original/value
For the first time, a supply chain BSC framework and adequate KPI-set for humanitarian
logistics were identified. They appear promising to fulfil the specific requirements within
the application area.
Keywords: Humanitarian logistics, performance measurement, key performance
indicators.
1327

1. MOTIVATION
The last decade was characterized by an increase of the number and damage caused by both
natural and manmade disasters. The catastrophes in Haiti, Chile, and Pakistan in the year 2010
alone illustrate the relevance of relief operations: these three biggest of 725 natural disasters
registered in 2010 affected 24 million people (Germany’ Relief Coalition 2011). Considering
the number of deaths, the International Disaster Database calculates 222.570 killed people in
Haiti alone; the Prime Minister of Haiti estimates the number of victims up to 316.000
(CRED 2011). In combination with the fact that the number of disasters has tripled between
the 1970s and 1990s, forecasts of its five-fold increase for the next 50 years underline the
necessity of research and action efforts (Swiss Reinsurance Company 2009, Thomas and
Kopczak 2005). Numerous studies have shown that humanitarian logistics significantly
contribute to the efficiency and effectiveness of humanitarian operations (Thomas and
Kopczak 2005; Tomasini and van Wassenhove 2009). Logistic related costs of relief
operations likely amount to between 40 and 60%, but can sum up to 80% of the total spend
including procurement costs (Long and Wood 1995; van Wassenhove 2006; Blecken 2010).
Based on the observations that the evolution of supply chain management (SCM) in
humanitarian organizations compared to the commercial sector is lagging behind up to 20
years (e.g. McGuire 2006), increased efficiency offers a large potential for savings of logistics
related costs and improved resource allocation. Besides, the development and application of
adequate SCM concepts promise to have an impact on the effectiveness of humanitarian
supply chains, e. g. increase of service quality, reduction of complexity or lead times
(Tomasini and van Wassenhove 2009, Schulz 2009). In contrast, the interface and
management function of logistics is underestimated: in consequence, roles and responsibilities
in humanitarian supply chains are not clear, the performance is not measured adequately, and
the use of technology and institutional learning are inadequate (Thomas and Kopczak 2005,
Tufinkgi 2006, Blecken 2010). It can be acknowledged that the recognition of the importance
of SCM continuously arises in the humanitarian sector. Logistics activities in humanitarian
supply chains have been partly enhanced in the recent years. Some humanitarian actors
installed e.g. shared equipment or globally pre-positioned stocks. Nevertheless, managing
logistics processes is still one of the major challenges in the humanitarian sector (Blecken et
al. 2009; Blecken 2010).
For improvements of logistics performance and reduction of logistics related costs,
insufficient processes have to be identified first. Therefore, an investigation of the entire
logistics process concerning supply chain drivers and a dedicated allocation of relevant
metrics are necessary in order to provide a basis for strategic, tactical, and operational
decision making (Stadtler and Kilger 2008). Based on the identification of standardized
processes (presented e.g. by Blecken 2010), the application of a performance measurement
system (PMS) puts humanitarian organizations in a position to collect relevant data, analyze
and optimize logistics performance of relief operations. Such a PMS is able to measure the
organizations success using relevant key performance indicators (KPI), weighted with
organization specific importance. In order to be used by various organizations, the PMS
should be designed respecting its reusability, modularity, and adaptability. As commercial
supply chains are able to revert to numerous established PMS-concepts, they cannot simply be
adopted for humanitarian logistics challenged by “(…) intangibility of the services offered,
immeasurability of the missions, unknowable outcomes, and the variety, interests, and
standards of stakeholders.” (Beamon and Balcik 2008). Until now, the need of measuring
humanitarian logistics performance, the lack of necessary IT support systems and adequate
1328

PMS were postulated (Blecken, Hellingrath 2008; Blecken 2010). The methodology used in
in this work is a mix of literature analysis and design science approach structured in four
phases. In the first phase the problem of performance measurement of humanitarian supply
chains is specified. Based on a comprehensive literature study of existing logistic PMS the
transferability to humanitarian logistics is investigated in the second phase. In combination
with a differentiation between commercial and humanitarian logistics, relevant and applicable
PMS and KPI for humanitarian logistics are selected following a target/actual comparison in
the third phase. Finally, in the fourth phase a first draft of a promising PMS concept for the
application area of humanitarian logistics is developed based on a design science approach.
2. STATE OF THE ART
2.1. HUMANITARIAN LOGISTICS AND SUPPLY CHAIN MANAGEMENT
A common view in describing the term “logistics” in general focuses on all transportation-
and warehousing processes including all sub functions, such as handling or commissioning,
with the aim of ensuring the availability of objects needed in line with demand (Baumgarten
et al. 2001). Nowadays, the term “supply chain management” has become popular and tends
to complement the term “logistics” in order to highlight the inter-organizational perspective,
management, and coordination function. As the Council of Supply Chain Management
Professionals (CSCMP) points out, it is of high importance to take the management of
coordination and collaboration with all partners involved into account (CSCMP 2011): “In
essence, supply chain management integrates supply and demand management within and
across companies” (CSCMP 2011). Therefore, in the following, the term logistics is used
when the focus lies on the physical operations. In contrast, the term supply chain management
is understood as the integrated and process-oriented planning and control of material,
information, and financial flows along the entire supply chain in business or other value
adding processes from the point of origin to the point of consumption (Kuhn and Hellingrath
2002).
As Tomasini and van Wassenhove (2009) pointed out, although the definitions of
“humanitarian” vary in the literature, there is no doubt about its three main principles
surrounding the humanitarian space: humanity, neutrality and impartiality. First, humanity
figures as a main objective of humanitarian organizations and its actions, so “human suffering
should be relieved wherever found” (Tomasini and van Wassenhove, 2009). Second,
neutrality can be understood as a restricted room for manoeuvre, as relief organizations
should be committed not to interfere in political issues within the operational area. Third,
impartiality obliges humanitarian actors to ensure equal treatment of beneficiary peers. An
isolated view on both, humanitarian and logistics, offers first ideas on humanitarian logistics
but does not provide a sufficient basis for an applicable definition, as its synthesis has to be
clarified. Although humanitarian logistics is a relatively young topic in supply chain
management research and several descriptions of humanitarian logistics have been presented,
no generally accepted definition has been provided during the last decade (Blecken 2010).
Blecken (2010) provided a definition of humanitarian logistics, which is mainly based on
Thomas and Kopczak (2005) and will be used in the following. Here “humanitarian logistics”
is described as the “process of planning, implementing and controlling the efficient, cost-
effective flow and storage of goods, materials and equipment as well as related information,
from point of origin to point of consumption for the purpose of meeting the beneficiary’s
requirements.” (Blecken 2010) This definition seems to be generic at first sight, but offers the
necessary scope on all relevant tasks, concepts, tools, and especially the management function
of SCM processes in humanitarian operations. Using the proposed definition in conjunction
1329

with characteristics of humanitarian supply chains, the consideration of all humanitarian
actors in a supply chain is enabled.
2.2. HUMANITARIAN VS. COMMERCIAL SUPPLY CHAINS
To specify the context of relief operations, the definition above has to be seen in the light of
main differences between humanitarian and commercial supply chains, upon latter several
works already have focused. As the existing SCM literature offers numerous promising
concepts for performance measurement, it has to be answered why they are not applicable for
humanitarian logistics. Three characteristics can be identified as causes for the differentiation:
supply chain flows, structures, and disaster management life cycles. The flows of personnel as
well as knowledge and skills have to be highlighted within the established supply chains
flows. This can be realized by considering the flow of personnel within the flow of material.
The flow of knowledge and skills should be taken into account within the flow of information.
Besides, the differentiation between typical humanitarian and commercial supply chain
structures is of high importance (Tomasini and van Wassenhove 2009). The main difference
can be found in the position of the customer in commercial supply chains: here, he is the one
who is asking for goods or services willing to pay for his benefit. In humanitarian supply
chains it is the donor who is paying for goods or services delivered by humanitarian
organization based on the beneficiary’s needs. The funding structure of humanitarian
organizations is often mixed by private, commercial or governmental donations. Additionally,
humanitarian supply chains have to be distinguished time-driven into different stages and its
specifications in disaster relief operations: the disaster management cycle (Tomasini and van
Wassenhove 2009). In current literature, the following four phases are distinguished
commonly: mitigation, preparedness, response, rehabilitation. In each stage specific tasks and
functions have to be fulfilled, which is caused mainly by different requirements on relief
operations. The characteristics flows, supply chain structures, and disaster management
lifecycle are responsible for important differences in humanitarian and commercial supply
chains, which are listed in the table below.
Table 1: Own selection of main differences between humanitarian and commercial logistics
(acc. to [a] Charles et al. 2009 and [b] Beamon 2004)
Commercial Supply Chain Humanitarian Supply Chain
Range [a]
From supplier’s supplier to customer’s
customer From donors and suppliers to beneficiaries
Actors [a] Known, with aligned incentives
Multiplicity in nature, but scarcity in numbers +
misaligned incentives
Customer
definition [a] End user = Buyer
End user (Beneficiary) ≠ Buyer (donor). Demand is
highly uncertain.
Supplier [a]
Supplier only, known in advance
generally, 2 or 3 in average Supplier and/or donor uncertain and multiple
Environment [a] More and more volatile Highly volatile and unstable
Shelf Life [a] Some years, but tends to shorten
Some weeks to some months in total, mounting and
dismantling included. Project oriented. Depends on
type of crises (sudden-onset or slow-onset disasters).
Demand Pattern
[b]
Relatively stable, predictable demand
patterns. Demands occur from fixed
locations in set quantities.
Demand is generated from random events that are
unpredictable in terms of timing, location, type, and
size. Demand requirements are estimated after they
are needed, based on an assessment of disaster
characteristics.
1330

Lead Time [b]
Lead time determined by the supplier-
manufacturer-DC-retailer chain.
Approximately zero lead times requirements (…),
but the actual lead time is still determined by the
chain of material flow.
Distribution
Network
Configuration [b]
Well-defined methods for determining
the number and locations of
distribution centers.
Challenging due to the nature of the unknowns
(locations, type and size of events, politics, and
culture), and “last mile” considerations.
Inventory Control
[b]
Utilizes well-defined methods for
determining inventory levels based on
lead time, demand and target customer
service levels.
Inventory control is challenging due to the high
variations in lead times, demands, and demand
locations.
Information
System [b]
Generally well-defined, using advanced
technology.
Information is often unreliable, incomplete or non-
existent.
Strategic Goals [b]
Typically: to produce high quality
products at low cost to maximize
profitability and achieve high customer
satisfaction.
Minimize loss of life and alleviate suffering.
[Thomas (2003)]
Performance
Measurement
System [b]
Traditionally: focused on resource
performance measures, such as
maximizing profit or minimizing costs.
Primary focus on output performance measures,
such as the time required to respond to a disaster
[Thomas (2002)] or ability to meet the needs of the
disaster (customer satisfaction).
What is
“Demand”? [b] Products. Supplies and People.
As shown in the table, the strategic goal on saving lives and relieving human suffering
radically determines humanitarian supply chains (for further explanations see the literature
referred). The following characteristics of humanitarian logistics can be highlighted as being
of crucial importance for managing the processes involved in relief operations: relatively
unstable, uncertain and unpredictable demand; role of donors as buyers and beneficiaries as
end users; high importance of speed (Beamon 2004); highly volatile and unstable
environment (Charles et al. 2009); partly temporary and unknown supply chain design (Jahre
and Jensen 2009); the importance of personnel as additional material flow (e.g. service
provider) and knowledge and skills as additional information flow (Tomasini and van
Wassenhove 2009); and finally the focus on procurement and distribution within the logistics
value chain (Blecken 2010). These findings are of high importance in order to provide
adequate PMS and KPIs for humanitarian logistics and supply chain management.
2.3. PERFORMANCE MEASUREMENT SYSTEMS
One promising way to increase the performance of value adding processes is to measure,
analyze and change them adequately. For performance measurement a set of indicators and its
assignment to processes and organization-specific targets is necessary. Each indicator has a
weighted importance for the overall performance, and that is the reason why the identification
of KPIs is needed. As Bürkler (1977) concluded, KPIs can be defined as business-oriented
relevant and numeric information. A PMS can be defined as systematization and
categorization of such KPIs, which prevents an isolated view and possible misinterpretation.
Thus, the indicators can be related to each other and weighted by targeting specific objectives
(Reichmann 1990).
In the last years a large amount of different logistics oriented performance measurement
concepts have been provided within the scientific community. Keller and Hellingrath (2007)
presented an overview of existing frameworks for the commercial sector systemized by an
orientation on the field of application. The following classifications were used: benchmarking,
cost-benefit analysis, potential analysis as well as performance measurement divided into
1331

economic, specific logistics and holistic logistics PMS. It can be stated, that commercial
enterprises are able to fall back on a wide range of established and proved PMS. They offer
several advantages and disadvantages in order to fulfill organization-specific and inter-
organizational requirements for performance measurement. Keller and Hellingrath (2007)
conclude, that a general comparability of these different PMS is nearly impossible as each
KPI includes differences in terms of classification, notation, definitions, calculations and
applications. They propose to develop a holistic approach for performance measurement,
which can be classified between the PMS investigated. The existing PMS and the developed
framework cannot be discussed in detail in this work, but out to be deepened in further
literature (Keller and Hellingrath 2007, Keller 2009). As already discussed in the previous
chapters and pointed out by Blecken (2010), there is a high degree of complexity to be
managed within humanitarian supply chains and its logistics processes. For this reason,
especially the approaches for supply chain performance measurement are of high importance
in the following. According to Keller (2009), the following PMS can be classified as SCM
PMS: various Balanced Scorecard (Brewer and Speh 2000; Stölzle et al. 2001; Weber et al.
2002; Jehle 2002)-, Hieber (2002)-, Kirchhausen (2004)-, DynaMoZ (2004)-, and Beamon
(1999)-approaches. These approaches seem to be relevant for performance measurement of
humanitarian supply chains and deserve a detailed examination based on an investigation of
requirements and restrictions for performance measurement in humanitarian logistics.
Additionally, by reflecting about developed and applied PMS in humanitarian logistics, the
relevant approaches identified in this chapter will be considered in order to be qualified as an
adequate approach.
2.4. PERFORMANCE MEASUREMENT IN HUMANITARIAN LOGISTICS
In practice of humanitarian organizations, on the one hand, performance measurement is seen
as useful by the large majority of humanitarian organizations. On the other hand, 55% of
humanitarian organizations do not monitor any KPIs, about 25% declare to control a few
indicators, and only 20% are measuring the performance consistently (Blecken 2010). The
need for performance measurement of humanitarian supply chains was recognized by the
scientific community. Based on extensive literature of existing KPIs and PMS for commercial
supply chains (e. g. Keller and Hellingrath 2007), initial works of its applicability for the
humanitarian sector have been undertaken (e.g. Beamon 2004, Davidson 2006, van der Laan,
de Brito and Vergunst 2007).
The current research in the area of performance measurement covers two directions. The first
one deals with requirements for performance measurement in humanitarian supply chains,
procedures for developing PMS and new KPIs as well as supporting information systems (e.g.
Beamon 2004; Schulz and Heigh 2009, Beamon and Balcik 2008; Blecken and Hellingrath
2008; Howden 2009; Schulz 2009, de Leeuw 2010). For example, Beamon (2004) discussed
the transferability of a PMS for commercial supply chains considering resource, output and
flexibility performance measures. Blecken and Hellingrath (2008) presented a review and
assessment of current SCM tools for humanitarian operations and their support of specific
performance indicators. These works give important insights on humanitarian performance
measurement, but only partly provide elements of a thorough PMS and its implementation,
which is applicable for different organizations covering different relief operation stages and
objectives.
The second direction focuses on investigations of PMS applied in certain organizations (e. g.
Davidson 2006; van der Laan, de Brito and Vergunst 2007, 2009; Samii 2008; Schulz and
Heigh 2009; Rongier et al. 2010). Davidson (2006) e. g. discusses different PMS (as the
Balanced Scorecard or the SCOR model) in order to select, implement, and evaluate a PMS
1332

for the International Federation of Red Cross and Red Crescent Societies (IFRC). Based on
interviews with the IFRC, existing PMS were abandoned and an organization specific
solution was chosen: a time-oriented PMS including the indicators (1) Appeal to Coverage,
(2) Donation-to-Delivery-Time, (3) Financial Efficiency, and (4) Assessment Accuracy
(Davidson 2006). Rongier et al. (2010) investigated different process-oriented PMS (Activity
Based Costing, the Fraunhofer Holistic Process PMS, SCOR-Model, and the Balanced
Scorecard) and presented a measurement concept exclusively for the response phase, which is
based on process definitions and a specific KPI selection for the French Red Cross. For
generic process mapping, the promising Business Process Management (BPM) approach was
chosen and, while a logistics-oriented perspective and existing process models for
humanitarian logistics was neglected (Rongier et al. 2010). Additionally, the focus on the
response phase does not reflect the requirements for performance measurement of
humanitarian organizations during the whole disaster response life cycle. These works focus
on organization-specific solutions and offer important cognitions about end user demands on
PMS as well as its applicability and prospects of success. Accordingly, the adaptability of
PMS presented for other organizations is neglected.
As organizations in the humanitarian sector differ greatly in terms of size, structure, field of
application, and professional staff, these findings have to be reviewed in order to fulfill the
requirements for a reusable, modular, and adaptable PMS. Additionally, the proposed PMS
needs to reflect a process driven view on logistics performance based on standardized
processes in order to identify vulnerability issues within the supply chain. These shortcomings
may be solved taking the Reference Task Model into account (RTM, Blecken 2010).
Additionally, adequate information systems are necessary to support the required data
collection and its analysis due to the manageability of the big amount of data (see also
Davidson 2006). Therefore, the end-user requirements (e.g. usability or costs) as well as
necessary functions (e.g. order management or monitoring) have to be fulfilled by the
information systems in order to ensure a sustainable acceptance of the user. On the basis of an
adequate use of the software the collection of relevant information on logistics performance
and costs is enabled. In result, aggregated information is able to be analyzed and visualized
with regards to decision support and management information systems. For this purpose
adequate information systems and its appropriate use are indispensable. These requirements
have to be considered within the design of the PMS. Latest publications in the fields of
humanitarian logistics clearly identify the described need for research on requirements,
design, and possible implementations of PMS for relief organizations (Chandraprakaikul
2010, Blecken 2010). Majewski et al. (2010) presented an extensive study on humanitarian
logistics challenges in the near future and formulated inter alia the following recommendation
for humanitarian organizations in the context of performance measurement: “Humanitarian
actors must design performance measurement systems to monitor, manage, and account for
the efficiency and effectiveness of their logistical systems.” (Majewski et al. 2010)
3. IDENTIFICATION OF REQUIREMENTS FOR PERFORMANCE
MEASUREMENT IN HUMANITARIAN LOGISTICS
3.1. REQUIREMENTS AND RESTRICTIONS
Before relevant KPI and suitable PMS are discussed, it has to be reviewed which
requirements for performance measurement of humanitarian logistics. Schulz and Heigh
(2009) provided an overview of KPI requirements, which is presented and described in the
following table.
1333

Table 2: KPI Requirements (NCPDM 1984 quoted in Schulz and Heigh 2009)
Requirement Short Description
Validity Address the real performance drivers.
Relevance Reveal decision relevant information.
Cardinality Cover a wide range of key issues under consideration.
Completeness
Use additional metrics if not all relevant issues can be covered
by only one.
Comparability
Allow intra- and inter-organizational comparisons as well as comparisons
over time.
Compatibility
Input data for calculating the metrics should be available from the
existing systems.
Cost and benefit
Development and continuous measuring cost have to be contrasted
with the resulting benefits.
In addition, the following two points should be added: manageability (Keller and Hellingrath
2007) and adaptability (Preißler 2008). By considering the manageability of possible KPIs, a
reasonable economic relationship between costs and benefits of measuring the KPI will be
ensured. Adaptable KPIs enable a necessary flexibility, which can be caused by changing
structures and processes. Thus, organizations using the selected KPIs do not have to invest in
time consuming redefinitions of metrics. As a final notice on requirements of KPIs, they
should be constructed in a way that an assignment of measurement points to specific process
steps is allowed. As VDI 4400 (2002) points out, existing SCM tools document relevant
processes by the identification of events in form of quantity and time data as each KPI has to
be quantifiable. Setting specific measurement points, concrete stages in process sequences are
predefined in order to evaluate the performance executed within the tasks. Such a process
orientation puts the organization in a position to analyze several tasks they have to deal with.
Therefore, a standardized process model is necessary as a basis. As already mentioned in the
chapters above, the reference model by Blecken (2010) seems to be a promising initial point
for generating organization-specific, time-oriented and comparable process models (for more
information see Blecken 2010). Additionally, several restrictions have to be considered in the
context of performance measurement of humanitarian organizations. Thomas and Kopczak
(2005) as well as Blecken (2010) have identified five restrictions for successful performance
measuring of humanitarian logistics: (1) lack of adequate IT systems; (2) limited possibilities
of data collection in field; (3) lack of time of the personnel; (4) lack of professional staff and
(5) the willingness as a crucial factor for the implementation of PMS. In order to cancel out
these environmental caused organizational restrictions, three conditions were given by van der
Laan et al. (2009). According to these, adequate performance measurement of humanitarian
organizations can only be realized by: (1) an increase of the recognition of the strategic
importance of SCM in humanitarian operations, (2) (organizational) willingness of measuring
operational performance, and (3) adequate use of existing software for humanitarian SCM.
According to van der Laan et al. (2009) humanitarian organizations or their executive
departments for performance measurement should ensure a clear allocation of responsibilities
and communicate which KPIs are necessary. Furthermore, definitive determinations have to
be made on how detailed, accurate, and actual the data is needed. Finally, the organization has
to offer an adequate information system infrastructure for internal and external data exchange
to their staff. These findings will be considered in the following chapters focusing on relevant
KPIs and their systematization in the PMS designed in chapter 4. The general requirements
will be completed in the following chapter, where specific requirements for performance
1334

measurement within the field of humanitarian logistics will be presented by considering
specific objectives of relief organizations.
3.2. RELEVANT KPIS
In the following, the results of initial works (mainly Davidson 2006; Beamon and Balcik
2008; van der Laan et al. 2009; Schulz and Heigh 2009; VDI 4400 2001, 2002) were used as a
set of generic and specific KPIs. They were reflected by the identified specifications and aims
of humanitarian supply chains as well as requirements and restrictions discussed in previous
chapters. The selection criteria are oriented mainly on end user requirements. Thus, an
appreciation of the KPIs measured by both management and operational personnel is forced.
This can only be realized by highlighting the main objectives of relief operations. The
objectives presented in the following were deduced by the definition and characteristics of
humanitarian logistics provided in the beginning and related to selected KPIs. .
Table 3: Identified KPI for humanitarian logistics ([1] e.g. Beamon 2004, [2] e.g. Bölsche
2009, [3] van der Laan et al. 2009, [4] Tomasini and Wassenhove 2009, [5] Tufinkgi 2006,
[6] Davidson 2006, [7] Samii 2008, [8] Blecken 2010, [9] Beamon and Balcik 2008, [10] VDI
4400 2001, [11] VDI 4400 2002, [12] Erdmann 2003)
Objective KPIs
Responsiveness/
Speed [1]
Minimum response time [9]
Percentage of products that were delivered within promised lead time [3]
Delivery date reliability [10], [11]
Donation-to-delivery Time [6]
Achievement
of Objectives [2]
Realised service level [3]
Degree of service [11]
Beneficiary's and
Donors Satisfaction [3]
Confirmation rate of customer's desired delivery date [11]
Complaint rate [11]
Reliability [4]
Delivery date reliability [10], [11]
Delivery reliability [10], [11]
Complaint rate [11]
Flexibility [5]
Number of individual units of Tier 1 supplies that an organization can provide in time
periode Tc [9]
Mix of different types of supplies that the relief chain can provide in a specified time
period [9]
Number of individual units of Tier 1 supplies that an organization can provide in time
period Tc [9]
Inventory
Performance [3]
Accuracy of stock records [3]
Stock efficacy [3]
Mean costs per incoming goods item [10]
Mean quality inspection costs per incoming goods item [10]
Evaluated turnover rate [10]
Bottleneck
Management [6]
Delivery quality reliability (Procurement) [10]
Delivery quantity reliability (Procurement) [10]
Delivery date reliability (Procurement) [10]
Cooperation [7]
Framework agreement quota [10]
Number of suppliers/logistic service providers [10]
Number of externally sources articles [10]
Information exchange quota [12]
Costs Efficiency [8]
Total cost (of resources used) [9]
Total Cost of distribution (including transportation and handling cost) [9]
Inventory investment (the investment value of held inventory) [9]
Inventory obsolescence (and spoilage) [9]
1335

Order/setup costs [9]
Inventory holding costs [9]
Cost of Supplies [9]
Number of relief workers employed per aid recipient [9]
Number of "value added" hours (the number of direct hours spent on dispending aid per
total number labour hours) [9]
Dollars spent per aid recipient [9]
Donor dollars received per time period [9]
Evaluated turnover rate (distribution) [11]
Mean costs for distribution activities per order-picking item [11]
Mean costs of transport per goods consignment [11]
Standardization [8] Degree of standardization [2]
Innovation [7]
Degree of investments in trainings [own acc. to 7]
Degree of investments in information systems [7]
Quota of supported processes by information systems [7]
For each description see the referenced literature. The relations made between objectives and
logistics KPIs support the recognition of the importance of performance measurement and
SCM involved in humanitarian operations. In combination with adequate SCM tools
supporting the data collection, the three mentioned conditions shall be fulfilled. The KPIs
identified represent a first prioritized set of relevant KPIs. It may be understood as an open
set, which should be corrected and complemented in further research, especially based on
application and evaluation of the PMS. As noticed, e.g. on the website of Humanitarian
Logistics Association (HLA), there also are several KPIs already in use by different
organizations, but not documented in the literature (HLA 2011). Therefore, a continuous
monitoring of the set and the changing requirements seems to be necessary.
3.3. SUITABLE PMS
As discussed in chapter 2.4 Keller and Hellingrath (2007) and Keller (2009) identified
relevant PMS for SCM. In the following, the mentioned concepts are shortly reviewed in the
following order: Hieber (2002)-, Kirchhausen (2004)-, DynaMoZ (2004)-, Beamon (1999)-
and the Balanced Scorecard- (Brewer and Speh 2000; Stölzle et al. 2001; Weber et al. 2002;
Jehle 2002) approaches. Hieber (2002) proposes to measure the performance by using the
SCOR KPIs. Although this concept seems beneficial for the commercial sector using the
broad and established SCORE KPIs collection, it is disadvantageous for the humanitarian
sector, caused by a high degree of complexity and a rigid character of the processes involved.
Kirchhausen (2004) presents an indicator-based approach for management support in field of
production and logistics. With its strong focus on resource utilization, the production side, and
intra-organizational processes it seems not to be transferable in the field of humanitarian
logistics, where production plays a subordinate and inter-organizational processes an
important role. The DynaMoZ (2004) could be interesting for evaluating the procurement side
of humanitarian organizations, but seems to be more suitable in commercial supply chains.
Based on the fact that humanitarian organizations mainly deliver from high stocks in order to
be capable of rapid deployment, the procurement agility has limited validity. Additionally, the
particularly important distribution side of humanitarian organizations within relief operations
is neglected in the DynaMoZ approach. The approach by Beamon (1999) focuses at the
measurement of flexibility within logistics processes, including volume-, delivery-, mix-, and
innovation-flexibility. The transferability and adaptability of this approach to humanitarian
supply chains was already discussed by Beamon (2004) and Beamon and Balcik (2008) as a
promising PMS framework. By the development of specific performance metrics for
1336

humanitarian relief chains “[T]he proposed performance measurement framework can be
used as a basis for performance measurement system in the relief sector” (Beamon and
Balcik 2008). It can be stated that, referred to the identified requirements for performance
measurement of humanitarian supply chains, a few necessary perspectives are missing in the
framework by now, e.g. innovation, standardization, cooperation or beneficiary's and donors
satisfaction.
Finally, various Balanced Scorecard (BSC) approaches were identified as suitable PMS
(Brewer and Speh 2000; Stölzle et al. 2001; Weber et al. 2002; Jehle 2002, Zimmermann
2003). Regularly, BSC approaches consist of four different perspectives: the customer,
process, innovation and growth as well as financial perspectives (e.g. Stölzle et al. 2001).
Here, adequate KPIs wanted for monitoring or available by existing data collection options,
may be flexibly integrated. The KPIs used may be a mix of financial and non-financial
metrics as well as a reflection of organization-specific objectives. Also, the perspectives may
vary, as e.g. Weber et al. (2002) presented a cooperation-oriented BSC-approach. Here, the
customer- as well as the innovation and growth perspectives were replaced by the
perspectives on cooperation quality and intensity. As Zimmermann (2003) showed, it is not
necessary to vary the classical BSC perspectives in order to develop a supply chain BSC, but
that it is possible to integrate additional perspectives. Jehle (2002) e.g. presented a network-
BSC by designing market-, cooperation-, process-, resource-, and success-perspectives and
integrated five independent supply chain controlling elements into the BSC designed. The
BSC approaches enable a flexible and adjustable PMS in order to select specific perspectives
and adequate KPIs, as needed by the organizational alignment. As Keller (2009) concludes,
inter-corporate BSC approaches offer a low application complexity and a high degree of
application flexibility. By these findings a BSC approach for performance measurement of
humanitarian organizations seems suitable and promising. The only restrictive points may be
seen in the importance for data collection and restricted IT-infrastructure, which has to be
seen as critical in the humanitarian sector.
Although the classical BSC approach was developed for the commercial sector, practical
examples illustrate its applicability in the humanitarian sector. Samii (2008) e.g. provides a
BSC for humanitarian BSC including the beneficiary (instead of customer), internal, financial
as well as the innovation and growth perspective with predefined goals and KPIs (14 in sum).
On the one hand, this application supports the estimation of the applicability of BSC as a
PMS for humanitarian logistics. On the other hand, two critical aspects should be noted: first,
Samii integrates the supply chain elements within the innovation and growth perspective,
which may neglect the importance of inter-organizational structures and processes; secondly,
a fixed KPI set may be not enough to address the varying organizational specifications and the
acceptance of a BSC application. Besides, Schulz and Heigh (2009) have presented the
development, design and execution of a specific BSC as PMS for the Logistics and Resource
Mobilization Department of the IFRC. Schulz and Heigh (2009) summarize that “[T]hese
insights are only a cut-out of a solution developed for the specific context of one
humanitarian organization”. Actually, important key success factors were also concluded,
whereupon the PMS/tool users have to be involved in its development, the PMS should early
be transferred to the organization, and necessary trainings have to be offered already at an
early stage (Schulz and Heigh 2009). In combination with forcing a common agreement of all
personnel involved (e.g. by communicating the importance of the PMS in meetings), the
acceptance and understanding of the tool and the indicators are ensured, which is of crucial
importance for a durable operation of the PMS installed. Otherwise, the management takes
risks of inadequate assistance by its personnel in dealing with all tasks (e.g. input data
collection) involved by the PMS. In results, the BSC designed is structured like Samii’s
1337

solution, so the restrictive aspects mentioned above apply also here: a general KPI set is
missing and the importance of SCM may be neglected. De Leeuw (2010) presented a general
mission map in order to provide a basis for organization-specific development of a BSC
approach without offering a set of KPIs. Here, the general relevance of the BSC’s
perspectives was emphasized by four hypothetical mini cases on the customer, internal,
learning and growth as well as the financial perspectives (de Leeuw 2010). Thus, a general
application could be justified. As a result the reference mission map according to the BSC
application sets reference points to each perspective as follows:
 customer perspective: (1) product and service attributes; (2) customer relationships, (3)
image
 internal perspective: (1) operations management; (2) donor management; (3) partner
management; (4) innovation; (5) regulatory and social
 learning and growth perspective: (1) human capital; (2) information capital; (3)
organizational capital
 financial perspective: (1) budgeting; (2) funding management; (3) cost management (de
Leeuw 2010).
These reference points are beneficial to structure the objectives and the according KPIs
identified in chapter 3.2. Unfortunately, no adjustments of the BSC design were made
respecting the specific application area of humanitarian organizations. As already mentioned
in the context of the results by Samii (2008) and Schulz and Heigh (2009), the design of a
BSC for humanitarian logistics should be reconsidered in order to emphasize the importance
of SCM. These practical experiences strengthen the decision of the identification of a supply
chain BSC as a PMS for humanitarian organizations. In summary, the following criteria can
be highlighted for the decision of a BSC: (1) multi-level assessment model; (2) high
application flexibility; (3) low application complexity; (4) mix of financial and non-financial
metrics. Based on these findings, in the next chapter a general and supply chain oriented BSC
for the application in the field of humanitarian logistics will be developed.
4. DEVELOPMENT OF A PMS FOR HUMANITARIAN LOGISTICS
The results generated by the comprehensive literature analysis and target/actual comparison in
section 3 form the basis for the design of an adequate PMS for humanitarian logistics. The
junction of the compiled set of adequate KPIs and the evaluation of suitable PMS, a supply
chain BSC will be proposed as a promising PMS for the domain of humanitarian logistics.
The supply chain BSC designed offers to fulfill the requirements for performance
measurement of humanitarian logistics. The chosen supply chain BSC is reusable and allows
an organization-specific configuration of the KPIs. Thus, the adaptability of the PMS
proposed is ensured by the provided set of KPIs, which can be extended on demand.
Furthermore, the perspectives chosen are not fixed and can be adapted if necessary.
Additionally, the specific demand of humanitarian organizations is ensured (e.g. objective-
orientation, low complexity and application flexibility). The objective-oriented selection of
KPIs identified above and its integration in the BSC offers low complexity of performance
measurement. The flexibility of BSC enables the consideration of different objectives of the
relief organizations. Referring to the conditions identified by van der Laan et al. (2009), the
importance of SCM in humanitarian supply chains is enabled by adding the network
perspective into the BSC construction. The supply chain BSC framework in combination of
1338

the identified objectives and general reference points by de Leeuw (2010) are illustrated in the
following table.
Table 4: Objectives and Reference Points of the Supply Chain BSC for Humanitarian
Logistics
Objectives Reference Points
Beneficiary
Perspective
 Responsiveness/Speed
 Achievement of Objectives
 Beneficiary's and Donors Satisfaction
(as both usually directly correlate)

Product and Service Attributes
 Image
Process
Perspective
 Reliability
 Flexibility
 Inventory Performance
 Bottleneck Management
 Standardization

Operations Management
 Regulatory and Social
Learning
and Growth
Perspective
 Innovation

Human Capital
 Information Capital
 Innovation
 Organizational Capital
Network
Perspective
 Cooperation

Customer Relationships
 Donor Management
 Partner Management
Financial
Perspective
 Cost Efficiency

Budgeting
 Funding Management
 Cost Management
For explanations of each objective, reference point and corresponding KPI see chapter 3.2. It
should be noted, that the beneficiary’s and donors satisfaction in the beneficiary perspective
were pooled, as they are correlated regulary (e.g. the adequate delivery date of health care
goods confirms the donations investments). Based on this overview of objectives and
reference points assigned in each perspective two benefits for applying organizations are
enabled: (1) recourse on the KPI set presented in chapter 3.2 and (2) the identification of data
sources by considering the reference points. It has to be mentioned, that the relations between
objectives, KPIs and the reference points may be overlapping on some parts. This aspect
should be examined by constructing different use cases. In order to not overload the scope of
this work, it has to be renounced to develop an exemplary BSC. In the context of development
procedures see Schulz and Heigh (2009).
5. APPLICATION, CONCLUSION AND OUTLOOK
The contribution of the paper was the development of an adequate PMS framework including
a KPI set, which forms a basis for its application in various humanitarian organizations. The
literature review enabled first conclusions for the application and adjustment of existing PMS
considering the characteristics and requirements of humanitarian logistics. The supply chain
BSC including the cooperation perspective was identified as a promising PMS for
humanitarian logistics.
It has to be stated, that the intermediate findings are conceptual at this stage. An application
and evaluation of the KPIs and the supply chain BSC for humanitarian logistics identified in
this work are necessary in order to validate the results. Additionally, adequate reference
1339

processes are needed in order to assign the KPIs to specific process steps and to identify
relevant measurement points. Finally, a description of procedures of developing organization-
specific supply chain BSC is missing.
Therefore, the first steps of future works are seen in the application of the supply chain BSC
in order to tackle its empirical evaluation. Additionally, the assumptions made in the context
of the restrictions for performance measurement of humanitarian logistics and data collection
have to be investigated within the test cases. Simultaneously, requirements for information
systems for humanitarian logistics should be deduced. These results have to be consolidated
and considered within the supply chain BSC for humanitarian logistics presented in this work.
REFERENCES
Beamon, B. M. (1999), “Measuring Supply Chain Performance”, International Journal of
Operations and Production Management, Vol. 19, No. 3, pp. 275-292.
Beamon, B. M. (2004), “Humanitarian Relief Chain: Issues and Challenges”, paper presented
at the 34th International Conference on Computers and Industrial Engineering, 13.-16.
November 2004, San Franciso.
Beamon, B. M., Balcik, B. (2008), “Performance Measurement in Humanitarian Relief
Chains”, International Journal of Public Sector Management, Vol. 21, No. 1, pp. 4-25.
Blecken, A. (2010), Humanitarian Logistics: Modelling Supply Chain Processes of
Humanitarian Organisations, Haupt Verlag, Bern et al.
Blecken, A., Hellingrath, B. (2008), “Supply Chain Management Software for Humanitarian
Operations: Review and Assessment of Current Tools”, in Fiedrich, F., van de Walle, B (eds),
Proceedings of the 5th International ISCRAM Conference, 5.-7. May 2008, Washington/USA,
pp. 342-351.
Blecken, A., Hellingrath, B., Dangelmaier, D., Schulz, S. F. (2009), “A Humanitarian Supply
Chain Process Reference Model”, International Journal of Services Technology, Vol. 12,
No.4, pp. 391 - 413.
Bölsche, D. (2009), Internationales Katastrophenmanagement: Logistik und Supply Chain
Management, Nomos, Baden-Baden.
Brito, M. P. de, van der Laan, E. A., Vergunst, D. A. (2007), “Humanitarian Organisations
and Performance Measurement”, in Tatham, P. (Ed.), CD-ROM Proceedings of the 1st
International Cardiff/Cranfield Humanitarian Logistics Symposium in Faringdon, UK, 2007.
Bürkler, A. (1977), Kennzahlensysteme als Führungsinstrument. Ein Lösungsvorschlag für
den gewerblichen Detailhandel in der Schweiz, Schulthess, Zurich.
Chandraprakaikul, W. (2010), “Humanitarian Supply Chain Management: Literature Review
and Future Research”, paper presented at 2nd International Conference on Logistics and
Transport, Queenstown/NZ, 16-18 December, available at:
http://preet.sesolution.com/iclt2010/Full%20Papers/Logistics%20and%20Supply%20Chain%
20Management/0308-Watcharavee.pdf (accessed 11 February 2010).
Charles, A., Lauras, M., Tomasini, R. (2009), “Learning from previous humanitarian
operations, a Business Process Reengineering approach”, paper presented at 6th International
ISCRAM Conference, 10-13 May, Gothenburg/Sweden, available at:
http://www.iscram.org/ISCRAM2009/papers/Contributions/142_Learning%20from%20previ
ous%20humanitarian%20operations_Lauras2009.pdf (accessed 20 June 2010).
CSCMP – Council on Supply Chain Management Professionals (2011), “Supply Chain
Management and Logistics Management Definitions”, available at:
http://cscmp.org/aboutcscmp/definitions/definitions.asp (accessed 10 February 2011).
1340

CRED – Centre for Research on the Epidemiology of Disasters (2011) “2010 Disasters in
Numbers”, available at: http://cred.be/sites/default/files/PressConference2010.pdf (accessed
25 January 2011)
Davidson, A. L. (2006), Key Performance Indicators in Humanitarian Logistics, Master
Thesis, Massachusetts Institute of Technology, Boston.
de Leeuw, S. (2010), “Towards a Reference Mission Map for Performance Measurement in
Humanitarian Supply Chains”, in Camarinha-Matos, L. M., Boucher, X., Afsarmanesh, H.
(Eds.) Collaborative Networks for a Sustainable World, Proceeding of the 11th IFIP WG 5.5
Working Conference on Virtual Enterprises, France, 2010, Springer-Verlag, St. Etienne,
pp.181-188.
Erdmann, M.-K. (2003), Supply Chain Performance Measurement: Operative und strategische
Management- und Controlling-Ansätze, Josef Eul, Köln.
Germany’ Relief Coalition (2011), “Short Review of the Year 2010” (own translation),
available at: http://www.aktion-deutschland-hilft.de/de/pressecenter/weitere-artikel/kurzer-
jahresrueckblick-2010-haiti-chile-pakistan/ (accessed 10 January 2011)
Hieber, R. (2002), Supply Chain Management – A Collaborative Performance Measurement
Approach, vdf, Zurich.
Howden, M. (2009), “How Humanitarian Logistics Information Systems Can Improve
Humanitarian Supply Chains: A View from the Field”, paper presented at 6th International
ISCRAM Conference, 10-13 May, Gothenburg/Sweden, available at:
http://www.iscram.org/ISCRAM2009/papers/Contributions/142_Learning%20from%20previ
ous%20humanitarian%20operations_Lauras2009.pdf (accessed 20 June 2010).
HLA - Humanitarian Logistics Association (2011), “Log-Forum: Key Performance Indicators
(KPI) and quality”, available at: http://www.humanitarianlogistics.org/log-
forum/certification/821010198 (accessed 14 January 2011).
Jahre, M., Jensen, L.-M., Listou, T. (2009), “Theory Development in Humanitarian Logistics:
a Framework and Three Cases, Management”, Research News, Vol. 32, No. 11, pp.1008-1023
Jehle, E., Stüllenberg, F., Schulze im Hove, A. (2002), “Netzwerk-Balanced Scorecard als
Instrument des Supply Chain Controlling”, Supply Chain Management, Vol. 4, pp. 19-25.
Keller, M (2009), Kennzahlenbasierte Wirtschaftlichkeitsbewertung der Integration von
Unternehmen in Produktions- und Logistiknetzwerken, Dissertation, Technische Universität
Dortmund, Dortmund.
Keller, M., Hellingrath, B. (2007), „Kennzahlenbasierte Wirtschaftlichkeitsbewertung in
Produktions- und Logistiknetzwerken“, in Otto, A., Obermaier, R. (Eds),
Logistikmanagement: Analyse, Bewertung und Gestaltung logistischer Systeme, Gabler,
Wiesbaden, pp. 51-76.
Kirchhausen, P. (2004), Konzeption eines kennzahlenbasierten Ansatzes zur Unterstützung
des Managements von Produktion und Logistik, Verlag Praxiswissen, Dortmund.
Long, D. C., Wood, D. F. (1995), “The Logistics of Famine Relief”, Journal of Business
Logistics, Vol. 16, No. 1, pp. 213-229.
Majewski, B., Navangul, K. A., Heigh, I. (2010), “A Peek into the Future of Humanitarian
Logistics: Forewarned is Forearmed”, Supply Chain Forum, Vol. 11, No. 3, pp. 4-19.
McGuire, G. A. (2006), Development of a Supply Chain Management Framework for Health
Care Goods Provided as Humanitarian assistance in Complex Political Emergencies, PhD
Thesis, Wirtschaftsuniversität Wien, Vienna.
Preißler, P. R. (2008), Betriebswirtschaftliche Kennzahlen: Formeln, Aussagekraft, Sollwerte,
Ermittlungsintervalle, Oldenbourg Wissenschaftsverlag, Munich.
1341

Reichmann, T. (1990), Controlling mit Kennzahlen: Grundlagen einer systemgestützten
Controlling-Konzeption, Vahlen, Munich.
Rongier, C., Gourc, D., Lauras, M., Galasso, F. (2010), “Towards a Performance
Measurement System to Control Disaster Response”, in Camarinha-Matos, L. M., Boucher,
X., Afsarmanesh, H. (Eds.) Collaborative Networks for a Sustainable World, Proceeding of
the 11th IFIP WG 5.5 Working Conference on Virtual Enterprises, France, 2010, Springer-
Verlag, St. Etienne, pp.189-196.
Samii, R. (2008), Leveraging Logistics Partnerships, Lessons from Humanitarian
Organizations, ERIM, Rotterdam.
Schulte, C. (2009), Logistik: Wege zur Optimierung der Supply Chain, Vahlen, Munich.
Schulz, S. (2009), Disaster Relief Logistics: Benefits of and Impediments to Cooperation
between Humanitarian Organizations, Haupt Verlag, Bern et al.
Schulz, S. F., Heigh, I. (2009), “Logistics Performance Management in Action: Design and
Piloting of a "Development Indicator Tool" for Regional Logistics Units of IFRC”, in
Tatham, P. (Ed.), CD-ROM Proceedings of the 1st International Cardiff/Cranfield
Humanitarian Logistics Symposium in Faringdon, UK, 2007.
Speh, T. W., Brewer. P. C (2000), “Using the Balanced Scorecard to Measure Supply Chain
Performance”, Journal of Business Logistics, Vol. 21, No. 1, pp. 75-93.
Stadtler, H., Kilger C. (2008), Supply Chain Management and Advanced Planning: Concepts,
Models, Software, and Case Studies, Springer-Verlag, Berlin et al.
Stölzle, W., Heusler, K. F., Karrer, M. (2001), „Die Integration der Balanced Scorecard in das
Supply Chain Management-Konzept (BSCM)“, Logistik Management, Vol. 2-3, No. 3,
pp. 73-85.
Swiss Reinsurance Company (2009), Natural Catastrophes and Man-made Disasters in 2008:
North America and Asia Suffer Heavy Losses, Swiss Reinsurance Company Ltd., Zurich.
Thomas, A. S., Kopczak, L. R. (2005), “From Logistics to Supply Chain Management: The
path forward in the humanitarian sector”, available at:
http://www.fritzinstitute.org/PDFs/WhitePaper/Fromlogisticsto.pdf (accessed 20 June 2010).
Tomasini, R., van Wassenhove, L. (2009), Humanitarian Logistics, Palgrave MacMillan,
Basingstoke.
Tufinkgi, P. (2006), Logistik im Kontext internationaler Katastrophenhilfe: Entwicklung eines
logistischen Referenzmodells für Katastrophenfälle, Haupt Verlag, Bern et al.
Van der Laan, E. A., de Brito, M. P., Vergunst, D. A. (2009), “Performance measurement in
Humanitarian Supply Chains”, International Journal Risk Assessment and Management,
Vol. 13, No. 1, pp. 22-45.
Van Wassenhove, L. (2006), “Blackett Memorial Lecture, Humanitarian Ais Logistics:
Supply Chain Management in High Gear”, Journal of the Operational Research Society, Vol.
57, pp. 475-589.
Verein Deutscher Ingenieure (VDI) (2001), VDI 4400 Logistic Indicator for Procurement,
VDI-Guidelines, Part 1, Verein Deutscher Ingenieure, Düsseldorf.
Verein Deutscher Ingenieure (VDI) (2002), VDI 4400 Logistic Indicator for Distribution,
VDI-Guidelines, Part 3, Verein Deutscher Ingenieure, Düsseldorf.
Weber, J., Bacher, A., Groll, M. (2002), „Konzeption einer Balanced Scorecard für das
Controlling von unternehmensübergreifenden Supply Chains“, krp – Kostenrechnungspraxis,
Vol. 46, No. 3, pp. 133-141.
Zimmermann, K. (2003), Supply Chain Balanced Scorecard, Unternehmensübergreifendes
Management von Wertschöpfungsketten, Deutscher Universitätsverlag, Wiesbaden.
1342