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A QUANTITATIVE STUDY INTO THE BOTTLENECKS WITHIN LAST MILE
DISTRIBUTION IN HUMANITARIAN LOGISTICS: A CASE ON ZIMBABWE
Name: Tinotenda R Gova
Student Number: 1044676
Degree Course Title: BSc (Hons) International Business
Department: Business School
Supervisor’s Name: Emel Aktas
Submission Date: 6th March 2014
Word Count: 8,309
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Abstract
This paper aims to identify the bottlenecks found within Last Mile Distribution,
with regard to aid organizations in Zimbabwe. The objectives were constructed
in order to: determine whether the bottlenecks identified had an impact on last
mile distribution operations and its impact on performance, and to illustrate how
these issues can be overcome so as to improve performance levels in aid
organization in Zimbabwe.
Secondary research was derived from numerous sources to aid in gaining a
clear comprehension of the topic so as to develop an appropriate research
approach. A survey was the chosen method to gather data, through a self-
completion questionnaire from 42 participants working within the humanitarian
supply chain from aid organizations in Zimbabwe. Primary quantitative data was
gathered and analysed using SPSS. Descriptive statistics were used to deduce
results pertaining to frequency in response and regression analysis was used in
determining the relationship between variables.
Results derived from the study suggest that the three bottlenecks, transport
resources, infrastructural degradation and financial limitations, all have a
positive relationship with last mile distribution. Results further go on to suggest
that last mile distribution has an impact on the performance levels of project and
relief execution in Zimbabwe. They further go on to suggest a need for
managers to create performance matrices for their organizations.
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Acknowledgement
Firstly I would like to thank the Almighty God for guiding and seeing me through
the duration of this project. I would like to thank my supervisor Dr Emel Aktas
for imparting her knowledge, support, time and guidance. Her guidance and
advice kept me motivated and guided in the right direction to complete my
project.
I would also like to thank my parents, family and friends for the motivation,
inspiration, prayers during the past few months. Their support, commitment and
understanding have kept me going.
Finally, I would like to thank the participants who took part in contributing to this
research. Without their input this project would not have been possible.
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CONTENTS
Chapter 1: Introduction........................................................................................8
1.1 Research Background................................................................................8
1.2 Industry background...................................................................................9
1.3 Rationale of Project....................................................................................9
1.4 Research Aim...........................................................................................10
1.5 Research Objectives................................................................................10
1.6 Research Structure..................................................................................10
Chapter 2: Literature Review.............................................................................13
2.1 Introduction..............................................................................................13
2.2 Logistics...................................................................................................13
2.3 Last Mile Distribution (LMD).....................................................................14
2.4 Bottlenecks in Last Mile Distribution........................................................16
2.4.1Transport and Infrastructural problems..................................................18
2.4.2 Financial Limitations..............................................................................19
2.4.3 Performance..........................................................................................20
2.5 Conceptual Framework and Hypothesis..................................................21
2.6 Summary of Literature Review.................................................................22
Chapter 3: Research Methodology....................................................................25
3.1 Introduction..............................................................................................25
3.2 Research Philosophy...............................................................................25
3.3 Research Approach.................................................................................25
3.4 Research Strategies.................................................................................26
3.4.1 Self-completion Questionnaires............................................................26
3.4.2 Alternative methods..............................................................................26
3.4.3 Justification...........................................................................................27
3.5 Sampling Method.....................................................................................27
3.6 Validity and Reliability..............................................................................28
3.7 Data Collection.........................................................................................28
3.8 Data Analysis...........................................................................................29
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3.9 Pilot Test..................................................................................................29
3.10 Research Ethics.....................................................................................30
3.11 Research Limitations..............................................................................30
3.12 Chapter Summary..................................................................................31
Chapter 4: Findings and Analysis......................................................................32
4.1 Introduction..............................................................................................32
4.2 Data Inconsistencies................................................................................32
4.3 Demographics..........................................................................................32
4.3.1 Gender..................................................................................................32
4.3.2 Occupation............................................................................................33
4.4 Reliability test...........................................................................................34
4.5 Regression analysis.................................................................................35
4.5.1 Transport Resources and Infrastructural degradation...........................36
4.5.2 Financial limitations...............................................................................37
4.5.3 Last Mile Distribution.............................................................................37
4.5.6 Performance..........................................................................................38
4.7 Summary..................................................................................................38
Chapter 5: Analysis and Discussion..................................................................40
5.1 Introduction..............................................................................................40
5.2 Transport and Infrastructural Degradation...............................................40
5.3 Financial Limitations.................................................................................41
5.4 Last Mile Distribution and Performance...................................................42
5.5 Summary..................................................................................................42
Chapter 6: Conclusions and Recommendations...............................................43
6.1 Introduction..............................................................................................43
6.2 Future Research......................................................................................44
Bibliography.......................................................................................................45
Appendices........................................................................................................49
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Appendix 1: Queationnaire …………………………………………………………52Appendix 2: Participant Information Sheet ………………………………………..53
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CHAPTER 1: INTRODUCTION
1.1 RESEARCH BACKGROUND
“The purpose of a humanitarian supply chain is to rapidly provide appropriate
supplies … so as to minimize human suffering.” (Balick, et al., 2008). Supply
chains must be fast and agile, responding rapidly to disasters, which occur in
any location, at any given time (Mbowha, 2006). Therefore, logistics is a very
important aspect of any supply chain, as it is involved at every possible stage in
any supply chain process. Logistics, however, has many different activities
within it, ranging from distribution, warehousing and Last Mile Distribution (LMD)
(Kovacs, 2009). However, within these processes or activities, there are some
underlying factors that can forge either a positive or negative impact on
performance levels (Balick, et al., 2008). Several authors in the past have
attempted to research into identifying bottlenecks affecting Last Mile Distribution
in many geographical areas (Balick, et al., 2008, Barabasoglu, 2002, Crainic,
1997, Roy, et al., 2012), but none have attempted to focus their research on
less economically developed countries, such as Zimbabwe, so as to try and
minimize challenges.
In the works of Balick et al. (2008) and Roy et al. (2012) it is evident that Last
Mile Distribution is an area that faces numerous challenges or rather, is affected
by factors that then affect performance. Their works however, concentrated on
issues of transport resources, planning and scheduling stating that “… main
operational decisions related to last mile distribution are relief supply allocation,
vehicle delivery, scheduling and routing.”, whilst other authors omitted these
factors and focused on areas of performance measurements and rapid
responsiveness (Barabasoglu, 2002). All authors hold one thing in common;
that being, their focus is mainly on the humanitarian sector meaning they focus
on international aid organizations or supranational organizations, such as CARE
International, GHM and UNICEF. Their results show that the same issues,
factors or bottlenecks affect numerous areas, some with specific mention to
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areas such the Philippines and India. No papers on areas such as Southern
Africa or African regions seem to have been studied as a specific location.
Some research stated that non-profit or non-governmental organizations make
distribution decisions using jury-rigged methods, which as a result may lead to
inefficient and ineffective results and performance levels (Balick, et al., 2008).
Last mile distribution is the last stage of the relief supply chain in aid
organizations, and is considered to be of grave importance (Kovacs, 2009).
1.2 INDUSTRY BACKGROUND
NGOs, as they are commonly known, are non-governmental organizations
aimed at providing services ranging from developmental and social services to
health, nutrition and sustainability of the populations. They are categorised as
being part of the humanitarian sector and are comprised of organizations such
as the Red Cross, and the United Nations (UNICEF Zimbabwe, 2011).
The humanitarian aid industry in Zimbabwe, as is the proposed case in this
study, has expanded over the years, from at first only having hosted national
and local charities or non-governmental organizations such as Zimbabwe Aid
Fund to now hosting organizations such as UNICEF, WFP, Oxfam and
numerous more. A common trait amongst these organizations is that of
distribution. They are focused on development and relief programmes, and all
have logistics operations within their working systems. However, as there are
numerous issues, their performances are not always at the recommended or
desired levels due to some constraints in their last mile distribution activities
(WFP, 2006).
1.3 RATIONALE OF PROJECT
As humanitarian aid agencies live from grant to grant and project to project,
there is little to no room for sufficient development, as both funding cycles and
planning cycles are unpredictable (Mbowha, 2006). That being said, strategic
Logistics functions, such as LMD, within an aid organisation is one that is
permanently needed for the functionality and execution of projects across the
many different sections (Balick, et al., 2008). In recent years, there have been
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issues affecting the effectiveness, performance, and execution process of
projects (Barabasoglu, 2002). Natural or man-made situations, in a developing
country, give the purpose of carrying out such a project in examining
bottlenecks in LMD in humanitarian aid agencies in Zimbabwe, looking at
different approaches used in previous studies, to create a more diverse and
effective means of execution and performance management.
Past research identified bottlenecks such as transport and vehicle sourcing and
operational decisions (Balick & Beamon, 2008), but had no specific country or
location directed at it. Thus, this study will seek to examine whether some of the
factors identified by past research can be applied to locations such as
Zimbabwe, and investigate into how they can be overcome.
1.4 RESEARCH AIM
This project aims to investigate and identify the bottlenecks within Last Mile
Distribution in the humanitarian supply chain, and to explore what impact last
mile distribution has on performance, relating to a case on Zimbabwe.
1.5 RESEARCH OBJECTIVES
The project seeks to meet the following objectives:
1. To identify bottlenecks within LMD operations that affects the level of
performance. And in order to answer this, the following questions will be
explored:
What bottlenecks affect Last Mile Distribution?
Does LMD have an impact on performance?
2. To make recommendations on ways to improve the performance of LMD
for aid organisations in Zimbabwe
1.6 RESEARCH STRUCTURE
The research is structured in chapters, all specifically allocated. Figure 1 below
illustrates and gives a brief background of every chapter and its contents.
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FIGURE 1: CHAPTER SYNOPSIS
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CHAPTER 2: LITERATURE REVIEW
2.1 INTRODUCTION
This chapter will present and explore existing literature on the constituents of
Logistics and LMD. I will be assessing arguments and criticisms into the views
of LMD in different humanitarian areas, with the main focus area being
Zimbabwe. Works will be presented, from prominent authors and academics
that have undertaken and written in-depth studies from previous and recent
years. I will look at case studies which I will relate to international aid
organizations in order to elicit a clear comprehension.
2.2 LOGISTICS
“Logistics is a process of strategically managing acquisition, movement and
storage of materials, parts and related information flow through the organization
and its marketing channels, to fulfil its tasks most cost effectively” (Mbowha,
2006). This statement is one term used to define what logistics is, but as it
appears, the term alone has different interpretations in context and meaning. A
general term for logistics would be: (However, within the same term are three
other variations of logistics), 1. Military logistics, which is the carrying out and
planning the maintenance and movement of forces, as well as those sectors of
the military that deal with development, design, distribution and movement,
amongst other functions (Deapartment of Defence, 2010); 2. Business logistics,
which is to create “place and time utility” in goods and products, making sure to
locate them at the right time, right place and in the correct quantities so as to
meet customer demand (Heyel, 1979).
Like in any operation in the supply chain, logistics has its own bottlenecks and
conflicting factors. In his book, Martin (1992, pp. 1-16) points out some
challenges faced, such as:
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- -Efficiency: inefficiencies cause for an increase in inventories and
logistics costs, resulting in higher than necessary costs for a given
service;
- Finances: the constant need for finances to carryout day-to-day activities
and distribution operations.
These problems are challenges for managers because poorly managed
logistics systems can produce a numerous number of problems, and as there is
no one set approach to tackling these, no one approach will work for every
organisation (Martin, 1992). It should not be dismissed that some of the above
issues are bottlenecks that fit into the humanitarian logistics framework.
2.3 LAST MILE DISTRIBUTION (LMD)
Last Mile Distribution (LMD) is a logistical feature of all sectors of logistics,
whether it is military, business or humanitarian logistics. In the case of this
research paper, it will be associated with humanitarian logistics, which is
described by Thomas and Mizushima (2005), as the process of planning,
implementing and controlling, efficiently, the cost-effective flow and storage of
goods and materials, as well as related information, from the point of origin to
the point of consumption for the purpose of meeting the requirements of the
end-user, the beneficiaries. A published report by USAID (2011) describes the
last mile as being the last stretch or distance to the point of delivery or retail
sale. It occurs or exists in conditions involving the physical movement of
products to a point wherein beneficiaries can access them. They go on to give a
specific distance of ten kilometres or ‘last mile’, which consequently means that
the distance is not a pre-determined one, but rather is determined by the
situation. The last mile is the most crucial element in in-country logistics, as it
determines the full delivery of products or goods. For instance, in the case of
delivering health commodities, sponsors or donors now take particular interest
in two processes within the supply chain. The first area of interest is that of
movement of goods from the supplier to the recipient and the second being the
main focus of their paper, from the LDP (Local Distribution Point) to the end-
user or beneficiary.
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Previous works have defined LMD as the final stage in any Supply Chain,
regardless of sector or industry. Put in laymen’s terms, LMD is the movement of
goods from the warehouse or storage facility of an organization to the end-user
or beneficiary. It is the ultimate, as well as crucial, stage of any supply chain as
it plays a huge and important role in both business and relief situations. It is
evident in both man-made and natural disaster situations, and plays a part of
making sure the necessary and required materials are moved from one point to
another in the most efficient and effective ways. Balick et al (2008, pp. 51-63)
defines LMD as the stage at the final points of a humanitarian or emergency
relief supply chain; it refers to the delivery of supplies from local distribution
centres (LDC) to the end-user, or in this case, beneficiaries.
However, they define it by coupling it with the decisions involved. They suggest
that LMD is the stage at which, taking into consideration the integration of
facility location, inventory management, transportation management and
distribution ideas, relief supplies from field warehouses are distributed to the
designated disaster areas, or areas with affected people. In addition to these
definitions, or rather detailed explanations, it should be considered that every
party involved in any form of logistics meets with LMD in distribution activities.
Accepting the given definitions, a consideration into the gravity of importance of
LMD in aid organisations should be highlighted. In the works of Balick et al.
there is stress on LMD in emergency relief activities, but the same importance
should be awarded to everyday projects, such as distribution projects of
educational materials or water sanitation resources, as a means to forming an
effective pattern regardless of LMD situation.
In order to have an effective LMD, there needs to be an effective flow of events
in the distribution plan. Agility and reliability are important factors in the last mile
process, and their presence can have a few benefits, such as, cost-cutting,
greater utilisation of products and greater control over errors (UNFPA, 2011).
To work effectively with agility and reliability, it involves the breakdown of larger
loads of products into smaller batches for delivery to numerous destinations, at
a greater frequency (USAID- Delivery Project, 2011). This then leads to the
discussion on how LMD, as mentioned previously, occurs in every form of
product movement or logistics. However, depending on the sector of business,
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the urgency and capacity at which it is carried out differs. Roy et al. (2012)
discuss a description of some differences between the humanitarian supply
chain and the business supply chain, as a way to differentiate between values
and the importance placed on LMD in each sector. The most outstanding
differences are:
- In the humanitarian chain, the end goal is to deliver what is needed to
ensure no loss of life, meaning an increased need in an efficient LMD
structure, whereas in the commercial chain (Oloruntoba, 2006), the
end goal is to generate profits, so planning can be carried out
depending in the urgency or value of goods;
- In humanitarian chains, there is a great risk and uncertainty, resulting
in extensive planning, needs assessments and structure, but in
commercial chains, the distribution is not uncertain and is normally
within known parameters or data.
These differences give a more concise look into how LMD is prioritised in
different sectors of business, but it should be noted that the importance of LMD
also depends on the products, time factors and situation in the respective areas.
Like in any activity and sector of business, there are challenges that can affect
the execution.
2.4 BOTTLENECKS IN LAST MILE DISTRIBUTION
It has been established that LMD is a crucial point in the supply chain,
particularly more so in the humanitarian chains. Humanitarian organisations
depend greatly on an effective and efficient supply chain, which in turn
guarantees an effective and efficient carrying out of a project or relief operation.
A previous statement, pointed out some factors that affect the LMD of relief
operations. Capacity of the infrastructure, availability and quantity of transport
assets in the country, politics of the situation, civil conflict in the area of
operations, and financial capabilities are factors affecting LMD within relief
operations (Roy, et al., 2012). These factors were based on Southern African
situations, but through further reading some of the same factors can be
identified in other regions of the world, mostly in Less Economically Developed
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Countries (LEDCs) such as India. Findings suggest that the intensity of natural
disasters highly affects the terrain of areas thus having a direct impact on the
available means of distribution resources (Barabasoglu, 2002). In LEDCs this is
a maddening factor because it limits the choices in transport resources, and
puts strain on the organizations involved. This results in issues with finances,
because certain allocations are pre-set for certain projects and unforeseen
bottlenecks such as, infrastructural problems, due to natural occurrences are
major bottlenecks. The factors are said to affect the supply chain process at the
tactical and operational levels, as well as strategic levels during the LMD
process, with particular regard to decision making (Roy, et al., 2012).
In humanitarian organisations, if a disaster is to occur, there is need for an
effective humanitarian logistics system with an agile LMD process, where the
factors listed below play a crucial role, and need to be kept at a high standard of
functionality. These factors are:
Facility location : identifying the most suitable place for inventory to be
kept or stored in the relief network (Jia H, 2005);
Inventory management : efficiently manage the inflow and outflow of the
relief materials (Melo, 2008);
Transportation decisions : to transport the relief to the needed area
(Kongsomsaksakul S, 2005);
Distribution decision : to quickly and efficiently distribute the relief
materials to the affected area and population.
Financial limitations : the scope at which the budget can sustain a project
or relief program.
The factors are often looked at individually, and treated independently in
literature; however unification between inventory management and facility
location decisions has been suggested to improve the supply chain, through a
reduction in associated costs and lower efficiencies of scale (Duran, et al.,
2007). This would suggest a possible advantage in any relief chain setting
(Balick, et al., 2008), but in the case of Zimbabwe, there is no evidence as to
whether this would be a suitable action.
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Roy et al, (2012) presents a framework with the aid of other authors’ works
(Balick et al (2008); Chopra & Meindl (2007); Zipkin (2000); Barbarosoglu &
Arda (2004)) on the effect of the four decisions illustrated above. Their research
into these factors all points to the importance of decision-making, performance,
and efficiency and effectiveness in the planning stages. Also, ensuring limited
challenges or eradicating any challenges within the last mile process requires
many operational and programmatic operations, such as making sure the staff
is adequately trained, having a capacity of resource mobilization and strategies
in coordinating the different parties involved in any activities of product
movement. In the following few sections, challenges identified in this section will
be drawn out and discussed with regard to aid organizations in Zimbabwe.
2.4.1 TRANSPORT AND INFRASTRUCTURAL PROBLEMS
Transportation and inventory decisions are integrated as a means to improving
decision making processes of the relief supply chain (Balick, et al., 2008), whilst
Crainic et al (1997) argues that transportation decisions have a direct effect on,
not only facility location and facility capacity, but also on inventory decisions at
the strategic level. Another argument is that transportation decisions also
directly affect activities at the distribution level, and especially at the crucial
stages of LMD (Sheu, 2007). Within all these arguments, the aspect of
infrastructure is not present, when in actual fact it goes hand in hand with
transport decisions.
Transportation is as an object of great weights, used to carry or move heavy
loads (Mohitpour, 2008), for examples school or classroom equipment. Quick
and efficient distribution is always a goal for relief supply chains, but this
depends on the number of available vehicles, accessibility to warehouses and
the efficiency of managing routing and scheduling processes (Melo, 2008), as
can be identified in the World Food Programme (WFP) in Zimbabwe. In the
report by USAID (USAID- Delivery Project, 2011) on Zimbabwe, the relationship
between transport resources and geographical infrastructure is suggested as
being an ever-occurring bottleneck in the LMD process. In line with this, Balick
et al. (2008) emphasis on this same relationship, suggesting it has a large
impact on the execution of activities. No lasting solutions have been identified or
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established as to how these can be overcome, because the terrain is degraded
by either high levels of rainfall or old unkempt roads or even in most cases, no
roads at all because of location and situation.
Transportation decisions and distribution decision need to be integrated in order
to have an effective, high performing and efficient transport system in the LMD.
In a project report by UNICEF Zimbabwe, transportation decisions were noted
as being influenced by distribution patterns and decisions, as well as around
infrastructural considerations. These factors were also noticed in other
organizations such as, USAID and WFP, and influenced or affected by the state
of the terrain in the areas of delivery.
Transport and Infrastructural problems serve as a bottleneck in the LMD
process of aid organizations in Zimbabwe, but with regard to infrastructure, the
WFP, in a report, suggested how the infrastructure in the country has
deteriorated over time due to the political and economic climate, and how roads
have not been competently maintained. In the same report they mention the
lack of adequate supplies of fuel in some areas of the country, which resulted in
problems within the LMD, with respect to fulfilling all targets by reaching certain
areas (WFP, 2006).
2.4.2 FINANCIAL LIMITATIONS
Money is a ‘need’ in the humanitarian sector, and the lack of its existence or
inappropriate distribution leads to a lack of activity and project development and
execution. In the case of Zimbabwe, LMD or logistical processes are somewhat
controlled by the availability of funds. Aid organizations work through financial
sources from international donors that equip them with the resources to
mobilise, source and execute projects or relief activities (Ludema, 2000).
Amongst these activities is LMD, which has already been established as being
an important process.
This has been identified as a bottleneck in Zimbabwe because for aid
organisations to be able to carry out LMD, including any logistical processes,
funds have to be sourced or delivered, first from the donors, then from the
respective sections in charge of the program. There are numerous aspects
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pertaining to sourcing funds, even from within an organization, which include
credit terms, payment schedules and consignment arrangements (Kleindorfer,
2004). An example would be that of the Education Transition Fund (ETF)
carried out by UNICEF Zimbabwe, based on delivering and distributing books
and learning materials to primary and secondary schools throughout Zimbabwe.
Bottlenecks were faced when unexpected occurrences transpired and the need
for more funds to source more distribution means arose. The main problem
here was that funds were to be sourced from the section implementing the
project, Basic Education and Gender Equality (BEGE), and because projects
are allocated specified amounts, plans to source funds need to be quickly
administered so as to ensure utmost levels of performance and effectiveness
(UNICEF, 2010). This serves as a bottleneck in that if funds are not properly
administered or if a system is not put in place for unexpected occurrences, the
effectiveness and performance of the LMD may be greatly affected.
2.4.3 PERFORMANCE
Like in any organisation, high performance levels are an objective. These are
determining factors towards the overall outcome of projects and activities
carried out in organizations. Performance is viewed as the process or action of
executing tasks, in an efficient manner (Folan & Browne, 2005). Organizations
use performance measurements in order to measure their effectiveness and
efficiency during and after the execution of projects, tasks or relief operations.
Performance measures are defined as a metric measure used to quantify the
efficiency and effectiveness of an action, in any setting of business and industry
(Neely, 2005). Within performance, efficiency and effectiveness are identified
and can be defined as, respectively, efficiency being the extent to which the
requirements of the customer are met, and effectiveness being the economic
measure of how resources are utilized, when given a level of effectiveness
(Folan & Browne, 2005). In the aid organizations in Zimbabwe performance
looks at factors such as turn-around times and communication means. These
affect the outcome of projects in some ways, such as correct delivery
destination, contingency planning and updating of execution.
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Performance measures differ between organizations and their practices, and
have been used interchangeably in literature. They are often looked at as a
relationship between performance measurement systems and how their set out
in their environment. This then leads to the suggestion by Rouse et al. (2003),
that performance measurement systems are used in assisting in the
development of actual performance measurement systems, through the
clarification of boundaries. However, with regard to aid organizations, no
performance measurement systems have been developed or set in place, due
to the different types of systems and requirements, that being, different
programme areas and projects.
Although this is an area of growing concern and interest, it is not to say that no
attempts have been made at creating systems that can be adopted throughout
an array of aid organizations. Performance systems with regard to aid
organizations have been created, such the Balanced Scorecard approach by
Kaplan (2001). However, these attempts proved to be a positive move for some
aid organizations, but not a best fit for aid organizations in Zimbabwe. As
mentioned previously, performance measurements differ from organization to
organization, due to their environment. Therefore, it would seem that the
humanitarian sector is lacking in means of measuring a crucial element within
their systems, which poses as a disadvantage, as the knowledge of
performance levels helps to enhance future activities.
2.5 CONCEPTUAL FRAMEWORK AND HYPOTHESIS
The discussions presented in the literature review represent different views on
what is considered to be the determining factor or bottleneck in LMD to obtain
good performance levels. Previous research studies have shown that different
bottlenecks occur in different areas or locations. The influence of these
bottlenecks on LMD, determines aspects of performance, such as effectiveness
and efficiency. Figure 1 illustrates the conceptual framework of the factors
influencing LMD to obtain a favourable level of performance, which is a
combination of elements from Balick et al. (2008) and Roy et al. (2012).
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FIGURE 2.1: CONCEPTUAL FRAMEWORK
Due to the findings derived from previous literature, pertinent hypothesis have
been generated with reference to the framework, for this study:
Hypothesis 1: Transport resources have a significant influence on LMD.
Hypothesis 2: Infrastructural degradation has a significant influence on LMD.
Hypothesis 3: Financial limitations have a significant influence on LMD.
Hypothesis 4: LMD has a significant influence on the performance in aid
organizations.
2.6 SUMMARY OF LITERATURE REVIEW
This research aims to further look into the bottlenecks faced by the aid
organizations. Past literature highlights bottlenecks and issues in Last Mile
Distribution on a broad scale, with no specified areas relating to all the problems
stated. However, all the bottlenecks identified in the literature can be associated
with numerous locations, ranging from relief or disaster to project execution.
Bottlenecks identified consist of financial limitations, transport resource issues
and infrastructural degradation, which can all be applied to the case on
Zimbabwe. Table 1 below gives an overview of the areas drawn out from the
literature, on a general scale, as a means and basis to aid in pin pointing the
issues of the related case of this research.
TABLE 2.1: SUMMARY OF FINDINGS FROM LITERATURE REVIEW
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Variable Items Sources
1
.
Last Mile
Distribution
-What is the level of efficiency
-Effectiveness
-Distribution decisions
Balick & Beamon (2008); Kovacs, G.
(2009). Barabasoglu, G. O. (2002),
Duran, S. G. (2007), Barabasoglu,
( 2002)
2
.
Transport
Resources
-Availability of trucks
-Costs of trucks
-Limitations in use
-Contractual limitations
Balick & Beamon (2008); Van
Wassenhove, L. (2006); Mbowha,
M. (2006); Thomas, A., &
Mizushima, M. (2005). Kovacs, G.
(2009). Barabasoglu, G. O. (2002),
Duran, S. G. (2007)
3
.
Infrastructural
Degradation
-Degraded roads, e.g. pot holes
-Rough terrain, remote areas, no
accessible roads
Balick & Beamon (2008); Van
Wassenhove, L. (2006); Mbowha,
M. (2006). Kovacs, G. (2009).
Barabasoglu, G. O. (2002)
4
.
Financial
Limitations
-Earmarking of funds
-Limits on contracts
-Lack of emergency funds
Balick & Beamon (2008); Mbowha,
M. (2006); Kovacs, G. (2009).
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.
Performance -Timelines
-Baselines
-Turn-around times
-Efficiency and effectiveness
Balick & Beamon (2008); Van
Wassenhove, L. (2006); Thomas,
A., & Mizushima, M. (2005),
Kovacs, G. (2009). Barabasoglu,
G. O. (2002)
The table above presents the items that will be further investigated into, that
have been derived from findings in the literature. These findings will further be
discussed in Chapter three within the methodology section.
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CHAPTER 3: RESEARCH METHODOLOGY
3.1 INTRODUCTION
This chapter reviews the research methods implemented to achieve the aims
and objectives of this study. This research will adopt the framework by
Saunders et al. (2009), the ‘Onion Model’ of research, as a means to
highlighting philosophical approaches. The research will adopt a Positivist
philosophy, deductive approach, survey strategy, and a quantitative data
collection technique.
3.2 RESEARCH PHILOSOPHY
As a means to achieving the aims and objectives of this study, a positivist
philosophy is adopted throughout the research. This philosophy is based on a
scientific approach towards researching, and is often used in framework and
hypothesis testing (Saunders, et al., 2009). Knowledge is gained from theory
then related to the researcher’s assumptions, thus leading to hypothesis
generation. Therefore, positivists favour quantitative techniques, such as
questionnaires and experiments. However, an interpretivist philosophy could
also be applied to gain an insight into individual perspectives (Bryman & Bell,
2011), but as this study is based on a theory and its impact, this philosophy
would not hold. To fulfil the research criteria of the philosophy, and however, as
there are two possible approaches, only one will be used: deductive.
3.3 RESEARCH APPROACH
For this study, a deductive approach will be assumed, through the identification
of theory before the data collection and its analysis. The approach is based
around a theory rather than an observation, seeking to confirm or reject a
hypothesis generated from the literature (Bryman & Bell, 2007). This approach
has been said to be one that tries to agglutinate theory and preconceived ideas
when analysing data (Saunders, et al., 2009). It has been chosen over the
23
inductive approach, which aims to gather data, and from that same data, extract
main themes and theories (Bryman & Bell, 2011). A deductive approach is
common in quantitative data research methods; the researcher will first identify
theory within the literature, and then seek to find the veracity or erroneous from
within the findings and results, with regard to the proposed framework and
hypothesis (Bryman & Bell, 2011). Also, as a means to collecting data from a
larger sample, the deductive approach is better, as well as being more
appropriate in generalising results.
3.4 RESEARCH STRATEGIES
3.4.1 SELF-COMPLETION QUESTIONNAIRES
Self-completion online questionnaires, comprising of quantitative, comprising of
closed- ended and open-ended questions, to obtain data that will be correlated
in a numerical and quantifiable manner (Bryman & Bell, 2011). Closed-ended
questions are questions formulated in a manner that restricts the participant to a
choice of pre-set answers in a small set, whilst open-ended questions offer
fewer restrictions as to the possible answers that participants can give
(Saunders, et al., 2009).Open-ended questions allow for a more in-depth and
descriptive response from the participant, giving a deeper insight into their
perceptions and opinions. However, due to their more dense nature, the
responses prove to be more challenging in computerizing and aggregating. In
this case the structure will be used to allow the participants to give both a
gauged and guided response as well as offering a more non-restricted platform
to give detail.
3.4.2 ALTERNATIVE METHODS
Previous research used observation methods and experimental field studies to
investigate LMD for different purposes and objectives (Balick & Beamon, 2008;
Bryman & Bell, 2011). However, the problem with these methods is that they
require more time than is allocated for this research, physical presence, and
24
have issues with reliability and validity (Saunders, et al., 2009; Zikmund, et al.,
2012), as well as requiring a great deal of participation and cooperation from
participants. For this reason observation methods and experimental field studies
were not used as they may limit data collected, as well as having time and cost
factors.
3.4.3 JUSTIFICATION
Questionnaires are the chosen method of data collection because, besides
being more favourable economically, they offer participants less pressure where
they can respond with assurance that their feedback will be anonymous, thus
creating room for reliability, unlike in interviews. Also, using questionnaires “can
help to gather valid and reliable data that is relevant to the research questions
and objectives.” (Saunders, et al., 2009). They are quicker to administer and
are more convenient to participants as they can complete at their own pace and
time (Bryman & Bell, 2011). The questions asked were broken down into a
systematic order, topic by topic, to ensure no confusion or ambiguity for the
participant.
As there are relationships needing to be measured and tested, questionnaires
will offer the best means into gathering data sufficient enough to test results in a
statistical manner.
3.5 SAMPLING METHOD
Snowball sampling is the chosen method for this research. This is a form of
convenience sampling, but differs in that participants are chosen due to their
relevance to research, and are then used to establish contacts with others
(Bryman & Bell, 2011). This leads to the advantages of this method, which are
of accessibility to the relevant participants, individuals working in the relief
logistics sector in this case, and the prospects of speeding the data collection
process. However, this method is often used in qualitative research, but can be
implemented into a research containing a quantitative aspect.
The sampling size consisted of 50 participants, of whom 42 completed the
questionnaire. The participants were all employees within aid organisations in
25
Zimbabwe and comprised of both males and females. These participants were
used due to the researcher’s accessibility and ability, and the relevance in
occupation in relation to the research.
3.6 VALIDITY AND RELIABILITY
Validity: The framework developed is cohesion of frameworks constructed and
tested by numerous researchers in past studies in context to different locations
and relief situations. Validity refers to whether devised indicators devised to
measure a concept or theory really measures that concept (Bryman & Bell,
2011).
Reliability: The reliability of the research was tested using Cronbach’s Alpha,
and tested during data analysis. Reliability is concerned with measuring the
consistency of measures within a concept (Bryman & Bell, 2011). The reliability
was tested for all the components within the framework to ensure a consistency
in results. The reliability is considered acceptable if all components score above
0.6. Also some personal information was selected from respondents, such as
gender and occupation.
3.7 DATA COLLECTION
42 self-completion questionnaires were gathered through an online survey in
aid organizations in Zimbabwe. This permitted data to be gathered quickly and
in an economically favourable manner. Questions were designed to gather
information on bottlenecks, efficiency and performance within aid organizations,
with regard to LMD. Closed-ended and open-ended question were posed as a
means to gathering relevant and quantifiable information on the challenges of
LMD.
Closed-ended questions were based on selection of a single answer that
participants found most agreeable to them, whilst in some questions the Likert
scale was used, requiring participants to show the level of agreement towards
difficulty and efficiency, of different aspects of their LMD processes. Open-
ended questions, on the other hand, allowed for participants to descriptively and
freely express their opinions and explanations on the topics asked in the
26
questionnaire survey. As the questionnaires were online, participants felt less
pressure and urgency to complete them. Therefore this encouraged participants
to complete the questionnaire.
3.8 DATA ANALYSIS
SPSS was used to analyse the data deduced from the questionnaire survey.
This is computer software designed to analyse quantitative data (Bryman & Bell,
2011). SPSS is used for this study to examine whether the relationships
between infrastructural degradation, transport resources, financial limitations,
and performance pose an actual challenge for LMD. Linear regression, along
with multiple linear regression where necessary, was used in the computing and
calculation of the data. Findings and results are presented using tables and
graphs, giving a descriptive observation into the results.
3.9 PILOT TEST
A pilot test is used as a means to enable the researcher to identify any potential
problems within the questionnaire before distribution to full sample (Saunders,
et al., 2009). A sample of 10 participants was used to conduct a trial and error
test of the questionnaire prior to full distribution. One participant suggested a
rank order/ Likert scale question to give individuals options to choose from, as
can be seen in Question 5 in the questionnaire in the Appendix, rather than
asking for a written description, as a means to measuring the effectiveness and
difficulty in their LMD and transport processes, whilst another participant
suggested changing a question from closed to open to ensure that the
challenges wishing to be identified are clearly brought out. These areas were
revised.
3.10 RESEARCH ETHICS
Ethical issues within this study were taken into full consideration when carrying
out the primary research. At the initial stage of completing questionnaires,
participants were informed about the purpose of the research and were assured
27
that their participation would be recorded anonymously, and that the recorded
data were for no other purpose but this research alone. Participants were under
no obligation to answer all questions and were free to skip or omit questions, at
their discretion. Taking part in the questionnaire was completely voluntary. All
participants were over the age of eighteen, being above age of consent for the
research.
3.11 RESEARCH LIMITATIONS
This research’s data collection method is aimed at investigating and discovering
what challenges face aid organisation in their LMD processes, as well in the
effectiveness and performance. However, there are some limitations that have
to be considered. As the basis of this research is based in a different country,
the first limitation is that of location, which then affected the ecological validity of
the study. This type of validity refers to the level at which the results or findings
are felicitous to the challenges found in LMD (Bryman & Bell, 2011). The use of
open-ended and closed-ended questions in the form of a survey questionnaire
may present the risk of low response rates (Bryman & Bell, 2011), due to
ambiguity of questions, and although the sample was relevantly chosen, there
may still be room for bias (Saunders, et al., 2009). This could be prevalent
through lack of knowledge of whether the relevant sample participant took the
survey, or whether someone else did. The risk of missing data was a realistic
factor because participants are not obligated to answer all the questions. It is
suggested to be easier for participants to not complete questions if they are
under no supervision, of an interviewer or researcher (Bryman & Bell, 2011).
With regard to the sample, the limitation is that it cannot be generalised, as it is
not only country specific, but also organization specific, therefore it cannot
represent a whole population using LMD in any logistics set-up. Acquiring full
feedback from the whole sample may have been difficult in that it was made up
of individuals working fulltime. Also there was no certain way of ensuring that
the questionnaires were completed by people in the required occupation or
organization sector, therefore the researcher had to keep this in consideration.
Future research may be undertaken to overcome these limitations.
28
3.12 CHAPTER SUMMARY
The chapter gave a critical outline the methodology approaches used in gather
the primary data. A questionnaire survey was used as data collection technique,
using a deductive approach, extracted from the positivist philosophy. The use of
closed-ended and open-ended questions was used in order to attain both
quantifiable and descriptive results, these results aid in improving the
conclusions and recommendations of the research. Issues on ethics were
discussed prior to the data collection in order to protect participants.
29
CHAPTER 4: FINDINGS AND ANALYSIS
4.1 INTRODUCTION
In this chapter the results deduced from the primary data collected on the
impact of bottlenecks affecting LMD and performance in aid organizations in
Zimbabwe. The results will be analysed in relation to the objectives of this
research and supported by existing theory within the literature review.
4.2 DATA INCONSISTENCIES
It is suggested that missing variables can affect the quality of results obtained
from the research, rendering it inaccurate or non-normal (Howells, 2006). In
regard to this study, a test was carried for missing values. Conclusions of the
test suggest there are some missing values in the data.
Therefore no action was required for missing data, leading to the next stage;
testing the reliability of the sample.
4.3 DEMOGRAPHICS
The demographics of this study were broken down into two categories of
gender and occupation. The gender category does not have any dramatic effect
on the outcome of the result. However, the occupation factor holds some weight
because for the research to have gathered adequate and accurate results, the
participants need to be in the specific sector of supply chains. The two
categories have been broken down below.
4.3.1 GENDER
Graph 4.1 gives descriptive information on the respondents. The gender
distribution was fairly equal, having a difference of 8, with 17 females and 24
males totalling to a sum of 42 respondents. The study was non-specific as to
the gender preference, as it doesn’t affect the outcome. Results also show a
percentage reading showing that 59.5% were males and 40.5% females.
30
.
GRAPH 4.1: GENDER DEMOGRAPHICS
4.3.2 OCCUPATION
In terms of occupation, Graph 4.2 shows that the breakdowns were significant
having 61% of the respondents in the Logistics sector, 23% in Supply and
Procurement and a minimal 14% in warehousing representing the lowest
occupational category of respondents
31
GRAPH 4.2: OCCUPATION DEMOGRAPHICS
Graph 4.2 aids in showing the validity in that the larger group of respondents
was in the occupation field highly involved in the processes of LMD within aid
organizations in Zimbabwe.
4.4 RELIABILITY TEST
The Cronbach alpha value is one of the most commonly used reliability tests ad
is calculated using the following formula (Bruin, 2006)
α= N .cv+(N−1 ) . c
In brief, N is the number of variables, v represents the average variance with c
being the average inert-item covariance amongst the items. For ease of
computing, SPSS has a reliability function that computes Conbrach’s alpha
value for each construct. Output of the individual reliability tests are summarised
in Table 4.1 below.
32
TABLE 4.1: RELIABILITY COEFFICIENTS
CONSTRUCT CRONBRACH’S ALPHA
Transport Resources 0.791
Infrastructural
Degradation
0.830
Financial Limitations 0.710
Last Mile Distribution 0.812
Performance 0.773
Cronbrach’s Alpha value suggests that values between 0.6 and 0.95 are
deemed acceptable and reliable (Bruin, 2006). Therefore, referring to Table 4.1
above, Cronbrach’s Alpha value for all the constructs was above the lower
acceptable limit but below the upper accepted limit, and as a result, the
reliability of the questionnaire is considered acceptable.
4.5 REGRESSION ANALYSIS
Regression testing is carried out as a means to determining relationships
between the variables derived from literature and tested through quantitative
methods. The testing has been administered upon the results so as to
determine the relationships between:
- Transport Resources and LMD
- Infrastructural Degradation and LMD
- Financial Limitations and LMD
- LMD and Performance
4.5.1 TRANSPORT RESOURCES AND INFRASTRUCTURAL
DEGRADATION
33
Firstly, findings obtained for the relationship between Transport Resources and
LMD are shown in Table 4.2, giving an illustrative view, as a means to
deduction.
Table 4.2: Regression Analysis on transport resources and LMD
The table clearly depicts that findings confirm that Transport Resources
positively correlate to LMD (b=0.685, p=.000), showing that there is a significant
relationship between the two.
In the second test, Infrastructural degradation and LMD were tested, and the
result was a positive correlation (b=0.775, p=.000), suggesting that a significant
relationship is evident between the two variables. The results are shown in
Table 4.3 below.
Table 4.3: Regression Analysis on infrastructural degradation and LMD
In conclusion, this suggests that the hypotheses below, H1 and H2 have not
been rejected.
Hypothesis 1: Transport resources have a significant influence on LMD.
Hypothesis 2: Infrastructural degradation has a significant a significant influence
on LMD.
34
4.5.2 FINANCIAL LIMITATIONS
Findings from Table 4.4 below confirm that Financial limitations positively
correlate with LMD (b=0.402, p=.000), therefore there is a significant
relationship financial limitations and LMD.
Table 4.4: Regression analysis on financial limitations and LMD
Therefore, the results suggest that hypothesis (H3), regarding financial
limitations and LMD, is in fact not rejected.
4.5.3 LAST MILE DISTRIBUTION
As all three variables are further tested, collectively, in relation to LMD, the
result suggests that there is a significant positive relationship between
Transport resources (b=0.23, p=0012), infrastructural degradation (b=.532,
p=.000), financial limitations (b=.536, p=.000) and LMD. Table 4.5 below clearly
outlines and confirms the relationship is positive and has a significant
relationship.
35
Table 4.5: Regression Analysis on LMD, Transport Resources,
Infrastructural Degradation and Financial Limitations
Therefore, in conclusion, the results suggest that there is a significant positive
result between the three variables and transport resources, infrastructural
degradation, financial limitations and LMD, thus suggesting that all the
hypotheses have been accepted.
4.5.6 PERFORMANCE
Findings deduced from Table 4.6 below suggest that there is a significant
positive relationship between LMD and performance (b= 0.860, p=.000).
Table 4.6: Regression Analysis on performance and LMD
This confirms evidence from previous literature that performance is an important
aspect of project and relief execution, and that LMD affects performance (Roy,
et al., 2012).
4.7 SUMMARY
In conclusion a regression analysis was performed in order to answer the
hypothesis and framework posed by this study. Results conclude that although
36
individually the three constructs all relate positively to LMD, combined they have
different, but positive relations. The results further show a positive relationship
between LMD and performance, suggesting that the three, transport resources,
infrastructural degradation and financial limitations impact LMD which then
impacts on performance.
37
CHAPTER 5: ANALYSIS AND DISCUSSION
5.1 INTRODUCTION
This chapter analyses the results derived from the quantitative data to
demonstrate how the aims and objectives have been accomplished. The results
will be discussed and backed up by works from the literature review.
5.2 TRANSPORT AND INFRASTRUCTURAL DEGRADATION
The results from the study affirm that there is a significant relationship between
transport resources and LMD and infrastructural degradation and LMD. In
previous works it was suggested that for LMD to be carried out seamlessly or to
a high standard, these two factors would have to considered highly so as to
create means of overcoming them to ensure good levels of performance
(Balick, et al., 2008). However, in past research no account was taken on
Zimbabwe as a specific topic, but regardless of this, the results agreed with that
of past research in highlighting that transport and infrastructural degradation
work together and without the combination of the two, no execution of relief or
projects is possible (Roy, et al., 2012).
In the area of Bulawayo in the Matebeland regions of Zimbabwe, the rural areas
lack proper roads due to the harsh weather conditions. This results in difficulties
arising for delivery trucks and aid to be distributed in such areas, thus putting a
strain on the operations of LMD (UNICEF, 2010). Figure 5.1 below gives a clear
picture of the main transport routes in areas of Zimbabwe, and how transport
means are a huge constraint.
38
Figure 5.1: Road Map of Zimbabwe 1
This study concludes that aid organizations in Zimbabwe need to always take
these two bottlenecks into account, as they affect their whole LMD operations.
5.3 FINANCIAL LIMITATIONS
The findings indicate a significant positive relationship between financial
limitations and LMD. This relationship is evident in the frameworks of Roy et al.
(2012) where they suggest that although finances do not impact LMD as much
as infrastructural degradation, for the operations of LMD to be carried out it is a
factor in that it makes available the resources needed available. Thus
supporting Roy et al. (2012) conceptualization of financial limitations, the study
suggests that funding logistical operations such as LMD influences the
performance of activities carried out in aid organizations in Zimbabwe, such as
UNICEF. Therefore, logisticians and managers should consider setting up
funding schemes solely located in their sections and schemes to make sure
funding is immediately available in cases of unexpected occurrences during
projects. However, the economic situation in Zimbabwe should be a factor taken
into consideration by the organizations. Although they attain funding from
external and international bodies (e.g. USAID), the situation on the ground can
highly affect their LMD operations.
5.4 LAST MILE DISTRIBUTION AND PERFORMANCE
39
A significant and positive relationship is evident between transport,
infrastructure, finances and LMD, which then results in a significant and positive
relationship between LMD and performance. Results suggest that LMD impacts
on the performance of projects and relief activities in Zimbabwe. Past research
suggests that for good performance to be achieved, LMD needs to have the
three identified bottlenecks working together, and having a positive impact
(Folan & Browne, 2005). However, other research by Duran et al. (2007)
suggests that performance is not only affected by LMD operations, but also by
other factors, such as management decisions and climate factors, which were
not identified in this particular study.
5.5 SUMMARY
In conclusion, from the results gathered it is evident that all suggested
relationships are not rejected. The results suggest that logisticians and
managers should take the three bottlenecks within LMD in to high
consideration, and find means of decreasing any negative implications they may
currently have on their LMD operations, as they will cause an impact on their
overall performance. Table 5.1 below shows the confirmation of findings from
the research.
Table 5.1 Confirmation of the findings
Factors/Variables Result
Transport Resources Accepted
Infrastructural Degradation Accepted
Financial Limitations Accepted
Last Mile Distribution (LMD) Accepted
Performance Accepted
40
CHAPTER 6: CONCLUSIONS AND RECOMMENDATIONS
6.1 INTRODUCTION
This chapter consummates the report and its findings, and also suggests future
research recommendations and research limitations.
To sum up the study the objectives were reached as shown below:
To identify the bottlenecks within LMD. The research derived three
bottlenecks consisting of transport resources, infrastructural degradation
and financial limitations, which suggested that if not properly addressed,
they would have a negative impact on LMD operations. The relationship
between some of these bottlenecks is more significant than others,
suggesting that more attention should be given, such as that of transport
resources and LMD. Managers and logisticians should consider
implementing systems stating levels of difficulty and means of
overcoming them, such as the Balanced Scorecard by Kaplan (2001).
To examine the impact of LMD on performance. Findings suggested
that, yes, LMD affects performance, but however, it should not be the
only determining factor, as other factors were evident in past literature.
Managers should create or adopt a performance measurement
framework to measure activity, efficiency and effectiveness for their
projects and relief operations.
To make recommendations on ways to improve LMD to improve
performance for aid organisations in Zimbabwe. These findings will
provide a framework for logisticians and managers in designing and
planning of projects at the last mile, to ensure positive results after
execution, thus increasing performance results, and also aiding in the
constructing of performance measures that are relevant to their
geographical area.
41
6.2 FUTURE RESEARCH
After concluding the study, some limitations were found. The limitations are
stated below, and recommendations follow.
The findings may not be applicable to every aid organization in Zimbabwe as
not all aid organizations are involved in distribution or logistics activities. There
are, however, other factors that may affect the performance of project execution
in aid organizations. The author of this study has chosen to focus on the
logistics aspect of project and relief execution. Different factors may have
different impact on performance (Kongsomsaksakul S, 2005).
As a recommendation, future research can look into the managerial influences
on LMD and performance, to test how internal or external management issues
impact the operations within LMD and how they affect performance. Also, a
further study into the creation of area specific performance measures could be
looked into, as a means to defining metrics of gauging projects and relief
activities. Lastly, future research could be looked into on how the economic
situation in Zimbabwe impacts the effectiveness of aid organizations and their
developmental projects, with regard to logistics.
42
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46
APPENDICES
Appendix 1: Questionnaire
I am a Brunel Business School undergraduate researching the driver of student
preference on smartphone. The purpose of this study is to examine how
consumer brand preference and how the preferences affect purchase
intensions. The research does not ask for personal details, except for very
generic details (age, gender and level of education), that cannot identify you as
a specific individual and your input will be entirely confidential. The researcher
will store your information in a secure, confidential manner. The results of this
study will be solely used to research the specified area of product placement.
This survey will take approximately 2-3 minutes
If you would like to take part in this questionnaire please give your consent for
participating and confirm you are over 18 years of age.
1. Please specify your gender by selecting the appropriate box below.
Male
Female
2. Please tick in the box below the occupation or occupational field that best
describes your job area.
Logistics and Distribution
Supply and Procurement
Warehousing
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3. Please mark with an 'X' the box that best describes the effectiveness of your
Last Mile distribution system.
Very effective
Effective
Somewhat Effective
Neither Effective nor Ineffective
4. From the bottlenecks listed below, please choose the one most relevant in
your logistics operations with regard to your Last Mile Distribution operations.
Degraded infrastructure
Financial limitations / earmarking
Limited transport resources
Communication infrastructure
5. In project execution, which of the four bottlenecks (challenges) listed below
would you suggest is the most difficult. Rank in order from 1 to 4. With 1 being
most difficult and 4 least difficult.
______ Transport
______ Infrastructure
______ Finances
______ Communication
6. In carrying out distribution projects in your organization, what factors are
most focused on in the Logistics section, i.e efficiency in delivery or making sure
goods have been delivered? Give a brief explanation in the box below.
_______________________________________________________________
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7. What method of communication is used during project execution in your
organization? Please mark with an 'X' in the appropriate box.
___ Cellular/Mobile phone
___ GPS Satellite Tracking
___ Radio voice devices i.e. 'walk talkie'
8. Please select the performance measures used in your organization below. If
none of the given options relate, please add in the space below.
Time lines
Baselines
Turn-around times
Enter text below
____________________
9. Would you ever consider implementing commercial logistics techniques into
your organization's humanitarian logistics systems? i.e. Fourth-party logistics
(4PL)
Yes
No
10. Briefly describe the transport system in your organization, focusing on the
major challenges. Enter answer in the box below.
11. What would you consider as the most limiting factor in sourcing or acquiring
transport resources within your organization/section?
Cost of trucks
Availability of trucks
Contractual limitations
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12. In the space provided below, please briefly describe the geographical/
infrastructural challenges you face in your organizations.
_______________________________________________________________
13. In the boxes below, please select the problem that affects projects
execution the most amongst the choices given below.
Degraded roads, e.g. potholes
Areas with no roads or vehicle paths
Rough terrain
14. Are emergency or contingency funds readily available for use in projects or
relief operations? Please select Yes/No below.
Yes
No
15. Are emergency/contingency funds readily available? Please select Yes/No
in the boxes below.
Yes
No
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Appendix 2: Participant Information Sheet
Brunel Business School
Research Ethics
Participant Information Sheet
1. Title of Research: The bottlenecks in Last Mile Distribution in Humanitarian Logistics: A case on Zimbabwe
2. Researcher: Tinotenda R Gova on International Business, Brunel Business School, Brunel University
3. Contact Email: E-mail: [email protected]
4. Purpose of the research: The aim of this research is to investigate the bottlenecks within the Humanitarian Logistics network in international aid organizations in Zimbabwe that affect the efficiency and performance of Last Mile Distribution; and look into how these can be improved. In addition this study will illustrate how the information can be implemented in international aid organizations, so as to improve efficiency and performance levels.
5. What is involved: A sample of 50 people from aid organizations in Zimbabwe will be asked to take a 5-7 minute online questionnaire, sent via an email link. The questions will consist of both open-ended and closed-ended questions. The aim is to measure the perception from the sample, on the implications caused by barriers in their Last Mile distribution processes, and the impact they have on efficiency and performance.
6. Voluntary nature of participation and confidentiality. The participants can choose to withdraw from the study at any time, and may refuse to answer any questions they do not wish to. The data collected will not be used for any other purpose but for this project alone. Participants' identity will be kept private and anonymous. If the participants have any queries they are able to contact me on the email above, or through Brunel Business School.
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