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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: 1044676@my.brunel.ac.uk

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.