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The Effect of Logistics Capability, Information
Technology Implementation and Innovation Ability on
Road Transportation Logistics Performance
by
Nur Fadiah Mohd Zawawi
A thesis submitted in fulfilment of the requirements for the degree of
Master of Entrepreneurship
Faculty of Entrepreneurship and Business
UNIVERSITI MALAYSIA KELANTAN
ii
THE EFFECT OF LOGISTICS CAPABILITY,
INFORMATION TECHNOLOGY IMPLEMENTATION
AND INNOVATION ABILITY ON ROAD
TRANSPORTATION LOGISTICS PERFORMANCE
NUR FADIAH MOHD ZAWAWI
MASTER OF ENTREPRENEURSHIP
ii
ACKNOWLEDGEMENTS
Thank you to Allah s.w.t for His opportunity, health, love and blessing, for taking me to
this stage, upon my completion of the study for Master in Entrepreneurship (Management). Shalawat is also sent to Prophet Muhammad ملسو هيلع هللا ىلص who had delivered the
truth to human beings in general and Muslim in particular. During the period of study,
there have been many treasurable people who have motivated and guided me through
the whole work of this research. They are my backbone through thick and thin.
In this valuable chance, I would first like to convey my deepest appreciation and thanks
to my precious family especially my dear husband, Marmizal Mohd Nawi, my beloved
parents, Haji Mohd Zawawi Mohd Daud and Hajah Che Rohainu Che Jafaar and my
beloved siblings for their endless love, pray, understanding and inspiration till the day I
completed this study. You are my forever supporters.
A sincere appreciation and thanks goes to my main supervisor, Prof. Dr. Sazali Abd
Wahab, the Dean of Malaysian Graduate School of Business and Entrepreneurship for
his cheerful encouragement, inspiration, and help in giving me such a positive working
climate. Many thanks to my co-supervisor, Dr. Abdullah Al-Mamun for his patience in
guiding me along the journey of this study.
I also would like to say a lot of thanks to my respected lecturers in Faculty of
Entrepreneurship and Business, Assc. Prof. Dr. Mohd Rafi Yaacob and Mr. Zuraimi
Abd Aziz for spending their time to share knowledge and experience. Your journeys
motivate me to work harder. To my fellow cliques of postgraduate studies, thank you
very much for your never ending support and encouragement. May our humble works
contribute to the nations.
To all my dear friends who have inspired me internally to stay focus in this academic
world, let us together cherish and share the knowledge for the sake of Allah s.w.t.
Thank you.
I hereby express my gratitude to all of them.
iii
TABLE OF CONTENTS
PAGE
THESIS DECLARATION I
ACKNOWLEDGEMENTS Ii
TABLE OF CONTENTS Iii
LIST OF TABLES Vii
LIST OF FIGURES Ix
ABSTRAK X
ABSTRACT Xii
CHAPTER 1 INTRODUCTION 1
1.1 Background of Study 1
1.1.1 Congestion and Its Impact 6
1.1.2 Empirical Evidences on Congestion’s Impact 8
1.1.3 Discussion 10
1.1.4 Definition of Terms 11
1.2 Problem statement 12
1.3 Research Questions 14
1.4 Research Objectives 15
1.5 Scope of Study 16
1.6 Significance of Study 16
1.7 Limitations of Study 18
CHAPTER 2 LITERATURE REVIEW AND HYPOTHESES
DEVELOPMENT
20
2.1 Introduction 20
2.2 The Concept of Logistics 20
2.3 Logistics and Supply Chain 22
2.4 Resource-Based View (RBV) Theory 23
2.5 East Coast Region of Peninsular Malaysia 25
2.6 Logistics Service Providers (LSPs) 26
2.6.1 LSP’s Descriptions 26
2.6.2 Capability of LSPs and Firm Performance 27
iv
2.7 IT Implementation 30
2.7.1 Definition of IT 30
2.7.2 IT Implementation and Firm Performance 31
2.8 Innovation Capability 35
2.8.1 Revolution of Innovation to Capability 35
2.8.2 Innovation Capability and Firm Performance 36
2.9 Firm Size as a Moderator 39
2.10 Logistics Firm Performance 40
2.11 Discussion 44
2.12 Theoretical Framework 43
2.13 Chapter Conclusion 45
CHAPTER 3 RESEARCH METHODOLOGY 47
3.1 Introduction 47
3.2 Research Design 47
3.3 Target Population 48
3.4 Sample Size 48
3.5 Response Rate 49
3.6 Unit of Analysis 50
3.7 Data Collection Method 51
3.8 Measurement Variables 51
3.9 Pilot Study 53
3.10 Procedure for Data Analysis 54
3.11 Data Cleaning and Transformation 55
3.12 Normality Test 55
3.13 Skewness Test 56
3.14 Multicollinearity Test 56
3.15 Descriptive Statistics 57
3.16 Reliability Test 58
3.17 Validity Test 58
3.18 Scatterplot 59
3.19 Correlation Analysis 60
v
3.20 Regression Analysis 61
3.21 Moderated Multiple Regression 61
3.22 Chapter Conclusion 64
CHAPTER 4 RESULTS AND DISCUSSION 65
4.1 Introduction 65
4.2 Data Analysis 65
4.2.1 Normality Test 65
4.2.2 Skewness Test 66
4.2.3 Frequency Distribution 66
4.2.3.1 Frequency Distribution 66
4.2.3.2 Size of Firm 76
4.2.4 Descriptive Statistics 78
4.2.5 Reliability Test 79
4.2.6 Bivariate Correlation 81
4.2.7 Scatterplot and Correlation Analysis: Hypotheses Testing 82
4.2.7.1 Capability of LSPs and Firm Performance 82
4.2.7.2 IT Implementation and Firm Performance 83
4.2.7.3 Innovation Capability and Firm Performance 85
4.2.8 Multicollinearity Statistics 86
4.2.9 Standard Multiple Regression 87
4.2.10 Moderated Multiple Regression (MMR): Hypotheses Testing 90
4.2.10.1 Moderating Effect of Firm Size on the Relationship of
Capability of LSPs and Firm Performance
90
4.2.10.2 Moderating Effect of Firm Size on the Relationship of
IT Implementation and Firm Performance
94
4.2.10.3 Moderating Effect of Firm Size on the Relationship of
Innovation Capability and Firm Performance
97
4.3 Discussion 100
4.4 Chapter Conclusion 103
vi
CHAPTER 5 CONCLUSION 105
5.1 Introduction 105
5.2 Key Findings 105
5.3 Implications of the Study 106
5.4 Limitations of the Study 109
5.5 Recommendations for Future Research 110
5.6 Overall Conclusion of the Study 111
REFERENCES 113
APPENDIX A 127
APPENDIX B 130
APPENDIX C 136
APPENDIX D 142
APPENDIX E 152
APPENDIX F 153
APPENDIX G 163
APPENDIX H 167
APPENDIX I 169
APPENDIX J 171
APPENDIX K 173
LIST OF TABLES
NO. PAGE
1.1 Costs of transport delays and disruptions 8
1.2 Seven classes of congestion impact and potential business
response
9
2.1 Performance indicators for effective and efficiency 44
3.1 Measurements of this study 52
3.2 Cronbach's Alpha for pilot survey 54
4.1 Demographic of respondents 67
4.2 Demographic of firms 70
4.3 Frequency of measurements 73
4.4 Mean and standard deviation 78
4.5 Value of Cronbach's Alpha for the actual survey 80
4.6 Bivariate correlations for independents variables 81
4.7 Correlation analysis for capability of LSPs and firm
performance
82
4.8 Correlation analysis for IT implementations and firm
performance
84
4.9 Correlation analysis for innovation capability and firm
performance
85
4.10 Model summary of standard multiple regression 87
4.11 ANOVA table 88
4.12 Coefficient for regression analysis 88
4.13 Model summary of firm performance, capability of LSPs and
firm size
91
4.14 Coefficients for variables involved 91
4.15 Model summary of firm performance, IT implementations and
firm size
94
4.16 Coefficients for the variables involved 95
4.17 Model summary of firm performance, innovation capability and
firm size
97
vii
viii
4.18 Coefficients for variables involved 98
ixi
LIST OF FIGURES
NO. PAGE
1.1 Dependency of seaports, airports and railway stations on road
transportation
5
1.2 Illustrated summarization of how congestion affects business
performance
10
2.1 Theoretical framework for this study 45
4.1 Percentage of highest education own by respondents 67
4.2 Positions of respondents in their organization 68
4.3 Working experience of respondents in current job 69
4.4 Working experience of respondents in current organization 69
4.5 Years of firms’ establishment 71
4.6 Characteristics of firms 72
4.7 Numbers of employees of a firm 78
xi
LIST OF ABBREVIATION
COL Capability of Logistics Service Providers
COL*FS Product Term of Capability of LSPs and Firm Size
EDI Electronic Data Interchange
ERP Enterprise Resource Planning
FP Firm Performance
FMM Federation of Malaysian Manufacturers
FS Firm Size
INNV Innovation Capability
INNV*FS Product Term of Innovation Capability and Firm Size
IT Information Technology
IT*FS Product Term of IT and Firm Size
LSPs Logistics Service Providers
MMR Moderated Multiple Regression
OLS Ordinary Least-squares
RBV Resource-Based View Theory
RFID Radio-frequency Identification
xii
Kesan Keupayaan Logistik, Implimentasi Teknologi Maklumat dan Kebolehan
Inovasi ke atas Prestasi Logistik Pengangkutan Jalan
ABSTRAK
Era globalisasi hari ini membuatkan para usahawan lebih aktif menjalankan aktiviti
perniagaan tanpa mengira sempadan negara. Setiap perniagaan yang dijalankan
memerlukan perkhidmatan logistik sama ada untuk perniagaan di dalam atau di luar
negara. Antara perkhidmatan yang paling penting adalah perkhidmatan logistik
pengangkutan jalan, demi melengkapkan kitaran logistik dan memastikan barangan
sampai ke destinasi yang sepatutnya. Malangnya, perkembangan perniagaan yang
positif ini telah membawa kepada isu kesesakan jalan raya yang kemudiannya memberi
kesan yang tidak baik kepada prestasi syarikat perkhidmatan logistik (LSPs)
terutamanya dari segi masa penghantaran dan peningkatan kos operasi. Dengan itu,
kajian ini telah mengadaptasi satu model untuk mengkaji bagaimana keupayaan LSPs,
pengaplikasian IT and keupayaan inovasi sesuatu syarikat LSPs memberi kesan kepada
prestasi syarikat itu sendiri. Selain itu, kajian ini juga mengkaji kesan saiz syarikat yang
bertindak sebagai perantara dalam model tersebut. Memandangkan kajian-kajian lalu
menunjukkan Pantai Timur Semenanjung Malaysia juga menghadapi masalah
kesesakan jalan raya yang melibatkan perkhidmatan logistik pengangkutan jalan, maka
kajian ini dilaksanakan di kawasan tersebut dengan tujuan menyediakan laporan terbaru
tentang keadaan di sana serta membantu rantau tersebut untuk mengembangkan
potensinya sebagaimana yang dirancangkan oleh Ekonomi Wilayah Pantai Timur.
Berlandaskan kajian kuantitatif, sebanyak 210 set soalan soal selidik telah diedarkan
kepada syarikat-syarikat LSPs di sekitar kawasan kajian. Sebanyak 81 soalan soal
selidik dikembalikan (38.57%) dan data tersebut dianalisa menggunakan SPSS.
Hasilnya, keputusan kajian mendapati keupayaan LSPs dan keupayaan inovasi
mempunyai hubungan signifikan yang positif terhadap prestasi syarikat LSPs itu
sendiri. Bagi pengaplikasian IT, keputusan menujukkan fenomena “productivity
paradox”, sebagaimana dapatan kajian-kajian yang terdahulu. Manakala, untuk kesan
pengantaraan, keputusan menunjukkan saiz syarikat mempengaruhi hubungan antara
keupayaan LSPs dan prestasi syarikat. Syarikat yang kecil memberi impak yang besar
kepada hubungan antara keupayaan LSPs dan prestasi syarikat. Dapatan-dapatan kajian
ini dilihat menampung kekurangan literatur dalam bidang logistik di Malaysia,
terutamanya dalam konteks Pantai Timur Semenanjung Malaysia. Lebih dari itu, kajian
ini adalah model pertama yang menggunakan saiz syarikat sebagai pembolehubah
perantaraan dalam kajian-kajian logistik. Dengan itu, dapatan ini memberi sumbangan
penting kepada ilmu pengetahuan yang sedia ada. Selain itu, kajian ini juga bertindak
sebagai informasi terkini buat bakal pelabur sama ada dari dalam atau luar negara untuk
membuat pelaburan di rantau tersebut. Tidak lupa juga, dapatan kajian ini berfaedah
untuk pihak kerajaan menambahbaik polisi yang sedia ada bagi memastikan prestasi
logistik di Malaysia setanding dengan negara-negara sedang membangun yang lain.
xiii
The Effect of Logistics Capability, Information Technology Implementation and
Innovation Ability on Road Transportation Logistics Performance
ABSTRACT
The globalization era makes business people today hustle and bustle doing their trade
boundlessly. Every trade needs logistics services to cater their activities either for local
or international business. Among the services, road transportation logistics service is
seem very vital in supporting other types of logistics transportations in order to
complete the logistics cycle. Hence, this phenomenon has created severe congestions
which then affect business performance of logistics service provider (LSP) firms
especially in terms of delivery delay and increment in operating cost. Due to these
issues, this study has adapted a model, investigating how capability of LSPs, IT
implementation and innovation capability relate with performance of road logistics
transportation. Additionally, this study also measured the moderating effect of firm size
on the examined relationships. Since previous literature found that the East Coast region
of Peninsular Malaysia faced with the congestions as a result of busy trade, this research
is tempted to investigate the region with the intention to provide latest report about the
situation there, thus helping the East Coast region to expand their potential, as planned
by the East Coast Region Development Council. Since this research is using
quantitative method, 210 questionnaires were distributed to LSP firms in the desired
research areas. With the final of 81 usable questionnaires (38.57%), the data was
analysed by using SPSS. The results found that the capability of LSPs and innovation
capability have positive significant relationships with firm performance. IT
implementation however produce “productivity paradox” phenomenon, parallel with
previous findings. Meanwhile, in terms of moderating effect of firm size, the results
found that firm size moderates the relationship of capability of LSPs and firm
performance. The relationship is found stronger in small firms compared to large firms.
Nevertheless, there is no moderating effect found for the relationships of IT
implementations and innovation capability with firm performance. The results of this
study bridge the gaps of previous literature which lack of logistics literature in
Malaysian context, especially in East Coast region. Moreover, this study is the first
model using firm size as a moderator variable in the logistics research. Therefore, the
results fill this gap and contribute importantly to the body of knowledge. Going further,
the study also gives latest information on logistics performance of the East Coast
region. This is very important to the potential investors, as their guidelines to invest in
the region, either local or foreign. Last but not least, the study might be beneficial for
our government to consider new improved policy if needed in order to enhance the
logistics performance in Malaysia, thus could stand steadily with other developing
countries in the world.
1
CHAPTER 1
INTRODUCTION
1.1 Background of Study
The concept of logistics outsourcing was traced quite far in history. It
started in the 1950s‘ and 1960s‘ with transportation and warehousing services.
In 1970s‘, the logistics services were upgraded to improve productivity and cost
reduction, while in 1980s‘, they concentrated on value-added services like
packaging, labeling and system support. Up to the 1990s‘, the logistics services
expended into numbers of services including import/export management, freight
forwarding, distribution, freight consolidation and reverse logistics (Mitra,
2008). This situation shows that logistics market has always been evolving in
order to cope with economic changes.
Intelligence (2013) reported that nowadays, the logistics market is once
again evolving to support the new trends of world trade. For instance, instead of
manufacturers‘ production in China, the geographic spread of logistics hubs is
changing and new ones are developed closer to greater customer‘s
concentrations. Thus, the industry is going through a shift in trade paths towards
developing markets such as to Brazil, Russia, South Africa and the Middle East
as well as South East Asia. As such, logistics providers are evolving service
offerings and expanding into these new geographic markets. As forecasted and
analyzed by Datamonitor (2010), the global logistics size will reach $4 trillion in
2
2013. The bigger the logistics size, the bigger the demand of logistics services
and vice versa.
This expansion of world‘s logistics industry is parallel with its growth in
Malaysia. Historically, in the 1950s and 1960s, agro-based sector like rubber,
palm oil, pepper and timber conquered Malaysian economy. In 1970,
agricultural sector contributed 30.9% to the Gross Domestic Product (GDP)
compared to only 14.8% from manufacturing sector. However, this percentage
increased after the announcement of Investment Incentives Act in 1968 and free
trade zones (FTZ) in 1971 where they enticed numbers of multinational
companies to launch export oriented operations with well infrastructures
facilities, competitive pay, as well as politically and economically stable region.
In the early 80‘s, Malaysian Government took initiatives to develop strength in
manufacturing sector through heavy industries such as automobile,
petrochemicals, cement and steel.
In the 1990s, Malaysia started to look forward in being a country with an
innovation-led economy (Hasnan, Noordin, & Osman, 2014). As reported by
Bank Negara Malaysia (2003), this effort was seen successful when the
manufacturing‘s sector in GDP rose to 33.1% in 1995 and it continued to
steadily arise and stabilized (Salina, 2004). The latest news from Bank Negara
(2013), GDP of manufacturing sector in Malaysia stabilized at 24% from 2009
to 2012 while MITI (2010) reported that exports of manufactured goods
increased by 11.6% to MYR461 billion from MYR413 billion in 2009 and
imports manufactured goods increased 19.9% to MYR430.5 billion from
MYR359 billion in 2009 (MITI, 2010).
3
Due to good expansion of manufacturing industry, logistics sector plays
a key role in supporting the industry as mentioned in the Third Industrial Master
Plan (IMP3) as an engine of growth with the target to increase GDP from 50.5%
in 2005 to 59.7% by 2020 (MITI, 2009). Not only IMP3, the logistics services is
also one of Malaysia‘s most important investments, together with other
components of service sector like Information and Technology Services,
Environmental Management Services, Medical and Healthcare Services etc.
(MIDA, 2012). The service sector is also supported by the National Key
Economic Areas (NKEAs) and contributed 55% to GDP in 2008 (MIDA, 2012).
Recently, MITI (2013) updated that service sector contributed 58% of GDP in
2011 and is targeted to reach 65% in 2020. Malaysia‘s Minister Industrial Trade
and Industry added, the service sector will contribute 60% to GDP by 2020,
making it a major contributor to Malaysia‘s economy in a very near ahead
(MITI, 2014b).
The Ministry of Science Technology and Innovation (MOSTI, 2010)
testified that Malaysia was fruitfully ranked at 24th tier in the Innovation
Competitiveness and was also successfully placed at 26th rank in the Global
Competitiveness Index for 2010-2011 session as a consequence from a favorable
achievement of the service sector (Hasnan et al., 2014). Walking through the
years, the logistics industry in Malaysia keeps growing and becomes one of the
most important sectors that supported the development of Malaysia as a whole
and is considered as one of the catalysts for the industrial development to link
with the international trade In IMP3, export trade is expected to increase to
MYR1.4 trillion in the year 2020 and total trade to increase to MYR2.8 trillion
4
(MITI, 2012). It is agreed by Banomyong and Supatn (2011) who said that
freight logistics activities are significant to support export activities.
In logistics sector, transportation is a very significant element of supply
chain (Tracey, 2004) and somehow it is considered as a backbone of logistics.
Tseng, Yue, and Taylor (2005) mentioned that transportation occupies one-third
of the amount in the logistics costs, therefore transportation system influences
the performance of logistics system vastly. The operation of transportation
determines the efficiency of moving products. The evolution in skills and
management principles enhances the moving load, service quality, delivery
speed, the usage of facilities, operation costs and energy saving. It can be
considered that transportation takes a decisive part in the manipulation of
logistics.
Furthermore, Rosena, Harlina and Sabariah (2008) and Sum, Teo, and
Ng (2001) confirmed that the vivid expansion in the external trade countries
such as Singapore, Malaysia, Indonesia and Thailand recently has resulted in an
increment of demand for more efficient and effective logistics services
especially logistics transportation service. This is crucial because the
performance of the industry will have an impact on the progress of the nation‘s
industrialization and its competitiveness in international trade.
Regarding to MITI (2009), Malaysia has four main modes of logistics
transportation which are land, sea, air and rail. Other than these four modes,
Malaysia also now involves in pipeline projects for the fifth mode of logistics
transportation. The Prime Minister previously has contributed an amount of
allocation for the pipeline projects (MITI, 2010), but the pipeline is not yet
5
considered as a main mode of transportation in Malaysia since it is still in the
development stages.
Meanwhile according to Penang Economic Monthly (2008) in Rosena et
al. (2008), logistics transportation services are including transport operators of
air, sea, road and rail; terminal operators and multimodal operators. Each of
these transportation modes; air, sea, road and rail are actually dependent on each
other. Air, sea and rail transportations are depending on road transportation like
trailers and trucks for haulage process from airports, seaports and railway
stations to the end point (consumers, factories, shop lots or warehouses).
Therefore, road transportation is very significant to complete the logistics
process holistically, as mentioned by Coyle (1996):
“Logistics is the process of planning, implementing and controlling the efficient,
effective flow and storage of raw materials, in-process inventory, finished goods,
services and related information from point of origin to point of consumption
(including inbound, outbound, internal, and external movements) for the
purpose of conforming to customer requirements”.
Figure 1.1: Dependency of seaports, airports and railway stations on road
transportation
Source: Own proposed concept
6
This research proposes a model that shows the dependency of seaports
(sea transportation), airports (air transportation) and rail stations (rail
transportation) with the road transportation, as shown in Figure 1.1. They need
trucks and trailers to haulage or distribute their products or goods to the end
users. Road transportation has the highest reliability to deliver goods from door
to door or warehouse to warehouse, depends to the types of road transportation.
For example, according to the National Bureau of Statistics (2011) in Mahpula,
Yang, Kurban, and Witlox (2013), out of 27,806.3 million tons total freight
traffic of the four major transportation modes in 2009 in Beijing, more than 76%
of cargo travels by road, 11.9% by rail and 11.4% travel by water.
According to David J. Bloomberg (2002), ―road transportations are
including cars, motorcycles, trucks and trailers‖. All of them are using roads as
their medium of travel. In logistics, trailers and trucks, which are also called as
motor carriers, have been used as transport for the delivery process. Therefore,
the combination of public users like cars and motorcycles with the logistics
motor carriers, it might cause road congestion.
1.1.1 Congestion and Its Impacts
Generally, congestion affects businesses negatively on deliveries,
business schedule, workers, customers and meeting with clients (Hartgen, 2007).
Hartgen (2007) did a survey on Charlotte businesses and he found that 78% of
businesses there consider congestion as a greater than average problem for their
business. For them, the traffic congestion interrupts business performance by
7
introducing time delays that can be hardly managed and avoided. Other than
Charlotte, this issue has been widely discussed especially in big countries like
Japan (Taniguchi, Noritake, Yamada, & Izumitani, 1999), UK (Trunick, 2004)
and China (Gui-yan, Zu-tuo, Zu, Jia-qi, & Lei-lei, 2007). McKinnon, Edwards,
Piecyk, and Palmer (2009) claimed that traffic congestion can spoil the
efficiency and quality of logistics operations.
Furthermore, Taniguchi et al. (1999) added, the congestion is pretty
worse in urban areas, partly due to increase of truck traffic, which led to increase
of transportation cost. This situation happened because of the fact that frequent
transportation of small capacity of goods decrease the cost of inventory as well
as satisfying consumer needs. It is true that such way can decrease inventory
cost, but when volume of traffics increase and network of the road are nearly in
full capacity, the vehicle movement becomes unbalanced and more risky to
incidents such as road works, breakdowns, accidents and bad weather, thus
giving bad impact on transit time, transportation cost and delivery reliability.
Most of the unfavourable effects of road congestion on performance of
logistics are usually related with this unreliability. In Malaysia for example, the
increase in commercial vehicle drivers has increased road accidents too. The
increment of accidents which involving lorry drivers (logistics transportation)
from 44,683 cases in 2008 to 65,944 cases in 2009 has made road accident as
one of the main major factors of death in Malaysia (Royal Malaysian Police
Force Record, 2010) in Daud, Mohamad, Hassan, and Yahya (2013). On the
other hand, Sankaran, Gore, and Coldwell (2005) suggested that congestion is
always being a catalyst of delays and rising costs, which might affect business
8
growth and increase service level. Furthermore, Systematics (2008) as well as
Short, Trego, and White (2010) said that from most previous transportation
literature, they found congestion as a cost factor, composed of operation
expansion and time delay. Badly, the delays were clearly lead to severe damage
of companies‘ image, customer relationships as well as their reputation (Zhang
& Figliozzi, 2010).
1.1.2 Empirical Evidences of Congestion‘s Impacts
Again, according to Hartgen (2007), congestion virtually affects all
angles of business like deliveries and shipping, business activities and workers-
customers relationship. It is proven that due to congestion, delivering and
receiving goods and merchandise cost of Charlotte business community lost
about 20.3% of delivery time. In short, that study claimed that traffic congestion
weakens business control and lengthen delivery time. Since the delay lead to
increase in operation cost, Zhang and Figliozzi (2010) did a study on importers
and exporters in China to observe the effect of the delay on their operating costs,
and the results are shown in Table 1.1.
Table 1.1: Costs of transport delays and disruptions
Transport Disruption Related Cost Importers Exporters
Increase administration workload and costs 42.9% 28.6%
Increase transport costs 28.6% 37.1%
Affect sales and promotion plans 35.7% 20.0%
Inventory costs 28.6% 2.9%
Account receivable and cash flow 0.0% 12.2%
Custom-port costs (inspection, storage, clearance, etc.)
7.1% 2.9%
Source: Zhang and Figliozzi (2010)
9
From Table 1.1, it is shown that the transportation delays of delivery
increased importers‘ and exporters‘ operating costs, especially in terms of
administration costs and transportation costs. The results simultaneously showed
the increment of operating costs charged by Logistics Service Providers (LSPs)
to their clients, due to the delays. Other than the delay and cost effects,
Weisbrod and Fitzroy (2011) from Economic Development Research
Incorporation, USA discussed the impact of congestion in a broader view of
economic and as a result, they divided the effects of congestion into seven
classes as well as their effects on LSPs‘ business and economy, as shown in
Table 1.2.
Table 1.2: Seven classes of congestion impact and potential business response
Class of Congestion Impact Implication for Business and Economy
Market and
Fleet Size
delivery area, market scale, fleet size/type,
delivery & reliability cost, assignment flexi
Business & Delivery
Schedules
delivery time shifts, truck dispatch, backhaul
operations, relief drivers, operating schedules
Intermodal Connections access to truck/rail/air/sea interchange terminals
Business Inventory and
Operations Management
inventory requirements, stocking costs, inventory
management/control, cross-docking opportunities
Worker Travel worker time/expense; worker schedule reliability,
service delivery cost
Business Relocation distribution from smaller, more dispersed locations, consolidation of production sites
Externalities: Interactions
with Other Activities
land use & development shifts, costs passed on to
workers and customers
Source: Weisbrod and Fitzroy (2011)
All in all, due to bad effects of congestion to logistics players as well as
the economy, LSPs‘ firms must improve their logistics systems, technology,
practices and ability to suit with the recent congestion problem. Thus, if there
10
are shortcomings in road transportation services like in terms of their service
capability and technologies embedded, it will affect other parties and logistics
performance as a whole. Due to the interest on these effects, we determine this
research to focus on road transportation with the intention to strengthen the road
logistics transportation services performance holistically.
1.1.3 Discussion
In order to make things clear, the literature mentioned above is
summarized into an illustration, as shown by Figure 1.2.
Figure 1.2: Illustrated summarization of how congestion affects business
performance
Source: Trunick (2004), (Sankaran et al., 2005), Systematics (2008),
(Short et al., 2010) and Weisbrod and Fitzroy (2011).
Therefore, from Figure 1.2 above, it is concluded that the issue of traffic
congestion has weaken the business performance of LSPs and other firms due to
delivery delay and rising of operation costs. At this stage, LSPs need to handle
the situation in the best manner to satisfy their customers as well as to sustain its
growth in the industry.
xii
1.1.4 Definition of Terms
Generally, firm performance and business performance carry a little bit
of difference in definitions but they are aimed to the same goals somehow.
Firm‘s ability normally is based on its performance (Bonn, 2000) and the level
of accomplished goal usually defines a firm‘s performance (Achrol & Etzel,
2003). This is why performance mirrored a firm. Different firms adopt different
methods in order to measure their performance based on their goals of business,
as mentioned by Collins & Porras (2000) in Mohamad and Sidek (2013).
According to many scholars, firm performance is measured by financial and
non-financial measures (Bagorogoza & de Waal, 2010; Bakar & Ahmad, 2010;
Darroch, 2005), or in other specific words they are cost and operational service
level (Kunadhamraks & Hanaoka, 2008).
Meanwhile, business performance is the result of operations, comprising the internal or external
achievement of the firm‘s objectives (C.-H. Lin, Peng, & Kao, 2008). Swanson (1999) defined performance as ―the valued productive output of a system in the form of goods or services‖. He
added that performance is also fulfillment and accomplishment. Rubio and Aragón (2009) resisted
that business performance can be categorized into four elements; rational goal (measured by financial indicators), internal process (measured by increased in quality of product and improved
organization), human relations (measured by increased in motivation of employees and reduced in
employees‘ absenteeism) and open system (measured by increased in customer satisfaction, company
The common aims between the firm performance and business
performance is about the achievement, accomplishment and fulfilment of a
firm‘s goals. Moreover, it can be concluded that both of them are measured by
financial and non-financial elements. Therefore, this study is using both terms
simultaneously without doubt, but will focus more on the non-financial
performance of a firm.
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1.2 Problem Statement
The expansion of manufacturing sector nowadays has boosted up the
demand of logistics services all over the world. Traffic volume of each mode of
transportations has increased dramatically year by year, including road
transportation which is rated higher than other modes, except airline (David J.
Bloomberg, 2002). The increment of traffic volumes has led to congestion, as
faced by China (Speece & Kawahara, 1995), New York (Trunick, 2004) and
UK, resulting to delivery time delay, cost increment, customer dissatisfaction
and risk of accident (McKinnon et al., 2009). Year by year passed, Yunus (2012)
reported that Malaysian logistics industry is forecasted to reach MYR203.71
billion by 2016 with the growth of 11.6% annually. This is in line with the
vision of MITI to increase trade between Malaysia and China to US$160 billion
by 2017 (MITI, 2014a).
Regardless the growth of logistics industry and demand in Malaysia,
some studies have found similar issues of congestion in East Coast region
especially in Kemaman and Kuantan (Zuraimi, Mohd Rafi, Mohamed Dahlan, &
Nur Fadiah, 2012) as well as other metropolitan areas in Malaysia (Almselati, Rahmat,
& Jaafar, 2011). Therefore, the LSP firms which operated in the region need to improve
their service capabilities especially in terms of their flexibility in handling expected or
unexpected events caused by the congestion. Empirical study done by Zhang and
Figliozzi (2010) also showed that the congestion has caused delivery delay and
operating costs increased by more than 70%.