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The underlying objective and purpose of this thesis is to test a model that studies relationship between costs to export, cost to import, GDP, per capita income and IT on logistics performance. This research will assist the logistics industry for identifying the opportunities and challenges in terms of their trade logistics performance, what factors affect this benchmarking tool and what steps can the logistics industry take to improvise their performance. The data is selected for 41 countries worldwide on the basis of their land area from World Bank for the year of 2010. When the viability of the model was checked the results shown that all the independent variables contribute some exertions to affect the logistic performance of any country. The exports and imports of goods and services contribute to about 40% and 42% to the logistic performance to be precise. However, GDP, IT, and income per capita have an impact of about 16%, 8%, and 61% to the logistic performance respectively. However, for the countries having lower degree of logistic performance can improve their performance by focusing on their imports and exports of goods and services, and their per capita income which are the factors having enormous effect on the logistic performance of any country.
Factors Affecting Logistic Performance: A Global Cross-Section Supply Chain Study by MUHAMMAD ZAIN SIDDIQUI Reg #: 8709 Submitted to: Mr Farhan Mehboob A thesis submitted in partial fulfillment of the requirements for the degree of Master of Business Administration to the Iqra University Karachi, Pakistan MAY, 2015 Abstract The underlying objective and purpose of this thesis is to test a model that studies relationship between costs to export, cost to import, GDP, per capita income and IT on logistics performance This research will assist the logistics industry for identifying the opportunities and challenges in terms of their trade logistics performance, what factors affect this benchmarking tool and what steps can the logistics industry take to improvise their performance The data is selected for 41 countries worldwide on the basis of their land area from World Bank for the year of 2010 When the viability of the model was checked the results shown that all the independent variables contribute some exertions to affect the logistic performance of any country The exports and imports of goods and services contribute to about 40% and 42% to the logistic performance to be precise However, GDP, IT, and income per capita have an impact of about 16%, 8%, and 61% to the logistic performance respectively However, for the countries having lower degree of logistic performance can improve their performance by focusing on their imports and exports of goods and services, and their per capita income which are the factors having enormous effect on the logistic performance of any country Table of Contents Factors Affecting Logistic Performance Chapter Introduction 4 Factors Affecting Logistic Performance 1.0 Overview The notion of logistics has travelled a long way in recent years As previously logistics was seen as individual components of product flow, such as storing, handling or transport However, now logistics has evolved into comprehensively managed and integrated supply chains Logistics form a significant base for success of organizations and businesses around the world as the logistics processes of distribution, production and sourcing have become global, and so countries need to focus on improving their logistic performance to achieve long-term growth in international markets In terms of global comparison, the importance of logistic services largely depends on the nation’s economic power For instance, the prospects of logistics services have been quite strong in Europe, Japan, and United States for a long time There are certain factors that affect a dynamics of logistics in a country First of all foreign trade, especially export is quite important to increase a country’s economic growth rate (Johnson, 2013) Moreover, export plays a key role for the countries to receive a greater share of the global market Satisfactory and sustainability levels of countries’ export depend on exporting high value-added products and increasing the diversity of products and markets Meanwhile, foreign trade transactions exhibit a complex view and have enhanced the importance of logistics Logistics is considered as an important constituent in the field of service, manufacturing and agriculture industry Moreover logistics has to be smoothly managed so that distribution and production functions can operate effectively According to a research by Hollweg and Wong (2009) cost to import & import of goods and services; cost to export & export of goods and services and GDP are indirectly proportional to logistics performance index On the other hand IT expense is directly proportional to logistics performance In this regard, countries that work on controlling their cost of import, cost of export, GDP, IT enhances the quality of logistics and ensures competitiveness and eventually reach the top positions in the Logistics Performance According to Christopher (2012) efficiency of logistics can be measured through the application of logistics performance index (LPI) This index primarily depends on the quality Factors Affecting Logistic Performance and competence of customs and border management, trade and transport infrastructure and logistics services In this paper, it is worked on the model that studies relationship between costs to export, cost to import, GDP, per capita income and IT on logistics performance This study investigates the affect of GDP, export and import of goods and services, cost to export and import, IT, and income per capita on logistic performance The introductory chapter of this study will provide background information relevant to research questions, its contextual framework, and problem identification, purpose of study, research question, justification and limitation of this research 1.1 Background The prospect of logistics performance starts with its definition According to World Bank, the logistic performance of countries at the same level of per capita income with the best logistics performance experience additional growth of 1% in gross domestic product (GDP) and 2% in trade So it’s essential to improve a countries’ logistics performance as it has significant valuable effects on the statistics of a countries’ economy Additionally no matter if there is successful logistics or not the trade cycle is always present and it eventually relies on the pace and extent of government strategy and measures that will liberalize logistics supply (Havenga, 2011) Furthermore World Bank denotes LPI as an index that captures mainly the main features of the existing logistics environment LPI is deliberated by the efforts of BRIC countries (Brazil, Russia, India and China); World Bank; and various other sophisticated emerging economies Efficient supply chain and logistics of any country can become its competitive advantage over its competitor, so focus should be on improving the Logistics Performance Index of a country LPI, as implied by the acronym, places great emphasis on performance, expressed through the reliability and predictability factor, unlike the conventional performance metrics, such as average delays and direct freight costs, or more generically expressed in terms of time and costs World Bank representatives, experts in the field, and academics, came to the Factors Affecting Logistic Performance conclusion that, currently important indicators such as reliability, predictability and quality of service, along with transparency of processes, cannot be comprehended solely from costs and time information “The predictability and reliability of shipments, while more difficult to measure, are more important for firms and may have a more dramatic impact on their ability to compete” (Arvis, et al 2007:4) 1.2 Problem Statement In the year 2007, Singapore had the highest logistic performance index score of 4.19 with logistic competence of 4.21 which is the highest of all (World Bank) Whereas, when the data was extracted for the year 2010 Germany was the country where logistic performance index found to be 4.11 with logistic competence of 4.11 (World Bank) (Shown below in table 1.2.1) Table: 1.2.1 LPI Score 4.19 LPI Score 4.11 Korinek and Sourdin (2011) study based on low, middle and higher-income countries gives the idea that relationship between logistics and trade is directly proportional Efficient logistics facilitates trade and play a crucial role of transporting goods over international border On the other hand if logistics performance is inefficient, it will result in trade block up due to extra money and time needed (Korinek & Sourdin, 2011) As developed countries are shifting from traditional agriculture and manufacturing model to globalized trade they are increasingly interacting in international markets and need an efficient logistics services to gain competitive advantage Therefore in this study we try to focus on logistics of developed and developing countries and finds out how quality and competency of logistics services is affected by country specific factors such as, GDP, export and import of goods and services, cost to export and import, IT, and income per capita Factors Affecting Logistic Performance 1.3 Purpose of Research As mentioned above the quality logistics performance serves as a competitive advantage for countries This research has tried to find factors which affect the Logistics dynamics and efficacy For this research 41 country’s data will be assessed and influence of different variables will be examined on logistics The independent variables which are selected for this research are also important and critical in today’s world i.e GDP, export and import of goods and services, cost to export and import, trade services, IT, and income per capita This research can serve as a guideline for regulatory bodies to select strategic actions for improving their logistics The fundamental idea of this research is to study the relationship between logistics performance and cost to export, cost to import, GDP, trade services, per capita income and IT (Arvis, et al 2007) on the basis of a model This research will explore the relationship between dependent and independent variables on the basis of a model 1.4 Objectives of Research The objective of this research is to assess the concept of logistics performance and various factors that affect its efficacy The value of logistics performance is dependent on various factors and this paper explores the relationship among them 1.5 Research Questions This study proposes to study the following questions: What is the impact of export and cost of goods and services on Logistics Performance? What is the impact of import and cost of goods and services on Logistics Performance? What is the impact of GDP on Logistics Performance? What is the impact of per capita income on Logistics Performance? What is the impact of Information Technology on Logistics Performance? 1.6 Research Hypothesis HO1: Export and cost of goods and services does not affect Logistics Performance? HO2: Import and cost of goods and services does not affect Logistics Performance? HO3: GDP does not affect Logistics Performance? HO4: Per capita income does not affect Logistics Performance? Factors Affecting Logistic Performance Ho5: Information Technology does not affect Logistics Performance? 1.7 Limitation of Study There are certain limitations in this research Limitation in terms of variables is that we have limited exposure of variables as we included the effect of only cost to export, cost to import, GDP, per capita income and IT on logistics performance, however dynamics of logistics are influenced by various other factors apart from these Moreover, Researchers can include other factors to investigate logistics performance further Another limitation is that this study is conducted on cross sectional data of 2010, so using panel or time series data can offer additional insights about the relationship of dependent and independent variables The data gathered in this research is based on 41 countries that are selected on the basis of their size So further research can include other countries as well Quantitative model has been applied to study association between dependent and independent variables, so qualitative aspects can also be assessed to further gain insights into this topic 1.8 Scope This research comprises on the data of 2010 for 41 countries The data was taken from the website of World Bank The countries were chosen on the basis of their size (area) and logistics data availability Similarly, the research area can be more broaden by taking the data for more countries other than these 41 already selected on the base of their land area Moreover, the research is based on the impacts of costs of exports and imports of goods and services, GDP, IT, and income per capita, where more other variables can be added to gauge the impact on logistic performance Factors Affecting Logistic Performance 10 Chapter Literature Review 10 logistics services The results of this study reveal that Cost to Import & Import of Goods and Services; Cost to Export & Export of Goods and Services and GDP are indirectly proportional to Logistics Performance Index On the other hand IT expense is directly proportional to Logistics Performance Index In this regard, countries that work on controlling their cost of import, cost of export, GDP, IT enhances the quality of logistics and ensures competitiveness and eventually reach the top positions in the Logistics Performance When the viability of the model was checked the results show that all the independent variables contribute some exertions to affect the logistic performance of any country The exports and imports of goods and services contribute to about 40% and 42% to the logistic performance to be precise However, GDP, IT, and income per capita have an impact of about 16%, 8%, and 61% to the logistic performance respectively However, for the countries having lower degree of logistic performance can improve their performance by focusing on their imports and exports of goods and services, and their per capita income which are the factors having enormous effect on the logistic performance of any country 5.2 Managerial Recommendation • With reference to above findings and results, this research suggests that policy-makers must pay attention on controlling its cost of import and export to enhance its logistics • performance index in comparison to other countries Moreover, particular focus should be on increasing GDP and per capita income as it helps to reduce income inequality and foster development According to the research findings, economic indicators such as per capita income and GDP, allow countries to • improve their logistics performance and experience multi-dimensional growth The prospect of advancing Information Technology promotes growth in logistics, so countries should try to adopt the leading logistics technology in their integrated supply chain networks, to improve their global logistics standing 5.3 Future Research • The future researches must incorporate variables other than those discussed in this research (cost to export, cost to import, GDP, per capita income and IT on logistics performance), to assess more significant factors that will help a country to improvise its • logistics performance index The sample time period used for this research is 2010, so future researchers can alter same time period to come to varying conclusion Future researchers can also use panel or time series data as it can offer additional insights about the relationship of dependent and • independent variables Since the data gathered in this research is based on 41 countries that are selected on the basis of their size, so future researchers can conduct research using other countries as well • Quantitative model has been applied to study association between dependent and independent variables, so qualitative aspects can also be assessed to further gain insights into this topic References Arvis, J F., Mustra, M A., Ojala, L., Shepherd, B., & Saslavsky, D (2012) Connecting to compete 2012: Trade logistics in the global economy Arvis, J F., Mustra, M A., Panzer, J., 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sustainable competitive advantage International Journal of Logistics: Research and Applications, 14(1), 6175 Solakivi, T., Töyli, J., Engblom, J., & Ojala, L (2011) Logistics outsourcing and company performance of SMEs: evidence from 223 firms operating in Finland.Strategic Outsourcing: An International Journal, 4(2), 131-151 Töyli, J., Häkkinen, L., Ojala, L., & Naula, T (2008) Logistics and financial performance: An analysis of 424 Finnish small and medium-sized enterprises International Journal of Physical Distribution & Logistics Management, 38(1), 57-80 Turkson, F E (2011) Logistics and bilateral exports in developing countries: A multiplicative form estimation of the logistics augmented gravity equation (No 11/06) CREDIT Research Paper Waters, D., & Rinsler, S (2014) Global logistics: New directions in supply chain management Kogan Page Publishers World Economic Forum (2013) “Outlook on the Logistics & Supply Chain Industry 2013” Retrieved from: http://www3.weforum.org/docs/WEF_GAC_LogisticsSupplyChainSystems_Outlook_ 2013.pd Yildiz, T (2014) Business Logistics: Theoretical and Practical Perspectives with Analyses Turkay Yildiz Appendix 1: Sample Countries Countries taken from World Bank Site, on the basis on country size in ascending order Countries/ Variables → ↓ Russian Federation China USA Canada Brazil India Argentina Kazakhstan Algeria Saudia Arabia Land area (sq km) Trade in services (% of GDP) Imports of goods and services (BoP, current US$) Exports Logistics Communicatio of goods Cost to Cost to performanc ns, computer, and export import e index: etc (% of services (US$ per (US$ per Overall service (BoP, container container (1=low to exports, BoP) current ) ) 5=high) US$) 16376870 7.977257 3.22E+11 43.84916 9327480 5.994173 1.52E+12 48.76669 9147420 6.56328 2.34E+12 47.37401 9093510 10.17227 4.93E+11 49.29414 8459420 4.40558 2.44E+11 58.08165 2973190 14.28498 4.4E+11 71.56412 2736690 7.396604 6.81E+10 46.52113 2699700 10.52689 4.42E+10 20.43275 2381740 9.551829 5.08E+10 64.97476 2149690 19.40039 1.74E+11 6.545371 4.46E+1 1.74E+1 1.84E+1 4.62E+1 2.34E+1 3.49E+1 8.12E+1 6.58E+1 6.07E+1 2.62E+1 2585 2685 2.61 500 545 3.49 1050 1315 3.86 1610 1660 3.87 1790 1975 3.2 1055 1105 3.12 1480 1810 3.1 3005 3055 2.83 1248 1318 2.36 765 936 3.22 GDP (current US$) 1.49E+1 5.93E+1 1.44E+1 1.58E+1 2.14E+1 1.68E+1 3.69E+1 1.48E+1 1.62E+1 4.51E+1 GDP per capita (curren t US$) 10481.3 4432.96 46611.9 46212.0 10992.9 1375.38 9123.71 9070.01 4566.89 16423.4 Mexico Indonesia Peru Angola South Africa Colombia Egypt, Arab Rep Nigeria Venezuela, RB Pakistan Turkey Chile Ukrain France Thailand Spain 1943950 3.89681 3.27E+11 1.872499 1811570 6.052753 1.54E+11 40.48767 1280000 6.334541 3.49E+10 16.40399 1246700 23.77959 3.54E+10 11.09877 1214470 8.929244 1E+11 15.73147 1109500 4.370378 4.67E+10 24.97717 995450 17.59968 5.99E+10 12.96299 910770 10.71713 6.78E+10 17.10158 882050 3.276982 4.97E+10 29.34841 770880 7.761895 4E+10 72.36463 769630 7.45612 1.97E+11 9.718889 743530 10.45442 6.7E+10 21.90269 579320 21.78881 7.32E+10 29.09048 547660 14.23293 7.61E+11 50.25206 510890 24.81778 2.07E+11 23.44137 498800 15.36936 4.08E+11 36.35059 3.14E+1 1.75E+1 3.93E+1 5.15E+1 9.97E+1 4.53E+1 4.88E+1 7.98E+1 6.76E+1 2.81E+1 1.56E+1 8.18E+1 6.93E+1 7.11E+1 2.28E+1 3.81E+1 1420 1880 3.05 644 660 2.76 860 880 2.8 1850 2840 2.25 1531 1807 3.46 1770 1700 2.77 613 755 2.61 1263 1440 2.59 2590 2868 2.68 611 680 2.53 990 1063 3.22 745 745 3.09 1560 1580 2.57 1078 1248 3.84 625 795 3.29 1221 1350 3.63 1.04E+1 7.08E+1 1.54E+1 8.25E+1 3.64E+1 2.86E+1 2.19E+1 2.29E+1 3.94E+1 1.76E+1 7.31E+1 2.16E+1 1.36E+1 2.55E+1 3.19E+1 1.38E+1 9127.54 2951.69 5283.22 4321.94 7271.72 6186.02 2698.36 1443.21 13657.7 1016.61 10049.7 12639.5 2973.98 39170.2 4613.68 29956.1 Iraq Sweden Paraguay Japan Germany Malaysia Oman Norway Poland Finland Philippines Italy New Zealand Ecuador UK 434320 15.66197 4.72E+10 27.06239 410340 23.69149 1.96E+11 63.92452 397300 12.15252 1.07E+10 67.74798 364500 5.448338 7.97E+11 59.66652 348610 15.56605 1.37E+12 54.82774 328550 26.32531 1.89E+11 29.77287 309500 14.15726 2.42E+10 24.65753 305470 20.30881 1.19E+11 38.8821 304200 13.26956 2.07E+11 41.79351 303900 22.72641 9.27E+10 75.24133 298170 12.75368 7.31E+10 70.94005 294140 10.16914 5.86E+11 40.28244 263310 12.98262 3.89E+10 24.47001 248360 7.732078 2.27E+10 22.4717 241930 18.84505 7.32E+11 51.74402 5.46E+1 2.23E+1 9.99E+0 8.72E+1 1.56E+1 2.32E+1 3.85E+1 1.71E+1 1.98E+1 9.64E+1 6.48E+1 5.45E+1 4.09E+1 1.96E+1 6.68E+1 3550 3650 2.11 697 735 4.08 1440 1750 2.75 880 970 3.97 872 937 4.11 450 450 3.44 725 660 2.84 955 929 3.93 884 884 3.44 540 620 3.89 630 730 3.14 1245 1245 3.64 855 825 3.65 1455 1402 2.77 950 1045 3.95 8.11E+1 4.63E+1 1.83E+1 5.49E+1 3.28E+1 2.47E+1 5.78E+1 4.18E+1 4.7E+11 2.35E+1 2E+11 2.04E+1 1.42E+1 5.8E+10 2.26E+1 2532.32 49359.8 2840.35 43063.1 40163.8 8690.57 20790.8 85443.0 12303.2 43863.9 2140.12 33786.6 32407.0 4008.23 36256.0 ... taken from World Bank Site, on the basis on country size in ascending order Countries/ Variables → ↓ Russian Federation China USA Canada Brazil India Argentina Kazakhstan Algeria Saudia Arabia... L., & Subramanian, U (2005) Global logistics indicators, supply chain metrics, and bilateral trade patterns Havenga, J H (2011) Trade facilitation through logistics performance: The enabling role... leading to provision of easily available information to all partners of supply chain These initiatives have also resulted in creation of a particular service, known as ‘virtual logistics chain? ??