A STUDY ON MEASURING SERVICE QUALITY AT NETWORK LOGISTICS PVT LTD

By

JITHENDRA.D 310011631017

A PROJECT REPORT Submitted to the FACULTY OF MANAGEMENT SCIENCES In partial fulfillment for the award of the degree of MASTER OF BUSINESS ADMINISTRATION

ANNA UNIVERSITY Tharamani Campus, Chennai 600113 July , 2013

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Certified that the Project report titled A study on the measuring service quality at Network Logistics Private Limited is the bonafide work of Mr.D.JITHENDRA, 310011631017 who carried out the work under my supervision. Certified further that to the best of my knowledge the work reported herein does not form part of any other project report or dissertation on the basis of which a degree or award was conferred on an earlier occasion on this or any other candidate.

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ABSTRACT
Logistics is a catalyst for economic development and trade-in an increasingly globalized world where goods are moving farther, faster and cheaper than ever. In the fastpaced and highly competitive market, service quality and customer satisfaction play an important role in determining success of an organization. This research applies the Logistic Service Quality (LSQ) model, using variables which include timely delivery, physical facilities, quality of information, quality of personnel, assurance and reliability in determining the most effective dimension in providing sound service quality to achieve customers satisfaction in the current market condition. This because the performance of a service-based company is based solely through their ability to provide good service to their customers in orders to satisfy their needs. This research will be carried out on Network Logistics Private Limited (NLPL), which is a Third Party Logistics (3PL) company. The research will measure the service quality of NLPL using SERVQUAL instrument and KANOS MODEL to categorize logistics service quality dimensions and their elements and understand the demands of users. The data were collected through a questionnaire survey in which a customers responded to a series of 40 attribute questions based on six key dimensions timely delivery, physical facilities, information, personnel, assurance and reliability. Hypotheses were taken on the fact that there is a gap existing between expectation and perception in this dimension and all hypotheses are proved significant and they all are accepted after conducting Paired T test, one sample t test and correlation test. Therefore it is better to conclude that the network logistics private limited is not performing up to the satisfaction of the customers and they need to take corrective steps to minimize these gaps as early as possible. The study concludes with some recommendations to improve the quality to attract the customers.

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ACKNOWLEDGEMENT

I take immense pleasure in thanking our H.O.D, Dr.S.N.GEETHA,Department of Management Studies, Anna University, CPT Campus, Tharamani, Chennai for all her valuable assistance in the project work.

I wish to express my deep sense of gratitude to my Internal Guide, K.Prabhakaran, for his able guidance and useful suggestions, which helped me in

completing the project work, in time.

I wish to express my deep gratitude to Mr.R.MUNAVER HUSSAIN, Operations Department manager NETWORK LOGISTICS PRIVATE LIMITED my guide who has been a great source of guidance, motivation, and encouragement. It has been a wonderful learning experience throughout and this work would have been impossible without him.

Finally, yet importantly, I would like to express my heartfelt thanks to my beloved parents for their blessings, my friends/classmates for their help and wishes for the successful completion of this project.

D.JITHENDRA

CONTENTS CHAPTER.NO. NAME OF THE CHAPTER PAGE.NO

ABSTRACT ACKNOWLEDGEMENT LIST OF TABLES LIST OF FIGURES LIST OF ABBREVATIONS 1 1.1 1.2 1.3 1.4 1.5 1.6 2 3 4 5 5.1 5.2 5.3 INTRODUCTION INDUSTRY PROFILE COMPANY PROFILE OBJECTIVE OF THE STUDY NEED FOR THE STUDY SCOPE OF THE STUDY LIMITATIONS OF THE STUDY REVIEW OF LITERATURE RESEARCH METHODOLOGY ANALYSIS AND INTERPRETATION FINDINGS SUGGESTIONS AND CONCLUSION FINDINGS SUGGESTIONS CONCLUSION BIBLIOGRAPHY APPENDICES ( Questionnaire)

iii iv vi vii viii 1 13 23 36 37 38 39 40 46 56 69 69 71 72 73 75

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LIST OF TABLES No 1.1 1.2 1.3 1.4 1.5 3.1 3.2 3.3 3.4 4.1 4.2 4.3 4.4 4.5 4.6 4.7 4.8 4.9 4.10 Title Key opportunities logistics industry Major players logistics industry Key players in Rs 100mn license fee category Market potential analysis Details of network logistics private limited Calculation of SERVQUAL scores SERVQUAL importance weights Calculation of weighted SERVQUAL scores Functional and dysfunctional question in the KANO questionnaire Reliability statistics for P and (P-E) scores SERVQUAL output (attribute) SERVQUAL output (dimension) Friedman test (mean) Test statistic for friedman test (mean) Paired t test Correlation test KANOS model output one KANOS model output two CS coefficients Page No 16 17 19 21 23 47 48 48 53 56 58 59 60 61 62 63 64 65 66

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LIST OF FIGURES No 1.1 1.2 1.3 1.4 1.5 1.6 1.7 3.1 3.2 4.1 4.2 Service quality gaps KANO'S model Ownership pattern of NLPL Logo of NLPL Network of NLPL Chronology of vessel / rig clearance Clients of NLPL KANO evaluation table KANOS model evaluation process SERVQUAL output (dimension) SII & DDI Title Page No 6 10 24 25 25 26 33 53 54 59 68

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LIST OF ABBREVIATIONS

Abbreviations TPL CLNI PDSQ LSQ DLA ASRS AGV CAGR EMS MTO NMDP ICD CFS PREM NLPL CHA MOHA MOD MMD ODAG OSV DSV CBDT Third Party Logistics

Expansion

Page No 2 4 4 4 7 8 8 13 14 15 15 16 16 21 23 23 32 32 32 32 32 32 32

Council Of Logistics Management Physical Distribution Service Quality Logistics Service Quality Defense Logistics Agency Automated Storage And Retrieval System Automated Guided Vehicle Compound Annual Growth Rate Express Mail Service Multimodal Transport Operation National Maritime Development Program Interface Control Document Container Freight Station Poverty Reduction And Economic Management Network Logistics Pvt. Ltd Custom House Agency Ministry Of Home Affairs Ministry Of Defense Mercantile Marine Department Offshore Defense Advisory Group Offshore Supply Vessels Dive Support Vessel Central Board Of Direct Taxes

CHAPTER I INTRODUCTION
1.1 INTRODUCTION TO STUDY 1.1.1 Logistics Logistics is the art and science of managing and controlling the flow of goods, energy, information and other resources like products, services, and people, from the source of production to the market place. It is difficult to accomplish any marketing or manufacturing without logistical support. It involves the integration of information, transportation, inventory, warehousing, material handling, and packaging. The operating responsibility of logistics is the geographical repositioning of raw materials, work in process, and finished inventories where required at the lowest cost possible. The word of logistics originates from the ancient Greek logos , which means ratio, word, calculation, reason, speech, and oration. Logistics as a concept is considered to evolve from the military's need to supply them as they moved from their base to a forward position. In ancient Greek, Roman and Byzantine empires, there were military officers with the title Logistikas who were responsible for financial and supply distribution matters.

1.1.2 Logistics management Logistics Management is that part of the supply chain which plans, implements and controls the efficient, effective forward and reverse flow and storage of goods, services and related information between the point of origin and the point of consumption in order to meet customers' requirements. 1. Business logistics: Logistics as a business concept evolved only in the 1950s. This was mainly due to the increasing complexity of supplying one's business with materials and shipping out products in an increasingly globalized supply chain, calling for experts in the field who are called Supply Chain Logisticians. This can be defined as having the right item in the right quantity at the right time for the right price and is the science of process and incorporates all industry sectors. The goal of logistic work is to manage the fruition of project life cycles, supply chains and resultant efficiencies.

2. Production logistics: The term is used for describing logistic processes within an industry. The purpose of production logistics is to ensure that each machine and workstation is being fed with the right product in the right quantity and quality at the right point in time. The issue is not the transportation itself, but to streamline and control the flow through the value adding processes and eliminates non-value adding ones. 1.1.3 The development of third party logistics (3pl) Companies have different options to consider in handling their logistics activities effectively and efficiently. They can Provide the functions in-house Own logistics subsidiaries Outsource the function and buy the service. Traditionally, logistics activities like distribution, inventory management, order processing, or materials management were handled internally by firms as support functions and were given low priority compared to other business functions. One can divide the principles underlying organizations decision to outsource into two groups, the internal and the external. The internal principle refers to recognizing a lack of in-house resource availability. The external principle puts emphasis on a firm's external competitive environment. Accordingly, trends like globalization, lead time reductions, and emerging technology contribute to the interest in outsourcing. Globalization increases the complexity of supply chains, given that the best supplier may be found halfway around the world, and customer needs are often as diverse as the countries in which they live. Lead time reductions, incorporating the shift to just-in-time production schemes, add to the increasing complexity and cause inventory and logistics control to be crucial to manufacturing and distribution operations. A recent study, conducted by Lieb and Butner (2007) among CEOs of third-party logistics providers in North America, reveals several industry dynamics that are currently operating in the marketplace. The Top 5 of these dynamics consists of 1. A continuing downward pressure on prices 2. A growing customer interest in outsourcing a broader array of logistics services 3. An increased pressure to internationalize company service offerings 4. Large-scale mergers of 3PL providers in North America 5. Increasing customer expectations with respect to IT support

Two of these dynamics, a continuing downward pressure on prices and pressures to internationalize service offerings, are also among the Top 5 of the main industry problems.

1.1.4 The importance of customer service and satisfaction in logistics The importance of customer service was recognized over 50 years ago while logistics, then known as physical distribution had been one of the longest standing subjects of study in marketing. However, the focus on logistics customer service and the related concept of customer satisfaction and service quality has only increasingly developed in the early 1970s and been seen as a key part of future research in the logistics discipline. Since then, more work has shifted the focus of customer service definition from a supplier's viewpoint to a customer perspective. This was due to the fact that firms that provide innovative customer service would benefit from increased customer satisfaction, closer customer- supplier relationships, increased customer loyalty, and profitability and a differential competitive advantage. Accordingly, it reviews related literature on customer service, satisfaction and service quality in logistics. It also demonstrates various ways in which measuring customer satisfaction has evolved in the literature. Since it was given attention in the early 1970s,

the concept of logistics customer service remains important until today. Much of the influence in developing the concept in the early 1970s to Mid 1980s came from the operations management, management science, and to some extent, marketing. The importance of customer service and satisfaction in logistics can be viewed from chronological perspectives.

1.1.5

Logistics leads to competitive advantage In the early years of the "customer focus" era, companies realized that in order to be

successful in business, they must integrate the ideas of having the right product, at the right price, combined with the right promotion and available at the right place, which are the four Ps of the marketing mix. A company may improve their competitive position by allocating resources more effectively and efficiently to these components of the marketing mix to create a market offering. It acts as the binding and unifying force for the total logistics supply chain of warehousing, transportation, inventory management, order processing, and related information flows.

1.1.6 Measuring logistics service performance In a study on the quality and productivity in the logistics process by The Council of Logistics Management (CLNI), Byrne and Markham (1991) define quality in logistics as the "means meeting agreed to customer requirements and expectations, including the following dimensions; (1) ease of inquiry, order placement and order transmission, (2) timely, reliable, order delivery and communication, (3) accurate, complete, undamaged orders and error-free paperwork, (4) timely and responsive post-sales support, (5) accurate, timely generation and transmission of information among the functions of business and with external parties to support the planning, management and execution of the activities". From this definition, the focus was given to the ease of ordering procedures, timeliness of delivery and communication, accuracy of orders and information as well as responsiveness. They measure logistics quality based on the ability to distribute a product or materials in conformance with customer requirements and standards. Specifically, logistics quality measures the ability to deliver products, materials and services without errors, defects, mistakes, or other gaps from customers' expectations. The developments of these definitions form the starting point of using a service quality approach to measure customer satisfaction.

1.1.7

Logistics service quality By taking into consideration SERVQUAL and other service quality research in

marketing, Mentzer et al (1999) expanded the use of the service quality concept into the logistics context. They argue that customer service should be combined with Physical Distribution Service Quality (PDSQ) to conceptualize Logistics Service Quality (LSQ). Thus, PDSQ, which consists of timeliness, availability and order condition, are viewed as the critical aspects of the customer's perception of LSQ. Other components comprise of marketing customer service components that were developed in line with traditional service quality research in marketing, which was based on the notion that logistics services involve people who often take orders and deliver products and procedures for placing orders and handling discrepancies. The interactions that the customers have with these people and procedures should affect their perceptions of overall logistics services.

1.1.8 Service quality gaps There are seven major gaps in the service quality concept, which are shown in Figure 1. The model is an extension of Parasuraman et al. (1985). According to the following explanation, the three important gaps, which are more associated with the external customers, are Gap1, Gap5 and Gap6; since they have a direct relationship with customers. 1. Gap1: Customers expectations versus management perceptions: as a result of the lack of a marketing research orientation, inadequate upward communication and too many layers of management. 2. Gap2: Management perceptions versus service specifications: as a result of inadequate commitment to service quality, a perception of unfeasibility, inadequate task standardization and an absence of goal setting. 3. Gap3: Service specifications versus service delivery: as a result of role ambiguity and conflict, poor employee-job fit and poor technology-job fit, inappropriate supervisory control systems, lack of perceived control and lack of teamwork. 4. Gap4: Service delivery versus external communication: as a result of inadequate horizontal communications and propensity to over-promise. 5. Gap5: The discrepancy between customer expectations and their perceptions of the service delivered: as a result of the influences exerted from the customer side and the shortfalls (gaps) on the part of the service provider. In this case, customer expectations are influenced by the extent of personal needs, word of mouth recommendation and past service experiences. 6. Gap6: The discrepancy between customer expectations and employees perceptions: as a result of the differences in the understanding of customer expectations by front-line service providers. 7. Gap7: The discrepancy between employees perceptions and management perceptions: as a result of the differences in the understanding of customer expectations between managers and service providers.

Figure 1.1 : Service Quality Gaps

According to Brown and Bond (1995), "the gap model is one of the best received and most heuristically valuable contributions to the services literature". The model identifies seven key discrepancies or gaps relating to managerial perceptions of service quality, and tasks associated with service delivery to customers. The first six gaps (Gap 1, Gap 2, Gap 3, Gap 4, Gap 6 and Gap 7) are identified as functions of the way in which service is delivered, whereas Gap 5 pertains to the customer and as such is considered to be the true measure of service

quality. The Gap on which the SERVQUAL methodology has influence is Gap 5. In the following, the SERVQUAL approach is demonstrated. Empirically validated on the customers of a single large logistics provider firm, Defense Logistics Agency (DLA) in the United States, LSQ is a scale for measuring logistics service quality that is conceptualized as six dimensions: reliability, information quality, assurance, staff and officers, timely delivery and physical facilities. Mentzer et al (2001) extended Mentzer et al's (1999) study by conceptualizing the six dimensions of LSQ as a process, by which perceptions of logistics service components affect one another and eventually lead to customer satisfaction across order placement, order receipt and satisfaction. 1. Reliability: This is the assessment of firms consistency and dependability in service performance. Through these items, it is evaluated that how well the service providers can keep their promise. The reliability dimension is deemed to be the most important among all the dimensions. The questions that are used to assess the reliability gap covers the areas like- keeping promise, complain handling, providing the correct service at the first time, served at the promised time, keep an error free record. Service providers ability to handling complains, deliver services on time, help to solve problems, perform right the first time, inform about events and services have been taken as the variables of reliability dimension by different researchers. 2. Assurance: Consistent with the previous research in social psychology and marketing channel relationships, trust in this study is defined as "the customer's perceived credibility and benevolence of a 3PL provider". Doney and Cannon (1997) emphasize the relevance of this definition in an industrial buying context due to some degree of risk in a purchase situation indicating the customer's trust in a 3PL provider firm as well as its contact person. The motivation behind this definition is explained below. It is generally agreed in the marketing literature that trust is essential industrial marketing settings as a key ingredient for successful relationships. In a third party logistics alliance study Moore (1998) demonstrates that trust is crucial in 3PL's relationship with the customers. Doney and Cannon (1997) consider trust as an important pre-requisite for building long-term relationships. 3. Timely delivery: Customers care most that the orders must arrive at the customer's premises as promised. In a broader perspective, it refers to the length of time between

order placement and receipt. These situations are represented by the timeliness dimension. This delivery time can be affected by the problems during transportation that may delay the transportation time. It could also be influenced by back-order time when products ordered are not available in stock. 4. Staffs and officers: Staffs and officers refer to the customer orientation of the supplier's logistics contact people. Having considered the fact that logistics services involve personnel who often take orders and deliver products, and are involved in procedures for placing orders and handling discrepancies; staffs and officers becomes one of the most vital variables in delivering service. Mentzer et al (2001) highlight the positive influence of staffs and officers on perceptions of timeliness in all four segments (general, textiles, electronics and construction) in their study. Most authors recognize that customers care about whether customer service personnel are knowledgeable, empathies with their situation, and help them resolve their problems. Parasuraman et al (1985) argue that in most service encounters, quality perceptions are formed during the service delivery. Similarly, Suprenant and Solomon (1987) suggest service quality perceptions are tied more to the service process, which involves personnel contact, than to the resulting service outcome. As such, staffs and officers is an important aspect of the employee-customer interface. 5. Physical facilities: In this dimension, the service provider must provide the following range of vehicles and conveyers. The vehicles are Pallet trucks, Walkie stackers, Sitdown counterbalance, Stand-up counterbalance, Straddle trucks, Side-loader trucks, Turret trucks, Hybrid trucks, PalletASRS machines, Rail-guided order pickers, Wireguided order pickers, AGVs, Manual cart, Single pallet jack, Double pallet jack, Manabroad pallet jack, Slip sheeter, Tugger etc. The conveyers are Non-powered roller, Powered roller, Powered belt, Skate wheel, Tow line, Pallet conveyer, Extensible, Tilt-tray sorter etc. 6. Information quality: The way customers perceive the information given by the suppliers/ service providers with regard to the variety of products that the customer may choose, forms the information quality construct. The quality of the information especially in terms of adequacy and availability of the products is very important to customers so that they are able to use the information to make decisions.

1.1.9 SERVQUAL SERVQUAL is used as a diagnostic technique for uncovering broad areas of an organization's service quality strengths and weaknesses. In 1993, Zeithaml et al. addressed what they viewed as a lack of consensus among researchers on the enlarged definition base of customer service. They expanded SERVQUAL to include the relationships among customer service expectation, service level antecedents, perceived service, service quality, customer satisfaction, and other intervening factors. Their research made a major contribution to the study of service marketing. Zeithaml et al. defined two additional gaps in service quality. One is the perceived service superiority gap which arises from a difference between desired service and perceived service. Desired service is that which customers want or desire before encountering a service. Perceived service is the customers' perception of the service level received. The other gap is the perceived service adequacy gap which arises from a difference between perceived service and adequate service. Perceived service was previously defined. Adequate service refers to the minimum level of service that customers are willing to accept. While service quality is a function of the perceived service gaps, customer satisfaction results from comparing predicted service to perceived service. Predicted service is the level of service that customers believe they are likely to get, while perceived service is how they feel after receiving the service. The present research differentiated service quality from customer satisfaction. This research focused on how to improve service quality and at the same time provide input into an innovation process. Kano's model is proposed to be integrated into SERVQUAL in order to eliminate the linearity assumption and to also provide innovative inputs. Kano's model categorizes the attributes of a product or service based on how well the attributes are able to satisfy customer needs. It is, therefore, able to help SERVQUAL to prioritize the improvement of an organization's weaknesses based on the category of need that can lead to the highest customer satisfaction. Kano's model can, additionally, enable SERVQUAL to focus on the attractive attributes that are most favored in the product/service innovation process. The following section describes how Kano's model categorizes the attributes of a product or service based on their ability to satisfy customer needs.

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1.1.10 KANOs model

Kano et al. (1984) developed a model to categorize the attributes of a product or service based on how well they are able to satisfy customer needs. The following are the popularly named Kano customer need categories (see also Figure 2): The must-be or basic needs: For these needs, customers become dissatisfied when performance of the service attribute is low. However, customer satisfaction does not rise above neutral even with a high performance of the service attribute. For instance, having unfriendly sales assistants causes customer dissatisfaction. Having friendly sales assistants, however, does not raise the level of customer satisfaction. The one-dimensional or performance needs: For these needs, customer satisfaction is a linear function of the performance of the service attribute. High attribute performance leads to high customer satisfaction. For example, in consumer shopping, a discount is likely to be a performance need where - within limits - larger discounts result in higher customer satisfaction. The attractive or excitement needs: Figure 1.2: Kanos Model for these needs, customer satisfaction

increases super-linearly with increasing attribute performance. There is, however, not a corresponding decrease in customer satisfaction with a decrease in attribute performance. For instance, a cosmetics customer may not be dissatisfied if there is no free bonus, but may be more satisfied if a bonus is provided. Considering Kano's model, one sees how it may not be enough to merely satisfy customers by meeting only their basic and performance needs. In a highly competitive marketplace, organizations need to adopt strategies and to create service attributes targeted specifically at exciting customers and over-satisfying them. Shen et al. (2000) discussed another important implication of Kano's model concerned with the timely delivery of products and services. Kano's model posited that attributes that had

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once been attractive, over time, become one-dimensional. With further time, they are taken for granted and fall into the category of meeting only customers' basic needs. Thus, the timely and continual development and introduction of services with innovative and novel attributes are important. Based on publications of Kano's model, Matzler and Hinterhuber (1998) summarized its following benefits: 1. Kano's model promotes understanding of product/service requirements. The attributes that have the greatest influence on customer satisfaction can be identified. 2. It provides valuable guidance in the following trade-off situation. If two service attributes cannot be promoted simultaneously due to technical or financial reasons, the attribute that has greater influence on customer satisfaction, can be determined. 3. The use of Kano's model can lead to developing a wide range of product/ service differentiation by examining the attractive attributes. The attractive attributes are the key to beating the competition in the marketplace. Despite the above benefits, Kano's model is restricted by several limitations (Bharadwaj and Menon, 1997). The first is that it classifies, but does not quantify either the numerical or the qualitative performance of the attributes. The second is that the model does not provide an explanation of what drives customers' perceptions, why the particular attributes are important to the customers, and what the customers' behavioral intentions are. Considering the functions of Kano's model, integrating it into SERVQUAL can help the latter to prioritize which service gaps to focus efforts on. The entire service development process can be further improved if periodic measurements can be systematically deployed into pragmatic ways for improvement. This is where quality function deployment can be useful.

1.1.11 five categories of quality elements 1. Attractive quality: when present, customers would be satisfied; yet when it is not present, customers would still accept without dissatisfaction. The corresponding element in Herzbergs theory is the motivator factor.

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2. One-dimensional quality: when present, customers would be satisfied; it varies in intensity; more the quality, higher the level of satisfaction, and vice versa; yet when it is not present, customers would be dissatisfied. 3. Must-be quality: customers believe that this quality is a necessity; when it is not present, customers would be dissatisfied. The corresponding element in Herzbergs theory is the hygiene factor. 4. Indifferent quality: customers would be indifferent whether the quality is present. 5. Reverse quality: when present, customers would be dissatisfied, and vice versa.

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1.2

LOGISTICS INDUSTRY PROFILE The Logistics industry includes five broad segments ocean freight, rail freight, air

freight, trucking and third party Logistics (3PL) services. The current size of the Indian Logistics Industry is estimated around $225bn and is expected to reach around $350bn by 2015. As per industry estimates as provided by the Fitch Rating Agency, there is a positive future outlook for the Indian Logistics Industry and it is estimated that the industry will grow at 15-20% over the next few years. Several factors helped the growth of logistics industry in India over the last decade that include changing tax system as well as a rapid growth in industries such as automobile, pharmaceuticals, FMCG and retail . 70% of the total domestic product is transported through the road network and 15% through the rail network. Domestic companies are willing to expand their efficiency to meet rising demand globally according to a study by industry body ASSOCHAM. Backed by strong economic fundamentals, the Indian Logistics Industry is slated for a 15% CAGR to size up to USD $350bn by 2015. Logistics costs in India are estimated to be approximately 13% of GDP which is considerably high when compared to the corresponding figures for other major economies of the world (as per World Bank 2010 report). For example in 2011 the logistics costs in the European Countries accounted for 7.15% of GDP (as per an article in The Hindu). Higher logistics costs are mainly due to poor infrastructure facilities in the country. The higher logistics cost represents higher products/services cost in the international market. The countrys organized logistics market represents 6% of the total market. The three major contributors for the growth of logistics industry are: emergence of organized retail, increase in foreign trade and India becoming a global manufacturing hub Growth in the logistics industry depends on infrastructure availability and involvement of private players and increased government spending which will catalyze the growth in the industry. 1.2.1 Growth drivers 1. Increased demand of 3PL services 2. Streamlining of indirect tax structure 3. Investment in transportation infrastructure 4. Infusion of qualified work force 5. Recognition of logistics management as a strategic tool 6. Globalization of manufacturing sectors

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1.2.2

Forces impacting logistics industry

(Porters five forces model) 1. Threat of new entrants: No entry barrier in terms of requirement for licensing needs and industry is vulnerable to easy scale up and intense competition. 2. Threat of Substitutes: The industry is highly customer oriented with multiple vendor options available to customers. 3. Bargaining power of consumers: A few large users of the industry and companies (e.g. the automobile industry) are able to significantly squeeze transporters. 4. Bargaining power of Suppliers: Government influence on fuel prices makes it difficult for players to predict, control and pass through fuel costs to customers. 5. Rivalry among competitors: Lack of differentiation in services leads to commoditization and further price erosion. 1.2.3 Key trends Rising investment in the rail and port spaces also fuels growth in allied industries like wagon manufacturing, port handling equipment, railway electrification systems and construction companies. 1. 3PL Services: Logistics services like transportation, warehousing, cross docking, inventory management, packing and freight forwarding are all part of third party logistics services. Companies in India currently outsource an estimated 52% of logistics, and 3PL represents only 1% of logistics cost. As of now, the 3PL activity is limited to only few industries like automotive, IT hardware, and telecom and infrastructure equipment. 2. Global Players: The industry is becoming more competent with entry of global giants like Gazeley Broekman (Walmarts Logistics partner), CH Robinson and Kerry logistics and large Indian Corporate houses like Tata, Reliance and Bharti group. A series of mergers and acquisitions like DHL acquiring Blue Dart, TNT acquiring Speedage Express Cargo Service and Fedex buying over Pafex, are also leading to consolidation of the industry at various levels and segments. 3. Express Logistics: Organized players have a monopoly over the express logistics industry. 65% of express business is in the hands of organized players, while semiorganized and unorganized players account for 25% and then the remaining 10% of the market by EMS Speed Post. On the domestic front, unorganized players hold

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41% of the market share based on price advantage and organized players account for 45% and EMS Speed Post the remaining 14%. 4. Warehouses: Warehouses have become key growth drivers in the logistics industry. Warehousing does not only provide conventional storing services, but also provides value-added services like consolidation and breaking up of cargo, packaging, labelling, bar coding and reverse logistics etc. Warehousing and related activities account for approximately 20% of total logistics industry and as per KPMG, an additional 120million square feet of warehousing space is needed in 2013 to meet demand gap in storage space. Our view is that warehousing will see a lot of investment in the coming years. 5. Logistics Parks: About 110 logistics parks spread over approximately 3,500 acres at an estimated cost of $1bn are expected to be operational and an estimated 45mn sq.ft of warehousing space with an investment of $500mn is expected to be developed by various logistics suppliers in the coming year. Majority of these logistics parks are planned in close proximity to state capitals. However, availability of large land parcels at relatively low cost, connectivity to multiple markets across states and industrial clusters has led to the emergence of some Tier 2 and Tier 3 cities as favoured destinations for the development of logistics parks and warehouses. To reduce the transportation cost and for quicker movement of cargo, Multimodal transport operation (MTO) is introduced which helps exporters with less documentation (for instance single document for all modes of transport). 1.2.4 Government initiative in the sector To emphasis the significance of government initiatives in the logistics industry and to increase the competence in the sector the government has introduced private sector participation, especially in the port sector The major initiative in transport infrastructure is an introduction of National Maritime Development Program (NMDP) with an investment of Rs 568bn. NMDP would be addressing the challenges of the growing international traffic demand of the country along with developing the port facilities at par with world class standards. In order to liberalize the railway services, the government opened its doors of container business to private parties The Government has removed the differential statelevel taxes that were causing higher unit and inventory carrying costs, and introduced uniform Goods and Services Tax (GST) to reorganize warehousing system in India.

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FDI Regulations In general 100% FDI under the automatic route is permitted for all logistics services. 1.2.5 Key opportunities
Service Container Haulage Capital Requirement Capital Intensive Entry Barrier High entry barrier in road segment Customer Needs Scheduled services and strong ICD network Drivers Government approval for privatization of rail container operation Establishment of dedicated freight corridor Standardization of containers Growing trade volume Opportunities Approval to private players for rail operation and rising demand from the railways to boost demand for wagon manufacturers CFS/ICDs that run their own container terminal, freight forwarder or shipping line are likely to gain from the surge in ocean freight

CFS

The CFS Medium business is characterized by high capital intensity. The requirements are dependent on facilitating infrastructure development such as railroads etc Less Capital intensive Low

Quick turnaround time

MTO

Network strengths and service quality

Growing international trade Expanding Domestic demand for efficient supply chain Growing need for door to door service and integrated services Booming oil demand, and rising trade flows

Being less capital intensive and with neutral working capital requirement, the MTO business gives higher return on equity and return on capital employed

Bulk Liquid

Capital Intensive

High

Port Connectivity and integrated service offerings

Less competition in the market

TABLE 1.1: Key Opportunities Logistics Industry

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Consolidation, entry of private players, growth in MTO business, and surge in ocean freight are some major opportunities to be tapped. 1.2.6 Key challenges 1. Geographical Coverage Insufficient: Insufficient distribution channels or

infrastructure bottlenecks restrict the scope to reach consumers of products nationwide. 2. Over-burdened ports: India has a long coastline. However, the countrys port system isnt utilized properly. 70% of the seaborne trade is managed by 2-3 of its 12 major ports. Remaining 185 minor ports in the country are largely underutilized. 3. Warehousing investment is low: The infrastructure including roads, airports and seaports are preliminary the main target areas of investment. However, warehousing, a facilitator for the agricultural sector, has attracted lower investment that reduced its pace of growth in comparison to rising farm output. 4. Technology Usage: Technology usage is still very low in India, which restricts the scope of increasing efficiency and productivity. 5. Cost/Quality of Service: According to industry analysts, logistics costs in India are among the worlds highest and outside of the metros and a few cities, the delivery time is very uncertain. Overburdened physical infrastructure is a major bottleneck currently faced by the Indian Logistics and Transportation players. 1.2.7 Major players Road Freight Express Container Haulage CONCOR Blue Dart Gati Transport Corporation Gateway Distriparks All Cargo Aegis Table 1.2: Major Players Logistics Industry CFS MTO Bulk liquid

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1.2.8 Organized players Multimodal Transport Operation (MTO) : Key Players in shipping liners: 1. APL Ltd 2. A.P. Moller Maersk 3. Compania Vepores Key players in Domestic Freight Forwarders: 1. AFL Ltd 2. Alpha Cargo Express 3. Air & Sea Cargo Systems Key players in International Freight Forwarders: 1. Geologistics 2. Kuehne + Nagel 3. Exel Kay players in Custom House Agents: 1. Tulsidas Khimji Pvt. Ltd 2. Velji Dosabhai & sons. Pvt. Ltd 3. Atlantic Shipping 4. N G Bhanushali & Company 4. Bax Global 5. Panalpina World Transport 4. Container Carriers international 5. Countrywide Express 6. Express Forwarders Sundamericana de 4. Wan Hai Lines Ltd, 5. K Line (America) Ltd, 6. Hanjin Shipping Co.Ltd

Container freight Station: Key players at JNPT: 1. Maersk India Private Ltd 2. Gateway Distriparks Ltd 3. Balmar Lawrie & Co 4. Punjab State Warehousing 5. Container Corporation of India Key players at Chennai: 1. Allcargo 2. Gateway Distriparks Ltd 3. Container Corporation of India 4. Central Warehousing Corporation 5. Maersk India 6. Sical Distriparks 7. Sun Global 8. Balmar Lawrie 6. Central Warehousing Corporation Distripark 7. Hind Terminal 8. Allcargo.

19 Third Party Logistics: Key players: 1. TVS logistics 2. DIESL (TATA) 3. Panalpina 4. TCI 5. Gati Express logistics: Key players: 1. DHL 2. FedEx 3. TNT 4. UPS 5. AFL 6. DTDC 7. First Flight Couriers 8. TCI Express 9. Gati 10. VR 6. Allcargo 7. V Trans 8. Total 9. VRL

Container Rail Business: Key players in Rs 100mn license fee category (sector-specific routes): Company Pipavav corporation Delhi roadways corp. Boxtrans (JM Baxi 12 and Co) Inlogistics (B2B) 12 Vizag & rajasthan; Tie ups 5-6 sidings planned with CFS/ ICD operators Kalamboli (JNPT); Tie ups 3 sidings planned with CFS/ ICD operators Table 1.3: Key Players In Rs 100mn License Fee Category assam 2 N/A N/A No of rakes Current infrastructure rail 0 N/A Planned N/A

1.2.9 Mumbai ranks highest; Nagpur, Gurgaon, Vizag the new emerging logistics destinations According to a recently released report by Cushman & Wakefield - Logistics Industry Real Estates New Powerhouse the Indian logistics industry is expected to grow annually at a rate of 15 to 20 per cent, reaching revenues of approximately US$ 385 billion by 2013.

20 Cushman & Wakefield estimates that the market share of organized logistics players is also expected to double to approximately 12 per cent during the same period. The report reveals that by 2012 there will be 110 logistics parks operational, spread over approximately 3,500 acres at an estimated cost of US$ 1 billion. While, are expected to be operational and estimated another 45 million sq. ft. of warehousing space with an investment of US$ 500 million is expected to be developed by various logistics companies by 2012 the same timeframe. With most of these developments concentrated in 14 locations, Cushman & Wakefield identified the front runners based on various parameters such as the existing logistical infrastructure, existing and proposed manufacturing clusters, consumer markets, state and union government initiatives and geographical location. These centres have a direct bearing on the real estate developments in and around such locations. Sanjay Dutt, Joint Managing Director for Cushman & Wakefield in India adds, Since almost one-third of the total realty development in the sector is expected to take place in emerging locations, many tier-2 and tier-3 cities and peripheral locations that offer good connectivity to multiple markets will witness increased activity from logistics players, providing a thrust to the real estate market. Emerging hubs include locations such as Nagpur, Vizag and Gurgaon have been rated which currently lagging behind in support infrastructure but are promising logistical hubs due to high ratings on other parameters such as geographic location, existing and proposed manufacturing clusters and SEZs and accessibility. There are many infrastructural developments taking place in these locations which would be increase the attractiveness of these locations in the next 3-5 years. Heightened manufacturing activities, and proposed SEZs increase the potential of locations like Bangalore, Indore, Alwar, Jamshedpur , Ahmedabad and Ambala of being developed as logistics hub. However, currently these locations do not rate high on parameters like geographic location, investment in infrastructure, have moderate retail penetration and limited presence of multi layered manufacturing industries. These locations however are touted to be emerging as major manufacturing hubs in the near future, which be critical in promoting the logistics industry in these regions. Kochi makes it to the last category of Nascent Hub largely due to its strategic location which allows it to connect effectively throughout southern India and through maritime routes and internationally due to the presence of the international airport. Yet challenges including infrastructure development, presence of manufacturing and government initiative rate this location lower than other destinations.

21 Location Attractiveness/ Market Potential Analysis Established Hubs Mumbai Kolkata Chennai Hyderabad Emerging Location Nagpur Gurgaon Vizag Promising Hubs Bangalore Indore Ambala Ahmedabad Jamshedpur Alwar Table 1.4: Market Potential Analysis Nascent Hubs Kochi

1.2.10 India 46th in global trade logistics: World Bank Countries like India, China and the US, which pursued aggressive reforms, have improved their global trade logistics performance despite the slowdown in progress in the sector over the last two years amid the global recession, the World Bank has said. India now ranks 46th in global trade logistics performance, whose top five slot are occupied by Singapore, Hong Kong, Finland, Germany and Netherlands in the list of 155 countries. The United States is ranked ninth, while Japan occupies the eight spot. Countries like Chile, China, India, Morocco, South Africa, Turkey and the US all improved their previous performance, the World Bank said, citing a study based on a comprehensive global survey of international freight forwarders and express carriers, as it released the "Connecting to Compete 2012: Trade Logistics in the Global Economy" report. "Trade logistics is key to economic competitiveness, growth and poverty reduction," Otaviano Canuto, World Bank Vice President for Poverty Reduction and Economic Management (PREM), said. "Unfortunately, the logistics gap between rich and poor countries continues and the convergence trend experienced between 2007 and 2010 has stalled as events like the global recession, and the European debt crisis shifted attention away from logistics reform," he said. According to the LPI, high-income economies dominate the top logistics rankings, while the economies with the worst performance are least developed countries that are also often landlocked, small islands or post-conflict states. Nevertheless, logistics performance is not simply determined by the level of per capita income, as many countries across different income groups have done better than their peers, the Bank said.

22 In the upper-middle income country category, top performers include South Africa, China and Turkey. In the lower middle income category, India, Morocco and the Philippines have above average performance improvements. And among low-income countries, outperformers included Benin, Malawi and Madagascar, the Bank reported. "Infrastructure stands out as the chief driver of progress in top performers, followed by improvements in logistics services and customs and border management," said Mona Haddad, Sector Manager of the World Bank's International Trade Department. The survey, which for the first time included environmental indicators, also found that green logistics is quickly gaining prominence in high-income and emerging economies - a positive development since logistics and freight-related activities may account for up to 15 per cent of human carbon dioxide emissions.

23 1.3 ORGANIZATION PROFILE

Network Logistics Pvt. Ltd (NLPL) is a rapidly growing International Freight Forwarding Company with worldwide network and partners across the globe. .Their Chennai Office is the control centre for operations worldwide. Network Logistics Pvt. Ltd. offers a wide array of services thus providing a single stop logistics provider for companies. The service offering has been designed to deliver efficient and on time logistics solutions in a cost effective manner. All service offerings from Network Logistics are subject to rigorous process monitoring and continual improvement in line with our stringent quality policy. Network Logistics Pvt., Ltd. is a leading freight forwarding and 3PL Logistics Company specializing in Oil & Gas and Offshore Logistics. Network Logistics is part of the reputed Admiral Marine Group established in 1968 and operate from our fully owned offices including ownership of their office infrastructure at 18 major ports in India. NLPL is one of the oldest licensed Custom House Agency (CHA) companies in India. NLPL has been accredited with the ISO 9001:2008 DNV certification. It is also a member of local and international freight forwarding associations and networks.

Legal Representative / CEO Country Main Markets Certificates

Mr. Noorul Ameen India Asia, Middle East ISO 9001:2008, CHA license, Steamer Agent 23, Moore Street, Chennai 600001.

Head Office

Tamil nadu, India Tel : +(91)-(44)- 43475050 Fax : +(91)-(44)- 42159953

Email

operations@networklogistics.in nlpl.enquiries@networklogistics.in

Website

www.networklogistics.in Table 1.5: Details of Network Logistics Private Limited

24 NLPL operates from their fully owned offices including ownership of their office infrastructure at 14 locations across India with strength of 180 dedicated staffs. It is an asset backed company wherein it operates from its own warehouses at strategic logistics hubs and deploys company owned transportation and material handling fleet including low bed trailers and cranes. We have been awarded the D&B-Axis Bank Business Gaurav SME Award 2011 in the Logistics Category. NLPL owns and leases open storage yards and closed warehouses at various ports. Our fleet of P&M includes 20A and 40A trailers and material handling equipments which include forklifts and cranes from 10MT to 180 MT. NLPL are one of the leading specialist in oil and gas logistics service providers in India covering air and sea freight forwarding including air/ sea charters, import and export clearances, statutory clearances and liaison from various ministries, transportation, shore base management, port and vessel agency, equipment and man power supply, etc.

1.3.1

Ownership pattern

Figure 1.3: Ownership Pattern of NLPL

25 1.3.2 Logo of NLPL

Figure 1.4: Logo of NLPL

1.3.3 Network of NLPL

Figure 1.5: Network of NLPL

1.3.4 Mission of NLPL 1. Meet on time delivery while ensuring global trade requirements are met. 2. Implement controls to manage international expenses for import and export activities. Provide direction to the development of new international business opportunities. 3. Mitigate risk through issue resolution, education and strategic planning. 4. Affect global trade controls through established policies and processes.

26 1.3.5 Chronology of vessel / rig clearance

Figure 1.6: Chronology of Vessel / Rig Clearance

27 1.3.6 Policies

Quality policy of NLPL 1. Precise Logistics Management: Our expertise coupled with the latest technology and integrated operations ensure a comprehensive logistics solution customized to your needs 2. Reliability: Your consignments at the right place, at the right time, at the right cost, meeting all statutory and regulatory requirements 3. Global Solutions: Partnering with equally reliable partners world wide makes us an effective global operator

Business ethics 1. No discrimination on the basis of caste, color, religion etc. 2. Our policies are fair and transparent 3. We provide proper safety to our employees 4. Honesty, Integrity, Loyalty, Fairness, Impartiality, Fidelity to trust and inviolability of confidence are incumbent upon every employee of our organization 5. We provide proper environment conditions 6. Information about our employees personal lives, health and work evaluations are kept confidential 7. We make regular measurement of employee satisfaction 8. Neither gives nor takes any illegal payment, remuneration, gift, donations, or comparable benefits to obtain business favors. 9. Comply with all regulations to preserve the environment 10. Employee should report to management any actual or possible violation of code or an event that could affect the business or reputation of the company. 11. Employees shall not falsely or maliciously attempt to injure the reputation of others. Our ethical dimension of business rests on the three key aspects of legitimacy, equitability & transparency. 12. We strictly implement ISO procedures without any deviations.

Trade compliance policy We comply with all applicable export, import and trade compliance laws of our country and the country in which we do business. It is the policy of Network Logistics to

28 comply strictly with Indian Government and host government laws and regulations when importing, exporting or re-exporting. The companys business goals never under any circumstances justify the violations of these laws. In furtherance of this policy, no person

acting for or on behalf of Network Logistics will ship, mail, hand carry or in any other way export / Import any products (whether new or used, entire units or parts), or any technical data, or knowingly cause or permit any other person to do so, without being certain. 1. That such export/import may lawfully be made to the intended recipient in the intended country of destination; 2. That the export/import is either covered by a license exception or an export/import license has been obtained; 3. That all documentation required for the export/import has been properly prepared and accompanies the export/import.

Drug and alcohol abuse policy Network Logistics Pvt. Ltd. is dedicated to the pursuit and dissemination of goods and services. The illegal or abusive use of drugs or alcohol by employees of our Organization jeopardizes the safety of the individual or a group, and is adverse to the development of our business. Network Logistics Pvt. Ltd. is therefore committed to having a campus that is free of the illegal or abusive use of drugs and alcohol. Network Logistics Pvt. Ltd. will not employ/hire anyone who is known currently to abuse drugs or alcohol. In order to inform all employees of their responsibilities under this policy, and to meet the responsibilities as set forth the following information is provided: 1 2 3 4 5 Prohibited conduct. Disciplinary sanctions that Network Logistics Pvt. Ltd. will impose on Employees. Applicable legal sanctions under federal, state and local laws. Health risks associated with the use of illegal drugs and the abuse of alcohol. Drug and alcohol information and treatment program resources.

1.3.7

Services of NLPL

1. Oil & Gas Logistics: Strategically located in all major ports around India, Network Logistics is a key provider of Oil & Gas logistics services. Our network of experienced team manages the logistics and supply chain requirements for your oil and gas materials and equipment. This knowledge of the industry, combined with established relationships, means

29 your equipment and supplies, rigs, bulk or packaged goods, and heavy lift transports are delivered where you need them, when you need them. Providing you with efficient and cost-saving solutions is the goal of our team of dedicated and innovative professionals. Practical options for your cargo transport are the common sense answers you need to the complex challenges of the oil and gas market.

Some of these are: a) b) c) d) e) Procurement and Expediting Warehousing and Distribution Air, Sea and Road Transport Export Compliance Line Item Material Tracking g) h) f) Export Packing Domestic and Foreign 24-hour Site Management Customs Clearance and many more activities

2. Freight Forwarding: The Company has a worldwide partnership network of professionals who are engaged in all aspects of shipping and international transportation. This partnership network is spread across 80 countries and 150 locations worldwide. a) b) c) d) Ability to offer customized solutions based on individual customer requirements. Range of services that cover every aspect of supply chain solution. Wide international network of partners to expedite cargo movement. Excellent relationships with shipping lines to achieve priority shipping.

3. Air & Sea Freight: we have an excellent network with several ocean carriers throughout the world. Our experienced professionals also provide customized solutions as per the clients' requirement thus avoiding unnecessary delays.

Our customized services include: a) b) Full-container-load (FCL) Less-than-container-load Consolidation c) Multimodal Sea/Air/Road d) e) Worldwide Consolidation Service Dry or liquid bulk shipments Transportation by (LCL) g) h) i) j) f) Refrigerated Services for perishable products Cargo / Freight Insurance Packing Options Cargo Tracking System Fumigation Services

30 4. Custom Clearance: Indian customs procedures are complex and involve various documents, incentives/concessions in duty. Our team consists of well experienced and trained staff, supported by fully computerized documentation and armed with the latest communication equipment. We also cater: a) b) c) d) Documentation for custom clearance Carting / Receiving Goods Examination Of Shipments Registration of the contract with customs for the project clearance e) Custom clearance of the import cargo at the port of entry f) g) Port handling Reconciliation of the contract after completion of import. j) i) h) Port handling and arranging bonded warehouse as and when required by the client Suggestion for effective packing for economic handling and safety Stuffing containers and at De-Stuffing Ports, ICD's of and

Customers warehouse

5. Plant & Machinery rental: We offer point to point, expert handling of over dimensional and heavy industrial equipments over land and sea. Our services in cargo handling are flexible and customized to match client requirements. Our combination of equipments, manpower and expertise is of immense service to clients, vendors and industry in situations where heavy lift solutions are desired with mobile cranes and crawlers. We have consistently and successfully served the onsite heavy lift requirements of refineries, power projects, windmills, and construction, infrastructure and oil/gas sectors in India.

6. Warehousing: Warehousing & Distribution services whereby the customer can manage their inventory efficiently thereby reducing costs & at the same time maintain a effective & faster delivery schedule. Being in the logistics industry it was only logical for Network Logistics that investing in warehousing formed a very vital part of growing the business and expanding the service portfolio. To this end we have made very prudent and strategic investments in creating a chain of warehouses, set up close to vital transport hubs and outside octroi limits. These warehouses are well maintained, well staffed and are secured by vigilant round the clock staff. Huge in size, well ventilated and clean they are used for the storage of both

31 consumer and industrial consignments. These warehouses have helped to add a competitive edge to our portfolio as they have served to give our customer that sense of security during transit and also reduced the chances of damage during storage. This service has served to push us up the value chain considerably.

Our warehousing services include: a) Modern warehouses. b) Adequate insured private warehousing space. c) Safe storage of goods, with proper Security in place. d) Control checks on entry & exit of goods. and well-equipped e) Computerized Inventory Control

System & Reporting f) Long & Short term Storage Facilities g) Pick-Up / Delivery service TO FROM major locations in India h) Less Than Truckloads (LTL) to Full Truck Loads (FTL) i) Cargo Tracking System

7. Transportation: We do our best to transport your goods from their port of origin, across oceans, and to their final port of destination in the fastest, safest, most reliable and economic manner possible We work tirelessly to ensure that any problems that may arise are dealt with in a logical manner and in line with our clients requirement , we have expertise in the handling of perishable goods as well as hazardous cargo, government construction materials, and extra large cargo exceeding the standard size regulations Furthermore, we use computer network software to manage bonded shipments, small and large sized truck shipments, containers and shipments. Any size, any weight, anywhere, anyhow, anytime, every time. Thats our forte in Transportation. 8. Project Cargo Movements: We have the personnels to manage complex transportation of large projects with experience, intelligence and knowledge, committed to researching all options, surveying potential problems, and reacting to extraordinary circumstances with quick and decisive actions. We specialize in project freight management and all associated planning and implementation services. Whether you are moving an individual heavy lift or complete industrial plant, we arrange for customized transportation concepts for the entire route on a door to door basis. The success of our Cargo team lies in its commitment to understanding what is required. We have specialist advisers who become fully conversant with the requirements of

32 a project and ensure that customer-specified deadlines, safety aspects and special instructions are strictly adhered

1.3.8 Specialization in rig / vessel / marine spread clearance

We have handled the Rig clearance of Jack-Up Rig PN3 for both inward and outward for M/s. Saipem (Portugal) Comercio Maritimo, at Kakinada in 2004. Further we have handled the dry dock of this jack-up rig at HSL Yard, Vizag in 2008. The complete scope including attendance and clearance of the imported AHT, the tow plans approvals, the MOHA, MOD, SPL permissions, MMD, Customs and Port liaison, etc. where handled with due efficiency. These services have been appreciated by the principals. We also have a good rapport with the ODAG and the Cuddalore Customs, and can execute the customs clearance and inspections in a smooth, efficient and economic manner.

1.3.9 Domain specialization and scope of activity in the indian oil and gas industry:

Support activities: 1. Licensed CHA & Steamer Agency by respective Customs House. 2. Fully integrated Oil & Gas Logistics and Support service provider. 3. Complete Logistics support for Offshore projects including operation and management of Offshore Supply and Shore Bases. 4. Network support at all major ports in India across East and West coasts through fully owned offices. 5. Import / Export/Clearances of Platforms, Drilling Rigs & Vessels. 6. 24x7 attendance to Drill Ships, Drill Rigs, Ships, OSV, DSV Marine Spread. Port, Customs, Immigration, Defense and Naval clearances for Drill Ships, Drill Rigs, Ships, OSV, DSV and Marine Spread 7. Husbandry services to Ship Owners/Fleet Owners/OSV/DSV Operators. 8. Liaison and support with principal contractors. 9. Liaison with various Ministries and processing of licenses and permits for Offshore and Oil Field projects including Ministry of SHIPPING/ PETROLEUM/ FINANCE/ HOME AFFAIRS, and Statutory Authorities including Customs, Excise, CBDT, etc.

33 10. Liaison and processing of Essentiality Certificates from Directorate General of Hydrocarbon. 11. Ministry of Home Affairs clearances for Foreigners working in Indian Offshore and Oil Fields. 12. Sign-on & Sign-off and Meet & Greet services. Crew and Officers travel arrangements, travel permits and related works.

Logistics activities:

1. Arranging and providing handling equipment like Cranes, Forklifts, Trailors, Multi-axle trailors for ODC, Trucking etc. 2. Operating & Management of Offshore Supply & Shore Bases including Material Storage and Handling Yards fully equipped with cranes and trailors. 3. International & Domestic Clearing & Forwarding/ Customs House Agency services for imports and exports and transshipment of cargo. 4. Freight forwarding, booking of Ocean and Air freight, Ex-Works Collection, Tracking of cargo, Door-to-Door and Door-to-Deck Delivery services. 5. Warehousing and Customs Bonding facilities.

1.3.10

clients of NLPL

Figure 1.7: Clients of NLPL

34

1.3.11 Details of contracts

Reliance Industries Ltd 1. Operations & Maintenance of Shore Base Equipments, Kakinada 2. Shore base Management Services, Karaikal 3. Clearing House Agent Services at various Indian Ports 4. Low Bed Trailer 20MT, 40FT, Kakinada 5. Plant & Machinery, Karaikal Gujarat State Petroleum Corporation Ltd 1. Shore base Support Services at Kakinada Hindustan Oil Exploration Company Ltd 1. Shore Base Management- Yards, Port operations, Equipments including Port Cranes, Guard Boat, Vessel Clearance, Manpower, Chopper Coordination, and Mechanical Installation Work for Tie-In job for Gas Compressor Package ENI India Ltd 1. Logistics Support Services & Facilities for ENI exploratory activities in Block ANDWN-2003/2 Andaman Sea, 2. Maintenance of Casings SAIPEM 1. Total Logistics, Rig Clearance & Dry Dock Movements - Shore Base Management, Freight Forwarding, ECs, MOHA, MOD, SPL SHELL India 1. All India transportation and delivery contract for marine lubricant deliveries on board vessels ABAN Offshore Ltd 1. Rig Import Clearance, Base Management, Equipment Supplies, Manpower, Port Clearance, Custom Clearance & Freight Forwarding Hind Offshore Pvt. Ltd (R.V.GEO Hindsagar - First Private Indian Seismic Survey Vessel) 1. Total Logistics, Vessel Clearance, Customs Clearance, Freight Forwarding, ECs, MOHA, MOD, SPL, Sign On & Sign Off, NED passes etc., MI Swaco 1. Logistics, Warehousing & Manpower

35 Transocean Offshore International Ventures Ltd 1. Logistics, Warehousing & Manpower Shapadu Malaysia 1. Offshore Construction, Equipment and Skilled Manpower Supply ONGC 1. Laying of 114.30 mm OD x 4.80 mm W.T ERW 3 LPE coated underground flow line at Karaikal (By our Group Company Admiral Marine Services Pvt. Ltd.) 2. Providing of 10 wells Group & Test Manifolds at KALI #2 EPT for development of KALI fields 3. Providing of Future wells provisions for new wells & oil manifold modification at GCS at Kuthalam Great Offshore 1. Marine Logistics & Port Terminal Services 2. Replacement of PLEM assembly & Dunlop Hoses job at Ennore Offshore FBMS, Chennai Greatship (India) Limited 1. Agency services related to Import/Export, husbandry and other ship agency services

36

1.4

OBJECTIVES OF THE STUDY

1. To determine the service functions on the basis of which customers of Network Logistics evaluate the quality of service. 2. To determine customers expectations and perceptions of the quality of Network Logistics. 3. To determine the extent of gap between customers expectations and perceptions. 4. To categorize the service attributes based on how well it is able to satisfy customer needs. 5. To locate areas of performance where improvements are needed.

37

1.5

NEED OF THE STUDY

1. To understand the level of service quality provided by Network Logistics, their customer satisfaction and the relationship between them. 2. To attract more customers Network Logistics need to improve their service quality. 3. Network Logstics plans different market strategies in the trade-off situation. So they need some valuable imformation on customers perception. 4. Network Logistics need to differentiate the service offering to various customers.

38

1.6

SCOPE OF THE STUDY

This study will focus only on the customers of NLPL. Incase customers asking different service from logistics firms, NLPL able to know identify the various market strategies to satisfy all logistics customers. These study extents upto NLPL customers. So NLPL need to understand the entire market. This study not differentiates the industry which customer belongs to. So there is possibility for further research based on different industry and overall customers of logistics industry.

39

1.7

LIMITATIONS OF THE STUDY

1. The survey is done only among NLPL customers, thus, the results are generally only applicable for NLPL only. Since the scope of the survey is very small, the results cannot be used to picture the condition of the whole Logistics industry. 2. The sample size is small to be analyzed statistically. As a result, the outcome of the test will not perfectly follow the normal statistical conditions. Since NLPL is a medium sized company, the customer population is relatively small, and not sufficient to produce a reliable result. 3. The accuracy of the data might be doubtful. Inaccuracy of data in these cases will often cause inconsistent results. 4. As non-probabilistic sampling methods have been used, in subsequent research, it would be useful to obtain a more representative population sample. In future, works relations between the variables proposed would be analyzed contemplating the sectored nature of the sample, accepting that relationship intensity may be modified according to the companys sector of activity.

40

CHAPTER II LITERATURE REVIEW

As the service sector of the global economy grows, the study of services and innovation are becoming increasingly important. Service products distributed regionally, nationally, and globally have become larger portions of company revenue streams; knowledge intensive business services aimed at enhancing performance require reliable methods of measurement, assessment, and improvement (Spohrer & Maglio, 2008). As a result, accurate and reliable instruments that assess service quality are of great interest to companies whose revenues come from service delivery. Perhaps the most popular and widely used service quality instrument is SERVQUAL.

2.1

SERVICE QUALITY In 1988 Parasuraman, Zeithaml, and Berry developed a generic instrument called

SERVQUAL to measure service quality based on input from focus groups. Although SERVQUAL was developed within the marketing sector, it also is used in a variety of organizational settings, including libraries and information centers (Kettinger & Lee, 1994; Nitecki, 1996). Since 1988 Parasuraman, Zeithaml, and Berry have made numerous changes to SERVQUAL, some in response to problems identified by other researchers. For instance, in 1994 they reported on three different SERVQUAL formats; they recommended that researchers use a format that separated customer expectation scores into tolerance zones. Researchers have continued to use SERVQUAL instruments. In 1997, Van Dyke, Kappelman, and Prybutok employed SERVQUAL in an IS context, while in 2002 Banwet and Datta measured IT service quality in a library service, as did Landrum and Prybutok in 2004. Still, some researchers question the appropriateness of using SERVQUAL in an IS or IT context; others disagree about whether the service quality should be the difference between expected and perceived service. Parasuraman, Zeithaml, and Berry (1988) stated that since service quality depends on the relationship of customer expectations with customer perceptions, it is appropriate to calculate service quality by subtracting expected from perceived service. One then achieves an overall measure of service quality by averaging the scores of all items (Brown, Churchill, & Peter, 1992). However, this procedure gives also rise to two issues: the first is disagreement over what really is being

41

measured in SERVQUAL with expectations and the second is the problematic nature of the resulting difference scores. These two issues are resolved if one follows Cronin and Taylor (1992), and Teas (1993), who recommended that expectation ratings be eliminated altogether. In addition, Liljander (1994) states that there is more support for performance only models than for the disconfirmation model of service quality. Bolton and Drew (1991) stated that assessments of overall service quality are affected only by perceptions of performance levels. They suggested that direct measures of disconfirmation are more important than expectations. Boulding, Kalra, Staelin, and Zeithaml (1993) also suggested that perceptions alone influence overall service quality. Furthermore, other studies suggested that SERVQUAL has unstable dimensions. For example, Jiang, Klein, and Carr (2002) used four dimensions in their study, while Landrum and Prybutok (2004) used five. Nitecki (1996) proposed a three-dimensional SERVQUAL model, as opposed the five dimensions proposed by Zeithaml, Parasuraman, and Berry in 1990. As we have noted, these issues are all resolved if customer expectations are eliminated from the model. The performance only approach to service quality utilizes the five of the seven SERVQUAL dimensionsthe five performance dimensions. Cronin and Taylor (1992), called this performance only subset instrument SERVPERF. When Cronin and Taylor (1992) compared SERVPERF to SERVQUAL, their results supported the dissenters: performance scores alone account for more variation in service quality than performance minus expectations. Performance alone provides better predictive validity than SERVQUAL which is gap-based (Brady, Cronin, & Brand, 2002; Cronin & Taylor 1992) and other studies show that performance scores alone exhibit better reliability and validity than difference scores (Babakus & Boller 1992; Brady et al., 2002; Landrum & Prybutok 2004; Landrum, Prybutok, Strutton,& Zhang, 2008). Based upon these findings, we used only performance scores to perform analysis on the five SERVQUAL service quality dimensions. We next discuss adapting the SERVQUAL instrument to library information services be-cause the test facilities were designated by the US Army Corps of Engineers as libraries. Cook and Thompson (2000) investigated the reliability and validity of SERVQUAL instrument in the context of library service. They found that SERVQUAL displayed three responsive dimensions, rather than the five dimensions originally proposed

42

by Parasuraman et al. (1988). As a result, they concluded that responsive, empathy, and assurance dimensions overlapped in this particular service domain. Nitecki and Hernon (2000) used SERVQUAL to assess library services at Yale University and found that among the five dimensions of SERVQUAL, respondents considered reliability the most important and empathy least important among the five quality dimensions (Landrum, Prybutok, Kappelman, & Zhang, 2008).

2.2

SERVQUAL INSTRUMENT AND ITS CONSTRUCTS The SERVQUAL instrument used in this study is based on a model of library

success that includes the following seven dimensions: service quality, system quality, information quality, user involvement, usefulness, user self-sufficiency, and user satisfaction (Parasuraman et al., 1994). SERVPERF, a SERVQUAL performance only instrument subset of SERVQUAL, uses only the first five of the seven SERVQUAL dimensions measuring only customers perceptions of service provider performance. Although additional dimensions, such as individual impact, work group impact, and organizational impact, have been identified as influencing system success (Myers, Kappelman, & Prybutok, 1997), these lie outside the scope of the present study. The SERVQUAL and SERVPERF versions used in this study were tested and validated over a ten year period with a series of studies since its refinement in 1994 (Landrum & Prybutok, 2004; Landrum, Prybutok, Kappelman, & Zhang, 2008; Landrum, Prybutok, Strutton, & Zhang , 2008). Although the SERVQUAL instrument is ubiquitously employed, it has received heavy criticism from both a theoretical and practical perspective. The issues questioned include the use of gap scores, the overlap among the five dimensions, poor predictive and convergent validity, and the ambiguous definition of the expectation construct, and unstable dimensionality (Babakus & Boller 1992; Carman, 1990; Brown, Churchill, & Peter, 1992; Van Dyke, Prybutok, & Kappelman, 1999). By discarding the expectations portion in the SERVQUAL model, Cronin and Taylor (1992) justify the SERVPERF or performance only instrument in place of the gap measurement approach. In addition, they show that the SERVPERF instrument empirically outperforms the SERVQUAL scale across several industries. As a result of these issues, the performance only measures are used and suggested by many scholars in various industries (Gilbert, Veloutsou, Goode, &

43

Moutinho, 2004; Keillor, Hult, & Kandemir, 2004; Law, Hui, & Zhao, 2004; Parasuraman et al., 1994; Van Dyke et al., 1997). We selected a library information system and adapted Parasuraman et al.s 1994 version of SERVQUAL with 21 questions in 5 dimensions of service performance to study it (Appendix, Section 1). We made minimal wording changes to the original content of the instrument; although we did measure the customer expectations, we did not use them in this study because we focused on the performance (SERVPERF). This focus was deemed appropriate because the in-tent was to examine the relative importance of the performance dimensions. The 21 questions are distributed among the 5 SERVPERF performance dimensions as follows: 1) five items are used to measure tangibles (questions 1-5) tangibles refer to physical facilities, equipment, and personnel; 2) five items are used to measure reliability (questions 6-10) reliability refers to the ability of a firm to perform promised service dependably and accurately; 3) four items are used to measure responsiveness (questions 11-14) responsiveness is the willingness to help customers and provide prompt service; 4) four items are used to measure assurance (questions 15-18) assurance is the ability of employees to inspire trust and confidence in customers; and 5) three items are used to measure empathy (questions 19-21) empathy refers to the amount of caring and individualized attention provided to customers. We also collected point data from each respondent indicating the perceived relative importance of each of the five SERVPERF dimensions; respondents were instructed to allocate 100 points among the five dimensions. KANOS MODEL When analyzing the growing body of the Kano model literature, several things become evident. First, the majority of authors who base their studies on the Kano model, focus their research primarily on the identification of the first three quality elements (attractive, one-dimensional and must-be). Second, there is an evident polarization between authors defining the model either as a satisfaction or as a quality model. This is in line with the traditional polarization between the satisfactionprecedes-quality- and the quality-precedes-satisfaction- camp, which roots in the persistent overlap of the dominating theories of customer satisfaction (disconfirmation paradigm - Oliver, 1980) and service quality (gap model - PZB, 1985).

2.3

44

Kano et al. (1984) developed a model for improvement and enhancement of a product or service. According to Kano, customer needs can be classified into three categories (Kano, 1995, 2001; Bergman and Klefsjo, 2003),the categories are must be, one dimensional and attractive. For the must be categories the need can be considered as the basic requirements for the product or services. Both the customer and the service or product provider agreed on the importance of the needs in these categories, they are expected but unspoken and unarticulated (Cheng Lim et al., 1999). For these categories of needs the level of satisfaction for the customer will not raise above the normal level if the product or service provider able to fulfill those needs but the customer will felt very disappointed if the needs are not fulfilled. In other words while a low performance on such attributes leads to dissatisfaction in a customer; a high performance does not lead to satisfaction (Kano et al., 1984; Matzler and Hinterhuber, 1998; Busacca and Padula, 2005). Meanwhile for the one dimensional categories, the needs that falls in these categories are actually the expectation of the customer towards the product function or the services that been provided by the service provider. These needs are very well expected, expressed and articulated by the customer. For the needs in this categories it can be expressed in a linear relationship, whereby if the customer needs are not fulfilled the level of satisfaction will be low and in other hand if the needs are fulfilled the level of satisfaction will become high (Redfem and Davey, 2003) and by providing for such needs, the product or service provider creates the expected quality for their product or services. It is important for the product and service provider to focus their resource to compete with their competitor in order for them to sustain themselves in the market. Lastly would be the attractive dimension. The needs that fall in this categories are the customer needs that they themselves doesnt realize that the need it. In other words the needs are unexpected and unspoken. The relationship between the needs in this categories and the customer satisfaction are one way linear relationship. If the product or service provider are able to provide the unexpected towards the customer, their level of satisfaction will increase, however if the satisfaction level will not been effected if the product or service provider attribute in this category are not performed well. In other words they lead to satisfaction of customers when present but do not lead to any dissatisfaction if not present (Berger et al., 1993) and by discovering such needs and expectations, and providing the customer with these, the product or service provider creates what can be called, the attractive quality (Kano et al., 1984; Lilja and Wiklund, 2006).By integrating the Kano Model and

45

SERVQUAL we would able to determine the service quality criteria that falls into the must be, one dimensional and attractive category. This information will be an important input towards the creating a training courses model. Accordingly, numerous names/definitions for the Kano model have emerged. For instance, some of the most prominent Kano-authors define the model as theory of three-factor structure of customer satisfaction (e.g. Fuchs and Weiermair, 2003), some define it as model of customer requirements (e.g. Lee and Newcomb, 1996) or model of customer needs (e.g. Jonsson Kvist and Klefsjo, 2006), while others define it as two-way model on quality (e.g. Schvaneveldt et al., 1991) or simply as theory of attractive quality (e.g. Nilsson-Witell and Fundin, 2005). Third, although Kano et al. (1984) were the first to present an integrated model of quality that incorporates different possible impacts of certain product attributes in the creation of customer satisfaction and dissatisfaction, it has to be pointed out that the phenomenon of product/service attributes, showing an asymmetric and nonlinear impact on OCS, had already been studied earlier. The first one to introduce the basic concept was Herzberg (1959). In his study on work motivation he presented the M-H (motivator-hygiene) theory of work

satisfaction, which represents

the rationale of the Kano model. Motivators are work A direct analogy can be drawn to Kanos

factors that primarily lead to employee satisfaction, whereas hygiene factors primarily contribute to dissatisfaction with a job. attractive- and must-be quality elements.

46

CHAPTER III RESEARCH METHODOLOGY

The present study is an attempt to make comparative assessment of the expected service and perceived service of NLPL, ability to explain variance in the overall service quality, power to distinguish among service objects/firms, parsimony in data collection, and, more importantly, their diagnostic ability to provide insights for managerial interventions in case of quality shortfalls. Data for making comparisons among the unweighted and weighted versions of the two scales were collected through a survey of the consumers of NLPL. For ensuring a greater generalizability of service quality attributes, it was considered desirable to select a service offering that is comprised of both the good (i.e., physical facilities) and service (i.e., safe and fast delivery of goods) components. At the analysis stage, collected data were pooled together thus constituting a total of 100 responses. The research started by identifying the companies to be studied. The proposal was an ad-hoc questionnaire which permitted data collection by means of mail or postal. The sample consisted in 100 companies, which were contacted by telephone to request for answering the SERVQUAL questionnaire. A first characterization of the companies examined shows large sized companies, spanning all sectors of business having head quarters in Chennai and around Chennai region. Then send the questionnaire to all other companies situated other then Chennai.

3.1 SERVQUAL (PROCEDURE TO FOLLOW) Outlined below are the instructions for carrying out a SERVQUAL survey. Using the questionnaire obtain the score for each of the 40 attributes both expected and perceived level of customer. Calculate the Gap Score for each of the statements where the Gap Score = Perception Expectation (see Table 6 below). 1. Obtain an average Gap Score for each dimension of service quality by assessing the Gap Scores for each of the statements that constitute the dimension and dividing the sum by the number of statements making up the dimension (see Table 6 below). 2. Sum the averages calculated in step 2 above and divide by 5 to obtain an average SERVQUAL score. This core is the unweighted measure of service quality for the area being measured.

47

3. If you want to have a weighted score, calculate the importance weights for each of the six dimensions of service quality constituting the SERVQUAL scale. The sum of the weights should add up to 100 (see Table 7 below). 4. Calculate the weighted average SERVQUAL score for each of the six dimensions of service quality multiplying the averages calculated in step 2 above by the weighted scores calculate in step 4 above (see Table 8 below). 5. Sum the scores calculated in step 5 above to obtain the weighted SERVQUAL score of service quality for the area being measured. 6. Dimension Statement
Reliability

Expectation Score

Perception Score

Gap Score

Average for Dimension

1 . 9 10 . 14 15 . 23 24 . 28 29 . 37 38 40 Unweighted Average SERVQUAL score:

Info

Physical facilities

Staff and officers

Timely delivery

Assurance

Table 3.1: Calculation of SERVQUAL Scores SERVQUAL Importance Weights: Listed below are the six sets of features pertaining to logistical service providers and the services they offer. We would like to know how much each of these sets of features is important to the customer. Please allocate 100 points among the six sets of features according to how important it is to you. Make sure the points add up to 100.

48

Dimensions 1. The ability to perform the promised service dependably and accurately. The service is accomplished on time, in the same manner and without errors every time 2. The knowledge and courtesy of NLPL and their ability to convey the trust, confidence and competence to perform the service. 3. The ability to provide safe and fast delivery 4. Attitude of officers and staff. 5. The physical facilities, equipment and material handling facilities made available to the customer 6. The clarity, completeness and accuracy of both verbal and written information communicated to the customer Total: Table 3.2: SERVQUAL Importance Weights SERVQUAL Dimension Reliability Assurance Timely delivery Staff and officers Physical facilities Information Average weighted score Table 3.3: Calculation of Weighted SERVQUAL Scores 3.2 STATTISTICAL TOOLS (SERVQAUL) Score from Table 1

Points

100

Weighting from Table Weighted Score 2

1. Friedman test (mean) 2. Paired t-test 3. Correlation test

49

3.2.1 Friedman test (mean) The Friedman test allows for the analysis of repeated-measures data if participants are assessed on two or more occasions or conditions or to matched-subjects data if participants are matched in pairs, triplets, or in some greater number. The Friedman test is applicable to problems with matched-subjects designs. With repeated-measures designs, each participant is a case in the SPSS data file and has scores on K variables, the score obtained on each of the K occasions or conditions. A researcher is interested in determining if subjects changed significantly across occasions (or conditions). For a matched-subjects design, participants are matched in sets of K participants, and each participant in a set is assessed once on a measure. Each set of participants is a case in the SPSS data file and has scores on K variables, the scores obtained on the measure by the participants within a set. Assumptions underlying a Friedman test: Assumption 1: Each set of K observations must represent a random sample from a population and must be independent of every other set of K observations. Assumption 2: The Chi-Square values for the Friedman test yield relatively accurate results to the extent that the sample size is large. Assumption 3: The Distribution of the differences scores between any pair of levels is continuous and symmetrical in the population. The Friedman rank test is primarily used to test whether k sample groups (i.e., the treatment levels) have been selected from populations having equal medians. That is, you test H0: M.1 = M.2 == M.k against the alternative H1: Not all M.j are equal (where j = 1, 2, . . . , k) From the above, the following test statistic FR is obtained: FR = ( +1)
12 2 =1

3 ( + 1)

(3.1)

Where 2 is the square of the rank total for group j (j = 1, 2, . . . , k) r is the number of independent blocks : k is the number of groups or treatment levels

50

As the number of blocks in the experiment gets large, the test statistic FR can be approximated by the chi-square distribution with k 1 degrees of freedom. Thus, for any selected level of significance , the decision rule is to reject the H0 if the computed value
2 of FR is greater than , the upper-tail critical value for the chi-square distribution having 2 k 1 degrees of freedom. That is, Reject H0 if FR > ; otherwise do not reject H0.

3.2.2 Paired t test A paired t-test helps determine whether the mean difference between paired observations is significant. Statistically, it is equivalent to performing a one-sample t-test on the differences between the paired observations. A paired t-test can also be used to evaluate whether the mean difference is equal to a specific value. Paired observations are related in some way. Examples include: 1. Cycle times recorded for the same individual before and after a training session 2. Ratings of competing products from a single evaluator Working rule for estimated standard error of difference. Step I : let D = ( xi yi ) , ( i =1,2, n ) denote the difference in observations for the unit. Step II Step III Step IV : calculate = . : calculate (D - )2 and S =
2 1

(3.2) (3.3) . (3.4)

: calculate standard error of difference: S.E.(1 2) =

Working rule for paired t-test 1. Null hypothesis: H0: 1 = 2. Alternative hypothesis: H1: 1 2 (two tailed test). 2. Calculation of test statistic: Estimated standard error of difference: S.E.(1 2) = Where S2 = 1
1

. (3.5) (3.6)

2 (2 )

Test statistic: t = . . Where = difference between each pair of observations

3. Level of significance: let = 0.05, or = 0.01 or = 0.1 as the case may be.

51

4. Critical value. Find from the table the value of t at the level of significance for (n - 1) degrees of freedom for the one tailed or two tailed test (for the case given by alternative hypothesis) i.e., find td,n-1 5. Decision. If the calculated value |t| < t,n-p then the null hypothesis is accepted and in case of calculated value of |t| > t,n-1 then the null hypothesis is rejected and alternative hypothesis is accepted.

3.2.3

Correlation analysis Correlation transformer to determine extent to which changes in value of an

attribute are associated with changes in another attribute. The data for a correlation analysis consists of two input columns. Each column contains values for one of the attributes of interest. The Correlation transformer can calculate various measures of association between the two input columns. You can select more than one statistic to calculate for a given pair of input columns.

The coefficient of correlation is calculated by the following steps: Step I : denote one series by x and other series by y. Step II : calculate and of the x and y series respectively. Step III: take the deviations of the observations in x-series from and write it under thecolumn headed by dx = x - . Take the deviations of the observations in yseries from and write it in a column headed by dy = y - . Step IV:square these deviations and write them under the columns headed by dx2 and dy2. Step V : multiply the respective dx and dy and write it under the column headed by dxdy. Step VI: apply the following formula to calculate r or rxy , the coefficient of correlation

r=

2 2

(3.7)

Where n is the number of observations in x or y series, x and y are the standard deviations of x and y. Consider two variables x and y:
1.

If r = 1, then x and y are perfectly positively correlated. The possible values of x and y all lie on a straight line with a positive slope in the (x, y) plane.

2.

If r = 0, then x and y are not correlated. They do not have an apparent linear relationship. However, this does not mean that x and y are statistically independent.

52

If r = -1, then x and y are perfectly negatively correlated. The possible values of x and y all lie on a straight line with a negative slope in the (x, y) plane. KANOS MODEL The measurement instrument in this study is based on the SERVQUALs six distinct dimensions of 40-item attributes proposed by Parasuraman et al. (1988) and Su (2008) evaluation instrument on NLPL service quality. We mainly take 40 attributes of six dimensions in SERVQUAL instrument as the principal and refer to service quality features (question items) of rapid transit system contained in each dimensions presented on Su (2001,2008) researches to obtain the 40 amended question items in the questionnaire and take as the NLPL service quality features in this study. The questionnaire is close-ended and anonymous for measuring customers service quality requirements of NLPL service and comprises two sections. The first section of questionnaire is question items used to assess customers perceived importance and performance to 40 service qualities attributes of NLPL. To each item, respondents are required to answer functional and dysfunctional scales by choosing one of five alternatives and answer their individual satisfied level. Construction of the Kano questionnaire Must-be, one-dimensional and attractive requirements as well as service requirements towards which the customer is indifferent can be classified by means of a questionnaire. For each service feature a pair of questions is formulated to which the customer can answer in one of five different ways (see also Kano,1984). The first question concerns the reaction of the customer if the service has that feature (functional form of the question), the second concerns his reaction if the service does not have that feature (dysfunctional form of the question). Following table shows single example Kano question Functional form of the question (e.g., if we provide technical expertise to customers, how do you feel?) Answer H-- This would be very helpful M-- This is a basic requirement I---This would not affect A--This would be a minor inconvenience U--This would be a major problem and I cant accept it

3.3

53

Dysfunctional form of the question (e.g., if we dont provide technical expertise to customers, how do you feel?)

H-- This would be very helpful M-- This is a basic requirement I---This would not affect A--This would be a minor inconvenience U--This would be a major problem and I cant accept it

Table 3.4: Functional and Dysfunctional Question in The Kano Questionnaire By combining the two answers in the following evaluation table, the service features can be classified:

Figure 3.1: KANO Evaluation Table If the customer answers, for example, This would be very helpful," as regards if we provide technical expertise to customers, how do you feel?" - the functional form of the question, and answers " This would not affect," as regards " if we dont provide technical expertise to customers, how do you feel?" - The dysfunctional form of the question, the combination of the questions in the evaluation table produces category A, indicating that providing technical expertise to customers is an attractive customer requirement from the customers viewpoint. If combining the answers yields category I, this means that the customer is indifferent to this service feature. He does not care whether it is present or not. Customers are, however, not willing to spend more on this feature. Category Q stands for questionable result. Normally, the answers do not fall into this category. Questionable scores signify that the question was phrased incorrectly or that the person interviewed misunderstood the question or crossed out a wrong answer by mistake.

Evaluation and interpretation The questionnaire is evaluated in three steps. After having combined the answers to the functional and dysfunctional question in the evaluation table (see fig. 6), the results of

54

the individual service criteria are listed in the table of results which shows the overall distribution of the requirement categories. The next step is to analyze and interpret the results.

Figure 3.2: KANOS Model Evaluation Process The easiest method is evaluation and interpretation according to the frequency of answers. If the questionnaire includes sufficient customer-oriented variables, the results can be used as the ideal basis for market segmentation and thus differentiation of services according to utility expectations of the different customer segments.

3.3.1 Customer satisfaction coefficient (CS coefficient) In 1993, Berger (Berger, 1993), proposed the Customer Satisfaction Coefficient (CSC). CSC calculates the ratio of the number of subjects that get satisfied with the presence of an item to the number of the subjects that get dissatisfied with the absence of that item. These two ratios, which are between 0 to 1 or 0 to -1, are plotted in a scatter diagram divided in four quadrants. The quadrants classify the attributes as neutral, excitement, performance and basic factors. Hence, depending on the quadrant in which each items fall in, it could easily be identified, and its right classification will be labeled. The CS coefficient is indicative of how strongly a product/service requirement (inquired

55

item) may influence customer satisfaction or, in case of its non-fulfillment, dissatisfaction. This will equip us with an index (Consumer Satisfaction Index: CSI) which will reinforce our analysis abilities (Kuo, 2004). The customer satisfaction index states whether satisfaction can be increased by providing quality elements, or whether fulfilling quality elements only prevents the customer from being dissatisfied. CSI comprises two indices: Satisfaction Increment Index (SII) and Dissatisfaction Decrement Index (DDI), which are to measure the extent that the presence/absence of an attribute will evoke dis/satisfaction. By knowing the SII and DDI of an attribute (enquired item), we can figure out how to manipulate that quality element to achieve maximum outcome. According to CQM (1993), the SII can be measured by the attractive quality ratio of an item, plus the one-dimensional quality ratio of the item; the DDI is the one-dimensional quality ratio plus the must-be quality ratio of that same item in inquiry. A minus sign is put in front of the DDI to emphasize its negative influence on customer satisfaction if this quality element is not fulfilled.
+ +++
+ +++

SII =
DDI =

(3.8)

(3.9)

After the SII and DDI are calculated, if the value of an item is close to 0, it can be deemed that the effect on dis/satisfaction is low. When it is close to 1, it means that the item has a positive effect on increasing satisfaction (provided that it is rendered); while its approximation to -1 implies that the item can decrease dissatisfaction ( in case of fulfillment). Based on these two indexes, we can find which items can influence customer satisfaction. Consequently, the items with higher absolute values are demonstrating greater influences, and are the ones we should pay attention to (Tontini, 2003).

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CHAPTER IV ANALYSIS AND INTERPRETATION

4.1

RELIABILITY ANALYSIS

Reliability analysis allows you to study the properties of measurement scales and the items that make them up. The Reliability Analysis procedure calculates a number of commonly used measures of scale reliability and also provides information about the relationships between individual items in the scale. Reliability Statistics for P scores Cronbach's Alpha 0.942 0.921 0.956 0.906 0.947 0.849 Reliability Statistics for (PE) scores Cronbach's Alpha 0.956 0.933 0.955 0.919 0.950 0.826

Dimensions Reliability Assurance Safe & fast delivery Personnel Physical facilities Information

N of Items 9 5 9 5 9 3

Table 4.1: Reliability Statistics for P and (P-E) Scores The attributes were segregated on the basis of logical reasoning and clubbed to form dimensions for which the reliability tests were done and the Cronbach Alpha scores calculated through SPSS reliability analysis. The iterative sequence of computing alphas and item-to-total correlation, followed by the deletion of items, was repeated several times which resulted in a set of six dimensions with 40 items, with alpha values ranging from 0.80 to 0.96 across six dimensions. The reliability tests were done on both perceived performance scores (P) and GAP scores (P-E). In most cases, the alpha values were comparable. A comparison of the alpha values for both performance and GAP scores is shown in Table 11. Whatever the reliability analysis gives positive results, the sample size is too small to calculate the test. So we cannot say that provided information about the perception on NLPL and gap score is reliable.

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4.2

SERVQUAL OUTPUT SERVQUAL instrument is used to calculate service quality gap score for 40 quality

of attributes. EXPECTATION FREQ OF RESPONSES 1 2 3 4

2 29

PERCEPTION AVG
3.635 3.651 3.444 3.730 3.698 3.651 3.397 3.492 3.810

FREQ OF RESPONSES 1
0 0 0 0 0 0 0 0 0

5
28 6

6
7

7
0

2
1 1 19 6

6
1 14 4 6 6 8 4 4 6

7
0 0 3 1 4 2 1 3 2

AVG
3.254 3.317 2.873 3.222 3.127 3.270 3.175 3.460 3.111

GAP -0.381 -0.333 -0.571 -0.508 -0.571 -0.381 -0.222 -0.032 -0.698

1 0 0 13 2 0 0 3 0 1 RELIABILITY 4 0 0 5 0 0 6 0 0 8 0 0 9 0 0 1 0 0 ASSURANCE 3 0 0 4 0 0
2 9 9 6 8

10 23 15 21 10 7 9 8 19 4 9 9 7 8

13 0 1 2

17 20

11 16 14 0 20 11 11 2 10 27 7 4 3 2 1 6 2

12 10 11 4 8 2 16 12 7 7

7 0 1 15 18
7 5

18 12 22 12 9

22 17

11 23 11 0

10 11 12

AVERAGE OF RELIABILITY = -0.411

6 19 20 4 6 4 4 5 1 5 3 6 2 6.429 6.314 6.257 6.886 6.114 0 0 0 0 0 2 18 8 8 13 10 8 4 6 10 4 1 2 0 2 3 6.000 5.229 5.886 5.686 5.543

-0.429 -1.086 -0.371 -1.200 -0.571

2 0 0 16 13 10
8 7 25 10 11 22

15 11 8 15 3 3 4 27

20 13 12 3 7 10

5 0 0 15 15 13 1 0 0 11 20 12

AVERAGE OF ASSURANCE = -0.731

4 8 6 3 2 5 3.460 3.714 3.508 3.952 3.683 3.524 3.460 3.730 3.317 0 0 0 0 0 0 0 0 0 10 17 3 18 6 11 6 10 7 8 4 7 4 11 5 6 4 0 0 3 1 1 0 2 0 0 2.968 3.286 2.984 3.206 3.032 3.016 3.063 3.127 2.825

-0.492 -0.429 -0.524 -0.746 -0.651 -0.508 -0.397 -0.603 -0.492

SAFE & FAST DELIVERY

2 0 0 4 0 0 5 0 0 6 0 0 8 0 0

10 21 9 12

14 14 11 6 6 13 7

3 0 0 18
3 7 5

16 11 19 1 14 24 28 10 0 4 8 5 5 5 3 1 1 2

10 19 8

16 10 5 5 6 11

10 18 7 5 20

7 0 0 16 10 15
3 16 25

17 10 12 7 12

9 0 0 17 16 10

15 12

AVERAGE OF DELIVERY = -0.538

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1 0 0 PERSONNEL 2 0 0 4 0 0 5 0 0

6 8

27 10 8 27

5 3 9 8 3

2 4 0 3 1

6.286 6.771 6.086 6.543 6.514

0 0 0 0 0

5 8

13 15 7

8 5 8 10 8

0 3 2 1 2

5.771 5.886 5.629 5.743 5.514

-0.514 -0.886 -0.457 -0.800 -1.000

17 10 7 6 5

3 0 0 17 12 12
3 5 29 7

10 12 11 4 5 20 24 9 6

17 24

AVERAGE OF PERSONNEL = -0.731 1 0 0 15 16 2 0 0 PHYSICAL FACILITIES 3 0 0 4 0 0 5 0 0 7 0 0 8 0 0

4 8 9 7 8 7 4 3.476 3.952 3.841 3.444 3.635 3.317 3.571 3.873 3.317 0 0 0 0 0 0 0 0 0 11 12 9 6 15 5 4 18 5 9 14 6 3 8 4 7 6 4 9 4 6 1 0 4 0 3 2 2 1 2 3.000 3.032 3.413 2.984 3.349 3.111 2.984 3.317 2.984

-0.476 -0.921 -0.429 -0.460 -0.286 -0.206 -0.587 -0.556 -0.333

14 12 19 1 7 23 9 5 2 5 7 9 2 3 2 2 1 2 3 1

13 14 3 6 14 21 9 4

23 10 12 10 8 8 3 14 11 9

24 10 13 26

6 0 0 16 16 12
6 4 24 11 13 21

24 12 8 9

9 0 0 16 13 18 1 0 0

14 11

AVERAGE OF TANGIBILITY = -0.473

8 6 7 14 21 23 11 10 25 3 5 6 4 5 2 11.000 0 10.952 0 11.238 0 6 16 7 14 13 8 11 9 6 9 4 8 6 4 1 1 9.667 8.810 9.333

-1.333 -2.143 -1.905

INFO

2 0 0 3 0 0

14 13

AVERAGE OF INFORMATION = -1.794 OVERALL GAP = -0.780

Table 4.2: SERVQUAL Output (Attribute) From the SERVQUAL instrument, gap score is -0.780. This indicates great opportunity for network logistics to improvement their service. All dimensions are having negative results. Expectations from customers are high when compare to perceptions and there are faults in the service that are generating unsatisfactory results among the customers. Reliability (-0.411) , safe & fast delivery (-0.538) and physical facilities (-0.473) are the dimensions which got low negative gaps shows that three dimensions makes good quality of service from network logistics. Information (-1.794) dimensions got very big gap when compare to other dimensions.

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4.2.1 SERVQUAL OUTPUT (DIMENSION) SERVQUAL instrument is used to calculate service quality gap score for 6 quality of dimensions. DIMENSION RELIABILITY ASSURANCE SAFE & FAST DELIERY PERSONNEL TANGIBILITY INFORMATION E 3.612 6.400 3.594 6.440 3.603 11.063 P 3.201 5.669 3.056 5.709 3.131 9.270 G -0.411 -0.731 -0.538 -0.731 -0.473 -1.794

Table 4.3: SERVQUAL Output (Dimension) REL

12 10 8

INFO

6 4 2 0

AS

E P

TAN

SAFE

PER Figure 4.1: SERVQUAL Output (Dimension) A radar chart was generated based on the mean scores on SERVQUAL dimensions. Chart reveals that gap exists on SERVQUAL dimension of information (-1.794). Assurance and personnel dimensions got -0.731 gap score between perception and expectation. Negative value simply means the quality of service received by the customers is less than the customers expected level, thus indicating poor service quality performance. According to Table above, the difference of mean between the customers perception and expectation yields negative values for all dimensions. Generally, it indicates that NLPL is performing below the expected level of their customers.

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4.3 FRIEDMAN TEST (MEAN) Friedman test is analyzed for perceived score given by customers for SERVQUAL 40 attributes of NLPL. The mean rank for 40 attributes is shown in following table.
ATTRIBUTE REL1 REL2 REL3 REL4 REL5 REL6 REL7 REL8 REL9 AS1 AS2 AS3 AS4 AS5 SAFE1 SAFE2 SAFE3 SAFE4 SAFE5 SAFE6 SAFE7 SAFE8 SAFE9 PER1 PER2 PER3 PER4 PER5 TAN1 TAN2 TAN3 TAN4 TAN5 TAN6 TAN7 TAN8 TAN9 INFO1 INFO2 INFO3

Dim Attributes Supplies the materials as per your indents Provides proper suppliers details and documentation Maintains proper receipt and accounting details Having flexible payments methods and conditions Informs accurate description of pipelines, rigs etc., Having the most suitable vehicle for transport Provides flexible in combining two or three destination Having proper documentation for custom clearance Provides Customer Specific Free Time Restricts multiple handling between terminals Takes care on duty and refund for goods Settles the issues on merit Specializes at various custom guidelines of other countries Sets clear Interpretation of Rules Inspects the materials after and before given to clients Having speed and consistency of transport Delivers the shipments on time Plans and schedules easy route for transportation Ensures vehicle safety Having safety precautionary items are well in condition Provides vigilance and securities for warehouse Examines the shipments for safety Concentrates on safe Transit of Goods Provides technical expertise to customers Having expert Labor force to handle materials Experts on port handling Having dedicated shipping professionals Having highly qualified, experienced staff Provides multimodal transportation Provides trailers, trucks, cranes to handle materials Establishes agents worldwide Sticks Labels to materials while packing Having wide space area to store material Always having covered sheds in warehouse Having warehouse layout that suitable for vehicle in and out Tracks exact location of materials Having warehousing Facilities at Good sheds Provides Reliable Information while communication Having proper Communication from Top to Bottom Provides information of Placement in Advance Table 4.4: Friedman Test (Mean)
INFO PHYSICAL FACILITIES PERSONNEL SAFE & FAST DELIVERY ASSURANCE RELIABILITY

Mean rank 23.61 24.48 15.39 22.37 21.13 23.11 20.74 22.04 19.73 23.67 16.35 23.31 21.07 19.50 18.75 23.74 18.02 22.43 18.72 19.52 19.66 20.99 14.98 21.68 22.56 20.85 19.74 19.64 18.13 19.13 25.86 17.65 23.60 20.12 17.43 23.26 17.52 21.64 17.95 19.93

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NULL HYPOTHESIS (H0): no significance difference between mean of perceived level of responses. ALTERNATIVE HYPOTHESIS (H1): significance difference between mean of perceived level of responses. According to mean ranks of Friedman test the 10 least are most important attributes and operations manager should take into consideration while they make a decision in future marketing strategy to reduce the Gap. These ten attributes comes from the following question in the questionnaire (REL3, AS2, SAFE3, SAFE5, SAFE9, TAN1, TAN4, TAN7, TAN9, INFO2). That are Maintains proper accounting details, Takes care on refunds for goods, Delivers the shipments on time, Ensuring vehicle safety, safe transmit of goods, Providing multimodal transportation, labeling, layout of warehouse suits for transportation, a good sheds and proper communication. N 50 Test statistic Chi-Square 109.537 DF 39 Asymp. Sig. 0

Table 4.5: Test Statistic for Friedman Test (Mean) From the asymptotic significances value is less than 0.05. Null hypothesis is rejected. Alternative hypothesis is accepted. There is an overall statistically significant difference between the mean ranks of the related groups.

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4.4 PAIRED T TEST

Paired t-test is conducted between expected average value from 40 attributes and perceived average values. So we can get whether customer feel any difference between expected and perceived service.

NULL HYPOTHESIS (H0): there is no significance difference between expected and perceived level of service. ALTERNATIVE HYPOTHESIS (H1): there is significance difference between expected and perceived level of service. Paired Samples Test Paired Differences Mean Std. Std. 95% Confidence Deviation Error Interval of the Mean Difference Lower Upper Pair 1 E&P .63712 .41842 .06615 .50330

DF

Sig. (2-tailed)

.77094 9.630

39

.000

Table 4.6: Paired T Test From the above results, test statistic (t) is less than 0.05. So null hypothesis is rejected. Alternative hypothesis is accepted. The responses of customers before service get from provider is differed from responses after serviced. This indicates customers got different service what they expected. We cant say the service is improved. But the change of feel happened. The SERVQUAL gap shows negative value. So that the service quality isnt improved.

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4.5

CORRELATION TEST Correlation analysis is between averages of all dimensions. Correlation transformer

to determine extent to which changes in value of an dimension is associated with changes in another dimension. NULL HYPOTHESIS (H0): there is no significance difference between service dimensions. ALTERNATIVE HYPOTHESIS (H1): there is significance difference between service dimensions. AVG OF REL AVG OF REL Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N 1 AVG OF AS .910 .000 100 1 AVG OF AVG AVG OF SAFE OF PER TAN .922 .000 100 .921 .000 100 1 .930 .000 100 .916 .000 100 .905 .000 100 1 .959 .000 100 .926 .000 100 .939 .000 100 .935 .000 100 1 AVG OF INFO .924 .000 100 .925 .000 100 .923 .000 100 .889 .000 100 .924 .000 100 1

100 .910 .000 100 .922 .000 100 .930 .000 100 .959 .000 100 .924 .000 100

AVG OF AS

100 .921 .000 100 .916 .000 100 .926 .000 100 .925 .000 100

AVG OF SAFE

100 .905 .000 100 .939 .000 100 .923 .000 100

AVG OF PER

100 .935 .000 100 .889 .000 100

AVG OF TAN

100 .924 .000 100

AVG OF INFO

100

Table 4.7: Correlation Test

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All Pearson correlation coefficient for dimensions are highly positive correlated. All significance value is less than 0.05. So null hypothesis is rejected. Alternative hypothesis is accepted. There is no significance difference between the averages of dimensions. From this analysis reliability dimension has strong relationship with physical facilities (0.959), furthermore, the physical facilities dimension has more relationship with safe & fast delivery (0.939). Physical facilities have good relationship with personnel dimension (0.935). This is substantiated by the coefficient of determination (r2 = 0.8817 and r2 = 0.8742), which indicates that 88.17% and 87.42 of the variation in physical facilities dimension can be explained by the timely delivery and personnel dimensions respectively.

4.6 KANOS MODEL OUTPUT Kano category Attractive Must be One dimensional Indifferent Reverse

Attribute number

Total 9 10 6 15 0 Total attributes 40

1,8,12,17,21,23,24,28,39 3,6,9,11,14,20,26,32,36,40 7,16,27,30,35,38 2,4,5,10,13,15,18,19,22,25,29,31,33,34,37 --

Table 4.8: KANOS Model Output One There are 10 service quality attributes, occupied most, categorized into must-be quality attributes, representing indispensable of service quality; 6 service quality attributes are categorized into one-dimensional, meaning the more sufficiency of those are the more customer satisfaction will result in and vice versa and 9 service quality attributes are categorized into attractive, indicating this attractive delights and attracts customers. Maximum 15 attributes shown as indifferent category, because of nearly thousands logistics service providers in Chennai. So all service providers not given as much different from others. And also repeatedly same projects are done through network logistics to customers. So they feel that 15 service quality attributes are similar to other service providers in India.

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No 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40

ATTRIBUTE REL1 REL2 REL3 REL4 REL5 REL6 REL7 REL8 REL9 AS1 AS2 AS3 AS4 AS5 SAFE1 SAFE2 SAFE3 SAFE4 SAFE5 SAFE6 SAFE7 SAFE8 SAFE9 PER1 PER2 PER3 PER4 PER5 TAN1 TAN2 TAN3 TAN4 TAN5 TAN6 TAN7 TAN8 TAN9 INFO1 INFO2 INFO3

A 72% 4% 12% 6% 14% 12% 26% 34% 20% 16% 14% 46% 24% 14% 20% 18% 42% 8% 14% 16% 38% 16% 72% 44% 4% 14% 26% 38% 16% 22% 22% 10% 16% 8% 16% 10% 12% 22% 56% 22%

KANO CLASSIFICATION O M I 16% 4% 8% 2% 40% 54% 12% 46% 30% 6% 36% 52% 12% 18% 56% 2% 44% 42% 32% 18% 24% 14% 20% 32% 12% 40% 28% 8% 6% 70% 10% 36% 30% 10% 14% 30% 2% 12% 62% 8% 40% 38% 6% 10% 64% 44% 8% 30% 14% 18% 26% 8% 34% 50% 10% 30% 46% 6% 42% 36% 16% 12% 34% 2% 22% 60% 8% 8% 12% 6% 10% 40% 4% 34% 58% 4% 44% 38% 38% 18% 18% 14% 14% 34% 14% 6% 64% 48% 20% 10% 6% 10% 66% 6% 72% 12% 8% 24% 52% 8% 18% 66% 66% 12% 6% 8% 46% 36% 6% 16% 66% 46% 14% 18% 6% 12% 26% 4% 62% 12%

R 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%

KANO CATEGORY A I M I I M O A M I M A I M I O A I I M A I A A I M O A I O I M I I O M I O A M

Table 4.9: KANOS Model Output Two

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4.6.1

Customer satisfaction coefficient (CS coefficient) CSC calculates the ratio of the number of subjects that get satisfied with the

presence of an item to the number of the subjects that get dissatisfied with the absence of that item. The CS coefficient is indicative of how strongly a service requirement may influence customer satisfaction or, in case of its dissatisfaction.
Attributes REL1 REL2 REL3 REL4 REL5 REL6 REL7 REL8 REL9 AS1 AS2 AS3 AS4 AS5 SAFE1 SAFE2 SAFE3 SAFE4 SAFE5 SAFE6 SAFE7 SAFE8 SAFE9 PER1 PER2 PER3 PER4 PER5 TAN1 TAN2 TAN3 TAN4 TAN5 TAN6 TAN7 TAN8 TAN9 INFO1 INFO2 INFO3 DDI -0.200 -0.420 -0.580 -0.420 -0.300 -0.460 -0.500 -0.340 -0.520 -0.140 -0.511 -0.240 -0.140 -0.480 -0.160 -0.520 -0.320 -0.420 -0.400 -0.480 -0.280 -0.240 -0.160 -0.160 -0.380 -0.480 -0.560 -0.280 -0.200 -0.680* -0.154 -0.780* -0.320 -0.260 -0.780* -0.540 -0.220 -0.600* -0.180 -0.660* SII 0.880* 0.060 0.240 0.120 0.260 0.140 0.580 0.480 0.320 0.240 0.267 0.560 0.260 0.220 0.260 0.620* 0.560 0.160 0.240 0.220 0.540 0.180 0.800* 0.500 0.080 0.180 0.640* 0.520 0.300 0.700* 0.269 0.160 0.240 0.160 0.820* 0.180 0.180 0.680* 0.620* 0.260

Table 4.10: CS Coefficients

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The customer satisfaction index states whether satisfaction can be increased by providing quality elements, or whether fulfilling quality elements only prevents the customer from being dissatisfied. Based on satisfaction increment index (SII) and dissatisfaction decrement index (DDI), we can find out which quality element can result in maximum outcome. For instance, a TAN7 with a negative CS-coefficient of -0.78 leads to more than proportional dissatisfaction; REL1 with a positive CS-coefficient of 0.88 can only slightly increase satisfaction. The SII and DDI (satisfaction increase and dissatisfaction decrease indices) of our attributes can be seen in the Table for each SERVQUAL attributes. Supply of the materials as per customers indents which have a high absolute level of DDI. The items which demonstrate both low absolute SII and DDI levels fall into the indifferent category since their effect in inducing either satisfaction or dissatisfaction is rather on the low end. In addition the items which enjoy high SII levels (more than 0.5) while their absolute DDI level is low (less than 0.5) are considered as attractive, that evoke surprise and pleasant satisfaction in case being sufficiently delivered (Kuo, 2004). Based on the above criteria attributes REL3,REL7,AS2, SAFE2, PER4 and TAN8 do not have much influence in the satisfaction or dissatisfaction of the customers However CS coefficients yields some further evidence with respect to the nature of ServQual items, revealing that attributes REL2,PER2 and TAN4 tend to be a weak excitement factors (Table 20).

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40 39 38 37 36 35 34 33 32 31 30 29 28 27 26 25 24 23 22 21 20 19 18 17 16 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1 -100% -80% -60% -40% DDI -20% 0% 20% 40% SII 60% 80% 100%

Figure 4.2: SII & DDI

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CHAPTER V FINDINGS, SUGGESTIONS & CONCLUSIONS

5.1 FINDINGS

This overall SERVQUAL gap (-0.780) indicates great opportunity for network logistics to improvement their service. NLPL must concentrate on accuracy of information and order of communication. Reliability (-0.411) , safe & fast delivery (-0.538) and physical facilities (-0.473) are the dimensions which got low negative gaps shows that three dimensions makes good quality of service from NLPL. NLPL have very well records on quickest delivery and handling materials in well. The difference of mean between the customers perception and expectation yields negative values for all dimensions. Generally, it indicates that NLPL is performing below the expected level of their customers. From the Friedman test the 10 least are most important attributes. That are Maintains proper accounting details, Takes care on refunds for goods, Delivers the shipments on time, Ensuring vehicle safety, safe transmit of goods, Providing multimodal transportation, labeling, layout of warehouse suits for transportation, a good sheds and proper communication. Paired t-test explains the responses of customers before service get from provider is differed from responses after serviced. This indicates customers got different service what they expected. Definitely the service from NLPL makes customers satisfaction. The correlation test between dimensions explains that the reliability dimension has strong relationship with physical facilities (0.959), furthermore, the physical facilities dimension has more relationship with safe & fast delivery (0.939). Physical facilities have good relationship with personnel dimension (0.935). so whenever taking decision providing any excess facilitating goods to customer NLPL must concentrate on whether enough workers are there and timely delivery is possible for that facilitating goods. This is substantiated by the coefficient of determination (r2 = 0.8817 and r2 = 0.8742), which

indicates that 88.17% and 87.42 of the variation in physical facilities dimension can be explained by the timely delivery and personnel dimensions respectively. According to KANOs model results The Attractive(A) attributes are supplies the materials as per customer indent, proper documentation for custom clearance, settles the

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issues on merit, delivers the shipments on time, vigilance and securities for warehouse, safe transit of goods, provides technical expertise, highly qualified and experienced staff, proper communication from top to bottom. The Must-be(M) attributes are maintains proper accounting details, most suitable vehicle for transport, customer specific free time, takes care on duty and refund for goods, sets clear interpretation of rules, safety precautionary items are well in condition, experts on port handling, sticks labels to materials, warehousing facilities at good sheds and provides information of placement in advance. The One-dimensional(O) attributes are provides flexible in combining two or three destination, speed and consistency of transport, dedicated shipping professionals, provides trailers, trucks, cranes to handle materials, tracks exact location of materials, reliable information while communication. The rest of 15 attributes are categorizes as Indifferent (I). The customer satisfaction coefficient explains five attributes increases the customer satisfaction. That are provides trailers, trucks, cranes to handle materials, sticks labels, having warehouse layout that suitable for vehicle in and out, reliable information while communication and provides information of placement in advance. Seven attributes decreases the customer dissatisfaction. That are supplies the materials as per your indents, speed and consistency of transport, safe transit of goods, dedicated shipping professionals, provides trailers, trucks, cranes to handle materials, having warehouse layout that suitable for vehicle in and out, reliable information while communication and proper communication from top to bottom.

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5.2

RECOMMENDATIONS

NLPL must maintain accuracy of information while communicating with customers. Handling materials like trailers, cranes for various sizes and various dimensions need to be focused. Air and shipping cargo workers able to attain their level of competency. Take care on duty and refunds of the goods. NLPL avoids multiple handling goods between terminals totally. While concentrating on export and import, NLPL having agents only on Asia and Middle East countries. So NLPL need to avail agents worldwide level. Whenever taking decision providing any excess facilitating goods to customer NLPL must concentrate on whether enough workers are there and timely delivery is possible for that facilitating goods. Must-be (M) attributes are in any case a decisive competitive factor, and if they are not fulfilled, the customer will not be interested in the service at all. Attractive (A) attributes are neither explicitly expressed nor expected by the customer. Fulfilling these requirements leads to more than proportional satisfaction. If they are not met, however, there is no feeling of dissatisfaction. One-dimensional (O) requirements are usually explicitly demanded by the customer. On safety concerns, inspects the materials after and before given to clients. Because safety leads to good quality of service.

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5.3

CONCLUSION

This study evaluated the situation of service quality based on the Service Quality gap Model to determine the fifth service gap in NLPL. The results shows that customers expect that six dimensions of SERVQUAL for delivering excellent service get high levels, but their perceptions resulting from the perceived service are evaluated in moderate level. It also became clear that all quality of dimensions need to be concentrated equally in logistics industry. In addition, it was found that in all six criteria of service quality model there are gaps between expectations and perceptions of customers, it means that the perceived services was nearly equal to expected needs of clients and customers get satisfaction with the perceived services. It is suggested that these SERVQUAL instrument is used to measure service quality continuously. If one knows to what extent a service feature influences the perceived service quality and in turn influences customer satisfaction (must - be, one- dimensional or attractive requirement), and if one is aware of the relative significance of this service feature and assessment from the customers viewpoint compared to the competitors, the satisfaction portfolio can be drawn up and suitable measures taken. Of utmost priority are those service requirements which the customer regards as important and which show disadvantages with respect to competitors products. The long- term objective is to improve customer satisfaction with regard to important service features in order to establish tenable competitive advantage.

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BIBLIOGRAPHY BOOKS:

1. Indian Chamber of Commerce, Logistics Sector Present situation and way forward, deloitte, 2012. 2. Harlina Suzana Jaafar, Logistics Service Quality and Relationship Quality in Third Party Relationships, 2nd edition, Loughborough University press, 2006.

JOURNALS:

1. Bienstock. Carol C., John T. Mentzer. And Monroe Murphy Bird (1997). "Measuring Physical Distribution Service Quality:' Journal of the Academy of Marketing Science, 25 (Winter), 31-44. 2. Brown, Tom J... Gilbel A. Churchill, and J. Paul Peter (1993), "Research Note: Improving the Measurement of Service Quality," Journal of Retailing, 69 (Spring), 127-39. 3. Cronin, J. Joseph and Steven A. Taylor (1992), "Measuring Service Quality: A Reexamination and Extension," Journal of Marketing, 56 (July), 55-68. 4. Lovelock, Christopher H. (1983), "Classifying Services to Gain Strategic Marketing Insights:' Journal of Marketing, 47 (Summer), 9-20. 5. Mentzer, John T. (1993), "Managing Channel Relations in the 21st Century:' Journal of Business Logistics, 14 (1),27-42. 6. Murphy, Paul R. and James M. Daley (1994), "A Framework for Applying Logistical Segmentation," Logistics Management, International 24 Journal of Physical Distribution And Richard F. Poist and

(10), 13-20. -

(1996),

"Comparative Views of Logistics and Marketing Practitioners Regarding Interfunctional Coordination;' International Journal of Physical Distribution and Logistics Management, 26 (8), 15-28. 7. Parasuraman, A., VA&arie A. Zeithaml, and Leonard L. Berry (1985), "A

Conceptual Model of Service Quality and Its Implications for Future Research;' Journal of Marketing, 49 (Fall). 41-50. and (1988), "SERVQUAL: A MultipleItem Scale for Measuring Consumer Perceptions of Service Quality;' Journal of

74

Retailing, 63 ( I), 12-37. and (1991), "Refinement and Reassessment of the SERVQUAL Scale;' Journal of Retailing, 67 (4),420-50 and (1993), "Research Note: More on Improving Service Quality Measurement~" Journal of Retailing, 69(1),140-47. and (1994), "Reassessment of Expectations as a Comparison Standard in Measuring Service Quality: Implications for Future Research;' Journal of Marketing, 58 (January), 111-24. 8. Berger, Charles; Blauth, Robert; Boger, David; Bolster, Christopher; Burchill, Gary; DuMouchel, William; Pouliot, Fred; Richter, Reinhard; Rubinoff, Allan; Shen, Diane; Timko, Mike; Walden, David. "Kanos Methods for Understanding Customer - defined Quality", In: Center for Quality Management Journal, Vol. 4 (Fall 1993), pp. 3 - 36. 9. Kano, N., N. Seraku, F. Takahashi and S. Tsuji: "Attractive Quality and Must- be Quality", Hinshitsu. The Journal of the Japanese Society for Quality Control, (April 1984), pp. 39 - 48. 10. Shen, X.X., Tan, K.C. and XIE,M. (2000), An integrated approach to innovative product development using Kanos model and QFD, European Journal of Innovation Management, Vol. 3 No. 2, pp. 91-9.

WEBSITES:

1. www.networklogistics.in 2. www.citeoperations.com 3. www.managementstudyguide.com 4. www.financialexpress.com

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A. We would like your impression about the performance of Network Logistics Private Ltd relative to your desired service
level, i.e., the level of service you desire. For each of the following attributes, please indicate your desired service level and your perceptions of Network Logistics Private Ltd by encircling one of the numbers in the third and the fourth column respectively. My Desired Service Level is Low 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 High 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 My Perception of NLPL Service Performance is Low High 1 2 3 4 5 6 7 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7 6 7

No

Attributes

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40

Supplies the materials as per your indents Provides proper suppliers details and documentation Maintains proper receipt and accounting details Having flexible payments methods and conditions Informs accurate description of pipelines, rigs etc., Having the most suitable vehicle for transport Provides flexible in combining two or three destination Having proper documentation for custom clearance Provides Customer Specific Free Time Restricts multiple handling between terminals Takes care on duty and refund for goods Settles the issues on merit Specializes at various custom guidelines of other countries Sets clear Interpretation of Rules Inspects the materials after and before given to clients Having speed and consistency of transport Delivers the shipments on time Plans and schedules easy route for transportation Ensures vehicle safety Having safety precautionary items are well in condition Provides vigilance and securities for warehouse Examines the shipments for safety Concentrates on safe Transit of Goods Provides technical expertise to customers Having expert Labor force to handle materials Experts on port handling Having dedicated shipping professionals Having highly qualified, experienced staff Provides multimodal transportation Provides trailers, trucks, cranes to handle materials Establishes agents worldwide Sticks Labels to materials while packing Having wide space area to store material Always having covered sheds in warehouse Having warehouse layout that suitable for vehicle in and out Tracks exact location of materials Having warehousing Facilities at Good sheds Provides Reliable Information while communication Having proper Communication from Top to Bottom Provides information of Placement in Advance

3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3

4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5 4 5

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B. We would like to know how much each of these sets of features is important to the customer. Please allocate 100 points among the five sets of features according to how important it is to you. Make sure the points add up to 100. Dimensions The ability to perform the promised service dependably and accurately. The service is accomplished on time, in the same manner and without errors every time. The knowledge and courtesy of NLPL and their ability to convey the trust, confidence and competence to perform the service. The ability to provide safe and fast delivery Attitude of officers and staff The physical facilities, equipment and material handling facilities made available to the customer The clarity, completeness and accuracy of both verbal and written information communicated to the customer Total 100 Points

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C. We would like to know how much each of these 40 features is important to the customer. Please choose any one among five options (H, M, I, A, U) if NLPL service has that feature and service does not have that feature. Make sure that you must give answers for Question 1 and Question 2 separately. Follow the below instructions. Functional (Q1): Dysfunctional (Q2):
Question 1: If the attribute meets the need, how do you feel? Question 2: If the attribute doesnt meet the need, how do you feel?

H-- This would be very helpful M-- This is a basic requirement I---This would not affect A--This would be a minor inconvenience U--This would be a major problem and I cant accept it

H--This would be very helpful M--This is a basic requirement I---This would not affect A--This would be a minor inconvenience U--This would be a major problem and I cant accept it.

S No

Attributes
( H-Happy; M-Must be; I-Indifferent; A-Acceptable; U-Unhappy)
Supplies the materials as per your indents Provides proper suppliers details and documentation Maintains proper receipt and accounting details Having flexible payments methods and conditions Informs accurate description of pipelines, rigs etc., Having the most suitable vehicle for transport Provides flexible in combining two or three destination Having proper documentation for custom clearance Provides Customer Specific Free Time Restricts multiple handling between terminals Takes care on duty and refund for goods Settles the issues on merit Specializes at various custom guidelines of other countries Sets clear Interpretation of Rules Inspects the materials after and before given to clients Having speed and consistency of transport Delivers the shipments on time Plans and schedules easy route for transportation Ensures vehicle safety Having safety precautionary items are well in condition Provides vigilance and securities for warehouse Examines the shipments for safety Concentrates on safe Transit of Goods Provides technical expertise to customers Having expert Labor force to handle materials Experts on port handling Having dedicated shipping professionals Having highly qualified, experienced staff Provides multimodal transportation Provides trailers, trucks, cranes to handle materials Establishes agents worldwide Sticks Labels to materials while packing Having wide space area to store material Always having covered sheds in warehouse Having warehouse layout that suitable for vehicle in and out Tracks exact location of materials Having warehousing Facilities at Good sheds Provides Reliable Information while communication Having proper Communication from Top to Bottom Provides information of Placement in Advance

Q1:Functional Q2:Dysfunctional H M I A U H M I A U

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39

40