The Autonomous Factors

This model demonstrates that the autonomous factors are unite on the left side and the reliant variable is joined on the correct side of the model. In this table all the free factors are centering or specifically influencing the reliant variable and the needy variable is client maintenance. The theory for this exploration is given underneath:2.7 ResearchHypothesis Following are the exploration theory of the examination: H1: Service quality has positive effect on the client maintenance. H0: Service quality has no positive effect on the client maintenance. H2: Customer fulfillment has positive effect on the client maintenance. H0: Customer Satisfaction has no positive impact on client maintenance. H3: Customer reliability has positive impact on the client maintenance. H0: Customer reliability has no positive effect on the client maintenance. H4: Environment   has positive effect on the client maintenance. H0: Environment has no positive impact on the client maintenance.3. MethodologyIn this exploration the easygoing examination has been utilized to clarify the impact of the free factors (benefit quality, consumer loyalty, client steadfastness, condition t) on the needy variable (client retention).The information for this exploration has been taken from 300 members by utilizing the instructive and mental estimation table (Krejcie, Robert 1970) . Add up to number of 160 surveys from out of 300 was returned which were totally and accurately filled by the members which were worthy for the investigation to go ahead. In this examination the helpful testing is been utilized to gather information from the members to bear on the exploration.3.1 InstrumentsIn this paper we have utilized the strategy which was beforehand embraced in the examinations, the poll was made out of aggregate 19 questions. First4 questions were of individual statistic and remaining 15 were of the 5 factors which were utilized as a part of this paper. Measurable bundle for sociologies (SPSS) rendition 20.0 was utilized for the investigation of the factors gathered through the survey.3.2 DateAnalysis procedures Unwavering quality examination is utilized as a part of this paper to check the dependability of the poll. As it is said in the past investigations that dependability examination acknowledgment run is over 0.70(Nunnally, 1978) . Pearson connection examination is utilized to check the connection between the diverse factors. What's more, the direct relapse investigation is utilized to discover the impact of the autonomous factors on the reliant factors.4. DataAnalysis and Results The Frequency table demonstrates that the information gathered from respondents incorporate 60% male and 40% female. Table no.1 Elucidation Keeping in mind the end goal to confirm the entomb thing consistency of things, Cronbach's alpha test was keep running on spss. The Cronbach's alpha test is utilized to recognize that how much our reactions on our examination are solid .The Cronbach's alpha shows esteems in above table including the estimation of every factor .The qualities are above to the standard esteem proposed by (Nummally, 1978) of 0.70, which exhibits that our instrument is dependable and we can irrefutably apply different measurable tests and decipher the results with assurance. Understanding Connection test was actualized to break down the connection between factors. Connection table proposed every one of the factors were emphatically associated to customer buy goal. The most connected variable was CL having Pearson Correlation estimation of r(120) = .648, p

Body & Cultural Text Essay

When a person has watched a film, advertisement or read a book, there are distinct elements that are evident throughout the work of art that seemingly communicate more than their surface meaning. This essay seeks to demonstrate how metaphor, connotation and metonym are usually used in distinct cultural texts such as in books, film and others. It specifically applies the basic concepts of communication theory to cultural texts, objects and images. Body Communication theory lays emphasis on exchange and production of meaning and information through symbols and signs (Littlejohn, 2002). It draws its argument from encoding and sending of a specific message, where it is received and decoded by the recipient and synthesized for a meaning and information to be drawn out of it. What communication theory depicts is that communication does permeate all evels of human experience while being central to comprehending a certain human behavior (Griffin, 1997). Through metonym, metaphor and connotation, the main elements of communication theory are brought into focus, since they are figurative use of sending certain messages but in distinct ways. Through them, cultural texts are deciphered and understood, where meanings are drawn beyond the surface meaning. Metonym Metonym, a figure of speech, is rhetorically used where a concept or entity is not called by its name but through the name of another thing that is associated intimately with it. It is the use of a single object or thing to identify another, which might be related. For example, in Act III, scene II of Shakespeare’s Julius Caesar, (Lines 74-77): ‘Friends, Romans, countrymen, lend me your ears’ (Pickering & Hoeper, 1982). ‘Ear’ in this case represents attention, since it is the ears that we use to pay attention to speech. Once the ‘lending ear’ (attention) has been heard, the basic understanding of ‘lend’ (to borrow something) is stretched to include nonmaterial things, in this case attention. Washington might be the capital of the United States, but it is usually used as an obvious metonym for the U. S. government. In film, metonym gives meaning to distinct elements of plot, such as in the recent movie, American Beauty. It is a comedy where personal, inner conflict is depicted through metonyms. For instance, the protagonist, ‘Tootsie’, shows signs of inner conflict when he lacks confidence to carry out a scam. In another level of conflict, metonyms in the form of coworkers, boss, father, friends, TV audience and his love depict the protagonist’s social conflict. The movie is all about different levels of conflict that are splendidly shown metonymically, through different contexts. This is achieved through outward projection of different levels of conflict on other characters it is seen, creating a very dramatic impact. Particular types of metonyms in substitution do influence our thoughts, actions and attitudes. This is achieved through focusing on a specific aspect and suppressing another inconsistent with a particular metonym. For example, Lakoff and Johnson argue that when you think about ‘Picasso’, your thoughts move beyond a piece of art (1980). You start thinking of it in relation to the individual, his artistic conception, technique, art in history and other relations. Connotation Connotation in texts, expressions and in mere words shows the expressed and emotive part of a language. Seemingly, all connotative signs and expressions lie vaguely midway between ambiguity and symbolism. For instance, the word ‘iron’ denotes a very tough metal but can connote that a man is a piece of ‘iron’ since he has won a boxing match without a problem. Connotations form a major component of poetry, where its power of expression, suggestion and emotion offers parameters that gauge the literary capability of an author while the cultural text awareness of the reader is revealed. This means that connotation must be culture and text bound to be of any significance. For instance, in Elizabethan times black was synonymous to piracy, lust, infidelity and cruelty. This is shown in Shakespeare’s depiction of Elizabethan disgust of the connotation black in more vivid racial terms. In Othello, Iago expresses that â€Å"†¦ an old black ram is tupping your white ewe† and â€Å"arise†¦or else the devil will make a grandsire of you† (Pickering & Hoeper, 1982). This association of Othello shows the established historical connotation that Western nations had concerning black as pure evil. The communicative element of connotation is pervasive and everywhere. It is expressed in all cultures and dwells across all ages in all literary styles, genres, cultural expression such as music, architecture and painting. Music offers something more to people beyond the rhythm and stones, thus connotation end up being capable of having double meanings and creating euphemisms. In film, connotation makes a communicative entry, as in the official poster of Ugly Betty, Season 2. In the poster, there is a darker background that lies behind Alexis, Amanda, Daniel, Marc, Claire and Willie, connoting Mode as being business and in that juncture, wealth and money equals evil and power. In the same poster, there is a white and blue background behind Betty, Hilda, Henry, Justin, Christina and Iganscio. This connotes family, happiness, tranquility and deeper peace. In hair product advertisements, the portrayal of hair as free flowing and seemingly in motion in an immaculate style connotes a woman readying herself to socialize, in that the free-flowing hair connotes freedom, as elaborated by Williamson, (1978). Metaphor Metaphors are simply comparisons showing two things, unlike in a major way, but importantly similar in a certain way. Being an analogy, a metaphor lies between two ideas or objects and elaborated through the usage of a certain word, which communicates figuratively. In books, metaphors communicate a poetic imagination that enables authors such as Shakespeare to show a comparison between the world and stage, where humans enter and leave the stage, as seen in the drama â€Å"As You Like It†, while Robert Frost’s poem, ‘The Road Not Taken’ compares the life of a person to a journey. In film, metaphors elaborate issues figuratively, such as in a short film entitled The Unique Oneness of Christian Savage. In the film, a child loses a best friend who falls from a tall tree where they had been playing. The child then runs away from the funeral and the words spoken, and starts beating the â€Å"evil† tree that killed the friend using a broken branch. This is a visual metaphor introducing an element of conflict without the use of words but very powerful. In adverts, metaphors are used in associating products using semantic domains that have positive connotations. The truth in an advert appears like a law for advertisers to keep off from explicitly making such statements that might be either true or false. For instance, in an air freshener advert, it might be said in an advert that it will bring a tropical breeze in your home. While it is obvious it cannot do this, what is metaphorically communicated is that your house will have fresh air. In addition, the communicative element of metaphors also takes a visual course, where it becomes a window of new thinking. These visuals give the individual a chance to escape while those who are creative can explain and interpret a novel world. In understanding the metaphor, the interpretation is on the world we live where we establish the relationship. In advertising, this is even clearer and true in the recent highly creative and digital images in advertisements. In fact, the smarter a metaphor is the more unforgettable and memorable the advert campaign. In some Ford Motors adverts, the car transforms itself in different terrains, into a metallic ape along a mountain and a crocodile in a river. This is a visual metaphor for strength and safety. Most importantly, the more fun and creative the metaphor, the more unforgettable the message it conveys. It has been a major sell for adverts with figurative images. For instance, there are adverts on the campaigns on Aids by the French. It has images which are very captivating and fearful but communicate their intention. One is a naked man having sex with a gigantic venomous arachnid, while another shows a female doing the same with another, a metaphor for unprotected sex. It is disgusting and scary to say the least, but aptly effective. Such graphical metaphors depict the underlying element of communicative theory, where the way communication is done might not be important, rather, it is whether the message has been communicated at all (Littlejohn, 2002). In the case of the French Aids Campaign adverts, the emotional figurative hook connects well with the audience. Conclusion Metonyms, connotation, and metaphors are demonstrated in cultural texts with a communicative element that edifies the spirit of the communication theory. All of them work in different ways to aid communication. References Griffin, E. (1997). A first look at communication theory (3rd edition). New York: McGraw-Hill. Lakoff, G. & Johnson, M. (1980). Metaphors We Live By. Chicago: University of Chicago Press. Littlejohn, S. W. (2002). Theories of human communication (7th edition). Belmont, CA: Wadsworth. Pickering, J. & Hoeper, J. (1982). Literature. London: Macmillan. Williamson, J. (1978). Decoding Advertisements. London: Marion Boyars.

New Hoarding Technique for Handling Disconnection in Mobile

Literature Survey On New Hoarding Technique for Handling Disconnection in Mobile Submitted by Mayur Rajesh Bajaj (IWC2011021) In Partial fulfilment for the award of the degree Of Master of Technology In INFORMATION TECHNOLOGY (Specialization: Wireless Communication and Computing) [pic] Under the Guidance of Dr. Manish Kumar INDIAN INSTITUTE OF INFORMATION TECHNOLOGY, ALLAHABAD (A University Established under sec. 3 of UGC Act, 1956 vide Notification no. F. 9-4/99-U. 3 Dated 04. 08. 2000 of the Govt. of India) (A Centre of Excellence in Information Technology Established by Govt. of India) Table of Contents [pic] 1.Introduction†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. 3 2. Related Work and Motivation 1. Coda: The Pioneering System for Hoarding†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. 4 2. Hoarding Based on Data Mining Techniques†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. 5 3. Hoarding Techniques Based on Program Trees†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. 8 4. Hoarding in a Distributed Environment†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. 9 5.Hoarding content for mobile learning†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ 10 6. Mobile Clients Through Cooperative Hoarding†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. 10 7. Comparative Discussion previous techniques†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. 11 3. Problem Definition†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. 11 4. New Approach Suggested 1. Zipf’s Law †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. 2 2. Object Hotspot Prediction Model†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢ € ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ 13 5. Schedule of Work†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. 13 6. Conclusion†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ 13 References†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ 14 . Introduction Mobile devices are the computers which are having wireless communication capabilities to access global data services from any location while roaming. Now a day’s mobile devices are supporting applications such as multimedia, World Wide Web and other high profile applications which demands continuous connections and Mobile devices are lacking here. However, mobile devices with wireless communication are frequently disconnected from the network due to the cost of wireless communication or the unavailability of the wireless network.Disconnection period of mobile device from its network is called as offline period. Such offline periods may appear for different reasons – intentional (e. g. , the available connection is too expensive for the user) or unintentional (e. g. , lack of infrastructure at a given time and location). During offline periods the user can only access materials located on the device’s local memory. Mobile systems typically have a relatively small amount of memory, which is often not enough to store all the needed data for ongoing activities to continue.In such a case, a decision should be taken on which part of the data has to be cached. Often we cannot count on the user’s own judgement of what he/she will need and prefetch. Rather, in our opinion, some sort of automatic prefetching would be desirable. Uninterrupted operation in offline mode will be in high demand and the mobile computer systems should provide support for it. Seamless disconnection can be achieved by loading the files that a user will access in the future from the network to the local storage. This preparation process for disconnected operation is called hoarding.Few of the parameters which complicate the hoarding process are prediction of future access pattern of the user, handling of hoard miss, limited local hoard memory and unpredictable disconnections and reconnection, activities on hoarded object at other clients, the asymmetry of communications bandwidth in downstream and upstream. An important point is to measure the quality of the hoarding and to try to improve it continuously. An often used metric in the evaluation of caching proxies is the hit ratio. Hit ratio is calculated by dividing the number of by the total number of uploaded predictions.It is a good measure for hoarding systems, though a better measure is the miss ratio – a percentage of accesses for which the cache is ineffective. In this work we have given brief overview of the techniques proposed in earlier days and also given the idea for the new hoarding technique. 2. Related Work and Motivation Before the early 1990’s, there was little research on hoarding. Since then, however, interest has increased dramatically among research scientists and professors around the globe and many techniques have been developed. Here we have listed few of the techniques and also will discuss them in brief. Coda: The Pioneering System for Hoarding †¢ Hoarding Based on Data Mining Techniques ? SEER Hoarding System (inspired by clustering technique) ? Association Rule-Based Techniques ? Hoarding Based on Hyper Graph ? Probability Graph Based Technique †¢ Hoarding Techniques Based on Program Trees †¢ Hoarding in a Distributed Environment †¢ Hoarding content for mobile learning †¢ Mobile Clients Through Cooperative Hoarding 2. 1 Coda Coda is a distributed file system based on client–server architecture, where there are many clients and a comparatively smaller number of servers.It is the first system that enabled users to work in disconnected mode. The concept of hoarding was introduced by the Coda group as a means of enabling disconnected operation. Disconnections in Coda are assumed to occur involuntarily due to network failures or voluntarily due to the detachment of a mobile client from the network. Voluntary and involuntary disconnections are handled the same way. The cache manager of Coda, called Venus, is designed to work in disconnected mode by serving client requests from the cache when the mobile client is detached from the network.Requests to the files that are not in the cache during disconnection are reflected to the client as failures. The hoarding system of Coda lets users select the files that they will hopefully need in the future. This information is used to decide what to load to the local storage. For disconnected operation, files are loaded to the client local storage, because the master copies are kept at stationary servers, there is the notion of replication and how to manage locks on the local copies. When the disconnection is voluntary, Coda handles this case by obtaining exclusive locks to files.However in case of involuntary disconnection, the system should defer the conflicting lock requests for an object to the reconnection time, which may not be predictable. The cache management system of Coda, called Venus, diff ers from the previous ones in that it incorporates user profiles in addition to the recent reference history. Each workstation maintains a list of pathnames, called the hoard database. These pathnames specify objects of interest to the user at the workstation that maintains the hoard database. Users can modify the hoard database via scripts, which are called hoard profiles.Multiple hoard profiles can be defined by the same user and a combination of these profiles can be used to modify the hoard database. Venus provides the user with an option to specify two time points during which all file references will be recorded. Due to the limitations of the mobile cache space, users can also specify priorities to provide the hoarding system with hints about the importance of file objects. Precedence is given to high priority objects during hoarding where the priority of an object is a combination of the user specified priority and a parameter indicating how recently it was accessed.Venus per forms a hierarchical cache management, which means that a directory is not purged unless all the subdirectories are already purged. In summary, the Coda hoarding mechanism is based on a least recently used (LRU) policy plus the user specified profiles to update the hoard data-base, which is used for cache management. It relies on user intervention to determine what to hoard in addition to the objects already maintained by the cache management system. In that respect, it can be classified as semi-automated.Researchers developed more advanced techniques with the aim of minimizing the user intervention in determining the set of objects to be hoarded. These techniques will be discussed in the following sections. 2. 2 Hoarding based on Data mining Techniques Knowing the interested pattern from the large collection of data is the basis of data mining. In the earlier history of hoarding related works researchers have applied many different data mining techniques in this arena of mobile hoa rding. Mainly clustering and association rule mining techniques were adopted from data mining domain. . 2. 1 SEER Hoarding System To automate the hoarding process, author developed a hoarding system called SEER that can make hoarding decisions without user intervention. The basic idea in SEER is to organize users’ activities as projects in order to provide more accurate hoarding decisions. A distance measure needs to be defined in order to apply clustering algorithms to group related files. SEER uses the notion of semantic distance based on the file reference behaviour of the files for which semantic distance needs to be calculated.Once the semantic distance between pairs of files are calculated, a standard clustering algorithm is used to partition the files into clusters. The developers of SEER also employ some filters based on the file type and other conventions introduced by the specific file system they assumed. The basic architecture of the SEER predictive hoarding syste m is provided in figure 1. The observer monitors user behaviour (i. e. , which files are accessed at what time) and feeds the cleaned and formatted access paths to the correlator, which then generates the distances among files in terms of user access behaviour.The distances are called the semantic distance and they are fed to the cluster generator that groups the objects with respect to their distances. The aim of clustering is, given a set of objects and a similarity or distance matrix that describes the pairwise distances or similarities among a set of objects, to group the objects that are close to each other or similar to each other. Calculation of the distances between files is done by looking at the high-level file references, such as open or status inquiry, as opposed to individual reads and writes, which are claimed to obscure the process of distance calculation. pic] Figure 1. Architecture of the SEER Predictive Hoarding System The semantic distance between two file referen ces is based on the number of intervening references to other files in between these two file references. This definition is further enhanced by the notion of lifetime semantic distance. Lifetime semantic distance between an open file A and an open file B is the number of intervening file opens (including the open of B). If the file A is closed before B is opened, then the distance is defined to be zero.The lifetime semantic distance relates two references to different files; however it needs to be somehow converted to a distance measure between two files instead of file references. Geometric mean of the file references is calculated to obtain the distance between the two files. Keeping all pairwise distances takes a lot of space. Therefore, only the distances among the closest files are represented (closest is determined by a parameter K, K closest pairs for each file are considered). The developers of SEER used a variation of an agglomerative (i. e. bottom up) clustering algorithm called k nearest neighbour, which has a low time and space complexity. An agglomerative clustering algorithm first considers individual objects as clusters and tries to combine them to form larger clusters until all the objects are grouped into one single cluster. The algorithm they used is based on merging sub clusters into larger clusters if they share at least kn neighbours. If the two files share less than kn close files but more than kf, then the files in the clusters are replicated to form overlapping clusters instead of being merged.SEER works on top of a user level replication system such as Coda and leaves the hoarding process to the underlying file system after providing the hoard database. The files that are in the same project as the file that is currently in use are included to the set of files to be hoarded. During disconnected operation, hoard misses are calculated to give a feedback to the system. 2. 2. 2 Association Rule-Based Techniques Association rule overview: Let I=i1,i2†¦.. im be a set of literals, called items and D be a set of transactions, such that ?T ? D; T? I. A transaction T contains a set of items X if X? T. An association rule is denoted by an implication of the form X ? Y, where X? I, Y ? I, and X ? Y = NULL. A rule X ? Y is said to hold in the transaction set D with confidence c if c% of the transactions in D that contain X also contain Y. The rule X? Y has support sin the transaction set D if s% of transactions in D contains X? Y. The problem of mining association rules is to find all the association rules that have a support and a confidence greater than user-specified thresholds.The thresholds for confidence and support are called minconf and minsup respectively. In Association Rule Based Technique for hoarding, authors described an application independent and generic technique for determining what should be hoarded prior to disconnection. This method utilizes association rules that are extracted by data mining techni ques for determining the set of items that should be hoarded to a mobile computer prior to disconnection. The proposed method was implemented and tested on synthetic data to estimate its effectiveness.The process of automated hoarding via association rules can be summarized as follows: Step 1: Requests of the client in the current session are used through an inferencing mechanism to construct the candidate set prior to disconnection. Step 2: Candidate set is pruned to form the hoard set. Step 3: Hoard set is loaded to the client cache. The need to have separate steps for constructing the candidate set and the hoard set arises from the fact that users also move from one machine to another that may have lower resources.The construction of the hoard set must adapt to such potential changes. Construction of candidate set: An inferencing mechanism is used to construct the candidate set of data items that are of interest to the client to be disconnected. The candidate set of the client is constructed in two steps; 1. The inferencing mechanism finds the association rules whose heads (i. e. , left hand side) match with the client’s requests in the current session, 2. The tails (i. e. , right hand side) of the matching rules are collected into the candidate set.Construction of Hoard set: The client that issued the hoard request has limited re-sources. The storage resource is of particular importance for hoarding since we have a limited space to load the candidate set. Therefore, the candidate set obtained in the first phase of the hoarding set should shrink to the hoard set so that it fits the client cache. Each data item in the candidate set is associated with a priority. These priorities together with various heuristics must be incorporated for determining the hoard set. The data items are used to sort the rules in descending order of priorities.The hoard set is constructed out of the data items with the highest priority in the candidate set just enough to fil l the cache. 3. Hoarding Based on Hyper Graph Hyper graph based approach presents a kind of low-cost automatic data hoarding technology based on rules and hyper graph model. It first uses data mining technology to extract sequence relevance rules of data from the broadcasting history, and then formulates hyper graph model, sorting the data into clusters through hyper graph partitioning methods and sorting them topologically.Finally, according to the data invalid window and the current visit record, data in corresponding clusters will be collected. Hyper graph model: Hyper graph model is defined as H = (V, E) where V={v1 ,v2 ,†¦ ,vn } is the vertices collection of hyper graph, and E={e1 ,e2 ,†¦ ,em } is super-edge collection of hyper graph (there supposed to be m super-edges in total). Hyper graph is an extension of graph, in which each super-edge can be connected with two or more vertices. Super-edge is the collection of a group of vertices in hyper graph, and superedge ei = {vi1, vi2, †¦ inj} in which vi1,vi2 ,†¦ ,vin ? V . In this model, vertices collection V corresponds to the history of broadcast data, in which each point corresponds to a broadcast data item, and each super-edge corresponds to a sequence model. Sequence model shows the orders of data items. A sequence model in size K can be expressed as p = . Use of hyper graph in hoarding are discussed in paper in details. 4. Probability Graph Based Technique This paper proposed a low-cost automated hoarding for mobile computing.Advantage of this approach is it does not explore application specific heuristics, such as the directory structure or file extension. The property of application independence makes this algorithm applicable to any predicative caching system to address data hoarding. The most distinguished feature of this algorithm is that it uses probability graph to represent data relationships and to update it at the same time when user’s request is processed. Before d isconnection, the cluster algorithm divides data into groups.Then, those groups with the highest priority are selected into hoard set until the cache is filled up. Analysis shows that the overhead of this algorithm is much lower than previous algorithms. Probability Graph: An important parameter used to construct probability graph is look-ahead period. It is a fixed number of file references that defines what it means for one file to be opened ‘soon’ after another. In other words, for a specific file reference, only references within the look-ahead period are considered related. In fact, look-ahead period is an approximate method to avoid traversing the whole trace.Unlike constructing probability graph from local file systems, in the context of mobile data access, data set is dynamically collected from remote data requests. Thus, we implemented a variation of algorithm used to construct probability graph, as illustrated in Figure 2. [pic] Figure 2. Constructing the prob ability graph The basic idea is simple: If a reference to data object A follows the reference to data object B within the look-ahead period, then the weight of directed arc from B to A is added by one. The look-ahead period affects absolute weight of arcs.Larger look-ahead period produces more arcs and larger weight. A ’s dependency to B is represented by the ratio of weight of arc from B to A divided by the total weight of arcs leaving B. Clustering: Before constructing the final hoard set, data objects are clustered into groups based on dependency among data objects. The main objective of the clustering phase is to guarantee closely related data objects are partitioned into the same group. In the successive selecting phase, data objects are selected into hoard set at the unit of group. This design provides more continuity in user operation when disconnected.Selecting Groups: The following four kinds of heuristic information are applicable for calculating priority for a grou p: †¢ Total access time of all data objects; †¢ Average access time of data objects; †¢ Access time of the start data object; †¢ Average access time per byte. 2. Hoarding Techniques Based on Program Trees A hoarding tool based on program execution trees was developed by author running under OS/2 operating system. Their method is based on analyzing program executions to construct a profile for each program depending on the files the program accesses.They proposed a solution to the hoarding problem in case of informed disconnections: the user tells the mobile computer that there is an imminent disconnection to fill the cache intelligently so that the files that will be used in the future are already there in the cache when needed. [pic] Figure 3. Sample program Tree This hoarding mechanism lets the user make the hoarding decision. They present the hoarding options to the user through a graphical user interface and working sets of applications are captured automatic ally. The working sets are detected by logging the user file accesses at the background.During hoarding, this log is analyzed and trees that represent the program executions are constructed. A node denotes a file and a link from a parent to one of its child nodes tells us that either the child is opened by the parent or it is executed by the parent. Roots of the trees are the initial processes. Program trees are constructed for each execution of a program, which captures multiple contexts of executions of the same program. This has the advantage that the whole context is captured from different execution times of the program.Finally, hoarding is performed by taking the union of all the execution trees of a running program. A sample program tree is provided in Figure 3. Due to the storage limitations of mobile computers, the number of trees that can be stored for a program is limited to 15 LRU program trees. Hoarding through program trees can be thought of as a generalization of a pr o-gram execution by looking at the past behaviour. The hoarding mechanism is enhanced by letting the user rule out the data files. Data files are automatically detected using three complementary heuristics: 1.Looking at the filename extensions and observing the filename conventions in OS/2, files can be distinguished as executable, batch files, or data files. 2. Directory inferencing is used as a spatial locality heuristic. The files that differ in the top level directory in their pathnames from the running program are assumed to be data files, but the programs in the same top level directory are assumed to be part of the same program. 3. Modification times of the files are used as the final heuristic to deter-mine the type of a file. Data files are assumed to be modified more recently and frequently than the executables.They devised a parametric model for evaluation, which is based on recency and frequency. 3. Hoarding in a Distributed Environment Another hoarding mechanism, which was presented for specific application in distributed system, assumes a specific architecture, such as infostations where mobile users are connected to the network via wireless local area networks (LANs) that offer a high bandwidth, which is a cheaper option compared to wireless wide area networks (WANs). The hoarding process is handed over to the infostations in that model and it is assumed that what the user wants to access is location-dependent.Hoarding is proposed to fill the gap between the capacity and cost trade-off between wireless WANS and wireless LANs. The infestations do the hoarding and when a request is not found in the infostation, then WAN will be used to get the data item. The hoarding decision is based on the user access patterns coupled with that user’s location information. Items frequently accessed by mobile users are recorded together with spatial information (i. e. , where they were accessed). A region is divided into hoarding areas and each infostation is responsible with one hoarding area. 4. Hoarding content for mobile learningHoarding in the learning context is the process for automatically choosing what part of the overall learning content should be prepared and made available for the next offline period of a learner equipped with a mobile device. We can split the hoarding process into few steps that we will discuss further in more details: 1. Predict the entry point of the current user for his/her next offline learning session. We call it the ‘starting point’. 2. Create a ‘candidate for caching’ set. This set should contain related documents (objects) that the user might access from the starting point we have selected. 3.Prune the set – the objects that probably will not be needed by the user should be excluded from the candidate set, thus making it smaller. This should be done based on user behaviour observations and domain knowledge. 4. Find the priority to all objects still in the hoarding set after pruning. Using all the knowledge available about the user and the current learning domain, every object left in the hoarding set should be assigned a priority value. The priority should mean how important the object is for the next user session and should be higher if we suppose that there is a higher probability that an object will be used sooner. . Sort the objects based on their priority, and produce an ordered list of objects. 6. Cache, starting from the beginning of the list (thus putting in the device cache those objects with higher priority) and continue with the ones with smaller weights until available memory is filled in. 5. Mobile Clients Through Cooperative Hoarding Recent research has shown that mobile users often move in groups. Cooperative hoarding takes advantage of the fact that even when disconnected from the network, clients may still be able to communicate with each other in ad-hoc mode.By performing hoarding cooperatively, clients can share their hoar d content during disconnections to achieve higher data accessibility and reduce the risk of critical cache misses. Two cooperative hoarding schemes, GGH and CAP, have been proposed. GGH improves hoard performance by al-lowing clients to take advantage of what their peers have hoarded when making their own hoarding decisions. On the other hand, CAP selects the best client in the group to Hoard each object to maximise the number of unique objects hoarded and minimise access cost. Simulation results show that compare to existing schemes.Details of GGH and CAP are given in paper. 2. 7 Comparative Discussion previous techniques The hoarding techniques discussed above vary depending on the target system and it is difficult to make an objective comparative evaluation of their effectiveness. We can classify the hoarding techniques as being auto-mated or not. In that respect, being the initial hoarding system, Coda is semiautomated and it needs human intervention for the hoarding decision. T he rest of the hoarding techniques discussed are fully automated; how-ever, user supervision is always desirable to give a final touch to the files to be hoarded.Among the automated hoarding techniques, SEER and program tree-based ones assume a specific operating system and use semantic information about the files, such as the naming conventions, or file reference types and so on to construct the hoard set. However, the ones based on association rule mining and infostation environment do not make any operating system specific assumptions. Therefore, they can be used in generic systems. Coda handles both voluntary and involuntary disconnections well.The infostation-based hoarding approach is also inherently designed for involuntary disconnections, because hoarding is done during the user passing in the range of the infostation area. However, the time of disconnection can be predicted with a certain error bound by considering the direction and the speed of the moving client predicting when the user will go out of range. The program tree-based methods are specifically designed for previously informed disconnections. The scenario assumed in the case of infostations is a distributed wire-less infrastructure, which makes it unique among the hoarding mechanisms.This case is especially important in today’s world where peer-to-peer systems are becoming more and more popular. 3. Problem Definition The New Technique that we have planned to design for hoarding will be used on Mobile Network. Goals that we have set are a. Finding a solution having optimal hit ratio in the hoard at local node. b. Technique should not have greater time complexity because we don’t have much time for performing hoarding operation after the knowledge of disconnection. c. Optimal utilization of hoard memory. d. Support for both intentional and unintentional disconnection. e.Proper handling of conflicts in hoarded objects upon reconnection. However, our priority will be for hit rati o than the other goals that we have set. We will take certain assumptions about for other issues if we find any scope of improvement in hit ratio. 4. New Approach 4. 1 Zipf’s Law It is a mathematical tool to describe the relationship between words in a text and their frequencies. Considering a long text and assigning ranks to all words by the frequencies in this text, the occurrence probability P (i) of the word with rank i satisfies the formula below, which is known as Zipf first law, where C is a constant.P (i) = [pic] †¦. (1) This formula is further extended into a more generalized form, known as Zipf-like law. P (i) = [pic]†¦. (2) Obviously, [pic]†¦. (3) Now According to (2) and (3), we have C[pic] [pic] Our work is to dynamically calculate for different streams and then according to above Formula (2) and (4), the hotspot can be predicted based on the ranking of an object. 4. 2 Object Hotspot Prediction Model 4. 2. 1 Hotspot Classification We classify hotsp ot into two categories: â€Å"permanent hotspot† and â€Å"stage hotspot†. Permanent hotspot is an object which is frequently accessed regularly.Stage hotspot can be further divided into two types: â€Å"cyclical hotspot† and â€Å"sudden hotspot†. Cyclical hotspot is an object which becomes popular periodically. If an object is considered as a focus suddenly, it is a sudden hotspot. 4. 2. 2. Hotspot Identification Hotspots in distributed stream-processing storage systems can be identified via a ranking policy (sorted by access frequencies of objects). In our design, the hotspot objects will be inserted into a hotspot queue. The maximum queue length is determined by the cache size and the average size of hotspot Objects.If an object’s rank is smaller than the maximum hotspot queue length (in this case, the rank is high), it will be considered as â€Å"hotspot† in our system. Otherwise it will be considered as â€Å"non hotspot†. And t he objects in the queue will be handled by hotspot cache strategy. 4. 2. 3 Hotspot Prediction This is our main section of interest, here we will try to determine the prediction model for hoard content with optimal hoard hit ratio. 5. Schedule of Work |Work |Scheduled Period |Remarks | |Studying revious work on Hoarding |July – Aug 2012 |Complete | |Identifying Problem |Sept 2012 |Complete | |Innovating New Approach |Oct 2012 |Ongoing | |Integrating with Mobile Arena as solution to Hoarding |Nov- Dec 2012 |- | |Simulation And Testing |Jan 2013 |- | |Optimization |Feb 2013 |- | |Simulation And Testing |Mar 2013 |- | |Writing Thesis Work / Journal Publication |Apr –May 2013 |- | 6. Conclusion In this literature survey we have discussed previous related work on hoarding. We have also given the requirements for the new technique that is planned to be design.Also we are suggesting a new approach that is coming under the category of Hoarding with Data Mining Techniques. Recen t studies have shown that the use of proposed technique i. e. Zipfs-Like law for caching over the web contents have improved the hit ratio to a greater extent. Here with this work we are expecting improvements in hit ratio of the local hoard. References [1]. James J. Kistler and Mahadev Satyanarayanan. Disconnected Operation in the Coda File System. ACM Transactions on Computer Systems, vol. 10, no. 1, pp. 3–25, 1992. [2]. Mahadev Satyanarayanan. The Evolution of Coda. ACM Transactions on Computer Systems, vol. 20, no. 2, pp. 85–124, 2002 [3]. Geoffrey H. Kuenning and Gerald J. Popek. Automated Hoarding for Mobile Computers.In Proceedings of the 16th ACM Symposium on Operating System Principles (SOSP 1997), October 5–8, St. Malo, France, pp. 264–275, 1997. [4]. Yucel Saygin, Ozgur Ulusoy, and Ahmed K. Elmagarmid. Association Rules for Supporting Hoarding in Mobile Computing Environments. In Proceedings of the 10th IEEE Workshop on Research Issues in Data Engineering (RIDE 2000), February 28–29, San Diego, pp. 71–78, 2000. [5]. Rakesh Agrawal and Ramakrishna Srikant, Fast Algorithms for Mining Association Rules. In Proceedings of the 20th International Conference on Very Large Databases, Chile, 1994. [6]. GUO Peng, Hu Hui, Liu Cheng. The Research of Automatic Data Hoarding Technique Based on Hyper Graph.Information Science and Engineering (ICISE), 1st International Conference, 2009. [7]. Huan Zhou, Yulin Feng, Jing Li. Probability graph based data hoarding for mobile environment. Presented at Information & Software Technology, pp. 35-41, 2003. [8]. Carl Tait, Hui Lei, Swarup Acharya, and Henry Chang. Intelligent File Hoarding for Mobile Computers. In Proceedings of the 1st Annual International Conference on Mobile Computing and Networking (MOBICOM’95), Berkeley, CA, 1995. [9]. Anna Trifonova and Marco Ronchetti. Hoarding content for mobile learning. Journal International Journal of Mobile Communications archive V olume 4 Issue 4, Pages 459-476, 2006. [10]. Kwong Yuen Lai, Zahir Tari, Peter Bertok.Improving Data Accessibility for Mobile Clients through Cooperative Hoarding. Data Engineering, ICDE proceedings 21st international Conference 2005. [11]. G. Zipf, Human Behavior and the Principle of Least Effort. Addison-Wesley, 1949. [12]. Chentao Wu, Xubin He, Shenggang Wan, Qiang Cao and Changsheng Xie. Hotspot Prediction and Cache in Distributed Stream-processing Storage Systems. Performance Computing and Communications Conference (IPCCC) IEEE 28th International, 2009. [13]. Lei Shi, Zhimin Gu, Lin Wei and Yun Shi. An Applicative Study of Zipf’s Law on Web Cache International Journal of Information Technology Vol. 12 No. 4 2006. [14]. Web link: http://en. wikipedia. org/wiki/Zipf%27s_law

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Regional integration for and against articles - Essay Example China is one such country that is doing great job in the context of regional integration. It has acted as a strong initiator of regional integration policies and development. China is struggling hard to establish cooperation within South East Asian countries by promoting their economic interests. Behind the attempts at enhancing economic development in Asian countries underlies a strong goal of a making Asia a peaceful and economically developed continent (Clarke, 2011). There are many benefits of establishing regional integration of China with other South East Asian countries. The most important benefit of regional integration is allowing those countries that have been disadvantaged from economic aspects due to some reasons a chance to make themselves economically sound. As economic regional integration implies removing barriers in trade and other economic aspects to allow free trade among nations, regional integration is a beneficial phase for the countries to become developed econ omically (Nicolas, 2007). In addition to the advantages of regional integration described above, there are other benefits as well. It helps to strengthen the integration of trade within a specific region. Besides, it provides enormous chance for private investors to start a business over there. It also allows the countries involved in regional integration to develop economically stable public sector organizations and institutions. Thus it promotes a peaceful environment within different countries based on mutual trust and cooperation with each other (Storey, 2011). Among the great benefits of regional integration lies economic development of many sectors in those countries that are involved in the process of regional integration. Firstly, it enables the tourism industry of one country to flourish by removing the borders between two countries and encouraging free trade among them. The decrease in cross-trade barrier gives tourists an opportunity to visit other countries without carin g for the hindrances regarding travel. Despite travelling and hospitality benefits, regional integration calls for a significant decrease in inflation rate by making cheaper products. Not only are the products become cheaper, they become diversified as well. It also allows the faster delivery of products and services in the integrated regions (Clarke, 2011). Due to these reasons, China has expanded the trade and economic development between ASEAN countries by making trade agreements between South East Asian countries. It has contributed a lot in making China and the other ASEAN countries to enjoy great benefits of regional integration. It is probably due to this fact that China has become a geographical region promoting diverse talent and skills. Hence, regional integration is the key to economic success of a country (Storey, 2011). China Regional Integration- Disadvantages China is a significant promoter of establishing mutually satisfying agreements of business or economic nature between nations. It has been a region that allows for the integration of political or economic nature between South East Asian regions. Regional integration can be defined as a process where mutual agreements are made to satisfy some great purpose that would be beneficial for the both regions. There are many benefits of regional integration for instance, economic development, integration of various industries and business at international level. In addition to the

Aldemar Hotel and Spa [Operations Management Case Study] Essay

Aldemar Hotel and Spa [Operations Management Case Study] - Essay Example Yield management has become particularly important in the travel and hospitality industry. This is primarily because the resources such as airline tickets and available rooms in a hotel are fixed and cannot be increased or decreased to manage the demand of the consumers at different periods of time (Barnes, 2008). This is also the main reason that yield management is so important for Aldemar. It allows the owner to manage the hotel’s limited resources which includes its rooms in the best possible manner. The managers at Aldemar cannot increase or decrease its room capacity to facilitate the demand of the customers. When there is increased demand of the rooms during holiday season, the management risks losing its important and loyal customers when the rooms are already booked and they cannot overbook due to its long-term impact of the customers’ perception and the hotel’s reputation. Similarly during low demand of the rooms, Aldemar faces issues of decreased reven ues and increased costs as rooms require maintenance and the organization has to pay for its overhead costs that remain more and less constant during all seasons. With the help of yield management, Aldemar can hope to move certain customers during the off-season thus keeping room occupancies more or less constant. What other approaches to capacity management could Aldemar use? There are other different approaches to capacity management that Aldemar can benefit from. One of them includes promotion. Aldemar Hotels can use promotion as a mode of attracting consumers during the off-peak season. They can offer rooms at discounted prices or could introduce new features during the off-peak season. They could use their online website to promote such offers. Another approach to capacity management is product development that falls under the category of demand management. Demand management includes managing price, promotion, reservations, and waiting etc. During the off-season, Aldemar Hotels can offer certain services and products that would attract a high number of customers. Aldemar can for example shift the opening and closing times of their hotels to accommodate their guests. They could allow guests to benefit from tour guides for discounted rates during off-peak season. Aldemar could particularly benefit from using its spa for product development. It could introduce new offers or products for consumers during the off-peak season. The third approach is to adjust the changeable resources in line with the demand of the organization. This is known as chase demand that involves sub-contracting, hiring part time labor, multi skilling and participation of the customers. For example, during peaks seasons, Aldemar can hire extra part-time labor to make up for the increased work load. They could add or share their equipment through partnership agreements. Furthermore, Aldemar can delegate extra work during off-season period such as renovations in the hotel rooms. Critically assess Aldemar’s current yield management practices (e.g. the organizational structures, procedures, performance monitoring). Even though yield management has come forward as one of the best approaches for managing capacity for the hospitality industry, many organizations fail to incorporate this management strategy in the best of manner. In this manner, they lose a

Synthesis Essay Example | Topics and Well Written Essays - 1000 words - 2

Synthesis - Essay Example reporter with the Associated Press, David Crary, brings to focus the conflict of interest that is linked with advertising particularly in relation to healthy living in his article: Group Wants Shrek off Anti-Obesity Campaign. All these articles focus on the different effects of advertising on the population, especially the advertising that does not focus on its effects on the population. The degree of increase in wealth as well as impact on culture that the international companies have attained in the past two decades can be linked to one innocent notion that was established by the management theorists which maintained that for businesses to succeed, they are to create brands but not products (Klein, 1999). Before this time, the main focus of the manufacturers was to produce goods and at one point, it was argued that the reason why the economy of America had not made a recovery from the depression was because the nation no linger knew the importance of making things. This has led to an environment that is full of advertisements which are meant to market all kinds of products by different manufacturers with the aim of increasing their market bases and making as many people as possible know about their existence. Various companies use different forms of advertising including mounting televisions in schools which has been done by Channel one with conditions that all th e teachers should air and the students have to watch the satellite broadcast programs that are aired every day (Baker, 2011). These broadcasts are filled with commercials that have been sanctioned by the schools and the company that is lending the television sets to the schools claims to have an audience that is more than fifty times that of MTV. It rakes in profits from selling two minutes out of every twelve programming minutes to commercials as well as in call contests. Some of these commercials include those that involve Shrek as the spokesman for an anti-obesity campaign. The advertisements that

Kodak and Fujifilm Essay Example for Free

Kodak and Fujifilm Essay Kodak, which was once known as Eastman Kodak Company, was founded by George Eastman in 1888. This invention enabled inventor Thomas Edison to create the first motion picture camera in 1891. Kodak’s photography and imaging was its main big thing and was widely used from photography equipment to film, paper and color chemicals. Kodak set the standards high for quality when making its motion picture films. (Kodak) In the 1980’s, Kodak’s market share reached 90%. In the 1800’s he also invented an emulsion-coating machine which enabled him to mass-produce photographic dry plates, he was one of the first to prove the great convenience of gelatin dry plates over the cumbersome and messy wet plate photography prevalent in his day. Dry plates could be exposed and developed at the photographers convenience; wet plates had to be coated, exposed at once, and developed while still wet. The name Kodak was born and the KODAK camera was placed on the market, with the slogan, You press the button we do the rest. (Kodak) Kodak went on to become one of the biggest expanding the major impact it brought to pictures. It grew into helping the health industry by devising films that detected radiation exposure for developing the atomic bomb. (Kodak) Kodak went on to play significant roles with joint ventures from Nasa, Sun Chemical, and other big ventures. By 1962 the company’s U. S. consolidated sales exceed $1 billion for the first time. Its work force tops 75,000. Today Kodak’s estimated total market capitalization is about $900 million (Forbes) Kodak was a pioneer of photography and imaging and that was its core business. Kodak came before Fujifilm and was able to evolve and adapt quickly to the market changes. In January 2012, Kodak filed for Chapter 11 bankruptcy protection in the United States District Court for the Southern District of New York and in January 2013 it exited bankruptcy. Kodak’s downfall I think was that it was not able to keep up with the technology changes and multiple new waves of how it evolved. Ethics and social responsibility was on its side because of the good it did for the world through the company’s research and the profit margin showed that. Being able to help NASA and hospitals showed there ethical practices. Customers were satisfied and they trusted the brand. Obviously for them to have gone bankrupt means there was a breakdown in financial strategies and decision making. Fujifilm was established in 1934 with the aim of producing photographic films. Over the decades we have diversified into new markets and built a strong presence around the globe. It was founded by (Fujifilm. com) It emerged with its photographic film manufacturing industry and then began operating, producing photographic film, print paper, dry plates, and other photosensitive materials. It went through several name changes starting as Fuji Photo film and ending up as Fujifilm. Fujifilm may have started as a manufacturer of photographic film, but the companys decision to branch into many areas of business including a transition to a digital camera manufacturer in the past several years has been a successful one. (camersabout. com) Fuji has crossed over into hospitals providing x-rays and medical imaging. Fujifilm has offered photographic film, motion picture film, color reversal film slides, microfilm, color negatives, 8mm motion picture film, and videotape. Beyond film, the company also has offered computer storage tape, computer floppy disks, and offset printing plates. Fujifilm made its first digital still camera in 1988, the DS-1P, and it was the worlds first digital camera with removable media. The company also created the first one-time-use recyclable film camera, the Quick Snap, in 1986. (Cameras about. com) Fuji dominated overseas and has embraced change and diversity to become a more effective force for a better future. Fujifilm has continued to maximize other resources effectively to achieve healthy growth.. In 2007, Fujifilm cameras ranked eighth worldwide in number of digital cameras manufactured, with about 8. 3 million units, according to a Techno Systems Research report. Fujifilm cameras, sometimes shortened to Fuji cameras, held a market share of about 6. 3%. (fujifilm. com) they too have been innovators and there management strategies have kept them on top and out of trouble such as bankruptcy. Kodak was not quick as Fuji was to adapt and they adapted quickly to stay well liked in the marketplace. They went from just hot in Japan to being second in the lead below Kodak in film usage, Both companies show what their approach to ethics and social responsibility are by their profits and success. It takes good decision making, quick turn around, and constant change to ensure diversity with any company. Flexibility, the right marketing, and speed are important in decision making. Fuji was smart and aggressive going from overseas to the global market with their low prices that made for a powerful marketing strategy. 1984 Los Angeles Olympics put them on the map when they became the official film of the event. Kodak made bad investments that caused them to eventually go bankrupt. It acquired Sterling drug for 1. 5 billion in January of 1988 and it turned out to be a bad investment and they wind up selling it off. Once it started falling the CEO was not able to revive it. Both companies made photography and imaging as their core business but Fuji even though it started later had the better adaptability. Fuji stayed reinventing itself and evolved with the change to invent better products. Kodak seems to come to a standstill even when the smart phone was introduced. When making decisions to build in flexibility you need to access the option, define the problem, adjust your approach and have innovative thinking. (Houston chronicle, by Amber Keefer, Demand Media) Before proceeding with you of action you have to choose an adequate course of action, and then you define the problem. Gather information, evaluating possible solutions and estimating the outcomes are crucial steps in the decision-making process. The objective is to take a situation from its current circumstances and move it toward a future goal. When making decisions you have to understand what you need to change and come up with ideas on how to improve the situation. After analyzing the problem, the next step is to find a solution before making a decision and implementing changes. Consider the advantages and disadvantages of each of the options available. Think about the value of the actions you can take. After you decide on a solution, you might want to change your approach.. Evaluate new information as it becomes available to you. Flexibility in decision making allows you to learn from your mistakes and then move toward a successful outcome. When you prepare to implement change, it is important to consider your organization’s future needs and objectives. You have to consider various options as solutions to a problem tend to put more thought into making decisions. Critical thinking is important. Flexibility in problem solving is key and involves interpreting information, drawing conclusions and considering the implications. A decision maker must identify weaknesses of the situation and move to remove it from the equation. Then finally as you approach the final decision change often requires adjusting your approach to meet the unexpected. Keeping an open mind is important when considering the overall situation and looking at all facets of the problem. Building flexibility in decision making requires that you be receptive to change. Even the best-laid plans hit unanticipated obstacles. The key is to know when to adjust your approach. Effective decision makers demonstrate the ability to shift priorities as the need arises and show a willingness to achieve objectives by taking advantage of new opportunities. (Houston chronicle, by Amber Keefer, Demand Media) Kodak was first out the door in the business industry but made some financial mistakes that cost them in the end. They were not fast paced like Fuji with keeping up with the industryand keeping their technology current. Fuji looked for newer marketing strategies to please their customers and kept evolving. That would explain their success today. , Fujifilm has transformed itself into a solidly profitable business, with a market capitalization, even after a rough year, of some $12. 6 billion to Kodak’s $220m (petapixel. com) Kodak filed a lawsuit against Fuji claiming they had infringed on Kodak’s digital photography patents.

Visiting Lake Manyara, Tanzania: History and wildlife

Visiting Lake Manyara, Tanzania: History and wildlife Introduction Lake Manyara is a sparkling body of water that glitters in its glory. And indeed, Lake Manyara National Park has often been described as a gem amongst the Tanzania’s northern tourism circuit. The Park forms a vital part of the larger Tarangire – ecosystem and serves as a dry season refuge for migratory animals. The park is safely nestled between the lake on the eastern side and the Gregory Rift Escarpment on the West, offering dramatic scenery that change with the seasons. During the rainy season the lake fills up and the surroundings become lush and green. During the dry season the lake partly dries up leaving a broad rim of bright white salt residue, making equally beautiful scenery. The park includes a unique forest that is fed by underground streams, rivers and springs. The forest is located on the South – Western part of the park in Mbulu plateaus. It is an important evergreen catchment forest, a source of important permanent rivers of which some of them pou r their water in Lake Manyara thus bringing life to the park and the surrounding areas. The Park is home to the rare blue monkey and numerous bird species. It is quite simply, a MUST DO for bird-lovers and keen wildlife photographers. History The name Manyara is derived from the maasai word â€Å"emanyara† referring to the Finger Euphorbia plant (Euphorbia tirucalli) meaning a plant which is a succulent. The park was first declared as a Game Reserve in 1957 mainly to protect its rhino and elephant populations. Sadly, rhino does not exist anymore because of poaching. In 1960 it was officially declared a National Park covering only 100km2. It was later on extended to the southern part towards Magara River. Between 1972 and 1990, two farm units were acquired and added to the park thus bringing its size to 330km2. Currently the park is 648.7km2 in size following the annexation of the Marang’ Forest Reserve in 2009. Dry land is 428 km2 and 220km2 is the lake- the wetland area. At its full size the lake covers about 470km2. Location Lake Manyara National Park lies between 3020’S, 35050’E and 3049’S, 35044’E as well as 3035’S, 35053’E and 3033’S, 35032’E (South) and between E3533 and E3532 (East).Park is located approximately 111.5km (from clock tower to the main gate) south- west of Arusha city. The park has two gates; one is Iyambi in the southern part of the park connecting it with Tarangire, and the other is the main gate which is close to Mto wa Mbu town. Mto wa Mbu is a small densely populated busy town which is multi ethnic with different cultural values of interest for tourists while on their way to Manyara, Ngorongoro and Serengeti. The town is the continuation of the main road to Ngorongoro and the Serengeti. Elevation The altitude varies from 960m above the sea level at the edge of the lake to 1,600m above the sea level along the valley walls of the Gregory Rift. Rainfall Like other areas in Northern Tanzania, annual rainfall pattern consists of short rains between October and December, followed by a dry season in January and thereafter long rains from February to June with the highest rainfall in April. However, Manyara has an erratic and unreliable rainfall patterns, ranging from 250mm to 1600mm per annum. Lake Manyara is highly alkaline and shallow, without any outgoing rivers. Even in rainiest months the depth doesn’t reach more than 1.5m, almost dropping to zero in the dry season. The reason why the ground water forest can survive years of extreme drought is because of springs that emerge at the escarpment base. Temperature Temperature in Lake Manyara is fairly mild, being at its highest from December to February with a mean maximum of 340C. Temperatures are lower from June to July with a minimum of 110C. It can become a bit cold when it rains. Humidity Humidity in lake ranges from 45% to 85% Attractions Attractions of Lake Manyara National Park include a unique ground water forest that is fed by underground streams and the Great Rift Valley Escarpment. The park also lesser and greater pinkish flamingos, hot water springs, wild animals like rare blue monkey, buffalo, wildebeest, zebra, giraffe, elephant, lion, baboon, leopard, antelope, cheetah, dik-dik and many more. The park is endowed with about 400 species of birds and varieties of insects. On inland of the floodplain there is a narrow belt of acacia woodland. The park is favored by the legendary tree-climbing lions and impressively tusked elephants. Pairs of klipspringer are often seen silhouetted on the rocks above a field of searing hot springs that steams and bubbles adjacent to the lakeshore in the far south of the park. Tourism Activities Visitors can engage themselves in the following activities: Day Game Drive Night Game Drive Canoeing when the water level is sufficiently high Wilderness walking safaris Bird watching ( November-June) Bush meal Cultural tour or cultural program at Mto wa Mbu village ( outside the park) Accessibility By air Fly to Lake Manyara Airstrip, which is at the top of the escarpment. Your ground operator will pick you at the airstrip and drive to the park main gate which is about 3km. It is possible to arrange connection flights to the other game parks from there. If your time is limited, this is the ideal option. By road Lake Manyara National Park lies on the main road to and from Ngorongoro. The park may be accessed on way from Arusha, Ngorongoro or Babati. From Arusha, drive West on the main Dodoma road for 84km until you get to Makuyuni village and if you are from Babati drive Makuyuni as well. From here turn right [west] drive on the main road leading to Ngorongoro gate for 26.5km until you get to the town of Mto -wa- mbu. About 1km from the village centre you will see a well marked park entrance gate on your left. The four wheel vehicle is feasible for park game drive. Shopping Mto wa Mbu town is a good place to buy various souvenirs. Also there are various small restaurants which offer typical Tanzanian food and beverages. It is important to fill up your vehicle at one of the filling stations at Mto wa Mbu as there are no fuel stations in the park. Accommodation-Inside the park The park has facilities for accommodation which include public tourist houses (bandas), and campsites ideal for budget visitors (prior booking is required). However there is one luxury tree lodge and one tented camp which are privately owned. Accommodation-Outside the park Luxury tented camps and lodges are available on the rift wall overlooking the Lake. In addition, guest houses and campsites are available in the nearby Mto wa Mbu town. Best time The park can be visited all-year round, however the dry season (July- October) is good for watching large mammals. On the other hand, the wet season (November-June) is good for bird watching and canoeing. Bird life is outstanding all year round; however it is probably better from September to April when migratory birds arrive. Park rules and regulations Game drive is allowed between 0600h and 1800h. Conservation fee to be paid at the entrance gates. Fees are for 24hrs single entry. Foreign visitors pay in foreign currency (USD) Payment is made through credit or debit cards( Visa card, Master card TANAPA cards-Exim CRDB banks) Camping is only allowed at authorized sites Speed Limit is 50kph (30mph) on all roads Off road driving is strictly prohibited Harassment of animals is strictly prohibited Loud music and noise are not permitted Littering is strictly prohibited. Getting out of your vehicle is not allowed except at designated picnic sites, view points and campsites It is strictly prohibited to introduce or remove any natural objects, plants or archeological artifacts. Domestic pets are strictly not allowed. Fires are only allowed at designated camping sites â€Å"Put fire out after use†. You enter the park at your own risk. Park management will not be held responsible for loss of property, life or damage of the same under any circumstances. Weapons, traps, poison and items of similar nature are strictly not allowed into the park. All accidents must be reported immediately to park officials. Adhere to instructions from park officials. Park contacts: Email address- [emailprotected] Hotlines. +255 689062294, +255 767536137

Gherkin and Pomegranate Cultivation

Gherkin and Pomegranate Cultivation Abstract Horticulture is an important component of agriculture accounting for a very significant share in the Indian economy. Rising consumer income and changing lifestyles are creating bigger markets for high-value horticultural products in India as well as throughout the world. Among these, the most important high-value export products are fruits and vegetables. This study was conducted to analyze the comparative advantage and competitiveness of pomegranate and gherkin which are the important foreign exchange earner among fruit and vegetable crops exported from India. The primary data was collected from Tumkur and Bijapur district of Karnataka, India and secondary data was collected from concerned government institutions, APEDA and also from exporters of fruits and vegetables. The Policy Analysis Matrix (PAM) was selected as the analytical tool to analyse the export competitiveness, comparative advantage, and the degree of government interventions in the production and export of gherkin and pomegranate. The policy distortions were measured through indicators of PAM. Garret ranking technique was used to analyse the constraints in the production and export of the selected crops. EPC of Gherkin (0.5) and pomegranate (0.45) values which found to be less than one indicates that producers are not protected through policy interventions. Whereas DRC (0.27 0.28) and PCR (0.43 0.59) values of Gherkin and Pomegranate respectively shows positive, social as well as private profit which indicates that, India has a competitive and comparative advantage in their production. The result for Garret ranking in case of gherkin shows that skilled labour and lack of superior quality are the major constraints in production and export of gherkin respectively. In case of pomegranate non availability of skilled labour, high incidence of pest and diseases, lack of transportation facilities, high residual effect of pesticide are the major constrain in production and export. The overall result shows that the cultivation as well as export of gherkin and pomegranate is economically profitable and efficient. Key Words: Gherkin, Pomegranate, PAM, EPC and DRC List of Acronyms Variable Definition APEDA Agricultural and Processed Food Products Export Development Authority CIF Cost Insurance and Freight Crores 10 million DRC Domestic Resource Cost EPC Effective Protection Coefficient EU European Union FAOSTAT Food and Agriculture Organization Statistics FOB Free On Border FYM Farm Yard Manure ha Hectares HEIA Horticulture Export Improvement Association kg Kilogram MHA Million Hectare MT Million Tons NHB National Horticulture Board NPCI Nominal Protection Coefficient on Inputs NPCO Nominal Protection Coefficient on Outputs NPV Net Present Value PAM Policy Analysis Matrix PCR Private Cost Ratio INR Indian Rupees UAE United Arab Emirates UK United Kingdom UNCOMTRADE United Nations Commodity Trade Statistics UNFAO United Nations Food and Agriculture Organization USA United States of America 1. Introduction 1.1 Background Indian agriculture is vested with the herculean responsibility of feeding over more than one billion people. Out of total, 72% of Indias population live in rural areas, further three-fourth of the rural populations depend on agriculture and allied activities for their livelihoods. The present growth in agriculture in India is hassle with problems most importantly, agricultural growth slowed down to 2.1% between 1998-99 and 2004-05. It is largely due to a decline in the food grain sector that grew at merely 0.6%. Given the high dependence of the poor on agriculture, the stagnation in this sector is currently threatening to stall poverty reduction in India (Reddy, 2007). Given the present scenario, the immediate question to be addressed is how agricultural growth can be accelerated. The question can be answered through by diversifying the consumption pattern towards high value agricultural commodities in general and high value horticultural products in particular such as fruits and vegetables. In recent years there has been a great deal of interest among policymakers and trade analysts in the role of horticultural products as a principle means of agricultural diversification and foreign exchange earnings in developing countries. Horticultural products have high income elasticity of demand as income goes up the demand raises rapidly. It grows especially in middle and high income developing countries. As people are more cautious on health and nutrition, there is a paradigm shift from high fat, high cholesterol foods such as meat and live stock products to low fat and low cholesterol foods such as fruits and vegetables. As a result, the world has change d its attention towards high value agricultural products. Hence, it is crucial to be competitive in the world market to reap the potential gains of increased and growing world demand for horticultural products such as fruits and vegetables. Thus, the purpose of the present study attempts to evaluate the consequences of international trade and competitiveness of Indian horticulture with special reference to pomegranate and gherkin crops. In the recent past, these two crops got high export potential and earned good foreign exchange. 1.2 Studies on export of fruits and vegetables There are many studies related to export of horticultural crops especially fruits and vegetables from India. Chiniwar (2009) explained the numerous opportunities and challenges of the horticulture sector and observed that there is a tremendous potential for Indian pomegranates in the global market. He examined the growth of pomegranate exports from India. The study revealed that the growth of pomegranate exports from India is moderate in comparision to the potential for its exports. Tamanna et al. (1999) examined the export potential of selected fruits from India by using Nominal Protection Coefficient (NPC). The results indicate that the exports of Indian fruits are highly competitive in the world market. Nalini et al. (2008) observed that India has made tremendous progress in the export of cucumber and gherkin products during the past 15 years (1990-2005). The export has increased by about 129 times with an impressive annual compound growth rate of 37.46 percent, as against only 4. 38 percent in the world market. An increasing and high value of Revealed Comparative Advantage (RCA) and a positive and increasing value for Revealed Symmetric Comparative Advantage (RSCA) have indicated high potential for their export. One percent increase in volume of international trade in cucumber and gherkin may increase the demand from India by 5.96 percent. This indicates that India is highly competitive in the export of cucumber and gherkin. It has ample scope to further increase its export. Gulati et al. (1994) analyzed the export competitiveness of selected agricultural commodities and identified the constraints in the export of fresh fruits, vegetables, processed fruits and vegetables. The above studies are related to export performance, growth, and constraints of fruits and vegetables. Most of these studies focused on aspects pertaining to export of fruits and vegetables. There are no studies on export policy especially related to efficiency and comparative advantage in world market. Therefore, the aim of the present study is to analyze the export competitiveness of pomegranate and gherkin by using Policy Analysis Matrix (PAM). The study has a high scope because competitiveness has become a key issue in the international market for export development of fruits and vegetables. 1.3 Research objectives In the present study, the export competitiveness of high value horticultural crops of India is analyzed. To be very precise, the study analyzes the competitiveness of gherkin and pomegranate in the world market. It also compares the advantages and constraints in the export of these crops with the following objectives and proposed hypothesis, which will be tested based on the results and conclusion. Specific objectives To assess the export competitiveness of Gherkin and Pomegranate To examine the production and export constraints of Gherkin and Pomegranate Hypothesis Export of gherkin and pomegranate are competitive in international markets 1.4 Structure of the thesis The study contains the results of the analysis of export competitiveness of horticultural crops in India. In the present study, opportunities are analyzed, constraints in production and export of gherkins and pomegranates from India. We further analyze the competitiveness and comparative advantage of these two crops in international market. The detailed information of this analysis is discussed in the following sections of the study. The first section of the thesis gives us an introduction and background on the nature of the problem, facts on the dynamics and underlying causes diversifying the consumption pattern of high value horticultural commodities. Further, a brief overview of existing studies on Indian agricultural and horticultural growth, export performance, and constraints will be discussed. The research question is broken down into specific objectives and a possible hypothesis has been put forth. The second section of the thesis will give a general overview of fruit and vegetable scenario in the world as well as in India. The section also explains the importance of selected fruit and vegetable by considering production, export and foreign exchange earnings which will help us to understand the export competitiveness of these crops from India. The third section deals with methodological framework which deals with the concepts and competitiveness of high value horticultural crops from India focusing on the application of PAM model for the study. In the same chapter, the current literature and outline of the major definitions for competitiveness and comparative advantage are studied. The above proposed model will be used as a tool to address the research objectives followed by data description. Fourth section highlights the findings of the research from the proposed model using collected information on pomegranate and gherkin cultivation, and their export. Finally, the proposed hypothesis is tested and the results inferred. The final section summarizes the whole research findings and provides meaningful policy implications. 2. Scenario of fruits and vegetables in India and the world 2.1 World scenario of fruits and vegetables 2.1.1 High value agricultural production Rising consumer income and changing lifestyles are creating bigger markets for high value agricultural products throughout the world. Among these, the most important high value export sector is horticulture, especially fruits and vegetables. The growing markets for these products present an opportunity for the farmers of developing countries to diversify their production out of staple grains and raise their income. Annual growth rates on the order of 8 to 10 percent in high value agricultural products is promising development (Fig.1), as the production, processing and marketing of these products create a lot of needed employment in rural areas. The rapid growth in high value exports has been part of fundamental and broad reaching trend towards globalization of the agro food system. Dietary changes, trade reform and technical changes in the food industry have contributed to the growth of high value agriculture and trade (World Bank, 2008). 2.1.2 World production of fruit and vegetables The production of fruit and vegetables all over the world grew by 30 percent between 1980 to 1990 and by 56 percent between 1990 to 2003. Much of this growth occurred in China where production grew up by 134 percent in 1980 and climbed to 200 percent by 1990 (UNFAO 2003). At present the world production of fruits and vegetables reached to 512 MT and 946.7MT respectively (Table 1 5). Vegetables: China is currently the worlds largest producer of vegetables, with the production 448.9 MT with an area of 23.9 MHA (47%) (Table 1), whereas India is in the 2nd position with the production of 125.8 MT with an area of 7.8 MHA (13%) followed by USA (4%), Turkey (3%) etc (Indian Horticulture Database, 2008) (Fig.2). Among the vegetable crops gherkin is considered for the study as it is one of the most important vegetable all over the world. Table 2 shows the international production of cucumber and gherkin from different parts of the world during 2007-08. China, Turkey, Iran, Russia and USA are the world largest producers of cucumber and gherkin (Table 3), whereas India position in the production is 34th but it reached 1st (Table 3) and 55th (Table 4) position in export of provisionally preserved and fresh cucumber gherkin respectively. Table 1 Major vegetables producing countries in the world (2007-08) Country Area(000 ha) Production(000 MT) Productivity(MT/ha) China 23936 448983 19 India 7803 125887 16 USA 1333 38075 29 Turkey 996 24454 25 Russia 970 16516 17 Egypt 598 16041 27 Iran 641 15993 25 Italy 528 13587 26 Spain 379 12676 33 Japan 433 11938 28 Others 16957 222625 13 Total 54573 946774 Source: Indian Horticulture Database (2008) Table 2 International production of cucumber and gherkin (2007-08) Country Production (MT) Share (%) China 28062000 62.9 Turkey 1875919 4.21 Iran, Islamic republic 1720000 3.86 Russian federation 1410000 3.16 USA 920000 2.06 Ukraine 775000 1.74 Japan 634000 1.42 Egypt 615000 1.38 Indonesia 600000 1.34 Spain 510000 1.14 Mexico 500000 1.12 Poland 492000 1.10 Iraq 480000 1.08 Netherland 445000 1.00 India 120000 0.27 Others 5452024 12.22 World 44610943 100 Source: Author, FAO (2008) Table 3 Major exporting countries of fresh cucumber and gherkin (2007) Country Value (USD) Share (%) Spain 557088 30.13 Mexico 437369 23.65 Netherland 419824 22.70 Canada 81707 4.42 Germany 44437 2.40 Turkey 40300 2.18 Greece 38920 2.10 Iran 27768 1.50 Belgium 25361 1.37 USA 16313 0.88 India 235 0.01 Others 159815 8.64 World 1849137 Source: Data from Agricultural and Processed food products Export development Authority (APEDA), India. Table 4 Major exporting countries of preserved cucumber and gherkin Country Value (USD) Share (%) India 33476 49.39 China 16754 24.72 Turkey 4193 6.19 Netherlands 3397 5.01 Belgium 2670 3.94 Vietnam 40300 2.11 Sri Lanka 1003 1.48 Germany 925 1.37 Spain 596 0.88 USA 992 0.87 World 65040 Source: U.N COMTRADE (2007) Fruits: World fruit production has steadily risen for the past four years (see Appendix 3 ). Table 5 shows the largest fresh fruit producers from different countries during 2007-08. China is the worlds largest fruit producer, producing 19 percent of the world fruits. India ranks second in the list of world producer accounting 12 percent of the worlds production followed by Brazil, where 7 percent of the worlds fruit was grown. (Figure 3) As production is increasing in China at alarming rate compare to other top producing countries. Production growth almost averaged 6 percent per year in China, while production growth in India averaged 2.73 percent per year. The EU experienced the lower annual growth rate of 0.89 percent. Whereas, the production in USA and Brazil has been relatively constant over the period, with average annual growth rates of 0.61 percent for the former and 0.34 percent for the later. Other countries Mexico, South Africa and Chile have experienced slightly higher av erage annual production growth rates of 2.12, 2.56 and 1.3 percent respectively over the same period (FAOSTAT 2008). Among all fruits pomegranate is considered for the present study. Figure 4 shows India is the world largest producer of pomegranate with 900 MT (36%) followed by Iran (31%), Iraq (3%), USA (4%) etc. Over the years Indias export rate for pomegranate has grown steadily to worth of INR0.61 million (US$13741) in 2007-08 with the share of 1.2 percent (Table 6). Table 5 Major fruit producing countries in the world (2007-08) Country Area(000 ha) Production(000 MT) Productivity(MT/ha) China 9587 94418 10 India 5775 63503 11 Brazil 1777 36818 21 USA 1168 24962 21 Italy 1246 17891 14 Spain 1835 15293 8 Mexico 1100 15041 14 Turkey 1049 12390 12 Iran 1256 12102 10 Indonesia 846 11615 14 Others 22841 208036 9 Total 48481 512070 Source: FAO Indian Horticulture Database (2008) Table 6 Pomegranate export from different parts of the world (2007) Country Value (USD) Share (%) Thailand 172781 15.06 Spain 138911 12.11 Vietnam 84532 7.37 Mexico 67739 5.91 Netherlands 63858 5.57 Madagascar 53822 4.69 Israel 45219 3.94 Uzbekistan 44128 3.85 Colombia 40459 3.53 Azerbaijan 37977 3.31 France 36975 3.22 Germany 17750 1.55 India 13741 1.20 Others 309565 27.45 World 1127457 100 Source: Agricultural and Processed Food Products Export Development Authority (APEDA), India 2.2 Scenario of fruits and vegetables in India. Horticulture is an important component of agriculture accounting for a very significant share in the Indian economy. It is identified as one of the potential sector for harnessing Indias competitive advantage in international trade. Further it prepares India to achieve an overall trade target of 1% or more in the share of world trade. Meanwhile, making the country self-sufficient in the last few decades, horticulture has played a very significant role in earning foreign exchange through export. Horticultural crops cover approximately 8.5 percent of total cropped area (20 MHA) (Table 7) with annual production of 207 MT, and productivity of 10.3 MT per hectare during the year 2007-08 (FAO Indian Horticulture Database 2008). Among the horticultural crops fruits and vegetables play an important role, whereas exports of fruits and vegetables have increased over the years (Table 8). During 2004-05 export of fruits and vegetables was INR 13637.13 million as against INR 24116.57 million during 2006-07 (APEDA, 2008) Table 7 Area, production and productivity of horticultural crops in India Year Area (MHA) Production (MT) Productivity (MT/ha) ) 2001-02 16.6 145.8 8.8 2002-03 16.3 144.4 8.9 2003-04 19.2 153.3 21 2004-05 21.1 170.8 8.1 2005-06 18.7 182.8 9.8 2006-07 19.4 191.8 9.9 2007-08 20.1 207.0 10.3 Source: FAO Indian Horticulture Database (2008) Table 8 Export of horticultural produce in India Products 2004-05 2005-06 2006-07 Quantity Value Quantity Value Quantity Value Floriculture seeds 34496 2871 42659 3922 50048 7713 Fresh Fruits vegetables 1296530 13637 1465040 16587 1983873 24117 Processed fruits vegetables 325293 9614 501826 13595 549949 17316 Total 1656319 261227 2009525 341051 258387 491459 Source: APEDA, India Note: Qty: MT, value : Million INR Vegetables: In vegetable production, India is next to China with a production of 125.8 million tonnes from 7.8 million hectares with a share of 13 percent in relation to world production (Table 9). The per capital consumption of vegetables is 120 grams per day (APEDA 2009). In case of Fresh vegetable Indias export has been increased from INR 433.14 Crore in 2006-07 to Rs 489.49 Crore in 2007-08. Major Export Destinations of these vegetables are UAE, UK, Nepal, and Saudi Arabia. (APEDA, 2009) Table 9 Area, production and productivity of vegetable crops in India Year Area (MHA) Production (MT) Productivity (MT/ha) ) 2001-02 6156 88622 14.4 2002-03 6092 84815 13.9 2003-04 6082 88334 14.5 2004-05 6744 101246 15.0 2005-06 7213 111399 15.4 2006-07 7584 115011 15.2 2007-08 7803 125887 16.1 Source: FAO Indian Horticulture Database (2008) Among all vegetables gherkin is considered for the present study due to following reasons. Indias export of gherkin has been steadily increased since 1997-98. It accounts for 24,490 tonnes of gherkins having an export potential of INR 50.27 crore as against 35,242 tonnes worth of INR 69.86 crore in 1999-2000 (Venkatesh, 2003). In recent year gherkin export has been increased to 61.5 million tonnes with a trade value of INR1465.5 million during 2007-08 (UNFAO Export Data, 2009). 2.2.1 Production and export importance of gherkin in India Gherkin crop is being selected for the present study. It is regarded as HEIA crop especially a hybrid crop. Gherkin cultivation and processing started in India in the early 90s and presently cultivated over 19,500 acres in the three southern states of Karnataka, Tamil Nadu and Andhra Pradesh. Although gherkin can grow virtually in any part of the country, the ideal conditions required for growth prevail in these three states where the growing season extends throughout the year. It requires adequate water and temperature between 15-36 degree centigrade and the right type of soil. The crop takes 85 days to reach the required maturity level. Productivity is approximately four to five tonnes per acre and the best months are from February to March followed by June to August. India is a major exporter of provisionally preserved gherkin. Table 10 11 shows the cucumber and gherkin export from India. In India, Karnataka stands first in export, where cultivation is steadily growing since 2001 -02 accounting for a worth of INR 1200 million. During 2006-07 gherkins accounts to INR 3133 million which has been exported (Table 12). Table 10 Cucumber and gherkin exports from India (2007-08) Country Value( Million INR) Quantity (Tonnes) Share (%) ) UAE 1.96 142.75 17.55 Bangladesh 1.92 290.00 17.17 Netherland 1.78 93.10 15.92 Russia 1.66 83.50 14.91 Estonia 0.80 43.94 7.17 Nepal 0.75 74.42 6.75 Oman 0.75 70.00 6.74 Spain 0.55 31.82 4.95 France 0.47 20.21 4.27 Others 0.51 26.42 4.56 Total 11.20 876.18 100 Source: Gherkin and Pomegranate Cultivation Gherkin and Pomegranate Cultivation Abstract Horticulture is an important component of agriculture accounting for a very significant share in the Indian economy. Rising consumer income and changing lifestyles are creating bigger markets for high-value horticultural products in India as well as throughout the world. Among these, the most important high-value export products are fruits and vegetables. This study was conducted to analyze the comparative advantage and competitiveness of pomegranate and gherkin which are the important foreign exchange earner among fruit and vegetable crops exported from India. The primary data was collected from Tumkur and Bijapur district of Karnataka, India and secondary data was collected from concerned government institutions, APEDA and also from exporters of fruits and vegetables. The Policy Analysis Matrix (PAM) was selected as the analytical tool to analyse the export competitiveness, comparative advantage, and the degree of government interventions in the production and export of gherkin and pomegranate. The policy distortions were measured through indicators of PAM. Garret ranking technique was used to analyse the constraints in the production and export of the selected crops. EPC of Gherkin (0.5) and pomegranate (0.45) values which found to be less than one indicates that producers are not protected through policy interventions. Whereas DRC (0.27 0.28) and PCR (0.43 0.59) values of Gherkin and Pomegranate respectively shows positive, social as well as private profit which indicates that, India has a competitive and comparative advantage in their production. The result for Garret ranking in case of gherkin shows that skilled labour and lack of superior quality are the major constraints in production and export of gherkin respectively. In case of pomegranate non availability of skilled labour, high incidence of pest and diseases, lack of transportation facilities, high residual effect of pesticide are the major constrain in production and export. The overall result shows that the cultivation as well as export of gherkin and pomegranate is economically profitable and efficient. Key Words: Gherkin, Pomegranate, PAM, EPC and DRC List of Acronyms Variable Definition APEDA Agricultural and Processed Food Products Export Development Authority CIF Cost Insurance and Freight Crores 10 million DRC Domestic Resource Cost EPC Effective Protection Coefficient EU European Union FAOSTAT Food and Agriculture Organization Statistics FOB Free On Border FYM Farm Yard Manure ha Hectares HEIA Horticulture Export Improvement Association kg Kilogram MHA Million Hectare MT Million Tons NHB National Horticulture Board NPCI Nominal Protection Coefficient on Inputs NPCO Nominal Protection Coefficient on Outputs NPV Net Present Value PAM Policy Analysis Matrix PCR Private Cost Ratio INR Indian Rupees UAE United Arab Emirates UK United Kingdom UNCOMTRADE United Nations Commodity Trade Statistics UNFAO United Nations Food and Agriculture Organization USA United States of America 1. Introduction 1.1 Background Indian agriculture is vested with the herculean responsibility of feeding over more than one billion people. Out of total, 72% of Indias population live in rural areas, further three-fourth of the rural populations depend on agriculture and allied activities for their livelihoods. The present growth in agriculture in India is hassle with problems most importantly, agricultural growth slowed down to 2.1% between 1998-99 and 2004-05. It is largely due to a decline in the food grain sector that grew at merely 0.6%. Given the high dependence of the poor on agriculture, the stagnation in this sector is currently threatening to stall poverty reduction in India (Reddy, 2007). Given the present scenario, the immediate question to be addressed is how agricultural growth can be accelerated. The question can be answered through by diversifying the consumption pattern towards high value agricultural commodities in general and high value horticultural products in particular such as fruits and vegetables. In recent years there has been a great deal of interest among policymakers and trade analysts in the role of horticultural products as a principle means of agricultural diversification and foreign exchange earnings in developing countries. Horticultural products have high income elasticity of demand as income goes up the demand raises rapidly. It grows especially in middle and high income developing countries. As people are more cautious on health and nutrition, there is a paradigm shift from high fat, high cholesterol foods such as meat and live stock products to low fat and low cholesterol foods such as fruits and vegetables. As a result, the world has change d its attention towards high value agricultural products. Hence, it is crucial to be competitive in the world market to reap the potential gains of increased and growing world demand for horticultural products such as fruits and vegetables. Thus, the purpose of the present study attempts to evaluate the consequences of international trade and competitiveness of Indian horticulture with special reference to pomegranate and gherkin crops. In the recent past, these two crops got high export potential and earned good foreign exchange. 1.2 Studies on export of fruits and vegetables There are many studies related to export of horticultural crops especially fruits and vegetables from India. Chiniwar (2009) explained the numerous opportunities and challenges of the horticulture sector and observed that there is a tremendous potential for Indian pomegranates in the global market. He examined the growth of pomegranate exports from India. The study revealed that the growth of pomegranate exports from India is moderate in comparision to the potential for its exports. Tamanna et al. (1999) examined the export potential of selected fruits from India by using Nominal Protection Coefficient (NPC). The results indicate that the exports of Indian fruits are highly competitive in the world market. Nalini et al. (2008) observed that India has made tremendous progress in the export of cucumber and gherkin products during the past 15 years (1990-2005). The export has increased by about 129 times with an impressive annual compound growth rate of 37.46 percent, as against only 4. 38 percent in the world market. An increasing and high value of Revealed Comparative Advantage (RCA) and a positive and increasing value for Revealed Symmetric Comparative Advantage (RSCA) have indicated high potential for their export. One percent increase in volume of international trade in cucumber and gherkin may increase the demand from India by 5.96 percent. This indicates that India is highly competitive in the export of cucumber and gherkin. It has ample scope to further increase its export. Gulati et al. (1994) analyzed the export competitiveness of selected agricultural commodities and identified the constraints in the export of fresh fruits, vegetables, processed fruits and vegetables. The above studies are related to export performance, growth, and constraints of fruits and vegetables. Most of these studies focused on aspects pertaining to export of fruits and vegetables. There are no studies on export policy especially related to efficiency and comparative advantage in world market. Therefore, the aim of the present study is to analyze the export competitiveness of pomegranate and gherkin by using Policy Analysis Matrix (PAM). The study has a high scope because competitiveness has become a key issue in the international market for export development of fruits and vegetables. 1.3 Research objectives In the present study, the export competitiveness of high value horticultural crops of India is analyzed. To be very precise, the study analyzes the competitiveness of gherkin and pomegranate in the world market. It also compares the advantages and constraints in the export of these crops with the following objectives and proposed hypothesis, which will be tested based on the results and conclusion. Specific objectives To assess the export competitiveness of Gherkin and Pomegranate To examine the production and export constraints of Gherkin and Pomegranate Hypothesis Export of gherkin and pomegranate are competitive in international markets 1.4 Structure of the thesis The study contains the results of the analysis of export competitiveness of horticultural crops in India. In the present study, opportunities are analyzed, constraints in production and export of gherkins and pomegranates from India. We further analyze the competitiveness and comparative advantage of these two crops in international market. The detailed information of this analysis is discussed in the following sections of the study. The first section of the thesis gives us an introduction and background on the nature of the problem, facts on the dynamics and underlying causes diversifying the consumption pattern of high value horticultural commodities. Further, a brief overview of existing studies on Indian agricultural and horticultural growth, export performance, and constraints will be discussed. The research question is broken down into specific objectives and a possible hypothesis has been put forth. The second section of the thesis will give a general overview of fruit and vegetable scenario in the world as well as in India. The section also explains the importance of selected fruit and vegetable by considering production, export and foreign exchange earnings which will help us to understand the export competitiveness of these crops from India. The third section deals with methodological framework which deals with the concepts and competitiveness of high value horticultural crops from India focusing on the application of PAM model for the study. In the same chapter, the current literature and outline of the major definitions for competitiveness and comparative advantage are studied. The above proposed model will be used as a tool to address the research objectives followed by data description. Fourth section highlights the findings of the research from the proposed model using collected information on pomegranate and gherkin cultivation, and their export. Finally, the proposed hypothesis is tested and the results inferred. The final section summarizes the whole research findings and provides meaningful policy implications. 2. Scenario of fruits and vegetables in India and the world 2.1 World scenario of fruits and vegetables 2.1.1 High value agricultural production Rising consumer income and changing lifestyles are creating bigger markets for high value agricultural products throughout the world. Among these, the most important high value export sector is horticulture, especially fruits and vegetables. The growing markets for these products present an opportunity for the farmers of developing countries to diversify their production out of staple grains and raise their income. Annual growth rates on the order of 8 to 10 percent in high value agricultural products is promising development (Fig.1), as the production, processing and marketing of these products create a lot of needed employment in rural areas. The rapid growth in high value exports has been part of fundamental and broad reaching trend towards globalization of the agro food system. Dietary changes, trade reform and technical changes in the food industry have contributed to the growth of high value agriculture and trade (World Bank, 2008). 2.1.2 World production of fruit and vegetables The production of fruit and vegetables all over the world grew by 30 percent between 1980 to 1990 and by 56 percent between 1990 to 2003. Much of this growth occurred in China where production grew up by 134 percent in 1980 and climbed to 200 percent by 1990 (UNFAO 2003). At present the world production of fruits and vegetables reached to 512 MT and 946.7MT respectively (Table 1 5). Vegetables: China is currently the worlds largest producer of vegetables, with the production 448.9 MT with an area of 23.9 MHA (47%) (Table 1), whereas India is in the 2nd position with the production of 125.8 MT with an area of 7.8 MHA (13%) followed by USA (4%), Turkey (3%) etc (Indian Horticulture Database, 2008) (Fig.2). Among the vegetable crops gherkin is considered for the study as it is one of the most important vegetable all over the world. Table 2 shows the international production of cucumber and gherkin from different parts of the world during 2007-08. China, Turkey, Iran, Russia and USA are the world largest producers of cucumber and gherkin (Table 3), whereas India position in the production is 34th but it reached 1st (Table 3) and 55th (Table 4) position in export of provisionally preserved and fresh cucumber gherkin respectively. Table 1 Major vegetables producing countries in the world (2007-08) Country Area(000 ha) Production(000 MT) Productivity(MT/ha) China 23936 448983 19 India 7803 125887 16 USA 1333 38075 29 Turkey 996 24454 25 Russia 970 16516 17 Egypt 598 16041 27 Iran 641 15993 25 Italy 528 13587 26 Spain 379 12676 33 Japan 433 11938 28 Others 16957 222625 13 Total 54573 946774 Source: Indian Horticulture Database (2008) Table 2 International production of cucumber and gherkin (2007-08) Country Production (MT) Share (%) China 28062000 62.9 Turkey 1875919 4.21 Iran, Islamic republic 1720000 3.86 Russian federation 1410000 3.16 USA 920000 2.06 Ukraine 775000 1.74 Japan 634000 1.42 Egypt 615000 1.38 Indonesia 600000 1.34 Spain 510000 1.14 Mexico 500000 1.12 Poland 492000 1.10 Iraq 480000 1.08 Netherland 445000 1.00 India 120000 0.27 Others 5452024 12.22 World 44610943 100 Source: Author, FAO (2008) Table 3 Major exporting countries of fresh cucumber and gherkin (2007) Country Value (USD) Share (%) Spain 557088 30.13 Mexico 437369 23.65 Netherland 419824 22.70 Canada 81707 4.42 Germany 44437 2.40 Turkey 40300 2.18 Greece 38920 2.10 Iran 27768 1.50 Belgium 25361 1.37 USA 16313 0.88 India 235 0.01 Others 159815 8.64 World 1849137 Source: Data from Agricultural and Processed food products Export development Authority (APEDA), India. Table 4 Major exporting countries of preserved cucumber and gherkin Country Value (USD) Share (%) India 33476 49.39 China 16754 24.72 Turkey 4193 6.19 Netherlands 3397 5.01 Belgium 2670 3.94 Vietnam 40300 2.11 Sri Lanka 1003 1.48 Germany 925 1.37 Spain 596 0.88 USA 992 0.87 World 65040 Source: U.N COMTRADE (2007) Fruits: World fruit production has steadily risen for the past four years (see Appendix 3 ). Table 5 shows the largest fresh fruit producers from different countries during 2007-08. China is the worlds largest fruit producer, producing 19 percent of the world fruits. India ranks second in the list of world producer accounting 12 percent of the worlds production followed by Brazil, where 7 percent of the worlds fruit was grown. (Figure 3) As production is increasing in China at alarming rate compare to other top producing countries. Production growth almost averaged 6 percent per year in China, while production growth in India averaged 2.73 percent per year. The EU experienced the lower annual growth rate of 0.89 percent. Whereas, the production in USA and Brazil has been relatively constant over the period, with average annual growth rates of 0.61 percent for the former and 0.34 percent for the later. Other countries Mexico, South Africa and Chile have experienced slightly higher av erage annual production growth rates of 2.12, 2.56 and 1.3 percent respectively over the same period (FAOSTAT 2008). Among all fruits pomegranate is considered for the present study. Figure 4 shows India is the world largest producer of pomegranate with 900 MT (36%) followed by Iran (31%), Iraq (3%), USA (4%) etc. Over the years Indias export rate for pomegranate has grown steadily to worth of INR0.61 million (US$13741) in 2007-08 with the share of 1.2 percent (Table 6). Table 5 Major fruit producing countries in the world (2007-08) Country Area(000 ha) Production(000 MT) Productivity(MT/ha) China 9587 94418 10 India 5775 63503 11 Brazil 1777 36818 21 USA 1168 24962 21 Italy 1246 17891 14 Spain 1835 15293 8 Mexico 1100 15041 14 Turkey 1049 12390 12 Iran 1256 12102 10 Indonesia 846 11615 14 Others 22841 208036 9 Total 48481 512070 Source: FAO Indian Horticulture Database (2008) Table 6 Pomegranate export from different parts of the world (2007) Country Value (USD) Share (%) Thailand 172781 15.06 Spain 138911 12.11 Vietnam 84532 7.37 Mexico 67739 5.91 Netherlands 63858 5.57 Madagascar 53822 4.69 Israel 45219 3.94 Uzbekistan 44128 3.85 Colombia 40459 3.53 Azerbaijan 37977 3.31 France 36975 3.22 Germany 17750 1.55 India 13741 1.20 Others 309565 27.45 World 1127457 100 Source: Agricultural and Processed Food Products Export Development Authority (APEDA), India 2.2 Scenario of fruits and vegetables in India. Horticulture is an important component of agriculture accounting for a very significant share in the Indian economy. It is identified as one of the potential sector for harnessing Indias competitive advantage in international trade. Further it prepares India to achieve an overall trade target of 1% or more in the share of world trade. Meanwhile, making the country self-sufficient in the last few decades, horticulture has played a very significant role in earning foreign exchange through export. Horticultural crops cover approximately 8.5 percent of total cropped area (20 MHA) (Table 7) with annual production of 207 MT, and productivity of 10.3 MT per hectare during the year 2007-08 (FAO Indian Horticulture Database 2008). Among the horticultural crops fruits and vegetables play an important role, whereas exports of fruits and vegetables have increased over the years (Table 8). During 2004-05 export of fruits and vegetables was INR 13637.13 million as against INR 24116.57 million during 2006-07 (APEDA, 2008) Table 7 Area, production and productivity of horticultural crops in India Year Area (MHA) Production (MT) Productivity (MT/ha) ) 2001-02 16.6 145.8 8.8 2002-03 16.3 144.4 8.9 2003-04 19.2 153.3 21 2004-05 21.1 170.8 8.1 2005-06 18.7 182.8 9.8 2006-07 19.4 191.8 9.9 2007-08 20.1 207.0 10.3 Source: FAO Indian Horticulture Database (2008) Table 8 Export of horticultural produce in India Products 2004-05 2005-06 2006-07 Quantity Value Quantity Value Quantity Value Floriculture seeds 34496 2871 42659 3922 50048 7713 Fresh Fruits vegetables 1296530 13637 1465040 16587 1983873 24117 Processed fruits vegetables 325293 9614 501826 13595 549949 17316 Total 1656319 261227 2009525 341051 258387 491459 Source: APEDA, India Note: Qty: MT, value : Million INR Vegetables: In vegetable production, India is next to China with a production of 125.8 million tonnes from 7.8 million hectares with a share of 13 percent in relation to world production (Table 9). The per capital consumption of vegetables is 120 grams per day (APEDA 2009). In case of Fresh vegetable Indias export has been increased from INR 433.14 Crore in 2006-07 to Rs 489.49 Crore in 2007-08. Major Export Destinations of these vegetables are UAE, UK, Nepal, and Saudi Arabia. (APEDA, 2009) Table 9 Area, production and productivity of vegetable crops in India Year Area (MHA) Production (MT) Productivity (MT/ha) ) 2001-02 6156 88622 14.4 2002-03 6092 84815 13.9 2003-04 6082 88334 14.5 2004-05 6744 101246 15.0 2005-06 7213 111399 15.4 2006-07 7584 115011 15.2 2007-08 7803 125887 16.1 Source: FAO Indian Horticulture Database (2008) Among all vegetables gherkin is considered for the present study due to following reasons. Indias export of gherkin has been steadily increased since 1997-98. It accounts for 24,490 tonnes of gherkins having an export potential of INR 50.27 crore as against 35,242 tonnes worth of INR 69.86 crore in 1999-2000 (Venkatesh, 2003). In recent year gherkin export has been increased to 61.5 million tonnes with a trade value of INR1465.5 million during 2007-08 (UNFAO Export Data, 2009). 2.2.1 Production and export importance of gherkin in India Gherkin crop is being selected for the present study. It is regarded as HEIA crop especially a hybrid crop. Gherkin cultivation and processing started in India in the early 90s and presently cultivated over 19,500 acres in the three southern states of Karnataka, Tamil Nadu and Andhra Pradesh. Although gherkin can grow virtually in any part of the country, the ideal conditions required for growth prevail in these three states where the growing season extends throughout the year. It requires adequate water and temperature between 15-36 degree centigrade and the right type of soil. The crop takes 85 days to reach the required maturity level. Productivity is approximately four to five tonnes per acre and the best months are from February to March followed by June to August. India is a major exporter of provisionally preserved gherkin. Table 10 11 shows the cucumber and gherkin export from India. In India, Karnataka stands first in export, where cultivation is steadily growing since 2001 -02 accounting for a worth of INR 1200 million. During 2006-07 gherkins accounts to INR 3133 million which has been exported (Table 12). Table 10 Cucumber and gherkin exports from India (2007-08) Country Value( Million INR) Quantity (Tonnes) Share (%) ) UAE 1.96 142.75 17.55 Bangladesh 1.92 290.00 17.17 Netherland 1.78 93.10 15.92 Russia 1.66 83.50 14.91 Estonia 0.80 43.94 7.17 Nepal 0.75 74.42 6.75 Oman 0.75 70.00 6.74 Spain 0.55 31.82 4.95 France 0.47 20.21 4.27 Others 0.51 26.42 4.56 Total 11.20 876.18 100 Source: