Seminar Advantage and Disadvantage Essay Example for Free

Seminar Advantage and Disadvantage Essay * The advantage in preparing your seminar in two months prior to your seminar is that you can prepare everything with excellence because you have a lot of time to prepare. * You have a lot of time to locate a good venue, decide a design so that can capture the audience interest by seeing the area so relaxing and refreshing. * Whatever food you plan to fix, try to keep to the middle of the road in your selections of what to fix. Think of the food not only for its basic food value but for how much enjoyment it will give in the eating of it. Once you have your menus made, purchase all of your groceries that can bought ahead * You can also get a very good speaker or host in your seminar * You can decide how many audience you are going to invite, and what your target market are. * You also have a lot of time to expand your prospective list. DISADVANTAGE * The disadvantage of this longer preparation is that there is a tendency that you are going to change everything of what you have planned earlier, because of changing of your plan every day to make your seminar beautiful until the day will come. ADVANTAGE IN SIX WEEK PRIOR TO YOUR SEMINAR * The advantage in this stage is you can allocate more of your time to perform what is your task in this period. * Make sure that your invitation card is amazing and creative. This time, you can change anytime your invitations if there is a computer error in your invitation. * You should check how obtaining and testimonial the speaker is, it is for you to know how effective he is as a speaker so that the audience will digest the agenda of your seminar clearly. * Preparing your agenda to cannot commit mistake in front of the audience. * You must check your site for the temperature problems, check the average of your sets, room type and shape of the area, for the finalization of the set ups of the venue. DISADVANTAGE * The disadvantage of this week there’s so many seminars are marvelously full of content but somehow more difficult to digest because there is one  keynote in the introduction by the speakers and the subjects is common chain of reasoning or unified body with perhaps many details but one overriding theme. ADVANTAGE IN THREE WEEKS PRIOR TO YOUR SEMINAR * The advantage of this week you will know that if they are available and interested in your seminar. * Distributing your list of potential attendees will shorten the time for you to look for an audience. * You have a little more time to develop your list of audience if the other response that they cannot come to the seminar. * You have a chance to convince the audience to attend the seminar by calling them. * By having the tarpaulin, media, and brochures, you do not need to come to that person and convince them to attend the seminar. * People will come and have a registration if they are interested. DISADVANTAGE * The disadvantage is that there’s an audience will refuse your invitation and there are times the publicity you made is not that effective most specially if you are lack of finance in conducting your seminar or your publication is too plain to get the attention of an audience to be in your seminar. TWO WEEKS PRIOR TO YOUR SEMINAR * The advantage of this week is that you have final attendees in your list. * The thing to do is to send them letter to confirm if ever they change their mind, you still have time to look for a replacement. * Obtain the material for presentation to prevent problems. * Create evaluation sheet and checklist for attendees in advance, for the event come the list is prepared. * Create a certification or token in advance to prevent hassle. DISADVANTAGE * The disadvantage of this week, you do not have much time to handle a big problems is there is, must especially in the venue. ADVANTAGE IN THREE DAYS PRIOR TO YOUR SEMINAR * This week you have a confirm attendees on your list book and you will instruct them where the venue is, what time it will be and the registration fee. * The event you are planning is well prepared and done. DISADVANTAGE * You do not have time if there will be an audience to back out. In venue, materials, invitation, token problems etc. there is no more time to fix.

Approaches To Sport And Exercise

Approaches To Sport And Exercise Critically discuss interdisciplinary and multidisciplinary approaches to sport and exercise science within the professional experience undertaken in term 1. Support your answers with relevant literature and theory Research within sport and exercises science is done in many different disciplines. The majority of published research, however, is mono-disciplinary (from a singular discipline) in nature (Burwitz et al. 1994). A professional experience was undertaken to assess the approaches to inter and multi-disciplinary within sport and exercise science research. The experience was of a sport science nature which involved assisting in an undergraduate research project of 3D biomechanical analysis of a gymnastic vault using CODA, focussing specifically on the approach and springboard take-off. Sports biomechanics uses the scientific methods of mechanics to study the effects of various forces on the sports performer (Bartlett, 2007). It is important to monitor technique in gymnastics to help prevent injury and improve performance. It is then possible to feed this information back to coaches to highlight strengths and weaknesses of individual athletes. Multi or inter-disciplinary research requires a combination of methods and knowledge from more than one sub-discipline (Burwitz et al. 1994). This essay will outline what multi and inter-disciplinary approaches to sport and exercise science are, compare how similar they are and then show how they differ. It will then outline how the two approaches can be applied to the professional experience undertaken. An interdisciplinary approach within sport and exercise science involves a partnership of coaches with sport and exercise scientists such as physiologist or psychologists. Smith (2005) split sport science from exercise science due to differences of individual needs from elite athletes to members of the public. Smith (2005) described sport science as being characterised by collaborations with coaches and performance directors and exercise science as being characterised by collaborations with general practitioners and professionals allied to medicine. Interdisciplinary research needs to involve a strong integration of information from more than one sub-discipline of sport and exercise science from the outset of a particular research programme (Burwitz et al. 1994). Williams and James (2001) stated that a sport or exercise team should have a scientific basis. Williams and James (2001) also developed a model to demonstrate inter-disciplinary approaches, where the goal of the sport or exe rcise is affected by each area involved. Multi-disciplinary research involves less integration of the sub-disciplines of sport and exercise science. Each discipline tends to work in parallel on a common topic (Burwitz et al. 1994). Miles et al (1997) adapted Burwitz et al. (1994) definition to state that multi-disciplinary research involves sport and exercise scientists working together to solve a problem in an isolated unitary fashion and co-coordinated manor. In a multi-disciplinary approach each sub-discipline will look for problems to a solution from within only that discipline, for example a biomechanist will look at technique. Then each discipline will collate their results, whereas in an interdisciplinary approach the biomechanist may work with a physiologist to look at technique changes due to fatigue (Burwitz et al. 1994). Multi-disciplinary research may be the result of a lack integration of sub-disciplines from the outset of sport and exercise science, and so it is harder to integrate then together when trying to bring about an inter-disciplinary approach to problem solving. Multi and inter-disciplinary research are both ways of improving research and developing is away from mono-disciplinary work in sport and exercise sciences. The majority of sport and exercise research is mono-disciplinary (Burwitz et al 1994) which is when research looks solely at one sub-discipline and provides answers and conclusions from only that discipline. Both multi and inter-disciplinary approaches endeavour to link sub-disciplines, such as psychology and biomechanics, together to improve the ability to solve problems such as injury, fatigue and poor technique. Both approaches work in teams or groups (that include the sport and exercises scientists, coacher or practitioners and the athlete or patient) to combine knowledge and methods from their different areas. Despite these similarities there are still major differences between the two stated approaches. The inter-disciplinary approach appears to be the best way to bring about improvements as it integrates the sub-disciplines which takes the form of ‘bridge-building (Squires et al 1975) which requires a combination of specialist knowledge from various disciplines focusing on a specific problem. Contrastingly, multi-disciplinary approaches collate rather than combine knowledge; therefore the sub-disciplines work separately during research processes before coming together to attempt to reach a conclusion about a stated problem (Burwitz et al 1994). It is also believed that an interdisciplinary approach will reveal potential conflicts between the sub-disciplines (Burwitz et al 1994). As there is immediate interaction between sub-disciplines, an opinion given by one area is disputed by another. This is less likely to occur in multi-disciplinary approaches as sub-disciplines do not work i n direct contact with one another. Despite the above examples no clear definition is given of the distinctions between the two approaches because many sport and exercise scientists have regarded multi and inter-disciplinary as synonymous terms (Burwitz et al 1994). The professional experience was involved with sport science which smith (2001) described as being characterised by collaborations with coaches and performance directors. It was first and foremost a biomechanical approach. Biomechanics is a highly scientific and mathematical based sub-discipline, usually looking at technique, and problems with technique, as causes of problems such as injury and failure of achievement. Gymnastics is a sport that utilises these methods frequently as it is a very technical sport where injuries can be common. This is due to the fact that gymnastics encompasses a seemingly endless quantity of movement skills (George 1980). During the professional experience questions were putt to the researcher regarding the involvement of other sub-disciplines to determine the dimension of the research. These questions were: ‘are there any sport scientists or performance director present for sub-disciplines other than biomechanics to help assess the primary information gathered from the research? ‘Will the results of the research be collated with other sub-disciplines and fed back to the performer? From the answers given to these questions it was concluded that the research being carried out was mono-disciplinary as there was no interaction, in any way, with other sub-disciplines. As discussed above there is an increasing need from multi or inter-disciplinary research in sport and exercise science, this study may have been improved by the introduction of other sub-disciplines and the feedback given to an athlete would have increased in value. The research itself was looking at the approach and take off of the gymnast during the vault, as well as having technique assessed biomechanically, the researcher may have advised the athlete to be assessed by a physiologist or physiotherapist, this may produce results that show differences in muscle pair which could lead to injury, for example one calf being larger than the other, which could mean production of force at take of is unbalanced. This could then be fed to the biomechanist who has also found that during takeoff the gymnast has been unbalanced and therefore the athlete would need to undergo strengthening in the shorter calf to get it up to a similar size to the other calf. This would create a multi-disciplinary approach as sub-disciplines of sport science will have collated data after the research to improve feed back to the performer. It may also have been helpful to have had a psychologist present at the time of testing who had watched the subject in competition and seen if their routine or performance differed between in and out of competition performance. It may be possible that the pressure of performing in competition had led the athlete miss time a move which led to a decrease in performance; the psychologist could then work with the performer to help improve confidence during competition and therefore improve the athletes performance. This would create an inter-disciplinary approach as sub-disciplines of sport science will have integrated during research to improve feed back to the performer. If the approachs dimension was changed to either a multi or an inter-disciplinary approach it will give the gymnast a much better chance of improving performance in competition. The professional experience undertaken was shown to be mono-disciplinary as it was a piece of research focusing solely on the biomechanics of the approach and take off of the gymnastics vault. As discussed above introducing further dimensions to the research may have been more beneficial to the athlete as they may receive more feedback. However the piece of research was an undergraduate study which had a primary focus on biomechanics and introducing other sub-disciplines may have confused the findings and taken away from the aims of the research. This essay has described multi and inter-disciplinary approaches within sport science and described their application within a sporting context.

Comparing the Blues in Hughes The Blues Im Playing and Baldwins Sonn

The Blues: in Hughes' The Blues I'm Playing and Baldwin's Sonny's Blues  Ã‚   In Langston Hughes' The Blues I'm Playing, the blues are the source of Oceola's life and her choices. Langston is trying to illustrate the conflict between life and art. The art in this story is represented in a confined manner, as a disciplined career with a white woman acting as the overseer in the young lady's life. Art to Oceola, with its profit, convenience and privileges offers an array of benefits, but being embodied in Dora Ellsworth, the art seems to drift away from life's vitality. Life in Oceola sings itself in jazz and blues in Harlem, ignores the artistic East 63rd Street and the rules by which are claims its superiority. There is a closeness between the blues and the life of Oceola as she summarizes her life for her patron. She remembers Mobile's roast pig and the large mouth of Billy Kersands, the minstrel leader who let her as a child place both hands inside it. The relevance of Negro experience to blues and jazz is the point in her recollection that her parents, both musicians, we... Comparing the Blues in Hughes' The Blues I'm Playing and Baldwin's Sonn The Blues: in Hughes' The Blues I'm Playing and Baldwin's Sonny's Blues  Ã‚   In Langston Hughes' The Blues I'm Playing, the blues are the source of Oceola's life and her choices. Langston is trying to illustrate the conflict between life and art. The art in this story is represented in a confined manner, as a disciplined career with a white woman acting as the overseer in the young lady's life. Art to Oceola, with its profit, convenience and privileges offers an array of benefits, but being embodied in Dora Ellsworth, the art seems to drift away from life's vitality. Life in Oceola sings itself in jazz and blues in Harlem, ignores the artistic East 63rd Street and the rules by which are claims its superiority. There is a closeness between the blues and the life of Oceola as she summarizes her life for her patron. She remembers Mobile's roast pig and the large mouth of Billy Kersands, the minstrel leader who let her as a child place both hands inside it. The relevance of Negro experience to blues and jazz is the point in her recollection that her parents, both musicians, we...

Developing Collaborative Partnerships :: Workforce Work Essays

Developing Collaborative Partnerships Collaboration has become the byword of the 1990s as a strategy for systemic change in human services, education, government, and community agencies. Increasingly, public and private funders are rewarding or requiring collaborative efforts. The advent of block grants is creating an urgent need for integrated, locally controlled services. Shrinking resources are causing many organizations to consider the potential benefits of working together. States are looking at ways to integrate their economic, work force, and technology development efforts (Bergman 1995). Perhaps most important is the realization that the complex problems and needs of families, workers, and communities are not being met effectively by existing services that are "fragmented, crisis oriented, discontinuous, and episodic" (Kadel 1991, p. vi). Collaboration involves more intense, long-term efforts than do cooperation or coordination. Collaborating agencies make a formal, sustained commitment to accomplishing a shared, clearly defined mission. Collaborative efforts can overcome such problems as fragmentation of client needs into distinct categories that ignore interrelated causes and solutions. They can make more services available or improve their accessibility and acceptability to clients (Melaville and Blank 1993). Collaborations require a change in thinking--the ability to see the "big picture"--and in operating--alteration of structures, policies, and rules to make service delivery seamless. Such changes, or "paradigm busting" (Bendle/Carman 1996) can be intimidating or threatening; in addition, other barriers must be overcome in order to make partnerships work: negative past experiences with collaboration; difficult past/present relationships among agencies; competition and turf issues; personality conflicts; differing organizational norms, values, and ideologies; lack of precedent; and fear of risk (Anderson 1996; National Assembly 1991). This Brief looks at successful collaborations involving work force development, family literacy, and welfare reform to identify the elements that make collaborations effective. Based on existing guidelines and successful programs, the steps needed to create and sustain collaborative relationships are described to help adult, career, and vocational educator s forge the linkages that could improve services. Collaborative Examples One-stop career centers are collaborative efforts among agencies that have traditionally provided employment and training services such as information, counseling, referral, and placement; U.S. Department of Labor funding has supported their development in several states. Before the federal initiative, a prototype arose in Waukesha, Wisconsin (Anderson 1996), where the Workforce Development Center provides an integrated, seamless system of employment services through the joint efforts of nine public and private agencies, including the state job service, a technical college, child care center, labor organization, and county health and human services department.

Essay on Technical Qualities, Symbolism, and Imagery of Dover Beach

Technical Qualities, Symbolism, and Imagery of "Dover Beach" In "Dover Beach," Matthew Arnold creates a dramatic monologue of the Victorian Era that shows how perceptions can be misleading. Arnold conveys the theme of "Dover Beach" through three essential developments: the technical qualities of the poem itself, symbolism, and imagery. The theme of illusion versus reality in "Dover Beach" reflects the speaker's awareness of the incompatibility between what is perceived and what truly is real. The technical qualities of the poem include rhythm and meter, rhyme, figures of speech, sound, and irony of the words. The mechanics alone do not explain why illusion and reality differ, but they do help to explain how Arnold sets up the poem to support the theme. The most prominent mechanisms include the rhythm and the meter of the lines and the stanzas of the poem. Line 1 is an iambic trimeter: The sea/is calm/to-night. The gentle pulsating rhythm of the iamb mirrors the ebb and flow of the sea. The actual words of the first line manifest this idea to picture a calm sea gently lapping at the beach. The second line, an iambic tetramater, also reveals a calm sea. However, line 3 breaks the pattern and forces the reader to break his or her own rhythm. Line 3 includes: Upon/the straits,//on the French/Coast/the light. The line begins and ends with an iamb, but the middle is broken up with an anapest. The anapest is a foreshadow of the tumult to come. The fourth line breaks up even farther with an anapest at the beginning, but the fifth line recovers the rhythm. Glimmering/and vast//out in/the tran/quil bay. The rhythm recovers by the end of the first stanza, but the original trimeter has not. The number of feet per lin... ...he speaker is supported by the rhythm and the meter, the lack of a consistent rhyme scheme, the figures of speech, the sound of the words, and the irony of the entire poem. The symbolism of the sea and the imagery of light and dark bring out the alternating visual and auditory qualities, which elaborate on illusion and reality, respectively, Arnold's portrayal of one person's battle with illusion and reality shows a complex view of humanity in a simple poem. Works Cited Arnold, Matthew. "Dover Beach." [1867] Literature. 5th ed. Eds. James H. Pickering and Jeffery D. Hoeper. Upper Saddle River, NJ: Prentice, 1997. 952-53. Ciardi, John. How Does A Poem Mean? Boston: Houghton, 1975. 196. Untermeyer, Louis. The Pursuit of Poetry. New York: Simon & Schuster, 1969. 57-59. Walcutt, Charles Child. The Explicator. Chicago: Quadrangle, 1968. 16-9.

GLOBALIZATION AT GENERAL ELECTRIC Essay

1.Why do you think GE has invested so aggressively in foreign expansion? What opportunities is it trying to exploit? ïÆ'ËœI think GE acted so aggressively because they saw a great opportunity to expand the company and if they didn’t do so, another company would have grabbed the opportunity and purchase the companies that were in trouble. In order for a company to grow at a rapid pace, it would have to take over other companies that are in financial jeopardy. Going international allowed the company to reach millions of new customers. ïÆ'ËœThe opportunities that they are trying to exploit are (1) the economic weakness in certain parts of the world with the aim of investing to the region, but in fact to acquiring companies, (1) to take advantage of economic uncertainty caused by the currency market collapse for the aim of purchasing or acquiring companies, (3) to help in process of development in under develop areas with the aim of profiting from it later 2.What is GE trying to achieve by moving some of the headquarters of its global businesses to foreign locations? How might such moves benefit the company? Do these moves benefit the Unites States? ïÆ'Ëœ GE strongly believes that to succeed internationally, it must be close to its customers. That’s why it builds or transfers its headquarters abroad. ïÆ'Ëœ The company might benefit from more attractive location, Tax advantages, Lower wages, well-educated labor force, Costs reduction, Industry of specialization, Foreign government invitation, Good infrastructure. ïÆ'ËœThe USA can benefit from good reputation of American companies, can establish diplomatic relationship with foreign counties, there might be a potential influence on Gross National Product (GNP). 3.What is the goal behind trying to â€Å"internationalize† these ranks? What do you think it means to â€Å"internationalize† these ranks? ïÆ'ËœThe goal behind internationalization is to get closer to its customers and have better knowledge of the local market, local culture and language of the country that they are doing business. ïÆ'ËœInternationalize is the integration of the local market knowledge and application of cultural sensitivity approach through engaging their local managers in the managerial decision-making process. 4.What does the GE example tell you about the nature of true global business? ïÆ'ËœGE’s example tells us that the true global business is a business that is headquartered locally (in overseas) for the aim of getting closer to its customers. It exploits their local market knowledge as well as their local culture and language knowledge.

Comparative Net Sales of Flower Shops Business

Objectives 1. Determine the business profile variables 2. Identify the services and kind of flowers being offered and the months when the sale is highest and lowest 3. Compare and analyse the sales of flowers during the seasons when it is in demand and not 4. Identify the problems being encountered and factors affecting the sales 5. Prepare plan of action Questionnaire I. Profile Variables Name of Business: ___________________ Type of Business: _______sole proprietorship _______corporation _______partnership _______others Area of Business:_______along the public market ______other commercial area _______residential area _______others Number of workers:_______ 1 _______2 _______3 _______4 _______5 and above Years in Operation_______1-5 years _______6-10 years _______11-15 years _______16-20 years _______ above 20 years II. Product/ Goods Supplier_______within the province _______outside the province _______outside the country _______outside the province and outside the country _______ within and outside the province _______within the province and outside the country Flowers being Sold: (displayed at the time of survey) _______ Rose ________ Malaysian Mums ________ Angels’ Breath ________ Anthurium ________ Birds of Paradise ________ Tulips ________ Star Gazer Peak Seasons for flowers: __________________________________ Estimated Sales:_______below 10000 _______10000-29999 _______30000-49999 _______50000-69999 _______70000-89999 _______90000 and above Dormant Seasons for flowers: _______________________________ Estimated Sales per day:_______0 – 499 _______500 – 999 _______1000 – 1499 _______1500 – 1999 _______2000 and above Problems Encountered: Dormant SeasonsPeak SeasonsNeverSometimesAlwaysNeverSometimesAlways Dried flowers Pests Few customers Delayed deliveries of ordered flowers Unpaid balances of customers Too many competitors Burdensome taxes Lack of necessary equipment Lack of stocked flowers Natural calamities Strongly D isagreeDisagreeAgreeStrongly Agree It is better to sold flowers on Peak Seasons only Customers are seem satisfied in your services and flowers Total sales each day depends on the business’ luck Flowers are important part of an occasion Flowershop business is an in-demand business anytime Descriptive Survey PROFILE VARIABLESNumber ofYears of Name of BusinessType of BusinessArea of BusinessworkersExistenceSupplier's Place 1Amang's FlowershopSole Proprietorshippublic market125outside the province 2Leony's FlowershopSole Proprietorshippublic market320outside the province 3Emily's FlowershopSole Proprietorshippublic market320outside the province 4Ley's FlowershopSole Proprietorshippublic market330outside the province 5Heaven's TouchSole Proprietorshippublic market18outside the province 6Petal and BloomSole Proprietorshipother commercial area21outside the province 7Maycee's FlowershopSoleProprietorshipother commercial area115outside the province 8Highland FlowershopSole Proprietors hipother commercial area417outside the province 9BloomerySole Proprietorshipother commercial area210outside the province 10Kelsey's FlowershopSole Proprietorshipother commercial area220outside the province 11Kart's FlowershopSole Proprietorshipother commercial area31outside the province 12Vic's FlowershopSole Proprietorshipother commercial area22outside the province 13Flowers and GreensSole Proprietorshipother commercial area31outside the province and outside the country 14Flowers 911Sole Proprietorshipother commercial area21outside the province 15Flowershop by SylviaSole Proprietorshipother commercial area32outside the province 16Te AmoSole Proprietorshipother commercial area11outside the province 17Christhialyn's FlowershopSole Proprietorshipother commercial area425outside the province 18SunshineSole Proprietorshipresidential area110outside the province 19Money Changer FlowershopSole Proprietorshipother commercial area25outside the province 20Carissa's FlowershopSole Proprietorshi pother commercial area24outside the province 21BobzenSole Proprietorshipother commercial area215outside the province 22Bobzen – branchSole Proprietorshipother commercial area11outside the province 23Zenaida's FlowershopSole Proprietorshipother commercial area28outside the province 24Sally's FlowershopSole Proprietorshipother commercial area217outside the province and outside the country 25Doni's FlowershopSole Proprietorshipother commercial area115outside the province 26Yolly's FlowershopSole Proprietorshipother commercial area110outside the province 27Dionisia's FlowershopSole Proprietorshipother commercial area115outside the province 28Rita's FlowershopSole Proprietorshippublic market12outside the province 29JeunesseSole Proprietorshippublic market12outside the province 30Myra Grace's FlowershopSole Proprietorshipother commercial area23outside the province Flowers being sold 1rose, malaysian mums, anthurium, angel's breath 2rose, malaysian mums, anthurium, angel's breath 3r ose, malaysian mums, anthurium, angel's breath 4rose, malaysian mums, anthurium, angel's breath 5rose, malaysian mums, anthurium, angel's breath 6rose, malaysianmums, birds of paradise, star gazer, angel's breath, anthurium 7rose, malaysianmums, star gazer, angel's breath, anthurium 8rose, malaysianmums, birds of paradise, star gazer, angel's breath, anthurium 9rose, malaysianmums, angel's breath 0rose, malaysianmums, star gazer, angel's breath, anthurium 11rose, malaysianmums, star gazer, angel's breath, anthurium 12rose, malaysianmums, star gazer, angel's breath, anthurium 13rose, malaysianmums, birds of paradise, star gazer, angel's breath, anthurium, tulips 14rose, malaysian mums, anthurium, angel's breath 15rose, malaysian mums, anthurium, angel's breath 16rose, malaysian mums, birds of paradise angel's breath, 17rose, malaysian mums, anthurium, angel's breath 18rose, malaysian mums, angel's breath 19rose, malaysian mums, angel's breath 20rose, malaysian mums, anthurium, angel' s breath 21rose, malaysian mums, angel's breath, star gazer 22rose, malaysian mums, angel's breath 23rose, malaysian mums, angel's breath 24rose, malaysianmums, birds of paradise, star gazer, angel's breath, anthurium, tulips 25rose, malaysian mums, angel's breath 26rose, malaysian mums, angel's breath 27rose, malaysian mums, angel's breath 8rose, malaysianmums, birds of paradise, star gazer, angel's breath, anthurium, tulips 29rose, malaysian mums, anthurium, angel's breath 30rose, malaysian mums, anthurium, angel's breath Peak Seasons for flowersEstimated SalesDormant Seasons/ MonthsEstimated Sales Valentines Day, All Souls Day10000July, August1000 Valentines Day, All Souls Day50000June, July1500 Valentines Day, All Souls Day50000June, August2000 Valentines Day, All Souls Day30000June, July3000 Valentines Day, All Souls Day30000July, August1500 Valentines Day, All Souls Day30000July, August500 Valentines Day, All Souls Day30000August, September1000 Valentines Day, All Souls Day100 000June, July5000 Valentines Day, All Souls Day30000July, August1000 Valentines Day, All Souls Day30000July, August1000Valentines Day, All Souls Day40000August, September1500 Valentines Day, All Souls Day35000August, September500 Valentines Day, All Souls Day100000July, August3000 Valentines Day, All Souls Day30000July, August500 Valentines Day, All Souls Day40000July, August1000 Valentines Day, All Souls Day30000July, August1000 Valentines Day, All Souls Day100000August, September2000 Valentines Day, All Souls Day40000August, September500 Valentines Day, All Souls Day50000July, August2000 Valentines Day, All Souls Day40000August, September1000 Valentines Day, All Souls Day100000August, September1500 Valentines Day, All Souls Day100000July, August2000 Valentines Day, All Souls Day100000August, September1000Valentines Day, All Souls Day80000June, July1000 Valentines Day, All Souls Day70000June, July500 Valentines Day, All Souls Day70000August, September500 Valentines Day, All Souls D ay30000July, August500 Valentines Day, All Souls Day60000July, August1000 Valentines Day, All Souls Day50000August, September1000 Valentines Day, All Souls Day40000August, September1000 Problems Encountered During Dormant Seasons P1P2P3P4P5P6P7P8P9P10 AlwaysSometimesAlwaysSometimesSometimesSometimesAlwaysAlwaysNeverSometimes AlwaysSometimesAlwaysSometimesSometimesSometimesAlwaysAlwaysNeverSometimes AlwaysSometimesAlwaysSometimesSometimesSometimesAlwaysSometimesNeverSometimesAlwaysSometimesAlwaysSometimesSometimesSometimesAlwaysSometimesNeverSometimes AlwaysSometimesAlwaysSometimesSometimesAlwaysAlwaysSometimesSometimesSometimes AlwaysSometimesAlwaysSometimesSometimesAlwaysAlwaysAlwaysNeverSometimes AlwaysSometimesAlwaysSometimesSometimesAlwaysAlwaysAlwaysNeverSometimes AlwaysSometimesAlwaysNeverSometimesAlwaysAlwaysSometimesSometimesSometimes AlwaysSometimesAlwaysSometimesSometimesAlwaysAlwaysSometimesNeverSometimes AlwaysSometimesAlwaysSometimesSometimesSometimesAlwaysSometimesNeve rSometimes AlwaysNeverAlwaysNeverSometimesSometimesAlwaysSometimesSometimesSometimes AlwaysSometimesAlwaysSometimesSometimesSometimesAlwaysNeverSometimesSometimes SometimesNeverAlwaysNeverSometimesAlwaysAlwaysNeverNeverSometimes AlwaysSometimesAlwaysNeverSometimesAlwaysAlwaysSometimesSometimesSometimes SometimesSometimesAlwaysNeverSometimesSometimesAlwaysSometimesNeverSometimes AlwaysSometimesAlwaysSometimesSometimesSometimesAlwaysAlwaysSometimesSometimes SometimesSometimesAlwaysSometimesSometimesAlwaysAlwaysNeverSometimesSometimes AlwaysSometimesAlwaysSometimesSometimesAlwaysAlwaysSometimesSometimesSometimes AlwaysNeverAlwaysNeverSometimesAlwaysAlwaysSometimesSometimesSometimes AlwaysNeverAlwaysSometimesSometimesSometimesAlwaysSometimesSometimesSometimes AlwaysSometimesAlwaysNeverSometimesSometimesAlwaysAlwaysSometimesSometimesAlwaysSometimesAlwaysNeverSometimesSometimesAlwaysAlwaysSometimesSometimes AlwaysAlwaysAlwaysNeverSometimesSometimesAlwaysSometimesNeverSometimes SometimesSo metimesAlwaysSometimesSometimesAlwaysAlwaysSometimesSometimesSometimes AlwaysSometimesAlwaysSometimesSometimesSometimesAlwaysAlwaysSometimesSometimes SometimesSometimesAlwaysNeverSometimesSometimesAlwaysSometimesNeverSometimes AlwaysSometimesAlwaysNeverSometimesAlwaysAlwaysSometimesNeverSometimes AlwaysNeverAlwaysNeverSometimesAlwaysAlwaysAlwaysSometimesSometimes SometimesSometimesAlwaysSometimesSometimesAlwaysAlwaysAlwaysSometimesSometimes AlwaysSometimesAlwaysSometimesSometimesAlwaysAlwaysAlwaysNeverSometimesProblems Encountered During Peak Seasons P1P2P3P4P5P6P7P8P9P10 NeverSometimesNeverSometimesSometimesAlwaysAlwaysAlwaysSometimesSometimes SometimesSometimesNeverSometimesSometimesAlwaysAlwaysAlwaysSometimesSometimes NeverSometimesNeverSometimesSometimesAlwaysAlwaysSometimesSometimesSometimes SometimesSometimesNeverSometimesSometimesAlwaysAlwaysSometimesNeverSometimes SometimesSometimesNeverSometimesSometimesAlwaysAlwaysSometimesSometimesSometimes NeverSometimesNeverSometimesSom etimesAlwaysAlwaysAlwaysNeverSometimes NeverSometimesNeverSometimesSometimesAlwaysAlwaysAlwaysSometimesSometimes NeverSometimesNeverSometimesSometimesAlwaysAlwaysSometimesSometimesS metimes NeverSometimesNeverSometimesSometimesAlwaysAlwaysSometimesNeverSometimes SometimesSometimesNeverSometimesSometimesSometimesAlwaysSometimesSometimesSometimes SometimesNeverNeverNeverSometimesAlwaysAlwaysSometimesSometimesSometimes NeverSometimesNeverSometimesSometimesAlwaysAlwaysNeverSometimesSometimes NeverNeverNeverNeverSometimesAlwaysAlwaysNeverSometimesSometimes NeverSometimesNeverSometimesSometimesAlwaysAlwaysSometimesSometimesSometimes NeverSometimesNeverNeverSometimesAlwaysAlwaysSometimesSometimesSometimes NeverSometimesNeverSometimesSometimesSometimesAlwaysAlwaysSometimesSometimes NeverSometimesNeverSometimesSometimesAlwaysAlwaysNeverSometimesSometimes NeverSometimesNeverSometimesSometimesAlwaysAlwaysSometimesSometimesSometimes NeverNeverNeverNeverSometimesAlwaysAlwaysSometimesSometimesSom etimes NeverNeverNeverSometimesSometimesAlwaysAlwaysSometimesSometimesSometimes NeverSometimesNeverNeverSometimesSometimesAlwaysAlwaysSometimesSometimes SometimesSometimesNeverNeverSometimesAlwaysAlwaysAlwaysSometimesSometimes SometimesAlwaysNeverSometimesSometimesSometimesAlwaysSometimesSometimesSometimes NeverSometimesNeverSometimesSometimesAlwaysAlwaysSometimesSometimesSometimes NeverSometimesNeverSometimesSometimesSometimesAlwaysAlwaysSometimesSometimes SometimesSometimesNeverNeverSometimesAlwaysAlwaysSometimesNeverSometimes SometimesSometimesNeverSometimesSometimesAlwaysAlwaysSometimesSometimesSometimes NeverNeverNeverSometimesSometimesAlwaysAlwaysAlwaysSometimesSometimes NeverSometimesNeverSometimesSometimesAlwaysAlwaysAlwaysSometimesSometimes NeverSometimesNeverSometimesSometimesAlwaysAlwaysAlwaysSometimesSometimes S1S2S3S4S5 DisagreeStrongly AgreeAgreeAgreeDisagree DisagreeAgreeStrongly AgreeStrongly AgreeDisagree DisagreeAgreeAgreeAgreeDisagree DisagreeAgreeAgreeStrongly Ag reeAgree DisagreeAgreeAgreeStrongly AgreeAgree AgreeStrongly AgreeAgreeStrongly AgreeDisagreeDisagreeStrongly AgreeAgreeStrongly AgreeDisagree DisagreeStrongly AgreeStrongly AgreeStrongly AgreeDisagree DisagreeStrongly AgreeStrongly AgreeStrongly AgreeAgree AgreeStrongly AgreeStrongly AgreeStrongly AgreeDisagree DisagreeStrongly AgreeStrongly AgreeStrongly AgreeDisagree DisagreeStrongly AgreeAgreeStrongly AgreeDisagree AgreeStrongly AgreeDisagreeStrongly AgreeDisagree AgreeAgreeDisagreeStrongly AgreeAgree AgreeStrongly AgreeAgreeStrongly AgreeDisagree DisagreeStrongly AgreeAgreeStrongly AgreeDisagree AgreeStrongly AgreeAgreeAgreeDisagree AgreeStrongly AgreeStrongly AgreeAgreeAgree DisagreeAgreeDisagreeStrongly AgreeAgree AgreeAgreeDisagreeStrongly AgreeDisagreeAgreeStrongly AgreeAgreeStrongly AgreeStrongly Agree AgreeStrongly AgreeAgreeStrongly AgreeDisagree DisagreeStrongly AgreeAgreeStrongly AgreeStrongly Agree DisagreeStrongly AgreeAgreeStrongly AgreeAgree AgreeStrongly AgreeDisa greeAgreeDisagree AgreeStrongly AgreeAgreeAgreeAgree AgreeStrongly AgreeAgreeAgreeDisagree AgreeStrongly AgreeStrongly AgreeStrongly AgreeDisagree AgreeStrongly AgreeDisagreeStrongly AgreeDisagree AgreeStrongly AgreeDisagreeStrongly AgreeDisagree PROFILE VARIABLES Respondents Type of BusinessArea of BusinessNumber of WorkersYears of ExistenceSupplier's Place 111152 211342 311342 411352 511122 612212 712132 812442 912222 1012242 1112312 1212212 312314 1412212 1512312 1612112 1712452 1813122 1912212 2012212 2112232 2212112 2312222 2412244 2512132 2612122 2712132 2811112 2911112 3012212 1. 001. 801. 972. 332. 13 Numeric Survey Flowers being SoldEstimated Sales rosesmalaysian mumsangel's breath anthuriumbirds of paradise tulipsstar gazerTotal No. of Flowers Being OfferedPeak SeasonsDormant Seasons 111111523 21111444 311111545 41111435 51111434 6111111632 71111433 8111111665 9111333 1011111533 1111111534 1211111532 131111111765 141111432 151111433 161111433 171111465 18111332 19111335 20 1111433 211111464 22111365 23111363 241111111753 251111452 26111352 27111332 281111111743 29111343 30111333 03030187311129 3. 903. 37 Dormant P1P2P3P4P5P6P7P8P9P10Composite Mean 132322233122. 33 232322233122. 33 332322232122. 22 432322232122. 22 532322332222. 44 632322333122. 44 732322333122. 44 832312332222. 33 932322332122. 33 1032322232122. 22 1131312232222. 11 1232322231222. 22 1321312331121. 89 1432312332222. 33 1522312232122. 00 1632322233222. 44 1722322331222. 22 1832322332222. 44 1931312332222. 22 2031322232222. 22 2132312233222. 33 2232312233222. 33 2333312232122. 22 2422322332222. 33 2532322233222. 44 2622312232122. 00 2732312332122. 22 2831312333222. 33 2922322333222. 44 3032322333122. 44 Mean2. 801. 873. 001. 602. 002. 503. 002. 271. 532. 002. 29Problems (Peak) Statements P1P2 P3P4 P5 P6P7 P8P9 P10Composite MeanS1S2S3S4S5Composite Mean 12122333222. 10243322. 80 22122333222. 20234423. 00 12122332222. 00233322. 60 22122332122. 00233433. 00 22122332222. 10233433. 00 1212233 3122. 00343423. 20 12122333222. 10243423. 00 12122332222. 00244423. 20 12122332121. 90244433. 40 22122232222. 00344423. 40 21112332221. 90244423. 20 12122331221. 90243423. 00 11112331221. 70342423. 00 12122332222. 00332433. 00 12112332221. 90343423. 20 12122233222. 00243423. 00 12122331221. 90343323. 00 12122332222. 00344333. 40 11112332221. 80232432. 80 11122332221. 90332422. 80 12112233221. 90343443. 60 22112333222. 10343423. 20 23122232222. 0243443. 40 12122332222. 00243433. 20 12122233222. 00342322. 80 22112332121. 90343333. 20 22122332222. 10343323. 00 11122333222. 00344423. 40 12122333222. 10342423. 00 12122333222. 10342423. 00 1. 301. 871. 001. 772. 002. 833. 002. 271. 872. 00 1. 992. 533. 773. 003. 772. 403. 09 Graphical Presentation G-1 Area of Business G-2 Number of Workers G-3 Years of Existence G-4 Estimated Sales During Peak Season G-5 Estimated Sales per Day during Dormant Season G-6 Central Tendencyof Problems Encountered During Dormant Season G-7 Central Tendency of Problems During Peak Season G-8 Statements Tabular Presentation Profile Variables Frequencies StatisticsType Of BusinessArea Of BusinessNumber Of WorkersYears Of ExistenceSupplier’s Place NValid3030303030 Missing00000 Range02342 Minimum11112 Maximum13454 Sum3054597064 Frequency Table Type Of Business FrequencyPercentValid PercentCumulative Percent ValidSole Proprietorship30100. 0100. 0100. 0 Area Of Business FrequencyPercentValid PercentCumulative Percent ValidPublic Market723. 323. 323. 3 Other Commercial Area2273. 373. 396. 7 Residential Area13. 33. 3100. 0 Total30100. 0100. 0 Number Of Workers FrequencyPercentValid PercentCumulative Percent Valid11136. 736. 736. 7 21136. 736. 773. 3 3620. 020. 093. 3 426. 76. 7100. 0 Total30100. 0100. 0 Years Of Existence FrequencyPercentValid PercentCumulative PercentValid1-5 years1343. 343. 343. 3 6-10 years516. 716. 760. 0 11-15 years413. 313. 373. 3 16-20 years516. 716. 790. 0 Above 20 years310. 010. 0100. 0 Total30100. 0100. 0 Supplie rs’ Place FrequencyPercentValid PercentCumulative Percent Valid22893. 393. 393. 3 426. 76. 7100. 0 Total30100. 0100. 0 Means Case Processing Summary Cases IncludedExcludedTotal NPercentNPercentNPercent Type Of Business * PVCompMean30100. 0%0. 0%30100. 0% Area Of Business * PVCompMean30100. 0%0. 0%30100. 0% Number Of Workers * PVCompMean30100. 0%0. 0%30100. 0% Years Of Existence * PVCompMean30100. 0%0. 0%30100. 0% Suppliers’ Place * PVCompMean30100. 0%0. 0%30100. 0% ReportPVCompMeanType Of BusinessArea Of BusinessNumber Of WorkersYears Of ExistenceSuppliers’ Place 1. 20Mean1. 001. 001. 001. 002. 00 N22222 Std. Deviation. 000. 000. 000. 000. 000 1. 40Mean1. 001. 671. 001. 332. 00 N33333 Std. Deviation. 000. 577. 000. 577. 000 1. 60Mean1. 002. 001. 861. 142. 00 N77777 Std. Deviation. 000. 000. 378. 378. 000 1. 80Mean1. 002. 131. 752. 132. 00 N88888 Std. Deviation. 000. 354. 886. 835. 000 2. 00Mean1. 001. 501. 504. 002. 00 N22222 Std. Deviation. 000. 707. 7071. 414. 000 2. 20Mean1. 001. 502. 753. 252. 50 N44444 Std. Deviation. 000. 577. 5001. 5001. 000 2. 40Mean1. 001. 003. 005. 002. 00 N11111 Std. Deviation†¦.. 2. 0Mean1. 002. 003. 004. 003. 00 N22222 Std. Deviation. 000. 0001. 414. 0001. 414 2. 80Mean1. 002. 004. 005. 002. 00 N11111 Std. Deviation†¦.. TotalMean1. 001. 801. 972. 332. 13 N3030303030 Std. Deviation. 000. 484. 9281. 446. 507 ANOVA Tablea Sum of SquaresDf Area Of Business * PVCompMeanBetween Groups(Combined)3. 7588 Within Groups3. 04221 Total6. 80029 Number Of Workers * PVCompMeanBetween Groups(Combined)15. 3608 Within Groups9. 60721 Total24. 96729 Years Of Existence * PVCompMeanBetween Groups(Combined)45. 5188 Within Groups15. 14921 Total60. 66729 SuppliersPlace * PVCompMeanBetween Groups(Combined)2. 4678 Within Groups5. 00021 Total7. 46729 a.No variance within groups – statistics for TypeOfBusiness * PVCompMean cannot be computed. ANOVA Tablea Mean SquareFSig. AreaOfBusiness * PVCompMeanBetween Groups(Combined) . 4703. 243. 015 Within Groups. 145 NumberOfWorkers * PVCompMeanBetween Groups(Combined)1. 9204. 197. 004 Within Groups. 457 YearsOfExistence * PVCompMeanBetween Groups(Combined)5. 6907. 887. 000 Within Groups. 721 SuppliersPlace * PVCompMeanBetween Groups(Combined). 3081. 295. 299 Within Groups. 238 a. No variance within groups – statistics for TypeOfBusiness * PVCompMean cannot be computed. Measures of Association EtaEta Squared AreaOfBusiness * PVCompMean. 743. 553 NumberOfWorkers * PVCompMean. 784. 615YearsOfExistence * PVCompMean. 866. 750 SuppliersPlace * PVCompMean. 575. 330 Flowers Being Sold Frequencies Statistics RosesMalaysian MumsAngel’s BreathAnthuriumBirds Of Paradise Tulips Star Gazer NValid30303030303030 Missing0000000 Range0001111 Sum303030187311 Frequency Tables Roses FrequencyPercentValid PercentCumulative Percent ValidAvailable30100. 0100. 0100. 0 Malaysian Mums FrequencyPercentValid PercentCumulative Percent ValidAvailable30100. 0100. 0100. 0 Birds Of Paradise FrequencyPercentValid PercentCumulative Percent ValidNot Available2376. 776. 776. 7 Available723. 323. 3100. 0 Total30100. 0100. 0 Angel’s Breath FrequencyPercentValid PercentCumulative PercentValidAvailable30100. 0100. 0100. 0 Tulips FrequencyPercentValid PercentCumulative Percent ValidNot Available2790. 090. 090. 0 Available310. 010. 0100. 0 Total30100. 0100. 0 Star Gazer FrequencyPercentValid PercentCumulative Percent ValidNot Available1963. 363. 363. 3 Available1136. 736. 7100. 0 Total30100. 0100. 0 Descriptive Statistics NSumStd. Deviation Roses3030. 000 Malaysian Mums3030. 000 Angel’s Breath3030. 000 Anthurium3018. 498 Birds Of Paradise307. 430 Tulips303. 305 Star Gazer3011. 490 Valid N (listwise)30 Anthurium FrequencyPercentValid PercentCumulative Percent ValidNot Available1240. 040. 040. 0 Available1860. 060. 0100. 0 Total30100. 0100. 0Estimated Sales during Peak and Dormant Season Frequencies Statistics Estimated Sales Peak SeasonEstimated Sales D ormant Season NValid3030 Missing00 Mean3. 903. 37 Median3. 003. 00 Std. Deviation1. 2691. 098 Range43 Minimum22 Maximum65 Frequency Table Estimated Sales Peak FrequencyPercentValid PercentCumulative Percent Valid10000 – 2999913. 33. 33. 3 30000 – 499991653. 353. 356. 7 50000 – 69999413. 313. 370. 0 70000 – 89999310. 010. 080. 0 90000 and above620. 020. 0100. 0 Total30100. 0100. 0 Estimated Sales Dormant FrequencyPercentValid PercentCumulative Percent Valid500 -999723. 323. 323. 3 1000 – 14991240. 040. 063. 3 1500 – 1999413. 313. 376. 7 000 and above723. 323. 3100. 0 Total30100. 0100. 0 Descriptive Statistics NRangeMinimumMaximumMeanStd. Deviation EstimatedSalesPeak304263. 901. 269 EstimatedSalesDormant303253. 371. 098 Valid N (listwise)30 Problems Encountered During Dormant Seasons Frequencies Statistics DP1DP2DP3DP4DP5DP6DP7DP8DP9DP10 NValid30303030303030303030 Missing0000000000 Mean2. 801. 873. 001. 602. 002. 503. 002. 271. 532. 00 Median3 . 002. 003. 002. 002. 002. 503. 002. 002. 002. 00 Mode323222a3222 Std. Deviation. 407. 434. 000. 498. 000. 509. 000. 640. 507. 000 Range1201010210 Minimum2131223112 Maximum3332233322 a. Multiple modes exist. The smallest value is shown Frequency TableDried Flowers (DP1) FrequencyPercentValid PercentCumulative Percent ValidSometimes620. 020. 020. 0 Always2480. 080. 0100. 0 Total30100. 0100. 0 Pests (DP2) FrequencyPercentValid PercentCumulative Percent ValidNever516. 716. 716. 7 Sometimes2480. 080. 096. 7 Always13. 33. 3100. 0 Total30100. 0100. 0 Few Customers (DP3) FrequencyPercentValid PercentCumulative Percent ValidAlways30100. 0100. 0100. 0 Delayed Deliveries of Ordered Flowers (DP4) FrequencyPercentValid PercentCumulative Percent ValidNever1240. 040. 040. 0 Sometimes1860. 060. 0100. 0 Total30100. 0100. 0 Unpaid Balances of Customers (DP5) FrequencyPercentValid PercentCumulative PercentValidSometimes30100. 0100. 0100. 0 Too many competitors (DP6) FrequencyPercentValid PercentCumul ative Percent ValidSometimes1550. 050. 050. 0 Always1550. 050. 0100. 0 Total30100. 0100. 0 Burdensome taxes (DP7) FrequencyPercentValid PercentCumulative Percent ValidAlways30100. 0100. 0100. 0 Lack of necessary equipment (DP8) FrequencyPercentValid PercentCumulative Percent ValidNever310. 010. 010. 0 Sometimes1653. 353. 363. 3 Always1136. 736. 7100. 0 Total30100. 0100. 0 Lack of stocked flowers (DP9) FrequencyPercentValid PercentCumulative Percent ValidNever1446. 746. 746. 7 Sometimes1653. 353. 3100. 0 Total30100. 0100. 0 Natural Calamities (DP10)FrequencyPercentValid PercentCumulative Percent ValidSometimes30100. 0100. 0100. 0 Descriptive Statistics NRangeMinimumMaximumMeanStd. Deviation DP1301232. 80. 407 DP2302131. 87. 434 DP3300333. 00. 000 DP4301121. 60. 498 DP5300222. 00. 000 DP6301232. 50. 509 DP7300333. 00. 000 DP8302132. 27. 640 DP9301121. 53. 507 DP10300222. 00. 000 Valid N (listwise)30 Means Case Processing Summary Cases IncludedExcludedTotal NPercentNPercentNPercent DP1 * DPCompMean30100. 0%0. 0%30100. 0% DP2 * DPCompMean30100. 0%0. 0%30100. 0% DP3 * DPCompMean30100. 0%0. 0%30100. 0% DP4 * DPCompMean30100. 0%0. 0%30100. 0% DP5 * DPCompMean30100. 0%0. 0%30100. 0% DP6 * DPCompMean30100. 0%0. 0%30100. 0%DP7 * DPCompMean30100. 0%0. 0%30100. 0% DP8 * DPCompMean30100. 0%0. 0%30100. 0% DP9 * DPCompMean30100. 0%0. 0%30100. 0% DP10 * DPCompMean30100. 0%0. 0%30100. 0% Report DPCompMeanDP1DP2DP3DP4DP5DP6DP7DP8DP9DP10 1. 89Mean2. 001. 003. 001. 002. 003. 003. 001. 001. 002. 00 N1111111111 Std. Deviation†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. 2. 00Mean2. 002. 003. 001. 002. 002. 003. 002. 001. 002. 00 N2222222222 Std. Deviation. 000. 000. 000. 000. 000. 000. 000. 000. 000. 000 2. 11Mean3. 001. 003. 001. 002. 002. 003. 002. 002. 002. 00 N1111111111 Std. Deviation†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. 2. 22Mean2. 891. 893. 001. 672. 002. 333. 001. 781. 442. 00 N9999999999 Std. Deviation. 333. 601. 000. 500. 000. 00. 000. 441. 527. 000 2. 33Mean2. 891. 893. 001. 442. 002. 563. 002. 561. 672. 00 N9999999999 Std. Deviation. 333. 333. 000. 527. 000. 527. 000. 527. 500. 000 2. 44Mean2. 882. 003. 002. 002. 002. 753. 002. 751. 632. 00 N8888888888 Std. Deviation. 354. 000. 000. 000. 000. 463. 000. 463. 518. 000 TotalMean2. 801. 873. 001. 602. 002. 503. 002. 271. 532. 00 N30303030303030303030 Std. Deviation. 407. 434. 000. 498. 000. 509. 000. 640. 507. 000 ANOVA Tablea,b,c,d Sum of SquaresdfMean Square DP1 * DPCompMeanBetween Groups(Combined)2. 1475. 429 Within Groups2. 65324. 111 Total4. 80029 DP2 * DPCompMeanBetween Groups(Combined)1. 6895. 338 Within Groups3. 7824. 157 Total5. 46729 DP4 * DPCompMeanBetween Groups(Combined)2. 9785. 596 Within Groups4. 22224. 176 Total7. 20029 DP6 * DPCompMeanBetween Groups(Combined)1. 7785. 356 Within Groups5. 72224. 238 Total7. 50029 DP8 * DPCompMeanBetween Groups(Combined)6. 58951. 318 Within Groups5. 27824. 220 Total11. 86729 DP9 * DPCompMeanBetween Groups(Combined)1. 3695. 274 Within Groups6. 09724. 254 Total7. 46729 a. No variance within gr oups – statistics for DP3 * DPCompMean cannot be computed. b. No variance within groups – statistics for DP5 * DPCompMean cannot be computed. c. No variance within groups – statistics for DP7 * DPCompMean cannot be computed. d.No variance within groups – statistics for DP10 * DPCompMean cannot be computed. ANOVA Tablea,b,c,d FSig. DP1 * DPCompMeanBetween Groups(Combined)3. 885. 010 DP2 * DPCompMeanBetween Groups(Combined)2. 146. 094 DP4 * DPCompMeanBetween Groups(Combined)3. 385. 019 DP6 * DPCompMeanBetween Groups(Combined)1. 491. 230 DP8 * DPCompMeanBetween Groups(Combined)5. 992. 001 DP9 * DPCompMeanBetween Groups(Combined)1. 078. 397 a. No variance within groups – statistics for DP3 * DPCompMean cannot be computed. b. No variance within groups – statistics for DP5 * DPCompMean cannot be computed. c. No variance within groups – statistics for DP7 * DPCompMean cannot be computed. d.No variance within groups – statistics for DP 10 * DPCompMean cannot be computed. Measures of Association EtaEta Squared DP1 * DPCompMean. 669. 447 DP2 * DPCompMean. 556. 309 DP4 * DPCompMean. 643. 414 DP6 * DPCompMean. 487. 237 DP8 * DPCompMean. 745. 555 DP9 * DPCompMean. 428. 183 Problems Encountered During Peak Seasons Frequencies Statistics PP1PP2PP3PP4PP5PP6PP7PP8PP9PP10 NValid30303030303030303030 Missing0000000000 Mean1. 301. 871. 001. 772. 002. 833. 002. 271. 872. 00 Median1. 002. 001. 002. 002. 003. 003. 002. 002. 002. 00 Mode1212233222 Std. Deviation. 466. 434. 000. 430. 000. 379. 000. 640. 346. 000 Range1201010210 Minimum1111223112 Maximum2312233322 Frequency Table Dried Flowers (PP1)FrequencyPercentValid PercentCumulative Percent ValidNever2170. 070. 070. 0 Sometimes930. 030. 0100. 0 Total30100. 0100. 0 Pests (PP2) FrequencyPercentValid PercentCumulative Percent ValidNever516. 716. 716. 7 Sometimes2480. 080. 096. 7 Always13. 33. 3100. 0 Total30100. 0100. 0 Few Customers (PP3) FrequencyPercentValid PercentCumulative P ercent ValidNever30100. 0100. 0100. 0 Delayed deliveries of ordered flowers (PP4) FrequencyPercentValid PercentCumulative Percent ValidNever723. 323. 323. 3 Sometimes2376. 776. 7100. 0 Total30100. 0100. 0 Unpaid balances of customers (PP5) FrequencyPercentValid PercentCumulative Percent ValidSometimes30100. 0100. 0100. 0 Too many competitors (PP6)FrequencyPercentValid PercentCumulative Percent ValidSometimes516. 716. 716. 7 Always2583. 383. 3100. 0 Total30100. 0100. 0 Burdensome taxes (PP7) FrequencyPercentValid PercentCumulative Percent ValidA;ways30100. 0100. 0100. 0 Lack of necessary equipment (PP8) FrequencyPercentValid PercentCumulative Percent ValidNever310. 010. 010. 0 Sometimes1653. 353. 363. 3 Always1136. 736. 7100. 0 Total30100. 0100. 0 Lack of stocked flowers (PP9) FrequencyPercentValid PercentCumulative Percent ValidNever413. 313. 313. 3 Sometimes2686. 786. 7100. 0 Total30100. 0100. 0 Natural Calamities (PP10) FrequencyPercentValid PercentCumulative Percent ValidSometime s30100. 0100. 0100. 0Case Processing Summary Cases IncludedExcludedTotal NPercentNPercentNPercent PP1 * PPCompMean30100. 0%0. 0%30100. 0% PP2 * PPCompMean30100. 0%0. 0%30100. 0% PP3 * PPCompMean30100. 0%0. 0%30100. 0% PP4 * PPCompMean30100. 0%0. 0%30100. 0% PP5 * PPCompMean30100. 0%0. 0%30100. 0% PP6 * PPCompMean30100. 0%0. 0%30100. 0% PP7 * PPCompMean30100. 0%0. 0%30100. 0% PP8 * PPCompMean30100. 0%0. 0%30100. 0% PP9 * PPCompMean30100. 0%0. 0%30100. 0% PP10 * PPCompMean30100. 0%0. 0%30100. 0% Report PPCompMeanPP1PP2PP3PP4PP5PP6PP7PP8PP9PP10 1. 70Mean1. 001. 001. 001. 002. 003. 003. 001. 002. 002. 00 N1111111111 Std. Deviation†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. 1. 80Mean1. 001. 001. 01. 002. 003. 003. 002. 002. 002. 00 N1111111111 Std. Deviation†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. 1. 90Mean1. 251. 751. 001. 502. 002. 883. 001. 881. 752. 00 N8888888888 Std. Deviation. 463. 463. 000. 535. 000. 354. 000. 641. 463. 000 2. 00Mean1. 181. 911. 002. 002. 002. 733. 002. 361. 822. 00 N11111111111111111111 Std. Deviatio n. 405. 302. 000. 000. 000. 467. 000. 505. 405. 000 2. 10Mean1. 502. 131. 001. 882. 002. 873. 002. 632. 002. 00 N8888888888 Std. Deviation. 535. 354. 000. 354. 000. 354. 000. 518. 000. 000 2. 20Mean2. 002. 001. 002. 002. 003. 003. 003. 002. 002. 00 N1111111111 Std. Deviation†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. TotalMean1. 301. 871. 001. 772. 002. 833. 002. 271. 872. 00N30303030303030303030 Std. Deviation. 466. 434. 000. 430. 000. 379. 000. 640. 346. 000 ANOVA Tablea,b,c,d Sum of SquaresdfMean Square PP1 * PPCompMeanBetween Groups(Combined)1. 1645. 233 Within Groups5. 13624. 214 Total6. 30029 PP2 * PPCompMeanBetween Groups(Combined)2. 1835. 437 Within Groups3. 28424. 137 Total5. 46729 PP4 * PPCompMeanBetween Groups(Combined)2. 4925. 498 Within Groups2. 87524. 120 Total5. 36729 PP6 * PPCompMeanBetween Groups(Combined). 2355. 047 Within Groups3. 93224. 164 Total4. 16729 PP8 * PPCompMeanBetween Groups(Combined)4. 5715. 914 Within Groups7. 29524. 304 Total11. 86729 PP9 * PPCompMeanBetween Groups(Combi ned). 3305. 066Within Groups3. 13624. 131 Total3. 46729 a. No variance within groups – statistics for PP3 * PPCompMean cannot be computed. b. No variance within groups – statistics for PP5 * PPCompMean cannot be computed. c. No variance within groups – statistics for PP7 * PPCompMean cannot be computed. d. No variance within groups – statistics for PP10 * PPCompMean cannot be computed. ANOVA Tablea,b,c,d FSig. PP1 * PPCompMeanBetween Groups(Combined)1. 087. 393 PP2 * PPCompMeanBetween Groups(Combined)3. 190. 024 PP4 * PPCompMeanBetween Groups(Combined)4. 160. 007 PP6 * PPCompMeanBetween Groups(Combined). 287. 916 PP8 * PPCompMeanBetween Groups(Combined)3. 008. 30 PP9 * PPCompMeanBetween Groups(Combined). 506. 769 a. No variance within groups – statistics for PP3 * PPCompMean cannot be computed. b. No variance within groups – statistics for PP5 * PPCompMean cannot be computed. c. No variance within groups – statistics for PP7 * PPCompM ean cannot be computed. d. No variance within groups – statistics for PP10 * PPCompMean cannot be computed. Measures of Association EtaEta Squared PP1 * PPCompMean. 430. 185 PP2 * PPCompMean. 632. 399 PP4 * PPCompMean. 681. 464 PP6 * PPCompMean. 237. 056 PP8 * PPCompMean. 621. 385 PP9 * PPCompMean. 309. 095 Statements Frequencies Statistics S1S2S3S4S5 NValid3030303030Missing00000 Mean2. 533. 773. 003. 772. 40 Median3. 004. 003. 004. 002. 00 Mode34342 Std. Deviation. 507. 430. 695. 430. 621 Range11212 Minimum23232 Maximum34444 Frequency Table It is better to sold flowers on peak seasons only (S1) FrequencyPercentValid PercentCumulative Percent ValidAgree1446. 746. 746. 7 Strongly Agree1653. 353. 3100. 0 Total30100. 0100. 0 Customers are seem satisfied in your services and flowers (S2) FrequencyPercentValid PercentCumulative Percent ValidAgree723. 323. 323. 3 Strongly Agree2376. 776. 7100. 0 Total30100. 0100. 0 Total sales of flowers depends on business’ luck (S3) Freque ncyPercentValid PercentCumulative PercentValidDisagree723. 323. 323. 3 Agree1653. 353. 376. 7 Strongly Disagree723. 323. 3100. 0 Total30100. 0100. 0 Flowers are important part of an occasion (S4) FrequencyPercentValid PercentCumulative Percent ValidAgree723. 323. 323. 3 Strongly Agree2376. 776. 7100. 0 Total30100. 0100. 0 Flower shop business is an in demand business anytime (S5) FrequencyPercentValid PercentCumulative Percent ValidDisagree2066. 766. 766. 7 Agree826. 726. 793. 3 Strongly Agree26. 76. 7100. 0 Total30100. 0100. 0 Means Case Processing Summary Cases IncludedExcludedTotal NPercentNPercentNPercent S1 * SSCompMean30100. 0%0. 0%30100. 0% S2 * SSCompMean30100. 0%0. 0%30100. 0%S3 * SSCompMean30100. 0%0. 0%30100. 0% S4 * SSCompMean30100. 0%0. 0%30100. 0% S5 * SSCompMean30100. 0%0. 0%30100. 0% Report SSCompMeanS1S2S3S4S5 2. 60Mean2. 003. 003. 003. 002. 00 N11111 Std. Deviation†¦.. 2. 80Mean2. 503. 502. 253. 502. 25 N44444 Std. Deviation. 577. 577. 500. 577. 500 3. 00Mean2 . 503. 672. 753. 832. 25 N1212121212 Std. Deviation. 522. 492. 622. 389. 452 3. 20Mean2. 574. 003. 293. 862. 29 N77777 Std. Deviation. 535. 000. 488. 378. 488 3. 40Mean2. 604. 003. 803. 802. 80 N55555 Std. Deviation. 548. 000. 447. 447. 837 3. 60Mean3. 004. 003. 004. 004. 00 N11111 Std. Deviation†¦.. TotalMean2. 533. 773. 003. 772. 40 N3030303030 Std.Deviation. 507. 430. 695. 430. 621 ANOVA Table Sum of SquaresDfMean Square S1 * SSCompMeanBetween Groups(Combined). 5525. 110 Within Groups6. 91424. 288 Total7. 46729 S2 * SSCompMeanBetween Groups(Combined)1. 7005. 340 Within Groups3. 66724. 153 Total5. 36729 S3 * SSCompMeanBetween Groups(Combined)6. 77151. 354 Within Groups7. 22924. 301 Total14. 00029 S4 * SSCompMeanBetween Groups(Combined)1. 0435. 209 Within Groups4. 32424. 180 Total5. 36729 S5 * SSCompMeanBetween Groups(Combined)3. 9715. 794 Within Groups7. 22924. 301 Total11. 20029 ANOVA Table FSig. S1 * SSCompMeanBetween Groups(Combined). 383. 855 S2 * SSCompMeanBetween Groups (Combined)2. 25. 085 S3 * SSCompMeanBetween Groups(Combined)4. 496. 005 S4 * SSCompMeanBetween Groups(Combined)1. 158. 358 S5 * SSCompMeanBetween Groups(Combined)2. 637. 049 Measures of Association EtaEta Squared S1 * SSCompMean. 272. 074 S2 * SSCompMean. 563. 317 S3 * SSCompMean. 695. 484 S4 * SSCompMean. 441. 194 S5 * SSCompMean. 595. 355 Results and Discussion Table1. Frequency Distribution of Respondents’ Profile Variables Profile VariablesFrequencyPercentageRank Type of BusinessSole Propreitorship301001 Corporation003 Patrtnership003 Others003 Total30100 Area of BusinessAlong the public market723. 32 Other Commercial Area2273. 31 Residential Area13. 33Others004 Total30100 Number of Workers11136. 71. 5 21136. 71. 5 3620. 02 426. 73 Total30100 Years of Existence1-5 years1343. 31 6-10 years516. 72. 5 11-15 years413. 34 16-20 years516. 72. 5 Above 20 years310. 05 Total30100 The purpose of the study is to determine the profile variables of flower shops and compare the net sal es during the seasons with low and high demand for flowers. The researcher conducted a survey in selected areas in Lipa City and Batangas City where flower shops are situated. All florist that the researcher have questioned, indicated that their business is only owned by one. All have a Sole Proprietorship type of business.After further asking, the researcher found out that it is better to have that type of business to lessen the liability to government, like taxes. As to the area of business, mostly our situated not along the public market but to other commercial area where people can see them easily. In Lipa City, only few shops are in the public market, but many are located in Mataas na Lupa near Robinsons. In Batangas City, most flower shops are seen on Plaza Mabini near Saint Bridget’s College. The result of the survey indicates that 7 out of 30 flower shops are located in public market, 22 are on other commercial area and only 1 was seen on a residential area. Shops are near each other therefore resulting to a tight competitive environment.The survey shows that most shops have only 1 or 2 workers/florist on it. 11 shops have 1 worker only as well as 2 workers. 6 shops have 3 workers and 4 shops have 4 workers. Meaning, 36. 7% prefer lower number of workers. This shows that owners are decreasing the numbers of workers to decrease the expense monthly. Few shops exist in a long time like above 20 years. 43. 3 % of surveyed shops are existing in 1-5 years already. They weren’t be existing in that long time if the business is always incurring loses, therefore despite the dormant and peak seasons, they still have a return on their capital . Table2. Frequency Distribution of Available FlowersFlowersFrequencyPercentageRank Roses30100%2 Malaysian Mums30100%2 Angel's Breath30100%2 Anthurium1823. 30%4 Birds of Paradise760%6 Tulips310%7 Star Gazer1136. 70%5 Most flower shops do not store many flowers. They only order what the customer demanded to them. The survey only indicated those flowers readily available in the flower shops at the time the researcher conducted the interview. All shops have the Malaysian Mums available. These are the flowers that are cheap but still possess beauty if arrange in a nice manner. These are mostly use for funeral purposes which are mostly demanded in a normal day. Roses and Angel’s breath are also available on all shops.Only 7 shops have available birds of paradise, 18 shops have anthurium, 11 shops have Star gazer, and only 3 shops have Tulips in them. These flowers are not only the flowers being sold. They are only the flowers being offered on a typical flower shops that the researcher have interviewed. Clearly stated in the graph G-4 and G-5 that the business is highly profitable during peak seasons like Valentine’s Day, All Souls Day, Mothers’ Day and any month when there is a public occasion. Most flower shops are having a profit of 30000 – 49999 pesos in a day dur ing those occasions. Unlike during a normal day 1000 – 1999 pesos only is the amount of their sales.After further questioning, the researcher found out that there are days that a shop has no sales at all during the few-demand-of-flowers seasons. Few demand seasons include months of June, July, August and September. Exuberant flower arrangements enliven all the meaningful celebration in our annual calendar. Therefore in those seasons flowers are greatly in demand resulting to very high sales on all flower shop business. There are shops which have sales up to 100000 pesos, the reason why more and more people are attracted to engage on this kind of business. Table3. Computed Mean and Verbal Interpretation of Problems Experienced ProblemsDormantPeakMeanVerbal InterpretationRankMeanVerbal InterpretationRank Dried flowers2. 80Always31. 30Never9 Pests1. 87Sometimes91. 87Sometimes6. 5 Few customers3. 00Always1. 51. 00Never10 Delayed Deliveries of ordered flowers1. 60Sometimes101. 77S ometimes8 Unpaid balances of customers2. 00Sometimes7. 52. 00Sometimes4. 5 Too many competitors2. 50Always52. 83Always2 Burdensome taxes3. 00Always1. 53. 00Always1 Lack of necessary equipment2. 27Sometimes62. 27Sometimes3 Lack of stocked flowers2. 53Always41. 87Sometimes6. 5 Natural Calamities2. 00Sometimes7. 52. 00Sometimes4. 5 Like any other business, Flower shops are often experiencing problems with regards to their operations.For the purpose of this research, the researcher decided to divide it to problems relating to peak seasons and dormant seasons. During dormant seasons, the mean for the problem of dried flowers is 2. 80. It means that they are always experiencing this problem during dormant season but during peak the mean is only 1. 3 meaning most or almost all flower shops do not encounter this kind of situation. The problem with Pest, having the same mean of 1. 87 during dormant and peak season is sometimes experience in whatever season it may be. Technologies are advanci ng therefore they have found a way to eliminate pests in their flowers. There are also days when the business have a few customers.This is true during dormant season having a mean of 3. 00. Dormant seasons are days when there is only little demand on a certain products, therefore on those days few people are going to flower shops to buy flowers. But at peak seasons, many consumers are craving for flowers resulting to a mean of 1, meaning the problem of â€Å"few customers† is never experience during peak season. . Taxes are part of a business. Therefore businessman and woman consider this as one of the major problems of an entrepreneur. Having a mean of 3. 00 in the survey for both seasons, it is therefore an all-year problem of these businesses as well as too many competitors.Delayed deliveries of ordered flowers, unpaid balances of customers, lack of necessary equipment and natural calamities are sometimes experience by the shops in whatever season it may be. Table4. Weight ed Mean Distribution on the Perception of the Owners as regards to Flower Shop Business StatementsMeanVerbal InterpretationRank It is better to sold flowers on Peak Seasons only2. 53Agree4 Customers are seem satisfied in your services and flowers3. 77Strongly Agree1. 5 Total sales each day depends on the business’ luck3. 00Agree3 Flowers are important part of an occasion3. 77Strongly Agree1. 5 Flower shop business is an in-demand business anytime2. 40Agree5 Most of the respondents agree on selling flowers only on seasons when it is in demand, 16 respondents strongly agree on this statement.Most of the shops are confident enough that their customers are satisfied in what they are offering. Belief in luck also affects the managerial skills of an entrepreneur. In the said survey, 16 respondents agree that the sales of a business depend on luck, but still 7 respondents disagree and 7 strongly disagree having a total of 14 disagreements. One must not only depend on luck for a busi ness to be successful. A manager must do something to increase the sales and make his business highly profitable having the capability to overcome different problems. With proper plan and strategies, business will bloom and will be returning one’s investment. Table5.Relationship between the Respondents’ Profile Variable and their Perception of as regards to Internet Cafe Business Profile VariableEtaEta SquaredP-ValueVerbal Interpretation Area Of Business 0. 7430. 5530. 015Not Significant Number Of Workers0. 7840. 6150. 004Not Significant Years Of Existence0. 8660. 750. 000Not Significant Suppliers’ Place 0. 5750. 330. 299Not Significant Table 3 displays the relationship between the respondents’ profile variable and their perception of as regards to Internet cafe business Review of Related Literature History The flower is the most perfect and fragile work of art given to us (Maia, 2008). It is a natural beauty and art. Flowers have been used for centuries as decoration, personal adornment, or for religious significance.Ancient Egyptians used flowers to honor their many gods and goddesses. Flowers were arranged in low bowls in an orderly, repetitious pattern-flower, bud, foliage, and so on. Special spouted vases were also used to hold flowers. Lotus flowers, also called water lilies, were Egyptian favorites. They came to symbolize sacredness and were associated with Isis, the Egyptian nature goddess. Flowers were sometimes used as decorations for the body, collar, and hair. Flowers were fashioned into elaborate wreaths and garlands by the ancient Greeks. The best wreath makers were often commissioned by wealthy Greeks to make wreaths for gifts, awards, or decoration.Chaplets, special wreaths for the head, were especially popular. Cornucopia, a horn-shaped container still used today, was filled with arrangements of flowers, fruits, and vegetables. Flowers arranged into wreaths and garlands were also popular in ancient Rome and well thr ough to the Middle Ages. The Victorian era saw great developments in the art of floral design. There was enormous enthusiasm for flowers, plants, and gardens; the most cultured young ladies were often schooled in the art of flower arrangement. Rules were first established regarding function and design. Magazines and books about floral arrangement were also published during this time.Proper Victorian ladies often had fresh nosegays, or tussie-mussies, a hand-held arrangement of tightly knotted flowers, for sentimental reasons, if not to freshen the air. Posy holders, fancy carriers for these small floral arrangements, came into fashion. Some were made of ivory, glass, or mother-of-pearl, and were elaborately decorated with jewels or etchings. Flowers were also made into small arrangements and tucked into a lady's decol-letage inside aptly named containers, bosom bottles. Ikebana, the Japanese art of floral arrangement since the sixth century, has been a principal influence on formal flower arrangement design. Its popularity still continues today.In the 1950s, free-form expression developed, incorporating pieces of driftwood and figurines within arrangements of flowers and live plants. Floral traditions of the past still have an impact on us today. It is still fashionable to mark special occasions with flowers, be it an anniversary, wedding, or birthday. People continue to use flowers to commemorate the dead. Today's floral arrangements reflect current styles, trends, and tastes. The best floral designers will follow the developing fashions and creatively adapt them to their arrangements. Business Through generation people have found a way to make this a source of livelihood. One does not have to be an artist to enjoy flowers (Tozer, 2009). Flower arrangements are in demand on certain seasons.The usual sources for flowers include florists shops, supermarket, corner grocery stores, farmers’ markets, roadside stands, greenhouses, mail-order catalogues, and your own or friend’s garden. Wholesale florists sell bulk flowers and related supplies to professionals in the trade. Floristry can involve the cultivation of flowers as well as their arrangement, and to the business of selling them. Much of the raw material supplied for the floristry trade comes from the cut flower industry. Florist shops, along with online stores are the main flower-only outlets, but supermarkets, garden supply stores and filling stations also sell flowers. The floristry business has a significant market in the corporate and social event world, as flowers play a large part in the decor of special events and meetings.Centerpieces, entryways, reception tables, bridal bouquets, wedding chuppahs and stage sets are only a few examples of how flowers are used in the business and social event settings. Flower Shops are wide-spreading in the Philippines. They can be seen along the public market and other commercial areas. Flowers for sale on those shops mostly come s from Baguio City, Davao City, Tagaytay City, Cotabato City and Laguna having a climate suitable for cultivating flowers. The trading post for all these flowers is situated near Dangwa Bus Terminal. The place is called Dimasalang Wholesale Flower Market which is most commonly called as Dangwa Wholesale Market (Asuncion, 2008). Large importers of flowers have set-up shop here as this has simply become the recognized epicenter of flowers in Metro Manila.