The firm of Mullin & Lonergan Associates, Inc. (M&L) was retained as consultants to conduct the Housing MarketAnalysis (HMA). M&L utilized a comprehensive approach to prepare the HMA involving the specific neighborhoods within the City of Erie. Data included in this report has been gathered from a variety of statistical sources and interviews. Statistical information from the U.S. Census Bureau’s Decennial Census (1990, 2000, and 2010) and 2006-2010 American Community Survey (ACS) Five-Year Estimates has been collected, organized, and analyzed. Workforce and employment data from the Economic Research Institute was also utilized and analyzed. In addition, data on household projections by income and age of householders, including 2010 current year estimates and 2015 projections, were acquired from the Environmental Systems Research Institute (ESRI) and was analyzed as part of this report.
First Nations Oweesta Corporation (Oweesta) conducted an in-depth marketanalysis on behalf of the Utah Division of Indian Affairs and the Utah Indian Housing Council. The Utah Indian housing Council is an economic development organization looking at creating a Community Development Financial Institution (CDFI) created to serve the Native communities of the state of Utah. The CDFI plans to provide housing financing and related development services to tribal and community members living on or near one of the seven Reservations of Utah: Utah Paiute, Utah Navajo, Ute Mountain Utes, Northern Ute and Ouray, Northwestern Band of the Shoshone Nation, Skull Valley Goshutes, Confederated Tribes of the Goshute Indians, and 10,000 -20,000 Native Americans in the Salt Lake metropolitan area. The purpose of the MarketAnalysis is to understand what need and demand may exist for housing financing and services for the Native Reservations in the state of Utah.
The provincial government and the tourism industry regularly conduct studies that identify numbers, nationalities, demographics and activities and interests of tourists, plus overall trends. Most tourism studies not only look at the international market, they also examine the national, provincial, regional and local markets. The gathering of local information means that even if any of the parks in the David Thompson Corridor are not likely currently or in the future to become a major international or national tourist destination, tourism information can still be a source of detailed data about local repeat visitors to these parks. Tourism research results must be consulted regularly by interpretation and education staff.
Enterprises of all sizes are increasingly embracing the Cloud-based service model because it provides them with agility, self-service, on-demand access to a much richer range of services and applications at a lower cost than was traditionally available. One of the primary components of the overall Cloud-based services market is the Infrastructure-as-a-Service (IaaS) market. According to Gartner 1 , the Cloud-based IaaS market will reach USD 10.5 billion in 2014. The initial set of IaaS solutions that were brought to market by Cloud Service Providers (CSPs) were the basic compute and storage services that are necessary to run applications. However, the IaaS market is highly dynamic and IaaS providers are deploying myriad new services including:
Uncertainty and attitudes to it are not the only reasons why neoclassical predictions may fail. Shiller (2003) highlights that market participants are humans and can make irrational systematic errors contrary to the assumption of rationality. Such errors affect prices and returns of assets, creating market inefficiencies. Studies in behavioral economics highlight inefficiencies, such as under- or over-reactions to information, as causes of market trends and, in extreme cases, of bubbles and crashes. Such reactions have been attributed to limited investor attention, overconfidence, mimicry and noise trading, explanations of many of which find roots in Kahneman and Tversky’s (1979) prospect theory, which postulates that decision makers evaluate outcomes from the perspective of their current endowment (and are predominantly loss-averse) and “revise” probabilities of outcomes when making decisions (predominantly overweighting probabilities of bad outcomes and underweighting those of good ones). The loss-aversion led Shefrin and Statman (1985) to formulate the ‘disposition effect’ in investment decisions: investors in traditional assets tend to keep assets that lose value too long and sell those that gain in value too early.
Competition within the city living market has intensified in recent years. In the more mature markets of Canary Wharf, Manchester and Birmingham developers have long appreciated the need to differentiate their production stand out from other attractive developments. Building high provides an obvious method of attracting attention to development. In addition to the creation of impact for marketing purposes, building high also has a fundamental benefit to the developer. It provides the potential for a higher return. However, this is a complex issue. The viability of any development depends primarily on an assessment of cost versus revenue. The particular issue relating to high rise buildings is that the relationship becomes increasingly complex as ever higher buildings are considered. As the height of buildings increase so does the cost of construction. However, at the same time there is recognisable potential in uplift in sales price from units on upper floors. This is especially the case in iconic or well designed buildings.
The best approach to advertising is to think of it in terms of media and which media will be most effective in reaching the target market. Then an advertising budget can be allocated to each medium. The advertising budget should include not only the cost of the advertising but also projections about how much business the advertising will bring in. Advertising media options include the Internet—Web sites, blogs, Facebook, YouTube, and Twitter; television; radio; newspapers; magazines; telephone books/directories; billboards; bench/bus/subway ads; direct mail; newsletters; and cooperative advertising with wholesalers, retailers, or other businesses. Some low cost product promotion alternatives are point-of-purchase displays, demonstrations, coupons, rebates, frequent-buyer clubs, publicity, and samples. Every business should also include some marketing material such as business cards, brochures, and pamphlets. Another avenue for promotion is free publicity, such as press releases, product launches, special events, including community involvement (e.g., America in Bloom), articles, and use of testimonials. Tradeshows can be an incredibly effective promotion and sales opportunity—if a firm attends the show that attracts its target customers and the promotion plan is in place.
The telemedicine market is segmented into tele hospital and tele home markets . The tele hospital market was worth $6.9 billion and tele home market was valued at nearly $2.9 billion, however the tele home segment is growing faster than the tele hospital segment at a projected CAGR of 22.5% vs. 16.8%
In a financially volatile market, as the stock market, it is important to have a very precise prediction of a future trend. Because of the financial crisis and scoring profits, it is mandatory to have a secure prediction of the values of the stocks. Stock Market Prediction is the act of trying to determine the future value of a company stock or other financial entity traded on an exchange. The successful prediction of stock’s future price could yield significant profit.
• Other operating costs • Distribution expenses across multiple locations • Sales and marketing strategy • Allowing co-branding to reduce marketing expenses • Comparable market multiples • Water problem pushes higher public market multiples • Synergies to potential buyers • Opportunities to integrate product with other solutions drives
The childrenswear market fits into Gereffi’s Apparel Value Chain model (1994) with modifications to the production, export and marketing networks. The push-pull marketing dynamics to show the collaborative and continuous relationship that exists among members of the same marketing network and between networks were visualized in this model by changing the one-way arrows to two-way arrows. A new two-way arrow was inserted between brand-named apparel companies and the discount chain, as a result of the high percentage of branded offerings in the discount channel noted in this study. One way arrows were changes to two-way arrows from the export networks the production networks to represent the various sourcing strategies identified in this study. A link was removed from the US garment factories to the department stores. It is understood that the link may have existed due to the past direct relationship, bypassing the export networks that existed with US garment factories and department stores. Brands were added as a layering component of the export and marketing networks.
The commercial segment consists primarily of individual travelers who are visiting Abilene for business purposes. This segment also consists of government demand and it is strongest Monday through Thursday, declines significantly on Friday and Saturday, and increases minimally on Sunday. The typical length of stay for commercial guests ranges from one to three days, and the rate of double occupancy is a low 1.2 to 1.3 people per room. Corporate travel in the DMA is generated by a variety of corporations several with sizable operations in Abilene. Examples include companies such as Broadwind Energy, Lauren Engineers & Construction and Siemens Energy Inc. to name a few. Furthermore, downtown Abilene hosts over 700 businesses and 6,000 employees according to City records all of which generate corporate transient demand that is estimated to be captured by the Proposed Hotel. This segment represents the largest source of business for local hotels accounting for approximately 50 percent of their market mix.
Daytona‟s trade area population includes a wide range of desirable population segments including active seniors, empty nesters and young families. The market is divided into specific subcategories and includes 16,000 “Senior Sun Seekers” whom are generally health-conscious watch cable television, read boating magazines and eat at family restaurants and steak houses. Approximately 23,000 or 20 percent of Daytona‟s trade area‟s population is classified as “Silver and Golds”. These seniors are well educated and financially prosperous. They drink imported wines, tend to own common stock, shop at Publix grocery stores order from the L.L. Bean, Eddie Bauer, and Land‟s End catalogs. They purchase golf clothing, go to the beach and dine out at least once a week. They go sailing, power boating, fishing and golfing and have taken an overseas cruise vacation.
HomeHealers offers homeowners a complete and thorough assessment of their home’s energy systems. The assessment provides the customer with a detailed energy systems analysis as well as a list of recommendations to substantially decrease energy use in their home. HomeHealers customers save significant money each month due to reduced energy costs.
Although the market is perceived to have grown substantially over the last twenty years (Westerhausen and Macbeth, 2003) it is difficult to quantify this in many destinations because backpackers are often not differentiated within visitor surveys. A potentially good indicator are occupancy figures from hostels (Keeley, 1995; Speed, & Harrison, 1999) whilst another way would be to take as a benchmark the figures from the tourist statistics of a country which does differentiate, for example, Australia, though due consideration would need to be given to the popularity of such countries. An alternative approach is to analyse the supply side; for example, the evident increase in the supply of products orientated to backbackers e.g. The Lonely Planet guides (Suvantola, 2002), and the establishment of backpacker routes in evidence in Australia and India (Scheyvens, 2002). We can also identify a growth in the provision of inexpensive accommodation in popular areas; Bali in 1977 had 14 such places, by 1994 this had increased to 34 places (Suvantola, 2002). The hostel market, in particular, has grown significantly and is no longer dominated by the International Youth Hostel Federation. Transport has also been a contributory factor. The introduction of Inter Rail passes in the 1970s facilitated backpacker travel across Europe at discounted rates. Similarly a number of bus/coach operators now have dedicated ticketing arrangements for backpackers which allow unlimited travel within certain areas or specified time frames (for example, National Express in Britain, Greyhound in the USA and Canada, and Greyhound Pioneer in Australia). In total, these developments bear witness to increased demand and lead to speculation that a degree of `institutionalisation' is developing.
Adoptive association rule is a method of market basket analysis based on faster rule generation algorithm. This method proposed by  was used in mining multi- measurement rule, depending on Adaptive Genetic Algorithm (AGA) with crossover matrix and mutation matrix. Dynamic adaptive support Apriori (DAS Apriori) was also developed as a technique to compute the minimal help for obtaining class association rules.
However, Smith (1979) found that in general, the main criminological theories are able to account equally well for male and female crime. Moreover, 25 years after the Equal Pay and Pay Discrimination Acts (passed in December 1975), improvements in the position o f women both in the labour market and society more generally have taken place which mean that many o f these arguments are now outdated. Such changes include later age marriages, rising divorce rates and the rise of single mothers, which mean that many women are now the sole providers for families. Improvements in qualifications gained by females mean that females are now out performing males in terms o f educational attainment (Epstein et al 1998). Highly skilled women are now more represented in higher ranking occupations (Blau and Kahn 2000). As generations progress, these changes will be reinforced by parenting, which will render these criticisms even more out o f date.
low technological content, bad for the growth potential of the country. In particular, the lack of specialisation in high-tech industries tends to reduce the development prospects of the country. Through CMSA, static factors (i.e. product and market effects) marginally contribute. The paper highlights that the initial structure of regional exports has a low effect in Emilia Romagna and Marche. In addition, for Veneto, the negative impact of the product effect is offset by the positive contribution of the market structure. In Lombardy, the opposite is true. In these cases, the dynamic effects assumes an important role. First, the competitiveness effect is strongly negative for Lombardy, while showing positive values for the other three regions. Secondly, there has been low ability to adapt exports to the global demand for Emilia Romagna, Lombardy and Marche; only Veneto shows a positive value of this component. Finally, Bentivoglio and Quintiliani (2004) show that at the end of the considered decade the structure of foreign trade of the four Italian regions continues to be dominated by the made in Italy and the low-tech commodities.
The problem of finding association rules using market basket analysis can be solved using the basic apriorialgorithm . But in applications like catalog design andcustomer segmentation the database used is very large. So, there is need of fastalgorithms for this task.Data mining finds interesting patterns from databases such as association rules, correlations, sequences,classifiers, clusters and many more of which the mining of association rules is one of the most popular problems. Association rule mining finds interesting association or correlation relationships among a large set of data items. Association rules are derived from the frequent item sets using support and confidence as threshold levels. The sets of items which have minimum support are known as Frequent Item set. The support of an item set is defined as the proportion of transactions in the data set which contain the item set. Confidence is defined as the measure of certainty or trustworthiness associated with each discovered pattern. Association rules derived depends on confidence. Frequent item set generation is done using data mining algorithms like Apriori , FP-Growth Algorithm, Eclat  and K-Apriori . Apriori algorithm for frequent item set mining is given below.