The recommendations to buy a multifamily property in leading multifamily real estate locations in the United States in 2024 were significantly higher than those to sell. According to 61 percent of the industry expert respondents, Jersey City was a good place to purchase a multifamily property in 2024. On the other hand, Pittsburg was city with the highest share of sell recommendations, at 33 percent.

As of 2024, three out of ten Latin American and Caribbean cities with the highest local purchasing power were located in Mexico. With an index score of 51.3, people in Querétaro had the highest domestic purchasing power in Mexico. In South America, the city with the highest domestic purchasing power for 2024 was Montevideo, scoring 53 index points.

Korea Jeonse to Purchase Price: Apartments: 6 Large Cities: Busan data was reported at 68.401 % in Jun 2018. This records an increase from the previous number of 68.391 % for May 2018. Korea Jeonse to Purchase Price: Apartments: 6 Large Cities: Busan data is updated monthly, averaging 67.790 % from Dec 1998 (Median) to Jun 2018, with 235 observations. The data reached an all-time high of 74.600 % in Apr 2002 and a record low of 56.000 % in Dec 1998. Korea Jeonse to Purchase Price: Apartments: 6 Large Cities: Busan data remains active status in CEIC and is reported by Kookmin Bank. The data is categorized under Global Database’s Korea – Table KR.EB036: Jeonse to Purchase Price Ratio.

Street food makes a significant contribution to the diet of many dwellers in low- and middle-income countries and its trade is a well-developed activity in the central Asian region. However, data on its purchase and nutritional value is still scarce. This study aimed to describe street food purchasing patterns in central Asia, according to time and place of purchase. A multicentre cross-sectional study was conducted in 2016/2017 in the main urban areas of four central Asian countries: Dushanbe (Tajikistan), Bishkek (Kyrgyzstan), Ashgabat (Turkmenistan) and Almaty (Kazakhstan). Street food markets (n = 34) and vending sites (n = 390) were selected by random and systematic sampling procedures. Data on the purchased foods and beverages were collected by direct observation. Time and geographic location of the purchases was registered, and their nutritional composition was estimated. A total of 714 customers, who bought 852 foods, were observed. Customers' influx, buying rate and purchase of industrial food were higher in city centers compared to the outskirts (median: 4.0 vs. 2.0 customers/10 min, p < 0.001; 5.0 vs. 2.0 food items/10 min, p < 0.001; 36.2 vs. 28.7%, p = 0.004). Tea, coffee, bread and savory pastries were most frequently purchased in the early morning, bread, main dishes and savory pastries during lunchtime, and industrial products in the mid-morning and mid-afternoon periods. Energy and macronutrient density was highest at 11:00–12:00 and lowest at 09:00–10:00. Purchases were smaller but more energy-dense in city centers, and higher in saturated and trans-fat in the peripheries. This work provides an overview of the street food buying habits in these cities, which in turn reflect local food culture. These findings from the main urban areas of four low- and middle-income countries which are currently under nutrition transition can be useful when designing public health interventions customized to the specificities of these food environments and their customers.

Korea Jeonse to Purchase Price: Apartments: 6 Large Cities data was reported at 73.175 % in Jun 2018. This records a decrease from the previous number of 73.256 % for May 2018. Korea Jeonse to Purchase Price: Apartments: 6 Large Cities data is updated monthly, averaging 66.754 % from Dec 1998 (Median) to Jun 2018, with 235 observations. The data reached an all-time high of 74.556 % in Apr 2017 and a record low of 52.901 % in Dec 1998. Korea Jeonse to Purchase Price: Apartments: 6 Large Cities data remains active status in CEIC and is reported by Kookmin Bank. The data is categorized under Global Database’s Korea – Table KR.EB036: Jeonse to Purchase Price Ratio.

According to a survey conducted in Japan in March 2024, the majority of respondents, 95.8 percent, reported purchasing fish and seafood at supermarkets, making them the most common places for such purchases. Fish specialty stores follow at a considerable distance, with 26.2 percent of respondents indicating that they buy from these establishments.

Korea Jeonse to Purchase Price: Apartments: 6 Large Cities: Daejon data was reported at 75.931 % in Jun 2018. This records an increase from the previous number of 75.921 % for May 2018. Korea Jeonse to Purchase Price: Apartments: 6 Large Cities: Daejon data is updated monthly, averaging 67.527 % from Dec 1998 (Median) to Jun 2018, with 235 observations. The data reached an all-time high of 77.800 % in Dec 2002 and a record low of 49.800 % in Dec 1998. Korea Jeonse to Purchase Price: Apartments: 6 Large Cities: Daejon data remains active status in CEIC and is reported by Kookmin Bank. The data is categorized under Global Database’s Korea – Table KR.EB036: Jeonse to Purchase Price Ratio.

Context

Nowadays, retail stores save a tremendous amount of data each day.this dataset contains historical purchase data for 5 different brand of chocolate.

Content

For the Segmentation file their is 8 columns ID a unique identifier for the customer.

Sex Biological sex (gender) of a customer. In this data set there are only 2 different options. male -->0 female -->1

Marital status Marital status of a customer.
single -->0 non-single (divorced / married) -->1

Age Integer The age of the customer

Education The level of education of the customer
other / unknown-->0 high school-->1 university-->2 graduate school-->3

Income annual income in US dollars of the customer.

Occupation Category of occupation of the customer. unemployed / unskilled -->0 skilled employee / official-->1 management / self-employed / highly qualified employee-->2

Settlement size The size of the city that the customer lives in.
small -->0 mid-sized city-->1 big city-->2

the purchase data set contains 17 columns ID: a unique identifier for the customer.

Day: Day when the customer has visited the store

Incidence: Purchase Incidence
customer has not purchased -->0 The customer has purchased -->1

Brand: Shows which brand the customer has purchased-->(1-5) No brand was purchased-->0

Quantity: Number of items bought by the customer

Last_Inc_Brand: Shows which brand the customer has purchased on their previous store visit-->(1-5) No brand was purchased-->0

Last_Inc_Quantity: Number of items bought by the customer from the product category of interest during their previous store visit

Price_1: Price of an item from Brand 1 on a particular day

Price_2: Price of an item from Brand 2 on a particular day

Price_3: Price of an item from Brand 3 on a particular day

Price_4: Price of an item from Brand 4 on a particular day

Price_5: Price of an item from Brand 5 on a particular day

Promotion_1: Indicator whether Brand 1 was on promotion or not on a particular day
There is no promotion-->0
There is promotion-->1

Promotion_2: Indicator of whether Brand 2 was on promotion or not on a particular day
There is no promotion-->0 There is promotion-->1

Promotion_3: Indicator of whether Brand 3 was on promotion or not on a particular day
There is no promotion-->0 There is promotion-->1

Promotion_4: Indicator of whether Brand 4 was on promotion or not on a particular day
There is no promotion-->0 There is promotion-->1

Promotion_5: categorical {0,1} Indicator of whether Brand 5 was on promotion or not on a particular day
There is no promotion-->0 There is promotion-->1

According to a survey conducted in August 2023 in Japan, the leading reason for purchases of used automobiles among city dwellers was to use it for shopping, while for people in rural areas it was to use it to commute to work or school. The survey showed significant discrepancies regarding the motivation for purchasing used cars depending on the area respondents lived in.

Brussels was the home of five Bitcoin ATMs as of June 2020, whereas Amsterdam had more than 20 of these cryptocurrency installations. In general, Bitcoin ATMs were to be found in the bigger cities of the two cities, but they also sporadically appeared in smaller cities. No recent data exists on the market size of Bitcoin in either Belgium or the Netherlands. In the first three quarters of 2017, there were approximately 44,000 transactions in Bitcoin from the Netherlands on a domestic trading platform called BTC Direct. This lack of market data has two reasons. First, the design of the digital currency (meant to provide privacy) makes it is difficult to trace. Second, Bitcoin did not reach the news in the two countries that often after 2017. Approximately 60 percent of the households in the Netherlands who invested in cryptocurrencies started doing so in that year. Data on cryptocurrencies in Belgium and the Netherlands therefore mostly stems from 2017 and 2018, not from 2019.

What can be said about cryptocurrencies in Belgium and the Netherlands?

According to a survey held in Belgium, Luxembourg and the Netherlands in early 2018, Dutch respondents had the highest cryptocurrency ownership. This could be any cryptocurrency, like Bitcoin but also Ethereum or Ripple. However, consumers from the Benelux region held much less blockchain-powered currencies than their European counterparts. Not only that, they also were less likely to buy into the trend of buying cryptocurrencies over time. This might have to do with the steep decline in Bitcoin prices by the time of the survey. The biggest reason for Dutch consumers to invest in the digital money was not because of technology or out of curiosity, but simply to earn money.

Who owns cryptocurrencies in the Netherlands?

Bitcoin was owned in roughly equal amounts by both male (69 percent) as well as female (65 percent) respondents to a 2018 survey in the Netherlands. Ethereum and Litecoin, however, were way more popular amongst male respondents. Women were overall less likely to invest in cryptocurrencies but did show an interest in coins like Ripple and TRON.

Property currently or historically owned and managed by the City of Chicago. Information provided in the database, or on the City’s website generally, should not be used as a substitute for title research, title evidence, title insurance, real estate tax exemption or payment status, environmental or geotechnical due diligence, or as a substitute for legal, accounting, real estate, business, tax or other professional advice. The City assumes no liability for any damages or loss of any kind that might arise from the reliance upon, use of, misuse of, or the inability to use the database or the City’s web site and the materials contained on the website. The City also assumes no liability for improper or incorrect use of materials or information contained on its website. All materials that appear in the database or on the City’s web site are distributed and transmitted "as is," without warranties of any kind, either express or implied as to the accuracy, reliability or completeness of any information, and subject to the terms and conditions stated in this disclaimer.

The following columns were added 4/14/2023:

• Sales Status
• Sale Offering Status
• Sale Offering Reason
• Square Footage - City Estimate
• Land Value (2022) -- Note: The year will change over time.

The following columns were added 3/19/2024:

• Application Use
• Grouped Parcels
• Application Deadline
• Offer Round
• Application URL

Ready-to-Move-in Luxury Homes Market Outlook

The global market size of ready-to-move-in luxury homes is projected to experience robust growth, with an estimated CAGR of 6.5% from 2024 to 2032. In 2023, the market size was valued at approximately $160 billion, and it is expected to reach around $285 billion by 2032. This surge in growth is primarily driven by increasing demand from high-net-worth individuals seeking immediate possession properties, as well as a burgeoning preference for luxury living spaces that offer convenience, exclusivity, and top-notch amenities. Urbanization and rising disposable incomes are also significant growth factors, as they enable more people to afford upscale housing options. Furthermore, as cities expand and develop, the need for premium housing that provides both luxury and immediate occupancy has become more pronounced.

One of the key growth factors for the ready-to-move-in luxury homes market is the shift in consumer behavior towards immediate gratification and convenience. Unlike traditional real estate investments that require buyers to wait for completion, ready-to-move-in properties allow purchasers to see exactly what they are buying, eliminating uncertainties associated with delays and potential discrepancies in the final product. This factor is increasingly appealing to discerning buyers who prioritize time savings and hassle-free transactions. Moreover, the pandemic has accelerated this trend as individuals now value having a secure, fully-furnished home that can serve as a sanctuary in uncertain times, thus driving demand for immediately available luxury properties.

The role of technological advancements in real estate is another pivotal growth factor in this market. The integration of smart home technologies and advanced security systems in luxury homes has heightened their appeal, providing affluent buyers with cutting-edge living experiences. Smart homes, equipped with automated systems for lighting, climate control, and security, enhance the convenience and sophistication of luxury properties. Additionally, these technologies offer energy efficiency and sustainability benefits, aligning with the growing consumer demand for green living spaces. Sellers and developers are leveraging these technologies to differentiate their offerings in an increasingly competitive market, thereby attracting a larger pool of potential buyers.

Furthermore, the global luxury real estate market is benefiting from an influx of foreign investment, particularly in regions with stable economic conditions and favorable investment climates. International buyers are drawn to ready-to-move-in luxury homes as they provide an opportunity to diversify their portfolios with tangible assets in prime locations. Tax incentives, investment-friendly policies, and the allure of a cosmopolitan lifestyle are compelling factors attracting overseas buyers. As a result, there is an increasing trend of cross-border property investments, particularly in metropolitan areas renowned for their luxury real estate markets, such as New York, London, and Singapore.

Regionally, the market dynamics are influenced by varying economic conditions and cultural preferences. In North America, the market is buoyed by a strong economy and a high concentration of affluent individuals seeking luxury properties as both primary and secondary residences. The Asia Pacific region, particularly China and India, is witnessing rapid urbanization and wealth accumulation, contributing significantly to the demand for luxury homes. Europe, with its rich cultural heritage and stable property markets, continues to attract international buyers, especially in cities like Paris and Berlin. Meanwhile, the Middle East & Africa region is capitalizing on its luxury tourism boom, with cities like Dubai becoming hotspots for high-end residential investments.

Property Type Analysis

Within the ready-to-move-in luxury homes market, the property type segment comprises apartments, villas, townhouses, and others. Each of these categories caters to diverse consumer preferences and lifestyle requirements. Apartments are often favored in densely populated urban areas where land is scarce, providing vertical living solutions with panoramic city views and convenient access to urban amenities. Luxury apartments often feature state-of-the-art facilities, including gyms, pools, and concierge services, appealing to buyers seeking a comprehensive living experience without the upkeep of standalone properties. As urban centers continue to grow, the demand for luxury apartments is expected to remain strong.

Villas, on t

The City of Galesburg has a number of lots which the City Council has determined are not necessary, appropriate or in the best interests of the City. These properties are offered for sale subject to conditions and restrictions on future use which the City may deem necessary and proper.The Request for Bid document includes two options for submitting a bid. The first option is a Development Plan bid. One example of this type of bid is using the city-owned property as additional yard area. The person submitting the bid must own the land that is adjacent to the vacant city-owned lot for a yard expansion. The purpose of the Development Plan bid is for the City to have more control over the proposed use of the property. The bidder submits detailed information on their plans for the property, which must take place within two years of purchasing the property. If the plan is not followed, the City has recourse by being able to take back ownership of the property from the bidder and the bidder forfeits 50% of their purchase price. A Development Plan bid option offers the City Council the ability to determine the best bid based upon the development proposed and not just the price.The second option is a No Development Plan bid. Using this option, a person can purchase a property without submitting plans for future redevelopment of the property. The bid document also includes a five-year reversion agreement for properties (i.e. if the City has to spend monies to fix a nuisance issue on a No Development Plan property during the first five years after ownership is transferred, the ownership of the property will revert back to the City).Sale of any of the properties would eliminate the need for City maintenance of the properties (i.e. weed mowing); and at the same time place the properties back on the property tax roll. Any proceeds from the sale are deposited in the Property Redevelopment Fund to allow continued funding for future foreclosures.

Korea Jeonse to Purchase Price: Apartments: 6 Large Cities: Gwangju data was reported at 75.647 % in Jun 2018. This records a decrease from the previous number of 76.087 % for May 2018. Korea Jeonse to Purchase Price: Apartments: 6 Large Cities: Gwangju data is updated monthly, averaging 74.053 % from Dec 1998 (Median) to Jun 2018, with 235 observations. The data reached an all-time high of 78.500 % in Sep 2014 and a record low of 58.200 % in Dec 1998. Korea Jeonse to Purchase Price: Apartments: 6 Large Cities: Gwangju data remains active status in CEIC and is reported by Kookmin Bank. The data is categorized under Global Database’s Korea – Table KR.EB036: Jeonse to Purchase Price Ratio.

Korea Jeonse to Purchase Price: Apartments: 6 Large Cities: Incheon data was reported at 75.792 % in Jun 2018. This records an increase from the previous number of 75.745 % for May 2018. Korea Jeonse to Purchase Price: Apartments: 6 Large Cities: Incheon data is updated monthly, averaging 57.596 % from Dec 1998 (Median) to Jun 2018, with 235 observations. The data reached an all-time high of 77.138 % in Jun 2017 and a record low of 41.867 % in Sep 2008. Korea Jeonse to Purchase Price: Apartments: 6 Large Cities: Incheon data remains active status in CEIC and is reported by Kookmin Bank. The data is categorized under Global Database’s Korea – Table KR.EB036: Jeonse to Purchase Price Ratio.

Contracts and modifications awarded by the City of Chicago since 1993. This data is currently maintained in the City’s Financial Management and Purchasing System (FMPS), which is used throughout the City for contract management and payment. Legacy System Records: Purchase Order/Contract Numbers that begin with alpha characters identify records imported from legacy systems. Records with a null value in the Contract Type field were imported from legacy systems. "Comptroller-Other" Contract Type: Some records where the Contract Type is "COMPTROLLER-OTHER" are ordinance-based agreements and may have start dates earlier than 1993. Depends Upon Requirements Contracts: If the contract Award Amount is $0, the contract is not cancelled, and the contract is a blanket contract, then the contract award total Depends Upon Requirements. A Depends Upon Requirements contract is an indefinite quantities contract in which the City places orders as needed and the vendor is not guaranteed any particular contract award amount.

Blanket vs. Standard Contracts: Only blanket contracts (contracts for repeated purchases) have FMPS end dates. Standard contracts (for example, construction contracts) terminate upon completion and acceptance of all deliverables. These dates are tracked outside of FMPS.

Negative Modifications: Some contracts are modified to delete scope and money from a contract. These reductions are indicated by negative numbers in the Award Amount field of this dataset.

Data Owner: Procurement Services. Time Period: 1993 to present. Frequency: Data is updated daily.

From December 2019 to July 2020, around 26.4 percent of the social media users from low-tier cities in China mentioned that they buy cosmetics and beauty products from live streaming, higher than the 21.5 percent among high-tier city residents. Meanwhile, around 2.6 percent of respondents from low-tier cities who bought beauty product online shopped via Kuaishou, a Chinese short video app.

The City of Cambridge owns and maintains most street lights in the City. These were purchased from NSTAR in 2005. Some street lights are owned by other organizations. DCR, the State, and Universities all own lights along the roadways they maintain. These are the locations of those lights. The Cambridge owned street lights are in the GIS layer INFRA_StreetLights. The origin of the lights are from an April 14, 2010 flyover. City of Cambridge, MA GIS basemap development project encompasses the land area of City of Cambridge with a 200 foot fringe surrounding the area and Charles River shoreline towards Boston. The basemap data was developed at 1" = 40' mapping scale using digital photogrammetric techniques. Planimetric features; both man-made and natural features like vegetation, rivers have been depicted. These features are important to all GIS/mapping applications and publication. A set of data layers such as Buildings, Roads, Rivers, Utility structures, 1 ft interval contours are developed and represented in the geodatabase. The features are labeled and coded in order to represent specific feature class for thematic representation and topology between the features is maintained for an accurate representation at the 1:40 mapping scale for both publication and analysis. The basemap data has been developed using procedures designed to produce data to the National Standard for Spatial Data Accuracy (NSSDA) and is intended for use at 1" = 40 ' mapping scale.THIS ONLY REFLECTS LIGHTS CAPTURED BY THE 2010 FLYOVER AND WAS NOT FIELD VERIFIEDExplore all our data on the Cambridge GIS Data Dictionary.Attributes NameType DetailsDescription ELEV type: Doublewidth: 8precision: 38 Elevation of top of street light above sea level

The Big Data in Smart Cities market is experiencing robust growth, driven by the increasing adoption of smart city initiatives globally. The market's expansion is fueled by the need for efficient urban management, improved public services, and enhanced citizen engagement. Governments and municipalities are increasingly leveraging big data analytics to optimize resource allocation, improve infrastructure planning, enhance public safety, and address environmental challenges. The integration of IoT devices, advanced analytics, and cloud computing technologies further accelerates this market growth. Key players like Cisco, IBM, and Microsoft are actively contributing to this expansion through the development of innovative data management and analytics solutions tailored for smart city applications. The market is segmented by deployment models (cloud, on-premise), data types (structured, unstructured), and application areas (traffic management, public safety, environmental monitoring). While the initial investment in infrastructure and data security can be a restraint, the long-term benefits of improved efficiency and citizen well-being are driving rapid adoption. The forecast period (2025-2033) anticipates continued significant expansion, as smart city initiatives gain wider acceptance and technological advancements continue to improve data processing and analytics capabilities. The competitive landscape is characterized by a mix of established technology vendors and specialized smart city solution providers. Strategic partnerships and mergers & acquisitions are likely to play a significant role in shaping the market dynamics. Regional variations in adoption rates are expected, with developed economies in North America and Europe leading the charge, while emerging economies in Asia-Pacific and Latin America are showing promising growth potential. Technological advancements in areas such as AI, machine learning, and edge computing will be critical drivers of future market expansion. Challenges remain, including data privacy concerns, interoperability issues, and the need for robust cybersecurity measures to ensure the secure management and analysis of sensitive urban data. However, the overall outlook for the Big Data in Smart Cities market remains highly positive, promising significant growth and transformation in urban environments globally.

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