Executive Summary

Due to the prime location, Venice was a center of trading and business, and nowadays it is one of the world’s most prominent tourist attractions. The economy of the historic city of Venice has gone through many changes throughout this time. In order to understand and see the economic health and trends of this historic area, WPI and the Venice Project Center set up the “shops” team to collect retail data and catalogue the economic landscape of Venice.

Since 2004, 7 different shops teams have collected data in different sesteries. This year, in 2018, the shops team will still do retail data collection and continue to capture a snapshot of the evolving storefronts. The objectives of the 2018 team are:

1. To collect data on types of retail in Venice accordance with standards used by previous teams.
2. To improve on the current web-based data visualization tool used by the center.
3. To analyze the changes and patterns in the retail sector over time and identify economic trends.

In order to understand Venice’s economy, the team did background research about residence and tourism. The retail sector is the reflection of demographic of local people because business and local customers are always interacting with each other. Since the 1970s, the local population of Venice has declined consistently; the population has fallen by one third since 1981.

The city is also aging: the average age of a Venetian has risen from 40.6 years to 48.3 years from 1971 to 2001. On the other hand, tourism has risen constantly over time, making it the major part of Venice’s economy. Since 1987, Venice has exceeded the recommended number of 15,000 residential tourists (i.e.tourists staying for at least one night) and 10,000 ‘day-trippers’, totaling a 25,000 per day capacity. This information is crucial for the team to consider while analyzing the economic trends of Venice.

The 2018 shops team chose the island of Giudecca and the sestiere of Cannaregio as the main focus of data collection. In the past 7 shops projects, VPC has never done data collection in the island of Giudecca, so the 2018 team chose to create a baseline of retail sector that future teams could use for analysis. Also, since there is past data on Cannaregio to serve as a baseline, the 2018 team decided to collect new data that could be compared to identify economic trends.

This project is mainly based on data collection, web-tool improvement, and data analysis. Firstly, the team will focus on collecting data on Venice’ retail as well as cleaning up past data. Previous teams stored their datasets in the City Knowledge App, which is the database for the VPC shops team.

In data collection this year, the team collected the following information of shops: shop names, addresses, districts, corporate ownership, ethnicity of ownership, years of opening and closing, and the modified NACE code. The team used paper and pen to do data collection, and later using photos to identify storefronts to cut down on time spent in the field.

Secondly, the team also developed a plan for improving the online visualization tool. The visualization website was created by 2015’s shops team to display the data points on the map. Since the website is inconsistent with the current VPC visual standards, the team decided to make the web-application look sleeker as well as to add features, and attempt to create a better user experience overall. Because the past data is stored in a way that is disjointed between years, the team also created a new database for storage of shops’ data. This new database is also able to track store conversions in the same locations throughout time.

Finally, in order to analyze the data we collect, the team looked at the openings of certain types of stores that have been collected this year to get a better understanding of the predominant economic types in a given area. The team used bar/ pie charts to analyze the economic activity type, amount of opening, corporate owned type as well as the target customers types to see the change over time for determining our conclusion.

The majority of stores on Giudecca are food-based retail (40.3%). In addition, 21% of stores are lodging-based retail, 12.9% are service-based retail, and 25.8% are goods-based retail.

In a similar way, the team was able to observe the target demographics that each store attempted to market toward. 39.1% of stores on Giudecca seemed to market toward tourists, whereas 26% of stores seemed to cater to residents. 34.4% were classified as “Mixed” , which means that a store had no obvious target market in either direction.

The team also made pie chart for the data collected from Cannaregio. The top classification for Cannaregio sestiere are bar (10%), restaurant (8.6%), and souvenir stores (6.7%).

The group also collected data on the target market of stores in Cannaregio. The majority, 40.7%, were found to be stores targeting tourists. These consist of stores such as large chains, souvenir stores, take out restaurants, and some bars.

The team also finalized the design for the new website. First, the team updated the look of the website to adhere to the new color scheme and design patterns of the other Venice Project Center websites. Next, the team added a search bar that users can search certain types of store by keyword. Also, the dataset can be filtered with through many different criteria and displayed on the map. In addition, census data can be overlayed in a heatmap style fashion with the menu on the top left of the screen.

In conclusion, since there’s not enough data from Giudecca, the team could not draw any conclusions about the data. For Cannaregio, the economy saw a slight increase in the ratio of opening stores increased to closed stores compared to past years, while the food-based activities saw a slight increase and good-based retail saw a contrasting decline. Considering all collected data as a whole set, the number of openings and closings both decreased compared to the historical data. Also, there’s slight decrease in restaurants and souvenir shops.

For future teams, our team has recommendation about the web-application, database and data collection method. For the web-application, our team suggests the future team can either work on the 2015’s website or build up a new web-app using the react framework created this year. For the database, our team recommends that the future teams sort the chamber of commerce data in the same structure as VPC data. This would increase website loading speed. For the data collection method, our team highly recommends the future team works on the CK input app as a large part of their project- it has many bugs that need to be fixed and need much more functionality in order to be useful. If the team finds out that the CK app is unusable, they should start to do data collection using photo or pen and paper as soon as possible.