Measuring CO2 emissions induced by online and brick-and-mortar retailing

We develop a method for empirically measuring the difference in carbon footprint between traditional and online retailing (“e-tailing”) from entry point to a geographical area to consumer residence. The method only requires data on the locations of brick-and-mortar stores, online delivery points, and residences of the region’s population, and on the goods transportation networks in the studied region. Such data are readily available in most countries, so the method is not country or region specific. The method has been evaluated using data from the Dalecarlia region in Sweden, and is shown to be robust to all assumptions made. In our empirical example, the results indicate that the average distance from consumer residence to a brick-and-mortar retailer is 48.54 km in the studied region, while the average distance to an online delivery point is 6.7 km. The results also indicate that e-tailing increases the average distance traveled from the regional entry point to the delivery point from 47.15 km for a brick-and-mortar store to 122.75 km for the online delivery points. However, as professional carriers transport the products in bulk to stores or online delivery points, which is more efficient than consumers’ transporting the products to their residences, the results indicate that consumers switching from traditional to e-tailing on average reduce their CO2 footprints by 84% when buying standard consumer electronics products. 

Measuring CO2 emissions induced by online and brick-and-mortar retailing

We develop a method for empirically measuring the difference in carbon footprint between traditional and online retailing (“e-tailing”) from entry point to a geographical area to consumer residence. The method only requires data on the locations of brick-and-mortar stores, online delivery points, and residences of the region’s population, and on the goods transportation networks in the studied region. Such data are readily available in most countries, so the method is not country or region specific. The method has been evaluated using data from the Dalecarlia region in Sweden, and is shown to be robust to all assumptions made. In our empirical example, the results indicate that the average distance from consumer residence to a brick-and-mortar retailer is 48.54 km in the studied region, while the average distance to an online delivery point is 6.7 km. The results also indicate that e-tailing increases the average distance traveled from the regional entry point to the delivery point from 47.15 km for a brick-and-mortar store to 122.75 km for the online delivery points. However, as professional carriers transport the products in bulk to stores or online delivery points, which is more efficient than consumers’ transporting the products to their residences, the results indicate that consumers switching from traditional to e-tailing on average reduce their CO2 footprints by 84% when buying standard consumer electronics products. 

Personalized Communications : A Cross Media tool for the future

Personalized communication is when the marketing message is adapted to each individual by using information from a databaseand utilizing it in the various, different media channels available today. That gives the marketer the possibility to create a campaign that cuts through today’s clutter of marketing messages and gets the recipients attention. PODi is a non-profit organization that was started with the aim of contributing knowledge in the field of digital printingtechnologies. They have created a database of case studies showing companies that have successfully implemented personalizedcommunication in their marketing campaigns. The purpose of the project was therefore to analyze PODi case studies with the main objective of finding out if/how successfully the PODi-cases have been and what made them so successful. To collect the data found in the PODi cases the authors did a content analysis with a sample size of 140 PODi cases from the year 2008 to 2010. The study was carried out by analyzing the cases' measurable ways of success: response rate, conversion rate, visited PURL (personalized URL:s) and ROI (Return On Investment). In order to find out if there were any relationships to be found between the measurable result and what type of industry, campaign objective and media vehicle that was used in the campaign, the authors put up different research uestions to explore that. After clustering and merging the collected data the results were found to be quite spread but shows that the averages of response rates, visited PURL and conversion rates were consistently very high. In the study the authors also collected and summarized what the companies themselves claim to be the reasons for success with their marketing campaigns. The resultshows that the creation of a personalized campaign is complex and dependent on many different variables. It is for instance ofgreat importance to have a well thought-out plan with the campaign and to have good data and insights about the customer in order to perform creative personalization. It is also important to make it easy for the recipient to reply, to use several media vehicles for multiple touch points and to have an attractive and clever design.