Peer Review Form

Business Model Canvas

John Tarpeh

Grand Canyon University

ENT-436

Business Model Canvas

The purpose of this business model canvas is to examine how human-centered design and technological advances can be used to solve real-world business problems, particularly in the transport sector context. The assignment is based on an improved hypothesis that states: The introduction of ridesharing apps into mainstream society will decrease the number of drunk-driving incidents by 5.6 percent. Therefore, this business model canvas will consist of the evaluation of the key ideas for partners, key activities, key resources, value propositions, customer relationships, customer segments, channels, cost structures, and revenue stream.

Key Partners

Ridesharing apps have changed the mode of personal transportation drastically over a few years (Dills & Mulholland, 2018). The key partners in the introduction of a ridesharing app into mainstream society will decrease the number of drunk-driving incidents will include the following: Information Technology Experts who will develop this app, refine it and make its interface easy to use. Emphasis is placed on the easy to use variable considering all the target customers will be logging into the app while drunk (Wang et al., 2017). Therefore, they should be able to navigate easily through its menu, find a nearby ride to share and head home as soon as possible. Without placing this aspect into consideration, most first-time users will have a bad experience with the app and most likely will not use it again. Resultantly, they will revert to their old habits of driving while drunk: a problem the app aimed to solve in the first place.

Bar owners and Club owners: These groups of individuals are essential partners as they are the ones who will be left with the customer’s automobile keys. They are to ensure that the right individuals contracted to deliver the customer’s car pick it and sign an agreement form before taking the vehicle for home delivery. This will minimize the chances of a customer losing their vehicle to thugs who might want to manipulate the situation and steal cars or personal belongings left in the vehicles while drunk clients have left.

Key activities

Some of the activities to be implemented in this business model in the transport sector context include the development of an effective and easy to use ridesharing app, availing the developed app in all android and IOS phone platforms via Google Play Store and Apple Store as well as having windows and Mac versions for club and bar owners, and training users how to navigate through the developed app. These activities are carried out to ensure that the developed app will run effectively and that there will be a smooth transaction between the customers and other stakeholders such as the sober driver allocated to taking the drunk individual to their homes, and between the club owner and the company assigned the duty to drive the clients’ car back to their residence.

Key resources

The vital resources to see to it that this business model succeeds are information technology experts, bar and club owners, smartphones and computers, and regular bar and club drinkers. Each of the previously named resources plays a central role in making sure that this business model is implemented successfully and serves the designated purpose effectively. Ultimately, the integration of these resources will see to it that drivers get home safely, their cars are also delivered safely, and the number of drunk-driving accidents is significantly reduced.

Value Proposition

This model sought out two key value propositions. First, it utilizes technology through readily available smartphones to provide a cheap and safe guaranteed avenue for drunk individuals to get home. Secondly, club and bar owners have to ensure that their regular and loyal customers get back home safely while safeguarding their vehicles from drinking-related accidents. These propositions will be achieved based on the fact that no drunk individual will be allowed to drive their cars after a night out with friends. Instead, they will seek for a ride to share with a registered sober member from the app.

Customer Relationships

In this case, the customer relationship involves offering a cheap, effective, and safe way to get home after night-out drinking with friends. These customers won’t have to drive home drunk. Instead, they will seek a ride to share while their car gets delivered by a professional company hired to fulfill the task. Additionally, the cashless and convenient form of payment makes it easy to conduct transactions (Özkan & Ward, 2020).

Customer Segments

The customer segment for this business model includes regular bar and club visitors who will benefit from the ridesharing app, which allows them to leave their cars at the club, share a ride home with a sober driver, and still have their automobiles delivered the next morning safely.

Channels

In the creation of this business model, the channels for communication to be used will be mobile phones and computers. The former will be a key device as the application will have to downloaded from Google Play Store for Android devices and the Apple Store from IOS devices. Also, these smartphones will be used in the communication between the customer and their respective driver as well as the club owners and individuals contracted to deliver the client’s cars at their homes.

Cost Structures

Cost structures for this business model include computer repairs, replacement of lost phones, runtime costs, and spare parts for devices used in the implementation of the project.

Revenue Streams

In this business model context, subscription by customers and subscription by companies to deliver client’s vehicles safely to their homes will be the key streams of revenue. Customers will have to pay to access the ridesharing app services (Agatz et al., 2012). At the same time, also companies interested in delivering cars to this business model clients will have to pay a one-time registration fee.

References

Agatz, N., Erera, A., Savelsbergh, M., & Wang, X. (2012). Optimization for dynamic ride-sharing: A review. European Journal of Operational Research, 223(2), 295-303.

Dills, A. K., & Mulholland, S. E. (2018). Ride‐sharing, fatal crashes, and crime. Southern Economic Journal, 84(4), 965-991.

Özkan, E., & Ward, A. R. (2020). Dynamic matching for real-time ride sharing. Stochastic Systems, 10(1), 29-70.

Wang, X., Ardakani, H. M., & Schneider, H. (2017). Does ride sharing have social benefits?.