Willkommen zur Umfrage / Welcome to the survey
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FlexTour is a software that will make your life as a tour operator easier. You will no longer be juggling with your daily tasks and trying to manage different communication channels. For happy customers and competitive tours, tour operators choose flexTour.
FlexTour was founded after a group of students from the class of IMTE 2018 were given the task to identify problems and create digital solutions for different companies in the field of tourism. FlexTour was given the challenge to find problems for tour operators and identify their daily challenges at the workplace. This project started at the beginning of March and the product development ended at the end of May with a pitch in front of potential investors.
Where did it start for us?
It started with identifying the problem experienced by tour operators. Some of the group members had former experience working for tour operators, but none of us was directing or leading a company. It was therefore important for us to call around and ask tour operators what their problems were. We asked detailed questions with general managers about their biggest problems as a tour operator.
The conclusion of the research gave us three major problems:
1. Lack of efficient communication between themselves and their tourists
2. Time-consuming problem solving
3. Lack of flexibility when managing tours
Some theories we learned on the way
From there, we started to apply some theory that we were guided to. The lean startup methodology, a process that would help startups to succeed and that can be described as learning- building -measure methods was applied. From there, we also learned about personas and the customers journey. With the personas, we looked at what types of customers we are targeting, and why. Our ideal persona was Phil Hellmuth, a middle-aged manager of a small tour operator company in Germany. We used him in our storytelling throughout our project and we often asked ourselves, “What would Phil Hellmuth do?” Using the customer’s journey we could describe his workday and where his peaks and downfall of working in a small tour operator company lay.
The real struggle for us – Who are we selling our product to?
After finding the problems for Phil Hellmuth came the next phase, how we could help him and test the feasibility of our plans. Our mentor and teacher Mr Marcel Broumels was often in our room and talked to us and when we had so many ideas he would say: “You started small, and then suddenly when I get back you want to save the world. You need to shrink your idea to something more feasible”. With that he meant, kill your darlings, something that was presented by Mr Roman Egger, and do not hold on the first idea you have.
So why did we have a problem surrounding our product, when we already had the persona and our customers? Well for us it was important to have a solution for what we called the “customer” and the “customer’s-customer”. The customer was the client we wanted to sell our product, the software, to. This would help tour operators with getting a more efficient daily routine and easy communication streams to his clients and partners by using one communication software for the tour operators and direct with their guest, and what we called, “customer’s-customer”. Many hours were spent on identifying the most important part of this product and our MVP- Minimum Viable Product. It was in our case important to find a reason why people would be willing to buy and use or product. It was therefore crucial to find the fine line between working out the idea and designing the platform. This platform would be used for the tour operators to create and adapt their tours and react quickly to changes from suppliers and clients. For the clients of the tour operators (i.e. travelers), there would be an application where they could access their day to day travel plan. Tour operators will have the authority to give access to their clients once they have confirmed their trip. They would receive push-notifications immediately updating them to any changes to their tour.
How much you can agree on when the deadline is approaching
By the end of the project with Mr Marcel Broumels, we had to make a prototype and pitch it in front of him; this was easier said than done when we could not agree on minor problems. It was then important for us to make a prototype and establish our market size and our revenue streams were. Research showed us that the German tour operators market share for SME was 37.7% and that’s where our specialization in this market would be. Our revenue streams would be a model consisting of fixed minimum prices depending on the size of the business and a variable price per user of the application.
The Shark Tank
Our final pitch in front of highly critical investors was daunting. They were prepared to ask us some tough questions and decide if they would be interested to invest in our idea and our project further. The date was on the 21st of May. The day we all had waited for, our final pitch. Shabab and Tommy had been practicing for days before the final day and hoping to carry and charm the investors with their message. Flextour- the software for all SME companies tour operators. We believe that we sold it very well with the story of Phil Hellmuth and this was something worthy of their investment. A question answer session followed the presentation. Our potential investors were interested to know whether we had been looking deeper into the competitors and if other companies were already using these types of software. Other questions were in regards to the pricing, and where we see ourself in the future.
We came to realize that there were many areas which we had not considered. We were too focused on the product and not on other factors such as pricing, similar features that competitors offered and their pricing model. We were too much into the thoughts of getting the perfect product and not being aware of the environment around. We realized it that we were lacking here the most. However, we did receive some of the more positive feedback from the day, and were considered by one investor as being in the top three companies that had been presented.
Our team at FlexTour and our expertise
Georgia has experience in a hospitality software company with a good eye for combining technology and hospitality. She had new ideas all the time, capable of leading when it was at boiling point in the group. Binod worked for five years in the tour operator business and has first-hand knowledge when it comes to the challenges faced by tour operators. During this project, he worked hard and took the lead when something needed to be done. Tommy has a tourism background from Norway and has always been a tech enthusiast, providing innovative ideas to the group. He, together with Shabab, was the voice of Flextour, speaking out and presenting in a persuasive way. As already mentioned Shabab and Tommy were the spokesperson of FlexTour. They both have good financial know-how and are experts in storytelling. Victorine has past experiences in marketing and was our critical eye when we were discussing our problems. Aleksandra worked as a tour guide in Russia and has backgrounds in intercultural communication beside that she and Edina were responsible for the design and the prototype of FlexTour. Edina has got tourism background and worked in the hotel industry. She is aware of the problems faced by tourists arising from miscommunication. She has seen the complication between tourists and tour operators during her working hours in the hotel.
Reflection on the project and the road for FlexTour
Our project work took several months. During all that time, we faced many problems but always tried to find proper solutions. Moreover, having a chance to develop our own product from the very beginning, we gained useful knowledge and extremely valuable experience in creative thinking and idea managing which could be applicable in creating new projects.
Above all else, the project work taught us teamwork. As all of us are from different countries and have different backgrounds and knowledge, we managed to collect completely different points of view because each team member had a freedom of deploying decisions and creative findings.
We did a really great job but we are at the beginning of a long journey and we have no intention to stop anywhere soon. The sky is the limit for our team, and maybe one day you will come across of using our product FlexTour software and be a happy traveler.
We strongly hope that our project experience will help you in starting your projects and inspire new achievements and innovations. Good luck!
The service-related sectors are heavily dependent on personnel. Particularly in the food and beverage industry, restaurateurs often require more staff during the peak hour or peak season. However, one of the challenges for restaurateurs remains to be staff management. According to Dermody (2002), managers claimed that one of the main issues employees care about when looking for a job is the working environment. Furthermore, compensation and monetary awards, as well as flexibility in work schedule, are other important factors considered by the job seekers. The recruiting problem exists for all levels of positions. Specifically, backhouse positions (e.g. dishwashers, kitchen assistants), which require less skill than those in the front of the house (e.g. waiters, hostesses, busboys), are found to be more challenging as managers often rely on immigrants to fill the positions. Moreover, finding qualified candidates for management positions is equally difficult, in which, previous studies discovered that identifying skilled managers has been a constant concern (Enz, 2004). Adding to that, the working environment in the dining industry features long working hours and tedious responsibilities, leading to a high fluctuation rate in the workforce. This can result in a knowledge gap among staff, addon job scopes, lower performance rate and lastly, affecting the customers’ experience (Kim, Leong & Lee 2005).
Diagram of ProStaff service: direct connection between restaurant owners and appropriate candidates
Reported by the National Restaurant Association, employee turnover across the entire restaurant industry was 61% in 2016 and that percentage is almost twice as high for front-line workers. Moreover, one of the consequences is that restaurants on average are losing around $150,000 per year due to the high employee turnover rate (Mack, 2017). Therefore, the idea of ProStaff serves as an online platform for restaurant owners and human resource department to look for potential candidates. ProStaff is a digital recruitment platform that provides a user-friendly interface to assist restaurateurs to search for qualified staff. By applying the gamification of Tinder’s swipe motion and the professional network structure from LinkedIn, the digital recruitment process can be the future envision for talent recruitment and management.
Prototype of a display page of the ProStaff application
The solution has several contributions to the food and beverage industry. First, as confirmed by three different restaurant managers in Salzburg that human resource is the main challenge, it calls an urgent need for a tool to simplify the staffing process in the hospitality industry. That is, ProStaff will be the new talent recruitment benchmark as the process is digitalized and more efficient as the present technology advances at a fast pace. With a clear navigating design, restaurant owners and job hunters ranging from Millennials to Baby Boomers can easily search for the appropriate candidate or job within minutes. Prostaff also provides legal services to advance the hiring process to benefit both parties efficiently. Candidates’ background will be verified prior their profile upload into the database, making sure they are experienced in the corresponding positions they are searching for. As some of our teammates experience long waiting periods for legal contracts and availability for part time jobs, we also provide services to deduce the processing time and complex legal procedures.
In order to meet the needs of target customers (i.e., restaurant owners), ProStaff will start from an adaptive website version to minimize risks in the initial phase. Benefits are mutual for ProStaff and restaurateurs, excluding the cost for app development. On the restaurant managers’ side, requires less time to familiarize with app usage. Adding to that, with the combination of LinkedIn and Tinder, future potential be applied with manpower agencies for fast solutions and have continuous updates on within their data pool of their candidates. For future potential cooperation, ProStaff can cooperate with AMS and manpower temporary agencies to help job seekers from various industries with the same interface design.
Easy gamification use of the application
Moreover, ProStaff will charge restaurateurs €300 per year + €25 per each successful match; on the other hand, job hunters do not need to pay unless they want higher visibility or information faster, a premium plan for €10 per month is provided. In order to break even within the 5-year achievement, we will need to acquire 175 restaurants (€61,250 with yearly membership and 350 successful matches (2 per each restaurant)) and 1,080 premium users (1,080x€30 with an average of a 3-month use). A long-term economic success is guaranteed through the annual subscription fee of €300 and €25 per each successful match. By extending our database, we contribute our customers with a bigger variety of highly qualified staff and ensure more successful matches. Also, ProStaff actively supports the economic stability of the region by providing an online environment for job seekers and businesses. ProStaff serves as an assistant to reduce time and budget for restaurant owners in the staffing process, which facilitates the managers to focus on the core business. In the job seekers’ perspective, it offers more opportunities to reach out to further employees. To sum up, ProStaff brings positive impacts and benefit to the local social ecosystem. It not only lowers the unemployment rate within the region but also improves the living quality of the wage earners.
Dermody, M. B. (2002). Recruitment and Retention Practices in Independent and Chain Restaurants. International Journal of Hospitality & Tourism Administration, 3(1), pp.107–117.
Enz, C. A. (2004). Issues of Concern for Restaurant Owners and Managers. Cornell Hotel and Restaurant Administration Quarterly, 45(4), pp.315–332.
Kim, W.G, Leong, J.K, Lee, Y.K. (2005). Effect of service orientation on job satisfaction, organizational commitment, and intention of leaving in a casual dining chain restaurant. International Journal of Hospitality Management, 24(2), pp. 171-193.
Mack, R. (2017). What is the Real Cost of Restaurant Employee Turnover?. Modern Restaurant Management. Retrieved from: https://www.modernrestaurantmanagement.com/what-is-the-real-cost-of-restaurant-employee-turnover/
We think, it is really important…
During our research we have found out that nowadays tourists during their trip are surrounded with loads of tourism information from brochures, travel guides, internet, social media, OTAs, DMOs and many more. Those travellers who do not plan their trip till the smallest detail, probably end up at a destination without a clue where to find exactly the information that this traveller needs. In addition, in urban destinations, where public transportation plays a crucial role in tourists experience, it is important to facilitate the right environment for the tourist to find the right information how to get from point A to point B.
Personalized travel Guide in Austria- Guide Me
Step by step, first ideas were born. Narrowing down wide range of possible areas and touchpoints that we could work on, brought us to the field of technology in tourism which enhances and improves experiences of travellers during their on site travel in Austria.
Why just not search things on Google?
-because Guide Me will guide You!
Guide Me is a tool that allows tourists to optimize their time while travelling and find the right and necessary information at the right moment and at a current place in a destination. Recent research (Moritz, 2015) that aimed at getting a deeper understanding of the current situation of the on-site travel experiences in Austria, suggested a customer demand for and mobile application with following elements: travel guide for points of interest and tourism attractions, public transport navigations, taxi services, booking of tickets, offline maps, social media. Moreover, research concluded that more than 71% of participants would want to have these features in one single app, that supports the initial idea of Guide Me. Guide me consists of all these features.
How Guide Me will guide You?
To be honest, it is not that easy…
Our initial task was to find out biggest traveller pains and identify problems that travellers encounter during their travel experience on site. After several rounds of interviews with travellers in a tourist dense areas, we gathered a pool of different ideas where we filtered those which were the most relevant for our traveler. The idea to create an app was based on the aim to create the ideal solution for travellers pocket during travel.
After developing the prototype, we tested our minimum viable product with travellers and one really competent industry practitioner that gave us many insights and opportunities to improve Guide Me´s initial features, maine elements and made it more user-friendly.
Guide Me offers real time travel information during the journey where travelers would be able to adjust their travel based on their preferences, hobbies, things they enjoy while travelling, budget and most importantly past travel patterns.
Real time information updates, transportation, restaurants, accommodation, attractions and social interactions… Guide Me is a tool that would help tourists to orient into the huge amount of tourism information available and help them to make the best and personalized travel plan as possible.
Our biggest challenge is to develop the information platform where we can aggregate all the data. As Guide Me uses GPS locations and travel routing, we need cartographic data or and sources of mapping as a basis of Guide Me. Afterwards, we need to aggregate the data that is available online about attractions, transport and restaurants and label each element with labels that categorize them based on traveller preference filters.
Why Guide Me would be better as Google? – because Guide Me will know the traveller…
In addition, our features include last touch from a local, meaning that information provided is authentic. Our success is based on how good connections we make with our stakeholders and how well be can create for both the tourist and also the Austrian tourism industry.
The Future of Guide Me…
From business side, Guide Me can be considered as the innovation in the app sector focusing on Austrian tourism market which is currently in expansion. Since tourists are searching for unified and obtained data into one place, Guide Me can be attractive solution for both sides, tourists and stakeholders which can recognize the quality and all the benefits that this app provides. According to the fact that nowadays applications are globally used and preferred during the journeys which many studies confirmed this one offers the most wanted solutions for travellers in one place. Moreover, Guide Me has the potential for future expansion in the global market.
Are we aiming too high?
As our main idea was to create a more personalized, better version of the existing travel applications, we need to provide all real time information needed during travellers journey. Our biggest competitor is Google and even though it is hart to compete with it and with several bigger players in the market, with the necessary support in order to create the right infrastructure and to develop high quality content, Guide Me would be recognized by the customers. Pulling the required data to provide this kind of service on a competing level is hard but not impossible to achieve. In general, such ideas are hard to realize for start ups as all the big competitors are on a large mass-market level, which are able to provide and process data on a much higher scale.
Personalization will continue to increase rapidly in importance in the upcoming years. Therefore, one can be confident that similar solutions will be on the market in near future. However Google, Lonely Planet, etc. are working constantly on the improvement of their services to achieve a higher level of personalization through artificial intelligence and other forms of new technologies. This means that the chances of entering this market successfully, which is dominated by giants is barely realistic.
In order to find out the main problems and needs of the market, we took inspiration from research, own experience and interviews. We thought that this was going to be the best combination to identify the main issues concerning visitor attractions. After our research, we quickly came to the conclusion that weather in general and weather dependability played a huge role in the success of attractions. For example, Day et al. (2012) and Dodds (2010) found that weather definitely has an impact on the decision-making process of tourists on which destination or attractions to visit. Also, the interviews with employees and visitors backed the identification of this issue.
When we found out that due to climate change, weather is getting more and more unpredictable, we decided to work on a solution that tackles this very issue. We tried to come up with a solution suitable for all the different stakeholders, for example, tourists, DMOs and the attractions. This is where we maybe bit off more than we can chew, as in the end it seemed that we were working too broadly and trying to solve multiple problems at the same time, which made it harder to come up with a viable product
– Research at the Salzburg Zoo
About 95% of tourists use digital tools in search of the best experience before, during and after travelling and access a dozen number of websites and apps in search for their desired destinations. Booking through mobile devices has increased in recent years and is expected to reach 25% of all online transactions. Taking into consideration all of the above, GOAT allows tourists to browse attractions which are available nearby, with ticket prices based on the local weather predictions. Another feature that the app offers to the customer, is the convenience of having all the purchased digital tickets stored in the app’s eWallet.
The weather impacts the proﬁtability of the DMOs in several ways, including reducing or increasing demand for a destination and reducing or increasing customer satisfaction after visiting the destination. GOAT helps to manage part of the attraction ticketing and by doing so it can reduce queues, increase the number of visitors on less busy days, whilst boosting the visibility of the individual attractions and their profit. Also, GOAT will support and increase the number of visits of rural destinations which are not so commercialised or publicly recognised.
The GOAT application uses a dynamic pricing algorithm, based on the weather forecast, availability and historical data, to encourage price sensitive customers to visit underutilised attractions. It combines the offers of a diversity of attractions in a single application, supporting attractions to overcome sales shortfalls due to bad weather conditions and simultaneously to promote their activities through in-app ads. This can be done online through our website or via our mobile application, on which the tickets can also be stored and displayed for use. From the customer perspective, GOAT is an intermediary that specialises in tourist attractions, providing a platform through which customers can search for, select, and purchase attraction tickets in destinations around the world. Moreover, every type of tourist attraction can benefit from using the application, from major tourist attractions in big cities to small-sized attractions in Austria’s mountain regions. The app will be attractive for the attractions, as it solves a big part of the weather dependability most tourist attractions have to deal with.
– Prototype GOAT application
The app has three revenue streams, the first and largest of which is commission. Between 10% and 20% of each ticket purchased via the app is taken as commission. The commission rate is dependent on the size of the attraction, the number of tickets made available via the app as well as any other contract conditions such as platform exclusivity. As the platform expands additional commission-based revenue will be generated through the inclusion of additional ancillary sales within each attraction, such as specific tours or events.
With multiple attractions competing for customers on the platform we will also generate revenue from sponsored listings. These will allow for attractions to purchase premium space among premium listings. Additional advert revenue could also be generated from restaurants and accommodation, paying to be listed alongside attractions which they are close to.
As the application requires the use of GPS in order to provide attraction recommendations, we will accumulate large amounts of geo-data displaying movement patterns. This could be anonymised and sold to DMOs as another revenue stream or could be used in part of a cooperation agreement with DMOs to offer the platform in their destination.
– Brainstorming session
Interviewing customers for problem identification, the customer journey mapping, continuous process of prototype testing, sharing and discussing our problems and ideas and the vibrant mood within the group were important in coming up with a solution for attractions, DMOs and travellers. However, due to time constraints we could not test our prototypes at the same attractions we visited for our problem identification. After presenting our pitch to experts from different sectors in the tourism industry, our problem was deemed a major problem for both indoor and outdoor attractions. However, our solutions in providing an online ticketing system for attractions in the form of an app that could also help DMOs spread visitors within destinations and avoid overcrowding and simultaneously show all attractions in destination in a single app was not viable to the experts. The two major reasons were: there is already a company (Guideme) offering a similar service in Austria and we did not consult the DMO of Salzburg city to find out how many Salzburg cards they sell in a year which includes free transport and entry to attractions in Salzburg that could have helped in our income projection. Nevertheless, an insight into offering a revenue management system for attractions as a solution of weather dependability was recommended by the experts instead of online travel agents.
Meet Our Team…
Imagine you are a tourist in Salzburg, travelling with a group of friends. You have been out for a long walk in the morning, where you firstly went up to Hohensalzburg and afterwards strolled along the Salzach.
You all took lots of pictures, and now most of you are getting hungry and are ready to find something to eat. However, you also need to have WiFi to share the pictures with your families, and you would need to charge your phones in order to keep on taking pictures in the afternoon without having to go to your hotel to charge. In addition, one of your friends is vegetarian.
You start scrolling through various Google results, and usually it is easy to see whether a place has WiFi or not or even vegetarian food, however to see if they have plugs accessible, requires some more thorough investigation, and you become impatient.
That’s when your friend shows you Accility.
Accility allows you to search for the amenities that your group needs. Your friend shows you how he searches for cafès and restaurants which offers WiFi, plugs and vegetarian food, and he instantly finds the closest place that offers all three of them. Super simple, super convenient.
You and you friends use the map-function to quickly navigate to Coffee Press which offers everything you need, and more. The map-function lets you further, easily identify specific amenities that you need with a traffic light system similar to the one in the picture below. Green are attractions that have all desired amenities, orange those who have most of them, red are the ones with no selected amenity.
How did we come up with Accility?
The idea of Accility emerged after efficient market research with tourists who had problems regarding the time-consuming research needed when they were in need of specific amenities in a destination. Some things are easy to find through Google or TripAdvisor, such as WiFi, vegetarian options etc., however the frustration occurs when they are in need of more than one amenity, and they need to look through a variety of websites and perhaps end up calling instead.
After identifying the problem, we brainstormed ways to solve it. Our solution needed to be time-efficient and user-friendly. We tried different solutions, did rapid prototyping and adjusted our solution according to the feedback we got along the process. We had to eliminate things like AR, Premium functions and verification in order to really simplify it and make it affordable. These are ideas we keep in mind for the future if the app proves to be successful. We want to keep it simple and convenient – because scrolling through thousands google pages isn’t. We want to make our app easy to use and simple to understand, with symbols and only the most relevant information so users don’t get frustrated when using it.
One threat is the short usage time-span in the beginning, as tourists in Salzburg will only need it for a short period, and locals will shortly learn which places have the amenities they typically need and therefore might not feel like they need the app anymore. Profitability is low due to the only revenue generated is from advertising within the app. This will be especially challenging in the beginning when the app will only be available for use in Salzburg.
The problems of app-usage-time will somehow be solved when we expand to several destination and the user will need/want to have the app in his/her phone for longer as they will be able to use it in other destinations as well. With increasing popularity of the app, in order to increase profitability, we also have an opportunity to develop and offer a premium-function where premium users have the possibility to discover the cafes/restaurants/attractions they need using AR technology. Our advantage is the immense market-size of Austria, Germany and Switzerland. Over 70 Million tourists annually are visiting these countries. If only a small portion of those use our app we could be successful over a long period of time, and in this calculation we do not even include the local users.
Our app has the possibility to make navigation to the right places within a destination very time-efficient and hustle-free. Some critique has been directed to us due to the fact that Google and Tripadvisor offer some of the same information regarding a small selection of amenities, and this is a clear threat for us which means that we need to differentiate us in being significantly easier to use and understand. With Accility we strongly believe that both tourists, students and locals will take advantage of it. We offer a larger number of amenities than our competitors, the process of finding them in the destination is easier and we are the only ones providing a simple app-solution focused on filtering the amenities by relevance and distance from your location. As any start-up need to be, we are prepared for pivoting and to implement new ideas when the market shows need for it. With the DMO’s in cooperation we will assure that the information is always up to date and increase the overall destination image by urging attractions to update their own amenities. We always like to recall our Win-Win-Win situation. A win for tourists who benefit of the simplicity of finding what they need, a win for the attractions who benefit of attracting their target market, and a win for the destination who ultimately increases its destination image.
In the last years we have witnessed the emergence of new disruptors in the hospitality scene, such as AirBnB. It`s no secret that hotels were left struggling a bit from the effects of these new types of accommodation providers based on the sharing economy. But why is that you might wonder? We did too, so we went out asking travelers about it with the occasion of our 2nd semester project in Innovation Management and eTourism Solutions. So, let´s start from the beginning.
How did we identify the Problem?
For our first steps we implied the Lean Start Up approach to identify possible problems. In this stage we made use of the placemat method and brainstorming. Then, interviews with travelers on the FH Campus and via phone followed. This way we could measure if the problem found by us was also felt by the respondents. Whilst listening to our interviewees, the occurring themes of customization and personalization started to become clear to us with people emphasizing that they do not feel special when staying in hotels. These points were also reinforced through conducting a trend analysis. A 2016 report from Deloitte found that in many categories, including travel, more than 50% of the consumers prefer purchasing personalized products or services and that they would even pay up to a 20% premium for it. Moreover, with the Experience Economy on the rise, personalization is about to become a must for businesses to thrive in the market.
Exploring the Problem through the lens of Personas and Customer Journey mapping
Once we had a general view upon the problem, we started to explore it in depth by creating 2 different personas, Maria – belonging to the leisure traveler segment -, and John – belonging to the frequent traveler segment. We looked at what are the needs and wants of these two personas and how do they feel across their customer journeys. This way we could really see the specific pains of such customers of hotels and learn how to transform them into gains. What stood out was that the guests are not properly welcomed, one of the most important moments when hotels could make a great impression on their guests is ruined by the boring check in, where you have to fill in always the same registration form, show your passport, and for repeat travelers this is indeed a very annoying process. More than that, hotels` rooms are filled with standardized and unnecessary things, such as the minibar, and the preferences of guests are many times not accounted for. Here`s a video our team has developed using Animaker in order to encapsulate these pains of hotel`s customers:
Coming up with the Solution and building an MVP
Once we could really visualize all these pains, our next step was to continue brainstorming for an eSolution which would bring increased value for hotel`s guests. We went through discussions on different technologies and opted for an interactive digital assistant under the form of a webpage, app or web pop-upbased on the needs and possibilities of each hotel.
From this point on, we had to see which features are worth including so that our solution would really address the identified pains. Firstly, we created a prototype by drawing on paper different features and went around the campus with it to ask some travelers what they think of it. Secondly, we pivoted some of the features and tried to increase the innovative character through an interactive interface which resembles a conversation with a friend or an assistant who is trying to help the traveler get a better and more personalized hotel experience.
We really wanted to emphasize this human like character and that`s how the name of Emma was attributed to our solution. After we knew what the personality of Emma would be like and how she helps hotel guests, we went on to design a virtual prototype. Throughout this step we have used www.canva.com for design purposes and www.invisionapp.com for prototyping how the website would work like. At the end of this process, we obtained a good MVP which was tested with a frequent traveler and a leisure traveler as well, receiving very good feedback.
The final form of our solution was a responsive and easily to integrate tool in the form of an app, website or pop-up page. This solution combines useful features such as the personal guest profile stating his/ her preferences, the pre-check in, the “problem manager” and the unique feature “my mini-bar choice”. EMMA has a modern and innovative interface resembling the process of creating a social media profile with focus on the guests` accommodation preferences. It is like a personal assistant which asks the guest what he/she desires and then stores these preferences in the guest`s profile. The guest sets up this profile one time and then the hotels he/she stays at can require access to it once they adapt EMMA. Through a single click the hotel has then access to valuable information which will help them to make the guest feel special during his/ her stay.
Therefore, the customer journey becomes very pleasant for the guest and the process of delivering a qualitative and personalized stay gets faster and more efficient for the hotel.
Beyond the creative and innovative process
So far so good, but many ideas remain just ideas because their developers fail to put together a business plan. We went on to look at our solution from the perspective of the Business Model Canvas. Now we didn`t just have a prototype, but a holistic view on who should be out partners, what is our market and how can we generate revenue streams. You can find more details on our market, competitors, pricing, needed resources and finances here: https://tinyurl.com/y685syur.
And just when we thought the hard part had passed, we discovered what`s one of the most crucial moments in such a project: pitching in front of investors to get funding. We kept hearing in this second semester that we should kill our darlings, referring to those project ideas we are too close to. Even though we pitched our solution many times, it never got easier to defend our “baby” and it really felt like it would have been good to know how to “kill our darlings” in some moments.
But while we live, we learn, and from this project we felt that even though most of the developed products, including EMMA, will never make it to the market, it was a chance to practice the innovation process and further our knowledge about what has to be taken into account in such projects. Our advice: carry on a very extensive market analysis once you get an idea of a solution and don`t be afraid to go further than Google`s first page of results.
If you ever want to start such a project, our team`s tips for you are:
Stay inspired & united!
Several decades ago the amount of digital information has begun to increase through the development of computer technologies. Whereas previously, in the late 1980s only 1% of all the world’s information was in digital format, nowadays more than 99% of the information is stored in this format (Hilbert, 2015). As a consequence, new computational approach and analytical tools are required. Until very recently researchers have troubles with analyzing large amounts of data as they used traditional methods of analyzing and statistical tools. It is obvious that this approach was not enough for analyzing the growing amount of information. Thus, computational social sciences (CSS) are being developed.
CSS is an emerging field of study which has now become an intersection of various different fields of study like social science, computer science, environment and engineering (Cioffi-Revilla, 2014). CSS is intended to process data and run simulations at planetary scale, where up to the whole world population is considered, in order to get a better understanding of global social dynamics. This makes sense in a more and more interconnected world, where the events occurring in one place can have tremendous consequences on the other side of the globe (Helbing et al, 2012). The new ICT-enabled study of society has been named CSS. This is a truly interdisciplinary approach, where social and behavioral scientists, cognitive scientists, agent theorists, computer scientists, mathematicians and physicists cooperate side-by-side to come up with innovative and theory-grounded models of the target phenomena. Computational social scientists strongly believe that a new era has started in the understanding of the structure and function of our society at different levels.
CSS is a powerful tool for fostering our understanding of the complexities of real socio-economic systems, by building “virtual computational social worlds” that we can analyze, experiment with, feed with and test against empirical data on a hitherto unprecedented scale (Lazer et al, 2009).. In the last couple of years, social scientists have started to organize and classify the number, variety, and severity of criticalities, if not pathologies and failures, recurring in complex social systems (Helbing et al, 2012). The analysis of huge data sets as obtained, say, from mobile phone calls, social networks, or commercial activities provides insight into phenomena and processes at the societal level. Investigating peoples’ electronic footprints did already contribute to understand the relationship between the structure of the society and the intensity of relationships (Onnela, 2007) and the way pandemic diseases spread (Balcan, 2009) as well as to identify the main laws of human communication behaviour (Karsai, 2011).
There is an increasing realization of the enormous potential of data-driven computational social science. In short, a computational social science is emerging that leverages the capacity to collect and analyze data with an unprecedented breadth and depth and scale (Lazer et al, 2009).
Aim & objectives of the study
The aim of the study is to identify the areas and scope of CSS. The study tries to understand the emerging role and contribution of CSS among research community as well as the tourism industry practitioners. This study collects and analyzes the literatures around CSS and CSS implementation in the Tourism industry. Our objective of the study is have broader view of this new field of study and know where the idea will lead to. We hear and see that the internet and big data presenting new opportunities and challenges to the researchers and the industry equally. The traditional ways of collecting and analyzing data is slowly being replaced by advanced ICT tools. Machine learnings, Big data, data visualization is changing the way of research methodologies. The study focuses to know which new problems are being solved with the help of computational science tools & technologies. We want to know why will the research community and tourism industry will integrate it in their study and work.
Meanwhile, there seems the demand of new sets of knowledge and skills to realize the new possibilities offered by the computational science. The study tries to find out if researchers are facing the knowledge & skill gap in the usage of advanced computational tools. The deeper study of the CSS tools and practices will be taken consideration into the study. Therefore, the goal of the study is to portray the emerging opportunities and challenges in the field of Computational science.
By the study we want to answer the following questions:
The world has changed for empirical sociologists. In this world dominated by computer scientists who created new ways of creating and collecting data, developed new analytical and statistical techniques, and provided new ways of visualizing and presenting information. These new data sources and techniques have the potential to transform the way in which social sciences are applied (Brynjolfsson et al, 2011). Despite the fact that computational social science is a relatively young science, it has already changed the processes of sociological analysis and has had an impact on other areas of science. As a result, computational social science is a focus of particular attention of researchers. Computational social science is a deeply multidisciplinary field, which includes experts with backgrounds in the social, natural, biological and applied sciences. There are certain differences in modelling approaches, depending on whether the origin of model is within industry, academia or the public sector (David et al, 2004; Heath et al, 2009).
According to Watts (2013), Computational social science is located at “the intersection of the social and computational sciences, an intersection that includes analysis of web-scale observational data, virtual lab-style experiments, and computational modeling”. As for social sciences, they comprise five traditional disciplines which investigate human and social dynamics: social psychology, anthropology, economics, political science, and sociology (Cioffi-Revilla, 2010).
As mentioned above, Computational social science is a more recent development than social sciences. Cioffi-Revilla (2010) claims that Computational social science is “an instrument-enabled scientific discipline”. This fact makes Computational social science similar to such scientific disciplines like microbiology, radio astronomy, or nanoscience. In these disciplines “it is the instrument of investigation that drives the development of theory and understanding” (Cioffi-Revilla, 2010).
The main methods which are widely used nowadays can be classified in five areas (Cioffi-Revilla, 2010):
– Automated information extraction (AIE)
Traditional method of analyzing and coding texts to extract information – content analysis has transformed into the computational analysis of all sorts of media (e.g. images, video, audio) in many fields. AIE is used mainly for the production of events data which then are analysed through various methodologies.
– Social network analysis (SNA)
SNA investigates social structures through the use of networks and graph theory. It has many computational applications for providing provide insightful information and knowledge not available through plain observation or through more traditional methods. For example, in the private, sector SNA is used for investigating customer interaction and analysis, information system development analysis, marketing, and business intelligence needs.
– Geospatial analysis [socio-GIS (geographic information systems) or social GIS]
Initially, GIS were used for getting spatially referenced data about the social world. Nowadays, GIS are combined with other quantitative techniques to produce unique new insights about spatial patterns that are otherwise unavailable through other statistical or mathematical models.
– Complexity modeling
Complexity modeling classifies computational problems in accordance with their difficulty. All of these problems are solved by a computer using an algorithm.
– Social simulations models
As a rule, simulation models meet the standards of “internal validity (the causal relationship) and external validity (whether it can be generalized to a wider popularity)” (Bryman, 2004).
A particularly valuable feature of computational simulation models is “their ability to run current and alternative policies to observe their effects (alternative scenarios), assuming a sufficiently well-developed base model of a given ‘target system.’” (Cioffi-Revilla, 2010).
Computational social science and tourism
Tourism has been ranked as the foremost industry in terms of volume of online transactions (Werthner and Ricci, 2004). For tourism organisations, both private and public, the internet has become one of the most important marketing communication channels (Wang and Fesenmaier, 2006).
Carson (2005) provides a summary of internet applications for tourism organisations and enterprises within an “online architecture” and proposes five important functions of the internet: communication, promotion, product distribution, management and research. This pre-supposes that enterprises would endeavour to learn and use these applications, enter partnerships and make effective use of the internet. Albert and Sanders (2003) talk about the four Ps marketing mix (of product, place, price and promotion) being enhanced by the four Cs of customer solution, cost, convenience and communication, while Newhagen and Rafaeli (1996) show that compared with other distribution and transaction channels the internet contains a truly huge amount of information which can be customised and personalized.
A recent UK survey found consumers trusted more sites with reviews than professional guides and travel agencies (eMarketer, 2007). Similar research in Germany and Austria showed online customer ratings have high credibility with consumers (Österreich Werbung, 2007) and a recent study by Gretzel et al. (2007) undertaken with tripadvisor.com users found that looking at other tourists’ By April 2007 there were apparently over 70 million blogs with around 120,000 new blogs created each day (Sifry, 2007) and currently there are around 102 million blogs, with 175,000 new blogs added each day (http://technorati.com). A study undertaken by Compete Inc. has found UGC has an influence on around 54 G. Akehurst 123 US$10 billion p.a. in online travel bookings and over 20% of consumers rely on UGC when trip planning (Sarks, 2007).
This information is clearly valuable to the tourism sciences industry. The advantage of having access to information and feedback, make users prefer online booking. Studies about consumer’s online behavior revealed that the decision of acquiring a product is very much influenced by other buyer’s opinions (Bucur, 2014). In the past one had trouble deciding to make a booking to a hotel not found in a guide or recommended by an agency, due to the lack of information. Now the problem is the excess of information. With so much sites providing rating and feedback, is impossible to read it all and become extremely difficult to find the relevant information for one to get an overall image. Some sites only provide a rating system (by stars or numbers) or text reviews, others also provide a text review and a rating (Kasper & Vela, 2013).
Big Data & Data Mining
Big data which is regarded as a prominent area of future technology has already started gaining attention in the tourism industry. Banjelloun et al confirms that big data’ is enabling new opportunities for research and analysis in a myriad of domains, including tourism. Big Data in the tourism sector, allows to extract valuable insight, such as better understanding tourists’ behaviours, detection of evolving preferences and needs, forecasting tourism demand for a destination, recommendation in real-time hotels, restaurants and activities to tourists according to their preference. Data mining is the extraction of interesting, previously unknown knowledge from potentially large and noisy datasets. Data mining could be especially valuable to the field of tourism science where abundant amounts of information regarding people’s movements and activities is available, yet untapped. Luke Bermingham and Ickjai Lee (2014 )
Database contains the important hidden information used for decision making. Different databases like relational, object oriented, transactional and spatial databases consist on the complex dataset B. Seerat & F. Azam (2012). The rapid growth in databases has created the need to develop such technologies to extract the nuggets of knowledge and information intelligently. Major data mining techniques used to extract the knowledge and information are: generalization, classification, clustering, association rule mining, data visualization, neural networks, fuzzy logic, Bayesian networks, genetic algorithms, decision tree, multi agent systems, CRISP-DM model, churn prediction, Case Based Reasoning and many more Zhai et al (2009)
Detection and extraction of opinions from online reviews is part of a new area of research developed in the last decade. Opinion mining, also called in scientific literature as sentiment analysis, studies the determination and classification of opinions or feelings expressed in text, through the use of computing machines. The challenge of the research area is to extract knowledge from unstructured data. The reviews contains opinions expressed in natural language, common to people but uninterpretable by computers (Bucur, 2014).
Khan and et al. presented literature survey of opinion mining. Their study focused various ma-chine learning algorithms for sentiment classification from unstructured reviews. They have discussed various applications of opinion mining such as search engines, recommendation systems, email filtering, Web ad filter-ing, questioning/answering systems.
With social media data, Miah et al have developed a method composed of four techniques to identify and predict tourist behavior and to forecast future and seasonal tourism demands for the purposes of tourism development, management and planning; the four techniques are as follows: 1) Textual metadata processing to identify keywords, which reflect tourists’ interests when taking photos, 2) geographical data clustering to identify popular location(s) for each of the identified tourist interests, 3) representative photo identification to identify the photo subjects that most frequently appear for each tourist interest, which provide insights into tourist’s own experience and interests, and 4) time series modelling to predict future tourism demand and reveal seasonal travel patterns for future planning and decision-making.
There are several Big Data projects launched and have demonstrated the potential of big data in the tourism domain.
Flux vision is an innovate solution initiated by Orange Labs, analyzes population flows in real-time using data from Orange’s mobile network. It converts millions of items of technical information from the mobile network.
Tourinflux project funded by public investment program for the future (PIA), The project aims at providing actors of the tourism industry with a set of tools allowing them to handle tourism data and provide an extensive dashboard to visualize and interpret the information available about the territory. With our big data system, we exploit mass data obtained from different websites, mobile applications, geo-localization, social media and connected objects to target and recommend the most appropriate tourism offer according to user profile, to monitor and analyze tourists ‘opinions in order to improve the customer experience and to provide dashboards, useful for decision-making and thus promote intelligent tourism in Morocco and contribute to its economic development.
In order to answer the research question of this paper, we will take the study into two parts. First (1) direct review of literature within the last decade in tourism domain with computational social science approaches. (2) Survey among the non-probability sample of tourism scholars and practitioners in the industry. The aim of reviewing literature is to provide a concise overview of general key methodologies that is used for tourism studies and reveal whether computational social science is integrated in tourism. Secondly, the survey will try to understand the frequency of usage of computational social science in tourism research, it’s utility, reliability and effectiveness in the tourism research and developing businesses. The sample will encompass two sub-groups. The first sub-group will consist of academics with different degree (e.g. master studies, Ph.D., associate professors and full professors). The second subgroup will encompass representatives from the tourism and hospitality industry. The questionnaire will include questions regarding current computational social science that they have been using in their studies and it’s challenges and barriers in CSS application process. Which kind of data are they usually using when they say computational social sciences like (administrative, commercial, photographs, videos and audios, social media data). Which specific type of problems are they looking to solve or which information are they trying to retrieve through CSS will be our interest and what skills and collaborations tourism scholars and practitioners would need in order to apply CSS.
From our study we expect to clearly outline the opportunities created by CSS in the field of tourism. The contribution made by the use of CSS in acquiring the new knowledge and solving various social issues will be made evident. We anticipate to find out the problems faced by the academicians and research community regarding the use of CSS in the process of quantitative studies. We expect that our findings from our study and research questions will allow both academicians and industry practitioners to assure the true potential of CSS and encourage to make better use of it in their study and work.
This year’s International Student Conference on Tourism Research (ISCONTOUR), organized jointly by FH-Krems and MCI Innsbruck, attracted about 300 participants from over 30 nations to Innsbruck to present their accepted papers.
Master’s students of the program Innovation and Management in Tourism (IMT) were also represented. The articles from the research seminar series “eTourism Research” (Prof. Roman Egger and Prof. Barbara Neuhofer) were submitted and all six papers were assessed in a tripple-blind-review procedure, despite a 50% rejection rate. Thus, the entire 4th semester of the Master students was on site to present their results at the ISCONTOUR.
The culmination of the event was the Best-Paper Award. Two groups won first and second place in the Best ICT Paper Award at the international competition. Victory was won by the study group Augmented Reality. They developed an AR prototype for the Salzburg Zoo to provide information about animals living in the zoo and tested the acceptance of such a solution. Second place went to the Virtual Reality group. In an experiment and with the help of biofeedback (heart rate, skin conduction ), they examined how 4D Virtual Reality (as additional stimuli, smells, wind, heat, etc.) differed from classic virtual reality in a holiday scenario with respect to the construct “presence”.
Do you know, where our students come from and to where we are exporting eTourism Know-How?