Research Proposal

Market research and potential business models for an animal communication and behaviour translation mobile application

Introduction

With the wide expansion of new media and information technologies, a development that has taken place in the domain of business is the use of mobile applications. Over the past few years, mobile applications have entered many industries and markets, many businesses- for example banks and shops- have developed mobile applications. In this vein, an interesting domain is the development of applications relating to animals, which appears to be a growing market. An example of an animal-related mobile application is Moocall, which is used in agriculture for monitoring dairy cattle close to giving birth. Another example in the domain of pet care is Petsnap which gives information on pet health. Despite the development and growth of mobile applications related to animals, an area that appears to be overlooked is the creation of mobile applications that can enhance our understanding of animal communication and behaviour. This research seeks to address this gap. It explores the potential markets and business models relevant to the creation and developments of applications on the understanding of animal communication and behaviour.    

To give more contextual information on the topic of this study and its importance, the global mobile app market revenue is predicted to be seventy five billion dollars in 2017, Kim et al (2016). This has further positive implications for the growth of applications related to animals, including applications on understanding animal communication and behaviour.

This takes us to the research questions of the MBA study.

I

Research questions

Research Question 1: What are the potential markets for the creation of a mobile application on understanding the communication and behaviour?

Research Question 2: What business models might be applicable to this mobile application?

Literature Review

This literature review will aim to define the key terms of the research proposal then analyse existing research in the domain of the two research questions. Bradbury and Vehrencamp (1998) described animals communication as “information sent by sender to a receiver”. Maynard-Smith and Harper (2003) stated animal communication must carry a “signal that is of interest to the receiver”. The signal is the vehicle for carrying the information. The signal is referred to as the “function of the behaviour”, Dusenbury (1992). Translation in the context of this research relates to the rendering of meaning ( Oxford Dictionary). A market is usually described as the buyers and sellers in consideration. Simon (2009) described markets a the starting point for strategic planning.  A business model is a conceptual tool containing a set of objects, concepts and their relationships with the objective to express the business logic of a specific firm. “This definition is sufficiently broad to embrace the different reflections on business models that sprung up in different fields such as e-business, computer science, strategy or management,” Pateli and Giaglis (2003).

In relation to the first research question the research will explore the current market for the application and will contextualise the research within the growing vegan movement. In this vein, research from a report commissioned by the Pet food manufacturers association in 2017 calculated the total number of pets in the UK is estimated to be fifty four million. Fish account for around thirty three million other animals around twenty one million. Twelve million households have a pet. Forty four percent of all UK households have a pet.   Current research from the RSPCA indicates that there are eight and half million dogs and eight million cats in the UK. Making them the largest two pet groups behind fish. The research will assess the market prospects for the application being initially aimed at cat and dog owners. There is a growing consensus that there is much more to be understood and learnt from animals and that they should no longer be treated as a wholesale commodity for consumption. Statistics from the 2016 Google Trends showed a ninety percent increase in ‘vegan’ searches in last twelve months (veganfoodandliving.com). The increase in animal welfare searches combined with the number of pets in the UK may indicate a strong potential market for a mobile application for animal communication and behaviour translation.

The cost of developing an app can range anywhere between £50,000 to over £1 million (savvyapps.com). Stated in research by Kumar et al (2016), before developing a mobile application there must be a precise cause defined to generate one. Therefore it is important that scope and criteria of an initial market version of the mobile application is defined. There is the ability with mobile applications to provide improvements via updates at any stage to the user however it is important to define the aims of an initial market ready application. Current research published on savvyapps.com carried out using Survey Monkey indicates a reduction of forty eight percent in the number of mobile application published that are paid for at the point of download between 2011 and 2017. Also published on savvyapps.com is an increase of thirty nine percent of the volume of apps that generate revenue through in app purchases and an eight percent increase in those that generate revenue through advertising between 2011 and 2017. This leads to a discussion on the importance of ‘big data’ in driving innovation in business models.

Currently, there are six popular app monetization models: direct sales, freemium, subscription, in-app purchases, sponsorship and crowdfunding. This research aims to  explore the commercial value and marketing avenues relating to generating shorter term direct revenue but also the longer term potential value of data collected from data involving animal communication and behaviour translation in terms of the potential new markets and services related to animal well-being, animal human interaction and learning.

The term ‘big data’ refers to “large volumes of complex and variable data that require advanced techniques and technologies to enable the capture, storage, distribution, management, and analysis of the information.” (TechAmerica Foundation's Federal Big Data Commission, 2012). Big data is a driver of many of the new business model developments. This is because exploring the value of data is of particular interest to internet companies because the creation of revenue can be difficult because of customer expectations that services should be free. Bringing together large data-sets allows for matching and connections that were not previously possible. “Linkages between, for example, weather data and satellite images for the catastrophic modelling performed by the Willis Group, or online and offline purchasing behaviours performed by Tesco, potentially enable businesses to make better informed decisions.” Schroeder, R. (2016). Over the past decade, many improvements have taken place in the domain of information technology such as the gathering, storage and analysis. For example the development of cloud storage and infographics. Big data has emerged as important domain in business management as it offers insight in almost all areas of business management, for example customer satisfaction and consumer insights.

Research Approach and Methods

The conceptual framework and theoretical underpinning of the research are from an ontological position of a pragmatist perspective and view of knowledge, for example with a commitment to uncertainty, and an acknowledgement that any knowledge is relative and not absolute. This approach is based on the view that reality is continuously questioned, negotiated and interpreted. Qualitative and quantitative methods are often combined in research with a pragmatic approach (Johnson & Onwuegbuzie, 2006). The epistemological stance of the research is aligned to the pragmatist objective to produce socially useful knowledge. This research aims to examine a socially useful mobile application with the understanding that current realities are constantly renegotiated.

To this aim the research will draw upon a variety of tools from both books, journals, reports, studies, databases and statistics as well as focused interviews ( see below).  To explore the first research question of the potential market for an animal communication and behaviour translation mobile application this research will explore relevant marketing database and trends that will help explore the prospects of this application. For example, the size of the market related to animals and revenue from mobile applications. Following the analysis of the market research focused interviews will be undertaken to give further insights into the key issues emerging from the data analysis. In addition the interviews will aim to explore the potential development from a technical view. The conference on  Animal Computer Interaction 2017 will be important to the research, for example through exploring key issues relating to development of the mobile application with researchers in the field.  Example of leading researchers in the field of Animal Computer interaction are Dr. Steve North at Exeter University and Dr. Clara Mancini at the Open University. The market research will also aim to draw upon relevant departmental expertise available at UCLAN for example Dr. Bogdan Matuszewski who specialises in computer vision. The insight provided, will help with understanding the process of translating visual data.

In light of the analysis and interpretation of secondary data ( i.e. statistics, reports and trends) primary data questions can answered as to which business models are most applicable to the development of this mobile application. Therefore, the focused interviews will also incorporate that aim to gauge the applicability of relevant business models, for example, in app purchases and data value.

Consent and potential issues.

As with any research methodology there are limitations and “problems with this design arise largely from difficulties with interpretation.” (Brewerton and Millward, 2001, p .53), i.e. the analysis of data relies on the researcher's interpretation of what is said.

Research Timetable

November 2017

Topic decision and review of literature

May 2017 - October 2017

Research Proposal  

November 2017

        ACI conference

    Secondary research gathering

           Focused interviews

February 2018 onwards.

Analysis followed by finalising dissertation        

References.

Atkinson, P., Delamont, S. and Coffey, A. (2004). Key themes in qualitative research: Continuities and changes, Rowman Altamira.

Basit, T. (2003). 'Manual or electronic? The role of coding in qualitative data analysis', Educational research, 45(2), pp. 143-154.

Feilzer, M. (2010). 'Doing mixed methods research pragmatically: Implications for the rediscovery of pragmatism as a research paradigm', Journal of mixed methods research, 4(1), pp. 6-16.

Gill, P., Arlitt, M., Li, Z. and Mahanti, A. (2007). 'Youtube traffic characterization: a view from the edge'. Proceedings of the 7th ACM SIGCOMM conference on Internet measurement.

Harms, W. F. (2004). 'Primitive content, translation, and the emergence of meaning in animal communication', Evolution of communication systems: A comparative approach, pp. 31-48.

Kumar, N. A., Krishna, K. H. and Manjula, R. (2016). 'Challenges and Best Practices in Mobile Application Development', Imperial Journal of Interdisciplinary Research, 2(12).

Kim, H., Kankanhalli, A. and Lee, H. (2016). 'Investigating decision factors in mobile application purchase: A mixed-methods approach', Information & Management, 53(6), pp. 727-739.

Ma, Z. (. (2015). 'Towards computational models of animal cognition, an introduction for computer scientists', Cognitive Systems Research, 33, pp. 42-69.

Mancini, C. (2017). 'Towards an animal-centred ethics for Animal–Computer Interaction', International Journal of Human-Computer Studies, 98, pp. 221-233.

North, S., Hall, C., Roshier, A.L. and Mancini, C. (2015). 'HABIT: Horse automated behaviour identification tool: A position paper'.

Osterwalder, A., Pigneur, Y. and Tucci, C. L. (2005). 'Clarifying business models: Origins, present, and future of the concept', Communications of the association for Information Systems, 16(1), pp. 1.

Palaiologou, I., Needham, D. and Male, T. (2015). Doing Research in Education: Theory and Practice, Sage.

Saunders, M. N. and Lewis, P. (2012). Doing research in business & management: An essential guide to planning your project, Pearson.

Schroeder, R. (2016). 'Big data business models: Challenges and opportunities', Cogent Social Sciences, 2(1), pp. 1166924.

http://www.veganfoodandliving.com/google-trends-shows-90-increase-in-vegan-searches-in-2016/

https://medium.com/@sm_app_intel/mobile-app-industry-revenue-statistics-wheres-the-money-come-from-82581a45186d

http://www.pfma.org.uk

https://savvyapps.com/blog/how-much-does-app-cost-massive-review-pricing-budget-considerations

                                                                        

                                                                

Appendix 1.

Source: https://hbr.org/2012/12/what-a-big-data-business-model