Impact Of Additive Manufacturing On Business Model Innovation In The Manufacturing Industry Essay.

Investigate the impact of Additive manufacturing on the business model innovation in the manufacturing industry - “A journey from prototyping to home fabrication”.

The Potential of Additive Manufacturing

This report proposes to conduct a research on the impact of additive manufacturing on business model innovation in the manufacturing industry. Technological innovation is measure of changing the market structure systematically and creating value. Additive manufacturing is disruptive innovative having an endless potential in the future market. Therefore, this study will aim to focus on value creation and change in business model innovation due to various factors such as economic effects.

Additive manufacturing has the potential of causing an industrial revolution due to the disruptive ability of this technology. Additive manufacturing will change the convention production systems and organizations will have to adapt to the change in need. The demand for the additive manufacturing is expected to increase significantly in the upcoming years so the organizations in the manufacturing industry will have to develop effective business models in order to meet the needs of the consumers (Bogers, Hagar and Bilberg 2016). The impact of additive manufacturing is not limited to few firms but will have a massive influence of the market structure.  The current trends in the market shows that there has been steady increase in the manufacturing of 3D printers in both industrial and home sectors. This has almost increased the scope and scale of options of manufacturing (Mellor, Hao and Zhang 2014). In the initial phase, the main purpose of using additive manufacturing technology was limited to developing the prototypes and prototyping is a common phenomenon in the market.  However, there has been significant hype in additive manufacturing as it has the potential of replacing the traditional technologies of manufacturing and production. This shows that additive manufacturing has already common in prototype and it is on its process where it will be used for home fabrication on a regular basis (Frazier 2014). Therefore, this study will depict the journey from prototyping to home fabrication for Additive manufacturing and the role of suitable and effective business model will be significant. This is a relative new topic and even though researches have been conducted on similar topics but empirical aspect has not been taken into consideration. This study has proposed a mixed research method for analysis of both subjective and objective view to understand the theoretical and practical implications along with the difference between them.

The objective of the current study are as follows:

• Investigation of the factors driving the growth in Additive manufacturing in the manufacturing industry
• Investigation of the factors driving the change in business model in the manufacturing industry Evaluation of the impact of additive manufacturing on business model innovation in the manufacturing industry

Primary question

• What is the impact of additive manufacturing on business model innovation in the manufacturing industry?

Secondary questions

• What are the factors driving the growth in Additive manufacturing in the manufacturing industry?
• What are the factors driving the change in business model in the manufacturing industry?

Research hypothesis 

H₀: There will be no change in business model innovation due to the increase in demand of additive manufacturing in the manufacturing industry

Role of Suitable and Effective Business Model

H₁: There will be change in business model innovation due to the increase in demand of additive manufacturing in the manufacturing industry

Weller, Kleer and Piller (2015) states that additive manufacturing refers the act of joining materials, layer by layer to develop three dimensional models. Additive manufacturing is a technology that is flexible in nature which means that it can be used for developing customized and personalised products. Digital manufacturing process is being used for directing 3D design ideas into parts without the use of moulds or tools. However, the technology is still not developed to that extent that it can be used for mass production as the throughput speed  is quite low and it is difficult to match up to the conventional process of manufacturing.  As opined by Rayna and Striukova (2016), reaching common standards of quality in the manufacturing industry is difficult to reach using additive manufacturing as it has not been defined effectively. According to Weller, Kleer and Piller (2015) the principle of layer manufacturing is a futuristic vision which can produce a functionally integrated part in one production step.  As stated by Huang et al. (2013), the need of assembly activities will be reduced considerably when layer manufacturing becomes a common phenomenon. This shows that there will be considerable change in the organizational processes when this principle of manufacturing can be put to use effectively by the manufacturing companies. As stated by Frazier (2014), additive manufacturing has a futuristic vision where it can transform the ideas of innovators to physical products. However, it is not feasible to fit this technology into the conventional business model as considerable amount of changes is required. This can somehow indicate that additive manufacturing and layer manufacturing will revolutionize the manufacturing organization and there will be considerable amount of change in business model (Baumers et al. 2016). Business model innovation is required to commercialize this technology of additive manufacturing.

Research methodology describes the philosophical framework for conducting the research. Research methodology is developed based on Saunders Research onion which unfolds all the aspects of the study. Research methodology is generally chosen based on the goals and objective of the study. In this current study, experimental method will be used to facilitate the description of behaviour, cause and effect relation and prediction from one variable to alternative variable (Taylor, Bogdan and DeVault 2015).

Research philosophy 

Research philosophy is chosen based on the perception of the reality of the researcher and the knowledge gained is defined. The practical consideration and perspective of a research is quite different for different research and philosophical approach defines the strategy used in a particular research (Saunders et al. 2015). In this current study, pragmatism is the research philosophy which has been taken in consideration. This will facilitate in keeping both the ontological view and the epistemological view. This means that the research will use different ways to bring out positive outcomes.

Research Methodology

Research approach 

Research approach is defined as the procedure and plans of the research and in this current study, deductive approach will be used to develop significant results. Deductive approach uses logical reasoning based on phenomenon and observations (Singh 2015). The causal relationship between two variables can be measured using this method and develop generalised findings.  The developed hypothesis can be tested using this approach and will facilitate establishing the relationship.

Research design 

Research design defines the plan of action in the research and two general research designs are conclusive and exploratory. However, in this current study, the conclusive research design has been chosen as it will facilitate in developing the relationship between the two components (Maxwell, Chmiel and Rogers 2015). Conclusive research can be further divided in to descriptive and causal research but as the study will use mix method analysis, sequential explanatory is the chosen research design.

Data collection and analysis 

Primary data collection method will be used to gather data for the research. The study consists of mixed methods so both quantitative and qualitative data will be collected. The quantitative data will be collected by using an online survey and will consist of close ended questions. The qualitative data will be collected by using an open-ended questionnaire. The quantitative data will be collected using inferential statistical analysis and SPSS is the tool that will be used for the analysis (Palinkas et al. 2015). The study will test the hypothesis and use regression analysis to identify the degree and nature of relationship between the variables. The qualitative data will be analysed using coding where both open coding and axial coding will be used. The analysis of both the quantitative and qualitative data will be compared to verify and infer the results.

Sampling 

The study will use both probabilistic sampling and non-probabilistic sampling to collect relevant data.  The quantitative data will be collected through simple random sampling where the respondents will be selected randomly so everyone in the population has the equal opportunity of being chosen for the study. In non-probabilistic sampling, convenience sampling will be used to select respondents based on suitability (Morse 2016). The survey will comprise of 100 respondents comprising on employees working in manufacturing sector and the interview will consist of 5 managers from the companies in the manufacturing industry.

Reliability and validity 

In order to check the reliability of the data, the study will use test retest reliability to check whether similar results are obtained from the study or not. Validity of the questionnaire will be checked by using a pilot study where the questionnaire will be sent to 10 respondents to take their opinion on the format, tone and relevance of the questions (Heale and Twycross 2015). This will facilitate in checking the divergent and convergent validity in the study.

Research Philosophy and Approach

Ethical consideration 

The study will use information and consent to make sure that the participants have prior information about the research and they participate on their own (Quinlan et al. 2019). The study will protect the privacy and anonymity of the respondents and the data collected will be deleted after the study is complete.

Expected results 

Additive manufacturing is expected to have a great deal of influence on innovation and technology in the manufacturing industry. The study is expected to identify the type of association between business model innovation and additive manufacturing. The research will also expected to provide a clear picture about how the use of additive manufacturing will be at home fabrication level in the near future and the implications of this transition from prototyping to home fabrication.

Research Plan

References 

Baumers, M., Dickens, P., Tuck, C. and Hague, R., 2016. The cost of additive manufacturing: machine productivity, economies of scale and technology-push. Technological forecasting and social change, 102, pp.193-201.

Bogers, M., Hadar, R. and Bilberg, A., 2016. Additive manufacturing for consumer-centric business models: Implications for supply chains in consumer goods manufacturing. Technological Forecasting and Social Change, 102, pp.225-239.

Frazier, W.E., 2014. Metal additive manufacturing: a review. Journal of Materials Engineering and Performance, 23(6), pp.1917-1928.

Heale, R. and Twycross, A., 2015. Validity and reliability in quantitative studies. Evidence-based nursing, pp.ebnurs-2015.

Huang, S.H., Liu, P., Mokasdar, A. and Hou, L., 2013. Additive manufacturing and its societal impact: a literature review. The International Journal of Advanced Manufacturing Technology, 67(5-8), pp.1191-1203.

Maxwell, J.A., Chmiel, M. and Rogers, S.E., 2015. Designing integration in multimethod and mixed methods research. In The Oxford handbook of multimethod and mixed methods research inquiry.

Mellor, S., Hao, L. and Zhang, D., 2014. Additive manufacturing: A framework for implementation. International Journal of Production Economics, 149, pp.194-201.

Morse, J.M., 2016. Mixed method design: Principles and procedures. Routledge.

Palinkas, L.A., Horwitz, S.M., Green, C.A., Wisdom, J.P., Duan, N. and Hoagwood, K., 2015. Purposeful sampling for qualitative data collection and analysis in mixed method implementation research. Administration and Policy in Mental Health and Mental Health Services Research, 42(5), pp.533-544.

Quinlan, C., Babin, B., Carr, J. and Griffin, M., 2019. Business research methods. South Western Cengage.

Rayna, T. and Striukova, L., 2016. From rapid prototyping to home fabrication: How 3D printing is changing business model innovation. Technological Forecasting and Social Change, 102, pp.214-224.

Saunders, M.N., Lewis, P., Thornhill, A. and Bristow, A., 2015. Understanding research philosophy and approaches to theory development.

Singh, K.D., 2015. Creating your own qualitative research approach: Selecting, integrating and operationalizing philosophy, methodology and methods. Vision, 19(2), pp.132-146.

Taylor, S.J., Bogdan, R. and DeVault, M., 2015. Introduction to qualitative research methods: A guidebook and resource. John Wiley & Sons.

Weller, C., Kleer, R. and Piller, F.T., 2015. Economic implications of 3D printing: Market structure models in light of additive manufacturing revisited. International Journal of Production Economics, 164, pp.43-56.