Journal of Student Research 2015

79

Contingency Valuation and Interviews in Open-Source Software Market:

CONCLUSION The market for statistical software provides economics with the

unique challenge of adapting long-standing theoretical models to some of the new challenges that information goods have presented in the digital age. Open-source software production utilizes rational software developers producing sections of code. They do this with no present benefit other than peer acknowledgment (ego-satisfaction) and gain in utility. Professional and academic economists who use statistical software seem to use price as a signaling mechanism of quality. For goods with no price, their perceptions about the quality would be negative. They are behaving rationally but may be overvaluing software that has a >0 price. The value in this research is the mixed-methods research design increasing the likelihood of accurate ques tions in the initial survey round. Willingness-to-Pay models have not evalu ated open-source goods on the scale they merit. The growth of technology companies, increase in open-source implementation, and potential market failure are all the main reasons further research should be investigated. The lack of valuable data found in this market may create a concern that the inherent structure of the methodology may be flawed. The data constructs mean very little inside of the testing group. It is the wide-ranging appeal to utilize mixed-methodology when data collection feasibility is low. Researchers will need to be careful to not introduce this bias as it can cause an increase in the anchoring effect (Boyle, 1979). It does encourage a survey taker to think about the question far more. While increasing reliabili ty, it also increases survey dropout rate. Investigators must review requests to be sent out over an extended period (12-18 months), comprising a large num ber of respondents (200 to 300). It also should involve a greater geograph ical scope than this research utilized. The overall process of using discrete choices, risk aversion, and factor analysis could provide intriguing statistics on this type of market. This theory of collaborative networks would have had a much larger impact on this paper’s final results if the interview transcripts were applicable to contributors involved in this system. Future research into how it is best suitable to use transparent, ethically-based, and collective dis tribution systems in a profit-seeking environment should be conducted.