Websites such as Indiegogo and Kickstarter have attracted much attention for their ability to enable organizations and individuals to raise funds from ordinary people who contribute for a number of reasons. This phenomenon is called crowdfunding. Crowdfunding permits organizations and individuals to obtain investments they otherwise might not receive from more traditional sources such as banks, angel investors, and stock markets. A number of now well-known startups had their origins in crowdfunding. More recently, established organizations have begun to use crowdfunding websites not only as a source of finance, but also as marketing platforms. In this way, they have been able to ensure a ready market for their new offerings, with full sales pipelines, and to use the platforms as vehicles to boost brand image and gain support for brand-related causes. This adaptation of crowdfunding for marketing purposes is not without its problems, however, and organizations would be well advised to consider not only the opportunities these platforms provide, but also their limitations and risks.

As the Internet of Things (IoT) begins to dominate the technology landscape, there will be new products and services that will become technically and financially feasible. Internet technologies and advancements in social interaction tools have led to an increase in the use of the crowd as a provider of business solutions. Yet, we have seen a mere fraction of the possibilities of crowdsourcing technologies. This is because most of the development, discussion, and research around crowdsourcing has focused on active-input crowdsourcing. However, the real transformative pressure will come from passive sources of data generated primarily by developing and growing sensor technologies. This next generation of crowdsourcing will be a game changer for entrepreneurial opportunities. As crowdsourcing systems proliferate, more input will be acquired from sensors, artificial intelligence, bots, and other devices. As a result of this explosion, the variety of product and service opportunities will swell as entrepreneurs become more aware of technologies merging—such as the combination of crowdsourcing, sensors, and big data into a new type of entrepreneurship: sensor-based entrepreneurship. The purpose of this research is to contribute by (1) clarifying the next generation of crowdsourcing and (2) developing and presenting a framework to help sensor-based entrepreneurs plan, develop, and map their new products and services.

The industrial context of this study is the hospitality industry, specifically the restaurant business. The hospitality industry has two essential characteristics that make this study valuable. Firstly, with the related travel and tourism industries, the three businesses make up the world's largest industry in the service sector. Secondly, consumers in these industries have been at the forefront of creating and using comment and reviews (i.e., user-generated content (UGC)) to make their purchasing decisions.

Additionally, the demand-side view of strategy is under-researched, especially in the areas of tourism, travel, and hospitality when viewed against the predominant perspectives in strategic management (e.g., resource-based view, transaction-cost economics, positioning, and dynamic capabilities) are supply-side views.

Using the tools available today it is possible to scrape and mine the websites, blogs, forums, communities and other places customers gather and use content analysis techniques to extract meaning from the content. Web 2.0 sources of qualitative data like blogs, forums, feedback (i.e., UGC) can offer better research material than offline traditional qualitative diaries. As a result, using crowdsourced, user-generated content may be a productive marketing research approach to investigate how demand-side strategic decision-making can be supported in the travel, tourism, and hospitality industries.

By using the collective effort of individual customers or groups of customers (i.e., crowdsourcing), the firm can expand the resources to which it has access. One of the primary reasons for the growth of crowdsourcing is the advances and widespread growth of information and communications technologies (ICT), especially Web technologies, have led to an explosion of possible crowdsourcing and co-creation opportunities.

This research examines how this age of crowdsourcing has impacted privacy and the market for privacy. To crowdsource services at a high level often requires an exchange of personal data from the customer to the firm. This study builds three conceptual models that help describe the evolution of crowdsourcing personal information across three different timeframes. These three stages are based on the amount and the level of sophistication of the crowdsourcing processing of information externalities that result from market transactions between the consumer and the firm. Ultimately, through the crowdsourcing of personal and private information are advancing to the most advance stage whereby a digital twin of each consumer is created. This twin can be used in a predictive analytic process to forecast the thoughts, behaviors and future actions of each consumer.

Most research on crowdsourcing focuses on the first section (i.e., the marketing activities) and how crowdsourcing is a positive marketing technique. Much less research aims its attention on the consequences and/or potential negative aspects of crowdsourcing. This second study connects to the overarching research question as it is a conceptual study that explores the consequences of crowdsourcing for market for privacy.