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There is growing interest in innovative online problem-solving models such as crowdsourcing to serve individuals, firms and the society as a whole. Crowdsourcing is the combination of efforts from various sets of individuals who are either volunteering or working part-time for socioeconomic production, basically in the cyber world. This hybrid work model is already in use by businesses and entrepreneurs; some of the platforms include Amazon mechanical Turk, 99designs, Hit RECORD and Design Crowd.

Much has been parleyed and published, and this is primarily because of the efficient socioeconomic potentials crowdsourcing offers.

This paper addressed the following three questions to help have a better understanding of crowdsourcing: who can perform crowdsourcing? why it is relevant to crowdsource in this present proliferated internet age and if there are going to be some changes in the future and the last but not the least what can be done to promote it in the society?

This paper discusses the three W’s and concludes with challenges facing the crowdsourcing work model.

The unprecedented growth in the volume, variety and velocity with which data is generated and collected over the last decade has led to the spread of big data phenomenon. Organizations have become increasingly involved in the collection and analysis of big data to improve their performance. Whereas the focus thus far has mainly been on big data collected from customers, the topic of how to collect data also from those who are not yet customers has been overlooked. A growing means of interacting with non-customers is through crowd-based phenomena, which are therefore examined in this study as a way to further collect big data. Therefore, this study aims to demonstrate the importance of jointly considering these phenomena under the proposed framework.

This study seeks to demonstrate that organizations can collect big data from a crowd of customers and non-customers through crowd-based phenomena such as crowdsourcing, citizen science and crowdfunding. The conceptual analysis conducted in this study produced an integrated framework through which companies can improve their performance.

Grounded in the resource-based view, this paper argues that non-customers can constitute a valuable resource insofar as they can be an additional source of big data when participating in crowd-based phenomena. Companies can, in this way, further improve their performance.

This study advances scientific knowledge of big data and crowd-based phenomena by providing an overview of how they can be jointly applied to further benefit organizations. Moreover, the framework posited in this study is an endeavour to stimulate further analyses of these topics and provide initial suggestions on how organizations can jointly leverage crowd-based phenomena and big data.

The purpose of this study is to examine the trend toward purchasing locally grown food and evaluate if tourists visiting Hawai'i are willing to pay more for locally produced foods that are more ecologically sustainable.

A research questionnaire was developed in order to investigate the attitudes and behaviors of tourists from the continental United States visiting Hawai'i in purchasing locally grown food in Hawai'i. The final sample includes 454 valid survey responses collected via Momentive, a market research services company.

According to the findings of this study, there are economic prospects to expand the use of locally cultivated food into the tourists' experience, as well as a willingness for tourists to support these activities financially. The Contingent Valuation study revealed that tourists from the continental United States were ready to pay a higher price to purchase food that is locally grown, signifying that tourists to Hawai'i are willing to aid the local agriculture business by increasing their restaurant/hotel meal bill, which will help Hawai'i become a more sustainable tourist destination.

While tourists from the United States mainland, which is the “an islands” top tourist market, have agreed with paying extra or an additional fee for locally grown food products, this study might not accurately represent the attitudes and behaviors of international tourists visiting Hawai'i. Future research should focus on the international tourist markets which may have different social norms or cultural differences thus could provide a broader spectrum of the current study's findings.

The results of this study provided quantitative evidence that tourists from the United States are interested in purchasing locally grown food items in Hawaii in addition to their willingness to pay an additional fee for these locally grown food products at a restaurant or a hotel dining room, thus addressing a gap in the tourism research.

The 2019 Global Assessment Report on Disaster Risk Reduction (GAR) cites earthquakes as the most damaging natural hazard globally, causing billions of dollars of damage and killing thousands of people. Earthquakes have the potential to drastically impact physical, social and economic landscapes; to reduce this risk, earthquake early warning (EEW) systems have been developed. However, these technical EEW systems do not operate in a vacuum; the inequities in social systems, along with the needs of diverse populations, must be considered when developing these systems and their associated communication campaigns.

This article reviews aspects of social vulnerability as they relate to ShakeAlert, the EEW system for the USA. The authors identified two theories (relationship management theory and mute group theory) to inform self-reflective questions for agencies managing campaigns for EEW systems, which can assist in the development of more inclusive communication practices. Finally, the authors suggest this work contributes to important conversations about diversity, equity and inclusion (DEI) issues within early warning systems and earthquake preparedness campaigns in general.

To increase inclusivity, Macnamara (2012) argues that self-reflective questioning while analyzing perspective, philosophy and approaches for a campaign can help. Specific to EEW campaigns, developers may find self-reflective questions a useful approach to increase inclusion. These questions are guided by two theories and are explored in the paper.

Several research limitations exist. First, this work explores two theories to develop a combined theoretical model for self-reflective questions. Further research is required to determine if this approach and the combination of these two theories have adequately informed the development of the reflective questions.

The authors could find little peer-reviewed work examining DEI for EEW systems, and ShakeAlert in particular. While articles on early warning systems exist that explore aspects of this, EEW and ShakeAlert, with its very limited time frames for warnings, creates unique challenges.