Metaverse and the Future of Work. The Effect of Individual Characteristics on User Adoption.

Digital technologies have been transforming the way work is performed in organizations. With the evolving workplace, new communication technologies such as Zoom and Slack received tremendous enterprise support. As more knowledge work has been performed remotely, to recreate an in-office experience online, new immersive technologies, such as the Metaverse can be used. However, the adoption of Metaverse may depend on the individual characteristics of employees. The goal of this research is to investigate factors influencing the employee adoption, such as personality traits and cultural characteristics. The results of this research can be beneficial for designers to understand the factors contributing to Metaverse adoption in the workplace

Creative Boredom in the Time of Covid-19

For many of us the lifestyle has changed during the time of Covid-19 pandemic. As we started spending more time indoors, limiting face-to-face interactions, sport activities and live entertainment has become a new way of living that requires some adjustments. While there are benefits of staying home such as less need to commute, prolonged staying at home may lead to boredom. Some types of boredom inspire creative behavior. With millions of people staying at home, the collective boredom leads to completely new experiences often utilizing digital technology. Mapping emerging online activities and determining factors of creativity and innovation in crisis using collective and individual boredom levels is an interesting research question. A variety of techniques can be employed with a focus on aggregate search data as a proxy for public interest. The results can be insightful for forming future policies on pandemics

To Gamify or Not? The Development of a Gamified Data Collection Instrument for User Self-Reported Data

In this paper we discuss a gamified data collection instrument that is designed to indirectly collect user personality traits data. Specifically, we provide an integrated view of how the individual’s personality data can be obtained via gamified systems and discuss the influence of gamified systems on user enjoyment and data quality. With a sample of 226 individuals, we examined two research questions. First, we explored how personality characteristics can be obtained via gamified survey systems. Second, we investigated how gamified systems affect user enjoyment and focused attention as opposed to traditional online surveys. Our results suggest that gamified systems have the potential to capture user data and at the same time provide a higher level of enjoyment for users. This study paves the way for future research investigating whether gamification is an appropriate tool to improve the quality of user self-reported data

Personality and games : enhancing online surveys through gamification

In this research, we evaluate the moderating role of personality on enjoyment and attention associated with a gamified data collection instrument, and the attractiveness of a surveying organization. In an online experiment, we compare a gamified survey with a traditional survey. The results suggest that gamified surveys are more enjoyable and users are more attentive when filling out gamified surveys. Specific personality traits moderate the effect of attention and enjoyment related to gamification, and the enjoyment associated with gamification increases the attractiveness of a surveying organization. These findings have theoretical and practical implications to improve the design of existing online surveys

Why Should I Like AI? The Effect of Personality Traits on the Acceptance of AI-Driven Virtual Assistants in the Workplace

New technologies and artificial intelligence (AI) are influencing the way the work is performed now and will be performed in the future. The World Economic Forum (2020) estimated that by 2025, machines will replace 85 million jobs. However, millions of new jobs facilitated by the collaboration of humans and machines will also emerge. Thus, it is important to understand the drivers of these changes to equip organizations and people with necessary knowledge and get ready for new opportunities. One of the prominent manifestations of AI in the workplace is the virtual assistant, a technology that is based on natural language processing and machine learning. Virtual assistants can be activated either via text or voice and are designed to automate certain tasks and improve employee productivity. Gartner predicted that by 2025, 50% of knowledge workers will use a virtual assistant daily (Bradley 2020). To achieve optimal workforce transformation, both organizations and employees should embrace AI. However, an interesting question is whether the employees are willing to accept AI, and if so, are there differences in individual acceptance? We propose that in addition to task characteristics, the AI acceptance is contingent upon individual user characteristics, such as personality traits. Personality is a combination of the attributes, qualities and characteristics of individuals that distinguish their behavior, thoughts, and feelings (Saucier and Srivastava 2015). Personality accelerates various aspects of human behavior including work, such as career mobility and career success, leadership, job satisfaction, and product preferences. Our aim in this research is to investigate the acceptance of AI-driven virtual assistants through the lens of individual employee characteristics. The results of this research will be useful to organizations that consequently can offer customized AI solutions to improve employee experience by adapting the communication behavior of virtual assistants to individual personality characteristics. In addition, the results will be useful to employees. By designing a virtual assistant that is compatible with an employee, we expect a better collaboration between humans and machines and consequently improved productivity and satisfaction. The study will be conducted in two stages. In the first stage, we will collect information about AI task characteristics through direct semi-structured interviews contrasted with the O*NET OnLine database sponsored by the U.S. Department of Labor (https://www.onetonline.org), as well as deployment of user personality characteristics. In the second stage, we will test potential AI solutions

Subjectivity of Diamond Prices in Online Retail: Insights from a Data Mining Study

Diamonds belong to a unique product category whose perceived value is largely dependent on socially constructed beliefs. To explore the degree to which the physical properties of a diamond can be used to predict the diamond price, we perform data mining on a large dataset of loose diamonds scraped from an online diamond retailer. We find that diamond weight, color and clarity are the key characteristics that influence diamond prices. The data mining results also suggest a high degree of subjectivity in diamond pricing that may reflect price obfuscation strategies employed by diamond retailers

From Classroom to Metaverse. Towards Methodology for Upskilling and Reskilling in the Age of Web 3.0

This century is characterized by swift changes in technology and digital environment. We live in a connected data-driven society with omni-social components and diverse range of capabilities that transform how we engage with friends, family, work and other facets of our life. Adapting to these changes requires new competencies, and for many individuals – upskilling and reskilling. These changes have become possible due to advancements in connectivity via the internet and the web. The first generation of the web, Web 1.0, provided global reach by allowing information access from any location. From the education perspective, this innovation enriched access to information and publisher resources. However, the majority of work-related training happened using traditional in-person approach. The next iteration of the web - Web 2.0 created an unparalleled reach characterized by high interactivity, social connectivity, and user-generated content. Web 2.0 made possible omni-social channels and opened possibilities for information in written, audio and video forms to be simultaneously available around the world. It gave rise to gamification and social rewards by bringing game mechanics to serious tasks. It enabled gig economy, democratized trading and created new web-centric models. Education benefited from MOOCs, gamified solutions, and video webinars such as Zoom, making knowledge accessible anywhere in the world. The next iteration of the web – Web 3.0 is emerging. Web 3.0 is characterized by decentralization that provides users with greater control over their information. With the internet of things connectivity, the user interaction can be vastly increased and new capabilities such as semantic web (Berners-Lee et al. 2001) and built-in AI applications may emerge while providing immersive experiences such as metaverse. There is a focus shift to blockchain, crypto-assets, NFT, decentralized finance, and smart contracts that requires different type of upskilling and reskilling. The goal of this research is to create a methodology of emerging needs for upskilling and reskilling in a new digital world, including gig careers, social media influencers, crypto-asset experts, and other emerging careers. To provide adequate training, we propose immersive scenarios, offering increasing media richness and modeling human interaction between virtual and real worlds. The first step in this program of research is the methodology and mapping new required skills to particular immersive scenarios while reinforcing skills necessary for vertical, horizontal and lattice career patterns. The proposed tools are branching scenario training based on user decisions in real time while learning through exploration, immersive scenarios with increased sensory richness such as metaverse, and role play serious games. The second step in this program is developing and testing the solutions using both Web 2.0 and Web 3.0 applications

Subjectivity of Diamond Prices in Online Retail: Insights from a Data Mining Study

Diamonds belong to a unique product category whose perceived value is largely dependent on socially constructed beliefs. To explore the degree to which the physical properties of a diamond can be used to predict the diamond price, we perform data mining on a large dataset of loose diamonds scraped from an online diamond retailer. We find that diamond weight, color and clarity are the key characteristics that influence diamond prices. The data mining results also suggest a high degree of subjectivity in diamond pricing that may reflect price obfuscation strategies employed by diamond retailers

Subjectivity of Diamond Prices in Online Retail: Insights from a Data Mining Study

Diamonds belong to a unique product category whose perceived value is largely dependent on socially constructed beliefs. To explore the degree to which the physical properties of a diamond can be used to predict the diamond price, we perform data mining on a large dataset of loose diamonds scraped from an online diamond retailer. We find that diamond weight, color and clarity are the key characteristics that influence diamond prices. The data mining results also suggest a high degree of subjectivity in diamond pricing that may reflect price obfuscation strategies employed by diamond retailers

The Strategic Value of Data Resources in Emergent Industries

In this paper we examine the strategic role of data resources in emergent industries. We contrast the resource-based view and the relational view theories to examine how data resources can help organizations create and capture value. We compare two organizations from two different industries to understand how different types of data resources can provide a competitive advantage. We also examine the role of strategic partnerships in capturing value created through the exploitation of data resources. We conclude that while data often serve as a required resource for entry into new markets, strategic partnerships play a critical role in capturing value created through the exploitation of data resources. The emergent partnership structures are remarkably similar across the two organizations. They target rapid market expansion through encapsulation of data resources within highly scalable web services and the use of standardized legal contracts. We also find that temporal decoupling between value creation and value capture can expose firms to the erosion of the competitive advantage gained through investment in data resources