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Studiens syfte var att undersöka och få en djupare förståelse för rekryterares uppfattning av AI som rekryteringsverktyg. För att besvara syftet genomfördes semistrukturerade intervjuer med sex respondenter vars huvudsakliga arbetsuppgift var rekrytering. Intervjuerna analyserades sedan med tematisk analys där tre huvudteman med respektive underteman identifierades. Huvudresultatet visade på att respondenterna varken litar på sig själva eller på AI till hundra procent, de belyser vikten av att människor ska ta dem slutgiltiga besluten samt identifierades en oro kring teknikens framfart. De beskrev även att AI är viktigt för att vara konkurrenskraftig då det finns andra aktörer på marknaden som tävlar om samma kunder, det krävs då att leverera kvalitetssäkra och effektiva processer. Sammantaget har AI gjort stora framsteg inom rekryteringsvärlden och används på olika sätt för att optimera processen, trots att verktygen idag inte fungerar felfritt är det effektivare än att inte använda dem.

The central question was how the relationship between trust-in-technology and intent-to-use Big Data Analytics in an organization is mediated by both Perceived Risk and Perceived Usefulness. Big Data Analytics is quickly becoming a critically important driver for business success. Many organizations are increasing their Information Technology budgets on Big Data Analytics capabilities. Technology Acceptance Model stands out as a critical theoretical lens primarily due to its assessment approach and predictive explanatory capacity to explain individual behaviors in the adoption of technology. Big Data Analytics use in this study was considered a voluntary act, therefore, well aligned with the Theory of Reasoned Action and the Technology Acceptance Model. Both theories have validated the relationships between beliefs, attitudes, intentions and usage behavior. Predicting intent-to-use Big Data Analytics is a broad phenomenon covering multiple disciplines in literature. Therefore, a robust methodology was employed to explore the richness of the topic. A deterministic philosophical approach was applied using a survey method approach as an exploratory study which is a variant of the mixed methods sequential exploratory design. The research approach consisted of two phases: instrument development and quantitative. The instrument development phase was anchored with a systemic literature review to develop an instrument and ended with a pilot study. The pilot study was instrumental in improving the tool and switching from a planned covariance-based SEM approach to PLS-SEM for data analysis. A total of 277 valid observations were collected. PLS-SEM was leveraged for data analysis because of the prediction focus of the study and the requirement to assess both reflective and formative measures in the same research model. The measurement and structural models were tested using the PLS algorithm. R2, f2, and Q2 were used as the basis for the acceptable fit measurement. Based on the valid structural model and after running the bootstrapping procedure, Perceived Risk has no mediating effect on Trust-in-Technology on Intent-to-Use. Perceived Usefulness has a full mediating effect. Level of education, training, experience and the perceived capability of analytics within an organization are good predictors of Trust-in-Technology.

Purpose: The purpose of this study is to develop an understanding of millennials’ attitudes toward and trust in the Bitcoin cryptocurrency and its value. The study also aims to analyze what this trust is based on. Theoretical frame of reference: Several theories are used to formulate a theoretical frame of reference. The theories of planned behavior, Word of mouth and Electronic Word of Mouth concern consumer behavior and are applied to millennials’ in this case. To take into account the value of Bitcoin, the study also incorporates the theory of trust in technology, which discusses among other things, how trust in technology is essential as it influences whether a person will use the product or service. Methodology: The study uses a qualitative method based on 12 semi-structured interviews conducted via Zoom or Skype. The selection for this study is made through goal-directed selection, which is a selection of respondents who to some extent have knowledge of, or affected by, what the study intends to analyze. Conclusion: The conclusion indicates that millennials who have information about cryptocurrency in advance tend to experience more confidence in Bitcoin, as it is based on their information about the technology behind Bitcoin. Millennials also experience trust in Bitcoin according to their perception that it is not controlled by a third party; however, the cryptocurrency’s value depends on how it is liked by its investors or users. The respondents with a negative attitude were found to lack general information about the cryptocurrency and were, therefore, unwilling to accept the risks that accompany it. The respondents with a positive attitude proved to have confidence in the technology behind Bitcoin and, therefore, spread positive information about it by Word of Mouth.

This dissertation addresses research questions related to defining a smart city and the associated activities. The general research question is explored in the dissertation via the conduct of three related studies. The finding from these three investigations are presented in the results section as 3 essays that collectively examine the smart city phenomena as it has emerged within the City. Essay 1 assesses building municipal open data capability. The study proposed an Opendata Roadmap Framework to enhance the organization's dynamic capability. The results provide a valuable practical framework to help cities develop open data capability. The results also provide a comparative study or benchmark for similar initiatives with other regional cities and within the nation. Essay 2 measures the residents' understanding and beliefs about smart cities. This portion of the research used a qualitative method that included interviewing residents and city officials to understand their definition of a smart city and what they believe makes a city smart. The interviews focused on understanding resident engagement because it is an important characteristic of a smart city. The gap between the city officials and residents understanding was examined. In addition, the interviews help identify essential factors associated with smart cities like trust in government, perceived security, perceived privacy, trust in technology, and perceived monetary value. Essay 3 examines the acceptance of smart city technologies and factors that affect the adoption of such technologies. This essay uses the insights from the other two essays to propose a smart city Unified Theory of Acceptance and Use of Technology (UTAUT) extension labelled Smart City UTAUT (SC-UTAUT). The new proposed model was tested using a survey method. The 1,786 valid responses were used to test the proposed structural equation model using Smart PLS. Results show a significant relationship between trust in technology, trust in government, perceived monetary value, effort expectancy, self-efficacy, and behavioral intention. The dissertation concludes with a summary of how the three essays make a cumulative contribution to the literature as well as providing practical guidance for becoming a smart city.