Business

Project

Today, nearly 1 in 5 adults in the world live with a mental disorder. As part of psychotherapy, dream analysis plays a pivotal role in revealing the subconscious mind and psychological state of a person. Current methods are mostly based on patients describing their encounters through verbal conversations, and the therapists decomposing and reassociating the given texts for diagnoses. If a picture is worth a thousand words, what if we could picture a dream while it is being described in real-time?
In this project, we propose an application of natural language processing, emotion detection and image generation for visualising dreams as an aid to both patients and therapists in psychotherapy. It aims to explore the potential use and adoption of artificial intelligence in dream analysis.

Project

The project studies the NZ retirement savings and investment scheme Kiwisaver participants’ decision-making process regarding their retirement savings and investments. Specifically, we will investigate the cognitive bias known as ‘investor inertia’, and its impact on Kiwisaver participants’ investment performance. At the initial setup of a Kiwisaver, participants choose a fund provider to invest his/her retirement savings with, and an investment style (e.g., conservative, moderate, aggressive). Participants tend to stay with their initial choice and do not switch either the fund provider or the investment style, even when it is optimal to do so. Through a better understanding of how people save for retirement and developing tools to improve investors’ portfolios, this proposal has the potential to help New Zealanders better secure their financial future. The project seeks to develop and democratise cutting-edge portfolio tools to help a broad set of investors – anyone saving for retirement – access these tools.

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“Data Scientist” has been ranked the best job in U.S. three years in a row with huge demand in Australasia as well. We use several tools in a data scientist’s tool kit such as machine learning algorithms, visualizations, data scraping to glean insights about Environmental, Social, and Governance (ESG) sentiment and how that is related to firm performance. With Fintech, processing of big data with natural language processing (NLP) has resulted in access to a wider range of content in the form of big data. Analysis of such data not only provides insightful perspectives on consumer demand but also on management intentions. We aim to develop several NLP algorithms to classify management and investor ESG sentiment by conducting textual analysis of unstructured data from financial reports and online content. Subsequently, the developed management and investor ESG sentiment indices would be used identify impact on firm performance and other research projects.

From June 2019, auditors are required to disclose critical audit matters (CAMs) for audits of large, accelerated filers in the U.S. The requirement to report CAMs, specified in AS3101, is the most significant change to the auditor’s report in over 70 years. While the objective of introducing CAMs in the audit report is to increase transparency and improve the informational value of statutory audits, auditors may disclose boilerplate CAMs for the same client overtime or report boilerplate CAMs for clients in similar industries, which could impair the intended value of CAMs.
Motivated by these regulatory concerns and the scant evidence to date, we aim to (1) perform textual analysis using hand-collected data on the detailed CAMs disclosure to understand the comparability/similarity of CAMs for clients within the same industries and for a specific client overtime, and (2) investigate factors affecting the reporting of boiler plate CAMs by the auditors.

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Following the adoption of ISA (NZ) 701, auditors are required to communicate ‘key audit matters (KAMs)’ as a separate section in the auditor’s report. Other than listed issuers, this standard also applies to unlisted reporting entities that are considered to have a higher level of public accountability for annual year-ends on or after 31 Dec 2018, a feature that is unique to the NZ jurisdiction. While research on KAMs in the extant literature so far has focused on listed firms, understanding the differences, if any, in the reporting of KAMs for unlisted entities compared to listed entities is of interest to better evaluate the costs and benefits of the new auditing standard and the value of audits for unlisted entities. In this project, we examine the disclosure of KAMs by auditors in NZ for a sample of unlisted reporting entities.

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This research is concerned with identifying themes about cybersecurity and privacy in committee discussions by legislators in the United States House of Representatives and Senate committees. The RA for this project will further develop their quantitative and qualitative skills through a text analysis of a large corpus of transcripts from these committees. The project lead will have performed a preliminary text analysis by the time the RA begins on the project. The RA will be responsible for further developing this work. They will write code in R or python to clean, process and engage in exploratory data analysis of text data. They will also engage in qualitative analysis of the textual data to help identify themes.

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Financing is an appealing offer for many consumers who want to buy cars, cell-phones, etc. It also helps firms increase their sales by enabling more consumers to afford their products. Often a financed product lasts longer than its loan length, so consumers keep using it till paying off its instalments. To constantly sell their new products to consumers, firms also offer trade-ins for financed products. That is, consumers who have a product in finance and have not yet paid off its instalments can trade-in their current product for a new one by extending their instalments. This project outlines the optimal terms of a financing and trade-in offer, that is, upfront payment, instalment, trade-in price, sales price, etc. The project will solve models of trade-in (without financing), financing (without trade-in), and financing and trade-in for their optimality and compare them w.r.t. firm profits and consumer welfare.

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This project aims to evaluate a feasible solution on Canvas that could enable real time audience interaction among lectures, seminars, workshops, and other events held in the University of Auckland. A question management system for real-time events was implemented across a Stage 2 course. It allowed participants to log a question or a comment via any device while remaining anonymous and view the list of questions and vote them up or down to affect their positions in the queue. Speakers could access the list of questions anytime, moderate them, and generate summary reports of the questions. Data has been collected on the usage of the application and its user perceptions. This project will focus on the synthesis and analysis of collected data and analysis findings to inform the project’s conclusion and recommendations. A key task is producing an academic publication to share the projects findings with a wider audience.

Project

Energy production and use contribute to greenhouse gas emissions. In New Zealand, energy-related greenhouse gas emissions account for 40% of total emissions. Since there is only a limited possibility of reducing methane from the agricultural sector, to reach the government net-zero carbon target by 2050, it is urgent to understand the energy-related emissions profile and its influencing factors. Limited research has been tackled in this area in New Zealand. This project will use input-output analysis and structural decomposition analysis to systematically investigate the driving forces shaping energy-related greenhouse gas emissions at national and sectoral levels. This project is built on the previous analysis with the newly released national input-output tables. The new evidence will assist policymakers in selecting appropriate policy instruments targeting key sectors to achieve emissions reduction effectively.

Recent years have witnessed a rapid growth of the sharing economy, an innovative business model that enables fee-based peer-to-peer sharing of under-utilized assets. Despite its significant economic success, empirical research that examines peer providers’ order fulfilment process on sharing economy platforms (SEPs) is still lacking. Leveraging a rich and diverse secondary dataset on a leading meal-sharing platform, this project aims to examine the effect of provider-consumer interactions on consumers’ and providers’ responses to order fulfilment disruptions on SEPs. Through this research, we aim to develop new behavioural theories, reduced-form and applied econometric models as well as provide new empirical evidence of consumer and provider behaviours in the order fulfilment process on SEPs.
Benefits to student: A student can develop skills for data analytics through various programming and statistical packages (e.g., Python, Stata), gain a better understanding of provider and consumer behaviours on SEPs, and acquire first-hand experience in conducting empirical Information Systems research.

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Is Pacific Business your passion? Are you interested in Kaupapa Pasifika approaches to business and economy? This project will develop a database of Kaupapa Pasifika and Indigenous philosophies of economy. The successful applicant will learn to refine keywords and search articles and relevant data sources through the University of Auckland Library and appropriate archives; code and annotate sources according to research themes; and develop a Zotero library. This will contribute to Kaupapa Pasifika at the University of Auckland Business School.
You will be mentored by two of the Faculty’s foremost scholars of Kaupapa Pasifika through this project. We will practise the kakala method: teu – prepare (narrowing scope/identifying and refining search terms), toli – collect (scoping and annotating sources), tui – thread (coding sources, consolidating themes) and luva – offer(handover process and reflections). This is an opportunity to build research relationships, learn research skills and develop content knowledge for your future studies.

Project

The Metaverse is disrupting a wide range of societal and economic structures. It enables virtual social connections that afford novel organizational mechanisms, information sharing with elaborate rules, new opportunities to monetize creative work, and untold perceived benefits. The Metaverse is rapidly changing traditional societal and economic dynamics in ways that will expand the use of technology and broaden participation in many domains of human interaction. Smart Contracts, and Non-Fungible Tokens (NFTs) for example reduce barriers to participation in valuable sectors of the economy through portable digital assets supported by blockchain technology. In the new age of the Metaverse social scientists must develop and update their understanding of how individuals interact with societal and economic structures. Individuals, organizations, and governments need guidance to maximize the benefits of a new digital economy, where users create, buy, and sell virtual products and services, while minimizing potential harm.

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New Zealand’s Rocket Lab is just one example of the increasing commercialisation of space, with the business of space moving from state actors in the 20th century (e.g. NASA) to visionary entrepreneurial corporations in the 21st (e.g. SpaceX). What was once science fiction is nearing commercial reality. This new business frontier has huge potential to improve humanity’s living conditions while generating massive profits, but also risks both the terrestrial and space environment. The current ways of doing international business may no longer be relevant to inter-global business, and the old “rules of the game” may become obsolete. This project is a first step in assessing the current state of the space industry as a global business, looking at industry structure, key players, regulatory environment, conventions, technologies, commercial opportunities, consumers and social and economic impact.

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The influence of artificial intelligence through use of algorithms is increasingly evident in all areas of society. Personal privacy is one such example. Existing rules contained in legislation such as the Privacy Act 2020 may no longer be fit for purpose in regulating machine-generated personal information. This project investigates whether separate rules or a code of practice under the Privacy Act might be developed and what it might contain. Specific areas of interest include information not covered by many existing privacy rules, such as publicly available information. Should such information, when used to compile inferred/derived data about individuals be treated as personal information? Similarly, access and correction rights (for instance opinions as opposed to factual data) and rules concerning data quality (accuracy) may be difficult in relation to inferred/derived data. Finally, to what extent do current intellectual property exceptions in the Privacy Act protect organisations’ algorithms and trade secrets?

Project

Despite the significant harm alcohol causes it is widely available for purchase in New Zealand. Groups such as Māori and Pacific are particularly heavily impacted by the adverse consequences of alcohol.
To inform consumers of the risks of alcohol, governments world-wide are increasingly mandating compulsory on-pack health warning labels. For example, over the next 18 months all alcoholic beverages sold in New Zealand will have to display a pregnancy warning label.
However, the evidence around the effectiveness of health warning labels is mixed. One reason for this may be that consumers do not believe that the harm is specific to them, or the product they are considering purchasing. Using construal level theory, this project will trial a novel idea to re-frame the information provided on health warning labels with the aim of making the information more relevant to consumers, thus making the warning more effective.

Project

This project explores how artists and other creators can and are using NFTs to innovate. Artists and other creators are using NFTs in a range of ways, they include creating new revenue streams, enabling new art forms and increasing engagement with fans, including community building outside social media platforms. The project is suitable for a wide range of students, they do not necessarily need a coding/technical, fine arts, business or law background.

On 13 February 2008, the then Prime Minister of Australia Kevin Rudd made a formal apology to the Stolen Generations of Australia. In that apology it was said that the “injustices of the past must never, never happen again”.
The policy of attempting to assimilate Indigenous Australian children through forcible removals from their families is well known. The New Zealand colonial government's ‘racial amalgamation’ policy, designed to turn Māori children into 'brown Britons' is less known. Yet history paints a strikingly similar picture in both countries.
Based on the overrepresentation of Indigenous Australian children in out-of-homecare and ongoing state removal of Māori children from their families, there are concerns that there is a “new stolen generation”.
We will explore if there have been sufficient changes since the formal end of the forced removal policies to guarantee that the past will “never, never happen again”.

Project

Pasifika people, those who have ancestral ties to islands in the South Pacific, are an essential part of the social and economic fabric of Aotearoa. Growing Polynesian communities in particular already make Auckland the largest Polynesian city. But Pasifika are significantly under-represented among the self-employed and founders of companies in Aotearoa. A literature search found few recent studies investigating the nature and significance of entrepreneurship among either Pasifika in Aotearoa or those residing in their homeland. This project, hosted by the Centre for Innovation and Entrepreneurship (CIE), will identify significant themes to stimulate research that improves understanding of entrepreneurship among Pasifika, entrepreneurship’s potential in their communities, and how it may be supported. Outcomes will include a literature database, an analysis of statistics from national and university sources, and social connections with researchers, community partners, business leaders, agencies, and other possible collaborators.

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To navigate towards our digital future in the age of accelerations (Friedman,2017), we must understand the roles played by emerging technologies ranging from artificial intelligence to metaverse (Huynh-The et al., 2022; Lee et al., 2021). They are independently disrupting, reshaping, and transforming the evolving nature of our home, work, business, and society (Brock & Von Wangenheim, 2019; Hirsh-Pasek et al., 2022; Laato et al., 2022; Mozumder et al., 2022; Piccialliet al., 2021). It is vital to understand the role of emerging technologies in a sustainable world, in a circular economy and particularly in a post COVID era. The application and adoption of emerging technologies is digitally transforming home, work, business, industry, government, and society as a whole. The potential of these emerging technologies to address some of the greatest challenges facing humanity is unparalleled.

Project

Electrification and use of sustainable biofuels are some of the strategies used to reduce the lifecycle greenhouse gas emissions from the transport sector, especially in New Zealand. In this study, Lifecycle Assessment (LCA) for the electrification and use of sustainable biofuels in the transport sector in New Zealand and Australia will be performed, focusing on greenhouse gas emissions and other societal implications of these strategies. Studies have reported that different biofuels and electricity sources have different lifecycle emissions, depending on the source of feedstock and production method. The study will focus on three general types of vehicles: battery electric, plug-in hybrid electric and internal combustion engine vehicles, with and without use of sustainable biofuels. Australia and New Zealand will be taken as case studies. The student will conduct literature review and perform comparative analysis.