Business

As Big Data moves further into mainstream adoption, its compliance with long-standing enterprise standards and industry regulations is becoming increasingly important. Strong data governance capabilities, like the ability to audit changes to data, trace your data’s lineage and sharing, assign role-based access to data, perform impact analysis and respect Indigenous Date Sovereignty are vital as Big Data becomes a standard part of enterprise technology. Unfortunately, most existing corporate governance frameworks do not include adequate Big Data governance frameworks, and the challenges and risks involved.

In this study we aim to understand present data governance frameworks in the industry and create new data governance frameworks for Big Data. We would also identify key factors for strong data governance, enabling businesses to democratize data access with confidence. This project will assess the existing frameworks for Quality Consistency, Data Policies Standards, Security Privacy, Regulatory Compliance and Retention Archiving.

A sustainability report contains information about a corporate’s environmental, social and governance (ESG) performance and plays an important role in today’s capital market. While there has been an increase in the number of sustainability reporting requirements around the world, most regulatory bodies and stock exchanges allow companies to issue sustainability reporting on a voluntary basis. On 20 June 2016, Singapore Exchange (SGX) introduced mandatory sustainability reporting. Effective from financial year ending on, or after, 31 December 2017, each listed company at SGX is required to prepare an annual sustainability report. As the first stock exchange in the world to mandate sustainability reporting, SGX provides us with a unique setting to explore the impact of moving from voluntary to mandatory sustainability reporting on corporate disclosure and capital market.

Following the adoption of IAS 701, auditors are required to communicate ‘key audit matters (KAMs)’ as a separate section in the auditor’s report. While the standard prescribes what must be addressed in the disclosure of KAMs, the adequacy of description, the complexity of the language used, as well as the form and presentation of KAMs is left to the discretion and professional judgement of the auditor.

The aim of this project is to develop a composite score to measure the quality of KAMs reported in the new auditor’s report, and examine the determinants of KAM reporting quality for listed firms in Australia.

Specifically, we assess (1) how the content/readability of the reported KAMs relate to audit fees, audit quality and auditor industry expertise, and (2) whether and how it varies over time.

How does the stock market value directors and top executives? We intend to examine the responses in stock prices to announcements of departures and appointments of directors and top executives. Directors might resign from the board foreseeing challenges ahead in order to protect their reputations. Investors will infer information about the firm’s future from their resignations. In turn, changes in stock prices shed light on the extent of problems.

If the quality of directors is heterogeneous, we can also infer the value of a director from the responses in stock prices to the appointment news. Similarly, we intend to investigate the initial stock price reactions to news of executive appointments and departures.

Decentralisation is a key feature of public blockchains such as Bitcoin and Ethereum, as well as DAOs (Decentralised Autonomous Organisations). Whilst decentralisation is an attractive concept for many, changes to the code of blockchains and DAOs will be required, for example, to fix errors or make improvements. There must be a process in place—a governance mechanism—to make changes. Even Bitcoin has a process for making changes to its code. The issues a governance mechanism must address include: who can put forward proposals for change; who decides which proposals are voted on; who is entitled to vote and how can they vote (is it one vote per token, one vote per person and/or are the votes weighted, for example, is a reputation system used?). This project will document the different types of governance mechanisms used, and proposed to be used, in public blockchains and DAOs.

There has been considerable anxiety on the part of Businesses in New Zealand and elsewhere as to the effect of the new European Privacy Regulation (GDPR). At the same time reform of New Zealand’s Data privacy framework is well advanced with the Privacy Bill approaching its final stages. It is therefore possible to assess whether New Zealand’s legal environment concerning data privacy is broadly complaint with the GDPR. However, GDPR itself remains opaque as its requirements are framed in high-level language whose practical implications may only be deciphered by examining a considerable volume of primary and secondary sources including opinions, guidelines and other documents (e.g. letters) emanating from official bodies of the European Union as well as case law. This project will seek to reach conclusions as to the likely manner in which the GDPR will be applied through examining these sources in relation to four key areas.

Female empowerment can boost economic development by promoting efficiency in resource allocation, both within and outside the household. Discriminatory gender norms that prescribe rigid gender roles and restrict female autonomy in decision-making can significantly hamper female empowerment. It is hence important to understand the factors that shape gender norms.

This project will exploit detailed household-level survey data from India for the years 2005-06 and 2015-16 and the roll out of mobile internet infrastructure to examine if exposure to new ideas through the internet leads to changes in attitudes of men and women toward female empowerment. It will also explore the role of education in driving the relationship between internet exposure and gender norms. The project will contribute to the emerging literature on culture, social norms and their impact on economic development and to the literature on how the internet influences socio-economic outcomes.

Indian data show that as the gender-gap in education (measured by the difference in numbers of male and female students) declines, the gender-gap in labour-force participation increases. That observation stands in sharp contrast with the experience of China and western countries operating under significantly less gender-biased institutions, measured by the Social Institutions and Gender Index (SIGI). The observation triggers a new hypothesis: gender-biased institutions may lower the effectiveness of education in promoting women’s participation, necessary for economic growth. We have designed a new theoretical model that rationalises the above hypothesis, filling a gap in the recently emerging literature on the impact of institutions through gender-based resource allocations on economic growth, and have the necessary data to test this hypothesis. The project involves the use of software (STATA / R / MatLab / Mathematica) to simulate and calibrate the model’s outcome to panel data, before conducting statistical tests of the hypothesis.

Reproducibility is a challenge in many fields. Economics is not an exception. We want to check if results are correct, and reproduce methods using a different data set. At the same time, there is also an increasing demand for using free open-source languages.

Student will use freely available programming languages (e.g. Julia, R or Python) to reproduce some reference papers related to Empirical Economics and Econometrics. Of particular interest would be empirical game theoretical models (auctions, discrete demand models), but other empirical studies could be considered. The output should be publicly available to the wider community.

This project is valuable for different reasons. The student will:

• improve their knowledge of econometric methods
• improve their numerical and coding skills
• contribute to the dissemination of knowledge in a free and transparent way.

The aim of this project is to analyze text messages from a laboratory experiment where an advisor with private information and a possible conflict of interest had to convince a decision maker of what choice to make. Messages will be categorized, and the effectiveness of different types of messages in persuading the decision maker evaluated. The candidate should be familiar with R and Stata. This project is an opportunity for the successful candidate to develop programming skills, an understanding of machine learning algorithms, and how to analyze text data using quantitative methods.

Inspired by the ride-sharing market in New Zealand, with Uber and Zoomy offering respectively a fixed price and an estimated price range per ride, we ask ourselves if competitors in the digital economy could deliberately offer distinct pricing schemes aimed at serving consumers with different levels of ambiguity tolerance with the aim of gaining market share.

Existing theoretical and experimental findings on decision-making under ambiguity propose that individuals hold different ambiguity attitudes. Theoretical models also exist to infer different types of utility representations over ambiguous outcomes in the individual decision-making process. However, there is a gap in the Industrial Organisation literature on how individuals decide when they are faced with ambiguity in competing pricing schemes.

We propose to introduce explicit ambiguity in the study of individual decision-making over binary pricing options and investigate how ambiguity attitudes and different types of utility representations over ambiguous outcomes affect individual decision-making under ambiguity; as well as the related competitiveness in the ride-sharing market, in particular.

Adding more value to domestic production and exporting more complex goods is essential to earning export income and sustaining a high quality of life. How to achieve this is a major unanswered question. Protectionism of domestic industries using tariffs is less and less possible under WTO rules. To what extent have import tariffs been replaced by other measures, such as export restrictions on domestic inputs used by downstream industries?

This proposal will uncover the determinants of export complexity: how can firms grow beyond exporting raw materials or lightly processed commodities; and what is the role of industrial policy in Asia to achieve this? We will start by collecting systematic data on industrial policy related to trade and then use this data to describe patterns and relate them to detailed trade data. Some statistical software experience, notably in Stata, is required.

A key aspect of supplier management is auditing, which includes the identification of human trafficking in global supply chains. It is estimated that modern slavery currently affects some 50 million people, with only 0.2% of victims assisted.

This project is the first part of a project to disrupt this heinous crime by improving decisions on the level and deployment of supplier inspection resources, using ideas from operations and supply chain management and decision analytics. The problem is specially challenging given adaptive/deceptive behaviour of traffickers.

The project will provide an overview of analytical approaches in the area of supply chain auditing (focused on human trafficking), and present connections to (i) analogous issues faced in terrorism, biosecurity, and disaster preparedness, and (ii) solutions to similar problems including sensor location and the dynamic location of emergency vehicles.

Intelligent automation is an umbrella term for robotic process automation, machine learning and artificial intelligence. These technologies are set to transform business by automating processes, driving decisions through insight from data and improving customer experience by applying machines that are capable of learning. While the popular media is giving the impression that such technological solutions have already been having significant impact on business, the reality is that very little implementation has happened so far. Some media reports suggest that the big challenge for businesses is the lack of appropriate skills that are critical to properly implement such solutions.

This project is therefore about understanding the state of demand and supply of skills relating to robotics, machine learning and artificial intelligence in New Zealand. Results from this study will inform the media and industry about the skills gap companies face and what skills they should be developing or seeking to acquire in order to benefit from the revolution of intelligent automation.

Sustainability reports are increasingly important for stakeholder communication and reporting has helped guide management attention toward sustainability issues. These reports vary significantly in content and researchers have proposed a variety of theories about why firms produce sustainability reports, ranging from scepticism of firm intentions to recognising genuine consideration of environmental and social issues.

To-date, these theories have been applied generally and there is limited research into how to classify the sustainability reporting strategies which individual firms actually undertake.

Prevalence of non-communicable diseases is a problem commonly caused by social, cultural, familial, behavioural, economic, and environmental factors. Current preventive/corrective approaches fail due to a lack of holistic, sustainable, systems perspectives. In this research, we propose to build a platform/ecosystem that supports Sustainable Social transformation in a Holistic and Adaptable manner using Real-time, Precise, and Persuasive (SSHARPP) principles, processes, and systems. It leverages ubiquitous smart exponential technologies, behavioural and chronic disease studies to design a platform that interweaves the virtual with the real. It supports individuals, families, and whānau to form healthy habits and balance various life dimensions.

The recent development of natural language processing (NLP) models and tools in artificial intelligence (AI) has made content generation almost costless. Given a sentence of words, they could make a new and coherent story out of it. Very soon these models will past the Turing test and no one could tell if an article is composed by human or not. The problem is, these AI-based ghost-writers could be abused and contribute towards the spread of fake news and hate speeches, or they could make all essay type assessments in schools meaningless.

The purpose of this project is to demonstrate how an AI-based ghost-writer works, and to design an AI-based ghostbuster that could potentially counter them by estimating the likelihood of any writing being generated by AI. The student will learn and apply cutting-edge NLP techniques to support the proof-of-concept prototyping of the research.

My research in solving difficult combinatorial problems relevant in logistics like the traveling salesman problem, or container relocation problem in a container port has resulted in three doctoral projects. This current project will provide optimal fractional solutions to very large instances of symmetric traveling salesman problem (STSP). A minimum of a tenfold increase in the size of problem instances solved is expected. This project will result in a good publication in operations management/research. This project explores a new area of research relating to a difficult problem of practical significance and requires computational experiments.

We are looking for a student who has interest in algorithms and solving problems using Python programming. The experience in this project will enhance the student’s practical programming skills useful for employability and trigger interest in research in a fascinating area that combines mathematical modelling and computational experimenting.

The Māori Identity and Financial Attitudes Study, or MIFAS is the first large-scale (n = 7,019) nationwide study of Māori aged 18 and that reports Māori beliefs and attitudes towards economic development. In this project, you will work with the MIFAS research group to report the representativeness of the MIFAS dataset in comparison with data gathered in the 2006 2013 New Zealand censuses and Te Kupenga (which is Statistics NZ’s first survey on Māori well-being conducted in 2013).

The student will work with the MIFAS team to consider what the general public need to know about the MIFAS sample to make an informed decision about whether the sample is representative of the overall Māori population. Variables analysed and reported include socio-economic status, health related behaviours, employment status, ethnic and affiliations, rural versus urban dwelling, Kiwisaver uptake and the utilisation of financial products and services.

Blockchain has the potential to change the world. Initial Coin Offering (ICO) is one of the main blockchain applications. Through ICOs new ventures raise capital by selling tokens to a crowd of investors. Often, this token is a cryptocurrency, a digital medium of value exchange based on the distributed ledger technology. The ICO market has grown dramatically since its emergence. Specifically, in 2018, entrepreneurs raised an estimated $11.9 billion through ICOs.These new ventures are active in a broad range of sectors, including not only financial services, high-tech, but also in entertainment, health, art and education. However, there is significant uncertainty related to the economic value that this new entrepreneurial practice might bring, and what the appropriate regulatory approach should be to protect investors but at the same time foster innovation and economic growth. The aim of this project is to better understand the regulatory environment surrounding ICOs, and the impact of regulation on cross country ICO diffusion.

Innovation increases firm productivity. Thus, developing cooperation strategies that improve innovation outputs is a priority in New Zealand and many advanced economies.

This study digs into the dynamics of cooperation in the business context and explores how research and development, as well as other important drivers of innovation, impact the creation of fresh know-how and relevant novel technologies.

As the student working in this project, you will be introduced to the scientific literature on innovation. You will read, describe, analyse, reinterpret and synthesize the most recent discoveries in the field. Based on previous studies, you will develop multiple tables, charts and analysis of the methodologies, specific contributions, and diverse approaches in the scrutiny of innovation determinants.

The final outcome of your work will be a document that will include a literature review discussing how cooperation best expands innovation as well as recommendations for managers interested in fostering innovation.

We surveyed cooperative and mutual organisations in New Zealand to understand their role in New Zealand’s future economic growth following calls from the United Nations, The World Bank, and OECD that these organisational forms are play an important role in sustainable economic, social and environmental development.

We seek a student researcher who is keen to work with survey data to fill some gaps using publically available information and help us to analyse the data. Moreover, we have a lot of qualitative data and we seek a student researcher who can help us search these data and draft summaries that illustrate and enrich our quantitative results.

Innovation in low and medium tech sectors is typically limited to incremental improvements, such as trial-and-error driven optimisation. However, firms in those sectors face a wide range of radical changes such as global competition and new technologies (e.g., 3D printing). Our project investigates how organisations develop the processes and capabilities needed to adapt to such changes through systematic innovation. To understand the underlying dynamics, we work closely with 4 organisations in the manufacturing and engineering sector. These firms are currently in the process of embedding the structures, skills and mindsets required for transformative change.

The student will work closely with us and (a) analyse interview data, (b) review relevant literature, and (c) develop company-specific outputs. This will equip them with skills in qualitative data analysis, academic writing, literature management and a practical understanding of the barriers firms face in becoming more innovation-driven companies.

Piloted in 2017, and repeated in 2018, Accelerate offers a research/action-learning initiative in which 30-40 top-performing students engage in a voluntary extra-curricular development programme. Our 2017 client organisation was St John Ambulance, with Auckland Museum in 2018. In 2018 each team of 6-7 students were mentored both by an academic and 1-2 second-year students, who were programme alumni from 2017. Teams researched, assessed, reported back and presented recommendations on a marketing and/or an innovation issue currently faced by St John, and Auckland Museum, respectively.

Emerging in our 2018 findings is not only the benefits of the programme for student participants, but also for all four parties (staff, students, client organisations and student mentors). Further, as the now two years of alumni indicate, their continued interest in being involved in the 2019 programme means a sense of ‘family’ is developing around Accelerate, with the potential for an ongoing community of interest.

In this project, marketing meets innovation through design. Students that are interested in this intersection and in learning more about how design becomes a vehicle for creative innovation should apply.

The student’s role in the project will be to:

• complete makerspace orientation and machine training at the Unleash space
• assist in collating, organising and code student and staff interviews
• carry out a literature review
• identify activities and programmes at other makerspaces
• assist in devising INNOVATE 100G interventions for 2020
  

The student will get both a practical exposure to visualisation and prototyping techniques (Unleash space), and through the literature review a deeper understanding for how these techniques can be put into practice. We are looking for a student who would like to grow his or her own creative confidence. The project can provide a good foundation for further Honours, Masters or PhD studies.

The impact of virtual reality (VR) on property marketing is currently not well understood. In this project, we will examine how the use of VR affects the property marketing process. In particular, this study will analyse the impact of VR technology on property buyer behaviour. By applying hedonic pricing models to a publicly available dataset consisting of property listings in the city of Wuhan China, we aim to disentangle how the use of VR in property marketing affects 1) listed properties’ time on the market, 2) their transaction prices (as compared to those non-VR listings) and 3) the buyers’ engagement (as proxied by the number of views on those listed properties).