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Item Adopting augmented reality to avoid underground utilities strikes during excavation : a thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy, School of Built Environment, College of Science, Massey University, New Zealand(Massey University, 2025) Khorrami Shad, HesamThe construction industry constantly pursues innovative methods to improve safety, enhance productivity, and reduce costs and project durations. Augmented Reality (AR) is a promising technology, potentially bringing about transformative changes in construction. AR is a promising technology for visualizing data in construction sites and preventing clashes and accidents. One of its promising applications is in the excavation sector, where accidental strikes on underground utilities pose serious safety risks, delays, and costly damages. However, while AR has gained increasing attention in recent years, its integration into construction practice remains limited. To address this limitation, this research investigates the potential of AR to facilitate identifying underground utility locations through a systematic review, industry engagement, and user-centred experimentation. Initially, a systematic literature review was conducted to explore the current applications of AR in construction safety. This review identified the safety purposes of AR across three project phases: pre-event (e.g., training, safety inspections, hazard alerting, enhanced visualization), during-event (e.g., pinpointing hazards), and post-event (e.g., safety estimation). However, the review also revealed a notable lack of studies focused on AR applications in excavation activities, particularly for underground utility strike prevention. In response, a study was undertaken to understand the needs, expectations, and challenges associated with adopting AR in the excavation sector. 31 professionals from the excavation industry participated in the within-subject experiment, interacting with two AR prototypes, delivered via Optical See-Through (OST) and Video See-Through (VST) devices. The findings indicated a clear preference for AR over traditional methods such as paper-based drawings. Participants showed a preference for VST rather than OST, given their familiarity with VST devices such as tablets. Further, accessibility emerged as the primary barrier to adopting AR within the excavation industry. Building on the literature and industry insights, an experimental study was designed to evaluate the effectiveness of different AR visualization methods in underground utility detection. A within-subject experiment involving 60 participants was conducted to compare four of the most cited visualization techniques for underground utilities: X-Ray, Shadow, Cross-Sectional, and a newly developed Combination method. Drawing on the Theory of Affordances and Task Load analysis, the study found that the Combination and X-Ray visualization methods perform superior to the Shadow. These results provide empirical support for the user-centered design of AR visualization techniques in excavation practice. This research contributes to the fields of human-computer interaction, construction safety, and digital technology adoption by advancing the use of AR for underground utility strike prevention. The study shifts the focus of AR from general safety training to real-time, spatial visualization for excavation, offering both theoretical insights and practical applications. Methodologically, it follows a structured mixed-methods approach, combining literature review, industry engagement, and experimental testing. Practically, it identifies user preferences, visualization methods, and key adoption factors such as usability and accessibility. Overall, this thesis fills the gap between emerging AR technologies and their integration into safer excavation practices.Item Construction projects status tracking : a real-time data-driven framework for delay management and analysis : a thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy in Building and Construction, School of Built Environment, College of Science, Massey University, New Zealand(Massey University, 2025-10-16) Radman, KambizConstruction delays remain one of the most critical challenges in project delivery, often resulting in cost overruns, schedule slippages, and weakened stakeholder confidence. Traditional delay management methods are largely reactive, relying on periodic reporting and fragmented communication across project teams. In contrast, the increasing availability of digital tools offers the opportunity to adopt more proactive, data-driven approaches. This study introduces a framework that centralises and analyses real-time project data from multiple stakeholders, including head contractors, subcontractors, consultants (via Building Information Modelling—BIM), and on-site teams. By integrating these diverse inputs into a unified Power BI dashboard, the framework enhances early detection of delays, improves coordination, and supports timely decision-making. Earned Value (EV) metrics are embedded as key control points, providing early signals of deviations and potential risks. Despite these advances, several research gaps remain. Existing systems are often costly and complex, highlighting the need for simple, inexpensive, and user-friendly solutions. Real-time data acquisition and centralisation are still underdeveloped, limiting the speed and reliability of insights. Current practice focuses heavily on retrospective reporting, with limited capability for real-time analytics or predictive forecasting. Stakeholder communication and coordination remain fragmented, while systematic early notification systems for emerging delays are rarely implemented. Ultimately, it is necessary to integrate historical and real-time data to facilitate predictive delay analytics. Addressing these gaps would help shift construction delay management from reactive intervention towards proactive risk mitigation. Guided by these gaps, the research is shaped around three central questions: (1) What causes delays in major construction projects, and how do these delays affect stakeholder collaboration? (2) How are digital technologies currently being deployed to improve project performance in relation to delays and risks? (3) How can a new framework be designed and evaluated to strengthen early delay detection and enhance project outcomes? To answer these questions, five objectives are established. First, to identify and analyse the key project stakeholders and the principal causes of delay. Second, to review and assess the role of digital technologies in construction projects. Third, to develop a framework that integrates real-time data for enhanced monitoring, reporting, and early detection of delays. Finally, to evaluate this framework in practice, assess its effectiveness in enhancing transparency, facilitating stakeholder coordination, and improving overall project performance. In doing so, this research contributes to the advancement of digital construction management by embedding real-time analytics into live project environments. The proposed framework not only enhances transparency and resource allocation but also lays the groundwork for predictive delay management, thereby aligning construction practices with the broader objectives of Industry 4.0.Item Customer experience in immersive virtual reality retail : exploring behaviors, emotions, and touchpoints across the shopping journey : a thesis with publications presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Information Technology, School of Mathematical and Computational Sciences, Massey University, Albany, Auckland, New Zealand(Massey University, 2025-08-01) Erensoy, AysuImmersive Virtual Reality (iVR) is transforming the retail landscape by merging sensory engagement with the personalization and convenience of digital platforms. As part of the rapidly evolving metaverse, iVR has the potential to redefine customer experience (CX) and create immersive, multisensory shopping environments. However, understanding how iVR shapes customer behaviors, emotions, and interactions across the shopping journey remains limited. These gaps hinder businesses from fully optimizing CX in this emerging domain. This research aims to address these challenges by exploring the influence of iVR retail touchpoints on CX and developing frameworks to advance theoretical and practical knowledge in iVR retail. This study employed a human-centered design methodology, integrating systematic literature reviews, semi-structured interviews with VR design experts, and iVR experiments with end-users. The literature review established a theoretical foundation, identifying challenges and opportunities in iVR retail. Semi-structured interviews with experts explored critical touchpoints, emotions, behaviors, and the design processes underlying iVR environments. Complementing these, VR experiments, card-sorting activities, and end-user interviews captured the behaviors and emotions of participants across the pre-purchase, purchase, and post-purchase stages of the shopping journey. This study offers significant theoretical advancements by extending the Stimulus-Organism-Response (S-O-R) model to better capture the complexities of CX in immersive virtual environments. It provides a nuanced understanding of how sensory stimuli influence emotional responses and consumer behaviors, particularly within iVR retail contexts. This extension enables a more comprehensive analysis of the relationships between touchpoints, emotions, and shopping processes. Additionally, the study adapts the Double Diamond framework, tailoring it to meet the unique demands of iVR design. This refined framework supports designers in addressing the iterative nature of immersive retail experiences across discovery, definition, development, and delivery phases. Additionally, the key outcome of this research is developing a CX framework that detailed the iVR customer journey, illustrating how user interactions, emotional responses, and behaviors evolve across the pre-purchase, purchase, and post purchase stages. These findings not only highlight the underlying mechanics of creating positive CX in iVR environments but also identify the drivers of emotional connection and satisfaction, laying the groundwork for further exploration and application in this transformative retail medium. This research contributes to both theoretical and practical understanding of iVR retail environments. Theoretically, it advances models such as the S-O-R model and refines the Double Diamond framework, aligning them with the complexities of immersive technologies and offering tools for analyzing how iVR reshapes CX. Practically, the study provides actionable design guidelines to address key challenges in iVR retail, including improving usability with intuitive interfaces, enhancing accessibility through features like voice navigation, and fostering emotional engagement via sensory-rich experiences. These guidelines support the creation of inclusive, engaging, and effective iVR shopping environments that serve as a roadmap for future studies for exploring and validating emergent technological innovations in iVR retail.Item Fruit measurement horticultural device : developing trust through usability across complex systems : a thesis submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy, College of Creative Arts / Toi Rauwhārangi, Massey University, Wellington, New Zealand(Massey University, 2024-12-11) Krige, ZenéThe agricultural technology (ag-tech) sector aims to use emerging technologies to meet changing consumer demands. To do this, the design of an intuitive smart object needed to be developed, and appraised for the horticultural industry of New Zealand. Its subsequent data needed to be expressed in tangible ways that empower decision-making about orchard operations. An elevated user experience of the device, along with quality data driving the system, would provide a successful engagement with an intelligent product system that sustains trust in the interaction and purpose of the product and integrates trust as a value within the system to advance resilience in horticultural innovation. Focusing on the task of fruit measurement, this project explores the conceptual design of a technology-driven device that can efficiently measure fruit size and count, throughout the season. The translation of this data in a format that enables stakeholders to analyse, query and act on it, seeks to inform and empower decision-making by the end users and stakeholders about the best time to harvest. This allows for better management of resources and deployment of labour and equipment. The consequence is a more sustainable orchard operation with greater productivity and benefits to all stakeholders. The project investigates the interrelationships between stakeholders, their equipment and orchard systems to drive product innovation by strengthening foundations of trust and utility, developing confidence in product use, and demonstrating its role in providing critical data into a horticultural management system with an inanimate object (product) placed within the orchard environment. This creative practice research project aims to address the opportunities that design can offer in bridging technological capability to usable products that can communicate trustworthy data clearly to end-users.Item Developing a framework for prefabrication supply chain integration in New Zealand using blockchain technology : a thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy, Construction Project Management, School of Built Environment, College of Sciences, Massey University, Auckland, New Zealand(Massey University, 2024) Bakhtiarizadeh, EhsanPrefabrication or off-site fabrication in New Zealand is snowballing in terms of its contribution to the delivery of construction projects. The increasing demand for new houses and the lack of affordable accommodations in New Zealand evolved the need for innovative and effective project delivery systems instead of conventional types. The prefabrication sub-sector is considered leverage for eliminating the shortcomings of traditional construction systems. However, this sub-sector of the construction industry struggles with challenges such as low coordination and integration across its supply chain partners. These challenges are attributed to the inefficient foundation of communication and information flow. This research addresses the problem of the relatively weak integration within New Zealand's prefabrication construction supply chain. The particular focus of the study is on information integration. The central point is that an effective and efficient exchange of information among supply chain stakeholders is imperative for enhancing supply chain integration in New Zealand's highly fragmented construction industry. Therefore, this study concludes that providing an effective information-integration-based platform for stakeholders involved in prefabrication projects will deliver integration improvement in the whole supply chain system. Blockchain technology, as a secure information integration instrument, capably improves the integration of information flow within the prefabrication sub-sector. Blockchain, a decentralised, safe, and unalterable information storage, offers numerous benefits to investors, clients, end-users, and other organisations or individuals. This technology, via its inherent features such as decentralisation, consensus mechanism, and immutability, supports organisations engaged in the supply chain with more transparent and trustful interactions and information flow. By adopting qualitative and quantitative data collection methods, this research provides insight into the applicability of blockchain technology within prefabrication construction supply chains. Minimum input requirements for blockchain according to types and patterns of information will be identified and categorised, and an applicable framework for using this new information integration technology will be proposed. Some key findings of this study are the identification and classification of (1) key stakeholders and recent project phases within the prefabrication supply chain, (2) flow of information across the stakeholders in different project phases, (3) important information attributes, (4) communication channels among stakeholders, and (4) impact of blockchain technology on facilitating information integration in the prefabrication construction industry of New Zealand. This research utilised pilot interviews, a questionnaire survey, a focus group study, and a validation survey to verify the objectives of the research and validate the proposed blockchain-based framework. The findings of this research could also be relevant to other industries facing similar challenges that rely heavily on information inputs. By identifying the importance of efficient information integration and the attributes crucial for successful project outcomes, stakeholders can prioritise investments in technologies like blockchain to streamline communication and data sharing across the supply chain. The identification of conventional communication modes like email, meetings, and internet-based applications in the prefabrication supply chain suggests a reliance on traditional methods for information exchange. However, the research underscores the importance of transparency, traceability, and reliability in communication, especially in the context of advanced information technology adoption. This implies a need for stakeholders to develop tailored communication strategies that leverage both conventional methods and emerging technologies to ensure effective collaboration throughout project phases. Finally, the development of a practical document management framework utilising blockchain technology presents opportunities for innovation and collaboration within the prefabrication industry. By demonstrating the applicability of blockchain in addressing document management challenges and validating the framework through expert feedback, the research paves the way for industry practitioners to adopt similar approaches in their projects. This suggests a broader trend towards embracing digital solutions and collaborative platforms to enhance information exchange, transparency, and project efficiency in the prefabrication sector.Item Evaluating woodchip bioreactors for mitigating drainage nitrate levels from a municipal wastewater land treatment site : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Environmental Sciences at Massey University, Palmerston North, New Zealand(Massey University, 2024-09-23) Romero Ramírez, Stefanía YaninaWoodchips bioreactors are a well-established end-of-drain treatment technology that has been widely used to reduce nitrate (NO₃-) from agricultural drainage water. However, their application to municipal wastewater land treatment sites remains less explored, despite potential advantages. In New Zealand, land application of pre-treated wastewater is a growing practice to mitigate excessive nutrient discharges to the aquatic environment. Land treatment can prove effective when operated correctly, but challenges arise when large volumes of wastewater, and small areas available for irrigation, necessitate high application rates, which can result in NO₃- enrichment of drainage water. The Levin Wastewater Land Treatment Site (LWLTS) is an example of where relatively high annual volumes of municipal wastewater are irrigated over an under-sized application area, resulting in high application depths (4667 mm/year). Consequently, surface drains and shallow groundwater transfer NO₃- to the Waiwiri Stream continually all year. In order to reduce the impact of the LWLTS on the water quality of the Waiwiri Stream, one of its resource consent requirements involves reducing the NO₃- levels in the Waiwiri Stream, downstream from the site. The objective of this thesis was to evaluate the potential use of woodchip bioreactors for reducing NO₃- concentrations in drainage water from LWLTS, including an assessment of the ability of soluble C dosing to enhance NO₃- removal. Initial experiments used small-scale column woodchips bioreactors, which simulated similar water temperatures and NO₃- concentrations to those at the LWLTS. The effect of different water hydraulic retention times (HRT) and the use of dosing with two soluble C sources, liquid sugar, and ethanol, were assessed. Under warm temperature conditions, the column bioreactors achieved 99% NO₃- removal efficiency with a 10-hour HRT. In contrast, under cool water temperatures at the same HRT, the NO₃- removal efficiency decreased to 31%. Soluble C dosing was an effective strategy for enhancing NO₃- removal, with the choice of C source proving to be crucial. Ethanol demonstrated to be more efficient than liquid sugar. Additionally, it was determined that dosing with ethanol at a C:N dosing rate of 1.5:1 achieved high removal efficiencies of 77% under warm conditions and at a 3.3-hour HRT, and 82% under cool conditions and at a 10-hour HRT. Based on the results of the column bioreactor study, the performance of pilot-scale woodchip bioreactors at reducing NO₃- levels in drainage water were evaluated at the LWLTS under field conditions. These experiments involved quantifying the effects of different HRTs and dosing with ethanol at different C:N ratios. Operating the bioreactors, at a 10-hour HRT achieved average NO₃- removal efficiencies of 43% and 59% during the cool and warm seasons, respectively. While, at a 20-hour HRT, the removal efficiencies were 69% and 85%, respectively. The variations in NO₃- removal efficiency between both seasons demonstrated that during the cool season the bioreactors were on average about one-third less effective. When bioreactors, operating at 6.6-hour HRT in cool conditions, were dosed with ethanol at a C:N ratio of 0.75:1, the NO₃- removal efficiency improved from 24% to 93%. This result demonstrates that under field conditions ethanol dosing proved to be a higher effective strategy for enhancing the performance of woodchip bioreactors, particularly during cool periods. Based on the findings of the pilot-scale bioreactors, two woodchip bioreactor designs were proposed for the LWLTS: a non-dosed woodchip bioreactor of 645 m³ operating at a long HRT (20 hours), and an ethanol-dosed woodchip bioreactor of 197 m³ operating at a short HRT (6.6 hours). The two proposed designs provide contrasting approaches, although both are expected to achieve the same annual NO₃- load removal (1174 kg N/year) and have similar annualised NO₃- removal costs ($6.90 and $6.50/kg N, respectively). In the long term, it is expected that the NO₃- removal of the larger non-dosed bioreactor will decline at a faster rate compared to the ethanol-dosed bioreactor due to relying solely of woodchips as the C source. However, it would be less susceptible to the risk of bioclogging and has greater capacity to increase NO₃- removal. In addition, ethanol dosing could be introduced to the larger non-dosed bioreactor in the future, when a decline in NO₃- removal efficiency is observed. Therefore, the overall flexibility of the larger bioreactor design is an advantage but comes with higher initial set-up cost. The results of this research demonstrate that woodchips bioreactors are effective treatment methods for mitigating drain water NO₃- levels at a municipal wastewater land application site. Additionally, C dosing using ethanol proved to be a promising cost-effective alternative to enhance bioreactor performance, allowing the use of relatively short HRTs, especially during cool conditions. This increases the daily volume of water that can be effectively treated.Item D2D communication based disaster response system under 5G networks : a thesis presented in partial fulfillment of the requirements for the degree of Doctor of Philosophy (PhD) in Computer and Electronics Engineering, Massey University, Auckland, New Zealand(Massey University, 2023-12-14) Ahmed, ShakilMany recent natural disasters such as tsunamis, hurricanes, volcanoes, earthquakes, etc. have led to the loss of billions of dollars, resources and human lives. These catastrophic disasters have attracted the researchers’ attention onto the significant damage to communication infrastructure. Further, communication within the first 72 hours after a disaster is critical to get help from rescuers. The advancement of wireless communication technologies, especially mobile devices and technologies, could help improve emergency communication systems. The next generation of mobile networks and technologies such as Device to Device (D2D) communication, the Internet of Things (IoT), Blockchain, and Big Data, can play significant roles in overcoming the drawbacks of the current disaster management system for data analysis and decision making. Next-generation cellular 5G and 6G network will provide several complex services for mobile phones and other communication devices. To integrate those services, the 5G cellular network will have the capabilities to handle the significant volume of data rate and the capacity to handle traffic congestion compared with the 4G or 3G cellular network. D2D communication technology, one of the major technologies in the 5G network, has the capability to exchange a high volume of traffic data directly between User Equipment (UE) without additional control from the Base Station(BS). D2D communication is used with other cell tiers in the 5G heterogeneous network (HetNet). Thus, the devices can form a cluster and cooperate with each other. As a result, the system tremendously increases network capacity as devices inside the cluster reuse the same spectrum or use an unlicensed spectrum. It will help to reduce the network’s traffic load and achieve significant throughput. D2D communication also has the ability to increase area spectral efficiency, reduce device power consumption, outage probabilities and improve network coverage. All of these characteristics are vital parameters for public safety and emergency communication applications. IoT paradigm is another promising technology with exciting features such as heterogeneity, interoperability, and flexibility. IoT has the capability to handle vast amounts of data. This huge amount of data creates Data security and data storage problems. Though, there are many technologies used to overcome the problem of validating data authenticity and data storage. Out of them, the Blockchain system is one of the emerging technologies which provides intrinsic data security. In addition, Big data technology provides data storage, modification, process, visualisation and representation in an efficient and easily understandable format. This feature is essential for disaster applications because it requires quickly collecting and processing vast amounts of data for a prompt response. Therefore, the main focus of this research work is exploring and utilising these emerging technologies (D2D, IoT, Big Data and Blockchain) and validating them with mathematical modelling for developing a disaster response system. This thesis proposes a disaster response framework by integrating the emerging technologies to overcome the problem of data communication, data security, data analysis and visualisation. Mathematical analysis and simulation models for multiple disaster sizes were developed based on D2D communication system. The result shows significant improvement in the disaster framework performance. The Quality of Services (QoS) is calculated for different scales of disaster impact. Approximately 40% disaster-affected people can get 5-10 dB and approximately 20% users get 20-25 dB Signal to Interference and Noise Ratio (SINR) when 70% infrastructure is damaged by a disaster. The network coverage increased by 25% and the network lifetime increased by 8%-14%. The research helps to develop a resilient disaster communication network which minimises the communication gap between the disaster-affected people and the rescue team. It identified the areas according to the needs of the disaster-affected people and offered a viable solution for the government and other stakeholders to visualize the disaster’s effect. This helps to make quick decisions and responses for pre and post-disaster.Item Thin film electrochemical sensor for water quality monitoring : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Engineering, Massey University, Auckland, New Zealand(Massey University, 2023-12-11) Lal, KartikayFreshwater is the most precious natural resource, essential for supporting life. Aquatic ecosystems flourish in freshwater sources, and many regions around the world depend on aquatic food sources, such as fish. Nitrogen and phosphorous are the two nutrients, in particular, that are essential for growth of aquatic plants and algae. However, with rising population and anthropogenic activities, excessive amounts of such nutrients enter our waterways through various natural processes, thereby degrading the quality of freshwater sources. Elevated levels of nitrate-nitrogen content, in particular, lead to consequences for both aquatic life as well as human health, which has been a cause for concern for many decades. As recommended by the World Health Organization, the maximum permissible nitrate level in water is 11.3 mg/L. These levels are often exceeded in coastal areas or freshwater bodies that are close to agricultural land. Therefore, it is essential to monitor nitrate levels in freshwater sources in real-time, which can be achieved by employing detection methods commonly used to detect ionic content in water. Hence, a comprehensive review was carried out on various field-deployable electrochemical and optical detection methods that could be employed for in-situ detection of nitrate ions in water. The primary focus was on electrochemical methods that could be integrated with low-cost planar electrodes to achieve targeted detection of nitrate ions in water. Designing resilient sensors for real-time monitoring of water quality is a challenging task due to the harsh environment to which they are subjected. There is a significant need for sensors with attributes such as repeatability, sensitivity, low-cost, and selectivity. These attributes were first explored by evaluating the performance of silver and copper materials on three distinct geometric patterns of electrodes. The experiments produced promising results with interdigitated pattern of copper electrodes that were successful in detecting 0.1-0.5 mg/L of nitrate ions in deionised water. The interdigitated geometric pattern of electrodes were further analyzed in four distinct materials namely, silver, gold, copper, and tin with real-world freshwater samples that were collected from three different freshwater bodies. The water samples were used to synthesize varying concentrations of nitrate ions. The results showed tin electrodes performed better over other materials for nitrate concentrations from 0.1-1 mg/L in complex matrix of real-world sample. The nitrate sensor eventually needs to be deployed in freshwater bodies, hence a real-time water quality monitoring system was also built that incorporated sensors to monitor five basic water quality parameters with the aim to monitor and study the quality of water around the local area.Item Modelling the co-dependent diffusion of innovation in two-sided markets : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Marketing at Massey University, Albany Campus, New Zealand(Massey University, 2023) Chen, Xing (Alison)With the advancement of technology, many innovations, like Electric Vehicles (EV) and contactless payment, are co-dependent. The diffusion of co-dependent innovation requires joint usage from more than one adopting group to enable functionality. For instance, EV owners will not drive their EVs unless they know that there are charging stations along their trips. Contactless payers will not pay with a “waving” or “tapping” of their contactless-enabled cards at the checkout unless they know that merchants accept this payment method. Prior literature terms innovations that are compatible and can be used together as complementary innovations, and those adopted in sequence as contingent innovations (Peterson & Mahajan, 1978). Researchers build models of such innovations based on multi-product growth models or the hardware-software paradigm relying on the operation of the network effects (Bayus, 1987; Bucklin & Sengupta, 1993b; Stremersch et al., 2007). However, these terminologies fail to accurately describe co-dependent innovations, which require uptake by more than one adopting group and will only function with simultaneous use. When there are two distinct adopting groups, the market in which the innovation diffuses is a two-sided market. There is co-dependency between the adopting groups, and thus, between the diffusion path of each innovation. As the diffusion of these co-dependent innovations is yet to be modelled, the current study aims to fill this gap. Using eight years of transaction-based data on a novel payment innovation in a developed western economy, we conceptualise co-dependent diffusion of innovation and examine its properties with three empirical studies. Results from Study 1 (presented in Chapter 2) demonstrate that prior models, including the multi-product Bass model, the model of indirect network effects, and the influx-outflow model proposed for a competitive two-sided market, fail to adequately depict the co-dependent diffusion of innovation. Building on findings from Study 1, Study 2 (presented in Chapter 3) shows that the Bass model with churn rates could be a promising candidate for modelling the co-dependent diffusion of innovation. In the payment innovation context, the churn rate represents the user dropout as a percentage of the current user base. Results reveal that merchants exhibit a higher churn rate than consumers, and the churn rates vary by industry. Simulated churn rates show opposite impacts on the innovation effect and the imitation effect in the diffusion process, where managerial implications can be drawn on tailoring strategies to different adopting groups based on the churn rates aiming to fuel the diffusion. Study 2 also highlights the potential of using churn rates as the proxy for the feedback effects between the adopting groups. As the interaction effect between the adopting groups is established in Study 2, Study 3 (presented in Chapter 4) applies the Vector Error Correction Model (VECM) to account for consumer and merchant usage simultaneously. In the short term, consumer usage increases as a result of the variation in merchants’ usage. The positive response of consumers remains significant in the long run. On the contrary, merchants exhibit decreasing response to the variation in consumers’ usage; thus, only the immediate response is strong and significant in the short run. It is worth noting that, unlike the impact of marketing mix factors on sales that will die down over time, the variation of usage in one adopting group at the early stage of the diffusion could permanently lift the usage of the other group. This provides the first robust insights into the empirical patterns of co-dependency during the diffusion of innovation in two-sided markets and demonstrates how other such markets can be studied in the future. Managers can stimulate usage on one side of the market in the early stage of the innovation growth to leverage the interaction effect between the two sides. As emerged from the current work, an early push of usage on the merchant side may drive the co-dependent diffusion of the innovation in the long run.Item Using market research methodologies to advance public engagement with emerging climate technologies : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy via publication in Marketing at Massey University, Manawatū, New Zealand(Massey University, 2022) Carlisle, DanielThe world is facing an unprecedented climate emergency that threatens humanity and global ecosystems. To help avoid some of the worst impacts, scientists are developing innovative technologies for addressing rising greenhouse gas emissions and climate change. However, in the early stages of research and development, the effectiveness, consequences, and desirability of implementing these technologies remains highly uncertain. Early public engagement is therefore critical for ensuring research and development pathways are acceptable to society. Currently, it remains unclear how best to engage the public on a global scale; an issue addressed in this thesis by drawing on theories and methodologies applied in the marketing discipline to advance the field of public engagement. The core methodology draws on marketing theories and measurement metrics by drawing on associative network theories of memory (ANTM) to model cognitive associations (i.e., public perceptions) with unfamiliar concepts. Study One is a replication and extension of work by (Wright, Teagle, & Feetham, 2014) and uses qualitative and quantitative methods to measure public perceptions of six climate engineering technologies across countries and over time. The results show strong perceptual differences between technologies, but remarkable consistency between countries and over time. This consistency validates the cognitive association method as a robust tool for rapid public engagement and tracking perceptions as they evolve. Study Two builds on Study One by drawing on additional dual processing theories and using an experimental design to test how citizens form opinions about emerging climate technologies. Contrary to concerns that survey methods elicit insufficiently considered responses, the study finds that citizens rely on rapid, snap judgements to form opinions, and that encouraging more thorough consideration does not affect their responses. Thus, the research further validates the use of survey methodologies for public engagement. Study Three shifts focus, measuring perceptions of alternative fuels for decarbonising the shipping industry – a previously unresearched topic. The study is also the first to use a mixed-method approach to modelling cognitive associations in academic literature. Again, the quantitative findings showed strong, previously-unknown differences in perceptions between alternative fuels. Furthermore, the qualitative analysis supplemented these findings with rich insights into the drivers behind differing public perceptions. This thesis makes several notable contributions: Practically, the results demonstrate the public’s consistent preference for Carbon Dioxide Removal over Solar Radiation Management, their cautious support for carbon capture technologies, a strong distaste for stratospheric aerosol injection and ammonia as a shipping fuel, a striking preference for nuclear propulsion over heavy fuel oil, support for hydrogen and biofuel powered shipping, support for local implementation of alternative shipping fuels, and conditional support for small-scale research into acceptable emerging technologies. Theoretically, the research advances ANTM and dual processing theories in the context of emerging technologies, yielding results that are broadly applicable to not only public engagement with science, but also market research, brand tracking, and consumer judgement. Methodologically, the research validates cognitive association methods for cross-country public engagement, demonstrates the ability to track perceptions over time, and demonstrates a mixed-method approach to modelling cognitive associations. Finally, the research demonstrates the importance of conducting early and ongoing public engagement to identify acceptable decarbonisation pathways, guide research trajectories, and inform climate policy.