Research@Lincoln

Recent Submissions

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    The number of larval instars in the flax weevil (Anagotus fairburni) (Coleoptera: Curculionidae)
    (Taylor & Francis Group, 2023-09-20) Brockelsby, WD; Miskelly, CM; Glare, Travis; Minor, MA
    The flax weevil Anagotus fairburni is a large flightless beetle, that is one of the members of the endemic insect ‘megafauna’ of New Zealand. It is a protected species that currently persists only on predator-free islands or in remote and difficult to access alpine areas. Little is documented about the ecology of the flax weevil. In this study we estimated the number of instars in the A. fairburni life cycle by measuring the head capsule widths of larvae collected in the field on Mana Island Scientific Reserve. We used kernel density function estimates to predict average head-capsule widths and the number of larval instars. We then used Brooks-Dyar’s law on the head capsule width data and analysed Brooks and Crosby indexes to refine the estimated number of instars based on imperfect data. Results from sampling of 86 larvae suggested four instar groupings, but further analysis based on Brooks-Dyar’s law found that A. fairburni likely passes through 6 or 7 larval stages prior to pupation, with some uncertainty for smaller instars. Our method provides new data on ecology of an endemic species and provides a framework for further work on similar endangered species where data is imperfect or difficult to gather.
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    The impact of online shopping on food stockpiling behaviour in China
    (Taylor & Francis Group, 2023-10-12) Xia, L; Ma, Wanglin; Wang, D; Li, J
    Food stockpiling is a common strategy to cope with food shortages, especially during major crises such as the COVID-19 pandemic. This paper investigates the effects of online shopping on household food stockpiling behaviour, using data collected from urban residents in China. Unlike previous studies considering only binary decisions, we take into account two-stage decisions (whether to stockpile and how much to stockpile). We employ a novel double-hurdle two-stage least square approach to model the sequential decision-making process and to address the endogeneity issue of online shopping. The empirical results show that online shopping significantly increases the probability that households choose to stockpile food and stockpiling ratio. Online shoppers in Eastern China are more likely to stockpile food, while their counterparts in the Western region tend to have a higher food stockpiling ratio. Online shopping significantly increases stockpiling ratio of perishable food such as fruits and vegetables relative to non-perishable food such as grains.
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    Impact of mobile payment adoption on household expenditures and subjective well-being
    (Wiley-Blackwell, 2023-09-26) He, Q; Ma, Wanglin; Vatsa, Puneet; Zheng, H
    This paper estimates the effects of mobile payment adoption on household expenditures and people's subjective well-being. We consider four categories of household expenditures (that on clothes, durable goods, consumer goods, and cultural and leisure activities) and four indicators (life satisfaction, contentment, income satisfaction, and depression) of subjective well-being. We use the Augmented Inverse Probability Weighting estimator to analyze the 2017 Chinese General Social Survey data while accounting for the selection bias inherent in mobile payment adoption. The empirical results show that people's decisions to adopt mobile payment are positively associated with their educational levels, car ownership, social interaction, internet penetration rate, and residential location. Mobile payment adoption significantly increases household expenditures on consumer goods and cultural and leisure activities but not on expenditures on clothes and durable goods. Moreover, mobile payment adoption significantly decreases people's contentment while increasing depression. We also find that mobile payment adoption significantly decreases the contentment of urban people but significantly increases the depression of rural people.
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    United Kingdom lamb consumer consumption behaviours and product preferences: A Latent Class Analysis (2020)
    (AERU, Lincoln University | Te Whare Wānaka o Aoraki, 2022-03) Tait, Peter; Saunders, Caroline; Dalziel, Paul; Rutherford, Paul; Driver, Tim; Guenther, Meike
    This study is part of a research programme entitled Unlocking Export Prosperity from the Agri-food Values of Aotearoa New Zealand. It is funded by the Ministry of Business, Innovation and Employment (MBIE) Endeavour Fund for science research programmes. The research aims to provide new knowledge on how local enterprises can achieve higher returns by ensuring global consumers understand the distinctive qualities of the physical, credence and cultural attributes of agri-food products that are “Made in New Zealand”. Agricultural exports are an important contributor to the New Zealand (NZ) economy and the United Kingdom (UK) is established as an important lamb product destination. It is critically important for NZ exporters to understand export markets and the different cultures and preferences of those consumers to safeguard market access, and for realising potential premiums. This report describes the results of a survey of UK lamb leg consumers that was designed to assess consumption behaviour and consumer willingness-to-pay (WTP) for credence attributes. While search attributes such as price or colour can be observed directly, and experience attributes such as flavour or texture can be assessed when consumed, credence attributes such as environmental sustainability cannot be immediately seen or experienced at the point of sale. For products promoting credence attributes, the role of verification, including labelling is of significant importance. Our approach is to apply a Choice Experiment economic valuation method, analysed using a statistical approach called Latent Class Modelling that describes profiles for different consumer segments identified in the data and provides estimates of attribute WTP across these segments.
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    United Kingdom lamb consumer consumption behaviours and product preferences: A Latent Class Analysis of New Zealand lamb
    (AERU, Lincoln University | Te Whare Wānaka o Aoraki, 2022-08) Tait, Peter; Saunders, Caroline; Dalziel, Paul; Rutherford, Paul; Driver, Tim; Guenther, Meike
    This study is part of a research programme entitled Unlocking Export Prosperity from the Agri-food Values of Aotearoa New Zealand. It is funded by the Ministry of Business, Innovation and Employment (MBIE) Endeavour Fund for science research programmes. Information on this research programme including reports of other surveys is available from the AERU website https://www.aeru.co.nz/projects/uep. The research aims to provide new knowledge on how local enterprises can achieve higher returns by ensuring global consumers understand the distinctive qualities of the physical, credence, and cultural attributes of agri-food products that are “Made in New Zealand”. Agricultural exports are an important contributor to the New Zealand (NZ) economy and the United Kingdom (UK) is established as an important lamb product destination. It is critically important for NZ exporters to understand export markets and the different cultures and preferences of those consumers to safeguard market access, and for realising potential premiums. This report describes the application of a survey of UK lamb leg consumers that is designed to examine consumption behaviour and consumer Willingness-to-Pay (WTP) for credence attributes. While search attributes such as price or colour can be observed directly, experience attributes such as flavour or texture can be assessed when consumed, credence attributes such as environmental sustainability cannot be immediately seen or experienced at the point of sale. For products promoting credence attributes, the role of verification, including labelling, is of significant importance. Our approach is to apply a Discrete Choice Experiment economic valuation method, analysed using a statistical approach called Latent Class Modelling that describes profiles for different consumer segments identified in the data and provides estimates of attribute WTP across these segments.