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Search results for: Sibongile Masemola
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</div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: Sibongile Masemola</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2</span> Building Brand Equity in a Stigmatised Market: A Cannabis Industry Case Study</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sibongile%20Masemola">Sibongile Masemola</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In 2018, South Africa decriminalised recreational cannabis use and private cultivation, since then, cannabis businesses have been established to meet the demand. However, marketing activities remain limited in this industry, and businesses are unable to disseminate promotional messages, however, as a solution, firms can promote their brands and positioning instead of the actual product (Bick, 2015). Branding is essential to create differences among cannabis firms and to attract and keep customers (Abrahamsson, 2014). Building cannabis firms into brands can better position them in the mind of the consumer so that they become and remain competitive. The aim of this study was to explore how South African cannabis retailers can build brand equity in a stigmatised market, despite significant restrictions on marketing efforts. Keller’s (2001) customer-based brand equity (CBBE) model was used as the as the theoretical framework and explored how cannabis firms build their businesses into brands through developing their brand identity, meaning, performance, and relationships, and ultimately creating brand equity. The study employed a qualitative research method, using semi-structured in-depth interviews among 17 participants to gain insights from cannabis owners and marketers in the recreational cannabis environment. Most findings were presented according to the blocks of CBBE model. Furthermore, a conceptual framework named the stigma-based brand equity (SBBE) model was adapted from Keller’s CBBE model to include an additional building block that accounts for industry-specific characteristics unique to stigmatised markets. Findings revealed the pervasiveness of education and its significance to brand building in a stigmatised industry. Results also demonstrated the overall effect stigma has on businesses and their consumers due to the longstanding negative evaluations of cannabis. Hence, through stigma-bonding, brands can develop deep identity-related psychological bonds with their consumers that will potentially lead to strong brand resonance. This study aims to contribute business-relevant knowledge for firms operating in core-stigmatised markets under controlled marketing regulations by exploring how cannabis firms can build brand equity. Practically, this study presents recommendations for retailers in stigmatised markets on how to destigmatise, build brand identity, create brand meaning, elicit desired brand responses, and develop brand relationships – ultimately building brand equity. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=branding" title="branding">branding</a>, <a href="https://publications.waset.org/abstracts/search?q=brand%20equity" title=" brand equity"> brand equity</a>, <a href="https://publications.waset.org/abstracts/search?q=cannabis" title=" cannabis"> cannabis</a>, <a href="https://publications.waset.org/abstracts/search?q=organisational%20stigma" title=" organisational stigma"> organisational stigma</a> </p> <a href="https://publications.waset.org/abstracts/150931/building-brand-equity-in-a-stigmatised-market-a-cannabis-industry-case-study" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/150931.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">101</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1</span> Linking Soil Spectral Behavior and Moisture Content for Soil Moisture Content Retrieval at Field Scale</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yonwaba%20Atyosi">Yonwaba Atyosi</a>, <a href="https://publications.waset.org/abstracts/search?q=Moses%20Cho"> Moses Cho</a>, <a href="https://publications.waset.org/abstracts/search?q=Abel%20Ramoelo"> Abel Ramoelo</a>, <a href="https://publications.waset.org/abstracts/search?q=Nobuhle%20Majozi"> Nobuhle Majozi</a>, <a href="https://publications.waset.org/abstracts/search?q=Cecilia%20Masemola"> Cecilia Masemola</a>, <a href="https://publications.waset.org/abstracts/search?q=Yoliswa%20Mkhize"> Yoliswa Mkhize</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Spectroscopy has been widely used to understand the hyperspectral remote sensing of soils. Accurate and efficient measurement of soil moisture is essential for precision agriculture. The aim of this study was to understand the spectral behavior of soil at different soil water content levels and identify the significant spectral bands for soil moisture content retrieval at field-scale. The study consisted of 60 soil samples from a maize farm, divided into four different treatments representing different moisture levels. Spectral signatures were measured for each sample in laboratory under artificial light using an Analytical Spectral Device (ASD) spectrometer, covering a wavelength range from 350 nm to 2500 nm, with a spectral resolution of 1 nm. The results showed that the absorption features at 1450 nm, 1900 nm, and 2200 nm were particularly sensitive to soil moisture content and exhibited strong correlations with the water content levels. Continuum removal was developed in the R programming language to enhance the absorption features of soil moisture and to precisely understand its spectral behavior at different water content levels. Statistical analysis using partial least squares regression (PLSR) models were performed to quantify the correlation between the spectral bands and soil moisture content. This study provides insights into the spectral behavior of soil at different water content levels and identifies the significant spectral bands for soil moisture content retrieval. The findings highlight the potential of spectroscopy for non-destructive and rapid soil moisture measurement, which can be applied to various fields such as precision agriculture, hydrology, and environmental monitoring. However, it is important to note that the spectral behavior of soil can be influenced by various factors such as soil type, texture, and organic matter content, and caution should be taken when applying the results to other soil systems. The results of this study showed a good agreement between measured and predicted values of Soil Moisture Content with high R2 and low root mean square error (RMSE) values. Model validation using independent data was satisfactory for all the studied soil samples. The results has significant implications for developing high-resolution and precise field-scale soil moisture retrieval models. These models can be used to understand the spatial and temporal variation of soil moisture content in agricultural fields, which is essential for managing irrigation and optimizing crop yield. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=soil%20moisture%20content%20retrieval" title="soil moisture content retrieval">soil moisture content retrieval</a>, <a href="https://publications.waset.org/abstracts/search?q=precision%20agriculture" title=" precision agriculture"> precision agriculture</a>, <a href="https://publications.waset.org/abstracts/search?q=continuum%20removal" title=" continuum removal"> continuum removal</a>, <a href="https://publications.waset.org/abstracts/search?q=remote%20sensing" title=" remote sensing"> remote sensing</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=spectroscopy" title=" spectroscopy"> spectroscopy</a> </p> <a href="https://publications.waset.org/abstracts/168913/linking-soil-spectral-behavior-and-moisture-content-for-soil-moisture-content-retrieval-at-field-scale" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/168913.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">99</span> </span> </div> </div> </div> </main> <footer> <div id="infolinks" class="pt-3 pb-2"> <div class="container"> <div style="background-color:#f5f5f5;" class="p-3"> <div class="row"> <div class="col-md-2"> <ul class="list-unstyled"> About <li><a href="https://waset.org/page/support">About Us</a></li> <li><a href="https://waset.org/page/support#legal-information">Legal</a></li> <li><a target="_blank" rel="nofollow" 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