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Purpose – The advancement of multimedia technology has spurred the use of multimedia in business practice. The adoption of audio and visual data will accelerate as marketing scholars become more aware of the value of audio and visual data and the technologies required to reveal insights into marketing problems. This chapter aims to introduce marketing scholars into this field of research.Design/methodology/approach – This chapter reviews the current technology in audio and visual data analysis and discusses rewarding research opportunities in marketing using these data.Findings – Compared with traditional data like survey and scanner data, audio and visual data provides richer information and is easier to collect. Given these superiority, data availability, feasibility of storage, and increasing computational power, we believe that these data will contribute to better marketing practices with the help of marketing scholars in the near future.Practical implications: The adoption of audio and visual data in marketing practices will help practitioners to get better insights into marketing problems and thus make better decisions.Value/originality – This chapter makes first attempt in the marketing literature to review the current technology in audio and visual data analysis and proposes promising applications of such technology. We hope it will inspire scholars to utilize audio and visual data in marketing research.

This paper describes the application of, enhancements to, and use of surface fire spread models in predicting and mitigating fire risk in the Wildland–Urban Interface (WUI). Research and fire management strategies undertaken in the East Bay Hill region (containing the 1991 Tunnel Fire) of the San Francisco Bay area over the past decade are reported. We ascertain that surface fire spread modeling has impacted policy and decision making, resulting in a regional strategic plan where large landowners and public agencies are able to implement fire mitigation practices. Although these practices involve extensive fuel management within a buffer zone between the wildland and residential properties, the residential property owners are still at risk, as no strategy within neighborhoods can be accurately mapped using the current scale of the data and models. WUI fires are eventually extinguished by fire fighters on the ground, up close, and at the backyard scale. We argue that large-scale (backyard scale) mapping and modeling of surface fire spread is necessary to engage the individual homeowner in a fuels management strategy. We describe our ongoing research and strategies, and suggest goals for future research and development in the area of large-scale WUI fire modeling and management.

A recent study reported Black women are frequently labeled unprofessional due to hair presentation, 1.5 times more likely to be sent home citing “unprofessional hair,” and 80% likely to alter their natural hair texture (Dove, 2019) through chemicals or heat to fit into organizational norms. Meanwhile, conversations about hair discrimination and bias remain whispers in The Ivory Tower. Despite this study, contemporary research regarding higher education and the politics of Black women, Black hair, and hair texture is sparse. The lack of representation in higher education organizations and lack of literature suggest that Black, higher education professional women are at risk of experiencing chilly work environments that could impact belonging, career trajectory, and earning potential. Some individuals outside the African Diaspora may consider the notion of a physical characteristic, like hair, to be insignificant, let alone a salient identity for Black women. However, my experience as a higher education practitioner and scholar states differently. I assert higher education institutions continue to perpetuate and reproduce oppressive dynamics that specifically target Black women and Black hair when hair discrimination and bias are left out of the conversation to address diversity and inclusion concerns. This chapter introduces a historical context of Black hair discrimination; explores my lived experiences navigating Black hair, hair texture, and professionalism in higher education; outlines challenges for higher education institutions and prioritizes Black women alongside diversity and inclusion efforts.

The racialized gendered body in consumer culture invokes the construction of identities and representation of beauty through embodiment practices. As companies hone in on consumer racial marker distinctions to enhance uniqueness as otherness for profit, an analysis of hair products marketed for Black hair textures provides an opportunity to analyze how products use these at the intersection of race, gender, and beauty. This study uses constructivist grounded theory to analyze the product names and long descriptions for 124 shampoos marketed for Black hair textures on the websites of two major retailers to answer the following questions: What message does the discourse of shampoo product descriptions marketed to Black hair textures communicate about beauty? What message does the discourse of shampoo product descriptions marketed to Black hair textures communicate about Blackness? How does this discourse define the embodiment of Black beauty through hair? The results reveal that the racialized gendered body in consumer culture invokes the construction of identities and representations of beauty through embodiment practices. Through advertisements and product descriptions, beauty companies create ideal images of the lived experiences achieved through consuming beauty products. By constructing visual interpretations of racial signifiers through text, marketing strategies encourage the consumption of otherness, creating a racialized space for Blackness consumption. Combining the five senses with the descriptions of shampoo products marketed for Black hair textures helps us see how beauty embodiment practices reinforce racialized and gendered practices to subjugate the Black body.

In this chapter, drone and vision camera technology have been combined for monitoring the crop product quality. Three vegetable crops such as tomato, cauliflower, and eggplant are considered for quality monitoring; hence, image datasets are collected for those vegetables only. The proposed method classified the vegetables into two classes as rotten and nonrotten products so the images were collected for rotten and nonrotten products. Three different features information such as chromatic features, contour features, and texture features have been extracted from the dataset and further used to train a Gaussian kernel support vector machine algorithm for identifying the product quality. The system utilized multiple features such as chromatic, contour, and texture features in classifier training which enhances the accuracy and robustness of the system. Chromatic features were utilized for detecting the crop while other features such as contour and texture features were utilized for further classifier building to identify the crop product quality. The performance of the system is evaluated based on the true positive rate, false discovery rate, positive predictive value, and accuracy. The proposed system identified good and bad products with a 97.9% of true positive rate, 2.43 % of false discovery rate, 97.73% positive predictive value, and 95.4% of accuracy. The achieved results concluded that the results are lucrative and the proposed system is efficient in agriculture product quality monitoring.

The growth of social media and the sharing economy is generating abundant unstructured image and video data. Computer vision techniques can derive rich insights from unstructured data and can inform recommendations for increasing profits and consumer utility – if only the model outputs are interpretable enough to earn the trust of consumers and buy-in from companies. To build a foundation for understanding the importance of model interpretation in image analytics, the first section of this article reviews the existing work along three dimensions: the data type (image data vs. video data), model structure (feature-level vs. pixel-level), and primary application (to increase company profits vs. to maximize consumer utility). The second section discusses how the “black box” of pixel-level models leads to legal and ethical problems, but interpretability can be improved with eXplainable Artificial Intelligence (XAI) methods. We classify and review XAI methods based on transparency, the scope of interpretability (global vs. local), and model specificity (model-specific vs. model-agnostic); in marketing research, transparent, local, and model-agnostic methods are most common. The third section proposes three promising future research directions related to model interpretability: the economic value of augmented reality in 3D product tracking and visualization, field experiments to compare human judgments with the outputs of machine vision systems, and XAI methods to test strategies for mitigating algorithmic bias.

This qualitative study investigated the relationship between beauty standards and identity in the United States from the perspective of 20 self-identified millennial Black women. During semi-structured virtual interviews, participants defined Black, American, and millennial beauty standards distinctly. American beauty was associated with Eurocentrism and mainstream media representation. Interpretations of a millennial beauty standard were aligned with perceptions of the generation as tolerant and politically conscious. Black American beauty standards embraced the range of hair textures and skin tones present in the African diaspora. While participants were cognizant of the different beauty ideals present, their interaction with beauty standards was ambivalent. Interviewees found beauty knowledge accessible through social media. However, they remain confined to a restrictive beauty standard due to workplace expectations around professionalism. Participants negotiated where and when to express their intracultural beauty ideals but participated in the beauty industry through processes of learning how to care for their hair in its natural state. Even though they have autonomy and flexibility in expressing their cultural styles, personal and professional repercussions are still plausible. Future studies can expand on these findings by exploring perceptions of American beauty standards from a different generation, region, or identity.

Building on a proposed four-phase model of the design revolution, I outline an expanded domain to which design ideas may be applied, and offer a design theory that has general application to the expanded design domain. Numerous disciplines within the domain of design, which have been separately developed, are converging through digital devices and software such as computer-aided design programs. I refer to this “Connection” as the first phase of the design revolution. In the second “Expansion” phase of the design revolution, I expect that the domain where principles of design are applied will be expanded beyond the visual to include all five human senses. The design theory that I propose is a logical application of design principles to various disciplines in the second phase of the revolution. In the third “Application” phase of the design revolution, the design theory will be applied not only to conventional objects of design such as products and services, but also to institutions and systems such as governments, firms, and households. Finally, in the fourth “Integration” phase of the revolution, various parts of the world will be integrated into a holistic system under a single design theory.