Mundane emotions: Losing yourself in boredom, time and technology

Marketing and consumer research has drawn attention to the positive and joyful emotional features of consumer tribes. However, research has little to say on boredom, an emotional state already prevalent in consumers' lives, yet exacerbated during the COVID-19 pandemic due to lockdown restrictions that prevented tribal consumption experiences. Informed by Heidegger's understanding of boredom as a fundamental mood tied to temporality, this research uses semi-structured interviews to identify two kinds of boredom – superficial and profound boredom – and their specific temporal dynamics. Superficial boredom is common and refers to a situational restlessness in which people desire distractions. In contrast, profound boredom refers to an existential discomfort in which people struggle with their sense of self, but ultimately can result in the discovery of tribal passions. We explain superficial boredom as a symptom of a dominant temporal regime that comprises connectivity and acceleration. Together these temporal logics fragment and compress time in ways that encourage mundane social media consumption that simply fills time. We also explain how profound boredom stems from an abundance of uninterrupted time spent in relative solitude. In extending Heidegger's theory of boredom to analyse contemporary boredom in an era where digital technology is ubiquitous, our research contributes to consumer research's understanding of mundane emotions and discusses what it means to be bored together.

A Novel Framework to Forecast COVID-19 Incidence Based on Google Trends Search Data

The global outbreak of coronavirus disease 2019 (COVID-19) has spread to more than 200 countries worldwide, leading to severe health and socioeconomic consequences. As such, the topic of monitoring and predicting epidemics has been attracting a lot of interest. Previous work reported search volumes from Google Trends are beneficial in decoding influenza dynamics, implying its potential for COVID-19 prediction. Therefore, a predictive model using the Wiener methods was built based on epidemic-related search queries from Google Trends, along with climate variables, aiming to forecast the dynamics of the weekly COVID-19 incidence in Washington, DC, USA. The Wiener model, which shares the merits of interpretability, low computation costs, and adaptation to nonlinear fluctuations, was used in this study. Models with multiple sets of features were constructed and further optimized by the highest weight selecting strategy. Furthermore, comparisons to the other two commonly used prediction models based on the autoregressive integrated moving average (ARIMA) and long short-term memory (LSTM) were also performed. Our results showed the predicted COVID-19 trends significantly correlated with the actual (rho <inline-formula> <tex-math notation="LaTeX">$=$</tex-math> </inline-formula> 0.88, <inline-formula> <tex-math notation="LaTeX">$p $</tex-math> </inline-formula> <inline-formula> <tex-math notation="LaTeX">$<$</tex-math> </inline-formula> 0.0001), outperforming those with ARIMA and LSTM approaches, indicating Google Trends data as a useful tool in terms of COVID-19 prediction. Also, the model using 20 search queries with the highest weighting outperformed all other models, supporting the highest weight feature selection as a feasible criterion. Google Trends search query data can be used to forecast the outbreak of COVID-19, which might assist health policymakers to allocate health care resources and taking preventive strategies. IEEE

Technology Trends 2023: The Competence Challenge

Competitiveness demands continuous competence growth. At year-end 2022 and within the steady state of post-COVID-19 change, Vector Consulting, with IEEE Software, contacted industry experts about their challenges and resolutions. A lack of competence is the biggest challenge identified in our annual industry survey with IEEE Software. The growing lack of competence is perceived across industries as both the major short-term as well as midterm challenge. Technology companies increasingly suffer from inadequate competencies, both in terms of quantity and quality. In turn, their innovation and competitiveness decrease.

Stakeholders' perception of a total market approach to HIV self-testing (HIVST) for the private sector in Nigeria.

BACKGROUND: The continuous supply of affordable and quality HIV self-test (HIVST) is a key pillar toward achieving the global HIV 95-95-95 target in Nigeria. This was a descriptive qualitative study that explored private sector stakeholders' perceptions of the enablers and barriers of the HIVST market in Nigeria. METHODS: A total of 29 In-depth interviews (IDIs) were conducted with HIVST supply chain stakeholders and private sector providers (PPMVs and Community Pharmacies). Responses were analyzed using Nvivo software and we systematically developed a total market approach analysis for supply chain stakeholders and archetypes for community Pharmacies and PPMVs based on insights gathered from their journey map. RESULTS: Challenges to the supply side dynamics include forecasting, point of care service delivery, the availability of free and subsidized HIVST kits in the market, neglect of private sector providers (Community Pharmacists and PPMVs) in the healthcare delivery system, limited demand for HIVST, and regulatory bottlenecks influences the overall market dynamics. High cost of the HIVST kit, which triggers low availability, accessibility and affordability from the demand side, depicts the need to understand the market dynamics. Addressing the barriers and optimizing the enablers of the three-model pharmacist and PPMV's will change the market dynamic and service delivery to generate demand. CONCLUSION: To address challenges which already exist, the government need to revise the process guidelines for introducing new HIVST products in the Nigerian market, developing contingency plans to ensure the supply of HIVST remains sufficient when experiencing economic shocks, and create a sustainable roadmap toward optimizing the market for HIVST kits.

Predicting User Satisfaction of Mobile Healthcare Services Using Machine Learning: Confronting the COVID-19 Pandemic

The outbreak of COVID-19 led to rapid development of the mobile healthcare services. Given that user satisfaction is of great significance in inducing marketing success in competition markets, this research explores and predicts user satisfaction with mobile healthcare services. Specifically, the current research aimed to design a machine learning model that predicts user satisfaction with healthcare services using big data from Google Play Store reviews and satisfaction ratings. By dealing with the sentimental features in online reviews with five classifiers, the authors find that logistic regression with term frequency-inverse document frequency (TF-IDF) and XGBoost with bag of words (BoW) have superior performances in predicting user satisfaction for healthcare services. Based on these results, the authors conclude that such user-generated texts as online reviews can be used to predict user satisfaction, and logistic regression with TF-IDF and XGBoost with BoW can be prioritized for developing online review analysis platforms for healthcare service providers.

IMPACT OF THE COVID-19 PANDEMIC ON THE FURNITURE MARKET IN SERBIA

The furniture industry is one of the strategic industries in Serbia, with about 30,000 employees. The subject of research in this paper was the furniture market in three selected regions in Serbia with the aim to consider the influence of certain factors on the demand for furniture during the COVID-19 pandemic, as follows: prices, quality, payment terms, brands, promotions, terms of purchase, frequency of furniture purchase, assortment, and online shopping. The methods used for the research included field research, surveys and analysis of the obtained data. The sample size included 210 respondents who were selected by random sampling method. When it comes to the impact of the COVID-19 pandemic, research shows that it did not significantly influence consumers' decision to buy furniture. Preference is given to domestic producers, both because of the availability of products and because of the more affordable price. When it comes to quality of furniture, the research showed that the 63% are satisfied with the ratio of price and quality, as well as the range offered on the market. The terms of payment are satisfactory, with the 58% customers opting for cash payments. On the other hand, the choice of the manufacturer is based on previous positive experience or recommendation, while going to the salon is the choice of 92% customers, compared to online shopping (8%). The conducted research is important for producers, distributors, and traders of furniture, as well as for the academic community because, for the first time, research was conducted on this topic in Serbia. © 2022 15th International Scientific Conference WoodEMA 2022 - Crisis Management and Safety Foresight in Forest-Based Sector and SMES Operating in the Global Environment. All rights reserved.

Dynamic relationship between green bonds and major financial asset markets from the perspective of climate change

In recent years, changes in the climate environment have caused a considerable impact on the economy and finance, especially after the signing of the Paris Agreement decided to prevent the further increase in the earth's temperature and smoothly transformed into a low-carbon society, various markets have been affected to varying degrees, and at the same time, green bonds as an emerging environmental protection tool have sprung up and become the focus of many investors and researchers. The emergence and rise of eco-friendly investment opportunities such as green bonds is bound to have an impact on other markets, but little research has been done on their dynamic correlation with the U.S. stock market, crude oil and gold markets, especially in our current period of COVID-19 tensions, it is necessary to explore the dynamics between markets and the risk aversion of green bonds to climate change. In this paper, we study the dynamic correlation between three green investment vehicles (S&P Green Bond, China Green Bond, and Climate Bond) and three major markets, and explore whether the linkage between each market will be affected by economic risks and climate change risks by adding climate risk proxy indicators and economic policy uncertainties. This is not only of guiding significance for investors who are eco-friendly to judge the effectiveness of asset allocation and hedging in investment decisions, but also has certain reference for policymakers and market participants who want to achieve green investment, which will help the market to maintain a stable and smooth transition to a low-carbon economy in the event of pressure.

DeepWare: Imaging Performance Counters With Deep Learning to Detect Ransomware

In the year passed, rarely a month passes without a ransomware incident being published in a newspaper or social media. In addition to the rise in the frequency of ransomware attacks, emerging attacks are very effective as they utilize sophisticated techniques to bypass existing organizational security perimeter. To tackle this issue, this paper presents "DeepWare,” which is a ransomware detection model inspired by deep learning and hardware performance counter (HPC). Different from previous works aiming to check all HPC results returned from a single timing for every running process, DeepWare carries out a simple yet effective concept of " imaging hardware performance counters with deep learning to detect ransomware ,” so as to identify ransomware efficiently and effectively. To be more specific, DeepWare monitors the system-wide change in the distribution of HPC data. By imaging the HPC values and restructuring the conventional CNN model, DeepWare can address HPC's nondeterminism issue by extracting the event-specific and event-wise behavioral features, which allows it to distinguish the ransomware activity from the benign one effectively. The experiment results across ransomware families show that the proposed DeepWare is effective at detecting different classes of ransomware with the 98.6% recall score, which is 84.41%, 60.93%, and 21% improvement over RATAFIA , OC-SVM , and EGB models respectively. DeepWare achieves an average MCC score of 96.8% and nearly zero false-positive rates by using just a 100 ms snapshot of HPC data. This timeliness of DeepWare is critical on the ground that organizations and individuals have the opportunity to take countermeasures in the first stage of the attack. Besides, the experiment conducted on unseen ransomware families such as CoronaVirus, Ryuk, and Dharma demonstrates that DeepWare has excellent potential to be a useful tool for zero-day attack detection.

Who are we and who are they? Historical transformations of violence in the human-animal relationship represented in artistic expressions

This study investigates the course of the transformations of violence present in the human-animal relationship in multiple periods of time, using artistic expressions to contribute to this theme. The study uses a multidisciplinary approach from the fields of Arts, History, and Philosophy seeking contributions to the literature on marketing and consumer behavior. Visual critical analysis is the methodology used to analyze six works of art from different historical periods and to understand the human-animal relationship over time. Findings suggest that forms of violence are present in the transforming human-animal relationship. The research challenges the marketing domain of the discussion about this relationship, limited to positive experiences with companion animals;it brings interpretations of the ways of violence in the human- animal relationship over time to understand the meanings and practices of the present;adds elements aimed at discussions and reflections necessary for researchers and marketing professionals, on the human-animal relationship and violence.Alternate :Este estudo investiga o percurso das transformações da violência presente na relação homem-animal, em múltiplos períodos do tempo, recorrendo a expressões artísticas, de forma a trazer contribuições para esta temática. O estudo utiliza uma abordagem multidisciplinar dos campos das Artes, História e Filosofia buscando contribuições à literatura de marketing e comportamento do consumidor. A análise crítica visual é a metodologia utilizada na análise de seis obras de artes de diferentes períodos históricos e compreensão da relação homem-animal no tempo. Os achados sugerem formas de violência que estão presentes nessa relação e se transformam. A pesquisa desafia o domínio da discussão sobre a relação homem-animal no campo do marketing, circunscrita a experiências positivas com animais de companhia;traz interpretações dos caminhos da violência na relação homem-animal ao longo do tempo para melhor compreender significados e práticas do presente;adiciona elementos visando discussões e reflexões, necessárias a pesquisadores e profissionais de marketing, sobre a relação homem-animal e violência.Alternate :Este estudio investiga el curso de las transformaciones de la violencia presente en la relación humano-animal, en múltiples períodos del tiempo, utilizando expresiones artísticas, con el fin de traer contribuciones a esta temática. El estudio utiliza un enfoque multidisciplinario de los campos de las Artes, la Historia y la Filosofía en busca de contribuciones a la literatura sobre marketing y comportamiento del consumidor. El análisis crítico visual es la metodología utilizada para analizar seis obras de arte de diferentes períodos históricos y comprender la relación humano-animal a lo largo del tiempo. Los hallazgos sugieren formas de violencia que están presentes en esta relación y se transforman. La investigación desafía el dominio de la discusión sobre la relación humano-animal en el campo del marketing, limitada a experiencias positivas con animales de compañía;trae interpretaciones de las formas de violencia en la relación humano-animal a lo largo del tiempo para comprender mejor los significados y prácticas del presente;añade elementos destinados a discusiones y reflexiones, necesarias para investigadores y profesionales del marketing, sobre la relación humano-animal y la violencia.

Retail Marketing Communication and the Consumer Behaviour of Selected Generations

Cábyová reviews Retail Marketing Communication and the Consumer Behaviour of Selected Generations by A. Kusá, T. Fasiang and D. Kollárová.

Who's Next: Rising Star Prediction via Diffusion of User Interest in Social Networks

Finding items with potential to increase sales is of great importance in online market. In this paper, we propose to study this novel and practical problem: rising star prediction. We call these potential items Rising Star , which implies their ability to rise from low-turnover items to best-sellers in the future. Rising stars can be used to help with unfair recommendation in e-commerce platform, balance supply and demand to benefit the retailers and allocate marketing resources rationally. Although the study of rising star can bring great benefits, it also poses challenges to us. The sales trend of rising star fluctuates sharply in the short-term and exhibits more contingency caused by some external events (e.g., COVID-19 caused increasing purchase of the face mask) than other items, which cannot be solved by existing sales prediction methods. To address above challenges, in this paper, we observe that the presence of rising stars is closely correlated with the early diffusion of user interest in social networks, which is validated in the case of Taocode (an intermediary that diffuses user interest in Taobao). Thus, we propose a novel framework, RiseNet, to incorporate the user interest diffusion process with the item dynamic features to effectively predict rising stars. Specifically, we adopt a coupled mechanism to capture the dynamic interplay between items and user interest, and a special designed GNN based framework to quantify user interest. Our experimental results on large-scale real-world datasets provided by Taobao demonstrate the effectiveness of our proposed framework.

Enabling Homecare With Robotic Technologies [From the Guest Editors]

The home health-care industry is under growing pressure to deliver services more effectively to meet the increasing demand from care recipients, particularly the elderly population. It is estimated that U.S. home health-care expenditures will rise from US[Formula Omitted]108.8 billion in 2019 to US$186.8 billion in 2027 [1] . A simultaneous ongoing shortage of physicians, registered nurses, certified nursing assistants, and social workers has created a major service delivery gap in the home health-care industry, especially in rural areas where timely access to quality health-care services is very limited [2] . The recent COVID-19 pandemic exacerbated this problem as it isolated many care recipients from their caregivers or friends.

Global Market Research for Value Proposition Innovation Amid Pandemics

Pandemic situations impact the ability of the startups to identify the product features that have match with market needs: the activity that requires direct interaction with the customers at the same physical space. Online tools can overcome this limitation, but early-stage startups have too limited resources and lack of access to the potential customers, which make their online interactions quite limited. The divergent creativity is required to identify the requirement elicitation methods and tools that could help startups to identify product/market fit with limited same physical space interaction with customers. The open innovation involving academia, experts, and researchers could help startups to get access to the market needs. This chapter reports one such consulting experience of the author with the Madrid (Spain)-based startup which successfully identified its market in pandemic time through global market research driven by secondary studies, primary research involving potential clients (or users) through online means, and limited interactions at the same physical space. Daily brainstorming with a team of researchers, experts, and professors helped to generate divergent ideas about identifying markets amid the pandemic and testing them in real context that proved to be successful for the startup. Overall impact is the ability of startup to innovate its business model for foreign markets. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Introduction

This chapter provides background information on innovating value propositions that are a component of business model innovations that underlie market research for market expansion in both domestic and international markets. The theoretical backdrop is then provided in order to highlight the gaps that this work aims to fill. The knowledge presented in this book is then positioned in relation to previously established practices for implementing business model improvements in both domestic and international markets, which is challenged by startups in reality. This book's key part on business model developments during the epidemic imparts important lessons for the startup community that is battling to compete in the pandemic and could also be valuable in the "new normal.” © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Consumers under pandemic anxiety: Suppressors, intensifiers, and resilients

COVID‐19 turned the lives of all people across the world upside down. Everyone faced the threat of catching the virus and denial of access to the physical marketplace. For many, it also brought the threat of partial or full unemployment. This trinity of upheaval produced heightened anxiety. The purpose of this article is to understand how consumers coped with anxiety during the pandemic and lockdown periods. We hypothesized that consumers coped with such anxiety by engaging in diverse creative and productive activities, which served as anxiety suppressors. In addition, we hypothesized that one's enduring mind positivity provided resilience and helped consumers mitigate their anxiety. In survey data from a random sample of 550 consumers in the United States, we found support for these hypotheses. Consumers who engaged in voluntary productive activities suffered less anxiety. And consumers with higher resilience levels also felt lower levels of anxiety. In addition, we found that enjoyment of shopping intensified the experience of COVID‐19‐induced anxiety. The research framework linking this specific set of antecedents to COVID‐induced anxiety and its affirmation in this study are new to the literature and therefore offer a notable contribution to it. These findings show two pathways to marketers: Organize and promote voluntary productive activities and offer means for consumers to cultivate personal resilience, on for‐profit and not‐for‐profit platforms. Also, we suggest a future consumer research agenda for when fate again brings us face‐to‐face with similar or even lesser catastrophes, which, according to scientific forecasters, it sadly but surely will.

Market Survey On Consumption Pattern Of Street Food Products In Prayagraj District

There is a dearth of knowledge regarding the consumption habits of street foods, despite the fact that individuals in low- and middle-income nations rely heavily on SF for their diet. An online survey employing a structured questionnaire was used to perform a cross-sectional study on 200 street food consumers in the Prayagraj/Allahabad District. Customers were approached and requested to participate who went to the randomly sampled Street Foods vendors and stores. The majority of consumers were male, between the ages of, and had at least a 10+2 and a Bachelor's degree. The primary findings showed that 91.5% of these consumers virtually always ate street food. In Prayagraj/Allahabad District, the most frequently consumed items were various types of street food products. chaat, bun, samosa, kachauri/khasta, fritters, south and north Indian chow mein, non-vegetarian, eggs, and dried goods. Consumers answered that they would prefer to buy healthier street foods (91.5%) if they were accessible. In the Prayagraj/Allahabad District, there is a sizable market for consumers of street food. Although street food is the majority of what is eaten, if healthier options are offered, people would be eager to buy them. Copyright © 2023 Wolters Kluwer Medknow Publications. All rights reserved.

Guest editorial: Sustainable business resilience and development in the pandemic economy: insights from organizational and consumer research

Businesses can survive or flourish in this unstable and fragile environment only if they get fresh insights about how the new marketplaces function and how to successfully operate in them (Öberseder et al., 2013). [...]for all organisations hoping to endure and grow in the post-pandemic climate, organisational resilience, based on market knowledge, is a desired, if not an essential, feature. [...]Soultana Anna Toumpalidou and Kleopatra Konstantoulaki, in their paper, tap on the new form of higher education provision in the pandemic economy;more specifically, the authors investigate the effect of attitudes towards distance learning as a drive of university students' decision-making. To this end, they study 1,550 university students in Greece and reveal three equally sized clusters, namely, technology mature, technology conservatives and sceptics of e-learning, pertaining to their attitudes towards online services provision in the higher education sector. [...]Kavita Sharma and Emmanuel Elioth Lulandala in their comprehensive research explore the impact of Covid-19 on the consumption of Over the Top (OTT) media services in India. [...]Miftachul Huda in his qualitative study examines the initiative of a low-price hotel in Malaysia to restore the financial sustainability through empowering the digital marketplace strategy in the tourism resilience sector during the Covid-19 pandemic.

Global Market Research for Value Proposition Innovation Amid Pandemics

Pandemic situations impact the ability of the startups to identify the product features that have match with market needs: the activity that requires direct interaction with the customers at the same physical space. Online tools can overcome this limitation, but early-stage startups have too limited resources and lack of access to the potential customers, which make their online interactions quite limited. The divergent creativity is required to identify the requirement elicitation methods and tools that could help startups to identify product/market fit with limited same physical space interaction with customers. The open innovation involving academia, experts, and researchers could help startups to get access to the market needs. This chapter reports one such consulting experience of the author with the Madrid (Spain)-based startup which successfully identified its market in pandemic time through global market research driven by secondary studies, primary research involving potential clients (or users) through online means, and limited interactions at the same physical space. Daily brainstorming with a team of researchers, experts, and professors helped to generate divergent ideas about identifying markets amid the pandemic and testing them in real context that proved to be successful for the startup. Overall impact is the ability of startup to innovate its business model for foreign markets. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Introduction

This chapter provides background information on innovating value propositions that are a component of business model innovations that underlie market research for market expansion in both domestic and international markets. The theoretical backdrop is then provided in order to highlight the gaps that this work aims to fill. The knowledge presented in this book is then positioned in relation to previously established practices for implementing business model improvements in both domestic and international markets, which is challenged by startups in reality. This book's key part on business model developments during the epidemic imparts important lessons for the startup community that is battling to compete in the pandemic and could also be valuable in the "new normal.” © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Young Adult's Consumption Patterns and Attitude towards Minimalist Lifestyle during COVID-19 Pandemic- An Exploratory Study

Purpose The COVID-19 pandemic disrupted the consumption patterns of people the world over. The patterns and trends of consumption that drive markets were no longer relevant during the pandemic. Newer factors drove the consumption decisions and consumers have changed their patterns. COVID pandemic enforced citizens globally to adopt minimalism. This research is aimed at qualitatively understanding the consumer experiences during the lockdown period and their future orientation towards a minimalist lifestyle. Method Participants were young adults of 18 to 25 years of age from India. A constructivist paradigm was adopted to understand the subjective meaning of their choices. Data was collected through Focused group discussions and content analysis was used to arrive at the themes. Findings Data revealed that priority was given to buying essential items during times of crisis. Stockpiling, conscious buying and simple living were the cornerstones of the consumption patterns. Practical implications Findings have implications for sustainable consumption practices with a minimalist approach. Understanding the future orientation of consumers towards adopting a minimalist lifestyle could help market researchers better understand sustainable consumption patterns, thereby helping them in tailoring their product marketing. The far-reaching implications of the results focus on green consumption values and ecological responsibility. Value This paper seeks to explore attitudes and beliefs on sustainable consumption in a young adult population during the Covid-19 outbreak and has implications for sustainable consumption practices using a minimalistic approach in the future. © 2022 RESTORATIVE JUSTICE FOR ALL.