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Consumer Behavior Research

Exploring the Depths of Consumer Insights for Strategic Business Growth

In an era where understanding consumer behavior is more than a competitive edge, it’s a survival imperative, NielsenIQ (NIQ) and GfK emerge as pivotal allies. This expertise is essential for businesses in B2C commerce, retail, and beyond, aiming to navigate the complex consumer landscape for informed, strategic decision-making.

Definition and Importance of Consumer Behavior Research

Consumer behavior research is the study of how individuals make decisions to spend their resources on consumption-related items. It involves understanding the what, why, when, and how of consumer purchases. This field is crucial for businesses as it sheds light on consumer preferences, buying patterns, and decision-making processes. By understanding these aspects, companies can tailor their products and marketing strategies effectively, ensuring alignment with consumer needs and market trends, ultimately leading to increased customer satisfaction and loyalty.

Overview of the Impact of Consumer Behavior Research on Marketing Strategies

The insights from consumer behavior research are instrumental in shaping targeted marketing strategies. By understanding consumer motivations and behaviors, businesses can create more relevant and engaging marketing messages, leading to improved customer engagement and retention. This research helps in segmenting the market, identifying potential customers, and understanding the factors that drive consumer decisions. It also aids in predicting future trends, enabling companies to stay ahead of the curve. Effective use of consumer behavior research can lead to the development of products and services that meet the evolving needs of consumers, thereby enhancing brand loyalty and market share.

Consumer and shopper insights

Understand consumer and shopper behavior, demographics, and loyalty with modern, representative consumer panels and customer survey capabilities.

Understanding Consumer Behavior

These diverse influences combine to form unique consumer profiles, which businesses must understand to effectively target their marketing efforts..

Factors Influencing Consumer Behavior

Consumer behavior is influenced by a complex interplay of psychological, social, cultural, and personal factors. Psychological factors include perceptions, attitudes, and motivation, which guide consumers’ emotional and cognitive responses. Social factors encompass family, friends, and societal norms that shape buying habits through peer influence and social trends. Cultural factors involve the broader societal beliefs, values, and customs that dictate consumer behavior in a particular region. Personal factors such as age, occupation, lifestyle, and economic status also significantly impact consumer choices. These diverse influences combine to form unique consumer profiles, which businesses must understand to effectively target their marketing efforts.

The Role of Consumer Behavior in Decision Making

Consumer behavior plays a critical role in the decision-making process. It involves understanding how consumers decide upon their needs and wants, choose among products and brands, and determine their purchase methods. This knowledge is vital for businesses to design and position their offerings in a way that resonates with the target audience. Understanding consumer behavior helps in predicting how consumers will respond to marketing messages and product features, enabling businesses to tailor their strategies to meet consumer needs effectively. It also assists in identifying opportunities for new product development and market expansion.

Consumer Behavior Theories and Models

Consumer behavior theories and models provide frameworks for understanding and predicting consumer actions. The Stimulus-Response Model, for instance, illustrates how marketing stimuli and environmental factors influence consumer responses. Maslow’s Hierarchy of Needs explains consumer motivation in terms of fulfilling basic to complex needs. The Theory of Reasoned Action and the Theory of Planned Behavior focus on the relationship between attitudes, intentions, and behaviors. The Consumer Decision Model outlines the cognitive process involving need recognition, information search, evaluation of alternatives, purchase decision, and post-purchase behavior. These models help businesses in developing strategies that align with consumer psychology and behavioral patterns. They also assist in segmenting the market and targeting consumers with personalized marketing approaches, enhancing the effectiveness of marketing campaigns and product offerings.

Research Methods in Consumer Behavior Research

Customer analytics is vital for businesses across various sectors, including FMCG, sales, and e-commerce. It enables companies to create personalized experiences, improve customer engagement, and boost retention, ultimately leading to increased revenue. By understanding consumer behavior through data analysis, businesses can make informed decisions that resonate with their target audience.

Quantitative Research Methods

Quantitative research methods in consumer behavior research involve structured techniques like surveys and questionnaires to collect numerical data. These methods are useful for gauging consumer attitudes, preferences, and behaviors across larger populations. Statistical analysis of this data helps in identifying trends, testing hypotheses, and making generalizations about consumer behavior. Quantitative research is valuable for businesses as it provides measurable and comparable insights that can guide strategic decision-making. It helps in understanding the magnitude of consumer responses to various marketing stimuli and in assessing the potential market size for new products or services.

Qualitative Research Methods

Qualitative research methods in consumer behavior focus on understanding the deeper motivations, thoughts, and feelings of consumers. Techniques like in-depth interviews, focus groups, and observational studies provide rich, detailed insights that are not typically captured through quantitative methods. This approach is crucial for exploring the underlying reasons behind consumer choices, preferences, and attitudes. Qualitative research helps businesses in gaining a deeper understanding of consumer experiences, emotions, and perceptions, which can be invaluable in developing more effective marketing strategies, product designs, and customer service approaches. It allows companies to explore new ideas and concepts with consumers, gaining insights that can lead to innovation and differentiation in the market.

Experimental Research in Consumer Behavior

Experimental research in consumer behavior involves manipulating one or more variables to observe the effect on another variable, typically consumer behavior or attitudes. This method is used to establish cause-and-effect relationships, providing insights into how changes in product features, pricing, or marketing strategies might influence consumer behavior. Controlled experiments, often conducted in laboratory settings or as field experiments, allow researchers to isolate the effects of specific variables. This type of research is particularly valuable for testing new products, pricing strategies, and marketing messages before full-scale implementation. It helps businesses in making informed decisions based on empirical evidence, reducing the risks associated with new initiatives.

Factors Affecting Consumer Behavior

Psychological factors.

Psychological factors play a significant role in shaping consumer behavior. These include individual motivations, perceptions, attitudes, and beliefs. Motivation drives consumers to fulfill their needs and desires, influencing their buying decisions. Perception, how consumers interpret information, can significantly impact their choices, as it shapes their understanding of products and brands. Attitudes and beliefs, formed through experiences and social influences, guide consumer preferences and loyalty. Understanding these psychological factors is crucial for businesses as they influence how consumers view and interact with products and services. By aligning marketing strategies with consumer psychology, businesses can more effectively influence purchasing decisions and build stronger customer relationships.

Social Factors

Social factors significantly influence consumer behavior, encompassing the impact of society, family, and peer groups. Family members and friends can influence buying decisions through recommendations or shared experiences. Social groups, including social networks and communities, also play a role in shaping consumer preferences and behaviors. The influence of social media has become particularly significant, as it not only connects consumers but also serves as a platform for sharing opinions and experiences about products and services. Understanding these social dynamics is important for businesses as they can leverage social influences through targeted marketing strategies, influencer partnerships, and social media campaigns. Recognizing the power of social factors can help businesses in building brand awareness and loyalty among consumer groups.

Cultural Factors

Cultural factors are deeply ingrained elements that influence consumer behavior, including values, beliefs, customs, and traditions. These factors vary across different regions and societies, affecting how consumers perceive and interact with products and services. Cultural influences can determine consumer preferences, buying habits, and brand perceptions. For instance, color symbolism, dietary preferences, and language can all vary significantly between cultures, impacting marketing strategies and product development. Businesses must understand and respect these cultural nuances to effectively cater to diverse consumer markets. Adapting products and marketing messages to align with cultural values and norms can significantly enhance a brand’s appeal and acceptance in different markets.

Personal Factors

Personal factors, including age, gender, occupation, lifestyle, and economic status, also significantly influence consumer behavior. These factors determine individual needs, preferences, and purchasing power. For example, younger consumers may prioritize trendy and innovative products, while older consumers might value functionality and durability. Lifestyle choices, such as health consciousness or environmental awareness, can also drive consumer preferences and choices. Economic factors, such as income and economic conditions, influence consumers’ ability to purchase and their sensitivity to price changes. Understanding these personal factors is crucial for businesses to segment their market effectively and tailor their products and marketing strategies to meet the specific needs of different consumer groups.

Consumer Purchase Decision Making

Stages of the consumer purchase decision-making process.

The consumer purchase decision-making process typically involves several key stages: problem recognition, information search, evaluation of alternatives, purchase decision, and post-purchase behavior.

In the problem recognition stage, consumers identify a need or desire.

During the information search, they seek out information about products or services that can fulfill their need. In the evaluation stage, consumers compare different options based on attributes such as price, quality, and brand reputation.

The purchase decision involves choosing a product and making the purchase. Finally, in the post-purchase stage, consumers evaluate their satisfaction with the purchase, which can influence future buying decisions and brand loyalty.

Understanding these stages is essential for businesses to effectively influence consumers at each step, from raising awareness to ensuring post-purchase satisfaction.

Influences on Consumer Purchase Decisions

Consumer purchase decisions are influenced by a multitude of factors, including product attributes, brand reputation, marketing messages, social influences, and personal preferences. Product features such as quality, price, and usability are key determinants of consumer choices. Brand reputation, built over time through consistent quality and marketing efforts, also significantly impacts purchase decisions. Marketing messages and advertising play a crucial role in shaping consumer perceptions and driving demand. Social influences, including recommendations from family and friends, as well as online reviews and influencer endorsements, can sway consumer decisions. Personal factors such as individual needs, preferences, and financial constraints also play a critical role. Businesses must consider these diverse influences when developing products and crafting marketing strategies to effectively appeal to their target audience.

Impulse Buying Behavior

Impulse buying behavior refers to unplanned purchases made by consumers, often driven by emotional factors rather than rational decision-making. This type of behavior is typically triggered by external stimuli such as attractive product displays, promotional offers, or persuasive sales tactics. Emotional responses, such as excitement or the desire for instant gratification, also play a significant role in impulse buying. Retailers often leverage this behavior by strategically placing impulse items near checkout areas or using limited-time offers to create a sense of urgency. Understanding the triggers of impulse buying can help businesses in designing marketing strategies and store layouts that encourage such purchases, potentially increasing sales and customer engagement.

Online Shopping and Consumer Behavior

Impact of online shopping on consumer behavior.

The rise of online shopping has significantly impacted consumer behavior, offering convenience, a wider selection of products, and often competitive pricing. Online shopping has changed the way consumers research products, compare prices, and make purchasing decisions. The ease of access to a vast array of products and the ability to shop at any time have increased the frequency and diversity of purchases. Online reviews and ratings have also become important factors in the decision-making process, as consumers increasingly rely on the opinions of others. Additionally, the personalized shopping experiences offered by many online retailers, through targeted recommendations and tailored marketing messages, have further influenced consumer buying habits. Understanding these shifts in consumer behavior is crucial for businesses to adapt their strategies for the digital marketplace, ensuring they meet the evolving needs and expectations of online shoppers.

Factors Influencing Online Buying Behavior

Several factors influence online buying behavior, including website usability, product variety, pricing, customer reviews, and the overall shopping experience. A user-friendly website with easy navigation and a seamless checkout process is crucial for attracting and retaining online shoppers. A diverse product range and competitive pricing are also key factors in attracting consumers. Customer reviews and ratings significantly impact purchase decisions, as they provide social proof and reduce perceived risk. The overall shopping experience, including customer service, delivery options, and return policies, also plays a vital role in influencing online buying behavior. Security and privacy concerns are additional considerations, as consumers are increasingly aware of data protection and online fraud. Businesses must address these factors to create a compelling online shopping experience that meets consumer expectations and drives online sales.

Comparison of Online and Offline Consumer Behavior

Online and offline consumer behaviors exhibit distinct differences, influenced by the unique aspects of each shopping environment. Online shopping offers convenience, a broader selection, and often more competitive pricing, leading to different purchasing patterns compared to offline shopping. Consumers tend to spend more time researching and comparing products online, while offline shopping is often driven by immediate needs and sensory experiences. The tactile experience and instant gratification of offline shopping are not replicable online, but the online environment offers personalized recommendations and a wealth of product information. Offline shopping also provides opportunities for personal interaction and immediate problem resolution, which can enhance customer satisfaction. Understanding these differences is crucial for businesses to tailor their strategies for each channel, ensuring a cohesive and complementary shopping experience that meets the needs and preferences of consumers in both online and offline environments.

Consumer Satisfaction and Loyalty

Importance of customer satisfaction in consumer behavior research.

Customer satisfaction is a critical component of consumer behavior research, as it directly impacts repeat purchases and brand loyalty. Satisfied customers are more likely to become repeat buyers, recommend the brand to others, and provide positive reviews. Customer satisfaction is influenced by various factors, including product quality, customer service, and overall shopping experience. Understanding and measuring customer satisfaction helps businesses identify areas for improvement, enhance customer experiences, and build long-term relationships with consumers. High levels of customer satisfaction lead to increased customer loyalty, which is essential for business growth and sustainability.

Factors Influencing Customer Satisfaction

Customer satisfaction is influenced by a range of factors, including product quality, price, service quality, brand image, and customer expectations. Product quality is a primary determinant of satisfaction, as consumers expect products to perform as advertised. Price also plays a role, as consumers evaluate the value they receive relative to the cost. Service quality, encompassing customer service interactions and the overall shopping experience, significantly impacts satisfaction levels. A positive, helpful, and efficient service experience can enhance satisfaction, while negative experiences can lead to dissatisfaction. Brand image, shaped by marketing communications and past experiences, influences consumer expectations and perceptions. Meeting or exceeding these expectations is key to achieving high levels of customer satisfaction. Additionally, personal factors such as individual needs, preferences, and past experiences also influence satisfaction. Businesses must consider these diverse factors to effectively meet consumer needs and enhance satisfaction levels.

Relationship Between Customer Satisfaction and Loyalty

The relationship between customer satisfaction and loyalty is strong and direct. Satisfied customers are more likely to develop a sense of loyalty to a brand, leading to repeat purchases and positive word-of-mouth recommendations. Loyalty is not just about repeat buying; it also involves an emotional connection and a preference for the brand over competitors. Satisfied customers are also more likely to be forgiving of minor issues and are less sensitive to price changes. Conversely, dissatisfied customers are more likely to switch to competitors and share negative experiences with others. Building customer loyalty requires consistently meeting or exceeding customer expectations, providing high-quality products and services, and maintaining positive customer relationships. Loyal customers are valuable assets to businesses, as they tend to have a higher lifetime value, lower acquisition costs, and can become brand advocates, promoting the brand through their networks.

Consumer Research and Marketing Strategies

Utilizing consumer research to develop effective marketing programs.

Consumer research is a vital tool for developing effective marketing programs. By understanding consumer needs, preferences, and behaviors, businesses can create targeted marketing strategies that resonate with their audience. Consumer research helps in identifying market segments, understanding consumer pain points, and uncovering opportunities for product development or enhancement. It also provides insights into the most effective channels and messages for reaching the target audience. Utilizing consumer research in marketing program development ensures that strategies are data-driven and customer-centric, increasing the likelihood of success. It enables businesses to tailor their marketing efforts to the specific needs and preferences of different consumer segments, improving engagement and response rates. Additionally, ongoing consumer research allows businesses to adapt their marketing strategies in response to changing consumer trends and market conditions, ensuring continued relevance and effectiveness.

Targeting Specific Consumer Segments Based on Research Findings

Targeting specific consumer segments based on research findings is a key strategy for effective marketing. Consumer research provides detailed insights into different consumer groups, including their demographics, psychographics, behaviors, and preferences. By analyzing this data, businesses can identify distinct segments within their target market, each with unique needs and characteristics. Targeting these segments with tailored marketing messages and product offerings increases the relevance and appeal of the brand to each group. For example, a segment characterized by health-conscious consumers would respond more positively to marketing messages emphasizing the health benefits of a product. Segment-specific targeting allows businesses to allocate marketing resources more efficiently, focusing on the most promising segments with the highest potential for conversion and loyalty. It also enhances the customer experience by providing consumers with products and marketing messages that are more closely aligned with their individual needs and preferences.

Adapting Marketing Strategies to Consumer Behavior Trends

Adapting marketing strategies to consumer behavior trends is essential for businesses to stay relevant and competitive. Consumer behavior is constantly evolving, influenced by factors such as technological advancements, cultural shifts, and economic changes. By staying attuned to these trends, businesses can anticipate changes in consumer needs and preferences, and adjust their marketing strategies accordingly. This may involve adopting new marketing channels, such as social media or influencer marketing, to reach consumers where they are most active. It could also mean developing new products or services that align with emerging consumer trends, such as sustainability or personalization. Adapting marketing strategies to consumer behavior trends requires a proactive approach, with ongoing research and analysis to identify emerging patterns. Businesses that successfully adapt to these trends can capture new market opportunities, enhance customer engagement, and maintain a competitive edge.

Case Studies in Consumer Behavior Research

Analysis of real-life examples and their implications.

Real-life case studies in consumer behavior research provide valuable insights into the practical application of theoretical concepts and the effectiveness of different marketing strategies. For example, a case study in the automotive industry might analyze how consumer preferences for eco-friendly vehicles have influenced car manufacturers’ product development and marketing strategies. In the retail sector, a case study could examine the impact of online shopping on brick-and-mortar stores and how these businesses have adapted to the digital era. These case studies offer concrete examples of how businesses have successfully navigated changes in consumer behavior, providing lessons and strategies that can be applied in other contexts. They also highlight the importance of consumer research in identifying market trends, understanding consumer needs, and developing effective marketing strategies. By analyzing real-life examples, businesses can gain a deeper understanding of consumer behavior, learn from the successes and challenges of others, and apply these insights to their own strategies.

Examination of Successful Marketing Campaigns Based on Consumer Behavior Research

Examining successful marketing campaigns that are based on consumer behavior research can provide valuable insights into effective marketing practices. These case studies demonstrate how a deep understanding of consumer needs, preferences, and behaviors can be leveraged to create impactful marketing campaigns. For instance, a campaign that effectively uses consumer data to personalize messages and offers can result in higher engagement and conversion rates. Another example might be a campaign that taps into current consumer trends, such as sustainability or wellness, to resonate with the target audience. Analyzing these successful campaigns can reveal key strategies and tactics that businesses can adopt, such as the use of specific channels, messaging techniques, or promotional offers. These case studies also highlight the importance of data-driven decision-making in marketing, showing how consumer research can inform and guide successful marketing initiatives.

Motivating Consumers and New Product Adoption

Strategies to motivate consumers to adopt new products.

Motivating consumers to adopt new products is a critical challenge for businesses. Effective strategies for encouraging new product adoption include leveraging social proof, offering free trials or samples, and creating educational content. Social proof, such as customer testimonials or influencer endorsements, can reduce perceived risk and increase consumer confidence in trying a new product. Free trials or samples allow consumers to experience the product firsthand, reducing barriers to adoption. Educational content, such as how-to guides or product demonstrations, can help consumers understand the value and benefits of the new product. Additionally, businesses can use targeted marketing campaigns to reach early adopters and innovators who are more likely to try new products and spread the word to others. Creating a sense of urgency or exclusivity around the new product, through limited-time offers or exclusive access, can also motivate consumers to adopt the product more quickly.

Innovations in Consumer Behavior Research for New Product Development

Innovations in consumer behavior research are playing a crucial role in new product development. Advanced analytics and data mining techniques allow businesses to analyze large datasets and uncover deep insights into consumer needs and preferences. Social listening tools enable companies to monitor social media and online conversations, gaining real-time insights into consumer opinions and trends. Virtual reality (VR) and augmented reality (AR) technologies are being used to test consumer reactions to new products in simulated environments, providing valuable feedback before market launch. Behavioral economics principles, such as understanding cognitive biases and decision-making processes, are also being applied to better predict consumer responses to new products. These innovations in consumer behavior research provide businesses with more accurate and comprehensive data, enabling them to develop products that are closely aligned with consumer needs and preferences, increasing the likelihood of market success.

Social Media and Consumer Behavior

Influence of social media on consumer behavior.

Social media has a profound influence on consumer behavior, shaping how consumers discover, research, and share information about products and services. Platforms like Facebook, Instagram, and Twitter serve as important channels for brand communication and engagement. Consumers use social media to seek recommendations, read reviews, and gather opinions from their networks, which significantly influences their purchasing decisions. Brands leverage social media for targeted advertising, influencer partnerships, and content marketing, creating opportunities for direct interaction and engagement with consumers. Social media also facilitates the spread of trends and viral content, quickly influencing consumer preferences and behaviors. The interactive and dynamic nature of social media means that consumer opinions and trends can rapidly change, requiring businesses to be agile and responsive in their social media strategies. Understanding the influence of social media on consumer behavior is essential for businesses to effectively engage with their audience and influence purchasing decisions.

Role of Social Media in Shaping Consumer Perceptions and Purchase Decisions

Recap of the importance of consumer behavior research.

Consumer behavior research is essential for businesses seeking to understand and effectively respond to the evolving needs and preferences of their target audience. It provides valuable insights into why consumers make certain choices, what influences their purchasing decisions, and how they interact with brands. This research is crucial for developing effective marketing strategies, creating products that meet consumer needs, and enhancing the overall customer experience. By staying informed about consumer behavior trends and applying these insights, businesses can improve customer engagement, increase brand loyalty, and drive growth. In today’s competitive marketplace, a deep understanding of consumer behavior is a key differentiator, enabling businesses to create more personalized, relevant, and impactful marketing initiatives.

Future Directions and Emerging Trends in Consumer Behavior Research

The future of consumer behavior research is marked by rapid advancements in technology and data analytics, leading to more sophisticated and nuanced understanding of consumer preferences and behaviors. Emerging trends include the use of artificial intelligence (AI) and machine learning to analyze consumer data, providing deeper and more predictive insights. The integration of biometric data, such as eye tracking and facial recognition, offers new ways to understand consumer responses to marketing stimuli. The growing importance of sustainability and ethical considerations is also influencing consumer behavior, leading to increased demand for eco-friendly and socially responsible products. Additionally, the rise of the experience economy is shifting focus from product features to customer experiences, requiring businesses to create more immersive and engaging customer interactions. Staying abreast of these trends and continuously innovating in consumer behavior research will be crucial for businesses to remain relevant and competitive in the changing market landscape.

How NIQ and GfK Can Help

In the complex world of consumer behavior, NIQ and GfK offer the expertise and tools necessary to navigate this landscape effectively. With comprehensive solutions like:

• NielsenIQ’s Homescan : Track, diagnose, and analyze consumer behavior from more than 250,000 households across 25 countries.
• Consumer analytics : Go deeper and create more clarity around shopper behavior with custom surveys and segmentation.
• Consumption moments : Reveal the true motivations behind customer consumption behavior and usage to guide product innovation and marketing strategy .
• gfknewron marke t : Create the right opportunities with gfknewron market
• gfknewron predict : Plan your future using the world’s most comprehensive sales tracking data for Tech & Durables.
• gfknewron Consumer : Understand your consumers’ behavior to redefine your success

By leveraging these tools, businesses can gain a competitive edge, adapting to market changes and consumer trends with agility and precision.

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The Black Box of Consumer Behaviour and Brand Value Perception: Case Study of the Slovak Republic

• First Online: 27 June 2020

Cite this chapter

• Jana Majerova 2 &
• Anna Krizanova 2  

Part of the book series: Contributions to Management Science ((MANAGEMENT SC.))

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Brand value, as subjectively perceived by customers, represents a source of valuable competitive advantage for an enterprise. However, there are numerous theoretical approaches to building and managing brand value, which bring about many problems in practice when it comes to its application. These are related to the variety of approaches to measuring brand value as well as to strategies of the building and management thereof. In order to avoid undesirable impacts associated with the implementation of an inappropriate branding pattern, marketing managers should primarily consider the nature of the socio-cultural profile of a country where the branding concept is to be applied and the country of origin of the concept itself. However, the awareness of the need to respect the socio-cultural profile of the country is not sufficient. It creates a space for identifying causalities and correlations among attributes of socio-cultural profiles and subjectively perceived sources of brand value. In accordance with the abovementioned factors, the aim of this chapter is to identify specifics in the perception of sources of brand value in the scope of the traditional quadratic typology of purchasing behaviour, based on a case study of the Slovak Republic. To fulfil this aim, the data obtained from our own survey has been statistically evaluated by means of factor analysis supported by the implementation of the KMO Test, Bartlett’s test of sphericity and the calculation of Cronbach’s Alpha. Thus, the specifics in brand value perception across traditional quadratic typology of purchasing behaviour can be identified, and a platform for future research on the relevant disparities in the cross-cultural investigation of brand value sources can be created.

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Aaker, D. A. (1996). Measuring brand equity across products and markets. California Management Review, 38 (3), 102. https://doi.org/10.2307/41165845 .

Article   Google Scholar  

Abbes, I., Hallem, Y., & Taga, N. (2020). Second-hand shopping and brand loyalty: The role of online collaborative redistribution platforms. Journal of Retailing and Consumer Services, 52 , UNSP 101885. https://doi.org/10.1016/j.jretconser.2019.101885

Adhikari, K., & Panda, R. K. (2019). The role of consumer-brand engagement towards driving brand loyalty: Mediating effect of relationship quality. Journal of Modelling in Management, 14 (4), 987–1005. https://doi.org/10.1108/JM2-03-2019-0067 .

Asberg, P., & Uggla, H. (2019). Introducing multi-dimensional brand architecture: Taking structure, market orientation and stakeholder alignment into account. Journal of Brand Management, 26 (5), 483–496. https://doi.org/10.1057/s41262-018-00147-1 .

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Berger, A. N., Cerqueiro, G., & Penas, M. F. (2015). Market size structure and small business lending: Are crisis times different from normal times? Review of Finance, 19 (5), 1965–1995. https://doi.org/10.2139/ssrn.2261932 .

Brakus, J. J., Schmitt, B. H., & Zarantonello, L. (2009). Brand experience: What is it? How is it measured? Does it affect loyalty? Journal of Marketing, 73 (3), 52–68. https://doi.org/10.1509/jmkg.73.3.52 .

Costa, M. C. (2019). Brand loyalty: What is it? How to measure it? Revista Ciencias Administrativas, 25 (3). https://doi.org/10.5020/2318-0722.2019.9614

de Lanauze, G. S., & Aurier, P. (2012). Impacts of perceived brand relationship orientation on attitudinal loyalty: An application to strong brands in the packaged goods sector. European Journal of Marketing, 46 (11–12), 1602–1627. https://doi.org/10.1108/03090561211260004 .

Fox, M. A. (2018). Drive-in theatres, technology, and cultural change. Economics, Management, and Financial Markets, 13 (2), 24–39. https://doi.org/10.22381/EMFM13220182 .

Gajanova, L., Nadanyiova, M., & Moravcikova, D. (2019). The use of demographic and psychographic segmentation to creating marketing strategy of brand loyalty. Scientific Annals of Economics and Business, 66 (1), 65–84. https://doi.org/10.2478/saeb-2019-0005 .

Gilal, F. G., Zhang, J., Gilal, R. G., & Gilal, N. G. (2020). Integrating intrinsic motivation into the relationship between product design and brand attachment: A cross-cultural investigation based on self-determination theory. European Journal of International Management, 14 (1), 1–27. https://doi.org/10.1504/EJIM.2020.103800 .

Hofstede, G. J., Jonker, C. M., Verwaart, T., & Yorke-Smith, N. (2019). The lemon car game across cultures: Evidence of relational rationality. Group Decision and Negotiation, 28 (5), 849–877. https://doi.org/10.1007/s10726-019-09630-9 .

Kataria, S., & Saini, V. (2019). The mediating impact of customer satisfaction in relation of brand equity and brand loyalty: An empirical synthesis and re-examination. South Asian Journal of Business Studies , early access online. https://doi.org/10.1108/SAJBS-03-2019-0046

Kennedy, R., & Hartnett, N. (2018). Marketing is scrambled: All evidence-based theorists are invited to breakfast. Australasian Marketing Journal, 26 (4), 303–306. https://doi.org/10.1016/j.ausmj.2018.10.003 .

Kicova, E., & Nadanyiova, M. (2017). Brand as a tool of company’s strategic marketing in practice. Lecture Notes in Management Science, 73 , 29–34. https://doi.org/10.26602/lnms.2017.73.29 .

Kim, D. H., & Song, D. (2019). Can brand experience shorten consumers’ psychological distance toward the brand? The effect of brand experience on consumers’ construal level. Journal of Brand Management, 26 (3), 255–267. https://doi.org/10.1057/s41262-018-0134-0 .

Kim, J., Lee, H., & Lee, J. (2020). Smartphone preferences and brand loyalty: A discrete choice model reflecting the reference point and peer effect. Journal of Retailing and Consumer Services, 52 , UNSP 101907. https://doi.org/10.1016/j.jretconser.2019.101907

Kliestikova, J., & Janoskova, K. (2017), Branding with understanding: How national profile of consumer influences brand value perception. Marketing and Management of Innovations, 3, 149-157. DOI: https://doi.org/10.21272/mmi.2017.3-14 .

Kliestikova, J., & Kovacova, M. (2017). Motion to innovation: Brand value sources have (not) changed over time. SHS Web of Conferences, 39 , UNSP 01010. https://doi.org/10.1051/shsconf/20173901010

Kliestikova, J., Kovacova, M., Krizanova, A., Durana, P., & Nica, E. (2019). Quo vadis brand loyalty? Comparative study of perceived brand value sources. Polish Journal of Management Studies, 19 (1), 190–203. https://doi.org/10.17512/pjms.2019.19.1.14 .

Liu, G. H., Zhang, X. Y., Huang, S., Zhang, L. Y., & Zhao, Y. (2020). Exploring consumers’ buying behavior in a large online promotion activity: The role of psychological distance and involvement. Journal of Theoretical and Applied Electronic Commerce Research, 15 (1), 66–80. https://doi.org/10.4067/S0718-18762020000100106 .

Lizbetinova, L., Starchon, P., Lorincova, S., Weberova, D., & Prusa, P. (2019). Application of cluster analysis in marketing communications in small and medium-sized enterprises: An empirical study in the Slovak Republic. Sustainability, 11 (8), 2302. https://doi.org/10.3390/su11082302 .

Park, C. W., MacInnis, D. J., Priester, J., Eisingerich, A. B., & Iacobucci, D. (2010). Brand attachment and brand attitude strength: Conceptual and empirical differentiation of two critical brand equity drivers. Journal of Marketing, 74 (6), 1–17. https://doi.org/10.1509/jmkg.74.6.1 .

Phua, P., Kennedy, R., Trinh, G., Page, B., & Hartnett, N. (2020), Examining older consumers’ loyalty towards older brands in grocery retailing. Journal of Retailing and Consumer Services, 52 , UNSP 101893. https://doi.org/10.1016/j.jretconser.2019.101893

Popescu Ljungholm, D. (2018). Employee–employer relationships in the gig economy: Harmonizing and consolidating labor regulations and safety nets. Contemporary Readings in Law and Social Justice, 10 (1), 144–150. https://doi.org/10.22381/CRLSJ10120188 .

Powell, S. M. (2019). Journal of Brand Management: Year end review 2019. Journal of Brand Management, 26 (6), 615–620. https://doi.org/10.1057/s41262-019-00172-8 .

Sroka, W., & Szanto, R. (2018). Corporate social responsibility and business ethics in controversial sectors: Analysis of research results. Journal of Entrepreneurship Management and Innovation, 14 (3), 111–126. https://doi.org/10.7341/20181435 .

Stonkute, E., Vveinhardt, J., & Sroka, W. (2018). Training the CSR sensitive mind-set: The integration of CSR into the training of business administration professionals. Sustainability, 10 (3), 754. https://doi.org/10.3390/su10030754 .

Svabova, L., Kramarova, K., & Durica, M. (2018). Prediction model of firm’s financial distress. Ekonomicko-manazerske spektrum, 12 (1), 16–29. https://doi.org/10.26552/ems.2018.1.16-29 .

Tanusondjaja, A., Greenacre, L., Banelis, M., Truong, O., & Andrews, T. (2015). International brands in emerging markets: The myths of segmentation. International Marketing Review, 32 (6), 783–796. https://doi.org/10.1108/IMR-08-2014-0286 .

Tuffnell, C., Kral, P., Durana, P., & Krulicky, T. (2019). Industry 4.0-based manufacturing systems: Smart production, sustainable supply chain networks, and real-time process monitoring. Journal of Self-Governance and Management Economics, 7 (2), 7–12. https://doi.org/10.22381/JSME7220191 .

Valaskova, K., Kliestikova, J., & Krizanova, A. (2018). Consumer perceptions of private label products: An empirical study. Journal of Competitiveness, 10 (3), 149–163. https://doi.org/10.7441/joc.2018.03.10 .

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Acknowledgements

The research leading to these results has received funding from the project entitled “Integrated model of management support for building and managing the brand value in the specific conditions of the Slovak Republic” in the framework of the Slovak Research and Development Agency programme under the grant agreement number APVV-15-0505.

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Majerova, J., Krizanova, A. (2020). The Black Box of Consumer Behaviour and Brand Value Perception: Case Study of the Slovak Republic. In: Sroka, W. (eds) Perspectives on Consumer Behaviour. Contributions to Management Science. Springer, Cham. https://doi.org/10.1007/978-3-030-47380-8_5

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Trends associated with consumer behaviour in the emerging Indian context have certain unique aspects. The huge market at the lower economic strata running to several millions of households for fast-moving consumer goods, the vast youth population that makes the market especially attractive to several multinational brands, the growth of luxury markets, the appearance of modern retail outlets in an environment that is still characterized by kirana shops and the enhanced rural patronage of goods and services spanning several categories are just some of the important factors that make the Indian context significantly different from the western markets. Case Studies in Consumer Behaviour adds value to the understanding of these context-specific challenges. This case collection on consumer behaviour has been selected based on the rich contextual and conceptual experience of the editor and the insights provided by Professor Paul Beamish of Ivey Business School, who has worked extensively on cases that relate to the Asian context. The cases provide an opportunity for students to blend theory with practice and understand how consumer behaviour concepts contribute to marketing strategies of brands. The Indian cases added to the collection provide an ethnic touch to the repertoire of issues pertinent to consumer behaviour. The digital era characterized by the social media and smart tablets require a basic understanding of the core concepts that influence consumers and this collection of cases provides the anchor on which several layers of thinking associated with consumer behaviour can be envisaged. The book is edited by Prof S.Ramesh Kumar, Professor of Marketing at IIM Bangalore in collaboration with Ivey Business School, Canada and published by Pearson Education .

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Impact of COVID‐19 on changing consumer behaviour: Lessons from an emerging economy

Debadyuti das.

1 Faculty of Management Studies, Delhi University, Delhi India

Ashutosh Sarkar

2 Indian Institute of Management Kozhikode, Kozhikode India

Arindam Debroy

3 Symbiosis Institute of Business Management Nagpur, Nagpur Maharashtra, India

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The present study investigates the impact of COVID‐19 on Consumers' changing way of life and buying behaviour based on their socio‐economic backgrounds. A questionnaire survey was carried out to understand the impact of COVID‐19 on consumers' affordability, lifestyle, and health awareness and how these effects influenced their buying behaviour. A total of 425 usable responses were analysed using the structural equation modelling considering Consumers' socio‐economic background as exogenous variables and Consumers' changing way of life and Adaptation in consumers’ buying behaviour as endogenous variables. The study reveals that COVID‐19 has affected the consumers in the unorganised sectors more than others and induced an increase in the demand for affordable substitutes for daily necessities. The demand for wellness and entertainment products is found to depend upon the occupation and family earning status of consumers which is jointly mediated by affordability and lifestyle changes. Further, the findings show that the demand for health and hygiene products depends on the current employment status and family earning status of consumers which is jointly mediated by affordability and awareness towards health and hygiene. The model developed in the present study allows the decision‐makers to identify which segments of the population with certain socio‐economic backgrounds could be targeted for wellness products and which ones could be targeted for health and hygiene products. In addition, the model provides rich insights to the managers as to what kind of product substitution would be viable in the market during the pandemic.

1. INTRODUCTION

COVID‐19 has disrupted humankind in a manner not seen in recent times, infecting 6.5 million people while leaving millions unemployed (Hensher,  2020 ). While the loss of life, occupation, and livelihood are well‐articulated impacts of COVID‐19, the loss of routine social and economic life over a prolonged period is having long‐lasting effects on people (Chriscaden,  2020 ). COVID‐19‐imposed ‘self‐isolation and social lockdown’ has increased mental stress and inflicted psychological and behavioural changes (Witteveen,  2020 ). Under constant fear of infection and restricted mobility, people are becoming more aware of health and changing their lifestyles and eating habits (Sánchez‐Sánchez et al.,  2020 ). Reported preliminary studies also suggest that the nature and extent of the impact of COVID‐19 is not similar across all citizens and depend on their condition of poverty, age, residential status, and other demographic variables (U n ited Nations, n.d.).

As a consequence of the economic, social, and psychological impact of COVID‐19, people have altered how and where they should spend their money (Rogers & Cosgrove,  2020 ). Kirk and Rifkin ( 2020 ) argued that consumers react, cope, and adapt to environmentally‐imposed constraints such as the COVID‐19 pandemic. During the pandemic, consumers have displayed a variety of unusual behaviours (Laato et al.,  2020 ; Pantano et al.,  2020 ) and forced them to spend more on essentials while cutting back discretionary spending. Consumers are also observed to have changed brands and products, substituted spends when stocked out, and become more sensitive towards health and hygiene. Market studies pertaining to the impact of COVID‐19 on consumers have also indicated increased spending on groceries, and health and hygiene products (Rogers & Cosgrove,  2020 ). The above changes have motivated researchers to explore how the consumers behaved during the pandemic and the reasons for such behaviour.

Some of the COVID‐19‐induced behaviours that were studied include consumption shifts (Kansiime et al.,  2021 ; Pakravan‐Charvadeh et al.,  2021 ), impulsive buying (Naeem,  2020 ), stockpiling, and panic buying (Billore & Anisimova,  2021 ; Keane & Neal,  2021 ; Naeem,  2020 ; Prentice et al.,  2021 ), product and brand substitution (Knowles et al.,  2020 ), and shifts in channel preferences (Mehrolia et al.,  2021 ; Pantano et al.,  2020 ). Researchers have attributed such behaviour to COVID‐19‐induced impacts on consumers' socio‐economic status, changing way of life, and influence on predisposed beliefs (Milaković, 2021 ), changes in the consumers' buying environment such as stockouts, supply and demand disruptions (Prentice et al., 2021 ), and external stimuli such as information and social media exposure. (Laato et al.,  2020 ; Naeem,  2020 ). It was also reported that a significant number of people have lost their jobs (Montenovo et al.,  2020 ) and family income dwindled as a consequence of COVID‐19 (Kansiime et al.,  2021 ). COVID‐19 has affected consumers' disposable income or affordability (Mahmud & Riley,  2021 ), lifestyle (Sánchez‐Sánchez et al.,  2020 ), and awareness (Li et al.,  2021 )—in short, their way of life—making them change their pre‐COVID spending habits. We, however, did not come across research studies that analysed the nature of changes in consumer behaviour due to changes in consumers' affordability, lifestyle changes, and awareness level. This suggests an opportunity to investigate the impact of COVID‐19 on Consumers' changing way of life and consequently on their buying behaviour based on the varying socio‐economic background of the population. Our research primarily focuses on studying consumption shifts and substitution behaviour and connects such changes to the changes in consumers' way of life. Such studies are very important for market researchers and firms in terms of segmentation of the market when a pandemic of this nature affects the entire population. Such studies would help firms in devising targeted marketing strategies during the ongoing pandemic and beyond. With this background, the present study seeks to address the following research questions:

• How has the socio‐economic background influenced Consumers' way of life including affordability, lifestyle changes, and awareness towards health and hygiene arising out of COVID‐19?
• To what extent has the Consumers' changing way of life arising out of COVID‐19 influenced Adaptation in their buying behaviour?
• How has the socio‐economic background led to the Adaptation in consumers' buying behaviour arising out of COVID‐19?

The methodology followed in this study involves investigating the influence of exogenous variables including occupation, current employment status, and family earning status on the intervening variables representing Consumers' changing way of life and finally on the dependent variables which reflect the Adaptation in consumers' buying behaviour. The study provides important insights to managers in terms of designing affordable substitute products of daily necessities for the vulnerable section of the society. In addition, it also provides insights to the policy planners in terms of developing appropriate intervention strategies for the affected consumers.

2. BACKGROUND LITERATURE

Adaptations in people's buying behaviour due to COVID‐19 are in line with the existing literature encompassing changes in consumers' needs and preferences induced by events that are environmental, social, biological, cognitive, and behavioural in nature (Mathur et al.,  2006 ). Such disruptions often force consumers to seek stability (Minton & Cabano,  2021 ) and, as a result, they display conservative and planned behaviour (Sarmento et al.,  2019 ). Such stability‐seeking behaviour induces austerity measures among consumers affected by economic recession or slowdown making consumers more price‐sensitive (Hampson & McGoldrick,  2013 ). While, in the past, pandemics such as influenza have affected economic activities significantly (Verikios et al.,  2016 ), some changes in consumers’ behaviour are not entirely due to the economic impacts. For example, during the outbreak of the Asian flu, consumers have displayed risk‐coping strategies that influenced their consumption of chicken meat (Yeung & Yee,  2012 ). Similarly, natural disasters such as Hurricane Katrina contributed to stress‐induced compulsive and impulsive buying behaviour among the affected residents of the US Gulf Coast (Sneath et al.,  2009 ). During natural disasters, consumers have been observed to have spent on luxury brands and premium categories displaying both cross‐category indulgence (Mark et al.,  2016 ) and impulsive buying behaviour (Kennett‐Hensel et al.,  2012 ).

Recently, adaptations in consumers' buying behaviour due to COVID‐19 have been studied under various themes (Kansiime et al.,  2021 ; Laato et al.,  2020 ; Pakravan‐Charvadeh et al.,  2021 ; Pantano et al.,  2020 ; Rayburn et al.,  2021 ). Gordon‐Wilson ( 2021 ) noted that external influences such as COVID‐19 affected ‘consumer's feelings for self‐control’ by changing their shopping behaviour, type of shopping and preference of store format, and consumption of unhealthy snacks and alcohol. Kim et al. ( 2021 ) highlighted the influence of protection motivation in explaining consumers' commitment to hygienic behaviour, prioritization of local restaurants, and conscious consumption. Guthrie et al. ( 2021 ) employed the react‐cope‐adapt framework to understand how consumer behaviour has evolved in terms of their usage of e‐commerce as a result of stressful events such as the COVID‐19. Eroglu et al. ( 2022 ) revealed that the crowding in retail stores significantly affects the shopping satisfaction of consumers during COVID‐19, which is mediated by customer‐employee rapport. They further argued that such relationships significantly differ based on consumers' perceptions about the appropriateness of retailer precautions, the severity of threats, and vulnerability to COVID‐19. Milaković ( 2021 ) demonstrated the moderating effect of consumer adaptability in explaining the influence of consumer vulnerability and consumer resilience on purchase satisfaction and finally on the repurchase intention of consumers. Yap et al. ( 2021 ) introduced a new dimension called technology‐mediated consumption as a coping strategy adopted by consumers in coping with pandemic‐induced stress and anxiety during the pandemic. They further discussed paradoxes explaining the nexus between the consumption of technology and consumer vulnerability. Nayal et al. ( 2021 ) identified various coping strategies for firms to take care of the employee and customer well‐being. Digitalization and innovation emerged as the two focus areas for adoption by firms for their survival post‐COVID‐19. In addition, the study further revealed that consumers have demonstrated a shift in their consumption behaviour during the present pandemic in favour of hygiene, sustainability, and local products.

The present study also deals with the shifts in consumption behaviour and product substitution behaviour among consumers that were observed during COVID‐19. However, our study is quite different from the existing studies in the sense that we attribute such shifts in consumption and product substitution behaviour to how COVID‐19 has impacted the Consumers' way of life. COVID‐19 pandemic has induced changes in consumers' demand—both in magnitude as well as in their preference (del Rio‐Chanona et al.,  2020 ). The pandemic has also resulted in increased consumption of certain products which were either consumed in lesser quantities or not consumed at all before the event (Kirk & Rifkin,  2020 ). Such effects have led to significant upward shifts in the market demand for these products. We refer to such shifts as ‘new demand’. Examples of ‘new demand’ include cleaning and personal hygiene products such as Lysol and hand sanitizers (Chaudhuri,  2020 ), health and wellness products such as vitamins, healthy foods, and other immunity boosters (Hess,  2020 ), packaged goods and beverages, household care products, fresh and organic foods, personal care products (Knowles et al.,  2020 ) and digital platforms (Debroy,  2020 ), which displayed a surge in demand during COVID‐19. Consumers have also displayed substitution behaviour during the pandemic (Knowles et al.,  2020 ) thereby changing significantly the consumption both by volume as well as product preference. Product substitution is also observed during this pandemic due to lifestyle changes while the change of preference is observed due to awareness of health. The literature on product substitution is characterized by several factors prompting substitution behaviour by consumers (Hamilton et al.,  2014 ). However, while studying new demand and product substitution behaviour under disruptive events, we observed that most of these studies are limited to the economic impacts of the events (Martin et al.,  2020 ) and hence, there is still scope for studying such behaviour considering the non‐economic impacts of the pandemic.

Disruption affects people's lives in a variety of ways derailing their normal ways of living. Earlier studies on disruptions dealt with disruption‐induced depression, lifestyle changes, changes in information, awareness, and education (Mathur et al.,  2006 ; Sneath et al.,  2009 ). During the present pandemic also, significant changes in lifestyle and health awareness (Arora & Grey,  2020 ) were observed. The fear of getting infected with COVID‐19 and the government‐imposed lockdowns have reduced mobility and physical activities (Sánchez‐Sánchez et al.,  2020 ); changed dietary and consumption behaviour (Kansiime et al.,  2021 ; Pakravan‐Charvadeh et al.,  2021 ), and sleep behaviour (Chopra et al.,  2020 ). COVID‐19 has also increased health concerns and awareness impacting consumption of health and wellness products in a significant manner (Baiano et al.,  2020 ; Hess,  2020 ). However, lifestyle changes, awareness towards health, and change in consumption behaviour arising out of COVID‐19 were not found to be uniform across people of diverse socio‐economic groups (Laato et al.,  2020 ). As COVID‐19 has affected the entire population in varying degrees based on their socio‐economic background, there exists a scope for research as to how different consumer groups have adapted their buying behaviour.

3. THEORETICAL MODEL AND DEVELOPMENT OF HYPOTHESES

In order to understand how COVID‐19 has impacted consumers’ way of life and consumer buying behaviour, we mainly draw from preliminary studies, market surveys, and published research articles on the impact of COVID‐19. This study mainly has three dimensions: (1) Consumers' socio‐economic background, (2) Consumers' changing way of life, and (3) Adaptation in consumers' buying behaviour as shown in Figure  1 , which serves as the theoretical model of the present work. Consumers' changing way of life has been captured through ‘Change in affordability’, ‘Lifestyle changes’ and ‘Awareness towards health and hygiene’ arising out of COVID‐19 while Adaptation in consumers' buying behaviour has been represented through ‘Creation of new demand for wellness and entertainment products’, ‘Creation of new demand for health and hygiene products’, ‘Substitution of daily necessities due to affordability’ and ‘Substitution of daily necessities due to awareness towards health’.

Theoretical model of the impact of COVID‐19 on consumer behaviour

3.1. Consumers' socio‐economic background and affordability

COVID‐19 has significantly influenced individual and household incomes and spending habits. However, such economic hardships varied based on their occupation, employment status, and socio‐demographic background (Witteveen,  2020 ). The adverse effects are estimated to be strongest for those occupations that are characterized by lower levels of skill, education, and income, have lesser possibilities of working remotely (Adams‐Prassl et al.,  2020 ), and require more face‐to‐face interpersonal contacts (Avdiu & Nayyar,  2020 ; Montenovo et al.,  2020 ). We have observed that some people have received lower than the regular salary in their current employment while a few others have lost their jobs during lockdowns which has adversely affected their capacity to sustain the household expenditure. Many studies have observed that family income, personal savings, and occupational status affected the ability of a household to continue their pre‐COVID spending (Kansiime et al.,  2021 ; Pakravan‐Charvadeh et al.,  2021 ; Piyapromdee & Spittal,  2020 ). In addition, the ability to support the household expenditure is found to depend upon the number of earning members, which further reflects the earning potential of a family (Addabbo,  2000 ). Hence, based on the above discussion, we postulate the following hypotheses:

Occupation significantly influences the affordability of consumers.

Current employment status significantly influences the affordability of consumers.

Family earning status significantly influences the affordability of consumers.

3.2. Consumers' socio‐economic background and lifestyle changes

COVID‐19 has brought a dramatic change in the lifestyle of people. However, the change is different for people belonging to different socio‐economic backgrounds. While occupations such as travel, restaurants, Micro, Small, and Medium Enterprises (MSME) have seen reduced business activities, there are people in other occupations, for whom work from home during the pandemic is like a much‐needed break from their monotonous schedule. Thus, the nature of occupation seems to have an impact on the work schedule and lifestyle changes of people. Many studies have noted that occupational social class and status are associated with the lifestyle of people (García‐Mayor et al.,  2021 ). Likewise, receiving a reduced salary or having lost their job during lockdown seems to have had a considerable influence on consumers' lifestyles in terms of daily routine, thought process, and social habits (Khubchandani et al.,  2020 ; PTI,  2020 ). On the other hand, the lifestyle of a family with multiple earning members may be significantly different from a family with a sole earning member (Pew Research,  2008 ). Thus, we advance the following hypotheses:

Occupation significantly influences the lifestyle changes of consumers.

Current employment status significantly influences the lifestyle changes of consumers.

Family earning status significantly influences the lifestyle changes of consumers.

3.3. Consumers' socio‐economic background and awareness towards health and hygiene

COVID‐19 has resulted in people becoming more conscious about their health and personal hygiene (Baiano et al.,  2020 ; Hess,  2020 ). Government advisories and campaigns for maintaining personal hygiene through regular hand washes and wearing masks have resulted in people becoming concerned about their hygiene like never before. However, as occupation varies with the level of education, so does the awareness towards health and hygiene (Teisl et al.,  1999 ). Similarly, awareness towards health and hygiene varies with employment status and family earning status (Prasad et al.,  2008 ). Based on this, we posit the following hypotheses:

Occupation significantly influences the awareness level of consumers towards their health and hygiene.

Current employment status significantly influences the awareness level of consumers towards their health and hygiene.

Family earning status significantly influences the awareness level of consumers towards their health and hygiene.

3.4. Affordability and consumers' buying behaviour

Due to reduced affordability, a large number of people are restricting their expenditure to mostly essentials and healthcare products while cutting down on non‐discretionary products (Martin et al.,  2020 ). This has led to a reduction in sales of many non‐essentials. The pandemic, however, has witnessed a significant rise in the demand for wellness and entertainment products delivered through digital platforms (Bakhtiani,  2021 ; Madnani et al.,  2020 ). Since such subscriptions by consumers are discretionary (Singh,  2020 ), we expect an influence of reduced affordability due to the pandemic on the creation of new demand. Equivalently, it could also be stated that a positive change in affordability would have a positive impact on the usage of such products (Bakhtiani,  2021 ; Madnani et al.,  2020 ). Earlier studies in economics and public health have noted that family income significantly influences demand for hygiene products and associated practices (Aunger et al.,  2016 ; Jacob et al.,  2014 ). In many cases, consumers with lower affordability also explored cheaper alternatives such as private labels and affordable brands (Mishra & Balsara,  2020 ). Therefore, based on the above arguments, we postulate the following hypotheses:

Creation of new demand for wellness and entertainment products is significantly associated with the change in affordability.

Creation of new demand for products relating to health and hygiene is significantly associated with the change in affordability.

The demand for affordable substitute products of daily necessities is significantly associated with the change in affordability.

3.5. Lifestyle changes and demand for wellness and entertainment products

Lifestyle changes due to COVID‐19 have made people more sensitive to fitness that caused a surge in demand for wellness products (Ojha,  2020 ). Many people are now preferring organic and herbal products and are subscribing to fitness classes and channels (Wernau & Gasparro,  2020 ). Furthermore, institutional lockdowns imposed by governments have forced people to stay at home and spend time with their families (Debroy,  2020 ). Additionally, with a regular source of entertainment such as restaurants and movie theatres remaining restricted, people have turned to online platforms for recreation. Even online yoga classes have experienced a spike in their viewership with the spread of this virus (Debroy,  2020 ). Thus, we propose the following hypothesis:

Creation of new demand for wellness and entertainment products is positively associated with Lifestyle changes.

3.6. Awareness towards health and hygiene and demand for health and hygiene products

Marketing experts have always emphasized the importance of increasing awareness among consumers to increase product demand (Baiano et al.,  2020 ; Hess,  2020 ). COVID‐19 has resulted in people becoming more conscious about their health and personal hygiene. As part of maintaining a proper and healthy lifestyle, regular hand washes and wearing masks are considered to be the defence mechanisms of protecting oneself from the virus. Common people have been spending more on buying healthcare products (Rakshit,  2020 ). Moreover, the current times have witnessed an incomparable urge in people to substitute unhealthy food items and daily necessities with healthy ones (Master,  2020 ; Renner et al.,  2020 ). Thus, the following hypotheses are advanced:

Creation of new demand for products relating to health and hygiene is positively associated with consumers' awareness towards health and hygiene.

The demand for healthy substitute products of daily necessities is positively associated with consumers' awareness towards health and hygiene.

3.7. Consumers' socio‐economic background and creation of new demand for wellness and entertainment products

During this pandemic, fitness and wellness products, and digital platforms such as Netflix have become very popular (Debroy,  2020 ). However, the nature of demand for wellness and entertainment products varied across people with different socio‐economic backgrounds. A person's occupation, employment status, and family income influence consumers' preference for wellness products (Suresh & Ravichandran,  2011 ) and also have a considerable impact on the creation of new demand for wellness and entertainment products (Madnani et al.,  2020 ). Therefore, we propose to investigate further the relationship between consumers with diverse socio‐economic backgrounds and the creation of new demand for wellness and entertainment products. Thus, we postulate the following hypotheses:

Occupation significantly influences the creation of new demand for wellness and entertainment products.

Current employment status significantly influences the creation of new demand for wellness and entertainment products.

Family earning status significantly influences the creation of new demand for wellness and entertainment products.

3.8. Consumers' socio‐economic background and creation of new demand for health and hygiene products

This pandemic has also seen an increased demand for health and hygiene products (Dsouza,  2020 ). People have been forced to spend on hand washes, sanitizers, and masks to protect against this rapidly spreading virus. As there are occupations that would put an individual and her/his family into different levels of vulnerabilities (Avdiu & Nayyar,  2020 ), we expect variations in the consumption of health and hygiene products based on their occupation (Riise et al.,  2003 ). Earlier research has established the relationship between family income and consumers' preference for healthy food (Galati et al.,  2019 ; Pakravan‐Charvadeh et al.,  2021 ). The reduced income and job losses would have a significant bearing on both mental stress as well as disposable income (Witteveen,  2020 ) which, in turn, influence the choice of consumers for health and hygiene products (Khubchandani et al.,  2020 ). Therefore, the creation of new demand for health and hygiene products seems to vary depending on the types of occupation, current employment status, and family earning status. Thus, we propose the following hypotheses:

Occupation significantly influences the creation of new demand for products relating to health and hygiene.

Current employment status significantly influences the creation of new demand for products relating to health and hygiene.

Family earning status significantly influences the creation of new demand for products relating to health and hygiene.

4. RESEARCH METHODOLOGY

4.1. design of survey instrument and its reliability.

The findings of Paul and Bhukya ( 2021 ) reveal that the impact of COVID‐19 on consumer behaviour is one of the important contemporary topics of research. However, we could not find any suitable questionnaire in the extant literature with specific reference to the hypothesized research model depicted in Figure  1 which could be directly utilized for data collection purposes. We came across several items in the literature for other kinds of disasters, which were found relevant for our study. In addition, we also observed through newspapers, electronic media, and social media the challenges faced by the consumers in respect of reduced salary, job losses, health issues, the surge in demand for products relating to health and hygiene, etc. arising out of COVID‐19. We took cognizance of all these aspects and framed an open‐ended questionnaire in the initial phase to develop an understanding of different types of challenges faced by the consumers and their impact on changing consumer behaviour. The open‐ended questionnaire was translated into Hindi, Malayalam, and Bengali with the help of three bilingual experts having expertise in Hindi, Malayalam, and Bengali languages respectively along with English. We administered this questionnaire to consumers with different linguistic and socio‐economic backgrounds. We identified five respondents from Government/Public Sector organisations, five from Multinational/Private sector firms, and five from MSMEs. In addition, we identified three independent businessmen and seven daily wage‐earners. All these respondents were requested to participate in the study after thoroughly explaining to them the purpose of undertaking this particular exercise. They agreed to take part in the study. However, the daily wage‐earners had to be given INR100/‐ each to motivate them to take part in the study. Amongst these respondents, some of them could understand Hindi well, some of them could understand Malayalam well while a few others could understand Bengali well. In the case of employees of Public sector and Private sector firms, the questionnaire was sent through email with the request to provide unambiguous responses within a week. In the case of the employees of MSMEs and independent businessmen, we took separate appointments through telephonic calls and requested that one of the authors would seek responses from them in person by maintaining the protocol of social distancing. One author from Delhi and another author from Kozhikode separately conducted this exercise in Delhi and Kozhikode respectively. Finally, in the case of daily wage‐earners, we directly talked to a few rickshaw‐pullers, a few street vendors, and a few masons and managed to secure their responses after incentivizing them. We asked the questions verbally to this category of respondents and they replied to the specific questions based on their experience. Thus, we had to record the conversations which were later transcribed.

Based on the responses received from the preliminary study, we summarized them under different sections and designed another open‐ended questionnaire. The purpose of designing the second‐round open‐ended questionnaire was to cross‐check the same with the experts and to ensure adequate and appropriate coverage of the items under different sections thereby taking care of the content validity of the questionnaire. For example, we identified several items reflecting the financial distress faced by the common people due to COVID‐19 and put them under ‘Affordability’. We requested the experts to exercise their judgment in terms of whether those items represent the essence of ‘Affordability’. Those experts were chosen who had considerable experience in selling essential items either through the offline or online channel. In addition, a few more experts were also selected who conducted research in consumer behaviour for a sufficient period. Accordingly, we selected experts from both academia and industry, which included one Professor of Marketing, two researchers doing research in consumer behaviour, one manager from an offline store selling essential items, and one executive from an online retailer. These experts were known to be thoroughly conversant with the impact of COVID‐19 on the consumers’ way of life and also their changing buying behaviour across consumers of varying socio‐economic backgrounds. The experts recommended the retention of most of the items and the removal of very few ones. Subsequently, we designed the close‐ended questionnaire based on the recommendation of the experts. The close‐ended questionnaire was divided into three sections. The first section contained questions relating to the socio‐demographic profile and earning status of the respondents. The second section carried questions about the factors influencing Consumers' changing way of life arising out of COVID‐19. Finally, the third section contained questions pertaining to the adaptations on consumers' buying behaviour due to COVID‐19. A five‐point Likert scale ranging from 1 = Not at all True to 5 = Absolutely True was used as a response format in the second and third sections. The questionnaire was shown to the same experts once again to elicit their opinion for evaluating its ease of understanding from the perspective of potential respondents. Based on the recommendation of experts, some questions were rephrased. This exercise helped us in ensuring the content validity of the questionnaire. Table  1 presents the first part of the questionnaire while Appendices  1 and 2 show the second and third parts of the questionnaire respectively.

Distribution of the respondents based on socio‐demographic background ( n  = 425)

Subsequently, the reliability of the questionnaire was tested by administering the survey on 30 respondents chosen carefully. Cronbach's alpha of the scale representing Consumers' changing way of life turned out to be 0.795 while the same for the scale showing Adaptation in consumers’ buying behaviour was found to be 0.895. Both the scales showed high corrected item‐to‐total correlations which indicated the presence of high internal consistency. Since the alpha value of both scales was well above the threshold level of 0.7, these scales were considered reliable (Hair et al.,  2009 ).

4.2. Target respondents and collection of data

The survey was administered amongst the respondents with diverse socio‐economic backgrounds in India. The questionnaire was circulated among people working in Government organisations, private sector organisations, MSMEs, and also among the daily wage‐earners. Given the diversity of the languages, we administered the survey in four languages including, English, Hindi, Malayalam, and Bengali. The above languages were chosen as a substantial percentage of the population of India speaks these languages. Efforts were also made to ensure that only one response is received from a single household. Because of the lockdown and the restrictions on mobility, we chose a variety of mediums to reach out to the potential respondents. We approached the potential respondents both through online and offline mode. In the case of online mode, the questionnaire was circulated on social media mainly through LinkedIn, WhatsApp, and Facebook urging people to respond to the questionnaire. These mediums were chosen for their immense popularity in India in terms of the number of users. They were further selected as the authors also have their active networks and groups in these platforms. In the case of offline mode, some respondents were sent questionnaires via email while others were administered through hard copies of the questionnaire in a language of their choice. Field‐workers were hired against remuneration who physically received the responses directly by visiting the respondents' doorsteps or by reaching out to them in public places like, malls, popular restaurants, and shops. Field‐workers were clearly instructed to explain the essence of the questionnaire to the respondents thoroughly before asking them to fill out the questionnaire. They were further advised not to fill out the questionnaire on behalf of the respondents. The questionnaire survey was administered over two months during August and September 2020. During this period, different parts of India were experiencing a variety of restrictions depending on the number and severity of COVID‐19 cases in different places. A total of 494 responses were received out of which 69 responses were found to be incomplete and incoherent. Thus, we were left with 425 usable responses for the final analysis.

4.3. Tests for potential bias in survey data

Non‐response bias was assessed by performing a t ‐test on the scores of early and late respondents based on the assumption that the opinions of late respondents are representative of the opinions of non‐respondents (Krause et al.,  2001 ). A total of 241 responses (56.7%) were received in the first month (i.e., August 2020) while 184 responses (43.3%) were received in the second month (i.e., September 2020). Respondents giving responses in the first month were considered as early respondents while those giving responses in the second month were treated as late respondents. T ‐tests were carried out between early respondents with 241 responses and late respondents with 184 responses on individual items. The results did not reveal any significant difference between the two groups for most of the items. This indicates that the data was relatively free from non‐response bias.

As this study relied on single respondents for doing the final analysis, the potential for common method bias to influence the results was also evaluated. We applied Harman's one‐factor test to evaluate common method bias separately on the scale representing Consumers’ changing way of life and the scale reflecting Adaptation in consumers’ buying behaviour . We carried out the above test separately for both the scales in IBM SPSS (version 25) by doing exploratory factor analysis without rotation. All 13 items representing Consumers’ changing way of life were allowed to be loaded into one single factor and again all 16 items reflecting Adaptation in consumers' buying behaviour were loaded into another single factor. It was found that the common factor representing Consumers' changing way of life explained only 25% of the total variance while the common factor capturing Adaptation in consumers' buying behaviour explained only 30.4% of the total variance. Since the total variance of a single factor was less than 50% in both the scales, the common method bias did not seem to be a concern for the present study (Podsakoff et al.,  2003 ).

5. DATA ANALYSIS AND INTERPRETATION

The 425 usable responses were also checked for missing values and inconsistency. An overview of the respondents' demographic profile, descriptive statistics, Confirmatory Factor Analysis (CFA), and the validation of the conceptual model using the Structured Equation Modelling (SEM) is presented in the following sub‐sections. We utilized IBM SPSS (version 25) for finding out the descriptive statistics of manifest variables and the demographic profile of the respondents. In addition, we also employed IBM SPSS AMOS (version 24) for carrying out CFA and SEM. Regarding descriptive statistics, we determined the minimum score, maximum score, mean and standard deviation of all items of both the scales and presented the same in Appendices  1 and 2 .

5.1. Demographic profile

The socio‐economic profile of 425 respondents revealed that most of them were of working age with a sizeable number of respondents (71.53%) turning out to be male. A majority of the respondents were employed (74.83%). However, a substantial portion of respondents lost their jobs or was receiving reduced salaries after the imposition of lockdown (35.76%). In terms of educational qualification, a major portion of the respondents (69.88%) were graduates with 56% of them having earned their degree in a professional course. The family earning status of the respondents showed that 29.88% were the sole earners in their family. The details of the demographic profile are provided in Table  1 .

5.2. Confirmatory factor analysis

The questionnaire developed through several rounds of an iterative process and validated by the experts allowed us to determine the underlying constructs. We observed that Consumers' changing way of life consists of three constructs while Adaptation in consumers' buying behaviour comprises four constructs. We applied CFA to assess how well the observed variables including 13 items relating to the Consumers' changing way of life and another 16 items representing Adaptation in consumers' buying behaviour arising out of COVID‐19 reflect unobserved or latent constructs in the hypothesized structure. In the CFA model, all seven constructs were allowed to be correlated with each other forming a composite measurement scale representing the Consumers' changing way of life and Adaptation in consumers' buying behaviour due to COVID‐19. The model was assessed by utilizing the maximum likelihood (ML) method. One of the prerequisites of the ML method is the normality of the endogenous variables (Kline,  2016 ). Thus, for ascertaining whether the data of the endogenous variables follow a normal distribution or not, we computed the kurtosis value. We observed that the values of almost all variables remained within the range of −7 to +7, which assuaged the concern regarding the non‐normality of the data (Mueller & Hancock,  2019 ).

All items were evaluated based on several criteria including items standardized regression weights, squared multiple correlations, and standardized residual covariance. In addition, the theoretical importance and practical significance of every item were taken into consideration while refining the model. This resulted in the removal of five variables of the Consumers' changing way of life and another three variables of Consumers' buying behaviour from the model thereby leaving eight items of Consumers' changing way of life and another 13 items of Consumers' buying behaviour in the final measurement model. This, however, did not significantly affect the content validity of the scale. Rather the model became further parsimonious. We found that one construct namely ‘lifestyle changes’ was left with only two items. However, it did not give rise to the problem of under‐identification of the measurement model. The findings of Das ( 2018 ) and Pullman et al. ( 2009 ) revealed several constructs which contain only two items. The presence of such constructs with two items did not create the problem of under‐identification of measurement models in the above research findings. Goodness of fit (GOF) measures of the final measurement model were as follows: χ 2  = 338.939, degrees of freedom ( df ) = 162, p  = .00, χ 2 / df  = 2.092, goodness fit index (GFI) = 0.931, Adjusted Goodness of Fit Index (AGFI) = 0.902, Comparative Fit Index (CFI) = 0.951, Tucker‐Lewis Index (TLI) = 0.937, Root Mean Square Error of Approximation (RMSEA) [90% CI] = 0.051 [0.043, 0.058], Standardized Root Mean Residual (SRMR) = 0.0512. For an adequate model fit, the fit indices of GFI, CFI, and TLI should be at least 0.9 while the same of RMSEA and SRMR should be less than 0.08 (Hair et al.,  2009 ). Thus, based on the fit indices, it could be inferred that the measurement model fits well with the data on all major indices. The details of the measurement results are shown in Table  2 , which includes the descriptive statistics of the constructs pertaining to the Consumers' changing way of life and Adaptation to consumers' buying behaviour . This includes the mean, standard deviation, and reliability value (Cronbach's alpha) of each construct and also the inter‐construct correlations.

Summary of the measurement results and inter‐construct correlations

The above table shows that Cronbach's alpha coefficients of six constructs out of seven have exceeded 0.7 thereby indicating sound reliability of these constructs (Hair et al.,  2009 ). Alpha coefficient of the remaining one construct reveals acceptable reliability value over 0.6 (Hair et al.,  2009 ). In addition, Table  2 also shows that almost all inter‐construct correlations are significant at 0.1% or 1% level. Only one inter‐construct correlation is significant at 10% level. These inter‐construct correlations help us in ascertaining the discriminant validity of all the constructs, which is discussed in the later part of this section.

This model was systematically evaluated for Construct Reliability (CR), convergent validity, and discriminant validity in order to validate the constructs of the Consumers' changing way of life and Adaptation to consumers' buying behaviour due to COVID‐19. In the present study, we have estimated the CR coefficient of all constructs which is shown in Table  3 . The estimate of CR lying between 0.6 to 0.7 is considered acceptable while the value above 0.7 suggests good reliability of a construct (Hair et al.,  2009 ). Thus, the six constructs may be considered to possess excellent reliability while the remaining one construct is characterized by an acceptable level of reliability.

Results of Reliability, Convergent and Discriminant validity of the consumers' changing way of life and consumers' buying behaviour

Abbreviations: AVE, average variance extracted; CR, construct reliability.

Convergent validity requires that the indicator variables of a given construct share a high proportion of variance in common. It was evaluated by following two different approaches. The first method involves the inspection of estimated factor loadings of items on the constructs in the final CFA model (Anderson & Gerbing,  1988 ). It was found that the standardized loadings of all items are greater than 0.5 and statistically significant ( p  < .001). The second method involves the assessment of convergent validity with the help of Average Variance Extracted (AVE). An AVE of 0.5 or more of a construct indicates a high level of convergent validity (Hair et al.,  2009 ). The seven constructs have AVE ranging from 0.477 to 0.648 as shown in Table  3 . Six constructs have more than the threshold level of AVE (0.5), thus indicating a high convergent validity of the above constructs. Only the lifestyle changes construct is found to have an AVE slightly below the threshold value. However, since this construct meets the criteria of convergent validity in the first method and in the second method, the value of AVE is somewhat close to the threshold value, the lifestyle changes construct may be considered to possess a reasonable level of convergent validity.

Discriminant validity is a measure of how a construct is distinct from other constructs in the same model and whether each construct is measuring different concepts (Hair et al.,  2009 ). Discriminant validity was also assessed by following two different approaches. The first method involves the investigation of the correlation between each pair of constructs in the CFA model. If the correlations between constructs are well below 0.9; then there is very little possibility that a group of items loading significantly on one construct would also load on another construct (Kline,  2016 ). The correlations between the constructs occurred within the range of −0.282 to 0.616, which were well below 0.9. This is reported in Table  2 . The second method involves the comparison of the AVE of each construct with the shared variance of each pair of constructs. If the square root of the AVE of each construct is more than the correlation of each pair of constructs, then this implies that the constructs account for a greater proportion of variance of the items that are assigned to them (Fornell & Larcker,  1981 ). Table  3 shows that the lowest value of AVE of a construct is 0.477. Its square root is 0.690, which exceeds the maximum correlation coefficient of 0.616 between a pair of constructs as reported in Table  2 . Thus, the seven construct CFA model demonstrates a satisfactory level of discriminant validity. This facilitated the SEM on the final measurement model to be carried out for investigating the relationships hypothesized in Section  3 .

5.3. Structural equation modelling

The final measurement model has been taken as the main input for developing the structural model. In the structural model, demographic variables of the respondents including occupation, current employment status, and family earning status were considered as the exogenous variables while Consumers' changing way of life and consumers’ buying behaviour arising out of COVID‐19 were treated as endogenous variables. This was investigated through SEM and the hypotheses formulated earlier were tested. The model was assessed utilizing the ML estimation method. GOF measures of the structural model were as follows: χ 2  = 887.533, df  = 324, p  = .00, χ 2 / df  = 2.739, GFI = 0.878, AGFI = 0.825, TLI = 0.840, CFI = 0.881, RMSEA [90% CI] = 0.064 [0.059, 0.069], SRMR = 0.075. The fit indices indicate that TLI and CFI are below the acceptable level of 0.9 while RMSEA and SRMR are within the acceptable range of 0.08 (Hair et al.,  2009 ). In this context, it is to be mentioned that the model complexity in terms of the number of observed variables, number of parameters estimated, etc. has a significant negative impact on GFI, AGFI, and CFI. Thus, the general rules of thumb with the cut‐off values of GFI or CFI being at least 0.9 may sometimes be misleading for complex models (Baumgartner & Homburg,  1996 ). A similar observation was also made by Srinivasan et al. ( 2002 ) in respect of model complexity. In one of the measurement models developed by them, both CFI and TLI were found below 0.9. However, since both RMSEA and SRMR remained within the acceptable range of 0.08, the model was considered reasonably fitting to the data. Based on the above argument, we can infer that the present findings indicate an acceptable level of fit to the above indices. The final structural model is shown in Figure  2 . We have shown only the significant paths in this model, which include both direct effects and total effects covering both direct and indirect effects. The interpretation of these paths has been provided in appropriate places of the following section.

Final model of the impact of COVID‐19 on consumer behaviour

6. MAJOR FINDINGS

6.1. influence of occupation, employment status and earning status on affordability.

The profile of the socio‐demographic and economic background of the respondents provided in Table  1 reveals that they differ in terms of their occupations, current employment status, and also their earning status. The respondents were categorized into five types of occupations described as Job1 through Job5. In terms of employment status, they were categorized into four types which have been shown as Emp1 through Emp4. Finally, the respondents were classified into three categories in terms of the earning potential of their family, which have been designated as Earn1 through Earn3. All these categorizations in terms of occupation, employment status, and earning status have been indicated in Table  4 . The categorical variables were transformed into binary variables individually before considering them as exogenous variables. In the structural model, Job1, Emp1, and Earn2 were considered as the reference categories for occupation, employment status, and earning status respectively following Cohen et al. ( 2003 ), as each one of them was the most dominant category in the respective socio‐economic classes and least likely to be affected compared to other categories by the pandemic. Out of 21 hypotheses formulated in Section  3 , 15 hypotheses had a direct effect while the remaining six hypotheses involved both direct and indirect (mediating) effects. Tables  4 and ​ and5 5 present the results of hypotheses that only have a direct effect, based on standardized regression weights (β), critical ratios (t‐value), and p values. Table  4 specifically describes the results of the effect of Consumers' socio‐economic background on their changing way of life. The results of Hypothesis  1a showing the relationship between occupation and affordability reveal that the affordability of people with four types of occupations (Job2 through Job5) was negatively affected due to COVID‐19 compared to the affordability of people belonging to the reference category, i.e., Job1. However, the negative effect was found to be significant only for people with occupation categories Job3 and Job5. This suggests that the lockdown affected the affordability of people in the unorganised sector more than the organised sector. The results of Hypothesis  1b explaining the relationship between current employment status and affordability indicate that there was a significant negative effect on the affordability of people of three types of employment (Emp2 through Emp4) due to COVID‐19 compared to the same belonging to the reference category, i.e., Emp1. This directly demonstrates that people having lost their job or receiving reduced salaries due to COVID‐19 were severely affected in terms of their affordability compared to the people who were receiving full salaries. Hypothesis  1c describing the relationship between family earning status and affordability shows that the affordability of people with two categories of earning status (Earn1 and Earn3) was not affected due to COVID‐19 compared to the reference category, i.e., Earn2. This further illustrates the fact that the respondents with a single earning member, multiple earning members, or non‐earning members cannot be differentiated in terms of their affordability due to COVID‐19. The significant impact of occupation with categories Job3 and Job5 on affordability and again the significant effect of employment status including categories Emp2 through Emp4 have been indicated in the final structural model (Figure  2 ).

Results of structural model for socio‐economic factors (direct effects) ( n  = 425)

Job1: Respondents who are working in government or public sector jobs; Job2: Respondents who are working in private sector jobs; Job3: Respondents who are working in MSME sectors/ Contractors/ Daily wage earners;

Job4: Respondents who own their own business or startups; Job5: Respondents with other job profiles.

Emp1: Respondents who are currently employed and getting full salary; Emp2: Respondents who are currently employed but are getting reduced salary; Emp3: Respondents who have lost their jobs during lockdown; Emp4: Respondents with other employment status;

Earn1: Respondents who are the sole earners of the family; Earn2: Respondents who are one of the earning members of the family; Earn3: Respondents who are the non‐earning members of the family.

Results of structural model of consumers' way of life (direct effects) ( n  = 425)

6.2. Influence of occupation, employment status and earning status on lifestyle changes

Following a similar approach, we investigated the influence of occupation, current employment status, and earning status on lifestyle changes of people due to COVID‐19. Hypothesis  2a showing the relationship between occupation and lifestyle changes reveals that the lifestyle changes of people with Job2 through Job5 were significantly affected in opposite direction compared to the lifestyle changes of people with reference category, i.e., Job1. This demonstrates that people other than those engaged in the Government or Public sector did not indulge themselves in lifestyle changes arising out of COVID‐19. Hypothesis  2b explaining the relationship between current employment status reveals that the lifestyle changes of people with Emp2 and Emp3 were positively affected compared to the lifestyle changes of people with reference category, i.e., Emp1. The effect was found to be significant. This signifies that the people receiving a reduced salary or having lost their jobs are becoming more concerned with doing yoga and using herbal products in their day‐to‐day life compared to the people receiving full salary. Hypothesis  2c delineating the relationship between family earning status and lifestyle changes shows that the lifestyle changes of people with Earn1 and Earn3 were not affected compared to the reference category, i.e., Earn2. This indicates that the lifestyle changes of people cannot be differentiated based on their earning status. The significant effect of occupation with categories Job2 through Job5 on lifestyle changes and further the significant effect of employment with categories Emp2 and Emp3 on lifestyle changes have been shown in Figure  2 .

6.3. Influence of occupation, employment status and earning status on awareness towards health

Hypothesis  3a describing the relationship between occupation and awareness towards health reveals that the health awareness of people with occupations Job2 through Job5 was negatively affected compared to the awareness of people with reference category, i.e., Job1. However, the effect was found significant only in the case of Job2. Hypothesis  3b showing the relationship between employment status and awareness towards health indicates that the awareness of people with categories Emp2, Emp3, and Emp4 was not affected compared to the reference category, i.e., Emp1. This implies that the awareness of people towards health cannot be distinguished based on their employment status. Finally, Hypothesis  3c outlining the relationship between earning status and awareness towards health shows that the awareness of people with Earn1 and Earn3 was not affected compared to the reference category, Earn2. This further explains that the awareness of people towards health cannot be discriminated against based on their earning status. The significant effect of occupation with category Job2 on awareness towards health is shown in Figure  2 .

6.4. Association of Affordability, Lifestyle Changes and Health Awareness with Demand for Wellness Products, Health Products, Substitution of Affordable necessities etc

Table  5 presents the results of the impact of different constructs constituting Consumers' changing way of life on the Adaptation in consumers’ buying behaviour . Hypothesis  4a reveals that the increase in demand for wellness and entertainment products was associated with a fall in affordability. However, the effect was not significant. Similarly, the increase in demand for products relating to health and hygiene was associated with a non‐significant decrease in affordability as specified in Hypothesis  4b . Hypothesis  4c shows that the fall in affordability had a significant influence on the demand for affordable substitute products of daily necessities. Hypothesis  5 shows that lifestyle changes had a significant positive influence on the demand for wellness products which explains the reported rise in demand for wellness and entertainment products during the pandemic. Further, increased awareness towards health and hygiene had a significant positive influence on the demand for products relating to health and hygiene as also on the demand for healthy substitute products of daily necessities as described in Hypotheses  6a and 6b respectively. The significant results of Hypotheses  4c , 5 , 6a , and 6b have been delineated in Figure  2 . Thus, our study validates many of the anecdotal explanations that are observed in market surveys and news reports on the effect of COVID‐19 on consumers' changing buying behaviour.

6.5. Influence of occupation on the demand for wellness products

Test results of the remaining six hypotheses involving both direct and indirect effects of socio‐economic background , Consumers’ changing way of life, and consumers' buying behaviour have been shown individually in Tables  6 , ​ ,7, 7 , ​ ,8, 8 , ​ ,9. 9 . These tables show the direct effect, indirect effect, and total effect of the relationships. We utilized the AMOS plugin developed by Gaskin and Lim ( 2018 ) for estimating the specific indirect effect in IBM SPSS AMOS (version 24). Table  6 presents the results of Hypothesis  7 explaining the influence of occupation on the demand for wellness and entertainment products. We considered Job1 as the reference category and tested the scores obtained by categories Job2 through Job5 against the reference category. The results show that the occupation with category Job3 had a significant negative influence on the creation of new demand for wellness and entertainment products compared to the reference category. The association is moderate which is mediated through two mediating constructs: (1) Change in affordability and (2) Lifestyle changes. Further, the mediation is partial. However, it was observed that the creation of new demand for wellness and entertainment products by the remaining categories of occupations including Job2, Job4, and Job5 did not significantly differ from the demand created by the reference category. We present the results of Hypothesis  7 in Table  6 for occupation with category Job3 only. We further show the results of the total significant effect of occupation with category Job3 on the demand for wellness and entertainment products in Figure  2 through a bold arrow.

Hypothesis  7 Influence of occupation on the demand for wellness products (direct, indirect and total effects) ( n  = 425)

Hypothesis  9 Influence of earning status on the demand for wellness products (direct, indirect and total effects) ( n  = 425)

Hypothesis  11 Influence of emp. Status on the creation of new demand for health products (direct, indirect and total effects) ( n  = 425)

Hypothesis  12 Influence of earning status on the creation of new demand for health products (direct, indirect and total effects) ( n  = 425)

6.6. Influence of employment status and earning status on the demand for wellness products

We investigated the results of Hypothesis  8 describing the influence of current employment status on the demand for wellness products considering Emp1 as the reference category and observed that the current employment status of people with categories Emp2 through Emp4 did not have a significant influence on the creation of new demand for wellness and entertainment products compared to the reference category. Since the results of Hypothesis  8 involving all categories of employment status were insignificant, we have not reported the results. We analysed the results of Hypothesis  9 explaining the influence of family earning status on the demand for wellness products considering Earn2 as the reference category. The results are presented in Table  7 . The results reveal that the earning status of people of category Earn1 had a significant negative influence on the creation of new demand for wellness and entertainment products compared to the reference category. The relationship is mediated by two mediating constructs: (1) Change in affordability and (2) Lifestyle changes and the mediation is full. It was further observed that the earning status of people of category Earn3 did not have any significant influence on the demand for wellness and entertainment products compared to the reference category. The significant effect of Hypothesis  9 explaining the influence of earning status with category Earn1 on the demand for wellness and entertainment products is represented in Figure  2 .

6.7. Influence of occupation, employment status and earning status on the demand for health products

We analysed the influence of occupation on the creation of new demand for health and hygiene products considering Job1 as the reference category and found that the occupation with categories Job2 through Job5 did not have a significant influence on the creation of new demand for health and hygiene products compared to the reference category. We, therefore, have not reported the results of Hypothesis  10 . We investigated the results of Hypothesis  11 delineating the influence of current employment status on the creation of new demand for health and hygiene products considering Emp1 as the reference category. The results show that the employment status of category Emp3 had a significant positive influence on the creation of new demand for health and hygiene products compared to the reference category. The association is mediated by two constructs: (1) Change in affordability and (2) Awareness towards health and hygiene and the mediation is partial. We did not observe any significant influence of employment status with categories Emp2 and Emp4 on the creation of new demand for health and hygiene products compared to the reference category. Table  8 presents the results of hypothesis Hypothesis  11 for employment status with category Emp3 only. We have further shown the total significant effect of Hypothesis  11 in respect of employment status of category Emp3 in Figure  2 . Finally, Table  9 outlines the results of Hypothesis  12 explaining the influence of earning status on the creation of new demand for health and hygiene products considering Earn2 as the reference category. The results reveal that the family earning status of category Earn3 had a significant positive influence on the creation of new demand for health and hygiene products compared to the reference category. The association is mediated by two constructs: (1) Change in affordability and (2) Awareness towards health and hygiene and the mediation is partial. The significant total effect of Hypothesis  12 in respect of earning status of category Earn3 is depicted in Figure  2 . The earning status of people of category Earn1 did not have any significant influence on the demand for health and hygiene products compared to the reference category.

7. DISCUSSION

7.1. theoretical contributions.

The main theoretical contribution of the study involves understanding the impact of the socio‐economic background of the respondents in terms of their occupation, employment status, and family earning status on Consumers’ changing way of life and subsequently on consumers’ changing buying behaviour at a granular level in the context of the pandemic. While earlier researchers had studied consumption shifts during the pandemic (Laato et al.,  2020 ; Pakravan‐Charvadeh et al.,  2021 ), we are not aware of any study that investigated the Consumers' changing way of life and their changing buying behaviour arising out of COVID‐19 based on the socio‐economic background of the consumers. Although the survey was carried out in India in the backdrop of COVID‐19 pandemic, the findings of the study could provide important insights to other emerging economies afflicted with COVID‐19. Thus, it may be considered as a significant contribution to the existing body of consumer behaviour literature.

Second , we have gone beyond panic buying and stockpiling behaviour, which are extensively covered in the earlier works (Kirk & Rifkin,  2020 ; Laato et al.,  2020 ), with an attempt to link affordability, lifestyle changes, and health awareness with consumer behaviour. The findings of the study demonstrating the impact of consumers' socio‐economic background on their affordability, lifestyle changes, and awareness towards health and finally on the adaptation in consumers' buying behaviour arising out of COVID‐19 have enabled us to develop a theoretical model which seems to be generalisable for other similar kinds of pandemics in the emerging economies. Third , the extant literature suggests that during the period of the pandemic, consumers focus mostly on essential products and exercise control on discretionary expenditure. However, the present study notes that the demand for some discretionary products (e.g., the demand for wellness and entertainment products) has shown a varying pattern depending on the occupation and earning potential of a family during the pandemic. We have further demonstrated that this change in demand for wellness products among consumers of certain socio‐economic groups is not merely due to the economic impacts but also due to the pandemic‐induced lifestyle changes. By including lifestyle changes, we have added a new dimension to the understanding of consumers’ behaviour during the pandemic and enriched similar studies by earlier researchers such as Naeem ( 2020 ) who attributed consumers’ impulsive buying to information overload. Fourth, the study reveals that the creation of new demand for health and hygiene products was found to depend upon the current employment status and family earning status of consumers which is jointly mediated by affordability and awareness towards health and hygiene. These findings enrich our understanding of consumers' behaviour in terms of their demand for wellness products as also the demand for health and hygiene products during the pandemic (Pakravan‐Charvadeh et al.,  2021 ). Finally , the study further reveals that the consumers demonstrated product substitution behaviour due to the availability of affordable substitutes of daily necessities and also due to the availability of healthy substitutes of daily necessities. Therefore, our study confirms product substitution behaviour during the pandemic as noted by Knowles et al. ( 2020 ). Thus, it may also be considered to be another unique contribution of the present study.

7.2. Managerial implications

The study reveals that the affordability of the most vulnerable section of people including daily wage earners and those working in MSMEs has been affected due to COVID‐19. The study also finds that the affordability of the people receiving a reduced salary or having lost their jobs has also been severely affected. This provides an important insight to the policy planners in terms of developing targeted intervention strategies with a view to providing economic aid to the affected people. In addition, the study provides insights to marketing managers in terms of designing and introducing affordable substitute products of daily necessities for a substantial section of the population. Thus, there lies an opportunity to penetrate the market with inexpensive substitutes in a market already occupied by established brands.

The study shows that people engaged in most of the occupations other than Government or public sector jobs are not much concerned with lifestyle changes arising out of COVID‐19. However, it shows that people receiving a reduced salary or having lost their jobs have become quite active in practicing yoga and utilizing herbal products. This possibly indicates that these consumers have become sensitive in maintaining their health due to the fear of contagion despite the challenging situation faced by them in their professional lives. On further scrutiny, we observed that the demand for wellness products by people working in the unorganised sectors is significantly lower than those working in the organised sectors. It is significantly less in a family with a sole earning member than in a family with multiple earning members. In addition, the demand for wellness products by people receiving a reduced salary or having lost their jobs does not significantly differ from people receiving full salary. Thus, the market planners need to carefully take into consideration the socio‐economic factors of the consumers including occupation, employment status, and family earning status while introducing wellness products in the market. Increased awareness towards health and hygiene motivates marketing managers to introduce innovative products relating to health and hygiene and healthy substitute products of daily necessities. To boost demand, designing appropriate awareness campaigns would be very useful. It is observed that the demand for health and hygiene products by people belonging to different occupations does not significantly differ from the people working in the government or public sector jobs. Further, the people who lost their jobs exhibited significantly more demand for health and hygiene products than those receiving full salary. In addition, the demand for such products by the non‐earning members of a family has significantly increased compared to the multiple earning members of a family. This is quite surprising. This probably indicates that even though the pandemic has negatively affected the economies across the globe, the sale of products relating to health and hygiene has significantly increased. The companies selling products relating to health and hygiene should go all out in their efforts to advertise and increase their sales during such a crisis. Finally, there is an opportunity to introduce healthy substitutes of daily necessities in a market already occupied by established brands.

Given that emerging economies such as India, where this study was carried out, have a large share of the unorganised or informal sector (Murthy,  2019 ), our findings are indicative of the nature of the economic impact that the unorganised sector has experienced during this pandemic. Post‐COVID it would be essential for firms dealing with daily necessities to expand their product assortments to include cheaper alternatives. Emerging economies are further characterized by a smaller market for health and hygiene as well as the wellness and digital entertainment market (Sood,  2020 ). The study observed that it is lifestyle and health awareness that affect the demand for wellness and entertainment products, and hygiene products respectively. Hence, firms dealing with such products in emerging markets should realise that it is important to focus on market creation through lifestyle changes and health awareness in addition to regular promotions. The study also gives enough insights into the customer segments that could be targeted for such efforts.

8. CONCLUSION

In this paper, we have carried out a questionnaire survey to understand the impact of COVID‐19 on consumers' affordability, lifestyle, and health awareness and how these effects influenced their buying behaviour. Analysis of the survey data revealed several interesting facts about the impact of COVID‐19 and how the consumers behaved. Some of the major findings of this study include: (1) COVID‐19 affected the affordability of consumers employed in the unorganised sectors more than those who were employed in the organised sector, (2) Type of occupation, current employment status, and the earning potential of a family had a varying degree of impact on lifestyle changes undergone by consumers, and (3) the health awareness was significantly higher for consumers who lost their jobs or had lower family earning status. It was observed that the demand for wellness and entertainment products was not affected much by affordability but by lifestyle changes while the demand for health and hygiene products was more influenced by consumer awareness towards health. Affordability, on the other hand, influenced the demand for affordable substitutes of daily necessities. Therefore, this study and the findings would be very useful for studying the effects of disruptive events on the nature of the shift in consumption behaviour and substitution behaviour exhibited by consumers. Further, the findings of this study would help organizations formulate appropriate strategies to cope with the shift in consumption and substitution behaviour as a result of the pandemic.

The study is not free from certain limitations. The imposition of lockdown in different parts of India at different points of time made it very difficult for us to carry out the survey. Further given the diversity and the large geographical size of India, we could not reach out to all the diverse groups, communities, and cultures. Increasing reach possibly could have generated more insights into consumer behaviour and market segmentation. Moreover, our study was limited to wellness, entertainment, and health products as also the products of daily necessities. Therefore, extending this research to include more diversity in terms of the nature of products would be useful in further refinement of marketing strategies under disruption.

The observations of Paul and Bhukya ( 2021 ) encourage us to propose extension of the present research primarily along the following directions: (1) cross‐country studies for understanding how the pandemic‐induced disruptions have affected consumer behaviour across various social groups based on culture, region, and age, (2) studies on how organizations cope with such adaptations in consumers' needs during pandemic, and (3) studies focusing on understanding how and to what extent consumers' consumption shifts influence retailers' strategies related to product selection, channel choice, promotions, and discounts. It can also be expected that the choice of the above strategies would differ based on retailers' location, the scale of operations, and the target segments. A major influence on the Consumers' changing way of life during such pandemic‐induced disruptions includes government interventions in the form of schemes, aids, and subsidies. An important extension of the present research would be to understand how such interventions were able to mitigate the adverse impacts of the pandemic on consumers' life and at the same time maintain the sustainability of business organizations.

CONFLICT OF INTEREST

The authors declare that there is no conflict of interest.

ACKNOWLEDGEMENTS

Biographies.

Debadyuti Das is a Professor at the Faculty of Management Studies, Delhi University in the Operations Management Area. He received his Ph.D. from IIT BHU. He has a rich blend of experience in both industry and academics spanning over more than two and half decades. He has extensive experience in executive education and management development programs. His current areas of research include Sustainable Supply Chain Management, Managing Carbon Footprint in Supply Chain, Distribution Network Design in Public Health, Efficient Sourcing and Distribution of water etc.

Ashutosh Sarkar is an Associate Professor at the Indian Institute of Management Kozhikode in the Quantitative Methods & Operations Management Area. He received his Ph.D. from Indian Institute of Technology Kharagpur and was a Fulbright Visiting Scholar at the Naveen Jindal School of Management, University of Texas at Dallas. Earlier, Dr. Sarkar has served as a faculty member at IIT Kharagpur and Institute of Technology‐Banaras Hindu University (now IIT BHU). He has extensive experience in executive education and training. His areas of interests include Inventory and Supply Chain Optimization, Application of Stochastic Dynamic Programming in Operations Management Problems, Purchasing and Supply Chain Risk Management.

Arindam Debroy is an Assistant Professor at the Symbiosis Institute of Business Management Nagpur in the Operations Management Area. He received his Ph.D. from Indian Institute of Technology Kharagpur. He has also received the Institute Fellowship during his doctoral program at IIT Kharagpur. His areas of interests include Inventory and Logistics & Supply Chain Management, Purchase Management, and Project Management.

APPENDIX 1. DESCRIPTIVE STATISTICS OF FACTORS INFLUENCING CONSUMERS' CHANGING WAY OF LIFE

APPENDIX 2. DESCRIPTIVE STATISTICS OF ADAPTATION IN CONSUMERS' BUYING BEHAVIOUR

Das, D. , Sarkar, A. , & Debroy, A. (2022). Impact of COVID‐19 on changing consumer behaviour: Lessons from an emerging economy . International Journal of Consumer Studies , 46 , 692–715. 10.1111/ijcs.12786 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

DATA AVAILABILITY STATEMENT

• Adams‐Prassl, A. , Boneva, T. , Golin, M. , & Rauh, C. (2020, April 1). Inequality in the impact of the coronavirus shock: New survey evidence for the UK . Cambridge‐INET Working Paper Series. IZA Institute of Labor Economics. [ Google Scholar ]
• Addabbo, T. (2000). Poverty dynamics: Analysis of household incomes in Italy . Labour , 14 ( 1 ), 119–144. 10.1111/1467-9914.00127 [ CrossRef ] [ Google Scholar ]
• Anderson, J. C. , & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two‐step approach . Psychological Bulletin , 103 ( 3 ), 411–423. 10.1037/0033-2909.103.3.411 [ CrossRef ] [ Google Scholar ]
• Arora, T. , & Grey, I. (2020). Health behaviour changes during COVID‐19 and the potential consequences: A mini‐review . Journal of Health Psychology , 25 ( 9 ), 1155–1163. 10.1177/1359105320937053 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Aunger, R. , Greenland, K. , Ploubidis, G. , Schmidt, W. , Oxford, J. , & Curtis, V. (2016). The determinants of reported personal and household hygiene behaviour: A multi‐country study . PLoS One , 11 ( 8 ), e0159551. 10.1371/journal.pone.0159551 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Avdiu, B. , & Nayyar, G. (2020). When face‐to‐face interactions become an occupational hazard: Jobs in the time of COVID‐19 . Economics Letters , 197 , 109648. [ Google Scholar ]
• Baiano, C. , Zappullo, I. , & Conson, M. (2020). Tendency to worry and fear of mental health during Italy's COVID‐19 lockdown . International Journal of Environmental Research and Public Health , 17 ( 16 ), 5928. 10.3390/ijerph17165928 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Bakhtiani, G. (2021). How the wellness market in India is witnessing a meteoric rise . Financial Express , February 6. https://www.financialexpress.com/brandwagon/how‐the‐wellness‐market‐in‐india‐is‐witnessing‐a‐meteoric‐rise/2189156/
• Baumgartner, H. , & Homburg, C. (1996). Applications of structural equation modeling in marketing and consumer research: A review . International Journal of Research in Consumer Marketing , 13 , 139–161. 10.1016/0167-8116(95)00038-0 [ CrossRef ] [ Google Scholar ]
• Billore, S. , & Anisimova, T. (2021). Panic buying research: A systematic literature review and future research agenda . International Journal of Consumer Studies , 45 , 777–804. 10.1111/ijcs.12669 [ CrossRef ] [ Google Scholar ]
• Chaudhuri, S. (2020, July 28). Lysol maker seeks to capitalize on Covid hygiene concerns in hotels, on planes . The Wall Street Journal . https://www.wsj.com/articles/lysol‐maker‐seeks‐to‐capitalize‐on‐covid‐hygiene‐concerns‐in‐hotels‐on‐planes‐11595939726
• Chopra, S. , Ranjan, P. , Singh, V. , Kumar, S. , Arora, M. , Hasan, M. S. , Kasiraj, R. , Kaur, D. , Vikram, N. K. , Malhotra, A. , Kumari, A. , Klanidhi, K. B. , & Baitha, U. (2020). Impact of COVID‐19 on lifestyle‐related behaviours—A cross‐sectional audit of responses from nine hundred and ninety‐five participants from India . Diabetes & Metabolic Syndrome: Clinical Research & Reviews , 14 ( 6 ), 2021–2030. 10.1016/j.dsx.2020.09.034 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Chriscaden, K. (2020). Impact of COVID‐19 on people’s livelihoods, their health and our food system . World Health Organization , October 13. https://www.who.int/news/item/13‐10‐2020‐impact‐of‐covid‐19‐on‐people's‐livelihoods‐their‐health‐and‐our‐food‐systems
• Cohen, J. , Cohen, P. , West, S. G. , & Aiken, L. S. . (2003). Applied multiple regression/correlation analysis for the behavioural sciences . Lawrence Erlbaum Associates Publishers. [ Google Scholar ]
• Das, D. (2018). Sustainable supply chain management in Indian organisations: An empirical investigation . International Journal of Production Research , 56 ( 17 ), 5776–5794. 10.1080/00207543.2017.1421326 [ CrossRef ] [ Google Scholar ]
• Debroy, L. (2020, April 3). How online exercise sessions are keeping India fit during lockdown . Outlook . https://www.outlookindia.com/website/story/india‐news‐how‐online‐exercise‐sessions‐are‐keeping‐india‐fit‐during‐the‐lockdown/350026
• del Rio‐Chanona, R. M. , Mealy, P. , Pichler, A. , Lafond, F. , & Farmer, J. D. (2020). Supply and demand shocks in the COVID‐19 pandemic: An industry and occupation perspective . Oxford Review of Economic Policy , 36 ( Supplement_1 ), S94–S137. 10.1093/oxrep/graa033 [ CrossRef ] [ Google Scholar ]
• Dsouza, S. (2020, March 30). Government expands lists of essential items to include hygiene products . Bloomberg . https://www.bloombergquint.com/business/government‐expands‐list‐of‐essential‐items‐to‐include‐hygiene‐products
• Eroglu, S. A. , Machleit, K. A. , & Neybert, E. G. (2022). Crowding in the time of COVID: Effects on rapport and shopping satisfaction . Journal of Retailing and Consumer Services , 64 , 102760. 10.1016/j.jretconser.2021.102760 [ CrossRef ] [ Google Scholar ]
• Fornell, C. , & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error . Journal of Marketing Research , 8 ( 3 ), 382–388. [ Google Scholar ]
• Galati, A. , Moavero, P. , & Crescimanno, M. (2019). Consumer awareness and acceptance of irradiated foods: The case of Italian consumers . British Food Journal , 121 ( 6 ), 1398–1412. 10.1108/BFJ-05-2018-0336 [ CrossRef ] [ Google Scholar ]
• García‐Mayor, J. , Moreno‐Llamas, A. , & De la Cruz‐Sánchez, E. (2021). High educational attainment redresses the effect of occupational social class on health‐related lifestyle: Findings from four Spanish national health surveys . Annals of Epidemiology , 58 , 29–37. 10.1016/j.annepidem.2021.02.010 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Gaskin, J. , & Lim, J. (2018). “Indirect effects”, AMOS Plugin . Gaskination's StatWiki. [ Google Scholar ]
• Gordon‐Wilson, S. (2021). Consumption practices during the COVID‐19 crisis . International Journal of Consumer Studies . 10.1111/ijcs.12701 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Guthrie, C. , Fosso‐Wamba, S. , & Arnaud, J. B. (2021). Online consumer resilience during a pandemic: An exploratory study of e‐commerce behavior before, during and after a COVID‐19 lockdown . Journal of Retailing and Consumer Services , 61 , 102570. 10.1016/j.jretconser.2021.102570 [ CrossRef ] [ Google Scholar ]
• Hair, J. F., Jr. , Black, W. C. , Babin, B. J. , Anderson, R. E. , & Tatham, R. L. (2009). Multivariate data analysis . Pearson Education. [ Google Scholar ]
• Hamilton, R. W. , Thompson, D. V. , Arens, Z. G. , Blanchard, S. J. , Häubl, G. , Kannan, P. K. , Khan, U. , Lehmann, D. R. , Meloy, M. G. , Roese, N. J. , & Thomas, M. (2014). Consumer substitution decisions: An integrative framework . Marketing Letters , 25 ( 3 ), 305–317. 10.1007/s11002-014-9313-2 [ CrossRef ] [ Google Scholar ]
• Hampson, D. P. , & McGoldrick, P. J. (2013). A typology of adaptive shopping patterns in recession . Journal of Business Research , 66 ( 7 ), 831–838. 10.1016/j.jbusres.2011.06.008 [ CrossRef ] [ Google Scholar ]
• Hensher, M. (2020). Covid‐19, unemployment, and health: Time for deeper solutions? The BMJ , 371 , m3687. 10.1136/bmj.m3687 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Hess, A. (2020, April 6). Our health is in danger: Wellness wants to fill the void . The New York Times . https://www.nytimes.com/2020/04/06/arts/virus‐wellness‐self‐care.html
• Jacob, I. , Khanna, M. , & Yadav, N. (2014). Beyond poverty: A study of diffusion & adoption of feminine hygiene products among low income group women in Mumbai . Procedia‐Social and Behavioral Sciences , 148 , 291–298. [ Google Scholar ]
• Kansiime, M. K. , Tambo, J. A. , Mugambi, I. , Bundi, M. , Kara, A. , & Owuor, C. (2021). COVID‐19 implications on household income and food security in Kenya and Uganda: Findings from a rapid assessment . World Development , 137 , 105199. 10.1016/j.worlddev.2020.105199 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Keane, M. , & Neal, T. (2021). Consumer panic in the COVID‐19 pandemic . Journal of Econometrics , 220 ( 1 ), 86–105. 10.1016/j.jeconom.2020.07.045 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Kennett‐Hensel, P. A. , Sneath, J. Z. , & Lacey, R. (2012). Liminality and consumption in the aftermath of a natural disaster . Journal of Consumer Marketing , 29 ( 1 ), 52–63. 10.1108/07363761211193046 [ CrossRef ] [ Google Scholar ]
• Khubchandani, J. , Kandiah, J. , & Saiki, D. (2020). The COVID‐19 pandemic, stress, and eating practices in the United States . European Journal of Investigation in Health, Psychology and Education , 10 ( 4 ), 950–956. 10.3390/ejihpe10040067 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Kim, J. , Yang, K. , Min, J. , & White, B. (2021). Hope, fear, and consumer behavioral change amid COVID‐19: Application of protection motivation theory . International Journal of Consumer Studies . 10.1111/ijcs.12700 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Kirk, C. P. , & Rifkin, L. S. (2020). I'll trade you diamonds for toilet paper: Consumer reacting, coping and adapting behaviors in the COVID‐19 pandemic . Journal of Business Research , 117 , 124–131. 10.1016/j.jbusres.2020.05.028 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Kline, R. B. (2016). Principles and practice of structural equation modeling (4th ed.). Guilford Press. [ Google Scholar ]
• Knowles, J. , Ettenson, R. , Lynch, P. , & Dollens, J. (2020, May 5). Growth opportunities for brands during covid‐19 opportunities . MIT Sloan Management Review . https://sloanreview.mit.edu/article/growth‐opportunities‐for‐brands‐during‐the‐covid‐19‐crisis/ [ Google Scholar ]
• Krause, D. R. , Pagell, M. , & Curkovic, S. (2001). Toward a measure of competitive priorities for purchasing . Journal of Operations Management , 19 ( 4 ), 497–512. 10.1016/S0272-6963(01)00047-X [ CrossRef ] [ Google Scholar ]
• Laato, S. , Islam, A. N. , Farooq, A. , & Dhir, A. (2020). Unusual purchasing behavior during the early stages of the COVID‐19 pandemic: The stimulus‐organism‐response approach . Journal of Retailing and Consumer Services , 57 , 102224. 10.1016/j.jretconser.2020.102224 [ CrossRef ] [ Google Scholar ]
• Li, X. , Zhang, D. , Zhang, T. , Ji, Q. , & Lucey, B. (2021). Awareness, energy consumption and pro‐environmental choices of Chinese households . Journal of Cleaner Production , 279 , 123734. 10.1016/j.jclepro.2020.123734 [ CrossRef ] [ Google Scholar ]
• Madnani, D. , Fernandes, S. , & Madnani, N. (2020). Analysing the impact of COVID‐19 on over‐the‐top media platforms in India . International Journal of Pervasive Computing and Communications , 16 ( 5 ), 457–475. 10.1108/IJPCC-07-2020-0083 [ CrossRef ] [ Google Scholar ]
• Mahmud, M. , & Riley, E. (2021). Household response to an extreme shock: Evidence on the immediate impact of the Covid‐19 lockdown on economic outcomes and well‐being in rural Uganda . World Development , 140 , 105318. 10.1016/j.worlddev.2020.105318 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Mark, T. , Southam, C. , Bulla, J. , & Meza, S. (2016). Cross‐category indulgence: Why do some premium brands grow during recession? Journal of Brand Management , 23 ( 5 ), 114–129. 10.1057/s41262-016-0004-6 [ CrossRef ] [ Google Scholar ]
• Martin, A. , Markhvida, M. , Hallegatte, S. , & Walsh, B. (2020). Socio‐economic impacts of COVID‐19 on household consumption and poverty . Economics of Disasters and Climate Change , 49 ( 3 ), 453–479. 10.1007/s41885-020-00070-3 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Master, F. (2020). Asia pivots toward plants for protein as coronavirus stirs meat safety fears . Reuters , April 22. https://www.reuters.com/article/us‐health‐coronavirus‐asia‐food/asia‐pivots‐toward‐plants‐for‐protein‐as‐coronavirus‐stirs‐meat‐safety‐fears‐idUKKCN224047?edition‐redirect=uk
• Mathur, A. , Moschis, G. P. , & Lee, E. (2006). Life events and brand preference changes . Journal of Consumer Behaviour: An International Research Review , 3 ( 2 ), 129–141. 10.1002/cb.128 [ CrossRef ] [ Google Scholar ]
• Mehrolia, S. , Alagarsamy, S. , & Solaikutty, V. M. (2021). Customers response to online food delivery services during COVID‐19 outbreak using binary logistic regression . International Journal of Consumer Studies , 45 ( 3 ), 396–408. 10.1111/ijcs.12630 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Milaković, I. K. (2021). Purchase experience during the COVID‐19 pandemic and social cognitive theory: The relevance of consumer vulnerability, resilience, and adaptability for purchase satisfaction and repurchase . International Journal of Consumer Studies , 45 ( 6 ), 1425–1442. 10.1111/ijcs.12672 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Minton, E. A. , & Cabano, F. G. (2021). Religiosity’s influence on stability‐seeking consumption during times of great uncertainty: The case of the coronavirus pandemic . Marketing Letters , 32 ( 2 ), 135–148. 10.1007/s11002-020-09548-2 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Mishra, P. , & Balsara, F. (2020). COVID‐19 and emergence of a new consumer products landscape in India . Earnst and Young . https://assets.ey.com/content/dam/ey‐sites/ey‐com/en_in/topics/consumer‐products‐retail/2020/06/covid‐19‐and‐emergence‐of‐new‐consumer‐products‐landscape‐in‐india.pdf?download
• Montenovo, L. , Jiang, X. , Rojas, F. L. , Schmutte, I. M. , Simon, K. I. , Weinberg, B. A. , & Wing, C. (2020). Determinants of disparities in covid‐19 job losses (No. w27132), National Bureau of Economic Research. [ Google Scholar ]
• Mueller, R. O. , & Hancock, G. R. (2019). Structural equation modeling. In Hancock G. R., Stapleton L. M., & Mueller R. O. (Eds.), The reviewer’s guide to quantitative methods in social sciences (2nd ed.). Routledge. [ Google Scholar ]
• Murthy, S. R. (2019). Measuring informal economy in India: Indian experience. In Seventh IMF Statistical Forum , Washington, DC. https://www.imf.org/‐/media/Files/Conferences/2019/7th‐statistics‐forum/session‐ii‐murthy.ashx#:∼:text=In_terms_of_employment_share,indicating_the_level_of_outsourcing [ Google Scholar ]
• Naeem, M. (2020). Understanding the customer psychology of impulse buying during COVID‐19 pandemic: Implications for retailers . International Journal of Retail & Distribution Management , 49 ( 3 ), 377–393. 10.1108/IJRDM-08-2020-0317 [ CrossRef ] [ Google Scholar ]
• Nayal, P. , Pandey, N. , & Paul, J. (2021). Covid‐19 pandemic and consumer‐employee‐organization wellbeing: A dynamic capability theory approach . Journal of Consumer Affairs . 10.1111/joca.12399 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Ojha, A. (2020, October 17). How COVID‐19 changed fitness regime of Indians; here’s what a survey revealed . Financial Express . https://www.financialexpress.com/lifestyle/health/how‐covid‐19‐changed‐fitness‐regime‐of‐indians‐heres‐what‐a‐survey‐revealed/2107825/
• Pakravan‐Charvadeh, M. R. , Mohammadi‐Nasrabadi, F. , Gholamrezai, S. , Vatanparast, H. , Flora, C. , & Nabavi‐Pelesaraei, A. (2021). The short‐term effects of COVID‐19 outbreak on dietary diversity and food security status of Iranian households (A case study in Tehran province) . Journal of Cleaner Production , 281 , 124537. 10.1016/j.jclepro.2020.124537 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Pantano, E. , Pizzi, G. , Scarpi, D. , & Dennis, C. (2020). Competing during a pandemic? Retailers' ups and downs during the COVID‐19 outbreak . Journal of Business Research , 116 , 209–213. 10.1016/j.jbusres.2020.05.036 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Paul, J. , & Bhukya, R. (2021). Forty‐five years of International Journal of Consumer Studies: A bibliometric review and directions for future research . International Journal of Consumer Studies , 45 ( 5 ), 937–963. 10.1111/ijcs.12727 [ CrossRef ] [ Google Scholar ]
• Pew Research . (2008, October 19). Family social activities and togetherness . https://www.pewresearch.org/internet/2008/10/19/family‐social‐activities‐and‐togetherness/ [ Google Scholar ]
• Piyapromdee, S. , & Spittal, P. (2020). The income and consumption effects of covid‐19 and the role of public policy . Fiscal Studies , 41 ( 4 ), 805–827. 10.1111/1475-5890.12252 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Podsakoff, P. M. , MacKenzie, S. B. , Lee, J. Y. , & Podsakoff, N. P. (2003). Common method biases in behavioural research: A critical review of the literature and recommended remedies . Journal of Applied Psychology , 88 ( 5 ), 879–903. [ PubMed ] [ Google Scholar ]
• Prasad, A. , Strijnev, A. , & Zhang, Q. (2008). What can grocery basket data tell us about health consciousness? International Journal of Research in Marketing , 25 ( 4 ), 301–309. 10.1016/j.ijresmar.2008.05.001 [ CrossRef ] [ Google Scholar ]
• Prentice, C. , Nguyen, M. , Nandy, P. , Winardi, M. A. , Chen, Y. , Le Monkhouse, L. , Sergio, D. , & Stantic, B. (2021). Relevant, or irrelevant, external factors in panic buying . Journal of Retailing and Consumer Services , 61 , 102587. 10.1016/j.jretconser.2021.102587 [ CrossRef ] [ Google Scholar ]
• PTI . (2020). COVID‐19 pandemic leads to worries about job loss, anxiety on lack of social interactions: surveys . The Economic Times , September 29. https://economictimes.indiatimes.com/news/politics‐and‐nation/covid‐19‐pandemic‐leads‐to‐worries‐about‐job‐loss‐anxiety‐on‐lack‐of‐social‐interactions‐surveys/articleshow/78391128.cms?from=mdr
• Pullman, M. E. , Maloni, M. J. , & Carter, C. R. (2009). Food for thought: Social versus environmental sustainability practices and performance outcomes . Journal of Supply Chain Management , 45 ( 4 ), 38–54. 10.1111/j.1745-493X.2009.03175.x [ CrossRef ] [ Google Scholar ]
• Rakshit, A. (2020, May 10). Covid‐19 impact: demand for personal hygiene, homecare products set to rise . Business Standard . https://www.business‐standard.com/article/current‐affairs/covid‐19‐impact‐demand‐for‐personal‐hygiene‐homecare‐products‐set‐to‐rise‐120051000431_1.html
• Rayburn, S. W. , McGeorge, A. , Anderson, S. , & Sierra, J. J. (2021). Crisis‐induced behavior: From fear and frugality to the familiar . International Journal of Consumer Studies . 10.1111/ijcs.12698 [ CrossRef ] [ Google Scholar ]
• Renner, B. , Baker, B. , Cook, J. , & Mellinger, J. (2020). The future of fresh: Patterns from the pandemic . Deloitte Insights , October 13. https://www2.deloitte.com/us/en/insights/industry/retail‐distribution/future‐of‐fresh‐food‐sales/pandemic‐consumer‐behavior‐grocery‐shopping.html
• Riise, T. , Moen, B. E. , & Nortvedt, M. W. (2003). Occupation, lifestyle factors and health‐related quality of life: The Hordaland Health Study . Journal of Occupational and Environmental Medicine , 45 ( 3 ), 324–332. 10.1097/01.jom.0000052965.43131.c3 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Rogers, K. , & Cosgrove, A. (2020, April 16). Future consumer index: How Covid‐19 is changing consumer behaviors . Ernst & Young . https://www.ey.com/en_gl/consumer‐products‐retail/how‐covid‐19‐could‐change‐consumer‐behavior
• Sánchez‐Sánchez, E. , Ramírez‐Vargas, G. , Avellaneda‐López, Y. , Orellana‐Pecino, J. I. , García‐Marín, E. , & Díaz‐Jimenez, J. (2020). Eating habits and physical activity of the Spanish population during the COVID‐19 pandemic period . Nutrients , 12 ( 9 ), 2826. 10.3390/nu12092826 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Sarmento, M. , Marques, S. , & Galan‐Ladero, M. (2019). Consumption dynamics during recession and recovery: A learning journey . Journal of Retailing and Consumer Services , 50 , 226–234. 10.1016/j.jretconser.2019.04.021 [ CrossRef ] [ Google Scholar ]
• Singh, D. (2020). How is coronavirus impacting the streaming platforms with an increasing appetite of viewers? Financial Express , April 04. https://www.financialexpress.com/brandwagon/how‐is‐coronavirus‐impacting‐the‐streaming‐platforms‐with‐an‐increasing‐appetite‐of‐viewers/1919916/
• Sneath, J. Z. , Lacey, R. , & Kennett‐Hensel, P. A. (2009). Coping with a natural disaster: Losses, emotions, and impulsive and compulsive buying . Marketing Letters , 20 ( 1 ), 45–60. 10.1007/s11002-008-9049-y [ CrossRef ] [ Google Scholar ]
• Sood, D. (2020). India has the potential to become a health and wellness hub . The Hindu Business Line , July 29. https://www.thehindubusinessline.com/opinion/india‐has‐the‐potential‐to‐become‐a‐health‐and‐wellness‐hub/article32220274.ece
• Srinivasan, R. , Lilien, G. L. , & Rangaswamy, A. (2002). Technological opportunism and radical technology adoption: An application to E‐Business . Journal of Marketing , 66 , 47–60. 10.1509/jmkg.66.3.47.18508 [ CrossRef ] [ Google Scholar ]
• Suresh, S. , Ravichandran, S. , & P, G. (2011). Understanding wellness center loyalty through lifestyle analysis . Health Marketing Quarterly , 28 ( 1 ), 16–37. 10.1080/07359683.2011.545307 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Teisl, M. F. , Levy, A. S. , & Derby, B. M. (1999). The effects of education and information source on consumer awareness of diet–disease relationships . Journal of Public Policy & Marketing , 18 ( 2 ), 197–207. 10.1177/074391569901800206 [ CrossRef ] [ Google Scholar ]
• United Nations . (n.d.). Everyone included: Social impact of COVID‐19 . https://www.un.org/development/desa/dspd/everyone‐included‐covid‐19.html [ Google Scholar ]
• Verikios, G. , Sullivan, M. , Stojanovski, P. , Giesecke, J. , & Woo, G. (2016). Assessing regional risks from pandemic influenza: A scenario analysis . The World Economy , 39 ( 8 ), 1225–1255. 10.1111/twec.12296 [ CrossRef ] [ Google Scholar ]
• Wernau, J. , & Gasparro, A. (2020, October 5), People are eating healthier and cooking more, food execs say . The Wall Street Journal . https://www.wsj.com/articles/consumers‐are‐eating‐healthier‐and‐cooking‐more‐food‐execs‐say‐11601926763
• Witteveen, D. (2020). Sociodemographic inequality in exposure to COVID‐19‐induced economic hardship in the United Kingdom . Research in Social Stratification and Mobility , 69 , 100551. 10.1016/j.rssm.2020.100551 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Yap, S. F. , Xu, Y. , & Tan, L. (2021). Coping with crisis: The paradox of technology and consumer vulnerability . International Journal of Consumer Studies , 45 , 1239–1257. 10.1111/ijcs.12724 [ CrossRef ] [ Google Scholar ]
• Yeung, R. , & Yee, W. M. (2012). Food safety concern: Incorporating marketing strategies into consumer risk coping framework . British Food Journal , 114 ( 1 ), 40–53. 10.1108/00070701211197356 [ CrossRef ] [ Google Scholar ]

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Unconscious drivers of consumer behavior: an examination of the effect of nature–nurture interactions on product desire.

1. Introduction

2. review of related studies, 2.1. the effect of nature on consumer behavior, 2.2. the effect of nurture on consumer behavior, 2.3. the nature–nurture interaction and consumer behavior, 2.4. the effect of environmental conditions on the drive to beautify, 2.5. the effect of environmental conditions on appetite and food preference, 2.6. the effect of early childhood environments on adult consumer behavior, 3. the current study, 4.1. participants, 4.2. procedures for experiment 1: female product desire, 4.3. analysis procedure for experiment 1: female product desire, 4.4. results for experiment 1: female product desire, 4.4.1. female beauty-signalling products, the effect of social conditions on desire for female beautifying products, the effect of financial conditions on desire for female beautifying products, the effect of perceived physical safety on desire for female beautifying products, 4.4.2. female wealth-signalling products, the effect of social conditions on desire for female wealth-signalling products, the effect of financial conditions on desire for female wealth-signalling products, the effect of perceived physical safety on desire for female wealth-signalling products, 4.5. procedure for experiment 2: male product desire, 4.6. analysis for experiment 2: male product desire, 4.6.1. male toughness-signalling products, the effect of social conditions on desire for male toughness-signalling products, the effect of financial conditions on desire for male toughness-signalling products, the effect of perceived physical safety on desire for male toughness-signalling products, 4.6.2. male wealth-signalling products, the effect of social conditions on desire for male wealth-signalling products, the effect of financial conditions on desire for male wealth-signalling products, 5. discussion, 6. study limitations, 7. practical and theoretical implications, 8. conclusions, supplementary materials, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

• Ramsey, D. The Total Money Makeover: A Proven Plan for Financial Fitness ; Thomas Nelson: Nashville, TN, USA, 2013. [ Google Scholar ]
• Avery, A.J. Commentary: Ineffectiveness of Commercial Weight-Loss Programs for Achieving Modest but Meaningful Weight Loss: Systematic Review and Meta-Analysis. Front. Public Health 2018 , 6 , 67. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Brown, D.T.; Link, C.R.; E Staten, M. The Success and Failure of Counseling Agency Debt Repayment Plans. East. Econ. J. 2011 , 38 , 99–117. [ Google Scholar ] [ CrossRef ]
• Hague, B.; Hall, J.; Kellett, S. Treatments for compulsive buying: A systematic review of the quality, effectiveness and progression of the outcome evidence. J. Behav. Addict. 2016 , 5 , 379–394. [ Google Scholar ] [ CrossRef ]
• Ramos, R.G.; Olden, K. Gene-Environment Interactions in the Development of Complex Disease Phenotypes. Int. J. Environ. Res. Public Health 2008 , 5 , 4–11. [ Google Scholar ] [ CrossRef ]
• Durante, K.M.; Griskevicius, V. Evolution and consumer behavior. Curr. Opin. Psychol. 2016 , 10 , 27–32. [ Google Scholar ] [ CrossRef ]
• Wang, Y.; Griskevicius, V. Conspicuous Consumption, Relationships, and Rivals: Women’s Luxury Products as Signals to Other Women. J. Consum. Res. 2014 , 40 , 834–854. [ Google Scholar ] [ CrossRef ]
• Hill, S.E.; Rodeheffer, C.D.; Griskevicius, V.; Durante, K.; White, A.E. Boosting beauty in an economic decline: Mating, spending, and the lipstick effect. J. Pers. Soc. Psychol. 2012 , 103 , 275–291. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Griskivicius, V.; Akerman, J.M.; Redden, J.P. Applied Evolutionary Psychology: Why We Buy: Evolution, Marketing, and Consumer Behavior ; Oxford University Press: New York, NY, USA, 2012; Chapter 19; pp. 311–329. [ Google Scholar ]
• Recession Graduates: The Long-Lasting Effects of an Unlucky Draw. Stanford Institute for Economic Policy Research (SIEPR). Available online: https://siepr.stanford.edu/publications/policy-brief/recession-graduates-long-lasting-effects-unlucky-draw (accessed on 27 June 2024).
• Murgea, A. Lipstick Effect In Romania: Propensity To Buy Cosmetics And Stock Market Evolutions. Ann. Univ. Apulensis Ser. Oeconomica 2012 , 2 , 512–525. [ Google Scholar ] [ CrossRef ]
• van Baardwijk, M.; Franses, P.H. The Hemline and the Economy: Is There Any Match? Economic Institute: Washington, DC, USA, 2010. [ Google Scholar ]
• Swaffield, J.; Roberts, S.C. Exposure to Cues of Harsh or Safe Environmental Conditions Alters Food Preferences. Evol. Psychol. Sci. 2015 , 1 , 69–76. [ Google Scholar ] [ CrossRef ]
• Swaffield, J.B.; Guo, Q. Environmental stress effects on appetite: Changing desire for high- and low-energy foods depends on the nature of the perceived threat. Evol. Mind Behav. 2020 , 18 , 1–13. [ Google Scholar ] [ CrossRef ]
• Nettle, D.; Andrews, C.; Bateson, M. Food Insecurity as a Driver of Obesity in Humans: The Insurance Hypothesis. Behav. Brain Sci. 2016 , 40 , 11–34. [ Google Scholar ] [ CrossRef ]
• Born, J.M.; Lemmens, S.G.T.; Rutters, F.; Nieuwenhuizen, A.G.; Formisano, E.; Goebel, R.; Westerterp-Plantenga, M.S. Acute stress and food-related reward activation in the brain during food choice during eating in the absence of hunger. Int. J. Obes. 2009 , 34 , 172–181. [ Google Scholar ] [ CrossRef ]
• Dressler, H.; Smith, C. Food choice, eating behavior, and food liking differs between lean/normal and overweight/obese, low-income women. Appetite 2013 , 65 , 145–152. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Schaller, M.; Kenrick, D.T.; Neel, R.; Neuberg, S.L. Evolution and Human Motivation: A Fundamental Motives Framework ; John Wiley & Sons Ltd.: Oxford, UK, 2017. [ Google Scholar ]
• Sapolsky, R.M. Determined: A Science of Life without Free Will ; Penguin Press: New York, NY, USA, 2023. [ Google Scholar ]
• Boyland, E.J.; Nolan, S.; Kelly, B.; Tudur-Smith, C.; Jones, A.; Halford, J.C.; Robinson, E. Advertising as a cue to consume: A systematic review and meta-analysis of the effects of acute exposure to unhealthy food and nonalcoholic beverage advertising on intake in children and adults. Am. J. Clin. Nutr. 2016 , 103 , 519–533. [ Google Scholar ] [ CrossRef ]
• Government of Canada. Canada.ca. Available online: https://www.canada.ca/en/health-canada/services/food-nutrition/healthy-eating-strategy/policy-update-restricting-food-advertising-primarily-directed-children.html (accessed on 20 June 2023).
• TFl Junk Food Ads Ban Will Tackle Child Obesity. London City Hall. Available online: https://www.london.gov.uk/programmes-strategies/communities-and-social-justice/food/tfl-junk-food-ads-ban-will-tackle-child-obesity (accessed on 29 October 2022).
• A Ban on Junk Food in Mexico. Euromonitor. Available online: https://www.euromonitor.com/article/a-ban-on-junk-food-in-mexico (accessed on 16 September 2020).
• Vasiliu, O. Therapeutic management of buying/shopping disorder: A systematic literature review and evidence-based recommendations. Front. Psychiatry 2022 , 13 , 1047280. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• De Waal, F. Different: Gender through the Eyes of a Primatologist ; W.W. Norton & Company: New York, NY, USA, 2023. [ Google Scholar ]
• Griskevicius, V.; Ackerman, J.M.; Cantú, S.M.; Delton, A.W.; Robertson, T.E.; Simpson, J.A.; Thompson, M.E.; Tybur, J.M. When the Economy Falters, Do People Spend or Save? Responses to Resource Scarcity Depend on Childhood Environments. Psychol. Sci. 2013 , 24 , 197–205. [ Google Scholar ] [ CrossRef ]
• Swaffield, J.B.; Guo, Q. How Childhood Socioeconomic Status Impacts Adult Food Preference: The Mediating Role of Stress and Trait Appetite. Behav. Sci. 2022 , 12 , 202. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Arbore, A.; Soscia, I.; Bagozzi, R. The Role of Signaling Identity in the Adoption of Personal Technologies. J. Assoc. Inf. Syst. 2014 , 15 , 86–110. [ Google Scholar ] [ CrossRef ]
• Berger, J.; Ward, M. Subtle Signals of Inconspicuous Consumption. J. Consum. Res. 2010 , 37 , 555–569. [ Google Scholar ] [ CrossRef ]
• Kassim, N.M.; Bogari, N.; Salamah, N.; Zain, M. Product status signaling as mediator between materialism and product satisfaction of Saudis and Malaysians. Soc. Behav. Pers. Int. J. 2016 , 44 , 973–985. [ Google Scholar ] [ CrossRef ]
• Trigg, A.B. Veblen, Bourdieu, and Conspicuous Consumption. J. Econ. Issues 2001 , 35 , 99–115. [ Google Scholar ] [ CrossRef ]
• Berger, J.; Heath, C. Where Consumers Diverge from Others: Identity Signaling and Product Domains. J. Consum. Res. 2007 , 34 , 121–134. [ Google Scholar ] [ CrossRef ]
• Van Kempen, L. Fooling the eye of the beholder: Deceptive status signalling among the poor in developing countries. J. Int. Dev. 2003 , 15 , 157–177. [ Google Scholar ] [ CrossRef ]
• Han, Y.J.; Nunes, J.C.; Drèze, X. Signaling Status with Luxury Goods: The Role of Brand Prominence. J. Mark. 2010 , 74 , 15–30. [ Google Scholar ] [ CrossRef ]
• White, K.; Argo, J.J.; Sengupta, J. Dissociative versus Associative Responses to Social Identity Threat: The Role of Consumer Self-Construal. J. Consum. Res. 2012 , 39 , 704–719. [ Google Scholar ] [ CrossRef ]
• Saad, G. The Evolutionary Bases of Consumption ; Lawrence Erlbaum Associates, Inc.: Mahwah, NJ, USA, 2007. [ Google Scholar ]
• Lewis, D.M.G.; Russell, E.M.; Al-Shawaf, L.; Ta, V.; Senveli, Z.; Ickes, W.; Buss, D.M. Why Women Wear High Heels: Evolution, Lumbar Curvature, and Attractiveness. Front. Psychol. 2017 , 8 , 1875. [ Google Scholar ] [ CrossRef ]
• Galbarczyk, A.; Ziomkiewicz, A. Tattooed men: Healthy bad boys and good-looking competitors. Pers. Individ. Differ. 2017 , 106 , 122–125. [ Google Scholar ] [ CrossRef ]
• Giebel, G.; Moran, J.; Schawohl, A.; Weierstall, R. The thrill of loving a dominant partner: Relationships between preference for a dominant mate, sensation seeking, and trait anxiety. Pers. Relationships 2015 , 22 , 275–284. [ Google Scholar ] [ CrossRef ]
• Heywood, W.; Patrick, K.; Smith, A.M.; Simpson, J.M.; Pitts, M.K.; Richters, J.; Shelley, J.M. Who Gets Tattoos? Demographic and Behavioral Correlates of Ever Being Tattooed in a Representative Sample of Men and Women. Ann. Epidemiology 2012 , 22 , 51–56. [ Google Scholar ] [ CrossRef ]
• Wingrove, S.; Paek, J.J.W.; de Leon, R.P.; Fitzsimons, G.M. Tying the value of goals to social class. J. Pers. Soc. Psychol. 2023 , 125 , 699–719. [ Google Scholar ] [ CrossRef ]
• Matud, M.P.; Bethencourt, J.M.; Ibáñez, I. Gender differences in psychological distress in Spain. Int. J. Soc. Psychiatry 2014 , 61 , 560–568. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Salafia, E.H.B.; Lemer, J.L. Associations Between Multiple Types of Stress and Disordered Eating Among Girls and Boys in Middle School. J. Child Fam. Stud. 2011 , 21 , 148–157. [ Google Scholar ] [ CrossRef ]
• Balhara, Y.S.; Verma, R.; Gupta, C. Gender differences in stress response: Role of developmental and biological determinants. Ind. Psychiatry J. 2011 , 20 , 4–10. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Miller, G. The Mating Mind: How Sexual Choice Shaped the Evolution of Human Nature ; Anchor Books: New York, NY, USA, 2001. [ Google Scholar ]
• Sundie, J.M.; Kenrick, D.T.; Griskevicius, V.; Tybur, J.M.; Vohs, K.D.; Beal, D.J. Peacocks, Porsches, and Thorstein Veblen: Conspicuous consumption as a sexual signaling system. J. Pers. Soc. Psychol. 2011 , 100 , 664–680. [ Google Scholar ] [ CrossRef ]
• Buss, D.M. The Evolution of Desire: Strategies of Human Mating ; Basic Books: New York, NY, USA, 2016. [ Google Scholar ]
• Bryan, A.D.; Webster, G.D.; Mahaffey, A.L. The Big, the Rich, and the Powerful: Physical, Financial, and Social Dimensions of Dominance in Mating and Attraction. Pers. Soc. Psychol. Bull. 2011 , 37 , 365–382. [ Google Scholar ] [ CrossRef ]
• Sapolsky, R. Behave: The Biology of Humans at Our Best and Worst ; Vintage: London, UK, 2017. [ Google Scholar ]
• Wieczorek, L.L.; Chivers, M.; Koehn, M.A.; DeBruine, L.M.; Jones, B.C. Age Effects on Women’s and Men’s Dyadic and Solitary Sexual Desire. Arch. Sex. Behav. 2022 , 51 , 3765–3789. [ Google Scholar ] [ CrossRef ]
• Bodenmann, G.; Atkins, D.C.; Schär, M.; Poffet, V. The association between daily stress and sexual activity. J. Fam. Psychol. 2010 , 24 , 271–279. [ Google Scholar ] [ CrossRef ]
• Hamilton, L.D.; Meston, C.M. Chronic Stress and Sexual Function in Women. J. Sex. Med. 2013 , 10 , 2443–2454. [ Google Scholar ] [ CrossRef ]
• Hamilton, L.D.; Julian, A.M. The Relationship Between Daily Hassles and Sexual Function in Men and Women. J. Sex Marital. Ther. 2014 , 40 , 379–395. [ Google Scholar ] [ CrossRef ]

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Swaffield, J.B.; Sierra Jimenez, J. Unconscious Drivers of Consumer Behavior: An Examination of the Effect of Nature–Nurture Interactions on Product Desire. Behav. Sci. 2024 , 14 , 789. https://doi.org/10.3390/bs14090789

Swaffield JB, Sierra Jimenez J. Unconscious Drivers of Consumer Behavior: An Examination of the Effect of Nature–Nurture Interactions on Product Desire. Behavioral Sciences . 2024; 14(9):789. https://doi.org/10.3390/bs14090789

Swaffield, Jim B., and Jesus Sierra Jimenez. 2024. "Unconscious Drivers of Consumer Behavior: An Examination of the Effect of Nature–Nurture Interactions on Product Desire" Behavioral Sciences 14, no. 9: 789. https://doi.org/10.3390/bs14090789

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• DOI: 10.55041/ijsrem28211
• Corpus ID: 267048425

A Case Study on the Impact of Brand Image on Customer Buying Behaviour with Special Reference to Nilgiris Supermarket in Mangalore

• Harish S. Pai
• Published in INTERANTIONAL JOURNAL OF… 15 January 2024

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