Understanding Of Consumers Research Articles

Decoding Consumer Minds in the Age of Online Accommodation Reviews: A Client Profiling Approach

In the era of online accommodation reviews, understanding the consumer mind is essential for the hospitality industry. This study seeks to profile consumers based on their reservation decisions made after reviewing online feedback and to explore the complex relationship between consumer perceptions and their decision-making processes. To lay a solid foundation for this research, a thorough bibliometric analysis was conducted to map the existing literature and identify key trends in the field. Data were collected using a non-probability convenience sampling method through an online survey targeting Romanian residents. Performing a hierarchical cluster analysis, followed by a K-means cluster analysis, distinct consumer segments with varying levels of trust and responsiveness were identified. The four primary clusters are Young Risk-Averse Planners, Trust-Oriented Quality Seekers, Skeptical Detail Seekers and Independent Value Seekers. Each segment displayed unique preferences regarding the types of reviews they value and their influence on booking decisions. These findings highlight the need for hotel managers and marketers to develop tailored strategies that cater to the diverse needs of consumers, enhancing service delivery and promoting sustainable tourism practices. This research provides valuable insights into the dynamics of online reviews and stresses the importance of understanding consumer perceptions in navigating the complexities of today’s hospitality industry.

What Do Chinese Guests Want for a Five-Star Hotel Guestroom?

ABSTRACT This study attempts to develop a comprehensive understanding of consumer needs of guest room design in the context of five-star hotels in China. Applying the Kano model and SOR framework, four studies were conducted, namely, a user-generated content (UGC) based semantic association analysis (N = 13,942), in-depth interviews with hotel designers (N = 20), affinity diagrams (N = 4) and online guest surveys using the Kano questionnaire (N = 1,220). The findings of these studies indicate that a hotel room design evaluation must include comfort, convenience, function, and gratification. The Kano model revealed that functional and dysfunctional factors impact customers’ levels of satisfaction differently. In addition, guests’ satisfaction with guest rooms is also influenced by their travel purposes. The mixed-methods approach revealed both explicit and implicit room needs from the perspectives of guests, hotel designers, and management, which can help managers focus more on the neglected demands of customers and has implications for innovative room design in five-star hotels.

Panic Buying: A Theoretical and Conceptual Review

Purpose: Panic buying is a consumer behaviour that can be complex to explain in critical, urgent, uncertain and crisis situations. This phenomenon has yet to be fully explored in research on consumer behaviour, and further investigation is required across a range of scientific fields. Panic buying may have many causes and consequences. Determining the causes of panic buying and understanding consumer psychology in crisis and disaster situations in terms of various theories can guide government officials, businesses, marketing practitioners and researchers in case it occurs again in consumer behaviour in the future. This study aims to conduct a conceptual and theoretical examination of panic buying and to focus on its causes. Material and Method: Panic buying was discussed conceptually and theoretically within the framework of the literature review and inferences were made. Findings: This study focuses on the conceptual and theoretical examination of panic buying and its causes. Theories such as Compensatory Control Theory, Social Influence Theory, Social Proof Theory, Scarcity Theory, Herd Behavior, Survival Psychology and Motivation Theory have been intensively the subject of studies on panic buying. It is more common in the literature to try to explain the reasons for panic buying during situations such as crises, pandemics and disasters. Results: Consumers who panic buy should be measured more in terms of their post-purchase feelings such as regret, sadness, empathy, satisfaction, and their intention to panic buying again. In addition, which marketing messages and strategies are more likely to cause panic buying and which strategies are more useful in controlling panic buying are also recommended for future research.

Consumer attitudes, willingness to pay and hedonic evaluations of innovative legume gnocchi products.

With growing concerns over the adverse effects of animal-derived products on health, animal welfare and the environment, the rising popularity of plant-based foods underscores the importance of understanding consumer preferences and determining acceptance. The present study takes the form of a case study that utilized innovative legume-based flours to develop multiple gnocchi products. The Becker-DeGroot-Marschak (BDM) mechanism as an auction method was employed to elicit consumers' willingness to pay (WTP) following a hedonic evaluation test involving 127 Spanish consumers. The findings indicate that a majority of consumers exhibit a high level of environmental concern, coupled with increased trust in, as well as perceptions of, the benefits of consuming plant-based products. However, they demonstrated moderate attitudes with regard to plant-based products. Notably, product sample tasting had a negative impact on consumers' WTP for legume-based gnocchi. The respondents' education level, income, financial situation, government support, environmental concerns, perceived risks, flavor and color significantly influenced consumers' WTP. The present study offers initial insights into consumer attitudes and WTP for legume-based products in Spain. The findings are of relevance for producers and marketers aiming to promote environmentally-sustainable food production and consumption. They may also play a pivotal role in facilitating the successful introduction and sale of such plant-based products in the Spanish market. Going forward, addressing any limitations of this study and exploring further research avenues will be crucial for refining our understanding of consumer behavior in this context. © 2024 The Author(s). Journal of the Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Implication of Characteristic-Based Adoption Model to Private Label Product in Malaysian Hypermarket

The rise of private label products has reshaped retail landscapes globally, challenging the dominance of national brands across various sectors, particularly in fast-moving consumer goods and groceries. While PLs have gained substantial market share in regions like Europe and North America, their adoption in developing markets, such as Asia, remains limited. Attempts to replicate European PL success in Asia have often faltered, highlighting the need for tailored approaches to navigate unique market dynamics. Fong and partners proposed a characteristic-based adoption model specifically for PL products in Malaysian hypermarkets, emphasizing the importance of understanding consumer responses through the perspective of Diffusion of Innovation theory. This study aims to explore the implications of Fong and partners’ model in Asian hypermarkets, offering insights to enhance PL market share. By examining the applicability of this model in the Malaysian context, this research contributes to a deeper understanding of PL adoption dynamics in developing markets and informs strategies for retailers to compete effectively in these environments.

A Cutting Edge Review of Cross-Cultural Marketing and Consumer Behaviour Analysis - A Data-Driven Strategy

Cross-cultural marketing faces unprecedented challenges and opportunities in the context of globalisation and digitalisation. This paper provides an overview of key topics in cross-cultural marketing, discusses the importance of consumer behaviour analysis, and focuses on the application of data-driven marketing strategies in cross-cultural marketing. Through in-depth research and case studies, this paper reveals the key role of data in understanding consumer needs, optimising marketing strategies and improving market competitiveness, providing effective strategic advice and practical guidance for international companies.

Willingness to Pay in Tourism and Its Influence on Sustainability

Financial support for environmental causes is more urgent than ever before. Thus, understanding consumer willingness to pay (WTP) for tourism is vital for policymakers, businesses, and researchers. This bibliometric study examined the trend of research on willingness to pay and tourism using 428 articles published in the Scopus indexed database between 1994 and 2023. The articles were extracted using the keywords “Willingness to pay tourism”. A Microsoft Excel sheet was used in the descriptive analysis, and a VOSviewer version 1.6.20 was used for the citation and co-occurrence analysis. The study found that willingness to pay is a complex aspect of environmental economics and tourism behaviour that is shaped by various aspects. Amongst other things, willingness to pay is shaped by aspects such as tourist biogeography, amongst others is the level of environmental awareness, environmental sensitivity, and education. In many respects, it is shaped by demographic factors such as age, gender, income bracket, and area of origin. Even though the major thrust of willingness to pay was anchored on sustainability and environmental protection, recent events in the mold of climate change, the COVID-19 pandemic, and technological innovation have played major roles in shaping tourists’ behaviour. Given the emerging thrust and focus, there is a need to respond to geographic knowledge gaps in tourism hotspots to understand how this will shape tourism sustainability from a Sustainable Development Goals (SDG) perspective going forward. In doing so, it will be critical to ensure continued fostering and understanding of how tourists’ willingness to pay for tourism destinations can lead to better design, marketing, and managed services to create memorable experiences that drive consumer loyalty.

Role of Social Capital in Building Financial Resilience

Global climate change has created an urgent need to promote the transformation of green economy. This study adopted the social capital theory as a framework, and the banking industry plays a central role in this process, not only to identify the current development of green finance in Taiwan through green financial products but also to understand the attitudes of different customers towards green finance. This study aims to understand the relationship between banks and diversified communities through social capital, promote the innovation and application of green technologies, and integrate external resources to facilitate multi-party collaboration. The study was analysed and evaluated using the latest versions of SPSS 26 and Smart PLS 4.0, with a total sample size of 501 respondents. The results demonstrate that financial resilience has a positive impact on social capital, while carboxylic acid has a positive effect on usage intention. Consequently, this study proposes that the social capital theory is a valuable tool for understanding consumer intentions regarding green finance.

A Hybrid Parameters Estimation Approach for Power Consumption Modeling of Ground Mobile Robots With Unknown Payload

ABSTRACTTypically, batteries are the main power source for mobile robots, and the practical constraints in carrying them pose challenges in achieving efficiency, autonomy, and safety objectives in robotic missions. Moreover, dealing with battery degradation requires a precise understanding of energy consumers' behavior in the system. Therefore, establishing an energy consumption model has an important role in addressing these challenges. This study focuses on the modeling and estimation of power consumption in indoor ground mobile robots with unknown payloads. We investigate key components and parameters that influence the actuation energy consumption of ground mobile robots equipped with DC motors, particularly in the context of pure rolling without slipping. To estimate the actuation power consumption of ground mobile robots, we present a hybrid parameters estimation approach. This method includes an offline step for estimating the mass‐decoupled coefficients of a power model, followed by two online steps for estimating the robot's unknown payload and its actuation power consumption. Simulation and experimental results with a differential drive robot (Turtlebot3) validate the effectiveness of the proposed approach. Additionally, the performance of the proposed power consumption estimation method is compared with two other data‐driven models based on multivariate linear regression and multilayer perceptron neural networks. The results demonstrate that the proposed method provides improved power consumption estimation accuracy on the selected indicators compared to the others. We also emphasize the importance of balancing the accuracy of power consumption estimation with its associated costs in the context of the proposed approach. This extra cost includes the energy needed for additional data measurement and processing. Considering this trade‐off is crucial for the practical implementation and resource optimization in robotic systems.

Blockchain empowerment: enhancing consumer trust and outreach through supply chain transparency

Despite the growing interest in blockchain for supply chain transparency, a gap remains in understanding consumer perceptions and attitudes toward blockchain-supported initiatives. This study examines how consumers perceive blockchain's role in enhancing supply chain transparency, the factors influencing consumer trust in blockchain-enabled transparency, and the implications for consumer engagement and behaviour within the supply chain network. Through a scenario-based experiment, we find that technology-supported transparency enhances consumer trust not only in the focal firm but also in various stakeholders involved. Specifically, consumers exhibit higher trust in retailers and other stakeholders when firms adopt decentralised transparency systems compared to centralised ones. Decentralised technology-supported transparency significantly influences consumers’ decisions to interact directly with stakeholders, shifting their preference toward responsible supply chain actors over focal firms. While multi-stakeholder transparency does not directly affect consumers’ purchase intentions, high trust in the technology positively influences their intention to purchase. Our study provides actionable managerial insights, guiding decision-makers in adopting decentralised transparency practices to strengthen stakeholder relationships and align with consumer expectations. By understanding the nuances of consumer trust in technology-supported transparency, firms can make more informed strategic decisions, ultimately enhancing the overall performance of their supply chains.

The decision-making process to consume sustainable food

An in-depth understanding of consumers’ decision-making in the sustainable food consumption is a crucial prerequisite for effective environmental, social and governance (ESG) management. The heuristic-systematic (HS) model appears to be useful for deepening our understanding of it. This study examines consumer (i.e., 600 Millennials and Generation Z (MZ) consumers in the middle-income class) reaction to the HS stimuli in the green domain. With eco-friendly eggs and plant-based eggs in the experiments, the MANOVA results showed that overall, S outperformed H in many aspects, but it was important to deliver real benefits that people can feel more closely everyday life.

Designing a Business Strategy Using Business Model Canvas (BMC) on Product Newcomer Gyura Hijab

In the dynamic and ever-evolving fashion industry, newcomers face significant challenges, particularly in crafting effective business strategies. This study aims to evaluate the feasibility of Gyura Hijab's business plan through an entrepreneurial lens and to analyze the development of a business strategy using the Business Model Canvas (BMC) framework. It focuses on understanding consumer preferences, hijab fashion trends, and aspirations for a modern lifestyle as a foundation for designing products and marketing strategies. The research employs a case study approach with qualitative methods to gain in-depth insights. A comprehensive SWOT analysis was conducted, supported by qualitative data collection and analysis to understand the internal and external factors influencing Gyura Hijab's business strategy. The findings indicate that Gyura Hijab is strategically positioned to expand its business through initiatives such as opening new branches in different regions with unique concepts and products. The company plans to develop a Budget Plan (RAB) for new stores with distinct decorations, products, and partnerships. It also aims to launch partnership programs as a promotional strategy, foster collaborations with loyal customers, and implement more aggressive marketing tactics both online and offline. This study contributes to the practical understanding of utilizing the BMC framework for business development in the hijab fashion industry. The novelty lies in tailoring the BMC framework to the specific needs of a hijab fashion business, providing actionable insights for practitioners and aspiring entrepreneurs in the industry.

Studying the Impact of Changing Consumer Behavior During Crisis Periods Through Store Classification

Since customer behavior changes unpredictably during crisis periods such as pandemics, many sectors have been affected differently. The retail sector in particular has been one of the most affected sectors. Retail companies that could not determine the right strategies against customer behavior change were in a difficult situation, and some even had to close down. The inability of consumers to do physical shopping for reasons such as socializing, experiencing products and interacting during the pandemic process required an understanding of changing consumer needs. In this study, to determine the changes in customer purchasing behaviors during the pandemic period, using the sales data of a company operating in the women’s clothing sector and whose sales loss approached 50% during the pandemic period, separate stores were divided into clusters using machine learning methods for the pre-pandemic and pandemic period. The clusters formed were examined and the stores in different clusters were determined depending on customer purchasing behavior. The aim of the study is to ensure that the company segments its stores correctly to gain competitive advantage. Firms will be able to determine the right strategies against changing consumer behavior through a correct store segmentation. First, stores that do not belong to any classification group are clustered using unsupervised machine learning methods. No significant change was observed in the clusters formed before and during the pandemic. This indicated that the pandemic had a similar effect on all stores. Then, pre-pandemic, pandemic period and both periods data were analyzed using 7 different machine learning classification algorithms. The results obtained were compared. For all three analyses, the random forest algorithm gave the highest accuracy rate. The random forest algorithm with the highest accuracy was hybridized with 3 different classification algorithms. The hybrid model consisting of random forest and support vector machine gave the highest accuracy rate (90%) for the period including all data for store classification. Thanks to the hybrid model created with random forest and support vector machines, companies can be advantageous against other companies in the competitive environment by creating separate strategies for each store class.

The Influence of Digital Marketing, Product Quality, and Emotional Factors on Consumer Satisfaction

The rapid evolution of digital technology has reshaped marketing approaches, with digital marketing emerging as a cornerstone in connecting brands with consumers. Alongside digital marketing, product quality and emotional factors have gained prominence in shaping consumer satisfaction. This study investigates the interplay between digital marketing, product quality, and emotional factors influencing consumer satisfaction in Indonesian markets. The research aims to evaluate their individual and collective impacts to provide insights for strategic optimization. Using a quantitative approach with a descriptive correlational design, data were collected through an online questionnaire from January to March 2024. A purposive sampling method was employed, targeting 150 respondents across Indonesia who had engaged with brands utilizing digital marketing strategies. The variables were measured using a 5-point Likert scale, and data were analyzed through multiple linear regression using SPSS. The findings reveal significant positive contributions from all three variables. Digital marketing had a regression coefficient of 0.321 (p < 0.001), emphasizing the importance of personalized and interactive strategies. Product quality demonstrated the highest influence with a coefficient of 0.412 (p < 0.001), confirming its critical role in exceeding consumer expectations and fostering loyalty. Emotional factors contributed a coefficient of 0.275 (p = 0.001), underscoring the relevance of positive brand interactions in enhancing satisfaction. The simultaneous effect of these variables was validated through an F-statistic of 42.7 (p < 0.001), with an R² value of 0.72, indicating strong explanatory power. This research provides a holistic framework for understanding consumer satisfaction by integrating digital marketing, product quality, and emotional factors. It recommends prioritizing product quality, optimizing digital marketing strategies, and fostering emotional connections to achieve sustained consumer loyalty. Future studies should explore these dynamics across diverse industries and consumer segments to expand upon these findings.

Optimists, moderates and sceptics – identifying consumer groups and their willingness to consume cultured proteins in Finland

PurposeIt is suggested that the detrimental externalities of intensive livestock production can be reduced by manufacturing animal proteins with cellular agriculture technologies. This study explores consumer attitudes towards cultured proteins based on representative Finnish survey data (n = 1,452).Design/methodology/approachSum variables from the principal component analysis were utilized in the cluster analysis to identify potential consumer groups of cultured proteins in Finland. A regression analysis was used to find out the explanatory factors of positive first reaction, willingness to taste, willingness to use and support for the establishment of a national cultured meat sector.FindingsMost of the respondents (72%) would taste cultured products, but attitudes of optimists (n = 516), moderates (n = 479) and sceptics (n = 457) differ in terms of the environment, livestock farming and cultured proteins. Most optimists (77%), almost quarter (23%) of moderates and less than a fifth (18%) of sceptics support cultured proteins. The environmental concerns are shared by optimists and moderates, whereas moderates and sceptics tend to be more suspicious. Positive attitudes are significantly influenced by social norms and respondents' beliefs regarding their global and national benefits. Major concerns pertain to anticipated dictation force of big companies, negative effects on Finnish agriculture, product attributes, use of genetically modified organisms and experienced (un)naturalness of cultured foods.Originality/valueThis study contributes to the understanding of Finnish consumers' attitudes towards cultured proteins. The identification of potential consumer segments and the elucidation of their attitudes are relevant, given the anticipated acceleration in the development of cultured foods.

Development of a Viewing-Purchase Model for Live Streaming Commerce: A Social Exchange Perspective

Live streaming commerce has rapidly emerged as a key platform in e-commerce, yet the socio-technical mechanisms underlying consumer-platform interactions remain underexplored. This study addresses this gap by examining both task-oriented purchasing behaviors and pleasure-driven engagement through the lens of social exchange theory. A web-based survey was conducted with 300 respondents in South Korea, all of whom had prior experience with live streaming commerce. The data were analyzed using PLS-SEM to evaluate the proposed model. The results reveal that procedural and interactional justice positively affect trust, while co-experience enhances perceived playfulness. Both trust and playfulness, in turn, significantly impact purchase and repeated viewing intentions. These findings provide valuable insights into the dynamics of live commerce, offering a comprehensive model for understanding consumer behavior in the context of live commerce.

Application and Development of Behavioural Economics in Consumer Decision Making

Behavioural economics, as an interdisciplinary field integrating psychology and economics, offers new perspectives for understanding consumer decision-making. This paper provides an overview of the core theories of behavioural economics, its applications in consumer decision making, and its developments and challenges in market practice and policy making. First, behavioural economics challenges traditional economic assumptions about rational decision-making by revealing core concepts such as limited rationality, prospect theory and behavioural biases, providing a deeper understanding of consumer behaviour. Second, the paper explores the effectiveness of behavioural economics in practical applications, such as improving firms' market performance and policy implementation by optimising marketing strategies, utilising personalised recommendations and developing behavioural intervention policies. However, behavioural economics still faces challenges in terms of theoretical universality, cross-cultural applicability and dynamic adaptation. Future research directions include theoretical integration, cross-cultural validation, adaptation to technological developments, optimisation of policy practices and intersection studies with psychology. The review in this paper aims to provide reference for academic research and practical application, to promote the further development of behavioural economics, and to provide theoretical support for policy making and market strategies.

Artificial intelligence in hospitality services: examining consumers’ receptivity to unmanned smart hotels

PurposeWith recent advances in artificial intelligence, the hospitality industry has introduced the concept of unmanned smart hotels staffed by service robots instead of human employees. Research is needed to understand consumers’ receptivity to such an innovation. This paper examines factors associated with consumers’ potential resistance to using automated service hotels via two sequential studies. Given that younger generations of consumers are typically early adopters of advanced technology and innovative services, our sampling approach focused on this consumer group.Design/methodology/approachTwo studies were conducted. Study 1 proposed and empirically tested a theoretical model. Results revealed that attitude, subjective norms and perceived behavioral control each positively influenced individuals’ intentions to use unmanned smart hotels. In Study 2, we further investigated aspects informing perceived security, a key variable in the use of unmanned smart hotels.FindingsFindings showed how people’s beliefs about unmanned smart hotels and security control assurances led to perceived security. These perceptions were shaped by perceived physical risks, privacy concerns, website design and hotel reputation. Overall, this research provides theoretical and practical implications for various stakeholders associated with unmanned smart hotels.Practical implicationsFindings of this study suggested that managers of unmanned smart hotels should design user-friendly, secure processes and offer comprehensive support resources to enhance customer experience and usage.Originality/valueThe findings provide a holistic understanding of consumers’ receptivity to unmanned smart hotels.

Consumer impatience in the e-commerce home delivery context: a consumer-centric supply chain perspective for time-based competition

PurposeThis paper aims to introduce the concept of consumer impatience, empirically explore how it relates to time-based logistics performance (delivery speed and delivery timeliness) and discuss its impact on consumer satisfaction. This research argues that gaining insights related to delivery performance from a consumer’s perspective can help the development of more effective time-based logistics strategies for e-commerce home deliveries.Design/methodology/approachHypotheses in this study are developed using attribution theory and tested with empirical data collected through an online behavioral consumer experiment. Middle-range theorizing is used to develop an understanding of the mechanisms that impact the relationship between time-based logistics performance and consumer satisfaction.FindingsFindings indicate that consumer impatience with delivery speed and delivery timeliness play an essential role in the relationship between time-based delivery performance and consumer satisfaction. Issues with delivery timeliness are shown to have a more negative impact on consumer satisfaction than issues with delivery speed, while delivery communication is demonstrated to have a positive relationship with consumer satisfaction.Originality/valueThis empirical study adds to existing time-based competition literature by taking a consumer-centric perspective and bringing a largely overlooked but critical concept – consumer impatience – into the logistics and supply chain management setting. Middle-range theorizing allows for a conceptualized understanding of consumers’ delivery experiences that can help companies develop proactive actions in their time-based competition initiatives.

Comprehensive framework for understanding consumers’ intentions of artificial intelligence devices in the hospitality industry: a meta-analysis

ABSTRACT Researchers are increasingly interested in consumer acceptance and adoption of artificial intelligence devices, but an integrated approach remains underexplored. This study uses Stimulus-Organism-Response theory as a theoretical framework, builds an integrated model based on 81 empirical studies, and examines the role of macro-moderating variables. The results show that stimulus factors affect consumers’ intentions through central and peripheral pathways. Notably, the study identified differences in the impact of negative and positive factors on consumer intentions and pointed out that culture-related macro-factors play a limited moderating role. Finally, this study provides suggestions for future research by summarising the gaps in previous research and provides practical recommendations for stakeholders in the hospitality industry based on the study conclusions.