Consumer Insights Research Articles

Factors Influencing Young Consumer Trust in Online Purchase Decision of Luxury Perfume in Malaysia: A Preliminary Qualitative Study

This qualitative study aims at investigating the factors influencing young consumer trust towards purchase decision of luxury perfume online. Data were collected through interviewing 5 consumers via real time online chatting method. Data were examined based on content analysis. A preliminary model was then developed as a basis to explain the relationship between the factors extracted, consumer trust and purchase decision. The findings of the study reveal crucial factors which influence consumer trust in purchasing luxury perfume online namely reputation of online sellers, peer customer reviews, recommendation from experts, proof of product authenticity and past experience. The study also incorporates in depth discussion regarding the criteria of reputable sellers. This study discloses meaningful consumer insights regarding motivation towards online shopping, the risks encountered and suggestions for making better purchase decisions. The findings provide invaluable insights for marketers especially those in the luxury perfume industry in Malaysia to devise effective marketing strategy for gaining consumer trust. This study contributes to implementing Sustainable Development Goals (SDG) item 12 emphasizing responsible consumption and production. Findings from this study provide guidelines for consumers in making purchase decisions and to avoid being scammed by online sellers; the findings benefit regulatory bodies in revising policies for protecting consumer rights in Malaysia.

Classification and regression tree approach for the prediction of the seasonal apparel market: focused on weather factors

PurposeClimate change-induced weather changes are severe and frequent, making it difficult to predict apparel sales. The primary goal of this study was to assess consumers' responses to winter apparel searches when external stimuli, such as weather, calendars and promotions arise and to develop a decision-making tool that allows apparel retailers to establish sales strategies according to external stimuli.Design/methodology/approachThe theoretical framework of this study was the effect of external stimuli, such as calendar, promotion and weather, on seasonal apparel search in a consumer's decision-making process. Using weather observation data and Google Trends over the past 12 years, from 2008 to 2020, consumers' responses to external stimuli were analyzed using a classification and regression tree to gain consumer insights into the decision process. The relative importance of the factors in the model was determined, a tree model was developed and the model was tested.FindingsWinter apparel searches increased when the average, maximum and minimum temperatures, windchill, and the previous day's windchill decreased. The month of the year varies depending on weather factors, and promotional sales events do not increase search activities for seasonal apparel. However, sales events during the higher-than-normal temperature season triggered search activity for seasonal apparel.Originality/valueConsumer responses to external stimuli were analyzed through classification and regression trees to discover consumer insights into the decision-making process to improve stock management because climate change-induced weather changes are unpredictable.

The Application of Artificial Intelligence and Big Data in the Food Industry.

Over the past few decades, the food industry has undergone revolutionary changes due to the impacts of globalization, technological advancements, and ever-evolving consumer demands. Artificial intelligence (AI) and big data have become pivotal in strengthening food safety, production, and marketing. With the continuous evolution of AI technology and big data analytics, the food industry is poised to embrace further changes and developmental opportunities. An increasing number of food enterprises will leverage AI and big data to enhance product quality, meet consumer needs, and propel the industry toward a more intelligent and sustainable future. This review delves into the applications of AI and big data in the food sector, examining their impacts on production, quality, safety, risk management, and consumer insights. Furthermore, the advent of Industry 4.0 applied to the food industry has brought to the fore technologies such as smart agriculture, robotic farming, drones, 3D printing, and digital twins; the food industry also faces challenges in smart production and sustainable development going forward. This review articulates the current state of AI and big data applications in the food industry, analyses the challenges encountered, and discusses viable solutions. Lastly, it outlines the future development trends in the food industry.

A computational linguistic analysis of the anatomy of production, consumption, and diffusion of misinformation and authentic information in social media: The case of the COVID-19 pandemic

Social media has become a powerful conduit for misinformation during major public events. As a result, an extant body of research has emerged on misinformation and its diffusion. However, the research is fragmented and has mainly focused on understanding the content of misinformation messages. Little attention is paid to the production and consumption of misinformation. This study presents the results of a detailed comparative analysis of the production, consumption, and diffusion of misinformation with authentic information. Our findings, based on extensive use of computational linguistic analyses of COVID-19 pandemic-related messages on the Twitter platform, revealed that misinformation and authentic information exhibit very different characteristics in terms of their contents, production, diffusion, and their ultimate consumption. To support our study, we carefully selected a sample of 500 widely propagated messages confirmed by fact-checking websites as misinformation or authentic information about pandemic-related topics from the Twitter platform. Detailed computational linguistic analyses were performed on these messages and their replies ( N = 198,750). Additionally, we analyzed approximately 1.2 million Twitter user accounts responsible for producing, forwarding, or replying to these messages. Our extensive and detailed findings were used to develop and propose a theoretical framework for understanding the diffusion of misinformation on social media. Our study offers insights for social media platforms, researchers, policymakers, and online information consumers about how misinformation spreads over social media platforms.

Sensory drivers of liking, emotions, conceptual and sustainability concepts in plant-based and dairy yoghurts

Replacing animal-based protein food products with plant-based protein products is essential for human health and the environment. For this reason, a number of plant-based (PB) yoghurts have been developed to replace dairy yoghurt. However, many of these products suffer from poor sensory quality. In order to improve the quality of these products, data on the sensory drivers of liking, emotional, and conceptual responses to PB yoghurts, PB alternatives (PB blends, PB/dairy blends) and dairy yoghurts are required. In addition, in order to optimise the design of these products for sustainability-oriented consumers, research is needed on the drivers of consumers’ conceptualisations of sustainability. To provide actionable product development guidance on these issues, multi-attribute research was undertaken in a central location test with New Zealand consumers, using a variety of commercial PB and dairy yoghurts (blind sample presentation) that were expanded in their range of sensory attributes through ingredient modifications, with the goal of quasi-replicating and extending prior research on the sensory drivers of liking, emotions, and conceptualisations of PB yoghurts. Results of the research confirmed previous literature findings on the sensory drivers of liking and non-sensory variables in the PB yoghurt space. Among the salient findings related to sensory drivers are that white and lighter coloured yoghurts with smooth and creamy appearance and mouthfeel, sweet taste, and vanilla or coconut flavours maximise liking and positive emotional responses to yoghurt products. In addition, a number of these and other sensory characteristics elicited specific positive conceptualisations of the yoghurts. Although sustainability conceptualisations were evoked less frequently, the major positive drivers of these conceptualisations were “white colour,” “sweet,” “even/smooth” appearance and texture, “oat-like flavour” and “coconut flavour.” “Dairy flavour” evoked conceptualisations related to “traditional” and “authentic,” but also elicited a number of negative sustainability concepts, such as “resource intensive,” “commercially farmed raw materials” and reduced conceptualisation of “animal friendly.” Other important sensory drivers of liking, emotions and conceptualisations are discussed, providing consumer insights and direction to product developers in their efforts to improve the sensory characteristics, acceptance and consumption of PB and other alternative yoghurt products.

Reconsidering the path for neural and physiological methods in consumer psychology

AbstractRecent decades have witnessed a burst of neuroscience research investigating mental and physiological processes central to consumer behavior, including sensory perception, memory, and decision making. Nonetheless, few publications that include neural and physiological measures, or develop conceptual frameworks around neuroscience principles, have been published in consumer psychology. It is clear that “consumer neuroscience” has thus far not lived up to its promises in the marketing literature. We suggest three main reasons for this. First, neural and other biological markers are often mistaken to be identical to the overlaying psychological constructs in traditional consumer psychology work. Second, somewhat surprisingly, there has been an overly narrow utilization of neural data. Most previous work focused on linking existing behavioral phenomena or psychological constructs central to consumer research to neural correlates using brain imaging techniques while ignoring other methods. We argue that much can be gained from improved integration of physiological measures and through them, different levels of analysis. Third, there remain significant structural hurdles to the broad adoption of neural and physiological measures for consumer researchers. We outline how addressing these three components can translate to a more holistic understanding of the consumer via both broader and deeper consumer insights.

OPEN-AMZPRE : Optimized Preprocessing with Ensemble Classification for Amazon Product Reviews Sentiment Prediction

Customer feedback plays a vital role in helping consumers make informed purchasing decisions. Understanding customer opinions and preferences through sentiment analysis is crucial. However, existing sentiment analysis methods face challenges when dealing with noisy, unstructured text data, leading to limitations in accuracy, precision, recall, and F1-score. To address these limitations, this paper introduces OPEN-AMZPRE, an innovative solution for sentiment prediction in Amazon Product Reviews. Unlike traditional approaches that rely on standard techniques like tokenization and stopword removal, OPEN-AMZPRE utilizes a comprehensive preprocessing pipeline. This pipeline includes various steps such as text normalization, lowercasing, handling rare words, expanding contractions, removing HTML tags, tokenization, removing stopwords, replacing slang words, removing digits, stemming, lemmatization, punctuation and special character removal, white space removal, spell checking and correction, and removal of duplicate text. Additionally, the proposed algorithm employs an ensemble classification approach by combining optimized versions of K-Nearest Neighbors (KNN), Naive Bayes, J48 (C4.5 decision tree), and Random Forest classifiers. The hyperparameters of each classifier are tuned to achieve optimal accuracy and performance. By combining the outputs of these classifiers, the algorithm produces robust sentiment predictions. The methods of accuracy, precision, recall, and F1-score are utilized to improve sentiment prediction and provide valuable insights for both consumers and businesses in relation to Amazon Product Reviews.

Exploring the role of consumer ethnocentrism in predicting the purchase intention for locally produced organic food in an emerging market

PurposeThe current study investigates the role of consumer ethnocentrism (CE) in the context of locally produced organic food. This research work further extends the extended theory of planned behavior (TPB) model by examining the mediating effect of extended TPB variables (ATT, SN, PBC, PV) between CE and PI for locally produced organic food.Design/methodology/approachData were obtained from the visitors of two shopping malls situated in a large, heavily populated city of India using survey method. Further, two-step approach was applied to analyze the hypothesized model.FindingsFindings indicate that CE is a substantial determinant of PI for locally produced organic food. Moreover, extended TPB mediates the relation between CE and PI for locally produced organic food.Practical implicationsPost Covid-19, market size of organic food is rapidly growing in India. In this regard, this study presents useful implications for the marketers of organic food for gaining better consumer insights to further develop appropriate marketing strategies.Originality/valueCE has been found to be a useful predictor of their food attitudes. However, studies, investigating the role of CE in the context of sustainable food consumption, are scant. Moreover, studies exploring the mediating effect of extended TPB variables are also very limited.

Exploring Consumer and Producer Views of Verjuice: A Grape-Based Product Made from Viticultural Waste

The wine sector is actively working to add value, increase sustainability, and reduce waste streams. One great example is to use thinned grapes, that are usually left to rot, to make verjuice. As verjuice has no identity standard, there is a wide scope for producers to innovate. Decisions regarding sensory characteristics and packaging are currently made by the verjuice producers, mainly winegrowers and winemakers but also chefs, without fully understanding the needs and wants of consumers. Using discussion groups and interviews, this study explored both consumer and producer views towards commercial verjuice regarding perceived sensory characteristics, possible end-uses, packaging, and desirable label elements. Similarities and differences were discovered between consumer views and verjuice producer practices. Consumers reported a diverse range of attributes beyond the sourness and sweetness that was the focus of producers, indicating potential for a broader range of applications of verjuice than currently considered. Sweeter variants were generally preferred for drinking, while sourer ones were favoured for cooking, although exceptions to this trend existed across consumers. Additionally, a mismatch between producer packaging choices and consumer preferences was identified, highlighting potential for producers to optimise packaging to better cater to consumer needs. This research explored an opportunity to create verjuice with desirable sensory characteristics for specific end-uses, providing product diversification for the wine industry’s revenue stream. Uncovering these consumer insights is key to better inform promotion of verjuice by producers and the agrifood sector seeking to enhance the value of their by-products.

Bibliometric Analysis of Eco-Friendly Practices in Contemporary Popular Culture

This study undertakes a thorough bibliometric examination of environmentally conscious behaviors in modern popular culture. By applying sophisticated bibliometric techniques and citation analysis, the research reveals important publication patterns, prolific writers, recurring themes, and seminal works in the multidisciplinary domain. The findings show a consistent increase in scholarly output, with significant peaks occurring in tandem with major world events and cultural movements. The discourse's interdisciplinary nature is emphasized by prolific writers and cooperative networks, while thematic clusters including consumer perspectives, green synthesis, and sustainability are revealed through keyword analysis. The ongoing importance of foundational research is highlighted by highly referenced works such as the mainstreaming of green product developments, the idea of planned behavior in green hotels, and the investigation of the Mediterranean diet. In addition to suggesting future options, such as greater consumer insights, breakthroughs in green synthesis, and investigation of sustainable business practices, the research offers cross-cluster insights that highlight the interdependence of topics. In summary, this research provides a sophisticated comprehension of environmentally conscious behaviors in popular culture, providing insightful information to scholars, instructors, and professionals across various disciplines.

A review of GPT Chat applications in Marketing

The purpose of this research is to determine what are the uses of GPT Chat in Marketing according to the academic literature published between 2020 and 2023? It seeks to analyze the applications of GPT chat in the Marketing industry, achieving: (i) to explain the main characteristics of GPT Chat, based on the collection of information from Open AI; (ii) to identify the advantages and disadvantages of the applications of GPT chat in marketing, based on the review of scientific papers, and (iii) to compare the applications of GPT chat in marketing. To this end, a qualitative research was developed with a descriptive scope based on the review of literature indexed in EBSCO, Science Direct and Google Scholar between 2020 and 2023, specifically 30 papers. This provided evidence that GPT chat can be used for content creation, consumer insight, personalized marketing strategy development, segment targeting, copywriting, market research, report development and cost reduction. Despite the advantages of GPT Chat, its implementation faces great challenges, due to the lack of knowledge about its scope and social impact, causing people to feel mistrust about its reliability.

Business Conditions in OECD Countries (2010-2019): A Longitudinal Analysis Applying Machine Learning

The purpose of this research is to determine what are the uses of GPT Chat in Marketing according to the academic literature published between 2020 and 2023? It seeks to analyze the applications of GPT chat in the Marketing industry, achieving: (i) to explain the main characteristics of GPT Chat, based on the collection of information from Open AI; (ii) to identify the advantages and disadvantages of the applications of GPT chat in marketing, based on the review of scientific papers, and (iii) to compare the applications of GPT chat in marketing. To this end, a qualitative research was developed with a descriptive scope based on the review of literature indexed in EBSCO, Science Direct and Google Scholar between 2020 and 2023, specifically 30 papers. This provided evidence that GPT chat can be used for content creation, consumer insight, personalized marketing strategy development, segment targeting, copywriting, market research, report development and cost reduction. Despite the advantages of GPT Chat, its implementation faces great challenges, due to the lack of knowledge about its scope and social impact, causing people to feel mistrust about its reliability.

Electric vehicle (EV) and driving towards sustainability: Comparison between EV, HEV, PHEV, and ICE vehicles to achieve net zero emissions by 2050 from EV

This study explores the environmental and economic implications of Internal Combustion Engine (ICE) vehicles, Hybrid Electric Vehicles (HEVs), Plug-in Hybrid Electric Vehicles (PHEVs), and Electric Vehicles (EVs). A case study in Indonesia is selected, focusing to achieve net zero emissions by 2050 and improve air quality. The research compares key factors such as emission costs, fueling time costs, maintenance costs, and vehicle selection for a comprehensive understanding of each vehicle type's viability in the automotive landscape. The analysis reveals that EVs exhibit the lowest CO and CO2 emissions of about 20 %, while HEVs and PHEVs demonstrate significant reductions compared to ICE vehicles. However, EVs produce higher NOx and N2O emissions of more than 70 %, indicating a dependence on fossil fuels for electricity generation. Air quality-related emissions, including SOx and PM10, are 90 % and 85 % higher in EVs, emphasizing the need for enhanced emission control technologies and the adoption of renewable energy sources. Despite their higher selling price and emission costs, EVs possess the lowest maintenance costs among the evaluated vehicles at only 0.00419 USD/km. Ultimately, HEVs present the most balanced combination of selling price, emission cost, and maintenance cost, making them an appealing option for the market. This study provides valuable insights for policymakers, automotive manufacturers, and consumers in transitioning towards more sustainable transportation solutions.

Ornamental Rhizoma Peanut: Perceptions and Use by Florida Consumers

Ornamental rhizoma peanut (Arachis glabrata Benth.; ORP) is a low-maintenance groundcover for use in urban and residential landscapes. Despite its availability since 2002, consumer insights on ORP have never been assessed. Online surveys are readily accepted by academic researchers as a valuable research tool. An online survey was distributed to 5820 Floridians with the objective to assess the use and perceptions of ORP by consumers. A total of 907 survey responses were received. Most respondents identified themselves as home gardeners (89%), white (93%), female (75%), and over age 65 (60%). Out of several turfgrass alternative benefits, respondents most valued reducing herbicide/pesticide and fertilizer/water usage and preventing weed establishment (χ2 = 204, df = 6, P < 0.001). The ORP selection purchased by respondents was predominately unknown. Most preferred ORP to flower heavily and frequently and maintain a canopy height below 20 cm in the landscape with infrequent mowing. Survey data show there is a potentially large consumer demand for ORP in Florida, but product availability, branding, and consumer access and engagement with information sources require additional focus in the coming years.

Consumer insights from text analysis

Consumer insights from text analysis

Impact of External and Internal Stimuli on Online Impulsive Buying Behavior: Mediating Role of Hedonic and Utilitarian Shopping Value

Purpose: This study delves into the examination of the multifaceted determinants that impact impulsive purchasing inclinations within the realm of online retail, while simultaneously considering the idiosyncratic disparities in consumer shopping patterns. Theoretical framework: The concept of perceived usefulness (PU) pertains to the degree to which a customer holds the belief that engaging in online purchasing will enhance their ability to carry out transactions effectively. The streamlined layout of a website facilitates user navigation and enhances their ability to access a wide range of information. Method: The research utilises a quantitative survey to collect valuable perspectives from a heterogeneous cohort of internet consumers. The empirical evidence indicates that the presence of external stimuli, namely perceive ease of use and perceive usefulness exerts a substantial influence on impulsive purchasing tendencies. Findings: The present study serves to enhance comprehension regarding the underlying mechanisms that drive impulsive purchasing behaviours in the contemporary digital era. Research, Practical & Social implications: It offers valuable insights for both marketers and consumers who aspire to adeptly navigate the intricate online shopping landscape. Originality: The research problem addressed in this study is the phenomenon of Impact of External and Internal Stimuli on Online Impulsive Buying Behavior: Mediating role of Hedonic and Utilitarian shopping value. this study proposes ideas for guiding government control in public events.

Research on the Impact of ChatGPT on The Economic Development of E-commerce Industry

This article summarizes the impact of the new artificial intelligence technology ChatGPT on the economic development of the e-commerce industry and provides an analysis of two main aspects. Firstly, this paper studies the application mechanism of ChatGPT in the e-commerce industry. By investigating the specific application of ChatGPT on the e-commerce platform, including fine recommendation, intelligent customer service and consumer insight, the potential of ChatGPT in improving the operational efficiency of e-commerce enterprises is revealed. The research results show that ChatGPT can provide personalized services and suggestions, help improve the quality and efficiency of customer service, and reduce the workload of manual customer service. Secondly, we predict the impact of ChatGPT on the future development of the e-commerce industry by mining the characteristics of Amazon's financial data. The results show that ChatGPT is expected to meet these challenges and have a positive impact on the e-commerce market. For example, the introduction of ChatGPT technology may change the competitive landscape of the e-commerce market and increase market concentration ; at the same time, ChatGPT's personalized recommendations and suggestions can improve consumers' shopping satisfaction and purchase rate, and promote the development of the e-commerce industry. In summary, this paper reveals the potential positive impact of ChatGPT on the economic development of the e-commerce industry by analyzing the application mechanism of ChatGPT in the e-commerce industry and predicting its impact on the future development of the e-commerce industry. These research results have important reference value for decision makers and practitioners in the e-commerce industry, and can help them better understand and respond to the challenges and opportunities of new artificial intelligence technologies for the industry.

Affordance, usefulness, enjoyment, and aesthetics in sustaining virtual reality engagement

As virtual reality (VR) continues to develop, it's attracting an increasing number of consumers who are seeking more diverse functions and experiences. This study presents a theoretical model designed to identify predictors of VR users' continuance intentions. Data was collected from VR users who had firsthand experiences with the technology, and partial least squares structural equation modeling was employed to analyze this data. The results showed a significant correlation between functional affordance and perceived usefulness. Cognitive affordance was found to have a significant association with perceived usefulness, but it also influenced perceived enjoyment. Moreover, physical affordance significantly related to both perceived usefulness and enjoyment. Perceived usefulness was found to directly affect both attitude and continuance intention, while empirical results validated the impact of perceived enjoyment on attitude. The element of shape showed a significant correlation with attitude. Finally, attitude was found to have a significant association with continuance intention. The findings from this study will provide valuable insights for VR companies, developers, and consumers.

“I guess it's quite trendy”: A qualitative insight into young meat-eaters’ sustainable food consumption habits and perceptions towards current and future protein alternatives

As the market for sustainable food continues to expand, there is a need to understand how consumers’ consumption habits and perceptions are changing. Targeting the younger populations is of interest as they arguably will shape the future of food. Therefore, the present study aimed to provide in-depth consumer insights on a range of topics from current consumption habits (i.e., meat reduction, plant-based meat/seafood (PBM/S)), towards future protein alternatives (i.e., cell-based meat/seafood (CBM/S), precision fermented dairy (PFD)). Online focus groups were conducted in the UK with meat-eaters (n = 38) aged 18–34. Codebook thematic analysis was applied using the Framework Matrix as a tool for data analysis. Key themes were presented using the COM-B model (Capability, Opportunity, Motivation), which identified areas of behavioural change. Results found a trend towards meat reduction, partially initiated by moving away from home and limited food budgets. Overall, participants acknowledged the environmental impact of food, but a notable knowledge gap was apparent when quantifying the effect, especially for dairy and seafood. Compared to PBM, few participants had tried PBS products, partially due to lower availability and familiarity. Enablers for PBM/S included convenience, positive sensory experiences and the influence of others, whilst barriers related to negative health connotations and over-processing. For CBM/S and PFD, animal welfare, curiosity and optimised nutrition acted as enablers, whilst barriers related to wider consumer acceptance, affordability and unnaturalness. In general, participants felt changing food consumption habits can have an impact on climate change and were optimistic about novel technologies supporting future protein transitions. Increasing public understanding around the environmental impact of food, especially seafood and dairy, and prioritising the affordability of sustainable food are suggested as intervention strategies to encourage sustainable food consumption.

Consumers' insight and behaviour towards mango quality and safety attributes: implications for integrated value chain development

PurposeThe purpose of this research is to segment Pakistani consumers based on their insights and preference towards mango quality and safety attributes and to demographically characterise each segment so that effective value chain (VC) development strategies may be developed.Design/methodology/approachFactor and cluster analysis were applied to data collected from 400 mango buyers randomly selected from seven different cities in Pakistan.FindingsThis empirical study identified four distinct segments of mango consumers in Pakistan. The diversity of consumers' perception was mainly based on four factors: food safety, price and marketing, physical quality and shelf life. Based on their demographic characteristics and preferences for product attributes, the identified consumer segments can be classified as “traditional consumers,” “safety-conscious consumers,” price and market-sensitive consumers,” quality-sensitive consumers” and “perfect consumers.” This knowledge is useful to develop mango VCs that target specific consumer segments based on their chain level abilities and aspirations.Research limitations/implicationsThis study offers actors of mango VCs an enhanced understanding of consumer segments based on their perceived preferences towards the quality and safety attributes of mangoes, which would help VC actors design and develop business strategies that deliver value specific to each consumer segments. Findings of this study could also be useful to policy makers to design extension strategies that promote food safety and quality standards in mango VCs. Moreover, this study presents yet another case of consumer segmentation study for VC development in developing countries, adding a stepping stone towards a general VC theory development.Originality/valueThe findings stimulate the momentum of the growing literature, particularly in the developing countries on consumer insights and behaviour toward fruit quality and safety attributes of mangoes.