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The purpose of this study is to critically review consumer knowledge in marketing and propose a future research agenda. Despite the many works that have examined this variable, given its strong influence on behaviour, it has generally been studied in association with other constructs, and no studies have focused on it in a specific way. Its definition, measurement and approaches to its role and usefulness are superficial and underdeveloped. After structuring and analysing the existing literature, the authors establish, (I) which aspects are of little use to the discipline, and (II) which research lines have the most potential and should be developed and studied in greater depth, to advance and complete the existing consumer knowledge framework.

A search was undertaken for documents in the main databases in which the term “consumer knowledge” appears in a marketing or consumer context, and a critical and reflexive approach was taken to analyse the main contributions and to structure them by content blocks.

Five main content blocks were identified. A set of research gaps were detected, mainly related to the lax conceptualisation of the topic, measurement problems and the scarcity of more useful works connected with business management, and several research lines are proposed that complement the existing framework to make it more complete and operational.

This paper offers a critical review and proposes a research agenda for one of the most used but little studied variables in the field of marketing, which may help academics and professionals in the discipline to continue developing useful theories and models.

El objetivo de este trabajo es revisar críticamente el conocimiento del consumidor en marketing y proponer una agenda de investigación futura. A pesar de los numerosos trabajos que han examinado esta variable, dada su fuerte influencia en el comportamiento, generalmente se ha estudiado en asociación con otros constructos, y ningún estudio se ha centrado en ella de manera específica. Su definición, medición y aproximaciones sobre su papel y utilidad son superficiales y poco desarrollados. Después de estructurar y analizar la literatura existente, establecemos (I) qué aspectos tienen poco uso para la disciplina y (II) qué líneas de investigación tienen más potencial y deben ser desarrolladas y estudiadas con mayor profundidad; para avanzar y completar el marco existente sobre conocimiento del consumidor.

Se realizó una búsqueda de documentos en las principales bases de datos en las que aparece el término “conocimiento del consumidor” en un contexto de marketing o consumo, y se adoptó un enfoque crítico y reflexivo para analizar las principales contribuciones y estructurarlas por bloques de contenido.

Se identificaron cinco bloques principales de contenido. Se detectó un conjunto de huecos de investigación, principalmente relacionados con la laxa conceptualización del tema, problemas de medición y la escasez de trabajos más útiles conectados con la gestión empresarial; y se proponen varias líneas de investigación que complementan el marco existente para hacerlo más completo y operativo.

Este documento ofrece una revisión crítica y propone una agenda de investigación para una de las variables más utilizadas pero poco estudiadas en el campo del marketing, lo que puede ayudar a académicos y profesionales en la disciplina a continuar desarrollando teorías y modelos útiles.

本文旨在对市场营销中的消费者知识进行批判性审视, 并提出未来的研究议程。虽然已有许多研究检验了该变量, 但由于其对行为产生强大影响, 通常会与其他结构变量一起研究, 而没有以特定方式专注于该变量。对其定义、测量以及其作用和用途的方法仍旧存在研究空白。通过对现有文献进行结构化分析后, 确定了以下两个方面：（I）哪些方面对该学科意义不大, （II）哪些研究方向最具研究潜力, 并且应该进一步深入发展和研究, 以推进和完善现有的消费者知识框架。

通过主要数据库检索市场营销或消费者背景下涉及“消费者知识”一词的文献, 采取批判性和反思性方法来分析其主要贡献, 并通过内容块对其进行结构化。

识别了五个主要内容块, 并发现存在一定程度的研究空白, 主要涉及该主题的概念松散化、测量问题以及与商业管理相关的有效研究的稀缺性。此外, 本文提出了几个研究线索, 这些线索为现有框架补充了信息, 使其更加完整且具备更强的操作性。

本文对市场营销领域中广泛使用但研究较少的变量进行了批判性评述, 并提出了相关研究议程。这一工作有助于学术界和专业人士继续发展实用的理论和模型。

The authors aimed to identify the opinions of young adult consumers regarding food processing companies’ (FPCs) credibility in terms of food safety (FS).

The authors surveyed Generation Z (GenZ) consumers. The authors assessed the reliability of the research questionnaire using Cronbach’s alpha statistics. The authors used descriptive statistics and one-way ANOVA analysis of variance in the data analysis to determine intergroup variability. The authors performed statistical analyses using IBM SPSS Statistics. 27.

The most valued determinants for consumers were competence and skills, and the most valued family members’ opinions on FS, followed by experts’ opinions. FS concerns are more associated with FPCs than with farmers. The ethics of conduct and moral responsibility play an important role in assessing the FPCs’ credibility.

The questionnaire did not focus on specific food industries, such as fruit and vegetables, fish, meat, dairy, etc. In the future, a similar survey on producers’ credibility should consider the issue of FS risks associated with the specifics of a particular industry.

The authors proposed a set of factors that may determine young adult consumers’ perception of the FPCs’ credibility, which they may use for research within other consumer groups.

Large-scale text-based data increasingly poses methodological challenges due to its size, scope and nature, requiring sophisticated methods for managing, visualizing, analyzing and interpreting such data. This paper aims to propose semantic network analysis (SemNA) as one possible solution to these challenges, showcasing its potential for consumer and marketing researchers through three application areas in phygital contexts.

This paper outlines three general application areas for SemNA in phygital contexts and presents specific use cases, data collection methodologies, analyses, findings and discussions for each application area.

The paper uncovers three application areas and use cases where SemNA holds promise for providing valuable insights and driving further adoption of the method: (1) Investigating phygital experiences and consumption phenomena; (2) Exploring phygital consumer and market discourse, trends and practices; and (3) Capturing phygital social constructs.

The limitations section highlights the specific challenges of the qualitative, interpretivist approach to SemNA, along with general methodological constraints.

Practical implications highlight SemNA as a pragmatic tool for managers to analyze and visualize company-/brand-related data, supporting strategic decision-making in physical, digital and phygital spaces.

This paper contributes to the expanding body of computational, tool-based methods by providing an overview of application areas for the qualitative, interpretivist approach to SemNA in consumer and marketing research. It emphasizes the diversity of research contexts and data, where the boundaries between physical and digital spaces have become increasingly intertwined with physical and digital elements closely integrated – a phenomenon known as phygital.

The objective of this study is to investigate the impact of the COVID-19 pandemic on the consumer payment behavior in Italy by correlating financial literacy with digital payment awareness, examining media anxiety and financial security, and including a gender analysis.

Consumers’ attitudes toward cashless payments were investigated using an online survey conducted from November 2021 to February 2022 on a sample of 836 Italian citizens by considering the behavioral characteristics and aspects of financial literacy. Structural equation modeling (SEM) was used to test the hypotheses and to determine whether the model was invariant by gender.

The analysis showed that the fear of contracting COVID-19 and the level of financial literacy had a direct influence on the payment behavior of Italians, which was completely different in its weighting. Fear due to the spread of news regarding the pandemic in the media indirectly influenced consumers’ noncash attitude. The preliminary results of the gender multigroup analysis showed that cashless payment was the same in the male and female subpopulations.

This research is noteworthy because of its interconnected examination. It examined the effects of the COVID-19 pandemic on people’s payment choices, assessed their knowledge, and considered the influence of media-induced anxiety. By combining these factors, the study offered an analysis from a gender perspective, providing understanding of how financial behaviors were shaped during the pandemic.

Artificial intelligence (AI) offers many benefits to improve predictive marketing practice. It raises ethical concerns regarding customer prioritization, market share concentration and consumer manipulation. This paper explores these ethical concerns from a contemporary perspective, drawing on the experiences and perspectives of AI and predictive marketing professionals. This study aims to contribute to the field by providing a modern perspective on the ethical concerns of AI usage in predictive marketing, drawing on the experiences and perspectives of professionals in the area.

The study conducted semistructured interviews for 6 weeks with 14 participants experienced in AI-enabled systems for marketing, using purposive and snowball sampling techniques. Thematic analysis was used to explore themes emerging from the data.

Results reveal that using AI in marketing could lead to unintended consequences, such as perpetuating existing biases, violating customer privacy, limiting competition and manipulating consumer behavior.

The authors identify seven unique themes and benchmark them with Ashok’s model to provide a structured lens for interpreting the results. The framework presented by this research is unique and can be used to support ethical research spanning social, technological and economic aspects within the predictive marketing domain.

La Inteligencia Artificial (IA) ofrece muchos beneficios para mejorar la práctica del marketing predictivo. Sin embargo, plantea preocupaciones éticas relacionadas con la priorización de clientes, la concentración de cuota de mercado y la manipulación del consumidor. Este artículo explora estas preocupaciones éticas desde una perspectiva contemporánea, basándose en las experiencias y perspectivas de profesionales en IA y marketing predictivo. El estudio tiene como objetivo contribuir a la literatura de este ámbito al proporcionar una perspectiva moderna sobre las preocupaciones éticas del uso de la IA en el marketing predictivo, basándose en las experiencias y perspectivas de profesionales en el área.

Para realizar el estudio se realizaron entrevistas semiestructuradas durante seis semanas con 14 participantes con experiencia en sistemas habilitados para IA en marketing, utilizando técnicas de muestreo intencional y de bola de nieve. Se utilizó un análisis temático para explorar los temas que surgieron de los datos.

Los resultados revelan que el uso de la IA en marketing podría tener consecuencias no deseadas, como perpetuar sesgos existentes, violar la privacidad del cliente, limitar la competencia y manipular el comportamiento del consumidor.

El estudio identifica siete temas y los comparan con el modelo de Ashok para proporcionar una perspectiva estructurada para interpretar los resultados. El marco presentado por esta investigación es único y puede utilizarse para respaldar investigaciones éticas que abarquen aspectos sociales, tecnológicos y económicos dentro del ámbito del marketing predictivo.

人工智能（AI）为改进预测营销实践带来了诸多益处。然而, 这也引发了与客户优先级、市场份额集中和消费者操纵等伦理问题相关的观点。本文从当代角度深入探讨了这些伦理观点, 充分借鉴了人工智能和预测营销领域专业人士的经验和观点。旨在通过现代视角提供关于在预测营销中应用人工智能时所涉及的伦理观点, 为该领域做出有益贡献。

本研究采用了目的性和雪球抽样技术, 与14位在人工智能营销系统领域具有丰富经验的参与者进行为期六周的半结构化访谈。研究采用主题分析方法, 旨在深入挖掘数据中显现的主要主题。

研究结果表明, 在营销领域使用人工智能可能引发一系列意外后果, 包括但不限于加强现有偏见、侵犯客户隐私、限制竞争以及操纵消费者行为。

本研究通过明确定义七个独特的主题, 并采用阿肖克模型进行基准比较, 为读者提供了一个结构化的视角, 以解释研究结果。所提出的框架具有独特之处, 可有效支持在跨足社会、技术和经济领域的预测营销中展开的伦理研究。

Collaborating with consumers during new product development can provide companies with significant benefits and competitive advantages. Although several studies have been conducted on the design of co-innovation platforms, there is still a need for a more comprehensive understanding of the co-innovation phenomenon. To address this gap, this research aims to identify the critical success factors of co-innovation platforms and provide an extensive analysis of the variables that determine their effectiveness.

This study presents a systematic literature review of co-innovation platforms based on an analysis of 89 articles published in 50 scholarly journals in the disciplines of information systems, marketing and business, covering the years from 2006 to 2022.

The review synthesizes the current state of scientific knowledge and groups prior studies thematically as critical success factors of co-innovation platforms. As a result, eight success factors have been identified in terms of quantity and quality of contributions. These factors include product involvement, perceived fairness, sense of community, interactive environment, employee involvement, participant diversity, assessment structure and task design.

The study consolidates existing research about the critical success of co-innovation platforms. It also provides a research framework that incorporates a diverse set of variables that can be used to assess co-innovation performance in future studies.

This study aims to understand pathways to success for food video bloggers (food vloggers) by identifying the drivers of positive reception among audiences. It examines how entertainment, information and interaction values affect attitudes toward food videos and vloggers. Additionally, it investigates the potential for product placement by studying the effects of attitudes toward food videos and vloggers on consumers’ behavioral intention regarding purchasing featured food ingredients.

An integrated model informed by theories (uses and gratification and stimulus-organism-response) was developed. An online survey was administered to 339 Vietnamese social media users. The data were analyzed using partial least square structural equation modeling (PLS-SEM).

The results show that food videos’ entertainment and information value positively impact the attitude toward food videos. However, the interaction value does not have a significant impact. All three values (entertainment value, information value and interaction) impact the attitude toward food vloggers. Both attitudes significantly influence purchase intention, showing that there is a pathway to product placement. The frequency of social media use can moderate these relationships, with a negative effect on the attitude toward food videos and a positive effect on the attitude toward food vloggers.

These findings provide insights into vlogger success pathways, not only in terms of audience reception but also in terms of product placement. This study offers comprehensive suggestions on pathways for success that are interesting for vloggers, food business operators, restaurant managers and audiences on how to design effective food videos and potentially encourage consumer purchases. These pathways can also be valuable for other behaviors, such as food safety advice and food waste reduction.

This paper examines the socio-emotional identities of handloom artisans in Sri Lanka as a novel technique for new product development.

Qualitative research methods, including observational research and semi-structured interviews with 27 artisans from different handloom communities in Sri Lanka were conducted and analyzed in thematic approach.

By highlighting the maker of the craft through their socio-emotional identities in an artisan-oriented approach, this paper provides insight into new product development for handloom in alignment with up-and-coming trends. Ultimately, this can increase the demand for handloom and sustain the sector in both local and international fashion markets.

This research study is one of the first of its kind to propose a novel approach for artisan-oriented product development through the application of artisans’ socio-emotional identities.

Operational risks can cause considerable, atypical disturbances and impact food supply chain (SC) resilience. Indicatively, the COVID-19 pandemic caused significant disruptions in the UK food services as nationwide stockouts led to unprecedented discrepancies between retail and home-delivery supply capacity and demand. To this effect, this study aims to examine the emergence of digital platforms as an innovative instrument for food SC resilience in severe market disruptions.

An interpretive multiple case-study approach was used to unravel how different generations of e-commerce food service providers, i.e. established and emergent, responded to the need for more resilient operations during the COVID-19 pandemic.

SC disruption management for high-impact low-frequency events requires analysing four research elements: platformisation, structural variety, process flexibility and system resource efficiency. Established e-commerce food operators use partner onboarding and local waste valorisation to enhance resilience. Instead, emergent e-commerce food providers leverage localised rapid upscaling and product personalisation.

Digital food platforms offer a highly customisable, multisided digital marketplace wherein platform members may aggregate product offerings and customers, thus sharing value throughout the network. Platform-induced disintermediation allows bidirectional flows of data and information among SC partners, ensuring compliance and safety in the food retail sector.

The study contributes to the SC configuration and resilience literature by investigating the interrelationship among platformisation, structural variety, process flexibility and system resource efficiency for safe and resilient food provision within exogenously disrupted environments.

In the wine industry, maintaining superior quality standards is crucial to meet the expectations of both producers and consumers. Traditional approaches to assessing wine quality involve labor-intensive processes and rely on the expertise of connoisseurs proficient in identifying taste profiles and key quality factors. In this research, we introduce an innovative and efficient approach centered on the analysis of volatile organic compounds (VOCs) signals using an electronic nose, thereby empowering nonexperts to accurately assess wine quality.

To devise an optimal algorithm for this purpose, we conducted four computational experiments, culminating in the development of a specialized deep learning network. This network seamlessly integrates 1D-convolutional and long-short-term memory layers, tailor-made for the intricate task at hand. Rigorous validation ensued, employing a leave-one-out cross-validation methodology to scrutinize the efficacy of our design.

The outcomes of these e-demonstrates were subjected to meticulous evaluation and analysis, which unequivocally demonstrate that our proposed architecture consistently attains promising recognition accuracies, ranging impressively from 87.8% to an astonishing 99.41%. All this is achieved within a remarkably brief timeframe of a mere 4 seconds. These compelling findings have far-reaching implications, promising to revolutionize the assessment and tracking of wine quality, ultimately affording substantial benefits to the wine industry and all its stakeholders, with a particular focus on the critical aspect of VOCs signal analysis.

This research has not been published anywhere else.