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Data-driven marketing is replacing conventional marketing strategies. The modern marketing strategy is based on insights derived from customer behavior information gathered from their facial expressions and neuro-signals. This study explores the potential for face recognition and neuro-marketing in modern-day marketing.

The study conducts an in-depth examination of the extant literature on neuro-marketing and facial recognition marketing. The articles for review are downloaded from the Scopus database, and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) is then used to screen and choose the relevant papers. The systematic literature review method is applied to conduct the study.

An extensive review of the literature reveals that the domains of neuro-marketing and face recognition marketing remain understudied. The authors’ review of selected papers delivers five neuro-marketing and facial recognition marketing themes that are essential to modern marketing concepts.

Neuro-marketing and facial recognition marketing are artificial intelligence (AI)-enabled marketing techniques that assist in gaining cognitive insights into human behavior. The findings would be of use to managers in designing marketing strategies to enhance their marketing approach and boost conversion rates.

The uniqueness of this study lies in that it provides an updated review on neuro-marketing and face recognition marketing.

This study aims to investigate the role of social media in increasing trust, self-perceived creativity and millennial entrepreneurial satisfaction.

The empirical analysis was conducted using a sample of 385 millennial entrepreneurs that were recruited for online survey. After conducting reliability and validity tests, the data were analyzed using partial least squares structural equation modeling.

The results showed that the quality of social media information had a direct and indirect positive and significant effect on trust and satisfaction. Social media marketing activities had a direct and indirect positive and significant effect on trust and self-perceived creativity. System Quality of social media also has a significant direct influence on trust. However, there is no direct relationship to satisfaction. Finally, social media marketing activities have a significant direct effect on trust and satisfaction.

This research can contribute to marketing experts and millennial entrepreneurs in improving the quality of advertising information and the credibility of social media used to support creativity, trust and satisfaction. In addition, marketing experts and millennial entrepreneurs with online-based communities should optimize their marketing activities on social media.

This study has shown a more comprehensive model of the relationship between information quality, system quality, social media marketing activities, self-perceived creativity, trust and satisfaction. This study also reveals a significant direct and indirect effect of social media marketing activities on satisfaction.

In a volatile agricultural postharvest market, producers require more personalized information about market dynamics for informed decisions on the marketed surplus. However, this adaptive strategy fails to benefit them if the selection of a computational price predictive model to disseminate information on the market outlook is not efficient, and the associated risk of perishability, and storage cost factor are not assumed against the seemingly favourable market behaviour. Consequently, the decision of whether to store or sell at the time of crop harvest is a perennial dilemma to solve. With the intent of addressing this challenge for agricultural producers, the study is focused on designing an agricultural decision support system (ADSS) to suggest a favourable marketing strategy to crop producers.

The present study is guided by an eclectic theoretical perspective from supply chain literature that included agency theory, transaction cost theory, organizational information processing theory and opportunity cost theory in revenue risk management. The paper models a structured iterative algorithmic framework that leverages the forecasting capacity of different time series and machine learning models, considering the effect of influencing factors on agricultural price movement for better forecasting predictability against market variability or dynamics. It also attempts to formulate an integrated risk management framework for effective sales planning decisions that factors in the associated costs of storage, rental and physical loss until the surplus is held for expected returns.

Empirical demonstration of the model was simulated on the dynamic markets of tomatoes, onions and potatoes in a north Indian region. The study results endorse that farmer-centric post-harvest information intelligence assists crop producers in the strategic sales planning of their produce, and also vigorously promotes that the effectiveness of decision making is contingent upon the selection of the best predictive model for every future market event.

As a policy implication, the proposed ADSS addresses the pressing need for a robust marketing support system for the socio-economic welfare of farming communities grappling with distress sales, and low remunerative returns.

Based on the extant literature studied, there is no such study that pays personalized attention to agricultural producers, enabling them to make a profitable sales decision against the volatile post-harvest market scenario. The present research is an attempt to fill that gap with the scope of addressing crop producer's ubiquitous dilemma of whether to sell or store at the time of harvesting. Besides, an eclectic and iterative style of predictive modelling has also a limited implication in the agricultural supply chain based on the literature; however, it is found to be a more efficient practice to function in a dynamic market outlook.

Factors influencing the use of mobile phone technologies for agricultural market information access remain a mixed debate, and there are contradictive views among studies. This study examined factors influencing the use of mobile phone technologies for agricultural marketing information access. The study is anchored on the technological acceptance model (TAM).

A descriptive cross-sectional research design was adopted with a sample size of 400 grape smallholder farmers. A structured questionnaire and focus group discussions (FGDs) were used to gather data. Descriptive, ordinal logistic regression and thematic approaches were used in data analysis.

The study confirmed grape smallholder farmers generally considered mobile phone technologies as an appropriate communication channel to stay informed about agricultural marketing information. It was found that reliable electricity supply, relevance, timeliness, perceived ease of use (PEOU) and perceived usefulness (PU) of mobile phone technologies influenced the level of agricultural marketing information access.

This research is limited to a selected number of grape smallholder farmers in Dodoma, Tanzania, and leaves out those without mobile phones. Also, the study was cross-sectional in nature, so it may not be necessarily capable of consistently providing critical and consistent information about the same population over a series of times.

This study contributes to the body of knowledge by integrating the use of mobile phone technologies to access marketing information in informing policy and decision-making processes to promote grape marketing.

Marketing is all about understanding your consumers and giving them what they want. However, this process becomes more complicated in times of economic crisis and national slowdown. Consumers can become scattered and unpredictable in their behaviour, making it hard to understand what they want or need. At times like these, it is more important than ever to rely on qualitative market research to understand the views of consumers and managers. Thus, this study aims to look at the significant consumer challenges that arise during times of crisis and the marketing strategies that managers prefer to counter the crisis.

The data collected for this study involves an extensive literature review followed by personal interviews with industry experts. This study presents two separate models, indicating hierarchical relationships among consumer challenges during crisis and marketing strategies using the total interpretive structural modelling approach. Further MICMAC analysis (popularly known as cross-impact matrix multiplication) was also performed to assess each variable's driving and dependence power.

“Price sensitiveness” and “adaptive buying” result as driving factors with the highest driving and lowest dependence power, which further gives rise to other consumer behaviour challenges. Likewise, the most critical strategies are “information systems” and the formation of “crisis management teams” during a crisis. At the same time, other strategies have resulted as linkage and dependent factors and none as the autonomous factor.

This paper provides a systematic understanding of how a manager can understand the challenges consumers face during a crisis and suggests a powerful summary of strategies companies can implement to sail through a crisis.

Artificial intelligence (AI) is transforming consumers' experiences and how firms identify, create, nurture and manage interactive marketing relationships. However, most marketers do not have a clear understanding of what AI is and how it may mutually benefit consumers and firms. In this paper, the authors conduct an extensive review of the marketing literature, develop an AI framework for understanding value co-creation in interactive buyer–seller marketing relationships, identify research gaps and offer a future research agenda.

The authors first conduct an extensive literature review in 16 top marketing journals on AI. Based on this review, an AI framework for understanding value co-creation in interactive buyer–seller marketing relationships was conceptualized.

The literature review led to a number of key research findings and summary areas: (1) an historical perspective, (2) definitions and boundaries of AI, (3) AI and interactive marketing, (4) relevant theories in the domain of interactive marketing and (5) synthesizing AI research based on antecedents to AI usage, interactive AI usage contexts and AI-enabled value co-creation outcomes.

This is one of the most extensive reviews of AI literature in marketing, including an evaluation of in excess or 300 conceptual and empirical research. Based on the findings, the authors offer a future research agenda, including a visual titled “What is AI in Interactive Marketing? AI design factors, AI core elements & interactive marketing AI usage contexts.”

This research aims to investigate how emerging destinations cope with digitalization of information, where they are in the process and how digitalization of information takes place in destination marketing organizations (DMOs). As a case for emerging destinations that must deal with the negative consequences of the digital divide, the Vietnamese Mekong Delta (VMD) will be examined. A new framework, solutions in general, and potential innovative approaches will be presented.

A mixed methods approach was used. Firstly, a content analysis comprising 68 criteria to examine 10 destination websites was conducted to evaluate the performance of provincial destination websites of VMD. Secondly, the authors interviewed five managers from VMD DMOs to reveal the strategy, status quo and their challenges with digitalization.

Some digitalization is evident in VMD DMOs, with the digitization of tourist information provision developing from analog formats to digital modes. The content analysis of the websites shows that provincial destination websites of VMD perform well with regard to communication but need improvements for transaction, and especially relationship aspects. Emerging destinations like VMD DMOs are reaching the second or third level in the digitalization process. Yet they face challenges with human and financial resources.

This research provides recommendations concerning destination website performance, the process of digitalization and how to promote digitalization and apply more digital instruments to move to the next stages of destination digitalization. Also, suggestions on how to overcome existing challenges/barriers in similar areas of the world are provided.

A new, extended more granulated version of the digitalization framework by Karpova et al. (2019) has been developed. The new model acknowledges the continued importance of printed information, provides information about the sequence of steps how to implement website dimensions, and which instruments are realistic to implement in different levels of digitalization considering the challenges and barriers developing destinations face.

Based on the key dimensions of the Metaverse environment (immersiveness, fidelity and sociability), this paper aims to develop the concept of sensory word-of-mouth (WOM) in Metaverse – the metaWOM. It attempts to upgrade the Reviewchain model and suggests the utilization of non-transferable tokens (NTTs) in curbing the explosion of fake WOM.

Following Macinnis’ (2011) approach to conceptual contributions, the authors browsed the currently available literature on WOM, Metaverse and NTT to portray the emergence of metaWOM.

By relying on Metaverse’s three building blocks, the authors map out the persuasiveness of metaWOM in the Metaverse-like environment. By incorporating NTT in the Reviewchain model, the authors upgraded it to provide a transparent, safe and trusted review ecosystem. An array of emerging research directions and research questions is presented.

This paper comprehensively analyzes the implications of a Metaverse-like environment on WOM and debates on technologies that can enhance the metaWOM persuasiveness. The proposed model in this paper can assist various stakeholders in understanding the complex nature of virtual information-seeking and giving.

This is the original attempt to delineate the sensory aspect of WOM in the Metaverse based on three crucial aspects of the Metaverse environment: immersiveness, fidelity and sociability. This paper extends the discussion on the issue of fake reviews and offers viable suggestions to curb the ever-growing number of fraudulent WOM.

The purpose of this study is to conduct a systematic literature review of the adoption of immersive marketing technology (IMT) in terms of strategic planning of its adoption, resource requirements and its implications and challenges.

This study categorizes and contextualizes qualitative approaches to evaluate the literature, with Scopus databases serving as the primary source of 90 selected articles in the areas of information technology, business and marketing strands. Theme analysis was carried out using thematic techniques and grounded approach principles to facilitate thematic coding and generate theme analysis.

The analysis was supported by the three concepts of business flexibility, agility and adaptability, which were drawn as a strategy for IMT adoption. The findings presented three main themes: proactive flexibility, responsive agility and reactive adaptability that enable business owner–managers to craft a strategy for IMT adoption.

The novel contribution of this study is the inclusion of key implications related to IMT as a starting point of the next level of innovative marketing for all academics, practitioners and business owner–managers.

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.