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Emojis are quickly becoming a popular new language in social media and marketing. The capability to express emotions and make message understanding easier is one of the primary reasons for using emojis. The aim of this research was to determine the influence of perceived usefulness, perceived ease of use, trust, and involvement on customer engagement due to emojis used in digital marketing communications among Generation Z (Gen Z) in South Africa.

Following the descriptive research approach, quantitative research was used in this study. A questionnaire (self-administered) was utilized to test the effectiveness of using emojis among 1,000 young consumers. Structural equation modeling was used to test the hypotheses.

The findings of the study yielded positive relationships between the variables, namely between trust and involvement; involvement and the perceived ease of use; involvement and perceived usefulness; perceived ease of use and perceived usefulness; trust and customer engagement; perceived usefulness and customer engagement; involvement and customer engagement; customer engagement and intention to purchase; trust and intention to purchase; and perceived usefulness and intention to purchase.

This study can help organizations in emerging markets use emojis in their digital marketing communications to engage customers and stimulate intention to purchase among young people, especially the Gen Z cohort, who seek organizations and brands that understand and connect with them.

By investigating the effects of emojis in digital marketing communications, this study contributes to the customer-centric process and the literature on emoji usage while also involving a credible digital language when communicating with members of Gen Z. By extending TAM, the findings of this study contribute to the TAM literature by demonstrating that emoji usage in digital marketing communications positively influences various attitudinal associations among Gen Z consumers.

Gamification in mobile apps has emerged as a compelling strategy to foster firm’s relationships with their customers through mobile applications. This study utilizes a meta-analytic review to demonstrate how gamification shapes consumer responses and how moderator variables play a role in this process.

The study employed a meta-analytic review to combine and synthesize data from 62 studies, including 71 independent samples and a sample size of 20,510 to test the research model and examine the role of moderators in this model.

Findings reveal that gamification, through the customer experience components (cognitive, hedonic, pragmatic and social elements), leads to customer engagement, resulting in word-of-mouth and loyalty. However, privacy concerns play a destructive role in this process, deteriorating customer–firm relationships. Moderator analysis indicates that gamification design elements, such as rewards, progression and customization systems, along with product and service benefit, involvement, familiarity and firm type moderate the relationship between gamification and customer response.

The meta-analysis main and moderator analysis results provide several insights for marketing managers that assist them in developing an effective gamification in mobile app strategy.

The findings reveal novel insights, encompassing both the bright and dark sides of the influence of gamification on customer response, while also examining the moderating roles of gamification, product and service and firm characteristics.

Against social cognitive and social exchange theories, this research paper aims to investigate the significance and interaction between perceived knowledge, involvement, trust and brand community engagement in brand communities (BC).

BC participants (n = 503) completed a cross-sectional survey for this research. Analysis was performed using PLS-SEM via SmartPLS (v. 4.1.0.2) and the novel Necessary Condition Analysis (NCA).

An integrative KITE model with positive and significant relationships of key BC constructs was established. The perceived BC knowledge influenced involvement and engagement. Furthermore, the constructs of involvement and trust were discovered to have a positive and significant impact on engagement, with trust having a substantial effect on BC engagement. The indirect effects of the trust construct via the BC knowledge and BC involvement constructs were also significant.

This research advances the existing conceptual approaches by introducing knowledge as the key BC constructs. The study illustrates that members’ knowledge about a BC facilitates their involvement in the BCs. The vital role of trust is revealed in the KITE model, as it is significantly related to BC knowledge, BC involvement and BC engagement with at least medium to large effect sizes. Notably, the role of trust is enhanced as it is the only necessary must-have (instead of “should-have”) condition to achieve high levels of BC engagement. Furthermore, the KITE model provides insights for marketers to develop a valuable BC.

Artificial intelligence (AI) has become a pivotal technology in both marketing and daily life. Despite extensive research on the benefits of AI, its adverse effects on customers have received limited attention.

We employed meta-analysis to synthesise effect sizes from 45 studies encompassing 50 independent samples (N = 19,503) to illuminate the negative facets of AI's impact on customer responses.

Adverse effects of AI, including privacy concern, perceived risks, customer alienation, and uniqueness neglect, have a negative and significant effect on customers' cognitive (perceived benefit, trust), affective (attitude and satisfaction) and behavioural responses (purchase, loyalty, well-being). Additionally, moderators in AI (online versus offline), customer (age, male vs. female), product (hedonic vs. utilitarian, high vs. low involvement), and firm level (service vs. manufacturing) and national level (individualism, power distance, masculinity, uncertainty avoidance, long-term orientation) moderate these relationships.

Our findings inform marketing managers about the drawbacks of utilising AI as part of their value proposition and provide recommendations on how to minimise these effects in different contexts. Additionally, policymakers need to consider the dark side of AI, especially among the vulnerable groups.

This paper is among the first research studies that synthesise previous research on the dark side of AI, providing a comprehensive view of its diminishing impact on customer responses.

Co-creation of services (CCOS) is a collaborative strategy that emphasises customer involvement and their expertise to increase the value of the service experience. In the service ecosystem, artificial intelligence (AI) plays a key role in value co-creation. Therefore, this study is undertaken to empirically uncover how AI can empower CCOS.

The source data were collected from 305 service provider respondents and quantitative methodology was applied for data analysis.

New service development augmented with AI provides tangible value to service providers while also providing intangible value to supportive customers. With AI, service providers adapt to new innovations and enrich additional information, which eventually outperforms human-created services.

AI adoption for CCOS empowerment in service businesses brings “service-market fit”, which represents the significant benefits wherein customers contribute to creativity, intuition, and contextual awareness of services, and AI contributes to large-scale service-related analysis by handling volumes of data, service personalisation, and more time to focus on challenging problems of the market.

This study presents theoretical concepts on AI-empowered CCOS, AI technological innovativeness, customer participation in human-AI interaction, AI-powered customer expertise, and perceived benefits in CCOS, and subsequently discusses the CCOS empowerment framework. Then, it proposes a novel conceptual model based on the theoretical concepts and empirically measures and validates the intention to adopt AI for CCOS empowerment. Overall, the study contributes to novel insight on empowering service co-creation with AI.

When coping with uncertainties, three characteristics distinguish firms: agility, adaptability and alignment (triple-A). Based on significant field research, the triple-A highlights the significance of coordinating agility, adaptability and alignment. Start-ups are facing a lot of challenges in this turbulent environment. However, this sector is undergoing a major transformation. Agility, adaptability and alignment concepts have had a major influence on the supply chain, but their implementation in start-ups has been less visible. This paper aims to identify, analyze and categorize the enablers for agility, adaptability and alignment in start-ups using the total interpretive structural modeling (TISM) approach.

In addition to the scheduled interview, a closed-ended questionnaire was used to collect data. To identify how the factors interact, the TISM technique is used, and the Matriced’Impacts Croises-Multipication Applique’ and Classment method is used to rank and categorize the agility, adaptability and alignment enablers.

This study identified ten agility, adaptability and alignment factors for start-ups. It has been found that the key importance should be given to management involvement, conflict management, collaboration and information integration.

This study primarily focused on the agility, adaptability and alignment factors in start-ups.

This study will help academics and key stakeholders understand the aspects that lead to agility, adaptability and alignment in start-ups.

Agility, adaptability and alignment concepts have had a major influence on the supply chain, but their implementation in start-ups has been less visible. Therefore, this is a novel attempt in this industry’s agility, adaptability and alignment.

This paper aims to describe the product development process (PDP) of companies in the textile industry, seeking to understand the dynamics of their management from different actors along the production chain.

Qualitative empirical research adopted a multiple case studies design in five large Brazilian organizations, each representing a link in the production chain.

Textile PDP follows structured steps. However, it is still an informal process. The use of methodologies and tools for decision-making and control gates throughout the process is limited. Performance indicators do not cover all dimensions of the PDP since sales and profit are the main parameters for assessing projects. The predevelopment macro phase varies according to the product type and the company's business model, whereas the postdevelopment macro phase is nonexistent. PDP projects are executed through collective efforts of multiple departments in cross-functional teams, except for the commodities firms.

The study allows managers of Brazilian textile companies to understand the best practices in the PDP and those that require more attention, taking into account different business models and sectors of the production chain.

Our results contribute to the literature and practitioners by providing an overview of PDP management in the textile industry, covering its different production chain actors, types of projects and companies' characteristics.

This paper aims to identify the interrelationships among critical factors for digital servitization (DS) implementation.

A multi-method research was used. Critical factors for a successful DS implementation were identified using a systematic literature review and expert interviews. The interpretive structural modeling (ISM) method was used to develop a hierarchical model of the identified factors, followed by the fuzzy Matrice d’Impacts Croisés Multiplication Appliqués à un Classement (MICMAC) analysis to assess their dependence and driving powers.

A total of 23 factors for DS implementation were identified, and the ISM model was developed. Based on MICMAC analysis, the factors were also grouped under four categories (dependent, driving, autonomous and linkage). A conceptual framework is proposed, highlighting that DS implementation relies on three main layers of critical factors: crafting alignment, scaling the change and achieving results.

The ISM and fuzzy MICMAC methods used in this study provided valuable insights into the interrelationship among the identified DS factors through a conceptual framework. To the best of the authors’ knowledge, the study is one of the first to identify critical factors influencing DS implementation and develop hierarchical relationships among them.

This study has two main objectives. First, to examine the indirect effects of digital platform capability and digital resilience on digital transformation (DT) outcomes for small- and medium-sized enterprises (SMEs), and second, to investigate how digital business model maturity influences these indirect effects.

The study adopts a quantitative design and collects data through a self-reporting survey from individuals in the technological industries. The Partial Least Squares-Structural Equation Modelling (PLS-SEM) and PLS multi-group analysis examine the measurement and structural models and the significance of differences in indirect paths based on the digital business model maturity level, serving as a moderator.

The findings of this study provide valuable insights into the internationalisation of digital SMEs. They indicate that digital platform capability and resilience fully mediate, connecting digital resources to SME growth. The study also confirms the digital business model maturity’s positive and significant moderating effect on these indirect relationships.

This research contributes to the existing literature by focusing on the international outcomes of platform ecosystems in developing markets. It explores how digital platform capability and resilience support the digital transformation of SMEs, considering their vulnerability due to their small size. The study also fills a research gap by investigating the relationship between big data, digital leadership and the international growth of digital platforms. Lastly, it explores the role of digital maturity in the relationships between antecedents, determinants and outcomes of digitalisation.

This study aims to synthesize and analyze research on the Supply Chain Management Practices (SCMPs)-performance nexus, examine current knowledge, identify emerging trends, and provide plausible suggestions for future research engagements in the manufacturing sector in the context of Developing and Emerging Economies (DEEs).

Following a systematic review approach, this study analyzed 20 peer-reviewed scientific journal articles published between 2007 and 2021. The study sample was systematically selected from the Web of Science (WoS) and Google Scholar databases, following strict evaluation and selection criteria.

Numerous dimensions of SCMPs have been considered in the extant literature; however, six have stood out as the most common. In addition, operational performance stood out as the most widely investigated measure in the SCM literature. Moreover, SCMPs have predominantly shown positive effects on performance outcomes. Methodological issues that future studies should consider are suggested.

The sample size was not sufficiently large relative to the rule of thumb set in the literature because of the scarcity of studies in the manufacturing sector in the DEEs context. Despite these limitations, the results of this study provide crucial insights into knowledge and practice.

This review is the first of its kind to examine the SCMPs-performance nexus in the context of DEEs. Based on the findings of this study, future research directions are proposed.