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Management, marketing and branding and strategy.

Undergraduate and postgraduate management courses.

This is a real-life case involving a confectionery manufacturer in Malaysia where it has grown over the years. As the market becomes more competitive, more challenges are confronting the company. Although there is still profit to be made, the margin is declining. Hence, the management of King's Biscuits Berhad must embark on the marketing environment scanning to prepare the company for future challenges and to ensure continued existence. As in the case of most strategy cases, little guidance was available for the students to reflect upon.

With the completion of this case study; student will be able to familiarize with the exercise of marketing environment scanning, determine the branding, product lines and positioning issues, adopt the marketing mix concept into real practice, and have the opportunity to visualize a true business scenario and simulate their minds and thinking towards managing a business.

Teaching note.

This study aims to discuss the current context, scope and impacts of a metaverse in the hospitality and tourism industry. Although existing literature discussed the potentials of the metaverse in this context, the ways the metaverse work is still being defined and accessing a complete metaverse is still not yet possible. This existing knowledge will become increasingly sophisticated and complex as developments in the metaverse continue, eventually contributing to a knowledge gap in knowledge, and its implications in shaping how the future digital environment should take form.

This work is based on a critical reflection of the existing developments and applications of the metaverse. Drawing from authors’ experiences, and synthesis of existing works and narratives, this work discusses the applications of the metaverse, critical factors for considerations and applications of the metaverse and proposes the way forward for potential users.

The metaverse provides new opportunities for the hospitality and tourism industry but the impact of the technology may not be felt immediately. The real challenge lies in developing a responsible digital environment for users and suppliers. Although the aspects to be considered are many, a lack of preparedness is a great obstacle.

This paper provides a comprehensive evaluation of how the metaverse can be applied in the hospitality and tourism sector aiming to provide diverse stakeholders insights into the associated opportunities and pitfalls.

To the best of the authors’ knowledge, this paper is among the first attempts to critically reflect on the possibilities of the metaverse, and contributes to the discussion on the attributes of the metaverse for tourism and hospitality (e.g. SSIs, decentralization) and includes discussion on special needs users, sustainable usage and climate change, and presents several agendas for further actions.

Emerging competitive dynamics demand small and medium-sized enterprises (SMEs) to continuously comprehend and respond to changing market conditions by implementing effective soft total quality management (STQM) practices. Firstly, the study intends to identify the key STQM practices perceived to foster knowledge sharing (KS). Secondly, this study aims to investigate the impact of market turbulence (MT) on the interaction between STQM practices and KS among SMEs.

A total of 215 valid samples were analysed. Incorporating a two-hidden-layer deep artificial neural network (ANN) into SEM approaches allows for more in-depth testing and high prediction power. This study employs a two-stage PLS-SEM-ANN predictive-analytical technique to provide a more comprehensive analysis and significant statistical contribution.

The PLS-SEM-ANN analysis reveals that STQM practices including employee involvement (EI), employee training (ET), top management commitment (TMC) and employee teamwork (EM) are critical to boosting KS. MT, interestingly, moderates the relationship between EM and KS while negatively moderating the relationship between TMC and KS.

The study contributes to the knowledge-based view theory by demonstrating the importance of integrating STQM and KS among SMEs to thrive in today's dynamic market environment.

Given the acute competition between music-streaming platforms (MSPs), the purpose of this study is to identify the relational motivators of brand loyalty towards the MSP in terms of user-brand involvement, brand trust, brand engagement, brand recommendation and brand loyalty.

Cross-sectional quantitative data, gathered from a total of 340 eligible respondents via an online questionnaire survey, were empirically analysed and validated using a hybrid predictive-analytics structural equation modelling (SEM) and Artificial Neural Network (ANN) method.

The results of this study demonstrate that user-brand involvement promotes brand loyalty toward a MSP by fostering brand engagement, brand trust and positive word-of-mouth. SEM and ANN data comparison reveals good consistency.

The generalizability of the research outcomes may be constrained, as this study only considers the data from a single country (i.e. Malaysia) and one music streaming platform (i.e. Spotify). This study highlighted the relevance of user-brand involvement and non-core supporting services in the cultivation of brand loyalty, particularly their salient roles in promoting favourable attitudes and behaviours towards platform brands.

The insights produced can aid MSPs in devising better user retention strategies that can be used to maintain their competitive edge over time. The findings of this study made it abundantly evident that practitioners should facilitate more user-brand cooperative activities to encourage user-brand involvement and, ultimately, foster brand loyalty.

This study has addressed a major research gap by examining the relational roots of brand loyalty, which transcend the typical focus on transactional factors and technical lock-in. This study pioneered the investigation of brand involvement with user involvement.

Though Blockchain has been studied in numerous contexts, the understanding of the impacts of Blockchain in achieving competitive advantages remains unexplored. Many industries, organizations and firms are still in a “wait and see” mode. This study aims at examining the effects of the technological, organizational and environmental factors drawn from the TOE framework in generating competitive advantage.

A dual-staged deep learning structural equation modeling artificial neural network analysis was conducted on 211 samples of small and medium enterprises. Four neural network models were engaged to rank the normalized importance of each of the predictor variables.

The research model can expound 57.99 and 47.33% of the variance in Blockchain adoption and competitive advantage correspondingly. The study successfully identified nonlinear relationships. The theoretical and managerial contributions are useful to scholars and practitioners such as industrial players, investors, chief executive officers (CEOs), managers, decision-makers and other stakeholders that intend to use Blockchain technology.

Unlike the existing technological–organizational–environmental (TOE) framework that uses a linear model and theoretically assumes that all relationships are linear, this has been the first study, which has successfully validated that there exist nonlinear relationships in the TOE framework. Further, very little has been theorized on the impacts of Blockchain adoption on competitive advantage, especially in the context of SMEs. Therefore, this study is the first one to provide the necessary theoretical foundation that may further extend the current knowledge of Blockchain technology adoption and its impacts.

The surging entrance of new mobile payment merchants into the growing market has prompted the need for an in-depth understanding of loyalty formation to retain customers. This study examines customers' loyalty generation process in mobile payment services by exploring the serial effect of cognitive drivers (i.e. brand awareness, perceived quality, brand image, perceived value and layout) on affective response, satisfaction and loyalty.

A survey using self-administered questionnaires was conducted. The data was collected from 370 consumers who have experience using mobile payment services in Vietnam. The data were submitted to partial least square structural equation modeling (PLS-SEM) and artificial neural networks (ANN) analysis.

The results indicated that all the proposed cognitive drivers show significant impacts on affective response, which, in turn, translates into satisfaction and loyalty. The post-hoc analysis revealed enjoyment as the vital affective response in determining satisfaction. Moreover, the multigroup analysis indicated that the relationship between affective response and satisfaction is stronger for the female group. In addition, the ANN's nonlinear result revealed complementary insight into the importance of cognitive drivers.

The current study revealed both linear and nonlinear mechanisms that explicate the roles of cognitive drivers and affective responses in fostering loyalty toward mobile payment merchants. The findings add to the existing literature that emphasizes consumers' initial mobile payment adoption.

The emergence of social media has brought the influencer marketing landscape to an unprecedented level, where many ordinary people are turning into social media influencers. The study aims to construct and validate a model to yield strategic insights on the relevance of content curation, influencer–fans interaction and parasocial relationships development in fostering favorable endorsement outcomes (i.e. purchase intention).

The present study analyzes data from a survey of 411 consumers using partial least squares-structural equation modelling (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA) to understand the net and combined effects of content attributes, interaction strategies and parasocial relationships on purchase intention.

PLS-SEM results reveal that content attributes (i.e. prestige and expertise) and interaction strategies (i.e. interactivity and self-disclosure) positively influence parasocial relationships, and in turn, lead to high purchase intention. Findings from fsQCA indicate six solutions with different combinations of content attributes, interaction strategies and parasocial relationships that sufficiently explain high purchase intention.

The present study demonstrates the roles of content attributes and interaction strategies in engendering parasocial relationship and the endorsement outcome (i.e. purchase intention) from both linear and non-linear (complexity) perspectives.

In the literature of industrial management, the focus is normally given on examining the factors that contribute to product innovation acceptance. The advocates of “pro-innovation bias” assume that consumers are open to new products and are willing to accept an innovative product. However, there is a high failure rate of technological innovations and most of the technological innovations were rejected due to users' resistance. Since the inception of innovation resistance theory (IRT), the number of studies that used IRT has gained much attention from scholars. However, the findings from these studies from various contexts are inconsistent, lack universality, and a clear understanding of technological innovation barriers. The study aims to determine whether the IRT theory is indeed valid and whether IRT is culturally invariant from the Eastern and Western cultures.

A meta-analysis based on a random-effects model and studies drawn from 24 countries and/or regions with a consolidated sample size of 10,463 was conducted. Cultural invariance was identified based on subgroup analysis. Moderator analysis was performed by applying the weighted linear regression.

The results reveal that tradition is the strongest barrier followed by the value, risk, image and usage barrier. Interestingly, there is a cultural invariance in IRT from the Eastern and Western cultures. Besides, there are significant moderating effects due to the temporal factor.

The study has contributed useful theoretical and managerial implications in advancing the product innovation literature.

The main aim of this study is to examine the effect of virtual store atmospheric factors on impulsive purchasing in the metaverse context.

Grounded in purposive sampling, 451 individuals with previous metaverse experience were recruited to accomplish the objectives of this research. Next, to identify both linear and nonlinear relationships, the data were analyzed using partial least squares structural equation modeling (PLS-SEM) and artificial neural network (ANN) approaches.

The findings underscore the significance of the virtual store environment and online trust in shaping impulsive buying behaviors within the metaverse retailing setting. Theoretically, this study elucidates the impact of virtual store atmosphere and trust on impulsive buying within a metaverse retail setting.

From the findings of the study, because of the importance of virtual shop content, practitioners must address its role in impulse purchases via affective online trust. The study’s findings are likely to help retailers strategize and improve their virtual store presentations in the metaverse.

The discovery adds to the understanding of consumer behavior in the metaverse by probing the roles of virtual store atmosphere, online trust and impulsive buying.

The COVID-19 pandemic has brought about significant changes to the lives of many people. One of which is the accelerated digitalization in the commerce sector. Hence, this study looks to determine the antecedents that affect users' mobile shopping actual use during a pandemic.

The research model was founded on the integration of the Protection Motivation Theory and Transactional Theory of Stress. This is in addition to further extending the integrated research model with other constructs to develop a multi-dimensional framework that accounted for the health, personal, technological and social dimensions. The data was collected from users of mobile shopping through an online survey which was then analyzed via Partial Least Squares–Structural Equation Modeling.

This study provides empirical support to establish the major role of COVID-19 pandemic in affecting the actual usage of mobile shopping. Furthermore, the determinants of actual usage of mobile shopping were found to be multi-dimensional. In particular, the Importance-Performance Map Analysis revealed that emphasis should be place on perceived vulnerability.

As other studies focused on users' intentions, this study looked into the factors that influence the actual usage of mobile shopping. Furthermore, this study emphasizes on the contextualization of time and situation in addition to a multi-dimensional approach toward the subject matter. Overall, this study offers practical insights to stakeholders to better tailor their mobile shopping services in times of a pandemic and advances the literature on actual usage of mobile shopping.