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Technologies have had a positive impact on the construction industry. Technologies such as BIM, automation, augmented and virtual reality, Internet of Things and robotics have been adopted by construction firms to enhance productivity. However, not much research has been done on the awareness and adoption of wearable technologies for health and safety (H&S) management. This paper investigates the level of awareness and adoption of wearable technologies for H&S management in the Nigerian construction industry.

A quantitative research method was adopted for the study. An electronic questionnaire format was used as an instrument to collect the data. Both descriptive (mean score) and inferential statistics (Kruskal–Wallis test) were used to analyse the data.

The results indicate that organisations rarely use H&S wearable devices for H&S management although professionals within the construction industry are somewhat aware of the common H&S wearable devices. The findings further indicate that all 11 variables were perceived as “rarely adopted”, whereas 2 variables were perceived as “aware”, 3 variables as “slightly aware” and the remaining 6 variables as “somewhat aware”.

Data were collected from only construction professionals working in government agencies, consultancy firms and grade D contracting firms in Lagos and Abuja. For a broader perspective, a study that expands the number of states and categories of construction firms is recommended.

The construction industry in Nigeria can use the recommendations to improve H&S management on site. Moreover, the recommendations can contribute to the development of policies to promote the adoption of wearable technologies in construction sites.

Research on wearable technologies, particularly in the Nigerian construction industry, is at the developing stage. With this article, the authors contribute to the body of knowledge in this area of research.

The proliferation of smartwatches in the digital age has radically transformed health and fitness management, offering users a multitude of functionalities that extend beyond mere physical activity tracking. While these modern wearables have empowered users with real-time data and personalized health insights, their environmental implications remain relatively unexplored despite a growing emphasis on sustainability. To bridge this gap, this study extends the UTAUT2 model with smartwatch features (mobility and availability) and perceived security to understand the drivers of smartwatch usage and its consequent impact on environmental sustainability.

The proposed theoretical model is evaluated based on data collected from 303 smartwatch users using a hybrid structural equation modeling–artificial neural network (SEM-ANN) approach.

The PLS-SEM results supported smartwatch features’ effect on performance and effort expectancy. The results also supported the role of performance expectancy, social influence, price value, habit and perceived security in smartwatch usage. The use of smartwatches was found to influence environmental sustainability significantly. However, the results did not support the association between effort expectancy, facilitating conditions and hedonic motivation with smartwatch use. The ANN results further complement these outcomes by showing that habit with a normalized importance of 100% is the most significant factor influencing smartwatch use.

Theoretically, this research broadens the UTAUT2 by introducing smartwatch features as external variables and environmental sustainability as a new outcome of technology use. On a practical level, the study offers insights for various stakeholders interested in smartwatch use and their environmental implications.

To develop the case, the authors used secondary sources including company annual reports, industry reports, news articles, social media sites, academic journal articles and company websites. This case has been classroom tested with students in the MBA Program and Master of Science in Management and Technology Program, and with undergraduates in an operations management course.

Movado Group, which has been a fierce competitor in the luxury watch market, has been facing unprecedented challenges posed by consumers’ enthusiasm for smartwatches and by their love of shopping online. The arrival of the COVID-19 pandemic has intensified these problems and brought new setbacks. This case examines these challenges to the company’s current business model. It then explores opportunities that could transform Movado into an innovative, digitally oriented organization capable of reaching consumers in a dynamic market while combating intense competition from the smart wearable devices that threaten traditional watch companies. The case also discusses the importance of building a robust supply chain through the lens of Industry 4.0 to guard against future supply chain disruptions.

Instructors can use this case in operations and supply chain management classes at the undergraduate and graduate levels. The focus of the case aligns with discussions of supply chain management and Industry 4.0. In particular, the case uses supply chain innovation theory to investigate the implications of Industry 4.0 in the watch industry and dovetails into discussions of omni-channel experience and virtual reality in retail that integrate multiple points of contact to reach consumers efficiently.

Purpose: In this technologically advanced era, it is crucial to understand how consumers adopt innovations so that producers and marketers can cater to these needs effectively. While existing technology adoption models have good explanatory power, a hybrid model must account for newer contexts.

Need for the Study: Most technology adoption papers in extant literature deal with the phenomenon’s functional, environmental and cognitive aspects. However, a mindset-oriented approach is largely absent from current studies. Mindsets are core beliefs people have about the malleability of human traits and characteristics that ultimately shape consumer behaviour. Investigating the adoption of such technologies through a deeper psychological lens will advance the field substantially.

Methodology: This conceptual paper utilised a literature review and theoretical integration to present a novel technology adoption model. The literature review of secondary data helped identify extant gaps, while academic integration of major concepts helped fill said gaps.

Findings: Based on the existing gaps in the literature, this study conceptualised a novel technology adoption model based on the foundation of Mindset Theory. Overall, relevant constructs, variables and scales have been presented along with future research propositions.

Practical Implications: From a global perspective, the findings of this chapter will enable marketers and practitioners to understand consumer adoption of new-age technologies. Producers of such technologies will also be able to cater to consumers more efficiently as a result of this study.

This paper aims to explore factors impacting wearable fitness tracking (WFT) device continued usage intention from perspectives of technology attributes (autonomy benefits), health attributes (self-health management benefits, diet-control benefits and health self-efficacy), and consumer attributes (age, gender, technological innovativeness, symbolic benefits, social benefits and hedonic benefits).

The study integrates constructs from the technology acceptance theories and the health promotion model to develop the research model and hypothesis. The empirical analysis was conducted using data from 217 respondents from India. Logistic regression was used to identify factors that discriminate between groups with low and high continued usage intentions.

Results indicate higher continued usage intention for WFT devices is driven by perceived benefits-health, autonomy, social and hedonic, and individual characteristics-technological innovativeness and perceived health self-efficacy. Further, perceived symbolic benefits, diet control benefits, age, and gender does not discriminate between the groups with low and high continued usage intentions.

The results may be limited to the context of the sample and the factors considered. The study suggests future research areas.

The paper offers insights for marketers, governments, insurance firms, and related healthcare services on promoting higher usage of WFT devices to yield dual benefits of preventive healthcare and higher profitability.

The study extends existing research by examining factors across consumer, health, and technological domains in a single framework and adds to the limited research in the context of usage of WFT devices in developing countries.

This paper explores optimal service resource management strategy, a continuous challenge for health information service to enhance service performance, optimise service resource utilisation and deliver interactive health information service.

An adaptive optimal service resource management strategy was developed considering a value co-creation model in health information service with a focus on collaborative and interactive with users. The deep reinforcement learning algorithm was embedded in the Internet of Things (IoT)-based health information service system (I-HISS) to allocate service resources by controlling service provision and service adaptation based on user engagement behaviour. The simulation experiments were conducted to evaluate the significance of the proposed algorithm under different user reactions to the health information service.

The results indicate that the proposed service resource management strategy, considering user co-creation in the service delivery, process improved both the service provider’s business revenue and users' individual benefits.

The findings may facilitate the design and implementation of health information services that can achieve a high user service experience with low service operation costs.

This study is amongst the first to propose a service resource management model in I-HISS, considering the value co-creation of the user in the service-dominant logic. The novel artificial intelligence algorithm is developed using the deep reinforcement learning method to learn the adaptive service resource management strategy. The results emphasise user engagement in the health information service process.

The purpose of this study is to analyse Benidorm, San Sebastián, Gijón, Málaga, Tenerife Island and Santander smart tourist destinations (STDs) as a touristic model and example to follow by other destinations in Spain and all over the world.

To fulfil the stated objective, this study follows several phases that introduce and classify a set of measures implemented by the six Spanish smart destinations to be designed as a STD.

Findings suggest that being a STD requires a high cost, and this is only accessible to big destinations with enough resources. Of the 50 Spanish provinces, eight are STDs, and these are localised in coastal areas. Obviously, this challenge is not within the reach of any Spanish city. Moreover, findings of the current study prove that the six Spanish smart destinations have a good air accessibility through their six airports, but the accessibility in a STD is not just physical; this must provide digital accessibility to tourists through destination marketing organisation’s website and app that will supply them with information on a wide range of services, including accommodations, tourist attractions, restaurants, public transport, museums and monuments’ locations, amongst many others.

From a resident point of view, a STD cannot be only focused on a technological and tourism context; a STD also requires knowing and meeting the needs of local residents and having a voice in decision-making processes. Hence, this study shows a new perspective on STDs that will benefit the literature on STDs.

The outbreak of the COVID-19 pandemic has led to the pervasiveness of food delivery apps (FDAs) and the increased scholars’ attention for the topic of FDA continuance usage intention. However, the limited understanding about possible segments of FDA users has hindered food retailers from providing FDAs with a personalized manner, which impairs the effectiveness of marketing strategies. Thus, this study aims to first explore key antecedents of users’ continuance intention toward FDAs and then segment and profile Taiwanese users based on the identified antecedents of FDA continuance intention and demographics.

An online survey was implemented to collect responses from FDA users in Taiwan. With a response rate of 82.4%, the final sample of 326 respondents (average age = 28.3; female = 54.9%) was analyzed by using two techniques of structural equation modeling (SEM) and cluster analysis.

The results indicate six antecedents of users’ continuance usage intention towards FDAs, including information quality, system quality, information quality, perceived usefulness, perceived enjoyment and satisfaction. Additionally, three distinct clusters of FDA users are successfully identified, labeled as “value sensitive users”, “time-sensitive users” and “security sensitive users”.

This study is one of the pioneers that explores the possible segments in FDA market, which helps FDA providers and food retailers develop more focused and appropriate strategies to encourage users to continue using FDAs. Our findings contribute to building an optimized version of “FDA Tech” that becomes an omni-channel solution to serve the increased home-delivery needs in the new normal era.

This study aims to investigate determinants such as performance expectancy (PE), health beliefs (HB), technological compatibility, trust and social influence (SI) of customers' efforts to cope with problems associated with using wearable health technology, thereby determining their use intention of such products. The moderating effect of the demographic variables is also investigated.

An online survey was used to collect panel data from 285 respondents in China. Structural equation modeling was used to test the hypotheses, and interaction moderation was applied to test the moderating effect of the demographic variables.

The results show that HB, technological compatibility, trust and SI significantly impact coping efforts associated with usage, which significantly influences intention to use. Only income significantly moderated the effect of coping efforts on the intention to use.

This is the first study combining coping theory and UTAUT to develop a model of drivers that encourages customers to overcome the constraints of using wearable technologies.

This paper aims to theorize and investigate the use of effective color features in artificial intelligence (AI) influencers, an emerging marketing trend in the social media context.

By analyzing 6,132 pictures posted by ten AI influencers on Instagram, this paper examines the effect of warm colors in AI influencers’ social media posts on consumer responses, and how other color features may moderate the effect of warm color. In addition, two experimental studies reveal the underlying process driving the effect of warm color.

Warmer color generated more favorable consumer responses, with brightness significantly moderating the relationship between warm color and favorable consumer responses. Moreover, the results of the experiments establish that perceived warmth and emotional trust mediate the causal effect of warm colors on consumer responses.

There is still little understanding about consumer perceptions of AI influencers and their acceptance of AI influencers’ product recommendations. As such, this research offers theoretical understanding of the color features influencing the effectiveness of recommendations by AI influencers.

Brands have started deploying AI influencers as their brand ambassadors to make product recommendations, representing a new wave of advertising on social media. The findings will thus benefit marketers in developing effective product recommendations using AI influencers.

The present research provides a novel understanding of how visual features, such as color can influence the effectiveness of AI influencers.