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The retail landscape is dramatically changing due to a series of socio-economic and technological challenges, which can be faced through the adoption of smart technologies. Accordingly, a significant number of publications in this field have been produced, albeit with fragmented results. Therefore, this paper aims at both providing a clear and organised overview of the main smart technologies for physical retailing, in terms of application fields and expected impact, while identifying the major shortcomings and future research avenues.

The research conducts a systematic review of the literature concerning the assimilation of smart technologies within physical retail environments, resulting in the analysis of 103 papers published from 2005 to 2023. The review highlights (1) the main smart technologies employed in retail stores, (2) their application area and (3) the beneficiaries of their adoption. Accordingly, these three aspects are initially assessed independently and then examined in combination.

The analysis presents a comprehensive list of 16 key technologies (what) that can support a wide range of processes, spanning from back-end functions to front-end activities, also enabling the connection with online channels (where), catering several and different benefits (why) to both customers and retailers (who). Besides, the research points out many uncovered topics that could be addressed by the academic community.

To the best of the authors’ knowledge, the review is the first one in the literature offering a thorough and organised overview of the different available technologies for in-store application and their impact on physical retail processes.

Technology-enabled healthcare focuses on providing better information flow and coordination in healthcare operations. Technology-enabled health services enable hospitals to manage their resources effectively, maintain continuous patient engagement and provide seamless services without compromising their perceived quality.

This study investigates the role of technology-enabled health services in improving perceived healthcare quality among patients. Data are collected from the users (n = 418) of health platforms offered in multi-specialty hospitals. Multiple learners are employed to accurately represent the users' perceived quality regarding the perceived usefulness of the features provided via these digital health platforms.

The best-fitted model using a decision tree classifier (accuracy = 0.86) derives the accurate significance of features offered in the digital health platform in fostering perceived healthcare quality. Diet and lifestyle recommendations (30%) and chatting with health professionals (11%) are the top features offered in digital health platforms that primarily influence the perceived quality of healthcare among users.

The predictability of perceived quality with the individual features existing in the digital health platform, the significance of the features on the perceived healthcare quality and the prediction rules showing the combined effect of features on healthcare quality can help healthcare managers accelerate digital transformation in hospitals by improving their digital health platform, designing and offering new health packages while strengthening their e-infrastructure.

The study represents perceived healthcare quality with the features offered in digital health platforms using machine learners based on users' post-pandemic experience. By advancing digital platforms with more patient-centric features using emerging technologies, this model can further foresee its impact on the perceived quality of healthcare, offering valuable directions to healthcare service providers. The study is limited to focusing on digital health platforms that can deal with people's general healthcare needs.

This study aims to investigate the factors that influence the continuance intention to use personal cloud storage services among Generation Y.

A quantitative online survey was carried out to collect data from 271 respondents. Structural equation modelling with SmartPLS 4.0 software was used to run the analysis and examine the hypothesized relationships in the research model.

The study revealed that both satisfaction and habit exert a significant influence on continuance intention, whereas self-efficacy does not demonstrate a significant effect. In addition, satisfaction was found to be influenced by confirmation, perceived usefulness and perceived security. Furthermore, confirmation and cloud storage service quality were found to impact perceived usefulness, while confirmation also had an effect on perceived security. However, the hypothesized moderating role of perceived privacy risk in the relationship between perceived usefulness, perceived security and satisfaction was not supported.

This study advances the field by adapting an expanded expectation-confirmation model that delineates the nuanced impacts of habit, user satisfaction and self-efficacy on Generation Y’s continuance intention to use personal cloud storage services. It challenges the conventional wisdom regarding self-efficacy’s influence on technology adoption, offering a more intricate portrayal of its role. This research contributes a distinctive theoretical perspective, emphasizing the complex interplay of factors that inform sustained user engagement with cloud technologies.

The purpose of this study is to investigate the continuous intention to use blockchain and FinTech innovations, focusing on the direct impact of user trust and perceived risks. It seeks to test how information technology (IT) quality directly affects user-perceived risk and trust and to identify how IT quality can influence FinTech continuance intentions. By examining these relationships, the study provides insights into how improvements in IT quality can mitigate perceived risks and enhance user trust, ultimately fostering sustained use of FinTech and blockchain technologies.

To achieve the purpose of this study, the model and hypotheses were examined based on the partial least squares structural equation modeling (PLS-SEM).

Results revealed that perceived risk is negatively impacted by system quality, while trust is positively impacted by information quality, and the most significant result in the study is continuous-use intention and uncertainty both are impacted by service quality. Also, the study used some control variables, and two of them (i.e. FinTech type and education) showed a positive significant relationship with continuance-use intention.

This study identifies several causal relationships between the continuance-use intention of blockchain and FinTech innovations and various factors, which can provide valuable insights for managers, enabling them to formulate appropriate strategies to foster sustainable growth in FinTech and blockchain. By leveraging these findings, managers can enhance IT quality, reduce perceived risks and build user trust, thereby promoting the ongoing adoption and success of blockchain and FinTech innovations.

The outcomes obtained will help both FinTech providers and researchers elucidate and understand the situation of users’ concerns about the unexpected risks/uncertainty in FinTech transactions can be mitigated through providing a high level of quality IT service and systems. Two main strategies can be merged to be used by FinTech providers/managers, first: trust building, second: risk-mitigating, both strategies can be used in the light of IT innovation and its aspects to meet the sustainable growth of FinTech.

The aim of the study is to investigate the impact of job characteristics on gig worker performance in India. In addition, this study examines the role of work–life balance as a mediator in exploring the impact of job characteristics, namely, flexibility and job autonomy and person–job fit on gig workers performance among location-based gig workers.

A total of 266 responses were collected by gig workers using a questionnaire-based survey. The responses were analyzed using the partial least square structural equation modeling technique.

The study results indicate that factors of job characteristics and person–job fit significantly enhance the gig worker performance and also finds work–life balance as significant mediator. These results provide evidence for the hypotheses, which emphasizes that these aspects will have a beneficial effect on the performance of gig workers.

This research contributes to the field of the gig economy by empirically examining the study factors to understand the work dynamics in flexible work arrangements. Based on the findings, the gig platforms and policymakers can formulate strategies for establishing job design for enhancing work–life balance, which subsequently enhances gig workers performance.

As fitness apps have integrated gamification elements into their design to transform exercise into a compelling and competitive experience, this study draws on the expectation confirmation model (ECM) and self-determination theory (SDT) to propose a comprehensive framework for sustained usage by satisfying the psychological needs of users.

A longitudinal study design is utilized where data from 598 fitness app users were gathered over two distinct phases separated by 24 weeks, where data were analyzed using structural equation modeling.

The findings until phase 1 depict that motivational affordances significantly affect mastery, autonomy and relatedness, which in turn exert a significant influence on flow. Identification and compliance have a more pronounced effect in phase 2 compared to stage 1 of the analysis.

Individuals are more prone to being swayed by fellow members of their social group who share an affiliation with fitness apps, leading them to sustain their usage of fitness apps. These insights can potentially guide app developers and marketers in formulating strategies based on modifiable factors to foster sustained growth for gamified fitness apps.

This study takes a novel stance by employing social impact theory (SIT) in a longitudinal setting to reveal how users react to identification and compliance effects during initial and post-adoption usage of gamified fitness apps.

Given the rising popularity of mobile commerce among young consumers, this study aims to examine the effect of mobile applications service quality (MASQ), service convenience (SERCON) and satisfaction contributing to the retention of young consumers towards mobile applications.

Primary data were collected from 213 active online young smartphone users who have used mobile apps for shopping through a structured questionnaire. Structural equation modelling is used to analyse the data.

The results of this study reveal that both MASQ and SERCON strongly support satisfaction, which leads to the retention of young customers.

This study is one of the few relevant pieces of research that would benefit mretailers encompassing mobile commerce applications to improve their MASQ and SERCON with cutthroat competition in gaining and retaining young customers for shopping through smartphone applications.

This study explores key dimensions of mobile commerce activities (MCAs), evaluates their impact on firm performance and examines the role of mobile commerce performance as a mediator and the role of industry competitive intensity as a moderator.

The qualitative research identified 21 principal retailers’ MCAs. A survey involving 172 retail executives was then conducted to examine the structure of MCAs and their impacts on firm performance.

Our findings reveal that the MCAs comprise four dimensions: guidance, connection, in-store conversion and relation. These dimensions jointly impact firm performance through mobile commerce performance, moderated by industry competition.

This study provides a foundational understanding of MCAs. Future research should continue to explore how these dimensions interact.

Retailers can enhance their management of MCA investments by focussing on four key areas: guidance, contact, in-store conversion and relation. By customizing activities and prioritizing those that strengthen customer relationship management within one area, retailers can effectively align their MCA strategies with their specific business context.

The study’s originality lies in identifying and empirically testing the dimensionality of MCAs, emphasizing the role of customer-centric mobile performance and expanding the understanding of MCA value creation.

With the advancement of digital transformation, it is important for e-retailers to use artificial intelligence (AI) for customer engagement (CE), as CE enables e-retail brands to succeed. Essentially, AI e-marketing (AIeMktg) is the use of AI technological approaches in e-marketing by blending customer data, and Retail 4.0 is the digitisation of the physical shopping experience. Therefore, in the era of Retail 4.0, this study investigates the factors influencing the use of AIeMktg for transforming CE.

The primary data were collected from 305 e-retailer customers, and the analysis was performed using a quantitative methodology.

The results reveal that AIeMktg has tremendous applications in Retail 4.0 for CE. First, it enables marketers to swiftly and responsibly use data to anticipate and predict customer demands and to provide relevant personalised messages and offers with location-based e-marketing. Second, through a continuous feedback loop, AIeMktg improves offerings by analysing and incorporating insights from a 360-degree view of CE.

The main contribution of this study is to provide theoretical underpinnings of CE, AIeMktg, factors influencing the use of AIeMktg, and customer commitment in the era of Retail 4.0. Subsequently, it builds and validates structural relationships among such theoretical underpinning variables in transforming CE with AIeMktg, which is important for customers to expect a different type of shopping experience across digital channels.

This article introduces the “YouWalk-YouReclaim” mobile application as a transformative tool aimed at co-assessing and enhancing campus environments in a post-pandemic context. It seeks to address the need for inclusive, dynamic and technology-driven spaces within university settings.

The study employs a comprehensive assessment framework through a case study at Northumbria University, Newcastle. It involves over 100 students from diverse fields who utilised the application to evaluate significant areas on campus, such as Student Central, Northumberland Road and the Northumbria Library. The methodology places emphasis on direct user engagement and the use of the application’s inbuilt-image library and visual documentation features.

The application effectively evaluated the functionality, spatial dynamics and user experiences across various campus spaces. Key findings include the importance of adaptability, personalised spaces and enhanced wayfinding to meet the evolving needs of the university community. The study also noted the potential of the app to facilitate multidimensional assessments and support user-centric improvements.

The findings suggest that institutions can leverage technology like the “YouWalk-YouReclaim” app to better understand and optimise their campus spaces, fostering more responsive, user-focused and sustainable environments. The study advocates continuous technological enhancements and user-centred assessments to cultivate efficient and enriching campus experiences.

This study is novel in its integration of digital technology with user-centred approaches to assess and enhance campus environments. By enabling real-time feedback and inclusive participation, “YouWalk-YouReclaim” exemplifies an innovative approach to campus space management.