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The emergence of social media platforms has revolutionized how brands develop partnerships with social media influencers (SMIs). However, users are seeking more meaningful engagement with SMIs, and little is known about how brands can shift their focus from transient engagements to continued engagement that builds long-term brand–consumer relationships. Extant research has provided inconsistent findings regarding consumer engagement behavior. To address this knowledge deficit, we contribute to the consumer engagement literature by developing and testing a conceptual model that explores and explains the relationships between the factors that influence continued engagement intention (CEI), a form of behavioral intention.

A literature review was conducted to identify gaps and develop a theoretically informed conceptual model and hypotheses. Survey data from 604 Instagram SMI followers were analyzed using partial least squares structural equation modeling using SmartPLS 3.3.3 to assess the structural model relationships and conduct post hoc analysis.

The findings suggest that it is important to positively influence consumer responses to elicit CEI. Furthermore, homophily attitudes toward SMIs moderate the relationship between SMI experience and CEI.

Brands must work with SMIs to create positive SMI experiences and develop CEI. Furthermore, SMIs should focus on brands that fit their lifestyles to enhance homophily attitudes and forge CEI.

This study contributes to the literature by combining social exchange and flow theories to develop and test a holistic framework for examining CEIs regarding SMIs and brands. The findings show that creating positive SMI experiences benefits brands seeking CEI.

This study presents a systematic literature review (SLR) of the interdisciplinary literature on drones in last-mile delivery (LMD) to extrapolate pertinent insights from and into the logistics management field.

Rooting their analytical categories in the LMD literature, the authors performed a deductive, theory refinement SLR on 307 interdisciplinary journal articles published during 2015–2022 to integrate this emergent phenomenon into the field.

The authors derived the potentials, challenges and solutions of drone deliveries in relation to 12 LMD criteria dispersed across four stakeholder groups: senders, receivers, regulators and societies. Relationships between these criteria were also identified.

This review contributes to logistics management by offering a current, nuanced and multifaceted discussion of drones' potential to improve the LMD process together with the challenges and solutions involved.

The authors provide logistics managers with a holistic roadmap to help them make informed decisions about adopting drones in their delivery systems. Regulators and society members also gain insights into the prospects, requirements and repercussions of drone deliveries.

This is one of the first SLRs on drone applications in LMD from a logistics management perspective.

This study aims to explore how service delivery can be enhanced through digital transformation in the public sector in South Africa.

This case study used a qualitative research approach to obtain data through semi-structured interviews. The units of analysis were made up of individual professionals limited to purposive sampling to select chief information officers, investigators and administrative officers from national government departments and state-owned enterprises. The collected data from 12 participants was thematically analysed. The findings revealed that the government lacks legislation and strategy for digital transformation, leading to inconsistent implementation of digital transformation that enhances service delivery in the public sector of South Africa.

The findings revealed that the government lacks legislation and strategy for digital transformation, leading to inconsistent implementation of digital transformation that enhances service delivery in the public sector of South Africa.

The study was limited to the public sector of South Africa; however, its recommendations are applicable to all organisations that need to provide their services using digital transformation.

Practically, the implications of this study will serve as a resourceful benchmark for the public sector and other organisations.

Socially, the implications of this study ensure proper implementation of its recommendations to enhance service delivery in the public sector and other organisations.

Regarding the value that this study brings, it proposes an amendment of the current legislative framework in favour of one that covers digital transformation, which has become dominant in today’s enhanced provision of service delivery.

This study serves a dual purpose. First, it aims to explore the phase-wise progression that small and medium-sized enterprises (SMEs) and startups must undertake to become successful ecosystem partners, supporting large industrial firms in their circular transition. Second, it seeks to examine how these small firms manage change and foster collaborative cultures through strategies enabled by positive organizational scholarship (POS) during their phased evolution.

This study provides empirical evidence through a multiple case study-based approach involving 12 born-circular SMEs/startups from 5 diverse Indian industrial sectors. Insights were gathered by conducting two rounds of semi-structured interviews with 24 participants and one validatory seminar with eight participants.

This research identified three distinct and complementary phases – compare, compete and collaborate – that SMEs/startups can undergo to emerge as successful ecosystem partners. Each phase encompasses specific business practices, including various circular activities. These activities serve as clear indicators of the smaller firms’ potential competence in aiding larger firms during their circular transitions.

This paper contributes to the theoretical understanding of the circular economy by outlining a trajectory for SMEs/startups to establish successful partnerships. Another contribution is the application of POS as a positive change management paradigm to facilitate circularity. Additionally, the study highlights the context of developing nations, which remain underexplored compared to their developed counterparts in circularity initiatives.

This research aims to contribute to the ongoing debate on the prospective advantages of implementing accrual accounting in countries where such a transition is underway, with a focus on Italian municipalities. The research seeks to ascertain the requisite conditions, in public sector accounting mangers’ perception, for a useful transition from modified cash accounting to full accrual accounting within the Italian context.

The methodology adopted is Qualitative Comparative Analysis, which involves conducting a survey through semi-structured interviews with accounting managers in municipal accounting departments. The sample is drawn from municipalities in the Emilia-Romagna region with populations exceeding 15,000 inhabitants.

The study shows that some stakeholders have a tangible demand for financial statement information. They believe that accrual accounting statements provide accurate insights into municipal financial health and that these statements are comparable across municipalities. All these factors together constitute sufficient conditions for considering useful the implementation of accrual accounting in local governments, in the opinion of public sector accounting managers.

This paper contextualises the broader international debate on transitioning to full accrual accounting in the New Institutional Sociology framework. The Qualitative Comparative Analysis is an underutilised methodology within the field of public sector accounting, and the public sector accounting managers’ point of view is scarcely investigated in literature.

One of the open questions is how to define a complete semantic description of an Internet of Things (IoT) system and how to ensure the device’s identification in this type of system. To answer this question, the authors needed to propose a mechanism to describe an IoT system based on an IoT context ontology description. This mechanism is based on semantic web services creation to identify objects in IoT system. This paper aims to propose a model to describe the IoT system. The authors suggest an approach to describe each category of contextual information separately and ensure the adaptation in the IoT system.

One of the open questions is how to define a complete semantic description of an IoT system and how to ensure the device’s identification in this type of system. To answer this question, the authors needed to propose a mechanism to describe an IoT system based on an IoT context ontology description. This mechanism is based on semantic web services creation to identify objects in IoT system.

One of the open questions is how to define a complete semantic description of an IoT system and how to ensure the device’s identification in this type of system. To answer this question, the authors needed to propose a mechanism to describe an IoT system based on an IoT context ontology description. This mechanism is based on semantic web services creation to identify objects in IoT system. This paper aims to propose a model to describe the IoT system. The authors suggest an approach to describe each category of contextual information separately and ensure the adaptation in the IoT system.

One of the open questions is how to define a complete semantic description of an IoT system and how to ensure the device’s identification in this type of system. To answer this question, the authors needed to propose a mechanism to describe an IoT system based on an IoT context ontology description. This mechanism is based on semantic web services creation to identify objects in IoT system. This paper aims to propose a model to describe the IoT system. The authors suggest an approach to describe each category of contextual information separately and ensure the adaptation in the IoT system.

Intelligent prediction of node localization in wireless sensor networks (WSNs) is a major concern for researchers. The huge amount of data generated by modern sensor array systems required computationally efficient calibration techniques. This paper aims to improve localization accuracy by identifying obstacles in the optimization process and network scenarios.

The proposed method is used to incorporate distance estimation between nodes and packet transmission hop counts. This estimation is used in the proposed support vector machine (SVM) to find the network path using a time difference of arrival (TDoA)-based SVM. However, if the data set is noisy, SVM is prone to poor optimization, which leads to overlapping of target classes and the pathways through TDoA. The enhanced gray wolf optimization (EGWO) technique is introduced to eliminate overlapping target classes in the SVM.

The performance and efficacy of the model using existing TDoA methodologies are analyzed. The simulation results show that the proposed TDoA-EGWO achieves a higher rate of detection efficiency of 98% and control overhead of 97.8% and a better packet delivery ratio than other traditional methods.

The proposed method is successful in detecting the unknown position of the sensor node with a detection rate greater than that of other methods.

Grounded in self-congruency theory, this study aims to investigate the impact of different types of congruence in social media influencer marketing on consumers’ online impulse buying intentions under the moderating influence of wishful identification.

This study collects survey responses from an online sample of 232 social media users and analyses them using partial least squares structural equation modelling.

This study delineates two distinct pathways influencing online impulse buying intentions within influencer marketing: direct consumer–product congruence and the conditional role of consumer–influencer congruence. Particularly, the alignment between a consumer’s self-image and the product’s attributes independently drives online impulse buying intentions. Conversely, consumer–influencer congruence, despite high alignment, fails to spur online impulse buying intentions unless amplified by wishful identification – the consumer’s aspirational desire to emulate the influencer. This finding underscores the complexity of impulsive consumer behaviours in the digital marketplace, highlighting the pivotal role of product appeal and the conditional influence of influencer relationships on spontaneous purchasing decisions.

This study pioneers by elucidating the congruence interplay between consumers, influencers and products in online impulse buying, emphasising wishful identification as a critical moderating factor. Theoretically, it expands self-congruency theory by detailing the distinct roles of congruence types on impulsive behaviours, notably underlining the essential role of wishful identification for the effect of consumer–influencer congruence. Practically, the insights equip brands with a deeper understanding of the key drivers behind impulsive purchases in an influencer-centric digital marketplace, offering strategic guidance for optimising influencer collaborations and product presentations to enhance consumer engagement and sales.