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In Ghana, the adoption and application of green building concepts and technologies have not been fully explored. The study aimed to look into the key barriers and how they affect this.

Purposive and snowball sampling techniques were used to select a total of 292 construction industry stakeholders in Ghana who provided information via a questionnaire survey used for the data collection. Exploratory factor analysis and Partial least squares structural equation modelling (PLS-SEM) were used for computing the data analyses.

According to the study findings, the top five most critical barriers to the uptake of green building concepts and technologies (GBCs and Ts) in Ghana are: lack of government incentives/supports for implementing green building technologies (GBTs), lack of knowledge and awareness of GBTs and their benefits, lack of GBTs databases and information, Lack of green building (GB) expertise/skilled labour and Higher costs of GBTs. Principal Component Factor Analysis was used to further analyse the data, which allowed for the reduction of the 27 (27) factors to just four (4) underlying critical barriers: (1) government and knowledge-associated barriers, (2) technical barriers, (3) cost and finance barriers and (4) stakeholders’ attitude barriers. PLS-SEM techniques were used to analyse this collection of barriers, and the results showed that stakeholders’ attitude-associated barriers and cost and finance-related barriers have a significant negative influence on the uptake of GBCs and Ts in Ghana. This study’s findings have provided empirical evidence of the critical barriers to the uptake of GBCs and Ts from all stakeholders. Stakeholders desirous of implementing GBCs and Ts would work against the negative influences on the uptake of GBCs and TS.

Although there has been an abundance of research to examine the critical barriers to GB, however, the uniqueness of this study is nested in modelling the influence of the barriers on the adoption of GBCs and Ts using the PLS-SEM path modelling.

User trust in social networking sites (SNS) has become an important issue in SNS discussions. This is because of its impact on knowledge sharing, social commerce, social interaction, among many others. However, information systems researchers have primarily explored the benefits of trust with little attention to its antecedents. In an attempt to address this knowledge gap, this study proposed a model that investigated the factors that promote trust among SNS users. Data was gathered from voluntary respondents using a questionnaire. A PLS-SEM analysis of 912 valid responses suggested that Norm of Reciprocity, Social Interaction Ties and Identification are significant factors that encourage Trust among SNS users. Shared Language was also identified to have impact on Norm of Reciprocity, Social Interaction Ties and Identification. The results of the study provide significant theoretical and practical contributions. They bridge the knowledge gap regarding the formation of Trust on SNS. The model evaluated explains 49.6% of the variance in Trust and thus suitable for analyzing the antecedents of Trust on SNS. Furthermore, with the significance of Identification, Social Interaction Ties and Norm of Reciprocity on Trust, SNS developers are tasked to offer SNS features that proliferate the formation of these factors as well as shared interpretations.

Considering the continuous rise in the public debt stock of developing countries (particularly Ghana) with the unstable economic growth rate for the past decades and the recent borrowing because of the impact of COVID 19, this paper aims to examine the causal relationships between public debt and economic growth over time.

The paper uses a dynamic multivariate autoregressive-distributed lag (ARDL)-based Granger-causality model to test the causal relationships between public debt and economic growth [gross domestic product (GDP)]. Annual time-series data that spanned 1978–2018 were sourced from the World Bank Development Indicator database and the IMF fiscal Affairs Department Database and WEO.

The results reveal that public debt has no causal relationship with GDP in the short-run but there is unidirectional Granger causality running from public debt to GDP in the long run. Again, investment spending has a negative bi-directional causal relationship with GDP in the short-run but they have a positive bi-directional causal relationship in the long run. Conversely, no short-run causal relationship exists between government consumption expenditure and GDP but long-run Granger causality runs from government consumption expenditure to GDP. Finally, public debt has a positive impact on the inflation rate in the short run.

The findings imply that government(s) must ensure high fiscal discipline to serve as a precursor for the effective and efficient use of recent borrowing, that is, the loans should be used for highly prioritized projects (preferably investment spending) that are well evaluated and self-sustained to add positively to the GDP.

This paper provides contemporary findings to augment extant literature on public debt and economic growth by using variables and empirical models, which prior studies could not sufficiently cover in a developing country perspective and affirms that public debt contributes to GDP only in the long run.

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 paper aims to explore how parasocial relationships with Korean celebrity endorsers on social media result in brand credibility and loyalty.

The participants were identified through a purposive sampling approach, and they were composed of consumers who purchased Korean-celebrity-endorsed products and services of a telecommunications company. The hypothesized relationships were gauged using a predictive approach as a research design via partial least squares (PLS) path modeling.

The findings show that all hypothesized relationships are supported. In particular, social media interaction was found to have a substantial, positive and significant effect on self-disclosure. Moreover, self-disclosure has a considerably significant and direct effect on parasocial relationships and was found to indirectly affect the link between social media interactions and parasocial relationships. The results further reveal that social media interactions and parasocial relationships predict source trustworthiness, leading to brand credibility and loyalty.

To the best of the authors’ knowledge, the present undertaking is the only study that examined how parasocial relationships on social media are built when foreign celebrities, in this case, the well-known Korean popular group BTS, endorse telecommunications products and services.

La presente investigación explora cómo las relaciones parasociales con celebridades coreanas en las redes sociales generan credibilidad de marca y lealtad.

Los participantes se identificaron mediante un muestreo intencional y estaban compuestos por consumidores que compraban productos y servicios de una empresa de telecomunicaciones avalados por famosos coreanos. Las relaciones hipotetizadas se midieron utilizando un enfoque predictivo como diseño de investigación mediante un modelo de mínimos cuadrados parciales (PLS).

Los resultados muestran que todas las relaciones hipotetizadas se confirman. En particular, la interacción con los medios sociales tiene un efecto sustancial, positivo y significativo en la autodivulgación. Además, la autodivulgación tiene un efecto considerablemente significativo y directo en las relaciones parasociales y se descubrió que afecta indirectamente al vínculo entre las interacciones en los medios sociales y las relaciones parasociales. Los resultados revelan además que las interacciones en los medios sociales y las relaciones parasociales predicen la fiabilidad de la fuente, lo que conduce a la credibilidad de la marca y a la lealtad.

El presente trabajo es el único estudio que examina cómo se construyen las relaciones parasociales en los medios sociales cuando celebridades extranjeras, en este caso, el conocido grupo popular coreano BTS, promocionan productos y servicios de telecomunicaciones.

本研究探讨了在社交媒体上与韩国名人的寄生关系如何建立品牌可信度和忠诚度。

通过目的性抽样确定参与者, 包括购买韩国名人代言的电信公司产品和服务的消费者。研究设计使用偏最小二乘法（PLS）模型对假设关系进行预测测量。

研究结果表明, 所有假设关系都得到了证实。特别是, 社交媒体互动对自我披露具有实质性的、积极的和显著的影响。此外, 自我披露对寄生关系也有明显的直接影响, 并被发现间接影响社交媒体互动与寄生关系之间的联系。研究结果进一步揭示了社会化媒体互动和寄生关系能够预测来源的可信度, 从而提高品牌可信度和忠诚度。

研究结果表明, 所有假设的关系都得到了证实。特别是, 社交媒体互动对自我披露具有实质性的、积极的和显著的影响。此外, 自我披露对寄生关系也有明显的直接影响, 并被发现间接影响社交媒体互动和寄生关系之间的联系。研究结果进一步揭示了社会化媒体互动和寄生关系能够预测来源的可信度, 从而提高品牌可信度和忠诚度。

本文是唯一一篇研究外国名人在社交媒体上推广电信产品和服务时如何建立寄生社会关系的研究。