Search results

The study investigated the effect of marketing communications’ dimensions on brand loyalty in the banking sector.

The study adopted the quantitative research approach which relied on the explanatory design due to the nature of the hypotheses tested. The convenience sampling technique was used to pull 377 customers of a branch of a commercial bank in Ghana. Furthermore, the PLS-SEM technique was deployed to assess the measurement model and test the research hypotheses.

Results show that the following dimensions of marketing communications are significant predictors of brand loyalty: direct marketing, public relations and sales promotion. The exception is advertising, which had an inverse relation with brand loyalty.

The results provide significant pointers to banks’ management that they should deploy a variety of marketing communication channels other than intensive advertising to reach and persuade customers.

The study illustrates the latest effort to extensively provide insights into how commercial banks could leverage marketing communication tools to sustain loyalty in an emerging economy that is intensively competitive.

Current research on mental health in the construction industry is fragmented, making it difficult to obtain a complete picture of young construction workers’ mental health conditions. This situation adversely affects research progress, mental health-care planning and resource allocation. To address this challenge, the purpose of this paper was to identify the themes of mental health conditions among young construction workers and their prevalence by geographical location.

The scoping review was conducted using meta-aggregation, guided by the CoCoPop (condition [mental health], context [construction industry] and population [construction workers 35 years old and younger]) and PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews) frameworks.

A total of 327 studies were retrieved, and 14 studies published between 1993 and 2022 met the inclusion criteria. The authors identified 13 mental health conditions and categorized them under nine themes. Mood disorders, anxiety disorders and substance-related disorders constituted the most researched themes. Studies predominantly focused on young male workers in the Global North. The prevalence estimates reported in most of the studies were above the respective country’s prevalence.

This review extends previous studies by focusing specifically on the themes of mental health conditions and giving attention to young construction workers whose health needs remain a global priority. The study emphasizes the need to give research attention to lesser-studied aspects of mental health, such as positive mental health. The need to focus on female construction workers and on homogenous sub-groups of young workers is also emphasized. The findings can guide future systematic reviews on the identified thematic areas and help to plan the development of interventions.

This study examines some pertinent individual-level factors and consequences of consumers' continuous social media brand engagement (SMBE) practices. Further, this study examines the moderating effect of other-efficacy to deepen the understanding.

Online survey data collected from 785 respondents, through a convenience sampling technique on Facebook, was analyzed through structural equation (SEM) modeling with AMOS 23.0.

The findings suggest that compatibility with lifestyle, perceived information quality and escapism, which significantly drive consumers' continuous engagement with brands on social media. However, perceived enjoyment does not. Other-efficacy duly moderates consumers' continuous SMBE practices. While continuous SMBE significantly drives consumer-based brand equity (CBBE), continuous SMBE does not have any significant relationship with consumers' subjective well-being (SWB).

This study reports robust findings on the effects of individual-level factors that drive consumers' continuous SMBE practices. However, the study only focused on Facebook brand pages. This is a limitation for generalizability of results because the research did not take a holistic view of all types of social media.

The research suggests a need for managers to project their brands and share relevant and stimulating information throughout their continuous SMBE with consumers to build strong consumer–brand relationships. Managers should also engage consumers with interesting social media messages as well as both informative and transformative creative strategies to excite them. This will further give consumers a reason to continuously interact with the brand on social media platforms.

This study is one of the very few works to tease out pertinent factors that drive consumers' continuous SMBE practices. The paper integrates the consumer-level factors and moderating effects of other-efficacy through the lens of Social Cognitive Theory (SCT) and Uses and Gratification Theory (UGT) to make a significant contribution to the SMBE literature.

Promoting positive mental health is increasingly being encouraged as the focus of research and policies on the mental health of construction personnel. Most measures of mental health, however, typically use negative indicators such as depression and anxiety and are not specifically developed for the construction workforce, especially those with a Global South background. These limitations have made it challenging to measure construction personnel’s positive mental health. The purpose of this study was, therefore, to develop a scale for measuring the positive mental health of construction personnel with a Global South background.

Guided by Keyes’ two-continua model of mental health, the study objectives were addressed through a mixed-methods study using the case of Ghana. Qualitative data collected from eight key stakeholder groups using 16 interviews and two rounds of focus group discussions were analysed thematically. Quantitative data were obtained through a survey of 425 construction personnel and analysed using confirmatory factor analysis and correlation analysis.

Thematic analysis revealed a four-dimensional structure of positive mental health, namely, emotional, psychological, social and spiritual. Confirmatory factor analysis and correlation analysis of the results indicated good instrument validity and reliability.

Existing measures of positive mental health are based on a three-dimensional model, i.e. emotional, social and psychological well-being. By including spiritual well-being, this study proposes a four-dimensional measurement model as a more comprehensive and promising measure to use in surveys of positive mental health among the construction workforce, especially those with a Global South background, and to develop suitable interventions for them.

Digital technology and SDGs have gained increasing interest from the research community. This chapter aims to explore the field through a holistic review of 188 publications from 2017 to 2022. For the systematic review of 188 articles, a three-step methodology comprising of PRISMA guidelines was performed, bibliometric analysis and text analysis using VOS-Viewer and Sentiment Analysis using RStudio had been undertaken. Bibliographic coupling revealed the following clusters Digital Space (Over all SDG), Localising SDGs, Financial Systems and Growth (SDG 8), Sustainable Supply Chain (SDG 9), Education (SDG 4), Energy Management (SDG 7), Smart Cities (SDG 11 and 13), Gender, Skills, and Responsibility (SDG 5 and 12), Food Management (SDG 1, 2 and 3), Business Innovation (SDG 8 and 9) and ICT (SDG 9). Next, co-occurrence analysis highlighted the following clusters Circular Economy (SDG 8), Higher Education System (SDG 4), Digital health (SDG 3), Industry 4.0 (SDG 9) and Supply Chain Management (SDG 9). Next, text analysis traced the most relevant areas of work within the theme. Finally, sentiment analysis revealed positive sentiments of the field. The research concluded that only a few SDGs had found major focus while the others don't have any solid ground in the literature. This chapter presents a knowledge structure by mapping the most relevant SDGs in the context of digital technology and sets directions for future research.

By extending the service robot acceptance model (sRAM), this study aims to explore and enhance the acceptance of chatbots. The study considered functional, relational, social, user and gratification elements in determining the acceptance of chatbots.

By using the purposive sampling technique, data of 321 service customers, gathered from millennials through a questionnaire and subsequent PLS-SEM modeling, was applied for hypotheses testing.

Findings revealed that the functional elements, perceived usefulness and perceived ease of use affect acceptance of chatbots. However, in social elements, only perceived social interactivity affects the acceptance of chatbots. Moreover, both user and gratification elements (hedonic motivation and symbolic motivation) significantly influence the acceptance of chatbots. Lastly, trust is the only contributing factor for the acceptance of chatbots in the relational elements.

The study extends the literature related to chatbots and offers several guidelines to the service industry to effectively employ chatbots.

This is one of the first studies that used newly developed sRAM in determining chatbot acceptance. Moreover, the study extended the sRAM by adding user and gratification elements and privacy concerns as originally sRAM model was limited to functional, relational and social elements.

Drawing on the natural resource-based view (NRBV) theory, the study aimed to examine the mediating role of green innovation (GI) in the nexus between green human resource management practices (Green HRMPs) and sustainable business performance (SBP).

This study adopted the descriptive time-lagged research design. Data were collected from 278 managerial staff of five mining companies in Ghana at different waves within a 3-month interval. Descriptive and inferential statistics were used to analyse the data received using the statistical package for the social sciences (SPSS) statistics (V. 26.0) and Smart PLS (V.4.0).

The study found that Green HRMPs significantly related more to economic performance (EP) than social performance (SP) but did not significantly relate to environmental performance (EnP). Moreover, the results revealed that GI partially mediated the nexus between Green HRMPs and both SP and EP but fully mediated the link between Green HRMPs and EnP.

The relevance of Green HRMPs in ensuring corporate sustainability has been largely established in the extant literature. However, there is an evidential dearth of studies in the literature concerning the mediating role of GI in the nexus between Green HRMPs and SBP, especially in developing economies context. Hence, this study serves as a significant contributing card from Ghana by advancing the NRBV theory.

Public–private partnership (PPP), a project financing arrangement between private investors and the public sector, has revolutionized the approach to the funding and development of public infrastructure worldwide. However, the increasing cases of financial risks and poor financial risk management related to the model threaten the sustainability and financial success of PPP projects leading to huge financial investment losses. This study aims to review existing literature to establish the key measures to control the financial risks of sustainable PPP projects.

A PRISMA-compliant systematic literature review method was used in this study. Data were sourced from academic databases consisting of 56 impactful peer-reviewed journal articles.

The review outcomes demonstrate 41 critical factors (measures) in mitigating the financial risks of sustainable PPP projects. They include minimum revenue guarantee, strategic alliance with private investors, financial transparency and accountability and sound macroeconomic policies. The principal results of the study were categorized and conceptualized into a financial risk management maturity model for sustainable PPP projects. Lastly, the study reveals that further studies and project policies must focus more on addressing financial challenges relating to climate risks, and health and safety concerns such as COVID-19 outbreak that have negative impacts on PPP projects.

The results provide essential research gaps and directions for future studies on measures to mitigate the financial risks of sustainable PPP projects. However, this study used small but significant existing publications.

A checklist and a conceptual maturity model are provided in this study to help practitioners to learn and improve upon their practices to mitigate the financial risks of sustainable PPP projects.

This study contributes to managerial measures to reduce huge losses in financial investments of PPP projects and the attainment of sustainability in public infrastructure projects with a financial risk maturity model.

Recent United Nations Climate Change Conferences recognise extreme climate change of heatwaves, floods and droughts as threatening risks to the resilience and success of public–private partnership (PPP) infrastructure projects. Such conferences together with available project reports and empirical studies recommend project managers and practitioners to adopt smart technologies and develop robust measures to tackle climate risk exposure. Comparatively, artificial intelligence (AI) risk management tools are better to mitigate climate risk, but it has been inadequately explored in the PPP sector. Thus, this study aims to explore the tools and roles of AI in climate risk management of PPP infrastructure projects.

Systematically, this study compiles and analyses 36 peer-reviewed journal articles sourced from Scopus, Web of Science, Google Scholar and PubMed.

The results demonstrate deep learning, building information modelling, robotic automations, remote sensors and fuzzy logic as major key AI-based risk models (tools) for PPP infrastructures. The roles of AI in climate risk management of PPPs include risk detection, analysis, controls and prediction.

For researchers, the findings provide relevant guide for further investigations into AI and climate risks within the PPP research domain.

This article highlights the AI tools in mitigating climate crisis in PPP infrastructure management.

This article provides strong arguments for the utilisation of AI in understanding and managing numerous challenges related to climate change in PPP infrastructure projects.