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Understanding the multifaceted images of tourism destinations is critical for effective destination marketing and management strategies. Traditional approaches, including conceptualization of destination images or analysis of their antecedents and consequences, are commonly used. This study aims to advocate the inclusion of visitors’ latent profiles based on cognitive images to enrich the evaluation and formulation of destination marketing and management strategies.

The analysis focuses on Serbia, an emerging destination, that attracts an increasing number of first-time, repeat and prospective visitors. Exploratory factor analysis and confirmatory factor analysis were used to test the potential dimensions (tangible and intangible cultural destination; infrastructural and accessible destination; active, nature and family destination; sensory and hospitable destination; and welcoming, value for money (VFM) and safe destination) of the cognitive destination image factors scale while subtypes (profiles) were obtained using latent profile analysis (LPA).

The cognitive image component encompasses the perceived attributes of a destination, whether derived from direct experience or acquired through other means. The study identified the following profiles: conventional destination; sensory and hospitable destination; welcoming, VFM and safe destination; secure and active family destination and accessible cultural destination, which are presented individually with their sociodemographic assets.

The main contribution of the paper is the application of a novel method (LPA) for profiling visitor segments based on cognitive destination image. From a theoretical perspective, this research contributes to the extant body of literature pertaining to the destination image, thereby facilitating the identification of discrete latent visitor segments and elucidating noteworthy differences among them concerning a cognitive image.

Following the recent rise in generative artificial intelligence (GenAI) tools, fundamental questions about their wider impacts have started to reverberate around various disciplines. This study aims to track the unfolding landscape of general issues surrounding GenAI tools and to elucidate the specific opportunities and limitations of these tools as part of the technology-assisted enhancement of mechanical engineering education and professional practices.

As part of the investigation, the authors conduct and present a brief scientometric analysis of recently published studies to unravel the emerging trend on the subject matter. Furthermore, experimentation was done with selected GenAI tools (Bard, ChatGPT, DALL.E and 3DGPT) for mechanical engineering-related tasks.

The study identified several pedagogical and professional opportunities and guidelines for deploying GenAI tools in mechanical engineering. Besides, the study highlights some pitfalls of GenAI tools for analytical reasoning tasks (e.g., subtle errors in computation involving unit conversions) and sketching/image generation tasks (e.g., poor demonstration of symmetry).

To the best of the authors’ knowledge, this study presents the first thorough assessment of the potential of GenAI from the lens of the mechanical engineering field. Combining scientometric analysis, experimentation and pedagogical insights, the study provides a unique focus on the implications of GenAI tools for material selection/discovery in product design, manufacturing troubleshooting, technical documentation and product positioning, among others.

Global crises have become increasingly recurrent events that jeopardize public-private partnerships (PPPs). In this context, the purpose of this paper is to expose the PPP-crisis research agenda by combining bibliometric and network analyses.

The PPP literature associated with global crises between the 2008 global financial crisis and 2022 was analyzed in three stages: (1) paper selection and screening for the inclusion/exclusion of articles relevant to this research, (2) semantic network development for examining thematic relationships among selected papers by considering the co-occurrence of keywords within the chosen studies and (3) calculation of network metrics for analysis.

The paper identified six research avenues for the PPP-crisis agenda: public interest, relational governance, risk management, user-pay PPPs, crisis management and financial performance. The PPP-crisis literature has spread significantly in the last five years driven by the case study approaches on a national or regional basis. Conversely, non-crisis periods generate room to strengthen user-pay PPPs and relational governance. The pandemic and post-pandemic times shared the priorities of the 2008 financial crisis but also strengthened the management of the risks and the structural drivers of the global crisis.

This study demonstrates that during global crisis periods, the public interest and financial performance gain relevance in a detriment of structural solutions to social legitimacy erosion of PPPs because of the urgency of giving tools to the public and private sectors to tackle the financial issues, which steer future issues for PPPs.

A lack of suitably qualified Building Information Modelling (BIM) professionals is understood to be a major barrier towards higher uptakes of BIM in the Australian construction industry. In response, Australian universities have tried to integrate the teaching of BIM into construction-related curricula, but with limited success. The acknowledged impediment is the lingering mismatch between what universities offer and what industry actually needs. However, the exact nature of that mismatch has yet to be identified. This study addresses that knowledge gap. It assesses both the current status of BIM competencies among university graduates and explores how BIM education at Australian universities may be improved to deliver BIM work readiness, as required by the industry.

This paper employed a qualitative research approach, utilizing 17 semi-structured interviews with experts in the Australian BIM industry. The Person-Organization (PO) fit theory, which emphasizes the congruence between individual and organizational characteristics, was utilized as a theoretical framework to examine the compatibility between “demand” and “ability” perspectives. The resulting data were analysed using this theoretical framework to gain insights into the PO fit perspectives in relation to BIM industry practices.

Findings reveal that graduates are generally competent regarding the use of BIM software. However, employers require much more than software skills, and expect recruits to have the capability to implement BIM as a process according to information management standards. Specifically, graduates are significantly deficient in matters of BIM protocols, collaboration and coordination, information workflows as well as completion and handover procedures.

This study is the first of its kind that bridges the gap between industry expectations and university education, in the Australian context, moving beyond the common discourse in education literature, which is exclusively focused on assessing students’ perceptions about BIM.

The application of circular economy (CE) has received wide coverage in the built environment, including public-private partnership (PPP) infrastructure projects, in recent times. However, current studies and practical implementation of CE are largely associated with construction demolition, waste and recycling management. Few studies exist on circular models and success factors of public infrastructures developed within the PPP contracts. Thus, the main objective of this article is to identify the models and key success factors associated with CE implementation in PPP infrastructure projects.

A systematic review of the literature was undertaken in this study using forty-two (42) peer-reviewed journal articles from Scopus, Web of Science, Google Scholar and PubMed.

The results show that environmental factors, sustainable economic growth, effective stakeholder management, sufficient funding, utilization of low-carbon materials, effective supply chain and procurement strategies facilitate the implementation of CE in PPP infrastructure projects. Key CE business models are centered around the extension of project life cycle value, circular inputs and recycling and reuse of projects.

Although the study presents relevant findings and gaps for further investigations, it has a limited sample size of 42 papers, which is expected to increase as CE gain more prominence in PPP infrastructure management in future.

The findings are relevant for decision-making by PPP practitioners to attain the social, economic and environmental benefits of transitioning to circular infrastructure management.

This study contributes to articulating the key models and measures toward sustainable CE in public infrastructure development.

There is a growing mismatch between the skill demands of the industry and the offerings of academia. One way of reducing this mismatch is by improving collaborations between practitioners and instructors using web-networking platforms. However, it is important to understand practitioners’ considerations while collaborating with instructors. Therefore, this study identified these considerations in order to infer inputs for the design of the graphical user interface (GUI) of a web-based platform for connecting instructors and practitioners.

A mixed method was adopted through a survey and focus group. A survey was used to capture practitioners’ considerations while collaborating with instructors for student development, and a focus group helped uncover an in-depth understanding of the study phenomena. The data were analyzed using descriptive and inferential statistics and thematic analysis.

The results show the willingness of practitioners to collaborate with instructors for student development, the ways by which practitioners are willing to meet instructors' course-support needs and their considerations in deciding to do so. Slight differences were observed between the results of the survey and the focus group regarding the ranking of the practitioners’ considerations. The study highlighted demographic differences in practitioners’ considerations when deciding on meeting instructors' course-support needs. The results provide a basis to deduce the GUI inputs of web-networking platforms for connecting instructors and practitioners.

This study revealed practitioners’ design needs and GUI inputs to facilitate the design of web-networking platforms for connecting instructors and practitioners. This study also contributes to user interface design principles, theories on individual differences and practitioners’ involvement in student professional development.

This study focuses on HR practices that foster employee engagement during Covid-19. Companies in transition economies are particularly vulnerable to crisis and downsizing and other recessionary practices are frequently used.

Drawing on the model of caring human resource management, we utilise interviews with human resource representatives of 10 banks in the transition economy of Bosnia and Herzegovina. We analyse the banks at two different times to demonstrate how and why companies adapt their HR practices.

Our findings show a changing mindset in the deployment of highly context-specific HR practices. Strengthening company culture through a sense of community and communication ensure stability and continuity in work. Rather than layoffs, flexible work has become standard.

By highlighting the interplay between HR practices and employee engagement, we contribute to the discussion on engagement in exceptional circumstances and challenging settings and demonstrate how caring responsibilities “migrate” into HR practices in the professional context of a transition economy.

We propose a context-specific “protective caring approach” to foster employee engagement during crises.

The purpose of this paper is to investigate the effect of the replacement of natural coarse aggregate (NCA) with different percentages of recycled coarse aggregate (RCA) on properties of low calcium fly ash (FA)-based geopolymer concrete (GPC) cured at oven temperature. Further, this paper aims to study the effect of partial replacement of FA by ground granulated blast slag (GGBS) in GPC made with both NCA and RCA cured under ambient temperature curing.

M25 grade of ordinary Portland cement (OPC) concrete was designed according to IS: 10262-2019 with 100% NCA as control concrete. Since no standard guidelines are available in the literature for GPC, the same mix proportion was adopted for the GPC by replacing the OPC with 100% FA and W/C ratio by alkalinity/binder ratio. All FA-based GPC mixes were prepared with 12 M of sodium hydroxide (NaOH) and an alkalinity ratio, i.e. sodium hydroxide to sodium silicate (NaOH:Na₂SiO₃) of 1:1.5, subjected to 90^°C temperature for 48 h of curing. The NCA were replaced with 50% and 100% RCA in both OPC and GPC mixes. Further, FA was partially replaced with 15% GGBS in GPC made with the above percentages of NCA and RCA, and they were given ambient temperature curing with the same molarity of NaOH and alkalinity ratio.

The workability, compressive strength, split tensile strength, flexural strength, water absorption, density, volume of voids and rebound hammer value of all the mixes were studied. Further, the relationship between compressive strength and other mechanical properties of GPC mixes were established and compared with the well-established relationships available for conventional concrete. From the experimental results, it is found that the compressive strength of GPC under ambient curing condition at 28 days with 100% NCA, 50% RCA and 100% RCA were, respectively, 14.8%, 12.85% and 17.76% higher than those of OPC concrete. Further, it is found that 85% FA and 15% GGBS-based GPC with RCA under ambient curing shown superior performance than OPC concrete and FA-based GPC cured under oven curing.

The scope of the present paper is limited to replace the FA by 15% GGBS. Further, only 50% and 100% RCA are used in place of natural aggregate. However, in future study, the replacement of FA by different amounts of GGBS (20%, 25%, 30% and 35%) may be tried to decide the optimum utilisation of GGBS so that the applications of GPC can be widely used in cast in situ applications, i.e. under ambient curing condition. Further, in the present study, the natural aggregate is replaced with only 50% and 100% RCA in GPC. However, further investigations may be carried out by considering different percentages between 50 and 100 with the optimum compositions of FA and GGBS to enhance the use of RCA in GPC applications. The present study is further limited to only the mechanical properties and a few other properties of GPC. For wider use of GPC under ambient curing conditions, the structural performance of GPC needs to be understood. Therefore, the structural performance of GPC subjected to different loadings under ambient curing with RCA to be investigated in future study.

The replacement percentage of natural aggregate by RCA may be further enhanced to 50% in GPC under ambient curing condition without compromising on the mechanical properties of concrete. This may be a good alternative for OPC and natural aggregate to reduce pollution and leads sustainability in the construction.

This study was carried out to analyze the importance of consumer preference data in forecasting demand in apparel retailing.

To collect preference data, 729 hypothetical stock keeping units (SKU) were derived using a full factorial design, from a combination of six attributes and three levels each. From the hypothetical SKU's, 63 practical SKU's were selected for further analysis. Two hundred two responses were collected from a store intercept survey. Respondents' utility scores for all 63 SKUs were calculated using conjoint analysis. In estimating aggregate demand, to allow for consumer substitution and to make the SKU available when a consumer wishes to buy more than one item in the same SKU, top three highly preferred SKU's utility scores of each individual were selected and classified using a decision tree and was aggregated. A choice rule was modeled to include substitution; by applying this choice rule, aggregate demand was estimated.

The respondents' utility scores were calculated. The value of Kendall's tau is 0.88, the value of Pearson's R is 0.98 and internal predictive validity using Kendall's tau is 1.00, and this shows the high quality of data obtained. The proposed model was used to estimate the demand for 63 SKUs. The demand was estimated at 6.04 per cent for the SKU cotton, regular style, half sleeve, medium priced, private label. The proposed model for estimating demand using consumer preference data gave better estimates close to actual sales than expert opinion data. The Spearman's rank correlation between actual sales and consumer preference data is 0.338 and is significant at 5 per cent level. The Spearman's rank correlation between actual sales and expert opinion is −0.059, and there is no significant relation between expert opinion data and actual sales. Thus, consumer preference model proves to be better in estimating demand than expert opinion data.

There has been a considerable amount of work done in choice-based models. There is a lot of scope in working in deterministic models.

The proposed consumer preference-based demand estimation model can be beneficial to the apparel retailers in increasing their profit by reducing stock-out and overstocking situations. Though conjoint analysis is used in demand estimation in other industries, it is not used in apparel for demand estimations and can be greater use in its simplest form.

This research is the first one to model consumer preferences-based data to estimate demand in apparel. This research was practically tested in an apparel retail store. It is original.

This study aims to review the current literature on the positive and negative effects of digitalisation in preventing corruption. It analyses existing research patterns and provides recommendations for future studies.

This paper employed bibliometric analysis and systematic review to scrutinise 190 papers from the Web of Science database from 2000 to 2023. Biblioshiny on R Studio was used for advanced bibliometric analysis to determine publication dynamics, influential journals, publications and impactful authors and a three-field plot to analyse relationships among countries, keywords and journals.

This study provides a bibliometric analysis of the past and actual developments in the field related to the effects of digitalisation on corruption. Based on the systematic literature review on a sample of the 50 most influential articles, this study identified background theories employed, the primary research methodologies adopted and valuable insights into both the positive and negative aspects of the impact of digitalisation on corruption.

This study provides an extended overview of the effects of digitalisation on corruption and advances new avenues for further research related to this field. The white and dark sides of the effects of digitalisation on corruption are highlighted. Furthermore, the study identifies the need for further research in this field to gain a more in-depth understanding of the nexus between digitalisation and corruption.