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Purpose: Nikoletta Taylor and Close, (2022) asserts that a skill gap analysis can be used to determine the lacking skill and carry out recruitment based on that gap. It goes without saying that for a student, that would be their first employment, and with internships, there is no way to experience all aspects of the working world.

Need for This Study: When it comes to the recruiter’s expectations and the applicant’s skills, specifically among students, a gap still exists, leading to a need for practical exposure for applicants.

Study Design/Methodology/Approach: A quantitative study was adopted. A questionnaire was prepared with constructs and variables from the review and a total of 403 responses was collected from reputed institutions in Tamil Nadu.

Findings: This study reveals that skill development is needed; it is found that experiential learning through the gamification process is a suitable learning strategy. The experiential learning factors supporting skill development are self-efficacy, outcome expectation, interest, choice actions, and performance, followed by review, feedback, and continuous improvement.

Originality/Value: Learning all these factors through the gamification process would give students practical exposure to real-time scenarios of the corporate world. The proposed model gives students experience through gamification and learning activities.

Although healthcare and healthy living are integral to the Sustainable Development Goals (SDGs) for 2030, the coronavirus epidemic has dealt a devastating blow to these efforts. As governments and policymakers were compelled to shift their focus to lockdowns, sustenance, procurement, and distribution of vaccines, the momentum for health initiatives slowed, and the already fragile health systems of emerging markets were subjected to additional shocks. However, in many underserved regions of the globe, the introduction of technology has greatly facilitated the distribution and adoption of healthcare services.

This chapter highlights mini-cases from four emerging nations: Bangladesh, Nigeria, Vietnam, and the Philippines. Although the countries are emerging, each one of them are in a distinct stage of development and face a unique set of healthcare-related challenges. The chapter showcases how four different organizations based in these countries leveraged the use of technology to take healthcare services to underserved populations. In doing so, they addressed the key challenges of imparting healthcare: geographic accessibility, availability, financial accessibility, and acceptability.

This chapter concludes with a discussion of the implications of expanding healthcare industries leading to increased healthcare waste. To prevent mass population exposure to hazardous substances, the emergence of intelligent healthcare waste collection and disposal systems will be an absolute necessity. Hence, with the development of healthcare services, governments and policymakers need to mechanize smart waste management systems to safeguard humans, animals, and the environment.

This study aims to analyse the structure of the Indian vaccine supply chain (SC) during the Covid-19 crisis and explore the underlying challenges at each stage in the network. It also brings out the difference in performance of various constituent states.

This study relied on both primary and secondary data for the analyses. For the primary data, the study gathered experts’ opinions to validate the authors’ inferences. For the secondary data, it relies on government data provided in websites.

Based on the quartile analysis and cluster analysis of the secondary data, the authors find that the constituent states responded differently during the first and second waves. This was due to the differences in SC characteristics attributed to varied demographics and administrative efficiency.

This paper’s analyses is primarily limited to secondary information and inferences are based on them. The study has important implications for implementing the large-scale vaccination drives by government and constituent states for better coordination and last-mile delivery.

The contribution is unique in studying the performance of constituent states using statistical techniques, with secondary data from authentic sources. It is also unique in combining this observation with validation from experts.

This study aims to explore the use of time series analyses to examine changes in travelers’ preferences in accommodation features by disentangling seasonal, trend and the COVID-19 pandemic’s once-off disruptive effects.

Longitudinal data are retrieved by online traveler reviews (n = 519,200) from the Canary Islands, Spain, over a period of seven years (2015 to 2022). A time series analysis decomposes the seasonal, trend and disruptive effects of six prominent accommodation features (view, terrace, pool, shop, location and room).

Single accommodation features reveal different seasonal patterns. Trend analyses indicate long-term trend effects and short-term disruption effects caused by Covid-19. In contrast, no long-term effect of the pandemic was found.

The findings stress the need to address seasonality at the single accommodation feature level. Beyond targeting specific features at different guest groups, new approaches could allow dynamic price optimization. Real-time insight can be used for the targeted marketing of platform providers and accommodation owners.

A novel application of a time series perspective reveals trends and seasonal changes in travelers’ accommodation feature preferences. The findings help better address travelers’ needs in P2P offerings.

Vicarious abusive supervision (VAS) has recently garnered the attention of hospitality researchers. VAS is prevalent in hospitality work settings characterized by long production chains and open operating environments. Based on the conservation of resources (CORs) theory, this study aims to examine how VAS influences hospitality employees’ work behaviours (i.e. supervisor-directed deviance, silence and helping behaviour) via affective rumination, with the moderating role of industry tenure as an individual contingency on the relationship between VAS and affective rumination.

The data were gathered from 233 restaurant frontline employees and their supervisors in Turkey. The authors tested the proposed model using partial least squares method through SmartPLS 3.

The results reveal that VAS triggers affective rumination, which, in turn, is positively related to supervisor-directed deviance and silence, and negatively related to helping behaviour. Moreover, industry tenure, as a buffer resource, significantly moderates the relationship between VAS and affective rumination.

To reduce the occurrence of VAS and mitigate its negative effects, managers should establish a work environment that embraces understanding and respect, pay attention to how they communicate with employees, implement appropriate interventions when VAS occurs and conduct stress management training and improve employees’ emotion regulation skills in ways that correspond to the employees’ industry experience.

This study advances research on VAS by offering insight into how VAS impacts employees’ work behaviours via the underlying mechanism of affective rumination through a COR lens. The findings also shed light on the salient buffering effect of industry tenure as an individual contingency.

The South African vocational education and training (VET) sector is required by legislation to redefine postsecondary education, advance industrialisation and expand the job market to address unemployment in the country. Yet, VET leaders' heterogenous educational and occupational backgrounds do not enable them to address the needs of the VET sector. Continuous professional development of leaders in the education sector needs to include support structures such as mentoring.

The present study sought to investigate how VET managers in South Africa perceive three different types of mentoring – individual, peer group and expert-based key performance area (KPA) mentoring – during a part-time professional leadership development programme. Using interactive qualitative analysis (IQA), the authors collected and analysed data from focus group discussions (n = 24) and individual interviews (n = 21) from two cohorts of the programme.

The results revealed that individual mentoring represented the most important driving mechanism, followed by peer group mentoring and expert-based KPA mentoring. Participants identified leadership as a prerequisite for their development. Emotions formed the final outcome of the mentoring framework.

Based on the findings, the authors suggest investigating the role played by leaders' interpersonal competences such as emotional competence in the workplace. Additionally, research needs to clarify if and how mentoring can support leaders to develop interpersonal competences in formal and informal settings.

The study offers empirical evidence on a three-pillar mentoring framework adopted in a professional development programme for leaders in VET in South Africa. It highlights the importance of individual, social and emotional factors.

Cloud computing gives several on-demand infrastructural services by dynamically pooling heterogeneous resources to cater to users’ applications. The task scheduling needs to be done optimally to achieve proficient results in a cloud computing environment. While satisfying the user’s requirements in a cloud environment, scheduling has been proven an NP-hard problem. Therefore, it leaves scope to develop new allocation models for the problem. The aim of the study is to develop load balancing method to maximize the resource utilization in cloud environment.

In this paper, the parallelized task allocation with load balancing (PTAL) hybrid heuristic is proposed for jobs coming from various users. These jobs are allocated on the resources one by one in a parallelized manner as they arrive in the cloud system. The novel algorithm works in three phases: parallelization, task allocation and task reallocation. The proposed model is designed for efficient task allocation, reallocation of resources and adequate load balancing to achieve better quality of service (QoS) results.

The acquired empirical results show that PTAL performs better than other scheduling strategies under various cases for different QoS parameters under study.

The outcome has been examined for the real data set to evaluate it with different state-of-the-art heuristics having comparable objective parameters.

This study investigates the factors influencing household financial choices in Malawi. The authors also compare how household financial decisions differ in urban and rural areas.

The authors utilize the logit model to examine the factors that influence household financial decisions using the Malawi Integrated Household Survey 2019–20, while Oaxaca–Blinder decomposition is used to estimate the variations in household financial decisions between urban and rural areas.

The authors find that the likelihood of saving increases with income, secondary and tertiary education, and age. The likelihood of saving also decreases with household size and remittances. Additionally, the authors report that marriage reduces the likelihood of loans, whereas sex, age, and income raise the likelihood of loans. According to this study’s findings, income discrepancies between urban and rural samples account for most observed household financial variations. The authors also find that most of the observed variations in household financial decision-making between urban and rural households are reduced when income equality, participation in agriculture, university education, and household size are considered.

Using data from the Malawi Integrated Household Survey 2019–20, this research analyzes the components that affect household financial decisions. While most studies only look at one component of household finances, this study concurrently addresses debt and savings. The study also evaluates whether changes in the variables between urban and rural households impact those households' financing choices.

The maintainability of urban spaces has become critical with rapid urbanization to create an effective and safe environment for the increasing population. The absence of scientific studies exploring the factors that affect urban space maintainability (USM) has hindered the incorporation of maintainability aspects during the urban space planning and designing stages. This paper aims to establish critical factors for USM.

Qualitative content analysis is performed under an abductive approach to developing USM factors. A bibliometric search is conducted using databases including Scopus Elsevier, Emerald Insight, Science Direct, IEEE XPLORE and the American Society of Civil Engineers. The selected primary data set comprises journal papers on USM published after 2000. Seventy-three journal articles are selected through a comprehensive screening procedure and subjected to further analysis. The literature findings are processed via a software-assisted systematic coding and visualizing of the key data using NVivo 12 software. The coded USM factors are validated based on experts’ consensus statements by conducting an expert focus group discussion.

Twelve critical factors are established for USM; they include six design stage-related factors, one construction stage-related factor and five operational stage-related factors.

Established USM factors give an insight into the main focus areas when incorporating maintainability into urban spaces.

The authors establish a set of maintainability factors for urban spaces based on the life cycle stages. USM factors such as vegetation management, interdepartmental coordination and work zone safety draw attention to context-specific aspects of USM.

This study aims to investigate the optimal process parameters of the wire-cut electrical discharge machining (WCEDM) for the machining of the GZR-AA7475 hybrid metal matrix composite (HMMC). HMMCs are prepared with 2 Wt.% graphite and 4 Wt.% zirconium dioxide reinforced with aluminium alloy 7475 (GZR-AA7475) composite by using the stir casting method. The objective is to enhance the mechanical properties of the material while preserving its unique features. WCEDM with a 0.18 mm molybdenum wire electrode is used for machining the composite.

To conduct experimental studies, a Taguchi L27 orthogonal array was adopted. Input variables such as peak current (I_p), pulse-on-time (T_ON) and flushing pressure (P_F) were used. The effect of process parameters on the output responses, such as material removal rate (MRR), surface roughness rate (SRR) and wire wear ratio (WWR), were investigated. The grey relational analysis (GRA) is used to obtain the optimal combination of the process parameters. Analysis of variance (ANOVA) was also used to identify the significant process parameters affecting the output responses.

Results from the current study concluded that the optimal condition for grey relational grade is obtained at T_ON = 105 µs, I_p = 100 A and P_F = 90 kg/cm². Peak current is the most prominent parameter influencing the MRR, whereas SRR and WRR are highly influenced by flushing pressure.

Identifying the optimal process parameters in WCEDM for machining of GZR-AA7475 HMMC. ANOVA and GRA are used to obtain the optimal combination of the process parameters.