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This research examines the applicability of the Employer Branding (EB) Mix model developed by Rayón et al. (2022), one of the few empirically validated models, to promote organizational commitment within the context of the Spanish healthcare sector.

A questionnaire was administered to 310 employees of a national company in the Spanish healthcare sector. Several multiple regression models were run between the EB dimensions and those of employees’ organizational commitment.

The results show that the elements of the EB Mix model have a positive relationship with employee’s commitment, especially affective and value commitment.

The existence of causality cannot be affirmed, in view of the sectional design with a single sample taken from the Spanish private healthcare sector. Additionally, it would be worth extending the analysis of the effect of the EB Mix model on the behavior of potential employees.

This research is extremely relevant, given that it can help organizations in the health sector to implement EB programs. The model is an effective tool for retaining human talent and can generate a competitive advantage for organizations that use it.

The EB Mix model presents a conceptually-based and empirically validated model that incorporates the perception of employees as co-creators of the internal brand, which promotes the democratization of organizations and includes the four Ps of the marketing mix.

Work-related stress is a significant occupational health issue. Stress cannot be viewed separately from the perceptual or interpretive act by the individual. Self-efficacy is a personal characteristic that explains a high proportion of variation in the performance of school principals.

The current study examines if the COVID-pandemic is related to burnout among school principals. Additionally, the study analyzes if the self-efficacy of school principals plays a mediating role in the impact that the COVID-19 crisis had on their burnout level. To explore this, the authors used survey data of 981 Flemish school principals.

The findings indicate that the COVID-19 pandemic is related to feelings of burnout among Flemish school principals. In addition, self-efficacy mediated the relationship between the COVID-19 scale and the four core subscales of burnout: exhaustion, mental distance, emotional impairment and cognitive impairment. No mediating effect of self-efficacy was found for the secondary symptoms of burnout, psychological distress and psychosomatic complaints.

This paper emphasizes the importance of school principal's self-efficacy experiences for crisis management. Implications for school leadership training and support are discussed.

Digitalization and marketing technologies have made it possible to overcome some barriers to pricing – a multidisciplinary field between marketing, finance and IT – and have set the stage for a paradigm shift in the pricing profession. Value creation, the pricing process, and price communication have been transformed by innovative business models and advanced algorithmic and human–machine solutions. This chapter synthesizes the literature to date and provides a comprehensive framework for an all-encompassing 360° pricing approach that broadens the understanding of pricing in the context of digital business across all steps of the price management process. Starting from product attributes and motivational beliefs in consumers' value assessment and adoption of (technological or digital) products or services, new business models and pricing models emerge in the digital economy, human–machine solutions for price implementation and repricing are increasingly applied, and price search and communication take place through a variety of digital communication channels. Each stage of this framework discusses concrete examples, highlighting the freemium strategy, the subscription model, price tracking and repricing tools, and digital price information channels such as e-commerce, marketplace, or price comparison platforms. The implications for price management in a digital, technology-driven landscape are discussed from the executive level to the analyst level.

Earned value management (EVM)–based models for estimating project actual duration (AD) and cost at completion using various methods are continuously developed to improve the accuracy and actualization of predicted values. This study primarily aimed to examine natural gradient boosting (NGBoost-2020) with the classification and regression trees (CART) base model (base learner). To the best of the authors' knowledge, this concept has never been applied to EVM AD forecasting problem. Consequently, the authors compared this method to the single K-nearest neighbor (KNN) method, the ensemble method of extreme gradient boosting (XGBoost-2016) with the CART base model and the optimal equation of EVM, the earned schedule (ES) equation with the performance factor equal to 1 (ES1). The paper also sought to determine the extent to which the World Bank's two legal factors affect countries and how the two legal causes of delay (related to institutional flaws) influence AD prediction models.

In this paper, data from 30 construction projects of various building types in Iran, Pakistan, India, Turkey, Malaysia and Nigeria (due to the high number of delayed projects and the detrimental effects of these delays in these countries) were used to develop three models. The target variable of the models was a dimensionless output, the ratio of estimated duration to completion (ETC(t)) to planned duration (PD). Furthermore, 426 tracking periods were used to build the three models, with 353 samples and 23 projects in the training set, 73 patterns (17% of the total) and six projects (21% of the total) in the testing set. Furthermore, 17 dimensionless input variables were used, including ten variables based on the main variables and performance indices of EVM and several other variables detailed in the study. The three models were subsequently created using Python and several GitHub-hosted codes.

For the testing set of the optimal model (NGBoost), the better percentage mean (better%) of the prediction error (based on projects with a lower error percentage) of the NGBoost compared to two KNN and ES1 single models, as well as the total mean absolute percentage error (MAPE) and mean lags (MeLa) (indicating model stability) were 100, 83.33, 5.62 and 3.17%, respectively. Notably, the total MAPE and MeLa for the NGBoost model testing set, which had ten EVM-based input variables, were 6.74 and 5.20%, respectively. The ensemble artificial intelligence (AI) models exhibited a much lower MAPE than ES1. Additionally, ES1 was less stable in prediction than NGBoost. The possibility of excessive and unusual MAPE and MeLa values occurred only in the two single models. However, on some data sets, ES1 outperformed AI models. NGBoost also outperformed other models, especially single models for most developing countries, and was more accurate than previously presented optimized models. In addition, sensitivity analysis was conducted on the NGBoost predicted outputs of 30 projects using the SHapley Additive exPlanations (SHAP) method. All variables demonstrated an effect on ETC(t)/PD. The results revealed that the most influential input variables in order of importance were actual time (AT) to PD, regulatory quality (RQ), earned duration (ED) to PD, schedule cost index (SCI), planned complete percentage, rule of law (RL), actual complete percentage (ACP) and ETC(t) of the ES optimal equation to PD. The probabilistic hybrid model was selected based on the outputs predicted by the NGBoost and XGBoost models and the MAPE values from three AI models. The 95% prediction interval of the NGBoost–XGBoost model revealed that 96.10 and 98.60% of the actual output values of the testing and training sets are within this interval, respectively.

Due to the use of projects performed in different countries, it was not possible to distribute the questionnaire to the managers and stakeholders of 30 projects in six developing countries. Due to the low number of EVM-based projects in various references, it was unfeasible to utilize other types of projects. Future prospects include evaluating the accuracy and stability of NGBoost for timely and non-fluctuating projects (mostly in developed countries), considering a greater number of legal/institutional variables as input, using legal/institutional/internal/inflation inputs for complex projects with extremely high uncertainty (such as bridge and road construction) and integrating these inputs and NGBoost with new technologies (such as blockchain, radio frequency identification (RFID) systems, building information modeling (BIM) and Internet of things (IoT)).

The legal/intuitive recommendations made to governments are strict control of prices, adequate supervision, removal of additional rules, removal of unfair regulations, clarification of the future trend of a law change, strict monitoring of property rights, simplification of the processes for obtaining permits and elimination of unnecessary changes particularly in developing countries and at the onset of irregular projects with limited information and numerous uncertainties. Furthermore, the managers and stakeholders of this group of projects were informed of the significance of seven construction variables (institutional/legal external risks, internal factors and inflation) at an early stage, using time series (dynamic) models to predict AD, accurate calculation of progress percentage variables, the effectiveness of building type in non-residential projects, regular updating inflation during implementation, effectiveness of employer type in the early stage of public projects in addition to the late stage of private projects, and allocating reserve duration (buffer) in order to respond to institutional/legal risks.

Ensemble methods were optimized in 70% of references. To the authors' knowledge, NGBoost from the set of ensemble methods was not used to estimate construction project duration and delays. NGBoost is an effective method for considering uncertainties in irregular projects and is often implemented in developing countries. Furthermore, AD estimation models do fail to incorporate RQ and RL from the World Bank's worldwide governance indicators (WGI) as risk-based inputs. In addition, the various WGI, EVM and inflation variables are not combined with substantial degrees of delay institutional risks as inputs. Consequently, due to the existence of critical and complex risks in different countries, it is vital to consider legal and institutional factors. This is especially recommended if an in-depth, accurate and reality-based method like SHAP is used for analysis.

This study aims to examine ethical practices in the banking sector by testing the relationships between customer perceptions of ethicality and brand attributes like affect, image and equity.

Drawing on the social exchange theory, the authors advance the consumer’s perspective in explaining brand equity in the banking sector. Following the survey technique, the authors used the Hayes’ Macro Process in analysing the data collected from 148 bank customers in New Zealand.

The findings suggest that customers’ perception of ethicality, brand image and affect are significantly associated with brand equity. Also, brand image and affect significantly mediate the relationship between customer’s perception of ethicality and brand equity.

The main limitation of this study is the use of survey and cross-sectional methods. Future research may adopt mixed-method techniques to provide insightful information on how these variables influence brand equity.

The study demonstrates the mechanisms that facilitate brand equity and contributes to theory by analysing the factors of brand equity in the banking sector, which has been less investigated.

The purpose of this study is to examine how the tourism economy affects local food availability, access, utilization and stability in dessert-prone agricultural heritage sites. Specifically, the study aims to explore the relationship between the tourism industry and local agricultural practices and how this connection influences food security in the Siwa Oasis, located in the Western Desert of Egypt.

The study employs a qualitative exploratory research design using in-depth interviews and focus groups to investigate the impact of the tourism economy on food security and identify potential benefits and limitations for food security in the region.

The research reveals that the tourism economy in Siwa Oasis has only a marginal contribution to food security. The study highlights a lack of a strong connection between the tourism industry and local agricultural practices within the heritage site. As a result, the potential benefits and synergies that could be achieved between tourism and agriculture have not been fully realized, leading to a limited impact on food stability.

This study primarily relies on qualitative data from Siwa Oasis, Egypt, which may limit the generalizability of findings beyond this specific context. Additionally, while the study provides valuable insights into the complex relationship between tourism and food security, it does not quantitatively measure the magnitude of tourism's impact. Future research could incorporate quantitative methods for a more comprehensive understanding of this relationship in diverse desert-prone regions. Finally, the study highlights the need for more integrated approaches to enhance food security through tourism, but the specific strategies and policy recommendations require further investigation and adaptation to local contexts.

This study underscores the need for tourism development strategies that prioritize food security in desert-prone areas like Siwa Oasis. Policymakers and stakeholders should promote sustainable tourism practices that enhance local agriculture, create diversified income sources and foster equitable benefits for communities. Moreover, recognizing the seasonal nature of tourism, interventions to address food shortages during off-peak periods are crucial. Efforts should also focus on skill development and gender-inclusive opportunities within the tourism sector to ensure broader community participation. Additionally, collaborations between tourism and agriculture should be encouraged to optimize food availability and stability while preserving cultural food traditions.

This study adds original insights by examining the specific impact of the tourism economy on food security in dessert-prone agricultural heritage sites. The study's originality lies in its exploration of the untapped potential for synergy between the tourism and agricultural sectors and the implications for local food security. This research contributes to understanding how tourism can improve food security in specific contexts and provides valuable insights into sustainable development in heritage sites.

Country and cultural heritage are inextricably linked for First Nations peoples. This chapter explores those relationships in the context of repatriating cultural heritage materials back to Country and conceptualising a place for its ‘awakening’ for the Ngadjuri community of Mid-North South Australia. These materials in the context of this book ‘interpreted’ as a form of data curation, requiring potentially unique information systems designs to achieve accessibility, recoverability, and durability in remote communities with limited internet and mobile phone coverage. On the other hand, it is critically important to note, that the processes, challenges and repatriation of culturally sensitive materials and remains, are dependant here on the limitations of language. The reference to the notion of ‘data’ as a descriptor, and an inadequate term on some level, does not, and is not intended to, diminish any of their cultural significance and gravity. These are challenges that are worth the intellectual and technological investment to realise a return to Country for generationally displaced peoples and their cultural property that also needs to make it home.

The paper draws extensively from Aristotle’s Poetics, a classical work on the aesthetics of drama. Drawing from symbolic and thematic elements from folklore and mythology, this paper aims to illustrate how the Poetics can be referenced as an allegorical device in the design of culture-building strategies and interventions.

This exploratory paper examines Aristotle’s “Poetics” and the range of creative expression this literature provides as a conceptual design framework for the development of a culture map in creating a distinctive organisational mythology. The Poetics articulates an Aristotelian perspective on theatre which infuses itself as a new language in offering structural and archetypical plot devices in the development of an organisational narrative.

Findings from this explorative study can provide a creative roadmap to culture practitioners and leaders, to be used as a determining reference point in developing culture maps and change management interventions.

Poetics has its detractors, notably Bertolt Brecht and Augusto Boal. Boal examines how Poetics promotes a narrative that suppresses free thinking and encourages a cult of feudal personality, therefore encouraging industrial and cultural oppression, which he rebelled against through the development of his “Theatre of the Oppressed”. This new kind of theatre discarded the Aristotelian model of thinking. Ideas proposed in the Poetics may also lend verisimilitude to the propagation of obsessive consumerism through the definitive symbolism it offers in the development of institutionalised personality cults.

The Poetics as a creatively driven reflexive study provides a forward movement in the study of culture design templates. Its definitive allegorical devices and metaphors act as action principles through which an enterprise culture and its value system can be examined and developed.

This study aims to identify specific factors that facilitate engagement and stay intention among Generation Z employees in the Indian banking, financial services and insurance (BFSI) context. Furthermore, using the frequency distribution of the identified factors, this study has ranked them in order of their association with stay intention.

Data were collected from 22 Gen Z employees working in the Indian private BFSI sector using unstructured interviews. Inductive content analysis was applied to identify the factors improving engagement and stay intention. Moreover, quantitative content analysis was applied to calculate the frequency distribution of the identified factors.

The study identified six prominent factors, namely, transformational leadership, employee investment practices, egalitarian practices, work-life balance, job crafting and sustainability, which significantly enhance employee engagement and stay intention among Gen Z employees. Moreover, based on the results of quantitative content analysis, it was found that transformational leadership exhibited the highest frequency in association with employee engagement and stay intention. Following this were employee involvement, egalitarian practices, work-life balance, job crafting and sustainability.

In the coming days, Generation Z will contribute to almost one-third of India’s workforce, of which the BFSI sector will be the major employer. However, the issue with this generation is their retention. Hence, the study identifies factors ensuring engagement and stay intention.

Owing to the paucity of research on stay intention as a variable of interest, this study tries to capture the perceptions of Gen Z towards factors inducing their engagement and stay intention. This study assesses intention to stay (ITS) as compared to intention to leave (ITL) as it is a proactive indicator of turnover. Lastly, this study uses a qualitative approach to identify factors influencing stay intention and engagement based on interactions with employees, which, to the best of the authors’ knowledge, no prior study has attempted.