Hasil untuk "Personnel management. Employment management"

Banji Rildwan Olaleye, Ademola Emmanuel Ayodele, Joseph Nembo Lekunze

Homestay tourism is increasingly recognised as a pathway to sustainable tourism development, especially in community-based destinations. This study examines the roles of local community attitudes and environmental sustainability in shaping perceived value and tourist satisfaction within Nigerian homestay tourism. Using a cross-sectional survey design, data were collected from 386 homestay tourists across south-western Nigeria and analysed with Partial Least Squares Structural Equation Modelling (PLS-SEM). The results reveal that local community attitude significantly boosts tourists’ perceived value, while environmental sustainability positively influences both perceived value and tourist satisfaction. However, perceived value does not strongly predict tourist satisfaction, and the moderating effect of community attitude on the relationship between value and satisfaction appears weak. This study contributes to the literature by integrating and extending the Theory of Planned Behaviour (TPB) beyond behavioural intention, demonstrating its relevance to understanding the formation of value–satisfaction in community-based tourism. It also challenges dominant tourism assumptions by showing that perceived value may serve as a supporting rather than primary determinant of satisfaction in rural homestay settings. In practice, the findings suggest that homestay operators and policymakers should focus on environmental sustainability practices and on enhancing experiential service quality, rather than relying solely on value-for-money propositions. By providing context-specific evidence from sub-Saharan Africa, this study advances sustainable tourism scholarship and offers strategic insights for inclusive rural tourism development.

Arnon Archankul, Jacco J. J. Thijssen

We consider singular control in inventory management under Knightian uncertainty, where decision makers have a smooth ambiguity preference over Gaussian-generated priors. We demonstrate that continuous-time smooth ambiguity is the infinitesimal limit of Kalman-Bucy filtering with recursive robust utility. Additionally, we prove that the cost function can be determined by solving forward-backward stochastic differential equations with quadratic growth. With a sufficient condition and utilising variational inequalities in a viscosity sense, we derive the value function and optimal control policy. By the change-of-coordinate technique, we transform the problem into two-dimensional singular control, offering insights into model learning and aligning with classical singular control free boundary problems. We numerically implement our theory using a Markov chain approximation, where inventory is modeled as cash management following an arithmetic Brownian motion. Our numerical results indicate that the continuation region can be divided into three key areas: (i) the target region; (ii) the region where it is optimal to learn and do nothing; and (iii) the region where control becomes predominant and learning should inactive. We demonstrate that ambiguity drives the decision maker to act earlier, leading to a smaller continuation region. This effect becomes more pronounced at the target region as the decision maker gains confidence from a longer learning period. However, these dynamics do not extend to the third region, where learning is excluded.

Probowo Erawan Sastroredjo, Marcel Ausloos, Polina Khrennikova

Our research investigates the relationship between eco-innovation and earnings management among 567 firms listed on the FTSE All-Share Index from 2014 to 2022. By examining how sustainability-driven innovation influences financial reporting practices, we explore the strategic motivations behind income smoothing in firms engaged in environmental initiatives. The findings reveal a positive association between eco-innovation and earnings management, suggesting that firms may leverage ecoinnovation not only for environmental signalling but also to project financial stability and meet stakeholder expectations. The analysis further uncovers that the propensity for earnings management is amplified in firms facing financial constraints, proxied by low Whited-Wu (WW) scores and weak sales performance, and in those characterised by high financial opacity. We employ a robust multi-method approach to address potential endogeneity and selection bias, including entropy balancing, propensity score matching (PSM), and the Heckman Test correction. Our research contributes to the literature by providing empirical evidence on the dual strategic role of ecoinnovation -balancing sustainability signalling with earnings management, under varying financial conditions. The findings offer actionable insights for regulators, investors, and policymakers navigating the intersection of corporate transparency, financial health, and environmental responsibility.

Jabulile Msimango-Galawe, Amukelani Mashele

Orientation: Coaching is gaining popularity in South Africa, and more academic institutions are offering qualifications; however, limited research explores how different teaching approaches build coaches’ confidence. Research purpose: This research aimed to examine the effectiveness of three coaching education approaches – one-on-one coaching, coaching supervision and peer coaching – in enhancing the confidence of postgraduate coaching students enrolled in a master’s in coaching programme at an academic institution in South Africa. Motivation for the study: Given the growing need for effective coaching education, this study is motivated by the desire to understand which teaching approaches best enhance students’ learning and confidence so that coaching programmes can better equip future coaches for success. Research approach/design and method: Purposive sampling was employed to collect primary data from 12 master’s in coaching students at a South African university through semi-structured interviews. The data were then analysed using thematic analysis. Main findings: The key findings indicate that each of the three coaching dyads significantly enhances students’ confidence while fostering the development of their professional development at various levels. It was evident that, although all three approaches played a role in student learning and confidence, participants perceived coaching supervision as the most effective approach in improving their confidence. Practical/managerial implications: Institutions of higher education that provide coaching programmes should allocate additional resources towards coaching supervision to bolster the confidence of students. Contribution/value-add: The study informs pedagogical approaches in coach education and enriches the broader field of coaching by deepening the understanding of teaching effectiveness.

Yutong Liang, Shuyue Huang, Hwansuk Chris Choi

This study investigates how multidimensional value and experience quality shape satisfaction and loyalty in shopping tourism. We extend the QVSL tradition by (i) specifying three hedonic value dimensions (entertainment, exploration, escapism), (ii) differentiating functional value into performance-oriented and money-saving facets, and (iii) incorporating epistemic value and experience quality as additional antecedents. We also model immediate behavioral outcomes (i.e., money spent and time spent) and test involvement as a moderating condition. Using path analysis on data from 413 mainland Chinese tourists in Japan, findings confirm that entertainment, functional value (for performance and money), epistemic value, and experience quality enhance shopping satisfaction. Functional values, epistemic value, and satisfaction drive destination loyalty. Money and time spent are additional outcomes of satisfaction. Involvement moderates the link between satisfaction and money spent. These insights offer strategic implications for Destination Marketing Organizations (DMOs) and retailers to optimize shopping environments and employee services, increasing tourist satisfaction, loyalty, and both time and money spent in the competitive shopping tourism market. Limitations include the cross-sectional design and the use of composite-indicator path analysis; future research could apply longitudinal or full SEM approaches, broaden contexts, and test additional constructs.

Ernest D. Bendera, Yee-Lee Chong, Lee Peng Ng

Orientation: The unsatisfactory performance of some Tanzanian public parastatals could be linked to low job satisfaction, which is largely attributed to problems in human resource management practices (HRMP). Employees have indicated inadequate perceived organisational support (POS), and scholars are suggesting that further examination of managers’ trustworthiness in these institutions is important. Research purpose: This study examines the direct and indirect effects of four HRMP dimensional variables on job satisfaction, focussing on the mediation effect of POS and the moderating effect of managers’ trustworthiness. Motivation for the study: Enhancing HRMP, employees’ POS and managers’ trustworthiness could improve employees’ job satisfaction in Tanzanian public parastatals. Consequently, the performance of these vital public institutions will improve. Research approach/design and method: A cross-sectional approach randomly selected 438 employees from different transportation parastatals to complete self-administered questionnaires. A partial least squares-structural equation modelling (PLS-SEM) was utilised to analyse quantitative data. Main findings: Three HRMP dimensional variables – training and development, performance appraisal and compensation and benefits – directly impacted job satisfaction. In addition, POS partially mediated the relationship. In contrast, the recruitment and selection dimensional variable did not show a significant direct relationship with job satisfaction; yet, POS fully mediated its effect. Meanwhile, trustworthiness moderated the relationship between POS and job satisfaction. Practical/managerial implications: The study’s findings suggest that enhancing HRMP, boosting POS and increasing managers’ trustworthiness could improve job satisfaction. Contribution/value-add: The findings present a novel and reliable conceptual framework that enhances our understanding of the complex interrelationships among the HRMP variables, POS, trustworthiness and job satisfaction.

Tiago Alexandre VIEIRA

Longtemps en marge des institutions du marché du travail traditionnelles, les plateformes de travail numériques sont confrontées à une offensive réglementaire. L’Espagne a adopté une série de mesures législatives – en particulier la loi Rider – qui la place aux avant-postes de ce mouvement mondial. À partir d’une étude de cas élargie conduite durant 18 mois auprès de divers acteurs, l’auteur évalue si elle est parvenue à réencastrer les livreurs travaillant via une plateforme dans les relations d’emploi classiques. Il brosse un tableau en demi-teinte: les livreurs ont désormais accès à un salaire fixe, aux congés payés et à la protection sociale, mais leurs espoirs ont été déçus s’agissant du traitement équitable, de l’autonomie et de la confiance mutuelle en raison de pratiques comme l’externalisation, le temps partiel subi et l’intensification de la surveillance. L’inefficacité de la disposition légale qui garantit l’accès des représentants des travailleurs aux algorithmes des plateformes en dit long sur l’ampleur des défis à relever.

Liwei Deng, Tianfu Wang, Yan Zhao et al.

Portfolio management is an important yet challenging task in AI for FinTech, which aims to allocate investors' budgets among different assets to balance the risk and return of an investment. In this study, we propose a general Multi-objectIve framework with controLLable rIsk for pOrtfolio maNagement (MILLION), which consists of two main phases, i.e., return-related maximization and risk control. Specifically, in the return-related maximization phase, we introduce two auxiliary objectives, i.e., return rate prediction, and return rate ranking, combined with portfolio optimization to remit the overfitting problem and improve the generalization of the trained model to future markets. Subsequently, in the risk control phase, we propose two methods, i.e., portfolio interpolation and portfolio improvement, to achieve fine-grained risk control and fast risk adaption to a user-specified risk level. For the portfolio interpolation method, we theoretically prove that the risk can be perfectly controlled if the to-be-set risk level is in a proper interval. In addition, we also show that the return rate of the adjusted portfolio after portfolio interpolation is no less than that of the min-variance optimization, as long as the model in the reward maximization phase is effective. Furthermore, the portfolio improvement method can achieve greater return rates while keeping the same risk level compared to portfolio interpolation. Extensive experiments are conducted on three real-world datasets. The results demonstrate the effectiveness and efficiency of the proposed framework.

Alejandra de la Rica Escudero, Eduardo C. Garrido-Merchan, Maria Coronado-Vaca

Financial portfolio management investment policies computed quantitatively by modern portfolio theory techniques like the Markowitz model rely on a set on assumptions that are not supported by data in high volatility markets. Hence, quantitative researchers are looking for alternative models to tackle this problem. Concretely, portfolio management is a problem that has been successfully addressed recently by Deep Reinforcement Learning (DRL) approaches. In particular, DRL algorithms train an agent by estimating the distribution of the expected reward of every action performed by an agent given any financial state in a simulator. However, these methods rely on Deep Neural Networks model to represent such a distribution, that although they are universal approximator models, they cannot explain its behaviour, given by a set of parameters that are not interpretable. Critically, financial investors policies require predictions to be interpretable, so DRL agents are not suited to follow a particular policy or explain their actions. In this work, we developed a novel Explainable Deep Reinforcement Learning (XDRL) approach for portfolio management, integrating the Proximal Policy Optimization (PPO) with the model agnostic explainable techniques of feature importance, SHAP and LIME to enhance transparency in prediction time. By executing our methodology, we can interpret in prediction time the actions of the agent to assess whether they follow the requisites of an investment policy or to assess the risk of following the agent suggestions. To the best of our knowledge, our proposed approach is the first explainable post hoc portfolio management financial policy of a DRL agent. We empirically illustrate our methodology by successfully identifying key features influencing investment decisions, which demonstrate the ability to explain the agent actions in prediction time.

Qian Zhang, Yi He, Yue Xiao et al.

As the Internet of Things (IoT) industry advances, the imperative to secure IoT devices has become increasingly critical. Current practices in both industry and academia advocate for the enhancement of device security through key installation. However, it has been observed that, in practice, IoT vendors frequently assign shared keys to batches of devices. This practice can expose devices to risks, such as data theft by attackers or large-scale Distributed Denial of Service (DDoS) attacks. To address this issue, our intuition is to assign a unique key to each device. Unfortunately, this strategy proves to be highly complex within the IoT context, as existing keys are typically hardcoded into the firmware, necessitating the creation of bespoke firmware for each device. Furthermore, correct pairing of device keys with their respective devices is crucial. Errors in this pairing process would incur substantial human and temporal resources to rectify and require extensive communication between IoT vendors, device manufacturers, and cloud platforms, leading to significant communication overhead. To overcome these challenges, we propose the OTA-Key scheme. This approach fundamentally decouples device keys from the firmware features stored in flash memory, utilizing an intermediary server to allocate unique device keys in two distinct stages and update keys. We conducted a formal security verification of our scheme using ProVerif and assessed its performance through a series of evaluations. The results demonstrate that our scheme is secure and effectively manages the large-scale distribution and updating of unique device keys. Additionally, it achieves significantly lower update times and data transfer volumes compared to other schemes.

Binh Tan Mai, Phuong Van Nguyen, Ngan Thi Thanh Vo et al.

Joseph Cohen, Xun Huan, Jun Ni

In the era of industrial big data, prognostics and health management is essential to improve the prediction of future failures to minimize inventory, maintenance, and human costs. Used for the 2021 PHM Data Challenge, the new Commercial Modular Aero-Propulsion System Simulation dataset from NASA is an open-source benchmark containing simulated turbofan engine units flown under realistic flight conditions. Deep learning approaches implemented previously for this application attempt to predict the remaining useful life of the engine units, but have not utilized labeled failure mode information, impeding practical usage and explainability. To address these limitations, a new prognostics approach is formulated with a customized loss function to simultaneously predict the current health state, the eventual failing component(s), and the remaining useful life. The proposed method incorporates principal component analysis to orthogonalize statistical time-domain features, which are inputs into supervised regressors such as random forests, extreme random forests, XGBoost, and artificial neural networks. The highest performing algorithm, ANN-Flux, achieves AUROC and AUPR scores exceeding 0.95 for each classification. In addition, ANN-Flux reduces the remaining useful life RMSE by 38% for the same test split of the dataset compared to past work, with significantly less computational cost.

Luca Caruso

Due to the ecologically unfavorable state of the living world, any formal commitment made by the accommodation sector for the practical implementation of corporate social responsibility (CSR) strategies needs to be followed up by a credible plan, courageous action, and an attentive monitoring and reporting phase. Only in this way can high-end hotels in cities emerge as regenerative sustainability (RS) hubs and better amalgamate whole life-cycle thinking and economic performance in their day-to-day activities. This paper provides a detailed literature review of the ongoing transformation of the hospitality sector toward the RS paradigm, which is a concept that underpins Hortel’s business model. Hortel is then contextualized as the first example of an eco-innovative turnkey business-to-business (B2B) service for a high-end hotel with an annexed restaurant. Hortel implemented nature-based solutions adapted to the hospitality sector in order to contribute to local urban biodiversity and bring hotel clients closer to nature through biophilic tactics. Services like Hortel can support, with today’s resources and competences, hotels that are putting at the core of their business model planetary health and societal well-being. It also includes the description of the prototype built at Four Points by Sheraton Catania, the monitoring phase that lasted between 2016 and 2017, and other strategic business-related initiatives. This paper also contributes to the advancement of the literature discussing regenerative business models, which to date has been a largely unexplored aspect of hospitality.

Trninić Zora

Background: The present study was designed to investigate the use of sound symbolic mappings in fictitious brand names. Sound symbolic mappings refer to the existence of a nonarbitrary relationship between individual sounds and associations of different attributes and concepts. Given that sounds have inherent meaning in them, brand names in line with the established symbolic effects could communicate tailored messages that are congruent with consumer expectations of a product. Purpose: As perceived congruency between a product and its label is highly desirable in marketing, the study sets out to test the noted effects in brand names. It was aimed to confirm the strength of sound symbolic effects through greater preference for names with a symbolic fit with the product. Study design/methodology/approach: Two product categories were chosen, and a set of fictitious brand names were created. The names differed only on the sounds purported to convey targeted symbolic associations of salient product characteristics. The participants were presented with a forced choice task consisting of paired name samples and a stated product category for each pair. Finding/conclusions: The results confirmed the presence of sound symbolic effects as participants favoured the names with embedded symbolism. This leads to a conclusion that sound symbolism may be used to affect consumer choices based on brand name preference. Limitations/future research: Even though the study included only two products and used forced choice tasks limited on name pairs, the findings clearly imply the potential of sound symbolic mappings in creating efficient brand names. Broadening the research to other products and the service sector would surely deliver intriguing results.

Merits Editorial Office

High-quality academic publishing is built on rigorous peer review [...]

Fernandes José, Machado Carolina Feliciana, Amaral Luís

Background: Present the relevance of the study and highlights the key points of literature overview. Purpose: As of May 25, 2018, General Data Protection Regulation (GDPR) has become mandatory for all organizations, public or private, that handle personal data of European citizens, regardless of their physical location. Higher education institutions (HEIs), namely public universities, are no exception to this requirement and, as in many other organizations, many HEIs begin the process of implementing the GDPR without meeting the minimum conditions necessary for implementation. The purpose of this study, therefore, is to present a model to determine the level of readiness of HEIs regarding the implementation of the GDPR. Study design/methodology/approach: With the objective of designing a new artefact as a readiness model for the implementation of the GDPR, this study follows Design Science Research as an approach to be used to build the readiness model, based on a set of 16 critical success factors (CSFs) previously determined. Findings/conclusions: A readiness model was designed, based on a set of 16 CSFs related to the implementation of GDPR in HEIs. Limitations/future research: This is a new area of study that needs further development, namely through the practical application of the model, allowing the improvement of the measurement levels of the different CSFs. Practical implications: The determined readiness model allows HEIs to realize a priori if they have the necessary conditions for the implementation of the GDPR, giving useful indications of the organizational dimensions and the CSFs that compose them where better performance is necessary to ensure a successful implementation. Originality/Value: As far as we know, this is the first model of readiness based on CSFs related to the implementation of GDPR in HEIs, being therefore a first contribution to the development of this area.

Iksan Kasmudi Satiran, Maemunah Sa’diyah

Islamic boarding schools play a major role, namely, as motivators, innovators, and community dynamists so that the relationship between pesantren and the community becomes harmonious, as a result, the existence and presence of Islamic boarding schools in community empowerment become stronger. The purpose of this journal is to see the success of the Al-Kahfi Islamic Boarding School in implementing personnel management with reference to seven main activities, namely recruitment (personnel procurement), personnel development and development, personnel promotion and transfer, compensation for personnel, personnel welfare, personnel evaluation, termination of employment. employment relationship (PHK). This type of research is field research, namely research conducted with the direct aim of excavating and researching data relating to the effectiveness of the implementation of personnel management and what factors influence the implementation of personnel management at the Al-Kahfi Integrated Islamic Boarding School in Bogor. This research was conducted in September 2021. The results of the study after conducting interviews and collecting related data, the Al-Kahfi Integrated Islamic Boarding School has implemented all the main activities of personnel management in a well-managed and managed manner.AbstrakPesantren memegang peranan utama yaitu sebagai motivator, inovator, dan dinamisator masyarakat sehingga hubungan pesantren dengan masyarakat menjadi harmonis, hasilnya keberadaan dan kehadiran lembaga pesantren dalam pemberdayaan masyarakat menjadi semakin kokoh. Tujuan dari jurnal ini adalah melihat keberhasilan Pesantren Terpadu Al-Kahfi dalam menerapkan manajemen personalia dengan mengacu kepada tujuh kegiatan utama yaitu rekrutmen (pengadaan personalia), pembinaan dan pengembangan personalia, promosi dan mutasi personalia, kompensasi bagi personalia, kesejahteraan personalia, evaluasi personalia, pemutusan hubungan kerja (PHK). Jenis penelitian ini adalah penelitian lapangan (Field Research), yakni penelitian yang dilakukan dengan tujuan langsung kelapangan untuk menggali dan meneliti data yang berkenaan dengan efektivitas penerapan menejemen personalia dan Faktor apa saja yang mempengaruhi penerapan manajemen personalia di Pesantren Terpadu Al-Kahfi Bogor. Penelitian ini dilakukan pada bulan September 2021. Hasil penelitian setelah melakukan wawancara dan pengambilan data terkait maka Pesantren Terpadu Al-Kahfi sudah mengimplementasikan semua kegiatan utama manajemen personalia dengan baik dan terkelola.

Omama Farooq, Syed Afzal Moshadi Shah , Shakir Hafeez

Smartphone addiction is a growing social issue globally, especially among young consumers. Few studies have examined the role of smartphone addiction and student performance in Pakistan. However, how daily life disturbance, positive anticipation, withdrawal, cyberspace orientation, overuse, tolerance, and student academic performance has not been examined in the literature in Pakistan. The purpose of the study is to examine the effect of daily life disturbance, positive anticipation, withdrawal, cyberspace orientation, overuse, and tolerance on student academic performance. The study has adopted a self-administered survey-based approach. A total of 375 responses were gathered from the university students in Pakistan. The study has used SPSS 25.0 version to analyse the data and report the findings. The findings indicate that ‘overuse’ has the most indirect effect on students’ performance, followed by Cyberspace and oriented relationship, tolerance, positive anticipation, and daily life disturbance. The study demands a particular intervention by the students to self-regulate their behaviour. Parents and teachers play their role in controlling mobile addiction. Policymakers may introduce policy-related interventions to control the excessive use of mobile phones. The study lays down future directions and discusses the limitations towards the end.

Dana Tomeh, Paul Sackett

Steele and Aronson (1995) showed that stereotype threat affects the test performance of stereotyped groups. A careful reading shows that threat affects test performance but does not eliminate Black–White mean score gaps. Sackett et al. (2004) reviewed characterization of this research in scholarly articles, textbooks, and popular press, and found that many mistakenly inferred that removing stereotype threats eliminated the Black– White performance gap. We examined whether the rate of mischaracterization of Steele and Aronson had decreased in the 15 years since Sackett et al. highlighted the common misinterpretation. We found that the misinterpretation rate dropped from 90.9% to 62.8% in journal articles and from 55.6% to 41.18% in textbooks, though this is only statistically significant in journal articles.