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Auxiliary power system is an indispensable part of the train; the auxiliary systems of both electric locomotives and EMUs mainly are powered by one of the two ways, which are either from auxiliary windings of traction transformers or from DC-link voltage of traction converters. Powered by DC-link voltage of traction converters, the auxiliary systems were maintained of uninterruptable power supply with energy from electric braking. Meanwhile, powered by traction transformers, the auxiliary systems were always out of power while passing the neutral section of power supply grid and control system is powered by battery at this time.

Uninterrupted power supply of auxiliary power system powered by auxiliary winding of traction transformer was studied. Failure reasons why previous solutions cannot be realized are analyzed. An uninterruptable power supply scheme for the auxiliary systems powered by auxiliary windings of traction transformers is proposed in this paper. The validity of the proposed scheme is verified by simulation and experimental results and on-site operation of an upgraded HXD3C type locomotive. This scheme is attractive for upgrading practical locomotives with the auxiliary systems powered by auxiliary windings of traction transformers.

This scheme regenerates braking power supplied to auxiliary windings of traction transformers while a locomotive runs in the neutral section of the power supply grid. Control objectives of uninterrupted power supply technology are proposed, which are no overvoltage, no overcurrent and uninterrupted power supply.

The control strategies of the scheme ensure both overvoltage free and inrush current free when a locomotive enters or leaves the neutral section. Furthermore, this scheme is cost low by employing updated control strategy of software and add both the two current sensors and two connection wires of hardware.

Highly committed, motivated and engaged employees assure organizational success and competitiveness. The study aims to examine the association between human resource development (HRD) practices and employee engagement with organizational commitment as a mediating variable.

Data were collected from 760 employees of 13 star-rated hotels comprising 5 (five-star) and 8 (four-star). The data supported the hypothesized relationships. Structural equation modeling was used to evaluate the proposed model and hypotheses. Construct validity and reliability were established through confirmatory factor analysis.

The results indicate that HRD practices and affective commitment are significantly associated. HRD practices and continuance commitment were shown to be non-significantly associated. HRD practices and normative commitment were shown to be non-significantly associated. Employee engagement and organizational commitment are significantly associated. The results further show that organizational commitment mediates the association between HRD practices and employee engagement.

The generalizability of the findings will be constrained due to the research's hotel industry focus and cross sectional data.

The study's findings will serve as valuable pointers for stakeholders and policymakers of the hotel industry in the adoption, design and implementation of proactive HRD interventions to keep highly engaged and committed employees for organizational competitiveness and sustainability.

By evidencing empirically that organizational commitment mediates the nexus between HRD practices and employee engagement, the study extends the literature.

Considering the ongoing discourse on diversity, equity and inclusion, brands aim to develop marketing campaigns that demonstrate respect for all individuals. Despite these intentions, many advertisements still provoke strong negative reactions from consumers due to brand transgressions in social media marketing campaigns that violate these values. The purpose of this paper is to analyze the repercussions that such social media marketing campaigns have on brands, categorizing these campaigns as brand transgressions in social media advertising.

This research uses a mixed-method design that includes semi-structured interviews (Study 1), a content analysis (Study 2) and an online experiment (Study 3).

This paper clarifies the elements that qualify as brand transgressions in advertising within the diversity, equity and inclusion discourse. The negative electronic word-of-mouth (e-WOM) associated with brand transgressions in advertising comprises negative emotions (e.g. anger, contempt, disgust and hate) and behavioural intentions to penalize the brand (e.g. negative word-of-mouth, brand avoidance and protest behaviours). The negative e-WOM stemming from these transgressions amplifies the adverse consequences for consumer–brand relationships by negatively influencing other consumers through sympathy towards the offended parties.

This paper offers brand managers guidelines for preventing and managing negative consumer reactions towards brands based on their responses to marketing campaigns that contradict the principles of diversity, equity and inclusion.

This paper contributes to the literature on brand transgressions related to diversity, equity and inclusion values by exploring their impact on consumer–brand relationships and highlighting the pivotal role of sympathy in perpetuating negative consequences.

Understanding consumer brand relationships from the perspective of the consumer has been a research topic for years. Despite this, there are still various ways in which the construct is interpreted. This paper aims to identify the most typical interpretation of brand relationships by consumers.

A four-study prototype analysis was conducted, in which a bottom-up approach was applied to identify lay people’s conceptualization of consumer brand relationships.

The prototype analysis generates a comprehensive list of features of consumer brand relationships that provide a nuanced understanding of the concept. The most typical characteristics of a brand relationship according to consumers are quality, bond, value and joy. Comparing this relationship prototype with existing literature shows that there may be a gap between theory and practice regarding the concept of brand relationship.

The prototypical conceptualization of brand relationships shows which aspects play a role in consumers' most common interpretation of the construct. This provides an opportunity to assess the validity of existing conceptualizations of brand relationships. Knowing which aspects are most relevant for consumers’ brand relationships allows brands to make adjustments as needed and improve at establishing and maintaining relationships with consumers.

The main goal of viral marketing is to affect brands positively. But most studies concern the causes of an ad going viral, not its impact on brands. In this sense, this study aims to demonstrate and compare video ads' value drivers on brands and sharing, determining which antecedents maximize results on each, enabling the best ad performance for advertisers.

A survey was conducted with 368 respondents who watched viral video ads from five global companies on YouTube. The proposed model was tested using structural equation modeling in SmartPLS4.

The results of this study demonstrated that product category involvement is essential for viral advertising. Furthermore, the entertainment value is the most relevant antecedent of sharing, but it does not affect brand equity; it is the social value responsible for brand equity.

Marketing managers should create ads that simultaneously generate entertainment and social values, maximizing sharing and branding effects. However, if only one of the two effects (brand/share) is achieved, then the advertiser will fail to obtain maximum performance.

The mainstream of viral marketing research is focused on antecedents of sharing. However, sharing is not enough to provide brand effects and return on investment of advertisement. This study reveals that different consumers’ values drive sharing and brand equity, suggesting that firms should consider a dual value generation strategy regarding the performance of viral video ads. On the other hand, this research conciliates the extant literature about the phenomena with the importance of product category involvement.

El objetivo principal del marketing viral es influir positivamente en las marcas. Pero la mayoría de las investigaciones se refieren a las causas de que un anuncio se vuelva viral, no a su impacto en las marcas. En este sentido, esta investigación tiene como objetivo demostrar y comparar los impulsores de valor de los anuncios de video en las marcas y su viralización, determinando qué antecedentes maximizan los resultados en cada uno, permitiendo el mejor rendimiento publicitario para los anunciantes.

Se realizó una encuesta con 368 participantes que vieron anuncios de video virales de cinco empresas globales en YouTube. El modelo estructural se analizó mediante ecuaciones estructurales basada en mínimos cuadrados utilizando SmartPLS4.

Los resultados demostraron que la participación en la categoría de productos es esencial para la publicidad viral. Además, el valor de entretenimiento es el antecedente más relevante de compartir, pero no afecta el valor de la marca; es el valor social responsable del valor de la marca.

Los gerentes de marketing deben crear anuncios que generen simultáneamente entretenimiento y valores sociales, maximizando los efectos de uso compartido y de marca. Sin embargo, si solo se consigue uno de los dos efectos (marca/participación), el anunciante no conseguirá obtener el máximo rendimiento.

La corriente principal de la investigación de marketing viral se centra en los antecedentes de compartir. Sin embargo, compartir no es suficiente para proporcionar efectos de marca y ROI de publicidad. Este estudio revela que los diferentes valores de los consumidores impulsan el intercambio y el valor de la marca, lo que sugiere que las empresas deberían considerar una estrategia de generación de valor dual con respecto al rendimiento de los anuncios de video virales. Por otro lado, esta investigación concilia la literatura existente sobre los fenómenos con la importancia de la participación de la categoría de productos.

病毒式营销的主要目标是对品牌产生积极的影响。但大多数研究关注的是广告走红的原因, 而不是它对品牌的影响。在这个意义上, 本研究旨在证明和比较视频广告对品牌和分享的价值驱动因素, 确定哪些前因能使每一个因素的结果最大化, 为广告商带来最佳的广告效果。

对368名受访者进行了调查, 他们在YouTube上观看了五家全球公司的病毒视频广告。在SmartPLS4中使用结构方程模型 对提议的模型进行了测试。

结果表明, 产品类别的参与对于病毒式广告来说是至关重要的。此外, 娱乐价值是分享的最相关前因, 但它并不影响品牌资产; 对品牌资产负责的是社会价值。

营销经理应该创造同时产生娱乐和社会价值的广告, 使分享和品牌效应最大化。然而, 如果只实现两种效果（品牌/分享）中的一种, 广告商将无法获得最大的绩效。

病毒式营销研究的主流是关注分享的前因后果。然而, 分享并不足以提供品牌效应和广告的投资回报率。本研究揭示了不同消费者的价值观对分享和品牌资产的推动作用, 表明企业应该考虑关于病毒视频广告表现的双重价值产生策略。另一方面, 本研究将现有的文献与产品类别参与的重要性结合在一起。

Engaged employees assure organizational competitiveness and sustainability. The purpose of this study is to explore the relationship between job resources and employee turnover intentions, with employee engagement as a mediating variable.

Data were collected from 934 employees of eight wholly-owned pharmaceutical industries. The proposed model and hypotheses were evaluated using structural equation modeling. Construct reliability and validity was established through confirmatory factor analysis.

Data supported the hypothesized relationship. The results show that job autonomy and employee engagement were significantly associated. Supervisory support and employee engagement were significantly associated. However, performance feedback and employee engagement were nonsignificantly associated. Employee engagement had a significant influence on employee turnover intentions. The results further show that employee engagement mediates the association between job resources and employee turnover intentions.

The generalizability of the findings will be constrained due to the research’s pharmaceutical industry focus and cross-sectional data.

The study’s findings will serve as valuable pointers for stakeholders and decision-makers in the pharmacuetical industry to develop a proactive and well-articulated employee engagement intervention to ensure organizational effectiveness, innovativeness and competitiveness.

By empirically demonstrating that employee engagement mediates the nexus of job resources and employee turnover intentions, the study adds to the corpus of literature.

This study aims to evaluate the effectiveness of machine learning models to yield profitability over the market benchmark, notably in periods of systemic instability, such as the ongoing war between Russia and Ukraine.

This study made computational experiments using support vector machine (SVM) classifiers to predict stock price movements for three financial markets and construct profitable trading strategies to subsidize investors’ decision-making.

On average, machine learning models outperformed the market benchmarks during the more volatile period of the Russia–Ukraine war, but not during the period before the conflict. Moreover, the hyperparameter combinations for which the profitability is superior were found to be highly sensitive to small variations during the model training process.

Investors should proceed with caution when applying machine learning models for stock price forecasting and trading recommendations, as their superior performance for volatile periods – in terms of generating abnormal gains over the market – was not observed for a period of relative stability in the economy.

This paper’s approach to search for financial strategies that succeed in outperforming the market provides empirical evidence about the effectiveness of state-of-the-art machine learning techniques before and after the conflict deflagration, which is of potential value for researchers in quantitative finance and market professionals who operate in the financial segment.

The digitalization of schools has intensified in recent years. It is reflected in policy documents as well as in extensive investments in digital technology and professional development initiatives to promote digitalization. At the same time, attempts are being made to “tame” the same digitization sometimes by regulations banning smartphones in class. This study aims to examine how smartphones are interpreted by vocational teachers in Sweden using the theoretical lens of technological frames.

The data consist of ten semi-structured interviews with vocational teachers, representing eight vocational programs in Sweden.

The results show breadth in how teachers understand, interpret and relate to the smartphone in vocational education. The authors show how the smartphone often forms an integral part of professional work and is thus difficult to separate from vocational teaching and nurturing vocational competencies.

The authors’ contributions include using technological frames to explore how smartphones are interpreted and understood by vocational teachers by demonstrating how they relate to the nature of the smartphone, the strategy for the smartphone and the smartphone in use. The theoretical framework is used to interpret restrictions on technology use, in this case a smartphone, in education. The results could be of interest to researchers as well as to teachers, school leaders and policymakers.

This paper aims to develop predictive methods, based on recurrent neural networks, useful to support facility managers in building maintenance tasks, by collecting information coming from a computerized maintenance management system (CMMS).

This study applies data-driven and text-mining approaches to a CMMS data set comprising more than 14,500 end-users’ requests for corrective maintenance actions, collected over 14 months. Unidirectional long short-term memory (LSTM) and bidirectional LSTM (Bi-LSTM) recurrent neural networks are trained to predict the priority of each maintenance request and the related technical staff assignment. The data set is also used to depict an overview of corrective maintenance needs and related performances and to verify the most relevant elements in the building and how the current facility management (FM) relates to the requests.

The study shows that LSTM and Bi-LSTM recurrent neural networks can properly recognize the words contained in the requests, thus correctly and automatically assigning the priority and predicting the technical staff to assign for each end-user’s maintenance request. The obtained global accuracy is very high, reaching 93.3% for priority identification and 96.7% for technical staff assignment. Results also show the main critical building elements for maintenance requests and the related intervention timings.

This work shows that LSTM and Bi-LSTM recurrent neural networks can automate the assignment process of end-users’ maintenance requests if trained with historical CMMS data. Results are promising; however, the trained LSTM and Bi-LSTM RNN can be applied only to different hospitals adopting similar categorization.

The data-driven and text-mining approaches can be integrated into the CMMS to support corrective maintenance management by facilities management contractors, i.e. to properly and timely identify the actions to be carried out and the technical staff to assign.

The improvement of the maintenance of the health-care system is a key component of improving health service delivery. This work shows how to reduce health-care service interruptions due to maintenance needs through machine learning methods.

This study develops original methods and tools easily integrable into IT workflow systems (i.e. CMMS) in the FM field.