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Due to government policies, accreditation demands, competition, digital India reforms and National Education Policy (NEP) 2020, the need for electronic human resource management (e-HRM) has increased considerably in the Indian higher education (HE) sector, but the literature has revealed that the adoption of e-HRM practices in Indian HE institutions (HEIs) is still in its embryonic stage; therefore, the purpose of the current qualitative study is to explore the challenges and facilitators of e-HRM adoption in the Indian HE sector through interpretative phenomenological analysis (IPA).

The present study incorporates IPA, to capture the personal lived experiences of the HR executives employed in the Indian HEIs. Using purposive sampling, semi-structured interviews were conducted with the HR executives employed in Indian universities and institutions to know the perspectives on the adoption of e-HRM practices in Indian HEIs.

The study identified two superordinate themes, namely, challenges and facilitators of e-HRM adoption in the Indian HE sector. The superordinate theme “challenges” comprises eight sub-themes. Further, the theme “facilitators” consists of six subthemes.

The study has implications for the stakeholders of the HE sector, i.e. HR practitioners, top executives of the HE sector, government and HE regulators and other stakeholders of the HE sector.

This study has given deep insights into the challenges and facilitators in the adoption of e-HRM practices in the Indian HE sector, and to the best of the authors’ knowledge, no study till date has filled this knowledge gap through qualitative exploration using IPA.

The outset of the COVID-19 pandemic caused disruptions of all forms in the supply chain globally for almost two and a half years. This study identifies various challenges in the effective functioning of the existing supply chain during COVID-19. The focus is to see the disruptions impacting the energy storage supply chains.

The procedure entails a thorough analysis of scholarly literature pertaining to various supply chain interruptions, confirmed and verified by experts working in an energy storage company in India. These experts also confirmed the occurrence of more disruptive factors during their interviews and questionnaire survey. Moreover, this process attempts to filter out the relevant causal disruption factors in an energy storage company by using the integrated approach of qualitative and quantitative methodologies.

The results provide practical insights for the company management in planning and devising new strategies to manage supply chain disruptions. Supply chains for companies in other industry sectors can also benefit from the proposed framework and results in making them more robust to counter future disastrous events.

The study provides an easily adaptable decision framework to different industries by closely examining supply chain disruptions and identifying associated causes for building a robust supply chain focused on the energy storage sector. It examines four disruption dimensions and investigates possible outcomes and impacts of disruptions.

Artificial intelligence (AI) offers many benefits to improve predictive marketing practice. It raises ethical concerns regarding customer prioritization, market share concentration and consumer manipulation. This paper explores these ethical concerns from a contemporary perspective, drawing on the experiences and perspectives of AI and predictive marketing professionals. This study aims to contribute to the field by providing a modern perspective on the ethical concerns of AI usage in predictive marketing, drawing on the experiences and perspectives of professionals in the area.

The study conducted semistructured interviews for 6 weeks with 14 participants experienced in AI-enabled systems for marketing, using purposive and snowball sampling techniques. Thematic analysis was used to explore themes emerging from the data.

Results reveal that using AI in marketing could lead to unintended consequences, such as perpetuating existing biases, violating customer privacy, limiting competition and manipulating consumer behavior.

The authors identify seven unique themes and benchmark them with Ashok’s model to provide a structured lens for interpreting the results. The framework presented by this research is unique and can be used to support ethical research spanning social, technological and economic aspects within the predictive marketing domain.

La Inteligencia Artificial (IA) ofrece muchos beneficios para mejorar la práctica del marketing predictivo. Sin embargo, plantea preocupaciones éticas relacionadas con la priorización de clientes, la concentración de cuota de mercado y la manipulación del consumidor. Este artículo explora estas preocupaciones éticas desde una perspectiva contemporánea, basándose en las experiencias y perspectivas de profesionales en IA y marketing predictivo. El estudio tiene como objetivo contribuir a la literatura de este ámbito al proporcionar una perspectiva moderna sobre las preocupaciones éticas del uso de la IA en el marketing predictivo, basándose en las experiencias y perspectivas de profesionales en el área.

Para realizar el estudio se realizaron entrevistas semiestructuradas durante seis semanas con 14 participantes con experiencia en sistemas habilitados para IA en marketing, utilizando técnicas de muestreo intencional y de bola de nieve. Se utilizó un análisis temático para explorar los temas que surgieron de los datos.

Los resultados revelan que el uso de la IA en marketing podría tener consecuencias no deseadas, como perpetuar sesgos existentes, violar la privacidad del cliente, limitar la competencia y manipular el comportamiento del consumidor.

El estudio identifica siete temas y los comparan con el modelo de Ashok para proporcionar una perspectiva estructurada para interpretar los resultados. El marco presentado por esta investigación es único y puede utilizarse para respaldar investigaciones éticas que abarquen aspectos sociales, tecnológicos y económicos dentro del ámbito del marketing predictivo.

人工智能（AI）为改进预测营销实践带来了诸多益处。然而, 这也引发了与客户优先级、市场份额集中和消费者操纵等伦理问题相关的观点。本文从当代角度深入探讨了这些伦理观点, 充分借鉴了人工智能和预测营销领域专业人士的经验和观点。旨在通过现代视角提供关于在预测营销中应用人工智能时所涉及的伦理观点, 为该领域做出有益贡献。

本研究采用了目的性和雪球抽样技术, 与14位在人工智能营销系统领域具有丰富经验的参与者进行为期六周的半结构化访谈。研究采用主题分析方法, 旨在深入挖掘数据中显现的主要主题。

研究结果表明, 在营销领域使用人工智能可能引发一系列意外后果, 包括但不限于加强现有偏见、侵犯客户隐私、限制竞争以及操纵消费者行为。

本研究通过明确定义七个独特的主题, 并采用阿肖克模型进行基准比较, 为读者提供了一个结构化的视角, 以解释研究结果。所提出的框架具有独特之处, 可有效支持在跨足社会、技术和经济领域的预测营销中展开的伦理研究。

Synthetic materials have many drawbacks in high-performance garments because they absorb less moisture and cause allergies to sensitive individuals. Cotton materials cannot satisfy all the requirements and cannot provide the required high performance. This study aims to use eco-friendly materials with a common structure to analyse their suitability for high-performance garment application.

This study used two eco-friendly yarns (bamboo, modal and bamboo: modal 50:50) and yarns per needle (two- and four-ply yarns). with a single jersey knit construction and gauge of 7. The physical, mechanical, appearance, comfort, thermal and ultraviolet protection factor (UPF) protection characteristics were evaluated using 15 tests.

The produced knitted fabrics showed high performance for use as garments with physical, mechanical, appearance, comfort, thermal and UPF protection characteristics that were achieved, tested and analysed. The highest-achieved samples with a good UPF (<15) were made from bamboo material, which has other high-performance characteristics such as antibacterial characteristics, a soft surface, thermal insulation and others.

The single jersey structure was used for producing fabrics as it is the common structure in the garment. Also, only gauge 7 was used for its economics and ease of production.

The purpose of this study is to explore the machining characteristics of electrical discharge machining (EDM) when a tool is fabricated using powder metallurgy. Because pure Cu tools obtained using conventional machining pose problems of high tool wear rate, tool oxidation causes loss of characteristics in tool shape.

The research investigation carried out experiments planned through Taguchi’s robust design of experiments and used analysis of variance (ANOVA) to carry out statistical analysis.

It has been found that copper and chromium electrodes give less metal removal rate as compared to the pure Cu tool. Analytical outcomes of ANOVA demonstrated that MRR is notably affected by the variable’s polarity, peak current, pulse on time and electrode type in the machining of EN9 steel with EDM, whereas the variables pulse on time, gap voltage and electrode type have a significant influence on EWR. Furthermore, the process also showed that the use of powder metallurgy tool effectively reduces the value of SR of the machined surface as well as the tool wear rate. The investigation exhibited the possibility of the use of powder metallurgy electrodes to upgrade the machining efficiency of EDM process.

There is no major limitation or implication of this study. However, the composition of the powders used in powder metallurgy for the fabrication of tools needs to be precisely controlled with careful control of process variables during subsequent fabrication of electrodes.

To the best of the authors’ knowledge, this is the first study that investigates the effectiveness of copper and chromium electrodes/tools fabricated by means of powder metallurgy in EDM of EN9 steel. The effectiveness of the tool is assessed in terms of productivity, as well as accuracy measures of MRR and surface roughness of the components in EDM machining.

Policymakers are developing government-level pandemic response strategies (GPRS) to assist architecture, engineering and construction (AEC) enterprises. However, the effectiveness of the GPRS has not been assessed. Therefore, this study aims to investigate the interrelationships between GPRS and AEC enterprises. To achieve that aim, the study objectives are to compare GPRS effectiveness between small-medium and large AEC enterprises, develop groupings to categorize interrelated GPRS and evaluate the effectiveness of the GPRS and interrelated constructs.

A systematic literature review and semi-structured interviews with 40 AEC industry professionals were carried out, generating 22 GPRS. Then, questionnaire survey data was collected among AEC professionals. In total, 114 valid survey answers were received and analyzed using the Kruskal–Wallis H test, normalized mean analysis, factor analysis and fuzzy synthetic evaluation.

Small-medium enterprises have four distinct critical GPRS: “form a special task force to provide support in maneuvering COVID-19,” “provide infrastructure investment budgets to local governments,” “develop employee assistance programs that fit all types of working groups” and “diversify existing supply chain.” Large enterprises have two distinct critical GPRS: “provide help in digitalizing existing construction projects” and “mandate COVID-19 as force majeure.” Eighteen GPRS can be categorized into the following five constructs: “market stability and financial aid,” “enterprise capability management,” “supply chain improvement,” “law and policy resources” and “information and workforce management.” The former two constructs are more effective than other GPRS constructs.

This is the first paper that evaluates the effectiveness of GPRS for AEC enterprises, providing new evidence to policymakers for well-informed decision-making in developing pandemic response strategies.

This study investigated the travel intentions (TIs) of Chinese travelers and their utilization of virtual tourism technology during the Zero COVID-19 policy period by using a stimulus-organism-response (SOR) model. The study specifically examines the interplay between knowledge of policy, perception of risk, TI, usage of virtual tourism technology (UVTT) and the mediating role of personal values.

The data were collected from 333 Chinese travelers through an online questionnaire, and structural equation modeling (SEM) was employed to test the proposed hypotheses.

The study suggests that knowledge of policy and risk perception increase changes in personal values (PVs), which, in turn, affect Chinese travelers' TIs and the UVTT, with PVs playing a mediating role. Risk perception has a positive effect on the UVTT.

This study highlights the positive impact of tourism policy knowledge and risk awareness on individual values as a stimulus. Stakeholders need to implement industry-specific policies that are in line with scientific developments. Tourism managers should prioritize understanding the psychological reactions of tourists in crises and provide support to mitigate negative emotions. Anticipating changes in PVs is crucial, as instability affects tourists' behavior. The findings of the study also provide valuable insights for technology designers and underscore the substitutability of virtual technologies in improving the tourism experience.

This study is the first to examine the mediating role of PVs in the relationship between knowledge of policy, tourism risk perception (TRP), TI and the UVTT based on the SOR model. The insights gained from this analysis can assist policymakers and tourism managers in understanding the psychological changes of tourists, thereby facilitating the development of appropriate tourism planning.