Exploring service employees ’ involvement in value co-creation: dimensions, antecedents and consequences

Purpose – Although customer co-creation has received a significant amount of attention in both practice and academics, most of the previous studies have been conducted from the customer perspective while how service employees are involved in the customer value co-creation process has been rarely examined. To fill in this gap, the purpose of this paper is to develop a scale of employee involvement in customer value co-creation, and test a theoretical model that investigates the antecedents and consequences of employee involvement in customer value co-creation. Design/methodology/approach – Based on a comprehensive literature review and 12 in-depth interviews with service employees, a scale of employee involvement in customer value co-creation was developed in Study 1. The items were purified, and the construct validity and reliability were evaluated via a survey (n = 178). In Study 2, the newly developed scale was cross-validated in a new service context and a conceptual model was tested by estimating a structural equation model with survey data collected from service employees (n = 225). Findings – The newly developed scale of employee involvement in customer value co-creation has demonstrated sufficient construct validity and reliability across different service contexts. Moreover, the results show that both customer orientation and perceived organizational support are positively associated with employee involvement in customer value co-creation, which, in turn, influences employees’ job satisfaction and job stress. In addition, firm cross-functional cooperation strengthens the relationships between perceived organizational support and employee involvement in customer value co-creation. Research limitations/implications – Future research from other service contexts and countries is needed to confirm the generalizability of the new scale and the findings. Practical implications – The findings of the study will provide implications to service managers regarding where to focus their organizational resources and how to facilitate employee involvement in customer value co-creation. Originality/value – This study takes an initial step to develop a scale of employee involvement in customer value co-creation and test the antecedents and consequences of employee involvement in customer value co-creation.

Download PDF: https://sumantri.eu.org/FQ5YVI

Artificial intelligence in action: shaping the future of public sector

Purpose – Artificial intelligence (AI) has transformed various sectors, including automotive, finance, media, travel and retail by leveraging new-age technologies. Education, banking, health care, social policy and regulation, within the public sector have witnessed significant AI applications and substantial benefits. The importance of AI in the public sector includes enhanced efficiency, improved decision-making, cost savings, citizen-centric services, etc. Despite these advancements, a mindful discussion on the societal impact of AI in the public sector demands comprehension regarding its subjugation. Therefore, this study aims to analyze the role of AI in transforming the public sector using a bibliometric analysis of recent trends and challenges. Design/methodology/approach – This study has used bibliometric analysis to trace the intellectual patterns of previous research. It comprises 231 articles from 2000 to 2024 from Scopus through the Scientific Procedures and Rationales for Systematic Literature Reviews protocol. This protocol has adopted a three-step process for identifying articles, i.e. assembling, arranging and assessing. Findings – The publication trend shows an upward trajectory since 2017, whereas network visualization protrudes with the recent trends and thematic expressions, namely, Global AI ethics and policy challenges in public sectors, AI adoption and governance in public sector, challenges and opportunities of implementing AI in public administration and AI’s role in economic and public transformation. Research limitations/implications – The findings suggest AI adoption in the public sector enhances transparency and efficiency but demands ethical guidelines, legal frameworks and stakeholder governance to address challenges such as data pr ivacy, algorithmic bias and public trust. Policies should promote responsible AI use, balancing innovation with accountability to improve public service delivery and uphold democratic values. Originality/value – This paper enhances the limited literature on the integration of AI in the public sector, focusing on emerging themes and trending topics with future research directions to furnish a holistic perspective. It aims to guide researchers and policymakers in exploring areas for further investigation in this domain.

Download PDF: https://jawop.eu.org/nS9uoP

in the workplace: influence

Purpose – Technology-mediated learning (TML) is gaining popularity among business organizations for upskilling their employees. However, high dropout rates have limited its effectiveness. Thus, we explore, if and how personalization of TML can improve its adoption and effectiveness in workplaces from the lens of the unified theory of acceptance and use of technology (UTAUT2) theory. Design/methodology/approach – An exploratory sequential mixed-method design was used for this study. Study 1 included interviews (N 5 27) of Learning and Development (L&D) leaders and employees (learners) of large global organizations, about their experiences with TML. Emergent themes led us to our research model, which integrates constructs of personalization, technology adoption and transfer of training (TT). In Study 2, a cross-sectional study w as conducted. Data were collected from employees who have experienced TML (N 5 406) and analyzed using PLS-SEM. Findings – Findings suggested that personalization of TML positively influenced intent to use TML and transfer skills, thereby improving TML effectiveness and proving its relevance in workplaces. Precisely, personalized TML recommendations from managers impacted (1) behavioral intention (BI) and TT directly; (2) BI through performance expectancy (PE); (3) TT through social influence and BI individually; and (4) TT through PE and BI sequentially. Likewise, allowing employees the flexibility to choose TML based on their interests influenced (1) BI directly and via hedonic motivation (HM) and (2) TT via HM and BI individually and sequentially. Practical implications – Using our model, L&D practitioners may design and personalize their TML ecosystems to foster adoption and transfer of training in workplaces. Originality/value – Personalization of learning in workplac es has received scant attention; thereby, our study expands existing knowledge in this relatively nascent field of research.

Download PDF: https://exempler.eu.org/1zjBzQ

Exploring attitudes towards disability employment in the Indian hotel industry: a qualitative inquiry

Purpose – This study investigates the attitudes and perceptions toward employing persons with disabilities (PWDs) in the Indian hotel industry, focusing on perspectives of senior management and frontline staff. It will also provide insights that could lead to policy changes and inclusive practices in the hospitality industry. Design/methodology/approach – Through qualitative methods, including 19 semi-structured in-depth interviews with hotel employees across Delhi NCR, Goa and Bengaluru, this research uncovered the complex and varied views on integrating PWDs into the hospitality workforce. Findings – Our investigation revealed a variety of perceptions after organising them into 18 sub-themes distributed across seven main themes. Results indicated that whil e senior managers often viewed PWD inclusion positively, citing benefits like enhanced loyalty and corporate social responsibility contributions, frontline staff expressed concerns about operational and service quality challenges. The findings also highlight the need for comprehensive training and support systems to integrate PWDs successfully. Originality/value – This research contributes new insights into the dynamics of disability employment within a high-interaction service sector, advocating for policy changes and inclusive practices. It suggests practical measures for promoting inclusivity and diversity in hotel operations, marking a significant step forward in understanding and advancing workplace inclusivity in developing economies.

Download PDF: https://crasmi.eu.org/90KRUP

Investigation on microstructure and mechanical properties of reformer furnace tube after 12 years’ service

The entire reformer furnace tube is analyzed and studied through OM, SEM and mechanical property test in this work. The microstructure of centrifugal casting tube and weld joint has deteriorated, with the primary carbides coarsened and growth. The primary carbides at the dendrite boundary have grown from lamellar and skeleton shape to continuous network and chain shape, and the primary carbides M7C3 and Nb(Ti)C transformed into M23C6 and G phase. The high temperature creep strength of reformer furnace tube decreased obviously. Through the investigation of the microstructure and mechanical properties of different zones in the entire reformer furnace tube, the weakest part of the reformer furnace tube is located in the middle and lower zone, and its remnant life h as been predicted. On the basis of the design temperature and pressure, the remnant life of this reformer furnace tube is 38000 hours. ARTICLE HISTORY Received 2 March 2025 Accepted 19 June 2025 KEYWORDS HPNbM alloy; reformer furnace tube; remnant life; carbide; creep strength Introduction With the rapid development of the petrochemical industry, factors such as the reduction in raw material quality and increasing demands for product purity have driven continual improvements in production technology [1,2]. Consequently, the service environ­ ment of production equipment is evolving towards extreme working conditions, such as high temperature and high pressure [3]. In petrochemical industry, the r

Download PDF: https://cocontoh.eu.org/FsEKo5

XLDGND

: Due to the strong non-stationarity of rotating machinery vibration signals under coupling effects of noise environments and time-varying conditions, traditional time-frequency analysis (TFA) methods and existing time-frequency networks struggle to dynamically characterize closely-spaced instantaneous frequencies (IFs) under noisy environments. Therefore, the time-frequency denoising and optimization network (TFDON) is proposed. In the TFDON, an attention-guided sparse denoising sub-network (SDSN) is first designed to eliminate noise aliasing interference and obtain the clean time-frequency representation (TFR). Then, the time-frequency optimization sub-network (TFOSN) with three-stage hybrid Transformer blocks (HTB) cascade is constructed. Within each HTB, an efficient grouped Swin-Transformer (EGST) is developed to compute the spatiotemporal character istics, and guided by a dual-layer attention mechanism, the time-frequency concentration is iteratively enhanced. Additionally, a weight-controllable joint loss function tailored for the TFR denoising and optimization is designed to achieve the optimal balance in two tasks. The performance of the TFDON in characterizing and noise suppression is verified by a simulated signal with closely-spaced IFs. Meanwhile, two bearing and a planetary gearbox vibration signal added noise are further analyzed, and the TFDON achieves the lowest Rényi entropy of 6.055, 6.387, and 6.077 at −5 dB, *Corresponding author. Downloaded for personal academic use. All rights reserved. https://papernode.online/

Download PDF: https://gemilang.eu.org/xLDGND

Military service and depression risk among American adults: a cross-­sectional analysis based on NHANES data from 2011 to 2023

Introduction Depression is a common mental health disorder with high morbidity and disability rates. Military personnel are often considered a vulnerable population for depression, but epidemiological studies on the prevalence in veterans are limited. This study explores the relationship between military service and depression risk among American adults using a cross-­sectional design based on National Health and Nutrition Examination Survey (NHANES) data from 2011 to 2023. Methods This cross-­sectional study used data from NHANES collected from 2011 to 2023. Depression was diagnosed based on the Patient Health Questionnaire-­9 (PHQ-­9) scores. Military service status was determined by responses to the demographic question. Binary logistic regression analys is was conducted to examine the association between military service and depression, as well as the factors influencing depression in veterans. Results After data cleaning, a total of 25 949 participants were included, 2407 individuals with military service and 2548 with depression. In the unadjusted analysis there was no significant difference in the prevalence of depression between military service and non-­ service individuals. However, after adjustment, military service was associated with a 23% reduction in the risk of depression (OR 0.77, 95% CI 0.61 to 0.96). Subgroup analysis showed that, among non-­Hispanic Black individuals, married persons, high-­income individuals and those witho

Download PDF: https://exemplede.eu.org/jZ873Y