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The paper aims to identify the effect of ignorance of correlatedness among process observations and to implement new sampling schemes; skip and mixed sampling, in order to reduce the effect of autocorrelation on process capability index (PCI) Cpm.

Autocorrelated observations are generated using autoregressive process of order two (AR (2)) using Monte Carlo simulations. The PCI is computed based on these observations assuming the independence. The skip and mixed sampling schemes are then used to form sub-groups among correlated observations. The PCI obtained using sub-groups from skip and mixed sampling schemes are assessed using sample mean and sample standard deviation.

The paper provides empirical insights into how the effect of autocorrelation decreases in the estimated value of PCI Cpm. The use of new sampling schemes, skip and mixed sampling, reduces the effect of autocorrelation on estimates of PCI Cpm.

This paper fulfills an identified need to study how to reduce the effect of autocorrelation on PCI Cpm.

The purpose of this paper is to improve the productivity and quality of the wire arc additive manufacturing process by benchmarking the strategies from the selected six strategies, namely, heat treatment process, inter pass cooling process, inter pass cold rolling process, peening process, friction stir processing and oscillation process.

To overcome the lack of certainty associated with correlations and relationships in quality functional deployment, fuzzy numbers have been integrated with the quality functional deployment framework. Twenty performance measures have been identified from the literature under five groups, namely, mechanical properties, physical properties, geometrical properties, cost and material properties. Using house of quality weights are allocated to performance measures and groups, relationships are established between performance measures and strategies, and correlations are assigned between strategies. Finally, for each strategy, relative importance, score and crisp values are calculated.

Inter pass cold rolling process strategy is computed with the highest crisp value of 15.80 which is followed by peening process, heat treatment process, friction stir processing, inter pass cooling process,] and oscillation process strategy.

To the best of the authors’ knowledge, there has been no research in the literature that analyzes the strategies to improve the quality and productivity of the wire arc additive manufacturing process.

This research investigates the impact of strategic research and development (R&D) (one led by a firm’s innovation orientation) on stock market performance during the economic disruption caused by the 2016 demonetization of high-value currency notes in India. It shows how firms’ strategic focus on innovation and integrated R&D initiatives can help mitigate shareholders’ losses and protect market value during negative macroeconomic shocks.

We analyzed financial and administrative data from firms listed in the Bombay Stock Exchange (BSE) 500 index and used the Fama French market model with appropriate instruments accounting for possible endogeneity to identify the impact. To ensure the reliability of our findings, we conducted robustness checks with alternate event windows, estimation methods, and variable measurements.

Strategic R&D plays a crucial role in building resilience against macroeconomic shocks. It effectively mitigated shareholders’ losses in the immediate aftermath of the shock, with an elasticity of abnormal returns of 7.65% on day zero, 13.1% during the first five days and 10.5% after the first fortnight. We also find that firms that are business-to-business (B2B), as well as those that are older and less leveraged, are better able to combat such a shock.

The study looked at one shock, namely demonetization. Future research is needed to demonstrate the generalizability of results during other macroeconomic shocks, like the COVID-19 pandemic. The study focuses on relatively near-term impacts, leaving the long-term value-creation effects of strategic R&D unexplored.

Innovation orientation acts as a structural enabler, allowing firms to make strategic R&D investments that mitigate losses during macroeconomic shocks. It explains that managers should avoid myopically managing R&D investments and align them with the firm’s innovation focus to enhance value creation.

While the currency demonetization was widely considered to be detrimental for firms as an unannounced negative monetary shock, our research shows that firms with high levels of strategic R&D were successfully able to counteract such a shock.

This is the first study to examine the short-term loss mitigation impact of firms’ focus on innovation and strategic R&D. It emphasizes the role of innovation-focused strategies during economic crises.

This paper aimed to test a proposed framework highlighting strategic green marketing initiatives and how they drive new technology implementation towards green corporate performance, underpinned by institutional isomorphism.

The study used a quantitative method and convenience sampling approach in gathering data using adapted questionnaires to solicit first-hand information from 225 employees of small and medium-sized enterprises (SMEs) in the tourism and hospitality sector underpinned by the theory of institutional isomorphism.

The study shows that green communication and green strategy alignment have significant predictive effects on new technology implementation. Cultural isomorphism significantly moderated the effects of implementing new technology (i.e. green communication and strategy alignment). In addition, “new technology implementation had a significant predictive effect on green corporate performance”. Meanwhile, the moderation effect of “green creative behaviour on the new technology-green corporate performance dyad was positive but insignificant.”

The study’s novel framework confirms how green communication strategy and green strategy alignment complement cultural isomorphism to explain the impact of new technology implementation on green corporate performance, underpinned by institutional isomorphism.

This paper investigates the consequences of job insecurity among hotel employees during the COVID-19 pandemic.

Data were obtained from the employees of two five-star chain hotels in Turkey. The study hypotheses were tested via structural equation modeling.

The research findings demonstrate that job insecurity exacerbates job tension. Job tension erodes employees’ trust in organization and aggravates their propensity to leave work early and be late for work. As hypothesized, job tension mediates the effect of job insecurity on organizational trust and the abovementioned outcomes.

This study adds to the hospitality literature by assessing the interrelationships of job insecurity, job tension, organizational trust and nonattendance intentions.

Based on the stimuli-organism-response model and relationship marketing theory, the effect of different dimensions of Servicescape (Ambience, Cleanliness, Functionality, Spatial Layout, Employee Service Quality) on Customer Satisfaction and Behavioral Intention in hospitals during the COVID-19 pandemic are considered.

The study takes a quantitative approach, applying structural equation model using partial least square structural equation modeling to test the hypotheses. A total of 360 responses were collected using questionnaires distributed to different individuals who visited private hospitals in the past two months in India.

Contradicting previous research, this study found that among servicescape dimensions, employee service quality had the maximum influence on customer satisfaction and cleanliness does not have any significant impact on customer satisfaction as hypothesized. Mediation results show that customer satisfaction has a partial mediation effect for all servicescape dimensions except ambience, as both direct and indirect effects are significant. Importance-performance map analysis was performed on the responses collected, and it was found that employee service quality is the most important dimension affecting servicescape, followed by functionality and spatial layout. Thus, health-care institutions should focus on these factors to keep their customers satisfied.

Past studies have focused on the roles of servicescape and customer satisfaction separately. The authors have extended the literature by examining the combined effects of both servicescape and customer satisfaction. The findings from the study, therefore, help in developing a deeper understanding of the literature on the behavior intention relationship in the context of health care, as well as in service marketing.

The Overall Equipment Effectiveness (OEE) is considered a standard for measuring equipment productivity in terms of efficiency. Still, Artificial Intelligence solutions are rarely used for analyzing OEE results and identifying corrective actions. Therefore, the approach proposed in this paper aims to provide a new rule-based Machine Learning (ML) framework for OEE enhancement and the selection of improvement actions.

Association Rules (ARs) are used as a rule-based ML method for extracting knowledge from huge data. First, the dominant loss class is identified and traditional methodologies are used with ARs for anomaly classification and prioritization. Once selected priority anomalies, a detailed analysis is conducted to investigate their influence on the OEE loss factors using ARs and Network Analysis (NA). Then, a Deming Cycle is used as a roadmap for applying the proposed methodology, testing and implementing proactive actions by monitoring the OEE variation.

The method proposed in this work has also been tested in an automotive company for framework validation and impact measuring. In particular, results highlighted that the rule-based ML methodology for OEE improvement addressed seven anomalies within a year through appropriate proactive actions: on average, each action has ensured an OEE gain of 5.4%.

The originality is related to the dual application of association rules in two different ways for extracting knowledge from the overall OEE. In particular, the co-occurrences of priority anomalies and their impact on asset Availability, Performance and Quality are investigated.

This study aims to examines both accrual and real-based earnings management (EM) behavior of listed corporations in tax-free countries during different economic situations. It also addresses the link between firm- and country-level determinants of accrual and real-based EM and explores economic conditions' influence on these determinants.

The study examines 1,608 firm-years, covers sixteen years (2004–2019), clustered into three periods according to the global financial crisis (GFC): four years prior (2004–2007), two years during (2008–2009), and ten years post the GFC (2010–2019). We employ the modified Jones model (performance-matched) developed by Kothari et al. (2005) to measure the accrual-based EM (positive and negative discretionary accrual EM) and the three levels model for Dechow et al. (1998) to measure the real-based EM (cash flow from operating, discretionary expenses and abnormal production cost).

The study finds a significant increase in EM practices in the listed corporations in tax-free countries during the economic downturn. These corporations are found to understate their earnings during the economic stress period. Simultaneously, the firm-level determinants of EM practices were at the same level of significance during different economic conditions in accrual-based EM. In contrast, the country-level EM determinants vary based on the economic conditions.

Financial reports' users gain a deep understanding of the quality of financial reports in the context of tax-free country. And, the study outcomes inspire policymakers to develop relevant legislation to mitigate financial reports' risk and adequately protect the financial reports' users.

One of the crucial elements of addressing global climate challenges through urban tourism is the continuing existence of urban forests. The reasoning is that the ecological attraction of urban forests can impact visitors’ intention to conduct pro-environmental behavior, including low-carbon actions. Thus, more visitors to urban forests will positively affect enhancing the quality of the urban environment. However, the extent to which ecological attraction can influence pro-environmental behavior warrants further investigation due to the complexity of psychosocial factors that impact behavioral intention. The main objective of this research is to examine the effects of the ecological attractiveness of urban forests on the pro-environmental behavior of visitors by exploring motivation, ecological experience, perceived value and knowledge as mediators. Moreover, whether the nature of the urban forest and facilities attract visitors simultaneously is also studied.

Data were collected from 615 respondents who visited three urban forests in Bandung, the second-most populous city in Indonesia, by five-point Likert questionnaires. As an analytical tool, SEM PLS was applied to establish the effect of the ecological performance of the urban forest on the increase in environmentally conscious behavior among urban forest visitors.

The findings demonstrate that the attractiveness of an urban forest affects the growth of environmentally responsible behaviors. Nonetheless, the attractiveness of urban forests is dictated more by their infrastructure than their ecological function. On the contrary, the visitors’ knowledge level can improve their motivation, environmental experience and perceived environmental value. These findings show the significance of developing educational programs with an emphasis on the experience of the visitors so that their ecological performance can contribute to improved low-carbon behavior. In conclusion, this work contributes to the management of sustainable urban tourism.

This work also has some limitations. First, the medium R-square on intention behavior to low-carbon action suggests investigating other influential factors to produce a more robust conscious behavior. Mkono and Hughes (2020) mention that many complex factors that cause positive intention do not necessarily lead to environmental action. Thus, many psychosocial variables need to be explored in different models. Second, the convenient sampling used here does not represent the whole population, making generalization difficult. Thus, further work needs to apply more rigorous sampling techniques to validate the findings. Further investigations may also need to be conducted in other urban forests in another Asian country with a similar and different social context for benchmarking, as this study found that the type of attractive urban forest design is a more dense forest, which differs from other studies based in Europe. Exploring more influencing behavioral factors of pro-environmental action in the model is also suggested. Thus, we could contribute more to support recreational activities in urban forests.

As an implication for planning an urban forest to increase its recreational function, the authors illustrate the importance of producing educational programs. Although the improved knowledge of visitors has been shown to strengthen their commitment to perform pro-environmental actions, the mediating role of motivation, experience and perceived value reveals that some activities are required to achieve visitor motivation to actual behavior. Consequently, designing an urban forest requires not only the enhancement of eco-attractions and artificial elements for the convenience of visitors but also the development of an environmental education program that can improve visitors’ environmental experience and perception of ecological value. The designed educational program may use an experiential education approach incorporating objective knowledge of Earth’s current state. The urban forest education program must encourage visitors’ connection and participation with nature. Moreover, knowledge and information about Earth’s environmental quality can increase visitors’ perceived value, ensuring that their activities in the urban forest contribute to improved health, environmental quality and social environment. Thus, with well-managed and provided education, they are encouraged to adopt low-carbon action because it complements their contribution to a better quality environment.

The theoretical contribution of this research is generated through the role of urban forest attractiveness in the intention to conduct low-carbon action, which influences solutions to existing urban environmental problems. This work exhibits that both ecological attractiveness and attractiveness of artificial elements in urban forests can attract visitors and subsequently boost their outdoor recreation motivation, ecological experience and perceived value and then turn them to boost their intention to conduct low-carbon action. The physical characteristics of a site are behavioral stimuli that can increase a person’s motivation, experience and perception of the value of the environment, thereby increasing their intention to engage in low-carbon actions. This environment behavioral construction is fundamental in understanding that urban forests offer ecological benefits and influence the social quality of urban communities. Nevertheless, without visitor activity, urban forests are merely physical entities that become increasingly demanding to maintain. Due to this, an urban forest that is socially active and has an influence on promoting environmentally conscious behavior is needed, and its presence is becoming ever more crucial. This work shows the significance of integrating psychosocial approaches into managing tourism in urban forests.