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This study aims to analyze the lean supply chain management (LSCM) strategy's role as a mechanism to address technology uncertainty and provide organizations with competitive advantage.

An empirical study was conducted of 276 Spanish focal firms in industrial sectors that occupy an intermediate position in the supply chain to investigate the influence of technology uncertainty on LSCM implementation and the latter's effect on operational performance and competitiveness. A covariance-based structural equation model (CB-SEM) was used to test three hypotheses.

Technological uncertainty encourages progress in the implementation of lean throughout the supply chain and so is a mechanism that not only brings stability to the focal company but also improves its performance and puts it in a better competitive position.

Managers are suggested to consider the strategic integration with supply chain partners and the establishment of long-term relationships based on trust and commitment advocated by LSCM to enhance organizations' capabilities and effectively and flexibly respond to technological changes.

This study focuses on the effects of environmental uncertainty on the supply chain. The past literature has focused on the behavior of individual firms to deal with uncertainty, but this work shifts the level of analysis to the supply chain. Therefore, the strategic change to deal with what is happening in the environment is now switched to the supply chain level.

This research aimed to fill several gaps in the tipping literature which has overlooked the server's perspective in identifying and understanding variables that influence a tip amount and therefore where they concentrate their efforts during the service encounter. Furthermore, the extant literature has theorized how or why certain variables influence the tip amount, but these studies fail to capture insight from server's which would supplement the theory and provide a more in-depth understanding of the mechanisms at play.

This study adopts a grounded theory approach using semi-structured one-on-one interviews with tipped restaurant employees who were identified and selected using snowball sampling. Content analysis is employed to code and categorize the data.

The content analysis revealed five categories where servers focus their time and effort to earn tips: service quality, connection, personal factors, expertise and food quality. The server's personality was identified as a variable the tipping literature has largely ignored as a determinant of the tip amount. Server's shift their style of service for groups of eight or more people, and for regular customers, who must dine in the restaurant at least once per week. Lastly, despite the many drawbacks associated with working for tips, servers would not want to replace it with any other method of compensation.

This is the first qualitative study focused on understanding the server's role in the service exchange relationship since McCarty et al. (1990) study. The results provide new insights on the often-studied variables from the tipping literature.

The link between supply chain agility (SCA) and performance has been tested in previous research with different samples and results. The present paper quantitatively analyses and summarises the impact of SCA on performance found in previous empirical papers and determines the influence of several identified moderators.

Using a meta-analysis approach based on a systematic literature review, a total of 63 empirical papers comprising a sample of 14,469 firms were meta-analysed to consider substantive (type of performance and SCA operationalisation) and extrinsic (economic region and industry) moderators.

Results confirm a significantly large, positive correlation between SCA and performance. None of the analysed moderators has enabled the identification of any significant differences between the SCA and performance correlations by subgroup. However, high heterogeneity in total variance, both in the full sample and the subgroups by moderator, demands further rigorously reported empirical research on this topic with clearly conceptualised variables and frameworks and the use of validated scales.

Several research gaps and best practice recommendations have been indicated to improve future empirical research on this topic.

Practitioners in different economic regions and industries will find consistent evidence of improvements in performance through SCA.

No meta-analysis has been found in previous research to estimate the value of the correlation between SCA and performance and the influence of moderating variables.