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THE highest strength wrought aluminium alloys currently available are based on the aluminium‐zinc‐magnesium‐copper system, and such alloys offer considerable potential for weight savings in airframe structures. However, these alloys have presented problems in service, arising from deficiencies in fracture toughness and fatigue crack propagation resistance together with a susceptibility to exfoliation corrosion and stress‐corrosion, which have led to restrictions being placed on their use by individual aircraft companies and by procurement authorities in a number of countries. This situation has led to the wide‐spread use in the UK and continental Europe of lower strength alloys of the aluminium‐copper‐magnesium‐silicon type, even though significant weight penalties are incurred in the process. There has been a more general acceptance of the high strength aluminium‐zinc‐magnesium‐copper alloys in the USA, where problems associated with their use have been partially alleviated by a willingness to replace components at short intervals, but even so during recent years a trend has developed there towards the use of lower strength versions of these alloys in attempts to improve airframe durability and reliability.

Antecedents and influences of workplace incivility have recently been studied in many areas of research but there is still a lack of consideration for the impact of culture. Theoretical considerations for the present research are based on the cultural dimensions of power distance and tightness/looseness because the collective levels of power distance are similar between Korea and Spain, but the collective levels of tightness/looseness are different between the two countries. The purpose of this paper is to examine whether individuals’ occupational position affects their normative reactions to incivility differently.

Participant (victim)’s (those who react to uncivil behaviors) social power (low vs high) and perpetrator’s (those who exhibit uncivil behaviors) social power (low vs high) were experimentally manipulated; all participants were randomly assigned to one of four perpetrator × victim conditions in relation to hierarchical positions (Ntot = 467).

The results suggest that the level of social and personal acceptability was greater either among Koreans than Spanish at a collective level or among people who endorsed higher power distance and tightness values. All in all, the findings highlight cultural influences on the importance of social hierarchy as a factor that can impact the people’s normative reactions to incivility.

The findings broaden our understanding of the psychology of employees in relation to incivility, by simultaneously considering the influences of culture (power distance and tightness/looseness) and social power.

The paper aims to clarify the effects of brand differentiation on the platform's formulation of channel strategy and help the online platform formulate the optimal channel strategy, which involves selecting a proper selling mode for each brand.

The paper develops a multistage game model consisting of one online platform and two competing manufacturers with differentiated brands and examines the effects of brand differentiation on these three channel members' profits under each candidate channel strategy.

The results show that the platform prefers to offer the reselling mode for both brands when the brand differentiation is low, and this preference will be enhanced by the decrease in order fulfilment cost. By contrast, when the brand differentiation is high, it will offer the reselling mode for the premium brand but the marketplace service for the economy brand if the order fulfilment cost is not high; or the marketplace mode will be offered to both brands if this cost is high.

This study assumes that the order fulfilment costs of platform and manufacturer are fixed and symmetric. Therefore, researchers are encouraged to consider asymmetric costs of order fulfilment.

The paper guides the online platform to formulate the optimal channel strategy for differentiated brands and provides managerial insights for differentiated brands entering online markets.

This paper explores platforms' optimal channel strategy by jointly considering the effects of brand differentiation and investigates the impacts of brand differentiation on the optimal decision making under four candidate options. Moreover, this paper has been extended to examine the case when the manufacturers' production costs cannot be neglected.

This study explores whether a firm's environmental and social (E&S) transparency affects corporate payout policies having two forms of dividend payout and stock repurchase payout.

Focusing on a large sample of S&P 500 firms, and utilizing Tobit estimators, the author examines whether a firm's environmental transparency and social transparency affect the levels of each dividend payout and stock repurchase payout. Transparency reflects comprehensive scores compiled by Bloomberg, capturing both the quantity (in terms of the number of data points) and the quality (with respect to objective and industry-relevant data points) of verified E&S information attributed to a firm's E&S practices.

The findings demonstrate that transparency, both environmental and social, relates to higher corporate payouts (i.e. higher dividend payout and higher stock repurchase payout). These positive relationships are magnified for firms suffering from high information asymmetry, low financial reporting quality and for those with weak governance. Moreover, the author finds that dividend payout is more stable in high E&S transparent firms than in low E&S transparent firms. The study findings continue to hold after a battery of robustness and sensitivity checks such as alternative measures, specifications, estimators, use of the instrumental variable regression approach and mitigation of omitted variable bias

The study findings suggest that investors' interests (demanding for high corporate payouts) and other stakeholders' interests (demanding for high E&S transparency) are not necessarily in conflict, and investors' demands can be met while maintaining commitment to high E&S transparency. In addition, the study results imply that higher E&S transparency complements higher corporate payouts and signals to the market both a firm's commitment to E&S transparency and its ability to have high corporate payouts. In this line, the study findings clarify the high value of E&S transparency screening in investors' decision-making process as such transparency leads to higher corporate payouts for investors (i.e. facilitating wealth transfer to shareholders). Finally, the study findings are relevant to standard setters and regulators who emphasize the importance of E&S transparency.

By integrating two distinct streams of literature on corporate finance and corporate social responsibility (CSR), the author introduces E&S transparency as a novel nonfinancial driver of corporate payout policies. Finally, the study findings are in line with the notion that firm transparency (reflected in E&S transparency) can be a crucial element in justifying a firm's corporate payout policies and, in an overall view, firm policies.

This study aims to reconcile conflicting empirical results from prior studies on the association between political connections (PCs) and firms’ performance. Furthermore, it investigates whether the contradictory findings were moderated by the different types of both PCs and firms’ performance measures. This study also makes a cross-country comparison of the empirical evidence to provide more insight.

This study used meta-analysis to integrate the previous studies’ findings on the association between PCs and firms’ performance and further investigated the moderators of such association.

The findings show that PCs have a positive association with firms’ performance. This result is apparent for both democratic and authoritarian countries, which suggests PCs’ beneficial consequences toward firms’ performance should not be disregarded in both contexts. This study also finds PCs and firms’ performance measures moderate the association between PCs and firms’ performance.

This study contributes to the stream of research that investigates the association between PCs and firms’ performance. To the best of our knowledge, it is among the first to implement statistical meta-analysis on the aforementioned literature while incorporating a cross-country comparison.

Omnichannel sales have provided new impetus for the development of catering merchants. The authors thus focus on how catering merchants should manage capacities at the ordering, production and delivery stages to meet customers’ needs in different channels under third-party platform delivery and merchant self-delivery. This is of great significance for the development of the omnichannel catering industry.

This paper formulates the capacity decisions of omnichannel catering merchants under the third-party platform delivery and merchant self-delivery mode. The authors mainly use queuing theory to analyze the queuing behavior of online and offline customers, and the impact of waiting time on customer shopping behavior. In addition, the authors also characterize the merchant’s capacity by the rate in queuing model.

The authors find that capacities at ordering stage and food production stage are composed of base capacities and safety capacities, but the delivery capacities only have the latter. And in the self-delivery mode, merchants can develop higher safety capacities by charging delivery fees. The authors prove that regardless of the delivery mode, omnichannel sales can bring higher profits to merchants by integrating demand.

The authors focus on analyzing the capacity management of omnichannel catering merchants at the ordering, production and delivery stages. And the authors also add the delivery process into the omnichannel for analysis, so as to solve the problem of capacity decision-making under different delivery modes. The management of delivery capacity and its impact on other stages’ capacities are not covered in other literature studies, which is one of the main innovations of this paper.

I‐V characteristics of GaAs n‐i‐n structures are calculated by considering impact ionization of carriers. Impact ionization at reverse‐biased n‐i junction becomes a cause of steep current rise when an acceptor density in the i‐layer is high. It is shown that an optimum acceptor density exists to keep a good isolation. Photoconduction transients of GaAs n‐i‐n structures are also simulated, and are shown to be strongly affected by existence of n‐i junctions.

This study presents a framework to estimate throughput and cost of additive manufacturing (AM) as related to process parameters, material thermodynamic properties and machine specifications. Taking a 3D model of the part design as input, the model uses a parametrization of the rate-limiting physics of the AM build process – herein focusing on laser powder bed fusion (LPBF) and scaling of LPBF melt pool geometry – to estimate part- and material-specific build time. From this estimate, per-part cost is calculated using a quantity-dependent activity-based production model.

Analysis tools that assess how design variables and process parameters influence production cost increase our understanding of the economics of AM, thereby supporting its practical adoption. To this aim, our framework produces a representative scaling among process parameters, build rate and production cost.

For exemplary alloys and LPBF system specifications, predictions reveal the underlying tradeoff between production cost and machine capability, and look beyond the capability of currently commercially available equipment. As a proxy for build quality, the number of times each point in the build is re-melted is derived analytically as a function of process parameters, showcasing the tradeoff between print quality due to increased melting cycles, and throughput.

Typical cost models for AM only assess single operating points and are not coupled to models of the representative rate-limiting process physics. The present analysis of LPBF elucidates this important coupling, revealing tradeoffs between equipment capability and production cost, and looking beyond the limits of current commercially available equipment.

This paper aims to examine how consumers respond to social media influencers that are created through artificial intelligence (AI) and compares effects to traditional (human) influencers.

Across two empirical studies, the authors examine the efficacy of AI social media influencers. With Study 1, the authors establish baseline effects for AI influencers and investigate how social-psychological distance impacts consumer perceptions. The authors also investigate the role of an influencer’s agency – being autonomous or externally managed – to test the boundaries of the results and determine the interactive effects between influencer type and influencer agency. Study 2 acts as an extension and validation of Study 1, whereby the authors provide generalisability and overlay the role of need for uniqueness as a moderated mediator.

The authors show that there are similarities and differences in the ways in which consumers view AI and human influencers. Importantly, the authors find no difference in terms of intention to follow or personalisation. This suggests that consumers are equally open to follow an AI or human influencer, and they perceive the level of personalisation provided by either influencer type as similar. Furthermore, while an AI influencer is generally perceived as having lower source trust, they are more likely to evoke word-of-mouth intentions. In understanding these effects, the authors show that social distance mediates the relationship between influencer type and the outcomes the authors investigate. Results also show that AI influencers can have a greater effect on consumers who have a high need for uniqueness. Finally, the authors find that a lack of influencer agency has a detrimental effect.

The studies investigate consumers’ general response to AI influencers within the context of Instagram, however, future research might examine consumers’ response to posts promoting specific products across a variety of category contexts and within different social media platforms.

The authors find that in some ways, an AI influencer can be as effective as a human influencer. Indeed, the authors suggest that there may be a spill-over effect from consumer experiences with other AI recommendation systems, meaning that consumers are open to AI influencer recommendations. However, the authors find consistent evidence that AI influencers are trusted less than traditional influencers, hence the authors caution brands from rushing to replace human influencers with their AI counterparts.

This paper offers novel insight into the increasingly prominent phenomenon of the AI influencer. Specifically, it takes initial steps towards developing understanding as to how consumers respond to AI influencers and contrast these effects with human influencers.

Parallel imports are authentic products that challenge those sold through authorized dealers. Such imports are fast becoming popular, especially in Asia. Authorized dealers need to find ways to combat against parallel imports. One such means is to first understand consumer perceptions of parallel imports. A survey among respondents from an Asian country, Singapore, showed that perception and not demography or past product experience influence purchase intention of parallel imports. Perception of beneficial and image properties, more so than perception of physical properties, influenced purchase intention. The factors influencing the magnitude of discount expected from parallel importers were different from those for purchase intention. Women expected higher discounts than men, while an inverse relationship was observed for income. The unique properties for each product category also influenced purchase intention and expected discount. Managerial implications are discussed together with directions for future research.