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The purpose of this paper is to discuss a practical approach taken by utilizing the non‐conformance/event management and failure investigation (FI) system to formally troubleshoot an actual process failure observed in the sequencing facility.

In this study the authors describe how the cause for the poor quality sequence data, as indicated from the quality score, involving high molecular weight follicular lymphoma DNA samples for a study of tumor‐associated genome rearrangements was successfully identified and confirmed through the application of a well structured FI process.

Through this FI process the underlying causes were effectively identified, immediate corrective actions were executed and a preventative action to avoid or minimize reoccurrences was also implemented and monitored for effectiveness.

This paper establishes that by applying a systematic, documented FI process the underlying causes of a process failure in an organization can be effectively identified and appropriate corrective and preventative actions can be successfully adopted.

Despite the growing popularity of ride-sharing in China, our understanding regarding users' trust and behavioral intention toward this new type of hailing service is still limited. This study aims to examine the joint influences of institution-based, process-based and characteristic-based antecedents on customers' trust and continuance intention toward ride-sharing. Furthermore, the study aims to investigate if the relative influences of institution-based and process-based antecedents on trust are contingent upon customers' prior experience.

Drawing upon trust-building literature and the elaboration-likelihood model, we developed a research model and conducted an online survey to users of Didi, the largest ride-sharing platform in China. We used the structural equation modeling technique to analyze the collected data and examine the proposed research model.

Ther major research findings of the study suggest that structural assurance, government support, platform reputation and disposition to trust exhibit significant and different degrees of influences on customers' trust beliefs and continuance intention toward ride-sharing. A multi-group analysis further suggests that customers with less use experience focus more on government support and platform reputation, while customers with more use experience are more likely influenced by structural assurance.

The study contributes to the extant literature by identifying the joint influences of institutional-based, process-based and characteristic-based antecedents on users' continuance intention of ride-sharing service and uncovers the mediation mechanism of trust and perceived risk. Moreover, the study refines the boundary condition of the proposed research model by revealing the moderating effect of use experience.

This paper aims to apply the Product Life Cycle (PLC) and Product Evolutionary Cycle (PEC) frameworks to the nicotine and tobacco market to predict the impact of television commercials for electronic cigarettes (e-cigarettes) on youth.

Surveys were administered over a three-year period to 417 alternative high school students from Southern California who had never used e-cigarettes, cigarettes or cigars at the baseline. Covariate-adjusted logistic regression causal mediation models were used to test competing hypotheses from the PLC and PEC frameworks.

Results support a refined version of the PEC framework where e-cigarette commercials increase the odds of e-cigarette use, which leads to subsequent use of competing products including cigarettes and cigars.

This investigation demonstrates the utility of frameworks that conceptualize youth-oriented marketing as a two-part process in which potential customers are first convinced to adopt a behavior and then enticed to use a specific product to enact the behavior.

Rising rates of nicotine and tobacco product use among youth may be partially attributable to e-cigarette commercials.

Regulations in the USA that permit television commercials for e-cigarettes but restrict the promotion of cigarettes and cigars have created an opportunity to study product adoption among youth consumers when one product has a strategic marketing advantage.

Generation Z makes up 20% of China’s population, and accounts for the highest share of household spend at 13% (vs. 3% for the United Kingdom and 4% for the United States). To advance marketers’ understanding about this group of consumers and capitalise on China’s booming market, this chapter uses rich statistics and information to show that China’s Generation Z has distinct behaviour patterns, which can be attributed to the unique background in which they grew up: (1) rigidity of social stratification, (2) abundance of materialism, (3) digital era, (4) limited (vs. extended) family, and (5) heavy schoolwork. Growing up in such a background, Generation Z’s lifestyle and consumption-related attitudes and behaviour are distinct from their predecessors. The chapter presents specific actions that marketers can take when targeting this distinct group of consumers in China, along with useful guidelines to HR managers for hiring them.

Drawing upon the needs–supplies fit theory, this study aims to examine how the expected and perceived algorithmic autonomy support (AAS) influences platform workers’ work stress and incivility, with a focus on the moderating role of self-direction.

Using data collected from 422 platform workers in China through multiple waves, the model is tested through polynomial regression and response surface analysis.

The results indicate that a mismatch between expected and perceived AAS is associated with higher levels of incivility among platform workers, and this relationship is mediated by work stress. These findings are particularly salient when self-direction is emphasized.

This study suggests that a universally high level of AAS may not necessarily reduce workers’ stress and incivility. Instead, it is important for platforms to ensure that their workers’ expectations of autonomy support are met and for workers to be given the space to exercise self-direction.

Previous studies have highlighted the need to pay attention to workers in mobile and ambiguous environments, and this study adds to this literature by focusing specifically on platform organizations and workplaces. This study provides valuable insights into the relationship between AAS, work stress and platform workers’ incivility.

Algorithms are widely used to manage various activities in the gig economy. Online car-hailing platforms, such as Uber and Lyft, are exemplary embodiments of such algorithmic management, where drivers are managed by algorithms for task allocation, work monitoring and performance evaluation. Despite employing substantially, the platforms face the challenge of maintaining and fostering drivers' work engagement. Thus, this study aims to examine how the algorithmic management of online car-hailing platforms affects drivers' work engagement.

Drawing on the transactional theory of stress, the authors examined the effects of algorithmic monitoring and fairness on online car-hailing drivers' work engagement and revealed the mediation effects of challenge-hindrance appraisals. Based on survey data collected from 364 drivers, the authors' hypotheses were examined using partial least squares structural equation modeling (PLS-SEM). The authors also applied path comparison analyses to further compare the effects of algorithmic monitoring and fairness on the two types of appraisals.

This study finds that online car-hailing drivers' challenge-hindrance appraisals mediate the relationship between algorithmic management characteristics and work engagement. Algorithmic monitoring positively affects both challenge and hindrance appraisals in online car-hailing drivers. However, algorithmic fairness promotes challenge appraisal and reduces hindrance appraisal. Consequently, challenge and hindrance appraisals lead to higher and lower work engagement, respectively. Further, the additional path comparison analysis showed that the hindering effect of algorithmic monitoring exceeds its challenging effect, and the challenge-promoting effect of algorithmic fairness is greater than the algorithm's hindrance-reducing effect.

This paper reveals the underlying mechanisms concerning how algorithmic monitoring and fairness affect online car-hailing drivers' work engagement and fills the gap in the research on algorithmic management in the context of online car-hailing platforms. The authors' findings also provide practical guidance for online car-hailing platforms on how to improve the platforms' algorithmic management systems.

Social media fatigue (SMF) has been widely recognized; however, previous studies have included various concepts into a single fatigue construct. Fatigue has typically been explored from the stressor-strain-outcome (SSO) or stimulus-organism-response (SOR) perspectives. To further investigate SMF, the authors split it into the two constructs of exhaustion and disinterest. Furthermore, the authors introduced the concept of emotional labor and identified rules that may affect surface and deep acting strategies.

The authors designed and conducted a survey to collect data from social networking platform users.

Results from 364 users of social networking platforms supported most of the authors' hypotheses. First, most of the display rules affect the choice of deep or surface acting. Second, both types of acting lead to exhaustion, but only surface acting leads to disinterest. Third, discontinuance intention is affected by both types of fatigue.

This study contributes to SMF research by adding more antecedents (deep and surface acting) based on the emotional labor perspective and showing the impacts of communication rules on emotional labor. In addition, this study also distinguishes disinterest-style fatigue from exhaustion.

The purpose of this study is to critically reflect on visually impaired customers’ technology assistance needs and the perceptions of existing technologies’ performance in the contexts of hospitality and tourism.

Following a qualitative approach, this study used in-depth semistructured interviews with 19 participants with visual impairments.

Positive and negative sides of technology-assisted experiences in the hotel, restaurant, and travel domains were summarized, and room for improvement was discussed to enhance the quality of life and travel experience of visually impaired customers.

Findings from this study offer actionable implications and future directions to technicians and managers to make hospitality and travel experiences more inclusive.

This timely reflection addresses a critical situation by offering original ideas and calling for more discussion of under-represented groups with visual impairments.

This paper aims to report the results of numerical analysis of turbulent fluid flow and forced-convection heat transfer in solar air channels with baffle-type attachments of various shapes. The effect of reconfiguring baffle geometry on the local and average heat transfer coefficients and pressure drop measurements in the whole domain investigated at constant surface temperature condition along the top and bottom channels’ walls is studied by comparing 15 forms of the baffle, which are simple (flat rectangular), triangular, trapezoidal, cascaded rectangular-triangular, diamond, arc, corrugated, +, S, V, double V (or W), Z, T, G and epsilon (or e)-shaped, with the Reynolds number changing from 12,000 to 32,000.

The baffled channel flow model is controlled by the Reynolds-averaged Navier–Stokes equations, besides the k-epsilon (or k-e) turbulence model and the energy equation. The finite volume method, by means of commercial computational fluid dynamics software FLUENT is used in this research work.

Over the range investigated, the Z-shaped baffle gives a higher thermal enhancement factor than with simple, triangular, trapezoidal, cascaded rectangular-triangular, diamond, arc, corrugated, +, S, V, W, T, G and e-shaped baffles by about 3.569-20.809; 3.696-20.127; 3.916-20.498; 1.834-12.154; 1.758-12.107; 7.272-23.333; 6.509-22.965; 8.917-26.463; 8.257-23.759; 5.513-18.960; 8.331-27.016; 7.520-26.592; 6.452-24.324; and 0.637-17.139 per cent, respectively. Thus, the baffle of Z-geometry is considered as the best modern model of obstacles to significantly improve the dynamic and thermal performance of the turbulent airflow within the solar channel.

This analysis reports an interesting strategy to enhance thermal transfer in solar air channels by use of attachments with various shapes

Food delivery apps (FDAs) have rapidly developed due to mobile technologies, changes in modern consumption and increased online use during the COVID-19 pandemic. Despite this, the platforms are struggling to build a stable customer base and make a profit. This study combined tech-driven motivators in an information system success model (ISSM) and emotional attachment operated by affect transfer theory (ATT) to explain why people might continue to use an FDA.

An online quantitative cross-sectional survey was carried out via the Prolific platform. Data were collected from 416 FDA users and analyzed to test the hypotheses using the partial least squares based structural equation modeling.

The study found that system quality, information quality and emotional attachment directly influence the continued use of FDA. Moreover, the results suggest that perceived social interactivity and perceived playfulness are significant antecedents of emotional attachment.

The findings of this study enrich the current literature on continuance intention in online food delivery services by integrating the technology- and affective-based factors. The findings also provide various practical implications for app designers and marketers to foster an emotional bond with users, resulting in high retention rate.

The study proposes the integrated framework of ISSM and ATT for enhancing understanding of consumer behaviors in the post-adoption stage for FDA.