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While Dalton and Radtke (2013) examine the effects of Machiavellianism and an organization's ethical environment within a low moral intensity setting, I examine the effects of Machiavellianism and an organization's ethical environment across both low and high moral intensity settings. Using a sample of 192 MTurk workers (i.e., online labor pool participants from Amazon's Mechanical Turk) and 127 undergraduate accounting students, the results using the full-sample of participants indicate the following: (1) Machiavellianism is negatively associated with whistle-blowing intentions across both low and high moral intensity scenarios; (2) an organization's ethical environment is positively associated with whistle-blowing intentions across both low and high moral intensity scenarios; and (3) in the low moral intensity scenario (but not the high moral intensity scenario), I find an interaction between Machiavellianism and the strength of the ethical environment. Implications for research and practice are discussed.

The purpose of this paper is to investigate how the effectiveness of systems for ensuring cooperation in online transactions is impacted by a positivity bias in the evaluation of the work that is produced. The presence of this bias can reduce the informativeness of the reputation system and negatively impact its ability to ensure quality.

This research combines survey and experimental methods, collecting data from 1,875 Mechanical Turk (MTurk) workers in five studies designed to investigate the informativeness of the MTurk reputation system.

The findings demonstrate the presence of a positivity bias in evaluations of workers on MTurk, which leaves them undifferentiated, except at the extremity of the reputation system and by status markers.

Because MTurk workers self-select tasks, the findings are limited in that they may only be generalizable to those who are interested in research-related work. Further, the tasks used in this research are largely subjective in nature, which may decrease their sensitivity to differences in quality.

For researchers, the results suggest that requiring 99 per cent approval rates (rather than the previously advised 95 per cent) should be used to identify high-quality workers on MTurk.

The research provides insights into the design and use of reputation systems and demonstrates how design decisions can exacerbate the effect of naturally occurring biases in evaluations to reduce the utility of these systems.

The purpose of this paper is to provide an investigation of how different types of gig workers engage in the gig economy. Specifically, the authors distinguish between workers who view gig work as primary income (or not) and those workers who view it as a job (or not).

In total, 1,190 Mechanical Turk (MTurk) workers completed surveys across two studies examining whether types of workers differ based on demographic characteristics, utilization of MTurk, why they participate in the gig economy on MTurk (i.e. push and pull factors) and how this impacts life satisfaction.

Workers relying on MTurk as a primary income had lower incomes and spent more time completing large numbers of work units. This group of workers also reported fewer pull factors (e.g. enjoyment) as a reason for working in the gig economy and had lower levels of self-reported current and predicted future life satisfaction. Individuals who view MTurk as a job were more likely to treat MTurk like a job – engaging in online communities and having a regular work schedule. These workers were more likely to report pull factors (e.g. enjoyment and challenge) and did not differ on life satisfaction.

The current research contributes to our understanding of MTurk, one of the largest online platforms for gig work, as part of the diverse gig economy and highlights potential areas for future research.

Political skill has emerged as a concept of interest within the information systems literature to explain individual performance outcomes. The purpose of this paper is to adapt political skill to technology-mediated contexts. Specifically, the authors seek to understand political skill's role in shaping microtask workers' opportunity recognition when utilizing online communities in microtask work environments.

The authors tested their research model using a survey of 348 Amazon Mechanical Turk (MTurk) workers who participate in microtask-related online communities. MTurk is a large, popular microtasking platform used by thousands of microtask workers daily, with several online communities supporting microtask workers.

Technology-based political skill plays a critical role in shaping the resources microtasking workers rely upon from online communities, including opportunity recognition and knowledge sharing. The ability to develop opportunity recognition positively impacts a microtask worker's ability to leverage online communities for microtask worker performance. Tenure in the community acts as a moderator within the model.

The present study makes several contributions. First, the authors adapt political skill to an online community to account for how microtask workers understand a community's socio-technical environment. Second, the authors demonstrate the antecedent role of political skill for opportunity recognition and knowledge sharing. Third, the authors provide empirical validation of the link between online communities and microtask worker performance.

Academic scholars have leveraged crowd work platforms such as Amazon Mechanical Turk for human subjects research for almost two decades. However, few scholars have reflected or questioned this mode of academic research. This paper aims to examine three fundamental problems of crowd work and elaborates on their lasting effects on impacting the validity and quality of human subjects research on crowd work.

A critical analysis is conducted on the characteristics of crowd work, and three fundamental problems of crowd work since its origin were identified, namely, the position of “Human-as-a-service,” the confusion of terminology and crowd work platforms’ abdication of responsibilities.

This paper explains that the three identified fundamental problems of crowd work render at least two lasting problems in crowd work-based research: first, the negligence of the teleological difference between crowd work and academic research; second, the ontological schism between scholars and institutional review boards (IRBs) in their ethical concerns and practices.

This paper critiques the foundation of crowd work-based research that has become growingly popular, extolled and taken for granted. Such a critique is deficient in literature and may seem a bit peculiar. However, we hold that it is time to take research ethics seriously in crowd work because we need to introspect and question ourselves as scholars: What is our motive or ethical stance in using crowd work for human subjects research? Is it for advancing scientific knowledge, promoting crowd workers’ welfare, or predominantly for benefiting ourselves from the fast, cheap and “good” data via crowd work?

This research examines the relationship between the timeliness in announcing the discovery of a data breach and consumer trust in an e-commerce company, as well as later trust-rebuilding efforts taken by the company to compensate users impacted by the breach.

A survey experiment was used to examine the effect of both trust-reducing events (announced data breaches) and trust-enhancing events (provision of identity theft protection and credit monitoring) on consumer trust. The timeliness of the breach announcement by an e-commerce company was manipulated between two randomly assigned groups of subjects; one group viewed an announcement of the breach immediately upon its discovery, and the other viewed an announcement made two months after the breach was discovered. Consumer trust was measured before the breach, after the breach was announced, and finally, after the announcement of data protection.

The results suggest that companies that delay a data breach announcement are likely to suffer a larger drop in consumer trust than those that immediately disclose the data breach. The results also suggest that trust can be repaired by providing data protection. However, even after providing identity theft protection and credit monitoring, companies that fail to promptly disclose a breach have lower repaired trust than companies that promptly disclose.

This study contributes to the literature on e-commerce trust by examining how a company's forthrightness in reporting a data breach impacts user trust at the time of the disclosure of the data breach and after subsequent efforts to repair trust.

The purpose of this paper is to identify under what circumstances advisor gender and advice justification influence advice taking by managers.

The authors designed a quasirational managerial decision experiment with both analytic and intuitive cues. The design was a 2 × 2 between-subjects factorial, in which gender (male/female) and advice justification (intuitive/analytic) were crossed. The experiment involved two independent samples, taken from Amazon Mechanical Turk workers and Brazilian professionals.

Results suggest that, in general, analytic justification is more valued than intuitive justification. The findings also infer that depending on the advisees’ sample and providing that advice justification is analytic, quasirational scenarios seem to favor male advisors (MTurk sample) or both male and female advisors with “male values” (professional sample), as analysis is traditionally considered a “male value.”

Analytic justification will likely lead to more advice utilization in quasirational managerial situations, as it may act as a safeguard for the accuracy of the offered advice.

The results might signal an ongoing, but slow, process leading to the mitigation of gender stereotypes, considering that the male gender stereotype was active in the MTurk sample, but not in the professional one.

This study contributes to the advice-taking research field by showing the interplay between advisor gender and advice justification in a quasirational managerial decision setting with both analytic and intuitive cues. In advice-taking literature, observations are usually collected from students. However, as this study focused on managerial decisions, the authors collected independent samples from MTurk workers and Brazilian professionals.

This paper aims to develop and psychometrically assess an individual’s perception of their work unit’s psychological sense of community (PSOCw) scale. This new scale is designed to capture the unique characteristics of a contemporary work unit that might include current practices such as hot-desking and workers located in physically separate locations.

This paper develops and then psychometrically accesses a new scale designed to better capture the psychological sense of community in a contemporary work unit.

The managerial implications for the PSOCw scale that is a psychometrically sound measure of work engagement, civility and collegiality in a work unit allow managers to audit a work unit based on these three dimensions and then take corrective actions to enhance the work unit’s sense of community.

The present study adapts previous work on PSOCw to a contemporary work environment where members of a work unit are often in physically separate locations and largely connect virtually.

This paper aims to explore the components of a negative memorable Airbnb experience.

Two studies of North American and British nationals were conducted online using an open-ended survey questionnaire with photo-elicitation via Amazon Mechanical Turk (MTurk). The grounded theory was used to analyse the collected data.

The findings of the current study are destination-specific and generalisation is limited. In addition, this study gathered data using an open-ended survey questionnaire with visual images (photo-elicitation technique) in MTurk. Moreover, the study participants were mainly Westerners.

Airbnb could provide hosts with a service quality checklist to warrant quality assurance across listings. Hosts must be informed, guided and monitored so that service quality standards are fulfilled. In addition, hosts should be incentivised to write an honest and accurate description of their listing.

Airbnb can provide hosts with a service quality checklist to ensure standardisation and quality assurance across listings. Hosts must be informed, guided and monitored so that service quality standards are fulfilled. In addition, hosts might benefit from training or workshops on the role of hosting and service quality management.

This is one of the first studies to explore the components of a negative memorable experience in the context of Airbnb.

负面的难忘体验：北美及英国Airbnb住客视角分析

在本文中, 我们探讨负面难忘的Airbnb体验的组成部分。

两项研究针对北美和英国居民的展开, 并使用亚马逊土耳其机器人（Amazon Mechanical Turk）来通过匿名调查问卷的方式在线进行照片提取。 采用扎根理论对收集到的数据进行了分析。

这项研究确定了负面令人难忘的Airbnb体验的三个最常见的组成部分：肮脏和恶劣的房间条件；恶劣的, 欺骗性的和粗鲁的主人行为；以及糟糕的客户服务。调查结果支持研究表明Airbnb的服务质量是不可预测的。

目前研究的结果是基于特定目的地的, 并且其概括性是有限的。 此外, 这项研究收集数据使用匿名调查问卷的MTurk视觉图像（照片提取技术）。 此外, 研究参与者主要是西方人。

爱彼迎可以为业主提供服务质量清单, 以保证整个列表款项的质量。 房主必须得到通知、指导和监测, 以便满足服务质量标准。 此外, 应该鼓励房主写一个诚实和准确的房源描述。

此研究在探索在Airbnb的背景下负面难忘体验的组成部分中处于领先地位。

爱彼迎, 记忆, 负面的难忘体验, 服务质量, 共享经济

研究论文

Experiencias negativas memorables: Perspectivas de los huéspedes de Airbnb de Norteamérica y Gran Bretaña

En este documento, exploramos los componentes de una experiencia negativa y memorable de las aerobombas.

Se realizaron dos estudios de ciudadanos norteamericanos y británicos en línea utilizando un cuestionario de encuesta abierto con foto-elicitación a través de Amazon Mechanical Turk. Se utilizó la teoría fundamentada para analizar los datos recogidos.

Este estudio identificó los tres componentes más comunes de las experiencias memorables negativas de las Airbnb: condiciones sucias y pobres de la habitación; comportamiento malo, engañoso y grosero del anfitrión; y un pobre servicio al cliente. Los resultados apoyan los estudios que indican que la calidad del servicio de Airbnb es impredecible.

Los hallazgos del estudio actual son específicos para cada destino y la generalización es limitada. Además, este estudio recopiló datos mediante un cuestionario de encuesta abierto con imágenes visuales (técnica de fotoelicitación) en MTurk. Además, los participantes del estudio eran principalmente occidentales.

Airbnb podría proporcionar a los anfitriones una lista de control de calidad del servicio para garantizar la calidad de los listados. Los anfitriones deben ser informados, guiados y monitoreados para que se cumplan los estándares de calidad del servicio. Además, se debería incentivar a los anfitriones para que escriban una descripción honesta y precisa de su listado.

Este es uno de los primeros estudios que explora los componentes de una experiencia negativa y memorable en el contexto de Airbnb.

Calidad de servicio, Memoria, Airbnb, Economía de compartir, Experiencia negativa memorable

Trabajo de investigación