Understanding the Turnover Intention of Crowd Workers of Microtask Crowdsourcing Platform

Microtask crowdsourcing is a relatively new work form enabled by information technologies. For both practitioners and academics, understanding the turnover intention of the users, requesters and crowd workers respectively, of microtask crowdsourcing is very important. However, compared with the relatively large literature on requester, studies focusing on worker crowd workers are limited. Therefore, in this study, we investigate the crowd workers’ intentions to leave the microtask crowdsourcing. The research goal is to analyze the motivations of crowd workers systematically and identify those factors that influenced their turnover intention. Based on perceived value and justice perspectives, a research model is developed. The proposed hypotheses will be tested using data from Amazon Mechanical Turk

Fairness in Algorithmic Management: How Practices Promote Fairness and Redress Unfairness on Digital Labor Platforms

Algorithmic management (AM) is employed on digital labor platforms (DLPs) to efficiently manage interactions between workers and clients. However, AM comes with ethical challenges, such as unfairness. Identifying best practices that counter these challenges promises to deliver actionable solutions. Therefore, we identify AM practices that workers deem particularly fair. We conduct seven online focus groups with a diverse set of platform workers and analyze the data through an organizational justice lens. Our findings reveal that AM practices can promote fairness by providing information, empowering workers, or autonomously executing tasks in their interest. Alternatively, in the case unfairness occurred, AM practices can redress unfairness. These practices include delegating dispute resolution to the involved actors, investigating evidence, and autonomously determining restorative consequences. Our findings have theoretical implications for fairness in algorithms, AM, and organizational justice literature. They might also be adopted in practice to improve workers’ conditions on DLPs

The Effect of Participation in Production Ideation Crowdsourcing on Affective Commitment as a Driver of Customer Loyalty in the United States Lodging Industry

Crowdsourcing and customer loyalty are two salient issues that offer tremendous opportunities and challenges in the U.S. lodging industry. Crowdsourcing has been empirically demonstrated to deliver substantial benefits at a reduced cost while retaining and enhancing the value of loyal customers has been the elusive “Holy Grail” of lodging companies for at least the past four decades. Moreover, the cost of today’s loyalty programs in the lodging industry is high and growing, while the true loyalty they ostensibly engender is dubious. Extant literature on crowdsourcing and customer loyalty suggests that the two constructs share a number of base theories and several psychological and other antecedents. The purpose of this study was to ascertain whether lodging companies might be able to leverage these shared theories and antecedents to reap the benefits generated by crowdsourcing the ideation of new products and services while simultaneously enhancing customer loyalty in the process. After analysis, the results show that shared psychological antecedents of self-esteem, social identity, and perceived knowledge, together with other incentives, significantly and positively affect customers’ willingness to participate in product ideation crowdsourcing, which in turn positively affects affective commitment as a mediating driver of customer loyalty. The analysis further shows that the effect that participation in product crowdsourcing has on affective commitment is moderated by the customers’ employment status, such that being a managerial level employee will amplify the positive effect on affective commitment while being a non-managerial employee will diminish that amplification. The study results contribute to the existing theory and literature related to both crowdsourcing and customer loyalty, while the practical application of these results can have a prodigious impact on the lodging industry. Companies should be able to invite their customers to help them cost-effectively develop better products and services with the reasonable expectation that these participants will become even more loyal to the company. Moreover, this loyalty is psychological in nature, and as such is both lower cost and harder to break. Crowdsourced products have been empirically demonstrated to often not only be superior to those developed in-house but also to command a sales and marketing premium by merely letting consumers know that the product or service had, in fact, been the product of people like them

Workers’ Affective Commitment in The Gig Economy: The Role of IS Quality, Organizational Support, and Fairness

Background: The rapidly growing gig economy brings lots of opportunities and challenges, and one of them is workers’ affective commitment. Because of the gig economy’s nature, gig workers depend on the technology-enabled platform to finish their tasks. We investigate how gig workers’ perception of the platform’s quality, or IS quality, will affect how they perceive organizational support and fairness, which further affects their affective commitment. Method: We surveyed 239 Uber drivers in Indonesia to test our model via snow-balling technique. We used PLS with a second-order formative construct model to validate our hypotheses. Results: The results showed that the two dimensions of IS quality, information quality and system quality, were positively associated with organizational support. Only information quality was positively associated with fairness. Both organizational support and fairness were positively associated with affective commitment. Conclusion: For uber drivers, information quality and system quality of the Uber App serve as drivers of perceived organization support. Information quality also contributes to perceived fairness. Drivers who perceive high organization support and fairness are more likely to be affectively committed to the organization

EFFECTS OF THE DIMENSIONS OF QUALITY OF WORK LIFE ON TURNOVER INTENTION OF MILLENNIAL EMPLOYEES IN THE U.S.

Voluntary employee turnover, or quitting jobs, in the U.S. has been steadily increasing since 2009. This study investigated the relationships among the dimensions of quality of work life (QWL), job satisfaction, organizational commitment, and turnover intention among millennial employees in the U.S. It sought to determine whether statistically significant relationships existed among these variables. The study tested a model of the relationships among the aforementioned constructs using structural equation modeling with the IBM® SPSS® Amos 25.0 (SPSS) software package. Using maximum likelihood estimation (MLE), 339 respondents drawn from Amazon Mechanical Turk (MTurk) were examined. Results showed that job characteristics and compensation and benefits had positive and significant effects on job satisfaction. Additionally, job satisfaction had statistically significant effects on organizational commitment and turnover intention. Neither of the dimensions of QWL had positive and significant relationships with organizational commitment. Finally, neither of the dimensions of QWL had direct and negatively significant relationships with turnover intention. This study contributes to the literature by informing on which dimensions of QWL directly attribute to enhanced job satisfaction and reductions in turnover intention. Such knowledge provides a better understanding of millennial employees and may aid in turnover reductions and costs incurred by organizations that are related to turnover

Assessing the Impacts of Crowdsourcing in Logistics and Supply Chain Operations

Crowdsourcing models, whereby firms start to delegate supply chain operations activities to a mass of actors in the marketplace, have grown drastically in recent years. 85% of the top global brands have reported to use crowdsourcing in the last ten year with top names such as Procter & Gamble, Unilever, and Nestle. These emergent business models, however, have remained unexplored in extant SCM literature. Drawing on various theoretical underpinnings, this dissertation aims to investigate and develop a holistic understanding of the importance and impacts of crowdsourcing in SCM from multiple perspectives. Three individual studies implementing a range of methodological approaches (archival data, netnography, and field and scenario-based experiments) are conducted to examine potential impacts of crowdsourcing in different supply chain processes from the customer’s, the crowdsourcing firm’s, and the supply chain partner’s perspectives. Essay 1 employs a mixed method approach to investigate “how, when, and why” crowdsourced delivery may affect customer satisfaction and behavioral intention in online retailing. Essay 2 uses a field experiment to address how the framing of motivation messages could enhance crowdsourced agents’ participation and performance level in crowdsourced inventory audit tasks. Lastly, Essay 3 explores the impact of crowdsourcing activities by the manufacturers on the relationship dynamics within the manufacturer-consumers-retailer triads

Online Labor Platforms and the Role of Job Security and Compensation (Mis)Fits for Gig Workers

Online labor platforms (OLPs) use algorithms to manage their workers. Prior research has examined how OLP management shapes workers’ attitudes, implicitly assuming that workers have the same preferences. However, research has largely neglected the role of (mis)fits between what workers need and what they receive from OLPs. Therefore, we conducted a survey with 121 Mechanical Turk workers and used polynomial regression analysis of workers’ actual needs and perceived OLP supplies. Our results suggest that higher job security fit decreases perceived exploitation and increases system satisfaction, whereas higher compensation fit decreases perceived exploitation. In addition, we find that job security misfit has decreasing marginal effects on perceived exploitation and increasing marginal effects on system satisfaction. Overall, we contribute to a more nuanced understanding of workers’ reactions to the design of OLPs by shedding light on the interplay between what gig workers need and what they perceive to receive from such platforms

Moderating Effects of Relationship Length and Contact Frequency on Customer Citizenship Behaviors

Studies show that contact frequency and relationship length impact co-creative and in-role behaviors with service providers. However, their influence on extra-role or customer citizenship behaviors (CCBs) remains unexplored. This study delves into the moderating role of relationship length and contact frequency within the CCB model. Utilizing an online survey (n = 665), the study unveils that perceived justice’s impact on affective commitment is not moderated by contact frequency, whereas the impact is stronger in short-term than in longer-term relationships. The perceived support-affective commitment-CCBs relationship is stronger in high contact than in low contact group. Similarly, the relationship is stronger for customers in long-term interaction with service providers. CCBs more strongly influence continuous relationship intention for low contact customers, but there is no difference in the association across the relationship length. This study contributes an original viewpoint by investigating the intervening effects of contact frequency and relationship length in the CCB model

The Effect of Mobile Gamification on Brand Loyalty

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