The reputational and ethical consequences of deceptive chatbot use.

The use of chatbots is becoming widespread as they offer significant economic opportunities. At the same time, however, customers seem to prefer interacting with human operators when making inquiries and as a result are not as cooperative with chatbots when their use is known. This specific situation creates an incentive for organizations to use chatbots without disclosing this to customers. Will this deceptive practice harm the reputation of the organization, and the employees who work for them? Across four experimental studies, we demonstrate that prospective customers, who interact with an organization using chatbots, perceive the organization to be less ethical if the organization does not disclose the information about the chatbot to their customers (Study 1). Moreover, employees that work for an organization which requires them to facilitate the deceptive use of a chatbot exhibit greater turnover intentions (Study 2) and receive worse job opportunities from recruiters in both a hypothetical experimental setting (Study 3) and from professional job recruiters in the field (Study 4). These results highlight that using chatbots deceptively has far reaching negative effects, which begin with the organization and ultimately impact their customers and the employees that work for them.

No person is an island: Unpacking the work and after-work consequences of interacting with artificial intelligence.

The artificial intelligence (AI) revolution has arrived, as AI systems are increasingly being integrated across organizational functions into the work lives of employees. This coupling of employees and machines fundamentally alters the work-related interactions to which employees are accustomed, as employees find themselves increasingly interacting with, and relying on, AI systems instead of human coworkers. This increased coupling of employees and AI portends a shift toward more of an "asocial system," wherein people may feel socially disconnected at work. Drawing upon the social affiliation model, we develop a model delineating both adaptive and maladaptive consequences of this situation. Specifically, we theorize that the more employees interact with AI in the pursuit of work goals, the more they experience a need for social affiliation (adaptive)-which may contribute to more helping behavior toward coworkers at work-as well as a feeling of loneliness (maladaptive), which then further impair employee well-being after work (i.e., more insomnia and alcohol consumption). In addition, we submit that these effects should be especially pronounced among employees with higher levels of attachment anxiety. Results across four studies (N = 794) with mixed methodologies (i.e., survey study, field experiment, and simulation study; Studies 1-4) with employees from four different regions (i.e., Taiwan, Indonesia, United States, and Malaysia) generally support our hypotheses. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Examining the effects of turnover intentions on organizational citizenship behaviors and deviance behaviors: A psychological contract approach.

Although turnover intentions are considered the most proximal antecedent of organizational exit, there is often temporal separation between thinking about leaving and actual exit. Using field data from 2 diverse samples of working adults, we explore a causal model of the effects of turnover intentions on employee behavior while they remain with the organization, focusing specifically on organizational citizenship behaviors (OCBs) and deviance behaviors (DBs). Utilizing expectancy theory as an explanatory framework, we argue that turnover intentions result in high levels of transactional contract orientation and low levels of relational contract orientation, which in turn lead to a decrease in the incidence of OCBs and an increase in the incidence of DBs. We first used a pilot study to investigate the direction of causality between turnover intentions and psychological contract orientations. Then, in Study 1, we tested our mediated model using a sample of employees from a large drug retailing chain. In Study 2, we expanded our model by arguing that the mediated effects are much stronger when the organization is deemed responsible for potential exit. We then tested our full model using a sample of employees from a large state-owned telecommunications corporation in China. Across both studies, results were generally consistent and supportive of our hypotheses. We discuss the implications of our findings for future theory, research, and practice regarding the management of both the turnover process and discretionary behaviors at work. (PsycINFO Database Record

Building a self-regulatory model of sleep deprivation and deception: the role of caffeine and social influence.

Employees are getting less sleep, which has been shown to deplete self-regulatory resources and increase unethical behavior (Barnes, Schaubroeck, Huth, & Ghumman, 2011; Christian & Ellis, 2011). In this study, we extend the original mediated model by examining the role of 2 moderators in the relationship between sleep deprivation, depletion, and deceptive behavior. First, we derive psychological arguments from the psychopharmacology literature to hypothesize that caffeine moderates the relationship between sleep deprivation and depletion by replenishing self-regulatory resources. Second, we draw from recent research in social psychology to hypothesize that social influence moderates the relationship between depletion and deceptive behavior, such that depleted individuals are less able to resist the negative influence of others. Results of a laboratory study provide support for our expanded model combining mediation and moderation, adding to our understanding of the role of sleep deprivation in the incidence of workplace deception. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

Examining the asymmetrical effects of goal faultlines in groups: a categorization-elaboration approach.

The purpose of this study was to use the categorization-elaboration model (CEM) to examine the asymmetrical effects of goal faultlines in groups, which are present when hypothetical dividing lines are created on the basis of different performance goals, splitting the group into subgroups. On the basis of the CEM, we expected groups with goal faultlines to exhibit higher levels of creative task performance than (a) groups with specific, difficult goals and (b) groups with do-your-best goals. We expected the benefits of goal faultlines to be due to increases in reflective reframing, which occurs when group members build on each other's ideas by shifting to alternate frames. However, we expected groups with goal faultlines to exhibit lower levels of routine task performance than (a) groups with do-your-best goals and (b) groups with specific, difficult goals, due to increased perceptions of loafing. Results from 87 groups generally supported our hypothesized model. Implications are discussed as well as possible limitations and directions for future research.

Surveying for "artifacts": the susceptibility of the OCB-performance evaluation relationship to common rater, item, and measurement context effects.

Despite the increased attention paid to biases attributable to common method variance (CMV) over the past 50 years, researchers have only recently begun to systematically examine the effect of specific sources of CMV in previously published empirical studies. Our study contributes to this research by examining the extent to which common rater, item, and measurement context characteristics bias the relationships between organizational citizenship behaviors and performance evaluations using a mixed-effects analytic technique. Results from 173 correlations reported in 81 empirical studies (N = 31,146) indicate that even after controlling for study-level factors, common rater and anchor point number similarity substantially biased the focal correlations. Indeed, these sources of CMV (a) led to estimates that were between 60% and 96% larger when comparing measures obtained from a common rater, versus different raters; (b) led to 39% larger estimates when a common source rated the scales using the same number, versus a different number, of anchor points; and (c) when taken together with other study-level predictors, accounted for over half of the between-study variance in the focal correlations. We discuss the implications for researchers and practitioners and provide recommendations for future research.