Sector-Specific Associations, Trust, and Survival of PPPs: A Behavioral Experiment Based on the Centipede Game

Abstract

Public-private partnerships (PPPs) have become widespread in the delivery of public services. This study explores behavioral mechanisms of building and eroding trust in partnering across sectors at the micro-level of interaction between public and private partners. Combining classic theoretical concepts on the development of interorganizational trust and administrative behavior, this study derives theory suggesting that partners’ sector affiliation may have adverse signaling effects on individuals’ intention to uphold effective partnerships over time, and that this intent may be moderated by sector-specific associations. Tested with a novel and dynamic multi-stage behavioral experiment based on the classic centipede game conducted with German graduate students (N=482; Obs.=4,338), results suggest that sector affiliation functions as a strong but potentially misleading signal for partners’ strategic behavior in PPPs and that sector-specific associations asymmetrically moderate respondents’ will to collaborate. These findings contribute to a more nuanced theoretical understanding of the micro-foundations of strategic behavior particularly at nascent stages of PPPs, calling into question basic assumptions about coordination efficiency in cross-sectoral partnerships.

Implicit Dimensions of Moral Licensing in Citizen-State Interactions

“…Citizens hold negative a priori beliefs about flawed performance and subpar service provision by stereotypically lazy bureaucrats working in essentially inefficient and dysfunctional institutions plagued by red tape (del Pino, Calzada, and Díaz-Pulido 2016; Giauque et al 2012;Pandey and Kingsley 2000;Willems 2020). Bureaucrats partially share this negative sentiment as well, since having to cope with slow-moving and complicated processes, limited resources but rising demands, as well as political and medial bureaucracy bashing, drains their motivational resources so that negative sentiment becomes internalized (Boccio, Weisz, and Lefkowitz 2016;Downe, Cowell, and Morgan 2016;Nabatchi 2018;Veage et al 2014;Weißmüller and Rometsch 2021;Weißmüller and Vogel 2021).…”

“…Research should be conducted with both citizens' and active civil servants' to maximize internal and external measurement validity, and replicating such experimental designs with samples from different countries will allow for a comparison across administrative traditions, following latest best practices and recent calls for research to overcome the replication crisis (van Witteloostuijn 2016). One promising approach to reveal implicit associations, sentiment, and stereotypes is the method of affective sentiment coding as a reliable method of revealing implicit associations and biases toward the public and the private sector as well as civil servants' perception of self (Weißmüller and Rometsch 2021;Weißmüller and Vogel 2021). Based on survey data of study participants' free associations, this mixed-methods approach reliably reveals latent and implicit associative constructs, patterns, and motives based on psychometric sentiment dictionaries (Schnabel and Asendorpf 2013;Võ et al 2009;Weißmüller and Rometsch 2021).…”

Aggressions and associations: How workplace violence affects what public employees think of citizens

“…Across studies that have been conducted on stereotypes in the public sector, perhaps the largest overlap in the terminology is the notion of association (Bertram et al, 2022; Weißmüller & Vogel, 2021; Willems, 2020). Associations are cognitive relations between two items (e.g., objects, traits, and ideas), with the result that being confronted with one item activates a representation of the second (VandenBos, 2015).…”

“…The literature also agrees that such associations do not occur singularly but in a larger network of multiple, simultaneous associations (Greenwald et al, 2002). There is also large agreement that associations are charged with emotional valence ranging from positive to negative (e.g., Vogel & Werkmeister, 2021; Weißmüller & Vogel, 2021).…”

“…Most researchers have fed responses from association tasks into frequency analysis and compiled lists of recurring associations with public sector categories (Bertram et al, 2022; Weißmüller & Vogel, 2021; Willems, 2020). This step is often followed by coding the emotional loading of these associations, either by asking respondents for the (non‐)desirability of attributes (Bertram et al, 2022; Willems, 2020) or by applying computer‐aided sentiment analysis (Weißmüller & Vogel, 2021). Beyond the emotional valence of associations, however, scholarship has not yet explored their overarching structure, such as the patterns in which associations frequently co‐occur (Vogel & Werkmeister, 2021).…”