Happy-productive groups: How positive affect links to performance through social resources

Peñalver, Jonathan; Salanova, Marisa; Martínez, Isabel; Schaufeli, Wilmar B.

doi:10.1080/17439760.2017.1402076

Cited by 64 publications

(68 citation statements)

References 79 publications

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“…On the other hand, unlike the aforementioned authors, it has been considered that the relationship is not direct, but rather mediated by the effect of the variables. Based on Broaden and Build Theory [ 91 , 92 ], team resilience [ 15 ] and group social resources [ 13 ] were considered as an underlying mechanism connecting group positive affect to team performance. Thus, groups that experience positive affect grow with adversity and reinforce their social bonds which allows them to complete both the required tasks and those that are not required formally by the job.…”

Section: Resultsmentioning

confidence: 99%

“…As far as we know, this relationship has commonly been called the happy-productive worker [ 97 ], and it has been analyzed from multiple perspectives and areas [ 98 , 99 ]. Based on happy-productive worker research and group theories, some authors have started a new research about happy-productive group [ 13 , 22 ] with promising results.…”

Section: Discussionmentioning

confidence: 99%

“…[ 11 , 12 ]. Moreover, group positive affect motivates groups to explore fitting behaviors for group performance, such as sharing goals, coordinating the activities, and feeding a positive work climate [ 13 ]. Based on the Broaden-and-Build Theory [ 14 ], which states that positive affect create resourceful environments and promote wellbeing, Salanova and colleagues [ 15 , 16 ] have consistently confirmed that the groups experience wellbeing (i.e., resilience and engagement) due to feeling positive affect.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Group Positive Affect and Beyond: An Integrative Review and Future Research Agenda

Peñalver

Salanova

Martínez

2020

IJERPH

Self Cite

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Group positive affect is defined as homogeneous positive affect among group members that emerges when working together. Considering that previous research has shown a significant relationship between group positive affect and a wide variety of group outcomes (e.g., behaviors, wellbeing, and performance), it is crucial to boost our knowledge about this construct in the work context. The main purpose is to review empirical research, to synthesize the findings and to provide research agenda about group positive affect, in order to better understand this construct. Through the PsycNET and Proquest Central databases, an integrative review was conducted to identify articles about group positive affect published between January 1990 and March 2019. A total of 44 articles were included and analyzed. Finding suggests that scholars have been more interested in understanding the outcomes of group positive affect and how to improve the productivity of groups than in knowing what the antecedents are. A summary conclusion is that group positive affect is related to leadership, job demands, job resources, diversity/similarity, group processes, and contextual factors, all of which influence the development of several outcomes and different types of wellbeing at the individual and group levels. However, with specific combinations of other conditions (e.g., group trust, negative affect, and interaction), high levels of group positive affect could cause harmful results. Conclusions shed light on group positive affect research and practice and might help Human Resources professionals to initiate empirically-based strategies related to recruitment, group design and leadership training.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Group Positive Affect and Beyond: An Integrative Review and Future Research Agenda

Peñalver

Salanova

Martínez

2020

IJERPH

Self Cite

View full text Add to dashboard Cite

show abstract

“…Moreover, Kim & Shin [80] found that cooperative group norms and group positive affect were significant predictors of team creativity, and that this relationship was fully mediated by collective efficacy (i.e., a sense of collective competence shared among team members with respect to responding to specific situational demands and allocating, coordinating, and integrating their resources). Peñalver et al [81] found full-mediation effect of group social resources (i.e., teamwork, coordination, supportive team climate) between group positive affect and in-and extra-role performance.…”

Section: Operationalization Of Collective Satisfactionmentioning

confidence: 99%

Happy-Productive Teams and Work Units: A Systematic Review of the ‘Happy-Productive Worker Thesis’

García-Sastre

Peíró

Montañez-Juan

et al. 2019

IJERPH

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The happy-productive worker thesis (HPWT) assumes that happy employees perform better. Given the relevance of teams and work-units in organizations, our aim is to analyze the state of the art on happy-productive work-units (HPWU) through a systematic review and integrate existing research on different collective well-being constructs and collective performance. Research on HPWU (30 studies, 2001–2018) has developed through different constructs of well-being (hedonic: team satisfaction, group affect; and eudaimonic: team engagement) and diverse operationalizations of performance (self-rated team performance, leader-rated team performance, customers’ satisfaction, and objective indicators), thus creating a disintegrated body of knowledge about HPWU. The theoretical frameworks to explain the HPWU relationship are attitude–behavior models, broaden-and-build theory, and the job-demands-resources model. Research models include a variety of antecedents, mediators, and moderating third variables. Most studies are cross-sectional, all propose a causal happy–productive relationship (not the reverse), and generally find positive significant relationships. Scarce but interesting time-lagged evidence supports a causal chain in which collective well-being leads to team performance (organizational citizenship behavior or team creativity), which then leads to objective work-unit performance. To conclude, we identify common issues and challenges across the studies on HPWU, and set out an agenda for future research.

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“…Additionally, group emotion influences team processes and outcomes [8]. For example, an increase in positive mood will lead to greater cooperativeness and less group conflict [9]. On the other hand, from the perspective of computer vision, consider the mood of a family posing for a group photograph at a wedding party, it is expected that there is an automated system recognizing the mood of the family.…”

Section: Introductionmentioning

confidence: 99%

Analyzing Group-Level Emotion with Global Alignment Kernel based Approach

Huang

Dhall

Goecke

et al. 2022

IEEE Trans. Affective Comput.

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From the perspective of social science, understanding group emotion has become increasingly important for teams to considerably accomplish organizational work. Currently, automatically analyzing the perceived affect of a group of people has been received increasingly interest in affective computing community. The variability in group size makes difficulty for group-level emotion recognition to straightforwardly measure the feature distance of two group-level images. Recent works attempted to resolve the preceding problem by using feature encoding. However, the early works lack of efficiency. To alleviate this problem, this paper aims to design a new method to effectively analyze the group behavior from a group-level image. Motivated by time-series kernel approaches explored in dynamic facial expression classification, this paper mainly concentrates on global alignment kernel and design support vector machine with the combined global alignment kernels (SVM-CGAK) to better recognize group-level emotion. Specifically, we first propose to use global alignment kernel to explicitly measure the distance of two group-level images. For improving the performance of global alignment kernel, we use the global weight sort scheme based on their spatial relation information to sort the faces from group-level image, making an efficient data structure to the global alignment kernel. With this new global alignment kernel, we construct the backbone of SVM-CGAK, namely, support vector machine with global alignment kernel. Furthermore, considering the challenging environment, we construct two global alignment kernels based on Reisz-based Volume Local Binary Pattern and deep convolutional neural network features, respectively. Lastly, to make the robustness of group-level emotion recognition, we propose SVM-CGAK combining both global alignment kernels with multiple kernel learning approach. It can enhance the discriminative ability of each global alignment kernel. Intensive experiments are conducted on three challenging group-level emotion databases. The experimental results demonstrate that the proposed approach achieves promising performance for group-level emotion recognition compared with the recent state-of-the-art methods.

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Happy-productive groups: How positive affect links to performance through social resources

Cited by 64 publications

References 79 publications

Group Positive Affect and Beyond: An Integrative Review and Future Research Agenda

Group Positive Affect and Beyond: An Integrative Review and Future Research Agenda

Happy-Productive Teams and Work Units: A Systematic Review of the ‘Happy-Productive Worker Thesis’

Analyzing Group-Level Emotion with Global Alignment Kernel based Approach

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