Heterogeneous Teams Research Articles

Unraveling key factors enhancing female entrepreneurial performance in China: a pls-sem and fsqca analysis

This study not only illuminates the complex interplay of factors affecting the entrepreneurial performance of 558 Chinese female entrepreneurs but also significantly contributes to the burgeoning literature on gender dynamics in entrepreneurship. By employing a gender-aware framework and mixed methods, including Partial Least Squares Structural Equation Modeling (PLS-SEM) and Fuzzy Set Qualitative Comparative Analysis (fsQCA), it breaks new ground in understanding the unique challenges and opportunities faced by female entrepreneurs. The identification of digital ability, opportunity development, entrepreneurial team heterogeneity, work-family conflict, and gender stereotypes as pivotal elements offer valuable insights for crafting targeted support strategies and policies to enhance female entrepreneurial performance (FEP). Furthermore, the study’s revelation of two distinct pathways to enhance FEP not only provides practical guidance for aspiring female entrepreneurs but also lays the groundwork for future research to explore the nuanced interactions between these factors.

Educational Heterogeneity in Executive Teams and CEO Power: Evidence from Chinese Listed Companies

This study examines the relationship between the educational heterogeneity of executive teams and CEO power using data from 480 Chinese A-share listed companies from 2008 to 2017. The findings reveal a significant inverted U-shaped relationship between educational heterogeneity in executive teams and CEO power.

How endogeneity problems are addressed in analyzing the relationship between diversity in top management teams and company financial performance—a systematic literature review

AbstractEndogeneity is a primary concern for empirical research that examines the relationship between firm leadership and company performance. This is especially true for demographic heterogeneity in boardrooms and top management teams, where reverse causalities are prevalent. Based on a systematic literature review, we contribute to the current state of empirical literature by highlighting the effects of mitigating endogeneity methodically, showing how studies differ in various types of demographic heterogeneity variables and endogeneity checks, and how all these influence performance outcomes in research. We thus offer a new perspective on the numerous empirical findings already available. Our findings show that most studies acknowledge and check for endogeneity concerns but do so by employing different methodical approaches. We further show that the utilization of various techniques affects the variability in study outcomes regarding relationship directions. Papers employing more sophisticated methods (e.g., System GMM) have a higher share of positive significant findings than our overall sample. Still, the general trend that an overwhelming share of papers finds at least some significant positive relationship between leadership demographic heterogeneity and financial performance holds firm all the techniques employed. We consider research created from 1990 to 2024 for our sample of 163 publications.

Human-Robot Team Performance Compared to Full Robot Autonomy in 16 Real-World Search and Rescue Missions: Adaptation of the DARPA Subterranean Challenge

Human operators in human-robot teams are commonly perceived to be critical for mission success. To explore the direct and perceived impact of operator input on task success and team performance, 16 real-world missions (10 h) were conducted based on the DARPA Subterranean Challenge. Missions involved deploying a heterogeneous team of robots to locate and identify artefacts such as climbing rope, drills and a mannequin representing a human survivor. Two conditions were evaluated: human operators that could control the robot team with state-of-the-art autonomy (Human-Robot Team) compared to autonomous missions without human operator input (Robot-Autonomy). Human interventions included creating waypoints to prioritise high-yield areas, and to navigate through error-prone spaces. Human-Robot Teams were often in directed autonomy mode (70% of mission time), found more items ( \(+\) 10.52%), traversed more distance ( \(+\) 12.71%), covered more unique ground ( \(+\) 10.56%), and longer time between safety-related events (34%). In routine conditions, both condition scores were comparable for artefacts, distance and coverage. Human-Robot Teams were faster at finding the first artefact but slower to respond to information from the robot team. Overall, operators contribute to mission-based outcomes, help to overcome environmental situations that can impede progress, and can assist robots to recover faster from difficult events.

Analyzing knowledge integration in convergence research

A pragmatic concern guides this perspective piece: How might researchers charged with leading convergence research better plan, design, implement, and evaluate the integrative processes and products of their research? We use a self-evaluation approach to assess the integrative processes and products of the first two years of a five-year National Science Foundation Growing Convergence Research project on addressing inland freshwater salinization. To examine the linkages between integration approaches and products, we analyzed the integrative qualities of fifteen research products and the collaborative processes used to generate these products. We found that large, heterogeneous teams with a broad mix of disciplines and professional expertise produced more interdisciplinary research products, but they relied on skilled integration by the leader, more intensive forms of collaboration, and inclusive problem framing. Teams that relied on deliberation by experts and used more consultative or cooperative mechanisms for engagement produced research that was more uni- or multi-disciplinary. We consider the efficacy of the various knowledge integration approaches used in this research and share empirically derived recommendations for designing, implementing, and evaluating convergence research. Our findings and lessons provide researchers at the helm of large-scale convergence and transdisciplinary research projects that address complex socio-environmental problems guidance on: (1) the planning and designing of projects with the explicit goal of knowledge integration; (2) the selection and implementation of appropriate knowledge integration approaches and tools; and (3) how knowledge integration can be conceptualized and evaluated for socio-environmental problems.

Top Management Team Heterogeneity, Top Management Incentives, and ESG Performance: Evidence from Chinese Listed Companies

The challenge of balancing economic and social benefits has emerged as a critical issue for corporate sustainable development. Environmental, social, and governance (ESG) criteria are key considerations for enterprises aiming to enhance both social and economic benefits simultaneously. Based on the upper echelons theory, differences in cognitive foundations and values brought about by top management team heterogeneity can influence corporate decisions. Taking A-share listed companies in China from 2011 to 2022 as samples, we construct a two-way fixed-effects model by firm and year to explore the impact of top management team heterogeneity on corporate ESG performance, and we introduce top management incentives as a moderating variable to further analyze the underlying mechanisms. Our results demonstrate that the gender heterogeneity, functional background heterogeneity, and overseas background heterogeneity of top management teams have significant positive impacts on corporate ESG performance, and monetary compensation incentives and control incentives to top management teams play a positive moderating role, while equity incentives exhibits a negative moderating effect. These findings remain robust across alternative measures of corporate ESG ratings and monetary and control incentives, and through the SYS-GMM model test and instrumental variable approach to address endogeneity. This research contributes to the literature on corporate ESG by validating and extending the understanding of how top management team characteristics affect organizational outcomes, and it provides practical guidance for enhancing corporate ESG practices. The implications of this study suggest that to enhance corporate ESG performance, enterprises should prioritize the promotion of top management team heterogeneity and tailor their incentive mechanisms accordingly.

Building effective student project teams: what has problem-solving styles got to do with it?

PurposeThe purpose of this study was to examine if team composition based on adaption-innovation (A-I) problem-solving styles is related to the teamwork quality and team effectiveness (TE) of student project teams participating in a [state-gifted program (SGP)].Design/methodology/approachA correlational design was conducted with a sample of 72 (SGP) participants, consisting of 15 project teams (n = 15), which formed three groups: (1) the homogeneous adaptive group, which consists of five homogeneous adaptive teams (n = 5); (2) the homogeneous innovative group, which consists of five homogeneous innovative teams (n = 5), and (3) the heterogeneous group (i.e. a mix of innovative and adaptive individuals), which consists of five heterogeneous teams (n = 5).FindingsA one-way ANOVA and post-hoc test revealed that team composition based on problem-solving styles is related to teamwork quality and TE. Regarding TE, both homogeneous groups (i.e. all adaptive or all innovative individuals) were more effective than the heterogeneous group. However, regarding teamwork quality, only the adaptive group had significantly higher teamwork quality than the heterogeneous group.Practical implicationsWe recommend that leadership educators utilize Kirton’s adaption-innovation inventory (KAI) as a tool for building effective student project teams. KAI can be used by leadership educators in two major ways: to assign students to groups (as done in the current study) or for team building, where team members share their KAI scores to better understand their problem-solving preferences.Originality/valueThe findings add to the literature by specifying the type of homogeneous groups (i.e. homogeneous adaptive), which may offer an advantage over heterogeneous groups regarding teamwork quality.

Leveraging social supports to cope with sales complexities and facilitate value-based selling in the cross-functional sales team contexts: JD-R perspective

In today's dynamic industrial market, adoption of a value-based selling (VBS) has emerged as a crucial approach, which forces companies to establish cross-functional sales teams. Yet how sales task and team complexities, as challenging/hindrance job demands, require team social supports, as job resources, to buffer against them in implementing VBS, remains an under-researched topic. Based on job demands-resources (JD-R) model, we investigate how sales task and sales team complexities moderate the link between social supports and VBS. Findings reveal that, as challenge job demands, demand ambiguity and task non-routineness positively moderate the instrumental/emotional support–VBS link and the instrumental support–VBS link, respectively. Whereas, as hindrance job demands, team instability negatively moderates the instrumental/emotional support-VBS link, and role ambiguity negatively moderates the instrumental support-VBS link. Additionally, team heterogeneity positively moderates the instrumental support-VBS link while negatively moderates the emotional support-VBS link. The study considers the roles of social supports (job resources) in shaping team VBS behavior under different sales complexities (job demands), not only contributing to the VBS literature by extending the research context to B2B cross-functional sales teams, also providing a insights on how to implement VBS and enhance performance via social supports in various sales situational complexities.

Educational heterogeneity of the founding team of innovative start-ups: confirmations and denials

This paper focuses on the value drivers of innovative start-ups (ISUs). Few companies can overcome the start-up stage; often, the early performance is insufficient, and the potential contribution of innovation to economic development is very poor. Studies based on a firm-level perspective show mixed results on the factors affecting the growth of ISUs. Most studies emphasize the role of “external” drivers of ISUs growth, while more knowledge is required of “internal” drivers. Consequently, this research focuses on the relationship between the features of the founding teams and the early performance of ISUs. Specifically, it concentrates on education heterogeneity and analyzes whether the heterogeneity of the founding team in terms of educational level (vertical heterogeneity) and field of studies (horizontal heterogeneity) affects the Italian ISUs performance. Growth regression and unconditional quantile regression models confirm the prior literature: the educational level affects the performance and the vertical heterogeneity in the composition of the founding team is relevant for ISUs performance. However, the results also suggest interesting denials: horizontal heterogeneity does not play any role, and no moderating effect of heterogeneity is shown. These findings are strongly attractive for new ventures and policymakers.

Functional heterogeneity in digital entrepreneurial teams and pivoting: the role of digital agility

PurposeThe rapid development of digital technologies drives digital entrepreneurs to pivot, a behavior that allows entrepreneurs to adjust original opportunities and explore new opportunities. This study aims to investigate the effect of the structural characteristics of digital entrepreneurial teams, the functional heterogeneity, on pivoting from the perspective of digital agility. Moreover, this study also examines the moderating effect of knowledge sharing.Design/methodology/approachTwo-phase survey data were sourced from Chinese digital entrepreneurial teams through the entrepreneurial networks of MBA programs of a Chinese business school and entrepreneurial support organizations in China. The sample of 272 teams with 708 entrepreneurs was collected to test the hypotheses.FindingsThe functional heterogeneity of digital entrepreneurial teams, including industry background heterogeneity and occupational experience heterogeneity, positively impacts pivoting by providing heterogeneous knowledge and resources. Moreover, this relationship is mediated by the digital agility of the digital team, and knowledge sharing moderates the relationship between functional heterogeneity and digital agility.Originality/valueWhile existing studies have mainly focused on the external factors, this study empirically investigates the team-level internal factors of digital pivoting in digital entrepreneurial teams, enriching the research perspective of pivoting. Moreover, the current study bridges the literature on digital agility with pivoting, broadening the theoretical mechanism of pivoting and expanding the theoretical boundaries of digital agility.

A Conception of Collaborative Decision Support Systems: Approach and Platform Architecture

The paper describes a general conception of collaborative decision support systems, in which teams providing decision support a) are formed flexibly in accordance with the problem and b) consist of both human experts and intelligent agents implementing AI methods and techniques. An analysis of the key problems of creating collaborative decision support systems based on the collaboration of humans and AI is carried out, the following problems are highlighted: ensuring interoperability (mutual understanding) between heterogeneous team members, reconciling differing positions of participants, ensuring trust between participants, ensuring the effectiveness of joint actions planning and maintaining a balance between predefined workflows and self-organization. Principles for constructing such systems have been formed, offering solutions to the identified problems. In particular, it is proposed to employ an ontology-oriented representation of information about the problem (in the form of multi-aspect ontology), a set of methods for monitoring team activities, reputation scheme, elements of explainable AI, as well as mechanisms of limited self-organization. The proposed concept forms the basis of a software platform for the development of collaborative decision support systems, the main architectural provisions of which are also presented in the paper. The use of the platform is illustrated by an example from the field of rational management of road infrastructure and the creation of a collaborative DSS for the development of measures to reduce road accidents.

The impact of sociality regimes on heterogeneous cooperative-competitive multi-agent reinforcement learning: a study with the predator-prey game

ABSTRACT The performance in multi-agent reinforcement learning (MARL) scenarios has usually been analysed in homogeneous teams with a few choices for the sociality regime (selfish, egalitarian, or altruistic). In this paper we analyse both homogeneous and heterogeneous teams in a variation of sociality regimes in the predator-prey game, using a novel normalisation of the weights so that the sum of all rewards is independent of the sociality regime. We find that the selfish regime is advantageous for both predator and prey teams, and for both homogeneous and heterogeneous teams. In particular, rewards are about 100% higher for the predator team when switching from the egalitarian to selfish regime and more than 400% higher from the altruistic regime. For the prey, the increase is around 40% and 100% respectively. The results are similar for homogeneous and heterogeneous situations. The takeaway message is that any study of homogeneous and heterogeneous cooperative-competitive multi-agent reinforcement learning teams should also take into account the sociality regimes before making conclusions on the preference of any algorithm.

How Member Heterogeneity Affects Organizational Innovation: Team Innovation Integration Model

People are the key to the realization of organizational innovation, but most of the existing studies focus on the effectiveness of leaders to organizational innovation, ignoring the innovation ability of grassroots teams. Based on the perspective of conflict transformation, this paper integrates multi-dimensional conceptual categories such as team heterogeneity, team conflict and organizational innovation, and constructs a team innovation integration model with systematic dynamic characteristics. The establishment of the model not only provides a framework for the research of organizational innovation at the team level in the academic field, but also provides practical application value for the improvement of organizational innovation ability.

Planning for heterogeneous teams of robots with temporal logic, capability, and resource constraints

This paper presents a comprehensive approach for planning for teams of heterogeneous robots with different capabilities and the transportation of resources. We use Capability Temporal Logic (CaTL), a formal language that helps express tasks involving robots with multiple capabilities with spatial, temporal, and logical constraints. We extend CaTL to also capture resource constraints, where resources can be divisible and indivisible, for instance, sand and bricks, respectively. Robots transport resources using various storage types, such as uniform (shared storage among resources) and compartmental (individual storage per resource). Robots’ resource transportation capacity is defined based on resource type and robot class. Robot and resource dynamics and the CaTL mission are jointly encoded in a Mixed Integer Linear Programming (MILP), which maximizes disjoint robot and resource robustness while minimizing spurious movement of both. We propose a multi-robustness approach for Multi-Class Signal Temporal Logic (mcSTL), allowing for generalized quantitative semantics across multiple predicate classes. Thus, we compute availability robustness scores for robots and resources separately. Finally, we conduct multiple experiments demonstrating functionality and time performance by varying resources and storage types.

Exploring the Impact of Influencing Factors on High-Quality Development in the Manufacturing Industry: A Comprehensive Analysis using Citespace Visualization and WSR-DEMATEL

High-quality development of the manufacturing industry is a key path to meet the growing needs of the people for a better life and boost China's economy under the double-cycle development pattern. The study focuses on the influencing factors of the high-quality development level of the manufacturing industry. Firstly, the study utilizes the Citespace visualization analysis tool to outline the research hotspots and development trends in this field, comprehensively understanding the interrelationships among influencing factors and their evolving tendencies. This provides valuable information resources for constructing the final indicator system of influencing factors; Secondly, the study constructed an index system of influencing factors based on the WSR (wuli-shili-renli) system methodology, and at the same time, it used the decision-making experiment and experimentation method (DEMATEL) to explore the interrelationships among the 11 influences and to calculate their centrality and causality; Finally, this study portrayed and comparatively analyzed the degree of importance of each influencing factor, and identifies the key influencing factors. The result shows that: Executive team heterogeneity, human capital structure, government subsidy, digital economy, business environment, and green technology innovation are the key influencing factors for the high-quality development of the manufacturing industry. The study can provide theoretical significance and practical enlightenment for the manufacturing industry to enhance its development level to realize high-quality development.

How to Sustain Healthcare Process Improvement in Heterogenous Teams? Evidence from a Systems Dynamic Model

This research investigates how to sustain process improvement (PI) initiatives in healthcare. Despite the abundant knowledge on PI, we know very little on why and how PI sustains over time. This is particularly true in the context of heterogeneous frontline teams of physicians and nurses with different operational characteristics such as attrition rates, skill sets, training, and goals. Our study builds a model that simulates the mutual, dynamic interaction of these stakeholders with each other and with processes with different characteristics in the presence of endogenous management prioritization. We build confidence in the model by calibrating it to data from PI teams at several family medicine clinics at a large US Midwestern healthcare system. The computational experiments performed using data from these teams yield several important insights for theory and practice. First, we find that process metrics, which are leading metrics related to the day-to-day functioning of the units, and outcome metrics, which are lagging metrics often tied to the unit's bottom line, are both critical for the functioning of the PI teams. Emphasizing one over the other can reduce sustainability while a mixed case in which one group of employees is incentivized to leading and another group to lagging can create a regime that is more effective in many scenarios. Second, we find that management interventions that improve short-term PI gains generally also reduce the likelihood of long-run sustainment. Third, we find that attrition and turnover among the team members affect sustainability of PI initiatives and reducing turnover for one class of employee, which attends lagging metrics, facilitates sustainment while reducing it for the other class, which attends leading metrics, can hinder sustainment. We conclude by discussing these implications to the practice of PI among healthcare teams.

The impact of BIM-based integration management on megaproject performance in China

With the rapid development of the global economy, the investment boom in megaprojects worldwide has been on the rise in the past several decades. As large temporary contract organizations, megaprojects are generally confronted with performance dilemmas. The managerial advantage of building information modeling (BIM) has been recognized as one of the critical factors for the success of megaprojects. In particular, BIM-based integration management (BIM IM) signifies the logical and reasonable coordination and integration of the required processes during the whole life-cycle of projects, which facilitates the implementation and management of megaprojects. However, limited empirical research has explored effective pathways for BIM IM in improving megaproject performance (MP). Thus, this study establishes a novel conceptual framework to explore the impacts of BIM IM on MP through information sharing (IS) and cooperation behavior (CB), as well as considering the moderating effects of top management team (TMT) heterogeneity and task conflict (TC). The empirical data were collected in megaprojects in China using the questionnaire survey, and data from 206 middle-senior managers was analyzed by structural equation modeling partial least-squares method. The research findings reveal the effectiveness of BIM IM in promoting IS and CB in megaprojects for ultimate MP. More specifically, BIM IM has a larger effect on IS than CB, and CB has a more profound impact on MP than IS. Meanwhile, TMT heterogeneity plays a negative moderating effect on the relationship between IS and MP, while TC shows a positive moderating effect on the relationship between CB and MP. The findings of this study provide new perspectives and practical strategies for stakeholders to support the effective use of BIM IM to achieve strategic management in megaprojects worldwide.

The effect of executive team heterogeneity on firms’ total factors of production: Evidence from China

This study examines the three kinds of heterogeneity of the executive team: heterogeneity of its professional background, overseas experience, and financial background. It also explores the mechanism and impact of these three heterogeneities on the enterprise’s total factor productivity using the Shanghai and Shenzhen A-share listed companies in China as the research samples from 2010–2022. Results reveal that (1) the heterogeneity of the executive team’s professional background, overseas experience and financial background of the military increased the total factor productivity of the enterprise; and (2) improving the enterprise’s financial flexibility, internal control quality, and research and development and innovation are effective paths for the rise in the level of the enterprise’s total factor productivity by the aforementioned heterogeneities.

The role of heterogeneity in autonomous perimeter defense problems

When is heterogeneity in the composition of an autonomous robotic team beneficial and when is it detrimental? We investigate and answer this question in the context of a minimally viable model that examines the role of heterogeneous speeds in perimeter defense problems, where defenders share a total allocated speed budget. We consider two distinct problem settings and develop strategies based on dynamic programming and on local interaction rules. We present a theoretical analysis of both approaches and our results are extensively validated using simulations. Interestingly, our results demonstrate that the viability of heterogeneous teams depends on the amount of information available to the defenders. Moreover, our results suggest a universality property: across a wide range of problem parameters the optimal ratio of the speeds of the defenders remains nearly constant.

The Association of Demographic Characteristics and Top Management Team Heterogeneity on Hospital Performance

This study aims to show how the demographic characteristics and heterogeneity of the top management team (TMT) associate with hospital’s performance as measured by the balanced scorecard (BSC). The study employs cross-sectional primary data from hospitals in Central Java Indonesia, collected from 242 hospitals. The result shows that the demographic characteristics including age, female, period of experience serving as TMT, level and specialization of education, were not associated with the hospital’s performance. Likewise, the short period of experience in the organization inside or outside of a hospital’s TMT members was not associated with the hospital’s performance. However, TMT’s heterogeneity showed a positive result towards the hospital’s performance. The academic and practical implications of the findings are discussed.