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1 – 10 of over 3000Hakeem A. Owolabi, Azeez A. Oyedele, Lukumon Oyedele, Hafiz Alaka, Oladimeji Olawale, Oluseyi Aju, Lukman Akanbi and Sikiru Ganiyu
Despite an enormous body of literature on conflict management, intra-group conflicts vis-à-vis team performance, there is currently no study investigating the conflict prevention…
Abstract
Purpose
Despite an enormous body of literature on conflict management, intra-group conflicts vis-à-vis team performance, there is currently no study investigating the conflict prevention approach to handling innovation-induced conflicts that may hinder smooth implementation of big data technology in project teams.
Design/methodology/approach
This study uses constructs from conflict theory, and team power relations to develop an explanatory framework. The study proceeded to formulate theoretical hypotheses from task-conflict, process-conflict, relationship and team power conflict. The hypotheses were tested using Partial Least Square Structural Equation Model (PLS-SEM) to understand key preventive measures that can encourage conflict prevention in project teams when implementing big data technology.
Findings
Results from the structural model validated six out of seven theoretical hypotheses and identified Relationship Conflict Prevention as the most important factor for promoting smooth implementation of Big Data Analytics technology in project teams. This is followed by power-conflict prevention, prevention of task disputes and prevention of Process conflicts respectively. Results also show that relationship and power conflicts interact on the one hand, while task and relationship conflict prevention also interact on the other hand, thus, suggesting the prevention of one of the conflicts could minimise the outbreak of the other.
Research limitations/implications
The study has been conducted within the context of big data adoption in a project-based work environment and the need to prevent innovation-induced conflicts in teams. Similarly, the research participants examined are stakeholders within UK projected-based organisations.
Practical implications
The study urges organisations wishing to embrace big data innovation to evolve a multipronged approach for facilitating smooth implementation through prevention of conflicts among project frontlines. This study urges organisations to anticipate both subtle and overt frictions that can undermine relationships and team dynamics, effective task performance, derail processes and create unhealthy rivalry that undermines cooperation and collaboration in the team.
Social implications
The study also addresses the uncertainty and disruption that big data technology presents to employees in teams and explore conflict prevention measure which can be used to mitigate such in project teams.
Originality/value
The study proposes a Structural Model for establishing conflict prevention strategies in project teams through a multidimensional framework that combines constructs like team power conflict, process, relationship and task conflicts; to encourage Big Data implementation.
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Managers must make numerous strategic decisions in order to initiate and implement a business model innovation (BMI). This paper examines how managers perceive the management team…
Abstract
Purpose
Managers must make numerous strategic decisions in order to initiate and implement a business model innovation (BMI). This paper examines how managers perceive the management team interacts when making BMI decisions. The paper also investigates how group biases and board members’ risk willingness affect this process.
Design/methodology/approach
Empirical data were collected through 26 in-depth interviews with German managing directors from 13 companies in four industries (mobility, manufacturing, healthcare and energy) to explore three research questions: (1) What group effects are prevalent in BMI group decision-making? (2) What are the key characteristics of BMI group decisions? And (3) what are the potential relationships between BMI group decision-making and managers' risk willingness? A thematic analysis based on Gioia's guidelines was conducted to identify themes in the comprehensive dataset.
Findings
First, the results show four typical group biases in BMI group decisions: Groupthink, social influence, hidden profile and group polarization. Findings show that the hidden profile paradigm and groupthink theory are essential in the context of BMI decisions. Second, we developed a BMI decision matrix, including the following key characteristics of BMI group decision-making managerial cohesion, conflict readiness and information- and emotion-based decision behavior. Third, in contrast to previous literature, we found that individual risk aversion can improve the quality of BMI decisions.
Practical implications
This paper provides managers with an opportunity to become aware of group biases that may impede their strategic BMI decisions. Specifically, it points out that managers should consider the key cognitive constraints due to their interactions when making BMI decisions. This work also highlights the importance of risk-averse decision-makers on boards.
Originality/value
This qualitative study contributes to the literature on decision-making by revealing key cognitive group biases in strategic decision-making. This study also enriches the behavioral science research stream of the BMI literature by attributing a critical influence on the quality of BMI decisions to managers' group interactions. In addition, this article provides new perspectives on managers' risk aversion in strategic decision-making.
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Martin Hemmert, Cecile K. Cho and Ji Young Lee
Building on upper echelons theory, the authors advance the literature on the influence of diversity on innovation by studying the link between top management team (TMT) gender…
Abstract
Purpose
Building on upper echelons theory, the authors advance the literature on the influence of diversity on innovation by studying the link between top management team (TMT) gender diversity and innovation performance and the link's boundary conditions.
Design/methodology/approach
The authors analyze survey data from 390 manufacturing establishments in Germany and India through an ordinary least square (OLS) regression analysis.
Findings
TMT gender diversity is positively related to innovation performance. The influence of gender diversity on innovation performance is not strengthened by team level attributes, including cognitive proficiency and openness to external information. In contrast, TMT gender diversity enhances innovation performance more strongly in Germany than in India, indicating the relevance of country-level cultural norms for leveraging gender diversity.
Research limitations/implications
The authors' study is built on data from two countries only, based on TMTs in the manufacturing sector and cross-sectional. Future studies may address these limitations by considering more countries, examining TMTs in the service sector and applying experimental or longitudinal research designs.
Practical implications
Executives should establish gender diverse TMTs to enhance innovation performance and leverage diverse views of male and female managers effectively. Managers located in countries with strongly hierarchical cultural norms should promote egalitarian values at the organizational level to increase the effectiveness of gender diverse TMTs.
Originality/value
This is the first study which examines the moderating effect of country-level cultural norms on the relationship between TMT gender diversity and innovation performance.
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Becky Wai-Ling Packard, Beronda L. Montgomery and Joi-Lynn Mondisa
The purpose of this study was to examine the experiences of multiple campus teams as they engaged in the assessment of their science, technology, engineering and mathematics…
Abstract
Purpose
The purpose of this study was to examine the experiences of multiple campus teams as they engaged in the assessment of their science, technology, engineering and mathematics (STEM) mentoring ecosystems within a peer assessment dialogue exercise.
Design/methodology/approach
This project utilized a qualitative multicase study method involving six campus teams, drawing upon completed inventory and visual mapping artefacts, session observations and debriefing interviews. The campuses included research universities, small colleges and minority-serving institutions (MSIs) across the United States of America. The authors analysed which features of the peer assessment dialogue exercise scaffolded participants' learning about ecosystem synergies and threats.
Findings
The results illustrated the benefit of instructor modelling, intra-team process time and multiple rounds of peer assessment. Participants gained new insights into their own campuses and an increased sense of possibility by dialoguing with peer campuses.
Research limitations/implications
This project involved teams from a small set of institutions, relying on observational and self-reported debriefing data. Future research could centre perspectives of institutional leaders.
Practical implications
The authors recommend dedicating time to the institutional assessment of mentoring ecosystems. Investing in a campus-wide mentoring infrastructure could align with campus equity goals.
Originality/value
In contrast to studies that have focussed solely on programmatic outcomes of mentoring, this study explored strategies to strengthen institutional mentoring ecosystems in higher education, with a focus on peer assessment, dialogue and learning exercises.
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Shameem Shagirbasha, Kumar Madhan and Juman Iqbal
Though there is an increasing corpus of work on contemporary styles of leadership, studies on distributed leadership (DL) are still in the nascent stage. Therefore, the purpose of…
Abstract
Purpose
Though there is an increasing corpus of work on contemporary styles of leadership, studies on distributed leadership (DL) are still in the nascent stage. Therefore, the purpose of this paper is to investigate how DL affects team effectiveness from the neglected perspectives of team cognition, team motivation and team coordination in startup companies using multi-level analysis.
Design/methodology/approach
The authors investigated the study variables through the lens of 42 teams in 18 startup organizations operating in India, representing an equitable distribution of the manufacturing and service sectors. M-plus was used to do statistical analysis on the multi-level model.
Findings
Drawing upon social exchange theory (SET), results indicated that DL had a favorable impact on team effectiveness and team cognitive processes, team motivation and team coordination mediates the association between DL and individual perceptions of team effectiveness.
Originality/value
Various studies have been carried out relating to leadership and how it impacts effectiveness. However, as far as the authors know, previous studies have failed to empirically address how DL drives team effectiveness by uncovering the mediating impact of team cognitive processes, team motivation and team coordination in the Indian startup context.
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Xi Zhang, Tianxue Xu, Xin Wei, Jiaxin Tang and Patricia Ordonez de Pablos
As a kind of knowledge-intensive team coordinated across physical distance, it is necessary to construct a meta-knowledge driven transactive memory system (TMS) for the knowledge…
Abstract
Purpose
As a kind of knowledge-intensive team coordinated across physical distance, it is necessary to construct a meta-knowledge driven transactive memory system (TMS) for the knowledge management of distributed agile team (DAT). This study aims to explore the comprehensive antecedents of TMS establishment in DATs and considers how TMS establishment is affected by herding behavior under the artificial intelligence (AI)-related knowledge work environment that emerges with technology penetration.
Design/methodology/approach
The data derived from 177 students of 52 DATs in a well-known Chinese business school, which were divided into 26 traditional knowledge work groups and 26 AI-related task groups to conduct a random comparative experiment. The ordinary least squares method was used to analyze the conceptual model and ANOVA was used to examine the differences in herding behavior between the control groups (traditional knowledge work DATs) and treatment groups (DATs engaged in AI-related knowledge work).
Findings
The results showed that knowledge diversity, professional knowledge, self-efficacy and social system use had significantly positive effects on the establishment of TMS. Interestingly, the authors also find that herding behavior may promote the process of establishing TMS of the new team, and this effect will be more significant when AI tasks are involved in team knowledge work.
Originality/value
By exploring the comprehensive antecedents of the establishment of TMS, this study provided a theoretical basis for knowledge management of DATs, especially in AI knowledge work teams. From a practical perspective, when the DAT is involved in AI-related knowledge works, managers should appropriately guide the convergence of employees’ behaviors and use the herding effects to accelerate the establishment of TMS, which will improve team knowledge sharing and innovation.
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This study aims to focus on the resource-based faultline of a top management team (TMT) and intends to investigate the impact of TMT resource-based faultline on corporate green…
Abstract
Purpose
This study aims to focus on the resource-based faultline of a top management team (TMT) and intends to investigate the impact of TMT resource-based faultline on corporate green innovation, by indicating the environmental management as a mediator and slack resources as a moderator to understand the relationship.
Design/methodology/approach
Based on the empirical data of Chinese listed manufacturing companies from 2008 to 2020, this study assesses the hypotheses using an OLS model with fixed effects of time and industry.
Findings
The results indicate that TMT resource-based faultline is significantly negatively correlated with corporate green innovation. The conclusion remains valid after endogeneity tests and robustness checks. Mechanism test shows that environmental management plays a mediating role in the association between TMT resource-based faultline and corporate green innovation. Moreover, slack resources diminish the negative association between TMT resource-based faultline and corporate green innovation.
Originality/value
The study not only expands the theoretical understanding of the deeper motivation of TMT faultline on corporate green innovation, but also provides a practical reference for optimizing the human resource allocation of the TMT and accelerating green transformation development.
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Fernando Martín-Alcázar, Marta Ruiz-Martínez and Gonzalo Sánchez-Gardey
This study aims to examine the connection between scholars' research performance and the multidisciplinary nature of their collaborative research. Furthermore, in response to…
Abstract
Purpose
This study aims to examine the connection between scholars' research performance and the multidisciplinary nature of their collaborative research. Furthermore, in response to mixed results regarding the effects of multidisciplinarity on research performance, this study explores how human resource management (HRM) practices may moderate this link.
Design/methodology/approach
The authors built a model based on the theoretical arguments and empirical evidence found in the review of diversity and HRM literature. The authors also performed a quantitative study based on a sample of scholars in the field of management. Different econometric estimations were used to test the proposed model.
Findings
The results of this empirical analysis suggest that multidisciplinary research has a non-linear effect on research performance. Certain HRM practices, such as development and collaboration, moderated the curvilinear relationship between multidisciplinarity and performance, displacing the optimum to allow higher performance at higher levels of multidisciplinary research.
Originality/value
The paper provides advances on previous works studying the curvilinear relationship between multidisciplinarity and the researchers' performance, confirming that multidisciplinarity is beneficial up to a threshold beyond which these benefits are attenuated. In addition, the findings shed light on important issues related to team-oriented HRM practices associated with the outcomes of multidisciplinary research.
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This study's main goal is to expand the theoretical perspective and discuss the unique influence of age and tenure on R&D teams' incremental innovation outcomes. We answer…
Abstract
Purpose
This study's main goal is to expand the theoretical perspective and discuss the unique influence of age and tenure on R&D teams' incremental innovation outcomes. We answer scholars call for additional research on age-related processes by testing pathways through which older employees can benefit organizational performance. The current study advances the literature by relating to the context-related process of cohesion and investigating its moderating influence on the relationship between team antecedents (i.e. age and tenure) and incremental innovation.
Design/methodology/approach
This research sample consists of 108 R&D teams operating in six mature high-tech organizations located in Israel. The participating entities design and manufacture state-of-the-art innovations in the semiconductors, communications and information technology sectors. The number of teams in each participating entity was 35, 21, 21, 19, 7 and 5, respectively. The sample consisted of 443 R&D employees and 212 team leaders/managers. The total sample comprised 655 participants. Team members filled out questionnaires to assess the independent variables. The dependent-variable questionnaire focusing on the team's incremental innovation accomplishments was completed by two managers for each team.
Findings
We found a negative association between team members' age and incremental innovation. Hypothesis 2, which predicted a positive association between team members' tenure and incremental innovation, was marginally supported. The interaction between team members' age and team members' tenure on incremental innovation was marginally supported. Hypothesis 4, which predicted that the negative association between team members' age and incremental innovation would be mitigated when the level of team cohesion is low, was supported. Hypothesis 5, which assumed that the positive association between team members' tenure and incremental innovation would be stronger when the level of cohesion is high, was supported.
Practical implications
This research's results regarding the negative influence of R&D employees' age on incremental innovation are crucial for managers and team leaders in the high-tech industry. Following the age stereotype, many of them avoid recruiting and assigning older employees to R&D teams dealing in innovation creation and development. They should expand their perspective and consider additional attributes in order to assign the employees that best match the team's mission. The results show that R&D teams produce high and similar levels of incremental innovation when the level of team members' tenure is high, regardless of their age.
Originality/value
This study benefited from a relatively high number of respondents and teams from leading high-tech organizations, a high response rate and a research design that made it possible to establish a linkage between data on the independent variables and data on incremental innovation collected from separate independent sources. The data on the dependent variable—incremental innovation—was based on independent assessments made by two managers for each team. The study's measurements were based on leading studies on innovation.
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As the application of artificial intelligence (AI) becomes more prevalent, many high-tech firms have employed AI applications to deal with emerging societal, technological and…
Abstract
Purpose
As the application of artificial intelligence (AI) becomes more prevalent, many high-tech firms have employed AI applications to deal with emerging societal, technological and environmental challenges. Big data analytical capability (BDAC) has become increasingly important in the AI application processes. Drawing upon the resource-based view and the theory of planned behavior, this study aims to investigate how BDAC and collaboration affect new product performance (NPP). Practically, a harmonic working team is particularly important for creating management synergies, this empirical analysis demonstrates the importance of BDAC and collaboration for NPP.
Design/methodology/approach
This paper focuses on the performance of firms that applied AI in their operations. This study collected data from firms in Greater China, including China and Taiwan, as Greater China is currently the leading manufacturer of semiconductor, electronic and electric products for AI applications in the manufacturing process. Confirmatory factor analysis and structural equation modeling is employed for statistical analysis.
Findings
The analytical results indicate that BDAC positively relates to collaboration capability (CC) in AI applications but not to team collaboration (TC). CC positively correlates with TC, and both CC and TC positively correlate with NPP. Further, the mediating effect was examined using the Sobel t-test, which reveals that CC is a significant mediator in the influence of BDAC on NPP.
Practical implications
The strategic implementation of BDAC and collaboration can allow an enterprise to improve its NPP when driven by the external environment to use AI, which further enhances NPP. These processes indicate that AI and BDAC are both crucial for the success of a company’s collaboration and for effective management to improve NPP in the face of global competition.
Originality/value
This study introduces the concept of BDAC to explain the relationship between CC and TC, as they pertain to NPP. This study presented a discussion of the theoretical and practical implications of the research findings and could provide a framework for managing BDAC.
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