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Drawing on job demands and resources theory and the challenge-hindrance stressor framework, this study aims to investigate the effect of team knowledge complexity on team information sharing and information searching and examine whether team learning goal orientation mediates these effects.

The authors conducted two studies. Study 1 used a field survey study conducted among 374 employees positioned in 68 new product teams. Study 2 used a three-wave online survey study conducted among 208 leaders to investigate the teams they managed.

The findings of the two studies reveal that team knowledge complexity has a positive direct effect on team information sharing and information searching. Furthermore, team learning goal orientation mediates these two relationships.

The findings indicate that team knowledge complexity is generally beneficial for the team information process. Therefore, instead of fearing an increase in the knowledge complexity of the projects, organizations should dare to present challenge demands to team members to enhance their engagement in information processing. Organizations could also pay attention to team member selection during team composition processes. For example, selecting team members with a high level of learning goal orientation is helpful in facilitating team information processing.

Although previous studies have found that knowledge complexity is beneficial for team output, less is known about how knowledge complexity influences team processes. This study clarifies the relationships between team knowledge complexity, information sharing and information searching and examines team learning goal orientation as a vital mediator.

Knowledge search is considered a broad concept and semi-intentional behavior. The path and boundary conditions through which search strategies affect intra-organizational knowledge creation remain elusive. Drawing on recombinant search theory and knowledge-based view, the authors seek to identify knowledge complexity as an important intermediate variable between knowledge search and innovation performance, such as research and development (R&D) output and R&D output quality. A second goal of this study is to examine the moderating roles of government support and technological turbulence.

The authors employed a longitudinal panel of 609 global pharmaceutical firms and obtained the firms' patent records from 1980 to 2015 for the analysis. The authors used generalized estimating equations (GEE) to evaluate the models and tested the consistency via panel fixed-effects estimations.

The authors' findings show that organizational routine-guided search has a negative effect on knowledge complexity, while routine-changing search exerts a positive impact on knowledge complexity. Governmental support and technological turbulence moderate these relationships. Notably, knowledge complexity has an inverted U-shaped relationship with innovation performance.

The authors' research context, the pharmaceutical industry, may constrain the generalizability of our findings. In addition, potential types of routine-guided and routine-changing search behaviors were not considered.

Despite these limitations, this study offers important implications. First, knowledge complexity transmits the effects of knowledge search on innovation performance. Practitioners should balance routine-guided and routine-changing search processes to build and manage complex knowledge. Second, a moderate level of knowledge complexity is the key to good R&D output and R&D output quality.

The study identifies knowledge complexity as one important intermediate variable between knowledge search behaviors and intra-organizational knowledge creation.

Seekers who visit professional virtual communities (PVCs) are usually motivated by knowledge-seeking, which is a complex cognitive process. How do seekers search for knowledge, and how is their search linked to prior knowledge or PVC situation factors? From the cognitive process and interactional psychology perspectives, this study investigated the three-way interactions between seekers’ expertise, task complexity, and perceptions of PVC features (i.e. knowledge quality and system quality) on knowledge-seeking strategies and resultant outcomes.

A field experiment was conducted with 119 seekers in a PVC using a 2 × 2 factorial design of seekers’ expertise (i.e. expert versus novice) and task complexity (i.e. low versus high).

The study reveals three significant insights: (1) For a high-complexity task, experts adopt an ask-directed searching strategy compared to novices, whereas novices adopt a browsing strategy; (2) For a high-complexity task, experts who perceive a high system quality are more likely than novices to adopt an ask-directed searching strategy; and (3) Task completion time and task quality are associated with the adoption of ask-directed searching strategies, whereas knowledge seekers’ satisfaction is more associated with the adoption of browsing strategy.

We draw on the perspectives of cognitive process and interactional psychology to explore potential two- and three-way interactions of seekers’ expertise, task complexity, and PVC features on the adoption of knowledge-seeking strategies in a PVC context. Our findings provide deep insights into seekers’ behavior in a PVC, given the popularity of the search for knowledge in PVCs.

Scholars have examined, in various ways, the complexity of knowledge in innovation. Recently, research has begun to focus on the role of a continuous process of knowledge recombination in our understanding of a changing structure of knowledge complexity and knowledge accumulation. Furthermore, we also claim that this process may reflect changes in the underlying innovation paradigm, or in other words the arrival of the information age. Yet, little is known about how knowledge complexity is increasing in the broader context of globalization, in which the influence of a rising diversity of locational sources may feature more prominently. We consider how knowledge recombination that relies upon the global spread of innovation activities will affect our theory of the relationship through which earlier contributions to knowledge become inputs to subsequent knowledge building that generates more (or less) complex knowledge artifacts. We propose that knowledge complexity rises when recombined elements are sourced across two dimensions of distance simultaneously, namely when sources which are derived from (i) disparate knowledge fields and (ii) distinct geographic locations are combined. We thereby develop an international business perspective on knowledge complexity through recombination by better appreciating the processes that may be necessary when knowledge is combined along global value chains. We also suggest some implications for changing organizational forms by highlighting the value of connecting previously unconnected geographically distant elements, which suggests a greater potential for more informal and indirectly diffused knowledge-based connections.

This paper aims to evaluate the effect of knowledge overlap, search width and problem complexity on the quality of problem-solving in teams that use the majority rule to aggregate heterogeneous knowledge of the team members.

The paper uses agent-based simulations to model iterative problem-solving by teams. The simulation results are analyzed using linear regressions to show the interactions among the variables in the model.

We find that knowledge overlap, search width and problem complexity interact to jointly impact the optimal solution in the iterative problem-solving process of teams using majority rule decisions. Interestingly, we find that more complex problems require less knowledge overlap. Search width and knowledge overlap act as substitutes, weakening each other’s performance effects.

The results suggest that team performance in iterative problem-solving depends on interactions among knowledge overlap, search width and problem complexity which need to be jointly examined to reflect realistic team dynamics.

The findings suggest that team formation and the choice of a search strategy should be aligned with problem complexity.

This paper contributes to the literature on problem-solving in teams. It is the first attempt to use agent-based simulations to model complex problem-solving in teams. The results have both theoretical and practical significance.

Increasingly, dynamic market environments lead to growing complexity in manufacturing and pose a severe threat for the competitiveness of manufacturing companies. Systematic guidance to manage this complexity, especially in the context of Industry 4.0 and the therewith rising trends such as digitalization and data-driven production optimization, is lacking. To address this deficit a case-based reasoning (CBR) system for providing knowledge about managing complexity in Industry 4.0 is presented.

First, the explicit knowledge representation for managing complexity in IT-based manufacturing is introduced. Second, the CBR process step to retrieve knowledge from an artificially composed case base with in total 70 cases of data-based complexity management in the context of Industry 4.0 is set out. Third, knowledge transfer alongside several maturity levels of information technology capabilities of manufacturing systems for reuse in new problem scenarios is introduced.

The paper comprises the conceptual approach for designing a CBR system to support data-based complexity management in manufacturing systems. Furthermore, the appropriateness of the CBR system to provide applicable knowledge for reducing and managing complexity in corporate practice is shown.

The presented research results are evaluated in the course of an embedded single case study and may therefore lack generalizability. Future research to test and enhance the appropriateness of the developed CBR system will strengthen the research contribution.

The paper provides a novel approach to systematically support knowledge transfer for data-based complexity management by transferring the well-known and established methodology of CBR to the rising application domain of manufacturing systems in the context of Industry 4.0.

This study aims to draw the attention of business process management (BPM) research and practice to the textual data generated in the processes and the potential of meaningful insights extraction. The authors apply standard natural language processing (NLP) approaches to gain valuable knowledge in the form of business process (BP) complexity concept suggested in the study. It is built on the objective, subjective and meta-knowledge extracted from the BP textual data and encompassing semantics, syntax and stylistics. As a result, the authors aim to create awareness about cognitive, attention and reading efforts forming the textual data-based BP complexity. The concept serves as a basis for the development of various decision-support solutions for BP workers.

The starting point is an investigation of the complexity concept in the BPM literature to develop an understanding of the related complexity research and to put the textual data-based BP complexity in its context. Afterward, utilizing the linguistic foundations and the theory of situation awareness (SA), the concept is empirically developed and evaluated in a real-world application case using qualitative interview-based and quantitative data-based methods.

In the practical, real-world application, the authors confirmed that BP textual data could be used to predict BP complexity from the semantic, syntactic and stylistic viewpoints. The authors were able to prove the value of this knowledge about the BP complexity formed based on the (1) professional contextual experience of the BP worker enriched by the awareness of cognitive efforts required for BP execution (objective knowledge), (2) business emotions enriched by attention efforts (subjective knowledge) and (3) quality of the text, i.e. professionalism, expertise and stress level of the text author, enriched by reading efforts (meta-knowledge). In particular, the BP complexity concept has been applied to an industrial example of Information Technology Infrastructure Library (ITIL) change management (CHM) Information Technology (IT) ticket processing. The authors used IT ticket texts from two samples of 28,157 and 4,625 tickets as the basis for the analysis. The authors evaluated the concept with the help of manually labeled tickets and a rule-based approach using historical ticket execution data. Having a recommendation character, the results showed to be useful in creating awareness regarding cognitive, attention and reading efforts for ITIL CHM BP workers coordinating the IT ticket processing.

While aiming to draw attention to those valuable insights inherent in BP textual data, the authors propose an unconventional approach to BP complexity definition through the lens of textual data. Hereby, the authors address the challenges specified by BPM researchers, i.e. focus on semantics in the development of vocabularies and organization- and sector-specific adaptation of standard NLP techniques.

The purpose of this paper is to analyze the role of a specific mechanism for cross-functional integration (CFI) in the relationship between product innovation and firm performance. It takes a contingency perspective, accounting for how these relationships vary depending on the degree of organizational knowledge complexity.

Hypotheses are tested via regression analysis with interaction effects in a sample of 105 wineries from Spain, using both objective and subjective firm performance data.

The results obtained confirm the existence of significant triple interaction effect of CFI, knowledge complexity and product innovation on firm performance. CFI has a negative moderating effect on the relationship between product innovation and performance and this effect varies according to the degree of organizational knowledge complexity.

This paper looks at variables that have been hitherto studied at the project or product level, at the firm level, in an attempt to untangle the relationship between innovation, CFI, knowledge complexity and firm performance. Study’s main limitations lie in the use of a cross-functional design and its focus on a single industry.

Firms dealing with complex organizational knowledge could use this CFI mechanism in the development of new products when their size and resources do not allow the creation of more formal temporal structures, such as cross-functional teams. However, unless the winery has to deal with a high degree of knowledge complexity, involving the oenologist in several functional areas for the purpose of coordination, may detract resources from product innovation effort and lead to a poorer performance.

This study showcases a mechanism of CFI not explored in previous research, but used in practice at many firms, i.e. the cross-pollination of ideas across different functional areas through the participation of the responsible for the product development, and tests its role in the relationship between product innovation and different types of firm performance.

Technological standardization can promote the development of complex products and systems (CoPS) (e.g. large aircraft, high-speed trains). Many studies argue that a superior network position contributes to improving a firm's ability to innovate; however, few studies have considered the aforementioned line of research as falling under the purview of CoPS standardization. This study focuses on CoPS integrators, which hold the most important enterprise roles in CoPS manufacturing and innovation, to analyze whether the two types of superior positions (i.e. the central position and the brokerage position) help the integrator influence the standardization process in a process moderated by technological complexity.

Considering the outstanding market performance of the railway transportation industry in China, the abundance of cooperative activities in this industry, and data availability, we adopt integrators from this industry as samples for the empirical analysis in this study. A negative binomial regression analysis with random effects was conducted to analyze the acquired panel data.

The results show that the central position has an inverted U-shaped effect on the integrator's ability to influence standardization and that the brokerage position has a positive effect. We also find that the underlying mechanism of the two types of network positions impacts the integrator's ability to influence standardization and that it has two modes: knowledge integration in related domains and knowledge integration in nonrelated domains. Moreover, technological complexity attenuates the effect of the central position and strengthens the effect of the brokerage position on the integrator's ability to influence standardization.

This paper contributes to the theoretical research on CoPS manufacturing and innovation and complements knowledge-based theory. The results could prove enlightening for integrators facing complex technological environments, allowing them to establish a reasonable external knowledge search strategy and choose appropriate cooperation partners according to their knowledge domains.

Although scholars have provided sufficient empirical evidence on the effectiveness of organizational rewards in managing knowledge sharing, little attention has been paid to the relationship between organizational rewards and knowledge hiding. Drawing on self-determination theory (SDT), this study aims to investigate the effects of financial and nonfinancial rewards on employees' knowledge-hiding behavior as well as the moderating role of task attributes.

This paper examines the hypotheses by conducting a time-lagged survey from a sample of 186 knowledge workers in Chinese high-tech firms.

The findings of this study reveal that financial rewards are positively associated with knowledge hiding, whereas nonfinancial rewards have a negative effect on knowledge. Moreover, task interdependence significantly moderates the effects of organizational rewards on employees' knowledge-hiding behavior. In addition, the interaction between nonfinancial rewards and task complexity is negatively related to knowledge hiding.

This study is one of the first to investigate the effects of financial rewards and nonfinancial rewards on employees' knowledge-hiding behavior, as well as the moderating roles of task interdependence and task complexity.