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This article aims to analyze the strategic work of Polish entrepreneurs in the furniture industry following the political changes in 1989. The authors examined how these entrepreneurs transitioned from local craftsmen or importers into leaders of international manufacturing companies and how their strategizing contributed to the unprecedented growth of the Polish furniture sector.

The authors examined extant data, specifically biographical interviews conducted with 11 prominent leaders in the Polish furniture industry (Hryniewicki, 2015, 2018). They analyzed within a theoretical framework that integrates J.C. Spender’s theory of strategic management with Barry Johnson’s concept of polarity management. Polarity is a way of understanding and managing interdependent, opposing pairs of values or perspectives that give rise to conflict.

The analysis reveals key patterns of strategic challenges at the level of human agency, history and sense-making. The authors identified four key polarities: life and business, knowledge presence and absence, concordance and discordance, and instrumental and non-instrumental sense-making.

The polarity concept illuminates the interplay of agency and determinism in strategic decision-making, offering valuable insights for methodology and a deeper understanding of Poland’s furniture industry.

In this chapter, the authors make the case that preserving and curating knowledge for the future involves more than changing methods and tactics or extending our current applications and technology to support knowledge capital. It means changing the way we think about the future. It means envisioning multiple futures where various elements may be known or unknown – a four-future quadrant. First, the authors explain what it means to think strategically in multiple known and unknown futures. Next, the chapter presents ideas for strategic thinking about future knowledge preservation and curation. Finally, the authors consider using the four futures to develop a flexible and relevant knowledge preservation and curation strategy.

The purpose of this paper is to examine the effects of performance management (PM) practices on in-bound open innovation (OI) and out-bound OI. To do this, the authors examine the organizational effectiveness as well as the non-financial and financial performance of Brazilian startups that have had recent OI relationships with larger companies.

Using data collected from 103 Brazilian startups, the hypotheses were tested via partial least squares–structural equation modeling (PLS-SEM). An additional analysis was performed using fuzzy-set qualitative comparative analysis (fsQCA).

The findings show that PM practices orchestrate in-bound OI and out-bound OI; however, only in-bound OI promotes organizational effectiveness in Brazilian startups. Organizational effectiveness results in good non-financial performance, which in turn improves financial performance. PM practices have an indirect effect on financial performance from the serial mediation of in-bound OI, organizational effectiveness and non-financial performance. Moreover, several combinations of conditions lead to high levels of organizational effectiveness, non-financial performance and financial performance.

This study provides new evidence and insights from an emerging market on the antecedents and consequences of startups' OI adoption.

Knowledge management (KM) is an important topic in the age of big data, and this study adds to the existing body of literature by providing a novel KM perspective on the technological phenomenon of artificial intelligence (AI). This study aims to discover how AI might facilitate knowledge-based business-to-business (B2B) marketing. In this chapter, the authors take a close look at the building blocks of AI and the relationships between them. Future research directions and also the effects of the various market information building components on B2B marketing are discussed. The study’s approach is theoretical; it tries to provide a framework for characterising the phenomenon of AI and its constituent parts. Additionally, this chapter provides a methodical analysis of the three categories of market information crucial to B2B marketing: knowledge of customers, knowledge of users, and knowledge of external markets. This research looks at AI through the lens of the conventional data processing framework, analysing the six pillars upon which AI systems are founded. It also explained how the framework’s components work together to transform data into actionable information. In this chapter, the authors will look at how AI works and how it can benefit B2B knowledge-based marketing. It’s not aimed at AI experts but rather at general marketing managers. In this chapter, the possible effects of AI on B2B marketing are discussed using examples from the real world.

Strategy scholars have theorized that a firm's strategic leaders play an important role in firm dynamic capabilities (DCs). However, little research to date has studied how leaders shape the development of DCs. This inductive theory-building study sheds new light on the multilevel architecture of DCs by uncovering that the three core DCs – sensing, seizing, and reconfiguring – operate through distinct individual, group, and organizational processes. Further, the role of strategic leadership is critical as organizational processes create DCs only when they are purposefully designed by firms' strategic leaders to enable change and opportunity pursuit. Whether strategic leaders design processes for change and opportunity pursuit, in turn, reflects the extent to which they view change as positive and desirable. Our insights about the role of strategic leaders' positive attitude toward change as an important aspect of firm DCs uncover new interconnections between strategic leadership, organizational design, and the micro-foundations of DCs. Collectively our findings about the role of positive attitude toward change, the purposeful design of processes for change, and the varying manifestations of these processes at different levels of analysis reveal the coupling of strategic and organizational processes in enabling strategic dynamism and change.

Online collaboration in today's world is a topic of genuine interest to Internet researchers. The purpose of this paper is to explore the role of group knowledge heterogeneity (GKH) in open collaboration performance using the mediating mechanisms of group cognition (GC) and interaction to understand the determinants of the success of online open collaboration platforms.

Study findings are based on partial least squares structural equation modeling (PLS-SEM), the formal mediation test and moderating effect analysis from Wikipedia's 160 online open collaborative groups.

For online knowledge heterogeneous groups, open collaboration performance is mediated by both GC and collaborative interaction (COL). The mediating role of GC is weak, while the mediating role of COL is strengthened when knowledge complexity (KC) is higher. By dividing group interaction into COL and communicative interaction (COM), the authors also observed that COL is effective for online open collaboration, whereas COM is limited.

These findings suggest that for more heterogeneous large groups, group interaction would explain more variance in performance than GC, offering an in-depth understanding of the relationship between group heterogeneity and open collaboration performance, answering what determines the success of online open collaboration platforms as well as explaining the inconsistency in prior findings. In addition, this study expands the application of Interactive Team Cognition (ITC) theory to the online open collaboration context.