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PurposeThis study aims to demonstrate the importance of organizational networks in organizational performance is relatively rich; less understood are processes in organizational networking that entrepreneurs and organizations use in making sense of rapidly changing contexts for organizational performance.Design/methodology/approachThis study conducts an exploratory organizational-level narrative analysis into firms' experiences in two major emerging markets (EMs), namely, Russia and India – to identify organizational networking processes in the midst of institutional upheavals. The study is based on in-depth case studies of firms in EMs sourced from interview data from senior management and consolidated with secondary data.FindingsThe authors find that initially firms rely on informal networks (includingblat/svyaziandjaan-pehchaan/jan-pehchan) and later formal (in the form ofbureaucraticfollowed byproprietary) networks to make sense of the changes and uncertainties in turbulent environments. The authors also demonstrate the cyclical nature of strategic sensemaking in the process of developing organizational networks for performance.OriginalityThe study has a number of theoretical and practical contributions. First, it extends the well-established business networking construct to a more inclusive organizational networking construct. Second, it demonstrates that sensemaking is dependent on interorganizational networking from the outset and throughout the growth of an organization in turbulent markets – from informal to formal bureaucratic and proprietary networks. Finally, this study is unique in documenting the entire process of sensemaking from scanning to performance as well as successfully demonstrating the cyclical nature of sensemaking.

Proponents of neoliberalism stipulate the importance of market self-regulation, privatization, unrestricted free trade and reduction in government interference in the functions of markets. Institutional political economy proponents prescribe that economics cannot be divorced from the social and political context since the market itself is an institution, which is to say is politically constructed. Transition economies are economies that undergo structural transformations intended to develop market-based institutions. Out of all transition economies, Russia experienced a stark contrast between the sudden deregulation followed by the more gradual state-led transition to a market economy. This study finds that the shock therapy approach proposed by the neoliberal policy in the beginning of the Russian transition led to severe setbacks in the national innovation system of Russia in the 1990s due to inabilities of the society and organizations to function in a newly liberalized economy without strong institutional frameworks. In 2000s, the new government managed to centralize the power and established strong functional institutions that provided a more clear-cut business environment that supported firms. This resulted in alignment of business strategies from short-term-profit-seeking with a strategic path of trading in the newly liberalized economy towards more long-term investment strategies including vertical integration, modernization and R&D.

AbstractEthical conduct of artificial intelligence (AI) is undoubtedly becoming an ever more pressing issue considering the inevitable integration of these technologies into our lives. The literature so far discussed the responsibility domains of AI; this study asks the question of how to instil ethicality into AI technologies. Through a three‐step review of the AI ethics literature, we find that (i) the literature is weak in identifying solutions in ensuring ethical conduct of AI, (ii) the role of professional conduct is underexplored, and (iii) based on the values extracted from studies about AI ethical breaches, we thus propose a conceptual framework that offers professionalism as a solution in ensuring ethical AI. The framework stipulates fairness, nonmaleficence, responsibility, freedom, and trust as values necessary for developers and operators, as well as transparency, privacy, fairness, trust, solidarity, and sustainability as organizational values to ensure sustainability in ethical development and operation of AI.