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This chapter develops a multi-path theory of diversified international expansion that explains how multiple wave-shaped performance curves are created as multinational companies expand into increasingly distant and dissimilar countries. According to this theory, multinational mobile network operators (MNOs) recover from over-diversified expansion by improving their local adaptation strategies by means of reconfiguring the value chain and entering local partnerships, by improving their global replication capabilities or by concentrating expansion to clusters of similar country markets. Three dynamic propositions are developed and exemplified concerning MNOs’ diversified international expansion. Implications for international diversification research finalize the chapter.

This study aims to characterise an intricate, idiosyncratic knowledge-creating mechanism in the modern digital context of cross-cultural business models (CBM). From an integrative socio-cultural and philosophical perspective, the authors suggest a novel concept of polychronic knowledge creation (PKC) and its metaphor to theorise such a complex phenomenon.

This paper is conceptual in nature. It critically reviews the literature characterising the flourishing of information and communication technology (ICT)-driven CBMs and clarifies a research gap. The authors draw a dynamic conceptual framework describing how knowledge is created poly-chronically within CBMs, while also articulating and justifying the occurrence of knowledge icebergs as a manifestation of critical cognitive variances and biases in such contexts.

Building upon existential phenomenology, the authors regard the sea as a parable of the CBM ecosystem and propose the new notion of PKC as a dynamic time-space synthesis and its associated sea-like heuristic metaphor. These elucidate how the intricate interconnectivity of a focal firm with its diverse strategic partners kindles a discursive, multi-path knowledge creation process in ICT-driven CBMs under multiple jurisdictions with manifold cultures.

Implications regarding the role of cross-cultural management in creating new knowledge within CBMs are provided.

The research complements and enriches Nonaka’s (1994) theory and its underlying metaphor “ba” (by incorporating the abstruse yet vital role of culture in the synthesizing process of knowledge creation) to propose the novel ideas of PKC and the sea-like heuristic metaphor in CBMs.

Green technology adoption (GTA) in small and micro enterprises (SMEs) is a complex multi-attribute group decision-making issue. Conflicts of opinions can hamper the achievement of group coherence. The purpose of this paper is to solve the conflict decision-making problem in SMEs.

This paper reconstructs the GTA evaluation index system for SMEs and proposes an intragroup coordination relationship model to mitigate group decision-making conflicts based on the cloud model and social networks (GCS). The numerical characteristics of these GTA indicators are determined using fuzzy theory and cloud model.

It was found that establishing a trust relationship network and a conflict coordination relationship could improve the consistency of group decision-making. The degree of coordination has subtle differences with the trust relationship. Particularly, the coordination relationship has obvious influences on the decision-making results among small groups in SMEs.

The conflict coordination model can significantly improve the consistency of group decision-making in SMEs. At the same time, it discusses the differences between the level of conflict coordination and the trust propagation in the process of group decision-making.

Based on the post-acceptance model of information system continuance (PAMISC), this study investigates the influence of the early-stage users' personal traits (specifically personal innovativeness and technology anxiety) and ex-post instrumentality perceptions (specifically price value, hedonic motivation, compatibility and perceived security) on social diffusion of smart technologies measured by the intention to recommend artificial intelligence-based voice assistant systems (AIVAS) to others.

Survey data from 400 US AIVAS users were collected and analyzed with Statistical Product and Service Solutions (SPSS) 18.0 and the partial least square technique using advanced analysis of composites (ADANCO) 2.1.

AIVAS technology is presently at the early stage of market penetration (about 25% of market penetration in the USA). A survey of AIVAS technology users reveals that personal innovativeness is directly and indirectly (through confirmation and continuance) associated with a stronger intention to recommend the use of the device to others. Confirmation is associated with all four ex-post instrumentality perceptions (hedonic motivation, compatibility, price value and perceived security). Among the four, however, only hedonic motivation and compatibility are significant predictors of satisfaction, which lead to use continuance and, eventually, intention to recommend. Finally, technology anxiety is found to be indirectly (but not directly) associated with a lower intention to recommend.

This is the first study conducted on the early-stage AIVAS users that evaluates the influence of both personal traits and ex-post instrumentality perceptions on users' intention for continuance and recommendation to others.

The purpose of this paper is to study the effect of the 2008 global financial crisis on housing market dynamics in an emerging economy like India using quarterly data (Q4 2008–2009 to Q1 2018–2019). The study explores the extent of linkages between housing prices, monetary policy and financial stability by explaining the nature of the shocks to the housing sector and the degree of impact of those shocks; the possibility of adverse feedback loop which is beyond the natural levels; and the usefulness of explicit and direct role of monetary policy for the housing market stability, which was the loudest demand immediately after the crisis.

The paper follows a three-step methodology: data transformations, a variable selection process “general-to-specific modelling” with the help of OxMetrics 6 Package, and vector autoregressive modelling with the help of EViews 10. F-test was used to describe the short-term relationships between the variables. Impulse response and variance decomposition were used to explain the type of relationship (negative or positive) and the period of the relationships, respectively.

The study finds that the housing sector is sensitive to the monetary policy shocks, whereas the contribution of the housing market shocks to the fluctuations in other market variables is not substantial, though not negligible. As far as the nature of the shocks is concerned, the observed dynamics in the real house prices are diverging from their fundamental levels. The housing market shocks are more or less static; it rules out the chances for a self-reinforcing feedback loop with the existing setup.

The study concludes that the observed dynamics in the real house prices are diverging from their fundamental levels. Given the limitation, the researchers could extend this study by decomposing the part of the risk to the sector contributed by the other drivers, which may be inherent imperfections in housing markets, weak and unreliable wealth effect, and the presence of behavioural biases.

The present study finds countercyclical measures to be more useful for this sector as compared to the forward-looking monetary policy reforms in this sector. The central bank in India should continue to refrain from responding directly to the housing sector fluctuations. Investors can enjoy investing in the housing sector without any fear of the crisis as of now. The effect of speculation is small but not negligible, which enjoins the investors and the policy-makers to remain watchful. Interest rate, money supply and inflation lead (Granger-cause) the housing prices. This information is relevant for spending and investment decisions.

The study feels that banks should avoid using monetary policy to balance the house prices. This will be beneficial both for the economy and the society, as any change in monetary policy to especially curb out surging housing prices may adversely affect the output, and finally, may lead to the deflation. The fear of deflation may cause devastating economic, financial and social effects.

The study contributes to the literature by shedding some new insights about the interrelationship between macroeconomic variables, housing prices and financial stability in the aftermath of the 2008–2009 financial crisis. Such types of studies are absent from emerging markets, particularly from India.

The purpose of this study is to extensively explore the vehicular network paradigm, challenges faced by them and provide a reasonable solution for securing these vulnerable networks. Vehicle-to-everything (V2X) communication has brought the long-anticipated goal of safe, convenient and sustainable transportation closer to reality. The connected vehicle (CV) paradigm is critical to the intelligent transportation systems vision. It imagines a society free of a troublesome transportation system burdened by gridlock, fatal accidents and a polluted environment. The authors cannot overstate the importance of CVs in solving long-standing mobility issues and making travel safer and more convenient. It is high time to explore vehicular networks in detail to suggest solutions to the challenges encountered by these highly dynamic networks.

This paper compiles research on various V2X topics, from a comprehensive overview of V2X networks to their unique characteristics and challenges. In doing so, the authors identify multiple issues encountered by V2X communication networks due to their open communication nature and high mobility, especially from a security perspective. Thus, this paper proposes a trust-based model to secure vehicular networks. The proposed approach uses the communicating nodes’ behavior to establish trustworthy relationships. The proposed model only allows trusted nodes to communicate among themselves while isolating malicious nodes to achieve secure communication.

Despite the benefits offered by V2X networks, they have associated challenges. As the number of CVs on the roads increase, so does the attack surface. Connected cars provide numerous safety-critical applications that, if compromised, can result in fatal consequences. While cryptographic mechanisms effectively prevent external attacks, various studies propose trust-based models to complement cryptographic solutions for dealing with internal attacks. While numerous trust-based models have been proposed, there is room for improvement in malicious node detection and complexity. Optimizing the number of nodes considered in trust calculation can reduce the complexity of state-of-the-art solutions. The theoretical analysis of the proposed model exhibits an improvement in trust calculation, better malicious node detection and fewer computations.

The proposed model is the first to add another dimension to trust calculation by incorporating opinions about recommender nodes. The added dimension improves the trust calculation resulting in better performance in thwarting attacks and enhancing security while also reducing the trust calculation complexity.