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The author investigates and debates around authenticity in relation to the heritage communities of a Chinese intangible cultural heritage (ICH) item ‘Nüshu’. Nüshu is a monosyllabic phonetic system of writing created and used by women in the Jiangyong County, Hunan Province, in Southern China. Drawing on insights from both online and offline ethnographies, this study argues that in the field of ICH, disputes over heritage authenticity are fiercely negotiated by different stakeholders, including powerful state and supra-state actors. However, the emergence of digital platform has become a way for Nüshu participants to perform their identity and competence and lay claim to their own heritage authenticity.

Due to the increasing size and complexity of construction projects, construction engineering and management involves the coordination of many complex and dynamic processes and relies on the analysis of uncertain, imprecise and incomplete information, including subjective and linguistically expressed information. Various modelling and computing techniques have been used by construction researchers and applied to practical construction problems in order to overcome these challenges, including fuzzy hybrid techniques. Fuzzy hybrid techniques combine the human-like reasoning capabilities of fuzzy logic with the capabilities of other techniques, such as optimization, machine learning, multi-criteria decision-making (MCDM) and simulation, to capitalise on their strengths and overcome their limitations. Based on a review of construction literature, this chapter identifies the most common types of fuzzy hybrid techniques applied to construction problems and reviews selected papers in each category of fuzzy hybrid technique to illustrate their capabilities for addressing construction challenges. Finally, this chapter discusses areas for future development of fuzzy hybrid techniques that will increase their capabilities for solving construction-related problems. The contributions of this chapter are threefold: (1) the limitations of some standard techniques for solving construction problems are discussed, as are the ways that fuzzy methods have been hybridized with these techniques in order to address their limitations; (2) a review of existing applications of fuzzy hybrid techniques in construction is provided in order to illustrate the capabilities of these techniques for solving a variety of construction problems and (3) potential improvements in each category of fuzzy hybrid technique in construction are provided, as areas for future research.

The market is a complex organism that has rich implications and essential stipulations. From the property right perspective, the market is a series of property rights, rules, and system arrangements (an aggregation of rights), which are constructed, owned, operated, and managed by the state and from which the government can benefit. The market property right is owned by the government (state). The costs of market property right include tangible (explicit) cost, system cost, human cost, and other cost components. The study on the cost components of market property right is conducive to establishing the principle of matching investment with ownership, matching investment with income, and integrating (unifying) cost with efficiency.

The extant literature provides much-needed support to understand marketing accountability and how marketing actions are related to financial performance (FP). However, we have limited understanding of the relationships between marketing actions and firms' social performance (SP) and environmental performance (EP). Understanding these links is critical to enhancing sustainable FP, SP, and EP. Moreover, the literature provides limited understanding of the measures by which SP and EP may be operationalized, or the data necessary to reach a conclusion. This study bridges these gaps by extensively reviewing the extant literature to offer a set of measures and data sources to operationalize SP and EP, and empirically show their relationships with marketing actions. We find that greenhouse gas (GHG) emission, environmental disclosure score, waste reduction, energy consumption, and recycling are prominent measures of EP, and that social disclosure score, philanthropy or community spending, and diversity of gender and race are prominent measures of SP. The KLD, ASSET4, and Bloomberg are prominent sources of data that can be used to operationalize SP, to which CDP may be added for EP. We also show that marketing actions positively affect EP and SP. This study contributes to the extant literature on SP and EP by identifying measures and data sources and linking marketing actions to both performance types. It contributes to policy development by identifying the importance of EP and SP and how marketing actions can help achieve such performance.

This chapter aimed to find out which factors affected three Estonian case firms’ serial nonlinear internationalization before and during the Covid-19 pandemic. It also studied how these firms responded to the pandemic and what they learned from their previous business experience. It contributed to the literature on serial nonlinear internationalization and to studies on the (potential) impacts of Covid-19 on firms’ local and international activities by showing that these case firms exited and re-entered foreign markets and experienced considerable export fluctuations before 2020, during and after it. Thus, serial nonlinear internationalization should be perceived as something normal, and it can be expected to occur both during stable and unstable times: it does not only characterize economic crises, and it should not be seen as a failure sign. The pandemic affected the case firms’ internationalization considerably – for instance, via demand fluctuations and travel restrictions – but it also created some additional business opportunities: for example, by creating demand for some additional products and by increasing some customer groups’ interest for some existing products. These firms’ (international) business experience acquired before Covid-19 was also useful during the pandemic as they continued with some previous expansion activities. On the other hand, they also tried something new. As a result, all firms’ total turnover increased in 2020, and it might also increase in 2021, despite some problems in the first quarter.

We are interested in modeling the impact of spatial and interindustry dependence on firm-level innovation of Chinese firms The existence of network ties between cities imply that changes taking place in one city could influence innovation by firms in nearby cities (local spatial spillovers), or set in motion a series of spatial diffusion and feedback impacts across multiple cities (global spatial spillovers). We use the term local spatial spillovers to reflect a scenario where only immediately neighboring cities are impacted, whereas the term global spatial spillovers represent a situation where impacts fall on neighboring cities, as well as higher order neighbors (neighbors to the neighboring cities, neighbors to the neighbors of the neighbors, and so on). Global spatial spillovers also involve feedback impacts from neighboring cities, and imply the existence of a wider diffusion of impacts over space (higher order neighbors).

Similarly, the existence of national interindustry input-output ties implies that changes occurring in one industry could influence innovation by firms operating in directly related industries (local interindustry spillovers), or set in motion a series of in interindustry diffusion and feedback impacts across multiple industries (global interindustry spillovers).

Typical linear models of firm-level innovation based on knowledge production functions would rely on city- and industry-specific fixed effects to allow for differences in the level of innovation by firms located in different cities and operating in different industries. This approach however ignores the fact that, spatial dependence between cities and interindustry dependence arising from input-output relationships, may imply interaction, not simply heterogeneity across cities and industries.

We construct a Bayesian hierarchical model that allows for both city- and industry-level interaction (global spillovers) and subsumes other innovation scenarios such as: (1) heterogeneity that implies level differences (fixed effects) and (2) contextual effects that imply local spillovers as special cases.