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The author develops and extends the asymptotic F- and t-test theory in linear regression models where the regressors could be deterministic trends, unit-root processes, near-unit-root processes, among others. The author considers both the exogenous case where the regressors and the regression error are independent and the endogenous case where they are correlated. In the former case, the author designs a new set of basis functions that are invariant to the parameter estimation uncertainty and uses them to construct a new series long-run variance estimator. The author shows that the F-test version of the Wald statistic and the t-statistic are asymptotically F and t distributed, respectively. In the latter case, the author shows that the asymptotic F and t theory is still possible, but one has to develop it in a pseudo-frequency domain. The F and t approximations are more accurate than the more commonly used chi-squared and normal approximations. The resulting F and t tests are also easy to implement – they can be implemented in exactly the same way as the F and t tests in a classical normal linear regression.

Measurement of diminishing or divergent cross section dispersion in a panel plays an important role in the assessment of convergence or divergence over time in key economic indicators. Econometric methods, known as weak σ-convergence tests, have recently been developed (Kong, Phillips, & Sul, 2019) to evaluate such trends in dispersion in panel data using simple linear trend regressions. To achieve generality in applications, these tests rely on heteroskedastic and autocorrelation consistent (HAC) variance estimates. The present chapter examines the behavior of these convergence tests when heteroskedastic and autocorrelation robust (HAR) variance estimates using fixed-b methods are employed instead of HAC estimates. Asymptotic theory for both HAC and HAR convergence tests is derived and numerical simulations are used to assess performance in null (no convergence) and alternative (convergence) cases. While the use of HAR statistics tends to reduce size distortion, as has been found in earlier analytic and numerical research, use of HAR estimates in nonparametric standardization leads to significant power differences asymptotically, which are reflected in finite sample performance in numerical exercises. The explanation is that weak σ-convergence tests rely on intentionally misspecified linear trend regression formulations of unknown trend decay functions that model convergence behavior rather than regressions with correctly specified trend decay functions. Some new results on the use of HAR inference with trending regressors are derived and an empirical application to assess diminishing variation in US State unemployment rates is included.

New asymptotic approximations are established for the Wald and t statistics in the presence of unknown but strong autocorrelation. The asymptotic theory extends the usual fixed-smoothing asymptotics under weak dependence to allow for near-unit-root and weak-unit-root processes. As the locality parameter that characterizes the neighborhood of the autoregressive root increases from zero to infinity, the new fixed-smoothing asymptotic distribution changes smoothly from the unit-root fixed-smoothing asymptotics to the usual fixed-smoothing asymptotics under weak dependence. Simulations show that the new approximation is more accurate than the usual fixed-smoothing approximation.

With the advance of the Silk Road Initiative proposed by China, it has been a focus of China government to develop strategic emerging industries. The development of strategic emerging industries needs the support of competitive intelligence on many aspects such as strategical planning, policy making, industrial structure adjustment, and technology innovation. However, so far there are few studies toward the competitive intelligence systems for strategic emerging industries. In this article, we focus on a number of issues related to the competitive intelligence for strategic emerging industries in China. First, we conduct a strengths, weaknesses, opportunities, and threats analysis on the situations of strategic emerging industries in China, based on which the necessity of building a competitive intelligence (CI) service system for strategic emerging industries is discussed. Next, the authors present a framework of a CI service system for strategic emerging industries in China. The principles, components, working process, and product forms are deeply described. The CI service system proposed in this article consists of a cooperation network platform, three layered organizations, and three systems, which integrates organizations, information, people, network, and service platforms into an ecosystem to offer competitive intelligence supports for government, industry, and enterprises. Finally, the authors discuss a case study of the proposed CI service system for the new energy automobile industry.

The current era of the fourth industrial revolution has attracted significant research on the use of digital technologies in improving construction project delivery. However, less emphasis has been placed on how these digital tools will influence the management of the construction workforce. To this end, using a review of existing works, this chapter explores the fourth industrial revolution and its associated technologies that can positively impact the management of the construction workforce when implemented. Also, the possible challenges that might truncate the successful deployment of digital technologies for effective workforce management were explored. The chapter submitted that implementing workforce management-specific digital platforms and other digital technologies designed for project delivery can aid effective workforce management within construction organisations. Technologies such as cloud computing, the Internet of Things, big data analytics, robotics and automation, and artificial intelligence, among others, offer significant benefits to the effective workforce management of construction organisations. However, several challenges, such as resistance to change due to fear of job loss, cost of investment in digital tools, organisational structure and culture, must be carefully considered as they might affect the successful use of digital tools and by extension, impact the success of workforce management in the organisations.

Even though following the laws of nature to construct harmonious nature–human interactions has long been one of the most influential philosophies in Chinese history, nature-based solutions (NBS), an innovative concept referring to the sustainable utilization of nature in solving various social and environmental challenges facing contemporary societies, can hardly be found in research papers and practices in Chinese context until very recently. Yet, some NBS features, and also NBS thinking, have already been successfully embedded within many environmental management decisions and practices, which are commonly characterized by (1) prioritization of nature preservation/restoration to economic activities and (2) functionalization of nature as a countermeasure to environmental and/or social issues. This chapter will present a comprehensive overview of the Beijing Afforestation Scheme, an exemplar case of NBS in the Chinese context. Starting from a description of Beijing and this massive afforestation project, it delineates major characteristics of this NBS, signified by (1) a shift from outcome-driven to integrated ecological resilience, (2) a change from recreating tree rows to restoring natural boreal forest, and (3) an evolution from top-down to adaptive and inclusive governance. Lastly, lessons learnt and future challenges are discussed.

Although primarily treated as two distinct research streams, strategic alliances and mergers and acquisitions together occupy much of the strategic management discourse. Alliances, in many cases, end in acquisitions as firms use alliances as intermediate strategic options to eventually acquire a partner. As the discipline of strategy matures and the frequency and the volume of inter-firm cooperation continue to rise, it is imperative to integrate these two research streams for a holistic understanding of the theory of the firm. The purpose of this conceptual piece is threefold. First, we review the extant studies that combine these two governance modes: alliance and acquisitions. Second, drawing on the dominant strategic management theories, we highlight how prior inter-firm alliances inform future acquisitions in terms of (a) pre-combination decisions, (b) post-deal integration processes, (c) alternatives and strategies, and (d) performance outcomes. Finally, in view of the emerging trends and evocative gaps, we offer a conceptual road map to encourage future theoretical development and empirical research.

The objective of this research work is to study the artificial intelligence (AI)-based product benefits and problems of the agritech industry. The research variables were developed from the existing review of literature connecting to AI-based benefits and problems, and 90 samples of primary data from agritech industry managers were gathered using a survey of a well-structured research questionnaire. The statistical package of IBM-SPSS 21 was utilized to analyze the data using the statistical techniques of descriptive and inferential statistical analysis. Results show that better information for faster decision-making has been ranked as the topmost AI benefit. This implies that the executives of agritech units have a concern about the quality of decisions they make and resistance to change from employees and internal culture has been ranked as the topmost AI problem.

Purpose – The purpose of the research was to examine the process of new teacher evaluation policy development in South Korea, in order to gain insight into how a controversial policy could be established in education. Research questions were about the process of the policy development, political actors involved and their influences, and the meaning of teacher evaluation in the newly established teacher evaluation policy.Methodology – The study uses a qualitative and descriptive-analytical process from a hermeneutics perspective that views policy as text to be interpreted. This perspective allows policy to be connected to a larger social context through interpretations of text. The main data sources included policy documents, statements by various organizations, research reports, and public media artifacts produced between 2000 and 2012. For data analysis, constant comparison and content analysis methods were used.Findings – The findings show that the process of developing a teacher evaluation system demonstrated an unsuccessful attempt to apply the Habermasian notion of discursive democracy. Relevant stakeholders were invited to deliberate on the reform, but official meetings ended prematurely without consensus. In the end, the government proceeded without full support of any stakeholders. During the deliberation process, teacher organizations and parent groups demonstrated conflicting perspectives on teacher work and the new evaluation system only partially accommodated both perspectives. The effectiveness of the new evaluation system remains to be researched.Value – The policy development process and the evaluation system shown in this study should inform similar efforts in other contexts.