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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.

Recent research on immersive experiences in online environments for higher education has attributed a fundamental role to two distinct yet connected psychological phenomena: the feelings of being virtually present in the education environment, often simply called presence, and peak episodes of flow. The authors conceptually delimitate these two psychological facets of e-learners’ experiences and examine their interplay. The authors show how flow episodes are elicited by students’ sense of control over the online education environment, their attention being focussed on the learning tasks, and their feelings of being physically placed in the online education setting. Also, the interactivity created by the online education environment evokes an e-learner’s imagery, which in turn triggers presence feelings and episodes of flow. The authors further show that, although presence and flow are triggered by some common antecedents, they differ in the object of the individual’s immersion, and that presence feelings facilitate flow. Moreover, the authors provide practical recommendations for higher education institutions, policy makers and the academic and information and communication technology community involved in e-learning, to make sure e-learner experiences reach their fullest potential.

The study aims at reviewing a synthesis of the impact of culture on the implementation of International Financial Reporting Standards (IFRS) in an attempt to provide directions for future research. From the extensive structured review of literature from 106 articles, 23 related articles were analysed. The SCOPUS database tool was used to search the articles. Over the last three decades (188–2018), a total of 23 articles were published from 18 journals. Four journals contribute to 39% articles including Advances in Accounting (2), Critical Perspectives on Accounting (2), European Research Studies Journal (2), and International Journal of Accounting (3). In total, 22% of the articles had no citations. Most of the articles used Hofstede’s theory of culture and utilised quantitative data analysis. Interestingly, 48% of the articles did not apply any theory. The study calls for future research on comparative and regional and other theories to inform the policymakers on cultural implication on global IFRS implementation.

The study examines organization citizenship behavior (OCB) as a mediating variable between instrumental work values (IWVs) and organizational performance; and group differences between family manager and nonfamily manager for integrated models in family hotels. Data were collected from 189 hotels (n = 921) ranging from budget to three-star family hotels in Ghana using questionnaire administered conveniently. Data were analyzed using structural equation modeling. Work value positively influences OCB and organizational performance of family hotels. OCB mediates the relationship between work values and organizational performance. The study also found significant support for group differences between family and nonfamily firms for IWVs and mediating effect of OCB on the relationship between IWVs and performance.

The increasing accumulation of synthetic plastic waste in oceans and landfills, along with the depletion of non-renewable fossil-based resources, has sparked environmental concerns and prompted the search for environmentally friendly alternatives. Biodegradable plastics derived from lignocellulosic materials are emerging as substitutes for synthetic plastics, offering significant potential to reduce landfill stress and minimise environmental impacts. This study highlights a sustainable and cost-effective solution by utilising agricultural residues and invasive plant materials as carbon substrates for the production of biopolymers, particularly polyhydroxybutyrate (PHB), through microbiological processes. Locally sourced residual materials were preferred to reduce transportation costs and ensure accessibility. The selection of suitable residue streams was based on various criteria, including strength properties, cellulose content, low ash and lignin content, affordability, non-toxicity, biocompatibility, shelf-life, mechanical and physical properties, short maturation period, antibacterial properties and compatibility with global food security. Life cycle assessments confirm that PHB dramatically lowers CO₂ emissions compared to traditional plastics, while the growing use of lignocellulosic biomass in biopolymeric applications offers renewable and readily available resources. Governments worldwide are increasingly inclined to develop comprehensive bioeconomy policies and specialised bioplastics initiatives, driven by customer acceptability and the rising demand for environmentally friendly solutions. The implications of climate change, price volatility in fossil materials, and the imperative to reduce dependence on fossil resources further contribute to the desirability of biopolymers. The study involves fermentation, turbidity measurements, extraction and purification of PHB, and the manufacturing and testing of composite biopolymers using various physical, mechanical and chemical tests.