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Presents the author′s examination of the way in which, without formal education, he built up a multi‐million pound business employing over 100 staff, and then sold it to take up something which he wished to do, namely, further his education via TEC, NVQs and the MCI level 4 and 5. Further shows that not only successful people can further their educational standards.

This paper examines Aman Ullah’s contributions to robust inference, finite sample econometrics, nonparametrics and semiparametrics, and panel and spatial models. His early works on robust inference and finite sample theory were mostly motivated by his thesis advisor, Professor Anirudh Lal Nagar. They eventually led to his most original rethinking of many statistics and econometrics models that developed into the monograph Finite Sample Econometrics published in 2004. His desire to relax distributional and functional-form assumptions lead him in the direction of nonparametric estimation and he summarized his views in his most influential textbook Nonparametric Econometrics (with Adrian Pagan) published in 1999 that has influenced a whole generation of econometricians. His innovative contributions in the areas of seemingly unrelated regressions, parametric, semiparametric and nonparametric panel data models, and spatial models have also inspired a larger literature on nonparametric and semiparametric estimation and inference and spurred on research in robust estimation and inference in these and related areas.

Due to social enterprises' (SEs) relevance to social value creation, marketing increases its attention to these hybrid organizations. However, there is no consensus on how strategic marketing can improve SE performance. Thus, this paper aims to discuss how commercial, social and societal strategic marketing approaches relate to compensatory and transformative social entrepreneurship scopes to improve SE performance.

This paper is conceptual. We hold discussions and raise reflections to advance knowledge on both marketing and social entrepreneurship fields, more precisely by intertwining them.

We develop a conceptual model for adapting three strategic marketing approaches to compensatory and transformative SEs. We argue that SEs have three types of performances: commercial, social and societal. Social and commercial strategic marketing are essential for SEs acting in compensating local failures of capitalism. Societal and commercial strategic marketing are essential for SEs focused on transformative actions to changing global system. Such relations can leverage social impact, which we conceptualize as compensatory or transformative.

The model contributes to improvements on strategic marketing decisions by marketers and entrepreneurs in social entrepreneurship.

We propose a decomposition of strategic marketing into three approaches: commercial, social and societal, which constitutes a novelty to the field. This can facilitate management of SEs with different actions and performances, whether at local or international levels.

This study aims to analyze the convergence of environmental degradation clubs in the Association of Southeast Asian Nations (ASEAN). In addition, this study also analyzes the influence of renewable energy and foreign direct investment (FDI) on each club as an intervention to change the convergence pattern in each club.

This study analyzes the club convergence of environmental degradation in an effort to find out the distribution of environmental degradation reduction policies. This study uses club convergence with the Phillips and Sul (PS) convergence methodology because it considers multiple steady-states and is robust. This study uses annual panel data from 1998 to 2020 and ASEAN country units with ecological footprints as proxies for environmental degradation. After obtaining the club results, the analysis continued by analyzing the impact of renewable energy and FDI on each club using panel data regression and the Stochastic Impacts by Regression on Population, Affluence and Technology model specification.

Based on club convergence, ASEAN countries can be grouped into three clubs with two divergent countries. Club 1 has an increasing pattern of environmental degradation, while Club 2 and Club 3 show no increase. Club 1 can primarily apply renewable energy to reduce environmental degradation, while Club 2 requires more FDI. The authors expect policymakers to take into account the clubs established to formulate collaborative policies among countries. The result that FDI reduces environmental degradation in this study is in line with the pollution halo hypothesis. This study also found that population has a significant effect on environmental degradation, so policies to regulate population need to be considered. On the other hand, increasing income has no effect on reducing environmental degradation. Therefore, the use of renewable energy and FDI toward green investment is expected to intensify within ASEAN countries to reduce environmental degradation.

This research is by far the first to apply PS Club convergence to environmental degradation in ASEAN. In addition, this study is also the first to analyze the influence of renewable energy and FDI on each club formed, considering the need for renewable energy use that has not been maximized in ASEAN.

This paper aims to offer empirical insights on how investing in e-commerce capabilities affects the relationship between loyalty programs and hotel operating performance so as to aid in identifying proper resource allocation strategies.

This study extended the model in Hua et al. (2015) by testing the interaction of e-commerce and loyalty programs.

The findings illustrate that proper allocation of company financial resources to e-commerce initiatives can help improve the impact of loyalty programs on hotel operating performance.

The results of this study illustrate that hotel performance can be improved by the synergy between loyalty program and e-commerce initiatives. Thus, hotel managers and owners can use results from this study to improve the efficiency of their asset allocation strategies, with five practical implications offered.

Theoretically, this study adapted and extended an integrative model of hotel operating performance (Hua et al., 2015) by identifying critical factors that elucidate the variance in firm performance. In addition, the moderating role of e-commerce provides a new conceptualization of information technology. Practically, this study makes several important contributions as well.

Emerging Economies (EEs) are characterized by sustained growth performance, but they suffer from inequality as well, especially the Gender Inequality. Literature points out a number of gender norms which play a significant role in aggravating the gender disparity. The chapter chooses a panel of 25 EEs for the period of 2007–2020 to investigate how gender norms can affect the female labor force participation (FLFP) and development relationship. Results suggest that EEs are in a stage of development where even if countries are growing at a reasonable rate, FLFP is falling. Further investigation reveals that skewed sex ratio can dampen the impact of development, whereas secondary school enrollment and legislation to protect women from sexual harassment in the workplace may foster the effect of development. Thus, policies to encourage parents to invest more on the girl child and providing legal support to women at the workplace can be effective policies to reduce gender inequality.

In the process of industrial growth, when existing industries go for technology upgradation and new modernised industries emerge, both capital intensity and energy demand of overall industry tend to rise steadily. This poses a serious challenge for sustainable development objectives. Towards this end, enhancing energy efficiency of individual industries is the only remedy. Against this backdrop, the study aims to probe the trends in capital intensities and energy efficiencies of individual industries in India.

This study uses panel data regression analysis on data of two-digit industries from 1980/1981–2016/2017. The statistical analysis includes relevant macroeconomic variables derived from the literature to ascertain the drivers of energy efficiency in industries.

The results brought out that capital deepening due to technology upgradation and modernisation and capital productivity growth are the decisive determinants of energy efficiency growth. Furthermore, the ever-increasing fuel price motivated industries to conserve energy on a steady basis, supplemented by energy conservation-specific policy interventions.

This study recommends policy initiatives to ascertain and address technology gaps industry-wise, so that its subsequent efficient capital utilisation, and energy conservation measures of industries would result in energy efficiency growth in industry. The policy must focus on energy-efficient capital intensification in fabricated metals, leather, textile and wood industries that are found less-energy-efficient despite being less-capital-intensive.

This study empirically explores the capital efficiency of industries by investigating the interaction between capital intensity and energy efficiency at a two-digit industry level. It explores the determinants of energy efficiency and proposes industry-specific policies for energy-efficiency-enhancement of the overall industry.

The authors propose to estimate a varying coefficient panel data model with different smoothing variables and fixed effects using a two-step approach. The pilot step estimates the varying coefficients by a series method. We then use the pilot estimates to perform a one-step backfitting through local linear kernel smoothing, which is shown to be oracle efficient in the sense of being asymptotically equivalent to the estimate knowing the other components of the varying coefficients. In both steps, the authors remove the fixed effects through properly constructed weights. The authors obtain the asymptotic properties of both the pilot and efficient estimators. The Monte Carlo simulations show that the proposed estimator performs well. The authors illustrate their applicability by estimating a varying coefficient production frontier using a panel data, without assuming distributions of the efficiency and error terms.