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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.

A semiparametric stochastic frontier model is proposed for panel data, incorporating several flexible features. First, a constant elasticity of substitution (CES) production frontier is considered without log-transformation to prevent induced non-negligible estimation bias. Second, the model flexibility is improved via semiparameterization, where the technology is an unknown function of a set of environment variables. The technology function accounts for latent heterogeneity across individual units, which can be freely correlated with inputs, environment variables, and/or inefficiency determinants. Furthermore, the technology function incorporates a single-index structure to circumvent the curse of dimensionality. Third, distributional assumptions are eschewed on both stochastic noise and inefficiency for model identification. Instead, only the conditional mean of the inefficiency is assumed, which depends on related determinants with a wide range of choice, via a positive parametric function. As a result, technical efficiency is constructed without relying on an assumed distribution on composite error. The model provides flexible structures on both the production frontier and inefficiency, thereby alleviating the risk of model misspecification in production and efficiency analysis. The estimator involves a series based nonlinear least squares estimation for the unknown parameters and a kernel based local estimation for the technology function. Promising finite-sample performance is demonstrated through simulations, and the model is applied to investigate productive efficiency among OECD countries from 1970–2019.

Growing environmental challenge awareness among consumers is today's business reality that pushes for sustainable product development. Governments, industries, and consumers' attention are significantly moved from traditional products to eco-friendly product development. Green product development is the future for manufacturing businesses' survival in most markets. Green product development is an emerging phenomenon and, unfortunately, lacks theoretical and empirical research regarding effective organizational policies and practices for green product development. This study aims at filling research gaps towards green product development by highlighting green employee aspects influenced by leadership for sustainable business growth. The study hypothesized relations between the green effect of transformational leadership on green product development as an outcome through green behaviour, green climate, and green innovative creativity. Data was collected from small and medium enterprises (SMEs) of Karachi through a self-administered survey questionnaire. Results revealed significant support for hypothesized relations through the partial least square statistical tool. This study contributes theoretical and empirical advancement in past literature wherein leadership style influences employee behaviour that leads to predict product development from an environmental perspective. Study inferences suggest for visionary green leadership style for sustainable business growth. Limitations of this study regarding other variable inclusiveness, sampling, and geography are potential extensions for further scholarly investigation.

Multinational enterprises (MNEs) own and control technological resources and capabilities that make them critical actors in accelerating the transition toward net zero. Even beyond the energy sector, stakeholders are putting increasing pressure on MNEs to reduce the carbon intensity of their operations, that is, to improve their carbon performance. While there is unambiguous evidence that national climate policy is a critical catalyst for long-term carbon performance improvements, there is limited research on how MNEs’ carbon strategies react to climate policies. This chapter reviews the concepts, drivers, and strategies connected to carbon performance in the broader sustainability and management literature to clarify potential complementarities to international business (IB). The authors then highlight how MNEs will face increasing institutional complexity along two dimensions: (1) the structural diversity of institutional environments and (2) institutional dynamism, primarily reflected by public policy. The proposed conceptual framework maps these two dimensions to national and subnational levels, and the authors present two data sources that allow the quantitative analysis of country differences in the diversity and dynamism of national climate policy. The authors conclude that there are ample opportunities for IB researchers to explore MNEs’ strategic reactions to climate policy and to inform policymakers about the consequences of national climate policy in the global economy.

One of the most marginalized communities in India is the Lesbian, Gay, Bisexual and Transgender (LGBT) community which commonly experiences discrimination. Many studies have countered that the LGBT community faces high discrimination in the banking and financing industry. As a result, this study concentrates on this marginalized community and its acceptance and continuation habit regarding mobile wallets. Consequently, this study has considered continuance intentions as a response to confirm the progress of the mobile-wallet industry. Also, this study tried to study the relationship between behavioral intention (BI) and continuous intention (CI) which is seriously lacks in the library of literature. The research operationalized the stimulus–organism–response (SOR) framework for the conceptual model and surveyed 100 self-proclaimed members of the LGBT community in India. The analysis has been done using the partial least structure (PLS). The findings demonstrate that variables like perceived trust (PT) directly influence the BI. On the other hand, variables like perceived ease of use (PEoU), social influence (SI), and satisfaction (S) doesn’t influence BI of the LGBT Community. The main outcome was a favorable association between BI and CI. It will help the stakeholders to understand how important this new market avenue is and how it can be explored. To ensure safe and secure transactions, a group think tank composed of important parties (financial institutions, mobile-wallet providers, the government, security specialists, etc.) should make recommendations. Mobile-wallet providers will attain benefit from this study’s understanding of user categories and ability to tailor their service offers as per the community.

After summarizing what has been learned so far, the purpose of this review is to suggest several promising avenues for future research on work-to-family enrichment (WFE) and family-to-work enrichment (FWE).

This is a literature review. After reviewing the existing research and searching for gaps in the literature, new areas of research will be proposed to fill these gaps.

While much has been learned about the antecedents and consequences of work–family enrichment in both directions, WFE and FWE, much remains to be learned.

Three important outcomes – job performance, organizational citizenship behavior, and counterproductive work behavior – need to be studied regarding WFE and FWE. Although supervisor support has been studied, the field needs to incorporate leadership theories and models to understand this phenomenon. Additional predictors of work outcomes – including emotional intelligence, leadership, emotional labor, social support, gender, and cross-cultural variables – need to be examined. Experience sampling methods and advanced research methodologies should also be used.

Although prior research has demonstrated the important effects of WFE and FWE, the practical effects on organizations in terms of job performance still need to be investigated.

The literature review conclusively demonstrates that WFE and FWE are both related to job satisfaction and family satisfaction.

This is the first review to summarize the existing meta-analytical research in this area and to propose the particular avenues of research advocated in this article.