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Culture and institutions are among the essential sources of comparative advantage in international trade and may influence a country's FDI influx. This paper aims to analyze the impact of cultural distance (CD) and institutional distance (ID) on the efficiency of China's outward foreign direct investment (OFDI) for the panel of 43 countries during 2003–2016.

The stochastic frontier approach (SFA) has been incorporated into the standard gravity model of gravity Kalirajan, 1999; Ravishankar and Stack, 2014). SFA has traditionally been implemented to evaluate the production frontier as the highest yield that could possibly be generated from specified input levels. The production process is viewed to be fully efficient if the real output is performed at frontier level. Otherwise, the production process is assumed technically inefficient, which implies potential scope for enhanced output. This error term is split into two parts, a non-negative term and more standard asymmetrical term. The former identifies inefficiencies in production, while the latter retrieves random disorders

The outcomes assert a U-shaped relationship between CD and the efficiency of China's OFDI. Put differently, when the CD is minimal, the “liability of foreignness” (LOF) effect plays a dominant role; and CD tends to reduce the efficiency of China's OFDI. On the flip side, when the culture distance is greater than a certain threshold level, the “advantages of foreignness” (AOF) effect plays a predominant role, and CD improves the efficiency of China's OFDI. Institutional distance results in the “LOF” effect significantly reduce the efficiency of China's OFDI.

Notwithstanding these contributions, our study has some limitations which offer directions for future research. The major limitation of this research work is the availability of comprehensive data for a well extended time, in particular for the variable of CD. Further, a firm-level study can shed light on the motivations and performance of China OFDI. Finally, given that our analysis focuses on emerging market multinational enterprises (EMNEs) from China, the findings might not be explicitly generalizable to MNEs from other developing countries. Future studies should concentrate on the comparative study of China's OFDI with other developing countries, to deepen our understanding of the effects of ID and CD on the efficiency of OFDI.

(1) The work is novel in nature as the authors attempt to explore the effect of ID and CD on efficiency of Chinese FDI. To the best of the authors’ knowledge, no research is conducted in this direction in terms of Chinese FDI. (2) Further, the prior studies employed standard gravity model, which may not correctly evaluate the trade potential viewed as the highest potential value. To overcome the shortcomings of the standard gravity model in estimation of the trade performance and efficiency, the SFA has been incorporated into the standard gravity model of gravity.

This study aims to empirically examine the impact of internal corporate governance mechanisms (ICGM) related to the size of the board, board composition, CEO duality and audit committee independence as a single metric on a firm’s investment decisions.

This study attempts to develop an internal corporate governance quality index comprising 10 items under four main ICGMs – size and independence of the board, CEO duality and audit committee independence – employing panel data analysis to investigate its impact on the investment decisions in 301 nonfinancial firms listed in six emerging capital markets in the Gulf Cooperation Council (GCC) member countries for the years 2015–2020. Data were extracted from sample companies' websites, stock markets, annual reports and Refinitiv database.

This study provides convincing evidence that effective ICGMs minimize inefficient investment and ultimately boost investment efficiency. The findings remain consistent even after considering the potential endogeneity bias.

This study provides empirical evidence on investment efficiency in the GCC region and emphasizes the importance of high-quality ICGMs in reducing inefficient investment. By examining the impact of ICGMs on investment inefficiencies, this study contributes to the corporate governance literature. The GCC region's unique economic and social contexts, with its growing economies, are considered to shed light on this issue.

The current research investigates how the adoption of Artificial Intelligence (AI)—a set of technologies designed to enhance decision-making and automate processes—impacts Integrated Financial Reporting (IFR) in Gulf Cooperation Council (GCC) listed firms, which present the typical features of emerging economies. It is postulated that their IFR is enhanced as firms within these markets experience AI adoption. In addition, the study also focuses on the role of audit quality towards AI adoption and the IFR relationship within these regions. To this effect, the study examines the moderation effect of audit quality (using its sub-components i.e. audit fee, audit industry specialization and restatement) on the relationship between AI adoption experience and IFR in GCC.

The investigation draws upon panel data consisting of 2,912 non-financial firm-year observations covering the period from 2010 to 2023 across GCC markets. To achieve its purpose, the study applies the conventional ordinary least square (OLS) to estimate the effect of AI adoption experience on IFR. Subsequently, to guarantee the robustness of the results, this study utilizes the propensity score matching (PSM) technique.

The results from empirical analysis disclose a direct impact of AI adoption on the IFR of the firms within GCC markets. Furthermore, the study also discovers that the high level of audit quality moderates this positive relationship. Therefore, in the GCC regions, firms with higher AI adoption show higher IFR effectiveness, mainly in the presence of specialized auditors and increased audit fees, whereas their relationship is stronger in the absence of restatements. The results are robust when tested through the PSM technique.

The results of this study highlight the significance for policymakers to ensure comprehensive AI adoption in GCC markets, as well as the appointment of industry specialists and the standardization of audit fees to support the improvement of IFR in the regions.

The objective of this paper is threefold. First, it aims to empirically study whether firm-specific/idiosyncratic uncertainty, macroeconomic/aggregate uncertainty and political uncertainty have an adverse influence on firms' investment decisions in Pakistan. After establishing this, it scrutinizes whether the uncertainty effects on investment are different for firms of different sizes. Finally, it investigates whether any heterogeneity exists in the uncertainty impacts across different industries.

The empirical analysis is based on an unbalanced panel data of 468 nonfinancial firms listed at the Pakistan Stock Exchange (PSX) during the period 2000–2018. Departing from the literature, the paper builds a time-varying composite volatility/uncertainty index based on the principal component analysis (PCA) by utilizing the constructed volatility series for sales, cash flows and return on assets to gauge firm-specific uncertainty for each firm included in the analysis. Likewise, the paper develops a PCA-based composite index for macroeconomic uncertainty by using the conditional variance series of consumer price index (CPI), industrial production index (IPI), the interest rate and the exchange rate obtained by estimating the (generalized) autoregressive conditional heteroscedastic, (G)ARCH, models. Finally, political uncertainty is measured by political risk components maintained by the Political Risk Services Group. The empirical framework of the paper augments the standard investment equation by incorporating all three types of uncertainty. Firms are grouped into small, medium and large categories based on firms' total assets and the size indicators are generated. Next, the indicators are multiplied by each uncertainty measure to quantify the differential effects of uncertainty across firm size. Firms are also differentiated by sectors to explore the sector-based asymmetries in the uncertainty effects. The “robust two-step system generalized method of moments (2SYS GMM) (dynamic panel data) estimator” is applied to estimate the empirical models.

The results provide robust and strong evidence of the detrimental influence of all three types of uncertainty on investment. Yet, it is observed that the strength of the influence considerably varies across uncertainty types. In particular, compared to firm-specific uncertainty, both macroeconomic and political uncertainties have more unfavorable effects. The analysis also reveals that the effects of all three types of uncertainty are quite different at small, medium and large firms. Specifically, it is observed that although the investment of all firms is influenced adversely by magnified uncertainty, the adverse effects of all three kinds of uncertainty are quite stronger at small firms than medium and large firms. These findings support the phenomenon of size-based asymmetries in the effects of uncertainty on investment. The results also provide evidence that either type of uncertainty quite differently affects the investment policy of firms in different sectors.

The findings help different stakeholders to know how different types of uncertainty differently affect corporate firms' investments. Further, they suggest that firm size has a vital role in ascertaining the adverse effects of uncertainty on investment. The paper identifies to which type of uncertainty investors and policymakers should care more about and to which types of firms and industries they should concern more during volatile times. Firms should have more fixed assets and expand their size to mitigate the detrimental effects on investment of internal and external uncertainties. The government should enhance the political stability to induce firms for a higher level of investment, which, in turn, will result in higher growth of the economy.

The originality of the paper is credited to four aspects. First, unlike most previous studies that have utilized a single volatility measure, this paper constructs composite uncertainty indices based on the weights determined by the PCA. Second, it examines the effect of political uncertainty over and above the effects of idiosyncratic and aggregate (macroeconomic uncertainty) for an emerging economy. Third, and most important, it provides first-hand empirical evidence on the role of firm size in establishing the asymmetric effects of uncertainty on investment. Finally, it provides evidence on the industry-based heterogeneity in the uncertainty effects.

With increasing marine resource development, the rapid development of the marine economy, and the continuous decline of the marine natural resource system, the contradiction between marine resources and economic development is becoming increasingly acute. The study of marine resources and economic development has become a hot and challenging issue in marine resource economics research in recent years. The purpose of this study is to analyze the current situation of marine resources and to realize the sustainable use of marine resources.

This study systematically reviews and analyzes the current status of research on marine resources and economic development issues in four main aspects: marine resource management, marine resources and economic growth, marine resources and economic security, and marine resource accounting in the field of marine resource economics.

It is found that compared to the current status of research on land-based resources and economic development, there is a significant lag in both theoretical construction and methodological innovation in marine resources and economic development.

The purpose of this study is to systematically grasp the current status of marine resources research, promote the coordinated development of marine resources and economic growth, and then realize the safe and sustainable development and utilization of marine resources.

The Sustainable Development Goals (SDGs) provide a blueprint for UN member states to achieve prosperity and peace. A resilient construction industry should positively contribute to the achievement of all SDGs. Yet it is currently unclear if the industry helps or hinders SDG achievement. This research aims to explore if the industry is positively engaging with all SDGs.

This research is split into two phases. The first is an objectivist Qualitative Content Analysis (QCA) of sustainability reports from the ten leading UK contractors to identify direct and indirect SDG references. The second research phase adopts a subjectivist ontological position consisting of twenty-one semi-structured interviews with a range of construction industry project-based professionals. Narrative analysis is used to structure the interview questions and analyse the data gained.

Many SDGs are excluded from sustainability reports, and where discussed, only some are engaged with substantially. The SDG knowledge held by construction professionals is reduced further still, and SDG progress is rarely measured. The ambiguity surrounding the SDGs enables discrepancies between reporting and professional perceptions. There is also a lack of regard for fellow contractor collaboration through fear of reduced competitive advantage.

This paper addresses a gap in the literature between contractor SDG knowledge and action. This serves as a platform for future research agendas regarding how the SDGs can be better understood and actioned in a construction management context. For industry, inconsistencies between organisational sustainability reporting and the knowledge and awareness of staff are exposed, due to the lack of collaborative practices currently adopted.

Drawing on the theoretical underpinnings of job crafting, this study aims to investigate how and when internal marketing orientation (IMO) promotes employees’ positive word of mouth (PWOM).

The two-wave, multisource data came from frontline employees and their supervisors in a hotel located in Eastern China. The hypothesized relationships were tested with Mplus with multilevel path analysis.

The results reveal that IMO encourages frontline employees to change the task, cognitive and relational boundaries of their jobs. Nevertheless, it is through relational crafting that IMO ultimately affects employees’ PWOM, especially when they work with supervisors high in felt responsibility for constructive change (FRCC).

To the best of the authors’ knowledge, this study is one of the first studies to investigate how organizations and supervisors can work together to encourage frontline employees’ PWOM.

The findings carry important implications for practitioners on how to encourage frontline employees’ PWOM in the service sector.

First, this research adds to the limited knowledge of how organizations and supervisors can work together to promote frontline employees’ PWOM in the service sector. Second, by proposing job crafting as a key intermediary mechanism underlying IMO’s impact on employee PWOM, this research not only offers a new theoretical perspective to understand how to promote frontline employees’ PWOM but also sheds new light on the underlying mechanisms through which IMO exerts its influence on frontline employees. Third, supervisors’ FRCC as a boundary condition of IMO can help service organizations more effectively capitalize on IMO to motivate frontline employees’ engagement in job crafting and subsequent PWOM.

Despite the vast potential of mobile phone use, grape smallholder farmers’ satisfaction with mobile phone use has attracted insufficient attention among scholars in Tanzania. The study examined factors influencing satisfaction with mobile phone use for accessing agricultural marketing information.

The study used a cross-sectional research design and a mixed research method. Structured questionnaire and focus group discussions were used to collect primary data from 400 sampled grape smallholder farmers. Data were analysed inferentially involving two-way analysis of variance, ordinal logistic regression and thematic analysis.

The findings indicate a statistically significant disparity in grape smallholder farmers’ satisfaction across different types of agricultural marketing information. Grape smallholder farmers exhibited higher satisfaction levels concerning information on selling time compared to all other types of agricultural marketing information (price, buyers, quality and quantity). Factors influencing grape smallholder farmers’ satisfaction with mobile phone use were related to perceived usefulness, ease of use, experience and cost.

This study contributes to scientific knowledge by providing actionable insights for formulating unique strategies for smallholder farmers’ satisfaction with agricultural marketing information.

Convection is one of the main heat transfer mechanisms in both high to low temperature media. The accurate convection heat transfer coefficient (HTC) value is required for exact prediction of heat transfer. As convection HTC depends on many variables including fluid properties, flow hydrodynamics, surface geometry and operating and boundary conditions, among others, its accurate estimation is often too hard. Homogeneous dispersion of nanoparticles in a base fluid (nanofluids) that found high popularities during the past two decades has also increased the level of this complexity. Therefore, this study aims to show the application of least-square support vector machines (LS-SVM) for prediction of convection heat transfer coefficient of nanofluids through circular pipes as an accurate alternative way and draw a clear path for future researches in the field.

The proposed LS-SVM model is developed using a relatively huge databank, including 253 experimental data sets. The predictive performance of this intelligent approach is validated using both experimental data and empirical correlations in the literature.

The results show that the LS-SVM paradigm with a radial basis kernel outperforms all other considered approaches. It presents an absolute average relative deviation of 2.47% and the regression coefficient (R²) of 0.99935 for the estimation of the experimental databank. The proposed smart paradigm expedites the procedure of estimation of convection HTC of nanofluid flow inside circular pipes.

Therefore, the focus of the current study is concentrated on the estimation of convection HTC of nanofluid flow through circular pipes using the LS-SVM. Indeed, this estimation is done using operating conditions and some simply measured characteristics of nanoparticle, base fluid and nanofluid.

The purpose of this paper is to identify critical Clean Development Mechanism (CDM) benefits and assess their relative significance in the context of developing economies (e.g. India).

This study has conducted face-to-face (offline/online) discussions with experts in order to identify appropriate criteria and related CDM benefits. Further, this study has used subsequently, using the analytic hierarchy process, a multi-criteria decision-making method and assess the relative significance of benefits of CDM projects.

The results reveal that knowledge and capacity building, technology transfer and social benefits are the most significant CDM benefits, respectively. It is because the knowledge and capacity building tends to disseminate the awareness on CDM benefits among policymakers and stakeholders, thereby, lead to efficient policy-making and encourage effective technology transfer in a way to achieve sustainable economic growth in the host country.

The literature is dominated by studies of CDM projects in Brazil, Mexico, Chile, Africa and China. Within the thousands of CDM projects globally, India only has 1,376 registered CDM projects. To the authors' knowledge, this is one of the first studies that highlight the relative significance of CDM benefits in the context of India. This study will enhance the implementation in the Indian scenario.