Search results

The purpose of this study is to examine different paths to overcoming the liability of foreignness. Based on the eclectic paradigm, the authors construct a theoretical framework comprising enterprise nature, location choice, entry mode and internationalization strategy.

The paper uses fuzzy-set qualitative comparative analysis (fsQCA) method to test the framework with data covering 120 multinational Chinese subsidiaries in 34 host in 2019.

The results show that liability of foreignness (LOF) is multiple concurrency, equifinality and asymmetry. When investing in Belt and Road (B&R) countries, non-SEOs can weaken LOF by applying the greenfield mode and resource-seeking strategy, other MNEs can implement a market- or resource-seeking strategy via cross-border M&A to reduce LOF. But when investing in non-B&R countries with a strategic asset-seeking strategy, the LOF is increased. The B&R initiative can reduce the LOF effectively.

The authors construct a general framework to explain the paths of overcoming LOF by bridging the OLI with LOF and introduce fsQCA method into the field of LOF to make up for the shortcoming of existing test method by explaining the influence of more than three factors on LOF.

We wanted to find out how infant multinationals originating from Poland enact opportunities in Sub-Saharan African (SSA) countries.

We conducted a comparative case study of four Polish firms operating in SSA.

We found that when entering SSA, studied firms employed effectual decision-making logic. Thus, their internationalization was means-driven, serendipitous, partnership-oriented, based on the “affordable loss” principle and focused on shaping opportunities in SSA, rather than predicting, analyzing and planning any firm-specific assets or capabilities.

We illuminated the nature of the means employed in effectual internationalization and the role of partners (“effectual stakeholders”) in this process. Thus, we contribute to a deeper understanding of how infant multinationals navigate extreme uncertainty in the emerging SSA markets.

The presence of green spaces plays a vital role in promoting urban sustainability. Urban green parks (UGPs) help create sustainable cities while providing fundamental ecological functions. However, rapid urbanization has destroyed crucial green areas in Ranchi City, endangering inhabitants’ health. This study aims to locate current UGPs and predict future UGP sites in Ranchi City, Jharkhand.

It uses geographic information system (GIS) and analytical hierarchical process (AHP) to evaluate potential UGP sites. It involves the active participation of urban communities to ensure that the UGPs are designed to meet dweller’s needs. The site suitability assessment is based on several parameters, including the normalized difference vegetation index (NDVI), land use and land cover (LULC), population distribution, PM 2.5 levels and the Urban Heat Island (UHI) effect. The integration of these factors enables an evaluation of potential UGP’s sites.

The findings of this research reveal that 54.39% of the evaluated areas are unsuitable, 15.55% are less suitable, 12.76% are moderately suitable, 11.52% are highly suitable and 5.78% are very highly suitable for UGPs site selection. These results emphasize that the middle and outer regions of Ranchi City are the most favorable locations for establishing UGPs. The NDVI is the most important element in UGP site appropriateness, followed by LULC, population distribution, PM 2.5 levels and the UHI effect.

This study improves the process of integrating AHP and GIS, and UGPs site selection maps help urban planners and decision-makers make better choices for Ranchi City’s sustainability and greenness.

This study aims to quantify the influence of urbanization on housing prices at the district-based level, while also investigating the heterogeneous impacts across different quantiles of housing prices.

The study uses remote-sensed spectral images from the Landsat 7 ETM+ satellite to measure urbanization, replacing prior reliance solely on urban population metrics. Subsequently, the two-step system generalized method of moments is used to evaluate how urbanization influences district-based housing prices through three spectrometries: Urban Index (UI), Normalized Difference Built-up Index (NDBI) and Built-Up Index (BUI). Finally, this study examines the heterogeneous impacts across various housing price quantiles through Dynamic Panel Quantile Regression with non-additive fixed effects under Markov Chain Monte Carlo simulation.

The study demonstrates that urbanization leads to an increase in regional housing prices. However, these impact magnitudes vary across housing price quantiles. Specifically, the impact exhibits an inverse V-shaped curve, with urbanization exerting a more pronounced influence on the 60th percentile of housing prices, while its effect on the 10th and 90th percentiles is comparatively weaker.

This study uses a novel method of remote sensing to measure urbanization and investigates its effects on housing prices. Furthermore, it provides an empirical application of non-additive fixed effect quantile regression for analyzing heterogeneity.

This paper aims to unravel the impact of post-pandemic COVID-19 on foreign direct investment (FDI) and its determinants in the South Asian Association for Regional Cooperation (SAARC) Countries.

The study utilized four macroeconomic variables includes growth domestic product growth rate (GDPG), inflation rate (IR), exchange rate (ER), and unemployment rate (UR) to assess their impact on post-pandemic FDI, along with two variables control of corruption (CC) and political stability (PS) to measure the influence of good governance. Random effects, fixed effects, cluster random effects, cluster fixed effects and generalized method of moments (GMM) models were applied to a balanced panel dataset comprising eight SAARC countries over the period 2010–2021. To identify the random trend component in each variable, three renowned unit root tests (Levin, Lin and Chu LLC, Im-Pesaran-Shin IPS and Augmented Dickey-Fuller ADF) were used, and co-integration associations between variables were verified through the Pedroni and Kao approaches. Data analysis was performed using STATA 17 software.

The major findings revealed that the variables have an order of integration at the first difference I (1). Nonetheless, this situation suggests the possibility of a long-term link between the series. And the main results of the findings show that the coefficients of GDPG, CC and PS are positive and significant in the long run, showing that these variables boosted FDI inflows in the SAARC region as they are significantly positively linked to FDI inflows. Similarly, the coefficients of UR, IR, ER and COVID-19 are negative and significant.

By identifying the specific impacts of the post-pandemic FDI and its determinants, governments and policymakers can formulate targeted policies and measures to mitigate the adverse effects and enhance investment attractiveness. Additionally, investors can gain a deeper understanding of the risk factors and adapt their strategies accordingly, ensuring resilience and sustainable growth. Finally, this paper adds value to the literature on the post-pandemic impact on FDI inflows in the SAARC region.

This paper is the first attempt to trace the impact of COVID-19 on Foreign Direct Investment and its determinants in the SAARC Countries. Most of the previous studies were analytical in nature and, if empirical, excluded some countries due to the unviability of the data set. This study includes all the SAARC member countries, and all variables' data are completely available. There is still a lack of empirical studies related to the SAARC region; this study attempts to fill the gap.

This research aims to propose a model for the complex decision-making involved in the ecological restoration of mega-infrastructure (e.g. railway engineering). This model is based on multi-source heterogeneous data and will enable stakeholders to solve practical problems in decision-making processes and prevent delayed responses to the demand for ecological restoration.

Based on the principle of complexity degradation, this research collects and brings together multi-source heterogeneous data, including meteorological station data, remote sensing image data, railway engineering ecological risk text data and ecological restoration text data. Further, this research establishes an ecological restoration plan library to form input feature vectors. Random forest is used for classification decisions. The ecological restoration technologies and restoration plant species suitable for different regions are generated.

This research can effectively assist managers of mega-infrastructure projects in making ecological restoration decisions. The accuracy of the model reaches 0.83. Based on the natural environment and construction disturbances in different regions, this model can determine suitable types of trees, shrubs and herbs for planting, as well as the corresponding ecological restoration technologies needed.

Managers should pay attention to the multiple types of data generated in different stages of megaproject and identify the internal relationships between these multi-source heterogeneous data, which provides a decision-making basis for complex management decisions. The coupling between ecological restoration technologies and restoration plant species is also an important factor in improving the efficiency of ecological compensation.

Unlike previous studies, which have selected a typical section of a railway for specialized analysis, the complex decision-making model for ecological restoration proposed in this research has wider geographical applicability and can better meet the diverse ecological restoration needs of railway projects that span large regions.

This paper aims to assess the current and future dynamics of land cover transitions and analyze the vegetation conditions in Abuja city since its establishment as the capital of Nigeria in 1991.

A random forest classifier embedded in the Google Earth Engine platform was used to classify Landsat imagery for the years 1990, 2001, 2014 and 2020. A post-classification comparison was used to detect the dynamics of land cover transitions. A hybrid simulation model that comprised cellular automata and Markovian was used to model the probable scenario of land cover changes for 2050. The trend of Normalized Difference Vegetation Index was examined using Mann–Kendall and Theil Sen’s from 2014 to 2022. Nighttime band data from the National Oceanic and Atmospheric Administration were obtained to analyze the trend of urbanization from 2014 to 2022.

The findings show that built-up areas increased by 40%, while vegetation, bare land and agricultural land decreased by 27%, 7% and 8%, respectively. Vegetation had the highest declining rate at 3.15% per annum. Built-up areas are expected to increase by 17.1% between 2020 and 2050 in contrast with other land cover. The proportion of areas with moderate vegetation improvement is estimated to be 15.10%, while the proportion of areas with no significant change was 38.10%. The overall proportion of degraded areas stands at 46.8% due to urbanization.

The findings provide a comprehensive insight into the dynamics of land cover transitions and vegetation variability induced by rapid urbanization in Abuja city, Nigeria. In addition, the findings provide valuable insights for policymakers and urban planners to develop a sustainable land use policy that promotes inclusivity, safety and resilience.

Although marketing is essential for a firm’s survival and growth, a set of entrepreneurial strategic orientations may help it gain a competitive advantage. Entrepreneurial marketing (EM) is critical for growing businesses to succeed in today's fast-paced industry. The present study aims to measure the role of EM on the business performance (BP) of Indian startups.

For this purpose, a thorough literature review was conducted to develop a scale from the proposed conceptual framework – EMICO by Jones and Rowley (2009b). To assess the reliability and validity of the scale (62 items), the data are analyzed by employing partial least square-structural equation modeling (PLS-SEM).

The scale is empirically tested, and the results lead to discussions. The results show the positive impact of entrepreneurial orientation (EO), marketing orientation (MO), innovation orientation (IO) and customer orientation (CO) on the BP of the startups. The paper concludes by suggesting managerial and practical implications, also providing future research agenda.

Our objective is to address the existing dearth of comprehensive scales for evaluating EM by undertaking a rigorous statistical approach. Notably, our research represents the pioneering effort in adopting the EMICO framework and subsequently formulating and empirically validating a robust scale specifically tailored for nascent or small-scale startups within the Indian context.

This study explores how the various aspects of corporate social responsibility (CSR) impact customer satisfaction (CS) within the restaurant sector. Furthermore, it seeks to reveal if there is a moderating role played by gender in the relationship between CSR dimensions and CS in the realm of restaurant services.

The findings of this research were obtained by analysing 352 questionnaires collected from Iranian restaurants. Structural equation modelling was used to test the conceptual model.

According to this research, responsibility (economic, legal, ethical and environmental) is related to CS. Additionally, this study delves into the specific influence of each facet of CSR on CS, a departure from prior research which treated CSR as a singular entity. Consequently, the findings of this study offer clarity on which dimension of CSR can impact CS. Prior studies examining the correlation between CSR and CS typically encompassed various CSR aspects, including economic, legal, ethical and philanthropic dimensions, with the environmental dimension often subsumed under ethical CSR. This research, however, recognises environmental CSR as the fifth distinct dimension. The results of this research show that CS is directly and significantly influenced by all aspects of CSR (except philanthropy). Also, the findings of this research show that gender does not make a difference on the impact of different dimensions of CSR on CS.

The findings of this study provide restaurant managers with a deeper understanding of CSR and how it can influence CS. The research demonstrates that environmental CSR had the strongest impact on Iranian CS among the five CSR dimensions investigated. The findings also support the notion that Iranian consumers are beginning to use CSR information to evaluate restaurants.

This research represents an early exploration of how individual facets of CSR affect CS. As part of this investigation, Carroll’s initial model was modified to include a novel element, environmental responsibility, to address environmental concerns' growing importance. This study contributes to the literature by demonstrating that CSR activities are not all equally effective.

This paper aims to present the continuous Nigerian Government’s failure to protect the lives and property of its citizens against the incessant itinerant herders’ violence, despite its numerous programs in attempts to end the carnage. It sought also to examine the relationship between this government’s failure to meet its responsibility and the ineluctable self-defense mechanisms adopted by the people of Plateau State, Nigeria.

The research was both quantitative and qualitative. The study was conducted in four of the 17 Local Government Areas of the state: Bassa, Jos-south, Riyom and Barkin Ladi. A sample size of 400 was determined using Yamane Taro’s sampling size formula. Four hundred respondents were interviewed using a Google questionnaire (found at this link: https://forms.gle/tu96ZDwP85e8JsGu8). In this study, a total of seven key informant interviews and nine focus group discussions were conducted.

The finding revealed that most indigenous ethnic groups were dissatisfied with the government’s handling of the nomadic herders’ aggression. Therefore, 99.1% of Berom, 99.0% of Irigwe and 92.9% of other ethnicities argued that the government’s failure to protect them is a tacit permission for self-defense. On the contrary, 60.0% of the Fulani were satisfied with the government’s strategies in ending the aggression and 95.0% of them argued that the government’s failure to protect its citizens is not an implied permission for self-defense. It was also found that a relationship exists between the government’s lack of capacity to end the nomadic herders’ aggression and implied consent for self-defense in Plateau State, Nigeria.

This is a research paper that uses primary data. The findings are germane to ending the challenge of recurrent aggression of nomadic herders on other Nigerians. The study concludes that the government must live up to its responsibility of the protection of its citizens’ lives and property, failure to do so is an implicit permission to the citizens to defend themselves. It also recommended that the government should return displaced people to their communities.