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Drawing on social network and information diffusion theories, the authors study the impact of the structural characteristics of a seller’s local social network on her promotion effectiveness in social commerce.

The authors define a local social network as one formed by a focal seller, her directly connected users and all links among these users. Using data from a large social commerce website in China, the authors build econometric models to investigate how the density, grouping and centralization of local social networks affect the number of likes received by products posted by sellers.

Local social networks with low density, grouping and centralization are associated with more likes on sellers’ posted products. The negative effects of grouping and centralization are reduced when density is high.

The paper deepens the understanding of the determinants of social commerce success from a network structure perspective. In particular, it draws attention to the role of sellers’ local social networks, forming a foundation for future research on social commerce.

This study examines the effect of social media marketing on voting intention applying a combination of fuzzy logic methodology and a multidimensional panel data model.

The study adopts a multidimensional panel data method that includes several fixed effects. The dependent variable is a multifaceted construct that measures the participants’ intention to vote. The independent variables are electronic word of mouth (eWOM), customisation (CUS), entertainment (ENT), interaction (INT), trendiness (TRD), candidate’s perceived image (CPI), religious beliefs (RB), gender and age. The grouping variables that signify fixed effects are employment status, level of education, mostly used social media and religion. First, the significance of said fixed effects was tested through an ANOVA process. Then, the main model was estimated, including the significant grouping variables as fixed effects.

Employment status and level of education were significant fixed effects. Also, eWOM, ENT, INT, CPI, RB and gender significantly affected participants’ voting intention.

Being based on a questionnaire that asked participants about how they perceive different aspects of social media, the present study is limited to their perceptions. Therefore, further studies covering the voters’ behaviour in action could be efficient complements to the present study.

The findings could guide the political parties into prioritizing the aspects of social media in forming an effective campaign resulting in being elected.

The findings have the potential to help the public in making better informed decisions when voting. Furthermore, the results of this study indicate applications for social media which are beyond leisure time fillers.

Fuzzy logic and multidimensional panel data estimates are this study’s novelty and originality. Structural equation modelling and crisp linguistic values have been used in previous studies on social media’s effect on voting intent. The former refines the data gathered from a questionnaire, and the latter considers the possibility of including different grouping factors to achieve a more efficient and less biased estimation.

The common language behind vernacular architecture only seems to be maintained in societies that preserve a traditional way of life. Changes in these societies can threaten their cultural heritage, while research may be a tool for its conservation and enhancement. In this paper, the habitat of a Mossi community is therefore studied as a first stage in analysing the possibilities of its maintenance.

After a previous study, data collection from a stay in Baasneere (Burkina Faso) and the analysis of 32 traditional residential units were completed. The research showed some common features which, when compared against the bibliography reviewed, could be defined as characteristic of the traditional architecture of this culture.

The home for a family unit consisted in an enclosure formed by the grouping of adobe constructions around a courtyard. As the family grew so did the compound, in a relationship directly linking the scales of architecture and the levels of kinship. The main daily activities took place in the courtyards while the individual interior spaces were understood as private shelters. Other typologies such as granaries, kitchens, warehouses and sheds were also analysed.

Some features of Mossi architecture already described in the existing bibliography were verified in the Baasneere case studies, showing that this tradition is still preserved. With a multidisciplinary approach, the house was examined not so much from the perspective of construction, but of its cultural configuration.

The study seeks to understand what teachers know about students’ friend networks and how they use that information for instruction.

This qualitative study relied on interviews and sociograms that teachers drew of students’ friend networks.

Our data suggest that teachers’ awareness of their students’ friend networks varies by their experience and their exposure to students. Also, their use of this information for instruction coalesces around dimensions of grouping and social support.

This study took place at one school. To more deeply understand what teachers perceive about their students’ friend networks and how they use that information for instruction, more studies could be done with teachers in more schools.

Implications might suggest developing teachers’ social competence to support their students’ learning and development.

While studies cited in this paper have explored teachers’ knowledge of students’ social networks, this study builds on this work by exploring how that information can be useful for instruction. In addition, this study explores the use of teachers drawing sociograms as representations of what they know about students’ friend networks.

The purpose of this study is twofold: first, to determine if pharmaceutical companies can be grouped based on their espoused values, and second, to examine the relationship between these values and company reputation.

A descriptive study design is used with two separate analyses: cluster analysis for grouping the companies; and descriptive data analysis for determining cluster differences.

The findings suggest that there are three value clusters: competent, community and interpersonal, with the community group showing the highest relative reputation, and the interpersonal cluster as the lowest. Brand portfolio composition appears to positively contribute to reputation. The effect of portfolio specialization is based on a company’s closeness to its therapeutic community, which may be influenced by the outward characteristics of its values.

Future research should examine the longitudinal effects of values on reputation combined with case studies.

Regardless of cluster classification, all firms should develop strong ties with their therapeutic communities using both personal and digital/omnichannel strategies.

A company’s values are becoming an important consideration for all customers and stakeholders.

To the best of the authors’ knowledge, this study is the first to systematically examine the activities of leading pharmaceutical firms to link a specific value cluster to company reputation.

This study aims to revisit the empirical debate about the asymmetric relationship between oil prices, energy consumption, CO₂ emissions and economic growth in a panel of 184 countries from 1981 to 2020.

A relatively new research method, the PVAR system GMM, is applied.

The outcome of the PVAR system GMM model at the group level in the study suggests that oil prices exert a positive but statistically insignificant effect on economic growth. Energy consumption is inversely related to economic growth but statistically significant, and the correlation between CO₂ emissions and economic growth is negative but statistically insignificant. The Granger causality test indicates that oil prices, CO₂ emissions, oil rents, energy consumption and savings jointly Granger-cause economic growth. A unidirectional causality runs from energy consumption, savings and economic growth to oil prices. At countries’ income grouping levels, oil prices, oil rent, CO₂ emissions, energy consumption and savings jointly Granger-cause economic growth for the high-income and upper-middle-income countries groups only, while those variables did not jointly Granger-cause economic growth for the low-income and lower-middle-income countries groups. The modulus emanating from the eigenvalue stability condition with the roots of the companion matrix indicates that the model is stable. The results support the asymmetric impacts of oil prices on economic growth and aid policy formulation, particularly the cross-country disparities regarding the nexus between oil prices and growth.

From a methodological perspective, to the best of the author’s knowledge, the study is the first attempt to use the PVAR system GMM and such a large sample group of 184 economies in the post-COVID-19 era to examine the impacts of oil prices on countries’ growth while controlling for other crucial variables, which is noteworthy. Two, using the World Bank categorisation of countries according to income groups, the study adds another layer of contribution to the literature by decomposing the 184 sample economies into four income groups: high-income, low-income, upper-middle-income and lower-middle-income groups to investigate the potential for asymmetric effects of oil prices on growth, the first of its kind in the post-COVID-19 period.

The purpose of this study is to systematically identify, assess, and categorize the barriers to digital transformation (DT) in the engineering and construction sectors, and thus to better understand the impact and how these sectors might be overcome.

This study adopted a sequential mixed qualitative and quantitative data collection and analysis approach. DT barriers were first identified from relevant literature and verified by an expert panel. Then, a questionnaire survey assessing the impacts of the identified DT barriers was distributed to construction professionals in China, and 192 valid responses were retrieved. Further, the data obtained were analyzed using ranking analysis, exploratory factor analysis (EFA), and partial least squares-structural equation modeling (PLS-SEM).

Based on the ranking analysis, the top three barriers are “lack of industry-specific standards and laws,” “lack of clear vision, strategy and direction for DT,” and “lack of support from top management for DT.” EFA enabled the grouping of the 26 barriers into 3 categories: (1) lack of laws and regulations (LLR), (2) lack of support and leadership (LSL), and (3) lack of resources and professionals (LRP). The PLS-SEM analysis revealed that LLR, LSL, and LRP were found to have significant negative impacts on DT.

These findings contribute to the body of knowledge on DT in the construction industry and help construction firms and government bodies improve the understanding of these barriers to DT and put forward relevant policies and incentives, thus seizing the DT benefits as a way to enhance construction project management.

The spread of fake news on Instagram is still a problem that needs to be solved. Teenagers are a generation that is vulnerable to fake news, for example, high school students. Students need media literacy to help them protect against fake news. The media literacy skills possessed by students influence the behavior of spreading fake news that they do. This study aims to examine the effect of student media literacy on the behavior of spreading fake news on Instagram among students at public high schools in Surabaya.

This study used an online survey to100 students at five public high school in Surabaya to get the data on their ability to respond to the fake news on social media Instagram.

It was found that there is a media literacy that has a significant effect on the behavior of spreading fake news on Instagram. Based on these findings, it can be concluded that media literacy influences the behavior of spreading fake news on Instagram, and other factors influence the rest. There are seven media literacy skills, and the high category are grouping, deduction, synthesis and abstraction abilities. Meanwhile, the abilities included in the medium category are analysis and evaluation abilities.

This paper will provide insight of the media literacy levels on teenagers in metropolitan city. This result can be used as guide to add the media literacy subject at high schools and can be used to strengthen the media literacy skills among teenagers.

The reform and opening-up of capital market is valued for promoting sustainable development, while its impact presented as the form of deregulation of short-selling on the green innovation of enterprises in developing countries remains unclear. The purpose of this study is to outline the significance of gradual reform of financial markets in developing countries for low-carbon transformation and provide implications for achieving carbon peaking and carbon neutrality goals.

Based on the green subdivided patent data and financial data of China’s A-share listed companies, this paper takes the implementation of securities margin trading program as a quasi-natural experiment and applies the difference-in-differences (DID) model to examine the impact of deregulation of short-selling constraints on the enterprises’ green transformation.

The findings reveal that the initiating securities margin trading program significantly enhances the green innovation performance of enterprises. These findings are valid after performing a series of robustness tests such as the parallel trend test, the placebo test and the methods to exclude other policy interference. Mechanism analyses demonstrate a two-faceted effect of the securities margin trading program on the green innovation of enterprises, in which short-selling policy increases the pressure on capital market deregulation and meanwhile induces the environmental protection investment. The heterogeneity results demonstrate that the impulsive effect imposed by securities margin trading program is more significant in experimental group samples with characteristics of lower financing constraints, belonging to heavy polluting industries and possessing better environmental supervision capability.

First, previous studies have focused on the impact of financial policies implemented by banking institutions on the green innovation of enterprises, but few literatures have explored the validity of relaxing short-selling restrictions or opening the capital market in the field of enterprise’s green transformation in developing country. From the view of securities market reform, this paper broadens the incentive and supervision effects of the relaxation of short-selling control on enterprise’s green innovation performance after the implementation of securities financing and securities lending policy in China’s capital market. Second, previous studies have explored the impact of command-and-control environmental regulations, as well as market-incentivized environmental regulations such as green finance, low-carbon pilots and environmental tax reform, on the green transition of enterprises. Recently the role of the securities market in the green development of enterprises has received more attention in academia. The pilot of margin financing and securities lending is essentially a market-incentivized regulatory tool, but there is few in-depth research on how it affects the green innovation of enterprises. This paper enriches the research on whether the market incentive financial regulation policy can contribute to the green transformation of enterprises under the Porter hypothesis. Third, some previous studies used the ordinary panel regression model to explore the impact of financial policy on enterprise’s innovation performance. However, due to the potential endogenous problems of the estimated model, it might get biased conclusions. Therefore, based on the method of quasi-natural experiment, this paper selects the margin trading pilot policy as an exogenous shock to solve the endogenous or reverse causality problem in traditional measurement model and applies the DID model to study the relationship between core indicator variables.