Search results

Political Corporate Social Responsibility (CSR), based on ideas about deliberative democracy, have been criticised for increasing corporate power and democratic deficits. Yet, deliberative ideals are flourishing in the corporate world in the form of dialogues with a broad set of stakeholders and engagement in wider societal issues. Extractive industry areas, with extensive corporate interventions in weak regulatory environments, are particularly vulnerable to asymmetrical power relations when businesses engage with society. This paper aims to illustrate in what way deliberative CSR practices in such contexts risk enhancing corporate power at the expense of community interests.

This paper is based on a retrospective qualitative study of a Canadian oil company, operating in an Albanian oilfield between 2009 and 2016. Through a study of three different deliberative CSR practices – market-based land acquisition, a grievance redress mechanism and dialogue groups – it highlights how these practices in various ways enforced corporate interests and prevented further community mobilisation.

By applying Laclau and Mouffe’s theory of hegemony, the analysis highlights how deliberative CSR activities isolated and silenced community demands, moved some community members into the corporate alliance and prevented alternative visions of the area to be articulated. In particular, the close connection between deliberative practices and monetary compensation flows is underlined in this dynamic.

The paper contributes to critical scholarship on political CSR by highlighting in what way deliberative practices, linked to monetary compensation schemes, enforce corporate hegemony by moving community members over to the corporate alliance.

The purpose of this paper is to ascertain the significant stimulating measures/enablers relating to the existing building regulations for promoting the adoption and overcoming the barriers to the uptake and implementation of the green building concept (GBC) in developing countries using Ghana as a case.

The quantitative research approach was used to attain the study’s goal. Purposive and snowball sampling techniques were found to be suitable for collecting data from 292 relevant stakeholders in Ghana’s construction industry. The mean score ranking technique, in conjunction with the relative importance index, was used to establish the relative ranking of, among other things, the stimulus measures for increasing green building uptake in Ghana. An exploratory factor analysis was also used to classify the most significant stimulation strategies for improving green building uptake.

“Educational programmes relevant to GBTs for developers, contractors, and policymakers,” “sufficient information on the cost and benefits of GBTs” and “mandated green building codes and regulations” were the top three listed stimulating measures to promote increasing use of green building technologies (GBTs). The enablers were classified as follows: government regulations and policies; commitment and GB research; education and publicity; and incentives and support.

The study was conducted in Ghana, a developing nation, and thus the findings and implications are peculiar to Ghana. However, the study’s findings have important practical implications for the adoption and marketing of GBCs and GBTs in other developing nations.

Prioritizing major stimulation initiatives may be beneficial in terms of overcoming the constraints to the adoption of GBCs and GBTs in developing countries.

This study aims to examine the impact of national culture on classification shifting in Eastern European Member States of EU Eastern European countries (EEU) vis-à-vis the Western Member States of EU (WEU). The EEU provides a unique sample to study the quality of financial reporting that the authors measure with classification shifting given that for more than five decades they were following the model of a centrally planned economy, where market-based financial reporting was absent. Yet, the EEU transitioned to a market-based economy and completed its accession to the EU.

This study uses a panel data set of firm year observations from 1996 and 2020 that covers the full transition of EEU. This empirical analysis is based on fixed effects panel regression analysis where the authors report a plethora of identifications.

This study finds classification shifting in the EEU countries since their transition to the market-based economy, though they have no long record of market-based financial reporting. This study also notices that cultural factors are associated with classification shifting across all Member States of the EU. This study further examines the impact of interactions between cultural characteristics and special items and reveal variability between WEU and EEU. As part of the robustness analysis, this study also tests the impact of culture on real earnings management measures for both WEU vs EEU, confirming the variability of the impact of culture on earnings management.

Future research could explore the role of religion differences in WEU vis-à-vis EEU states, as they are also subject to cultural differences.

The findings are important for regulators, external monitors and investors, as they show that cultural factors affect earnings management with some variability across countries in the EU, and they should be acknowledged in policymaking.

The findings show that cultural differences between EEU and the “old” Member States of the EU could explain classification shifting.

To the best of the authors’ knowledge, this is the first study that sheds light on the impact of national culture on classification shifting in EEU of EU vis-à-vis the “old” WEU of EU.

This study aims to explore how CEO narcissism drives investment in corporate social responsibility (CSR) and its mediating mechanism.

This study includes panel regression based on archival data.

CEO narcissism leads to signaling of organizational virtuous orientation that results in increase in CSR investment.

Relevance of CEO traits on CSR remains unexplored in emerging markets context, especially the underlying mechanism. This study uncovers these mechanisms.

This paper aims to identify the combination of innovation determinants driving the creation of innovative products amongst market leaders and market followers in food and beverage (F&B) firms.

This research is based on the case study methodology by using two types of data sources: (1) semi-structured interviews with industry experts and (2) in-depth interviews with managers. In addition, a questionnaire adapted from prior research was used to consider market and firm types.

Suggesting an integrated theoretical framework based on firm-based factors and market-based factors, this study identified a combination of determinants significantly impacting innovative products in the market. Specifically, these determinants are competition intensity and innovation capability (a combination of research and development (R&D) investment and marketing capabilities). The study also examined how these determinants vary depending on whether the firms are market leaders or market followers.

This research provides practical insights for managers working in the F&B industry by using case studies and exploring the determinants of developing innovative products. In doing so, suitable strategies can be selected according to the market and firm situations.

The originality of the study is shown by focussing on how different combinations of market and firm factors could be applied in creating successful innovative products in the food sector.

This study aims to explore the ways that social enterprises (SE) create value by embedding themselves in networks through the process of social innovation (SI). The processes of achieving common social missions were studied through selected organizations using an open approach to SI. Novel operational structures as well as unique forms of created value were explored.

Two organizations embedded in local and international networks were studied and were chosen due to their SI profiles. The study was based on qualitative exploratory research. In-depth analysis was conducted through interviews, open discussions, document analysis as well as personal observation to understand the dynamic interrelatedness of the main factors influencing success of SI ventures.

This paper identified the role of SI in SEs embedded in networks. Furthermore, the social value creation processes of these organizations as well as the value they create were explored. Based on the findings, SI is rooted in the personality of the included members of the network. The tools of collaboration are platforms that connect the network members to each other. The embedded organizations apply the concept of community sharing with the aim of social value creation.

By focusing mainly on system design principles, the sample consists of mainly those at the core of organizations in facilitator roles, leaving peripheral actor perceptions to be determined by secondhand observations.

While providing a general summary of factors influencing SI activities from extent literature, the paper mainly contributes by providing deeper insight into complex models of SI practices used by SEs. The paper further contributes to popularizing the growing role of SI activities in SEs.

This paper aims to apply several data mining techniques for predicting the daily precision improvement of Jakarta Islamic Index (JKII) prices based on big data of symmetric volatility in Indonesia’s Islamic stock market.

This research uses big data mining techniques to predict daily precision improvement of JKII prices by applying the AdaBoost, K-nearest neighbor, random forest and artificial neural networks. This research uses big data with symmetric volatility as inputs in the predicting model, whereas the closing prices of JKII were used as the target outputs of daily precision improvement. For choosing the optimal prediction performance according to the criteria of the lowest prediction errors, this research uses four metrics of mean absolute error, mean squared error, root mean squared error and R-squared.

The experimental results determine that the optimal technique for predicting the daily precision improvement of the JKII prices in Indonesia’s Islamic stock market is the AdaBoost technique, which generates the optimal predicting performance with the lowest prediction errors, and provides the optimum knowledge from the big data of symmetric volatility in Indonesia’s Islamic stock market. In addition, the random forest technique is also considered another robust technique in predicting the daily precision improvement of the JKII prices as it delivers closer values to the optimal performance of the AdaBoost technique.

This research is filling the literature gap of the absence of using big data mining techniques in the prediction process of Islamic stock markets by delivering new operational techniques for predicting the daily stock precision improvement. Also, it helps investors to manage the optimal portfolios and to decrease the risk of trading in global Islamic stock markets based on using big data mining of symmetric volatility.

This research is a pioneer in using big data mining of symmetric volatility in the prediction of an Islamic stock market index.

Considering rapid digitalization development, this study examines the impacts of digital technology innovation on social responsibility in platform enterprises.

The study applies the event study method and cross-sectional regression analysis, taking 168 digital technology innovations for social responsibility issued by 88 listed platform enterprises from 2011 to 2022 to study the impact of digital technology innovations for social responsibility announcements of different announcement content and platform attributes on the stock market value of platform enterprises.

The results show that, first, the positive stock market reaction is produced on the same day as the digital technology innovation announcement. Second, the announcement of the platform’s public social responsibility and the announcement of co-innovation and radical innovation bring more positive stock market reactions. In addition, the announcements mentioned above issued by trading platforms bring more positive stock market reactions. Finally, the social responsibility attribution characteristics of the announcement did not have a significant differentiated impact on the stock market reaction.

Most scholars have studied digital technology innovation for social responsibility through modeling rather than second-hand data to empirically examine. This study uses second-hand data with the instrumental stakeholder theory to provide a new research perspective on platform social responsibility. In addition, in order to explore the different impacts of digital technology innovation on social responsibility, this study has classified digital technology innovation for social responsibility according to its social responsibility and digital technology innovation characteristics.

Corporate social responsibility (CSR) promotes society, reduces risk, and encourages ethical business practices. Due to its relevance, we study how CSR influences firms' sustainable development. We analyze data from 427 New York Stock Exchange (NYSE)-listed firms from 2008 to 2022. The Refinitiv environmental and social score is used to measure CSR, whereas for firms' sustainable development we rely on corporate sustainable growth rate (SGR) and market-based metrics. The analysis employs various econometric techniques, including ordinary least square, fixed effect regression, two-stage least square, generalized method of moment, and simultaneous quantile regression. The results indicate that CSR has a positive and significant effect on firms' sustainable development across all models. This relationship supports the notion that socially responsible business can contribute to long-term financial sustainability in line with “stakeholder theory”, indicating that companies should accommodate the concerns of various stakeholders, including society and the environment, to achieve sustainable development. We evaluate how the conditional distributions of SGR and firms’ value are affected by CSR, categorizing them into high, moderate, and low regimes. The quantile regression estimates indicate that the effect of CSR is more pronounced at upper quantiles, followed by moderate and low regimes. These findings underscore the importance of considering CSR in assessing the SGR and enterprises market value. We also confirm that our results are robust under range of different econometrics' methods. Finally, we enlighten current literature, and our research has useful policy implications for management and investors.