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The purpose of this paper is to examine the impact of social movements engendered by the Arab Spring crisis on the relationship between corporate social responsibility disclosure (CSRD) and corporate governance attributes, particularly board composition, considering the importance of governance after the Arab Spring event.

Content analysis was used to examine the extent and nature of CSRD in annual reports of Jordanian companies listed on the Amman Stock Exchange covering the period 2009–2016. A dynamic regression model using panel data is then undertaken for a sample of 114 listed companies over the period to analyse the potential impact of board composition on the level of CSRD.

The results reveal that there was a significant increase in the level of CSRD post-the Arab Spring crisis; and that governance appears to be a key driver. Specifically, board age, directors educated in business and/or accounting-related fields and foreign members are found to have a significant positive relationship with CSRD.

Looking at the Arab region pre- and after the Arab Spring helps to complete the global picture of how company governance can lead to improved CSR performance. Specifically, this region has been behind in developing rules and codes that include CSR. The results show that having a diverse board, with directors with expertise specific to the context, increases the effectiveness of stakeholder management through CSRD. The results, therefore, offer valuable insights for companies, policymakers and for the development of regulations.

With the proliferation of ideas submitted by users in firm-built online user innovation communities, community managers are faced with the problem of user idea overload. The purpose of this paper is to explore the influencing factors on the idea adoption to identify high quality ideas, and then propose a method to quickly filter high value ideas.

The authors collected more than 110,000 data submitted by Xiaomi community users and analyzed the factors affecting idea adoption using a multinomial logistic regression model. In addition, the authors also used BP neural network to predict the idea adoption process.

The empirical results show that idea semantics, number of likes, number of comments, number of related posts, the existence of pictures and self-presentation have positive impact on idea adoption, while idea length and idea timeliness had negative impact on idea adoption. In addition, this paper calculates the idea evaluation value through the idea adoption process predicted by neural network and the mean value of idea term frequency inverse document frequency (TF-IDF).

This empirical study expands the theoretical perspective of idea adoption research by using dual-process theory and enriches the research methods in the field of idea adoption research through the multinomial logistic regression method. Based on our findings, firms can quickly identify valuable ideas and effectively alleviate the information overload problem of online user innovation communities.

Green innovation in supply chains is crucial for socioeconomic development and stability. Factors that influence collaborative green innovation in the supply chain are complex and diverse. Exploring the main influencing factors and their mechanisms is essential for promoting collaborative green innovation in supply chains. Therefore, this study analyzes how upstream and downstream enterprises in the supply chain collaborate to develop green technological innovations, thereby providing a theoretical basis for improving the overall efficiency of the supply chain and advancing green innovation technology.

Based on evolutionary game theory, this study divides operational scenarios into pure market and government-regulated operations, thereby constructing collaborative green innovation relationships in different scenarios. Through evolutionary analysis of various entities in different operational scenarios, combined with numerical simulation analysis, we compared the evolutionary stability of collaborative green innovation behavior in supply chains with and without government regulation.

Under pure market mechanisms, the higher the green innovation capability, the stronger the willingness of various entities to collaborate in green innovation. However, under government regulation, a decrease in green innovation capability increases the willingness to collaborate with various entities. Environmental tax rates and green subsidy levels promote collaborative innovation in the short term but inhibit collaborative innovation in the long term, indicating that policy orientation has a short-term impact. Additionally, the greater the penalty for collaborative innovation breaches, the stronger the intention to engage in collaborative green innovation in the supply chain.

We introduce the factors influencing green innovation capability and social benefits in the study of the innovation behavior of upstream and downstream enterprises, expanding the research field of collaborative innovation in the supply chain. By comparing the collaborative innovation behavior of various entities in the supply chain under a pure market scenario and government regulations, this study provides a new perspective for analyzing the impact of corresponding government policies on the green innovation capability of upstream and downstream enterprises, enriching theoretical research on green innovation in the supply chain to some extent.

The authors investigate the relationship between instant messenger (IM) use and work performance, mediated by interruptions and two key indicators of the stress associated with technology use: overload and complexity.

The authors validate this research model using partial least squares structural equation modelling (PLS-SEM) with data collected through a survey of 416 working professionals.

The data reveal that while IM use contributes minimally to work interruptions and to a greater extent to technological complexity, these two constructs fully mediate the direct influence of IM use at work on technology overload, and meanwhile significantly and directly contribute to work performance.

This research provides theoretical insights into the deployment of IM and its actual impacts in the workplace. To improve the generalisation of the findings, the authors call for more IM-related research in other countries, with more native theories and various methodologies in this domain.

The level of stress generated through IM use is moderate, considering IM is not a significant contributor to work interruptions. Thus, despite the potential negative effects of IM communication, the positive effects of using IM at work prevail. As a result, the technology can be promoted as long as employees, their managers and the organisation as a whole are well prepared. Employees can transfer skills and behaviour from the personal setting to their work environment and thus may find an intrinsic motivation to make better use of the IM technology at work.

The authors argue that this research model is novel for its perspective on evaluating the actual impacts of IM use at work instead of the reasons of using it. The authors conceptualise the process to explain how IM contributes to interruptions and other technostress indicators in the working context, and the impact on performance. Contrary to some prior research, the authors find that overall IM applications do not have a negative impact on work performance, and instead may enhance it.

Based on the principles of the social capital theory (SCT), this study aimed to generate hypotheses and evaluate a mediated moderated model that examined the impact of social capital on online brand community happiness (OBCH).

Using 215 online questionnaires from users of private online brand communities (OBCs) , researchers examined the hypothesized connections between variables. The SPSS 21.0 and AMOS 26.0 were applied to fulfill the purpose.

For the goodness of model fit, the authors have applied cut off criteria for fit indexes given by Hu and Bentler (1999) and model-fit measures indicators, i.e. CMIN/DF 1.397, CFI 0.958, SRMR 0.045, RMSEA 0.043 and PCLOSE 0.866, which meet the minimum acceptable criteria. Based on the results, social capital significantly affects psychological well-being (PWB), which, consequently, leads toward increased happiness among OBCs. Furthermore, membership duration moderates the relationship between PWB and OBCs.

The authors have utilized a cross-sectional research design, and it limits the researcher’s ability to generalize the findings. These findings imply how social capital leverages PWB and OBCH. Moreover, the presence of membership duration helps to understand that members who spend more time in the community are happier in the OBCs.

In this age of social media, it provides valuable guidance to the administrators of private Facebook groups dedicated to specific brands, enhancing the definition and development of OBC operations and community interactions.

This research takes a broader look at social capital’s impact on happiness among private OBCs. The current research contributes to the existing body of work by emphasizing the role of PWB in generating happiness. The study is novel in examining the mediating moderating model of PWB and membership duration to explore deep insights for social media platforms.

This study uses a meta-analysis approach to analyse the impact of applying corporate green accounting practices as vital sustainable development tools on firm performance. This study aims to examine the moderating effects of country-specific variables and characteristics on the association between corporate green accounting and firm performance.

Three databases were used for a meta-analysis of 68 independent studies involving 19,625 subjects conducted over 25 years from 1996 to 2020.

The results show that corporate green accounting positively affects firm performance, but country-specific variables do not moderate this association. The positive association between corporate green accounting and firm performance was enhanced when it was measured in terms of environmental costs. Subgroup analyses revealed that study characteristics are significant source of heterogeneity in the corporate green accounting indicators-firm performance association.

The findings suggest that firms should strategise to integrate environmental costs into their respective financial accounting frameworks, which would help managers justify the contribution of their firms towards environmental protection.

Accessing accurate and timely information on corporate environmental functioning can assist national policymakers in framing appropriate legislation on environmental protection and sustainable development.

Although meta-analysis has been used previously in accounting research (Guthrie and Murthy, 2009; Alcouffe et al., 2019), to the best of the authors’ knowledge, this is the first study to use a meta-analytical technique to examine the impact of corporate green accounting on firm performance.

The purpose of this paper is to create a model that connects drivers between organizational innovation and business model innovation (BMI) to guide empirical research and the design of innovation management strategies.

The model was designed based on the results of a systematic literature review over the past 25 years that provides common predictor variables to build bridges between these two types of innovations.

It is a conceptual relationship between organizational innovation and BMI based on processes, new structures and customer relationship management. Moreover, there are five bridges from common predictors: strategy, top management, exploratory learning, technological innovation and environmental complexity.

The relationships between organizational innovation and BMI have been neglected in the literature. The model fills this gap by proposing hypotheses for empirical research and critical variables and relationships to steer organizational and business model innovation.

This study explores features that impact consumers' purchase intention through artificial intelligence (AI), because it is believed that through artificial intelligence, consumers' intention to purchase grows significantly, especially in the retail sector, whereby retailers provide lucrative offers to motivate consumers. The study develops a theoretical framework based on media-richness theory to investigate the role of perceived anthropomorphism toward an intention to purchase products using AI.

The study is based on cross-sectional data through an online survey. The data have been analyzed using PLS-SEM and SPSS PROCESS macro.

The results show that consumers tend to demand anthropomorphized products to gain a better shopping experience and, therefore, demand features that attract and motivate them to purchase through artificial intelligence via mediating variables, such as perceived animacy and perceived intelligence. Moreover, trust in artificial intelligence moderates the relationship between perceived anthropomorphism and perceived animacy.

The study investigates and concludes with managerial and academic insights into consumer purchase intention through artificial intelligence in the retail and marketing sector.